diff --git a/checkpoint-11900/config.json b/checkpoint-11900/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..44297312cc29516aa24d174765d6093fc1fdeeb7
--- /dev/null
+++ b/checkpoint-11900/config.json
@@ -0,0 +1,253 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900",
+ "architectures": [
+ "LlavaLlamaModel"
+ ],
+ "drop_path_rate": 0.0,
+ "hidden_size": 2560,
+ "image_aspect_ratio": "resize",
+ "interpolate_mode": "linear",
+ "llm_cfg": {
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/llm",
+ "add_cross_attention": false,
+ "architectures": [
+ "LlamaForCausalLM"
+ ],
+ "attention_bias": false,
+ "attention_dropout": 0.0,
+ "bad_words_ids": null,
+ "begin_suppress_tokens": null,
+ "bos_token_id": 1,
+ "chunk_size_feed_forward": 0,
+ "cross_attention_hidden_size": null,
+ "decoder_start_token_id": null,
+ "diversity_penalty": 0.0,
+ "do_sample": false,
+ "early_stopping": false,
+ "encoder_no_repeat_ngram_size": 0,
+ "eos_token_id": 2,
+ "exponential_decay_length_penalty": null,
+ "finetuning_task": null,
+ "forced_bos_token_id": null,
+ "forced_eos_token_id": null,
+ "hidden_act": "silu",
+ "hidden_size": 2560,
+ "id2label": {
+ "0": "LABEL_0",
+ "1": "LABEL_1"
+ },
+ "initializer_range": 0.02,
+ "intermediate_size": 6912,
+ "is_decoder": false,
+ "is_encoder_decoder": false,
+ "label2id": {
+ "LABEL_0": 0,
+ "LABEL_1": 1
+ },
+ "length_penalty": 1.0,
+ "max_length": 20,
+ "max_position_embeddings": 4096,
+ "min_length": 0,
+ "model_max_length": 4096,
+ "model_type": "llama",
+ "no_repeat_ngram_size": 0,
+ "num_attention_heads": 20,
+ "num_beam_groups": 1,
+ "num_beams": 1,
+ "num_hidden_layers": 32,
+ "num_key_value_heads": 20,
+ "num_return_sequences": 1,
+ "output_attentions": false,
+ "output_hidden_states": false,
+ "output_scores": false,
+ "pad_token_id": 0,
+ "prefix": null,
+ "pretraining_tp": 1,
+ "problem_type": null,
+ "pruned_heads": {},
+ "remove_invalid_values": false,
+ "repetition_penalty": 1.0,
+ "return_dict": true,
+ "return_dict_in_generate": false,
+ "rms_norm_eps": 1e-05,
+ "rope_scaling": null,
+ "rope_theta": 10000.0,
+ "sep_token_id": null,
+ "suppress_tokens": null,
+ "task_specific_params": null,
+ "temperature": 1.0,
+ "tf_legacy_loss": false,
+ "tie_encoder_decoder": false,
+ "tie_word_embeddings": false,
+ "tokenizer_class": null,
+ "tokenizer_model_max_length": 4096,
+ "tokenizer_padding_side": "right",
+ "top_k": 50,
+ "top_p": 1.0,
+ "torch_dtype": "bfloat16",
+ "torchscript": false,
+ "typical_p": 1.0,
+ "use_bfloat16": false,
+ "use_cache": false,
+ "vocab_size": 32000
+ },
+ "mm_hidden_size": 1152,
+ "mm_projector_cfg": {
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/mm_projector",
+ "add_cross_attention": false,
+ "architectures": [
+ "MultimodalProjector"
+ ],
+ "bad_words_ids": null,
+ "begin_suppress_tokens": null,
+ "bos_token_id": null,
+ "chunk_size_feed_forward": 0,
+ "cross_attention_hidden_size": null,
+ "decoder_start_token_id": null,
+ "diversity_penalty": 0.0,
+ "do_sample": false,
+ "early_stopping": false,
+ "encoder_no_repeat_ngram_size": 0,
+ "eos_token_id": null,
+ "exponential_decay_length_penalty": null,
+ "finetuning_task": null,
+ "forced_bos_token_id": null,
+ "forced_eos_token_id": null,
+ "id2label": {
+ "0": "LABEL_0",
+ "1": "LABEL_1"
+ },
+ "is_decoder": false,
+ "is_encoder_decoder": false,
+ "label2id": {
+ "LABEL_0": 0,
+ "LABEL_1": 1
+ },
+ "length_penalty": 1.0,
+ "max_length": 20,
+ "min_length": 0,
+ "mm_projector_type": "mlp_downsample",
+ "model_type": "v2l_projector",
+ "no_repeat_ngram_size": 0,
+ "num_beam_groups": 1,
+ "num_beams": 1,
+ "num_return_sequences": 1,
+ "output_attentions": false,
+ "output_hidden_states": false,
+ "output_scores": false,
+ "pad_token_id": null,
+ "prefix": null,
+ "problem_type": null,
+ "pruned_heads": {},
+ "remove_invalid_values": false,
+ "repetition_penalty": 1.0,
+ "return_dict": true,
+ "return_dict_in_generate": false,
+ "sep_token_id": null,
+ "suppress_tokens": null,
+ "task_specific_params": null,
+ "temperature": 1.0,
+ "tf_legacy_loss": false,
+ "tie_encoder_decoder": false,
+ "tie_word_embeddings": true,
+ "tokenizer_class": null,
+ "top_k": 50,
+ "top_p": 1.0,
+ "torch_dtype": "bfloat16",
+ "torchscript": false,
+ "typical_p": 1.0,
+ "use_bfloat16": false
+ },
+ "mm_projector_lr": null,
+ "mm_use_im_patch_token": false,
+ "mm_use_im_start_end": false,
+ "mm_vision_select_feature": "cls_patch",
+ "mm_vision_select_layer": -2,
+ "model_dtype": "torch.bfloat16",
+ "model_type": "llava_llama",
+ "num_video_frames": 8,
+ "resume_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/checkpoint-11500",
+ "s2": false,
+ "s2_max_split_size": 336,
+ "s2_scales": "336,672,1008",
+ "transformers_version": "4.36.2",
+ "tune_language_model": true,
+ "tune_mm_projector": true,
+ "tune_vision_tower": true,
+ "vision_resolution": -1,
+ "vision_tower_cfg": {
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/vision_tower",
+ "add_cross_attention": false,
+ "architectures": [
+ "SiglipVisionModel"
+ ],
+ "attention_dropout": 0.0,
+ "bad_words_ids": null,
+ "begin_suppress_tokens": null,
+ "bos_token_id": null,
+ "chunk_size_feed_forward": 0,
+ "cross_attention_hidden_size": null,
+ "decoder_start_token_id": null,
+ "diversity_penalty": 0.0,
+ "do_sample": false,
+ "early_stopping": false,
+ "encoder_no_repeat_ngram_size": 0,
+ "eos_token_id": null,
+ "exponential_decay_length_penalty": null,
+ "finetuning_task": null,
+ "forced_bos_token_id": null,
+ "forced_eos_token_id": null,
+ "hidden_act": "gelu_pytorch_tanh",
+ "hidden_size": 1152,
+ "id2label": {
+ "0": "LABEL_0",
+ "1": "LABEL_1"
+ },
+ "image_size": 384,
+ "intermediate_size": 4304,
+ "is_decoder": false,
+ "is_encoder_decoder": false,
+ "label2id": {
+ "LABEL_0": 0,
+ "LABEL_1": 1
+ },
+ "layer_norm_eps": 1e-06,
+ "length_penalty": 1.0,
+ "max_length": 20,
+ "min_length": 0,
+ "model_type": "siglip_vision_model",
+ "no_repeat_ngram_size": 0,
+ "num_attention_heads": 16,
+ "num_beam_groups": 1,
+ "num_beams": 1,
+ "num_channels": 3,
+ "num_hidden_layers": 27,
+ "num_return_sequences": 1,
+ "output_attentions": false,
+ "output_hidden_states": false,
+ "output_scores": false,
+ "pad_token_id": null,
+ "patch_size": 14,
+ "prefix": null,
+ "problem_type": null,
+ "pruned_heads": {},
+ "remove_invalid_values": false,
+ "repetition_penalty": 1.0,
+ "return_dict": true,
+ "return_dict_in_generate": false,
+ "sep_token_id": null,
+ "suppress_tokens": null,
+ "task_specific_params": null,
+ "temperature": 1.0,
+ "tf_legacy_loss": false,
+ "tie_encoder_decoder": false,
+ "tie_word_embeddings": true,
+ "tokenizer_class": null,
+ "top_k": 50,
+ "top_p": 1.0,
+ "torch_dtype": "bfloat16",
+ "torchscript": false,
+ "typical_p": 1.0,
+ "use_bfloat16": false
+ }
+}
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..425e01cb99551b4b9242bbfffe5042e4dab9f090
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e16feb908e83de7948f133af315081b18bc8661dd5680b1e830476d0132938bf
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_1_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_1_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..4c8f0ff2164ad980580ffe252e3cefbcd1bf0dfa
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_1_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:47f14a70e8c8f21d0ead644dc2d1cb465a729b710c8ca139a61e11289085130c
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_2_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_2_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..17e7dcfcda311fe98e1e51b3435d6f03eb547922
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_2_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b282117719e06098acdff5535759074c2b41b2a077fb455987c6ed61fc9aad75
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_3_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_3_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..36eb27147341acf850188f3d9d1efbf6e525d251
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_3_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b488f8196b3ca11647334633206edd0918a60f48dcdb0adf8d958244e42d9764
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_4_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_4_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..1e9b02b88519cfa1a619da0d3cb55064b5904778
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_4_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4e3c7119bbcb3e948f801d52390d1d2a67b67cc0f2841a9d86e096754e834c53
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_5_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_5_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..e1ff23a8c76e111a75c3204f5ec2b5119a620cb0
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_5_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:545bdd1c243aa362e78a2a61f5de3dcc530fdff06c1118dbe4fbd10186885b60
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_6_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_6_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..ff9a4fbced98368c5a676a0cf373217ba9ef387e
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_6_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4d341406942df99af515cfebd48e33ef83aebdac5a39934d1b01790b5ea2dc5b
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/bf16_zero_pp_rank_7_mp_rank_00_optim_states.pt b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_7_mp_rank_00_optim_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..b90437d89555912d0871c8d91895f71434098634
--- /dev/null
+++ b/checkpoint-11900/global_step11900/bf16_zero_pp_rank_7_mp_rank_00_optim_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e808100a2bf9ffd60a778770bb2832bf1f3c67829a45f22b8416d2bf11c24462
+size 4722230103
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_0_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_0_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..d23a9c0faee750ecbd1e5f96f3b820a4ee8bd736
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_0_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:91d2be6c9218d48dac0fec2185b29da65a9348cdbe10390090c15b3b1249dcbe
+size 413988
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_1_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_1_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..1b7db38e4a4b68e4779b0e8171cdf7903415d8ca
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_1_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cddafad2e5d10a8340d15d2011546e4f9072eeba09f5ae4bd5ed3a8220d5e260
+size 413988
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_2_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_2_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..f7d4e0eadea258624503866f4b074903142ca910
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_2_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:610cc1d7f0a0c8bf0ad12cc381bc428be3d85fe7313a39d0f55a105c8ff7a71a
+size 413988
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_3_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_3_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..ae21867ce7504b937df3d823ca286c0057e84c33
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_3_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d67159e213a62e2864f2ba8086ef0d2b52489712a50b57526c5f76a4c039d30a
+size 413988
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_4_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_4_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..d5fe514e495855c1a1fef2ef108ae61138774bab
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_4_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f9524f78cfd7a20009ec30e55152d38cbc93cf6630b88c4ca5342d57d0802f3
+size 413988
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_5_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_5_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..d695fa9e152d67f0e5f28c7db288e8fd4cbae8ae
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_5_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:64c19b85f0bdb37f7a9ed93ea10bce8392a3964700d7a1b5f8dd3dc2dfece17c
+size 413988
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_6_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_6_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..2c46463b9b78d38324103b1db824cd43e0688355
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_6_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f5fc2fca47cff61908821663d681977d83f5ccf6242b8741665efe0baff6979f
+size 413988
diff --git a/checkpoint-11900/global_step11900/zero_pp_rank_7_mp_rank_00_model_states.pt b/checkpoint-11900/global_step11900/zero_pp_rank_7_mp_rank_00_model_states.pt
new file mode 100644
index 0000000000000000000000000000000000000000..85ac1d8b2a84c4f6285bd758521e283a2e96ec0e
--- /dev/null
+++ b/checkpoint-11900/global_step11900/zero_pp_rank_7_mp_rank_00_model_states.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:789e3ee152ac13aa2e8902b45d36a27aa774930a78ca0a9eadf6aad458d160fb
+size 413988
diff --git a/checkpoint-11900/latest b/checkpoint-11900/latest
new file mode 100644
index 0000000000000000000000000000000000000000..04f241ff9e03d5551095c3acbf6a446bf647c694
--- /dev/null
+++ b/checkpoint-11900/latest
@@ -0,0 +1 @@
+global_step11900
\ No newline at end of file
diff --git a/checkpoint-11900/llm/config.json b/checkpoint-11900/llm/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..cc0aa92bd96efcdcc640e1ffca5fafc2d352c9b7
--- /dev/null
+++ b/checkpoint-11900/llm/config.json
@@ -0,0 +1,32 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/llm",
+ "architectures": [
+ "LlamaForCausalLM"
+ ],
+ "attention_bias": false,
+ "attention_dropout": 0.0,
+ "bos_token_id": 1,
+ "eos_token_id": 2,
+ "hidden_act": "silu",
+ "hidden_size": 2560,
+ "initializer_range": 0.02,
+ "intermediate_size": 6912,
+ "max_position_embeddings": 4096,
+ "model_max_length": 4096,
+ "model_type": "llama",
+ "num_attention_heads": 20,
+ "num_hidden_layers": 32,
+ "num_key_value_heads": 20,
+ "pad_token_id": 0,
+ "pretraining_tp": 1,
+ "rms_norm_eps": 1e-05,
+ "rope_scaling": null,
+ "rope_theta": 10000.0,
+ "tie_word_embeddings": false,
+ "tokenizer_model_max_length": 4096,
+ "tokenizer_padding_side": "right",
+ "torch_dtype": "bfloat16",
+ "transformers_version": "4.36.2",
+ "use_cache": false,
+ "vocab_size": 32000
+}
diff --git a/checkpoint-11900/llm/generation_config.json b/checkpoint-11900/llm/generation_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..bf84ec1a28ba89feb07162d95b06633a40b4975f
--- /dev/null
+++ b/checkpoint-11900/llm/generation_config.json
@@ -0,0 +1,7 @@
+{
+ "_from_model_config": true,
+ "bos_token_id": 1,
+ "eos_token_id": 2,
+ "pad_token_id": 0,
+ "transformers_version": "4.36.2"
+}
diff --git a/checkpoint-11900/llm/model-00001-of-00002.safetensors b/checkpoint-11900/llm/model-00001-of-00002.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..bf97f1d77bde1530d166322e24d17e294e368697
--- /dev/null
+++ b/checkpoint-11900/llm/model-00001-of-00002.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:160cdacee1c8bd833184e358926133805fc11c976741a25f7b8809c433852af2
+size 4974521464
diff --git a/checkpoint-11900/llm/model-00002-of-00002.safetensors b/checkpoint-11900/llm/model-00002-of-00002.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..9c241ca2b12e0aeb2ee2b926551e0b2e30ced259
--- /dev/null
+++ b/checkpoint-11900/llm/model-00002-of-00002.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a5174749cbe7d2efb6ba225ccb6cc6f419cb674a7b94db949a828fb5bb9a3c13
+size 428632856
diff --git a/checkpoint-11900/llm/model.safetensors.index.json b/checkpoint-11900/llm/model.safetensors.index.json
new file mode 100644
index 0000000000000000000000000000000000000000..8b173c9ac8194749df58c92051618c0ff74c4c20
--- /dev/null
+++ b/checkpoint-11900/llm/model.safetensors.index.json
@@ -0,0 +1,298 @@
+{
+ "metadata": {
+ "total_size": 5403120640
+ },
+ "weight_map": {
+ "lm_head.weight": "model-00002-of-00002.safetensors",
+ "model.embed_tokens.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.input_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.norm.weight": "model-00002-of-00002.safetensors"
+ }
+}
diff --git a/checkpoint-11900/llm/special_tokens_map.json b/checkpoint-11900/llm/special_tokens_map.json
new file mode 100644
index 0000000000000000000000000000000000000000..14761dcf1466dc232bd41de9c21d4c617b15755e
--- /dev/null
+++ b/checkpoint-11900/llm/special_tokens_map.json
@@ -0,0 +1,24 @@
+{
+ "bos_token": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "eos_token": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "pad_token": "",
+ "unk_token": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ }
+}
diff --git a/checkpoint-11900/llm/tokenizer.model b/checkpoint-11900/llm/tokenizer.model
new file mode 100644
index 0000000000000000000000000000000000000000..3b7eab905db502ae7629c8a3c1f8412a3178c4c2
--- /dev/null
+++ b/checkpoint-11900/llm/tokenizer.model
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7aedb3582ecda9fa99ee9242c17a9658f6744db083ee6ebdc8fb14857f84d220
+size 499723
diff --git a/checkpoint-11900/llm/tokenizer_config.json b/checkpoint-11900/llm/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..47ab96cd62cc374653a0ea0fb77f9457e0f53481
--- /dev/null
+++ b/checkpoint-11900/llm/tokenizer_config.json
@@ -0,0 +1,43 @@
+{
+ "add_bos_token": true,
+ "add_eos_token": false,
+ "add_prefix_space": true,
+ "added_tokens_decoder": {
+ "0": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "1": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "2": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ }
+ },
+ "bos_token": "",
+ "clean_up_tokenization_spaces": false,
+ "eos_token": "",
+ "legacy": false,
+ "model_max_length": 4096,
+ "pad_token": "",
+ "padding_side": "right",
+ "sp_model_kwargs": {},
+ "spaces_between_special_tokens": false,
+ "tokenizer_class": "LlamaTokenizer",
+ "unk_token": "",
+ "use_default_system_prompt": false
+}
diff --git a/checkpoint-11900/mm_projector/config.json b/checkpoint-11900/mm_projector/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..42234ef77e0036c1e92d4914bd9fdbd8d693af72
--- /dev/null
+++ b/checkpoint-11900/mm_projector/config.json
@@ -0,0 +1,10 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/mm_projector",
+ "architectures": [
+ "MultimodalProjector"
+ ],
+ "mm_projector_type": "mlp_downsample",
+ "model_type": "v2l_projector",
+ "torch_dtype": "bfloat16",
+ "transformers_version": "4.36.2"
+}
diff --git a/checkpoint-11900/mm_projector/model.safetensors b/checkpoint-11900/mm_projector/model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..25b51569f448053ddac96daae2aa1eae0aa9086d
--- /dev/null
+++ b/checkpoint-11900/mm_projector/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ea87319d485227b1679d459a29bf423078274ed9cc4c6a6d68efe6ccdae02892
+size 36729360
diff --git a/checkpoint-11900/rng_state_0.pth b/checkpoint-11900/rng_state_0.pth
new file mode 100644
index 0000000000000000000000000000000000000000..fc929e783118d90d60e8ed23a46ed17d58f070a7
--- /dev/null
+++ b/checkpoint-11900/rng_state_0.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cfee7792e373bc4f2e2c6a05b8fd239a8934a9e750f2bcb4d6a752c83a95e675
+size 21687
diff --git a/checkpoint-11900/rng_state_1.pth b/checkpoint-11900/rng_state_1.pth
new file mode 100644
index 0000000000000000000000000000000000000000..2455787246d278a41af027b4821a0a9980a8b12b
--- /dev/null
+++ b/checkpoint-11900/rng_state_1.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b124f629d2d70a74af545b007dc89569ebceccf6661ebfc4f9567210ac6c701f
+size 21687
diff --git a/checkpoint-11900/rng_state_2.pth b/checkpoint-11900/rng_state_2.pth
new file mode 100644
index 0000000000000000000000000000000000000000..81a8b247a877cc71fda42daafa5efbd12e3b93c9
--- /dev/null
+++ b/checkpoint-11900/rng_state_2.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a668a0848f7bbb499d74db45fa777942e8f6c92c1e0f6c5c5a5aa5079964201
+size 21687
diff --git a/checkpoint-11900/rng_state_3.pth b/checkpoint-11900/rng_state_3.pth
new file mode 100644
index 0000000000000000000000000000000000000000..97c06b34543e1fc12f6627d498b838df13f99dfb
--- /dev/null
+++ b/checkpoint-11900/rng_state_3.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a2b8f85cc2d9b5264be911136a09181bdc6a1e9d691e4fc913ff930cea6c86e5
+size 21687
diff --git a/checkpoint-11900/rng_state_4.pth b/checkpoint-11900/rng_state_4.pth
new file mode 100644
index 0000000000000000000000000000000000000000..eccc1ec3663f5ee2897e99ac8ecc03c5a773f134
--- /dev/null
+++ b/checkpoint-11900/rng_state_4.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aee5ccac64db6c38edc9d752999c3cf6df4f1b7442b1689bb111a672cf858653
+size 21687
diff --git a/checkpoint-11900/rng_state_5.pth b/checkpoint-11900/rng_state_5.pth
new file mode 100644
index 0000000000000000000000000000000000000000..427917369058a4a6217b643e2abe65f1a7c8f6ff
--- /dev/null
+++ b/checkpoint-11900/rng_state_5.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5d160edeace5cc4d3b8b0e1fea79e623657eb5bd2ec0977ae41a7f1ec8dc3c10
+size 21687
diff --git a/checkpoint-11900/rng_state_6.pth b/checkpoint-11900/rng_state_6.pth
new file mode 100644
index 0000000000000000000000000000000000000000..e33f2aa30eb2375dbeed5d967b3bf87415e54967
--- /dev/null
+++ b/checkpoint-11900/rng_state_6.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:244880196327bb05a163dd9bf21e2a97f6a437c92938bd5bc03b14460357eeee
+size 21687
diff --git a/checkpoint-11900/rng_state_7.pth b/checkpoint-11900/rng_state_7.pth
new file mode 100644
index 0000000000000000000000000000000000000000..51da94e98244271d7616e419f761c11794738a28
--- /dev/null
+++ b/checkpoint-11900/rng_state_7.pth
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d666b54fef8eb195b33afa8e4bd98bbc865a31733c80760a0946ed7cf5b3e35b
+size 21687
diff --git a/checkpoint-11900/scheduler.pt b/checkpoint-11900/scheduler.pt
new file mode 100644
index 0000000000000000000000000000000000000000..e2bcb05422911e6f087890cdf68f750fb8b0cda7
--- /dev/null
+++ b/checkpoint-11900/scheduler.pt
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7d47fb793bad63d37c1e3d1579743f720fa29687663792556cf7fc9d78ac3de8
+size 627
diff --git a/checkpoint-11900/trainer_state.json b/checkpoint-11900/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce33bb3ec6919b3750b12e122457f47e4335be30
--- /dev/null
+++ b/checkpoint-11900/trainer_state.json
@@ -0,0 +1,71421 @@
+{
+ "best_metric": null,
+ "best_model_checkpoint": null,
+ "epoch": 0.9956076134699854,
+ "eval_steps": 500,
+ "global_step": 11900,
+ "is_hyper_param_search": false,
+ "is_local_process_zero": true,
+ "is_world_process_zero": true,
+ "log_history": [
+ {
+ "epoch": 0.0,
+ "learning_rate": 5.571030640668524e-08,
+ "loss": 0.8031,
+ "step": 1
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.1142061281337048e-07,
+ "loss": 0.8071,
+ "step": 2
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.6713091922005573e-07,
+ "loss": 0.7913,
+ "step": 3
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.2284122562674096e-07,
+ "loss": 0.8033,
+ "step": 4
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.785515320334262e-07,
+ "loss": 0.805,
+ "step": 5
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.3426183844011146e-07,
+ "loss": 0.8159,
+ "step": 6
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.899721448467967e-07,
+ "loss": 0.8095,
+ "step": 7
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 4.456824512534819e-07,
+ "loss": 0.7973,
+ "step": 8
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 5.013927576601672e-07,
+ "loss": 0.7913,
+ "step": 9
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 5.571030640668524e-07,
+ "loss": 0.8118,
+ "step": 10
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 6.128133704735377e-07,
+ "loss": 0.7926,
+ "step": 11
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 6.685236768802229e-07,
+ "loss": 0.7805,
+ "step": 12
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 7.242339832869082e-07,
+ "loss": 0.7913,
+ "step": 13
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 7.799442896935934e-07,
+ "loss": 0.7994,
+ "step": 14
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 8.356545961002786e-07,
+ "loss": 0.7979,
+ "step": 15
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 8.913649025069638e-07,
+ "loss": 0.7736,
+ "step": 16
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 9.470752089136491e-07,
+ "loss": 0.7817,
+ "step": 17
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.0027855153203343e-06,
+ "loss": 0.7678,
+ "step": 18
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.0584958217270195e-06,
+ "loss": 0.7265,
+ "step": 19
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.1142061281337048e-06,
+ "loss": 0.7331,
+ "step": 20
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.16991643454039e-06,
+ "loss": 0.7349,
+ "step": 21
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.2256267409470754e-06,
+ "loss": 0.7219,
+ "step": 22
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.2813370473537607e-06,
+ "loss": 0.7335,
+ "step": 23
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.3370473537604459e-06,
+ "loss": 0.7127,
+ "step": 24
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.392757660167131e-06,
+ "loss": 0.7235,
+ "step": 25
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.4484679665738164e-06,
+ "loss": 0.6903,
+ "step": 26
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.5041782729805015e-06,
+ "loss": 0.6748,
+ "step": 27
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.5598885793871869e-06,
+ "loss": 0.6899,
+ "step": 28
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.615598885793872e-06,
+ "loss": 0.6611,
+ "step": 29
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.6713091922005572e-06,
+ "loss": 0.6656,
+ "step": 30
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.7270194986072425e-06,
+ "loss": 0.6954,
+ "step": 31
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.7827298050139277e-06,
+ "loss": 0.683,
+ "step": 32
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.838440111420613e-06,
+ "loss": 0.6812,
+ "step": 33
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.8941504178272982e-06,
+ "loss": 0.6796,
+ "step": 34
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.9498607242339835e-06,
+ "loss": 0.6593,
+ "step": 35
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.0055710306406687e-06,
+ "loss": 0.6622,
+ "step": 36
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.061281337047354e-06,
+ "loss": 0.6774,
+ "step": 37
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.116991643454039e-06,
+ "loss": 0.6606,
+ "step": 38
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.1727019498607245e-06,
+ "loss": 0.658,
+ "step": 39
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.2284122562674097e-06,
+ "loss": 0.6551,
+ "step": 40
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.284122562674095e-06,
+ "loss": 0.621,
+ "step": 41
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.33983286908078e-06,
+ "loss": 0.6396,
+ "step": 42
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.395543175487465e-06,
+ "loss": 0.6604,
+ "step": 43
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.4512534818941507e-06,
+ "loss": 0.6269,
+ "step": 44
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.506963788300836e-06,
+ "loss": 0.6314,
+ "step": 45
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.5626740947075214e-06,
+ "loss": 0.623,
+ "step": 46
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.618384401114206e-06,
+ "loss": 0.6306,
+ "step": 47
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.6740947075208917e-06,
+ "loss": 0.6014,
+ "step": 48
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.729805013927577e-06,
+ "loss": 0.6312,
+ "step": 49
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.785515320334262e-06,
+ "loss": 0.617,
+ "step": 50
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.841225626740947e-06,
+ "loss": 0.6195,
+ "step": 51
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.8969359331476327e-06,
+ "loss": 0.6213,
+ "step": 52
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.9526462395543174e-06,
+ "loss": 0.6236,
+ "step": 53
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.008356545961003e-06,
+ "loss": 0.6158,
+ "step": 54
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.064066852367688e-06,
+ "loss": 0.5968,
+ "step": 55
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.1197771587743737e-06,
+ "loss": 0.6257,
+ "step": 56
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.1754874651810585e-06,
+ "loss": 0.6096,
+ "step": 57
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.231197771587744e-06,
+ "loss": 0.6253,
+ "step": 58
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.286908077994429e-06,
+ "loss": 0.6213,
+ "step": 59
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.3426183844011143e-06,
+ "loss": 0.6041,
+ "step": 60
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.3983286908077995e-06,
+ "loss": 0.6098,
+ "step": 61
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.454038997214485e-06,
+ "loss": 0.614,
+ "step": 62
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.5097493036211698e-06,
+ "loss": 0.6163,
+ "step": 63
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.5654596100278553e-06,
+ "loss": 0.6006,
+ "step": 64
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.6211699164345405e-06,
+ "loss": 0.5992,
+ "step": 65
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.676880222841226e-06,
+ "loss": 0.6079,
+ "step": 66
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.7325905292479116e-06,
+ "loss": 0.607,
+ "step": 67
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.7883008356545963e-06,
+ "loss": 0.6128,
+ "step": 68
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.844011142061282e-06,
+ "loss": 0.6046,
+ "step": 69
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.899721448467967e-06,
+ "loss": 0.5908,
+ "step": 70
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.955431754874652e-06,
+ "loss": 0.6016,
+ "step": 71
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.011142061281337e-06,
+ "loss": 0.615,
+ "step": 72
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.0668523676880225e-06,
+ "loss": 0.6117,
+ "step": 73
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.122562674094708e-06,
+ "loss": 0.5916,
+ "step": 74
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.178272980501394e-06,
+ "loss": 0.6005,
+ "step": 75
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.233983286908078e-06,
+ "loss": 0.5826,
+ "step": 76
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.289693593314764e-06,
+ "loss": 0.6087,
+ "step": 77
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.345403899721449e-06,
+ "loss": 0.5953,
+ "step": 78
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.401114206128134e-06,
+ "loss": 0.581,
+ "step": 79
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.456824512534819e-06,
+ "loss": 0.5961,
+ "step": 80
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.5125348189415045e-06,
+ "loss": 0.5837,
+ "step": 81
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.56824512534819e-06,
+ "loss": 0.5881,
+ "step": 82
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.623955431754875e-06,
+ "loss": 0.6076,
+ "step": 83
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.67966573816156e-06,
+ "loss": 0.5977,
+ "step": 84
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.735376044568246e-06,
+ "loss": 0.6113,
+ "step": 85
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.79108635097493e-06,
+ "loss": 0.5748,
+ "step": 86
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.846796657381616e-06,
+ "loss": 0.6021,
+ "step": 87
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.902506963788301e-06,
+ "loss": 0.5738,
+ "step": 88
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.9582172701949865e-06,
+ "loss": 0.5804,
+ "step": 89
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.013927576601672e-06,
+ "loss": 0.5796,
+ "step": 90
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.069637883008357e-06,
+ "loss": 0.591,
+ "step": 91
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.125348189415043e-06,
+ "loss": 0.5811,
+ "step": 92
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.181058495821727e-06,
+ "loss": 0.5667,
+ "step": 93
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.236768802228412e-06,
+ "loss": 0.6095,
+ "step": 94
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.292479108635098e-06,
+ "loss": 0.5935,
+ "step": 95
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.3481894150417834e-06,
+ "loss": 0.57,
+ "step": 96
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.403899721448468e-06,
+ "loss": 0.5865,
+ "step": 97
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.459610027855154e-06,
+ "loss": 0.6119,
+ "step": 98
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.515320334261839e-06,
+ "loss": 0.6189,
+ "step": 99
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.571030640668524e-06,
+ "loss": 0.6001,
+ "step": 100
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.62674094707521e-06,
+ "loss": 0.5787,
+ "step": 101
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.682451253481894e-06,
+ "loss": 0.5809,
+ "step": 102
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.7381615598885795e-06,
+ "loss": 0.5708,
+ "step": 103
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.7938718662952654e-06,
+ "loss": 0.6033,
+ "step": 104
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.849582172701951e-06,
+ "loss": 0.5802,
+ "step": 105
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.905292479108635e-06,
+ "loss": 0.587,
+ "step": 106
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.961002785515321e-06,
+ "loss": 0.5665,
+ "step": 107
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.016713091922006e-06,
+ "loss": 0.5883,
+ "step": 108
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.072423398328692e-06,
+ "loss": 0.5707,
+ "step": 109
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.128133704735376e-06,
+ "loss": 0.5862,
+ "step": 110
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.1838440111420615e-06,
+ "loss": 0.5918,
+ "step": 111
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.2395543175487475e-06,
+ "loss": 0.564,
+ "step": 112
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.295264623955433e-06,
+ "loss": 0.571,
+ "step": 113
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.350974930362117e-06,
+ "loss": 0.5589,
+ "step": 114
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.406685236768803e-06,
+ "loss": 0.5875,
+ "step": 115
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.462395543175488e-06,
+ "loss": 0.5771,
+ "step": 116
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.518105849582173e-06,
+ "loss": 0.5563,
+ "step": 117
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.573816155988858e-06,
+ "loss": 0.5947,
+ "step": 118
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.6295264623955435e-06,
+ "loss": 0.5625,
+ "step": 119
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.685236768802229e-06,
+ "loss": 0.5658,
+ "step": 120
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.740947075208915e-06,
+ "loss": 0.5672,
+ "step": 121
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.796657381615599e-06,
+ "loss": 0.5932,
+ "step": 122
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.852367688022284e-06,
+ "loss": 0.5779,
+ "step": 123
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.90807799442897e-06,
+ "loss": 0.5683,
+ "step": 124
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.963788300835655e-06,
+ "loss": 0.565,
+ "step": 125
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.0194986072423395e-06,
+ "loss": 0.5455,
+ "step": 126
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.0752089136490255e-06,
+ "loss": 0.5816,
+ "step": 127
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.130919220055711e-06,
+ "loss": 0.5675,
+ "step": 128
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.186629526462397e-06,
+ "loss": 0.575,
+ "step": 129
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.242339832869081e-06,
+ "loss": 0.5656,
+ "step": 130
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.298050139275766e-06,
+ "loss": 0.5686,
+ "step": 131
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.353760445682452e-06,
+ "loss": 0.5917,
+ "step": 132
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.409470752089137e-06,
+ "loss": 0.5935,
+ "step": 133
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.465181058495823e-06,
+ "loss": 0.5816,
+ "step": 134
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.5208913649025075e-06,
+ "loss": 0.5658,
+ "step": 135
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.576601671309193e-06,
+ "loss": 0.5707,
+ "step": 136
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.632311977715879e-06,
+ "loss": 0.5605,
+ "step": 137
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.688022284122564e-06,
+ "loss": 0.5882,
+ "step": 138
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.743732590529249e-06,
+ "loss": 0.5645,
+ "step": 139
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.799442896935934e-06,
+ "loss": 0.5875,
+ "step": 140
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.85515320334262e-06,
+ "loss": 0.5554,
+ "step": 141
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.910863509749304e-06,
+ "loss": 0.5579,
+ "step": 142
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.96657381615599e-06,
+ "loss": 0.5873,
+ "step": 143
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.022284122562675e-06,
+ "loss": 0.5785,
+ "step": 144
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.07799442896936e-06,
+ "loss": 0.5596,
+ "step": 145
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.133704735376045e-06,
+ "loss": 0.5765,
+ "step": 146
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.18941504178273e-06,
+ "loss": 0.5682,
+ "step": 147
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.245125348189415e-06,
+ "loss": 0.5593,
+ "step": 148
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.3008356545961e-06,
+ "loss": 0.5568,
+ "step": 149
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.356545961002787e-06,
+ "loss": 0.5685,
+ "step": 150
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.41225626740947e-06,
+ "loss": 0.5681,
+ "step": 151
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.467966573816156e-06,
+ "loss": 0.5858,
+ "step": 152
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.523676880222843e-06,
+ "loss": 0.5611,
+ "step": 153
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.579387186629528e-06,
+ "loss": 0.5584,
+ "step": 154
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.635097493036211e-06,
+ "loss": 0.5517,
+ "step": 155
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.690807799442898e-06,
+ "loss": 0.56,
+ "step": 156
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.746518105849583e-06,
+ "loss": 0.5673,
+ "step": 157
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.802228412256268e-06,
+ "loss": 0.5571,
+ "step": 158
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.857938718662954e-06,
+ "loss": 0.5716,
+ "step": 159
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.913649025069639e-06,
+ "loss": 0.5634,
+ "step": 160
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.969359331476324e-06,
+ "loss": 0.5602,
+ "step": 161
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.025069637883009e-06,
+ "loss": 0.5444,
+ "step": 162
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.080779944289694e-06,
+ "loss": 0.5793,
+ "step": 163
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.13649025069638e-06,
+ "loss": 0.5443,
+ "step": 164
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.192200557103064e-06,
+ "loss": 0.5449,
+ "step": 165
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.24791086350975e-06,
+ "loss": 0.5599,
+ "step": 166
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.303621169916436e-06,
+ "loss": 0.5362,
+ "step": 167
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.35933147632312e-06,
+ "loss": 0.5649,
+ "step": 168
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.415041782729805e-06,
+ "loss": 0.5734,
+ "step": 169
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.470752089136492e-06,
+ "loss": 0.5595,
+ "step": 170
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.526462395543177e-06,
+ "loss": 0.5483,
+ "step": 171
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.58217270194986e-06,
+ "loss": 0.5569,
+ "step": 172
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.637883008356547e-06,
+ "loss": 0.5591,
+ "step": 173
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.693593314763233e-06,
+ "loss": 0.5639,
+ "step": 174
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.749303621169918e-06,
+ "loss": 0.5504,
+ "step": 175
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.805013927576603e-06,
+ "loss": 0.5627,
+ "step": 176
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.860724233983288e-06,
+ "loss": 0.5587,
+ "step": 177
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.916434540389973e-06,
+ "loss": 0.5603,
+ "step": 178
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.972144846796658e-06,
+ "loss": 0.5558,
+ "step": 179
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0027855153203343e-05,
+ "loss": 0.5519,
+ "step": 180
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.008356545961003e-05,
+ "loss": 0.5488,
+ "step": 181
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0139275766016714e-05,
+ "loss": 0.5417,
+ "step": 182
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0194986072423399e-05,
+ "loss": 0.5537,
+ "step": 183
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0250696378830086e-05,
+ "loss": 0.5349,
+ "step": 184
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0306406685236769e-05,
+ "loss": 0.5355,
+ "step": 185
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0362116991643454e-05,
+ "loss": 0.5492,
+ "step": 186
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0417827298050141e-05,
+ "loss": 0.5627,
+ "step": 187
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0473537604456825e-05,
+ "loss": 0.5576,
+ "step": 188
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0529247910863511e-05,
+ "loss": 0.5411,
+ "step": 189
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0584958217270197e-05,
+ "loss": 0.5494,
+ "step": 190
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.064066852367688e-05,
+ "loss": 0.5574,
+ "step": 191
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0696378830083567e-05,
+ "loss": 0.5522,
+ "step": 192
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0752089136490252e-05,
+ "loss": 0.546,
+ "step": 193
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0807799442896935e-05,
+ "loss": 0.5454,
+ "step": 194
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0863509749303622e-05,
+ "loss": 0.5463,
+ "step": 195
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0919220055710307e-05,
+ "loss": 0.5607,
+ "step": 196
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0974930362116993e-05,
+ "loss": 0.5493,
+ "step": 197
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1030640668523678e-05,
+ "loss": 0.5301,
+ "step": 198
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1086350974930363e-05,
+ "loss": 0.5335,
+ "step": 199
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1142061281337048e-05,
+ "loss": 0.5532,
+ "step": 200
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1197771587743733e-05,
+ "loss": 0.5332,
+ "step": 201
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.125348189415042e-05,
+ "loss": 0.5719,
+ "step": 202
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1309192200557103e-05,
+ "loss": 0.5222,
+ "step": 203
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1364902506963789e-05,
+ "loss": 0.5481,
+ "step": 204
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1420612813370475e-05,
+ "loss": 0.5465,
+ "step": 205
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1476323119777159e-05,
+ "loss": 0.552,
+ "step": 206
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1532033426183844e-05,
+ "loss": 0.5473,
+ "step": 207
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1587743732590531e-05,
+ "loss": 0.5439,
+ "step": 208
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1643454038997214e-05,
+ "loss": 0.5462,
+ "step": 209
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1699164345403901e-05,
+ "loss": 0.5401,
+ "step": 210
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1754874651810586e-05,
+ "loss": 0.5498,
+ "step": 211
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.181058495821727e-05,
+ "loss": 0.5567,
+ "step": 212
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1866295264623957e-05,
+ "loss": 0.5436,
+ "step": 213
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1922005571030642e-05,
+ "loss": 0.5484,
+ "step": 214
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1977715877437325e-05,
+ "loss": 0.5411,
+ "step": 215
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2033426183844012e-05,
+ "loss": 0.5581,
+ "step": 216
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2089136490250697e-05,
+ "loss": 0.5441,
+ "step": 217
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2144846796657384e-05,
+ "loss": 0.5574,
+ "step": 218
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2200557103064068e-05,
+ "loss": 0.5588,
+ "step": 219
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2256267409470753e-05,
+ "loss": 0.5554,
+ "step": 220
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.231197771587744e-05,
+ "loss": 0.5342,
+ "step": 221
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2367688022284123e-05,
+ "loss": 0.568,
+ "step": 222
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2423398328690808e-05,
+ "loss": 0.5387,
+ "step": 223
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2479108635097495e-05,
+ "loss": 0.5469,
+ "step": 224
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2534818941504178e-05,
+ "loss": 0.5312,
+ "step": 225
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2590529247910865e-05,
+ "loss": 0.5462,
+ "step": 226
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.264623955431755e-05,
+ "loss": 0.5595,
+ "step": 227
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2701949860724234e-05,
+ "loss": 0.5355,
+ "step": 228
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.275766016713092e-05,
+ "loss": 0.548,
+ "step": 229
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2813370473537606e-05,
+ "loss": 0.547,
+ "step": 230
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2869080779944293e-05,
+ "loss": 0.5309,
+ "step": 231
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2924791086350976e-05,
+ "loss": 0.557,
+ "step": 232
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2980501392757661e-05,
+ "loss": 0.5592,
+ "step": 233
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3036211699164346e-05,
+ "loss": 0.5326,
+ "step": 234
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3091922005571032e-05,
+ "loss": 0.5262,
+ "step": 235
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3147632311977717e-05,
+ "loss": 0.5443,
+ "step": 236
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3203342618384402e-05,
+ "loss": 0.541,
+ "step": 237
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3259052924791087e-05,
+ "loss": 0.5411,
+ "step": 238
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3314763231197774e-05,
+ "loss": 0.5406,
+ "step": 239
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3370473537604457e-05,
+ "loss": 0.5488,
+ "step": 240
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3426183844011142e-05,
+ "loss": 0.5626,
+ "step": 241
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.348189415041783e-05,
+ "loss": 0.5479,
+ "step": 242
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3537604456824513e-05,
+ "loss": 0.5583,
+ "step": 243
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3593314763231198e-05,
+ "loss": 0.5572,
+ "step": 244
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3649025069637885e-05,
+ "loss": 0.5438,
+ "step": 245
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3704735376044568e-05,
+ "loss": 0.5382,
+ "step": 246
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3760445682451255e-05,
+ "loss": 0.5321,
+ "step": 247
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.381615598885794e-05,
+ "loss": 0.5513,
+ "step": 248
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3871866295264624e-05,
+ "loss": 0.546,
+ "step": 249
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.392757660167131e-05,
+ "loss": 0.5539,
+ "step": 250
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3983286908077996e-05,
+ "loss": 0.5551,
+ "step": 251
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4038997214484679e-05,
+ "loss": 0.5484,
+ "step": 252
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4094707520891366e-05,
+ "loss": 0.5445,
+ "step": 253
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4150417827298051e-05,
+ "loss": 0.5497,
+ "step": 254
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4206128133704738e-05,
+ "loss": 0.5279,
+ "step": 255
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4261838440111421e-05,
+ "loss": 0.5312,
+ "step": 256
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4317548746518106e-05,
+ "loss": 0.5578,
+ "step": 257
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4373259052924793e-05,
+ "loss": 0.549,
+ "step": 258
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4428969359331477e-05,
+ "loss": 0.5359,
+ "step": 259
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4484679665738162e-05,
+ "loss": 0.5571,
+ "step": 260
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4540389972144849e-05,
+ "loss": 0.5211,
+ "step": 261
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4596100278551532e-05,
+ "loss": 0.5446,
+ "step": 262
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4651810584958219e-05,
+ "loss": 0.533,
+ "step": 263
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4707520891364904e-05,
+ "loss": 0.548,
+ "step": 264
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4763231197771588e-05,
+ "loss": 0.546,
+ "step": 265
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4818941504178274e-05,
+ "loss": 0.5171,
+ "step": 266
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.487465181058496e-05,
+ "loss": 0.5478,
+ "step": 267
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4930362116991646e-05,
+ "loss": 0.5389,
+ "step": 268
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.498607242339833e-05,
+ "loss": 0.5388,
+ "step": 269
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5041782729805015e-05,
+ "loss": 0.5412,
+ "step": 270
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5097493036211702e-05,
+ "loss": 0.5354,
+ "step": 271
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5153203342618385e-05,
+ "loss": 0.5453,
+ "step": 272
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.520891364902507e-05,
+ "loss": 0.5322,
+ "step": 273
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5264623955431757e-05,
+ "loss": 0.5533,
+ "step": 274
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5320334261838443e-05,
+ "loss": 0.5358,
+ "step": 275
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5376044568245128e-05,
+ "loss": 0.5376,
+ "step": 276
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5431754874651813e-05,
+ "loss": 0.5359,
+ "step": 277
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5487465181058498e-05,
+ "loss": 0.5518,
+ "step": 278
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5543175487465183e-05,
+ "loss": 0.5365,
+ "step": 279
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5598885793871868e-05,
+ "loss": 0.5345,
+ "step": 280
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5654596100278553e-05,
+ "loss": 0.5424,
+ "step": 281
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.571030640668524e-05,
+ "loss": 0.5337,
+ "step": 282
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5766016713091924e-05,
+ "loss": 0.5202,
+ "step": 283
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.582172701949861e-05,
+ "loss": 0.5293,
+ "step": 284
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5877437325905294e-05,
+ "loss": 0.549,
+ "step": 285
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.593314763231198e-05,
+ "loss": 0.5346,
+ "step": 286
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5988857938718664e-05,
+ "loss": 0.5482,
+ "step": 287
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.604456824512535e-05,
+ "loss": 0.5549,
+ "step": 288
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6100278551532035e-05,
+ "loss": 0.5293,
+ "step": 289
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.615598885793872e-05,
+ "loss": 0.5656,
+ "step": 290
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6211699164345405e-05,
+ "loss": 0.5305,
+ "step": 291
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.626740947075209e-05,
+ "loss": 0.5557,
+ "step": 292
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6323119777158775e-05,
+ "loss": 0.5374,
+ "step": 293
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.637883008356546e-05,
+ "loss": 0.5183,
+ "step": 294
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6434540389972145e-05,
+ "loss": 0.5629,
+ "step": 295
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.649025069637883e-05,
+ "loss": 0.5362,
+ "step": 296
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.654596100278552e-05,
+ "loss": 0.532,
+ "step": 297
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.66016713091922e-05,
+ "loss": 0.5322,
+ "step": 298
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6657381615598886e-05,
+ "loss": 0.528,
+ "step": 299
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6713091922005575e-05,
+ "loss": 0.5609,
+ "step": 300
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6768802228412256e-05,
+ "loss": 0.5438,
+ "step": 301
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.682451253481894e-05,
+ "loss": 0.5241,
+ "step": 302
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.688022284122563e-05,
+ "loss": 0.5318,
+ "step": 303
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6935933147632312e-05,
+ "loss": 0.539,
+ "step": 304
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6991643454039e-05,
+ "loss": 0.5516,
+ "step": 305
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7047353760445685e-05,
+ "loss": 0.5418,
+ "step": 306
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7103064066852367e-05,
+ "loss": 0.5453,
+ "step": 307
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7158774373259056e-05,
+ "loss": 0.5144,
+ "step": 308
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.721448467966574e-05,
+ "loss": 0.5553,
+ "step": 309
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7270194986072423e-05,
+ "loss": 0.5618,
+ "step": 310
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.732590529247911e-05,
+ "loss": 0.525,
+ "step": 311
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7381615598885796e-05,
+ "loss": 0.5315,
+ "step": 312
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.743732590529248e-05,
+ "loss": 0.5413,
+ "step": 313
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7493036211699167e-05,
+ "loss": 0.549,
+ "step": 314
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7548746518105852e-05,
+ "loss": 0.5299,
+ "step": 315
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7604456824512537e-05,
+ "loss": 0.5693,
+ "step": 316
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7660167130919222e-05,
+ "loss": 0.5535,
+ "step": 317
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7715877437325907e-05,
+ "loss": 0.5383,
+ "step": 318
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7771587743732592e-05,
+ "loss": 0.5564,
+ "step": 319
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7827298050139278e-05,
+ "loss": 0.5521,
+ "step": 320
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7883008356545963e-05,
+ "loss": 0.5272,
+ "step": 321
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7938718662952648e-05,
+ "loss": 0.5204,
+ "step": 322
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7994428969359333e-05,
+ "loss": 0.5537,
+ "step": 323
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8050139275766018e-05,
+ "loss": 0.5412,
+ "step": 324
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8105849582172703e-05,
+ "loss": 0.5343,
+ "step": 325
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.816155988857939e-05,
+ "loss": 0.5388,
+ "step": 326
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8217270194986074e-05,
+ "loss": 0.5325,
+ "step": 327
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.827298050139276e-05,
+ "loss": 0.525,
+ "step": 328
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8328690807799444e-05,
+ "loss": 0.5467,
+ "step": 329
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.838440111420613e-05,
+ "loss": 0.5329,
+ "step": 330
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8440111420612814e-05,
+ "loss": 0.5338,
+ "step": 331
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.84958217270195e-05,
+ "loss": 0.5236,
+ "step": 332
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8551532033426184e-05,
+ "loss": 0.5235,
+ "step": 333
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8607242339832873e-05,
+ "loss": 0.5295,
+ "step": 334
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8662952646239555e-05,
+ "loss": 0.5306,
+ "step": 335
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.871866295264624e-05,
+ "loss": 0.5102,
+ "step": 336
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.877437325905293e-05,
+ "loss": 0.5463,
+ "step": 337
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.883008356545961e-05,
+ "loss": 0.5163,
+ "step": 338
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8885793871866295e-05,
+ "loss": 0.5452,
+ "step": 339
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8941504178272984e-05,
+ "loss": 0.547,
+ "step": 340
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8997214484679666e-05,
+ "loss": 0.5442,
+ "step": 341
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9052924791086354e-05,
+ "loss": 0.5389,
+ "step": 342
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.910863509749304e-05,
+ "loss": 0.5253,
+ "step": 343
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.916434540389972e-05,
+ "loss": 0.5252,
+ "step": 344
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.922005571030641e-05,
+ "loss": 0.5388,
+ "step": 345
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9275766016713095e-05,
+ "loss": 0.5336,
+ "step": 346
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9331476323119776e-05,
+ "loss": 0.5342,
+ "step": 347
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9387186629526465e-05,
+ "loss": 0.5227,
+ "step": 348
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.944289693593315e-05,
+ "loss": 0.5062,
+ "step": 349
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9498607242339835e-05,
+ "loss": 0.5286,
+ "step": 350
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.955431754874652e-05,
+ "loss": 0.5326,
+ "step": 351
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9610027855153206e-05,
+ "loss": 0.5219,
+ "step": 352
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.966573816155989e-05,
+ "loss": 0.5258,
+ "step": 353
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9721448467966576e-05,
+ "loss": 0.5307,
+ "step": 354
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.977715877437326e-05,
+ "loss": 0.5314,
+ "step": 355
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9832869080779946e-05,
+ "loss": 0.5438,
+ "step": 356
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.988857938718663e-05,
+ "loss": 0.5321,
+ "step": 357
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9944289693593316e-05,
+ "loss": 0.5139,
+ "step": 358
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 2e-05,
+ "loss": 0.5207,
+ "step": 359
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99999996328208e-05,
+ "loss": 0.5364,
+ "step": 360
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999998531283215e-05,
+ "loss": 0.54,
+ "step": 361
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999996695387335e-05,
+ "loss": 0.5216,
+ "step": 362
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999994125133287e-05,
+ "loss": 0.5454,
+ "step": 363
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999990820521264e-05,
+ "loss": 0.5464,
+ "step": 364
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999998678155151e-05,
+ "loss": 0.5201,
+ "step": 365
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999998200822432e-05,
+ "loss": 0.541,
+ "step": 366
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999976500540042e-05,
+ "loss": 0.5372,
+ "step": 367
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999970258499083e-05,
+ "loss": 0.5408,
+ "step": 368
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99999632821019e-05,
+ "loss": 0.5416,
+ "step": 369
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999955571349014e-05,
+ "loss": 0.5459,
+ "step": 370
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999947126240977e-05,
+ "loss": 0.5258,
+ "step": 371
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999937946778418e-05,
+ "loss": 0.5256,
+ "step": 372
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999992803296201e-05,
+ "loss": 0.5362,
+ "step": 373
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999917384792477e-05,
+ "loss": 0.5381,
+ "step": 374
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999906002270605e-05,
+ "loss": 0.536,
+ "step": 375
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999989388539723e-05,
+ "loss": 0.5304,
+ "step": 376
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999881034173242e-05,
+ "loss": 0.5351,
+ "step": 377
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999986744859958e-05,
+ "loss": 0.5387,
+ "step": 378
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999985312867725e-05,
+ "loss": 0.5333,
+ "step": 379
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999838074407296e-05,
+ "loss": 0.5152,
+ "step": 380
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999822285790825e-05,
+ "loss": 0.516,
+ "step": 381
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999805762829e-05,
+ "loss": 0.539,
+ "step": 382
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999978850552303e-05,
+ "loss": 0.5299,
+ "step": 383
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999770513874187e-05,
+ "loss": 0.5556,
+ "step": 384
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999751787883787e-05,
+ "loss": 0.5509,
+ "step": 385
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999973232755321e-05,
+ "loss": 0.5262,
+ "step": 386
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999971213288388e-05,
+ "loss": 0.5146,
+ "step": 387
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999691203877286e-05,
+ "loss": 0.5112,
+ "step": 388
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999966954053496e-05,
+ "loss": 0.544,
+ "step": 389
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999647142858496e-05,
+ "loss": 0.519,
+ "step": 390
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999624010849536e-05,
+ "loss": 0.5349,
+ "step": 391
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999960014450978e-05,
+ "loss": 0.5184,
+ "step": 392
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999575543840982e-05,
+ "loss": 0.5374,
+ "step": 393
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999955020884495e-05,
+ "loss": 0.5205,
+ "step": 394
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999524139523538e-05,
+ "loss": 0.5536,
+ "step": 395
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999497335878666e-05,
+ "loss": 0.5277,
+ "step": 396
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99994697979123e-05,
+ "loss": 0.5181,
+ "step": 397
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999441525626464e-05,
+ "loss": 0.5173,
+ "step": 398
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999412519023233e-05,
+ "loss": 0.5443,
+ "step": 399
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999382778104734e-05,
+ "loss": 0.5279,
+ "step": 400
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999935230287316e-05,
+ "loss": 0.5472,
+ "step": 401
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999321093330736e-05,
+ "loss": 0.5348,
+ "step": 402
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999289149479767e-05,
+ "loss": 0.5534,
+ "step": 403
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999256471322593e-05,
+ "loss": 0.5447,
+ "step": 404
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999223058861613e-05,
+ "loss": 0.5312,
+ "step": 405
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999188912099278e-05,
+ "loss": 0.5267,
+ "step": 406
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99991540310381e-05,
+ "loss": 0.5221,
+ "step": 407
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999118415680642e-05,
+ "loss": 0.5456,
+ "step": 408
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999908206602952e-05,
+ "loss": 0.5202,
+ "step": 409
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999044982087394e-05,
+ "loss": 0.5202,
+ "step": 410
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999007163856998e-05,
+ "loss": 0.5302,
+ "step": 411
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998968611341102e-05,
+ "loss": 0.5081,
+ "step": 412
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998929324542543e-05,
+ "loss": 0.5599,
+ "step": 413
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99988893034642e-05,
+ "loss": 0.5327,
+ "step": 414
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998848548109017e-05,
+ "loss": 0.5236,
+ "step": 415
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998807058479986e-05,
+ "loss": 0.5366,
+ "step": 416
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998764834580147e-05,
+ "loss": 0.5525,
+ "step": 417
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998721876412613e-05,
+ "loss": 0.5199,
+ "step": 418
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998678183980532e-05,
+ "loss": 0.518,
+ "step": 419
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999863375728711e-05,
+ "loss": 0.5472,
+ "step": 420
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998588596335612e-05,
+ "loss": 0.5363,
+ "step": 421
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998542701129357e-05,
+ "loss": 0.5383,
+ "step": 422
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999849607167171e-05,
+ "loss": 0.5367,
+ "step": 423
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99984487079661e-05,
+ "loss": 0.5358,
+ "step": 424
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998400610016003e-05,
+ "loss": 0.5414,
+ "step": 425
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998351777824956e-05,
+ "loss": 0.5361,
+ "step": 426
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998302211396537e-05,
+ "loss": 0.5266,
+ "step": 427
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999825191073439e-05,
+ "loss": 0.5149,
+ "step": 428
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998200875842206e-05,
+ "loss": 0.5253,
+ "step": 429
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998149106723737e-05,
+ "loss": 0.5362,
+ "step": 430
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998096603382785e-05,
+ "loss": 0.5377,
+ "step": 431
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998043365823205e-05,
+ "loss": 0.5397,
+ "step": 432
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99979893940489e-05,
+ "loss": 0.5267,
+ "step": 433
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999793468806384e-05,
+ "loss": 0.5379,
+ "step": 434
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997879247872042e-05,
+ "loss": 0.5283,
+ "step": 435
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997823073477577e-05,
+ "loss": 0.5098,
+ "step": 436
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997766164884572e-05,
+ "loss": 0.5102,
+ "step": 437
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997708522097202e-05,
+ "loss": 0.5374,
+ "step": 438
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997650145119702e-05,
+ "loss": 0.5158,
+ "step": 439
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997591033956353e-05,
+ "loss": 0.5019,
+ "step": 440
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997531188611507e-05,
+ "loss": 0.5368,
+ "step": 441
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999747060908955e-05,
+ "loss": 0.5247,
+ "step": 442
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997409295394938e-05,
+ "loss": 0.5346,
+ "step": 443
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999734724753217e-05,
+ "loss": 0.5386,
+ "step": 444
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99972844655058e-05,
+ "loss": 0.5305,
+ "step": 445
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999722094932044e-05,
+ "loss": 0.5347,
+ "step": 446
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997156698980755e-05,
+ "loss": 0.5309,
+ "step": 447
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997091714491465e-05,
+ "loss": 0.5383,
+ "step": 448
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999702599585734e-05,
+ "loss": 0.524,
+ "step": 449
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996959543083207e-05,
+ "loss": 0.5387,
+ "step": 450
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996892356173946e-05,
+ "loss": 0.5336,
+ "step": 451
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996824435134486e-05,
+ "loss": 0.5338,
+ "step": 452
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996755779969827e-05,
+ "loss": 0.5231,
+ "step": 453
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996686390685e-05,
+ "loss": 0.5371,
+ "step": 454
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996616267285104e-05,
+ "loss": 0.5467,
+ "step": 455
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996545409775286e-05,
+ "loss": 0.5239,
+ "step": 456
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996473818160752e-05,
+ "loss": 0.5296,
+ "step": 457
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999640149244676e-05,
+ "loss": 0.5514,
+ "step": 458
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996328432638622e-05,
+ "loss": 0.5196,
+ "step": 459
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996254638741702e-05,
+ "loss": 0.5297,
+ "step": 460
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999618011076142e-05,
+ "loss": 0.5309,
+ "step": 461
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996104848703243e-05,
+ "loss": 0.5313,
+ "step": 462
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996028852572705e-05,
+ "loss": 0.5292,
+ "step": 463
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995952122375385e-05,
+ "loss": 0.5368,
+ "step": 464
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995874658116917e-05,
+ "loss": 0.5373,
+ "step": 465
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999579645980299e-05,
+ "loss": 0.5392,
+ "step": 466
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995717527439348e-05,
+ "loss": 0.5315,
+ "step": 467
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995637861031786e-05,
+ "loss": 0.5325,
+ "step": 468
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995557460586153e-05,
+ "loss": 0.5468,
+ "step": 469
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995476326108355e-05,
+ "loss": 0.5525,
+ "step": 470
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995394457604354e-05,
+ "loss": 0.5133,
+ "step": 471
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995311855080155e-05,
+ "loss": 0.5228,
+ "step": 472
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995228518541828e-05,
+ "loss": 0.5394,
+ "step": 473
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999514444799549e-05,
+ "loss": 0.5449,
+ "step": 474
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995059643447313e-05,
+ "loss": 0.5181,
+ "step": 475
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994974104903536e-05,
+ "loss": 0.533,
+ "step": 476
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999488783237043e-05,
+ "loss": 0.5344,
+ "step": 477
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999480082585433e-05,
+ "loss": 0.5248,
+ "step": 478
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999471308536163e-05,
+ "loss": 0.5394,
+ "step": 479
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994624610898778e-05,
+ "loss": 0.5263,
+ "step": 480
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999453540247226e-05,
+ "loss": 0.5065,
+ "step": 481
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994445460088635e-05,
+ "loss": 0.5423,
+ "step": 482
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994354783754504e-05,
+ "loss": 0.5219,
+ "step": 483
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994263373476526e-05,
+ "loss": 0.5298,
+ "step": 484
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994171229261417e-05,
+ "loss": 0.5212,
+ "step": 485
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999407835111594e-05,
+ "loss": 0.5283,
+ "step": 486
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999398473904692e-05,
+ "loss": 0.5377,
+ "step": 487
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999389039306123e-05,
+ "loss": 0.536,
+ "step": 488
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993795313165795e-05,
+ "loss": 0.5229,
+ "step": 489
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99936994993676e-05,
+ "loss": 0.5259,
+ "step": 490
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999360295167368e-05,
+ "loss": 0.5236,
+ "step": 491
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993505670091123e-05,
+ "loss": 0.5245,
+ "step": 492
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999340765462708e-05,
+ "loss": 0.5348,
+ "step": 493
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993308905288745e-05,
+ "loss": 0.5415,
+ "step": 494
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993209422083367e-05,
+ "loss": 0.5391,
+ "step": 495
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999310920501825e-05,
+ "loss": 0.5202,
+ "step": 496
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993008254100765e-05,
+ "loss": 0.5172,
+ "step": 497
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992906569338314e-05,
+ "loss": 0.534,
+ "step": 498
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999280415073837e-05,
+ "loss": 0.5294,
+ "step": 499
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992700998308453e-05,
+ "loss": 0.5486,
+ "step": 500
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992597112056134e-05,
+ "loss": 0.5134,
+ "step": 501
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992492491989045e-05,
+ "loss": 0.5241,
+ "step": 502
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999238713811487e-05,
+ "loss": 0.528,
+ "step": 503
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999228105044135e-05,
+ "loss": 0.5463,
+ "step": 504
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992174228976265e-05,
+ "loss": 0.5119,
+ "step": 505
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999206667372747e-05,
+ "loss": 0.5352,
+ "step": 506
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991958384702855e-05,
+ "loss": 0.5365,
+ "step": 507
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999184936191038e-05,
+ "loss": 0.5205,
+ "step": 508
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991739605358042e-05,
+ "loss": 0.5034,
+ "step": 509
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991629115053908e-05,
+ "loss": 0.5319,
+ "step": 510
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999151789100609e-05,
+ "loss": 0.5195,
+ "step": 511
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991405933222758e-05,
+ "loss": 0.5319,
+ "step": 512
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991293241712128e-05,
+ "loss": 0.5359,
+ "step": 513
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999117981648248e-05,
+ "loss": 0.5251,
+ "step": 514
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991065657542146e-05,
+ "loss": 0.5134,
+ "step": 515
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990950764899502e-05,
+ "loss": 0.5365,
+ "step": 516
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999083513856299e-05,
+ "loss": 0.5388,
+ "step": 517
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99907187785411e-05,
+ "loss": 0.5144,
+ "step": 518
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990601684842385e-05,
+ "loss": 0.5203,
+ "step": 519
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990483857475428e-05,
+ "loss": 0.5384,
+ "step": 520
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990365296448892e-05,
+ "loss": 0.5309,
+ "step": 521
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999024600177148e-05,
+ "loss": 0.5405,
+ "step": 522
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990125973451956e-05,
+ "loss": 0.5271,
+ "step": 523
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990005211499137e-05,
+ "loss": 0.5266,
+ "step": 524
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998988371592188e-05,
+ "loss": 0.521,
+ "step": 525
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998976148672912e-05,
+ "loss": 0.5432,
+ "step": 526
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998963852392982e-05,
+ "loss": 0.5378,
+ "step": 527
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998951482753302e-05,
+ "loss": 0.5218,
+ "step": 528
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99893903975478e-05,
+ "loss": 0.5309,
+ "step": 529
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99892652339833e-05,
+ "loss": 0.5238,
+ "step": 530
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9989139336848708e-05,
+ "loss": 0.5364,
+ "step": 531
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9989012706153273e-05,
+ "loss": 0.5396,
+ "step": 532
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988885341906292e-05,
+ "loss": 0.5236,
+ "step": 533
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988757244117118e-05,
+ "loss": 0.5107,
+ "step": 534
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988628412795158e-05,
+ "loss": 0.5068,
+ "step": 535
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988498847949872e-05,
+ "loss": 0.5272,
+ "step": 536
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988368549590778e-05,
+ "loss": 0.5193,
+ "step": 537
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998823751772744e-05,
+ "loss": 0.5314,
+ "step": 538
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9988105752369487e-05,
+ "loss": 0.524,
+ "step": 539
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998797325352659e-05,
+ "loss": 0.51,
+ "step": 540
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987840021208477e-05,
+ "loss": 0.5412,
+ "step": 541
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987706055424935e-05,
+ "loss": 0.5195,
+ "step": 542
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987571356185807e-05,
+ "loss": 0.5251,
+ "step": 543
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987435923500978e-05,
+ "loss": 0.5078,
+ "step": 544
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987299757380393e-05,
+ "loss": 0.5461,
+ "step": 545
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998716285783406e-05,
+ "loss": 0.5278,
+ "step": 546
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998702522487202e-05,
+ "loss": 0.5154,
+ "step": 547
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998688685850439e-05,
+ "loss": 0.5246,
+ "step": 548
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998674775874133e-05,
+ "loss": 0.5102,
+ "step": 549
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9986607925593046e-05,
+ "loss": 0.5195,
+ "step": 550
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998646735906982e-05,
+ "loss": 0.5231,
+ "step": 551
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9986326059181965e-05,
+ "loss": 0.5364,
+ "step": 552
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998618402593986e-05,
+ "loss": 0.5223,
+ "step": 553
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9986041259353937e-05,
+ "loss": 0.5358,
+ "step": 554
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985897759434677e-05,
+ "loss": 0.5318,
+ "step": 555
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998575352619262e-05,
+ "loss": 0.5339,
+ "step": 556
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985608559638364e-05,
+ "loss": 0.5275,
+ "step": 557
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985462859782544e-05,
+ "loss": 0.5343,
+ "step": 558
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985316426635863e-05,
+ "loss": 0.5217,
+ "step": 559
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985169260209075e-05,
+ "loss": 0.5284,
+ "step": 560
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998502136051299e-05,
+ "loss": 0.5254,
+ "step": 561
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984872727558468e-05,
+ "loss": 0.5316,
+ "step": 562
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998472336135642e-05,
+ "loss": 0.525,
+ "step": 563
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984573261917825e-05,
+ "loss": 0.5241,
+ "step": 564
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998442242925369e-05,
+ "loss": 0.5233,
+ "step": 565
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984270863375105e-05,
+ "loss": 0.5282,
+ "step": 566
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984118564293197e-05,
+ "loss": 0.5263,
+ "step": 567
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983965532019142e-05,
+ "loss": 0.5201,
+ "step": 568
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998381176656419e-05,
+ "loss": 0.5317,
+ "step": 569
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983657267939627e-05,
+ "loss": 0.5263,
+ "step": 570
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.99835020361568e-05,
+ "loss": 0.5158,
+ "step": 571
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983346071227107e-05,
+ "loss": 0.5344,
+ "step": 572
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983189373162003e-05,
+ "loss": 0.5306,
+ "step": 573
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983031941972994e-05,
+ "loss": 0.5402,
+ "step": 574
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998287377767164e-05,
+ "loss": 0.5339,
+ "step": 575
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982714880269557e-05,
+ "loss": 0.5216,
+ "step": 576
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998255524977842e-05,
+ "loss": 0.5053,
+ "step": 577
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982394886209943e-05,
+ "loss": 0.5199,
+ "step": 578
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982233789575904e-05,
+ "loss": 0.5293,
+ "step": 579
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982071959888138e-05,
+ "loss": 0.5093,
+ "step": 580
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998190939715852e-05,
+ "loss": 0.5355,
+ "step": 581
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9981746101399e-05,
+ "loss": 0.5191,
+ "step": 582
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998158207262156e-05,
+ "loss": 0.5267,
+ "step": 583
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998141731083825e-05,
+ "loss": 0.5117,
+ "step": 584
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9981251816061168e-05,
+ "loss": 0.5119,
+ "step": 585
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9981085588302468e-05,
+ "loss": 0.518,
+ "step": 586
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998091862757436e-05,
+ "loss": 0.5203,
+ "step": 587
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9980750933889098e-05,
+ "loss": 0.5326,
+ "step": 588
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9980582507259e-05,
+ "loss": 0.5318,
+ "step": 589
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998041334769644e-05,
+ "loss": 0.5275,
+ "step": 590
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998024345521383e-05,
+ "loss": 0.5346,
+ "step": 591
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9980072829823656e-05,
+ "loss": 0.5313,
+ "step": 592
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9979901471538442e-05,
+ "loss": 0.5433,
+ "step": 593
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997972938037077e-05,
+ "loss": 0.5223,
+ "step": 594
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9979556556333283e-05,
+ "loss": 0.5244,
+ "step": 595
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9979382999438672e-05,
+ "loss": 0.5391,
+ "step": 596
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997920870969968e-05,
+ "loss": 0.5366,
+ "step": 597
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997903368712911e-05,
+ "loss": 0.518,
+ "step": 598
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978857931739805e-05,
+ "loss": 0.5125,
+ "step": 599
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978681443544687e-05,
+ "loss": 0.5062,
+ "step": 600
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978504222556704e-05,
+ "loss": 0.51,
+ "step": 601
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978326268788873e-05,
+ "loss": 0.5224,
+ "step": 602
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978147582254266e-05,
+ "loss": 0.5183,
+ "step": 603
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977968162966e-05,
+ "loss": 0.529,
+ "step": 604
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997778801093726e-05,
+ "loss": 0.5163,
+ "step": 605
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977607126181264e-05,
+ "loss": 0.508,
+ "step": 606
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977425508711303e-05,
+ "loss": 0.5383,
+ "step": 607
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997724315854071e-05,
+ "loss": 0.5161,
+ "step": 608
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977060075682878e-05,
+ "loss": 0.5294,
+ "step": 609
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997687626015125e-05,
+ "loss": 0.5113,
+ "step": 610
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997669171195933e-05,
+ "loss": 0.525,
+ "step": 611
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9976506431120665e-05,
+ "loss": 0.5313,
+ "step": 612
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9976320417648868e-05,
+ "loss": 0.5248,
+ "step": 613
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9976133671557587e-05,
+ "loss": 0.537,
+ "step": 614
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9975946192860544e-05,
+ "loss": 0.5232,
+ "step": 615
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9975757981571512e-05,
+ "loss": 0.5132,
+ "step": 616
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.99755690377043e-05,
+ "loss": 0.531,
+ "step": 617
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997537936127279e-05,
+ "loss": 0.532,
+ "step": 618
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9975188952290915e-05,
+ "loss": 0.5399,
+ "step": 619
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997499781077265e-05,
+ "loss": 0.5195,
+ "step": 620
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997480593673203e-05,
+ "loss": 0.5213,
+ "step": 621
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9974613330183156e-05,
+ "loss": 0.5198,
+ "step": 622
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997441999114017e-05,
+ "loss": 0.5242,
+ "step": 623
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9974225919617258e-05,
+ "loss": 0.5376,
+ "step": 624
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9974031115628688e-05,
+ "loss": 0.521,
+ "step": 625
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973835579188753e-05,
+ "loss": 0.5179,
+ "step": 626
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997363931031182e-05,
+ "loss": 0.5341,
+ "step": 627
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973442309012296e-05,
+ "loss": 0.4995,
+ "step": 628
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973244575304657e-05,
+ "loss": 0.5421,
+ "step": 629
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973046109203414e-05,
+ "loss": 0.5164,
+ "step": 630
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972846910723146e-05,
+ "loss": 0.5236,
+ "step": 631
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972646979878483e-05,
+ "loss": 0.5341,
+ "step": 632
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972446316684106e-05,
+ "loss": 0.5337,
+ "step": 633
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972244921154746e-05,
+ "loss": 0.5226,
+ "step": 634
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972042793305196e-05,
+ "loss": 0.5177,
+ "step": 635
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971839933150307e-05,
+ "loss": 0.5229,
+ "step": 636
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997163634070496e-05,
+ "loss": 0.513,
+ "step": 637
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971432015984126e-05,
+ "loss": 0.5055,
+ "step": 638
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971226959002796e-05,
+ "loss": 0.4982,
+ "step": 639
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971021169776024e-05,
+ "loss": 0.5206,
+ "step": 640
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9970814648318937e-05,
+ "loss": 0.4946,
+ "step": 641
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997060739464669e-05,
+ "loss": 0.5367,
+ "step": 642
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997039940877451e-05,
+ "loss": 0.5368,
+ "step": 643
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997019069071767e-05,
+ "loss": 0.5131,
+ "step": 644
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996998124049149e-05,
+ "loss": 0.5253,
+ "step": 645
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9969771058111357e-05,
+ "loss": 0.5273,
+ "step": 646
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9969560143592705e-05,
+ "loss": 0.5247,
+ "step": 647
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996934849695102e-05,
+ "loss": 0.5292,
+ "step": 648
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9969136118201852e-05,
+ "loss": 0.5262,
+ "step": 649
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9968923007360788e-05,
+ "loss": 0.5031,
+ "step": 650
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9968709164443483e-05,
+ "loss": 0.523,
+ "step": 651
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9968494589465645e-05,
+ "loss": 0.5326,
+ "step": 652
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996827928244302e-05,
+ "loss": 0.4976,
+ "step": 653
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996806324339143e-05,
+ "loss": 0.5387,
+ "step": 654
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996784647232673e-05,
+ "loss": 0.5141,
+ "step": 655
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996762896926485e-05,
+ "loss": 0.5372,
+ "step": 656
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9967410734221757e-05,
+ "loss": 0.5209,
+ "step": 657
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9967191767213475e-05,
+ "loss": 0.5474,
+ "step": 658
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9966972068256087e-05,
+ "loss": 0.5331,
+ "step": 659
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9966751637365726e-05,
+ "loss": 0.513,
+ "step": 660
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996653047455858e-05,
+ "loss": 0.5238,
+ "step": 661
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996630857985089e-05,
+ "loss": 0.5155,
+ "step": 662
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996608595325895e-05,
+ "loss": 0.5119,
+ "step": 663
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996586259479911e-05,
+ "loss": 0.5187,
+ "step": 664
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9965638504487773e-05,
+ "loss": 0.5293,
+ "step": 665
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9965413682341393e-05,
+ "loss": 0.5285,
+ "step": 666
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996518812837648e-05,
+ "loss": 0.5239,
+ "step": 667
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964961842609602e-05,
+ "loss": 0.524,
+ "step": 668
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964734825057374e-05,
+ "loss": 0.5324,
+ "step": 669
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964507075736463e-05,
+ "loss": 0.5108,
+ "step": 670
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99642785946636e-05,
+ "loss": 0.5108,
+ "step": 671
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964049381855566e-05,
+ "loss": 0.5037,
+ "step": 672
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963819437329184e-05,
+ "loss": 0.5381,
+ "step": 673
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963588761101347e-05,
+ "loss": 0.5213,
+ "step": 674
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963357353188993e-05,
+ "loss": 0.5213,
+ "step": 675
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963125213609113e-05,
+ "loss": 0.5493,
+ "step": 676
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996289234237876e-05,
+ "loss": 0.5336,
+ "step": 677
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996265873951503e-05,
+ "loss": 0.5166,
+ "step": 678
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996242440503508e-05,
+ "loss": 0.5261,
+ "step": 679
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9962189338956124e-05,
+ "loss": 0.516,
+ "step": 680
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9961953541295413e-05,
+ "loss": 0.5128,
+ "step": 681
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9961717012070273e-05,
+ "loss": 0.5057,
+ "step": 682
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9961479751298066e-05,
+ "loss": 0.514,
+ "step": 683
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996124175899622e-05,
+ "loss": 0.5306,
+ "step": 684
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996100303518221e-05,
+ "loss": 0.5231,
+ "step": 685
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9960763579873568e-05,
+ "loss": 0.5202,
+ "step": 686
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996052339308788e-05,
+ "loss": 0.5057,
+ "step": 687
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9960282474842784e-05,
+ "loss": 0.5059,
+ "step": 688
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9960040825155968e-05,
+ "loss": 0.5282,
+ "step": 689
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9959798444045184e-05,
+ "loss": 0.5417,
+ "step": 690
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9959555331528226e-05,
+ "loss": 0.5122,
+ "step": 691
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995931148762295e-05,
+ "loss": 0.5125,
+ "step": 692
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9959066912347262e-05,
+ "loss": 0.5131,
+ "step": 693
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958821605719122e-05,
+ "loss": 0.5258,
+ "step": 694
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958575567756546e-05,
+ "loss": 0.5234,
+ "step": 695
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958328798477602e-05,
+ "loss": 0.5072,
+ "step": 696
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958081297900413e-05,
+ "loss": 0.5149,
+ "step": 697
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995783306604315e-05,
+ "loss": 0.5273,
+ "step": 698
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995758410292404e-05,
+ "loss": 0.5115,
+ "step": 699
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9957334408561374e-05,
+ "loss": 0.5219,
+ "step": 700
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9957083982973488e-05,
+ "loss": 0.5097,
+ "step": 701
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956832826178765e-05,
+ "loss": 0.5104,
+ "step": 702
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956580938195654e-05,
+ "loss": 0.5237,
+ "step": 703
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956328319042648e-05,
+ "loss": 0.519,
+ "step": 704
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956074968738306e-05,
+ "loss": 0.5404,
+ "step": 705
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9955820887301227e-05,
+ "loss": 0.5104,
+ "step": 706
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995556607475007e-05,
+ "loss": 0.5055,
+ "step": 707
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9955310531103552e-05,
+ "loss": 0.5312,
+ "step": 708
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9955054256380436e-05,
+ "loss": 0.5138,
+ "step": 709
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995479725059954e-05,
+ "loss": 0.5236,
+ "step": 710
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9954539513779737e-05,
+ "loss": 0.5212,
+ "step": 711
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9954281045939958e-05,
+ "loss": 0.5143,
+ "step": 712
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995402184709918e-05,
+ "loss": 0.5225,
+ "step": 713
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9953761917276443e-05,
+ "loss": 0.5255,
+ "step": 714
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995350125649083e-05,
+ "loss": 0.5169,
+ "step": 715
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9953239864761486e-05,
+ "loss": 0.5122,
+ "step": 716
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952977742107606e-05,
+ "loss": 0.5222,
+ "step": 717
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952714888548432e-05,
+ "loss": 0.5347,
+ "step": 718
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952451304103278e-05,
+ "loss": 0.5194,
+ "step": 719
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952186988791494e-05,
+ "loss": 0.5115,
+ "step": 720
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951921942632493e-05,
+ "loss": 0.521,
+ "step": 721
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951656165645736e-05,
+ "loss": 0.5169,
+ "step": 722
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951389657850744e-05,
+ "loss": 0.5083,
+ "step": 723
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951122419267085e-05,
+ "loss": 0.5222,
+ "step": 724
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9950854449914384e-05,
+ "loss": 0.5328,
+ "step": 725
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9950585749812326e-05,
+ "loss": 0.502,
+ "step": 726
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9950316318980632e-05,
+ "loss": 0.5185,
+ "step": 727
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99500461574391e-05,
+ "loss": 0.528,
+ "step": 728
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994977526520756e-05,
+ "loss": 0.5134,
+ "step": 729
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9949503642305908e-05,
+ "loss": 0.5163,
+ "step": 730
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9949231288754094e-05,
+ "loss": 0.5277,
+ "step": 731
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948958204572114e-05,
+ "loss": 0.5142,
+ "step": 732
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948684389780026e-05,
+ "loss": 0.5133,
+ "step": 733
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948409844397934e-05,
+ "loss": 0.5184,
+ "step": 734
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948134568446006e-05,
+ "loss": 0.4933,
+ "step": 735
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994785856194445e-05,
+ "loss": 0.5337,
+ "step": 736
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9947581824913536e-05,
+ "loss": 0.5312,
+ "step": 737
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994730435737359e-05,
+ "loss": 0.5064,
+ "step": 738
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9947026159344985e-05,
+ "loss": 0.5289,
+ "step": 739
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9946747230848152e-05,
+ "loss": 0.5196,
+ "step": 740
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994646757190357e-05,
+ "loss": 0.5098,
+ "step": 741
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9946187182531785e-05,
+ "loss": 0.5362,
+ "step": 742
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945906062753383e-05,
+ "loss": 0.5438,
+ "step": 743
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945624212589007e-05,
+ "loss": 0.5376,
+ "step": 744
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945341632059356e-05,
+ "loss": 0.508,
+ "step": 745
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945058321185175e-05,
+ "loss": 0.5277,
+ "step": 746
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994477427998728e-05,
+ "loss": 0.528,
+ "step": 747
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9944489508486528e-05,
+ "loss": 0.515,
+ "step": 748
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9944204006703828e-05,
+ "loss": 0.5223,
+ "step": 749
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9943917774660145e-05,
+ "loss": 0.5251,
+ "step": 750
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99436308123765e-05,
+ "loss": 0.51,
+ "step": 751
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9943343119873966e-05,
+ "loss": 0.5188,
+ "step": 752
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9943054697173676e-05,
+ "loss": 0.5078,
+ "step": 753
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99427655442968e-05,
+ "loss": 0.505,
+ "step": 754
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994247566126458e-05,
+ "loss": 0.5079,
+ "step": 755
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99421850480983e-05,
+ "loss": 0.521,
+ "step": 756
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9941893704819307e-05,
+ "loss": 0.5151,
+ "step": 757
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9941601631448986e-05,
+ "loss": 0.5118,
+ "step": 758
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9941308828008794e-05,
+ "loss": 0.5173,
+ "step": 759
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994101529452023e-05,
+ "loss": 0.5219,
+ "step": 760
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9940721031004853e-05,
+ "loss": 0.5182,
+ "step": 761
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9940426037484268e-05,
+ "loss": 0.5159,
+ "step": 762
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994013031398014e-05,
+ "loss": 0.5232,
+ "step": 763
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9939833860514187e-05,
+ "loss": 0.5113,
+ "step": 764
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9939536677108176e-05,
+ "loss": 0.5284,
+ "step": 765
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993923876378393e-05,
+ "loss": 0.5181,
+ "step": 766
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993894012056334e-05,
+ "loss": 0.5263,
+ "step": 767
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993864074746832e-05,
+ "loss": 0.508,
+ "step": 768
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993834064452086e-05,
+ "loss": 0.5173,
+ "step": 769
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9938039811743e-05,
+ "loss": 0.5273,
+ "step": 770
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9937738249156836e-05,
+ "loss": 0.5169,
+ "step": 771
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9937435956784506e-05,
+ "loss": 0.5033,
+ "step": 772
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9937132934648213e-05,
+ "loss": 0.4927,
+ "step": 773
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993682918277021e-05,
+ "loss": 0.5177,
+ "step": 774
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99365247011728e-05,
+ "loss": 0.51,
+ "step": 775
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9936219489878343e-05,
+ "loss": 0.5046,
+ "step": 776
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9935913548909258e-05,
+ "loss": 0.5577,
+ "step": 777
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9935606878288008e-05,
+ "loss": 0.5247,
+ "step": 778
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9935299478037114e-05,
+ "loss": 0.5033,
+ "step": 779
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993499134817915e-05,
+ "loss": 0.5286,
+ "step": 780
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9934682488736745e-05,
+ "loss": 0.5342,
+ "step": 781
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993437289973258e-05,
+ "loss": 0.5145,
+ "step": 782
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993406258118939e-05,
+ "loss": 0.5139,
+ "step": 783
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993375153312996e-05,
+ "loss": 0.5159,
+ "step": 784
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9933439755577134e-05,
+ "loss": 0.506,
+ "step": 785
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9933127248553813e-05,
+ "loss": 0.5219,
+ "step": 786
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993281401208294e-05,
+ "loss": 0.5383,
+ "step": 787
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993250004618752e-05,
+ "loss": 0.5096,
+ "step": 788
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9932185350890606e-05,
+ "loss": 0.5199,
+ "step": 789
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9931869926215315e-05,
+ "loss": 0.5117,
+ "step": 790
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9931553772184805e-05,
+ "loss": 0.5312,
+ "step": 791
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9931236888822295e-05,
+ "loss": 0.5135,
+ "step": 792
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993091927615105e-05,
+ "loss": 0.5282,
+ "step": 793
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9930600934194405e-05,
+ "loss": 0.5438,
+ "step": 794
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993028186297573e-05,
+ "loss": 0.5087,
+ "step": 795
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9929962062518458e-05,
+ "loss": 0.5244,
+ "step": 796
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9929641532846074e-05,
+ "loss": 0.5054,
+ "step": 797
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992932027398212e-05,
+ "loss": 0.5353,
+ "step": 798
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992899828595018e-05,
+ "loss": 0.5065,
+ "step": 799
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9928675568773906e-05,
+ "loss": 0.5293,
+ "step": 800
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992835212247699e-05,
+ "loss": 0.5097,
+ "step": 801
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9928027947083195e-05,
+ "loss": 0.5242,
+ "step": 802
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992770304261632e-05,
+ "loss": 0.5199,
+ "step": 803
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9927377409100222e-05,
+ "loss": 0.5333,
+ "step": 804
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992705104655882e-05,
+ "loss": 0.5338,
+ "step": 805
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992672395501608e-05,
+ "loss": 0.5206,
+ "step": 806
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992639613449602e-05,
+ "loss": 0.5262,
+ "step": 807
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9926067585022718e-05,
+ "loss": 0.5317,
+ "step": 808
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9925738306620294e-05,
+ "loss": 0.5414,
+ "step": 809
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9925408299312935e-05,
+ "loss": 0.5112,
+ "step": 810
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992507756312487e-05,
+ "loss": 0.5168,
+ "step": 811
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99247460980804e-05,
+ "loss": 0.5242,
+ "step": 812
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9924413904203847e-05,
+ "loss": 0.51,
+ "step": 813
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992408098151962e-05,
+ "loss": 0.5168,
+ "step": 814
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992374733005216e-05,
+ "loss": 0.5223,
+ "step": 815
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9923412949825975e-05,
+ "loss": 0.5066,
+ "step": 816
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9923077840865615e-05,
+ "loss": 0.5063,
+ "step": 817
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9922742003195696e-05,
+ "loss": 0.5171,
+ "step": 818
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9922405436840872e-05,
+ "loss": 0.5278,
+ "step": 819
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9922068141825864e-05,
+ "loss": 0.5183,
+ "step": 820
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9921730118175443e-05,
+ "loss": 0.5055,
+ "step": 821
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9921391365914426e-05,
+ "loss": 0.5416,
+ "step": 822
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9921051885067695e-05,
+ "loss": 0.5098,
+ "step": 823
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9920711675660178e-05,
+ "loss": 0.543,
+ "step": 824
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992037073771686e-05,
+ "loss": 0.5269,
+ "step": 825
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9920029071262778e-05,
+ "loss": 0.4967,
+ "step": 826
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9919686676323015e-05,
+ "loss": 0.5036,
+ "step": 827
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9919343552922727e-05,
+ "loss": 0.518,
+ "step": 828
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9918999701087104e-05,
+ "loss": 0.5273,
+ "step": 829
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9918655120841403e-05,
+ "loss": 0.5271,
+ "step": 830
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991830981221092e-05,
+ "loss": 0.5263,
+ "step": 831
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991796377522102e-05,
+ "loss": 0.5187,
+ "step": 832
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9917617009897113e-05,
+ "loss": 0.5042,
+ "step": 833
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9917269516264662e-05,
+ "loss": 0.5248,
+ "step": 834
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9916921294349187e-05,
+ "loss": 0.4992,
+ "step": 835
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9916572344176258e-05,
+ "loss": 0.5347,
+ "step": 836
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9916222665771506e-05,
+ "loss": 0.5343,
+ "step": 837
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9915872259160603e-05,
+ "loss": 0.511,
+ "step": 838
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991552112436929e-05,
+ "loss": 0.5374,
+ "step": 839
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991516926142334e-05,
+ "loss": 0.5074,
+ "step": 840
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99148166703486e-05,
+ "loss": 0.5287,
+ "step": 841
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991446335117097e-05,
+ "loss": 0.5089,
+ "step": 842
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991410930391638e-05,
+ "loss": 0.5148,
+ "step": 843
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9913754528610846e-05,
+ "loss": 0.5282,
+ "step": 844
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991339902528041e-05,
+ "loss": 0.5093,
+ "step": 845
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9913042793951184e-05,
+ "loss": 0.5292,
+ "step": 846
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9912685834649324e-05,
+ "loss": 0.5164,
+ "step": 847
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991232814740105e-05,
+ "loss": 0.5011,
+ "step": 848
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991196973223262e-05,
+ "loss": 0.5238,
+ "step": 849
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9911610589170363e-05,
+ "loss": 0.5173,
+ "step": 850
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9911250718240653e-05,
+ "loss": 0.5082,
+ "step": 851
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991089011946991e-05,
+ "loss": 0.5063,
+ "step": 852
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991052879288462e-05,
+ "loss": 0.5203,
+ "step": 853
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9910166738511315e-05,
+ "loss": 0.5008,
+ "step": 854
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9909803956376588e-05,
+ "loss": 0.5135,
+ "step": 855
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9909440446507074e-05,
+ "loss": 0.5087,
+ "step": 856
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990907620892947e-05,
+ "loss": 0.5175,
+ "step": 857
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9908711243670526e-05,
+ "loss": 0.5173,
+ "step": 858
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990834555075704e-05,
+ "loss": 0.5081,
+ "step": 859
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9907979130215868e-05,
+ "loss": 0.517,
+ "step": 860
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990761198207392e-05,
+ "loss": 0.5276,
+ "step": 861
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9907244106358158e-05,
+ "loss": 0.5121,
+ "step": 862
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9906875503095594e-05,
+ "loss": 0.5236,
+ "step": 863
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99065061723133e-05,
+ "loss": 0.524,
+ "step": 864
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9906136114038398e-05,
+ "loss": 0.5112,
+ "step": 865
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990576532829806e-05,
+ "loss": 0.5318,
+ "step": 866
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990539381511952e-05,
+ "loss": 0.5188,
+ "step": 867
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9905021574530055e-05,
+ "loss": 0.5064,
+ "step": 868
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9904648606557007e-05,
+ "loss": 0.528,
+ "step": 869
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9904274911227762e-05,
+ "loss": 0.5179,
+ "step": 870
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990390048856976e-05,
+ "loss": 0.5177,
+ "step": 871
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99035253386105e-05,
+ "loss": 0.516,
+ "step": 872
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9903149461377532e-05,
+ "loss": 0.525,
+ "step": 873
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9902772856898457e-05,
+ "loss": 0.5407,
+ "step": 874
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9902395525200933e-05,
+ "loss": 0.5232,
+ "step": 875
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9902017466312668e-05,
+ "loss": 0.5302,
+ "step": 876
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9901638680261426e-05,
+ "loss": 0.5218,
+ "step": 877
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9901259167075023e-05,
+ "loss": 0.5213,
+ "step": 878
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9900878926781327e-05,
+ "loss": 0.5346,
+ "step": 879
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990049795940827e-05,
+ "loss": 0.5155,
+ "step": 880
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9900116264983815e-05,
+ "loss": 0.523,
+ "step": 881
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9899733843536e-05,
+ "loss": 0.5037,
+ "step": 882
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9899350695092914e-05,
+ "loss": 0.516,
+ "step": 883
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.989896681968268e-05,
+ "loss": 0.5274,
+ "step": 884
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.98985822173335e-05,
+ "loss": 0.5063,
+ "step": 885
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9898196888073612e-05,
+ "loss": 0.507,
+ "step": 886
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9897810831931314e-05,
+ "loss": 0.5332,
+ "step": 887
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.989742404893496e-05,
+ "loss": 0.5391,
+ "step": 888
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9897036539112945e-05,
+ "loss": 0.5041,
+ "step": 889
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9896648302493734e-05,
+ "loss": 0.5138,
+ "step": 890
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9896259339105835e-05,
+ "loss": 0.5398,
+ "step": 891
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9895869648977812e-05,
+ "loss": 0.516,
+ "step": 892
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9895479232138282e-05,
+ "loss": 0.5177,
+ "step": 893
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9895088088615915e-05,
+ "loss": 0.4917,
+ "step": 894
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9894696218439436e-05,
+ "loss": 0.526,
+ "step": 895
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.989430362163762e-05,
+ "loss": 0.5205,
+ "step": 896
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98939102982393e-05,
+ "loss": 0.5188,
+ "step": 897
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9893516248273362e-05,
+ "loss": 0.5392,
+ "step": 898
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.989312147176874e-05,
+ "loss": 0.5131,
+ "step": 899
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9892725968754426e-05,
+ "loss": 0.5156,
+ "step": 900
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9892329739259462e-05,
+ "loss": 0.4967,
+ "step": 901
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9891932783312948e-05,
+ "loss": 0.5241,
+ "step": 902
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9891535100944033e-05,
+ "loss": 0.5174,
+ "step": 903
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9891136692181926e-05,
+ "loss": 0.5355,
+ "step": 904
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.989073755705588e-05,
+ "loss": 0.5073,
+ "step": 905
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9890337695595202e-05,
+ "loss": 0.518,
+ "step": 906
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988993710782926e-05,
+ "loss": 0.5088,
+ "step": 907
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988953579378748e-05,
+ "loss": 0.5005,
+ "step": 908
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988913375349932e-05,
+ "loss": 0.5177,
+ "step": 909
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988873098699431e-05,
+ "loss": 0.5096,
+ "step": 910
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9888327494302025e-05,
+ "loss": 0.5153,
+ "step": 911
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98879232754521e-05,
+ "loss": 0.5335,
+ "step": 912
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9887518330474216e-05,
+ "loss": 0.5308,
+ "step": 913
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9887112659398108e-05,
+ "loss": 0.5303,
+ "step": 914
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9886706262253574e-05,
+ "loss": 0.5258,
+ "step": 915
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988629913907045e-05,
+ "loss": 0.5278,
+ "step": 916
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988589128987864e-05,
+ "loss": 0.5097,
+ "step": 917
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9885482714708093e-05,
+ "loss": 0.5024,
+ "step": 918
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988507341358881e-05,
+ "loss": 0.5346,
+ "step": 919
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9884663386550853e-05,
+ "loss": 0.5104,
+ "step": 920
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988425263362433e-05,
+ "loss": 0.5202,
+ "step": 921
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98838411548394e-05,
+ "loss": 0.5188,
+ "step": 922
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9883428950226294e-05,
+ "loss": 0.5121,
+ "step": 923
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9883016019815268e-05,
+ "loss": 0.5089,
+ "step": 924
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9882602363636656e-05,
+ "loss": 0.5172,
+ "step": 925
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9882187981720827e-05,
+ "loss": 0.52,
+ "step": 926
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9881772874098218e-05,
+ "loss": 0.5118,
+ "step": 927
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9881357040799312e-05,
+ "loss": 0.531,
+ "step": 928
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9880940481854646e-05,
+ "loss": 0.5273,
+ "step": 929
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9880523197294804e-05,
+ "loss": 0.5082,
+ "step": 930
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9880105187150435e-05,
+ "loss": 0.5142,
+ "step": 931
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987968645145224e-05,
+ "loss": 0.5217,
+ "step": 932
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987926699023096e-05,
+ "loss": 0.504,
+ "step": 933
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9878846803517408e-05,
+ "loss": 0.5272,
+ "step": 934
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987842589134243e-05,
+ "loss": 0.5336,
+ "step": 935
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9878004253736945e-05,
+ "loss": 0.5198,
+ "step": 936
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9877581890731915e-05,
+ "loss": 0.5233,
+ "step": 937
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987715880235835e-05,
+ "loss": 0.5315,
+ "step": 938
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9876734988647334e-05,
+ "loss": 0.5072,
+ "step": 939
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9876310449629973e-05,
+ "loss": 0.5278,
+ "step": 940
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9875885185337453e-05,
+ "loss": 0.5219,
+ "step": 941
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9875459195801e-05,
+ "loss": 0.5161,
+ "step": 942
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98750324810519e-05,
+ "loss": 0.5227,
+ "step": 943
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987460504112149e-05,
+ "loss": 0.5114,
+ "step": 944
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9874176876041157e-05,
+ "loss": 0.5262,
+ "step": 945
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9873747985842343e-05,
+ "loss": 0.508,
+ "step": 946
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9873318370556546e-05,
+ "loss": 0.5422,
+ "step": 947
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9872888030215313e-05,
+ "loss": 0.5087,
+ "step": 948
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9872456964850246e-05,
+ "loss": 0.5138,
+ "step": 949
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9872025174493003e-05,
+ "loss": 0.5138,
+ "step": 950
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9871592659175296e-05,
+ "loss": 0.5301,
+ "step": 951
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987115941892888e-05,
+ "loss": 0.4924,
+ "step": 952
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987072545378557e-05,
+ "loss": 0.5321,
+ "step": 953
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9870290763777243e-05,
+ "loss": 0.5333,
+ "step": 954
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9869855348935817e-05,
+ "loss": 0.5032,
+ "step": 955
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986941920929326e-05,
+ "loss": 0.5294,
+ "step": 956
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986898234488161e-05,
+ "loss": 0.5085,
+ "step": 957
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9868544755732948e-05,
+ "loss": 0.4924,
+ "step": 958
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9868106441879403e-05,
+ "loss": 0.496,
+ "step": 959
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9867667403353162e-05,
+ "loss": 0.5076,
+ "step": 960
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9867227640186474e-05,
+ "loss": 0.5201,
+ "step": 961
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9866787152411624e-05,
+ "loss": 0.5204,
+ "step": 962
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986634594006097e-05,
+ "loss": 0.5269,
+ "step": 963
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9865904003166904e-05,
+ "loss": 0.5226,
+ "step": 964
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9865461341761885e-05,
+ "loss": 0.5212,
+ "step": 965
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986501795587842e-05,
+ "loss": 0.5216,
+ "step": 966
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9864573845549063e-05,
+ "loss": 0.5174,
+ "step": 967
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9864129010806437e-05,
+ "loss": 0.5356,
+ "step": 968
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9863683451683204e-05,
+ "loss": 0.4997,
+ "step": 969
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9863237168212084e-05,
+ "loss": 0.5137,
+ "step": 970
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986279016042585e-05,
+ "loss": 0.5368,
+ "step": 971
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9862342428357327e-05,
+ "loss": 0.5209,
+ "step": 972
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9861893972039402e-05,
+ "loss": 0.5135,
+ "step": 973
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9861444791504997e-05,
+ "loss": 0.517,
+ "step": 974
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9860994886787106e-05,
+ "loss": 0.5308,
+ "step": 975
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9860544257918765e-05,
+ "loss": 0.5223,
+ "step": 976
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9860092904933065e-05,
+ "loss": 0.5231,
+ "step": 977
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9859640827863157e-05,
+ "loss": 0.5187,
+ "step": 978
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9859188026742235e-05,
+ "loss": 0.524,
+ "step": 979
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9858734501603553e-05,
+ "loss": 0.5258,
+ "step": 980
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985828025248041e-05,
+ "loss": 0.5138,
+ "step": 981
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985782527940617e-05,
+ "loss": 0.5222,
+ "step": 982
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9857369582414246e-05,
+ "loss": 0.5048,
+ "step": 983
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98569131615381e-05,
+ "loss": 0.498,
+ "step": 984
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985645601681125e-05,
+ "loss": 0.5268,
+ "step": 985
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9855998148267265e-05,
+ "loss": 0.5111,
+ "step": 986
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9855539555939768e-05,
+ "loss": 0.5131,
+ "step": 987
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985508023986244e-05,
+ "loss": 0.5085,
+ "step": 988
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985462020006901e-05,
+ "loss": 0.4973,
+ "step": 989
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9854159436593258e-05,
+ "loss": 0.5084,
+ "step": 990
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9853697949469027e-05,
+ "loss": 0.499,
+ "step": 991
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98532357387302e-05,
+ "loss": 0.5203,
+ "step": 992
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9852772804410728e-05,
+ "loss": 0.4915,
+ "step": 993
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98523091465446e-05,
+ "loss": 0.5183,
+ "step": 994
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9851844765165863e-05,
+ "loss": 0.505,
+ "step": 995
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9851379660308624e-05,
+ "loss": 0.5046,
+ "step": 996
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9850913832007042e-05,
+ "loss": 0.515,
+ "step": 997
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985044728029532e-05,
+ "loss": 0.503,
+ "step": 998
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984998000520772e-05,
+ "loss": 0.5179,
+ "step": 999
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9849512006778557e-05,
+ "loss": 0.5145,
+ "step": 1000
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9849043285042203e-05,
+ "loss": 0.5222,
+ "step": 1001
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9848573840033068e-05,
+ "loss": 0.4923,
+ "step": 1002
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984810367178564e-05,
+ "loss": 0.5156,
+ "step": 1003
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984763278033444e-05,
+ "loss": 0.5181,
+ "step": 1004
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9847161165714043e-05,
+ "loss": 0.5291,
+ "step": 1005
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984668882795909e-05,
+ "loss": 0.5196,
+ "step": 1006
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9846215767104266e-05,
+ "loss": 0.5165,
+ "step": 1007
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984574198318431e-05,
+ "loss": 0.5066,
+ "step": 1008
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9845267476234013e-05,
+ "loss": 0.5345,
+ "step": 1009
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984479224628822e-05,
+ "loss": 0.5275,
+ "step": 1010
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9844316293381834e-05,
+ "loss": 0.5111,
+ "step": 1011
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9843839617549805e-05,
+ "loss": 0.4976,
+ "step": 1012
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984336221882714e-05,
+ "loss": 0.5251,
+ "step": 1013
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9842884097248892e-05,
+ "loss": 0.5083,
+ "step": 1014
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9842405252850175e-05,
+ "loss": 0.5086,
+ "step": 1015
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.984192568566616e-05,
+ "loss": 0.535,
+ "step": 1016
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9841445395732054e-05,
+ "loss": 0.5005,
+ "step": 1017
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.984096438308313e-05,
+ "loss": 0.5042,
+ "step": 1018
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9840482647754716e-05,
+ "loss": 0.5152,
+ "step": 1019
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9840000189782184e-05,
+ "loss": 0.5217,
+ "step": 1020
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983951700920097e-05,
+ "loss": 0.5063,
+ "step": 1021
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9839033106046548e-05,
+ "loss": 0.5153,
+ "step": 1022
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983854848035446e-05,
+ "loss": 0.5272,
+ "step": 1023
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9838063132160292e-05,
+ "loss": 0.5123,
+ "step": 1024
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983757706149969e-05,
+ "loss": 0.5136,
+ "step": 1025
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9837090268408342e-05,
+ "loss": 0.5199,
+ "step": 1026
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9836602752922004e-05,
+ "loss": 0.5092,
+ "step": 1027
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9836114515076473e-05,
+ "loss": 0.5272,
+ "step": 1028
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98356255549076e-05,
+ "loss": 0.5041,
+ "step": 1029
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98351358724513e-05,
+ "loss": 0.529,
+ "step": 1030
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9834645467743524e-05,
+ "loss": 0.5032,
+ "step": 1031
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9834154340820296e-05,
+ "loss": 0.5256,
+ "step": 1032
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983366249171767e-05,
+ "loss": 0.5248,
+ "step": 1033
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9833169920471778e-05,
+ "loss": 0.5205,
+ "step": 1034
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9832676627118784e-05,
+ "loss": 0.5149,
+ "step": 1035
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9832182611694916e-05,
+ "loss": 0.5022,
+ "step": 1036
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983168787423645e-05,
+ "loss": 0.5143,
+ "step": 1037
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9831192414779724e-05,
+ "loss": 0.5363,
+ "step": 1038
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9830696233361113e-05,
+ "loss": 0.4941,
+ "step": 1039
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9830199330017063e-05,
+ "loss": 0.5166,
+ "step": 1040
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982970170478406e-05,
+ "loss": 0.5323,
+ "step": 1041
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9829203357698647e-05,
+ "loss": 0.5265,
+ "step": 1042
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9828704288797425e-05,
+ "loss": 0.5111,
+ "step": 1043
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982820449811704e-05,
+ "loss": 0.5161,
+ "step": 1044
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9827703985694194e-05,
+ "loss": 0.5233,
+ "step": 1045
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9827202751565644e-05,
+ "loss": 0.5273,
+ "step": 1046
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9826700795768197e-05,
+ "loss": 0.5168,
+ "step": 1047
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982619811833872e-05,
+ "loss": 0.504,
+ "step": 1048
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982569471931412e-05,
+ "loss": 0.5216,
+ "step": 1049
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982519059873137e-05,
+ "loss": 0.5331,
+ "step": 1050
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9824685756627487e-05,
+ "loss": 0.5473,
+ "step": 1051
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9824180193039545e-05,
+ "loss": 0.5213,
+ "step": 1052
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9823673908004673e-05,
+ "loss": 0.5104,
+ "step": 1053
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982316690156005e-05,
+ "loss": 0.5322,
+ "step": 1054
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9822659173742904e-05,
+ "loss": 0.52,
+ "step": 1055
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9822150724590528e-05,
+ "loss": 0.5226,
+ "step": 1056
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9821641554140252e-05,
+ "loss": 0.4941,
+ "step": 1057
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9821131662429476e-05,
+ "loss": 0.5173,
+ "step": 1058
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9820621049495637e-05,
+ "loss": 0.5042,
+ "step": 1059
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9820109715376236e-05,
+ "loss": 0.5264,
+ "step": 1060
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9819597660108823e-05,
+ "loss": 0.5155,
+ "step": 1061
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9819084883731e-05,
+ "loss": 0.5059,
+ "step": 1062
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9818571386280422e-05,
+ "loss": 0.5237,
+ "step": 1063
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9818057167794803e-05,
+ "loss": 0.5203,
+ "step": 1064
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98175422283119e-05,
+ "loss": 0.5128,
+ "step": 1065
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9817026567869527e-05,
+ "loss": 0.5125,
+ "step": 1066
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9816510186505562e-05,
+ "loss": 0.5056,
+ "step": 1067
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9815993084257913e-05,
+ "loss": 0.5249,
+ "step": 1068
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9815475261164563e-05,
+ "loss": 0.5111,
+ "step": 1069
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9814956717263534e-05,
+ "loss": 0.5204,
+ "step": 1070
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9814437452592908e-05,
+ "loss": 0.5045,
+ "step": 1071
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9813917467190817e-05,
+ "loss": 0.4943,
+ "step": 1072
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9813396761095446e-05,
+ "loss": 0.5294,
+ "step": 1073
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9812875334345032e-05,
+ "loss": 0.5243,
+ "step": 1074
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.981235318697787e-05,
+ "loss": 0.508,
+ "step": 1075
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98118303190323e-05,
+ "loss": 0.5013,
+ "step": 1076
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9811306730546728e-05,
+ "loss": 0.494,
+ "step": 1077
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9810782421559595e-05,
+ "loss": 0.5325,
+ "step": 1078
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9810257392109405e-05,
+ "loss": 0.5255,
+ "step": 1079
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9809731642234715e-05,
+ "loss": 0.5053,
+ "step": 1080
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9809205171974136e-05,
+ "loss": 0.5062,
+ "step": 1081
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9808677981366334e-05,
+ "loss": 0.5201,
+ "step": 1082
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9808150070450015e-05,
+ "loss": 0.4957,
+ "step": 1083
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980762143926395e-05,
+ "loss": 0.5247,
+ "step": 1084
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9807092087846956e-05,
+ "loss": 0.5265,
+ "step": 1085
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9806562016237913e-05,
+ "loss": 0.528,
+ "step": 1086
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9806031224475743e-05,
+ "loss": 0.5301,
+ "step": 1087
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9805499712599426e-05,
+ "loss": 0.5281,
+ "step": 1088
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9804967480647996e-05,
+ "loss": 0.5024,
+ "step": 1089
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9804434528660536e-05,
+ "loss": 0.5087,
+ "step": 1090
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9803900856676182e-05,
+ "loss": 0.5004,
+ "step": 1091
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980336646473413e-05,
+ "loss": 0.5165,
+ "step": 1092
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980283135287362e-05,
+ "loss": 0.4901,
+ "step": 1093
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9802295521133942e-05,
+ "loss": 0.5026,
+ "step": 1094
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980175896955446e-05,
+ "loss": 0.5191,
+ "step": 1095
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9801221698174564e-05,
+ "loss": 0.5122,
+ "step": 1096
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980068370703371e-05,
+ "loss": 0.5061,
+ "step": 1097
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9800144996171415e-05,
+ "loss": 0.5216,
+ "step": 1098
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.979960556562723e-05,
+ "loss": 0.5257,
+ "step": 1099
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.979906541544077e-05,
+ "loss": 0.5028,
+ "step": 1100
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9798524545651705e-05,
+ "loss": 0.5225,
+ "step": 1101
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9797982956299754e-05,
+ "loss": 0.5049,
+ "step": 1102
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9797440647424687e-05,
+ "loss": 0.5348,
+ "step": 1103
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9796897619066327e-05,
+ "loss": 0.5152,
+ "step": 1104
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9796353871264555e-05,
+ "loss": 0.5002,
+ "step": 1105
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.97958094040593e-05,
+ "loss": 0.5106,
+ "step": 1106
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9795264217490547e-05,
+ "loss": 0.5306,
+ "step": 1107
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9794718311598337e-05,
+ "loss": 0.5149,
+ "step": 1108
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9794171686422746e-05,
+ "loss": 0.4985,
+ "step": 1109
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9793624342003927e-05,
+ "loss": 0.526,
+ "step": 1110
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.979307627838207e-05,
+ "loss": 0.5112,
+ "step": 1111
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9792527495597423e-05,
+ "loss": 0.5188,
+ "step": 1112
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9791977993690292e-05,
+ "loss": 0.5096,
+ "step": 1113
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9791427772701017e-05,
+ "loss": 0.5175,
+ "step": 1114
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9790876832670018e-05,
+ "loss": 0.5098,
+ "step": 1115
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9790325173637744e-05,
+ "loss": 0.5037,
+ "step": 1116
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9789772795644714e-05,
+ "loss": 0.5231,
+ "step": 1117
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9789219698731484e-05,
+ "loss": 0.5139,
+ "step": 1118
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9788665882938677e-05,
+ "loss": 0.5106,
+ "step": 1119
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9788111348306963e-05,
+ "loss": 0.522,
+ "step": 1120
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978755609487706e-05,
+ "loss": 0.4982,
+ "step": 1121
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9787000122689753e-05,
+ "loss": 0.5091,
+ "step": 1122
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978644343178586e-05,
+ "loss": 0.5313,
+ "step": 1123
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978588602220627e-05,
+ "loss": 0.5007,
+ "step": 1124
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978532789399191e-05,
+ "loss": 0.5144,
+ "step": 1125
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978476904718377e-05,
+ "loss": 0.5293,
+ "step": 1126
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9784209481822892e-05,
+ "loss": 0.5137,
+ "step": 1127
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9783649197950362e-05,
+ "loss": 0.4985,
+ "step": 1128
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978308819560733e-05,
+ "loss": 0.5455,
+ "step": 1129
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9782526474834988e-05,
+ "loss": 0.4913,
+ "step": 1130
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978196403567459e-05,
+ "loss": 0.5198,
+ "step": 1131
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9781400878167446e-05,
+ "loss": 0.5024,
+ "step": 1132
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.97808370023549e-05,
+ "loss": 0.5142,
+ "step": 1133
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978027240827837e-05,
+ "loss": 0.5143,
+ "step": 1134
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.977970709597931e-05,
+ "loss": 0.5094,
+ "step": 1135
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977914106549924e-05,
+ "loss": 0.5372,
+ "step": 1136
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9778574316879724e-05,
+ "loss": 0.5168,
+ "step": 1137
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9778006850162384e-05,
+ "loss": 0.4953,
+ "step": 1138
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9777438665388885e-05,
+ "loss": 0.5212,
+ "step": 1139
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9776869762600963e-05,
+ "loss": 0.5067,
+ "step": 1140
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977630014184039e-05,
+ "loss": 0.5148,
+ "step": 1141
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9775729803148994e-05,
+ "loss": 0.5136,
+ "step": 1142
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9775158746568665e-05,
+ "loss": 0.508,
+ "step": 1143
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9774586972141337e-05,
+ "loss": 0.5262,
+ "step": 1144
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9774014479908996e-05,
+ "loss": 0.5161,
+ "step": 1145
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977344126991368e-05,
+ "loss": 0.5174,
+ "step": 1146
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9772867342197494e-05,
+ "loss": 0.5228,
+ "step": 1147
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977229269680258e-05,
+ "loss": 0.5263,
+ "step": 1148
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9771717333771133e-05,
+ "loss": 0.4995,
+ "step": 1149
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9771141253145405e-05,
+ "loss": 0.5082,
+ "step": 1150
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977056445496771e-05,
+ "loss": 0.5178,
+ "step": 1151
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.97699869392804e-05,
+ "loss": 0.5053,
+ "step": 1152
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9769408706125882e-05,
+ "loss": 0.5052,
+ "step": 1153
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9768829755546625e-05,
+ "loss": 0.5217,
+ "step": 1154
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9768250087585143e-05,
+ "loss": 0.5274,
+ "step": 1155
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9767669702284e-05,
+ "loss": 0.5186,
+ "step": 1156
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9767088599685828e-05,
+ "loss": 0.5069,
+ "step": 1157
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9766506779833288e-05,
+ "loss": 0.523,
+ "step": 1158
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.976592424276911e-05,
+ "loss": 0.4902,
+ "step": 1159
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.976534098853608e-05,
+ "loss": 0.5006,
+ "step": 1160
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9764757017177025e-05,
+ "loss": 0.5004,
+ "step": 1161
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9764172328734828e-05,
+ "loss": 0.5145,
+ "step": 1162
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9763586923252428e-05,
+ "loss": 0.493,
+ "step": 1163
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9763000800772812e-05,
+ "loss": 0.5021,
+ "step": 1164
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9762413961339025e-05,
+ "loss": 0.5073,
+ "step": 1165
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9761826404994166e-05,
+ "loss": 0.5356,
+ "step": 1166
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9761238131781373e-05,
+ "loss": 0.523,
+ "step": 1167
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9760649141743855e-05,
+ "loss": 0.513,
+ "step": 1168
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9760059434924857e-05,
+ "loss": 0.5363,
+ "step": 1169
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9759469011367695e-05,
+ "loss": 0.5097,
+ "step": 1170
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975887787111572e-05,
+ "loss": 0.5259,
+ "step": 1171
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975828601421234e-05,
+ "loss": 0.5167,
+ "step": 1172
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975769344070103e-05,
+ "loss": 0.4906,
+ "step": 1173
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9757100150625295e-05,
+ "loss": 0.525,
+ "step": 1174
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975650614402871e-05,
+ "loss": 0.5207,
+ "step": 1175
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975591142095489e-05,
+ "loss": 0.5033,
+ "step": 1176
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9755315981447513e-05,
+ "loss": 0.5178,
+ "step": 1177
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975471982555031e-05,
+ "loss": 0.4966,
+ "step": 1178
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9754122953307052e-05,
+ "loss": 0.524,
+ "step": 1179
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9753525364761577e-05,
+ "loss": 0.5143,
+ "step": 1180
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975292705995777e-05,
+ "loss": 0.5026,
+ "step": 1181
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9752328038939562e-05,
+ "loss": 0.5305,
+ "step": 1182
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9751728301750943e-05,
+ "loss": 0.5092,
+ "step": 1183
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975112784843596e-05,
+ "loss": 0.5055,
+ "step": 1184
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975052667903871e-05,
+ "loss": 0.5055,
+ "step": 1185
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9749924793603333e-05,
+ "loss": 0.5254,
+ "step": 1186
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974932219217403e-05,
+ "loss": 0.4859,
+ "step": 1187
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9748718874795057e-05,
+ "loss": 0.524,
+ "step": 1188
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9748114841510723e-05,
+ "loss": 0.5059,
+ "step": 1189
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9747510092365373e-05,
+ "loss": 0.4723,
+ "step": 1190
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974690462740343e-05,
+ "loss": 0.4963,
+ "step": 1191
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974629844666935e-05,
+ "loss": 0.522,
+ "step": 1192
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9745691550207647e-05,
+ "loss": 0.5129,
+ "step": 1193
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9745083938062896e-05,
+ "loss": 0.5143,
+ "step": 1194
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974447561027971e-05,
+ "loss": 0.51,
+ "step": 1195
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9743866566902766e-05,
+ "loss": 0.4938,
+ "step": 1196
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974325680797679e-05,
+ "loss": 0.5115,
+ "step": 1197
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9742646333546564e-05,
+ "loss": 0.5036,
+ "step": 1198
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9742035143656907e-05,
+ "loss": 0.5087,
+ "step": 1199
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9741423238352713e-05,
+ "loss": 0.5302,
+ "step": 1200
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9740810617678912e-05,
+ "loss": 0.5194,
+ "step": 1201
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9740197281680495e-05,
+ "loss": 0.5209,
+ "step": 1202
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9739583230402503e-05,
+ "loss": 0.5251,
+ "step": 1203
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9738968463890026e-05,
+ "loss": 0.4995,
+ "step": 1204
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9738352982188217e-05,
+ "loss": 0.5176,
+ "step": 1205
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9737736785342265e-05,
+ "loss": 0.4993,
+ "step": 1206
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9737119873397427e-05,
+ "loss": 0.5252,
+ "step": 1207
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9736502246399006e-05,
+ "loss": 0.5087,
+ "step": 1208
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.973588390439236e-05,
+ "loss": 0.5036,
+ "step": 1209
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9735264847422893e-05,
+ "loss": 0.5247,
+ "step": 1210
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9734645075536063e-05,
+ "loss": 0.5141,
+ "step": 1211
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9734024588777393e-05,
+ "loss": 0.5,
+ "step": 1212
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9733403387192443e-05,
+ "loss": 0.5339,
+ "step": 1213
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.973278147082683e-05,
+ "loss": 0.5397,
+ "step": 1214
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9732158839726233e-05,
+ "loss": 0.5121,
+ "step": 1215
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9731535493936365e-05,
+ "loss": 0.5215,
+ "step": 1216
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9730911433503007e-05,
+ "loss": 0.5149,
+ "step": 1217
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.973028665847199e-05,
+ "loss": 0.4978,
+ "step": 1218
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9729661168889193e-05,
+ "loss": 0.5068,
+ "step": 1219
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9729034964800546e-05,
+ "loss": 0.5087,
+ "step": 1220
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9728408046252035e-05,
+ "loss": 0.5171,
+ "step": 1221
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9727780413289706e-05,
+ "loss": 0.4988,
+ "step": 1222
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.972715206595964e-05,
+ "loss": 0.5109,
+ "step": 1223
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9726523004307987e-05,
+ "loss": 0.5163,
+ "step": 1224
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9725893228380938e-05,
+ "loss": 0.5143,
+ "step": 1225
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9725262738224743e-05,
+ "loss": 0.4988,
+ "step": 1226
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9724631533885706e-05,
+ "loss": 0.5187,
+ "step": 1227
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9723999615410175e-05,
+ "loss": 0.4917,
+ "step": 1228
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9723366982844555e-05,
+ "loss": 0.5087,
+ "step": 1229
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.972273363623531e-05,
+ "loss": 0.5089,
+ "step": 1230
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9722099575628947e-05,
+ "loss": 0.5231,
+ "step": 1231
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9721464801072027e-05,
+ "loss": 0.526,
+ "step": 1232
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.972082931261117e-05,
+ "loss": 0.5141,
+ "step": 1233
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9720193110293033e-05,
+ "loss": 0.5202,
+ "step": 1234
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971955619416435e-05,
+ "loss": 0.5147,
+ "step": 1235
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9718918564271883e-05,
+ "loss": 0.5051,
+ "step": 1236
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9718280220662463e-05,
+ "loss": 0.5223,
+ "step": 1237
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9717641163382963e-05,
+ "loss": 0.4992,
+ "step": 1238
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9717001392480316e-05,
+ "loss": 0.5245,
+ "step": 1239
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9716360908001498e-05,
+ "loss": 0.5031,
+ "step": 1240
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9715719709993557e-05,
+ "loss": 0.525,
+ "step": 1241
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9715077798503564e-05,
+ "loss": 0.5027,
+ "step": 1242
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971443517357867e-05,
+ "loss": 0.5122,
+ "step": 1243
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971379183526606e-05,
+ "loss": 0.5119,
+ "step": 1244
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971314778361298e-05,
+ "loss": 0.5363,
+ "step": 1245
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9712503018666725e-05,
+ "loss": 0.508,
+ "step": 1246
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9711857540474653e-05,
+ "loss": 0.5225,
+ "step": 1247
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971121134908415e-05,
+ "loss": 0.4993,
+ "step": 1248
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9710564444542683e-05,
+ "loss": 0.5271,
+ "step": 1249
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9709916826897747e-05,
+ "loss": 0.502,
+ "step": 1250
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9709268496196912e-05,
+ "loss": 0.519,
+ "step": 1251
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9708619452487777e-05,
+ "loss": 0.5257,
+ "step": 1252
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9707969695818013e-05,
+ "loss": 0.5047,
+ "step": 1253
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9707319226235337e-05,
+ "loss": 0.5178,
+ "step": 1254
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9706668043787505e-05,
+ "loss": 0.5169,
+ "step": 1255
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.970601614852235e-05,
+ "loss": 0.5234,
+ "step": 1256
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9705363540487737e-05,
+ "loss": 0.5084,
+ "step": 1257
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9704710219731594e-05,
+ "loss": 0.5308,
+ "step": 1258
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9704056186301898e-05,
+ "loss": 0.4999,
+ "step": 1259
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.970340144024668e-05,
+ "loss": 0.5197,
+ "step": 1260
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9702745981614018e-05,
+ "loss": 0.5139,
+ "step": 1261
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9702089810452046e-05,
+ "loss": 0.513,
+ "step": 1262
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9701432926808955e-05,
+ "loss": 0.5229,
+ "step": 1263
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9700775330732977e-05,
+ "loss": 0.5081,
+ "step": 1264
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.970011702227241e-05,
+ "loss": 0.5058,
+ "step": 1265
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9699458001475594e-05,
+ "loss": 0.5179,
+ "step": 1266
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9698798268390927e-05,
+ "loss": 0.521,
+ "step": 1267
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9698137823066856e-05,
+ "loss": 0.5244,
+ "step": 1268
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969747666555188e-05,
+ "loss": 0.5232,
+ "step": 1269
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969681479589455e-05,
+ "loss": 0.4983,
+ "step": 1270
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9696152214143476e-05,
+ "loss": 0.4996,
+ "step": 1271
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9695488920347313e-05,
+ "loss": 0.5006,
+ "step": 1272
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969482491455477e-05,
+ "loss": 0.5173,
+ "step": 1273
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969416019681461e-05,
+ "loss": 0.5322,
+ "step": 1274
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9693494767175644e-05,
+ "loss": 0.5,
+ "step": 1275
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969282862568674e-05,
+ "loss": 0.5144,
+ "step": 1276
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969216177239682e-05,
+ "loss": 0.5095,
+ "step": 1277
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969149420735485e-05,
+ "loss": 0.4908,
+ "step": 1278
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9690825930609857e-05,
+ "loss": 0.5235,
+ "step": 1279
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9690156942210912e-05,
+ "loss": 0.5159,
+ "step": 1280
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968948724220715e-05,
+ "loss": 0.5012,
+ "step": 1281
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9688816830647743e-05,
+ "loss": 0.5233,
+ "step": 1282
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9688145707581927e-05,
+ "loss": 0.5285,
+ "step": 1283
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9687473873058987e-05,
+ "loss": 0.4938,
+ "step": 1284
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9686801327128256e-05,
+ "loss": 0.5234,
+ "step": 1285
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968612806983913e-05,
+ "loss": 0.5155,
+ "step": 1286
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9685454101241048e-05,
+ "loss": 0.5218,
+ "step": 1287
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9684779421383496e-05,
+ "loss": 0.5122,
+ "step": 1288
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968410403031603e-05,
+ "loss": 0.5191,
+ "step": 1289
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9683427928088243e-05,
+ "loss": 0.5145,
+ "step": 1290
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9682751114749783e-05,
+ "loss": 0.4944,
+ "step": 1291
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968207359035036e-05,
+ "loss": 0.5042,
+ "step": 1292
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9681395354939714e-05,
+ "loss": 0.5227,
+ "step": 1293
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9680716408567667e-05,
+ "loss": 0.4942,
+ "step": 1294
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968003675128407e-05,
+ "loss": 0.5026,
+ "step": 1295
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.967935638313884e-05,
+ "loss": 0.5096,
+ "step": 1296
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9678675304181932e-05,
+ "loss": 0.5114,
+ "step": 1297
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9677993514463368e-05,
+ "loss": 0.5041,
+ "step": 1298
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9677311014033217e-05,
+ "loss": 0.5283,
+ "step": 1299
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.967662780294159e-05,
+ "loss": 0.524,
+ "step": 1300
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9675943881238672e-05,
+ "loss": 0.5259,
+ "step": 1301
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9675259248974675e-05,
+ "loss": 0.5022,
+ "step": 1302
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.967457390619988e-05,
+ "loss": 0.5028,
+ "step": 1303
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9673887852964623e-05,
+ "loss": 0.5134,
+ "step": 1304
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9673201089319275e-05,
+ "loss": 0.5189,
+ "step": 1305
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9672513615314278e-05,
+ "loss": 0.507,
+ "step": 1306
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9671825431000107e-05,
+ "loss": 0.5226,
+ "step": 1307
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9671136536427308e-05,
+ "loss": 0.5185,
+ "step": 1308
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9670446931646463e-05,
+ "loss": 0.5154,
+ "step": 1309
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966975661670822e-05,
+ "loss": 0.5179,
+ "step": 1310
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966906559166327e-05,
+ "loss": 0.541,
+ "step": 1311
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966837385656236e-05,
+ "loss": 0.5082,
+ "step": 1312
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9667681411456286e-05,
+ "loss": 0.4997,
+ "step": 1313
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.96669882563959e-05,
+ "loss": 0.5202,
+ "step": 1314
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9666294391432108e-05,
+ "loss": 0.5297,
+ "step": 1315
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966559981661586e-05,
+ "loss": 0.5074,
+ "step": 1316
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9664904531998165e-05,
+ "loss": 0.4969,
+ "step": 1317
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9664208537630073e-05,
+ "loss": 0.5015,
+ "step": 1318
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966351183356271e-05,
+ "loss": 0.5037,
+ "step": 1319
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9662814419847228e-05,
+ "loss": 0.4986,
+ "step": 1320
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966211629653485e-05,
+ "loss": 0.5048,
+ "step": 1321
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9661417463676834e-05,
+ "loss": 0.5106,
+ "step": 1322
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966071792132451e-05,
+ "loss": 0.5144,
+ "step": 1323
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9660017669529236e-05,
+ "loss": 0.5227,
+ "step": 1324
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965931670834245e-05,
+ "loss": 0.5105,
+ "step": 1325
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965861503781562e-05,
+ "loss": 0.4987,
+ "step": 1326
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9657912658000272e-05,
+ "loss": 0.5063,
+ "step": 1327
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965720956894799e-05,
+ "loss": 0.5112,
+ "step": 1328
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9656505770710404e-05,
+ "loss": 0.5036,
+ "step": 1329
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9655801263339198e-05,
+ "loss": 0.4904,
+ "step": 1330
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965509604688611e-05,
+ "loss": 0.5203,
+ "step": 1331
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9654390121402927e-05,
+ "loss": 0.5097,
+ "step": 1332
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965368348694149e-05,
+ "loss": 0.5146,
+ "step": 1333
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965297614355369e-05,
+ "loss": 0.4991,
+ "step": 1334
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965226809129147e-05,
+ "loss": 0.5255,
+ "step": 1335
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9651559330206827e-05,
+ "loss": 0.5182,
+ "step": 1336
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9650849860351818e-05,
+ "loss": 0.5092,
+ "step": 1337
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9650139681778527e-05,
+ "loss": 0.537,
+ "step": 1338
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9649428794539122e-05,
+ "loss": 0.5066,
+ "step": 1339
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9648717198685798e-05,
+ "loss": 0.5199,
+ "step": 1340
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9648004894270816e-05,
+ "loss": 0.4998,
+ "step": 1341
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9647291881346485e-05,
+ "loss": 0.5155,
+ "step": 1342
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9646578159965163e-05,
+ "loss": 0.5068,
+ "step": 1343
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9645863730179263e-05,
+ "loss": 0.4993,
+ "step": 1344
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.964514859204125e-05,
+ "loss": 0.5225,
+ "step": 1345
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9644432745603644e-05,
+ "loss": 0.5065,
+ "step": 1346
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9643716190919014e-05,
+ "loss": 0.5013,
+ "step": 1347
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9642998928039976e-05,
+ "loss": 0.499,
+ "step": 1348
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.96422809570192e-05,
+ "loss": 0.515,
+ "step": 1349
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9641562277909424e-05,
+ "loss": 0.5082,
+ "step": 1350
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9640842890763413e-05,
+ "loss": 0.5162,
+ "step": 1351
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9640122795633997e-05,
+ "loss": 0.4928,
+ "step": 1352
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9639401992574065e-05,
+ "loss": 0.4976,
+ "step": 1353
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9638680481636535e-05,
+ "loss": 0.5015,
+ "step": 1354
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9637958262874404e-05,
+ "loss": 0.4962,
+ "step": 1355
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.963723533634071e-05,
+ "loss": 0.5228,
+ "step": 1356
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9636511702088535e-05,
+ "loss": 0.5255,
+ "step": 1357
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.963578736017102e-05,
+ "loss": 0.5213,
+ "step": 1358
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.963506231064136e-05,
+ "loss": 0.5361,
+ "step": 1359
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9634336553552803e-05,
+ "loss": 0.5014,
+ "step": 1360
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9633610088958638e-05,
+ "loss": 0.5107,
+ "step": 1361
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9632882916912217e-05,
+ "loss": 0.501,
+ "step": 1362
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9632155037466942e-05,
+ "loss": 0.513,
+ "step": 1363
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9631426450676264e-05,
+ "loss": 0.4982,
+ "step": 1364
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9630697156593688e-05,
+ "loss": 0.5127,
+ "step": 1365
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.962996715527277e-05,
+ "loss": 0.488,
+ "step": 1366
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9629236446767118e-05,
+ "loss": 0.5273,
+ "step": 1367
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.962850503113039e-05,
+ "loss": 0.506,
+ "step": 1368
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9627772908416302e-05,
+ "loss": 0.4915,
+ "step": 1369
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9627040078678617e-05,
+ "loss": 0.506,
+ "step": 1370
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9626306541971153e-05,
+ "loss": 0.5139,
+ "step": 1371
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.962557229834777e-05,
+ "loss": 0.4852,
+ "step": 1372
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9624837347862398e-05,
+ "loss": 0.532,
+ "step": 1373
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9624101690569e-05,
+ "loss": 0.5052,
+ "step": 1374
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9623365326521603e-05,
+ "loss": 0.5007,
+ "step": 1375
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9622628255774288e-05,
+ "loss": 0.4933,
+ "step": 1376
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9621890478381175e-05,
+ "loss": 0.5235,
+ "step": 1377
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9621151994396443e-05,
+ "loss": 0.5125,
+ "step": 1378
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.962041280387433e-05,
+ "loss": 0.5039,
+ "step": 1379
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9619672906869114e-05,
+ "loss": 0.5263,
+ "step": 1380
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961893230343513e-05,
+ "loss": 0.5178,
+ "step": 1381
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9618190993626768e-05,
+ "loss": 0.5091,
+ "step": 1382
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961744897749846e-05,
+ "loss": 0.5201,
+ "step": 1383
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9616706255104705e-05,
+ "loss": 0.5166,
+ "step": 1384
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9615962826500038e-05,
+ "loss": 0.5028,
+ "step": 1385
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961521869173906e-05,
+ "loss": 0.5015,
+ "step": 1386
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9614473850876413e-05,
+ "loss": 0.507,
+ "step": 1387
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9613728303966794e-05,
+ "loss": 0.513,
+ "step": 1388
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961298205106496e-05,
+ "loss": 0.5002,
+ "step": 1389
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9612235092225704e-05,
+ "loss": 0.5226,
+ "step": 1390
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9611487427503883e-05,
+ "loss": 0.4932,
+ "step": 1391
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9610739056954406e-05,
+ "loss": 0.5077,
+ "step": 1392
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9609989980632222e-05,
+ "loss": 0.5023,
+ "step": 1393
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9609240198592344e-05,
+ "loss": 0.52,
+ "step": 1394
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9608489710889837e-05,
+ "loss": 0.488,
+ "step": 1395
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9607738517579807e-05,
+ "loss": 0.4979,
+ "step": 1396
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9606986618717428e-05,
+ "loss": 0.5187,
+ "step": 1397
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9606234014357905e-05,
+ "loss": 0.5141,
+ "step": 1398
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9605480704556516e-05,
+ "loss": 0.5124,
+ "step": 1399
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960472668936857e-05,
+ "loss": 0.4959,
+ "step": 1400
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960397196884945e-05,
+ "loss": 0.495,
+ "step": 1401
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960321654305457e-05,
+ "loss": 0.514,
+ "step": 1402
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9602460412039416e-05,
+ "loss": 0.5115,
+ "step": 1403
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9601703575859504e-05,
+ "loss": 0.527,
+ "step": 1404
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960094603457042e-05,
+ "loss": 0.5074,
+ "step": 1405
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960018778822779e-05,
+ "loss": 0.51,
+ "step": 1406
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9599428836887302e-05,
+ "loss": 0.5231,
+ "step": 1407
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9598669180604685e-05,
+ "loss": 0.5108,
+ "step": 1408
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959790881943573e-05,
+ "loss": 0.5175,
+ "step": 1409
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959714775343627e-05,
+ "loss": 0.4948,
+ "step": 1410
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9596385982662197e-05,
+ "loss": 0.5196,
+ "step": 1411
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959562350716945e-05,
+ "loss": 0.4951,
+ "step": 1412
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959486032701403e-05,
+ "loss": 0.5001,
+ "step": 1413
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959409644225197e-05,
+ "loss": 0.5112,
+ "step": 1414
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959333185293937e-05,
+ "loss": 0.5144,
+ "step": 1415
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9592566559132384e-05,
+ "loss": 0.5077,
+ "step": 1416
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9591800560887207e-05,
+ "loss": 0.5186,
+ "step": 1417
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9591033858260094e-05,
+ "loss": 0.5239,
+ "step": 1418
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9590266451307348e-05,
+ "loss": 0.5225,
+ "step": 1419
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.958949834008532e-05,
+ "loss": 0.5016,
+ "step": 1420
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.958872952465042e-05,
+ "loss": 0.4952,
+ "step": 1421
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9587960005059104e-05,
+ "loss": 0.4957,
+ "step": 1422
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9587189781367888e-05,
+ "loss": 0.5117,
+ "step": 1423
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.958641885363333e-05,
+ "loss": 0.5254,
+ "step": 1424
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9585647221912044e-05,
+ "loss": 0.5041,
+ "step": 1425
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9584874886260695e-05,
+ "loss": 0.4954,
+ "step": 1426
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9584101846736002e-05,
+ "loss": 0.5099,
+ "step": 1427
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9583328103394733e-05,
+ "loss": 0.5261,
+ "step": 1428
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9582553656293707e-05,
+ "loss": 0.4948,
+ "step": 1429
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9581778505489797e-05,
+ "loss": 0.5298,
+ "step": 1430
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9581002651039928e-05,
+ "loss": 0.5066,
+ "step": 1431
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9580226093001077e-05,
+ "loss": 0.5078,
+ "step": 1432
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9579448831430264e-05,
+ "loss": 0.5214,
+ "step": 1433
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9578670866384574e-05,
+ "loss": 0.5257,
+ "step": 1434
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9577892197921136e-05,
+ "loss": 0.5086,
+ "step": 1435
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9577112826097134e-05,
+ "loss": 0.5219,
+ "step": 1436
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.95763327509698e-05,
+ "loss": 0.509,
+ "step": 1437
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9575551972596422e-05,
+ "loss": 0.5082,
+ "step": 1438
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9574770491034333e-05,
+ "loss": 0.5165,
+ "step": 1439
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9573988306340924e-05,
+ "loss": 0.5104,
+ "step": 1440
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9573205418573634e-05,
+ "loss": 0.5131,
+ "step": 1441
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9572421827789954e-05,
+ "loss": 0.5001,
+ "step": 1442
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.957163753404743e-05,
+ "loss": 0.5068,
+ "step": 1443
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.957085253740366e-05,
+ "loss": 0.5094,
+ "step": 1444
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9570066837916285e-05,
+ "loss": 0.504,
+ "step": 1445
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956928043564301e-05,
+ "loss": 0.5258,
+ "step": 1446
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956849333064158e-05,
+ "loss": 0.5101,
+ "step": 1447
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9567705522969796e-05,
+ "loss": 0.5094,
+ "step": 1448
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9566917012685515e-05,
+ "loss": 0.5293,
+ "step": 1449
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9566127799846642e-05,
+ "loss": 0.515,
+ "step": 1450
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9565337884511128e-05,
+ "loss": 0.4926,
+ "step": 1451
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956454726673699e-05,
+ "loss": 0.5152,
+ "step": 1452
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9563755946582277e-05,
+ "loss": 0.5183,
+ "step": 1453
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956296392410511e-05,
+ "loss": 0.5313,
+ "step": 1454
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9562171199363646e-05,
+ "loss": 0.4952,
+ "step": 1455
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9561377772416103e-05,
+ "loss": 0.5244,
+ "step": 1456
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9560583643320745e-05,
+ "loss": 0.5044,
+ "step": 1457
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.955978881213589e-05,
+ "loss": 0.5245,
+ "step": 1458
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9558993278919904e-05,
+ "loss": 0.5117,
+ "step": 1459
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9558197043731214e-05,
+ "loss": 0.4932,
+ "step": 1460
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9557400106628285e-05,
+ "loss": 0.4863,
+ "step": 1461
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9556602467669645e-05,
+ "loss": 0.5167,
+ "step": 1462
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9555804126913868e-05,
+ "loss": 0.5063,
+ "step": 1463
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9555005084419585e-05,
+ "loss": 0.5097,
+ "step": 1464
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9554205340245468e-05,
+ "loss": 0.5213,
+ "step": 1465
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.955340489445025e-05,
+ "loss": 0.4985,
+ "step": 1466
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9552603747092714e-05,
+ "loss": 0.5026,
+ "step": 1467
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9551801898231692e-05,
+ "loss": 0.506,
+ "step": 1468
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9550999347926064e-05,
+ "loss": 0.5001,
+ "step": 1469
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.955019609623477e-05,
+ "loss": 0.5154,
+ "step": 1470
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.95493921432168e-05,
+ "loss": 0.5028,
+ "step": 1471
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9548587488931187e-05,
+ "loss": 0.5032,
+ "step": 1472
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9547782133437024e-05,
+ "loss": 0.508,
+ "step": 1473
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9546976076793456e-05,
+ "loss": 0.5321,
+ "step": 1474
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954616931905967e-05,
+ "loss": 0.4916,
+ "step": 1475
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954536186029492e-05,
+ "loss": 0.4889,
+ "step": 1476
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954455370055849e-05,
+ "loss": 0.5233,
+ "step": 1477
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9543744839909743e-05,
+ "loss": 0.4962,
+ "step": 1478
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9542935278408066e-05,
+ "loss": 0.4988,
+ "step": 1479
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9542125016112913e-05,
+ "loss": 0.5181,
+ "step": 1480
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954131405308379e-05,
+ "loss": 0.5045,
+ "step": 1481
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9540502389380245e-05,
+ "loss": 0.5008,
+ "step": 1482
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.953969002506189e-05,
+ "loss": 0.522,
+ "step": 1483
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9538876960188378e-05,
+ "loss": 0.5198,
+ "step": 1484
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9538063194819418e-05,
+ "loss": 0.5029,
+ "step": 1485
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9537248729014767e-05,
+ "loss": 0.5282,
+ "step": 1486
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9536433562834235e-05,
+ "loss": 0.5243,
+ "step": 1487
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.953561769633769e-05,
+ "loss": 0.5025,
+ "step": 1488
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9534801129585044e-05,
+ "loss": 0.5192,
+ "step": 1489
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.953398386263626e-05,
+ "loss": 0.4863,
+ "step": 1490
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9533165895551356e-05,
+ "loss": 0.5097,
+ "step": 1491
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.95323472283904e-05,
+ "loss": 0.5092,
+ "step": 1492
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9531527861213514e-05,
+ "loss": 0.5021,
+ "step": 1493
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9530707794080864e-05,
+ "loss": 0.5236,
+ "step": 1494
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9529887027052676e-05,
+ "loss": 0.5116,
+ "step": 1495
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952906556018922e-05,
+ "loss": 0.5081,
+ "step": 1496
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9528243393550825e-05,
+ "loss": 0.4812,
+ "step": 1497
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9527420527197867e-05,
+ "loss": 0.5272,
+ "step": 1498
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9526596961190772e-05,
+ "loss": 0.4959,
+ "step": 1499
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952577269559002e-05,
+ "loss": 0.5129,
+ "step": 1500
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952494773045614e-05,
+ "loss": 0.5061,
+ "step": 1501
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9524122065849722e-05,
+ "loss": 0.5036,
+ "step": 1502
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9523295701831388e-05,
+ "loss": 0.5044,
+ "step": 1503
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952246863846183e-05,
+ "loss": 0.516,
+ "step": 1504
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9521640875801783e-05,
+ "loss": 0.5064,
+ "step": 1505
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9520812413912032e-05,
+ "loss": 0.5003,
+ "step": 1506
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9519983252853415e-05,
+ "loss": 0.5019,
+ "step": 1507
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9519153392686828e-05,
+ "loss": 0.5233,
+ "step": 1508
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.951832283347321e-05,
+ "loss": 0.516,
+ "step": 1509
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9517491575273552e-05,
+ "loss": 0.5068,
+ "step": 1510
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9516659618148897e-05,
+ "loss": 0.5093,
+ "step": 1511
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9515826962160342e-05,
+ "loss": 0.5433,
+ "step": 1512
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9514993607369037e-05,
+ "loss": 0.4968,
+ "step": 1513
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9514159553836177e-05,
+ "loss": 0.5295,
+ "step": 1514
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.951332480162301e-05,
+ "loss": 0.5024,
+ "step": 1515
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9512489350790838e-05,
+ "loss": 0.4909,
+ "step": 1516
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9511653201401012e-05,
+ "loss": 0.5222,
+ "step": 1517
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.951081635351494e-05,
+ "loss": 0.538,
+ "step": 1518
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9509978807194075e-05,
+ "loss": 0.5152,
+ "step": 1519
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.950914056249992e-05,
+ "loss": 0.5195,
+ "step": 1520
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9508301619494033e-05,
+ "loss": 0.496,
+ "step": 1521
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.950746197823802e-05,
+ "loss": 0.5049,
+ "step": 1522
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9506621638793548e-05,
+ "loss": 0.4945,
+ "step": 1523
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9505780601222323e-05,
+ "loss": 0.5202,
+ "step": 1524
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9504938865586107e-05,
+ "loss": 0.523,
+ "step": 1525
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9504096431946716e-05,
+ "loss": 0.522,
+ "step": 1526
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9503253300366013e-05,
+ "loss": 0.49,
+ "step": 1527
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9502409470905913e-05,
+ "loss": 0.5066,
+ "step": 1528
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.950156494362839e-05,
+ "loss": 0.4991,
+ "step": 1529
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9500719718595454e-05,
+ "loss": 0.4954,
+ "step": 1530
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9499873795869178e-05,
+ "loss": 0.5012,
+ "step": 1531
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9499027175511682e-05,
+ "loss": 0.4998,
+ "step": 1532
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9498179857585143e-05,
+ "loss": 0.5168,
+ "step": 1533
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.949733184215178e-05,
+ "loss": 0.5179,
+ "step": 1534
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9496483129273866e-05,
+ "loss": 0.5061,
+ "step": 1535
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9495633719013733e-05,
+ "loss": 0.527,
+ "step": 1536
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9494783611433754e-05,
+ "loss": 0.506,
+ "step": 1537
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9493932806596357e-05,
+ "loss": 0.5057,
+ "step": 1538
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9493081304564025e-05,
+ "loss": 0.5144,
+ "step": 1539
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9492229105399287e-05,
+ "loss": 0.518,
+ "step": 1540
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9491376209164726e-05,
+ "loss": 0.526,
+ "step": 1541
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.949052261592297e-05,
+ "loss": 0.5012,
+ "step": 1542
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948966832573671e-05,
+ "loss": 0.5005,
+ "step": 1543
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9488813338668676e-05,
+ "loss": 0.5124,
+ "step": 1544
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948795765478166e-05,
+ "loss": 0.5017,
+ "step": 1545
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9487101274138494e-05,
+ "loss": 0.5069,
+ "step": 1546
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9486244196802075e-05,
+ "loss": 0.4965,
+ "step": 1547
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9485386422835334e-05,
+ "loss": 0.5156,
+ "step": 1548
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948452795230127e-05,
+ "loss": 0.5098,
+ "step": 1549
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948366878526292e-05,
+ "loss": 0.5146,
+ "step": 1550
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948280892178338e-05,
+ "loss": 0.4822,
+ "step": 1551
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9481948361925796e-05,
+ "loss": 0.52,
+ "step": 1552
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9481087105753364e-05,
+ "loss": 0.5043,
+ "step": 1553
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948022515332933e-05,
+ "loss": 0.4827,
+ "step": 1554
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9479362504716987e-05,
+ "loss": 0.5335,
+ "step": 1555
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9478499159979693e-05,
+ "loss": 0.5135,
+ "step": 1556
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9477635119180843e-05,
+ "loss": 0.5032,
+ "step": 1557
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947677038238389e-05,
+ "loss": 0.5122,
+ "step": 1558
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947590494965234e-05,
+ "loss": 0.5083,
+ "step": 1559
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9475038821049744e-05,
+ "loss": 0.5332,
+ "step": 1560
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9474171996639702e-05,
+ "loss": 0.4818,
+ "step": 1561
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947330447648588e-05,
+ "loss": 0.5206,
+ "step": 1562
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9472436260651976e-05,
+ "loss": 0.5059,
+ "step": 1563
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947156734920175e-05,
+ "loss": 0.5188,
+ "step": 1564
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9470697742199018e-05,
+ "loss": 0.5141,
+ "step": 1565
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9469827439707632e-05,
+ "loss": 0.505,
+ "step": 1566
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946895644179151e-05,
+ "loss": 0.5005,
+ "step": 1567
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946808474851461e-05,
+ "loss": 0.5152,
+ "step": 1568
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9467212359940944e-05,
+ "loss": 0.5156,
+ "step": 1569
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9466339276134584e-05,
+ "loss": 0.5007,
+ "step": 1570
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946546549715964e-05,
+ "loss": 0.514,
+ "step": 1571
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9464591023080274e-05,
+ "loss": 0.5101,
+ "step": 1572
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9463715853960714e-05,
+ "loss": 0.5019,
+ "step": 1573
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9462839989865226e-05,
+ "loss": 0.5165,
+ "step": 1574
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9461963430858125e-05,
+ "loss": 0.5078,
+ "step": 1575
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9461086177003788e-05,
+ "loss": 0.5235,
+ "step": 1576
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946020822836663e-05,
+ "loss": 0.4954,
+ "step": 1577
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945932958501113e-05,
+ "loss": 0.5357,
+ "step": 1578
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945845024700181e-05,
+ "loss": 0.4957,
+ "step": 1579
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9457570214403242e-05,
+ "loss": 0.5249,
+ "step": 1580
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9456689487280056e-05,
+ "loss": 0.5397,
+ "step": 1581
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9455808065696925e-05,
+ "loss": 0.5026,
+ "step": 1582
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9454925949718583e-05,
+ "loss": 0.4986,
+ "step": 1583
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9454043139409803e-05,
+ "loss": 0.5172,
+ "step": 1584
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945315963483542e-05,
+ "loss": 0.5243,
+ "step": 1585
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945227543606031e-05,
+ "loss": 0.4918,
+ "step": 1586
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945139054314941e-05,
+ "loss": 0.5084,
+ "step": 1587
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945050495616769e-05,
+ "loss": 0.5445,
+ "step": 1588
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9449618675180205e-05,
+ "loss": 0.5013,
+ "step": 1589
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9448731700252025e-05,
+ "loss": 0.5026,
+ "step": 1590
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9447844031448288e-05,
+ "loss": 0.5368,
+ "step": 1591
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.944695566883418e-05,
+ "loss": 0.5089,
+ "step": 1592
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9446066612474942e-05,
+ "loss": 0.4996,
+ "step": 1593
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9445176862435864e-05,
+ "loss": 0.5315,
+ "step": 1594
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.944428641878228e-05,
+ "loss": 0.4945,
+ "step": 1595
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9443395281579583e-05,
+ "loss": 0.5109,
+ "step": 1596
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9442503450893216e-05,
+ "loss": 0.4996,
+ "step": 1597
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.944161092678867e-05,
+ "loss": 0.4923,
+ "step": 1598
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9440717709331484e-05,
+ "loss": 0.5056,
+ "step": 1599
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943982379858726e-05,
+ "loss": 0.5007,
+ "step": 1600
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943892919462164e-05,
+ "loss": 0.498,
+ "step": 1601
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943803389750032e-05,
+ "loss": 0.5099,
+ "step": 1602
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943713790728904e-05,
+ "loss": 0.5205,
+ "step": 1603
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943624122405361e-05,
+ "loss": 0.5158,
+ "step": 1604
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9435343847859873e-05,
+ "loss": 0.5149,
+ "step": 1605
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9434445778773724e-05,
+ "loss": 0.5091,
+ "step": 1606
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9433547016861124e-05,
+ "loss": 0.5026,
+ "step": 1607
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9432647562188062e-05,
+ "loss": 0.502,
+ "step": 1608
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9431747414820597e-05,
+ "loss": 0.4999,
+ "step": 1609
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9430846574824835e-05,
+ "loss": 0.5014,
+ "step": 1610
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9429945042266925e-05,
+ "loss": 0.4999,
+ "step": 1611
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9429042817213072e-05,
+ "loss": 0.5387,
+ "step": 1612
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9428139899729538e-05,
+ "loss": 0.5215,
+ "step": 1613
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9427236289882618e-05,
+ "loss": 0.49,
+ "step": 1614
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9426331987738678e-05,
+ "loss": 0.5053,
+ "step": 1615
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9425426993364126e-05,
+ "loss": 0.5108,
+ "step": 1616
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9424521306825414e-05,
+ "loss": 0.5044,
+ "step": 1617
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.942361492818906e-05,
+ "loss": 0.5024,
+ "step": 1618
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.942270785752162e-05,
+ "loss": 0.5122,
+ "step": 1619
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.942180009488971e-05,
+ "loss": 0.4883,
+ "step": 1620
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9420891640359986e-05,
+ "loss": 0.5229,
+ "step": 1621
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9419982493999164e-05,
+ "loss": 0.5099,
+ "step": 1622
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941907265587401e-05,
+ "loss": 0.506,
+ "step": 1623
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941816212605134e-05,
+ "loss": 0.5054,
+ "step": 1624
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9417250904598012e-05,
+ "loss": 0.5049,
+ "step": 1625
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941633899158095e-05,
+ "loss": 0.4866,
+ "step": 1626
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9415426387067113e-05,
+ "loss": 0.5025,
+ "step": 1627
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9414513091123527e-05,
+ "loss": 0.4994,
+ "step": 1628
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941359910381726e-05,
+ "loss": 0.4944,
+ "step": 1629
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9412684425215426e-05,
+ "loss": 0.4999,
+ "step": 1630
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.94117690553852e-05,
+ "loss": 0.5114,
+ "step": 1631
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.94108529943938e-05,
+ "loss": 0.5099,
+ "step": 1632
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9409936242308496e-05,
+ "loss": 0.4935,
+ "step": 1633
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9409018799196615e-05,
+ "loss": 0.5183,
+ "step": 1634
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940810066512553e-05,
+ "loss": 0.5118,
+ "step": 1635
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9407181840162664e-05,
+ "loss": 0.4947,
+ "step": 1636
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940626232437549e-05,
+ "loss": 0.4854,
+ "step": 1637
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9405342117831533e-05,
+ "loss": 0.5058,
+ "step": 1638
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940442122059837e-05,
+ "loss": 0.5044,
+ "step": 1639
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940349963274363e-05,
+ "loss": 0.5109,
+ "step": 1640
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940257735433499e-05,
+ "loss": 0.5157,
+ "step": 1641
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9401654385440176e-05,
+ "loss": 0.5039,
+ "step": 1642
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9400730726126967e-05,
+ "loss": 0.5233,
+ "step": 1643
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9399806376463197e-05,
+ "loss": 0.5069,
+ "step": 1644
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9398881336516743e-05,
+ "loss": 0.4975,
+ "step": 1645
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9397955606355535e-05,
+ "loss": 0.4895,
+ "step": 1646
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939702918604756e-05,
+ "loss": 0.5138,
+ "step": 1647
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939610207566084e-05,
+ "loss": 0.5043,
+ "step": 1648
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9395174275263474e-05,
+ "loss": 0.5129,
+ "step": 1649
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939424578492358e-05,
+ "loss": 0.5204,
+ "step": 1650
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939331660470935e-05,
+ "loss": 0.5179,
+ "step": 1651
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939238673468902e-05,
+ "loss": 0.4908,
+ "step": 1652
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9391456174930872e-05,
+ "loss": 0.5208,
+ "step": 1653
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9390524925503244e-05,
+ "loss": 0.5036,
+ "step": 1654
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938959298647453e-05,
+ "loss": 0.5021,
+ "step": 1655
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9388660357913155e-05,
+ "loss": 0.4836,
+ "step": 1656
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9387727039887613e-05,
+ "loss": 0.5131,
+ "step": 1657
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9386793032466447e-05,
+ "loss": 0.4923,
+ "step": 1658
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938585833571824e-05,
+ "loss": 0.4989,
+ "step": 1659
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938492294971164e-05,
+ "loss": 0.4997,
+ "step": 1660
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938398687451533e-05,
+ "loss": 0.5122,
+ "step": 1661
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938305011019806e-05,
+ "loss": 0.5224,
+ "step": 1662
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938211265682861e-05,
+ "loss": 0.5035,
+ "step": 1663
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938117451447583e-05,
+ "loss": 0.4923,
+ "step": 1664
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938023568320862e-05,
+ "loss": 0.4831,
+ "step": 1665
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.937929616309591e-05,
+ "loss": 0.5233,
+ "step": 1666
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9378355954206706e-05,
+ "loss": 0.4931,
+ "step": 1667
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9377415056610044e-05,
+ "loss": 0.5169,
+ "step": 1668
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9376473470375027e-05,
+ "loss": 0.5293,
+ "step": 1669
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9375531195570793e-05,
+ "loss": 0.4901,
+ "step": 1670
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.937458823226655e-05,
+ "loss": 0.494,
+ "step": 1671
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9373644580531538e-05,
+ "loss": 0.4901,
+ "step": 1672
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9372700240435054e-05,
+ "loss": 0.4935,
+ "step": 1673
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9371755212046448e-05,
+ "loss": 0.5092,
+ "step": 1674
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.937080949543512e-05,
+ "loss": 0.5221,
+ "step": 1675
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9369863090670518e-05,
+ "loss": 0.5167,
+ "step": 1676
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9368915997822143e-05,
+ "loss": 0.4965,
+ "step": 1677
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936796821695955e-05,
+ "loss": 0.5117,
+ "step": 1678
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9367019748152328e-05,
+ "loss": 0.4949,
+ "step": 1679
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936607059147014e-05,
+ "loss": 0.4979,
+ "step": 1680
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9365120746982683e-05,
+ "loss": 0.5053,
+ "step": 1681
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936417021475971e-05,
+ "loss": 0.5028,
+ "step": 1682
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9363218994871026e-05,
+ "loss": 0.4857,
+ "step": 1683
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9362267087386487e-05,
+ "loss": 0.5216,
+ "step": 1684
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936131449237599e-05,
+ "loss": 0.5015,
+ "step": 1685
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9360361209909494e-05,
+ "loss": 0.513,
+ "step": 1686
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9359407240057003e-05,
+ "loss": 0.4847,
+ "step": 1687
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9358452582888575e-05,
+ "loss": 0.5185,
+ "step": 1688
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.935749723847431e-05,
+ "loss": 0.4861,
+ "step": 1689
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.935654120688437e-05,
+ "loss": 0.5161,
+ "step": 1690
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9355584488188965e-05,
+ "loss": 0.4871,
+ "step": 1691
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9354627082458342e-05,
+ "loss": 0.525,
+ "step": 1692
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9353668989762817e-05,
+ "loss": 0.504,
+ "step": 1693
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.935271021017275e-05,
+ "loss": 0.4978,
+ "step": 1694
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9351750743758543e-05,
+ "loss": 0.5007,
+ "step": 1695
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9350790590590657e-05,
+ "loss": 0.5096,
+ "step": 1696
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.93498297507396e-05,
+ "loss": 0.5025,
+ "step": 1697
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9348868224275943e-05,
+ "loss": 0.5048,
+ "step": 1698
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9347906011270283e-05,
+ "loss": 0.5047,
+ "step": 1699
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9346943111793286e-05,
+ "loss": 0.512,
+ "step": 1700
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.934597952591567e-05,
+ "loss": 0.5133,
+ "step": 1701
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.934501525370818e-05,
+ "loss": 0.4905,
+ "step": 1702
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9344050295241648e-05,
+ "loss": 0.4937,
+ "step": 1703
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9343084650586922e-05,
+ "loss": 0.5147,
+ "step": 1704
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9342118319814923e-05,
+ "loss": 0.4967,
+ "step": 1705
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.934115130299661e-05,
+ "loss": 0.5341,
+ "step": 1706
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9340183600202998e-05,
+ "loss": 0.4955,
+ "step": 1707
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.933921521150515e-05,
+ "loss": 0.4864,
+ "step": 1708
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9338246136974182e-05,
+ "loss": 0.5248,
+ "step": 1709
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9337276376681264e-05,
+ "loss": 0.5103,
+ "step": 1710
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.93363059306976e-05,
+ "loss": 0.5182,
+ "step": 1711
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.933533479909446e-05,
+ "loss": 0.5186,
+ "step": 1712
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9334362981943163e-05,
+ "loss": 0.5112,
+ "step": 1713
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9333390479315074e-05,
+ "loss": 0.4874,
+ "step": 1714
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9332417291281608e-05,
+ "loss": 0.4948,
+ "step": 1715
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9331443417914232e-05,
+ "loss": 0.5153,
+ "step": 1716
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9330468859284462e-05,
+ "loss": 0.5004,
+ "step": 1717
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932949361546387e-05,
+ "loss": 0.4919,
+ "step": 1718
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9328517686524073e-05,
+ "loss": 0.5057,
+ "step": 1719
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9327541072536733e-05,
+ "loss": 0.5056,
+ "step": 1720
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9326563773573576e-05,
+ "loss": 0.4943,
+ "step": 1721
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9325585789706366e-05,
+ "loss": 0.5114,
+ "step": 1722
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932460712100692e-05,
+ "loss": 0.4955,
+ "step": 1723
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9323627767547118e-05,
+ "loss": 0.4962,
+ "step": 1724
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932264772939887e-05,
+ "loss": 0.5037,
+ "step": 1725
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9321667006634146e-05,
+ "loss": 0.5101,
+ "step": 1726
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932068559932497e-05,
+ "loss": 0.5041,
+ "step": 1727
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9319703507543415e-05,
+ "loss": 0.4974,
+ "step": 1728
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9318720731361593e-05,
+ "loss": 0.5173,
+ "step": 1729
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.931773727085168e-05,
+ "loss": 0.5043,
+ "step": 1730
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9316753126085902e-05,
+ "loss": 0.5068,
+ "step": 1731
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9315768297136523e-05,
+ "loss": 0.5033,
+ "step": 1732
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9314782784075866e-05,
+ "loss": 0.5153,
+ "step": 1733
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9313796586976306e-05,
+ "loss": 0.5235,
+ "step": 1734
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9312809705910266e-05,
+ "loss": 0.4886,
+ "step": 1735
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9311822140950213e-05,
+ "loss": 0.493,
+ "step": 1736
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.931083389216867e-05,
+ "loss": 0.5066,
+ "step": 1737
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930984495963822e-05,
+ "loss": 0.4965,
+ "step": 1738
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930885534343147e-05,
+ "loss": 0.497,
+ "step": 1739
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930786504362111e-05,
+ "loss": 0.4967,
+ "step": 1740
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930687406027985e-05,
+ "loss": 0.4892,
+ "step": 1741
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930588239348047e-05,
+ "loss": 0.5099,
+ "step": 1742
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9304890043295796e-05,
+ "loss": 0.5118,
+ "step": 1743
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.93038970097987e-05,
+ "loss": 0.504,
+ "step": 1744
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.93029032930621e-05,
+ "loss": 0.5056,
+ "step": 1745
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930190889315898e-05,
+ "loss": 0.499,
+ "step": 1746
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930091381016236e-05,
+ "loss": 0.5259,
+ "step": 1747
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9299918044145315e-05,
+ "loss": 0.5033,
+ "step": 1748
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9298921595180968e-05,
+ "loss": 0.5005,
+ "step": 1749
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9297924463342495e-05,
+ "loss": 0.518,
+ "step": 1750
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.929692664870313e-05,
+ "loss": 0.5143,
+ "step": 1751
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9295928151336134e-05,
+ "loss": 0.5061,
+ "step": 1752
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9294928971314843e-05,
+ "loss": 0.5013,
+ "step": 1753
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9293929108712624e-05,
+ "loss": 0.5112,
+ "step": 1754
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9292928563602912e-05,
+ "loss": 0.4963,
+ "step": 1755
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9291927336059175e-05,
+ "loss": 0.5058,
+ "step": 1756
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9290925426154948e-05,
+ "loss": 0.4977,
+ "step": 1757
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9289922833963798e-05,
+ "loss": 0.5122,
+ "step": 1758
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9288919559559353e-05,
+ "loss": 0.5096,
+ "step": 1759
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.928791560301529e-05,
+ "loss": 0.5032,
+ "step": 1760
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9286910964405345e-05,
+ "loss": 0.4987,
+ "step": 1761
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9285905643803277e-05,
+ "loss": 0.5022,
+ "step": 1762
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9284899641282925e-05,
+ "loss": 0.4889,
+ "step": 1763
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.928389295691816e-05,
+ "loss": 0.5117,
+ "step": 1764
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9282885590782916e-05,
+ "loss": 0.5068,
+ "step": 1765
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.928187754295116e-05,
+ "loss": 0.5271,
+ "step": 1766
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9280868813496927e-05,
+ "loss": 0.497,
+ "step": 1767
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9279859402494288e-05,
+ "loss": 0.5223,
+ "step": 1768
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9278849310017372e-05,
+ "loss": 0.5151,
+ "step": 1769
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9277838536140357e-05,
+ "loss": 0.5233,
+ "step": 1770
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.927682708093747e-05,
+ "loss": 0.4949,
+ "step": 1771
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9275814944482988e-05,
+ "loss": 0.5211,
+ "step": 1772
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9274802126851237e-05,
+ "loss": 0.4977,
+ "step": 1773
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9273788628116593e-05,
+ "loss": 0.5169,
+ "step": 1774
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9272774448353484e-05,
+ "loss": 0.5062,
+ "step": 1775
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.927175958763639e-05,
+ "loss": 0.4999,
+ "step": 1776
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9270744046039834e-05,
+ "loss": 0.5578,
+ "step": 1777
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92697278236384e-05,
+ "loss": 0.5188,
+ "step": 1778
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9268710920506707e-05,
+ "loss": 0.5076,
+ "step": 1779
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926769333671943e-05,
+ "loss": 0.4947,
+ "step": 1780
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926667507235131e-05,
+ "loss": 0.5049,
+ "step": 1781
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9265656127477114e-05,
+ "loss": 0.5118,
+ "step": 1782
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926463650217167e-05,
+ "loss": 0.489,
+ "step": 1783
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9263616196509855e-05,
+ "loss": 0.5062,
+ "step": 1784
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9262595210566598e-05,
+ "loss": 0.5238,
+ "step": 1785
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9261573544416872e-05,
+ "loss": 0.4939,
+ "step": 1786
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926055119813571e-05,
+ "loss": 0.491,
+ "step": 1787
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9259528171798184e-05,
+ "loss": 0.4932,
+ "step": 1788
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925850446547942e-05,
+ "loss": 0.5256,
+ "step": 1789
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92574800792546e-05,
+ "loss": 0.5049,
+ "step": 1790
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925645501319895e-05,
+ "loss": 0.4982,
+ "step": 1791
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925542926738774e-05,
+ "loss": 0.5154,
+ "step": 1792
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92544028418963e-05,
+ "loss": 0.5136,
+ "step": 1793
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9253375736800014e-05,
+ "loss": 0.4918,
+ "step": 1794
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9252347952174294e-05,
+ "loss": 0.5009,
+ "step": 1795
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925131948809463e-05,
+ "loss": 0.5235,
+ "step": 1796
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9250290344636537e-05,
+ "loss": 0.5012,
+ "step": 1797
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92492605218756e-05,
+ "loss": 0.4942,
+ "step": 1798
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9248230019887438e-05,
+ "loss": 0.5102,
+ "step": 1799
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.924719883874773e-05,
+ "loss": 0.4946,
+ "step": 1800
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9246166978532203e-05,
+ "loss": 0.5077,
+ "step": 1801
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.924513443931663e-05,
+ "loss": 0.5084,
+ "step": 1802
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9244101221176834e-05,
+ "loss": 0.4944,
+ "step": 1803
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9243067324188696e-05,
+ "loss": 0.5069,
+ "step": 1804
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9242032748428138e-05,
+ "loss": 0.4945,
+ "step": 1805
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.924099749397114e-05,
+ "loss": 0.507,
+ "step": 1806
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9239961560893717e-05,
+ "loss": 0.5152,
+ "step": 1807
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.923892494927195e-05,
+ "loss": 0.4897,
+ "step": 1808
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9237887659181963e-05,
+ "loss": 0.4968,
+ "step": 1809
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9236849690699924e-05,
+ "loss": 0.5118,
+ "step": 1810
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.923581104390207e-05,
+ "loss": 0.5128,
+ "step": 1811
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9234771718864667e-05,
+ "loss": 0.4928,
+ "step": 1812
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9233731715664036e-05,
+ "loss": 0.5075,
+ "step": 1813
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9232691034376556e-05,
+ "loss": 0.5109,
+ "step": 1814
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9231649675078647e-05,
+ "loss": 0.4918,
+ "step": 1815
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9230607637846785e-05,
+ "loss": 0.5056,
+ "step": 1816
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9229564922757487e-05,
+ "loss": 0.4999,
+ "step": 1817
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9228521529887333e-05,
+ "loss": 0.5066,
+ "step": 1818
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9227477459312942e-05,
+ "loss": 0.4944,
+ "step": 1819
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9226432711110983e-05,
+ "loss": 0.5145,
+ "step": 1820
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.922538728535819e-05,
+ "loss": 0.5033,
+ "step": 1821
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.922434118213132e-05,
+ "loss": 0.5292,
+ "step": 1822
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9223294401507196e-05,
+ "loss": 0.5067,
+ "step": 1823
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9222246943562702e-05,
+ "loss": 0.5016,
+ "step": 1824
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9221198808374746e-05,
+ "loss": 0.4928,
+ "step": 1825
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9220149996020306e-05,
+ "loss": 0.5077,
+ "step": 1826
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9219100506576396e-05,
+ "loss": 0.4962,
+ "step": 1827
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9218050340120095e-05,
+ "loss": 0.5081,
+ "step": 1828
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9216999496728513e-05,
+ "loss": 0.5203,
+ "step": 1829
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9215947976478825e-05,
+ "loss": 0.511,
+ "step": 1830
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9214895779448254e-05,
+ "loss": 0.5018,
+ "step": 1831
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.921384290571406e-05,
+ "loss": 0.4929,
+ "step": 1832
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9212789355353567e-05,
+ "loss": 0.4992,
+ "step": 1833
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.921173512844414e-05,
+ "loss": 0.5106,
+ "step": 1834
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9210680225063204e-05,
+ "loss": 0.4934,
+ "step": 1835
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9209624645288224e-05,
+ "loss": 0.5013,
+ "step": 1836
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9208568389196715e-05,
+ "loss": 0.4948,
+ "step": 1837
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920751145686624e-05,
+ "loss": 0.4963,
+ "step": 1838
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9206453848374425e-05,
+ "loss": 0.499,
+ "step": 1839
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920539556379893e-05,
+ "loss": 0.4947,
+ "step": 1840
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920433660321747e-05,
+ "loss": 0.5145,
+ "step": 1841
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920327696670782e-05,
+ "loss": 0.4967,
+ "step": 1842
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9202216654347786e-05,
+ "loss": 0.52,
+ "step": 1843
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9201155666215237e-05,
+ "loss": 0.5103,
+ "step": 1844
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9200094002388084e-05,
+ "loss": 0.5124,
+ "step": 1845
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9199031662944294e-05,
+ "loss": 0.5054,
+ "step": 1846
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.919796864796188e-05,
+ "loss": 0.4923,
+ "step": 1847
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.919690495751891e-05,
+ "loss": 0.5264,
+ "step": 1848
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9195840591693486e-05,
+ "loss": 0.4979,
+ "step": 1849
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.919477555056378e-05,
+ "loss": 0.5072,
+ "step": 1850
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9193709834208005e-05,
+ "loss": 0.5136,
+ "step": 1851
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9192643442704413e-05,
+ "loss": 0.5028,
+ "step": 1852
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9191576376131328e-05,
+ "loss": 0.52,
+ "step": 1853
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91905086345671e-05,
+ "loss": 0.5033,
+ "step": 1854
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9189440218090146e-05,
+ "loss": 0.5088,
+ "step": 1855
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9188371126778923e-05,
+ "loss": 0.5009,
+ "step": 1856
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9187301360711943e-05,
+ "loss": 0.5068,
+ "step": 1857
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9186230919967764e-05,
+ "loss": 0.4997,
+ "step": 1858
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9185159804624994e-05,
+ "loss": 0.5098,
+ "step": 1859
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9184088014762292e-05,
+ "loss": 0.4964,
+ "step": 1860
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9183015550458367e-05,
+ "loss": 0.5084,
+ "step": 1861
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.918194241179197e-05,
+ "loss": 0.5049,
+ "step": 1862
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9180868598841916e-05,
+ "loss": 0.4998,
+ "step": 1863
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9179794111687063e-05,
+ "loss": 0.5073,
+ "step": 1864
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9178718950406304e-05,
+ "loss": 0.5088,
+ "step": 1865
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.917764311507861e-05,
+ "loss": 0.4973,
+ "step": 1866
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9176566605782974e-05,
+ "loss": 0.5177,
+ "step": 1867
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9175489422598455e-05,
+ "loss": 0.5072,
+ "step": 1868
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9174411565604157e-05,
+ "loss": 0.5095,
+ "step": 1869
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.917333303487923e-05,
+ "loss": 0.4966,
+ "step": 1870
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9172253830502883e-05,
+ "loss": 0.5067,
+ "step": 1871
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9171173952554367e-05,
+ "loss": 0.5058,
+ "step": 1872
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.917009340111298e-05,
+ "loss": 0.5126,
+ "step": 1873
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.916901217625807e-05,
+ "loss": 0.5041,
+ "step": 1874
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.916793027806905e-05,
+ "loss": 0.4989,
+ "step": 1875
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9166847706625357e-05,
+ "loss": 0.5211,
+ "step": 1876
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91657644620065e-05,
+ "loss": 0.499,
+ "step": 1877
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9164680544292023e-05,
+ "loss": 0.4914,
+ "step": 1878
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9163595953561523e-05,
+ "loss": 0.5074,
+ "step": 1879
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9162510689894653e-05,
+ "loss": 0.534,
+ "step": 1880
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.916142475337111e-05,
+ "loss": 0.5084,
+ "step": 1881
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9160338144070635e-05,
+ "loss": 0.5069,
+ "step": 1882
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9159250862073028e-05,
+ "loss": 0.5611,
+ "step": 1883
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9158162907458135e-05,
+ "loss": 0.4864,
+ "step": 1884
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9157074280305847e-05,
+ "loss": 0.5034,
+ "step": 1885
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9155984980696112e-05,
+ "loss": 0.5303,
+ "step": 1886
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9154895008708923e-05,
+ "loss": 0.4934,
+ "step": 1887
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9153804364424325e-05,
+ "loss": 0.4889,
+ "step": 1888
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9152713047922406e-05,
+ "loss": 0.5199,
+ "step": 1889
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9151621059283306e-05,
+ "loss": 0.5035,
+ "step": 1890
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9150528398587226e-05,
+ "loss": 0.5213,
+ "step": 1891
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9149435065914395e-05,
+ "loss": 0.4933,
+ "step": 1892
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9148341061345114e-05,
+ "loss": 0.4935,
+ "step": 1893
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9147246384959715e-05,
+ "loss": 0.5199,
+ "step": 1894
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9146151036838583e-05,
+ "loss": 0.5242,
+ "step": 1895
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9145055017062165e-05,
+ "loss": 0.4793,
+ "step": 1896
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.914395832571094e-05,
+ "loss": 0.5142,
+ "step": 1897
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.914286096286545e-05,
+ "loss": 0.4923,
+ "step": 1898
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9141762928606282e-05,
+ "loss": 0.4866,
+ "step": 1899
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9140664223014064e-05,
+ "loss": 0.4988,
+ "step": 1900
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9139564846169486e-05,
+ "loss": 0.4838,
+ "step": 1901
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913846479815328e-05,
+ "loss": 0.5151,
+ "step": 1902
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913736407904623e-05,
+ "loss": 0.493,
+ "step": 1903
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9136262688929167e-05,
+ "loss": 0.4959,
+ "step": 1904
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913516062788297e-05,
+ "loss": 0.5162,
+ "step": 1905
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9134057895988574e-05,
+ "loss": 0.4908,
+ "step": 1906
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913295449332696e-05,
+ "loss": 0.5083,
+ "step": 1907
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913185041997915e-05,
+ "loss": 0.5152,
+ "step": 1908
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913074567602623e-05,
+ "loss": 0.5059,
+ "step": 1909
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9129640261549324e-05,
+ "loss": 0.509,
+ "step": 1910
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9128534176629613e-05,
+ "loss": 0.5031,
+ "step": 1911
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9127427421348316e-05,
+ "loss": 0.5084,
+ "step": 1912
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9126319995786717e-05,
+ "loss": 0.5322,
+ "step": 1913
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.912521190002614e-05,
+ "loss": 0.5027,
+ "step": 1914
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9124103134147945e-05,
+ "loss": 0.505,
+ "step": 1915
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9122993698233576e-05,
+ "loss": 0.5083,
+ "step": 1916
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9121883592364486e-05,
+ "loss": 0.5209,
+ "step": 1917
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9120772816622213e-05,
+ "loss": 0.509,
+ "step": 1918
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9119661371088318e-05,
+ "loss": 0.5019,
+ "step": 1919
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9118549255844425e-05,
+ "loss": 0.4998,
+ "step": 1920
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91174364709722e-05,
+ "loss": 0.4973,
+ "step": 1921
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9116323016553363e-05,
+ "loss": 0.5233,
+ "step": 1922
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.911520889266968e-05,
+ "loss": 0.492,
+ "step": 1923
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.911409409940297e-05,
+ "loss": 0.5242,
+ "step": 1924
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91129786368351e-05,
+ "loss": 0.5041,
+ "step": 1925
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.911186250504798e-05,
+ "loss": 0.5142,
+ "step": 1926
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9110745704123577e-05,
+ "loss": 0.5063,
+ "step": 1927
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9109628234143905e-05,
+ "loss": 0.497,
+ "step": 1928
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9108510095191025e-05,
+ "loss": 0.4973,
+ "step": 1929
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.910739128734705e-05,
+ "loss": 0.4926,
+ "step": 1930
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9106271810694137e-05,
+ "loss": 0.5205,
+ "step": 1931
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9105151665314497e-05,
+ "loss": 0.4997,
+ "step": 1932
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9104030851290393e-05,
+ "loss": 0.5069,
+ "step": 1933
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.910290936870413e-05,
+ "loss": 0.5012,
+ "step": 1934
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.910178721763806e-05,
+ "loss": 0.5198,
+ "step": 1935
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91006643981746e-05,
+ "loss": 0.5206,
+ "step": 1936
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9099540910396194e-05,
+ "loss": 0.4984,
+ "step": 1937
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9098416754385355e-05,
+ "loss": 0.5317,
+ "step": 1938
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909729193022463e-05,
+ "loss": 0.4949,
+ "step": 1939
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9096166437996626e-05,
+ "loss": 0.4801,
+ "step": 1940
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9095040277783993e-05,
+ "loss": 0.5191,
+ "step": 1941
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909391344966943e-05,
+ "loss": 0.5103,
+ "step": 1942
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909278595373569e-05,
+ "loss": 0.4988,
+ "step": 1943
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9091657790065565e-05,
+ "loss": 0.49,
+ "step": 1944
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909052895874191e-05,
+ "loss": 0.528,
+ "step": 1945
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9089399459847615e-05,
+ "loss": 0.4989,
+ "step": 1946
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9088269293465634e-05,
+ "loss": 0.4941,
+ "step": 1947
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9087138459678956e-05,
+ "loss": 0.5119,
+ "step": 1948
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.908600695857062e-05,
+ "loss": 0.5093,
+ "step": 1949
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9084874790223735e-05,
+ "loss": 0.5122,
+ "step": 1950
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9083741954721423e-05,
+ "loss": 0.4985,
+ "step": 1951
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.908260845214689e-05,
+ "loss": 0.5291,
+ "step": 1952
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9081474282583367e-05,
+ "loss": 0.5037,
+ "step": 1953
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9080339446114148e-05,
+ "loss": 0.4901,
+ "step": 1954
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.907920394282256e-05,
+ "loss": 0.4888,
+ "step": 1955
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9078067772792006e-05,
+ "loss": 0.4985,
+ "step": 1956
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.907693093610591e-05,
+ "loss": 0.5106,
+ "step": 1957
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9075793432847763e-05,
+ "loss": 0.5031,
+ "step": 1958
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.907465526310109e-05,
+ "loss": 0.5117,
+ "step": 1959
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9073516426949485e-05,
+ "loss": 0.5219,
+ "step": 1960
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9072376924476568e-05,
+ "loss": 0.5064,
+ "step": 1961
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9071236755766028e-05,
+ "loss": 0.5332,
+ "step": 1962
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9070095920901588e-05,
+ "loss": 0.5191,
+ "step": 1963
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.906895441996703e-05,
+ "loss": 0.5143,
+ "step": 1964
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.906781225304618e-05,
+ "loss": 0.491,
+ "step": 1965
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9066669420222915e-05,
+ "loss": 0.5089,
+ "step": 1966
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9065525921581158e-05,
+ "loss": 0.5046,
+ "step": 1967
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9064381757204884e-05,
+ "loss": 0.501,
+ "step": 1968
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9063236927178116e-05,
+ "loss": 0.5061,
+ "step": 1969
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9062091431584924e-05,
+ "loss": 0.5049,
+ "step": 1970
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9060945270509427e-05,
+ "loss": 0.4905,
+ "step": 1971
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.90597984440358e-05,
+ "loss": 0.4926,
+ "step": 1972
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9058650952248257e-05,
+ "loss": 0.4932,
+ "step": 1973
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9057502795231066e-05,
+ "loss": 0.5016,
+ "step": 1974
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9056353973068544e-05,
+ "loss": 0.4863,
+ "step": 1975
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.905520448584505e-05,
+ "loss": 0.5144,
+ "step": 1976
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9054054333645006e-05,
+ "loss": 0.4898,
+ "step": 1977
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.905290351655287e-05,
+ "loss": 0.4975,
+ "step": 1978
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9051752034653153e-05,
+ "loss": 0.526,
+ "step": 1979
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9050599888030413e-05,
+ "loss": 0.5172,
+ "step": 1980
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9049447076769265e-05,
+ "loss": 0.4884,
+ "step": 1981
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904829360095436e-05,
+ "loss": 0.5012,
+ "step": 1982
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904713946067041e-05,
+ "loss": 0.5017,
+ "step": 1983
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904598465600217e-05,
+ "loss": 0.5158,
+ "step": 1984
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904482918703444e-05,
+ "loss": 0.5017,
+ "step": 1985
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9043673053852073e-05,
+ "loss": 0.496,
+ "step": 1986
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9042516256539974e-05,
+ "loss": 0.5146,
+ "step": 1987
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904135879518309e-05,
+ "loss": 0.497,
+ "step": 1988
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9040200669866426e-05,
+ "loss": 0.5092,
+ "step": 1989
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903904188067502e-05,
+ "loss": 0.4902,
+ "step": 1990
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903788242769398e-05,
+ "loss": 0.5079,
+ "step": 1991
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9036722311008442e-05,
+ "loss": 0.5132,
+ "step": 1992
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9035561530703605e-05,
+ "loss": 0.5149,
+ "step": 1993
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903440008686471e-05,
+ "loss": 0.4911,
+ "step": 1994
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9033237979577053e-05,
+ "loss": 0.5114,
+ "step": 1995
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9032075208925967e-05,
+ "loss": 0.5084,
+ "step": 1996
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903091177499685e-05,
+ "loss": 0.4958,
+ "step": 1997
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9029747677875132e-05,
+ "loss": 0.5,
+ "step": 1998
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.90285829176463e-05,
+ "loss": 0.5156,
+ "step": 1999
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9027417494395896e-05,
+ "loss": 0.501,
+ "step": 2000
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9026251408209494e-05,
+ "loss": 0.4945,
+ "step": 2001
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9025084659172733e-05,
+ "loss": 0.4951,
+ "step": 2002
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9023917247371292e-05,
+ "loss": 0.4994,
+ "step": 2003
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9022749172890904e-05,
+ "loss": 0.5328,
+ "step": 2004
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9021580435817343e-05,
+ "loss": 0.5034,
+ "step": 2005
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.902041103623644e-05,
+ "loss": 0.5178,
+ "step": 2006
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.901924097423407e-05,
+ "loss": 0.4987,
+ "step": 2007
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.901807024989615e-05,
+ "loss": 0.4948,
+ "step": 2008
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9016898863308667e-05,
+ "loss": 0.4785,
+ "step": 2009
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9015726814557632e-05,
+ "loss": 0.496,
+ "step": 2010
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9014554103729125e-05,
+ "loss": 0.5314,
+ "step": 2011
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9013380730909255e-05,
+ "loss": 0.503,
+ "step": 2012
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.901220669618419e-05,
+ "loss": 0.5094,
+ "step": 2013
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9011031999640152e-05,
+ "loss": 0.5112,
+ "step": 2014
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9009856641363406e-05,
+ "loss": 0.5092,
+ "step": 2015
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9008680621440262e-05,
+ "loss": 0.5008,
+ "step": 2016
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9007503939957085e-05,
+ "loss": 0.503,
+ "step": 2017
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.900632659700028e-05,
+ "loss": 0.5023,
+ "step": 2018
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9005148592656312e-05,
+ "loss": 0.4859,
+ "step": 2019
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9003969927011683e-05,
+ "loss": 0.4745,
+ "step": 2020
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.900279060015296e-05,
+ "loss": 0.5014,
+ "step": 2021
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9001610612166735e-05,
+ "loss": 0.4822,
+ "step": 2022
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9000429963139668e-05,
+ "loss": 0.4995,
+ "step": 2023
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8999248653158463e-05,
+ "loss": 0.5026,
+ "step": 2024
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8998066682309864e-05,
+ "loss": 0.5068,
+ "step": 2025
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8996884050680675e-05,
+ "loss": 0.5157,
+ "step": 2026
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8995700758357744e-05,
+ "loss": 0.4847,
+ "step": 2027
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.899451680542796e-05,
+ "loss": 0.4887,
+ "step": 2028
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8993332191978277e-05,
+ "loss": 0.5107,
+ "step": 2029
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8992146918095684e-05,
+ "loss": 0.5014,
+ "step": 2030
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8990960983867222e-05,
+ "loss": 0.5074,
+ "step": 2031
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.898977438937998e-05,
+ "loss": 0.5281,
+ "step": 2032
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8988587134721103e-05,
+ "loss": 0.4978,
+ "step": 2033
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8987399219977768e-05,
+ "loss": 0.5055,
+ "step": 2034
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8986210645237216e-05,
+ "loss": 0.5146,
+ "step": 2035
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8985021410586732e-05,
+ "loss": 0.5041,
+ "step": 2036
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8983831516113645e-05,
+ "loss": 0.5209,
+ "step": 2037
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.898264096190534e-05,
+ "loss": 0.4876,
+ "step": 2038
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8981449748049248e-05,
+ "loss": 0.5127,
+ "step": 2039
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8980257874632836e-05,
+ "loss": 0.5006,
+ "step": 2040
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8979065341743642e-05,
+ "loss": 0.4796,
+ "step": 2041
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8977872149469236e-05,
+ "loss": 0.4946,
+ "step": 2042
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.897667829789724e-05,
+ "loss": 0.5015,
+ "step": 2043
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8975483787115326e-05,
+ "loss": 0.4806,
+ "step": 2044
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8974288617211217e-05,
+ "loss": 0.5259,
+ "step": 2045
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8973092788272677e-05,
+ "loss": 0.5037,
+ "step": 2046
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8971896300387525e-05,
+ "loss": 0.506,
+ "step": 2047
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8970699153643623e-05,
+ "loss": 0.5138,
+ "step": 2048
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.896950134812889e-05,
+ "loss": 0.5103,
+ "step": 2049
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8968302883931283e-05,
+ "loss": 0.4973,
+ "step": 2050
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8967103761138817e-05,
+ "loss": 0.524,
+ "step": 2051
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8965903979839547e-05,
+ "loss": 0.5037,
+ "step": 2052
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8964703540121577e-05,
+ "loss": 0.4964,
+ "step": 2053
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8963502442073073e-05,
+ "loss": 0.499,
+ "step": 2054
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8962300685782224e-05,
+ "loss": 0.507,
+ "step": 2055
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8961098271337296e-05,
+ "loss": 0.5196,
+ "step": 2056
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8959895198826582e-05,
+ "loss": 0.489,
+ "step": 2057
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.895869146833843e-05,
+ "loss": 0.5034,
+ "step": 2058
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8957487079961235e-05,
+ "loss": 0.5135,
+ "step": 2059
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.895628203378345e-05,
+ "loss": 0.4917,
+ "step": 2060
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8955076329893565e-05,
+ "loss": 0.503,
+ "step": 2061
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8953869968380117e-05,
+ "loss": 0.53,
+ "step": 2062
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8952662949331707e-05,
+ "loss": 0.4998,
+ "step": 2063
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8951455272836963e-05,
+ "loss": 0.4908,
+ "step": 2064
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8950246938984573e-05,
+ "loss": 0.5131,
+ "step": 2065
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.894903794786328e-05,
+ "loss": 0.5325,
+ "step": 2066
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.894782829956186e-05,
+ "loss": 0.5071,
+ "step": 2067
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8946617994169146e-05,
+ "loss": 0.5157,
+ "step": 2068
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8945407031774018e-05,
+ "loss": 0.4963,
+ "step": 2069
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8944195412465404e-05,
+ "loss": 0.5301,
+ "step": 2070
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8942983136332282e-05,
+ "loss": 0.5193,
+ "step": 2071
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8941770203463674e-05,
+ "loss": 0.4954,
+ "step": 2072
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8940556613948656e-05,
+ "loss": 0.5124,
+ "step": 2073
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8939342367876345e-05,
+ "loss": 0.51,
+ "step": 2074
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.893812746533591e-05,
+ "loss": 0.4831,
+ "step": 2075
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8936911906416572e-05,
+ "loss": 0.4994,
+ "step": 2076
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8935695691207598e-05,
+ "loss": 0.5263,
+ "step": 2077
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8934478819798296e-05,
+ "loss": 0.4893,
+ "step": 2078
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8933261292278033e-05,
+ "loss": 0.5132,
+ "step": 2079
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8932043108736217e-05,
+ "loss": 0.5076,
+ "step": 2080
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.89308242692623e-05,
+ "loss": 0.527,
+ "step": 2081
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.89296047739458e-05,
+ "loss": 0.5058,
+ "step": 2082
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.892838462287627e-05,
+ "loss": 0.5095,
+ "step": 2083
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8927163816143302e-05,
+ "loss": 0.4916,
+ "step": 2084
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8925942353836558e-05,
+ "loss": 0.4806,
+ "step": 2085
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.892472023604573e-05,
+ "loss": 0.5076,
+ "step": 2086
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8923497462860572e-05,
+ "loss": 0.5209,
+ "step": 2087
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8922274034370875e-05,
+ "loss": 0.4888,
+ "step": 2088
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8921049950666484e-05,
+ "loss": 0.5002,
+ "step": 2089
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.891982521183729e-05,
+ "loss": 0.5068,
+ "step": 2090
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.891859981797323e-05,
+ "loss": 0.4904,
+ "step": 2091
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.89173737691643e-05,
+ "loss": 0.5147,
+ "step": 2092
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8916147065500524e-05,
+ "loss": 0.489,
+ "step": 2093
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8914919707071997e-05,
+ "loss": 0.5265,
+ "step": 2094
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8913691693968846e-05,
+ "loss": 0.4928,
+ "step": 2095
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.891246302628125e-05,
+ "loss": 0.5037,
+ "step": 2096
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.891123370409944e-05,
+ "loss": 0.5027,
+ "step": 2097
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8910003727513697e-05,
+ "loss": 0.496,
+ "step": 2098
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8908773096614333e-05,
+ "loss": 0.4993,
+ "step": 2099
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8907541811491726e-05,
+ "loss": 0.4809,
+ "step": 2100
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.89063098722363e-05,
+ "loss": 0.4981,
+ "step": 2101
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8905077278938524e-05,
+ "loss": 0.5007,
+ "step": 2102
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.890384403168891e-05,
+ "loss": 0.5164,
+ "step": 2103
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.890261013057802e-05,
+ "loss": 0.5046,
+ "step": 2104
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8901375575696476e-05,
+ "loss": 0.5137,
+ "step": 2105
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.890014036713493e-05,
+ "loss": 0.5103,
+ "step": 2106
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8898904504984096e-05,
+ "loss": 0.5071,
+ "step": 2107
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8897667989334726e-05,
+ "loss": 0.5271,
+ "step": 2108
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889643082027763e-05,
+ "loss": 0.5044,
+ "step": 2109
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8895192997903657e-05,
+ "loss": 0.4989,
+ "step": 2110
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8893954522303707e-05,
+ "loss": 0.5072,
+ "step": 2111
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889271539356873e-05,
+ "loss": 0.4782,
+ "step": 2112
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889147561178972e-05,
+ "loss": 0.4853,
+ "step": 2113
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889023517705773e-05,
+ "loss": 0.5108,
+ "step": 2114
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888899408946384e-05,
+ "loss": 0.5195,
+ "step": 2115
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.88877523490992e-05,
+ "loss": 0.4972,
+ "step": 2116
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888650995605499e-05,
+ "loss": 0.4881,
+ "step": 2117
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8885266910422454e-05,
+ "loss": 0.4766,
+ "step": 2118
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888402321229287e-05,
+ "loss": 0.4896,
+ "step": 2119
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8882778861757573e-05,
+ "loss": 0.5269,
+ "step": 2120
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8881533858907945e-05,
+ "loss": 0.5108,
+ "step": 2121
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888028820383541e-05,
+ "loss": 0.5037,
+ "step": 2122
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8879041896631448e-05,
+ "loss": 0.4973,
+ "step": 2123
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8877794937387576e-05,
+ "loss": 0.5348,
+ "step": 2124
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8876547326195373e-05,
+ "loss": 0.5247,
+ "step": 2125
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.887529906314645e-05,
+ "loss": 0.5148,
+ "step": 2126
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8874050148332484e-05,
+ "loss": 0.5,
+ "step": 2127
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.887280058184518e-05,
+ "loss": 0.4996,
+ "step": 2128
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8871550363776308e-05,
+ "loss": 0.5084,
+ "step": 2129
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8870299494217675e-05,
+ "loss": 0.5191,
+ "step": 2130
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8869047973261148e-05,
+ "loss": 0.5196,
+ "step": 2131
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8867795800998623e-05,
+ "loss": 0.5111,
+ "step": 2132
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8866542977522057e-05,
+ "loss": 0.4926,
+ "step": 2133
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8865289502923455e-05,
+ "loss": 0.5095,
+ "step": 2134
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8864035377294865e-05,
+ "loss": 0.5105,
+ "step": 2135
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8862780600728384e-05,
+ "loss": 0.507,
+ "step": 2136
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.886152517331616e-05,
+ "loss": 0.486,
+ "step": 2137
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8860269095150387e-05,
+ "loss": 0.5058,
+ "step": 2138
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.88590123663233e-05,
+ "loss": 0.4886,
+ "step": 2139
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8857754986927196e-05,
+ "loss": 0.5001,
+ "step": 2140
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8856496957054406e-05,
+ "loss": 0.5071,
+ "step": 2141
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8855238276797315e-05,
+ "loss": 0.5145,
+ "step": 2142
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.885397894624836e-05,
+ "loss": 0.5025,
+ "step": 2143
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8852718965500018e-05,
+ "loss": 0.4977,
+ "step": 2144
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8851458334644814e-05,
+ "loss": 0.4879,
+ "step": 2145
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8850197053775326e-05,
+ "loss": 0.499,
+ "step": 2146
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8848935122984177e-05,
+ "loss": 0.4959,
+ "step": 2147
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884767254236404e-05,
+ "loss": 0.4981,
+ "step": 2148
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884640931200763e-05,
+ "loss": 0.5005,
+ "step": 2149
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8845145432007715e-05,
+ "loss": 0.4988,
+ "step": 2150
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884388090245711e-05,
+ "loss": 0.4929,
+ "step": 2151
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8842615723448678e-05,
+ "loss": 0.5127,
+ "step": 2152
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884134989507532e-05,
+ "loss": 0.5139,
+ "step": 2153
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8840083417430003e-05,
+ "loss": 0.4953,
+ "step": 2154
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8838816290605732e-05,
+ "loss": 0.5164,
+ "step": 2155
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883754851469555e-05,
+ "loss": 0.5008,
+ "step": 2156
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883628008979257e-05,
+ "loss": 0.4822,
+ "step": 2157
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8835011015989927e-05,
+ "loss": 0.5138,
+ "step": 2158
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8833741293380826e-05,
+ "loss": 0.5049,
+ "step": 2159
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883247092205851e-05,
+ "loss": 0.5085,
+ "step": 2160
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883119990211626e-05,
+ "loss": 0.4884,
+ "step": 2161
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8829928233647422e-05,
+ "loss": 0.5028,
+ "step": 2162
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8828655916745383e-05,
+ "loss": 0.5221,
+ "step": 2163
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8827382951503575e-05,
+ "loss": 0.5228,
+ "step": 2164
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8826109338015478e-05,
+ "loss": 0.5035,
+ "step": 2165
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8824835076374622e-05,
+ "loss": 0.4917,
+ "step": 2166
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.882356016667458e-05,
+ "loss": 0.5087,
+ "step": 2167
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8822284609008985e-05,
+ "loss": 0.4921,
+ "step": 2168
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8821008403471497e-05,
+ "loss": 0.5027,
+ "step": 2169
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8819731550155845e-05,
+ "loss": 0.5117,
+ "step": 2170
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8818454049155792e-05,
+ "loss": 0.4992,
+ "step": 2171
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.881717590056515e-05,
+ "loss": 0.4923,
+ "step": 2172
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8815897104477786e-05,
+ "loss": 0.4898,
+ "step": 2173
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8814617660987603e-05,
+ "loss": 0.523,
+ "step": 2174
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.881333757018857e-05,
+ "loss": 0.5144,
+ "step": 2175
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8812056832174673e-05,
+ "loss": 0.4931,
+ "step": 2176
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.881077544703998e-05,
+ "loss": 0.4996,
+ "step": 2177
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8809493414878585e-05,
+ "loss": 0.4943,
+ "step": 2178
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.880821073578463e-05,
+ "loss": 0.4915,
+ "step": 2179
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8806927409852323e-05,
+ "loss": 0.5129,
+ "step": 2180
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8805643437175892e-05,
+ "loss": 0.4973,
+ "step": 2181
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8804358817849634e-05,
+ "loss": 0.4808,
+ "step": 2182
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8803073551967884e-05,
+ "loss": 0.5014,
+ "step": 2183
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8801787639625025e-05,
+ "loss": 0.5324,
+ "step": 2184
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8800501080915496e-05,
+ "loss": 0.4964,
+ "step": 2185
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.879921387593377e-05,
+ "loss": 0.5127,
+ "step": 2186
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8797926024774375e-05,
+ "loss": 0.5176,
+ "step": 2187
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8796637527531883e-05,
+ "loss": 0.5158,
+ "step": 2188
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8795348384300922e-05,
+ "loss": 0.5075,
+ "step": 2189
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.879405859517616e-05,
+ "loss": 0.4952,
+ "step": 2190
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8792768160252308e-05,
+ "loss": 0.5071,
+ "step": 2191
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8791477079624138e-05,
+ "loss": 0.5143,
+ "step": 2192
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8790185353386453e-05,
+ "loss": 0.4903,
+ "step": 2193
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.878889298163412e-05,
+ "loss": 0.5099,
+ "step": 2194
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8787599964462044e-05,
+ "loss": 0.5002,
+ "step": 2195
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8786306301965175e-05,
+ "loss": 0.4997,
+ "step": 2196
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8785011994238516e-05,
+ "loss": 0.5037,
+ "step": 2197
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8783717041377113e-05,
+ "loss": 0.5111,
+ "step": 2198
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8782421443476072e-05,
+ "loss": 0.4795,
+ "step": 2199
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.878112520063052e-05,
+ "loss": 0.4958,
+ "step": 2200
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8779828312935664e-05,
+ "loss": 0.5096,
+ "step": 2201
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.877853078048673e-05,
+ "loss": 0.5011,
+ "step": 2202
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8777232603379012e-05,
+ "loss": 0.5011,
+ "step": 2203
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8775933781707836e-05,
+ "loss": 0.4967,
+ "step": 2204
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8774634315568583e-05,
+ "loss": 0.5074,
+ "step": 2205
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8773334205056687e-05,
+ "loss": 0.4919,
+ "step": 2206
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8772033450267617e-05,
+ "loss": 0.5044,
+ "step": 2207
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8770732051296895e-05,
+ "loss": 0.5007,
+ "step": 2208
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.876943000824009e-05,
+ "loss": 0.5067,
+ "step": 2209
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8768127321192825e-05,
+ "loss": 0.4923,
+ "step": 2210
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8766823990250756e-05,
+ "loss": 0.4937,
+ "step": 2211
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8765520015509597e-05,
+ "loss": 0.5473,
+ "step": 2212
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8764215397065105e-05,
+ "loss": 0.5043,
+ "step": 2213
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8762910135013088e-05,
+ "loss": 0.4941,
+ "step": 2214
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8761604229449402e-05,
+ "loss": 0.5032,
+ "step": 2215
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8760297680469938e-05,
+ "loss": 0.4992,
+ "step": 2216
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875899048817065e-05,
+ "loss": 0.4925,
+ "step": 2217
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8757682652647538e-05,
+ "loss": 0.5178,
+ "step": 2218
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875637417399663e-05,
+ "loss": 0.5141,
+ "step": 2219
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875506505231403e-05,
+ "loss": 0.4848,
+ "step": 2220
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8753755287695866e-05,
+ "loss": 0.4989,
+ "step": 2221
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875244488023832e-05,
+ "loss": 0.4951,
+ "step": 2222
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875113383003763e-05,
+ "loss": 0.4867,
+ "step": 2223
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8749822137190065e-05,
+ "loss": 0.4955,
+ "step": 2224
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8748509801791962e-05,
+ "loss": 0.514,
+ "step": 2225
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.874719682393968e-05,
+ "loss": 0.4934,
+ "step": 2226
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8745883203729648e-05,
+ "loss": 0.504,
+ "step": 2227
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8744568941258335e-05,
+ "loss": 0.5041,
+ "step": 2228
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8743254036622243e-05,
+ "loss": 0.4908,
+ "step": 2229
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.874193848991795e-05,
+ "loss": 0.5062,
+ "step": 2230
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8740622301242045e-05,
+ "loss": 0.5084,
+ "step": 2231
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8739305470691197e-05,
+ "loss": 0.4935,
+ "step": 2232
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8737987998362106e-05,
+ "loss": 0.4952,
+ "step": 2233
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8736669884351523e-05,
+ "loss": 0.5139,
+ "step": 2234
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8735351128756238e-05,
+ "loss": 0.4954,
+ "step": 2235
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8734031731673096e-05,
+ "loss": 0.5215,
+ "step": 2236
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8732711693199e-05,
+ "loss": 0.5039,
+ "step": 2237
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.873139101343087e-05,
+ "loss": 0.5171,
+ "step": 2238
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8730069692465708e-05,
+ "loss": 0.4796,
+ "step": 2239
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8728747730400533e-05,
+ "loss": 0.5093,
+ "step": 2240
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.872742512733243e-05,
+ "loss": 0.5096,
+ "step": 2241
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8726101883358534e-05,
+ "loss": 0.4824,
+ "step": 2242
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8724777998576006e-05,
+ "loss": 0.5057,
+ "step": 2243
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.872345347308207e-05,
+ "loss": 0.5089,
+ "step": 2244
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.872212830697399e-05,
+ "loss": 0.501,
+ "step": 2245
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8720802500349095e-05,
+ "loss": 0.5236,
+ "step": 2246
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.871947605330473e-05,
+ "loss": 0.5291,
+ "step": 2247
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8718148965938312e-05,
+ "loss": 0.5228,
+ "step": 2248
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8716821238347296e-05,
+ "loss": 0.4989,
+ "step": 2249
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8715492870629183e-05,
+ "loss": 0.4978,
+ "step": 2250
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8714163862881527e-05,
+ "loss": 0.4955,
+ "step": 2251
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8712834215201918e-05,
+ "loss": 0.5113,
+ "step": 2252
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8711503927688007e-05,
+ "loss": 0.5227,
+ "step": 2253
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.871017300043748e-05,
+ "loss": 0.5006,
+ "step": 2254
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8708841433548076e-05,
+ "loss": 0.5215,
+ "step": 2255
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8707509227117578e-05,
+ "loss": 0.5261,
+ "step": 2256
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8706176381243822e-05,
+ "loss": 0.5057,
+ "step": 2257
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8704842896024685e-05,
+ "loss": 0.4915,
+ "step": 2258
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8703508771558093e-05,
+ "loss": 0.4977,
+ "step": 2259
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8702174007942012e-05,
+ "loss": 0.4921,
+ "step": 2260
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.870083860527447e-05,
+ "loss": 0.4881,
+ "step": 2261
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.869950256365353e-05,
+ "loss": 0.5051,
+ "step": 2262
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8698165883177308e-05,
+ "loss": 0.5007,
+ "step": 2263
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8696828563943962e-05,
+ "loss": 0.5076,
+ "step": 2264
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8695490606051694e-05,
+ "loss": 0.4853,
+ "step": 2265
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8694152009598767e-05,
+ "loss": 0.5068,
+ "step": 2266
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8692812774683477e-05,
+ "loss": 0.4871,
+ "step": 2267
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8691472901404174e-05,
+ "loss": 0.4977,
+ "step": 2268
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8690132389859254e-05,
+ "loss": 0.4994,
+ "step": 2269
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.868879124014715e-05,
+ "loss": 0.4928,
+ "step": 2270
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8687449452366362e-05,
+ "loss": 0.5154,
+ "step": 2271
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8686107026615418e-05,
+ "loss": 0.5094,
+ "step": 2272
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8684763962992903e-05,
+ "loss": 0.4799,
+ "step": 2273
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8683420261597445e-05,
+ "loss": 0.5091,
+ "step": 2274
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8682075922527717e-05,
+ "loss": 0.5067,
+ "step": 2275
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.868073094588245e-05,
+ "loss": 0.5016,
+ "step": 2276
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8679385331760405e-05,
+ "loss": 0.5159,
+ "step": 2277
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8678039080260403e-05,
+ "loss": 0.5221,
+ "step": 2278
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8676692191481303e-05,
+ "loss": 0.4992,
+ "step": 2279
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.867534466552202e-05,
+ "loss": 0.5096,
+ "step": 2280
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8673996502481507e-05,
+ "loss": 0.5064,
+ "step": 2281
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.867264770245877e-05,
+ "loss": 0.4879,
+ "step": 2282
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8671298265552855e-05,
+ "loss": 0.5101,
+ "step": 2283
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8669948191862866e-05,
+ "loss": 0.5155,
+ "step": 2284
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.866859748148794e-05,
+ "loss": 0.5111,
+ "step": 2285
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.866724613452727e-05,
+ "loss": 0.4805,
+ "step": 2286
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8665894151080097e-05,
+ "loss": 0.5088,
+ "step": 2287
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8664541531245698e-05,
+ "loss": 0.5163,
+ "step": 2288
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.866318827512341e-05,
+ "loss": 0.5177,
+ "step": 2289
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8661834382812608e-05,
+ "loss": 0.4867,
+ "step": 2290
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8660479854412713e-05,
+ "loss": 0.5183,
+ "step": 2291
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8659124690023205e-05,
+ "loss": 0.4917,
+ "step": 2292
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.865776888974359e-05,
+ "loss": 0.5098,
+ "step": 2293
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.865641245367344e-05,
+ "loss": 0.4977,
+ "step": 2294
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8655055381912367e-05,
+ "loss": 0.5151,
+ "step": 2295
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8653697674560023e-05,
+ "loss": 0.524,
+ "step": 2296
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8652339331716114e-05,
+ "loss": 0.4991,
+ "step": 2297
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8650980353480395e-05,
+ "loss": 0.5015,
+ "step": 2298
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8649620739952658e-05,
+ "loss": 0.5034,
+ "step": 2299
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8648260491232753e-05,
+ "loss": 0.4985,
+ "step": 2300
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8646899607420567e-05,
+ "loss": 0.4961,
+ "step": 2301
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8645538088616038e-05,
+ "loss": 0.5044,
+ "step": 2302
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8644175934919156e-05,
+ "loss": 0.5092,
+ "step": 2303
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8642813146429943e-05,
+ "loss": 0.5069,
+ "step": 2304
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8641449723248482e-05,
+ "loss": 0.5064,
+ "step": 2305
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8640085665474898e-05,
+ "loss": 0.5085,
+ "step": 2306
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8638720973209353e-05,
+ "loss": 0.5056,
+ "step": 2307
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.863735564655208e-05,
+ "loss": 0.4973,
+ "step": 2308
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8635989685603327e-05,
+ "loss": 0.5089,
+ "step": 2309
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8634623090463413e-05,
+ "loss": 0.4941,
+ "step": 2310
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8633255861232692e-05,
+ "loss": 0.4903,
+ "step": 2311
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.863188799801157e-05,
+ "loss": 0.5029,
+ "step": 2312
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8630519500900495e-05,
+ "loss": 0.4915,
+ "step": 2313
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8629150369999967e-05,
+ "loss": 0.4913,
+ "step": 2314
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8627780605410528e-05,
+ "loss": 0.5075,
+ "step": 2315
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8626410207232762e-05,
+ "loss": 0.4993,
+ "step": 2316
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8625039175567316e-05,
+ "loss": 0.5164,
+ "step": 2317
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8623667510514867e-05,
+ "loss": 0.4919,
+ "step": 2318
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8622295212176142e-05,
+ "loss": 0.5125,
+ "step": 2319
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.862092228065192e-05,
+ "loss": 0.5005,
+ "step": 2320
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.861954871604302e-05,
+ "loss": 0.4824,
+ "step": 2321
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8618174518450317e-05,
+ "loss": 0.4943,
+ "step": 2322
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8616799687974724e-05,
+ "loss": 0.5029,
+ "step": 2323
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.86154242247172e-05,
+ "loss": 0.4923,
+ "step": 2324
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8614048128778755e-05,
+ "loss": 0.5028,
+ "step": 2325
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8612671400260445e-05,
+ "loss": 0.4956,
+ "step": 2326
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.861129403926337e-05,
+ "loss": 0.5067,
+ "step": 2327
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8609916045888677e-05,
+ "loss": 0.4775,
+ "step": 2328
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.860853742023756e-05,
+ "loss": 0.4859,
+ "step": 2329
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.860715816241126e-05,
+ "loss": 0.5,
+ "step": 2330
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.860577827251107e-05,
+ "loss": 0.5103,
+ "step": 2331
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8604397750638314e-05,
+ "loss": 0.5085,
+ "step": 2332
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8603016596894375e-05,
+ "loss": 0.4992,
+ "step": 2333
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.860163481138068e-05,
+ "loss": 0.5093,
+ "step": 2334
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8600252394198702e-05,
+ "loss": 0.5172,
+ "step": 2335
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8598869345449957e-05,
+ "loss": 0.4971,
+ "step": 2336
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8597485665236016e-05,
+ "loss": 0.5007,
+ "step": 2337
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8596101353658488e-05,
+ "loss": 0.4957,
+ "step": 2338
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8594716410819027e-05,
+ "loss": 0.4941,
+ "step": 2339
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8593330836819342e-05,
+ "loss": 0.4833,
+ "step": 2340
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8591944631761185e-05,
+ "loss": 0.4959,
+ "step": 2341
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.859055779574635e-05,
+ "loss": 0.5065,
+ "step": 2342
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.858917032887668e-05,
+ "loss": 0.5085,
+ "step": 2343
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8587782231254065e-05,
+ "loss": 0.5195,
+ "step": 2344
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8586393502980442e-05,
+ "loss": 0.5003,
+ "step": 2345
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8585004144157798e-05,
+ "loss": 0.4933,
+ "step": 2346
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8583614154888154e-05,
+ "loss": 0.5186,
+ "step": 2347
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8582223535273587e-05,
+ "loss": 0.4988,
+ "step": 2348
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8580832285416223e-05,
+ "loss": 0.5032,
+ "step": 2349
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8579440405418222e-05,
+ "loss": 0.5109,
+ "step": 2350
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.857804789538181e-05,
+ "loss": 0.503,
+ "step": 2351
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8576654755409233e-05,
+ "loss": 0.5101,
+ "step": 2352
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8575260985602806e-05,
+ "loss": 0.5242,
+ "step": 2353
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8573866586064877e-05,
+ "loss": 0.5165,
+ "step": 2354
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.857247155689785e-05,
+ "loss": 0.5158,
+ "step": 2355
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8571075898204167e-05,
+ "loss": 0.4967,
+ "step": 2356
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.856967961008632e-05,
+ "loss": 0.5094,
+ "step": 2357
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8568282692646844e-05,
+ "loss": 0.4908,
+ "step": 2358
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8566885145988326e-05,
+ "loss": 0.48,
+ "step": 2359
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8565486970213397e-05,
+ "loss": 0.5177,
+ "step": 2360
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8564088165424733e-05,
+ "loss": 0.496,
+ "step": 2361
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8562688731725053e-05,
+ "loss": 0.5195,
+ "step": 2362
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8561288669217125e-05,
+ "loss": 0.4852,
+ "step": 2363
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8559887978003766e-05,
+ "loss": 0.4954,
+ "step": 2364
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8558486658187843e-05,
+ "loss": 0.5074,
+ "step": 2365
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8557084709872253e-05,
+ "loss": 0.4885,
+ "step": 2366
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8555682133159952e-05,
+ "loss": 0.4868,
+ "step": 2367
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8554278928153942e-05,
+ "loss": 0.5194,
+ "step": 2368
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.855287509495727e-05,
+ "loss": 0.4986,
+ "step": 2369
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8551470633673023e-05,
+ "loss": 0.5032,
+ "step": 2370
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.855006554440434e-05,
+ "loss": 0.5006,
+ "step": 2371
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8548659827254408e-05,
+ "loss": 0.5124,
+ "step": 2372
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8547253482326458e-05,
+ "loss": 0.4894,
+ "step": 2373
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8545846509723757e-05,
+ "loss": 0.5089,
+ "step": 2374
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8544438909549636e-05,
+ "loss": 0.4991,
+ "step": 2375
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.854303068190746e-05,
+ "loss": 0.5044,
+ "step": 2376
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.854162182690064e-05,
+ "loss": 0.5011,
+ "step": 2377
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8540212344632646e-05,
+ "loss": 0.4879,
+ "step": 2378
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8538802235206977e-05,
+ "loss": 0.5249,
+ "step": 2379
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8537391498727187e-05,
+ "loss": 0.489,
+ "step": 2380
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8535980135296876e-05,
+ "loss": 0.5214,
+ "step": 2381
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8534568145019687e-05,
+ "loss": 0.5325,
+ "step": 2382
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.853315552799931e-05,
+ "loss": 0.5143,
+ "step": 2383
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8531742284339486e-05,
+ "loss": 0.5069,
+ "step": 2384
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.853032841414399e-05,
+ "loss": 0.4942,
+ "step": 2385
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852891391751666e-05,
+ "loss": 0.4831,
+ "step": 2386
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8527498794561367e-05,
+ "loss": 0.4999,
+ "step": 2387
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8526083045382025e-05,
+ "loss": 0.4998,
+ "step": 2388
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852466667008261e-05,
+ "loss": 0.5075,
+ "step": 2389
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8523249668767135e-05,
+ "loss": 0.5047,
+ "step": 2390
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852183204153965e-05,
+ "loss": 0.5177,
+ "step": 2391
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852041378850427e-05,
+ "loss": 0.486,
+ "step": 2392
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.851899490976514e-05,
+ "loss": 0.4809,
+ "step": 2393
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.851757540542645e-05,
+ "loss": 0.5098,
+ "step": 2394
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8516155275592457e-05,
+ "loss": 0.4916,
+ "step": 2395
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8514734520367438e-05,
+ "loss": 0.5143,
+ "step": 2396
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8513313139855734e-05,
+ "loss": 0.4984,
+ "step": 2397
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8511891134161718e-05,
+ "loss": 0.4834,
+ "step": 2398
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8510468503389825e-05,
+ "loss": 0.4972,
+ "step": 2399
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8509045247644524e-05,
+ "loss": 0.4988,
+ "step": 2400
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8507621367030326e-05,
+ "loss": 0.5079,
+ "step": 2401
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8506196861651802e-05,
+ "loss": 0.514,
+ "step": 2402
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8504771731613568e-05,
+ "loss": 0.4905,
+ "step": 2403
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8503345977020262e-05,
+ "loss": 0.5006,
+ "step": 2404
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8501919597976602e-05,
+ "loss": 0.4949,
+ "step": 2405
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.850049259458733e-05,
+ "loss": 0.5129,
+ "step": 2406
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8499064966957233e-05,
+ "loss": 0.498,
+ "step": 2407
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8497636715191153e-05,
+ "loss": 0.499,
+ "step": 2408
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8496207839393984e-05,
+ "loss": 0.4932,
+ "step": 2409
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.849477833967065e-05,
+ "loss": 0.5081,
+ "step": 2410
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.849334821612612e-05,
+ "loss": 0.497,
+ "step": 2411
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8491917468865426e-05,
+ "loss": 0.5113,
+ "step": 2412
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8490486097993635e-05,
+ "loss": 0.5037,
+ "step": 2413
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.848905410361586e-05,
+ "loss": 0.4858,
+ "step": 2414
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.848762148583726e-05,
+ "loss": 0.4957,
+ "step": 2415
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8486188244763038e-05,
+ "loss": 0.5217,
+ "step": 2416
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8484754380498452e-05,
+ "loss": 0.496,
+ "step": 2417
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8483319893148794e-05,
+ "loss": 0.4957,
+ "step": 2418
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.848188478281941e-05,
+ "loss": 0.4935,
+ "step": 2419
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8480449049615684e-05,
+ "loss": 0.4964,
+ "step": 2420
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.847901269364305e-05,
+ "loss": 0.4948,
+ "step": 2421
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.847757571500699e-05,
+ "loss": 0.4968,
+ "step": 2422
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8476138113813037e-05,
+ "loss": 0.5153,
+ "step": 2423
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8474699890166753e-05,
+ "loss": 0.513,
+ "step": 2424
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8473261044173756e-05,
+ "loss": 0.5264,
+ "step": 2425
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8471821575939713e-05,
+ "loss": 0.4933,
+ "step": 2426
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8470381485570327e-05,
+ "loss": 0.5192,
+ "step": 2427
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8468940773171357e-05,
+ "loss": 0.4959,
+ "step": 2428
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8467499438848606e-05,
+ "loss": 0.5083,
+ "step": 2429
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.846605748270791e-05,
+ "loss": 0.5058,
+ "step": 2430
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8464614904855168e-05,
+ "loss": 0.5126,
+ "step": 2431
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8463171705396313e-05,
+ "loss": 0.5123,
+ "step": 2432
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.846172788443733e-05,
+ "loss": 0.4949,
+ "step": 2433
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8460283442084246e-05,
+ "loss": 0.497,
+ "step": 2434
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8458838378443134e-05,
+ "loss": 0.5059,
+ "step": 2435
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8457392693620114e-05,
+ "loss": 0.5048,
+ "step": 2436
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8455946387721356e-05,
+ "loss": 0.518,
+ "step": 2437
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.845449946085306e-05,
+ "loss": 0.5013,
+ "step": 2438
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8453051913121494e-05,
+ "loss": 0.4975,
+ "step": 2439
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8451603744632952e-05,
+ "loss": 0.504,
+ "step": 2440
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.845015495549378e-05,
+ "loss": 0.5083,
+ "step": 2441
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.844870554581038e-05,
+ "loss": 0.5114,
+ "step": 2442
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8447255515689185e-05,
+ "loss": 0.4908,
+ "step": 2443
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.844580486523668e-05,
+ "loss": 0.4994,
+ "step": 2444
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8444353594559392e-05,
+ "loss": 0.5013,
+ "step": 2445
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.84429017037639e-05,
+ "loss": 0.5016,
+ "step": 2446
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8441449192956823e-05,
+ "loss": 0.5037,
+ "step": 2447
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8439996062244828e-05,
+ "loss": 0.4919,
+ "step": 2448
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.843854231173463e-05,
+ "loss": 0.4875,
+ "step": 2449
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8437087941532982e-05,
+ "loss": 0.4861,
+ "step": 2450
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8435632951746685e-05,
+ "loss": 0.5123,
+ "step": 2451
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8434177342482594e-05,
+ "loss": 0.4923,
+ "step": 2452
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8432721113847596e-05,
+ "loss": 0.5275,
+ "step": 2453
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8431264265948636e-05,
+ "loss": 0.529,
+ "step": 2454
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8429806798892694e-05,
+ "loss": 0.5048,
+ "step": 2455
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8428348712786803e-05,
+ "loss": 0.485,
+ "step": 2456
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.842689000773804e-05,
+ "loss": 0.5057,
+ "step": 2457
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8425430683853527e-05,
+ "loss": 0.5013,
+ "step": 2458
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8423970741240426e-05,
+ "loss": 0.4978,
+ "step": 2459
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.842251018000595e-05,
+ "loss": 0.4971,
+ "step": 2460
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8421049000257362e-05,
+ "loss": 0.5246,
+ "step": 2461
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.841958720210196e-05,
+ "loss": 0.4989,
+ "step": 2462
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8418124785647092e-05,
+ "loss": 0.5098,
+ "step": 2463
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8416661751000156e-05,
+ "loss": 0.5075,
+ "step": 2464
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.841519809826859e-05,
+ "loss": 0.4991,
+ "step": 2465
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8413733827559873e-05,
+ "loss": 0.4971,
+ "step": 2466
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.841226893898154e-05,
+ "loss": 0.5031,
+ "step": 2467
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8410803432641165e-05,
+ "loss": 0.4909,
+ "step": 2468
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840933730864637e-05,
+ "loss": 0.5077,
+ "step": 2469
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840787056710482e-05,
+ "loss": 0.5273,
+ "step": 2470
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8406403208124227e-05,
+ "loss": 0.5063,
+ "step": 2471
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8404935231812348e-05,
+ "loss": 0.5041,
+ "step": 2472
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8403466638276983e-05,
+ "loss": 0.493,
+ "step": 2473
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840199742762598e-05,
+ "loss": 0.4928,
+ "step": 2474
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840052759996723e-05,
+ "loss": 0.506,
+ "step": 2475
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.839905715540868e-05,
+ "loss": 0.503,
+ "step": 2476
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8397586094058303e-05,
+ "loss": 0.4865,
+ "step": 2477
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.839611441602413e-05,
+ "loss": 0.4936,
+ "step": 2478
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8394642121414238e-05,
+ "loss": 0.501,
+ "step": 2479
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8393169210336747e-05,
+ "loss": 0.4826,
+ "step": 2480
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8391695682899814e-05,
+ "loss": 0.5122,
+ "step": 2481
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.839022153921166e-05,
+ "loss": 0.5038,
+ "step": 2482
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8388746779380532e-05,
+ "loss": 0.4954,
+ "step": 2483
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.838727140351473e-05,
+ "loss": 0.5098,
+ "step": 2484
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.83857954117226e-05,
+ "loss": 0.4984,
+ "step": 2485
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8384318804112533e-05,
+ "loss": 0.5117,
+ "step": 2486
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.838284158079297e-05,
+ "loss": 0.4905,
+ "step": 2487
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8381363741872386e-05,
+ "loss": 0.4969,
+ "step": 2488
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8379885287459315e-05,
+ "loss": 0.5055,
+ "step": 2489
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8378406217662314e-05,
+ "loss": 0.4903,
+ "step": 2490
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8376926532590012e-05,
+ "loss": 0.4854,
+ "step": 2491
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.837544623235107e-05,
+ "loss": 0.5033,
+ "step": 2492
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8373965317054195e-05,
+ "loss": 0.5127,
+ "step": 2493
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8372483786808133e-05,
+ "loss": 0.488,
+ "step": 2494
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8371001641721685e-05,
+ "loss": 0.4882,
+ "step": 2495
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8369518881903698e-05,
+ "loss": 0.5022,
+ "step": 2496
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8368035507463053e-05,
+ "loss": 0.4967,
+ "step": 2497
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8366551518508685e-05,
+ "loss": 0.4857,
+ "step": 2498
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8365066915149573e-05,
+ "loss": 0.4862,
+ "step": 2499
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8363581697494738e-05,
+ "loss": 0.4842,
+ "step": 2500
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8362095865653257e-05,
+ "loss": 0.4985,
+ "step": 2501
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8360609419734227e-05,
+ "loss": 0.5008,
+ "step": 2502
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.835912235984682e-05,
+ "loss": 0.5087,
+ "step": 2503
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8357634686100236e-05,
+ "loss": 0.4947,
+ "step": 2504
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.835614639860372e-05,
+ "loss": 0.4921,
+ "step": 2505
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.835465749746657e-05,
+ "loss": 0.4997,
+ "step": 2506
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8353167982798124e-05,
+ "loss": 0.5113,
+ "step": 2507
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8351677854707763e-05,
+ "loss": 0.4809,
+ "step": 2508
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8350187113304918e-05,
+ "loss": 0.5035,
+ "step": 2509
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8348695758699065e-05,
+ "loss": 0.5228,
+ "step": 2510
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8347203790999716e-05,
+ "loss": 0.5196,
+ "step": 2511
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.834571121031644e-05,
+ "loss": 0.4999,
+ "step": 2512
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8344218016758847e-05,
+ "loss": 0.5013,
+ "step": 2513
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.834272421043659e-05,
+ "loss": 0.5062,
+ "step": 2514
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8341229791459365e-05,
+ "loss": 0.5037,
+ "step": 2515
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833973475993692e-05,
+ "loss": 0.5002,
+ "step": 2516
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8338239115979038e-05,
+ "loss": 0.501,
+ "step": 2517
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833674285969556e-05,
+ "loss": 0.4984,
+ "step": 2518
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833524599119636e-05,
+ "loss": 0.4887,
+ "step": 2519
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8333748510591364e-05,
+ "loss": 0.5059,
+ "step": 2520
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833225041799054e-05,
+ "loss": 0.5056,
+ "step": 2521
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8330751713503902e-05,
+ "loss": 0.494,
+ "step": 2522
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8329252397241504e-05,
+ "loss": 0.497,
+ "step": 2523
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.832775246931346e-05,
+ "loss": 0.5149,
+ "step": 2524
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.832625192982991e-05,
+ "loss": 0.4997,
+ "step": 2525
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8324750778901047e-05,
+ "loss": 0.5015,
+ "step": 2526
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8323249016637118e-05,
+ "loss": 0.5,
+ "step": 2527
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8321746643148394e-05,
+ "loss": 0.5136,
+ "step": 2528
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8320243658545215e-05,
+ "loss": 0.5003,
+ "step": 2529
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8318740062937944e-05,
+ "loss": 0.482,
+ "step": 2530
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8317235856437006e-05,
+ "loss": 0.476,
+ "step": 2531
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.831573103915286e-05,
+ "loss": 0.4906,
+ "step": 2532
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8314225611196013e-05,
+ "loss": 0.5128,
+ "step": 2533
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8312719572677018e-05,
+ "loss": 0.5126,
+ "step": 2534
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8311212923706473e-05,
+ "loss": 0.5084,
+ "step": 2535
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8309705664395024e-05,
+ "loss": 0.5062,
+ "step": 2536
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.830819779485335e-05,
+ "loss": 0.4906,
+ "step": 2537
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8306689315192187e-05,
+ "loss": 0.5119,
+ "step": 2538
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8305180225522306e-05,
+ "loss": 0.4949,
+ "step": 2539
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.830367052595454e-05,
+ "loss": 0.4931,
+ "step": 2540
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8302160216599745e-05,
+ "loss": 0.5127,
+ "step": 2541
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8300649297568837e-05,
+ "loss": 0.488,
+ "step": 2542
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8299137768972766e-05,
+ "loss": 0.5083,
+ "step": 2543
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829762563092254e-05,
+ "loss": 0.4948,
+ "step": 2544
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8296112883529197e-05,
+ "loss": 0.5074,
+ "step": 2545
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829459952690383e-05,
+ "loss": 0.5196,
+ "step": 2546
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8293085561157578e-05,
+ "loss": 0.4939,
+ "step": 2547
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829157098640161e-05,
+ "loss": 0.4937,
+ "step": 2548
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829005580274716e-05,
+ "loss": 0.4949,
+ "step": 2549
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.828854001030549e-05,
+ "loss": 0.4918,
+ "step": 2550
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.828702360918792e-05,
+ "loss": 0.5065,
+ "step": 2551
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8285506599505803e-05,
+ "loss": 0.4884,
+ "step": 2552
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8283988981370543e-05,
+ "loss": 0.5058,
+ "step": 2553
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8282470754893585e-05,
+ "loss": 0.5247,
+ "step": 2554
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.828095192018643e-05,
+ "loss": 0.5005,
+ "step": 2555
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.82794324773606e-05,
+ "loss": 0.4886,
+ "step": 2556
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8277912426527696e-05,
+ "loss": 0.5016,
+ "step": 2557
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8276391767799326e-05,
+ "loss": 0.4991,
+ "step": 2558
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8274870501287174e-05,
+ "loss": 0.5007,
+ "step": 2559
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8273348627102948e-05,
+ "loss": 0.4941,
+ "step": 2560
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.827182614535841e-05,
+ "loss": 0.4995,
+ "step": 2561
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8270303056165364e-05,
+ "loss": 0.4974,
+ "step": 2562
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.826877935963566e-05,
+ "loss": 0.5034,
+ "step": 2563
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8267255055881197e-05,
+ "loss": 0.4848,
+ "step": 2564
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8265730145013903e-05,
+ "loss": 0.5114,
+ "step": 2565
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.826420462714577e-05,
+ "loss": 0.5084,
+ "step": 2566
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8262678502388824e-05,
+ "loss": 0.5176,
+ "step": 2567
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8261151770855134e-05,
+ "loss": 0.4974,
+ "step": 2568
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8259624432656816e-05,
+ "loss": 0.5196,
+ "step": 2569
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.825809648790604e-05,
+ "loss": 0.4914,
+ "step": 2570
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8256567936715e-05,
+ "loss": 0.4887,
+ "step": 2571
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8255038779195957e-05,
+ "loss": 0.513,
+ "step": 2572
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.82535090154612e-05,
+ "loss": 0.4801,
+ "step": 2573
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.825197864562307e-05,
+ "loss": 0.4912,
+ "step": 2574
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.825044766979395e-05,
+ "loss": 0.5092,
+ "step": 2575
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8248916088086268e-05,
+ "loss": 0.5197,
+ "step": 2576
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.82473839006125e-05,
+ "loss": 0.4776,
+ "step": 2577
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.824585110748516e-05,
+ "loss": 0.4789,
+ "step": 2578
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8244317708816815e-05,
+ "loss": 0.5079,
+ "step": 2579
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8242783704720066e-05,
+ "loss": 0.5039,
+ "step": 2580
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8241249095307566e-05,
+ "loss": 0.4892,
+ "step": 2581
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823971388069201e-05,
+ "loss": 0.4991,
+ "step": 2582
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823817806098614e-05,
+ "loss": 0.4969,
+ "step": 2583
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8236641636302737e-05,
+ "loss": 0.4987,
+ "step": 2584
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823510460675463e-05,
+ "loss": 0.49,
+ "step": 2585
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8233566972454696e-05,
+ "loss": 0.4967,
+ "step": 2586
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823202873351585e-05,
+ "loss": 0.4846,
+ "step": 2587
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8230489890051048e-05,
+ "loss": 0.5066,
+ "step": 2588
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8228950442173304e-05,
+ "loss": 0.513,
+ "step": 2589
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8227410389995668e-05,
+ "loss": 0.4966,
+ "step": 2590
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8225869733631234e-05,
+ "loss": 0.5062,
+ "step": 2591
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8224328473193137e-05,
+ "loss": 0.488,
+ "step": 2592
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.822278660879457e-05,
+ "loss": 0.4971,
+ "step": 2593
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.822124414054875e-05,
+ "loss": 0.5029,
+ "step": 2594
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8219701068568957e-05,
+ "loss": 0.4926,
+ "step": 2595
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8218157392968505e-05,
+ "loss": 0.4797,
+ "step": 2596
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.821661311386076e-05,
+ "loss": 0.5108,
+ "step": 2597
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8215068231359118e-05,
+ "loss": 0.5117,
+ "step": 2598
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.821352274557704e-05,
+ "loss": 0.4963,
+ "step": 2599
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8211976656628007e-05,
+ "loss": 0.5159,
+ "step": 2600
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.821042996462557e-05,
+ "loss": 0.4822,
+ "step": 2601
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8208882669683305e-05,
+ "loss": 0.4933,
+ "step": 2602
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.820733477191484e-05,
+ "loss": 0.4897,
+ "step": 2603
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8205786271433845e-05,
+ "loss": 0.4959,
+ "step": 2604
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8204237168354038e-05,
+ "loss": 0.5009,
+ "step": 2605
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8202687462789175e-05,
+ "loss": 0.4853,
+ "step": 2606
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8201137154853065e-05,
+ "loss": 0.523,
+ "step": 2607
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8199586244659554e-05,
+ "loss": 0.512,
+ "step": 2608
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8198034732322532e-05,
+ "loss": 0.4876,
+ "step": 2609
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8196482617955938e-05,
+ "loss": 0.5184,
+ "step": 2610
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8194929901673752e-05,
+ "loss": 0.536,
+ "step": 2611
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.819337658359e-05,
+ "loss": 0.4823,
+ "step": 2612
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.819182266381875e-05,
+ "loss": 0.504,
+ "step": 2613
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8190268142474113e-05,
+ "loss": 0.5123,
+ "step": 2614
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8188713019670253e-05,
+ "loss": 0.4874,
+ "step": 2615
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8187157295521366e-05,
+ "loss": 0.4956,
+ "step": 2616
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8185600970141703e-05,
+ "loss": 0.5148,
+ "step": 2617
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.818404404364555e-05,
+ "loss": 0.4907,
+ "step": 2618
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.818248651614724e-05,
+ "loss": 0.4943,
+ "step": 2619
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8180928387761157e-05,
+ "loss": 0.5055,
+ "step": 2620
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.817936965860172e-05,
+ "loss": 0.4992,
+ "step": 2621
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8177810328783395e-05,
+ "loss": 0.5033,
+ "step": 2622
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8176250398420694e-05,
+ "loss": 0.4799,
+ "step": 2623
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.817468986762817e-05,
+ "loss": 0.4893,
+ "step": 2624
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8173128736520427e-05,
+ "loss": 0.5092,
+ "step": 2625
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.81715670052121e-05,
+ "loss": 0.4862,
+ "step": 2626
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8170004673817882e-05,
+ "loss": 0.5004,
+ "step": 2627
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8168441742452502e-05,
+ "loss": 0.4948,
+ "step": 2628
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8166878211230736e-05,
+ "loss": 0.5071,
+ "step": 2629
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8165314080267406e-05,
+ "loss": 0.5127,
+ "step": 2630
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8163749349677363e-05,
+ "loss": 0.5117,
+ "step": 2631
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8162184019575534e-05,
+ "loss": 0.5178,
+ "step": 2632
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.816061809007685e-05,
+ "loss": 0.5083,
+ "step": 2633
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8159051561296323e-05,
+ "loss": 0.5078,
+ "step": 2634
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.815748443334898e-05,
+ "loss": 0.5072,
+ "step": 2635
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8155916706349913e-05,
+ "loss": 0.4987,
+ "step": 2636
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8154348380414245e-05,
+ "loss": 0.5096,
+ "step": 2637
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.815277945565715e-05,
+ "loss": 0.5288,
+ "step": 2638
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8151209932193844e-05,
+ "loss": 0.4849,
+ "step": 2639
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.814963981013958e-05,
+ "loss": 0.4918,
+ "step": 2640
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8148069089609667e-05,
+ "loss": 0.4967,
+ "step": 2641
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8146497770719448e-05,
+ "loss": 0.5129,
+ "step": 2642
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8144925853584315e-05,
+ "loss": 0.4814,
+ "step": 2643
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8143353338319712e-05,
+ "loss": 0.5177,
+ "step": 2644
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8141780225041104e-05,
+ "loss": 0.5168,
+ "step": 2645
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8140206513864026e-05,
+ "loss": 0.5167,
+ "step": 2646
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8138632204904033e-05,
+ "loss": 0.4849,
+ "step": 2647
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8137057298276745e-05,
+ "loss": 0.4971,
+ "step": 2648
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8135481794097814e-05,
+ "loss": 0.5189,
+ "step": 2649
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.813390569248294e-05,
+ "loss": 0.4916,
+ "step": 2650
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.813232899354786e-05,
+ "loss": 0.5015,
+ "step": 2651
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8130751697408364e-05,
+ "loss": 0.499,
+ "step": 2652
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8129173804180285e-05,
+ "loss": 0.4776,
+ "step": 2653
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.812759531397949e-05,
+ "loss": 0.4923,
+ "step": 2654
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8126016226921898e-05,
+ "loss": 0.5178,
+ "step": 2655
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.812443654312348e-05,
+ "loss": 0.4954,
+ "step": 2656
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8122856262700227e-05,
+ "loss": 0.5286,
+ "step": 2657
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.81212753857682e-05,
+ "loss": 0.5092,
+ "step": 2658
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8119693912443487e-05,
+ "loss": 0.5141,
+ "step": 2659
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8118111842842227e-05,
+ "loss": 0.5079,
+ "step": 2660
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8116529177080594e-05,
+ "loss": 0.4833,
+ "step": 2661
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8114945915274826e-05,
+ "loss": 0.5262,
+ "step": 2662
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8113362057541175e-05,
+ "loss": 0.5065,
+ "step": 2663
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.811177760399596e-05,
+ "loss": 0.492,
+ "step": 2664
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.811019255475554e-05,
+ "loss": 0.4939,
+ "step": 2665
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8108606909936312e-05,
+ "loss": 0.4864,
+ "step": 2666
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.810702066965472e-05,
+ "loss": 0.4914,
+ "step": 2667
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.810543383402725e-05,
+ "loss": 0.5023,
+ "step": 2668
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8103846403170427e-05,
+ "loss": 0.4967,
+ "step": 2669
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8102258377200837e-05,
+ "loss": 0.4998,
+ "step": 2670
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8100669756235087e-05,
+ "loss": 0.5019,
+ "step": 2671
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8099080540389845e-05,
+ "loss": 0.5198,
+ "step": 2672
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8097490729781815e-05,
+ "loss": 0.5041,
+ "step": 2673
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8095900324527745e-05,
+ "loss": 0.4983,
+ "step": 2674
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8094309324744428e-05,
+ "loss": 0.4895,
+ "step": 2675
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8092717730548702e-05,
+ "loss": 0.5035,
+ "step": 2676
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8091125542057442e-05,
+ "loss": 0.51,
+ "step": 2677
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8089532759387586e-05,
+ "loss": 0.4928,
+ "step": 2678
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8087939382656082e-05,
+ "loss": 0.4932,
+ "step": 2679
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8086345411979952e-05,
+ "loss": 0.5225,
+ "step": 2680
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.808475084747625e-05,
+ "loss": 0.4933,
+ "step": 2681
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.808315568926207e-05,
+ "loss": 0.5014,
+ "step": 2682
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.808155993745456e-05,
+ "loss": 0.4988,
+ "step": 2683
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8079963592170903e-05,
+ "loss": 0.4932,
+ "step": 2684
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.807836665352832e-05,
+ "loss": 0.4945,
+ "step": 2685
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8076769121644097e-05,
+ "loss": 0.4966,
+ "step": 2686
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8075170996635538e-05,
+ "loss": 0.516,
+ "step": 2687
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8073572278620015e-05,
+ "loss": 0.5308,
+ "step": 2688
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8071972967714918e-05,
+ "loss": 0.4975,
+ "step": 2689
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8070373064037702e-05,
+ "loss": 0.5108,
+ "step": 2690
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8068772567705858e-05,
+ "loss": 0.4995,
+ "step": 2691
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8067171478836916e-05,
+ "loss": 0.4989,
+ "step": 2692
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8065569797548453e-05,
+ "loss": 0.4833,
+ "step": 2693
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8063967523958093e-05,
+ "loss": 0.4976,
+ "step": 2694
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80623646581835e-05,
+ "loss": 0.5101,
+ "step": 2695
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8060761200342376e-05,
+ "loss": 0.5045,
+ "step": 2696
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8059157150552477e-05,
+ "loss": 0.4985,
+ "step": 2697
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80575525089316e-05,
+ "loss": 0.4916,
+ "step": 2698
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.805594727559758e-05,
+ "loss": 0.4951,
+ "step": 2699
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80543414506683e-05,
+ "loss": 0.5025,
+ "step": 2700
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8052735034261683e-05,
+ "loss": 0.5244,
+ "step": 2701
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8051128026495703e-05,
+ "loss": 0.4934,
+ "step": 2702
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8049520427488362e-05,
+ "loss": 0.5106,
+ "step": 2703
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8047912237357724e-05,
+ "loss": 0.5032,
+ "step": 2704
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8046303456221885e-05,
+ "loss": 0.4925,
+ "step": 2705
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8044694084198985e-05,
+ "loss": 0.4961,
+ "step": 2706
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8043084121407214e-05,
+ "loss": 0.4993,
+ "step": 2707
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80414735679648e-05,
+ "loss": 0.5052,
+ "step": 2708
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8039862423990012e-05,
+ "loss": 0.5097,
+ "step": 2709
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803825068960117e-05,
+ "loss": 0.5066,
+ "step": 2710
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803663836491663e-05,
+ "loss": 0.5189,
+ "step": 2711
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8035025450054796e-05,
+ "loss": 0.4867,
+ "step": 2712
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803341194513411e-05,
+ "loss": 0.4937,
+ "step": 2713
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803179785027307e-05,
+ "loss": 0.512,
+ "step": 2714
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8030183165590197e-05,
+ "loss": 0.4938,
+ "step": 2715
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8028567891204074e-05,
+ "loss": 0.4957,
+ "step": 2716
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.802695202723332e-05,
+ "loss": 0.4973,
+ "step": 2717
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8025335573796596e-05,
+ "loss": 0.5068,
+ "step": 2718
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8023718531012602e-05,
+ "loss": 0.4977,
+ "step": 2719
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80221008990001e-05,
+ "loss": 0.4864,
+ "step": 2720
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8020482677877868e-05,
+ "loss": 0.5293,
+ "step": 2721
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.801886386776475e-05,
+ "loss": 0.4882,
+ "step": 2722
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8017244468779625e-05,
+ "loss": 0.4978,
+ "step": 2723
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8015624481041408e-05,
+ "loss": 0.4887,
+ "step": 2724
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8014003904669073e-05,
+ "loss": 0.4994,
+ "step": 2725
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8012382739781623e-05,
+ "loss": 0.498,
+ "step": 2726
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.801076098649811e-05,
+ "loss": 0.5084,
+ "step": 2727
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8009138644937626e-05,
+ "loss": 0.5097,
+ "step": 2728
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8007515715219317e-05,
+ "loss": 0.5071,
+ "step": 2729
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8005892197462355e-05,
+ "loss": 0.5053,
+ "step": 2730
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8004268091785973e-05,
+ "loss": 0.4957,
+ "step": 2731
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8002643398309434e-05,
+ "loss": 0.4895,
+ "step": 2732
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.800101811715205e-05,
+ "loss": 0.4991,
+ "step": 2733
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.799939224843317e-05,
+ "loss": 0.4882,
+ "step": 2734
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7997765792272203e-05,
+ "loss": 0.4993,
+ "step": 2735
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7996138748788573e-05,
+ "loss": 0.4852,
+ "step": 2736
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.799451111810178e-05,
+ "loss": 0.5067,
+ "step": 2737
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7992882900331336e-05,
+ "loss": 0.5039,
+ "step": 2738
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.799125409559682e-05,
+ "loss": 0.4889,
+ "step": 2739
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7989624704017838e-05,
+ "loss": 0.4925,
+ "step": 2740
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.798799472571405e-05,
+ "loss": 0.4827,
+ "step": 2741
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7986364160805156e-05,
+ "loss": 0.4894,
+ "step": 2742
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7984733009410896e-05,
+ "loss": 0.5013,
+ "step": 2743
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7983101271651052e-05,
+ "loss": 0.4842,
+ "step": 2744
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.798146894764546e-05,
+ "loss": 0.5058,
+ "step": 2745
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7979836037513977e-05,
+ "loss": 0.5045,
+ "step": 2746
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7978202541376533e-05,
+ "loss": 0.4997,
+ "step": 2747
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7976568459353078e-05,
+ "loss": 0.5177,
+ "step": 2748
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.797493379156361e-05,
+ "loss": 0.4966,
+ "step": 2749
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7973298538128174e-05,
+ "loss": 0.4932,
+ "step": 2750
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.797166269916686e-05,
+ "loss": 0.4896,
+ "step": 2751
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.797002627479979e-05,
+ "loss": 0.4984,
+ "step": 2752
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7968389265147142e-05,
+ "loss": 0.5047,
+ "step": 2753
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.796675167032913e-05,
+ "loss": 0.4992,
+ "step": 2754
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7965113490466013e-05,
+ "loss": 0.4927,
+ "step": 2755
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.796347472567809e-05,
+ "loss": 0.4969,
+ "step": 2756
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7961835376085702e-05,
+ "loss": 0.497,
+ "step": 2757
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7960195441809242e-05,
+ "loss": 0.4832,
+ "step": 2758
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.795855492296914e-05,
+ "loss": 0.5121,
+ "step": 2759
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7956913819685865e-05,
+ "loss": 0.5147,
+ "step": 2760
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7955272132079935e-05,
+ "loss": 0.4937,
+ "step": 2761
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7953629860271906e-05,
+ "loss": 0.5006,
+ "step": 2762
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7951987004382384e-05,
+ "loss": 0.4956,
+ "step": 2763
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.795034356453201e-05,
+ "loss": 0.5006,
+ "step": 2764
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.794869954084147e-05,
+ "loss": 0.51,
+ "step": 2765
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.79470549334315e-05,
+ "loss": 0.4736,
+ "step": 2766
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.794540974242287e-05,
+ "loss": 0.5055,
+ "step": 2767
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7943763967936395e-05,
+ "loss": 0.5209,
+ "step": 2768
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7942117610092938e-05,
+ "loss": 0.493,
+ "step": 2769
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.794047066901339e-05,
+ "loss": 0.4909,
+ "step": 2770
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7938823144818712e-05,
+ "loss": 0.5175,
+ "step": 2771
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7937175037629876e-05,
+ "loss": 0.4814,
+ "step": 2772
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793552634756792e-05,
+ "loss": 0.5145,
+ "step": 2773
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793387707475392e-05,
+ "loss": 0.5087,
+ "step": 2774
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793222721930898e-05,
+ "loss": 0.504,
+ "step": 2775
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793057678135427e-05,
+ "loss": 0.4912,
+ "step": 2776
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7928925761010984e-05,
+ "loss": 0.5088,
+ "step": 2777
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.792727415840037e-05,
+ "loss": 0.484,
+ "step": 2778
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7925621973643713e-05,
+ "loss": 0.5029,
+ "step": 2779
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7923969206862347e-05,
+ "loss": 0.5131,
+ "step": 2780
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7922315858177638e-05,
+ "loss": 0.4955,
+ "step": 2781
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7920661927711002e-05,
+ "loss": 0.5075,
+ "step": 2782
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7919007415583903e-05,
+ "loss": 0.469,
+ "step": 2783
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7917352321917834e-05,
+ "loss": 0.5087,
+ "step": 2784
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7915696646834343e-05,
+ "loss": 0.4729,
+ "step": 2785
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7914040390455014e-05,
+ "loss": 0.4914,
+ "step": 2786
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7912383552901473e-05,
+ "loss": 0.5058,
+ "step": 2787
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7910726134295396e-05,
+ "loss": 0.4916,
+ "step": 2788
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7909068134758497e-05,
+ "loss": 0.5064,
+ "step": 2789
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7907409554412526e-05,
+ "loss": 0.501,
+ "step": 2790
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.790575039337929e-05,
+ "loss": 0.5054,
+ "step": 2791
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7904090651780624e-05,
+ "loss": 0.4934,
+ "step": 2792
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.790243032973842e-05,
+ "loss": 0.5042,
+ "step": 2793
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.79007694273746e-05,
+ "loss": 0.4681,
+ "step": 2794
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7899107944811133e-05,
+ "loss": 0.5011,
+ "step": 2795
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7897445882170038e-05,
+ "loss": 0.5067,
+ "step": 2796
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.789578323957336e-05,
+ "loss": 0.5044,
+ "step": 2797
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7894120017143205e-05,
+ "loss": 0.5046,
+ "step": 2798
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.789245621500171e-05,
+ "loss": 0.4989,
+ "step": 2799
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7890791833271058e-05,
+ "loss": 0.4721,
+ "step": 2800
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7889126872073473e-05,
+ "loss": 0.5095,
+ "step": 2801
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7887461331531224e-05,
+ "loss": 0.496,
+ "step": 2802
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.788579521176662e-05,
+ "loss": 0.4881,
+ "step": 2803
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7884128512902018e-05,
+ "loss": 0.5057,
+ "step": 2804
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.788246123505981e-05,
+ "loss": 0.5034,
+ "step": 2805
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7880793378362432e-05,
+ "loss": 0.4997,
+ "step": 2806
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.787912494293237e-05,
+ "loss": 0.4959,
+ "step": 2807
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.787745592889214e-05,
+ "loss": 0.4812,
+ "step": 2808
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7875786336364316e-05,
+ "loss": 0.5047,
+ "step": 2809
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.78741161654715e-05,
+ "loss": 0.4924,
+ "step": 2810
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7872445416336343e-05,
+ "loss": 0.5078,
+ "step": 2811
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7870774089081537e-05,
+ "loss": 0.4883,
+ "step": 2812
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.786910218382982e-05,
+ "loss": 0.5038,
+ "step": 2813
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7867429700703967e-05,
+ "loss": 0.5137,
+ "step": 2814
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7865756639826805e-05,
+ "loss": 0.5147,
+ "step": 2815
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.786408300132119e-05,
+ "loss": 0.4802,
+ "step": 2816
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7862408785310025e-05,
+ "loss": 0.5072,
+ "step": 2817
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7860733991916263e-05,
+ "loss": 0.5101,
+ "step": 2818
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7859058621262893e-05,
+ "loss": 0.4928,
+ "step": 2819
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7857382673472946e-05,
+ "loss": 0.499,
+ "step": 2820
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7855706148669494e-05,
+ "loss": 0.5024,
+ "step": 2821
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.785402904697566e-05,
+ "loss": 0.4932,
+ "step": 2822
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7852351368514597e-05,
+ "loss": 0.5075,
+ "step": 2823
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7850673113409514e-05,
+ "loss": 0.499,
+ "step": 2824
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7848994281783648e-05,
+ "loss": 0.5007,
+ "step": 2825
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.784731487376029e-05,
+ "loss": 0.5201,
+ "step": 2826
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7845634889462763e-05,
+ "loss": 0.4836,
+ "step": 2827
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.784395432901445e-05,
+ "loss": 0.5021,
+ "step": 2828
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.784227319253875e-05,
+ "loss": 0.5008,
+ "step": 2829
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7840591480159127e-05,
+ "loss": 0.5007,
+ "step": 2830
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7838909191999077e-05,
+ "loss": 0.4969,
+ "step": 2831
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.783722632818214e-05,
+ "loss": 0.4959,
+ "step": 2832
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.78355428888319e-05,
+ "loss": 0.5112,
+ "step": 2833
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.783385887407198e-05,
+ "loss": 0.5032,
+ "step": 2834
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.783217428402605e-05,
+ "loss": 0.5036,
+ "step": 2835
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7830489118817812e-05,
+ "loss": 0.5104,
+ "step": 2836
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7828803378571028e-05,
+ "loss": 0.4815,
+ "step": 2837
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7827117063409483e-05,
+ "loss": 0.4726,
+ "step": 2838
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.782543017345702e-05,
+ "loss": 0.4989,
+ "step": 2839
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.782374270883751e-05,
+ "loss": 0.4892,
+ "step": 2840
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7822054669674878e-05,
+ "loss": 0.4928,
+ "step": 2841
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7820366056093083e-05,
+ "loss": 0.4805,
+ "step": 2842
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7818676868216137e-05,
+ "loss": 0.4995,
+ "step": 2843
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.781698710616808e-05,
+ "loss": 0.4744,
+ "step": 2844
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7815296770073002e-05,
+ "loss": 0.4918,
+ "step": 2845
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7813605860055034e-05,
+ "loss": 0.5363,
+ "step": 2846
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7811914376238354e-05,
+ "loss": 0.4904,
+ "step": 2847
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7810222318747173e-05,
+ "loss": 0.4744,
+ "step": 2848
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780852968770575e-05,
+ "loss": 0.4957,
+ "step": 2849
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7806836483238387e-05,
+ "loss": 0.521,
+ "step": 2850
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780514270546942e-05,
+ "loss": 0.4905,
+ "step": 2851
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780344835452324e-05,
+ "loss": 0.494,
+ "step": 2852
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780175343052427e-05,
+ "loss": 0.4928,
+ "step": 2853
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7800057933596975e-05,
+ "loss": 0.4872,
+ "step": 2854
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.779836186386587e-05,
+ "loss": 0.4856,
+ "step": 2855
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7796665221455503e-05,
+ "loss": 0.5121,
+ "step": 2856
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7794968006490475e-05,
+ "loss": 0.4866,
+ "step": 2857
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7793270219095418e-05,
+ "loss": 0.498,
+ "step": 2858
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.779157185939501e-05,
+ "loss": 0.4983,
+ "step": 2859
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.778987292751397e-05,
+ "loss": 0.501,
+ "step": 2860
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7788173423577063e-05,
+ "loss": 0.5019,
+ "step": 2861
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7786473347709094e-05,
+ "loss": 0.5126,
+ "step": 2862
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.778477270003491e-05,
+ "loss": 0.5096,
+ "step": 2863
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7783071480679397e-05,
+ "loss": 0.506,
+ "step": 2864
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7781369689767488e-05,
+ "loss": 0.4847,
+ "step": 2865
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7779667327424152e-05,
+ "loss": 0.5061,
+ "step": 2866
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.777796439377441e-05,
+ "loss": 0.5108,
+ "step": 2867
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.777626088894331e-05,
+ "loss": 0.486,
+ "step": 2868
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7774556813055956e-05,
+ "loss": 0.4891,
+ "step": 2869
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7772852166237483e-05,
+ "loss": 0.5196,
+ "step": 2870
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7771146948613078e-05,
+ "loss": 0.507,
+ "step": 2871
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7769441160307967e-05,
+ "loss": 0.5085,
+ "step": 2872
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.776773480144741e-05,
+ "loss": 0.4863,
+ "step": 2873
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.776602787215672e-05,
+ "loss": 0.4874,
+ "step": 2874
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7764320372561238e-05,
+ "loss": 0.5047,
+ "step": 2875
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7762612302786372e-05,
+ "loss": 0.495,
+ "step": 2876
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.776090366295754e-05,
+ "loss": 0.5146,
+ "step": 2877
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.775919445320022e-05,
+ "loss": 0.4959,
+ "step": 2878
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7757484673639936e-05,
+ "loss": 0.4918,
+ "step": 2879
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7755774324402244e-05,
+ "loss": 0.4994,
+ "step": 2880
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7754063405612744e-05,
+ "loss": 0.4843,
+ "step": 2881
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7752351917397078e-05,
+ "loss": 0.5114,
+ "step": 2882
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.775063985988093e-05,
+ "loss": 0.4892,
+ "step": 2883
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.774892723319003e-05,
+ "loss": 0.5053,
+ "step": 2884
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7747214037450146e-05,
+ "loss": 0.4994,
+ "step": 2885
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7745500272787084e-05,
+ "loss": 0.4916,
+ "step": 2886
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7743785939326697e-05,
+ "loss": 0.5066,
+ "step": 2887
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7742071037194882e-05,
+ "loss": 0.484,
+ "step": 2888
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7740355566517567e-05,
+ "loss": 0.5008,
+ "step": 2889
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7738639527420738e-05,
+ "loss": 0.4982,
+ "step": 2890
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.773692292003041e-05,
+ "loss": 0.4913,
+ "step": 2891
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7735205744472642e-05,
+ "loss": 0.5338,
+ "step": 2892
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7733488000873538e-05,
+ "loss": 0.5042,
+ "step": 2893
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.773176968935924e-05,
+ "loss": 0.4934,
+ "step": 2894
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7730050810055935e-05,
+ "loss": 0.499,
+ "step": 2895
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.772833136308985e-05,
+ "loss": 0.5032,
+ "step": 2896
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7726611348587255e-05,
+ "loss": 0.5151,
+ "step": 2897
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7724890766674457e-05,
+ "loss": 0.4901,
+ "step": 2898
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7723169617477815e-05,
+ "loss": 0.5074,
+ "step": 2899
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.772144790112372e-05,
+ "loss": 0.4803,
+ "step": 2900
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7719725617738605e-05,
+ "loss": 0.4699,
+ "step": 2901
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.771800276744895e-05,
+ "loss": 0.5076,
+ "step": 2902
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.771627935038127e-05,
+ "loss": 0.4943,
+ "step": 2903
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7714555366662133e-05,
+ "loss": 0.4933,
+ "step": 2904
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7712830816418137e-05,
+ "loss": 0.5069,
+ "step": 2905
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7711105699775925e-05,
+ "loss": 0.4909,
+ "step": 2906
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7709380016862182e-05,
+ "loss": 0.4913,
+ "step": 2907
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7707653767803638e-05,
+ "loss": 0.4997,
+ "step": 2908
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.770592695272706e-05,
+ "loss": 0.4943,
+ "step": 2909
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7704199571759257e-05,
+ "loss": 0.5002,
+ "step": 2910
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.770247162502708e-05,
+ "loss": 0.4869,
+ "step": 2911
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7700743112657427e-05,
+ "loss": 0.504,
+ "step": 2912
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7699014034777227e-05,
+ "loss": 0.4923,
+ "step": 2913
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7697284391513462e-05,
+ "loss": 0.5013,
+ "step": 2914
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7695554182993145e-05,
+ "loss": 0.5073,
+ "step": 2915
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7693823409343335e-05,
+ "loss": 0.4885,
+ "step": 2916
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.769209207069114e-05,
+ "loss": 0.5021,
+ "step": 2917
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7690360167163693e-05,
+ "loss": 0.4975,
+ "step": 2918
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.768862769888818e-05,
+ "loss": 0.5013,
+ "step": 2919
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7686894665991837e-05,
+ "loss": 0.5013,
+ "step": 2920
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7685161068601915e-05,
+ "loss": 0.4903,
+ "step": 2921
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.768342690684573e-05,
+ "loss": 0.4874,
+ "step": 2922
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.768169218085063e-05,
+ "loss": 0.5023,
+ "step": 2923
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7679956890744008e-05,
+ "loss": 0.4943,
+ "step": 2924
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7678221036653295e-05,
+ "loss": 0.505,
+ "step": 2925
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7676484618705966e-05,
+ "loss": 0.4858,
+ "step": 2926
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7674747637029533e-05,
+ "loss": 0.4885,
+ "step": 2927
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7673010091751557e-05,
+ "loss": 0.4894,
+ "step": 2928
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7671271982999637e-05,
+ "loss": 0.4983,
+ "step": 2929
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7669533310901405e-05,
+ "loss": 0.4914,
+ "step": 2930
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.766779407558455e-05,
+ "loss": 0.5021,
+ "step": 2931
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7666054277176788e-05,
+ "loss": 0.4882,
+ "step": 2932
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7664313915805885e-05,
+ "loss": 0.4862,
+ "step": 2933
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7662572991599648e-05,
+ "loss": 0.5032,
+ "step": 2934
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7660831504685923e-05,
+ "loss": 0.4968,
+ "step": 2935
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7659089455192594e-05,
+ "loss": 0.4915,
+ "step": 2936
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7657346843247595e-05,
+ "loss": 0.5019,
+ "step": 2937
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.765560366897889e-05,
+ "loss": 0.4972,
+ "step": 2938
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7653859932514494e-05,
+ "loss": 0.4978,
+ "step": 2939
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.765211563398246e-05,
+ "loss": 0.5023,
+ "step": 2940
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7650370773510885e-05,
+ "loss": 0.5064,
+ "step": 2941
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7648625351227894e-05,
+ "loss": 0.481,
+ "step": 2942
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7646879367261673e-05,
+ "loss": 0.4964,
+ "step": 2943
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7645132821740437e-05,
+ "loss": 0.4971,
+ "step": 2944
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7643385714792446e-05,
+ "loss": 0.4873,
+ "step": 2945
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7641638046546e-05,
+ "loss": 0.4941,
+ "step": 2946
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7639889817129435e-05,
+ "loss": 0.4745,
+ "step": 2947
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.763814102667114e-05,
+ "loss": 0.4895,
+ "step": 2948
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7636391675299546e-05,
+ "loss": 0.5155,
+ "step": 2949
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.76346417631431e-05,
+ "loss": 0.4832,
+ "step": 2950
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.763289129033032e-05,
+ "loss": 0.4912,
+ "step": 2951
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7631140256989753e-05,
+ "loss": 0.5079,
+ "step": 2952
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.762938866324998e-05,
+ "loss": 0.4972,
+ "step": 2953
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7627636509239646e-05,
+ "loss": 0.4955,
+ "step": 2954
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7625883795087405e-05,
+ "loss": 0.4958,
+ "step": 2955
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.762413052092198e-05,
+ "loss": 0.4923,
+ "step": 2956
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7622376686872122e-05,
+ "loss": 0.4913,
+ "step": 2957
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.762062229306662e-05,
+ "loss": 0.51,
+ "step": 2958
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7618867339634314e-05,
+ "loss": 0.4916,
+ "step": 2959
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7617111826704083e-05,
+ "loss": 0.5067,
+ "step": 2960
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.761535575440484e-05,
+ "loss": 0.517,
+ "step": 2961
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7613599122865545e-05,
+ "loss": 0.4977,
+ "step": 2962
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.76118419322152e-05,
+ "loss": 0.5007,
+ "step": 2963
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.761008418258284e-05,
+ "loss": 0.4947,
+ "step": 2964
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7608325874097548e-05,
+ "loss": 0.5109,
+ "step": 2965
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7606567006888453e-05,
+ "loss": 0.4925,
+ "step": 2966
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7604807581084714e-05,
+ "loss": 0.4935,
+ "step": 2967
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7603047596815538e-05,
+ "loss": 0.4883,
+ "step": 2968
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.760128705421017e-05,
+ "loss": 0.5063,
+ "step": 2969
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7599525953397898e-05,
+ "loss": 0.4865,
+ "step": 2970
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7597764294508048e-05,
+ "loss": 0.5095,
+ "step": 2971
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7596002077669988e-05,
+ "loss": 0.4756,
+ "step": 2972
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.759423930301313e-05,
+ "loss": 0.4943,
+ "step": 2973
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7592475970666926e-05,
+ "loss": 0.5059,
+ "step": 2974
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7590712080760865e-05,
+ "loss": 0.493,
+ "step": 2975
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7588947633424478e-05,
+ "loss": 0.4919,
+ "step": 2976
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7587182628787343e-05,
+ "loss": 0.492,
+ "step": 2977
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.758541706697908e-05,
+ "loss": 0.5072,
+ "step": 2978
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.758365094812933e-05,
+ "loss": 0.4911,
+ "step": 2979
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.75818842723678e-05,
+ "loss": 0.4993,
+ "step": 2980
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7580117039824224e-05,
+ "loss": 0.5072,
+ "step": 2981
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.757834925062838e-05,
+ "loss": 0.4968,
+ "step": 2982
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7576580904910088e-05,
+ "loss": 0.4873,
+ "step": 2983
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.757481200279921e-05,
+ "loss": 0.5004,
+ "step": 2984
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7573042544425644e-05,
+ "loss": 0.5078,
+ "step": 2985
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.757127252991933e-05,
+ "loss": 0.486,
+ "step": 2986
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7569501959410253e-05,
+ "loss": 0.5065,
+ "step": 2987
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7567730833028436e-05,
+ "loss": 0.5147,
+ "step": 2988
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7565959150903943e-05,
+ "loss": 0.4804,
+ "step": 2989
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.756418691316688e-05,
+ "loss": 0.4937,
+ "step": 2990
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7562414119947392e-05,
+ "loss": 0.4972,
+ "step": 2991
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7560640771375668e-05,
+ "loss": 0.4794,
+ "step": 2992
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.755886686758193e-05,
+ "loss": 0.5034,
+ "step": 2993
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7557092408696446e-05,
+ "loss": 0.5085,
+ "step": 2994
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7555317394849532e-05,
+ "loss": 0.4924,
+ "step": 2995
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7553541826171535e-05,
+ "loss": 0.5068,
+ "step": 2996
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.755176570279284e-05,
+ "loss": 0.4977,
+ "step": 2997
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7549989024843883e-05,
+ "loss": 0.4948,
+ "step": 2998
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7548211792455134e-05,
+ "loss": 0.5113,
+ "step": 2999
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.754643400575711e-05,
+ "loss": 0.4921,
+ "step": 3000
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7544655664880357e-05,
+ "loss": 0.4879,
+ "step": 3001
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7542876769955475e-05,
+ "loss": 0.5032,
+ "step": 3002
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7541097321113093e-05,
+ "loss": 0.4926,
+ "step": 3003
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7539317318483893e-05,
+ "loss": 0.4976,
+ "step": 3004
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7537536762198584e-05,
+ "loss": 0.4868,
+ "step": 3005
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.753575565238793e-05,
+ "loss": 0.5015,
+ "step": 3006
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.753397398918272e-05,
+ "loss": 0.4932,
+ "step": 3007
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.75321917727138e-05,
+ "loss": 0.5025,
+ "step": 3008
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7530409003112042e-05,
+ "loss": 0.5077,
+ "step": 3009
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7528625680508372e-05,
+ "loss": 0.5092,
+ "step": 3010
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7526841805033742e-05,
+ "loss": 0.483,
+ "step": 3011
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.752505737681916e-05,
+ "loss": 0.4801,
+ "step": 3012
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7523272395995657e-05,
+ "loss": 0.5236,
+ "step": 3013
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.752148686269433e-05,
+ "loss": 0.4854,
+ "step": 3014
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7519700777046285e-05,
+ "loss": 0.4899,
+ "step": 3015
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7517914139182694e-05,
+ "loss": 0.4946,
+ "step": 3016
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.751612694923476e-05,
+ "loss": 0.4829,
+ "step": 3017
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.751433920733372e-05,
+ "loss": 0.4841,
+ "step": 3018
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7512550913610867e-05,
+ "loss": 0.5057,
+ "step": 3019
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.751076206819752e-05,
+ "loss": 0.4959,
+ "step": 3020
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.750897267122505e-05,
+ "loss": 0.5034,
+ "step": 3021
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7507182722824854e-05,
+ "loss": 0.4933,
+ "step": 3022
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7505392223128385e-05,
+ "loss": 0.5029,
+ "step": 3023
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.750360117226713e-05,
+ "loss": 0.5082,
+ "step": 3024
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7501809570372614e-05,
+ "loss": 0.4933,
+ "step": 3025
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7500017417576406e-05,
+ "loss": 0.4984,
+ "step": 3026
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7498224714010113e-05,
+ "loss": 0.5161,
+ "step": 3027
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7496431459805387e-05,
+ "loss": 0.5026,
+ "step": 3028
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.749463765509391e-05,
+ "loss": 0.5023,
+ "step": 3029
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.749284330000742e-05,
+ "loss": 0.5051,
+ "step": 3030
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7491048394677682e-05,
+ "loss": 0.503,
+ "step": 3031
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7489252939236506e-05,
+ "loss": 0.5008,
+ "step": 3032
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7487456933815746e-05,
+ "loss": 0.507,
+ "step": 3033
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7485660378547293e-05,
+ "loss": 0.5189,
+ "step": 3034
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7483863273563072e-05,
+ "loss": 0.4798,
+ "step": 3035
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7482065618995063e-05,
+ "loss": 0.4859,
+ "step": 3036
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7480267414975274e-05,
+ "loss": 0.5047,
+ "step": 3037
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7478468661635763e-05,
+ "loss": 0.4966,
+ "step": 3038
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7476669359108614e-05,
+ "loss": 0.4787,
+ "step": 3039
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7474869507525967e-05,
+ "loss": 0.4912,
+ "step": 3040
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7473069107019993e-05,
+ "loss": 0.4911,
+ "step": 3041
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7471268157722907e-05,
+ "loss": 0.4955,
+ "step": 3042
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7469466659766963e-05,
+ "loss": 0.4862,
+ "step": 3043
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7467664613284455e-05,
+ "loss": 0.5016,
+ "step": 3044
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7465862018407718e-05,
+ "loss": 0.5008,
+ "step": 3045
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.746405887526913e-05,
+ "loss": 0.5055,
+ "step": 3046
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.74622551840011e-05,
+ "loss": 0.4982,
+ "step": 3047
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7460450944736087e-05,
+ "loss": 0.5026,
+ "step": 3048
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7458646157606585e-05,
+ "loss": 0.4959,
+ "step": 3049
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.745684082274514e-05,
+ "loss": 0.4894,
+ "step": 3050
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7455034940284313e-05,
+ "loss": 0.4976,
+ "step": 3051
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.745322851035673e-05,
+ "loss": 0.4959,
+ "step": 3052
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7451421533095047e-05,
+ "loss": 0.4848,
+ "step": 3053
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.744961400863196e-05,
+ "loss": 0.5046,
+ "step": 3054
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7447805937100203e-05,
+ "loss": 0.4826,
+ "step": 3055
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7445997318632555e-05,
+ "loss": 0.4998,
+ "step": 3056
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7444188153361836e-05,
+ "loss": 0.4941,
+ "step": 3057
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.74423784414209e-05,
+ "loss": 0.4904,
+ "step": 3058
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.744056818294265e-05,
+ "loss": 0.4982,
+ "step": 3059
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.743875737806002e-05,
+ "loss": 0.4896,
+ "step": 3060
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7436946026905986e-05,
+ "loss": 0.5043,
+ "step": 3061
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.743513412961357e-05,
+ "loss": 0.4901,
+ "step": 3062
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7433321686315824e-05,
+ "loss": 0.4888,
+ "step": 3063
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7431508697145855e-05,
+ "loss": 0.498,
+ "step": 3064
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7429695162236798e-05,
+ "loss": 0.5043,
+ "step": 3065
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7427881081721828e-05,
+ "loss": 0.4807,
+ "step": 3066
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7426066455734167e-05,
+ "loss": 0.483,
+ "step": 3067
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7424251284407075e-05,
+ "loss": 0.5025,
+ "step": 3068
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7422435567873846e-05,
+ "loss": 0.5057,
+ "step": 3069
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.742061930626782e-05,
+ "loss": 0.4982,
+ "step": 3070
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7418802499722377e-05,
+ "loss": 0.5053,
+ "step": 3071
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7416985148370938e-05,
+ "loss": 0.5214,
+ "step": 3072
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.741516725234696e-05,
+ "loss": 0.4795,
+ "step": 3073
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7413348811783938e-05,
+ "loss": 0.4918,
+ "step": 3074
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7411529826815416e-05,
+ "loss": 0.4958,
+ "step": 3075
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.740971029757497e-05,
+ "loss": 0.502,
+ "step": 3076
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7407890224196217e-05,
+ "loss": 0.4911,
+ "step": 3077
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7406069606812822e-05,
+ "loss": 0.503,
+ "step": 3078
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7404248445558476e-05,
+ "loss": 0.4926,
+ "step": 3079
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7402426740566922e-05,
+ "loss": 0.4967,
+ "step": 3080
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7400604491971937e-05,
+ "loss": 0.4957,
+ "step": 3081
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7398781699907337e-05,
+ "loss": 0.4982,
+ "step": 3082
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7396958364506983e-05,
+ "loss": 0.4722,
+ "step": 3083
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7395134485904775e-05,
+ "loss": 0.4908,
+ "step": 3084
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.739331006423465e-05,
+ "loss": 0.5098,
+ "step": 3085
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7391485099630584e-05,
+ "loss": 0.4836,
+ "step": 3086
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7389659592226597e-05,
+ "loss": 0.5039,
+ "step": 3087
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7387833542156743e-05,
+ "loss": 0.4989,
+ "step": 3088
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7386006949555124e-05,
+ "loss": 0.4883,
+ "step": 3089
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7384179814555872e-05,
+ "loss": 0.4955,
+ "step": 3090
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7382352137293172e-05,
+ "loss": 0.5069,
+ "step": 3091
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7380523917901233e-05,
+ "loss": 0.4878,
+ "step": 3092
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7378695156514318e-05,
+ "loss": 0.4928,
+ "step": 3093
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7376865853266717e-05,
+ "loss": 0.5107,
+ "step": 3094
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7375036008292775e-05,
+ "loss": 0.4845,
+ "step": 3095
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7373205621726864e-05,
+ "loss": 0.5126,
+ "step": 3096
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7371374693703395e-05,
+ "loss": 0.4847,
+ "step": 3097
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.736954322435683e-05,
+ "loss": 0.5076,
+ "step": 3098
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7367711213821663e-05,
+ "loss": 0.4967,
+ "step": 3099
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.736587866223243e-05,
+ "loss": 0.508,
+ "step": 3100
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7364045569723706e-05,
+ "loss": 0.4877,
+ "step": 3101
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7362211936430103e-05,
+ "loss": 0.4913,
+ "step": 3102
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7360377762486277e-05,
+ "loss": 0.5046,
+ "step": 3103
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7358543048026925e-05,
+ "loss": 0.5047,
+ "step": 3104
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7356707793186777e-05,
+ "loss": 0.4684,
+ "step": 3105
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7354871998100605e-05,
+ "loss": 0.5183,
+ "step": 3106
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7353035662903225e-05,
+ "loss": 0.4857,
+ "step": 3107
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.735119878772949e-05,
+ "loss": 0.4787,
+ "step": 3108
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7349361372714294e-05,
+ "loss": 0.4873,
+ "step": 3109
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7347523417992564e-05,
+ "loss": 0.4822,
+ "step": 3110
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7345684923699277e-05,
+ "loss": 0.4815,
+ "step": 3111
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.734384588996944e-05,
+ "loss": 0.5008,
+ "step": 3112
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.734200631693811e-05,
+ "loss": 0.5086,
+ "step": 3113
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7340166204740373e-05,
+ "loss": 0.4907,
+ "step": 3114
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7338325553511357e-05,
+ "loss": 0.4919,
+ "step": 3115
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7336484363386237e-05,
+ "loss": 0.5166,
+ "step": 3116
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7334642634500217e-05,
+ "loss": 0.4958,
+ "step": 3117
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7332800366988552e-05,
+ "loss": 0.4995,
+ "step": 3118
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.733095756098653e-05,
+ "loss": 0.5063,
+ "step": 3119
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.732911421662947e-05,
+ "loss": 0.4965,
+ "step": 3120
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.732727033405275e-05,
+ "loss": 0.5028,
+ "step": 3121
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7325425913391772e-05,
+ "loss": 0.484,
+ "step": 3122
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7323580954781986e-05,
+ "loss": 0.516,
+ "step": 3123
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7321735458358872e-05,
+ "loss": 0.4818,
+ "step": 3124
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.731988942425796e-05,
+ "loss": 0.4944,
+ "step": 3125
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7318042852614817e-05,
+ "loss": 0.5021,
+ "step": 3126
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7316195743565045e-05,
+ "loss": 0.5114,
+ "step": 3127
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7314348097244288e-05,
+ "loss": 0.5076,
+ "step": 3128
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7312499913788225e-05,
+ "loss": 0.503,
+ "step": 3129
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7310651193332586e-05,
+ "loss": 0.4836,
+ "step": 3130
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.730880193601313e-05,
+ "loss": 0.4987,
+ "step": 3131
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7306952141965664e-05,
+ "loss": 0.4865,
+ "step": 3132
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7305101811326017e-05,
+ "loss": 0.4911,
+ "step": 3133
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7303250944230084e-05,
+ "loss": 0.5219,
+ "step": 3134
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7301399540813773e-05,
+ "loss": 0.4941,
+ "step": 3135
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.729954760121305e-05,
+ "loss": 0.4856,
+ "step": 3136
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7297695125563915e-05,
+ "loss": 0.496,
+ "step": 3137
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.72958421140024e-05,
+ "loss": 0.4944,
+ "step": 3138
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7293988566664586e-05,
+ "loss": 0.4983,
+ "step": 3139
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7292134483686594e-05,
+ "loss": 0.4886,
+ "step": 3140
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7290279865204567e-05,
+ "loss": 0.498,
+ "step": 3141
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.728842471135472e-05,
+ "loss": 0.4731,
+ "step": 3142
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.728656902227327e-05,
+ "loss": 0.5268,
+ "step": 3143
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.72847127980965e-05,
+ "loss": 0.5159,
+ "step": 3144
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7282856038960724e-05,
+ "loss": 0.5017,
+ "step": 3145
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7280998745002286e-05,
+ "loss": 0.4799,
+ "step": 3146
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7279140916357588e-05,
+ "loss": 0.4828,
+ "step": 3147
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.727728255316306e-05,
+ "loss": 0.5081,
+ "step": 3148
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7275423655555163e-05,
+ "loss": 0.4772,
+ "step": 3149
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7273564223670422e-05,
+ "loss": 0.5074,
+ "step": 3150
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.727170425764537e-05,
+ "loss": 0.4899,
+ "step": 3151
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7269843757616605e-05,
+ "loss": 0.4881,
+ "step": 3152
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7267982723720755e-05,
+ "loss": 0.4807,
+ "step": 3153
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.726612115609448e-05,
+ "loss": 0.5115,
+ "step": 3154
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7264259054874492e-05,
+ "loss": 0.5049,
+ "step": 3155
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.726239642019753e-05,
+ "loss": 0.496,
+ "step": 3156
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7260533252200383e-05,
+ "loss": 0.4848,
+ "step": 3157
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7258669551019872e-05,
+ "loss": 0.5023,
+ "step": 3158
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.725680531679286e-05,
+ "loss": 0.5088,
+ "step": 3159
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.725494054965625e-05,
+ "loss": 0.5108,
+ "step": 3160
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7253075249746984e-05,
+ "loss": 0.4842,
+ "step": 3161
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7251209417202036e-05,
+ "loss": 0.4926,
+ "step": 3162
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724934305215843e-05,
+ "loss": 0.5006,
+ "step": 3163
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7247476154753222e-05,
+ "loss": 0.4902,
+ "step": 3164
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724560872512351e-05,
+ "loss": 0.5061,
+ "step": 3165
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724374076340643e-05,
+ "loss": 0.4807,
+ "step": 3166
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724187226973916e-05,
+ "loss": 0.4988,
+ "step": 3167
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7240003244258904e-05,
+ "loss": 0.4889,
+ "step": 3168
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.723813368710293e-05,
+ "loss": 0.488,
+ "step": 3169
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.723626359840852e-05,
+ "loss": 0.5014,
+ "step": 3170
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7234392978313012e-05,
+ "loss": 0.4979,
+ "step": 3171
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7232521826953773e-05,
+ "loss": 0.4916,
+ "step": 3172
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7230650144468212e-05,
+ "loss": 0.5112,
+ "step": 3173
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7228777930993784e-05,
+ "loss": 0.477,
+ "step": 3174
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7226905186667965e-05,
+ "loss": 0.5136,
+ "step": 3175
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.722503191162829e-05,
+ "loss": 0.5031,
+ "step": 3176
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7223158106012326e-05,
+ "loss": 0.4908,
+ "step": 3177
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.722128376995767e-05,
+ "loss": 0.4848,
+ "step": 3178
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.721940890360197e-05,
+ "loss": 0.4897,
+ "step": 3179
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7217533507082907e-05,
+ "loss": 0.489,
+ "step": 3180
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.721565758053821e-05,
+ "loss": 0.5087,
+ "step": 3181
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7213781124105623e-05,
+ "loss": 0.5086,
+ "step": 3182
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7211904137922962e-05,
+ "loss": 0.4942,
+ "step": 3183
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.721002662212805e-05,
+ "loss": 0.4779,
+ "step": 3184
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.720814857685878e-05,
+ "loss": 0.4938,
+ "step": 3185
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7206270002253056e-05,
+ "loss": 0.4867,
+ "step": 3186
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7204390898448837e-05,
+ "loss": 0.4784,
+ "step": 3187
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.720251126558411e-05,
+ "loss": 0.4861,
+ "step": 3188
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.720063110379692e-05,
+ "loss": 0.5038,
+ "step": 3189
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7198750413225327e-05,
+ "loss": 0.5021,
+ "step": 3190
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7196869194007448e-05,
+ "loss": 0.4814,
+ "step": 3191
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.719498744628143e-05,
+ "loss": 0.4862,
+ "step": 3192
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.719310517018546e-05,
+ "loss": 0.5017,
+ "step": 3193
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7191222365857764e-05,
+ "loss": 0.4901,
+ "step": 3194
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7189339033436607e-05,
+ "loss": 0.4953,
+ "step": 3195
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7187455173060294e-05,
+ "loss": 0.5086,
+ "step": 3196
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7185570784867168e-05,
+ "loss": 0.4942,
+ "step": 3197
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7183685868995616e-05,
+ "loss": 0.5027,
+ "step": 3198
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.718180042558405e-05,
+ "loss": 0.4924,
+ "step": 3199
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.717991445477093e-05,
+ "loss": 0.517,
+ "step": 3200
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7178027956694753e-05,
+ "loss": 0.4834,
+ "step": 3201
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7176140931494064e-05,
+ "loss": 0.4947,
+ "step": 3202
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.717425337930743e-05,
+ "loss": 0.5267,
+ "step": 3203
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7172365300273467e-05,
+ "loss": 0.5019,
+ "step": 3204
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7170476694530834e-05,
+ "loss": 0.4692,
+ "step": 3205
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.716858756221821e-05,
+ "loss": 0.4858,
+ "step": 3206
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7166697903474335e-05,
+ "loss": 0.5162,
+ "step": 3207
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.716480771843798e-05,
+ "loss": 0.493,
+ "step": 3208
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7162917007247937e-05,
+ "loss": 0.4835,
+ "step": 3209
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7161025770043065e-05,
+ "loss": 0.5061,
+ "step": 3210
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7159134006962248e-05,
+ "loss": 0.4877,
+ "step": 3211
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7157241718144404e-05,
+ "loss": 0.4893,
+ "step": 3212
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7155348903728497e-05,
+ "loss": 0.4832,
+ "step": 3213
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.715345556385353e-05,
+ "loss": 0.4912,
+ "step": 3214
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.715156169865854e-05,
+ "loss": 0.4865,
+ "step": 3215
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7149667308282604e-05,
+ "loss": 0.4766,
+ "step": 3216
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.714777239286484e-05,
+ "loss": 0.5137,
+ "step": 3217
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7145876952544395e-05,
+ "loss": 0.4717,
+ "step": 3218
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7143980987460475e-05,
+ "loss": 0.5099,
+ "step": 3219
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7142084497752304e-05,
+ "loss": 0.5271,
+ "step": 3220
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.714018748355915e-05,
+ "loss": 0.4995,
+ "step": 3221
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.713828994502033e-05,
+ "loss": 0.522,
+ "step": 3222
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7136391882275186e-05,
+ "loss": 0.4746,
+ "step": 3223
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7134493295463104e-05,
+ "loss": 0.4952,
+ "step": 3224
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.713259418472351e-05,
+ "loss": 0.4802,
+ "step": 3225
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.713069455019586e-05,
+ "loss": 0.4934,
+ "step": 3226
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.712879439201967e-05,
+ "loss": 0.5037,
+ "step": 3227
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7126893710334465e-05,
+ "loss": 0.497,
+ "step": 3228
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7124992505279833e-05,
+ "loss": 0.4945,
+ "step": 3229
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.712309077699538e-05,
+ "loss": 0.4899,
+ "step": 3230
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.712118852562077e-05,
+ "loss": 0.5034,
+ "step": 3231
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.71192857512957e-05,
+ "loss": 0.4879,
+ "step": 3232
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7117382454159887e-05,
+ "loss": 0.4883,
+ "step": 3233
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7115478634353117e-05,
+ "loss": 0.4988,
+ "step": 3234
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7113574292015185e-05,
+ "loss": 0.4861,
+ "step": 3235
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.711166942728595e-05,
+ "loss": 0.5031,
+ "step": 3236
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.710976404030529e-05,
+ "loss": 0.4695,
+ "step": 3237
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.710785813121313e-05,
+ "loss": 0.4973,
+ "step": 3238
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7105951700149433e-05,
+ "loss": 0.5143,
+ "step": 3239
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7104044747254202e-05,
+ "loss": 0.4813,
+ "step": 3240
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7102137272667466e-05,
+ "loss": 0.513,
+ "step": 3241
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7100229276529314e-05,
+ "loss": 0.4643,
+ "step": 3242
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7098320758979854e-05,
+ "loss": 0.492,
+ "step": 3243
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7096411720159244e-05,
+ "loss": 0.4903,
+ "step": 3244
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7094502160207672e-05,
+ "loss": 0.5142,
+ "step": 3245
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7092592079265368e-05,
+ "loss": 0.4952,
+ "step": 3246
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7090681477472605e-05,
+ "loss": 0.491,
+ "step": 3247
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7088770354969685e-05,
+ "loss": 0.5151,
+ "step": 3248
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.708685871189695e-05,
+ "loss": 0.503,
+ "step": 3249
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7084946548394797e-05,
+ "loss": 0.5048,
+ "step": 3250
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7083033864603632e-05,
+ "loss": 0.4966,
+ "step": 3251
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7081120660663923e-05,
+ "loss": 0.5089,
+ "step": 3252
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7079206936716163e-05,
+ "loss": 0.4987,
+ "step": 3253
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.707729269290089e-05,
+ "loss": 0.4891,
+ "step": 3254
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.707537792935868e-05,
+ "loss": 0.4912,
+ "step": 3255
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7073462646230144e-05,
+ "loss": 0.4958,
+ "step": 3256
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7071546843655932e-05,
+ "loss": 0.4796,
+ "step": 3257
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.706963052177673e-05,
+ "loss": 0.494,
+ "step": 3258
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.706771368073327e-05,
+ "loss": 0.5072,
+ "step": 3259
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7065796320666312e-05,
+ "loss": 0.5034,
+ "step": 3260
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7063878441716665e-05,
+ "loss": 0.5014,
+ "step": 3261
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7061960044025162e-05,
+ "loss": 0.509,
+ "step": 3262
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.706004112773269e-05,
+ "loss": 0.504,
+ "step": 3263
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7058121692980157e-05,
+ "loss": 0.494,
+ "step": 3264
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7056201739908528e-05,
+ "loss": 0.494,
+ "step": 3265
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.705428126865879e-05,
+ "loss": 0.4973,
+ "step": 3266
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7052360279371978e-05,
+ "loss": 0.4877,
+ "step": 3267
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.705043877218916e-05,
+ "loss": 0.4844,
+ "step": 3268
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7048516747251444e-05,
+ "loss": 0.5011,
+ "step": 3269
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.704659420469997e-05,
+ "loss": 0.4979,
+ "step": 3270
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7044671144675935e-05,
+ "loss": 0.4596,
+ "step": 3271
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7042747567320548e-05,
+ "loss": 0.5083,
+ "step": 3272
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.704082347277507e-05,
+ "loss": 0.4956,
+ "step": 3273
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7038898861180805e-05,
+ "loss": 0.481,
+ "step": 3274
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7036973732679084e-05,
+ "loss": 0.507,
+ "step": 3275
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7035048087411283e-05,
+ "loss": 0.4831,
+ "step": 3276
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.703312192551881e-05,
+ "loss": 0.4758,
+ "step": 3277
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.703119524714311e-05,
+ "loss": 0.503,
+ "step": 3278
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.702926805242568e-05,
+ "loss": 0.508,
+ "step": 3279
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7027340341508043e-05,
+ "loss": 0.5148,
+ "step": 3280
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.702541211453176e-05,
+ "loss": 0.469,
+ "step": 3281
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.702348337163843e-05,
+ "loss": 0.4877,
+ "step": 3282
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7021554112969696e-05,
+ "loss": 0.5001,
+ "step": 3283
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.701962433866723e-05,
+ "loss": 0.4817,
+ "step": 3284
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7017694048872756e-05,
+ "loss": 0.5152,
+ "step": 3285
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7015763243728014e-05,
+ "loss": 0.5012,
+ "step": 3286
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.70138319233748e-05,
+ "loss": 0.4863,
+ "step": 3287
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7011900087954945e-05,
+ "loss": 0.4832,
+ "step": 3288
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7009967737610312e-05,
+ "loss": 0.5042,
+ "step": 3289
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.70080348724828e-05,
+ "loss": 0.5057,
+ "step": 3290
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7006101492714362e-05,
+ "loss": 0.5154,
+ "step": 3291
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7004167598446967e-05,
+ "loss": 0.4931,
+ "step": 3292
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.700223318982264e-05,
+ "loss": 0.5065,
+ "step": 3293
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7000298266983428e-05,
+ "loss": 0.4968,
+ "step": 3294
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.699836283007143e-05,
+ "loss": 0.4878,
+ "step": 3295
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6996426879228775e-05,
+ "loss": 0.4811,
+ "step": 3296
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6994490414597627e-05,
+ "loss": 0.5043,
+ "step": 3297
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6992553436320195e-05,
+ "loss": 0.4804,
+ "step": 3298
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6990615944538725e-05,
+ "loss": 0.481,
+ "step": 3299
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6988677939395496e-05,
+ "loss": 0.4824,
+ "step": 3300
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.698673942103283e-05,
+ "loss": 0.4943,
+ "step": 3301
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6984800389593076e-05,
+ "loss": 0.4982,
+ "step": 3302
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6982860845218637e-05,
+ "loss": 0.4838,
+ "step": 3303
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.698092078805194e-05,
+ "loss": 0.5223,
+ "step": 3304
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6978980218235454e-05,
+ "loss": 0.4791,
+ "step": 3305
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.697703913591169e-05,
+ "loss": 0.4881,
+ "step": 3306
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6975097541223195e-05,
+ "loss": 0.4824,
+ "step": 3307
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6973155434312544e-05,
+ "loss": 0.4667,
+ "step": 3308
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6971212815322365e-05,
+ "loss": 0.509,
+ "step": 3309
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.696926968439531e-05,
+ "loss": 0.5058,
+ "step": 3310
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6967326041674076e-05,
+ "loss": 0.5017,
+ "step": 3311
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.69653818873014e-05,
+ "loss": 0.4986,
+ "step": 3312
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6963437221420046e-05,
+ "loss": 0.5003,
+ "step": 3313
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6961492044172824e-05,
+ "loss": 0.4991,
+ "step": 3314
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6959546355702584e-05,
+ "loss": 0.495,
+ "step": 3315
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6957600156152206e-05,
+ "loss": 0.4848,
+ "step": 3316
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6955653445664612e-05,
+ "loss": 0.4958,
+ "step": 3317
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.695370622438276e-05,
+ "loss": 0.4899,
+ "step": 3318
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6951758492449646e-05,
+ "loss": 0.4963,
+ "step": 3319
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6949810250008302e-05,
+ "loss": 0.4902,
+ "step": 3320
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.69478614972018e-05,
+ "loss": 0.4889,
+ "step": 3321
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.694591223417325e-05,
+ "loss": 0.4899,
+ "step": 3322
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.694396246106579e-05,
+ "loss": 0.4928,
+ "step": 3323
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6942012178022613e-05,
+ "loss": 0.5079,
+ "step": 3324
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6940061385186936e-05,
+ "loss": 0.48,
+ "step": 3325
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6938110082702014e-05,
+ "loss": 0.4855,
+ "step": 3326
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6936158270711148e-05,
+ "loss": 0.4925,
+ "step": 3327
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6934205949357666e-05,
+ "loss": 0.4942,
+ "step": 3328
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.693225311878494e-05,
+ "loss": 0.507,
+ "step": 3329
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6930299779136382e-05,
+ "loss": 0.4764,
+ "step": 3330
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6928345930555432e-05,
+ "loss": 0.49,
+ "step": 3331
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6926391573185576e-05,
+ "loss": 0.4877,
+ "step": 3332
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.692443670717033e-05,
+ "loss": 0.491,
+ "step": 3333
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6922481332653248e-05,
+ "loss": 0.4942,
+ "step": 3334
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6920525449777937e-05,
+ "loss": 0.4978,
+ "step": 3335
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.691856905868802e-05,
+ "loss": 0.4789,
+ "step": 3336
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6916612159527166e-05,
+ "loss": 0.4907,
+ "step": 3337
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6914654752439083e-05,
+ "loss": 0.5074,
+ "step": 3338
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.691269683756752e-05,
+ "loss": 0.4883,
+ "step": 3339
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6910738415056245e-05,
+ "loss": 0.4935,
+ "step": 3340
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6908779485049093e-05,
+ "loss": 0.5326,
+ "step": 3341
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6906820047689907e-05,
+ "loss": 0.5007,
+ "step": 3342
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6904860103122587e-05,
+ "loss": 0.473,
+ "step": 3343
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6902899651491056e-05,
+ "loss": 0.4961,
+ "step": 3344
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.690093869293929e-05,
+ "loss": 0.4919,
+ "step": 3345
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6898977227611288e-05,
+ "loss": 0.5026,
+ "step": 3346
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6897015255651093e-05,
+ "loss": 0.5022,
+ "step": 3347
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6895052777202784e-05,
+ "loss": 0.4966,
+ "step": 3348
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.689308979241048e-05,
+ "loss": 0.511,
+ "step": 3349
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6891126301418334e-05,
+ "loss": 0.4936,
+ "step": 3350
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.688916230437053e-05,
+ "loss": 0.4949,
+ "step": 3351
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.68871978014113e-05,
+ "loss": 0.504,
+ "step": 3352
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6885232792684914e-05,
+ "loss": 0.4937,
+ "step": 3353
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6883267278335668e-05,
+ "loss": 0.5026,
+ "step": 3354
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.68813012585079e-05,
+ "loss": 0.4734,
+ "step": 3355
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.687933473334599e-05,
+ "loss": 0.4808,
+ "step": 3356
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6877367702994353e-05,
+ "loss": 0.4932,
+ "step": 3357
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6875400167597433e-05,
+ "loss": 0.5041,
+ "step": 3358
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6873432127299725e-05,
+ "loss": 0.4932,
+ "step": 3359
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6871463582245753e-05,
+ "loss": 0.4834,
+ "step": 3360
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6869494532580072e-05,
+ "loss": 0.499,
+ "step": 3361
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6867524978447286e-05,
+ "loss": 0.4741,
+ "step": 3362
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6865554919992026e-05,
+ "loss": 0.5121,
+ "step": 3363
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6863584357358974e-05,
+ "loss": 0.5057,
+ "step": 3364
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.686161329069283e-05,
+ "loss": 0.4854,
+ "step": 3365
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685964172013835e-05,
+ "loss": 0.4994,
+ "step": 3366
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685766964584031e-05,
+ "loss": 0.4862,
+ "step": 3367
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685569706794354e-05,
+ "loss": 0.4974,
+ "step": 3368
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6853723986592885e-05,
+ "loss": 0.5175,
+ "step": 3369
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685175040193325e-05,
+ "loss": 0.5038,
+ "step": 3370
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6849776314109568e-05,
+ "loss": 0.5083,
+ "step": 3371
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6847801723266798e-05,
+ "loss": 0.5001,
+ "step": 3372
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6845826629549952e-05,
+ "loss": 0.5107,
+ "step": 3373
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6843851033104076e-05,
+ "loss": 0.5127,
+ "step": 3374
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6841874934074244e-05,
+ "loss": 0.491,
+ "step": 3375
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6839898332605575e-05,
+ "loss": 0.495,
+ "step": 3376
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.683792122884322e-05,
+ "loss": 0.4971,
+ "step": 3377
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6835943622932377e-05,
+ "loss": 0.5114,
+ "step": 3378
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6833965515018257e-05,
+ "loss": 0.4907,
+ "step": 3379
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.683198690524614e-05,
+ "loss": 0.519,
+ "step": 3380
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6830007793761323e-05,
+ "loss": 0.4936,
+ "step": 3381
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.682802818070914e-05,
+ "loss": 0.4878,
+ "step": 3382
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6826048066234967e-05,
+ "loss": 0.4965,
+ "step": 3383
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6824067450484214e-05,
+ "loss": 0.5071,
+ "step": 3384
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.682208633360233e-05,
+ "loss": 0.4647,
+ "step": 3385
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6820104715734803e-05,
+ "loss": 0.484,
+ "step": 3386
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6818122597027152e-05,
+ "loss": 0.4863,
+ "step": 3387
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.681613997762494e-05,
+ "loss": 0.4965,
+ "step": 3388
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6814156857673753e-05,
+ "loss": 0.4948,
+ "step": 3389
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6812173237319232e-05,
+ "loss": 0.4834,
+ "step": 3390
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6810189116707042e-05,
+ "loss": 0.5055,
+ "step": 3391
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6808204495982887e-05,
+ "loss": 0.5029,
+ "step": 3392
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6806219375292513e-05,
+ "loss": 0.495,
+ "step": 3393
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.68042337547817e-05,
+ "loss": 0.4815,
+ "step": 3394
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6802247634596256e-05,
+ "loss": 0.4937,
+ "step": 3395
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.680026101488204e-05,
+ "loss": 0.5125,
+ "step": 3396
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.679827389578494e-05,
+ "loss": 0.4883,
+ "step": 3397
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6796286277450882e-05,
+ "loss": 0.503,
+ "step": 3398
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6794298160025822e-05,
+ "loss": 0.4779,
+ "step": 3399
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6792309543655774e-05,
+ "loss": 0.4657,
+ "step": 3400
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6790320428486757e-05,
+ "loss": 0.5017,
+ "step": 3401
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6788330814664856e-05,
+ "loss": 0.4918,
+ "step": 3402
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.678634070233617e-05,
+ "loss": 0.4799,
+ "step": 3403
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6784350091646852e-05,
+ "loss": 0.4953,
+ "step": 3404
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6782358982743084e-05,
+ "loss": 0.5107,
+ "step": 3405
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6780367375771075e-05,
+ "loss": 0.4833,
+ "step": 3406
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6778375270877095e-05,
+ "loss": 0.493,
+ "step": 3407
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6776382668207424e-05,
+ "loss": 0.4983,
+ "step": 3408
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6774389567908394e-05,
+ "loss": 0.482,
+ "step": 3409
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.677239597012638e-05,
+ "loss": 0.502,
+ "step": 3410
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6770401875007766e-05,
+ "loss": 0.5169,
+ "step": 3411
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6768407282699e-05,
+ "loss": 0.4878,
+ "step": 3412
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6766412193346555e-05,
+ "loss": 0.5064,
+ "step": 3413
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6764416607096942e-05,
+ "loss": 0.5101,
+ "step": 3414
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6762420524096712e-05,
+ "loss": 0.5111,
+ "step": 3415
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6760423944492442e-05,
+ "loss": 0.4933,
+ "step": 3416
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6758426868430758e-05,
+ "loss": 0.4991,
+ "step": 3417
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6756429296058314e-05,
+ "loss": 0.5079,
+ "step": 3418
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6754431227521806e-05,
+ "loss": 0.4799,
+ "step": 3419
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6752432662967958e-05,
+ "loss": 0.4992,
+ "step": 3420
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6750433602543546e-05,
+ "loss": 0.5113,
+ "step": 3421
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.674843404639537e-05,
+ "loss": 0.4779,
+ "step": 3422
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6746433994670258e-05,
+ "loss": 0.509,
+ "step": 3423
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6744433447515098e-05,
+ "loss": 0.4972,
+ "step": 3424
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.67424324050768e-05,
+ "loss": 0.4903,
+ "step": 3425
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6740430867502307e-05,
+ "loss": 0.4894,
+ "step": 3426
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6738428834938606e-05,
+ "loss": 0.4954,
+ "step": 3427
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6736426307532722e-05,
+ "loss": 0.4985,
+ "step": 3428
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6734423285431705e-05,
+ "loss": 0.4952,
+ "step": 3429
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6732419768782656e-05,
+ "loss": 0.5189,
+ "step": 3430
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6730415757732702e-05,
+ "loss": 0.4859,
+ "step": 3431
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6728411252429006e-05,
+ "loss": 0.5037,
+ "step": 3432
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.672640625301877e-05,
+ "loss": 0.4977,
+ "step": 3433
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6724400759649243e-05,
+ "loss": 0.4831,
+ "step": 3434
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.672239477246769e-05,
+ "loss": 0.4928,
+ "step": 3435
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6720388291621423e-05,
+ "loss": 0.4899,
+ "step": 3436
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6718381317257793e-05,
+ "loss": 0.4841,
+ "step": 3437
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6716373849524187e-05,
+ "loss": 0.5012,
+ "step": 3438
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.671436588856802e-05,
+ "loss": 0.5064,
+ "step": 3439
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6712357434536747e-05,
+ "loss": 0.4881,
+ "step": 3440
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6710348487577863e-05,
+ "loss": 0.4914,
+ "step": 3441
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6708339047838897e-05,
+ "loss": 0.4985,
+ "step": 3442
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6706329115467412e-05,
+ "loss": 0.4928,
+ "step": 3443
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.670431869061101e-05,
+ "loss": 0.4741,
+ "step": 3444
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6702307773417334e-05,
+ "loss": 0.4799,
+ "step": 3445
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6700296364034048e-05,
+ "loss": 0.5049,
+ "step": 3446
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6698284462608866e-05,
+ "loss": 0.5034,
+ "step": 3447
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6696272069289533e-05,
+ "loss": 0.4924,
+ "step": 3448
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6694259184223833e-05,
+ "loss": 0.5037,
+ "step": 3449
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6692245807559578e-05,
+ "loss": 0.4939,
+ "step": 3450
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.669023193944463e-05,
+ "loss": 0.4952,
+ "step": 3451
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668821758002688e-05,
+ "loss": 0.4887,
+ "step": 3452
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668620272945424e-05,
+ "loss": 0.5063,
+ "step": 3453
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6684187387874686e-05,
+ "loss": 0.4739,
+ "step": 3454
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668217155543621e-05,
+ "loss": 0.5013,
+ "step": 3455
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668015523228685e-05,
+ "loss": 0.4862,
+ "step": 3456
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6678138418574673e-05,
+ "loss": 0.4973,
+ "step": 3457
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6676121114447784e-05,
+ "loss": 0.4797,
+ "step": 3458
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6674103320054335e-05,
+ "loss": 0.5063,
+ "step": 3459
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6672085035542497e-05,
+ "loss": 0.4745,
+ "step": 3460
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.667006626106048e-05,
+ "loss": 0.4841,
+ "step": 3461
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6668046996756544e-05,
+ "loss": 0.4975,
+ "step": 3462
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6666027242778972e-05,
+ "loss": 0.5235,
+ "step": 3463
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.666400699927608e-05,
+ "loss": 0.4883,
+ "step": 3464
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6661986266396235e-05,
+ "loss": 0.5063,
+ "step": 3465
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6659965044287826e-05,
+ "loss": 0.4858,
+ "step": 3466
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6657943333099287e-05,
+ "loss": 0.4754,
+ "step": 3467
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6655921132979082e-05,
+ "loss": 0.4743,
+ "step": 3468
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6653898444075713e-05,
+ "loss": 0.4887,
+ "step": 3469
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6651875266537718e-05,
+ "loss": 0.4948,
+ "step": 3470
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.664985160051367e-05,
+ "loss": 0.4873,
+ "step": 3471
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6647827446152183e-05,
+ "loss": 0.486,
+ "step": 3472
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6645802803601893e-05,
+ "loss": 0.4984,
+ "step": 3473
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.664377767301149e-05,
+ "loss": 0.5056,
+ "step": 3474
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.664175205452969e-05,
+ "loss": 0.4926,
+ "step": 3475
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.663972594830524e-05,
+ "loss": 0.5159,
+ "step": 3476
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6637699354486936e-05,
+ "loss": 0.5252,
+ "step": 3477
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6635672273223597e-05,
+ "loss": 0.4872,
+ "step": 3478
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.663364470466409e-05,
+ "loss": 0.4877,
+ "step": 3479
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6631616648957303e-05,
+ "loss": 0.4879,
+ "step": 3480
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6629588106252173e-05,
+ "loss": 0.4756,
+ "step": 3481
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6627559076697672e-05,
+ "loss": 0.5409,
+ "step": 3482
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6625529560442793e-05,
+ "loss": 0.5017,
+ "step": 3483
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6623499557636584e-05,
+ "loss": 0.4925,
+ "step": 3484
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6621469068428114e-05,
+ "loss": 0.4936,
+ "step": 3485
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.66194380929665e-05,
+ "loss": 0.5126,
+ "step": 3486
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6617406631400884e-05,
+ "loss": 0.4967,
+ "step": 3487
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6615374683880445e-05,
+ "loss": 0.4864,
+ "step": 3488
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6613342250554406e-05,
+ "loss": 0.4922,
+ "step": 3489
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6611309331572022e-05,
+ "loss": 0.4962,
+ "step": 3490
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6609275927082577e-05,
+ "loss": 0.4899,
+ "step": 3491
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.66072420372354e-05,
+ "loss": 0.4947,
+ "step": 3492
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.660520766217985e-05,
+ "loss": 0.5001,
+ "step": 3493
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6603172802065317e-05,
+ "loss": 0.5018,
+ "step": 3494
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6601137457041242e-05,
+ "loss": 0.5025,
+ "step": 3495
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6599101627257087e-05,
+ "loss": 0.4887,
+ "step": 3496
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6597065312862358e-05,
+ "loss": 0.4875,
+ "step": 3497
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.659502851400659e-05,
+ "loss": 0.5023,
+ "step": 3498
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6592991230839355e-05,
+ "loss": 0.4966,
+ "step": 3499
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.659095346351027e-05,
+ "loss": 0.5032,
+ "step": 3500
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6588915212168977e-05,
+ "loss": 0.4823,
+ "step": 3501
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.658687647696516e-05,
+ "loss": 0.5014,
+ "step": 3502
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.658483725804853e-05,
+ "loss": 0.4557,
+ "step": 3503
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6582797555568834e-05,
+ "loss": 0.5108,
+ "step": 3504
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.658075736967587e-05,
+ "loss": 0.5026,
+ "step": 3505
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6578716700519454e-05,
+ "loss": 0.5017,
+ "step": 3506
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.657667554824945e-05,
+ "loss": 0.4901,
+ "step": 3507
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6574633913015742e-05,
+ "loss": 0.4907,
+ "step": 3508
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.657259179496827e-05,
+ "loss": 0.4864,
+ "step": 3509
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6570549194256995e-05,
+ "loss": 0.495,
+ "step": 3510
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6568506111031913e-05,
+ "loss": 0.5021,
+ "step": 3511
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6566462545443066e-05,
+ "loss": 0.5074,
+ "step": 3512
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.656441849764052e-05,
+ "loss": 0.4989,
+ "step": 3513
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6562373967774382e-05,
+ "loss": 0.509,
+ "step": 3514
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6560328955994796e-05,
+ "loss": 0.5201,
+ "step": 3515
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.655828346245194e-05,
+ "loss": 0.5027,
+ "step": 3516
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.655623748729602e-05,
+ "loss": 0.4831,
+ "step": 3517
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.655419103067729e-05,
+ "loss": 0.5112,
+ "step": 3518
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6552144092746032e-05,
+ "loss": 0.4874,
+ "step": 3519
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6550096673652565e-05,
+ "loss": 0.4991,
+ "step": 3520
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.654804877354724e-05,
+ "loss": 0.4899,
+ "step": 3521
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.654600039258045e-05,
+ "loss": 0.5151,
+ "step": 3522
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6543951530902618e-05,
+ "loss": 0.5163,
+ "step": 3523
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6541902188664206e-05,
+ "loss": 0.4763,
+ "step": 3524
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6539852366015702e-05,
+ "loss": 0.5012,
+ "step": 3525
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6537802063107646e-05,
+ "loss": 0.4732,
+ "step": 3526
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6535751280090598e-05,
+ "loss": 0.51,
+ "step": 3527
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6533700017115162e-05,
+ "loss": 0.5077,
+ "step": 3528
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.653164827433197e-05,
+ "loss": 0.5029,
+ "step": 3529
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6529596051891696e-05,
+ "loss": 0.4791,
+ "step": 3530
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6527543349945047e-05,
+ "loss": 0.5035,
+ "step": 3531
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6525490168642765e-05,
+ "loss": 0.4892,
+ "step": 3532
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6523436508135624e-05,
+ "loss": 0.4915,
+ "step": 3533
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6521382368574442e-05,
+ "loss": 0.4816,
+ "step": 3534
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.651932775011006e-05,
+ "loss": 0.481,
+ "step": 3535
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6517272652893367e-05,
+ "loss": 0.4885,
+ "step": 3536
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6515217077075276e-05,
+ "loss": 0.506,
+ "step": 3537
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.651316102280674e-05,
+ "loss": 0.4849,
+ "step": 3538
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6511104490238753e-05,
+ "loss": 0.5038,
+ "step": 3539
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6509047479522332e-05,
+ "loss": 0.5172,
+ "step": 3540
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.650698999080854e-05,
+ "loss": 0.4906,
+ "step": 3541
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6504932024248462e-05,
+ "loss": 0.4895,
+ "step": 3542
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6502873579993238e-05,
+ "loss": 0.4769,
+ "step": 3543
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6500814658194024e-05,
+ "loss": 0.5035,
+ "step": 3544
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.649875525900202e-05,
+ "loss": 0.5003,
+ "step": 3545
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.649669538256846e-05,
+ "loss": 0.4854,
+ "step": 3546
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6494635029044613e-05,
+ "loss": 0.4941,
+ "step": 3547
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.649257419858178e-05,
+ "loss": 0.4851,
+ "step": 3548
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6490512891331304e-05,
+ "loss": 0.4964,
+ "step": 3549
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6488451107444556e-05,
+ "loss": 0.5009,
+ "step": 3550
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.648638884707295e-05,
+ "loss": 0.496,
+ "step": 3551
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6484326110367924e-05,
+ "loss": 0.5007,
+ "step": 3552
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.648226289748096e-05,
+ "loss": 0.5075,
+ "step": 3553
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.648019920856357e-05,
+ "loss": 0.4816,
+ "step": 3554
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6478135043767303e-05,
+ "loss": 0.5059,
+ "step": 3555
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.647607040324374e-05,
+ "loss": 0.4913,
+ "step": 3556
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6474005287144507e-05,
+ "loss": 0.4945,
+ "step": 3557
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.647193969562125e-05,
+ "loss": 0.4799,
+ "step": 3558
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6469873628825665e-05,
+ "loss": 0.5039,
+ "step": 3559
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6467807086909468e-05,
+ "loss": 0.4956,
+ "step": 3560
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.646574007002442e-05,
+ "loss": 0.5098,
+ "step": 3561
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6463672578322315e-05,
+ "loss": 0.4929,
+ "step": 3562
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.646160461195498e-05,
+ "loss": 0.4958,
+ "step": 3563
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6459536171074278e-05,
+ "loss": 0.4969,
+ "step": 3564
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6457467255832108e-05,
+ "loss": 0.5093,
+ "step": 3565
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.64553978663804e-05,
+ "loss": 0.4717,
+ "step": 3566
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.645332800287112e-05,
+ "loss": 0.498,
+ "step": 3567
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.645125766545628e-05,
+ "loss": 0.5006,
+ "step": 3568
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6449186854287903e-05,
+ "loss": 0.5093,
+ "step": 3569
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.644711556951807e-05,
+ "loss": 0.5111,
+ "step": 3570
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6445043811298887e-05,
+ "loss": 0.5057,
+ "step": 3571
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.644297157978249e-05,
+ "loss": 0.4916,
+ "step": 3572
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.644089887512106e-05,
+ "loss": 0.4835,
+ "step": 3573
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6438825697466808e-05,
+ "loss": 0.4892,
+ "step": 3574
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6436752046971975e-05,
+ "loss": 0.4817,
+ "step": 3575
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6434677923788848e-05,
+ "loss": 0.483,
+ "step": 3576
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6432603328069732e-05,
+ "loss": 0.5143,
+ "step": 3577
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.643052825996699e-05,
+ "loss": 0.507,
+ "step": 3578
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6428452719632994e-05,
+ "loss": 0.4962,
+ "step": 3579
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.642637670722017e-05,
+ "loss": 0.5072,
+ "step": 3580
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.642430022288097e-05,
+ "loss": 0.4931,
+ "step": 3581
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6422223266767883e-05,
+ "loss": 0.4838,
+ "step": 3582
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.642014583903343e-05,
+ "loss": 0.5034,
+ "step": 3583
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.641806793983017e-05,
+ "loss": 0.5004,
+ "step": 3584
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6415989569310698e-05,
+ "loss": 0.4913,
+ "step": 3585
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6413910727627637e-05,
+ "loss": 0.4919,
+ "step": 3586
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6411831414933647e-05,
+ "loss": 0.5063,
+ "step": 3587
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6409751631381428e-05,
+ "loss": 0.481,
+ "step": 3588
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.640767137712371e-05,
+ "loss": 0.5164,
+ "step": 3589
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6405590652313256e-05,
+ "loss": 0.4764,
+ "step": 3590
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.640350945710287e-05,
+ "loss": 0.4895,
+ "step": 3591
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.640142779164538e-05,
+ "loss": 0.5138,
+ "step": 3592
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6399345656093663e-05,
+ "loss": 0.476,
+ "step": 3593
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6397263050600615e-05,
+ "loss": 0.4773,
+ "step": 3594
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6395179975319178e-05,
+ "loss": 0.5097,
+ "step": 3595
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6393096430402323e-05,
+ "loss": 0.5019,
+ "step": 3596
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6391012416003053e-05,
+ "loss": 0.4923,
+ "step": 3597
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.638892793227442e-05,
+ "loss": 0.4851,
+ "step": 3598
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6386842979369487e-05,
+ "loss": 0.4981,
+ "step": 3599
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6384757557441373e-05,
+ "loss": 0.5019,
+ "step": 3600
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6382671666643223e-05,
+ "loss": 0.492,
+ "step": 3601
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.638058530712821e-05,
+ "loss": 0.4817,
+ "step": 3602
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6378498479049553e-05,
+ "loss": 0.5039,
+ "step": 3603
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6376411182560498e-05,
+ "loss": 0.5044,
+ "step": 3604
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6374323417814325e-05,
+ "loss": 0.5089,
+ "step": 3605
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6372235184964357e-05,
+ "loss": 0.4915,
+ "step": 3606
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6370146484163935e-05,
+ "loss": 0.4752,
+ "step": 3607
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6368057315566454e-05,
+ "loss": 0.5043,
+ "step": 3608
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.636596767932533e-05,
+ "loss": 0.5013,
+ "step": 3609
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.636387757559402e-05,
+ "loss": 0.482,
+ "step": 3610
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6361787004526006e-05,
+ "loss": 0.524,
+ "step": 3611
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.635969596627482e-05,
+ "loss": 0.5078,
+ "step": 3612
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.635760446099401e-05,
+ "loss": 0.4964,
+ "step": 3613
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6355512488837173e-05,
+ "loss": 0.4827,
+ "step": 3614
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6353420049957932e-05,
+ "loss": 0.4924,
+ "step": 3615
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6351327144509954e-05,
+ "loss": 0.5235,
+ "step": 3616
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6349233772646923e-05,
+ "loss": 0.4919,
+ "step": 3617
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6347139934522572e-05,
+ "loss": 0.5046,
+ "step": 3618
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6345045630290664e-05,
+ "loss": 0.5007,
+ "step": 3619
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6342950860105e-05,
+ "loss": 0.4592,
+ "step": 3620
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.63408556241194e-05,
+ "loss": 0.4886,
+ "step": 3621
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.633875992248774e-05,
+ "loss": 0.4956,
+ "step": 3622
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.633666375536392e-05,
+ "loss": 0.4919,
+ "step": 3623
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6334567122901862e-05,
+ "loss": 0.5073,
+ "step": 3624
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.633247002525555e-05,
+ "loss": 0.5198,
+ "step": 3625
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6330372462578972e-05,
+ "loss": 0.481,
+ "step": 3626
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6328274435026174e-05,
+ "loss": 0.4838,
+ "step": 3627
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6326175942751222e-05,
+ "loss": 0.4937,
+ "step": 3628
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.632407698590822e-05,
+ "loss": 0.4734,
+ "step": 3629
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6321977564651313e-05,
+ "loss": 0.4866,
+ "step": 3630
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6319877679134662e-05,
+ "loss": 0.5065,
+ "step": 3631
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6317777329512485e-05,
+ "loss": 0.4771,
+ "step": 3632
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6315676515939015e-05,
+ "loss": 0.4991,
+ "step": 3633
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6313575238568535e-05,
+ "loss": 0.494,
+ "step": 3634
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6311473497555343e-05,
+ "loss": 0.4731,
+ "step": 3635
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6309371293053793e-05,
+ "loss": 0.5089,
+ "step": 3636
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.630726862521826e-05,
+ "loss": 0.4857,
+ "step": 3637
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6305165494203147e-05,
+ "loss": 0.4843,
+ "step": 3638
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6303061900162912e-05,
+ "loss": 0.5002,
+ "step": 3639
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6300957843252027e-05,
+ "loss": 0.4996,
+ "step": 3640
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6298853323625003e-05,
+ "loss": 0.4843,
+ "step": 3641
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6296748341436386e-05,
+ "loss": 0.491,
+ "step": 3642
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6294642896840768e-05,
+ "loss": 0.4923,
+ "step": 3643
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6292536989992754e-05,
+ "loss": 0.4955,
+ "step": 3644
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6290430621046994e-05,
+ "loss": 0.4928,
+ "step": 3645
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6288323790158175e-05,
+ "loss": 0.4971,
+ "step": 3646
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6286216497481014e-05,
+ "loss": 0.488,
+ "step": 3647
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6284108743170256e-05,
+ "loss": 0.493,
+ "step": 3648
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.628200052738069e-05,
+ "loss": 0.4973,
+ "step": 3649
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6279891850267134e-05,
+ "loss": 0.4951,
+ "step": 3650
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6277782711984446e-05,
+ "loss": 0.4991,
+ "step": 3651
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.62756731126875e-05,
+ "loss": 0.4884,
+ "step": 3652
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6273563052531227e-05,
+ "loss": 0.4774,
+ "step": 3653
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6271452531670577e-05,
+ "loss": 0.4959,
+ "step": 3654
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6269341550260537e-05,
+ "loss": 0.4922,
+ "step": 3655
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6267230108456126e-05,
+ "loss": 0.5079,
+ "step": 3656
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6265118206412412e-05,
+ "loss": 0.482,
+ "step": 3657
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6263005844284468e-05,
+ "loss": 0.4812,
+ "step": 3658
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6260893022227425e-05,
+ "loss": 0.521,
+ "step": 3659
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6258779740396443e-05,
+ "loss": 0.4847,
+ "step": 3660
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6256665998946708e-05,
+ "loss": 0.499,
+ "step": 3661
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6254551798033444e-05,
+ "loss": 0.4978,
+ "step": 3662
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6252437137811913e-05,
+ "loss": 0.4887,
+ "step": 3663
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.62503220184374e-05,
+ "loss": 0.4927,
+ "step": 3664
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.624820644006524e-05,
+ "loss": 0.4999,
+ "step": 3665
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6246090402850783e-05,
+ "loss": 0.5203,
+ "step": 3666
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6243973906949434e-05,
+ "loss": 0.4929,
+ "step": 3667
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6241856952516604e-05,
+ "loss": 0.4796,
+ "step": 3668
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.623973953970776e-05,
+ "loss": 0.4937,
+ "step": 3669
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6237621668678406e-05,
+ "loss": 0.4927,
+ "step": 3670
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6235503339584052e-05,
+ "loss": 0.4964,
+ "step": 3671
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6233384552580272e-05,
+ "loss": 0.4833,
+ "step": 3672
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6231265307822658e-05,
+ "loss": 0.4704,
+ "step": 3673
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.622914560546684e-05,
+ "loss": 0.5002,
+ "step": 3674
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6227025445668473e-05,
+ "loss": 0.4905,
+ "step": 3675
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.622490482858326e-05,
+ "loss": 0.4894,
+ "step": 3676
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6222783754366926e-05,
+ "loss": 0.4877,
+ "step": 3677
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6220662223175233e-05,
+ "loss": 0.4793,
+ "step": 3678
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6218540235163983e-05,
+ "loss": 0.4839,
+ "step": 3679
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6216417790489005e-05,
+ "loss": 0.4906,
+ "step": 3680
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6214294889306158e-05,
+ "loss": 0.4857,
+ "step": 3681
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.621217153177134e-05,
+ "loss": 0.4932,
+ "step": 3682
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.621004771804049e-05,
+ "loss": 0.4943,
+ "step": 3683
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.620792344826956e-05,
+ "loss": 0.517,
+ "step": 3684
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6205798722614552e-05,
+ "loss": 0.4828,
+ "step": 3685
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6203673541231497e-05,
+ "loss": 0.473,
+ "step": 3686
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6201547904276463e-05,
+ "loss": 0.4931,
+ "step": 3687
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6199421811905542e-05,
+ "loss": 0.508,
+ "step": 3688
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.619729526427487e-05,
+ "loss": 0.4883,
+ "step": 3689
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6195168261540612e-05,
+ "loss": 0.4819,
+ "step": 3690
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6193040803858965e-05,
+ "loss": 0.5097,
+ "step": 3691
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6190912891386154e-05,
+ "loss": 0.5071,
+ "step": 3692
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6188784524278455e-05,
+ "loss": 0.4829,
+ "step": 3693
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6186655702692162e-05,
+ "loss": 0.4916,
+ "step": 3694
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6184526426783607e-05,
+ "loss": 0.5002,
+ "step": 3695
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.618239669670915e-05,
+ "loss": 0.4863,
+ "step": 3696
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.61802665126252e-05,
+ "loss": 0.5061,
+ "step": 3697
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6178135874688183e-05,
+ "loss": 0.4785,
+ "step": 3698
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6176004783054556e-05,
+ "loss": 0.5046,
+ "step": 3699
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6173873237880832e-05,
+ "loss": 0.5005,
+ "step": 3700
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6171741239323537e-05,
+ "loss": 0.4856,
+ "step": 3701
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6169608787539234e-05,
+ "loss": 0.5233,
+ "step": 3702
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6167475882684522e-05,
+ "loss": 0.4767,
+ "step": 3703
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6165342524916035e-05,
+ "loss": 0.5088,
+ "step": 3704
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6163208714390437e-05,
+ "loss": 0.5114,
+ "step": 3705
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6161074451264425e-05,
+ "loss": 0.503,
+ "step": 3706
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.615893973569473e-05,
+ "loss": 0.4942,
+ "step": 3707
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.615680456783812e-05,
+ "loss": 0.4998,
+ "step": 3708
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.615466894785139e-05,
+ "loss": 0.5169,
+ "step": 3709
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6152532875891372e-05,
+ "loss": 0.4753,
+ "step": 3710
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6150396352114926e-05,
+ "loss": 0.481,
+ "step": 3711
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6148259376678957e-05,
+ "loss": 0.4966,
+ "step": 3712
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6146121949740393e-05,
+ "loss": 0.5167,
+ "step": 3713
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6143984071456197e-05,
+ "loss": 0.4961,
+ "step": 3714
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.614184574198336e-05,
+ "loss": 0.5012,
+ "step": 3715
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.613970696147892e-05,
+ "loss": 0.4894,
+ "step": 3716
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.613756773009994e-05,
+ "loss": 0.4937,
+ "step": 3717
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6135428048003513e-05,
+ "loss": 0.4853,
+ "step": 3718
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6133287915346772e-05,
+ "loss": 0.5156,
+ "step": 3719
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6131147332286872e-05,
+ "loss": 0.4906,
+ "step": 3720
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6129006298981015e-05,
+ "loss": 0.4942,
+ "step": 3721
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6126864815586427e-05,
+ "loss": 0.5072,
+ "step": 3722
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6124722882260372e-05,
+ "loss": 0.5006,
+ "step": 3723
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6122580499160144e-05,
+ "loss": 0.4895,
+ "step": 3724
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6120437666443067e-05,
+ "loss": 0.5041,
+ "step": 3725
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6118294384266506e-05,
+ "loss": 0.4864,
+ "step": 3726
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6116150652787852e-05,
+ "loss": 0.4983,
+ "step": 3727
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6114006472164535e-05,
+ "loss": 0.5044,
+ "step": 3728
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6111861842554014e-05,
+ "loss": 0.4779,
+ "step": 3729
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6109716764113778e-05,
+ "loss": 0.4895,
+ "step": 3730
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6107571237001356e-05,
+ "loss": 0.4795,
+ "step": 3731
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6105425261374305e-05,
+ "loss": 0.4991,
+ "step": 3732
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6103278837390218e-05,
+ "loss": 0.4792,
+ "step": 3733
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6101131965206714e-05,
+ "loss": 0.4891,
+ "step": 3734
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6098984644981463e-05,
+ "loss": 0.5137,
+ "step": 3735
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6096836876872143e-05,
+ "loss": 0.5098,
+ "step": 3736
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6094688661036483e-05,
+ "loss": 0.5053,
+ "step": 3737
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6092539997632236e-05,
+ "loss": 0.4915,
+ "step": 3738
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.609039088681719e-05,
+ "loss": 0.4916,
+ "step": 3739
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6088241328749172e-05,
+ "loss": 0.484,
+ "step": 3740
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6086091323586034e-05,
+ "loss": 0.5012,
+ "step": 3741
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6083940871485663e-05,
+ "loss": 0.4669,
+ "step": 3742
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.608178997260598e-05,
+ "loss": 0.4923,
+ "step": 3743
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6079638627104937e-05,
+ "loss": 0.4927,
+ "step": 3744
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6077486835140518e-05,
+ "loss": 0.4755,
+ "step": 3745
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6075334596870746e-05,
+ "loss": 0.4855,
+ "step": 3746
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.607318191245367e-05,
+ "loss": 0.4979,
+ "step": 3747
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.607102878204738e-05,
+ "loss": 0.4754,
+ "step": 3748
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6068875205809978e-05,
+ "loss": 0.5086,
+ "step": 3749
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.606672118389963e-05,
+ "loss": 0.5113,
+ "step": 3750
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6064566716474506e-05,
+ "loss": 0.5014,
+ "step": 3751
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.606241180369283e-05,
+ "loss": 0.4899,
+ "step": 3752
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.606025644571285e-05,
+ "loss": 0.5102,
+ "step": 3753
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6058100642692837e-05,
+ "loss": 0.4875,
+ "step": 3754
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6055944394791113e-05,
+ "loss": 0.5025,
+ "step": 3755
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.605378770216602e-05,
+ "loss": 0.4748,
+ "step": 3756
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.605163056497594e-05,
+ "loss": 0.4893,
+ "step": 3757
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6049472983379285e-05,
+ "loss": 0.4999,
+ "step": 3758
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6047314957534487e-05,
+ "loss": 0.5149,
+ "step": 3759
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.604515648760004e-05,
+ "loss": 0.4722,
+ "step": 3760
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6042997573734437e-05,
+ "loss": 0.5037,
+ "step": 3761
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6040838216096233e-05,
+ "loss": 0.4684,
+ "step": 3762
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6038678414843994e-05,
+ "loss": 0.5232,
+ "step": 3763
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6036518170136326e-05,
+ "loss": 0.4807,
+ "step": 3764
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.603435748213187e-05,
+ "loss": 0.4972,
+ "step": 3765
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6032196350989306e-05,
+ "loss": 0.4843,
+ "step": 3766
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.603003477686733e-05,
+ "loss": 0.4668,
+ "step": 3767
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6027872759924678e-05,
+ "loss": 0.4949,
+ "step": 3768
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6025710300320124e-05,
+ "loss": 0.4948,
+ "step": 3769
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6023547398212467e-05,
+ "loss": 0.4746,
+ "step": 3770
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6021384053760546e-05,
+ "loss": 0.476,
+ "step": 3771
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6019220267123223e-05,
+ "loss": 0.4951,
+ "step": 3772
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.60170560384594e-05,
+ "loss": 0.4662,
+ "step": 3773
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.601489136792801e-05,
+ "loss": 0.4972,
+ "step": 3774
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6012726255688013e-05,
+ "loss": 0.4956,
+ "step": 3775
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6010560701898405e-05,
+ "loss": 0.4779,
+ "step": 3776
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6008394706718224e-05,
+ "loss": 0.5058,
+ "step": 3777
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6006228270306526e-05,
+ "loss": 0.5015,
+ "step": 3778
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6004061392822407e-05,
+ "loss": 0.4791,
+ "step": 3779
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6001894074424987e-05,
+ "loss": 0.4736,
+ "step": 3780
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5999726315273435e-05,
+ "loss": 0.4803,
+ "step": 3781
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.599755811552693e-05,
+ "loss": 0.5038,
+ "step": 3782
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5995389475344715e-05,
+ "loss": 0.4888,
+ "step": 3783
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5993220394886024e-05,
+ "loss": 0.4943,
+ "step": 3784
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5991050874310156e-05,
+ "loss": 0.5088,
+ "step": 3785
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5988880913776434e-05,
+ "loss": 0.4833,
+ "step": 3786
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5986710513444205e-05,
+ "loss": 0.499,
+ "step": 3787
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5984539673472856e-05,
+ "loss": 0.4909,
+ "step": 3788
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5982368394021804e-05,
+ "loss": 0.4929,
+ "step": 3789
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5980196675250504e-05,
+ "loss": 0.4894,
+ "step": 3790
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5978024517318428e-05,
+ "loss": 0.4776,
+ "step": 3791
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5975851920385103e-05,
+ "loss": 0.4832,
+ "step": 3792
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5973678884610062e-05,
+ "loss": 0.4832,
+ "step": 3793
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.597150541015289e-05,
+ "loss": 0.4827,
+ "step": 3794
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5969331497173203e-05,
+ "loss": 0.4805,
+ "step": 3795
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5967157145830638e-05,
+ "loss": 0.4961,
+ "step": 3796
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.596498235628487e-05,
+ "loss": 0.5165,
+ "step": 3797
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5962807128695606e-05,
+ "loss": 0.4927,
+ "step": 3798
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5960631463222592e-05,
+ "loss": 0.5033,
+ "step": 3799
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.595845536002559e-05,
+ "loss": 0.4744,
+ "step": 3800
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5956278819264417e-05,
+ "loss": 0.4675,
+ "step": 3801
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5954101841098895e-05,
+ "loss": 0.4773,
+ "step": 3802
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.59519244256889e-05,
+ "loss": 0.4848,
+ "step": 3803
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5949746573194334e-05,
+ "loss": 0.4883,
+ "step": 3804
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5947568283775125e-05,
+ "loss": 0.4869,
+ "step": 3805
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5945389557591237e-05,
+ "loss": 0.4972,
+ "step": 3806
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.594321039480267e-05,
+ "loss": 0.4711,
+ "step": 3807
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5941030795569452e-05,
+ "loss": 0.4634,
+ "step": 3808
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5938850760051643e-05,
+ "loss": 0.4964,
+ "step": 3809
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5936670288409335e-05,
+ "loss": 0.4977,
+ "step": 3810
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5934489380802653e-05,
+ "loss": 0.5042,
+ "step": 3811
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5932308037391756e-05,
+ "loss": 0.493,
+ "step": 3812
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.593012625833683e-05,
+ "loss": 0.4989,
+ "step": 3813
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.59279440437981e-05,
+ "loss": 0.4855,
+ "step": 3814
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.592576139393581e-05,
+ "loss": 0.483,
+ "step": 3815
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5923578308910254e-05,
+ "loss": 0.4849,
+ "step": 3816
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.592139478888174e-05,
+ "loss": 0.483,
+ "step": 3817
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5919210834010628e-05,
+ "loss": 0.511,
+ "step": 3818
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5917026444457288e-05,
+ "loss": 0.4953,
+ "step": 3819
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.591484162038214e-05,
+ "loss": 0.4849,
+ "step": 3820
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5912656361945626e-05,
+ "loss": 0.4783,
+ "step": 3821
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5910470669308217e-05,
+ "loss": 0.4872,
+ "step": 3822
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5908284542630425e-05,
+ "loss": 0.5001,
+ "step": 3823
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5906097982072793e-05,
+ "loss": 0.4711,
+ "step": 3824
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.590391098779589e-05,
+ "loss": 0.468,
+ "step": 3825
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5901723559960322e-05,
+ "loss": 0.5036,
+ "step": 3826
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5899535698726723e-05,
+ "loss": 0.483,
+ "step": 3827
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5897347404255757e-05,
+ "loss": 0.4843,
+ "step": 3828
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.589515867670813e-05,
+ "loss": 0.4897,
+ "step": 3829
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.589296951624457e-05,
+ "loss": 0.4886,
+ "step": 3830
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5890779923025832e-05,
+ "loss": 0.4777,
+ "step": 3831
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5888589897212726e-05,
+ "loss": 0.495,
+ "step": 3832
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5886399438966068e-05,
+ "loss": 0.4896,
+ "step": 3833
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5884208548446716e-05,
+ "loss": 0.4846,
+ "step": 3834
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5882017225815566e-05,
+ "loss": 0.4673,
+ "step": 3835
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5879825471233538e-05,
+ "loss": 0.4854,
+ "step": 3836
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5877633284861577e-05,
+ "loss": 0.4916,
+ "step": 3837
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.587544066686068e-05,
+ "loss": 0.4774,
+ "step": 3838
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5873247617391854e-05,
+ "loss": 0.4825,
+ "step": 3839
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5871054136616154e-05,
+ "loss": 0.4933,
+ "step": 3840
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5868860224694656e-05,
+ "loss": 0.5059,
+ "step": 3841
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.586666588178848e-05,
+ "loss": 0.4819,
+ "step": 3842
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5864471108058755e-05,
+ "loss": 0.4753,
+ "step": 3843
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.586227590366667e-05,
+ "loss": 0.5028,
+ "step": 3844
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.586008026877342e-05,
+ "loss": 0.5122,
+ "step": 3845
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.585788420354025e-05,
+ "loss": 0.5066,
+ "step": 3846
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5855687708128433e-05,
+ "loss": 0.4991,
+ "step": 3847
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5853490782699266e-05,
+ "loss": 0.4953,
+ "step": 3848
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5851293427414075e-05,
+ "loss": 0.4834,
+ "step": 3849
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.584909564243424e-05,
+ "loss": 0.49,
+ "step": 3850
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5846897427921147e-05,
+ "loss": 0.4989,
+ "step": 3851
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.584469878403623e-05,
+ "loss": 0.481,
+ "step": 3852
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5842499710940936e-05,
+ "loss": 0.5093,
+ "step": 3853
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5840300208796767e-05,
+ "loss": 0.4943,
+ "step": 3854
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5838100277765244e-05,
+ "loss": 0.4794,
+ "step": 3855
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5835899918007917e-05,
+ "loss": 0.4951,
+ "step": 3856
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5833699129686376e-05,
+ "loss": 0.4958,
+ "step": 3857
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5831497912962235e-05,
+ "loss": 0.5049,
+ "step": 3858
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5829296267997142e-05,
+ "loss": 0.4801,
+ "step": 3859
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.582709419495277e-05,
+ "loss": 0.4781,
+ "step": 3860
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5824891693990845e-05,
+ "loss": 0.5053,
+ "step": 3861
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.58226887652731e-05,
+ "loss": 0.5095,
+ "step": 3862
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.582048540896131e-05,
+ "loss": 0.5,
+ "step": 3863
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.581828162521728e-05,
+ "loss": 0.4818,
+ "step": 3864
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5816077414202848e-05,
+ "loss": 0.4957,
+ "step": 3865
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5813872776079882e-05,
+ "loss": 0.477,
+ "step": 3866
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.581166771101028e-05,
+ "loss": 0.4875,
+ "step": 3867
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5809462219155976e-05,
+ "loss": 0.4905,
+ "step": 3868
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.580725630067893e-05,
+ "loss": 0.4993,
+ "step": 3869
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5805049955741135e-05,
+ "loss": 0.486,
+ "step": 3870
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5802843184504614e-05,
+ "loss": 0.4895,
+ "step": 3871
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5800635987131426e-05,
+ "loss": 0.5033,
+ "step": 3872
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.579842836378366e-05,
+ "loss": 0.4842,
+ "step": 3873
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.579622031462343e-05,
+ "loss": 0.479,
+ "step": 3874
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5794011839812888e-05,
+ "loss": 0.5077,
+ "step": 3875
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.579180293951422e-05,
+ "loss": 0.4942,
+ "step": 3876
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5789593613889632e-05,
+ "loss": 0.4722,
+ "step": 3877
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5787383863101366e-05,
+ "loss": 0.48,
+ "step": 3878
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5785173687311704e-05,
+ "loss": 0.4909,
+ "step": 3879
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5782963086682946e-05,
+ "loss": 0.4962,
+ "step": 3880
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5780752061377436e-05,
+ "loss": 0.502,
+ "step": 3881
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5778540611557538e-05,
+ "loss": 0.4961,
+ "step": 3882
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.577632873738565e-05,
+ "loss": 0.506,
+ "step": 3883
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5774116439024206e-05,
+ "loss": 0.4868,
+ "step": 3884
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5771903716635666e-05,
+ "loss": 0.4888,
+ "step": 3885
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.576969057038253e-05,
+ "loss": 0.5003,
+ "step": 3886
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5767477000427306e-05,
+ "loss": 0.4854,
+ "step": 3887
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.576526300693257e-05,
+ "loss": 0.4996,
+ "step": 3888
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5763048590060894e-05,
+ "loss": 0.4976,
+ "step": 3889
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5760833749974898e-05,
+ "loss": 0.4881,
+ "step": 3890
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5758618486837232e-05,
+ "loss": 0.494,
+ "step": 3891
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5756402800810582e-05,
+ "loss": 0.4804,
+ "step": 3892
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.575418669205765e-05,
+ "loss": 0.4861,
+ "step": 3893
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.575197016074118e-05,
+ "loss": 0.4914,
+ "step": 3894
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5749753207023944e-05,
+ "loss": 0.4872,
+ "step": 3895
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574753583106875e-05,
+ "loss": 0.489,
+ "step": 3896
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574531803303843e-05,
+ "loss": 0.4924,
+ "step": 3897
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574309981309585e-05,
+ "loss": 0.4816,
+ "step": 3898
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574088117140391e-05,
+ "loss": 0.4639,
+ "step": 3899
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.573866210812553e-05,
+ "loss": 0.4816,
+ "step": 3900
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5736442623423675e-05,
+ "loss": 0.4962,
+ "step": 3901
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5734222717461338e-05,
+ "loss": 0.4772,
+ "step": 3902
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5732002390401527e-05,
+ "loss": 0.5055,
+ "step": 3903
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5729781642407305e-05,
+ "loss": 0.5134,
+ "step": 3904
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5727560473641755e-05,
+ "loss": 0.4845,
+ "step": 3905
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.572533888426798e-05,
+ "loss": 0.4959,
+ "step": 3906
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5723116874449136e-05,
+ "loss": 0.5198,
+ "step": 3907
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5720894444348393e-05,
+ "loss": 0.4905,
+ "step": 3908
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5718671594128957e-05,
+ "loss": 0.4815,
+ "step": 3909
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.571644832395406e-05,
+ "loss": 0.5216,
+ "step": 3910
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5714224633986978e-05,
+ "loss": 0.4948,
+ "step": 3911
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5712000524391004e-05,
+ "loss": 0.4868,
+ "step": 3912
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5709775995329475e-05,
+ "loss": 0.488,
+ "step": 3913
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.570755104696574e-05,
+ "loss": 0.4918,
+ "step": 3914
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5705325679463198e-05,
+ "loss": 0.4765,
+ "step": 3915
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5703099892985267e-05,
+ "loss": 0.501,
+ "step": 3916
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5700873687695405e-05,
+ "loss": 0.4919,
+ "step": 3917
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5698647063757086e-05,
+ "loss": 0.4837,
+ "step": 3918
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5696420021333828e-05,
+ "loss": 0.4798,
+ "step": 3919
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5694192560589184e-05,
+ "loss": 0.4893,
+ "step": 3920
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5691964681686715e-05,
+ "loss": 0.4969,
+ "step": 3921
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5689736384790038e-05,
+ "loss": 0.4692,
+ "step": 3922
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5687507670062788e-05,
+ "loss": 0.4862,
+ "step": 3923
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5685278537668627e-05,
+ "loss": 0.4888,
+ "step": 3924
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.568304898777126e-05,
+ "loss": 0.518,
+ "step": 3925
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.568081902053441e-05,
+ "loss": 0.4963,
+ "step": 3926
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.567858863612184e-05,
+ "loss": 0.4802,
+ "step": 3927
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5676357834697342e-05,
+ "loss": 0.5066,
+ "step": 3928
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5674126616424735e-05,
+ "loss": 0.495,
+ "step": 3929
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5671894981467866e-05,
+ "loss": 0.4616,
+ "step": 3930
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5669662929990622e-05,
+ "loss": 0.4896,
+ "step": 3931
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5667430462156918e-05,
+ "loss": 0.4981,
+ "step": 3932
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.566519757813069e-05,
+ "loss": 0.4783,
+ "step": 3933
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5662964278075913e-05,
+ "loss": 0.5017,
+ "step": 3934
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5660730562156596e-05,
+ "loss": 0.4876,
+ "step": 3935
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5658496430536772e-05,
+ "loss": 0.4888,
+ "step": 3936
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5656261883380504e-05,
+ "loss": 0.484,
+ "step": 3937
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.565402692085189e-05,
+ "loss": 0.5082,
+ "step": 3938
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5651791543115056e-05,
+ "loss": 0.4958,
+ "step": 3939
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.564955575033416e-05,
+ "loss": 0.4958,
+ "step": 3940
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5647319542673386e-05,
+ "loss": 0.5015,
+ "step": 3941
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.564508292029695e-05,
+ "loss": 0.4872,
+ "step": 3942
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5642845883369114e-05,
+ "loss": 0.471,
+ "step": 3943
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.564060843205414e-05,
+ "loss": 0.484,
+ "step": 3944
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5638370566516344e-05,
+ "loss": 0.4949,
+ "step": 3945
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5636132286920066e-05,
+ "loss": 0.4749,
+ "step": 3946
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5633893593429677e-05,
+ "loss": 0.4953,
+ "step": 3947
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5631654486209572e-05,
+ "loss": 0.513,
+ "step": 3948
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5629414965424187e-05,
+ "loss": 0.4946,
+ "step": 3949
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5627175031237986e-05,
+ "loss": 0.4743,
+ "step": 3950
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.562493468381545e-05,
+ "loss": 0.4942,
+ "step": 3951
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5622693923321105e-05,
+ "loss": 0.5027,
+ "step": 3952
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.562045274991951e-05,
+ "loss": 0.5063,
+ "step": 3953
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5618211163775242e-05,
+ "loss": 0.5087,
+ "step": 3954
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.561596916505291e-05,
+ "loss": 0.4906,
+ "step": 3955
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5613726753917166e-05,
+ "loss": 0.4729,
+ "step": 3956
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5611483930532677e-05,
+ "loss": 0.4925,
+ "step": 3957
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5609240695064146e-05,
+ "loss": 0.4867,
+ "step": 3958
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.560699704767631e-05,
+ "loss": 0.4978,
+ "step": 3959
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5604752988533933e-05,
+ "loss": 0.4827,
+ "step": 3960
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.560250851780181e-05,
+ "loss": 0.4758,
+ "step": 3961
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.560026363564476e-05,
+ "loss": 0.5156,
+ "step": 3962
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5598018342227645e-05,
+ "loss": 0.4874,
+ "step": 3963
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5595772637715345e-05,
+ "loss": 0.4942,
+ "step": 3964
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5593526522272774e-05,
+ "loss": 0.4825,
+ "step": 3965
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5591279996064884e-05,
+ "loss": 0.4938,
+ "step": 3966
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.558903305925665e-05,
+ "loss": 0.5092,
+ "step": 3967
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5586785712013073e-05,
+ "loss": 0.4806,
+ "step": 3968
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5584537954499186e-05,
+ "loss": 0.5001,
+ "step": 3969
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5582289786880064e-05,
+ "loss": 0.4897,
+ "step": 3970
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5580041209320797e-05,
+ "loss": 0.4813,
+ "step": 3971
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5577792221986512e-05,
+ "loss": 0.4873,
+ "step": 3972
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5575542825042368e-05,
+ "loss": 0.4936,
+ "step": 3973
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.557329301865355e-05,
+ "loss": 0.4823,
+ "step": 3974
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.557104280298527e-05,
+ "loss": 0.4738,
+ "step": 3975
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.556879217820278e-05,
+ "loss": 0.4857,
+ "step": 3976
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5566541144471355e-05,
+ "loss": 0.4782,
+ "step": 3977
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.55642897019563e-05,
+ "loss": 0.5053,
+ "step": 3978
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5562037850822954e-05,
+ "loss": 0.4842,
+ "step": 3979
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5559785591236683e-05,
+ "loss": 0.4971,
+ "step": 3980
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5557532923362883e-05,
+ "loss": 0.4861,
+ "step": 3981
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.555527984736698e-05,
+ "loss": 0.4977,
+ "step": 3982
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.555302636341443e-05,
+ "loss": 0.5032,
+ "step": 3983
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5550772471670724e-05,
+ "loss": 0.4829,
+ "step": 3984
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5548518172301373e-05,
+ "loss": 0.5062,
+ "step": 3985
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5546263465471926e-05,
+ "loss": 0.4957,
+ "step": 3986
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.554400835134796e-05,
+ "loss": 0.4942,
+ "step": 3987
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.554175283009508e-05,
+ "loss": 0.4794,
+ "step": 3988
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5539496901878915e-05,
+ "loss": 0.4872,
+ "step": 3989
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5537240566865145e-05,
+ "loss": 0.4901,
+ "step": 3990
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.553498382521946e-05,
+ "loss": 0.4855,
+ "step": 3991
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5532726677107583e-05,
+ "loss": 0.4874,
+ "step": 3992
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.553046912269527e-05,
+ "loss": 0.4815,
+ "step": 3993
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5528211162148305e-05,
+ "loss": 0.5012,
+ "step": 3994
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.552595279563251e-05,
+ "loss": 0.4831,
+ "step": 3995
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5523694023313723e-05,
+ "loss": 0.487,
+ "step": 3996
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5521434845357824e-05,
+ "loss": 0.4729,
+ "step": 3997
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5519175261930716e-05,
+ "loss": 0.4859,
+ "step": 3998
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.551691527319833e-05,
+ "loss": 0.4979,
+ "step": 3999
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.551465487932663e-05,
+ "loss": 0.4947,
+ "step": 4000
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.551239408048162e-05,
+ "loss": 0.48,
+ "step": 4001
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5510132876829313e-05,
+ "loss": 0.4818,
+ "step": 4002
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5507871268535765e-05,
+ "loss": 0.4845,
+ "step": 4003
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.550560925576706e-05,
+ "loss": 0.5188,
+ "step": 4004
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5503346838689314e-05,
+ "loss": 0.479,
+ "step": 4005
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5501084017468665e-05,
+ "loss": 0.5038,
+ "step": 4006
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5498820792271284e-05,
+ "loss": 0.5002,
+ "step": 4007
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.549655716326338e-05,
+ "loss": 0.5109,
+ "step": 4008
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5494293130611175e-05,
+ "loss": 0.4899,
+ "step": 4009
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5492028694480938e-05,
+ "loss": 0.4973,
+ "step": 4010
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5489763855038954e-05,
+ "loss": 0.4873,
+ "step": 4011
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.548749861245155e-05,
+ "loss": 0.4707,
+ "step": 4012
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.548523296688507e-05,
+ "loss": 0.48,
+ "step": 4013
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5482966918505897e-05,
+ "loss": 0.4909,
+ "step": 4014
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5480700467480437e-05,
+ "loss": 0.496,
+ "step": 4015
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.547843361397513e-05,
+ "loss": 0.4784,
+ "step": 4016
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5476166358156446e-05,
+ "loss": 0.49,
+ "step": 4017
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5473898700190884e-05,
+ "loss": 0.5039,
+ "step": 4018
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5471630640244966e-05,
+ "loss": 0.4724,
+ "step": 4019
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5469362178485252e-05,
+ "loss": 0.481,
+ "step": 4020
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.546709331507833e-05,
+ "loss": 0.5026,
+ "step": 4021
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5464824050190816e-05,
+ "loss": 0.4854,
+ "step": 4022
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5462554383989347e-05,
+ "loss": 0.5195,
+ "step": 4023
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.546028431664061e-05,
+ "loss": 0.4913,
+ "step": 4024
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5458013848311305e-05,
+ "loss": 0.4944,
+ "step": 4025
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.545574297916816e-05,
+ "loss": 0.4911,
+ "step": 4026
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5453471709377945e-05,
+ "loss": 0.4948,
+ "step": 4027
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.545120003910745e-05,
+ "loss": 0.4996,
+ "step": 4028
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.54489279685235e-05,
+ "loss": 0.4778,
+ "step": 4029
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.544665549779294e-05,
+ "loss": 0.4836,
+ "step": 4030
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5444382627082657e-05,
+ "loss": 0.4674,
+ "step": 4031
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5442109356559556e-05,
+ "loss": 0.4828,
+ "step": 4032
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543983568639058e-05,
+ "loss": 0.4952,
+ "step": 4033
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5437561616742703e-05,
+ "loss": 0.4733,
+ "step": 4034
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543528714778291e-05,
+ "loss": 0.4976,
+ "step": 4035
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543301227967824e-05,
+ "loss": 0.4952,
+ "step": 4036
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543073701259574e-05,
+ "loss": 0.496,
+ "step": 4037
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.542846134670251e-05,
+ "loss": 0.4901,
+ "step": 4038
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5426185282165652e-05,
+ "loss": 0.5044,
+ "step": 4039
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5423908819152317e-05,
+ "loss": 0.4779,
+ "step": 4040
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.542163195782968e-05,
+ "loss": 0.5076,
+ "step": 4041
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5419354698364944e-05,
+ "loss": 0.4836,
+ "step": 4042
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5417077040925334e-05,
+ "loss": 0.4994,
+ "step": 4043
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.541479898567812e-05,
+ "loss": 0.5221,
+ "step": 4044
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.541252053279059e-05,
+ "loss": 0.4938,
+ "step": 4045
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.541024168243007e-05,
+ "loss": 0.4794,
+ "step": 4046
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5407962434763897e-05,
+ "loss": 0.4798,
+ "step": 4047
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5405682789959455e-05,
+ "loss": 0.4878,
+ "step": 4048
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5403402748184156e-05,
+ "loss": 0.5025,
+ "step": 4049
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5401122309605437e-05,
+ "loss": 0.4778,
+ "step": 4050
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5398841474390754e-05,
+ "loss": 0.4801,
+ "step": 4051
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5396560242707613e-05,
+ "loss": 0.4845,
+ "step": 4052
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5394278614723535e-05,
+ "loss": 0.4736,
+ "step": 4053
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5391996590606066e-05,
+ "loss": 0.5036,
+ "step": 4054
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.53897141705228e-05,
+ "loss": 0.5004,
+ "step": 4055
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.538743135464134e-05,
+ "loss": 0.4898,
+ "step": 4056
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5385148143129328e-05,
+ "loss": 0.4723,
+ "step": 4057
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5382864536154437e-05,
+ "loss": 0.5157,
+ "step": 4058
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5380580533884364e-05,
+ "loss": 0.4803,
+ "step": 4059
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5378296136486837e-05,
+ "loss": 0.5016,
+ "step": 4060
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5376011344129608e-05,
+ "loss": 0.5045,
+ "step": 4061
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.537372615698047e-05,
+ "loss": 0.4805,
+ "step": 4062
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5371440575207233e-05,
+ "loss": 0.5004,
+ "step": 4063
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.536915459897774e-05,
+ "loss": 0.4941,
+ "step": 4064
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5366868228459866e-05,
+ "loss": 0.4623,
+ "step": 4065
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.536458146382151e-05,
+ "loss": 0.4911,
+ "step": 4066
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.536229430523061e-05,
+ "loss": 0.4749,
+ "step": 4067
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5360006752855113e-05,
+ "loss": 0.4797,
+ "step": 4068
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.535771880686302e-05,
+ "loss": 0.4853,
+ "step": 4069
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5355430467422343e-05,
+ "loss": 0.4968,
+ "step": 4070
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.535314173470112e-05,
+ "loss": 0.4907,
+ "step": 4071
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5350852608867436e-05,
+ "loss": 0.4847,
+ "step": 4072
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5348563090089394e-05,
+ "loss": 0.5151,
+ "step": 4073
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5346273178535126e-05,
+ "loss": 0.4775,
+ "step": 4074
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.534398287437279e-05,
+ "loss": 0.4907,
+ "step": 4075
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5341692177770583e-05,
+ "loss": 0.466,
+ "step": 4076
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5339401088896715e-05,
+ "loss": 0.5019,
+ "step": 4077
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.533710960791944e-05,
+ "loss": 0.4801,
+ "step": 4078
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5334817735007037e-05,
+ "loss": 0.4967,
+ "step": 4079
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.533252547032781e-05,
+ "loss": 0.4966,
+ "step": 4080
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.533023281405009e-05,
+ "loss": 0.5023,
+ "step": 4081
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5327939766342237e-05,
+ "loss": 0.5038,
+ "step": 4082
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5325646327372658e-05,
+ "loss": 0.4999,
+ "step": 4083
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.532335249730976e-05,
+ "loss": 0.4819,
+ "step": 4084
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5321058276321988e-05,
+ "loss": 0.4924,
+ "step": 4085
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5318763664577838e-05,
+ "loss": 0.4895,
+ "step": 4086
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5316468662245805e-05,
+ "loss": 0.4882,
+ "step": 4087
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.531417326949442e-05,
+ "loss": 0.4849,
+ "step": 4088
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5311877486492264e-05,
+ "loss": 0.4824,
+ "step": 4089
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5309581313407914e-05,
+ "loss": 0.483,
+ "step": 4090
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5307284750409993e-05,
+ "loss": 0.4939,
+ "step": 4091
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.530498779766716e-05,
+ "loss": 0.5149,
+ "step": 4092
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5302690455348085e-05,
+ "loss": 0.4828,
+ "step": 4093
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.530039272362148e-05,
+ "loss": 0.4805,
+ "step": 4094
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5298094602656077e-05,
+ "loss": 0.4946,
+ "step": 4095
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5295796092620646e-05,
+ "loss": 0.4826,
+ "step": 4096
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5293497193683974e-05,
+ "loss": 0.5091,
+ "step": 4097
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5291197906014886e-05,
+ "loss": 0.4893,
+ "step": 4098
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5288898229782234e-05,
+ "loss": 0.4873,
+ "step": 4099
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5286598165154892e-05,
+ "loss": 0.4815,
+ "step": 4100
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5284297712301773e-05,
+ "loss": 0.4878,
+ "step": 4101
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5281996871391805e-05,
+ "loss": 0.4834,
+ "step": 4102
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5279695642593958e-05,
+ "loss": 0.4621,
+ "step": 4103
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.527739402607722e-05,
+ "loss": 0.4742,
+ "step": 4104
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.527509202201062e-05,
+ "loss": 0.4787,
+ "step": 4105
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5272789630563202e-05,
+ "loss": 0.495,
+ "step": 4106
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.527048685190404e-05,
+ "loss": 0.495,
+ "step": 4107
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5268183686202245e-05,
+ "loss": 0.51,
+ "step": 4108
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5265880133626956e-05,
+ "loss": 0.4721,
+ "step": 4109
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5263576194347334e-05,
+ "loss": 0.498,
+ "step": 4110
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5261271868532568e-05,
+ "loss": 0.5005,
+ "step": 4111
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5258967156351878e-05,
+ "loss": 0.4735,
+ "step": 4112
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.525666205797451e-05,
+ "loss": 0.4863,
+ "step": 4113
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5254356573569748e-05,
+ "loss": 0.4886,
+ "step": 4114
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5252050703306895e-05,
+ "loss": 0.4866,
+ "step": 4115
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5249744447355282e-05,
+ "loss": 0.5044,
+ "step": 4116
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5247437805884273e-05,
+ "loss": 0.4863,
+ "step": 4117
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5245130779063255e-05,
+ "loss": 0.5085,
+ "step": 4118
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.524282336706165e-05,
+ "loss": 0.4725,
+ "step": 4119
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5240515570048903e-05,
+ "loss": 0.4866,
+ "step": 4120
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5238207388194493e-05,
+ "loss": 0.485,
+ "step": 4121
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5235898821667916e-05,
+ "loss": 0.5004,
+ "step": 4122
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5233589870638708e-05,
+ "loss": 0.4852,
+ "step": 4123
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5231280535276426e-05,
+ "loss": 0.4778,
+ "step": 4124
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5228970815750666e-05,
+ "loss": 0.4932,
+ "step": 4125
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5226660712231032e-05,
+ "loss": 0.4973,
+ "step": 4126
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5224350224887179e-05,
+ "loss": 0.4899,
+ "step": 4127
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5222039353888774e-05,
+ "loss": 0.4763,
+ "step": 4128
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5219728099405516e-05,
+ "loss": 0.4994,
+ "step": 4129
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.521741646160714e-05,
+ "loss": 0.4798,
+ "step": 4130
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5215104440663399e-05,
+ "loss": 0.4698,
+ "step": 4131
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.521279203674408e-05,
+ "loss": 0.472,
+ "step": 4132
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5210479250018995e-05,
+ "loss": 0.4933,
+ "step": 4133
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5208166080657982e-05,
+ "loss": 0.4828,
+ "step": 4134
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.520585252883092e-05,
+ "loss": 0.497,
+ "step": 4135
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5203538594707699e-05,
+ "loss": 0.4824,
+ "step": 4136
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.520122427845825e-05,
+ "loss": 0.4743,
+ "step": 4137
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5198909580252517e-05,
+ "loss": 0.5035,
+ "step": 4138
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.519659450026049e-05,
+ "loss": 0.5019,
+ "step": 4139
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.519427903865218e-05,
+ "loss": 0.5058,
+ "step": 4140
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.519196319559762e-05,
+ "loss": 0.4959,
+ "step": 4141
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.518964697126688e-05,
+ "loss": 0.4922,
+ "step": 4142
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.518733036583005e-05,
+ "loss": 0.5021,
+ "step": 4143
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5185013379457254e-05,
+ "loss": 0.4927,
+ "step": 4144
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5182696012318641e-05,
+ "loss": 0.5034,
+ "step": 4145
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.518037826458439e-05,
+ "loss": 0.498,
+ "step": 4146
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5178060136424706e-05,
+ "loss": 0.5033,
+ "step": 4147
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5175741628009824e-05,
+ "loss": 0.4818,
+ "step": 4148
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5173422739510003e-05,
+ "loss": 0.5017,
+ "step": 4149
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5171103471095533e-05,
+ "loss": 0.4716,
+ "step": 4150
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5168783822936735e-05,
+ "loss": 0.4648,
+ "step": 4151
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.516646379520395e-05,
+ "loss": 0.4952,
+ "step": 4152
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5164143388067554e-05,
+ "loss": 0.4907,
+ "step": 4153
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5161822601697945e-05,
+ "loss": 0.4882,
+ "step": 4154
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5159501436265553e-05,
+ "loss": 0.4774,
+ "step": 4155
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5157179891940837e-05,
+ "loss": 0.4901,
+ "step": 4156
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5154857968894278e-05,
+ "loss": 0.4773,
+ "step": 4157
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5152535667296395e-05,
+ "loss": 0.4894,
+ "step": 4158
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5150212987317721e-05,
+ "loss": 0.4976,
+ "step": 4159
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5147889929128825e-05,
+ "loss": 0.4964,
+ "step": 4160
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5145566492900305e-05,
+ "loss": 0.4747,
+ "step": 4161
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5143242678802787e-05,
+ "loss": 0.4627,
+ "step": 4162
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5140918487006918e-05,
+ "loss": 0.483,
+ "step": 4163
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5138593917683374e-05,
+ "loss": 0.4939,
+ "step": 4164
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.513626897100287e-05,
+ "loss": 0.4938,
+ "step": 4165
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5133943647136131e-05,
+ "loss": 0.4925,
+ "step": 4166
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5131617946253928e-05,
+ "loss": 0.4871,
+ "step": 4167
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5129291868527052e-05,
+ "loss": 0.4939,
+ "step": 4168
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5126965414126309e-05,
+ "loss": 0.4752,
+ "step": 4169
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.512463858322255e-05,
+ "loss": 0.4781,
+ "step": 4170
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5122311375986649e-05,
+ "loss": 0.4782,
+ "step": 4171
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.511998379258951e-05,
+ "loss": 0.4739,
+ "step": 4172
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5117655833202052e-05,
+ "loss": 0.5065,
+ "step": 4173
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5115327497995238e-05,
+ "loss": 0.5288,
+ "step": 4174
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.511299878714005e-05,
+ "loss": 0.4939,
+ "step": 4175
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5110669700807496e-05,
+ "loss": 0.5027,
+ "step": 4176
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5108340239168614e-05,
+ "loss": 0.5097,
+ "step": 4177
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5106010402394477e-05,
+ "loss": 0.4741,
+ "step": 4178
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5103680190656169e-05,
+ "loss": 0.4856,
+ "step": 4179
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5101349604124816e-05,
+ "loss": 0.5238,
+ "step": 4180
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5099018642971568e-05,
+ "loss": 0.4797,
+ "step": 4181
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5096687307367601e-05,
+ "loss": 0.5027,
+ "step": 4182
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5094355597484111e-05,
+ "loss": 0.481,
+ "step": 4183
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.509202351349234e-05,
+ "loss": 0.5015,
+ "step": 4184
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.508969105556354e-05,
+ "loss": 0.4847,
+ "step": 4185
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5087358223869e-05,
+ "loss": 0.4803,
+ "step": 4186
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5085025018580029e-05,
+ "loss": 0.4904,
+ "step": 4187
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5082691439867973e-05,
+ "loss": 0.4654,
+ "step": 4188
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5080357487904198e-05,
+ "loss": 0.4828,
+ "step": 4189
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5078023162860099e-05,
+ "loss": 0.5049,
+ "step": 4190
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5075688464907099e-05,
+ "loss": 0.4923,
+ "step": 4191
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5073353394216652e-05,
+ "loss": 0.4693,
+ "step": 4192
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5071017950960234e-05,
+ "loss": 0.4917,
+ "step": 4193
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5068682135309347e-05,
+ "loss": 0.495,
+ "step": 4194
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5066345947435525e-05,
+ "loss": 0.4869,
+ "step": 4195
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5064009387510333e-05,
+ "loss": 0.4836,
+ "step": 4196
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5061672455705352e-05,
+ "loss": 0.4999,
+ "step": 4197
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.50593351521922e-05,
+ "loss": 0.5058,
+ "step": 4198
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.505699747714252e-05,
+ "loss": 0.4897,
+ "step": 4199
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5054659430727974e-05,
+ "loss": 0.4752,
+ "step": 4200
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5052321013120263e-05,
+ "loss": 0.4942,
+ "step": 4201
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5049982224491115e-05,
+ "loss": 0.4665,
+ "step": 4202
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5047643065012276e-05,
+ "loss": 0.497,
+ "step": 4203
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5045303534855524e-05,
+ "loss": 0.5008,
+ "step": 4204
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5042963634192667e-05,
+ "loss": 0.4908,
+ "step": 4205
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5040623363195535e-05,
+ "loss": 0.498,
+ "step": 4206
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5038282722035986e-05,
+ "loss": 0.4864,
+ "step": 4207
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5035941710885915e-05,
+ "loss": 0.5004,
+ "step": 4208
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5033600329917227e-05,
+ "loss": 0.5207,
+ "step": 4209
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5031258579301868e-05,
+ "loss": 0.4731,
+ "step": 4210
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5028916459211804e-05,
+ "loss": 0.4995,
+ "step": 4211
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5026573969819035e-05,
+ "loss": 0.4928,
+ "step": 4212
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.502423111129558e-05,
+ "loss": 0.4968,
+ "step": 4213
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5021887883813488e-05,
+ "loss": 0.4896,
+ "step": 4214
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.501954428754484e-05,
+ "loss": 0.4845,
+ "step": 4215
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5017200322661735e-05,
+ "loss": 0.4936,
+ "step": 4216
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5014855989336308e-05,
+ "loss": 0.4902,
+ "step": 4217
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5012511287740715e-05,
+ "loss": 0.4821,
+ "step": 4218
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5010166218047139e-05,
+ "loss": 0.4979,
+ "step": 4219
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.50078207804278e-05,
+ "loss": 0.4948,
+ "step": 4220
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5005474975054928e-05,
+ "loss": 0.4824,
+ "step": 4221
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5003128802100792e-05,
+ "loss": 0.4921,
+ "step": 4222
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.500078226173769e-05,
+ "loss": 0.4964,
+ "step": 4223
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4998435354137937e-05,
+ "loss": 0.4867,
+ "step": 4224
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4996088079473884e-05,
+ "loss": 0.4999,
+ "step": 4225
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4993740437917898e-05,
+ "loss": 0.5114,
+ "step": 4226
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4991392429642389e-05,
+ "loss": 0.4886,
+ "step": 4227
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.498904405481978e-05,
+ "loss": 0.4818,
+ "step": 4228
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4986695313622525e-05,
+ "loss": 0.5041,
+ "step": 4229
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4984346206223108e-05,
+ "loss": 0.4954,
+ "step": 4230
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4981996732794038e-05,
+ "loss": 0.494,
+ "step": 4231
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4979646893507847e-05,
+ "loss": 0.4941,
+ "step": 4232
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4977296688537101e-05,
+ "loss": 0.4994,
+ "step": 4233
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4974946118054392e-05,
+ "loss": 0.4972,
+ "step": 4234
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4972595182232328e-05,
+ "loss": 0.4681,
+ "step": 4235
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4970243881243558e-05,
+ "loss": 0.4936,
+ "step": 4236
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4967892215260751e-05,
+ "loss": 0.4879,
+ "step": 4237
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.49655401844566e-05,
+ "loss": 0.4786,
+ "step": 4238
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4963187789003835e-05,
+ "loss": 0.4921,
+ "step": 4239
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.49608350290752e-05,
+ "loss": 0.4926,
+ "step": 4240
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4958481904843473e-05,
+ "loss": 0.4689,
+ "step": 4241
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4956128416481459e-05,
+ "loss": 0.478,
+ "step": 4242
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4953774564161991e-05,
+ "loss": 0.4967,
+ "step": 4243
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.495142034805792e-05,
+ "loss": 0.4759,
+ "step": 4244
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4949065768342136e-05,
+ "loss": 0.4725,
+ "step": 4245
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4946710825187545e-05,
+ "loss": 0.4913,
+ "step": 4246
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4944355518767086e-05,
+ "loss": 0.4778,
+ "step": 4247
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4941999849253723e-05,
+ "loss": 0.4754,
+ "step": 4248
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4939643816820449e-05,
+ "loss": 0.4989,
+ "step": 4249
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4937287421640277e-05,
+ "loss": 0.4903,
+ "step": 4250
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.493493066388625e-05,
+ "loss": 0.4936,
+ "step": 4251
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4932573543731441e-05,
+ "loss": 0.4945,
+ "step": 4252
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.493021606134895e-05,
+ "loss": 0.5001,
+ "step": 4253
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4927858216911897e-05,
+ "loss": 0.4595,
+ "step": 4254
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.492550001059343e-05,
+ "loss": 0.4922,
+ "step": 4255
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4923141442566732e-05,
+ "loss": 0.4985,
+ "step": 4256
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4920782513005003e-05,
+ "loss": 0.5076,
+ "step": 4257
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4918423222081473e-05,
+ "loss": 0.5075,
+ "step": 4258
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4916063569969398e-05,
+ "loss": 0.5165,
+ "step": 4259
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4913703556842066e-05,
+ "loss": 0.4758,
+ "step": 4260
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.491134318287278e-05,
+ "loss": 0.4828,
+ "step": 4261
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4908982448234875e-05,
+ "loss": 0.4891,
+ "step": 4262
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.490662135310172e-05,
+ "loss": 0.4657,
+ "step": 4263
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.49042598976467e-05,
+ "loss": 0.5058,
+ "step": 4264
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4901898082043232e-05,
+ "loss": 0.4888,
+ "step": 4265
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4899535906464757e-05,
+ "loss": 0.4943,
+ "step": 4266
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4897173371084743e-05,
+ "loss": 0.4916,
+ "step": 4267
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4894810476076688e-05,
+ "loss": 0.4967,
+ "step": 4268
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.489244722161411e-05,
+ "loss": 0.5103,
+ "step": 4269
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4890083607870559e-05,
+ "loss": 0.4885,
+ "step": 4270
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4887719635019605e-05,
+ "loss": 0.5045,
+ "step": 4271
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.488535530323485e-05,
+ "loss": 0.4692,
+ "step": 4272
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4882990612689918e-05,
+ "loss": 0.5159,
+ "step": 4273
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.488062556355847e-05,
+ "loss": 0.4899,
+ "step": 4274
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4878260156014182e-05,
+ "loss": 0.4831,
+ "step": 4275
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4875894390230757e-05,
+ "loss": 0.4664,
+ "step": 4276
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4873528266381927e-05,
+ "loss": 0.4861,
+ "step": 4277
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.487116178464145e-05,
+ "loss": 0.4937,
+ "step": 4278
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4868794945183113e-05,
+ "loss": 0.4788,
+ "step": 4279
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4866427748180729e-05,
+ "loss": 0.4746,
+ "step": 4280
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4864060193808133e-05,
+ "loss": 0.5078,
+ "step": 4281
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4861692282239181e-05,
+ "loss": 0.4726,
+ "step": 4282
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4859324013647773e-05,
+ "loss": 0.4855,
+ "step": 4283
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4856955388207821e-05,
+ "loss": 0.4965,
+ "step": 4284
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.485458640609327e-05,
+ "loss": 0.4585,
+ "step": 4285
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4852217067478082e-05,
+ "loss": 0.4939,
+ "step": 4286
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4849847372536252e-05,
+ "loss": 0.4907,
+ "step": 4287
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4847477321441806e-05,
+ "loss": 0.4992,
+ "step": 4288
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4845106914368786e-05,
+ "loss": 0.4741,
+ "step": 4289
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4842736151491268e-05,
+ "loss": 0.5102,
+ "step": 4290
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.484036503298335e-05,
+ "loss": 0.4947,
+ "step": 4291
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4837993559019157e-05,
+ "loss": 0.5033,
+ "step": 4292
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4835621729772838e-05,
+ "loss": 0.4976,
+ "step": 4293
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4833249545418572e-05,
+ "loss": 0.4881,
+ "step": 4294
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4830877006130561e-05,
+ "loss": 0.4842,
+ "step": 4295
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4828504112083038e-05,
+ "loss": 0.5006,
+ "step": 4296
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4826130863450257e-05,
+ "loss": 0.4883,
+ "step": 4297
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4823757260406498e-05,
+ "loss": 0.4763,
+ "step": 4298
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4821383303126067e-05,
+ "loss": 0.4734,
+ "step": 4299
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.48190089917833e-05,
+ "loss": 0.5042,
+ "step": 4300
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4816634326552561e-05,
+ "loss": 0.4874,
+ "step": 4301
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.481425930760823e-05,
+ "loss": 0.4944,
+ "step": 4302
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4811883935124716e-05,
+ "loss": 0.512,
+ "step": 4303
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.480950820927646e-05,
+ "loss": 0.5002,
+ "step": 4304
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.480713213023793e-05,
+ "loss": 0.4948,
+ "step": 4305
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4804755698183606e-05,
+ "loss": 0.4853,
+ "step": 4306
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4802378913288009e-05,
+ "loss": 0.4656,
+ "step": 4307
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4800001775725684e-05,
+ "loss": 0.4808,
+ "step": 4308
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4797624285671187e-05,
+ "loss": 0.4804,
+ "step": 4309
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4795246443299119e-05,
+ "loss": 0.4866,
+ "step": 4310
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4792868248784098e-05,
+ "loss": 0.5026,
+ "step": 4311
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4790489702300768e-05,
+ "loss": 0.4892,
+ "step": 4312
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4788110804023798e-05,
+ "loss": 0.4854,
+ "step": 4313
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4785731554127885e-05,
+ "loss": 0.4904,
+ "step": 4314
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4783351952787754e-05,
+ "loss": 0.4885,
+ "step": 4315
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4780972000178151e-05,
+ "loss": 0.4908,
+ "step": 4316
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.477859169647385e-05,
+ "loss": 0.4939,
+ "step": 4317
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4776211041849651e-05,
+ "loss": 0.4988,
+ "step": 4318
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4773830036480377e-05,
+ "loss": 0.4819,
+ "step": 4319
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4771448680540881e-05,
+ "loss": 0.4991,
+ "step": 4320
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4769066974206041e-05,
+ "loss": 0.4881,
+ "step": 4321
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.476668491765076e-05,
+ "loss": 0.511,
+ "step": 4322
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4764302511049962e-05,
+ "loss": 0.4744,
+ "step": 4323
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4761919754578603e-05,
+ "loss": 0.4949,
+ "step": 4324
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4759536648411668e-05,
+ "loss": 0.4802,
+ "step": 4325
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4757153192724154e-05,
+ "loss": 0.4845,
+ "step": 4326
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4754769387691096e-05,
+ "loss": 0.4661,
+ "step": 4327
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4752385233487554e-05,
+ "loss": 0.4855,
+ "step": 4328
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4750000730288605e-05,
+ "loss": 0.465,
+ "step": 4329
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4747615878269358e-05,
+ "loss": 0.4894,
+ "step": 4330
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.474523067760495e-05,
+ "loss": 0.5,
+ "step": 4331
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4742845128470538e-05,
+ "loss": 0.5042,
+ "step": 4332
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4740459231041306e-05,
+ "loss": 0.4949,
+ "step": 4333
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4738072985492462e-05,
+ "loss": 0.505,
+ "step": 4334
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4735686391999249e-05,
+ "loss": 0.4786,
+ "step": 4335
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4733299450736925e-05,
+ "loss": 0.482,
+ "step": 4336
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4730912161880772e-05,
+ "loss": 0.4861,
+ "step": 4337
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4728524525606111e-05,
+ "loss": 0.4779,
+ "step": 4338
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4726136542088277e-05,
+ "loss": 0.4865,
+ "step": 4339
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4723748211502628e-05,
+ "loss": 0.4938,
+ "step": 4340
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4721359534024562e-05,
+ "loss": 0.4721,
+ "step": 4341
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4718970509829489e-05,
+ "loss": 0.4929,
+ "step": 4342
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4716581139092851e-05,
+ "loss": 0.5027,
+ "step": 4343
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.471419142199011e-05,
+ "loss": 0.4993,
+ "step": 4344
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4711801358696755e-05,
+ "loss": 0.4877,
+ "step": 4345
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4709410949388311e-05,
+ "loss": 0.491,
+ "step": 4346
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4707020194240313e-05,
+ "loss": 0.5074,
+ "step": 4347
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4704629093428331e-05,
+ "loss": 0.5038,
+ "step": 4348
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4702237647127957e-05,
+ "loss": 0.4815,
+ "step": 4349
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4699845855514807e-05,
+ "loss": 0.5135,
+ "step": 4350
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4697453718764525e-05,
+ "loss": 0.4867,
+ "step": 4351
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4695061237052781e-05,
+ "loss": 0.5028,
+ "step": 4352
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4692668410555269e-05,
+ "loss": 0.5103,
+ "step": 4353
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4690275239447704e-05,
+ "loss": 0.486,
+ "step": 4354
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4687881723905834e-05,
+ "loss": 0.4773,
+ "step": 4355
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4685487864105431e-05,
+ "loss": 0.486,
+ "step": 4356
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4683093660222288e-05,
+ "loss": 0.502,
+ "step": 4357
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4680699112432223e-05,
+ "loss": 0.5118,
+ "step": 4358
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4678304220911086e-05,
+ "loss": 0.475,
+ "step": 4359
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4675908985834744e-05,
+ "loss": 0.4904,
+ "step": 4360
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4673513407379095e-05,
+ "loss": 0.494,
+ "step": 4361
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4671117485720058e-05,
+ "loss": 0.4699,
+ "step": 4362
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4668721221033586e-05,
+ "loss": 0.4813,
+ "step": 4363
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4666324613495641e-05,
+ "loss": 0.5052,
+ "step": 4364
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4663927663282228e-05,
+ "loss": 0.5067,
+ "step": 4365
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4661530370569366e-05,
+ "loss": 0.4903,
+ "step": 4366
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4659132735533104e-05,
+ "loss": 0.4757,
+ "step": 4367
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4656734758349509e-05,
+ "loss": 0.4849,
+ "step": 4368
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4654336439194686e-05,
+ "loss": 0.5033,
+ "step": 4369
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4651937778244748e-05,
+ "loss": 0.4794,
+ "step": 4370
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.464953877567585e-05,
+ "loss": 0.4982,
+ "step": 4371
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4647139431664167e-05,
+ "loss": 0.4785,
+ "step": 4372
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4644739746385894e-05,
+ "loss": 0.4746,
+ "step": 4373
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4642339720017249e-05,
+ "loss": 0.4791,
+ "step": 4374
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4639939352734484e-05,
+ "loss": 0.482,
+ "step": 4375
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4637538644713873e-05,
+ "loss": 0.4858,
+ "step": 4376
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4635137596131715e-05,
+ "loss": 0.4855,
+ "step": 4377
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4632736207164326e-05,
+ "loss": 0.4978,
+ "step": 4378
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4630334477988064e-05,
+ "loss": 0.4673,
+ "step": 4379
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4627932408779295e-05,
+ "loss": 0.4958,
+ "step": 4380
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4625529999714416e-05,
+ "loss": 0.5042,
+ "step": 4381
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4623127250969858e-05,
+ "loss": 0.4891,
+ "step": 4382
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4620724162722062e-05,
+ "loss": 0.5032,
+ "step": 4383
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4618320735147501e-05,
+ "loss": 0.4884,
+ "step": 4384
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4615916968422674e-05,
+ "loss": 0.4967,
+ "step": 4385
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4613512862724103e-05,
+ "loss": 0.4824,
+ "step": 4386
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4611108418228342e-05,
+ "loss": 0.4766,
+ "step": 4387
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.460870363511195e-05,
+ "loss": 0.4905,
+ "step": 4388
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.460629851355154e-05,
+ "loss": 0.4821,
+ "step": 4389
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.460389305372372e-05,
+ "loss": 0.4958,
+ "step": 4390
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4601487255805146e-05,
+ "loss": 0.4676,
+ "step": 4391
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4599081119972486e-05,
+ "loss": 0.501,
+ "step": 4392
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.459667464640244e-05,
+ "loss": 0.4787,
+ "step": 4393
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4594267835271725e-05,
+ "loss": 0.5029,
+ "step": 4394
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4591860686757089e-05,
+ "loss": 0.5047,
+ "step": 4395
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4589453201035302e-05,
+ "loss": 0.5009,
+ "step": 4396
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4587045378283162e-05,
+ "loss": 0.4818,
+ "step": 4397
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4584637218677488e-05,
+ "loss": 0.4601,
+ "step": 4398
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4582228722395128e-05,
+ "loss": 0.504,
+ "step": 4399
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4579819889612949e-05,
+ "loss": 0.4719,
+ "step": 4400
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4577410720507842e-05,
+ "loss": 0.5031,
+ "step": 4401
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4575001215256735e-05,
+ "loss": 0.4812,
+ "step": 4402
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4572591374036567e-05,
+ "loss": 0.4906,
+ "step": 4403
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4570181197024307e-05,
+ "loss": 0.4945,
+ "step": 4404
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4567770684396947e-05,
+ "loss": 0.4849,
+ "step": 4405
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.456535983633151e-05,
+ "loss": 0.4788,
+ "step": 4406
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4562948653005032e-05,
+ "loss": 0.4917,
+ "step": 4407
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4560537134594586e-05,
+ "loss": 0.4728,
+ "step": 4408
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.455812528127726e-05,
+ "loss": 0.4997,
+ "step": 4409
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4555713093230173e-05,
+ "loss": 0.493,
+ "step": 4410
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4553300570630464e-05,
+ "loss": 0.4758,
+ "step": 4411
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4550887713655297e-05,
+ "loss": 0.4887,
+ "step": 4412
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.454847452248187e-05,
+ "loss": 0.4892,
+ "step": 4413
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4546060997287392e-05,
+ "loss": 0.4678,
+ "step": 4414
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.45436471382491e-05,
+ "loss": 0.5012,
+ "step": 4415
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4541232945544263e-05,
+ "loss": 0.5001,
+ "step": 4416
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4538818419350164e-05,
+ "loss": 0.4674,
+ "step": 4417
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4536403559844123e-05,
+ "loss": 0.5016,
+ "step": 4418
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.453398836720347e-05,
+ "loss": 0.4768,
+ "step": 4419
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.453157284160557e-05,
+ "loss": 0.4941,
+ "step": 4420
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.452915698322781e-05,
+ "loss": 0.4916,
+ "step": 4421
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4526740792247597e-05,
+ "loss": 0.4901,
+ "step": 4422
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4524324268842369e-05,
+ "loss": 0.4863,
+ "step": 4423
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4521907413189587e-05,
+ "loss": 0.4917,
+ "step": 4424
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4519490225466733e-05,
+ "loss": 0.4962,
+ "step": 4425
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4517072705851312e-05,
+ "loss": 0.485,
+ "step": 4426
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.451465485452086e-05,
+ "loss": 0.4956,
+ "step": 4427
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4512236671652932e-05,
+ "loss": 0.4826,
+ "step": 4428
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4509818157425112e-05,
+ "loss": 0.4832,
+ "step": 4429
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4507399312015005e-05,
+ "loss": 0.4936,
+ "step": 4430
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4504980135600242e-05,
+ "loss": 0.4902,
+ "step": 4431
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4502560628358473e-05,
+ "loss": 0.4943,
+ "step": 4432
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4500140790467377e-05,
+ "loss": 0.4822,
+ "step": 4433
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.449772062210466e-05,
+ "loss": 0.4996,
+ "step": 4434
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.449530012344805e-05,
+ "loss": 0.5047,
+ "step": 4435
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4492879294675297e-05,
+ "loss": 0.4677,
+ "step": 4436
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4490458135964173e-05,
+ "loss": 0.4872,
+ "step": 4437
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4488036647492482e-05,
+ "loss": 0.4731,
+ "step": 4438
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4485614829438046e-05,
+ "loss": 0.4759,
+ "step": 4439
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4483192681978715e-05,
+ "loss": 0.4946,
+ "step": 4440
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4480770205292363e-05,
+ "loss": 0.4783,
+ "step": 4441
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4478347399556878e-05,
+ "loss": 0.4796,
+ "step": 4442
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.447592426495019e-05,
+ "loss": 0.495,
+ "step": 4443
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4473500801650243e-05,
+ "loss": 0.4885,
+ "step": 4444
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4471077009835001e-05,
+ "loss": 0.4771,
+ "step": 4445
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.446865288968246e-05,
+ "loss": 0.4934,
+ "step": 4446
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4466228441370638e-05,
+ "loss": 0.5003,
+ "step": 4447
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4463803665077573e-05,
+ "loss": 0.4921,
+ "step": 4448
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4461378560981335e-05,
+ "loss": 0.4844,
+ "step": 4449
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4458953129260014e-05,
+ "loss": 0.484,
+ "step": 4450
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4456527370091722e-05,
+ "loss": 0.477,
+ "step": 4451
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4454101283654594e-05,
+ "loss": 0.4759,
+ "step": 4452
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.445167487012679e-05,
+ "loss": 0.4673,
+ "step": 4453
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4449248129686504e-05,
+ "loss": 0.4975,
+ "step": 4454
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4446821062511942e-05,
+ "loss": 0.5007,
+ "step": 4455
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4444393668781334e-05,
+ "loss": 0.5061,
+ "step": 4456
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4441965948672943e-05,
+ "loss": 0.4783,
+ "step": 4457
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4439537902365047e-05,
+ "loss": 0.5025,
+ "step": 4458
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4437109530035951e-05,
+ "loss": 0.4762,
+ "step": 4459
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.443468083186399e-05,
+ "loss": 0.503,
+ "step": 4460
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.443225180802751e-05,
+ "loss": 0.4933,
+ "step": 4461
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4429822458704896e-05,
+ "loss": 0.4887,
+ "step": 4462
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4427392784074545e-05,
+ "loss": 0.4973,
+ "step": 4463
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.442496278431488e-05,
+ "loss": 0.5274,
+ "step": 4464
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4422532459604357e-05,
+ "loss": 0.4956,
+ "step": 4465
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.442010181012144e-05,
+ "loss": 0.4856,
+ "step": 4466
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4417670836044635e-05,
+ "loss": 0.5036,
+ "step": 4467
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4415239537552457e-05,
+ "loss": 0.5218,
+ "step": 4468
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4412807914823452e-05,
+ "loss": 0.4733,
+ "step": 4469
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4410375968036185e-05,
+ "loss": 0.4742,
+ "step": 4470
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4407943697369255e-05,
+ "loss": 0.4971,
+ "step": 4471
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4405511103001274e-05,
+ "loss": 0.4941,
+ "step": 4472
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.440307818511088e-05,
+ "loss": 0.4734,
+ "step": 4473
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4400644943876736e-05,
+ "loss": 0.494,
+ "step": 4474
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4398211379477534e-05,
+ "loss": 0.5102,
+ "step": 4475
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.439577749209198e-05,
+ "loss": 0.4926,
+ "step": 4476
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.439334328189881e-05,
+ "loss": 0.4995,
+ "step": 4477
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4390908749076787e-05,
+ "loss": 0.5003,
+ "step": 4478
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4388473893804683e-05,
+ "loss": 0.5023,
+ "step": 4479
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.438603871626131e-05,
+ "loss": 0.4786,
+ "step": 4480
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4383603216625499e-05,
+ "loss": 0.4957,
+ "step": 4481
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4381167395076101e-05,
+ "loss": 0.5121,
+ "step": 4482
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4378731251791989e-05,
+ "loss": 0.4638,
+ "step": 4483
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4376294786952067e-05,
+ "loss": 0.4954,
+ "step": 4484
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4373858000735262e-05,
+ "loss": 0.4954,
+ "step": 4485
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4371420893320515e-05,
+ "loss": 0.4881,
+ "step": 4486
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4368983464886799e-05,
+ "loss": 0.5036,
+ "step": 4487
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4366545715613112e-05,
+ "loss": 0.4723,
+ "step": 4488
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4364107645678465e-05,
+ "loss": 0.4846,
+ "step": 4489
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4361669255261905e-05,
+ "loss": 0.4819,
+ "step": 4490
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.43592305445425e-05,
+ "loss": 0.4875,
+ "step": 4491
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4356791513699334e-05,
+ "loss": 0.4895,
+ "step": 4492
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4354352162911522e-05,
+ "loss": 0.4762,
+ "step": 4493
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4351912492358196e-05,
+ "loss": 0.4905,
+ "step": 4494
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4349472502218515e-05,
+ "loss": 0.4592,
+ "step": 4495
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4347032192671668e-05,
+ "loss": 0.4966,
+ "step": 4496
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4344591563896857e-05,
+ "loss": 0.4847,
+ "step": 4497
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4342150616073312e-05,
+ "loss": 0.4795,
+ "step": 4498
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4339709349380285e-05,
+ "loss": 0.5128,
+ "step": 4499
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4337267763997054e-05,
+ "loss": 0.4757,
+ "step": 4500
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4334825860102917e-05,
+ "loss": 0.4912,
+ "step": 4501
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4332383637877203e-05,
+ "loss": 0.4773,
+ "step": 4502
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.432994109749925e-05,
+ "loss": 0.4955,
+ "step": 4503
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4327498239148434e-05,
+ "loss": 0.4786,
+ "step": 4504
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4325055063004145e-05,
+ "loss": 0.4953,
+ "step": 4505
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4322611569245806e-05,
+ "loss": 0.4892,
+ "step": 4506
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4320167758052848e-05,
+ "loss": 0.4917,
+ "step": 4507
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4317723629604743e-05,
+ "loss": 0.4832,
+ "step": 4508
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.431527918408097e-05,
+ "loss": 0.4878,
+ "step": 4509
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4312834421661044e-05,
+ "loss": 0.4948,
+ "step": 4510
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4310389342524494e-05,
+ "loss": 0.4869,
+ "step": 4511
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4307943946850883e-05,
+ "loss": 0.491,
+ "step": 4512
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4305498234819783e-05,
+ "loss": 0.4886,
+ "step": 4513
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4303052206610801e-05,
+ "loss": 0.4815,
+ "step": 4514
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4300605862403563e-05,
+ "loss": 0.4738,
+ "step": 4515
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4298159202377719e-05,
+ "loss": 0.5164,
+ "step": 4516
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4295712226712941e-05,
+ "loss": 0.4937,
+ "step": 4517
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4293264935588921e-05,
+ "loss": 0.4743,
+ "step": 4518
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4290817329185388e-05,
+ "loss": 0.4843,
+ "step": 4519
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.428836940768207e-05,
+ "loss": 0.4989,
+ "step": 4520
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4285921171258741e-05,
+ "loss": 0.4858,
+ "step": 4521
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4283472620095192e-05,
+ "loss": 0.477,
+ "step": 4522
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4281023754371226e-05,
+ "loss": 0.4741,
+ "step": 4523
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4278574574266681e-05,
+ "loss": 0.4952,
+ "step": 4524
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4276125079961417e-05,
+ "loss": 0.4953,
+ "step": 4525
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4273675271635313e-05,
+ "loss": 0.5021,
+ "step": 4526
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4271225149468272e-05,
+ "loss": 0.4825,
+ "step": 4527
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.426877471364022e-05,
+ "loss": 0.4693,
+ "step": 4528
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4266323964331112e-05,
+ "loss": 0.4788,
+ "step": 4529
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4263872901720914e-05,
+ "loss": 0.469,
+ "step": 4530
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4261421525989625e-05,
+ "loss": 0.4949,
+ "step": 4531
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4258969837317265e-05,
+ "loss": 0.4905,
+ "step": 4532
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4256517835883874e-05,
+ "loss": 0.488,
+ "step": 4533
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4254065521869519e-05,
+ "loss": 0.5049,
+ "step": 4534
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4251612895454282e-05,
+ "loss": 0.5057,
+ "step": 4535
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4249159956818279e-05,
+ "loss": 0.4912,
+ "step": 4536
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4246706706141646e-05,
+ "loss": 0.5032,
+ "step": 4537
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4244253143604531e-05,
+ "loss": 0.4765,
+ "step": 4538
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4241799269387122e-05,
+ "loss": 0.4854,
+ "step": 4539
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4239345083669615e-05,
+ "loss": 0.4815,
+ "step": 4540
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.423689058663224e-05,
+ "loss": 0.5124,
+ "step": 4541
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4234435778455242e-05,
+ "loss": 0.4851,
+ "step": 4542
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4231980659318891e-05,
+ "loss": 0.5049,
+ "step": 4543
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4229525229403486e-05,
+ "loss": 0.4756,
+ "step": 4544
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4227069488889338e-05,
+ "loss": 0.4865,
+ "step": 4545
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.422461343795679e-05,
+ "loss": 0.4887,
+ "step": 4546
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4222157076786201e-05,
+ "loss": 0.4804,
+ "step": 4547
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4219700405557958e-05,
+ "loss": 0.4999,
+ "step": 4548
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4217243424452466e-05,
+ "loss": 0.4974,
+ "step": 4549
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4214786133650162e-05,
+ "loss": 0.5029,
+ "step": 4550
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4212328533331493e-05,
+ "loss": 0.4983,
+ "step": 4551
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4209870623676934e-05,
+ "loss": 0.5079,
+ "step": 4552
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4207412404866992e-05,
+ "loss": 0.5062,
+ "step": 4553
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.420495387708218e-05,
+ "loss": 0.496,
+ "step": 4554
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4202495040503043e-05,
+ "loss": 0.5021,
+ "step": 4555
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4200035895310151e-05,
+ "loss": 0.492,
+ "step": 4556
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4197576441684096e-05,
+ "loss": 0.4871,
+ "step": 4557
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4195116679805483e-05,
+ "loss": 0.4845,
+ "step": 4558
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4192656609854949e-05,
+ "loss": 0.4746,
+ "step": 4559
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4190196232013154e-05,
+ "loss": 0.486,
+ "step": 4560
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4187735546460775e-05,
+ "loss": 0.4918,
+ "step": 4561
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4185274553378513e-05,
+ "loss": 0.5124,
+ "step": 4562
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.41828132529471e-05,
+ "loss": 0.4785,
+ "step": 4563
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4180351645347279e-05,
+ "loss": 0.4927,
+ "step": 4564
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.417788973075982e-05,
+ "loss": 0.5018,
+ "step": 4565
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4175427509365516e-05,
+ "loss": 0.4941,
+ "step": 4566
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.417296498134518e-05,
+ "loss": 0.4783,
+ "step": 4567
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4170502146879656e-05,
+ "loss": 0.5057,
+ "step": 4568
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4168039006149799e-05,
+ "loss": 0.5271,
+ "step": 4569
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4165575559336496e-05,
+ "loss": 0.4779,
+ "step": 4570
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4163111806620646e-05,
+ "loss": 0.4642,
+ "step": 4571
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.416064774818318e-05,
+ "loss": 0.5108,
+ "step": 4572
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4158183384205052e-05,
+ "loss": 0.4914,
+ "step": 4573
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4155718714867232e-05,
+ "loss": 0.4902,
+ "step": 4574
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4153253740350717e-05,
+ "loss": 0.4846,
+ "step": 4575
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4150788460836516e-05,
+ "loss": 0.4685,
+ "step": 4576
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4148322876505675e-05,
+ "loss": 0.4808,
+ "step": 4577
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4145856987539261e-05,
+ "loss": 0.4915,
+ "step": 4578
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.414339079411835e-05,
+ "loss": 0.4938,
+ "step": 4579
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4140924296424055e-05,
+ "loss": 0.4984,
+ "step": 4580
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4138457494637501e-05,
+ "loss": 0.4884,
+ "step": 4581
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4135990388939839e-05,
+ "loss": 0.4833,
+ "step": 4582
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4133522979512252e-05,
+ "loss": 0.4856,
+ "step": 4583
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4131055266535926e-05,
+ "loss": 0.4952,
+ "step": 4584
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4128587250192087e-05,
+ "loss": 0.5056,
+ "step": 4585
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.412611893066197e-05,
+ "loss": 0.4818,
+ "step": 4586
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4123650308126839e-05,
+ "loss": 0.4854,
+ "step": 4587
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4121181382767986e-05,
+ "loss": 0.4762,
+ "step": 4588
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4118712154766708e-05,
+ "loss": 0.4713,
+ "step": 4589
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4116242624304343e-05,
+ "loss": 0.4836,
+ "step": 4590
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.411377279156224e-05,
+ "loss": 0.4767,
+ "step": 4591
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4111302656721775e-05,
+ "loss": 0.4845,
+ "step": 4592
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.410883221996434e-05,
+ "loss": 0.4769,
+ "step": 4593
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.410636148147136e-05,
+ "loss": 0.4906,
+ "step": 4594
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4103890441424271e-05,
+ "loss": 0.4971,
+ "step": 4595
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4101419100004537e-05,
+ "loss": 0.481,
+ "step": 4596
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4098947457393641e-05,
+ "loss": 0.4774,
+ "step": 4597
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4096475513773097e-05,
+ "loss": 0.4893,
+ "step": 4598
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4094003269324428e-05,
+ "loss": 0.4874,
+ "step": 4599
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4091530724229188e-05,
+ "loss": 0.5024,
+ "step": 4600
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.408905787866895e-05,
+ "loss": 0.5141,
+ "step": 4601
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4086584732825306e-05,
+ "loss": 0.4768,
+ "step": 4602
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4084111286879878e-05,
+ "loss": 0.5029,
+ "step": 4603
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4081637541014306e-05,
+ "loss": 0.4939,
+ "step": 4604
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4079163495410248e-05,
+ "loss": 0.4798,
+ "step": 4605
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.407668915024939e-05,
+ "loss": 0.4618,
+ "step": 4606
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4074214505713437e-05,
+ "loss": 0.4803,
+ "step": 4607
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4071739561984115e-05,
+ "loss": 0.4847,
+ "step": 4608
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4069264319243178e-05,
+ "loss": 0.4754,
+ "step": 4609
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4066788777672393e-05,
+ "loss": 0.5171,
+ "step": 4610
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4064312937453556e-05,
+ "loss": 0.4757,
+ "step": 4611
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.406183679876848e-05,
+ "loss": 0.5263,
+ "step": 4612
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4059360361799004e-05,
+ "loss": 0.4928,
+ "step": 4613
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4056883626726989e-05,
+ "loss": 0.4916,
+ "step": 4614
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4054406593734316e-05,
+ "loss": 0.482,
+ "step": 4615
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4051929263002884e-05,
+ "loss": 0.4772,
+ "step": 4616
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.404945163471462e-05,
+ "loss": 0.4909,
+ "step": 4617
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4046973709051467e-05,
+ "loss": 0.4879,
+ "step": 4618
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4044495486195404e-05,
+ "loss": 0.492,
+ "step": 4619
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4042016966328411e-05,
+ "loss": 0.4755,
+ "step": 4620
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4039538149632508e-05,
+ "loss": 0.526,
+ "step": 4621
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4037059036289722e-05,
+ "loss": 0.4765,
+ "step": 4622
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4034579626482112e-05,
+ "loss": 0.4763,
+ "step": 4623
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4032099920391753e-05,
+ "loss": 0.4879,
+ "step": 4624
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.402961991820075e-05,
+ "loss": 0.4795,
+ "step": 4625
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4027139620091221e-05,
+ "loss": 0.4731,
+ "step": 4626
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4024659026245307e-05,
+ "loss": 0.4775,
+ "step": 4627
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4022178136845173e-05,
+ "loss": 0.5075,
+ "step": 4628
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4019696952073008e-05,
+ "loss": 0.4915,
+ "step": 4629
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4017215472111016e-05,
+ "loss": 0.4835,
+ "step": 4630
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.401473369714143e-05,
+ "loss": 0.4964,
+ "step": 4631
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.40122516273465e-05,
+ "loss": 0.4938,
+ "step": 4632
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4009769262908498e-05,
+ "loss": 0.4688,
+ "step": 4633
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4007286604009717e-05,
+ "loss": 0.4844,
+ "step": 4634
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.400480365083248e-05,
+ "loss": 0.5028,
+ "step": 4635
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.400232040355912e-05,
+ "loss": 0.4694,
+ "step": 4636
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3999836862371992e-05,
+ "loss": 0.5068,
+ "step": 4637
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3997353027453484e-05,
+ "loss": 0.526,
+ "step": 4638
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3994868898985996e-05,
+ "loss": 0.5087,
+ "step": 4639
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.399238447715195e-05,
+ "loss": 0.4647,
+ "step": 4640
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3989899762133797e-05,
+ "loss": 0.5089,
+ "step": 4641
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3987414754114e-05,
+ "loss": 0.477,
+ "step": 4642
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3984929453275045e-05,
+ "loss": 0.4633,
+ "step": 4643
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3982443859799446e-05,
+ "loss": 0.4792,
+ "step": 4644
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3979957973869738e-05,
+ "loss": 0.508,
+ "step": 4645
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.397747179566847e-05,
+ "loss": 0.4722,
+ "step": 4646
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3974985325378215e-05,
+ "loss": 0.4924,
+ "step": 4647
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.397249856318157e-05,
+ "loss": 0.4871,
+ "step": 4648
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3970011509261155e-05,
+ "loss": 0.4978,
+ "step": 4649
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3967524163799606e-05,
+ "loss": 0.4922,
+ "step": 4650
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3965036526979586e-05,
+ "loss": 0.4957,
+ "step": 4651
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3962548598983774e-05,
+ "loss": 0.4908,
+ "step": 4652
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3960060379994875e-05,
+ "loss": 0.489,
+ "step": 4653
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.395757187019561e-05,
+ "loss": 0.4736,
+ "step": 4654
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3955083069768733e-05,
+ "loss": 0.4822,
+ "step": 4655
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3952593978897002e-05,
+ "loss": 0.4798,
+ "step": 4656
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3950104597763212e-05,
+ "loss": 0.4925,
+ "step": 4657
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3947614926550168e-05,
+ "loss": 0.4817,
+ "step": 4658
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3945124965440701e-05,
+ "loss": 0.4935,
+ "step": 4659
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3942634714617671e-05,
+ "loss": 0.5021,
+ "step": 4660
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3940144174263943e-05,
+ "loss": 0.492,
+ "step": 4661
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3937653344562417e-05,
+ "loss": 0.4698,
+ "step": 4662
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3935162225696006e-05,
+ "loss": 0.4974,
+ "step": 4663
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3932670817847647e-05,
+ "loss": 0.4825,
+ "step": 4664
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3930179121200303e-05,
+ "loss": 0.4825,
+ "step": 4665
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.392768713593695e-05,
+ "loss": 0.4866,
+ "step": 4666
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3925194862240589e-05,
+ "loss": 0.498,
+ "step": 4667
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3922702300294246e-05,
+ "loss": 0.4945,
+ "step": 4668
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3920209450280959e-05,
+ "loss": 0.4962,
+ "step": 4669
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3917716312383797e-05,
+ "loss": 0.4794,
+ "step": 4670
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3915222886785844e-05,
+ "loss": 0.4718,
+ "step": 4671
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3912729173670207e-05,
+ "loss": 0.485,
+ "step": 4672
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3910235173220015e-05,
+ "loss": 0.4924,
+ "step": 4673
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3907740885618415e-05,
+ "loss": 0.4844,
+ "step": 4674
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3905246311048575e-05,
+ "loss": 0.4807,
+ "step": 4675
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3902751449693693e-05,
+ "loss": 0.4933,
+ "step": 4676
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3900256301736976e-05,
+ "loss": 0.4699,
+ "step": 4677
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3897760867361657e-05,
+ "loss": 0.4775,
+ "step": 4678
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3895265146750994e-05,
+ "loss": 0.4956,
+ "step": 4679
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3892769140088259e-05,
+ "loss": 0.4707,
+ "step": 4680
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3890272847556747e-05,
+ "loss": 0.4774,
+ "step": 4681
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3887776269339783e-05,
+ "loss": 0.4832,
+ "step": 4682
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38852794056207e-05,
+ "loss": 0.4933,
+ "step": 4683
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3882782256582852e-05,
+ "loss": 0.4934,
+ "step": 4684
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.388028482240963e-05,
+ "loss": 0.4822,
+ "step": 4685
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3877787103284428e-05,
+ "loss": 0.4891,
+ "step": 4686
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3875289099390672e-05,
+ "loss": 0.4905,
+ "step": 4687
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38727908109118e-05,
+ "loss": 0.5032,
+ "step": 4688
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3870292238031283e-05,
+ "loss": 0.4791,
+ "step": 4689
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3867793380932597e-05,
+ "loss": 0.4809,
+ "step": 4690
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3865294239799254e-05,
+ "loss": 0.4697,
+ "step": 4691
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.386279481481478e-05,
+ "loss": 0.5101,
+ "step": 4692
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3860295106162722e-05,
+ "loss": 0.477,
+ "step": 4693
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3857795114026648e-05,
+ "loss": 0.4973,
+ "step": 4694
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3855294838590143e-05,
+ "loss": 0.4843,
+ "step": 4695
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3852794280036823e-05,
+ "loss": 0.4937,
+ "step": 4696
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3850293438550317e-05,
+ "loss": 0.481,
+ "step": 4697
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3847792314314272e-05,
+ "loss": 0.4813,
+ "step": 4698
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3845290907512367e-05,
+ "loss": 0.4771,
+ "step": 4699
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3842789218328289e-05,
+ "loss": 0.5068,
+ "step": 4700
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3840287246945759e-05,
+ "loss": 0.4914,
+ "step": 4701
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38377849935485e-05,
+ "loss": 0.4749,
+ "step": 4702
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3835282458320278e-05,
+ "loss": 0.4946,
+ "step": 4703
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3832779641444864e-05,
+ "loss": 0.4967,
+ "step": 4704
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3830276543106053e-05,
+ "loss": 0.4846,
+ "step": 4705
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3827773163487663e-05,
+ "loss": 0.4776,
+ "step": 4706
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3825269502773538e-05,
+ "loss": 0.505,
+ "step": 4707
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3822765561147529e-05,
+ "loss": 0.465,
+ "step": 4708
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3820261338793515e-05,
+ "loss": 0.4896,
+ "step": 4709
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3817756835895399e-05,
+ "loss": 0.5086,
+ "step": 4710
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38152520526371e-05,
+ "loss": 0.5081,
+ "step": 4711
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3812746989202559e-05,
+ "loss": 0.4698,
+ "step": 4712
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3810241645775738e-05,
+ "loss": 0.497,
+ "step": 4713
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.380773602254062e-05,
+ "loss": 0.4849,
+ "step": 4714
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3805230119681203e-05,
+ "loss": 0.4766,
+ "step": 4715
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3802723937381512e-05,
+ "loss": 0.4944,
+ "step": 4716
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3800217475825597e-05,
+ "loss": 0.489,
+ "step": 4717
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3797710735197516e-05,
+ "loss": 0.4637,
+ "step": 4718
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.379520371568135e-05,
+ "loss": 0.482,
+ "step": 4719
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3792696417461213e-05,
+ "loss": 0.5144,
+ "step": 4720
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3790188840721223e-05,
+ "loss": 0.4927,
+ "step": 4721
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.378768098564553e-05,
+ "loss": 0.4736,
+ "step": 4722
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3785172852418303e-05,
+ "loss": 0.4891,
+ "step": 4723
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3782664441223724e-05,
+ "loss": 0.495,
+ "step": 4724
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3780155752246e-05,
+ "loss": 0.4943,
+ "step": 4725
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3777646785669357e-05,
+ "loss": 0.4907,
+ "step": 4726
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3775137541678052e-05,
+ "loss": 0.4822,
+ "step": 4727
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3772628020456346e-05,
+ "loss": 0.4896,
+ "step": 4728
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3770118222188529e-05,
+ "loss": 0.4812,
+ "step": 4729
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3767608147058913e-05,
+ "loss": 0.4859,
+ "step": 4730
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3765097795251822e-05,
+ "loss": 0.4721,
+ "step": 4731
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.376258716695161e-05,
+ "loss": 0.4959,
+ "step": 4732
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.376007626234265e-05,
+ "loss": 0.4818,
+ "step": 4733
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3757565081609327e-05,
+ "loss": 0.4732,
+ "step": 4734
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3755053624936055e-05,
+ "loss": 0.4902,
+ "step": 4735
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.375254189250726e-05,
+ "loss": 0.4942,
+ "step": 4736
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3750029884507394e-05,
+ "loss": 0.4723,
+ "step": 4737
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3747517601120934e-05,
+ "loss": 0.5007,
+ "step": 4738
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3745005042532369e-05,
+ "loss": 0.5025,
+ "step": 4739
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.374249220892621e-05,
+ "loss": 0.4768,
+ "step": 4740
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3739979100486986e-05,
+ "loss": 0.494,
+ "step": 4741
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3737465717399259e-05,
+ "loss": 0.5006,
+ "step": 4742
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3734952059847589e-05,
+ "loss": 0.4787,
+ "step": 4743
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3732438128016578e-05,
+ "loss": 0.486,
+ "step": 4744
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3729923922090836e-05,
+ "loss": 0.5041,
+ "step": 4745
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3727409442254994e-05,
+ "loss": 0.4867,
+ "step": 4746
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3724894688693704e-05,
+ "loss": 0.5076,
+ "step": 4747
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3722379661591643e-05,
+ "loss": 0.5011,
+ "step": 4748
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3719864361133502e-05,
+ "loss": 0.4931,
+ "step": 4749
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3717348787503993e-05,
+ "loss": 0.4803,
+ "step": 4750
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3714832940887854e-05,
+ "loss": 0.4869,
+ "step": 4751
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3712316821469831e-05,
+ "loss": 0.4963,
+ "step": 4752
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3709800429434702e-05,
+ "loss": 0.4769,
+ "step": 4753
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.370728376496726e-05,
+ "loss": 0.477,
+ "step": 4754
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3704766828252321e-05,
+ "loss": 0.5086,
+ "step": 4755
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3702249619474712e-05,
+ "loss": 0.4896,
+ "step": 4756
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.369973213881929e-05,
+ "loss": 0.4693,
+ "step": 4757
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3697214386470932e-05,
+ "loss": 0.4847,
+ "step": 4758
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3694696362614524e-05,
+ "loss": 0.4807,
+ "step": 4759
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3692178067434982e-05,
+ "loss": 0.4717,
+ "step": 4760
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3689659501117243e-05,
+ "loss": 0.4815,
+ "step": 4761
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3687140663846252e-05,
+ "loss": 0.4829,
+ "step": 4762
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3684621555806988e-05,
+ "loss": 0.4869,
+ "step": 4763
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3682102177184444e-05,
+ "loss": 0.4915,
+ "step": 4764
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3679582528163633e-05,
+ "loss": 0.4821,
+ "step": 4765
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3677062608929583e-05,
+ "loss": 0.4984,
+ "step": 4766
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3674542419667347e-05,
+ "loss": 0.4911,
+ "step": 4767
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3672021960562001e-05,
+ "loss": 0.4761,
+ "step": 4768
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3669501231798638e-05,
+ "loss": 0.4801,
+ "step": 4769
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3666980233562364e-05,
+ "loss": 0.5164,
+ "step": 4770
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3664458966038314e-05,
+ "loss": 0.4852,
+ "step": 4771
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.366193742941164e-05,
+ "loss": 0.4944,
+ "step": 4772
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.365941562386751e-05,
+ "loss": 0.4886,
+ "step": 4773
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3656893549591121e-05,
+ "loss": 0.4837,
+ "step": 4774
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3654371206767678e-05,
+ "loss": 0.4903,
+ "step": 4775
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3651848595582416e-05,
+ "loss": 0.4611,
+ "step": 4776
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3649325716220579e-05,
+ "loss": 0.4914,
+ "step": 4777
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.364680256886744e-05,
+ "loss": 0.4672,
+ "step": 4778
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.364427915370829e-05,
+ "loss": 0.4768,
+ "step": 4779
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3641755470928435e-05,
+ "loss": 0.4871,
+ "step": 4780
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3639231520713207e-05,
+ "loss": 0.4953,
+ "step": 4781
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3636707303247953e-05,
+ "loss": 0.4642,
+ "step": 4782
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.363418281871804e-05,
+ "loss": 0.5042,
+ "step": 4783
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3631658067308857e-05,
+ "loss": 0.485,
+ "step": 4784
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.362913304920581e-05,
+ "loss": 0.4988,
+ "step": 4785
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3626607764594329e-05,
+ "loss": 0.4921,
+ "step": 4786
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3624082213659854e-05,
+ "loss": 0.5012,
+ "step": 4787
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3621556396587856e-05,
+ "loss": 0.4926,
+ "step": 4788
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3619030313563821e-05,
+ "loss": 0.4879,
+ "step": 4789
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3616503964773252e-05,
+ "loss": 0.4911,
+ "step": 4790
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3613977350401675e-05,
+ "loss": 0.4665,
+ "step": 4791
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3611450470634631e-05,
+ "loss": 0.4938,
+ "step": 4792
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3608923325657686e-05,
+ "loss": 0.4847,
+ "step": 4793
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3606395915656423e-05,
+ "loss": 0.5109,
+ "step": 4794
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3603868240816445e-05,
+ "loss": 0.4765,
+ "step": 4795
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3601340301323371e-05,
+ "loss": 0.4859,
+ "step": 4796
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3598812097362846e-05,
+ "loss": 0.505,
+ "step": 4797
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3596283629120527e-05,
+ "loss": 0.5041,
+ "step": 4798
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3593754896782099e-05,
+ "loss": 0.4924,
+ "step": 4799
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.359122590053326e-05,
+ "loss": 0.467,
+ "step": 4800
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3588696640559725e-05,
+ "loss": 0.5029,
+ "step": 4801
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3586167117047238e-05,
+ "loss": 0.4932,
+ "step": 4802
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.358363733018155e-05,
+ "loss": 0.4759,
+ "step": 4803
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3581107280148443e-05,
+ "loss": 0.5209,
+ "step": 4804
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3578576967133712e-05,
+ "loss": 0.4676,
+ "step": 4805
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3576046391323176e-05,
+ "loss": 0.4666,
+ "step": 4806
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3573515552902663e-05,
+ "loss": 0.4912,
+ "step": 4807
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3570984452058035e-05,
+ "loss": 0.4882,
+ "step": 4808
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.356845308897516e-05,
+ "loss": 0.475,
+ "step": 4809
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3565921463839934e-05,
+ "loss": 0.4938,
+ "step": 4810
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3563389576838264e-05,
+ "loss": 0.4858,
+ "step": 4811
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3560857428156086e-05,
+ "loss": 0.4817,
+ "step": 4812
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.355832501797935e-05,
+ "loss": 0.5182,
+ "step": 4813
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3555792346494023e-05,
+ "loss": 0.5071,
+ "step": 4814
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.35532594138861e-05,
+ "loss": 0.486,
+ "step": 4815
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.355072622034158e-05,
+ "loss": 0.4677,
+ "step": 4816
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3548192766046499e-05,
+ "loss": 0.4871,
+ "step": 4817
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3545659051186897e-05,
+ "loss": 0.505,
+ "step": 4818
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3543125075948842e-05,
+ "loss": 0.4679,
+ "step": 4819
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.354059084051842e-05,
+ "loss": 0.518,
+ "step": 4820
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3538056345081729e-05,
+ "loss": 0.4902,
+ "step": 4821
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.35355215898249e-05,
+ "loss": 0.4813,
+ "step": 4822
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3532986574934071e-05,
+ "loss": 0.4975,
+ "step": 4823
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.35304513005954e-05,
+ "loss": 0.4795,
+ "step": 4824
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.352791576699507e-05,
+ "loss": 0.4782,
+ "step": 4825
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3525379974319282e-05,
+ "loss": 0.491,
+ "step": 4826
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.352284392275425e-05,
+ "loss": 0.4788,
+ "step": 4827
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3520307612486211e-05,
+ "loss": 0.4711,
+ "step": 4828
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3517771043701427e-05,
+ "loss": 0.4901,
+ "step": 4829
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3515234216586169e-05,
+ "loss": 0.4877,
+ "step": 4830
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3512697131326726e-05,
+ "loss": 0.4863,
+ "step": 4831
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.351015978810942e-05,
+ "loss": 0.4971,
+ "step": 4832
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3507622187120582e-05,
+ "loss": 0.4835,
+ "step": 4833
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3505084328546554e-05,
+ "loss": 0.4859,
+ "step": 4834
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3502546212573715e-05,
+ "loss": 0.4858,
+ "step": 4835
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.350000783938845e-05,
+ "loss": 0.4833,
+ "step": 4836
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3497469209177166e-05,
+ "loss": 0.4879,
+ "step": 4837
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.349493032212629e-05,
+ "loss": 0.4848,
+ "step": 4838
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3492391178422271e-05,
+ "loss": 0.4863,
+ "step": 4839
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3489851778251563e-05,
+ "loss": 0.48,
+ "step": 4840
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3487312121800661e-05,
+ "loss": 0.4777,
+ "step": 4841
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3484772209256061e-05,
+ "loss": 0.4783,
+ "step": 4842
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3482232040804286e-05,
+ "loss": 0.5042,
+ "step": 4843
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3479691616631869e-05,
+ "loss": 0.4642,
+ "step": 4844
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3477150936925374e-05,
+ "loss": 0.4839,
+ "step": 4845
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3474610001871379e-05,
+ "loss": 0.4922,
+ "step": 4846
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3472068811656477e-05,
+ "loss": 0.4956,
+ "step": 4847
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3469527366467281e-05,
+ "loss": 0.479,
+ "step": 4848
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3466985666490428e-05,
+ "loss": 0.502,
+ "step": 4849
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3464443711912566e-05,
+ "loss": 0.4734,
+ "step": 4850
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3461901502920371e-05,
+ "loss": 0.4976,
+ "step": 4851
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3459359039700525e-05,
+ "loss": 0.4828,
+ "step": 4852
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3456816322439742e-05,
+ "loss": 0.488,
+ "step": 4853
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3454273351324747e-05,
+ "loss": 0.4822,
+ "step": 4854
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.345173012654228e-05,
+ "loss": 0.4855,
+ "step": 4855
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3449186648279114e-05,
+ "loss": 0.4978,
+ "step": 4856
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3446642916722027e-05,
+ "loss": 0.4827,
+ "step": 4857
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3444098932057818e-05,
+ "loss": 0.5126,
+ "step": 4858
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3441554694473307e-05,
+ "loss": 0.4707,
+ "step": 4859
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3439010204155334e-05,
+ "loss": 0.5114,
+ "step": 4860
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3436465461290757e-05,
+ "loss": 0.5015,
+ "step": 4861
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.343392046606645e-05,
+ "loss": 0.4831,
+ "step": 4862
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3431375218669307e-05,
+ "loss": 0.4898,
+ "step": 4863
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.342882971928624e-05,
+ "loss": 0.4893,
+ "step": 4864
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3426283968104178e-05,
+ "loss": 0.4799,
+ "step": 4865
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3423737965310073e-05,
+ "loss": 0.4845,
+ "step": 4866
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3421191711090895e-05,
+ "loss": 0.4986,
+ "step": 4867
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3418645205633625e-05,
+ "loss": 0.4814,
+ "step": 4868
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.341609844912527e-05,
+ "loss": 0.4772,
+ "step": 4869
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3413551441752855e-05,
+ "loss": 0.4904,
+ "step": 4870
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.341100418370342e-05,
+ "loss": 0.4926,
+ "step": 4871
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3408456675164023e-05,
+ "loss": 0.4714,
+ "step": 4872
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3405908916321748e-05,
+ "loss": 0.471,
+ "step": 4873
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3403360907363687e-05,
+ "loss": 0.5065,
+ "step": 4874
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3400812648476956e-05,
+ "loss": 0.4832,
+ "step": 4875
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3398264139848687e-05,
+ "loss": 0.4877,
+ "step": 4876
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3395715381666038e-05,
+ "loss": 0.4762,
+ "step": 4877
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3393166374116175e-05,
+ "loss": 0.4868,
+ "step": 4878
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3390617117386285e-05,
+ "loss": 0.4823,
+ "step": 4879
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3388067611663578e-05,
+ "loss": 0.4737,
+ "step": 4880
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3385517857135274e-05,
+ "loss": 0.4901,
+ "step": 4881
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3382967853988623e-05,
+ "loss": 0.4653,
+ "step": 4882
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3380417602410884e-05,
+ "loss": 0.4864,
+ "step": 4883
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3377867102589336e-05,
+ "loss": 0.4931,
+ "step": 4884
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3375316354711277e-05,
+ "loss": 0.4761,
+ "step": 4885
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3372765358964024e-05,
+ "loss": 0.489,
+ "step": 4886
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3370214115534912e-05,
+ "loss": 0.4897,
+ "step": 4887
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3367662624611293e-05,
+ "loss": 0.4856,
+ "step": 4888
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3365110886380537e-05,
+ "loss": 0.5125,
+ "step": 4889
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3362558901030035e-05,
+ "loss": 0.4959,
+ "step": 4890
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3360006668747195e-05,
+ "loss": 0.4597,
+ "step": 4891
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3357454189719437e-05,
+ "loss": 0.5056,
+ "step": 4892
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3354901464134208e-05,
+ "loss": 0.4856,
+ "step": 4893
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3352348492178972e-05,
+ "loss": 0.4788,
+ "step": 4894
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3349795274041208e-05,
+ "loss": 0.4858,
+ "step": 4895
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3347241809908408e-05,
+ "loss": 0.4982,
+ "step": 4896
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3344688099968092e-05,
+ "loss": 0.4558,
+ "step": 4897
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3342134144407796e-05,
+ "loss": 0.482,
+ "step": 4898
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3339579943415069e-05,
+ "loss": 0.5045,
+ "step": 4899
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.333702549717748e-05,
+ "loss": 0.4684,
+ "step": 4900
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3334470805882615e-05,
+ "loss": 0.4804,
+ "step": 4901
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3331915869718088e-05,
+ "loss": 0.4914,
+ "step": 4902
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3329360688871518e-05,
+ "loss": 0.4885,
+ "step": 4903
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3326805263530545e-05,
+ "loss": 0.4959,
+ "step": 4904
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3324249593882832e-05,
+ "loss": 0.4996,
+ "step": 4905
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3321693680116054e-05,
+ "loss": 0.4728,
+ "step": 4906
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3319137522417908e-05,
+ "loss": 0.4861,
+ "step": 4907
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3316581120976109e-05,
+ "loss": 0.4854,
+ "step": 4908
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3314024475978388e-05,
+ "loss": 0.4933,
+ "step": 4909
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.331146758761249e-05,
+ "loss": 0.4676,
+ "step": 4910
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3308910456066191e-05,
+ "loss": 0.4983,
+ "step": 4911
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3306353081527265e-05,
+ "loss": 0.5059,
+ "step": 4912
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3303795464183522e-05,
+ "loss": 0.4859,
+ "step": 4913
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3301237604222786e-05,
+ "loss": 0.5003,
+ "step": 4914
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.329867950183289e-05,
+ "loss": 0.4709,
+ "step": 4915
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3296121157201689e-05,
+ "loss": 0.5096,
+ "step": 4916
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.329356257051706e-05,
+ "loss": 0.4888,
+ "step": 4917
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3291003741966898e-05,
+ "loss": 0.4876,
+ "step": 4918
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3288444671739106e-05,
+ "loss": 0.4887,
+ "step": 4919
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3285885360021615e-05,
+ "loss": 0.4732,
+ "step": 4920
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3283325807002374e-05,
+ "loss": 0.4874,
+ "step": 4921
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3280766012869338e-05,
+ "loss": 0.4845,
+ "step": 4922
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3278205977810492e-05,
+ "loss": 0.4866,
+ "step": 4923
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3275645702013836e-05,
+ "loss": 0.4692,
+ "step": 4924
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3273085185667385e-05,
+ "loss": 0.4743,
+ "step": 4925
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.327052442895917e-05,
+ "loss": 0.4811,
+ "step": 4926
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3267963432077242e-05,
+ "loss": 0.4902,
+ "step": 4927
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3265402195209675e-05,
+ "loss": 0.475,
+ "step": 4928
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3262840718544552e-05,
+ "loss": 0.4967,
+ "step": 4929
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3260279002269977e-05,
+ "loss": 0.4948,
+ "step": 4930
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3257717046574074e-05,
+ "loss": 0.467,
+ "step": 4931
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.325515485164498e-05,
+ "loss": 0.4723,
+ "step": 4932
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3252592417670856e-05,
+ "loss": 0.4997,
+ "step": 4933
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3250029744839867e-05,
+ "loss": 0.4764,
+ "step": 4934
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3247466833340216e-05,
+ "loss": 0.492,
+ "step": 4935
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.324490368336011e-05,
+ "loss": 0.4627,
+ "step": 4936
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.324234029508777e-05,
+ "loss": 0.484,
+ "step": 4937
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3239776668711444e-05,
+ "loss": 0.4789,
+ "step": 4938
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3237212804419398e-05,
+ "loss": 0.4715,
+ "step": 4939
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3234648702399903e-05,
+ "loss": 0.4995,
+ "step": 4940
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3232084362841267e-05,
+ "loss": 0.4747,
+ "step": 4941
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3229519785931795e-05,
+ "loss": 0.4898,
+ "step": 4942
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3226954971859827e-05,
+ "loss": 0.5059,
+ "step": 4943
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3224389920813703e-05,
+ "loss": 0.4816,
+ "step": 4944
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3221824632981797e-05,
+ "loss": 0.474,
+ "step": 4945
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3219259108552488e-05,
+ "loss": 0.4707,
+ "step": 4946
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3216693347714183e-05,
+ "loss": 0.4751,
+ "step": 4947
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3214127350655294e-05,
+ "loss": 0.4763,
+ "step": 4948
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3211561117564267e-05,
+ "loss": 0.517,
+ "step": 4949
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3208994648629546e-05,
+ "loss": 0.4788,
+ "step": 4950
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3206427944039604e-05,
+ "loss": 0.4886,
+ "step": 4951
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3203861003982933e-05,
+ "loss": 0.4797,
+ "step": 4952
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3201293828648032e-05,
+ "loss": 0.4796,
+ "step": 4953
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3198726418223428e-05,
+ "loss": 0.4591,
+ "step": 4954
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3196158772897663e-05,
+ "loss": 0.4763,
+ "step": 4955
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3193590892859291e-05,
+ "loss": 0.4906,
+ "step": 4956
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3191022778296887e-05,
+ "loss": 0.492,
+ "step": 4957
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.318845442939904e-05,
+ "loss": 0.4808,
+ "step": 4958
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3185885846354365e-05,
+ "loss": 0.495,
+ "step": 4959
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3183317029351483e-05,
+ "loss": 0.4769,
+ "step": 4960
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3180747978579039e-05,
+ "loss": 0.4781,
+ "step": 4961
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3178178694225695e-05,
+ "loss": 0.4663,
+ "step": 4962
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3175609176480122e-05,
+ "loss": 0.4681,
+ "step": 4963
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.317303942553102e-05,
+ "loss": 0.4945,
+ "step": 4964
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3170469441567104e-05,
+ "loss": 0.47,
+ "step": 4965
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3167899224777098e-05,
+ "loss": 0.4708,
+ "step": 4966
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.316532877534975e-05,
+ "loss": 0.5071,
+ "step": 4967
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.316275809347382e-05,
+ "loss": 0.4788,
+ "step": 4968
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.316018717933809e-05,
+ "loss": 0.4694,
+ "step": 4969
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3157616033131361e-05,
+ "loss": 0.4749,
+ "step": 4970
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.315504465504244e-05,
+ "loss": 0.4792,
+ "step": 4971
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3152473045260168e-05,
+ "loss": 0.4936,
+ "step": 4972
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3149901203973383e-05,
+ "loss": 0.5079,
+ "step": 4973
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3147329131370956e-05,
+ "loss": 0.4884,
+ "step": 4974
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3144756827641769e-05,
+ "loss": 0.4967,
+ "step": 4975
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3142184292974723e-05,
+ "loss": 0.48,
+ "step": 4976
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3139611527558729e-05,
+ "loss": 0.502,
+ "step": 4977
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3137038531582721e-05,
+ "loss": 0.4875,
+ "step": 4978
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3134465305235653e-05,
+ "loss": 0.4827,
+ "step": 4979
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3131891848706492e-05,
+ "loss": 0.479,
+ "step": 4980
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3129318162184216e-05,
+ "loss": 0.4702,
+ "step": 4981
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3126744245857835e-05,
+ "loss": 0.4727,
+ "step": 4982
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.312417009991636e-05,
+ "loss": 0.4882,
+ "step": 4983
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3121595724548825e-05,
+ "loss": 0.4865,
+ "step": 4984
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3119021119944287e-05,
+ "loss": 0.4924,
+ "step": 4985
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3116446286291811e-05,
+ "loss": 0.499,
+ "step": 4986
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3113871223780481e-05,
+ "loss": 0.4787,
+ "step": 4987
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3111295932599396e-05,
+ "loss": 0.478,
+ "step": 4988
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3108720412937681e-05,
+ "loss": 0.4822,
+ "step": 4989
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3106144664984473e-05,
+ "loss": 0.4804,
+ "step": 4990
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3103568688928917e-05,
+ "loss": 0.4707,
+ "step": 4991
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3100992484960185e-05,
+ "loss": 0.4968,
+ "step": 4992
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3098416053267463e-05,
+ "loss": 0.4693,
+ "step": 4993
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3095839394039953e-05,
+ "loss": 0.4758,
+ "step": 4994
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3093262507466873e-05,
+ "loss": 0.5018,
+ "step": 4995
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3090685393737464e-05,
+ "loss": 0.4784,
+ "step": 4996
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3088108053040974e-05,
+ "loss": 0.4755,
+ "step": 4997
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.308553048556667e-05,
+ "loss": 0.4867,
+ "step": 4998
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3082952691503843e-05,
+ "loss": 0.4803,
+ "step": 4999
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3080374671041793e-05,
+ "loss": 0.4798,
+ "step": 5000
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3077796424369842e-05,
+ "loss": 0.4852,
+ "step": 5001
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.307521795167732e-05,
+ "loss": 0.4841,
+ "step": 5002
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3072639253153583e-05,
+ "loss": 0.5082,
+ "step": 5003
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3070060328988e-05,
+ "loss": 0.4823,
+ "step": 5004
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3067481179369951e-05,
+ "loss": 0.4915,
+ "step": 5005
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.306490180448885e-05,
+ "loss": 0.5137,
+ "step": 5006
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3062322204534105e-05,
+ "loss": 0.509,
+ "step": 5007
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3059742379695158e-05,
+ "loss": 0.4846,
+ "step": 5008
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3057162330161453e-05,
+ "loss": 0.4945,
+ "step": 5009
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.305458205612246e-05,
+ "loss": 0.4883,
+ "step": 5010
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3052001557767671e-05,
+ "loss": 0.4953,
+ "step": 5011
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.304942083528658e-05,
+ "loss": 0.5003,
+ "step": 5012
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3046839888868706e-05,
+ "loss": 0.4656,
+ "step": 5013
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3044258718703581e-05,
+ "loss": 0.492,
+ "step": 5014
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.304167732498076e-05,
+ "loss": 0.4865,
+ "step": 5015
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3039095707889808e-05,
+ "loss": 0.486,
+ "step": 5016
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3036513867620309e-05,
+ "loss": 0.4977,
+ "step": 5017
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.303393180436186e-05,
+ "loss": 0.4894,
+ "step": 5018
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3031349518304078e-05,
+ "loss": 0.4717,
+ "step": 5019
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3028767009636593e-05,
+ "loss": 0.5052,
+ "step": 5020
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3026184278549062e-05,
+ "loss": 0.4768,
+ "step": 5021
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.302360132523114e-05,
+ "loss": 0.4759,
+ "step": 5022
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3021018149872516e-05,
+ "loss": 0.4861,
+ "step": 5023
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3018434752662882e-05,
+ "loss": 0.5004,
+ "step": 5024
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3015851133791955e-05,
+ "loss": 0.4867,
+ "step": 5025
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3013267293449463e-05,
+ "loss": 0.4708,
+ "step": 5026
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3010683231825158e-05,
+ "loss": 0.4981,
+ "step": 5027
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.30080989491088e-05,
+ "loss": 0.4881,
+ "step": 5028
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.300551444549016e-05,
+ "loss": 0.4787,
+ "step": 5029
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3002929721159043e-05,
+ "loss": 0.504,
+ "step": 5030
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3000344776305258e-05,
+ "loss": 0.511,
+ "step": 5031
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2997759611118634e-05,
+ "loss": 0.4751,
+ "step": 5032
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2995174225789008e-05,
+ "loss": 0.5148,
+ "step": 5033
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2992588620506251e-05,
+ "loss": 0.5013,
+ "step": 5034
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2990002795460228e-05,
+ "loss": 0.4959,
+ "step": 5035
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2987416750840836e-05,
+ "loss": 0.4788,
+ "step": 5036
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2984830486837985e-05,
+ "loss": 0.4932,
+ "step": 5037
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2982244003641599e-05,
+ "loss": 0.487,
+ "step": 5038
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2979657301441615e-05,
+ "loss": 0.4873,
+ "step": 5039
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2977070380427993e-05,
+ "loss": 0.4762,
+ "step": 5040
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2974483240790705e-05,
+ "loss": 0.4804,
+ "step": 5041
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2971895882719741e-05,
+ "loss": 0.4935,
+ "step": 5042
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2969308306405102e-05,
+ "loss": 0.4742,
+ "step": 5043
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2966720512036813e-05,
+ "loss": 0.5088,
+ "step": 5044
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2964132499804907e-05,
+ "loss": 0.4828,
+ "step": 5045
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.296154426989944e-05,
+ "loss": 0.4859,
+ "step": 5046
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2958955822510482e-05,
+ "loss": 0.4948,
+ "step": 5047
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2956367157828113e-05,
+ "loss": 0.4609,
+ "step": 5048
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.295377827604244e-05,
+ "loss": 0.5,
+ "step": 5049
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.295118917734357e-05,
+ "loss": 0.4859,
+ "step": 5050
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2948599861921644e-05,
+ "loss": 0.4748,
+ "step": 5051
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2946010329966811e-05,
+ "loss": 0.4679,
+ "step": 5052
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2943420581669231e-05,
+ "loss": 0.4995,
+ "step": 5053
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2940830617219087e-05,
+ "loss": 0.5,
+ "step": 5054
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2938240436806575e-05,
+ "loss": 0.4732,
+ "step": 5055
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2935650040621901e-05,
+ "loss": 0.4839,
+ "step": 5056
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2933059428855303e-05,
+ "loss": 0.4713,
+ "step": 5057
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2930468601697022e-05,
+ "loss": 0.4795,
+ "step": 5058
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2927877559337311e-05,
+ "loss": 0.4778,
+ "step": 5059
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2925286301966451e-05,
+ "loss": 0.4813,
+ "step": 5060
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2922694829774733e-05,
+ "loss": 0.5003,
+ "step": 5061
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2920103142952465e-05,
+ "loss": 0.4835,
+ "step": 5062
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2917511241689963e-05,
+ "loss": 0.4714,
+ "step": 5063
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2914919126177576e-05,
+ "loss": 0.5055,
+ "step": 5064
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.291232679660565e-05,
+ "loss": 0.4942,
+ "step": 5065
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2909734253164557e-05,
+ "loss": 0.4614,
+ "step": 5066
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2907141496044679e-05,
+ "loss": 0.4689,
+ "step": 5067
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2904548525436429e-05,
+ "loss": 0.4843,
+ "step": 5068
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2901955341530213e-05,
+ "loss": 0.472,
+ "step": 5069
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2899361944516464e-05,
+ "loss": 0.489,
+ "step": 5070
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2896768334585635e-05,
+ "loss": 0.5033,
+ "step": 5071
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2894174511928189e-05,
+ "loss": 0.4797,
+ "step": 5072
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2891580476734602e-05,
+ "loss": 0.4992,
+ "step": 5073
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2888986229195375e-05,
+ "loss": 0.4896,
+ "step": 5074
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2886391769501016e-05,
+ "loss": 0.4872,
+ "step": 5075
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2883797097842048e-05,
+ "loss": 0.4663,
+ "step": 5076
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2881202214409016e-05,
+ "loss": 0.4954,
+ "step": 5077
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2878607119392479e-05,
+ "loss": 0.5041,
+ "step": 5078
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2876011812983009e-05,
+ "loss": 0.4777,
+ "step": 5079
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.287341629537119e-05,
+ "loss": 0.5026,
+ "step": 5080
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2870820566747633e-05,
+ "loss": 0.471,
+ "step": 5081
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2868224627302952e-05,
+ "loss": 0.4873,
+ "step": 5082
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2865628477227787e-05,
+ "loss": 0.488,
+ "step": 5083
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2863032116712781e-05,
+ "loss": 0.4907,
+ "step": 5084
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2860435545948609e-05,
+ "loss": 0.4816,
+ "step": 5085
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2857838765125945e-05,
+ "loss": 0.4917,
+ "step": 5086
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.285524177443549e-05,
+ "loss": 0.4916,
+ "step": 5087
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2852644574067955e-05,
+ "loss": 0.4771,
+ "step": 5088
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.285004716421407e-05,
+ "loss": 0.4911,
+ "step": 5089
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2847449545064572e-05,
+ "loss": 0.4913,
+ "step": 5090
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2844851716810225e-05,
+ "loss": 0.4803,
+ "step": 5091
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2842253679641799e-05,
+ "loss": 0.4891,
+ "step": 5092
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2839655433750084e-05,
+ "loss": 0.4777,
+ "step": 5093
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2837056979325886e-05,
+ "loss": 0.4791,
+ "step": 5094
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2834458316560023e-05,
+ "loss": 0.4653,
+ "step": 5095
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2831859445643333e-05,
+ "loss": 0.4935,
+ "step": 5096
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.282926036676666e-05,
+ "loss": 0.5006,
+ "step": 5097
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2826661080120877e-05,
+ "loss": 0.463,
+ "step": 5098
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.282406158589686e-05,
+ "loss": 0.4902,
+ "step": 5099
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2821461884285506e-05,
+ "loss": 0.4759,
+ "step": 5100
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2818861975477728e-05,
+ "loss": 0.4796,
+ "step": 5101
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2816261859664448e-05,
+ "loss": 0.4833,
+ "step": 5102
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2813661537036613e-05,
+ "loss": 0.4863,
+ "step": 5103
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2811061007785175e-05,
+ "loss": 0.4719,
+ "step": 5104
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2808460272101113e-05,
+ "loss": 0.4843,
+ "step": 5105
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.280585933017541e-05,
+ "loss": 0.4763,
+ "step": 5106
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2803258182199064e-05,
+ "loss": 0.4812,
+ "step": 5107
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2800656828363098e-05,
+ "loss": 0.4878,
+ "step": 5108
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2798055268858544e-05,
+ "loss": 0.4949,
+ "step": 5109
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2795453503876449e-05,
+ "loss": 0.5089,
+ "step": 5110
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2792851533607875e-05,
+ "loss": 0.482,
+ "step": 5111
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2790249358243902e-05,
+ "loss": 0.5057,
+ "step": 5112
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2787646977975623e-05,
+ "loss": 0.5177,
+ "step": 5113
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2785044392994142e-05,
+ "loss": 0.461,
+ "step": 5114
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2782441603490585e-05,
+ "loss": 0.479,
+ "step": 5115
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.277983860965609e-05,
+ "loss": 0.5029,
+ "step": 5116
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.277723541168181e-05,
+ "loss": 0.475,
+ "step": 5117
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2774632009758911e-05,
+ "loss": 0.4754,
+ "step": 5118
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2772028404078581e-05,
+ "loss": 0.483,
+ "step": 5119
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2769424594832014e-05,
+ "loss": 0.4806,
+ "step": 5120
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2766820582210421e-05,
+ "loss": 0.4651,
+ "step": 5121
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2764216366405036e-05,
+ "loss": 0.4875,
+ "step": 5122
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2761611947607095e-05,
+ "loss": 0.4948,
+ "step": 5123
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2759007326007862e-05,
+ "loss": 0.4835,
+ "step": 5124
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2756402501798606e-05,
+ "loss": 0.4828,
+ "step": 5125
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2753797475170613e-05,
+ "loss": 0.4781,
+ "step": 5126
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.275119224631519e-05,
+ "loss": 0.4875,
+ "step": 5127
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2748586815423646e-05,
+ "loss": 0.4688,
+ "step": 5128
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2745981182687323e-05,
+ "loss": 0.479,
+ "step": 5129
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2743375348297567e-05,
+ "loss": 0.4941,
+ "step": 5130
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.274076931244573e-05,
+ "loss": 0.5048,
+ "step": 5131
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2738163075323198e-05,
+ "loss": 0.4627,
+ "step": 5132
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2735556637121356e-05,
+ "loss": 0.4784,
+ "step": 5133
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2732949998031612e-05,
+ "loss": 0.4883,
+ "step": 5134
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2730343158245389e-05,
+ "loss": 0.4992,
+ "step": 5135
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2727736117954122e-05,
+ "loss": 0.4715,
+ "step": 5136
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.272512887734926e-05,
+ "loss": 0.4769,
+ "step": 5137
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2722521436622263e-05,
+ "loss": 0.5004,
+ "step": 5138
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2719913795964618e-05,
+ "loss": 0.4909,
+ "step": 5139
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.271730595556782e-05,
+ "loss": 0.4747,
+ "step": 5140
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2714697915623374e-05,
+ "loss": 0.4969,
+ "step": 5141
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2712089676322803e-05,
+ "loss": 0.479,
+ "step": 5142
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2709481237857643e-05,
+ "loss": 0.4771,
+ "step": 5143
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2706872600419456e-05,
+ "loss": 0.5098,
+ "step": 5144
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2704263764199803e-05,
+ "loss": 0.4819,
+ "step": 5145
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2701654729390264e-05,
+ "loss": 0.4838,
+ "step": 5146
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2699045496182442e-05,
+ "loss": 0.4829,
+ "step": 5147
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2696436064767943e-05,
+ "loss": 0.4952,
+ "step": 5148
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2693826435338394e-05,
+ "loss": 0.4854,
+ "step": 5149
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.269121660808544e-05,
+ "loss": 0.483,
+ "step": 5150
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2688606583200728e-05,
+ "loss": 0.4843,
+ "step": 5151
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2685996360875933e-05,
+ "loss": 0.4863,
+ "step": 5152
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2683385941302737e-05,
+ "loss": 0.4922,
+ "step": 5153
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2680775324672839e-05,
+ "loss": 0.4687,
+ "step": 5154
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2678164511177948e-05,
+ "loss": 0.494,
+ "step": 5155
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.26755535010098e-05,
+ "loss": 0.4872,
+ "step": 5156
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.267294229436013e-05,
+ "loss": 0.4892,
+ "step": 5157
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2670330891420694e-05,
+ "loss": 0.4867,
+ "step": 5158
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.266771929238326e-05,
+ "loss": 0.4676,
+ "step": 5159
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2665107497439623e-05,
+ "loss": 0.4976,
+ "step": 5160
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2662495506781575e-05,
+ "loss": 0.4855,
+ "step": 5161
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.265988332060093e-05,
+ "loss": 0.4878,
+ "step": 5162
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.265727093908952e-05,
+ "loss": 0.4841,
+ "step": 5163
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.265465836243918e-05,
+ "loss": 0.4876,
+ "step": 5164
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2652045590841774e-05,
+ "loss": 0.4905,
+ "step": 5165
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2649432624489171e-05,
+ "loss": 0.4761,
+ "step": 5166
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2646819463573257e-05,
+ "loss": 0.4716,
+ "step": 5167
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.264420610828593e-05,
+ "loss": 0.4791,
+ "step": 5168
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2641592558819102e-05,
+ "loss": 0.4844,
+ "step": 5169
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2638978815364705e-05,
+ "loss": 0.4864,
+ "step": 5170
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2636364878114682e-05,
+ "loss": 0.4723,
+ "step": 5171
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2633750747260985e-05,
+ "loss": 0.4821,
+ "step": 5172
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.263113642299559e-05,
+ "loss": 0.4819,
+ "step": 5173
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2628521905510476e-05,
+ "loss": 0.4784,
+ "step": 5174
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2625907194997652e-05,
+ "loss": 0.4812,
+ "step": 5175
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2623292291649119e-05,
+ "loss": 0.4735,
+ "step": 5176
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2620677195656916e-05,
+ "loss": 0.4846,
+ "step": 5177
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.261806190721308e-05,
+ "loss": 0.5012,
+ "step": 5178
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2615446426509663e-05,
+ "loss": 0.5073,
+ "step": 5179
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.261283075373874e-05,
+ "loss": 0.4963,
+ "step": 5180
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2610214889092399e-05,
+ "loss": 0.4903,
+ "step": 5181
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2607598832762728e-05,
+ "loss": 0.485,
+ "step": 5182
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2604982584941846e-05,
+ "loss": 0.4773,
+ "step": 5183
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2602366145821879e-05,
+ "loss": 0.4819,
+ "step": 5184
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2599749515594964e-05,
+ "loss": 0.4781,
+ "step": 5185
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2597132694453258e-05,
+ "loss": 0.4648,
+ "step": 5186
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.259451568258893e-05,
+ "loss": 0.4819,
+ "step": 5187
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2591898480194165e-05,
+ "loss": 0.5044,
+ "step": 5188
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2589281087461152e-05,
+ "loss": 0.4943,
+ "step": 5189
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2586663504582104e-05,
+ "loss": 0.4827,
+ "step": 5190
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.258404573174925e-05,
+ "loss": 0.4828,
+ "step": 5191
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2581427769154826e-05,
+ "loss": 0.4685,
+ "step": 5192
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2578809616991081e-05,
+ "loss": 0.4819,
+ "step": 5193
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2576191275450287e-05,
+ "loss": 0.4996,
+ "step": 5194
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2573572744724718e-05,
+ "loss": 0.4831,
+ "step": 5195
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2570954025006672e-05,
+ "loss": 0.499,
+ "step": 5196
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2568335116488457e-05,
+ "loss": 0.4894,
+ "step": 5197
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2565716019362393e-05,
+ "loss": 0.4802,
+ "step": 5198
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2563096733820816e-05,
+ "loss": 0.479,
+ "step": 5199
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2560477260056072e-05,
+ "loss": 0.4739,
+ "step": 5200
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2557857598260532e-05,
+ "loss": 0.4864,
+ "step": 5201
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.255523774862657e-05,
+ "loss": 0.4791,
+ "step": 5202
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2552617711346572e-05,
+ "loss": 0.4939,
+ "step": 5203
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.254999748661295e-05,
+ "loss": 0.4796,
+ "step": 5204
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2547377074618114e-05,
+ "loss": 0.4678,
+ "step": 5205
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2544756475554505e-05,
+ "loss": 0.4995,
+ "step": 5206
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2542135689614565e-05,
+ "loss": 0.483,
+ "step": 5207
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2539514716990753e-05,
+ "loss": 0.4679,
+ "step": 5208
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2536893557875543e-05,
+ "loss": 0.4865,
+ "step": 5209
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.253427221246142e-05,
+ "loss": 0.4795,
+ "step": 5210
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2531650680940888e-05,
+ "loss": 0.4777,
+ "step": 5211
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.252902896350646e-05,
+ "loss": 0.4953,
+ "step": 5212
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.252640706035066e-05,
+ "loss": 0.5058,
+ "step": 5213
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2523784971666039e-05,
+ "loss": 0.4991,
+ "step": 5214
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2521162697645144e-05,
+ "loss": 0.4984,
+ "step": 5215
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.251854023848055e-05,
+ "loss": 0.4979,
+ "step": 5216
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.251591759436483e-05,
+ "loss": 0.4866,
+ "step": 5217
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2513294765490593e-05,
+ "loss": 0.4815,
+ "step": 5218
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2510671752050441e-05,
+ "loss": 0.4922,
+ "step": 5219
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2508048554236996e-05,
+ "loss": 0.4619,
+ "step": 5220
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2505425172242895e-05,
+ "loss": 0.4701,
+ "step": 5221
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2502801606260792e-05,
+ "loss": 0.4784,
+ "step": 5222
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2500177856483351e-05,
+ "loss": 0.4772,
+ "step": 5223
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2497553923103247e-05,
+ "loss": 0.4912,
+ "step": 5224
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.249492980631317e-05,
+ "loss": 0.4981,
+ "step": 5225
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2492305506305824e-05,
+ "loss": 0.4649,
+ "step": 5226
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2489681023273927e-05,
+ "loss": 0.4915,
+ "step": 5227
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2487056357410215e-05,
+ "loss": 0.4691,
+ "step": 5228
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2484431508907429e-05,
+ "loss": 0.4756,
+ "step": 5229
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2481806477958323e-05,
+ "loss": 0.4938,
+ "step": 5230
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.247918126475567e-05,
+ "loss": 0.4832,
+ "step": 5231
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2476555869492262e-05,
+ "loss": 0.4856,
+ "step": 5232
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2473930292360889e-05,
+ "loss": 0.4804,
+ "step": 5233
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2471304533554364e-05,
+ "loss": 0.5037,
+ "step": 5234
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2468678593265518e-05,
+ "loss": 0.4744,
+ "step": 5235
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2466052471687178e-05,
+ "loss": 0.4723,
+ "step": 5236
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2463426169012204e-05,
+ "loss": 0.4755,
+ "step": 5237
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2460799685433457e-05,
+ "loss": 0.4816,
+ "step": 5238
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.245817302114382e-05,
+ "loss": 0.4794,
+ "step": 5239
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2455546176336177e-05,
+ "loss": 0.4817,
+ "step": 5240
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2452919151203439e-05,
+ "loss": 0.5024,
+ "step": 5241
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.245029194593852e-05,
+ "loss": 0.4645,
+ "step": 5242
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2447664560734352e-05,
+ "loss": 0.4934,
+ "step": 5243
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2445036995783876e-05,
+ "loss": 0.4699,
+ "step": 5244
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2442409251280058e-05,
+ "loss": 0.4868,
+ "step": 5245
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2439781327415858e-05,
+ "loss": 0.4947,
+ "step": 5246
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2437153224384269e-05,
+ "loss": 0.4851,
+ "step": 5247
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2434524942378283e-05,
+ "loss": 0.5058,
+ "step": 5248
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2431896481590912e-05,
+ "loss": 0.4728,
+ "step": 5249
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2429267842215181e-05,
+ "loss": 0.4873,
+ "step": 5250
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2426639024444118e-05,
+ "loss": 0.4701,
+ "step": 5251
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2424010028470779e-05,
+ "loss": 0.4963,
+ "step": 5252
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.242138085448823e-05,
+ "loss": 0.501,
+ "step": 5253
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2418751502689537e-05,
+ "loss": 0.4718,
+ "step": 5254
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.24161219732678e-05,
+ "loss": 0.5091,
+ "step": 5255
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.241349226641611e-05,
+ "loss": 0.493,
+ "step": 5256
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2410862382327587e-05,
+ "loss": 0.4905,
+ "step": 5257
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.240823232119536e-05,
+ "loss": 0.4691,
+ "step": 5258
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2405602083212567e-05,
+ "loss": 0.4941,
+ "step": 5259
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2402971668572364e-05,
+ "loss": 0.4871,
+ "step": 5260
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2400341077467912e-05,
+ "loss": 0.4755,
+ "step": 5261
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2397710310092396e-05,
+ "loss": 0.4886,
+ "step": 5262
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2395079366639011e-05,
+ "loss": 0.5008,
+ "step": 5263
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2392448247300959e-05,
+ "loss": 0.4723,
+ "step": 5264
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2389816952271456e-05,
+ "loss": 0.4819,
+ "step": 5265
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.238718548174374e-05,
+ "loss": 0.4801,
+ "step": 5266
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2384553835911049e-05,
+ "loss": 0.5106,
+ "step": 5267
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2381922014966641e-05,
+ "loss": 0.5061,
+ "step": 5268
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.237929001910379e-05,
+ "loss": 0.4961,
+ "step": 5269
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2376657848515774e-05,
+ "loss": 0.4996,
+ "step": 5270
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.237402550339589e-05,
+ "loss": 0.4873,
+ "step": 5271
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2371392983937449e-05,
+ "loss": 0.4964,
+ "step": 5272
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2368760290333771e-05,
+ "loss": 0.493,
+ "step": 5273
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2366127422778192e-05,
+ "loss": 0.4932,
+ "step": 5274
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2363494381464052e-05,
+ "loss": 0.4952,
+ "step": 5275
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2360861166584717e-05,
+ "loss": 0.4878,
+ "step": 5276
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2358227778333556e-05,
+ "loss": 0.4842,
+ "step": 5277
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2355594216903956e-05,
+ "loss": 0.4739,
+ "step": 5278
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2352960482489317e-05,
+ "loss": 0.4898,
+ "step": 5279
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2350326575283047e-05,
+ "loss": 0.45,
+ "step": 5280
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2347692495478565e-05,
+ "loss": 0.4845,
+ "step": 5281
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2345058243269314e-05,
+ "loss": 0.4905,
+ "step": 5282
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.234242381884874e-05,
+ "loss": 0.4936,
+ "step": 5283
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2339789222410301e-05,
+ "loss": 0.4803,
+ "step": 5284
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2337154454147476e-05,
+ "loss": 0.4985,
+ "step": 5285
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2334519514253747e-05,
+ "loss": 0.4824,
+ "step": 5286
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2331884402922613e-05,
+ "loss": 0.4794,
+ "step": 5287
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2329249120347591e-05,
+ "loss": 0.4644,
+ "step": 5288
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.23266136667222e-05,
+ "loss": 0.4718,
+ "step": 5289
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2323978042239982e-05,
+ "loss": 0.4865,
+ "step": 5290
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.232134224709448e-05,
+ "loss": 0.4865,
+ "step": 5291
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2318706281479256e-05,
+ "loss": 0.4886,
+ "step": 5292
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2316070145587888e-05,
+ "loss": 0.4689,
+ "step": 5293
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2313433839613964e-05,
+ "loss": 0.4984,
+ "step": 5294
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2310797363751078e-05,
+ "loss": 0.497,
+ "step": 5295
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.230816071819285e-05,
+ "loss": 0.4869,
+ "step": 5296
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2305523903132897e-05,
+ "loss": 0.5057,
+ "step": 5297
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2302886918764856e-05,
+ "loss": 0.4959,
+ "step": 5298
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.230024976528238e-05,
+ "loss": 0.4867,
+ "step": 5299
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2297612442879129e-05,
+ "loss": 0.4817,
+ "step": 5300
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2294974951748775e-05,
+ "loss": 0.4834,
+ "step": 5301
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2292337292085006e-05,
+ "loss": 0.4934,
+ "step": 5302
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2289699464081521e-05,
+ "loss": 0.4969,
+ "step": 5303
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2287061467932033e-05,
+ "loss": 0.4713,
+ "step": 5304
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.228442330383026e-05,
+ "loss": 0.4615,
+ "step": 5305
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2281784971969944e-05,
+ "loss": 0.4634,
+ "step": 5306
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.227914647254483e-05,
+ "loss": 0.4882,
+ "step": 5307
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2276507805748676e-05,
+ "loss": 0.4769,
+ "step": 5308
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.227386897177526e-05,
+ "loss": 0.4874,
+ "step": 5309
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2271229970818366e-05,
+ "loss": 0.504,
+ "step": 5310
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2268590803071787e-05,
+ "loss": 0.4827,
+ "step": 5311
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2265951468729336e-05,
+ "loss": 0.4654,
+ "step": 5312
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2263311967984834e-05,
+ "loss": 0.5182,
+ "step": 5313
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2260672301032116e-05,
+ "loss": 0.4757,
+ "step": 5314
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2258032468065024e-05,
+ "loss": 0.4899,
+ "step": 5315
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2255392469277421e-05,
+ "loss": 0.4886,
+ "step": 5316
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2252752304863178e-05,
+ "loss": 0.4833,
+ "step": 5317
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2250111975016173e-05,
+ "loss": 0.4766,
+ "step": 5318
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2247471479930303e-05,
+ "loss": 0.4942,
+ "step": 5319
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2244830819799478e-05,
+ "loss": 0.4695,
+ "step": 5320
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2242189994817614e-05,
+ "loss": 0.4811,
+ "step": 5321
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2239549005178642e-05,
+ "loss": 0.4927,
+ "step": 5322
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2236907851076505e-05,
+ "loss": 0.4838,
+ "step": 5323
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2234266532705161e-05,
+ "loss": 0.4872,
+ "step": 5324
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2231625050258576e-05,
+ "loss": 0.492,
+ "step": 5325
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2228983403930727e-05,
+ "loss": 0.4847,
+ "step": 5326
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2226341593915612e-05,
+ "loss": 0.4641,
+ "step": 5327
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2223699620407227e-05,
+ "loss": 0.5174,
+ "step": 5328
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.222105748359959e-05,
+ "loss": 0.4728,
+ "step": 5329
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2218415183686732e-05,
+ "loss": 0.4889,
+ "step": 5330
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2215772720862691e-05,
+ "loss": 0.5182,
+ "step": 5331
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2213130095321517e-05,
+ "loss": 0.4757,
+ "step": 5332
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.221048730725727e-05,
+ "loss": 0.4729,
+ "step": 5333
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2207844356864031e-05,
+ "loss": 0.4839,
+ "step": 5334
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2205201244335889e-05,
+ "loss": 0.4946,
+ "step": 5335
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2202557969866934e-05,
+ "loss": 0.4686,
+ "step": 5336
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2199914533651289e-05,
+ "loss": 0.4722,
+ "step": 5337
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2197270935883068e-05,
+ "loss": 0.4708,
+ "step": 5338
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2194627176756408e-05,
+ "loss": 0.5,
+ "step": 5339
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2191983256465455e-05,
+ "loss": 0.463,
+ "step": 5340
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2189339175204373e-05,
+ "loss": 0.4606,
+ "step": 5341
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2186694933167326e-05,
+ "loss": 0.5079,
+ "step": 5342
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2184050530548496e-05,
+ "loss": 0.4716,
+ "step": 5343
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2181405967542082e-05,
+ "loss": 0.4788,
+ "step": 5344
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2178761244342286e-05,
+ "loss": 0.488,
+ "step": 5345
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2176116361143326e-05,
+ "loss": 0.4836,
+ "step": 5346
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2173471318139431e-05,
+ "loss": 0.4844,
+ "step": 5347
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2170826115524845e-05,
+ "loss": 0.4895,
+ "step": 5348
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2168180753493817e-05,
+ "loss": 0.4887,
+ "step": 5349
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2165535232240611e-05,
+ "loss": 0.4839,
+ "step": 5350
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2162889551959506e-05,
+ "loss": 0.4759,
+ "step": 5351
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.216024371284479e-05,
+ "loss": 0.4753,
+ "step": 5352
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.215759771509076e-05,
+ "loss": 0.4875,
+ "step": 5353
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2154951558891728e-05,
+ "loss": 0.4858,
+ "step": 5354
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2152305244442014e-05,
+ "loss": 0.4829,
+ "step": 5355
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2149658771935955e-05,
+ "loss": 0.4784,
+ "step": 5356
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.21470121415679e-05,
+ "loss": 0.4715,
+ "step": 5357
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2144365353532204e-05,
+ "loss": 0.4761,
+ "step": 5358
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2141718408023233e-05,
+ "loss": 0.4941,
+ "step": 5359
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2139071305235368e-05,
+ "loss": 0.4754,
+ "step": 5360
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2136424045363007e-05,
+ "loss": 0.4846,
+ "step": 5361
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2133776628600552e-05,
+ "loss": 0.4779,
+ "step": 5362
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2131129055142411e-05,
+ "loss": 0.481,
+ "step": 5363
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2128481325183022e-05,
+ "loss": 0.4914,
+ "step": 5364
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2125833438916812e-05,
+ "loss": 0.4922,
+ "step": 5365
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2123185396538242e-05,
+ "loss": 0.4835,
+ "step": 5366
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2120537198241763e-05,
+ "loss": 0.4769,
+ "step": 5367
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2117888844221852e-05,
+ "loss": 0.4646,
+ "step": 5368
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2115240334672997e-05,
+ "loss": 0.4822,
+ "step": 5369
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2112591669789685e-05,
+ "loss": 0.4844,
+ "step": 5370
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2109942849766432e-05,
+ "loss": 0.4739,
+ "step": 5371
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.210729387479775e-05,
+ "loss": 0.4888,
+ "step": 5372
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.210464474507817e-05,
+ "loss": 0.496,
+ "step": 5373
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2101995460802235e-05,
+ "loss": 0.4643,
+ "step": 5374
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2099346022164496e-05,
+ "loss": 0.4959,
+ "step": 5375
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2096696429359518e-05,
+ "loss": 0.4997,
+ "step": 5376
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2094046682581872e-05,
+ "loss": 0.5001,
+ "step": 5377
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.209139678202615e-05,
+ "loss": 0.4878,
+ "step": 5378
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2088746727886949e-05,
+ "loss": 0.4932,
+ "step": 5379
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2086096520358872e-05,
+ "loss": 0.4941,
+ "step": 5380
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2083446159636543e-05,
+ "loss": 0.4906,
+ "step": 5381
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2080795645914595e-05,
+ "loss": 0.4808,
+ "step": 5382
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2078144979387674e-05,
+ "loss": 0.5055,
+ "step": 5383
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2075494160250423e-05,
+ "loss": 0.4768,
+ "step": 5384
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2072843188697516e-05,
+ "loss": 0.4818,
+ "step": 5385
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2070192064923627e-05,
+ "loss": 0.4919,
+ "step": 5386
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2067540789123441e-05,
+ "loss": 0.4866,
+ "step": 5387
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2064889361491663e-05,
+ "loss": 0.4826,
+ "step": 5388
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2062237782222996e-05,
+ "loss": 0.4683,
+ "step": 5389
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2059586051512164e-05,
+ "loss": 0.4713,
+ "step": 5390
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.20569341695539e-05,
+ "loss": 0.4872,
+ "step": 5391
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2054282136542946e-05,
+ "loss": 0.5091,
+ "step": 5392
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2051629952674055e-05,
+ "loss": 0.4817,
+ "step": 5393
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2048977618141995e-05,
+ "loss": 0.5097,
+ "step": 5394
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2046325133141542e-05,
+ "loss": 0.4779,
+ "step": 5395
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2043672497867479e-05,
+ "loss": 0.4591,
+ "step": 5396
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2041019712514607e-05,
+ "loss": 0.4957,
+ "step": 5397
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2038366777277743e-05,
+ "loss": 0.475,
+ "step": 5398
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2035713692351698e-05,
+ "loss": 0.483,
+ "step": 5399
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2033060457931308e-05,
+ "loss": 0.4841,
+ "step": 5400
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.203040707421141e-05,
+ "loss": 0.4775,
+ "step": 5401
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2027753541386865e-05,
+ "loss": 0.466,
+ "step": 5402
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2025099859652532e-05,
+ "loss": 0.4859,
+ "step": 5403
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.202244602920329e-05,
+ "loss": 0.4848,
+ "step": 5404
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2019792050234022e-05,
+ "loss": 0.4779,
+ "step": 5405
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2017137922939629e-05,
+ "loss": 0.4719,
+ "step": 5406
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2014483647515014e-05,
+ "loss": 0.4811,
+ "step": 5407
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2011829224155101e-05,
+ "loss": 0.4836,
+ "step": 5408
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2009174653054815e-05,
+ "loss": 0.4754,
+ "step": 5409
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2006519934409105e-05,
+ "loss": 0.4843,
+ "step": 5410
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.200386506841291e-05,
+ "loss": 0.4793,
+ "step": 5411
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.20012100552612e-05,
+ "loss": 0.4602,
+ "step": 5412
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1998554895148953e-05,
+ "loss": 0.4766,
+ "step": 5413
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.199589958827114e-05,
+ "loss": 0.4675,
+ "step": 5414
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1993244134822767e-05,
+ "loss": 0.4753,
+ "step": 5415
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1990588534998834e-05,
+ "loss": 0.4726,
+ "step": 5416
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1987932788994362e-05,
+ "loss": 0.4837,
+ "step": 5417
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1985276897004367e-05,
+ "loss": 0.475,
+ "step": 5418
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1982620859223902e-05,
+ "loss": 0.4957,
+ "step": 5419
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1979964675848004e-05,
+ "loss": 0.5041,
+ "step": 5420
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1977308347071735e-05,
+ "loss": 0.4591,
+ "step": 5421
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1974651873090163e-05,
+ "loss": 0.4675,
+ "step": 5422
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1971995254098374e-05,
+ "loss": 0.4879,
+ "step": 5423
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1969338490291455e-05,
+ "loss": 0.464,
+ "step": 5424
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1966681581864507e-05,
+ "loss": 0.4879,
+ "step": 5425
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1964024529012648e-05,
+ "loss": 0.5053,
+ "step": 5426
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.196136733193099e-05,
+ "loss": 0.5042,
+ "step": 5427
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1958709990814677e-05,
+ "loss": 0.4944,
+ "step": 5428
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1956052505858851e-05,
+ "loss": 0.4783,
+ "step": 5429
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1953394877258662e-05,
+ "loss": 0.5042,
+ "step": 5430
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1950737105209278e-05,
+ "loss": 0.4801,
+ "step": 5431
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1948079189905872e-05,
+ "loss": 0.502,
+ "step": 5432
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1945421131543639e-05,
+ "loss": 0.4985,
+ "step": 5433
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1942762930317768e-05,
+ "loss": 0.4746,
+ "step": 5434
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1940104586423465e-05,
+ "loss": 0.4948,
+ "step": 5435
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1937446100055954e-05,
+ "loss": 0.4836,
+ "step": 5436
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1934787471410457e-05,
+ "loss": 0.4663,
+ "step": 5437
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1932128700682216e-05,
+ "loss": 0.5137,
+ "step": 5438
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1929469788066481e-05,
+ "loss": 0.4803,
+ "step": 5439
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1926810733758511e-05,
+ "loss": 0.4849,
+ "step": 5440
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1924151537953574e-05,
+ "loss": 0.4916,
+ "step": 5441
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1921492200846949e-05,
+ "loss": 0.4784,
+ "step": 5442
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.191883272263393e-05,
+ "loss": 0.4805,
+ "step": 5443
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1916173103509819e-05,
+ "loss": 0.4756,
+ "step": 5444
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.191351334366992e-05,
+ "loss": 0.5125,
+ "step": 5445
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1910853443309566e-05,
+ "loss": 0.4804,
+ "step": 5446
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.190819340262408e-05,
+ "loss": 0.4834,
+ "step": 5447
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1905533221808805e-05,
+ "loss": 0.4813,
+ "step": 5448
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1902872901059102e-05,
+ "loss": 0.501,
+ "step": 5449
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1900212440570324e-05,
+ "loss": 0.4523,
+ "step": 5450
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1897551840537848e-05,
+ "loss": 0.4583,
+ "step": 5451
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1894891101157058e-05,
+ "loss": 0.4717,
+ "step": 5452
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1892230222623345e-05,
+ "loss": 0.4813,
+ "step": 5453
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1889569205132119e-05,
+ "loss": 0.495,
+ "step": 5454
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1886908048878785e-05,
+ "loss": 0.4842,
+ "step": 5455
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1884246754058775e-05,
+ "loss": 0.4882,
+ "step": 5456
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1881585320867521e-05,
+ "loss": 0.4802,
+ "step": 5457
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1878923749500466e-05,
+ "loss": 0.4653,
+ "step": 5458
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1876262040153064e-05,
+ "loss": 0.4861,
+ "step": 5459
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1873600193020786e-05,
+ "loss": 0.4977,
+ "step": 5460
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.18709382082991e-05,
+ "loss": 0.4697,
+ "step": 5461
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1868276086183494e-05,
+ "loss": 0.4973,
+ "step": 5462
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1865613826869463e-05,
+ "loss": 0.5125,
+ "step": 5463
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1862951430552514e-05,
+ "loss": 0.4998,
+ "step": 5464
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1860288897428158e-05,
+ "loss": 0.4609,
+ "step": 5465
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1857626227691924e-05,
+ "loss": 0.47,
+ "step": 5466
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1854963421539348e-05,
+ "loss": 0.4728,
+ "step": 5467
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.185230047916597e-05,
+ "loss": 0.4885,
+ "step": 5468
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1849637400767351e-05,
+ "loss": 0.49,
+ "step": 5469
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1846974186539055e-05,
+ "loss": 0.5007,
+ "step": 5470
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1844310836676658e-05,
+ "loss": 0.4694,
+ "step": 5471
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.184164735137574e-05,
+ "loss": 0.4736,
+ "step": 5472
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1838983730831904e-05,
+ "loss": 0.5052,
+ "step": 5473
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1836319975240751e-05,
+ "loss": 0.4826,
+ "step": 5474
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1833656084797898e-05,
+ "loss": 0.4675,
+ "step": 5475
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1830992059698967e-05,
+ "loss": 0.4842,
+ "step": 5476
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1828327900139596e-05,
+ "loss": 0.4937,
+ "step": 5477
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1825663606315425e-05,
+ "loss": 0.4691,
+ "step": 5478
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1822999178422114e-05,
+ "loss": 0.4715,
+ "step": 5479
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.182033461665533e-05,
+ "loss": 0.4987,
+ "step": 5480
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.181766992121074e-05,
+ "loss": 0.4855,
+ "step": 5481
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1815005092284033e-05,
+ "loss": 0.4915,
+ "step": 5482
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.18123401300709e-05,
+ "loss": 0.469,
+ "step": 5483
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1809675034767043e-05,
+ "loss": 0.4964,
+ "step": 5484
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1807009806568181e-05,
+ "loss": 0.4829,
+ "step": 5485
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1804344445670034e-05,
+ "loss": 0.4707,
+ "step": 5486
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1801678952268338e-05,
+ "loss": 0.4788,
+ "step": 5487
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.179901332655883e-05,
+ "loss": 0.4759,
+ "step": 5488
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1796347568737268e-05,
+ "loss": 0.4847,
+ "step": 5489
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1793681678999412e-05,
+ "loss": 0.4786,
+ "step": 5490
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1791015657541037e-05,
+ "loss": 0.4953,
+ "step": 5491
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1788349504557917e-05,
+ "loss": 0.4832,
+ "step": 5492
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1785683220245849e-05,
+ "loss": 0.4776,
+ "step": 5493
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1783016804800631e-05,
+ "loss": 0.4789,
+ "step": 5494
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1780350258418078e-05,
+ "loss": 0.4819,
+ "step": 5495
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1777683581294003e-05,
+ "loss": 0.4795,
+ "step": 5496
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1775016773624246e-05,
+ "loss": 0.4736,
+ "step": 5497
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1772349835604638e-05,
+ "loss": 0.5113,
+ "step": 5498
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1769682767431026e-05,
+ "loss": 0.4702,
+ "step": 5499
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1767015569299274e-05,
+ "loss": 0.4802,
+ "step": 5500
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1764348241405249e-05,
+ "loss": 0.4804,
+ "step": 5501
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1761680783944829e-05,
+ "loss": 0.4852,
+ "step": 5502
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1759013197113895e-05,
+ "loss": 0.4836,
+ "step": 5503
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.175634548110835e-05,
+ "loss": 0.4939,
+ "step": 5504
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1753677636124101e-05,
+ "loss": 0.5088,
+ "step": 5505
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1751009662357059e-05,
+ "loss": 0.471,
+ "step": 5506
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1748341560003149e-05,
+ "loss": 0.489,
+ "step": 5507
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.174567332925831e-05,
+ "loss": 0.4822,
+ "step": 5508
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.174300497031848e-05,
+ "loss": 0.4794,
+ "step": 5509
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1740336483379613e-05,
+ "loss": 0.4821,
+ "step": 5510
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1737667868637674e-05,
+ "loss": 0.4755,
+ "step": 5511
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1734999126288637e-05,
+ "loss": 0.4849,
+ "step": 5512
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1732330256528477e-05,
+ "loss": 0.4922,
+ "step": 5513
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1729661259553193e-05,
+ "loss": 0.4849,
+ "step": 5514
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1726992135558776e-05,
+ "loss": 0.4955,
+ "step": 5515
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1724322884741242e-05,
+ "loss": 0.4834,
+ "step": 5516
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1721653507296604e-05,
+ "loss": 0.5012,
+ "step": 5517
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1718984003420899e-05,
+ "loss": 0.4802,
+ "step": 5518
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1716314373310154e-05,
+ "loss": 0.4789,
+ "step": 5519
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.171364461716042e-05,
+ "loss": 0.4883,
+ "step": 5520
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1710974735167755e-05,
+ "loss": 0.4702,
+ "step": 5521
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1708304727528223e-05,
+ "loss": 0.4768,
+ "step": 5522
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1705634594437893e-05,
+ "loss": 0.4884,
+ "step": 5523
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1702964336092857e-05,
+ "loss": 0.4935,
+ "step": 5524
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.17002939526892e-05,
+ "loss": 0.4804,
+ "step": 5525
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.169762344442303e-05,
+ "loss": 0.4896,
+ "step": 5526
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1694952811490451e-05,
+ "loss": 0.4846,
+ "step": 5527
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1692282054087594e-05,
+ "loss": 0.4812,
+ "step": 5528
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1689611172410577e-05,
+ "loss": 0.5226,
+ "step": 5529
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1686940166655543e-05,
+ "loss": 0.4731,
+ "step": 5530
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1684269037018641e-05,
+ "loss": 0.475,
+ "step": 5531
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1681597783696027e-05,
+ "loss": 0.5193,
+ "step": 5532
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1678926406883866e-05,
+ "loss": 0.4724,
+ "step": 5533
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1676254906778331e-05,
+ "loss": 0.4698,
+ "step": 5534
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1673583283575607e-05,
+ "loss": 0.4757,
+ "step": 5535
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1670911537471889e-05,
+ "loss": 0.48,
+ "step": 5536
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1668239668663377e-05,
+ "loss": 0.4737,
+ "step": 5537
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1665567677346285e-05,
+ "loss": 0.4547,
+ "step": 5538
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.166289556371683e-05,
+ "loss": 0.4934,
+ "step": 5539
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1660223327971239e-05,
+ "loss": 0.4754,
+ "step": 5540
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1657550970305752e-05,
+ "loss": 0.473,
+ "step": 5541
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1654878490916617e-05,
+ "loss": 0.4748,
+ "step": 5542
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.165220589000009e-05,
+ "loss": 0.486,
+ "step": 5543
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1649533167752434e-05,
+ "loss": 0.4595,
+ "step": 5544
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.164686032436992e-05,
+ "loss": 0.4842,
+ "step": 5545
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1644187360048838e-05,
+ "loss": 0.4897,
+ "step": 5546
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.164151427498547e-05,
+ "loss": 0.4752,
+ "step": 5547
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1638841069376125e-05,
+ "loss": 0.4937,
+ "step": 5548
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1636167743417111e-05,
+ "loss": 0.4841,
+ "step": 5549
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1633494297304738e-05,
+ "loss": 0.4826,
+ "step": 5550
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.163082073123534e-05,
+ "loss": 0.4777,
+ "step": 5551
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1628147045405248e-05,
+ "loss": 0.4806,
+ "step": 5552
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1625473240010814e-05,
+ "loss": 0.4643,
+ "step": 5553
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1622799315248382e-05,
+ "loss": 0.5037,
+ "step": 5554
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1620125271314322e-05,
+ "loss": 0.4654,
+ "step": 5555
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1617451108404996e-05,
+ "loss": 0.4785,
+ "step": 5556
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1614776826716791e-05,
+ "loss": 0.4712,
+ "step": 5557
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.161210242644609e-05,
+ "loss": 0.4797,
+ "step": 5558
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1609427907789294e-05,
+ "loss": 0.4672,
+ "step": 5559
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.160675327094281e-05,
+ "loss": 0.5135,
+ "step": 5560
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.160407851610304e-05,
+ "loss": 0.5052,
+ "step": 5561
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1601403643466422e-05,
+ "loss": 0.4833,
+ "step": 5562
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.159872865322938e-05,
+ "loss": 0.5247,
+ "step": 5563
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1596053545588355e-05,
+ "loss": 0.5032,
+ "step": 5564
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1593378320739796e-05,
+ "loss": 0.4918,
+ "step": 5565
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1590702978880159e-05,
+ "loss": 0.4745,
+ "step": 5566
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1588027520205915e-05,
+ "loss": 0.4933,
+ "step": 5567
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1585351944913532e-05,
+ "loss": 0.4832,
+ "step": 5568
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1582676253199498e-05,
+ "loss": 0.4923,
+ "step": 5569
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1580000445260305e-05,
+ "loss": 0.4878,
+ "step": 5570
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1577324521292445e-05,
+ "loss": 0.4873,
+ "step": 5571
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1574648481492434e-05,
+ "loss": 0.4808,
+ "step": 5572
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1571972326056794e-05,
+ "loss": 0.4868,
+ "step": 5573
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.156929605518204e-05,
+ "loss": 0.49,
+ "step": 5574
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1566619669064709e-05,
+ "loss": 0.468,
+ "step": 5575
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1563943167901348e-05,
+ "loss": 0.4702,
+ "step": 5576
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1561266551888505e-05,
+ "loss": 0.4777,
+ "step": 5577
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1558589821222742e-05,
+ "loss": 0.4819,
+ "step": 5578
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1555912976100623e-05,
+ "loss": 0.4927,
+ "step": 5579
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.155323601671873e-05,
+ "loss": 0.4894,
+ "step": 5580
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.155055894327364e-05,
+ "loss": 0.4895,
+ "step": 5581
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1547881755961952e-05,
+ "loss": 0.4753,
+ "step": 5582
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1545204454980268e-05,
+ "loss": 0.483,
+ "step": 5583
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1542527040525192e-05,
+ "loss": 0.4889,
+ "step": 5584
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1539849512793348e-05,
+ "loss": 0.4702,
+ "step": 5585
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1537171871981363e-05,
+ "loss": 0.4892,
+ "step": 5586
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1534494118285865e-05,
+ "loss": 0.4854,
+ "step": 5587
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1531816251903503e-05,
+ "loss": 0.4915,
+ "step": 5588
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1529138273030927e-05,
+ "loss": 0.4627,
+ "step": 5589
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1526460181864799e-05,
+ "loss": 0.4904,
+ "step": 5590
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.152378197860178e-05,
+ "loss": 0.5022,
+ "step": 5591
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1521103663438551e-05,
+ "loss": 0.4974,
+ "step": 5592
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1518425236571797e-05,
+ "loss": 0.48,
+ "step": 5593
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1515746698198211e-05,
+ "loss": 0.4676,
+ "step": 5594
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1513068048514489e-05,
+ "loss": 0.4756,
+ "step": 5595
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1510389287717345e-05,
+ "loss": 0.4957,
+ "step": 5596
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.150771041600349e-05,
+ "loss": 0.4611,
+ "step": 5597
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1505031433569658e-05,
+ "loss": 0.4657,
+ "step": 5598
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1502352340612576e-05,
+ "loss": 0.4936,
+ "step": 5599
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1499673137328986e-05,
+ "loss": 0.4698,
+ "step": 5600
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1496993823915639e-05,
+ "loss": 0.4816,
+ "step": 5601
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1494314400569288e-05,
+ "loss": 0.4927,
+ "step": 5602
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1491634867486707e-05,
+ "loss": 0.4541,
+ "step": 5603
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1488955224864667e-05,
+ "loss": 0.48,
+ "step": 5604
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1486275472899943e-05,
+ "loss": 0.4936,
+ "step": 5605
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1483595611789336e-05,
+ "loss": 0.4853,
+ "step": 5606
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1480915641729633e-05,
+ "loss": 0.4817,
+ "step": 5607
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.147823556291765e-05,
+ "loss": 0.4931,
+ "step": 5608
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1475555375550191e-05,
+ "loss": 0.4849,
+ "step": 5609
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1472875079824087e-05,
+ "loss": 0.4649,
+ "step": 5610
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1470194675936159e-05,
+ "loss": 0.4762,
+ "step": 5611
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1467514164083252e-05,
+ "loss": 0.4908,
+ "step": 5612
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1464833544462203e-05,
+ "loss": 0.4826,
+ "step": 5613
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1462152817269879e-05,
+ "loss": 0.4964,
+ "step": 5614
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.145947198270313e-05,
+ "loss": 0.4881,
+ "step": 5615
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1456791040958828e-05,
+ "loss": 0.4719,
+ "step": 5616
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1454109992233851e-05,
+ "loss": 0.4977,
+ "step": 5617
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1451428836725087e-05,
+ "loss": 0.4921,
+ "step": 5618
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1448747574629424e-05,
+ "loss": 0.476,
+ "step": 5619
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1446066206143766e-05,
+ "loss": 0.4831,
+ "step": 5620
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1443384731465021e-05,
+ "loss": 0.4824,
+ "step": 5621
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1440703150790102e-05,
+ "loss": 0.4794,
+ "step": 5622
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1438021464315939e-05,
+ "loss": 0.4919,
+ "step": 5623
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.143533967223946e-05,
+ "loss": 0.4893,
+ "step": 5624
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1432657774757607e-05,
+ "loss": 0.4674,
+ "step": 5625
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1429975772067322e-05,
+ "loss": 0.4806,
+ "step": 5626
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1427293664365568e-05,
+ "loss": 0.5062,
+ "step": 5627
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1424611451849301e-05,
+ "loss": 0.4882,
+ "step": 5628
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1421929134715492e-05,
+ "loss": 0.4883,
+ "step": 5629
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1419246713161128e-05,
+ "loss": 0.4493,
+ "step": 5630
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1416564187383185e-05,
+ "loss": 0.4925,
+ "step": 5631
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1413881557578662e-05,
+ "loss": 0.4814,
+ "step": 5632
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1411198823944553e-05,
+ "loss": 0.4868,
+ "step": 5633
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1408515986677877e-05,
+ "loss": 0.4744,
+ "step": 5634
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1405833045975644e-05,
+ "loss": 0.4786,
+ "step": 5635
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.140315000203488e-05,
+ "loss": 0.4724,
+ "step": 5636
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1400466855052617e-05,
+ "loss": 0.4885,
+ "step": 5637
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.139778360522589e-05,
+ "loss": 0.4876,
+ "step": 5638
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.139510025275175e-05,
+ "loss": 0.4921,
+ "step": 5639
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.139241679782725e-05,
+ "loss": 0.5004,
+ "step": 5640
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1389733240649454e-05,
+ "loss": 0.4859,
+ "step": 5641
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1387049581415428e-05,
+ "loss": 0.4938,
+ "step": 5642
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.138436582032225e-05,
+ "loss": 0.4681,
+ "step": 5643
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1381681957567e-05,
+ "loss": 0.4845,
+ "step": 5644
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1378997993346782e-05,
+ "loss": 0.4733,
+ "step": 5645
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.137631392785868e-05,
+ "loss": 0.4937,
+ "step": 5646
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1373629761299811e-05,
+ "loss": 0.4775,
+ "step": 5647
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1370945493867284e-05,
+ "loss": 0.471,
+ "step": 5648
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1368261125758224e-05,
+ "loss": 0.4901,
+ "step": 5649
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1365576657169754e-05,
+ "loss": 0.4707,
+ "step": 5650
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.136289208829902e-05,
+ "loss": 0.4803,
+ "step": 5651
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1360207419343157e-05,
+ "loss": 0.4749,
+ "step": 5652
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1357522650499317e-05,
+ "loss": 0.4835,
+ "step": 5653
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.135483778196466e-05,
+ "loss": 0.4921,
+ "step": 5654
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1352152813936354e-05,
+ "loss": 0.4825,
+ "step": 5655
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1349467746611569e-05,
+ "loss": 0.4778,
+ "step": 5656
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1346782580187486e-05,
+ "loss": 0.4877,
+ "step": 5657
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1344097314861292e-05,
+ "loss": 0.5045,
+ "step": 5658
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1341411950830179e-05,
+ "loss": 0.4885,
+ "step": 5659
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1338726488291351e-05,
+ "loss": 0.4939,
+ "step": 5660
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1336040927442023e-05,
+ "loss": 0.4826,
+ "step": 5661
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1333355268479403e-05,
+ "loss": 0.4694,
+ "step": 5662
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1330669511600716e-05,
+ "loss": 0.467,
+ "step": 5663
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1327983657003197e-05,
+ "loss": 0.5067,
+ "step": 5664
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1325297704884081e-05,
+ "loss": 0.4779,
+ "step": 5665
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.132261165544062e-05,
+ "loss": 0.4802,
+ "step": 5666
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.131992550887005e-05,
+ "loss": 0.4811,
+ "step": 5667
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1317239265369648e-05,
+ "loss": 0.5074,
+ "step": 5668
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.131455292513667e-05,
+ "loss": 0.4494,
+ "step": 5669
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1311866488368392e-05,
+ "loss": 0.4755,
+ "step": 5670
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1309179955262097e-05,
+ "loss": 0.5055,
+ "step": 5671
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1306493326015074e-05,
+ "loss": 0.4714,
+ "step": 5672
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1303806600824613e-05,
+ "loss": 0.4855,
+ "step": 5673
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1301119779888015e-05,
+ "loss": 0.4815,
+ "step": 5674
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1298432863402595e-05,
+ "loss": 0.4807,
+ "step": 5675
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1295745851565667e-05,
+ "loss": 0.4727,
+ "step": 5676
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1293058744574552e-05,
+ "loss": 0.4793,
+ "step": 5677
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.129037154262658e-05,
+ "loss": 0.4741,
+ "step": 5678
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.128768424591909e-05,
+ "loss": 0.4584,
+ "step": 5679
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1284996854649424e-05,
+ "loss": 0.4911,
+ "step": 5680
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1282309369014937e-05,
+ "loss": 0.4811,
+ "step": 5681
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.127962178921298e-05,
+ "loss": 0.4769,
+ "step": 5682
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1276934115440924e-05,
+ "loss": 0.4743,
+ "step": 5683
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1274246347896136e-05,
+ "loss": 0.48,
+ "step": 5684
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1271558486775995e-05,
+ "loss": 0.4874,
+ "step": 5685
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1268870532277889e-05,
+ "loss": 0.463,
+ "step": 5686
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1266182484599209e-05,
+ "loss": 0.4752,
+ "step": 5687
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1263494343937354e-05,
+ "loss": 0.4682,
+ "step": 5688
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1260806110489726e-05,
+ "loss": 0.4947,
+ "step": 5689
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1258117784453746e-05,
+ "loss": 0.4735,
+ "step": 5690
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1255429366026826e-05,
+ "loss": 0.4578,
+ "step": 5691
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1252740855406397e-05,
+ "loss": 0.4827,
+ "step": 5692
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1250052252789891e-05,
+ "loss": 0.4848,
+ "step": 5693
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1247363558374745e-05,
+ "loss": 0.4687,
+ "step": 5694
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1244674772358406e-05,
+ "loss": 0.473,
+ "step": 5695
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.124198589493833e-05,
+ "loss": 0.4834,
+ "step": 5696
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1239296926311975e-05,
+ "loss": 0.4675,
+ "step": 5697
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.123660786667681e-05,
+ "loss": 0.4829,
+ "step": 5698
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1233918716230308e-05,
+ "loss": 0.4824,
+ "step": 5699
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1231229475169945e-05,
+ "loss": 0.4713,
+ "step": 5700
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1228540143693209e-05,
+ "loss": 0.4831,
+ "step": 5701
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.12258507219976e-05,
+ "loss": 0.4796,
+ "step": 5702
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.122316121028061e-05,
+ "loss": 0.4962,
+ "step": 5703
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1220471608739748e-05,
+ "loss": 0.4918,
+ "step": 5704
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1217781917572524e-05,
+ "loss": 0.4789,
+ "step": 5705
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1215092136976466e-05,
+ "loss": 0.5123,
+ "step": 5706
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1212402267149094e-05,
+ "loss": 0.478,
+ "step": 5707
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1209712308287941e-05,
+ "loss": 0.4826,
+ "step": 5708
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.120702226059055e-05,
+ "loss": 0.4965,
+ "step": 5709
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1204332124254463e-05,
+ "loss": 0.469,
+ "step": 5710
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1201641899477231e-05,
+ "loss": 0.4617,
+ "step": 5711
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.119895158645642e-05,
+ "loss": 0.4843,
+ "step": 5712
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1196261185389593e-05,
+ "loss": 0.4833,
+ "step": 5713
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1193570696474317e-05,
+ "loss": 0.4829,
+ "step": 5714
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1190880119908175e-05,
+ "loss": 0.4845,
+ "step": 5715
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1188189455888747e-05,
+ "loss": 0.4692,
+ "step": 5716
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1185498704613632e-05,
+ "loss": 0.4786,
+ "step": 5717
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1182807866280419e-05,
+ "loss": 0.4714,
+ "step": 5718
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1180116941086719e-05,
+ "loss": 0.4922,
+ "step": 5719
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1177425929230137e-05,
+ "loss": 0.4893,
+ "step": 5720
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.117473483090829e-05,
+ "loss": 0.476,
+ "step": 5721
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1172043646318809e-05,
+ "loss": 0.4827,
+ "step": 5722
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1169352375659314e-05,
+ "loss": 0.4936,
+ "step": 5723
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1166661019127447e-05,
+ "loss": 0.4858,
+ "step": 5724
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1163969576920846e-05,
+ "loss": 0.4639,
+ "step": 5725
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1161278049237157e-05,
+ "loss": 0.5047,
+ "step": 5726
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1158586436274042e-05,
+ "loss": 0.4743,
+ "step": 5727
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1155894738229156e-05,
+ "loss": 0.485,
+ "step": 5728
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.115320295530017e-05,
+ "loss": 0.4729,
+ "step": 5729
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1150511087684757e-05,
+ "loss": 0.4761,
+ "step": 5730
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1147819135580588e-05,
+ "loss": 0.4886,
+ "step": 5731
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1145127099185363e-05,
+ "loss": 0.4789,
+ "step": 5732
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1142434978696763e-05,
+ "loss": 0.495,
+ "step": 5733
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1139742774312495e-05,
+ "loss": 0.4717,
+ "step": 5734
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1137050486230251e-05,
+ "loss": 0.495,
+ "step": 5735
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1134358114647752e-05,
+ "loss": 0.4825,
+ "step": 5736
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1131665659762712e-05,
+ "loss": 0.476,
+ "step": 5737
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.112897312177285e-05,
+ "loss": 0.4794,
+ "step": 5738
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.11262805008759e-05,
+ "loss": 0.4632,
+ "step": 5739
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1123587797269596e-05,
+ "loss": 0.5031,
+ "step": 5740
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1120895011151675e-05,
+ "loss": 0.4687,
+ "step": 5741
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1118202142719887e-05,
+ "loss": 0.5017,
+ "step": 5742
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1115509192171988e-05,
+ "loss": 0.4941,
+ "step": 5743
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.111281615970573e-05,
+ "loss": 0.4736,
+ "step": 5744
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1110123045518882e-05,
+ "loss": 0.4698,
+ "step": 5745
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1107429849809215e-05,
+ "loss": 0.491,
+ "step": 5746
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1104736572774506e-05,
+ "loss": 0.4839,
+ "step": 5747
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1102043214612539e-05,
+ "loss": 0.4779,
+ "step": 5748
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1099349775521103e-05,
+ "loss": 0.4833,
+ "step": 5749
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1096656255697991e-05,
+ "loss": 0.4852,
+ "step": 5750
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1093962655341002e-05,
+ "loss": 0.4684,
+ "step": 5751
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1091268974647947e-05,
+ "loss": 0.4879,
+ "step": 5752
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.108857521381664e-05,
+ "loss": 0.4902,
+ "step": 5753
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1085881373044895e-05,
+ "loss": 0.4738,
+ "step": 5754
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1083187452530539e-05,
+ "loss": 0.4899,
+ "step": 5755
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1080493452471403e-05,
+ "loss": 0.4831,
+ "step": 5756
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1077799373065321e-05,
+ "loss": 0.4738,
+ "step": 5757
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1075105214510135e-05,
+ "loss": 0.4864,
+ "step": 5758
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1072410977003693e-05,
+ "loss": 0.4776,
+ "step": 5759
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1069716660743852e-05,
+ "loss": 0.4847,
+ "step": 5760
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1067022265928472e-05,
+ "loss": 0.482,
+ "step": 5761
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1064327792755405e-05,
+ "loss": 0.4857,
+ "step": 5762
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1061633241422538e-05,
+ "loss": 0.4833,
+ "step": 5763
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1058938612127744e-05,
+ "loss": 0.4706,
+ "step": 5764
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1056243905068899e-05,
+ "loss": 0.481,
+ "step": 5765
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1053549120443893e-05,
+ "loss": 0.4646,
+ "step": 5766
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1050854258450623e-05,
+ "loss": 0.4928,
+ "step": 5767
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.104815931928699e-05,
+ "loss": 0.4864,
+ "step": 5768
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1045464303150892e-05,
+ "loss": 0.4873,
+ "step": 5769
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1042769210240248e-05,
+ "loss": 0.4881,
+ "step": 5770
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1040074040752971e-05,
+ "loss": 0.4759,
+ "step": 5771
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1037378794886977e-05,
+ "loss": 0.4723,
+ "step": 5772
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1034683472840201e-05,
+ "loss": 0.468,
+ "step": 5773
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1031988074810578e-05,
+ "loss": 0.4803,
+ "step": 5774
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1029292600996042e-05,
+ "loss": 0.5059,
+ "step": 5775
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1026597051594534e-05,
+ "loss": 0.4792,
+ "step": 5776
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.102390142680401e-05,
+ "loss": 0.4762,
+ "step": 5777
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1021205726822429e-05,
+ "loss": 0.4988,
+ "step": 5778
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1018509951847743e-05,
+ "loss": 0.4742,
+ "step": 5779
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1015814102077921e-05,
+ "loss": 0.4762,
+ "step": 5780
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1013118177710942e-05,
+ "loss": 0.4947,
+ "step": 5781
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1010422178944772e-05,
+ "loss": 0.4727,
+ "step": 5782
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.10077261059774e-05,
+ "loss": 0.4662,
+ "step": 5783
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1005029959006818e-05,
+ "loss": 0.4927,
+ "step": 5784
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1002333738231016e-05,
+ "loss": 0.4872,
+ "step": 5785
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.099963744384799e-05,
+ "loss": 0.4899,
+ "step": 5786
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0996941076055751e-05,
+ "loss": 0.4824,
+ "step": 5787
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0994244635052304e-05,
+ "loss": 0.4645,
+ "step": 5788
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0991548121035664e-05,
+ "loss": 0.4843,
+ "step": 5789
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.098885153420386e-05,
+ "loss": 0.4767,
+ "step": 5790
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.098615487475491e-05,
+ "loss": 0.4897,
+ "step": 5791
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0983458142886848e-05,
+ "loss": 0.4754,
+ "step": 5792
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0980761338797707e-05,
+ "loss": 0.4671,
+ "step": 5793
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0978064462685536e-05,
+ "loss": 0.4932,
+ "step": 5794
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0975367514748378e-05,
+ "loss": 0.4822,
+ "step": 5795
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0972670495184286e-05,
+ "loss": 0.5096,
+ "step": 5796
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0969973404191322e-05,
+ "loss": 0.5035,
+ "step": 5797
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.096727624196754e-05,
+ "loss": 0.4778,
+ "step": 5798
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0964579008711018e-05,
+ "loss": 0.4801,
+ "step": 5799
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0961881704619823e-05,
+ "loss": 0.4845,
+ "step": 5800
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.095918432989204e-05,
+ "loss": 0.4793,
+ "step": 5801
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0956486884725748e-05,
+ "loss": 0.4717,
+ "step": 5802
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0953789369319031e-05,
+ "loss": 0.4756,
+ "step": 5803
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0951091783869998e-05,
+ "loss": 0.485,
+ "step": 5804
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0948394128576739e-05,
+ "loss": 0.496,
+ "step": 5805
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.094569640363736e-05,
+ "loss": 0.4963,
+ "step": 5806
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0942998609249968e-05,
+ "loss": 0.4884,
+ "step": 5807
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0940300745612679e-05,
+ "loss": 0.4687,
+ "step": 5808
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0937602812923617e-05,
+ "loss": 0.4779,
+ "step": 5809
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0934904811380904e-05,
+ "loss": 0.4892,
+ "step": 5810
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0932206741182672e-05,
+ "loss": 0.4831,
+ "step": 5811
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0929508602527052e-05,
+ "loss": 0.4711,
+ "step": 5812
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0926810395612187e-05,
+ "loss": 0.4934,
+ "step": 5813
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0924112120636222e-05,
+ "loss": 0.48,
+ "step": 5814
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0921413777797305e-05,
+ "loss": 0.4744,
+ "step": 5815
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0918715367293595e-05,
+ "loss": 0.4796,
+ "step": 5816
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0916016889323246e-05,
+ "loss": 0.4669,
+ "step": 5817
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0913318344084428e-05,
+ "loss": 0.4656,
+ "step": 5818
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0910619731775311e-05,
+ "loss": 0.4658,
+ "step": 5819
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0907921052594066e-05,
+ "loss": 0.4817,
+ "step": 5820
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0905222306738879e-05,
+ "loss": 0.4862,
+ "step": 5821
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0902523494407928e-05,
+ "loss": 0.4828,
+ "step": 5822
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0899824615799406e-05,
+ "loss": 0.4725,
+ "step": 5823
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0897125671111507e-05,
+ "loss": 0.4827,
+ "step": 5824
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.089442666054243e-05,
+ "loss": 0.4902,
+ "step": 5825
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0891727584290381e-05,
+ "loss": 0.465,
+ "step": 5826
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0889028442553565e-05,
+ "loss": 0.4795,
+ "step": 5827
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.08863292355302e-05,
+ "loss": 0.4693,
+ "step": 5828
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0883629963418501e-05,
+ "loss": 0.4781,
+ "step": 5829
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.088093062641669e-05,
+ "loss": 0.5004,
+ "step": 5830
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0878231224723001e-05,
+ "loss": 0.4815,
+ "step": 5831
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0875531758535668e-05,
+ "loss": 0.4879,
+ "step": 5832
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0872832228052919e-05,
+ "loss": 0.4919,
+ "step": 5833
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0870132633472999e-05,
+ "loss": 0.5049,
+ "step": 5834
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0867432974994162e-05,
+ "loss": 0.4874,
+ "step": 5835
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0864733252814654e-05,
+ "loss": 0.4906,
+ "step": 5836
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0862033467132732e-05,
+ "loss": 0.4875,
+ "step": 5837
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0859333618146659e-05,
+ "loss": 0.4617,
+ "step": 5838
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0856633706054698e-05,
+ "loss": 0.4761,
+ "step": 5839
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0853933731055122e-05,
+ "loss": 0.4735,
+ "step": 5840
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0851233693346204e-05,
+ "loss": 0.4843,
+ "step": 5841
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0848533593126225e-05,
+ "loss": 0.4845,
+ "step": 5842
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0845833430593467e-05,
+ "loss": 0.4731,
+ "step": 5843
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0843133205946218e-05,
+ "loss": 0.4897,
+ "step": 5844
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0840432919382774e-05,
+ "loss": 0.501,
+ "step": 5845
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0837732571101437e-05,
+ "loss": 0.4934,
+ "step": 5846
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0835032161300499e-05,
+ "loss": 0.4878,
+ "step": 5847
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0832331690178274e-05,
+ "loss": 0.4885,
+ "step": 5848
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0829631157933071e-05,
+ "loss": 0.4741,
+ "step": 5849
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0826930564763207e-05,
+ "loss": 0.5027,
+ "step": 5850
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0824229910867002e-05,
+ "loss": 0.4769,
+ "step": 5851
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0821529196442782e-05,
+ "loss": 0.4863,
+ "step": 5852
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0818828421688873e-05,
+ "loss": 0.4707,
+ "step": 5853
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.081612758680361e-05,
+ "loss": 0.4718,
+ "step": 5854
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0813426691985331e-05,
+ "loss": 0.469,
+ "step": 5855
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0810725737432381e-05,
+ "loss": 0.4993,
+ "step": 5856
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0808024723343104e-05,
+ "loss": 0.4695,
+ "step": 5857
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0805323649915854e-05,
+ "loss": 0.4555,
+ "step": 5858
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0802622517348982e-05,
+ "loss": 0.4673,
+ "step": 5859
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0799921325840851e-05,
+ "loss": 0.4788,
+ "step": 5860
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0797220075589825e-05,
+ "loss": 0.4518,
+ "step": 5861
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0794518766794272e-05,
+ "loss": 0.4822,
+ "step": 5862
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.079181739965257e-05,
+ "loss": 0.4787,
+ "step": 5863
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0789115974363086e-05,
+ "loss": 0.4897,
+ "step": 5864
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0786414491124208e-05,
+ "loss": 0.4997,
+ "step": 5865
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0783712950134324e-05,
+ "loss": 0.4807,
+ "step": 5866
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0781011351591819e-05,
+ "loss": 0.4609,
+ "step": 5867
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0778309695695088e-05,
+ "loss": 0.4857,
+ "step": 5868
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.077560798264253e-05,
+ "loss": 0.4819,
+ "step": 5869
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0772906212632547e-05,
+ "loss": 0.4784,
+ "step": 5870
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0770204385863547e-05,
+ "loss": 0.4976,
+ "step": 5871
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0767502502533945e-05,
+ "loss": 0.473,
+ "step": 5872
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0764800562842149e-05,
+ "loss": 0.4696,
+ "step": 5873
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0762098566986578e-05,
+ "loss": 0.4932,
+ "step": 5874
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0759396515165657e-05,
+ "loss": 0.4942,
+ "step": 5875
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.075669440757782e-05,
+ "loss": 0.4632,
+ "step": 5876
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.075399224442149e-05,
+ "loss": 0.477,
+ "step": 5877
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0751290025895104e-05,
+ "loss": 0.49,
+ "step": 5878
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0748587752197106e-05,
+ "loss": 0.4698,
+ "step": 5879
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0745885423525934e-05,
+ "loss": 0.4739,
+ "step": 5880
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0743183040080043e-05,
+ "loss": 0.4757,
+ "step": 5881
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0740480602057877e-05,
+ "loss": 0.4677,
+ "step": 5882
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0737778109657899e-05,
+ "loss": 0.4867,
+ "step": 5883
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0735075563078565e-05,
+ "loss": 0.4678,
+ "step": 5884
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0732372962518337e-05,
+ "loss": 0.4661,
+ "step": 5885
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0729670308175683e-05,
+ "loss": 0.4743,
+ "step": 5886
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.072696760024908e-05,
+ "loss": 0.4877,
+ "step": 5887
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0724264838936998e-05,
+ "loss": 0.4869,
+ "step": 5888
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0721562024437919e-05,
+ "loss": 0.4722,
+ "step": 5889
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0718859156950329e-05,
+ "loss": 0.4959,
+ "step": 5890
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.071615623667271e-05,
+ "loss": 0.4653,
+ "step": 5891
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0713453263803553e-05,
+ "loss": 0.4606,
+ "step": 5892
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.071075023854136e-05,
+ "loss": 0.49,
+ "step": 5893
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0708047161084626e-05,
+ "loss": 0.4895,
+ "step": 5894
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.070534403163185e-05,
+ "loss": 0.4806,
+ "step": 5895
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0702640850381542e-05,
+ "loss": 0.4713,
+ "step": 5896
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0699937617532216e-05,
+ "loss": 0.4832,
+ "step": 5897
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0697234333282382e-05,
+ "loss": 0.4784,
+ "step": 5898
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0694530997830556e-05,
+ "loss": 0.4696,
+ "step": 5899
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0691827611375268e-05,
+ "loss": 0.5059,
+ "step": 5900
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.068912417411503e-05,
+ "loss": 0.4705,
+ "step": 5901
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0686420686248382e-05,
+ "loss": 0.4696,
+ "step": 5902
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0683717147973856e-05,
+ "loss": 0.4935,
+ "step": 5903
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0681013559489985e-05,
+ "loss": 0.4837,
+ "step": 5904
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.067830992099531e-05,
+ "loss": 0.4748,
+ "step": 5905
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0675606232688377e-05,
+ "loss": 0.4827,
+ "step": 5906
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0672902494767731e-05,
+ "loss": 0.5115,
+ "step": 5907
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0670198707431927e-05,
+ "loss": 0.4813,
+ "step": 5908
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0667494870879513e-05,
+ "loss": 0.4771,
+ "step": 5909
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0664790985309058e-05,
+ "loss": 0.5049,
+ "step": 5910
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0662087050919111e-05,
+ "loss": 0.4861,
+ "step": 5911
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.065938306790825e-05,
+ "loss": 0.4752,
+ "step": 5912
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0656679036475038e-05,
+ "loss": 0.4789,
+ "step": 5913
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.065397495681805e-05,
+ "loss": 0.4715,
+ "step": 5914
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.065127082913586e-05,
+ "loss": 0.4669,
+ "step": 5915
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0648566653627048e-05,
+ "loss": 0.4878,
+ "step": 5916
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.06458624304902e-05,
+ "loss": 0.4657,
+ "step": 5917
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0643158159923902e-05,
+ "loss": 0.4867,
+ "step": 5918
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0640453842126742e-05,
+ "loss": 0.4842,
+ "step": 5919
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0637749477297317e-05,
+ "loss": 0.4846,
+ "step": 5920
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.063504506563422e-05,
+ "loss": 0.4753,
+ "step": 5921
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0632340607336056e-05,
+ "loss": 0.4803,
+ "step": 5922
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.062963610260143e-05,
+ "loss": 0.4649,
+ "step": 5923
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0626931551628948e-05,
+ "loss": 0.5102,
+ "step": 5924
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0624226954617221e-05,
+ "loss": 0.4758,
+ "step": 5925
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0621522311764857e-05,
+ "loss": 0.4701,
+ "step": 5926
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0618817623270484e-05,
+ "loss": 0.4919,
+ "step": 5927
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.061611288933272e-05,
+ "loss": 0.5002,
+ "step": 5928
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0613408110150185e-05,
+ "loss": 0.4994,
+ "step": 5929
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.061070328592151e-05,
+ "loss": 0.4734,
+ "step": 5930
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0607998416845329e-05,
+ "loss": 0.4737,
+ "step": 5931
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0605293503120268e-05,
+ "loss": 0.4695,
+ "step": 5932
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0602588544944972e-05,
+ "loss": 0.4705,
+ "step": 5933
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.059988354251808e-05,
+ "loss": 0.4683,
+ "step": 5934
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.059717849603824e-05,
+ "loss": 0.4895,
+ "step": 5935
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0594473405704088e-05,
+ "loss": 0.4732,
+ "step": 5936
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0591768271714285e-05,
+ "loss": 0.4844,
+ "step": 5937
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.058906309426748e-05,
+ "loss": 0.4746,
+ "step": 5938
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0586357873562332e-05,
+ "loss": 0.4765,
+ "step": 5939
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0583652609797501e-05,
+ "loss": 0.4753,
+ "step": 5940
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0580947303171651e-05,
+ "loss": 0.4755,
+ "step": 5941
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0578241953883445e-05,
+ "loss": 0.4855,
+ "step": 5942
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0575536562131556e-05,
+ "loss": 0.4863,
+ "step": 5943
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0572831128114658e-05,
+ "loss": 0.4672,
+ "step": 5944
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0570125652031425e-05,
+ "loss": 0.4928,
+ "step": 5945
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0567420134080531e-05,
+ "loss": 0.4896,
+ "step": 5946
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0564714574460664e-05,
+ "loss": 0.4839,
+ "step": 5947
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0562008973370508e-05,
+ "loss": 0.4808,
+ "step": 5948
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0559303331008752e-05,
+ "loss": 0.4783,
+ "step": 5949
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0556597647574083e-05,
+ "loss": 0.4887,
+ "step": 5950
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.05538919232652e-05,
+ "loss": 0.4867,
+ "step": 5951
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0551186158280795e-05,
+ "loss": 0.5122,
+ "step": 5952
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0548480352819573e-05,
+ "loss": 0.4623,
+ "step": 5953
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0545774507080237e-05,
+ "loss": 0.4677,
+ "step": 5954
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.054306862126149e-05,
+ "loss": 0.4772,
+ "step": 5955
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0540362695562043e-05,
+ "loss": 0.4747,
+ "step": 5956
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0537656730180606e-05,
+ "loss": 0.4751,
+ "step": 5957
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0534950725315893e-05,
+ "loss": 0.4904,
+ "step": 5958
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0532244681166628e-05,
+ "loss": 0.4845,
+ "step": 5959
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0529538597931524e-05,
+ "loss": 0.4788,
+ "step": 5960
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.052683247580931e-05,
+ "loss": 0.4771,
+ "step": 5961
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0524126314998711e-05,
+ "loss": 0.4895,
+ "step": 5962
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0521420115698448e-05,
+ "loss": 0.4743,
+ "step": 5963
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0518713878107268e-05,
+ "loss": 0.4543,
+ "step": 5964
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0516007602423896e-05,
+ "loss": 0.4893,
+ "step": 5965
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0513301288847076e-05,
+ "loss": 0.4831,
+ "step": 5966
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0510594937575537e-05,
+ "loss": 0.4739,
+ "step": 5967
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0507888548808034e-05,
+ "loss": 0.4901,
+ "step": 5968
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0505182122743309e-05,
+ "loss": 0.4903,
+ "step": 5969
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0502475659580107e-05,
+ "loss": 0.4827,
+ "step": 5970
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0499769159517186e-05,
+ "loss": 0.4875,
+ "step": 5971
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0497062622753296e-05,
+ "loss": 0.4978,
+ "step": 5972
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.049435604948719e-05,
+ "loss": 0.4832,
+ "step": 5973
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0491649439917636e-05,
+ "loss": 0.4586,
+ "step": 5974
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0488942794243393e-05,
+ "loss": 0.4639,
+ "step": 5975
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0486236112663224e-05,
+ "loss": 0.4936,
+ "step": 5976
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0483529395375896e-05,
+ "loss": 0.4603,
+ "step": 5977
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0480822642580178e-05,
+ "loss": 0.4836,
+ "step": 5978
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0478115854474848e-05,
+ "loss": 0.5113,
+ "step": 5979
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0475409031258678e-05,
+ "loss": 0.4747,
+ "step": 5980
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0472702173130447e-05,
+ "loss": 0.4841,
+ "step": 5981
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0469995280288936e-05,
+ "loss": 0.4726,
+ "step": 5982
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0467288352932923e-05,
+ "loss": 0.47,
+ "step": 5983
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0464581391261198e-05,
+ "loss": 0.4819,
+ "step": 5984
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0461874395472549e-05,
+ "loss": 0.4767,
+ "step": 5985
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0459167365765765e-05,
+ "loss": 0.4681,
+ "step": 5986
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0456460302339636e-05,
+ "loss": 0.4776,
+ "step": 5987
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0453753205392967e-05,
+ "loss": 0.4719,
+ "step": 5988
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0451046075124544e-05,
+ "loss": 0.4728,
+ "step": 5989
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0448338911733178e-05,
+ "loss": 0.4883,
+ "step": 5990
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0445631715417666e-05,
+ "loss": 0.5035,
+ "step": 5991
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0442924486376813e-05,
+ "loss": 0.4744,
+ "step": 5992
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0440217224809427e-05,
+ "loss": 0.498,
+ "step": 5993
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.043750993091432e-05,
+ "loss": 0.4707,
+ "step": 5994
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0434802604890306e-05,
+ "loss": 0.4854,
+ "step": 5995
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0432095246936195e-05,
+ "loss": 0.4768,
+ "step": 5996
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0429387857250806e-05,
+ "loss": 0.4729,
+ "step": 5997
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.042668043603296e-05,
+ "loss": 0.483,
+ "step": 5998
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0423972983481477e-05,
+ "loss": 0.4757,
+ "step": 5999
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0421265499795181e-05,
+ "loss": 0.4865,
+ "step": 6000
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0418557985172899e-05,
+ "loss": 0.4946,
+ "step": 6001
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0415850439813462e-05,
+ "loss": 0.4533,
+ "step": 6002
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0413142863915695e-05,
+ "loss": 0.4847,
+ "step": 6003
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0410435257678433e-05,
+ "loss": 0.4828,
+ "step": 6004
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0407727621300516e-05,
+ "loss": 0.4671,
+ "step": 6005
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0405019954980779e-05,
+ "loss": 0.4716,
+ "step": 6006
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0402312258918061e-05,
+ "loss": 0.4786,
+ "step": 6007
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.03996045333112e-05,
+ "loss": 0.4873,
+ "step": 6008
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0396896778359047e-05,
+ "loss": 0.479,
+ "step": 6009
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0394188994260445e-05,
+ "loss": 0.463,
+ "step": 6010
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0391481181214244e-05,
+ "loss": 0.4551,
+ "step": 6011
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0388773339419294e-05,
+ "loss": 0.4634,
+ "step": 6012
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0386065469074447e-05,
+ "loss": 0.4834,
+ "step": 6013
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0383357570378553e-05,
+ "loss": 0.4901,
+ "step": 6014
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0380649643530476e-05,
+ "loss": 0.4779,
+ "step": 6015
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0377941688729074e-05,
+ "loss": 0.4925,
+ "step": 6016
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0375233706173207e-05,
+ "loss": 0.4912,
+ "step": 6017
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0372525696061735e-05,
+ "loss": 0.4781,
+ "step": 6018
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0369817658593524e-05,
+ "loss": 0.4854,
+ "step": 6019
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0367109593967445e-05,
+ "loss": 0.4858,
+ "step": 6020
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0364401502382364e-05,
+ "loss": 0.4811,
+ "step": 6021
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0361693384037154e-05,
+ "loss": 0.4865,
+ "step": 6022
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0358985239130685e-05,
+ "loss": 0.4867,
+ "step": 6023
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.035627706786183e-05,
+ "loss": 0.4796,
+ "step": 6024
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.035356887042947e-05,
+ "loss": 0.486,
+ "step": 6025
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0350860647032488e-05,
+ "loss": 0.4733,
+ "step": 6026
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0348152397869757e-05,
+ "loss": 0.4706,
+ "step": 6027
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0345444123140159e-05,
+ "loss": 0.4709,
+ "step": 6028
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0342735823042585e-05,
+ "loss": 0.4718,
+ "step": 6029
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0340027497775915e-05,
+ "loss": 0.476,
+ "step": 6030
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0337319147539042e-05,
+ "loss": 0.4838,
+ "step": 6031
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0334610772530851e-05,
+ "loss": 0.4914,
+ "step": 6032
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.033190237295024e-05,
+ "loss": 0.4516,
+ "step": 6033
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0329193948996097e-05,
+ "loss": 0.4834,
+ "step": 6034
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0326485500867316e-05,
+ "loss": 0.4735,
+ "step": 6035
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0323777028762804e-05,
+ "loss": 0.4786,
+ "step": 6036
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0321068532881454e-05,
+ "loss": 0.4708,
+ "step": 6037
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0318360013422162e-05,
+ "loss": 0.5103,
+ "step": 6038
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0315651470583836e-05,
+ "loss": 0.5011,
+ "step": 6039
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0312942904565379e-05,
+ "loss": 0.4685,
+ "step": 6040
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0310234315565699e-05,
+ "loss": 0.4897,
+ "step": 6041
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0307525703783698e-05,
+ "loss": 0.489,
+ "step": 6042
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0304817069418292e-05,
+ "loss": 0.4754,
+ "step": 6043
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0302108412668387e-05,
+ "loss": 0.4889,
+ "step": 6044
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0299399733732893e-05,
+ "loss": 0.4967,
+ "step": 6045
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.029669103281073e-05,
+ "loss": 0.4701,
+ "step": 6046
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0293982310100814e-05,
+ "loss": 0.4751,
+ "step": 6047
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0291273565802058e-05,
+ "loss": 0.4912,
+ "step": 6048
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0288564800113383e-05,
+ "loss": 0.4817,
+ "step": 6049
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0285856013233708e-05,
+ "loss": 0.4599,
+ "step": 6050
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0283147205361959e-05,
+ "loss": 0.4964,
+ "step": 6051
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0280438376697056e-05,
+ "loss": 0.4632,
+ "step": 6052
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0277729527437924e-05,
+ "loss": 0.463,
+ "step": 6053
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0275020657783492e-05,
+ "loss": 0.493,
+ "step": 6054
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0272311767932686e-05,
+ "loss": 0.4833,
+ "step": 6055
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0269602858084435e-05,
+ "loss": 0.4912,
+ "step": 6056
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0266893928437673e-05,
+ "loss": 0.481,
+ "step": 6057
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0264184979191331e-05,
+ "loss": 0.4745,
+ "step": 6058
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0261476010544345e-05,
+ "loss": 0.4958,
+ "step": 6059
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0258767022695645e-05,
+ "loss": 0.491,
+ "step": 6060
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0256058015844173e-05,
+ "loss": 0.4881,
+ "step": 6061
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0253348990188863e-05,
+ "loss": 0.4736,
+ "step": 6062
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.025063994592866e-05,
+ "loss": 0.4744,
+ "step": 6063
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.02479308832625e-05,
+ "loss": 0.4759,
+ "step": 6064
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0245221802389328e-05,
+ "loss": 0.4655,
+ "step": 6065
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0242512703508085e-05,
+ "loss": 0.4912,
+ "step": 6066
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.023980358681772e-05,
+ "loss": 0.4852,
+ "step": 6067
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0237094452517178e-05,
+ "loss": 0.4838,
+ "step": 6068
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0234385300805403e-05,
+ "loss": 0.4851,
+ "step": 6069
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0231676131881348e-05,
+ "loss": 0.4732,
+ "step": 6070
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.022896694594396e-05,
+ "loss": 0.4902,
+ "step": 6071
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.022625774319219e-05,
+ "loss": 0.4603,
+ "step": 6072
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0223548523824996e-05,
+ "loss": 0.4785,
+ "step": 6073
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0220839288041328e-05,
+ "loss": 0.4651,
+ "step": 6074
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.021813003604014e-05,
+ "loss": 0.4707,
+ "step": 6075
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0215420768020388e-05,
+ "loss": 0.5073,
+ "step": 6076
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0212711484181034e-05,
+ "loss": 0.4872,
+ "step": 6077
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0210002184721033e-05,
+ "loss": 0.4836,
+ "step": 6078
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0207292869839343e-05,
+ "loss": 0.46,
+ "step": 6079
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.020458353973493e-05,
+ "loss": 0.4641,
+ "step": 6080
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0201874194606748e-05,
+ "loss": 0.4703,
+ "step": 6081
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.019916483465377e-05,
+ "loss": 0.4775,
+ "step": 6082
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.019645546007495e-05,
+ "loss": 0.4857,
+ "step": 6083
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0193746071069262e-05,
+ "loss": 0.4703,
+ "step": 6084
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0191036667835668e-05,
+ "loss": 0.4713,
+ "step": 6085
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0188327250573133e-05,
+ "loss": 0.4823,
+ "step": 6086
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0185617819480628e-05,
+ "loss": 0.4943,
+ "step": 6087
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0182908374757126e-05,
+ "loss": 0.4849,
+ "step": 6088
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0180198916601592e-05,
+ "loss": 0.4815,
+ "step": 6089
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0177489445212998e-05,
+ "loss": 0.486,
+ "step": 6090
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0174779960790318e-05,
+ "loss": 0.4575,
+ "step": 6091
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0172070463532524e-05,
+ "loss": 0.4709,
+ "step": 6092
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.016936095363859e-05,
+ "loss": 0.4649,
+ "step": 6093
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0166651431307494e-05,
+ "loss": 0.4872,
+ "step": 6094
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0163941896738213e-05,
+ "loss": 0.4819,
+ "step": 6095
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0161232350129715e-05,
+ "loss": 0.4658,
+ "step": 6096
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0158522791680985e-05,
+ "loss": 0.4744,
+ "step": 6097
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0155813221591004e-05,
+ "loss": 0.4849,
+ "step": 6098
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0153103640058745e-05,
+ "loss": 0.4775,
+ "step": 6099
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0150394047283192e-05,
+ "loss": 0.4644,
+ "step": 6100
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0147684443463328e-05,
+ "loss": 0.4933,
+ "step": 6101
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0144974828798131e-05,
+ "loss": 0.4612,
+ "step": 6102
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0142265203486583e-05,
+ "loss": 0.4857,
+ "step": 6103
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0139555567727674e-05,
+ "loss": 0.4879,
+ "step": 6104
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0136845921720385e-05,
+ "loss": 0.4769,
+ "step": 6105
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0134136265663698e-05,
+ "loss": 0.4763,
+ "step": 6106
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.01314265997566e-05,
+ "loss": 0.4778,
+ "step": 6107
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0128716924198083e-05,
+ "loss": 0.4715,
+ "step": 6108
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.012600723918713e-05,
+ "loss": 0.468,
+ "step": 6109
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0123297544922728e-05,
+ "loss": 0.5026,
+ "step": 6110
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0120587841603868e-05,
+ "loss": 0.4965,
+ "step": 6111
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.011787812942954e-05,
+ "loss": 0.4759,
+ "step": 6112
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0115168408598728e-05,
+ "loss": 0.4755,
+ "step": 6113
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.011245867931043e-05,
+ "loss": 0.4671,
+ "step": 6114
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0109748941763635e-05,
+ "loss": 0.4646,
+ "step": 6115
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0107039196157335e-05,
+ "loss": 0.4868,
+ "step": 6116
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.010432944269052e-05,
+ "loss": 0.4626,
+ "step": 6117
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0101619681562183e-05,
+ "loss": 0.4982,
+ "step": 6118
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0098909912971322e-05,
+ "loss": 0.4729,
+ "step": 6119
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0096200137116924e-05,
+ "loss": 0.4953,
+ "step": 6120
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0093490354197994e-05,
+ "loss": 0.4823,
+ "step": 6121
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0090780564413518e-05,
+ "loss": 0.4974,
+ "step": 6122
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0088070767962497e-05,
+ "loss": 0.4955,
+ "step": 6123
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0085360965043923e-05,
+ "loss": 0.4789,
+ "step": 6124
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0082651155856795e-05,
+ "loss": 0.4786,
+ "step": 6125
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.007994134060011e-05,
+ "loss": 0.4877,
+ "step": 6126
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0077231519472866e-05,
+ "loss": 0.4656,
+ "step": 6127
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.007452169267406e-05,
+ "loss": 0.4981,
+ "step": 6128
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0071811860402692e-05,
+ "loss": 0.5001,
+ "step": 6129
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0069102022857757e-05,
+ "loss": 0.4817,
+ "step": 6130
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0066392180238258e-05,
+ "loss": 0.4879,
+ "step": 6131
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0063682332743196e-05,
+ "loss": 0.4897,
+ "step": 6132
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0060972480571565e-05,
+ "loss": 0.4781,
+ "step": 6133
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0058262623922368e-05,
+ "loss": 0.4542,
+ "step": 6134
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.005555276299461e-05,
+ "loss": 0.4887,
+ "step": 6135
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0052842897987288e-05,
+ "loss": 0.4949,
+ "step": 6136
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0050133029099401e-05,
+ "loss": 0.4703,
+ "step": 6137
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0047423156529952e-05,
+ "loss": 0.4776,
+ "step": 6138
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0044713280477946e-05,
+ "loss": 0.4973,
+ "step": 6139
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0042003401142383e-05,
+ "loss": 0.4845,
+ "step": 6140
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0039293518722262e-05,
+ "loss": 0.4794,
+ "step": 6141
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0036583633416593e-05,
+ "loss": 0.4974,
+ "step": 6142
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0033873745424369e-05,
+ "loss": 0.4832,
+ "step": 6143
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.00311638549446e-05,
+ "loss": 0.4864,
+ "step": 6144
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0028453962176287e-05,
+ "loss": 0.4641,
+ "step": 6145
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0025744067318435e-05,
+ "loss": 0.4801,
+ "step": 6146
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0023034170570044e-05,
+ "loss": 0.4759,
+ "step": 6147
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0020324272130117e-05,
+ "loss": 0.4816,
+ "step": 6148
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0017614372197667e-05,
+ "loss": 0.4867,
+ "step": 6149
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0014904470971686e-05,
+ "loss": 0.4779,
+ "step": 6150
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0012194568651184e-05,
+ "loss": 0.4897,
+ "step": 6151
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0009484665435163e-05,
+ "loss": 0.4805,
+ "step": 6152
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0006774761522626e-05,
+ "loss": 0.4745,
+ "step": 6153
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.000406485711258e-05,
+ "loss": 0.4776,
+ "step": 6154
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0001354952404027e-05,
+ "loss": 0.4708,
+ "step": 6155
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.998645047595975e-06,
+ "loss": 0.4719,
+ "step": 6156
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.995935142887424e-06,
+ "loss": 0.4778,
+ "step": 6157
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.993225238477377e-06,
+ "loss": 0.479,
+ "step": 6158
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.99051533456484e-06,
+ "loss": 0.4616,
+ "step": 6159
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.987805431348818e-06,
+ "loss": 0.4924,
+ "step": 6160
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.985095529028317e-06,
+ "loss": 0.4886,
+ "step": 6161
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.982385627802338e-06,
+ "loss": 0.473,
+ "step": 6162
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.979675727869884e-06,
+ "loss": 0.5046,
+ "step": 6163
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.976965829429958e-06,
+ "loss": 0.4845,
+ "step": 6164
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.97425593268157e-06,
+ "loss": 0.4805,
+ "step": 6165
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.971546037823713e-06,
+ "loss": 0.4887,
+ "step": 6166
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.968836145055402e-06,
+ "loss": 0.4882,
+ "step": 6167
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.966126254575634e-06,
+ "loss": 0.4744,
+ "step": 6168
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.963416366583412e-06,
+ "loss": 0.4752,
+ "step": 6169
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.960706481277742e-06,
+ "loss": 0.4858,
+ "step": 6170
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.957996598857622e-06,
+ "loss": 0.4589,
+ "step": 6171
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.955286719522059e-06,
+ "loss": 0.4713,
+ "step": 6172
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.952576843470048e-06,
+ "loss": 0.5407,
+ "step": 6173
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.949866970900602e-06,
+ "loss": 0.4929,
+ "step": 6174
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.947157102012716e-06,
+ "loss": 0.4734,
+ "step": 6175
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.944447237005392e-06,
+ "loss": 0.4758,
+ "step": 6176
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.941737376077634e-06,
+ "loss": 0.4628,
+ "step": 6177
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.93902751942844e-06,
+ "loss": 0.4739,
+ "step": 6178
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.93631766725681e-06,
+ "loss": 0.4739,
+ "step": 6179
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.93360781976174e-06,
+ "loss": 0.488,
+ "step": 6180
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.930897977142245e-06,
+ "loss": 0.484,
+ "step": 6181
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.928188139597313e-06,
+ "loss": 0.4858,
+ "step": 6182
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.925478307325944e-06,
+ "loss": 0.4791,
+ "step": 6183
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.922768480527138e-06,
+ "loss": 0.4836,
+ "step": 6184
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.920058659399895e-06,
+ "loss": 0.471,
+ "step": 6185
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.91734884414321e-06,
+ "loss": 0.4773,
+ "step": 6186
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.914639034956079e-06,
+ "loss": 0.4778,
+ "step": 6187
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.911929232037507e-06,
+ "loss": 0.4983,
+ "step": 6188
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.909219435586485e-06,
+ "loss": 0.4768,
+ "step": 6189
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.906509645802009e-06,
+ "loss": 0.4848,
+ "step": 6190
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.903799862883077e-06,
+ "loss": 0.4802,
+ "step": 6191
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.901090087028685e-06,
+ "loss": 0.4775,
+ "step": 6192
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.898380318437822e-06,
+ "loss": 0.4846,
+ "step": 6193
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.895670557309484e-06,
+ "loss": 0.4832,
+ "step": 6194
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.892960803842668e-06,
+ "loss": 0.4866,
+ "step": 6195
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.890251058236368e-06,
+ "loss": 0.4776,
+ "step": 6196
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.887541320689573e-06,
+ "loss": 0.4772,
+ "step": 6197
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.884831591401276e-06,
+ "loss": 0.5,
+ "step": 6198
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.882121870570465e-06,
+ "loss": 0.4832,
+ "step": 6199
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.879412158396134e-06,
+ "loss": 0.4802,
+ "step": 6200
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.876702455077272e-06,
+ "loss": 0.4718,
+ "step": 6201
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.873992760812871e-06,
+ "loss": 0.4742,
+ "step": 6202
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.87128307580192e-06,
+ "loss": 0.4717,
+ "step": 6203
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.868573400243402e-06,
+ "loss": 0.4813,
+ "step": 6204
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.865863734336305e-06,
+ "loss": 0.4895,
+ "step": 6205
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.86315407827962e-06,
+ "loss": 0.4889,
+ "step": 6206
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.860444432272328e-06,
+ "loss": 0.4873,
+ "step": 6207
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.857734796513417e-06,
+ "loss": 0.4915,
+ "step": 6208
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.855025171201874e-06,
+ "loss": 0.4696,
+ "step": 6209
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.852315556536674e-06,
+ "loss": 0.4605,
+ "step": 6210
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.84960595271681e-06,
+ "loss": 0.4808,
+ "step": 6211
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.846896359941258e-06,
+ "loss": 0.4867,
+ "step": 6212
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.844186778409002e-06,
+ "loss": 0.4805,
+ "step": 6213
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.841477208319015e-06,
+ "loss": 0.4754,
+ "step": 6214
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.838767649870287e-06,
+ "loss": 0.4691,
+ "step": 6215
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.83605810326179e-06,
+ "loss": 0.4701,
+ "step": 6216
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.833348568692507e-06,
+ "loss": 0.4799,
+ "step": 6217
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.830639046361412e-06,
+ "loss": 0.4803,
+ "step": 6218
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.82792953646748e-06,
+ "loss": 0.4602,
+ "step": 6219
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.825220039209687e-06,
+ "loss": 0.4757,
+ "step": 6220
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.822510554787004e-06,
+ "loss": 0.4817,
+ "step": 6221
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.819801083398411e-06,
+ "loss": 0.4772,
+ "step": 6222
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.817091625242879e-06,
+ "loss": 0.4876,
+ "step": 6223
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.814382180519375e-06,
+ "loss": 0.4803,
+ "step": 6224
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.81167274942687e-06,
+ "loss": 0.4761,
+ "step": 6225
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.808963332164337e-06,
+ "loss": 0.4727,
+ "step": 6226
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.806253928930743e-06,
+ "loss": 0.468,
+ "step": 6227
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.80354453992505e-06,
+ "loss": 0.4583,
+ "step": 6228
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.800835165346234e-06,
+ "loss": 0.4972,
+ "step": 6229
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.798125805393255e-06,
+ "loss": 0.4874,
+ "step": 6230
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.795416460265074e-06,
+ "loss": 0.4627,
+ "step": 6231
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.79270713016066e-06,
+ "loss": 0.5072,
+ "step": 6232
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.789997815278973e-06,
+ "loss": 0.4845,
+ "step": 6233
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.787288515818968e-06,
+ "loss": 0.4799,
+ "step": 6234
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.784579231979612e-06,
+ "loss": 0.47,
+ "step": 6235
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.781869963959861e-06,
+ "loss": 0.4865,
+ "step": 6236
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.779160711958673e-06,
+ "loss": 0.4727,
+ "step": 6237
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.776451476175006e-06,
+ "loss": 0.4904,
+ "step": 6238
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.773742256807812e-06,
+ "loss": 0.4865,
+ "step": 6239
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.771033054056044e-06,
+ "loss": 0.4669,
+ "step": 6240
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.768323868118656e-06,
+ "loss": 0.4877,
+ "step": 6241
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.765614699194598e-06,
+ "loss": 0.469,
+ "step": 6242
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.762905547482825e-06,
+ "loss": 0.473,
+ "step": 6243
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.760196413182283e-06,
+ "loss": 0.4738,
+ "step": 6244
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.757487296491918e-06,
+ "loss": 0.4813,
+ "step": 6245
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.754778197610674e-06,
+ "loss": 0.4992,
+ "step": 6246
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.752069116737504e-06,
+ "loss": 0.4679,
+ "step": 6247
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.74936005407134e-06,
+ "loss": 0.456,
+ "step": 6248
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.746651009811137e-06,
+ "loss": 0.4749,
+ "step": 6249
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.74394198415583e-06,
+ "loss": 0.4758,
+ "step": 6250
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.741232977304356e-06,
+ "loss": 0.4719,
+ "step": 6251
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.738523989455659e-06,
+ "loss": 0.4639,
+ "step": 6252
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.735815020808672e-06,
+ "loss": 0.4738,
+ "step": 6253
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.733106071562332e-06,
+ "loss": 0.4639,
+ "step": 6254
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.730397141915567e-06,
+ "loss": 0.4905,
+ "step": 6255
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.727688232067318e-06,
+ "loss": 0.4697,
+ "step": 6256
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.72497934221651e-06,
+ "loss": 0.4867,
+ "step": 6257
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.722270472562078e-06,
+ "loss": 0.4721,
+ "step": 6258
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.71956162330295e-06,
+ "loss": 0.4716,
+ "step": 6259
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.716852794638046e-06,
+ "loss": 0.4712,
+ "step": 6260
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.714143986766294e-06,
+ "loss": 0.4798,
+ "step": 6261
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.711435199886618e-06,
+ "loss": 0.4679,
+ "step": 6262
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.708726434197944e-06,
+ "loss": 0.4605,
+ "step": 6263
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.706017689899189e-06,
+ "loss": 0.4812,
+ "step": 6264
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.703308967189273e-06,
+ "loss": 0.4768,
+ "step": 6265
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.700600266267109e-06,
+ "loss": 0.4735,
+ "step": 6266
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.697891587331618e-06,
+ "loss": 0.4862,
+ "step": 6267
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.695182930581715e-06,
+ "loss": 0.4751,
+ "step": 6268
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.692474296216303e-06,
+ "loss": 0.4512,
+ "step": 6269
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.689765684434305e-06,
+ "loss": 0.4947,
+ "step": 6270
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.687057095434624e-06,
+ "loss": 0.4816,
+ "step": 6271
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.684348529416166e-06,
+ "loss": 0.4744,
+ "step": 6272
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.681639986577841e-06,
+ "loss": 0.4612,
+ "step": 6273
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.678931467118553e-06,
+ "loss": 0.4734,
+ "step": 6274
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.676222971237197e-06,
+ "loss": 0.4665,
+ "step": 6275
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.673514499132683e-06,
+ "loss": 0.4761,
+ "step": 6276
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.670806051003906e-06,
+ "loss": 0.4849,
+ "step": 6277
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.668097627049765e-06,
+ "loss": 0.479,
+ "step": 6278
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.665389227469152e-06,
+ "loss": 0.471,
+ "step": 6279
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.662680852460963e-06,
+ "loss": 0.4824,
+ "step": 6280
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.659972502224089e-06,
+ "loss": 0.4746,
+ "step": 6281
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.657264176957419e-06,
+ "loss": 0.4834,
+ "step": 6282
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.654555876859841e-06,
+ "loss": 0.4928,
+ "step": 6283
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.651847602130247e-06,
+ "loss": 0.4866,
+ "step": 6284
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.649139352967515e-06,
+ "loss": 0.4769,
+ "step": 6285
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.646431129570531e-06,
+ "loss": 0.4794,
+ "step": 6286
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.643722932138172e-06,
+ "loss": 0.4776,
+ "step": 6287
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.64101476086932e-06,
+ "loss": 0.4743,
+ "step": 6288
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.638306615962847e-06,
+ "loss": 0.4793,
+ "step": 6289
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.635598497617636e-06,
+ "loss": 0.4823,
+ "step": 6290
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.632890406032556e-06,
+ "loss": 0.467,
+ "step": 6291
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.630182341406477e-06,
+ "loss": 0.4598,
+ "step": 6292
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.627474303938267e-06,
+ "loss": 0.4697,
+ "step": 6293
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.624766293826798e-06,
+ "loss": 0.4777,
+ "step": 6294
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.62205831127093e-06,
+ "loss": 0.4762,
+ "step": 6295
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.619350356469524e-06,
+ "loss": 0.4949,
+ "step": 6296
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.616642429621449e-06,
+ "loss": 0.4867,
+ "step": 6297
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.613934530925556e-06,
+ "loss": 0.4907,
+ "step": 6298
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.611226660580709e-06,
+ "loss": 0.4929,
+ "step": 6299
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.60851881878576e-06,
+ "loss": 0.4616,
+ "step": 6300
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.605811005739558e-06,
+ "loss": 0.4869,
+ "step": 6301
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.603103221640956e-06,
+ "loss": 0.4846,
+ "step": 6302
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.600395466688801e-06,
+ "loss": 0.4695,
+ "step": 6303
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.597687741081942e-06,
+ "loss": 0.4904,
+ "step": 6304
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.594980045019224e-06,
+ "loss": 0.4837,
+ "step": 6305
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.592272378699486e-06,
+ "loss": 0.4682,
+ "step": 6306
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.589564742321569e-06,
+ "loss": 0.4882,
+ "step": 6307
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.586857136084309e-06,
+ "loss": 0.483,
+ "step": 6308
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.58414956018654e-06,
+ "loss": 0.4886,
+ "step": 6309
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.581442014827101e-06,
+ "loss": 0.491,
+ "step": 6310
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.57873450020482e-06,
+ "loss": 0.4758,
+ "step": 6311
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.576027016518527e-06,
+ "loss": 0.4617,
+ "step": 6312
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.573319563967043e-06,
+ "loss": 0.4783,
+ "step": 6313
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.570612142749196e-06,
+ "loss": 0.4769,
+ "step": 6314
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.56790475306381e-06,
+ "loss": 0.4733,
+ "step": 6315
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.565197395109694e-06,
+ "loss": 0.4816,
+ "step": 6316
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.56249006908568e-06,
+ "loss": 0.4784,
+ "step": 6317
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.559782775190574e-06,
+ "loss": 0.4769,
+ "step": 6318
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.55707551362319e-06,
+ "loss": 0.4679,
+ "step": 6319
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.554368284582339e-06,
+ "loss": 0.4917,
+ "step": 6320
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.551661088266825e-06,
+ "loss": 0.4883,
+ "step": 6321
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.548953924875459e-06,
+ "loss": 0.4608,
+ "step": 6322
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.546246794607037e-06,
+ "loss": 0.4799,
+ "step": 6323
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.543539697660363e-06,
+ "loss": 0.4842,
+ "step": 6324
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.540832634234238e-06,
+ "loss": 0.4864,
+ "step": 6325
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.538125604527455e-06,
+ "loss": 0.4847,
+ "step": 6326
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.535418608738808e-06,
+ "loss": 0.5013,
+ "step": 6327
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.53271164706708e-06,
+ "loss": 0.4738,
+ "step": 6328
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.53000471971107e-06,
+ "loss": 0.4796,
+ "step": 6329
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.527297826869553e-06,
+ "loss": 0.4594,
+ "step": 6330
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.524590968741324e-06,
+ "loss": 0.4737,
+ "step": 6331
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.521884145525153e-06,
+ "loss": 0.4757,
+ "step": 6332
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.519177357419824e-06,
+ "loss": 0.5014,
+ "step": 6333
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.516470604624109e-06,
+ "loss": 0.4906,
+ "step": 6334
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.513763887336781e-06,
+ "loss": 0.4728,
+ "step": 6335
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.511057205756614e-06,
+ "loss": 0.4792,
+ "step": 6336
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.508350560082364e-06,
+ "loss": 0.4579,
+ "step": 6337
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.505643950512811e-06,
+ "loss": 0.4688,
+ "step": 6338
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.502937377246707e-06,
+ "loss": 0.489,
+ "step": 6339
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.500230840482817e-06,
+ "loss": 0.4965,
+ "step": 6340
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.497524340419896e-06,
+ "loss": 0.4631,
+ "step": 6341
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.494817877256696e-06,
+ "loss": 0.4601,
+ "step": 6342
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.49211145119197e-06,
+ "loss": 0.4815,
+ "step": 6343
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.489405062424464e-06,
+ "loss": 0.4815,
+ "step": 6344
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.486698711152928e-06,
+ "loss": 0.489,
+ "step": 6345
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.483992397576106e-06,
+ "loss": 0.4806,
+ "step": 6346
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.481286121892734e-06,
+ "loss": 0.4701,
+ "step": 6347
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.478579884301554e-06,
+ "loss": 0.4687,
+ "step": 6348
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.475873685001295e-06,
+ "loss": 0.4647,
+ "step": 6349
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.473167524190692e-06,
+ "loss": 0.4665,
+ "step": 6350
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.470461402068478e-06,
+ "loss": 0.4681,
+ "step": 6351
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.467755318833376e-06,
+ "loss": 0.482,
+ "step": 6352
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.46504927468411e-06,
+ "loss": 0.4852,
+ "step": 6353
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.462343269819398e-06,
+ "loss": 0.4887,
+ "step": 6354
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.459637304437962e-06,
+ "loss": 0.4993,
+ "step": 6355
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.456931378738515e-06,
+ "loss": 0.4926,
+ "step": 6356
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.454225492919765e-06,
+ "loss": 0.4916,
+ "step": 6357
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.451519647180427e-06,
+ "loss": 0.4718,
+ "step": 6358
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.448813841719207e-06,
+ "loss": 0.4794,
+ "step": 6359
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.446108076734803e-06,
+ "loss": 0.461,
+ "step": 6360
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.44340235242592e-06,
+ "loss": 0.486,
+ "step": 6361
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.440696668991253e-06,
+ "loss": 0.467,
+ "step": 6362
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.437991026629497e-06,
+ "loss": 0.4657,
+ "step": 6363
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.435285425539337e-06,
+ "loss": 0.4854,
+ "step": 6364
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.43257986591947e-06,
+ "loss": 0.4839,
+ "step": 6365
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.42987434796858e-06,
+ "loss": 0.4686,
+ "step": 6366
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.427168871885345e-06,
+ "loss": 0.4639,
+ "step": 6367
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.424463437868445e-06,
+ "loss": 0.4912,
+ "step": 6368
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.421758046116557e-06,
+ "loss": 0.4673,
+ "step": 6369
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.419052696828352e-06,
+ "loss": 0.4861,
+ "step": 6370
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.416347390202499e-06,
+ "loss": 0.4816,
+ "step": 6371
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.41364212643767e-06,
+ "loss": 0.4647,
+ "step": 6372
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.410936905732522e-06,
+ "loss": 0.4781,
+ "step": 6373
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.40823172828572e-06,
+ "loss": 0.4912,
+ "step": 6374
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.405526594295915e-06,
+ "loss": 0.4641,
+ "step": 6375
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.402821503961766e-06,
+ "loss": 0.4802,
+ "step": 6376
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.400116457481924e-06,
+ "loss": 0.4938,
+ "step": 6377
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.397411455055028e-06,
+ "loss": 0.4878,
+ "step": 6378
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.394706496879733e-06,
+ "loss": 0.4762,
+ "step": 6379
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.392001583154675e-06,
+ "loss": 0.4799,
+ "step": 6380
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.389296714078493e-06,
+ "loss": 0.4966,
+ "step": 6381
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.386591889849819e-06,
+ "loss": 0.4841,
+ "step": 6382
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.383887110667285e-06,
+ "loss": 0.5037,
+ "step": 6383
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.381182376729516e-06,
+ "loss": 0.4769,
+ "step": 6384
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.378477688235144e-06,
+ "loss": 0.4716,
+ "step": 6385
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.375773045382782e-06,
+ "loss": 0.4908,
+ "step": 6386
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.373068448371054e-06,
+ "loss": 0.4506,
+ "step": 6387
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.370363897398573e-06,
+ "loss": 0.4837,
+ "step": 6388
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.367659392663947e-06,
+ "loss": 0.4797,
+ "step": 6389
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.364954934365783e-06,
+ "loss": 0.4906,
+ "step": 6390
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.362250522702685e-06,
+ "loss": 0.4653,
+ "step": 6391
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.35954615787326e-06,
+ "loss": 0.4811,
+ "step": 6392
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.356841840076102e-06,
+ "loss": 0.4746,
+ "step": 6393
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.354137569509804e-06,
+ "loss": 0.4864,
+ "step": 6394
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.351433346372955e-06,
+ "loss": 0.4882,
+ "step": 6395
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.348729170864145e-06,
+ "loss": 0.4855,
+ "step": 6396
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.346025043181955e-06,
+ "loss": 0.4606,
+ "step": 6397
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.343320963524964e-06,
+ "loss": 0.482,
+ "step": 6398
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.340616932091752e-06,
+ "loss": 0.4876,
+ "step": 6399
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.33791294908089e-06,
+ "loss": 0.4936,
+ "step": 6400
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.335209014690946e-06,
+ "loss": 0.495,
+ "step": 6401
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.332505129120489e-06,
+ "loss": 0.4882,
+ "step": 6402
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.32980129256808e-06,
+ "loss": 0.4871,
+ "step": 6403
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.327097505232274e-06,
+ "loss": 0.4526,
+ "step": 6404
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.324393767311625e-06,
+ "loss": 0.4816,
+ "step": 6405
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.321690079004691e-06,
+ "loss": 0.4765,
+ "step": 6406
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.318986440510018e-06,
+ "loss": 0.4737,
+ "step": 6407
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.316282852026147e-06,
+ "loss": 0.4784,
+ "step": 6408
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.313579313751621e-06,
+ "loss": 0.4744,
+ "step": 6409
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.310875825884972e-06,
+ "loss": 0.4675,
+ "step": 6410
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.308172388624739e-06,
+ "loss": 0.465,
+ "step": 6411
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.305469002169442e-06,
+ "loss": 0.477,
+ "step": 6412
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.30276566671762e-06,
+ "loss": 0.4649,
+ "step": 6413
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.300062382467785e-06,
+ "loss": 0.4649,
+ "step": 6414
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.29735914961846e-06,
+ "loss": 0.468,
+ "step": 6415
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.294655968368153e-06,
+ "loss": 0.4863,
+ "step": 6416
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.291952838915379e-06,
+ "loss": 0.4815,
+ "step": 6417
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.289249761458643e-06,
+ "loss": 0.4916,
+ "step": 6418
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.286546736196447e-06,
+ "loss": 0.4722,
+ "step": 6419
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.283843763327293e-06,
+ "loss": 0.5097,
+ "step": 6420
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.281140843049674e-06,
+ "loss": 0.4785,
+ "step": 6421
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.278437975562083e-06,
+ "loss": 0.4712,
+ "step": 6422
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.275735161063006e-06,
+ "loss": 0.4693,
+ "step": 6423
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.273032399750925e-06,
+ "loss": 0.4631,
+ "step": 6424
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.270329691824318e-06,
+ "loss": 0.4736,
+ "step": 6425
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.267627037481667e-06,
+ "loss": 0.4763,
+ "step": 6426
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.264924436921438e-06,
+ "loss": 0.475,
+ "step": 6427
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.262221890342104e-06,
+ "loss": 0.5036,
+ "step": 6428
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.259519397942125e-06,
+ "loss": 0.4682,
+ "step": 6429
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.256816959919962e-06,
+ "loss": 0.4808,
+ "step": 6430
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.254114576474068e-06,
+ "loss": 0.4676,
+ "step": 6431
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.251412247802896e-06,
+ "loss": 0.4549,
+ "step": 6432
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.248709974104897e-06,
+ "loss": 0.4904,
+ "step": 6433
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.246007755578514e-06,
+ "loss": 0.4909,
+ "step": 6434
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.243305592422184e-06,
+ "loss": 0.479,
+ "step": 6435
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.240603484834347e-06,
+ "loss": 0.4879,
+ "step": 6436
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.237901433013427e-06,
+ "loss": 0.4899,
+ "step": 6437
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.235199437157858e-06,
+ "loss": 0.4525,
+ "step": 6438
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.232497497466057e-06,
+ "loss": 0.4823,
+ "step": 6439
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.229795614136452e-06,
+ "loss": 0.4723,
+ "step": 6440
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.227093787367454e-06,
+ "loss": 0.4649,
+ "step": 6441
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.224392017357471e-06,
+ "loss": 0.4885,
+ "step": 6442
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.221690304304915e-06,
+ "loss": 0.4626,
+ "step": 6443
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.218988648408187e-06,
+ "loss": 0.4568,
+ "step": 6444
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.216287049865681e-06,
+ "loss": 0.4942,
+ "step": 6445
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.213585508875792e-06,
+ "loss": 0.5012,
+ "step": 6446
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.210884025636916e-06,
+ "loss": 0.4838,
+ "step": 6447
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.208182600347432e-06,
+ "loss": 0.4744,
+ "step": 6448
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.20548123320573e-06,
+ "loss": 0.4823,
+ "step": 6449
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.20277992441018e-06,
+ "loss": 0.4897,
+ "step": 6450
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.200078674159154e-06,
+ "loss": 0.4671,
+ "step": 6451
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.197377482651023e-06,
+ "loss": 0.4986,
+ "step": 6452
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.194676350084148e-06,
+ "loss": 0.4702,
+ "step": 6453
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.191975276656898e-06,
+ "loss": 0.4758,
+ "step": 6454
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.189274262567622e-06,
+ "loss": 0.4712,
+ "step": 6455
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.186573308014672e-06,
+ "loss": 0.4757,
+ "step": 6456
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.183872413196392e-06,
+ "loss": 0.4419,
+ "step": 6457
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.181171578311132e-06,
+ "loss": 0.483,
+ "step": 6458
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.17847080355722e-06,
+ "loss": 0.4725,
+ "step": 6459
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.175770089133e-06,
+ "loss": 0.4854,
+ "step": 6460
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.173069435236796e-06,
+ "loss": 0.5029,
+ "step": 6461
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.170368842066932e-06,
+ "loss": 0.4741,
+ "step": 6462
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.167668309821729e-06,
+ "loss": 0.4736,
+ "step": 6463
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.164967838699504e-06,
+ "loss": 0.5017,
+ "step": 6464
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.162267428898568e-06,
+ "loss": 0.4903,
+ "step": 6465
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.159567080617226e-06,
+ "loss": 0.4764,
+ "step": 6466
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.156866794053783e-06,
+ "loss": 0.4889,
+ "step": 6467
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.154166569406537e-06,
+ "loss": 0.4664,
+ "step": 6468
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.15146640687378e-06,
+ "loss": 0.494,
+ "step": 6469
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.148766306653801e-06,
+ "loss": 0.4731,
+ "step": 6470
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.146066268944883e-06,
+ "loss": 0.4908,
+ "step": 6471
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.143366293945305e-06,
+ "loss": 0.4881,
+ "step": 6472
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.140666381853343e-06,
+ "loss": 0.4623,
+ "step": 6473
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.137966532867268e-06,
+ "loss": 0.4839,
+ "step": 6474
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.135266747185348e-06,
+ "loss": 0.484,
+ "step": 6475
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.132567025005842e-06,
+ "loss": 0.4819,
+ "step": 6476
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.129867366527004e-06,
+ "loss": 0.4728,
+ "step": 6477
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.127167771947086e-06,
+ "loss": 0.4608,
+ "step": 6478
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.12446824146434e-06,
+ "loss": 0.4677,
+ "step": 6479
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.121768775276997e-06,
+ "loss": 0.4838,
+ "step": 6480
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.11906937358331e-06,
+ "loss": 0.4658,
+ "step": 6481
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.116370036581504e-06,
+ "loss": 0.4829,
+ "step": 6482
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.113670764469803e-06,
+ "loss": 0.4701,
+ "step": 6483
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.110971557446437e-06,
+ "loss": 0.4751,
+ "step": 6484
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.108272415709624e-06,
+ "loss": 0.4502,
+ "step": 6485
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.105573339457574e-06,
+ "loss": 0.4784,
+ "step": 6486
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.102874328888493e-06,
+ "loss": 0.4574,
+ "step": 6487
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.100175384200595e-06,
+ "loss": 0.4764,
+ "step": 6488
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.097476505592074e-06,
+ "loss": 0.4746,
+ "step": 6489
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.094777693261124e-06,
+ "loss": 0.4867,
+ "step": 6490
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.092078947405937e-06,
+ "loss": 0.4723,
+ "step": 6491
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.089380268224694e-06,
+ "loss": 0.4829,
+ "step": 6492
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.086681655915574e-06,
+ "loss": 0.4703,
+ "step": 6493
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.083983110676755e-06,
+ "loss": 0.4804,
+ "step": 6494
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.081284632706408e-06,
+ "loss": 0.4808,
+ "step": 6495
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.078586222202698e-06,
+ "loss": 0.4923,
+ "step": 6496
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.075887879363783e-06,
+ "loss": 0.4779,
+ "step": 6497
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.073189604387815e-06,
+ "loss": 0.4824,
+ "step": 6498
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.07049139747295e-06,
+ "loss": 0.4912,
+ "step": 6499
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.06779325881733e-06,
+ "loss": 0.477,
+ "step": 6500
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.065095188619096e-06,
+ "loss": 0.4758,
+ "step": 6501
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.062397187076384e-06,
+ "loss": 0.467,
+ "step": 6502
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.059699254387323e-06,
+ "loss": 0.4954,
+ "step": 6503
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.057001390750035e-06,
+ "loss": 0.4689,
+ "step": 6504
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.054303596362646e-06,
+ "loss": 0.4764,
+ "step": 6505
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.051605871423266e-06,
+ "loss": 0.4866,
+ "step": 6506
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.048908216130002e-06,
+ "loss": 0.4834,
+ "step": 6507
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.046210630680968e-06,
+ "loss": 0.4618,
+ "step": 6508
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.043513115274257e-06,
+ "loss": 0.4803,
+ "step": 6509
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.040815670107964e-06,
+ "loss": 0.4672,
+ "step": 6510
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.038118295380179e-06,
+ "loss": 0.4937,
+ "step": 6511
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.035420991288987e-06,
+ "loss": 0.4753,
+ "step": 6512
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.032723758032462e-06,
+ "loss": 0.4871,
+ "step": 6513
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.030026595808682e-06,
+ "loss": 0.4761,
+ "step": 6514
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.027329504815714e-06,
+ "loss": 0.509,
+ "step": 6515
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.024632485251624e-06,
+ "loss": 0.4935,
+ "step": 6516
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.021935537314467e-06,
+ "loss": 0.4866,
+ "step": 6517
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.019238661202296e-06,
+ "loss": 0.4957,
+ "step": 6518
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.016541857113157e-06,
+ "loss": 0.4776,
+ "step": 6519
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.013845125245095e-06,
+ "loss": 0.4852,
+ "step": 6520
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.01114846579614e-06,
+ "loss": 0.4643,
+ "step": 6521
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.008451878964336e-06,
+ "loss": 0.4801,
+ "step": 6522
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.005755364947699e-06,
+ "loss": 0.4683,
+ "step": 6523
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.00305892394425e-06,
+ "loss": 0.4803,
+ "step": 6524
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.000362556152013e-06,
+ "loss": 0.4789,
+ "step": 6525
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.997666261768989e-06,
+ "loss": 0.4686,
+ "step": 6526
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.994970040993187e-06,
+ "loss": 0.5007,
+ "step": 6527
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.9922738940226e-06,
+ "loss": 0.4736,
+ "step": 6528
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.989577821055231e-06,
+ "loss": 0.4812,
+ "step": 6529
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.986881822289062e-06,
+ "loss": 0.49,
+ "step": 6530
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.98418589792208e-06,
+ "loss": 0.4833,
+ "step": 6531
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.98149004815226e-06,
+ "loss": 0.4741,
+ "step": 6532
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.978794273177576e-06,
+ "loss": 0.4823,
+ "step": 6533
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.97609857319599e-06,
+ "loss": 0.4539,
+ "step": 6534
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.973402948405466e-06,
+ "loss": 0.4686,
+ "step": 6535
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.970707399003961e-06,
+ "loss": 0.4727,
+ "step": 6536
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.968011925189426e-06,
+ "loss": 0.4807,
+ "step": 6537
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.9653165271598e-06,
+ "loss": 0.4661,
+ "step": 6538
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.962621205113025e-06,
+ "loss": 0.4563,
+ "step": 6539
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.959925959247036e-06,
+ "loss": 0.4915,
+ "step": 6540
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.957230789759752e-06,
+ "loss": 0.4776,
+ "step": 6541
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.954535696849108e-06,
+ "loss": 0.4824,
+ "step": 6542
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.951840680713013e-06,
+ "loss": 0.4858,
+ "step": 6543
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.949145741549378e-06,
+ "loss": 0.4641,
+ "step": 6544
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.946450879556108e-06,
+ "loss": 0.4672,
+ "step": 6545
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.943756094931106e-06,
+ "loss": 0.4964,
+ "step": 6546
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.941061387872263e-06,
+ "loss": 0.4896,
+ "step": 6547
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.938366758577462e-06,
+ "loss": 0.4759,
+ "step": 6548
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.935672207244596e-06,
+ "loss": 0.4772,
+ "step": 6549
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.932977734071533e-06,
+ "loss": 0.4732,
+ "step": 6550
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.93028333925615e-06,
+ "loss": 0.4791,
+ "step": 6551
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.927589022996308e-06,
+ "loss": 0.4696,
+ "step": 6552
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.92489478548987e-06,
+ "loss": 0.4734,
+ "step": 6553
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.922200626934682e-06,
+ "loss": 0.4917,
+ "step": 6554
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.919506547528599e-06,
+ "loss": 0.4855,
+ "step": 6555
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.916812547469461e-06,
+ "loss": 0.4893,
+ "step": 6556
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.914118626955106e-06,
+ "loss": 0.4473,
+ "step": 6557
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.911424786183362e-06,
+ "loss": 0.4829,
+ "step": 6558
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.908731025352055e-06,
+ "loss": 0.4882,
+ "step": 6559
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.906037344659e-06,
+ "loss": 0.4827,
+ "step": 6560
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.903343744302016e-06,
+ "loss": 0.469,
+ "step": 6561
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.900650224478899e-06,
+ "loss": 0.4783,
+ "step": 6562
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.897956785387463e-06,
+ "loss": 0.4845,
+ "step": 6563
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.895263427225497e-06,
+ "loss": 0.4707,
+ "step": 6564
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.89257015019079e-06,
+ "loss": 0.4974,
+ "step": 6565
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.889876954481122e-06,
+ "loss": 0.4709,
+ "step": 6566
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.887183840294274e-06,
+ "loss": 0.4527,
+ "step": 6567
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.88449080782802e-06,
+ "loss": 0.4861,
+ "step": 6568
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.881797857280113e-06,
+ "loss": 0.4684,
+ "step": 6569
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.879104988848326e-06,
+ "loss": 0.4724,
+ "step": 6570
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.876412202730405e-06,
+ "loss": 0.4827,
+ "step": 6571
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.873719499124101e-06,
+ "loss": 0.4686,
+ "step": 6572
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.871026878227151e-06,
+ "loss": 0.4915,
+ "step": 6573
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.868334340237293e-06,
+ "loss": 0.4946,
+ "step": 6574
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.86564188535225e-06,
+ "loss": 0.4845,
+ "step": 6575
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.86294951376975e-06,
+ "loss": 0.4632,
+ "step": 6576
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.86025722568751e-06,
+ "loss": 0.4733,
+ "step": 6577
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.857565021303238e-06,
+ "loss": 0.4629,
+ "step": 6578
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.85487290081464e-06,
+ "loss": 0.4984,
+ "step": 6579
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.852180864419413e-06,
+ "loss": 0.4787,
+ "step": 6580
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.84948891231525e-06,
+ "loss": 0.4913,
+ "step": 6581
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.846797044699831e-06,
+ "loss": 0.4955,
+ "step": 6582
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.844105261770844e-06,
+ "loss": 0.478,
+ "step": 6583
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.84141356372596e-06,
+ "loss": 0.4816,
+ "step": 6584
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.838721950762845e-06,
+ "loss": 0.4711,
+ "step": 6585
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.836030423079157e-06,
+ "loss": 0.4757,
+ "step": 6586
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.833338980872558e-06,
+ "loss": 0.4635,
+ "step": 6587
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.830647624340689e-06,
+ "loss": 0.4623,
+ "step": 6588
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.827956353681191e-06,
+ "loss": 0.4898,
+ "step": 6589
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.82526516909171e-06,
+ "loss": 0.4753,
+ "step": 6590
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.822574070769867e-06,
+ "loss": 0.4799,
+ "step": 6591
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.819883058913285e-06,
+ "loss": 0.4814,
+ "step": 6592
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.817192133719583e-06,
+ "loss": 0.5005,
+ "step": 6593
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.814501295386373e-06,
+ "loss": 0.4939,
+ "step": 6594
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.811810544111258e-06,
+ "loss": 0.4781,
+ "step": 6595
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.809119880091829e-06,
+ "loss": 0.4704,
+ "step": 6596
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.806429303525685e-06,
+ "loss": 0.4791,
+ "step": 6597
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.803738814610409e-06,
+ "loss": 0.4631,
+ "step": 6598
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.801048413543581e-06,
+ "loss": 0.4904,
+ "step": 6599
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.79835810052277e-06,
+ "loss": 0.4783,
+ "step": 6600
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.79566787574554e-06,
+ "loss": 0.4744,
+ "step": 6601
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.792977739409455e-06,
+ "loss": 0.4782,
+ "step": 6602
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.790287691712059e-06,
+ "loss": 0.478,
+ "step": 6603
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.78759773285091e-06,
+ "loss": 0.4799,
+ "step": 6604
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.784907863023537e-06,
+ "loss": 0.4553,
+ "step": 6605
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.782218082427478e-06,
+ "loss": 0.4705,
+ "step": 6606
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.779528391260257e-06,
+ "loss": 0.4689,
+ "step": 6607
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.776838789719396e-06,
+ "loss": 0.4538,
+ "step": 6608
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.774149278002402e-06,
+ "loss": 0.4857,
+ "step": 6609
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.771459856306791e-06,
+ "loss": 0.4831,
+ "step": 6610
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.768770524830058e-06,
+ "loss": 0.4744,
+ "step": 6611
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.766081283769695e-06,
+ "loss": 0.4704,
+ "step": 6612
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.763392133323192e-06,
+ "loss": 0.476,
+ "step": 6613
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.760703073688027e-06,
+ "loss": 0.4742,
+ "step": 6614
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.758014105061674e-06,
+ "loss": 0.469,
+ "step": 6615
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.755325227641596e-06,
+ "loss": 0.4838,
+ "step": 6616
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.752636441625259e-06,
+ "loss": 0.4951,
+ "step": 6617
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.749947747210112e-06,
+ "loss": 0.4718,
+ "step": 6618
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.747259144593604e-06,
+ "loss": 0.4653,
+ "step": 6619
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.744570633973177e-06,
+ "loss": 0.472,
+ "step": 6620
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.741882215546259e-06,
+ "loss": 0.4854,
+ "step": 6621
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.739193889510276e-06,
+ "loss": 0.4681,
+ "step": 6622
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.736505656062648e-06,
+ "loss": 0.4679,
+ "step": 6623
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.733817515400793e-06,
+ "loss": 0.4907,
+ "step": 6624
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.731129467722113e-06,
+ "loss": 0.4657,
+ "step": 6625
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.728441513224008e-06,
+ "loss": 0.4657,
+ "step": 6626
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.725753652103868e-06,
+ "loss": 0.4826,
+ "step": 6627
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.72306588455908e-06,
+ "loss": 0.4653,
+ "step": 6628
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.720378210787024e-06,
+ "loss": 0.4729,
+ "step": 6629
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.717690630985065e-06,
+ "loss": 0.4685,
+ "step": 6630
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.715003145350576e-06,
+ "loss": 0.4579,
+ "step": 6631
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.712315754080913e-06,
+ "loss": 0.4743,
+ "step": 6632
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.709628457373421e-06,
+ "loss": 0.4584,
+ "step": 6633
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.706941255425452e-06,
+ "loss": 0.4803,
+ "step": 6634
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.704254148434338e-06,
+ "loss": 0.4585,
+ "step": 6635
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.70156713659741e-06,
+ "loss": 0.4726,
+ "step": 6636
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.698880220111987e-06,
+ "loss": 0.4588,
+ "step": 6637
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.69619339917539e-06,
+ "loss": 0.4938,
+ "step": 6638
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.69350667398493e-06,
+ "loss": 0.4575,
+ "step": 6639
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.690820044737905e-06,
+ "loss": 0.4914,
+ "step": 6640
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.688133511631611e-06,
+ "loss": 0.4948,
+ "step": 6641
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.685447074863333e-06,
+ "loss": 0.4842,
+ "step": 6642
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.682760734630357e-06,
+ "loss": 0.4749,
+ "step": 6643
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.68007449112995e-06,
+ "loss": 0.4753,
+ "step": 6644
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.677388344559386e-06,
+ "loss": 0.4793,
+ "step": 6645
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.67470229511592e-06,
+ "loss": 0.4646,
+ "step": 6646
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.672016342996805e-06,
+ "loss": 0.4625,
+ "step": 6647
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.669330488399286e-06,
+ "loss": 0.4775,
+ "step": 6648
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.6666447315206e-06,
+ "loss": 0.4756,
+ "step": 6649
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.663959072557979e-06,
+ "loss": 0.4676,
+ "step": 6650
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.66127351170865e-06,
+ "loss": 0.4726,
+ "step": 6651
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.658588049169825e-06,
+ "loss": 0.4714,
+ "step": 6652
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.655902685138712e-06,
+ "loss": 0.4803,
+ "step": 6653
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.653217419812517e-06,
+ "loss": 0.4892,
+ "step": 6654
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.650532253388435e-06,
+ "loss": 0.4818,
+ "step": 6655
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.64784718606365e-06,
+ "loss": 0.4835,
+ "step": 6656
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.64516221803534e-06,
+ "loss": 0.4779,
+ "step": 6657
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.642477349500686e-06,
+ "loss": 0.4493,
+ "step": 6658
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.639792580656845e-06,
+ "loss": 0.486,
+ "step": 6659
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.637107911700984e-06,
+ "loss": 0.4814,
+ "step": 6660
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.634423342830247e-06,
+ "loss": 0.4684,
+ "step": 6661
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.631738874241781e-06,
+ "loss": 0.4948,
+ "step": 6662
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.629054506132719e-06,
+ "loss": 0.4751,
+ "step": 6663
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.62637023870019e-06,
+ "loss": 0.4949,
+ "step": 6664
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.623686072141322e-06,
+ "loss": 0.4846,
+ "step": 6665
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.621002006653223e-06,
+ "loss": 0.5014,
+ "step": 6666
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.618318042433001e-06,
+ "loss": 0.4761,
+ "step": 6667
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.615634179677754e-06,
+ "loss": 0.455,
+ "step": 6668
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.612950418584575e-06,
+ "loss": 0.4812,
+ "step": 6669
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.610266759350551e-06,
+ "loss": 0.445,
+ "step": 6670
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.60758320217275e-06,
+ "loss": 0.4593,
+ "step": 6671
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.604899747248251e-06,
+ "loss": 0.48,
+ "step": 6672
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.602216394774114e-06,
+ "loss": 0.485,
+ "step": 6673
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.599533144947386e-06,
+ "loss": 0.4597,
+ "step": 6674
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.596849997965122e-06,
+ "loss": 0.4916,
+ "step": 6675
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.594166954024359e-06,
+ "loss": 0.4836,
+ "step": 6676
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.591484013322128e-06,
+ "loss": 0.4712,
+ "step": 6677
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.588801176055447e-06,
+ "loss": 0.4779,
+ "step": 6678
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.586118442421341e-06,
+ "loss": 0.4899,
+ "step": 6679
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.583435812616817e-06,
+ "loss": 0.4701,
+ "step": 6680
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.580753286838875e-06,
+ "loss": 0.4788,
+ "step": 6681
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.57807086528451e-06,
+ "loss": 0.4701,
+ "step": 6682
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.575388548150702e-06,
+ "loss": 0.4718,
+ "step": 6683
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.572706335634437e-06,
+ "loss": 0.4727,
+ "step": 6684
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.570024227932678e-06,
+ "loss": 0.4729,
+ "step": 6685
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.567342225242397e-06,
+ "loss": 0.4713,
+ "step": 6686
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.564660327760543e-06,
+ "loss": 0.4734,
+ "step": 6687
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.561978535684065e-06,
+ "loss": 0.4841,
+ "step": 6688
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.5592968492099e-06,
+ "loss": 0.4794,
+ "step": 6689
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.556615268534984e-06,
+ "loss": 0.4915,
+ "step": 6690
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.553933793856234e-06,
+ "loss": 0.4734,
+ "step": 6691
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.551252425370577e-06,
+ "loss": 0.4661,
+ "step": 6692
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.548571163274915e-06,
+ "loss": 0.4723,
+ "step": 6693
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.54589000776615e-06,
+ "loss": 0.4812,
+ "step": 6694
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.543208959041174e-06,
+ "loss": 0.4868,
+ "step": 6695
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.540528017296876e-06,
+ "loss": 0.4789,
+ "step": 6696
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.537847182730126e-06,
+ "loss": 0.4894,
+ "step": 6697
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.535166455537795e-06,
+ "loss": 0.4734,
+ "step": 6698
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.532485835916754e-06,
+ "loss": 0.4674,
+ "step": 6699
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.529805324063843e-06,
+ "loss": 0.4828,
+ "step": 6700
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.527124920175918e-06,
+ "loss": 0.4801,
+ "step": 6701
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.524444624449812e-06,
+ "loss": 0.4383,
+ "step": 6702
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.521764437082355e-06,
+ "loss": 0.4693,
+ "step": 6703
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.519084358270368e-06,
+ "loss": 0.4689,
+ "step": 6704
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.516404388210668e-06,
+ "loss": 0.4543,
+ "step": 6705
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.513724527100055e-06,
+ "loss": 0.4868,
+ "step": 6706
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.511044775135336e-06,
+ "loss": 0.4848,
+ "step": 6707
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.508365132513296e-06,
+ "loss": 0.4832,
+ "step": 6708
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.505685599430715e-06,
+ "loss": 0.4872,
+ "step": 6709
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.503006176084366e-06,
+ "loss": 0.4848,
+ "step": 6710
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.50032686267102e-06,
+ "loss": 0.4751,
+ "step": 6711
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.497647659387426e-06,
+ "loss": 0.4748,
+ "step": 6712
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.494968566430346e-06,
+ "loss": 0.4774,
+ "step": 6713
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.492289583996511e-06,
+ "loss": 0.4901,
+ "step": 6714
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.489610712282658e-06,
+ "loss": 0.477,
+ "step": 6715
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.486931951485515e-06,
+ "loss": 0.4673,
+ "step": 6716
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.484253301801794e-06,
+ "loss": 0.4684,
+ "step": 6717
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.481574763428208e-06,
+ "loss": 0.4901,
+ "step": 6718
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.47889633656145e-06,
+ "loss": 0.4841,
+ "step": 6719
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.476218021398224e-06,
+ "loss": 0.4742,
+ "step": 6720
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.473539818135205e-06,
+ "loss": 0.473,
+ "step": 6721
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.470861726969075e-06,
+ "loss": 0.4822,
+ "step": 6722
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.4681837480965e-06,
+ "loss": 0.4779,
+ "step": 6723
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.46550588171414e-06,
+ "loss": 0.4748,
+ "step": 6724
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.462828128018642e-06,
+ "loss": 0.4784,
+ "step": 6725
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.460150487206652e-06,
+ "loss": 0.4835,
+ "step": 6726
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.45747295947481e-06,
+ "loss": 0.4796,
+ "step": 6727
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.454795545019737e-06,
+ "loss": 0.4778,
+ "step": 6728
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.452118244038052e-06,
+ "loss": 0.4831,
+ "step": 6729
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.449441056726364e-06,
+ "loss": 0.4749,
+ "step": 6730
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.446763983281276e-06,
+ "loss": 0.4853,
+ "step": 6731
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.444087023899377e-06,
+ "loss": 0.491,
+ "step": 6732
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.44141017877726e-06,
+ "loss": 0.4564,
+ "step": 6733
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.438733448111496e-06,
+ "loss": 0.4818,
+ "step": 6734
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.436056832098655e-06,
+ "loss": 0.4734,
+ "step": 6735
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.433380330935293e-06,
+ "loss": 0.4585,
+ "step": 6736
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.430703944817967e-06,
+ "loss": 0.4646,
+ "step": 6737
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.428027673943213e-06,
+ "loss": 0.4824,
+ "step": 6738
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.425351518507565e-06,
+ "loss": 0.4706,
+ "step": 6739
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.422675478707556e-06,
+ "loss": 0.4733,
+ "step": 6740
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.4199995547397e-06,
+ "loss": 0.5001,
+ "step": 6741
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.417323746800504e-06,
+ "loss": 0.4803,
+ "step": 6742
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.414648055086471e-06,
+ "loss": 0.4705,
+ "step": 6743
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.41197247979409e-06,
+ "loss": 0.4768,
+ "step": 6744
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.409297021119843e-06,
+ "loss": 0.4859,
+ "step": 6745
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.406621679260206e-06,
+ "loss": 0.4715,
+ "step": 6746
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.403946454411645e-06,
+ "loss": 0.462,
+ "step": 6747
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.401271346770622e-06,
+ "loss": 0.4751,
+ "step": 6748
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.398596356533581e-06,
+ "loss": 0.4768,
+ "step": 6749
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.395921483896963e-06,
+ "loss": 0.471,
+ "step": 6750
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.393246729057196e-06,
+ "loss": 0.5009,
+ "step": 6751
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.39057209221071e-06,
+ "loss": 0.4724,
+ "step": 6752
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.38789757355391e-06,
+ "loss": 0.471,
+ "step": 6753
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.38522317328321e-06,
+ "loss": 0.4789,
+ "step": 6754
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.382548891595006e-06,
+ "loss": 0.4581,
+ "step": 6755
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.379874728685681e-06,
+ "loss": 0.4895,
+ "step": 6756
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.37720068475162e-06,
+ "loss": 0.4833,
+ "step": 6757
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.37452675998919e-06,
+ "loss": 0.4793,
+ "step": 6758
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.371852954594755e-06,
+ "loss": 0.4747,
+ "step": 6759
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.369179268764662e-06,
+ "loss": 0.4749,
+ "step": 6760
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.366505702695264e-06,
+ "loss": 0.4625,
+ "step": 6761
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.363832256582892e-06,
+ "loss": 0.4828,
+ "step": 6762
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.361158930623877e-06,
+ "loss": 0.4782,
+ "step": 6763
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.358485725014531e-06,
+ "loss": 0.4788,
+ "step": 6764
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.355812639951168e-06,
+ "loss": 0.4712,
+ "step": 6765
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.35313967563008e-06,
+ "loss": 0.4894,
+ "step": 6766
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.350466832247568e-06,
+ "loss": 0.4702,
+ "step": 6767
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.347794109999912e-06,
+ "loss": 0.4668,
+ "step": 6768
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.345121509083384e-06,
+ "loss": 0.4578,
+ "step": 6769
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.34244902969425e-06,
+ "loss": 0.4826,
+ "step": 6770
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.339776672028765e-06,
+ "loss": 0.4897,
+ "step": 6771
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.337104436283176e-06,
+ "loss": 0.4767,
+ "step": 6772
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.334432322653717e-06,
+ "loss": 0.5019,
+ "step": 6773
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.331760331336622e-06,
+ "loss": 0.4777,
+ "step": 6774
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.329088462528113e-06,
+ "loss": 0.4643,
+ "step": 6775
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.326416716424396e-06,
+ "loss": 0.4687,
+ "step": 6776
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.323745093221672e-06,
+ "loss": 0.4902,
+ "step": 6777
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.32107359311614e-06,
+ "loss": 0.4804,
+ "step": 6778
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.318402216303978e-06,
+ "loss": 0.4833,
+ "step": 6779
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.31573096298136e-06,
+ "loss": 0.4916,
+ "step": 6780
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.313059833344459e-06,
+ "loss": 0.4769,
+ "step": 6781
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.310388827589424e-06,
+ "loss": 0.4853,
+ "step": 6782
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.30771794591241e-06,
+ "loss": 0.4967,
+ "step": 6783
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.30504718850955e-06,
+ "loss": 0.4618,
+ "step": 6784
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.302376555576974e-06,
+ "loss": 0.4827,
+ "step": 6785
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.299706047310803e-06,
+ "loss": 0.458,
+ "step": 6786
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.297035663907146e-06,
+ "loss": 0.4838,
+ "step": 6787
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.294365405562107e-06,
+ "loss": 0.4725,
+ "step": 6788
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.29169527247178e-06,
+ "loss": 0.4844,
+ "step": 6789
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.289025264832247e-06,
+ "loss": 0.479,
+ "step": 6790
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.286355382839584e-06,
+ "loss": 0.4811,
+ "step": 6791
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.283685626689851e-06,
+ "loss": 0.4781,
+ "step": 6792
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.281015996579106e-06,
+ "loss": 0.4775,
+ "step": 6793
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.278346492703394e-06,
+ "loss": 0.4994,
+ "step": 6794
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.275677115258761e-06,
+ "loss": 0.4812,
+ "step": 6795
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.273007864441227e-06,
+ "loss": 0.4621,
+ "step": 6796
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.27033874044681e-06,
+ "loss": 0.4713,
+ "step": 6797
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.267669743471525e-06,
+ "loss": 0.4923,
+ "step": 6798
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.265000873711368e-06,
+ "loss": 0.4829,
+ "step": 6799
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.262332131362326e-06,
+ "loss": 0.4658,
+ "step": 6800
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.259663516620389e-06,
+ "loss": 0.5034,
+ "step": 6801
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.256995029681526e-06,
+ "loss": 0.4598,
+ "step": 6802
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.254326670741694e-06,
+ "loss": 0.4704,
+ "step": 6803
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.251658439996854e-06,
+ "loss": 0.4928,
+ "step": 6804
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.248990337642946e-06,
+ "loss": 0.4666,
+ "step": 6805
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.246322363875904e-06,
+ "loss": 0.4721,
+ "step": 6806
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.24365451889165e-06,
+ "loss": 0.474,
+ "step": 6807
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.240986802886105e-06,
+ "loss": 0.4743,
+ "step": 6808
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.238319216055175e-06,
+ "loss": 0.4705,
+ "step": 6809
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.235651758594753e-06,
+ "loss": 0.4877,
+ "step": 6810
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.23298443070073e-06,
+ "loss": 0.4727,
+ "step": 6811
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.230317232568977e-06,
+ "loss": 0.4659,
+ "step": 6812
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.227650164395369e-06,
+ "loss": 0.4665,
+ "step": 6813
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.224983226375756e-06,
+ "loss": 0.461,
+ "step": 6814
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.222316418705995e-06,
+ "loss": 0.4809,
+ "step": 6815
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.219649741581925e-06,
+ "loss": 0.4596,
+ "step": 6816
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.216983195199372e-06,
+ "loss": 0.4577,
+ "step": 6817
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.214316779754154e-06,
+ "loss": 0.4787,
+ "step": 6818
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.211650495442088e-06,
+ "loss": 0.4803,
+ "step": 6819
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.20898434245897e-06,
+ "loss": 0.4821,
+ "step": 6820
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.206318321000588e-06,
+ "loss": 0.4678,
+ "step": 6821
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.203652431262733e-06,
+ "loss": 0.501,
+ "step": 6822
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.200986673441173e-06,
+ "loss": 0.4752,
+ "step": 6823
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.198321047731665e-06,
+ "loss": 0.4762,
+ "step": 6824
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.195655554329969e-06,
+ "loss": 0.4846,
+ "step": 6825
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.192990193431824e-06,
+ "loss": 0.4847,
+ "step": 6826
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.19032496523296e-06,
+ "loss": 0.4782,
+ "step": 6827
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.187659869929104e-06,
+ "loss": 0.4777,
+ "step": 6828
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.184994907715969e-06,
+ "loss": 0.4826,
+ "step": 6829
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.182330078789262e-06,
+ "loss": 0.4972,
+ "step": 6830
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.179665383344674e-06,
+ "loss": 0.4655,
+ "step": 6831
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.177000821577888e-06,
+ "loss": 0.4884,
+ "step": 6832
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.174336393684577e-06,
+ "loss": 0.4607,
+ "step": 6833
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.17167209986041e-06,
+ "loss": 0.4567,
+ "step": 6834
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.169007940301034e-06,
+ "loss": 0.4858,
+ "step": 6835
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.166343915202106e-06,
+ "loss": 0.473,
+ "step": 6836
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.163680024759252e-06,
+ "loss": 0.4651,
+ "step": 6837
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.161016269168101e-06,
+ "loss": 0.4667,
+ "step": 6838
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.158352648624263e-06,
+ "loss": 0.5024,
+ "step": 6839
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.155689163323348e-06,
+ "loss": 0.478,
+ "step": 6840
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.153025813460947e-06,
+ "loss": 0.4516,
+ "step": 6841
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.15036259923265e-06,
+ "loss": 0.478,
+ "step": 6842
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.147699520834033e-06,
+ "loss": 0.4709,
+ "step": 6843
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.145036578460656e-06,
+ "loss": 0.4604,
+ "step": 6844
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.142373772308078e-06,
+ "loss": 0.4652,
+ "step": 6845
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.139711102571846e-06,
+ "loss": 0.4943,
+ "step": 6846
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.137048569447492e-06,
+ "loss": 0.4631,
+ "step": 6847
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.134386173130539e-06,
+ "loss": 0.4891,
+ "step": 6848
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.131723913816508e-06,
+ "loss": 0.4725,
+ "step": 6849
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.129061791700903e-06,
+ "loss": 0.4699,
+ "step": 6850
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.126399806979217e-06,
+ "loss": 0.4892,
+ "step": 6851
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.123737959846937e-06,
+ "loss": 0.4647,
+ "step": 6852
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.121076250499539e-06,
+ "loss": 0.4725,
+ "step": 6853
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.118414679132484e-06,
+ "loss": 0.4585,
+ "step": 6854
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.115753245941225e-06,
+ "loss": 0.481,
+ "step": 6855
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.113091951121215e-06,
+ "loss": 0.4593,
+ "step": 6856
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.110430794867884e-06,
+ "loss": 0.4727,
+ "step": 6857
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.107769777376657e-06,
+ "loss": 0.4692,
+ "step": 6858
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.105108898842946e-06,
+ "loss": 0.4705,
+ "step": 6859
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.102448159462155e-06,
+ "loss": 0.4907,
+ "step": 6860
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.099787559429682e-06,
+ "loss": 0.4831,
+ "step": 6861
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.0971270989409e-06,
+ "loss": 0.4815,
+ "step": 6862
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.094466778191194e-06,
+ "loss": 0.4879,
+ "step": 6863
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.091806597375925e-06,
+ "loss": 0.4851,
+ "step": 6864
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.089146556690437e-06,
+ "loss": 0.4682,
+ "step": 6865
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.086486656330082e-06,
+ "loss": 0.4849,
+ "step": 6866
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.083826896490186e-06,
+ "loss": 0.4875,
+ "step": 6867
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.081167277366076e-06,
+ "loss": 0.4755,
+ "step": 6868
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.078507799153053e-06,
+ "loss": 0.4663,
+ "step": 6869
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.07584846204643e-06,
+ "loss": 0.4806,
+ "step": 6870
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.073189266241492e-06,
+ "loss": 0.4771,
+ "step": 6871
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.070530211933522e-06,
+ "loss": 0.4727,
+ "step": 6872
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.067871299317786e-06,
+ "loss": 0.4623,
+ "step": 6873
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.065212528589545e-06,
+ "loss": 0.5038,
+ "step": 6874
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.062553899944049e-06,
+ "loss": 0.4703,
+ "step": 6875
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.059895413576535e-06,
+ "loss": 0.4934,
+ "step": 6876
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.057237069682235e-06,
+ "loss": 0.4898,
+ "step": 6877
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.054578868456364e-06,
+ "loss": 0.4677,
+ "step": 6878
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.05192081009413e-06,
+ "loss": 0.5034,
+ "step": 6879
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.049262894790725e-06,
+ "loss": 0.4796,
+ "step": 6880
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.046605122741343e-06,
+ "loss": 0.4751,
+ "step": 6881
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.04394749414115e-06,
+ "loss": 0.4621,
+ "step": 6882
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.041290009185325e-06,
+ "loss": 0.4772,
+ "step": 6883
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.038632668069011e-06,
+ "loss": 0.471,
+ "step": 6884
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.035975470987357e-06,
+ "loss": 0.4558,
+ "step": 6885
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.033318418135494e-06,
+ "loss": 0.4728,
+ "step": 6886
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.03066150970855e-06,
+ "loss": 0.4667,
+ "step": 6887
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.02800474590163e-06,
+ "loss": 0.4804,
+ "step": 6888
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.025348126909837e-06,
+ "loss": 0.4809,
+ "step": 6889
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.02269165292827e-06,
+ "loss": 0.4799,
+ "step": 6890
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.020035324152e-06,
+ "loss": 0.456,
+ "step": 6891
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.017379140776103e-06,
+ "loss": 0.4874,
+ "step": 6892
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.014723102995635e-06,
+ "loss": 0.4772,
+ "step": 6893
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.012067211005645e-06,
+ "loss": 0.4651,
+ "step": 6894
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.00941146500117e-06,
+ "loss": 0.4828,
+ "step": 6895
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.006755865177233e-06,
+ "loss": 0.4682,
+ "step": 6896
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.00410041172886e-06,
+ "loss": 0.4852,
+ "step": 6897
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.001445104851052e-06,
+ "loss": 0.4691,
+ "step": 6898
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.998789944738801e-06,
+ "loss": 0.4742,
+ "step": 6899
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.996134931587092e-06,
+ "loss": 0.4673,
+ "step": 6900
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.993480065590902e-06,
+ "loss": 0.502,
+ "step": 6901
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.990825346945188e-06,
+ "loss": 0.4744,
+ "step": 6902
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.9881707758449e-06,
+ "loss": 0.4806,
+ "step": 6903
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.985516352484987e-06,
+ "loss": 0.4837,
+ "step": 6904
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.982862077060376e-06,
+ "loss": 0.4685,
+ "step": 6905
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.98020794976598e-06,
+ "loss": 0.466,
+ "step": 6906
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.977553970796713e-06,
+ "loss": 0.4756,
+ "step": 6907
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.974900140347473e-06,
+ "loss": 0.472,
+ "step": 6908
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.97224645861314e-06,
+ "loss": 0.4496,
+ "step": 6909
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.969592925788592e-06,
+ "loss": 0.4872,
+ "step": 6910
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.966939542068694e-06,
+ "loss": 0.4819,
+ "step": 6911
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.964286307648305e-06,
+ "loss": 0.4716,
+ "step": 6912
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.96163322272226e-06,
+ "loss": 0.4722,
+ "step": 6913
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.958980287485394e-06,
+ "loss": 0.4683,
+ "step": 6914
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.956327502132523e-06,
+ "loss": 0.4634,
+ "step": 6915
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.953674866858462e-06,
+ "loss": 0.4692,
+ "step": 6916
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.951022381858005e-06,
+ "loss": 0.4735,
+ "step": 6917
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.948370047325946e-06,
+ "loss": 0.4642,
+ "step": 6918
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.945717863457057e-06,
+ "loss": 0.4884,
+ "step": 6919
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.943065830446104e-06,
+ "loss": 0.4975,
+ "step": 6920
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.940413948487838e-06,
+ "loss": 0.5001,
+ "step": 6921
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.937762217777007e-06,
+ "loss": 0.4835,
+ "step": 6922
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.935110638508339e-06,
+ "loss": 0.4903,
+ "step": 6923
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.93245921087656e-06,
+ "loss": 0.4688,
+ "step": 6924
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.929807935076376e-06,
+ "loss": 0.4764,
+ "step": 6925
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.927156811302486e-06,
+ "loss": 0.4792,
+ "step": 6926
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.92450583974958e-06,
+ "loss": 0.4833,
+ "step": 6927
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.921855020612333e-06,
+ "loss": 0.4812,
+ "step": 6928
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.919204354085408e-06,
+ "loss": 0.4649,
+ "step": 6929
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.916553840363458e-06,
+ "loss": 0.4554,
+ "step": 6930
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.913903479641131e-06,
+ "loss": 0.4636,
+ "step": 6931
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.911253272113056e-06,
+ "loss": 0.5109,
+ "step": 6932
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.908603217973853e-06,
+ "loss": 0.4811,
+ "step": 6933
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.905953317418131e-06,
+ "loss": 0.4753,
+ "step": 6934
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.903303570640488e-06,
+ "loss": 0.4691,
+ "step": 6935
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.900653977835507e-06,
+ "loss": 0.4661,
+ "step": 6936
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.898004539197766e-06,
+ "loss": 0.4696,
+ "step": 6937
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.89535525492183e-06,
+ "loss": 0.4606,
+ "step": 6938
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.892706125202254e-06,
+ "loss": 0.4798,
+ "step": 6939
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.890057150233572e-06,
+ "loss": 0.4586,
+ "step": 6940
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.887408330210316e-06,
+ "loss": 0.4835,
+ "step": 6941
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.884759665327008e-06,
+ "loss": 0.4821,
+ "step": 6942
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.882111155778152e-06,
+ "loss": 0.4927,
+ "step": 6943
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.879462801758239e-06,
+ "loss": 0.4873,
+ "step": 6944
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.876814603461763e-06,
+ "loss": 0.4801,
+ "step": 6945
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.87416656108319e-06,
+ "loss": 0.476,
+ "step": 6946
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.871518674816982e-06,
+ "loss": 0.464,
+ "step": 6947
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.86887094485759e-06,
+ "loss": 0.4831,
+ "step": 6948
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.866223371399453e-06,
+ "loss": 0.4791,
+ "step": 6949
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.863575954636993e-06,
+ "loss": 0.4936,
+ "step": 6950
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.860928694764632e-06,
+ "loss": 0.4846,
+ "step": 6951
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.858281591976768e-06,
+ "loss": 0.4687,
+ "step": 6952
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.8556346464678e-06,
+ "loss": 0.4587,
+ "step": 6953
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.852987858432104e-06,
+ "loss": 0.4825,
+ "step": 6954
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.850341228064048e-06,
+ "loss": 0.4723,
+ "step": 6955
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.84769475555799e-06,
+ "loss": 0.4522,
+ "step": 6956
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.845048441108276e-06,
+ "loss": 0.484,
+ "step": 6957
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.842402284909242e-06,
+ "loss": 0.4794,
+ "step": 6958
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.839756287155213e-06,
+ "loss": 0.4794,
+ "step": 6959
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.837110448040495e-06,
+ "loss": 0.4825,
+ "step": 6960
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.834464767759392e-06,
+ "loss": 0.4612,
+ "step": 6961
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.831819246506187e-06,
+ "loss": 0.4708,
+ "step": 6962
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.829173884475158e-06,
+ "loss": 0.4607,
+ "step": 6963
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.826528681860567e-06,
+ "loss": 0.4605,
+ "step": 6964
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.823883638856675e-06,
+ "loss": 0.4779,
+ "step": 6965
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.821238755657716e-06,
+ "loss": 0.4447,
+ "step": 6966
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.818594032457922e-06,
+ "loss": 0.4876,
+ "step": 6967
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.815949469451506e-06,
+ "loss": 0.4654,
+ "step": 6968
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.813305066832679e-06,
+ "loss": 0.4654,
+ "step": 6969
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.810660824795632e-06,
+ "loss": 0.4729,
+ "step": 6970
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.808016743534546e-06,
+ "loss": 0.4886,
+ "step": 6971
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.805372823243595e-06,
+ "loss": 0.4669,
+ "step": 6972
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.802729064116933e-06,
+ "loss": 0.4781,
+ "step": 6973
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.800085466348715e-06,
+ "loss": 0.485,
+ "step": 6974
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.797442030133067e-06,
+ "loss": 0.4754,
+ "step": 6975
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.794798755664116e-06,
+ "loss": 0.4706,
+ "step": 6976
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.79215564313597e-06,
+ "loss": 0.476,
+ "step": 6977
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.789512692742731e-06,
+ "loss": 0.4709,
+ "step": 6978
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.786869904678486e-06,
+ "loss": 0.481,
+ "step": 6979
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.784227279137314e-06,
+ "loss": 0.4754,
+ "step": 6980
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.781584816313271e-06,
+ "loss": 0.4683,
+ "step": 6981
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.778942516400413e-06,
+ "loss": 0.4823,
+ "step": 6982
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.776300379592778e-06,
+ "loss": 0.4723,
+ "step": 6983
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.773658406084395e-06,
+ "loss": 0.4722,
+ "step": 6984
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.771016596069273e-06,
+ "loss": 0.478,
+ "step": 6985
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.768374949741427e-06,
+ "loss": 0.474,
+ "step": 6986
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.765733467294842e-06,
+ "loss": 0.4582,
+ "step": 6987
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.763092148923496e-06,
+ "loss": 0.4778,
+ "step": 6988
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.760450994821363e-06,
+ "loss": 0.4914,
+ "step": 6989
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.757810005182391e-06,
+ "loss": 0.4729,
+ "step": 6990
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.755169180200524e-06,
+ "loss": 0.4858,
+ "step": 6991
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.752528520069697e-06,
+ "loss": 0.4731,
+ "step": 6992
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.74988802498383e-06,
+ "loss": 0.4915,
+ "step": 6993
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.747247695136825e-06,
+ "loss": 0.4868,
+ "step": 6994
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.74460753072258e-06,
+ "loss": 0.484,
+ "step": 6995
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.74196753193498e-06,
+ "loss": 0.4831,
+ "step": 6996
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.739327698967891e-06,
+ "loss": 0.4833,
+ "step": 6997
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.736688032015168e-06,
+ "loss": 0.4727,
+ "step": 6998
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.734048531270664e-06,
+ "loss": 0.4703,
+ "step": 6999
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.731409196928214e-06,
+ "loss": 0.438,
+ "step": 7000
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.728770029181638e-06,
+ "loss": 0.4715,
+ "step": 7001
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.726131028224742e-06,
+ "loss": 0.4702,
+ "step": 7002
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.723492194251326e-06,
+ "loss": 0.4689,
+ "step": 7003
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.720853527455174e-06,
+ "loss": 0.4701,
+ "step": 7004
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.718215028030056e-06,
+ "loss": 0.475,
+ "step": 7005
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.71557669616974e-06,
+ "loss": 0.4504,
+ "step": 7006
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.71293853206797e-06,
+ "loss": 0.4582,
+ "step": 7007
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.710300535918482e-06,
+ "loss": 0.4723,
+ "step": 7008
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.707662707914997e-06,
+ "loss": 0.4739,
+ "step": 7009
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.705025048251228e-06,
+ "loss": 0.4664,
+ "step": 7010
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.702387557120876e-06,
+ "loss": 0.4789,
+ "step": 7011
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.699750234717622e-06,
+ "loss": 0.4828,
+ "step": 7012
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.697113081235147e-06,
+ "loss": 0.4587,
+ "step": 7013
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.694476096867105e-06,
+ "loss": 0.4863,
+ "step": 7014
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.691839281807153e-06,
+ "loss": 0.4657,
+ "step": 7015
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.689202636248923e-06,
+ "loss": 0.4932,
+ "step": 7016
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.68656616038604e-06,
+ "loss": 0.4581,
+ "step": 7017
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.683929854412114e-06,
+ "loss": 0.4734,
+ "step": 7018
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.681293718520746e-06,
+ "loss": 0.4629,
+ "step": 7019
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.678657752905522e-06,
+ "loss": 0.4578,
+ "step": 7020
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.676021957760023e-06,
+ "loss": 0.4507,
+ "step": 7021
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.673386333277802e-06,
+ "loss": 0.4571,
+ "step": 7022
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.670750879652414e-06,
+ "loss": 0.4914,
+ "step": 7023
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.668115597077388e-06,
+ "loss": 0.4869,
+ "step": 7024
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.665480485746255e-06,
+ "loss": 0.4831,
+ "step": 7025
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.662845545852526e-06,
+ "loss": 0.4795,
+ "step": 7026
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.6602107775897e-06,
+ "loss": 0.4938,
+ "step": 7027
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.657576181151266e-06,
+ "loss": 0.4709,
+ "step": 7028
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.654941756730687e-06,
+ "loss": 0.4714,
+ "step": 7029
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.652307504521437e-06,
+ "loss": 0.4525,
+ "step": 7030
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.649673424716958e-06,
+ "loss": 0.4659,
+ "step": 7031
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.647039517510685e-06,
+ "loss": 0.4626,
+ "step": 7032
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.644405783096044e-06,
+ "loss": 0.4977,
+ "step": 7033
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.641772221666446e-06,
+ "loss": 0.4793,
+ "step": 7034
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.639138833415285e-06,
+ "loss": 0.4711,
+ "step": 7035
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.636505618535953e-06,
+ "loss": 0.4851,
+ "step": 7036
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.633872577221815e-06,
+ "loss": 0.4648,
+ "step": 7037
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.631239709666234e-06,
+ "loss": 0.4492,
+ "step": 7038
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.628607016062553e-06,
+ "loss": 0.4862,
+ "step": 7039
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.625974496604109e-06,
+ "loss": 0.4618,
+ "step": 7040
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.623342151484229e-06,
+ "loss": 0.457,
+ "step": 7041
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.620709980896215e-06,
+ "loss": 0.4916,
+ "step": 7042
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.618077985033363e-06,
+ "loss": 0.5061,
+ "step": 7043
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.6154461640889555e-06,
+ "loss": 0.4657,
+ "step": 7044
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.612814518256265e-06,
+ "loss": 0.4678,
+ "step": 7045
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.610183047728543e-06,
+ "loss": 0.4981,
+ "step": 7046
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.607551752699043e-06,
+ "loss": 0.4745,
+ "step": 7047
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.604920633360991e-06,
+ "loss": 0.4684,
+ "step": 7048
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.6022896899076045e-06,
+ "loss": 0.4702,
+ "step": 7049
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.59965892253209e-06,
+ "loss": 0.4809,
+ "step": 7050
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.597028331427643e-06,
+ "loss": 0.4865,
+ "step": 7051
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.594397916787439e-06,
+ "loss": 0.4956,
+ "step": 7052
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.591767678804642e-06,
+ "loss": 0.4843,
+ "step": 7053
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.589137617672415e-06,
+ "loss": 0.4779,
+ "step": 7054
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.586507733583892e-06,
+ "loss": 0.4786,
+ "step": 7055
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.583878026732204e-06,
+ "loss": 0.4609,
+ "step": 7056
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.581248497310465e-06,
+ "loss": 0.4686,
+ "step": 7057
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5786191455117765e-06,
+ "loss": 0.479,
+ "step": 7058
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.575989971529223e-06,
+ "loss": 0.4769,
+ "step": 7059
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.573360975555885e-06,
+ "loss": 0.4699,
+ "step": 7060
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.570732157784823e-06,
+ "loss": 0.5061,
+ "step": 7061
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.56810351840909e-06,
+ "loss": 0.4889,
+ "step": 7062
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.56547505762172e-06,
+ "loss": 0.4664,
+ "step": 7063
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.562846775615734e-06,
+ "loss": 0.4808,
+ "step": 7064
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.560218672584143e-06,
+ "loss": 0.487,
+ "step": 7065
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.557590748719943e-06,
+ "loss": 0.4975,
+ "step": 7066
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5549630042161236e-06,
+ "loss": 0.4613,
+ "step": 7067
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.552335439265652e-06,
+ "loss": 0.4905,
+ "step": 7068
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.549708054061484e-06,
+ "loss": 0.4649,
+ "step": 7069
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.547080848796564e-06,
+ "loss": 0.5153,
+ "step": 7070
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.544453823663825e-06,
+ "loss": 0.4835,
+ "step": 7071
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.541826978856185e-06,
+ "loss": 0.4816,
+ "step": 7072
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.539200314566543e-06,
+ "loss": 0.465,
+ "step": 7073
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.536573830987798e-06,
+ "loss": 0.4549,
+ "step": 7074
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.533947528312825e-06,
+ "loss": 0.4682,
+ "step": 7075
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.531321406734486e-06,
+ "loss": 0.456,
+ "step": 7076
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.528695466445638e-06,
+ "loss": 0.4794,
+ "step": 7077
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.526069707639115e-06,
+ "loss": 0.461,
+ "step": 7078
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.523444130507743e-06,
+ "loss": 0.4683,
+ "step": 7079
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.52081873524433e-06,
+ "loss": 0.471,
+ "step": 7080
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.518193522041679e-06,
+ "loss": 0.4773,
+ "step": 7081
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5155684910925754e-06,
+ "loss": 0.472,
+ "step": 7082
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5129436425897876e-06,
+ "loss": 0.4755,
+ "step": 7083
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.510318976726074e-06,
+ "loss": 0.4634,
+ "step": 7084
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.507694493694179e-06,
+ "loss": 0.476,
+ "step": 7085
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.505070193686835e-06,
+ "loss": 0.4749,
+ "step": 7086
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.502446076896754e-06,
+ "loss": 0.4622,
+ "step": 7087
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.4998221435166504e-06,
+ "loss": 0.4815,
+ "step": 7088
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.497198393739209e-06,
+ "loss": 0.4569,
+ "step": 7089
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.494574827757107e-06,
+ "loss": 0.4719,
+ "step": 7090
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.4919514457630085e-06,
+ "loss": 0.4518,
+ "step": 7091
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.489328247949565e-06,
+ "loss": 0.4851,
+ "step": 7092
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.486705234509412e-06,
+ "loss": 0.4957,
+ "step": 7093
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.484082405635169e-06,
+ "loss": 0.4889,
+ "step": 7094
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.481459761519454e-06,
+ "loss": 0.4776,
+ "step": 7095
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.478837302354859e-06,
+ "loss": 0.4728,
+ "step": 7096
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.476215028333964e-06,
+ "loss": 0.4643,
+ "step": 7097
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.473592939649341e-06,
+ "loss": 0.468,
+ "step": 7098
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.470971036493546e-06,
+ "loss": 0.4845,
+ "step": 7099
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.468349319059114e-06,
+ "loss": 0.4818,
+ "step": 7100
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.465727787538584e-06,
+ "loss": 0.4749,
+ "step": 7101
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.463106442124459e-06,
+ "loss": 0.477,
+ "step": 7102
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.46048528300925e-06,
+ "loss": 0.4793,
+ "step": 7103
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.457864310385439e-06,
+ "loss": 0.4767,
+ "step": 7104
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.455243524445499e-06,
+ "loss": 0.474,
+ "step": 7105
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.452622925381887e-06,
+ "loss": 0.4725,
+ "step": 7106
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.450002513387053e-06,
+ "loss": 0.4833,
+ "step": 7107
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.4473822886534285e-06,
+ "loss": 0.4849,
+ "step": 7108
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.444762251373433e-06,
+ "loss": 0.498,
+ "step": 7109
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.442142401739469e-06,
+ "loss": 0.4671,
+ "step": 7110
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.439522739943929e-06,
+ "loss": 0.4719,
+ "step": 7111
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.436903266179187e-06,
+ "loss": 0.4683,
+ "step": 7112
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.434283980637611e-06,
+ "loss": 0.4745,
+ "step": 7113
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4316648835115445e-06,
+ "loss": 0.4699,
+ "step": 7114
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4290459749933296e-06,
+ "loss": 0.4847,
+ "step": 7115
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.426427255275284e-06,
+ "loss": 0.5188,
+ "step": 7116
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.423808724549715e-06,
+ "loss": 0.483,
+ "step": 7117
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.421190383008921e-06,
+ "loss": 0.4699,
+ "step": 7118
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.418572230845178e-06,
+ "loss": 0.4695,
+ "step": 7119
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4159542682507535e-06,
+ "loss": 0.4848,
+ "step": 7120
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.413336495417896e-06,
+ "loss": 0.4621,
+ "step": 7121
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.410718912538853e-06,
+ "loss": 0.464,
+ "step": 7122
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.40810151980584e-06,
+ "loss": 0.4818,
+ "step": 7123
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.405484317411071e-06,
+ "loss": 0.4593,
+ "step": 7124
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4028673055467456e-06,
+ "loss": 0.4669,
+ "step": 7125
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.400250484405041e-06,
+ "loss": 0.4662,
+ "step": 7126
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.397633854178125e-06,
+ "loss": 0.4847,
+ "step": 7127
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.395017415058154e-06,
+ "loss": 0.4946,
+ "step": 7128
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3924011672372745e-06,
+ "loss": 0.4734,
+ "step": 7129
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3897851109076055e-06,
+ "loss": 0.4795,
+ "step": 7130
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.387169246261262e-06,
+ "loss": 0.4637,
+ "step": 7131
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3845535734903385e-06,
+ "loss": 0.4562,
+ "step": 7132
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.381938092786926e-06,
+ "loss": 0.4704,
+ "step": 7133
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.37932280434309e-06,
+ "loss": 0.5288,
+ "step": 7134
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.376707708350881e-06,
+ "loss": 0.4919,
+ "step": 7135
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.374092805002353e-06,
+ "loss": 0.476,
+ "step": 7136
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.371478094489526e-06,
+ "loss": 0.4844,
+ "step": 7137
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.368863577004415e-06,
+ "loss": 0.4514,
+ "step": 7138
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3662492527390195e-06,
+ "loss": 0.4578,
+ "step": 7139
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.363635121885324e-06,
+ "loss": 0.4904,
+ "step": 7140
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.361021184635296e-06,
+ "loss": 0.4677,
+ "step": 7141
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.358407441180901e-06,
+ "loss": 0.4727,
+ "step": 7142
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.355793891714073e-06,
+ "loss": 0.4931,
+ "step": 7143
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.353180536426746e-06,
+ "loss": 0.4635,
+ "step": 7144
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.350567375510831e-06,
+ "loss": 0.4627,
+ "step": 7145
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.347954409158229e-06,
+ "loss": 0.4851,
+ "step": 7146
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.345341637560822e-06,
+ "loss": 0.4668,
+ "step": 7147
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3427290609104825e-06,
+ "loss": 0.4759,
+ "step": 7148
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.34011667939907e-06,
+ "loss": 0.4839,
+ "step": 7149
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.337504493218427e-06,
+ "loss": 0.4695,
+ "step": 7150
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.33489250256038e-06,
+ "loss": 0.4707,
+ "step": 7151
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.332280707616742e-06,
+ "loss": 0.4862,
+ "step": 7152
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.329669108579312e-06,
+ "loss": 0.4982,
+ "step": 7153
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3270577056398765e-06,
+ "loss": 0.4853,
+ "step": 7154
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.324446498990202e-06,
+ "loss": 0.46,
+ "step": 7155
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.321835488822052e-06,
+ "loss": 0.489,
+ "step": 7156
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.319224675327165e-06,
+ "loss": 0.4728,
+ "step": 7157
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.316614058697264e-06,
+ "loss": 0.4661,
+ "step": 7158
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.31400363912407e-06,
+ "loss": 0.4589,
+ "step": 7159
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.311393416799275e-06,
+ "loss": 0.477,
+ "step": 7160
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.308783391914566e-06,
+ "loss": 0.4748,
+ "step": 7161
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.306173564661606e-06,
+ "loss": 0.4859,
+ "step": 7162
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.303563935232059e-06,
+ "loss": 0.4681,
+ "step": 7163
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.30095450381756e-06,
+ "loss": 0.4732,
+ "step": 7164
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.298345270609738e-06,
+ "loss": 0.4953,
+ "step": 7165
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.295736235800202e-06,
+ "loss": 0.4648,
+ "step": 7166
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.293127399580548e-06,
+ "loss": 0.4667,
+ "step": 7167
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.290518762142359e-06,
+ "loss": 0.4753,
+ "step": 7168
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.287910323677199e-06,
+ "loss": 0.4855,
+ "step": 7169
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.285302084376629e-06,
+ "loss": 0.4779,
+ "step": 7170
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.282694044432182e-06,
+ "loss": 0.4729,
+ "step": 7171
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2800862040353834e-06,
+ "loss": 0.4795,
+ "step": 7172
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.277478563377738e-06,
+ "loss": 0.4546,
+ "step": 7173
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.274871122650746e-06,
+ "loss": 0.4783,
+ "step": 7174
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.272263882045884e-06,
+ "loss": 0.484,
+ "step": 7175
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.269656841754612e-06,
+ "loss": 0.4802,
+ "step": 7176
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2670500019683895e-06,
+ "loss": 0.4704,
+ "step": 7177
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.264443362878648e-06,
+ "loss": 0.4744,
+ "step": 7178
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.261836924676806e-06,
+ "loss": 0.4763,
+ "step": 7179
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.259230687554273e-06,
+ "loss": 0.4847,
+ "step": 7180
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.25662465170244e-06,
+ "loss": 0.4645,
+ "step": 7181
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.254018817312676e-06,
+ "loss": 0.4808,
+ "step": 7182
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2514131845763535e-06,
+ "loss": 0.4698,
+ "step": 7183
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.248807753684812e-06,
+ "loss": 0.4562,
+ "step": 7184
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.246202524829389e-06,
+ "loss": 0.4745,
+ "step": 7185
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.243597498201398e-06,
+ "loss": 0.474,
+ "step": 7186
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.240992673992142e-06,
+ "loss": 0.4557,
+ "step": 7187
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.238388052392906e-06,
+ "loss": 0.4624,
+ "step": 7188
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.235783633594966e-06,
+ "loss": 0.4785,
+ "step": 7189
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2331794177895785e-06,
+ "loss": 0.4791,
+ "step": 7190
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.230575405167989e-06,
+ "loss": 0.4867,
+ "step": 7191
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2279715959214216e-06,
+ "loss": 0.473,
+ "step": 7192
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2253679902410914e-06,
+ "loss": 0.4794,
+ "step": 7193
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2227645883181926e-06,
+ "loss": 0.4752,
+ "step": 7194
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.220161390343914e-06,
+ "loss": 0.4562,
+ "step": 7195
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.217558396509416e-06,
+ "loss": 0.4697,
+ "step": 7196
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.214955607005861e-06,
+ "loss": 0.479,
+ "step": 7197
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.212353022024381e-06,
+ "loss": 0.4691,
+ "step": 7198
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.209750641756099e-06,
+ "loss": 0.5009,
+ "step": 7199
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2071484663921265e-06,
+ "loss": 0.4813,
+ "step": 7200
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2045464961235545e-06,
+ "loss": 0.4723,
+ "step": 7201
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2019447311414615e-06,
+ "loss": 0.4889,
+ "step": 7202
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.199343171636903e-06,
+ "loss": 0.4896,
+ "step": 7203
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1967418178009396e-06,
+ "loss": 0.4664,
+ "step": 7204
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1941406698245945e-06,
+ "loss": 0.465,
+ "step": 7205
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1915397278988895e-06,
+ "loss": 0.4895,
+ "step": 7206
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.188938992214827e-06,
+ "loss": 0.4543,
+ "step": 7207
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.186338462963392e-06,
+ "loss": 0.4568,
+ "step": 7208
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.183738140335556e-06,
+ "loss": 0.4777,
+ "step": 7209
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.181138024522274e-06,
+ "loss": 0.4731,
+ "step": 7210
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1785381157144954e-06,
+ "loss": 0.4658,
+ "step": 7211
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.175938414103143e-06,
+ "loss": 0.4924,
+ "step": 7212
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.173338919879127e-06,
+ "loss": 0.4749,
+ "step": 7213
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.170739633233341e-06,
+ "loss": 0.46,
+ "step": 7214
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.168140554356671e-06,
+ "loss": 0.486,
+ "step": 7215
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.165541683439976e-06,
+ "loss": 0.4737,
+ "step": 7216
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.162943020674116e-06,
+ "loss": 0.4437,
+ "step": 7217
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.160344566249918e-06,
+ "loss": 0.4727,
+ "step": 7218
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1577463203582056e-06,
+ "loss": 0.4749,
+ "step": 7219
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.155148283189779e-06,
+ "loss": 0.4594,
+ "step": 7220
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.152550454935432e-06,
+ "loss": 0.4536,
+ "step": 7221
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.149952835785936e-06,
+ "loss": 0.4791,
+ "step": 7222
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.147355425932045e-06,
+ "loss": 0.4786,
+ "step": 7223
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.144758225564511e-06,
+ "loss": 0.4874,
+ "step": 7224
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1421612348740564e-06,
+ "loss": 0.4724,
+ "step": 7225
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.139564454051393e-06,
+ "loss": 0.4492,
+ "step": 7226
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1369678832872205e-06,
+ "loss": 0.4765,
+ "step": 7227
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.134371522772218e-06,
+ "loss": 0.4604,
+ "step": 7228
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.131775372697051e-06,
+ "loss": 0.4776,
+ "step": 7229
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.129179433252369e-06,
+ "loss": 0.4757,
+ "step": 7230
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.126583704628811e-06,
+ "loss": 0.4783,
+ "step": 7231
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.123988187016994e-06,
+ "loss": 0.4575,
+ "step": 7232
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.121392880607524e-06,
+ "loss": 0.4542,
+ "step": 7233
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.118797785590987e-06,
+ "loss": 0.4811,
+ "step": 7234
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.116202902157955e-06,
+ "loss": 0.4668,
+ "step": 7235
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.113608230498989e-06,
+ "loss": 0.4617,
+ "step": 7236
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.1110137708046245e-06,
+ "loss": 0.4798,
+ "step": 7237
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.108419523265398e-06,
+ "loss": 0.4776,
+ "step": 7238
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.105825488071814e-06,
+ "loss": 0.4692,
+ "step": 7239
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.1032316654143685e-06,
+ "loss": 0.5049,
+ "step": 7240
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.100638055483539e-06,
+ "loss": 0.497,
+ "step": 7241
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.098044658469794e-06,
+ "loss": 0.4646,
+ "step": 7242
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.095451474563577e-06,
+ "loss": 0.4768,
+ "step": 7243
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0928585039553196e-06,
+ "loss": 0.4877,
+ "step": 7244
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.090265746835448e-06,
+ "loss": 0.4736,
+ "step": 7245
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.087673203394353e-06,
+ "loss": 0.4889,
+ "step": 7246
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.085080873822427e-06,
+ "loss": 0.4775,
+ "step": 7247
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.082488758310039e-06,
+ "loss": 0.4754,
+ "step": 7248
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.079896857047541e-06,
+ "loss": 0.4945,
+ "step": 7249
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.07730517022527e-06,
+ "loss": 0.4771,
+ "step": 7250
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.074713698033551e-06,
+ "loss": 0.4622,
+ "step": 7251
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0721224406626895e-06,
+ "loss": 0.4601,
+ "step": 7252
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.069531398302982e-06,
+ "loss": 0.4758,
+ "step": 7253
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0669405711447e-06,
+ "loss": 0.4787,
+ "step": 7254
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.064349959378102e-06,
+ "loss": 0.4817,
+ "step": 7255
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.061759563193431e-06,
+ "loss": 0.4727,
+ "step": 7256
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.059169382780914e-06,
+ "loss": 0.4839,
+ "step": 7257
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.05657941833077e-06,
+ "loss": 0.4819,
+ "step": 7258
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.053989670033191e-06,
+ "loss": 0.4709,
+ "step": 7259
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.051400138078357e-06,
+ "loss": 0.5036,
+ "step": 7260
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.048810822656431e-06,
+ "loss": 0.4635,
+ "step": 7261
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.046221723957566e-06,
+ "loss": 0.4943,
+ "step": 7262
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.043632842171891e-06,
+ "loss": 0.466,
+ "step": 7263
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.04104417748952e-06,
+ "loss": 0.487,
+ "step": 7264
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.038455730100562e-06,
+ "loss": 0.5054,
+ "step": 7265
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.035867500195095e-06,
+ "loss": 0.4723,
+ "step": 7266
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.033279487963189e-06,
+ "loss": 0.4646,
+ "step": 7267
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.030691693594901e-06,
+ "loss": 0.49,
+ "step": 7268
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.028104117280265e-06,
+ "loss": 0.4855,
+ "step": 7269
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0255167592092995e-06,
+ "loss": 0.4694,
+ "step": 7270
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.022929619572009e-06,
+ "loss": 0.4606,
+ "step": 7271
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.020342698558387e-06,
+ "loss": 0.4617,
+ "step": 7272
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.017755996358404e-06,
+ "loss": 0.4771,
+ "step": 7273
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.015169513162018e-06,
+ "loss": 0.4914,
+ "step": 7274
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.012583249159167e-06,
+ "loss": 0.4829,
+ "step": 7275
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.009997204539775e-06,
+ "loss": 0.488,
+ "step": 7276
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.007411379493755e-06,
+ "loss": 0.4732,
+ "step": 7277
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.004825774210992e-06,
+ "loss": 0.4704,
+ "step": 7278
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.002240388881369e-06,
+ "loss": 0.4658,
+ "step": 7279
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.999655223694743e-06,
+ "loss": 0.4793,
+ "step": 7280
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.997070278840961e-06,
+ "loss": 0.4676,
+ "step": 7281
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.994485554509842e-06,
+ "loss": 0.4818,
+ "step": 7282
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9919010508912075e-06,
+ "loss": 0.4762,
+ "step": 7283
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.989316768174848e-06,
+ "loss": 0.4686,
+ "step": 7284
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.986732706550536e-06,
+ "loss": 0.4748,
+ "step": 7285
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.984148866208047e-06,
+ "loss": 0.4721,
+ "step": 7286
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.98156524733712e-06,
+ "loss": 0.48,
+ "step": 7287
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.978981850127487e-06,
+ "loss": 0.4841,
+ "step": 7288
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.976398674768863e-06,
+ "loss": 0.4418,
+ "step": 7289
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.973815721450942e-06,
+ "loss": 0.4861,
+ "step": 7290
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.971232990363406e-06,
+ "loss": 0.4719,
+ "step": 7291
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.968650481695926e-06,
+ "loss": 0.4704,
+ "step": 7292
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.966068195638143e-06,
+ "loss": 0.4914,
+ "step": 7293
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.963486132379694e-06,
+ "loss": 0.4566,
+ "step": 7294
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.960904292110194e-06,
+ "loss": 0.4767,
+ "step": 7295
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.958322675019243e-06,
+ "loss": 0.4918,
+ "step": 7296
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.955741281296421e-06,
+ "loss": 0.4656,
+ "step": 7297
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.953160111131295e-06,
+ "loss": 0.4493,
+ "step": 7298
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.950579164713422e-06,
+ "loss": 0.4678,
+ "step": 7299
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.947998442232332e-06,
+ "loss": 0.4811,
+ "step": 7300
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.945417943877541e-06,
+ "loss": 0.4744,
+ "step": 7301
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.942837669838552e-06,
+ "loss": 0.4583,
+ "step": 7302
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9402576203048474e-06,
+ "loss": 0.498,
+ "step": 7303
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.937677795465898e-06,
+ "loss": 0.4433,
+ "step": 7304
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.935098195511151e-06,
+ "loss": 0.4787,
+ "step": 7305
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.932518820630048e-06,
+ "loss": 0.4839,
+ "step": 7306
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.929939671012005e-06,
+ "loss": 0.4922,
+ "step": 7307
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9273607468464185e-06,
+ "loss": 0.451,
+ "step": 7308
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.924782048322683e-06,
+ "loss": 0.4665,
+ "step": 7309
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.922203575630164e-06,
+ "loss": 0.4927,
+ "step": 7310
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9196253289582104e-06,
+ "loss": 0.4512,
+ "step": 7311
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.917047308496159e-06,
+ "loss": 0.4649,
+ "step": 7312
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.914469514433331e-06,
+ "loss": 0.4551,
+ "step": 7313
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9118919469590285e-06,
+ "loss": 0.4659,
+ "step": 7314
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9093146062625395e-06,
+ "loss": 0.4642,
+ "step": 7315
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.906737492533129e-06,
+ "loss": 0.4668,
+ "step": 7316
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.904160605960051e-06,
+ "loss": 0.4703,
+ "step": 7317
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.901583946732542e-06,
+ "loss": 0.4792,
+ "step": 7318
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.899007515039817e-06,
+ "loss": 0.4782,
+ "step": 7319
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.896431311071086e-06,
+ "loss": 0.4555,
+ "step": 7320
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.893855335015532e-06,
+ "loss": 0.4866,
+ "step": 7321
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.891279587062321e-06,
+ "loss": 0.4725,
+ "step": 7322
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.888704067400605e-06,
+ "loss": 0.4588,
+ "step": 7323
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.886128776219525e-06,
+ "loss": 0.4671,
+ "step": 7324
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8835537137081955e-06,
+ "loss": 0.4611,
+ "step": 7325
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.880978880055716e-06,
+ "loss": 0.4666,
+ "step": 7326
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.878404275451176e-06,
+ "loss": 0.473,
+ "step": 7327
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.875829900083642e-06,
+ "loss": 0.4906,
+ "step": 7328
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.873255754142167e-06,
+ "loss": 0.4585,
+ "step": 7329
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.870681837815784e-06,
+ "loss": 0.4581,
+ "step": 7330
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.868108151293513e-06,
+ "loss": 0.4791,
+ "step": 7331
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.865534694764348e-06,
+ "loss": 0.4673,
+ "step": 7332
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.86296146841728e-06,
+ "loss": 0.4584,
+ "step": 7333
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.860388472441274e-06,
+ "loss": 0.4574,
+ "step": 7334
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8578157070252815e-06,
+ "loss": 0.4765,
+ "step": 7335
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8552431723582335e-06,
+ "loss": 0.4709,
+ "step": 7336
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.852670868629048e-06,
+ "loss": 0.4589,
+ "step": 7337
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.85009879602662e-06,
+ "loss": 0.4735,
+ "step": 7338
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8475269547398335e-06,
+ "loss": 0.4506,
+ "step": 7339
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.844955344957559e-06,
+ "loss": 0.488,
+ "step": 7340
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.842383966868642e-06,
+ "loss": 0.4864,
+ "step": 7341
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.839812820661912e-06,
+ "loss": 0.4675,
+ "step": 7342
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.837241906526182e-06,
+ "loss": 0.4823,
+ "step": 7343
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.834671224650254e-06,
+ "loss": 0.4612,
+ "step": 7344
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.832100775222906e-06,
+ "loss": 0.478,
+ "step": 7345
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.829530558432898e-06,
+ "loss": 0.4456,
+ "step": 7346
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8269605744689805e-06,
+ "loss": 0.4765,
+ "step": 7347
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.824390823519882e-06,
+ "loss": 0.481,
+ "step": 7348
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.82182130577431e-06,
+ "loss": 0.4775,
+ "step": 7349
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.819252021420966e-06,
+ "loss": 0.4842,
+ "step": 7350
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.816682970648522e-06,
+ "loss": 0.4671,
+ "step": 7351
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.814114153645641e-06,
+ "loss": 0.4894,
+ "step": 7352
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.811545570600961e-06,
+ "loss": 0.4694,
+ "step": 7353
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.808977221703115e-06,
+ "loss": 0.4797,
+ "step": 7354
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.8064091071407115e-06,
+ "loss": 0.4816,
+ "step": 7355
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.803841227102339e-06,
+ "loss": 0.4575,
+ "step": 7356
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.801273581776575e-06,
+ "loss": 0.4852,
+ "step": 7357
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.798706171351971e-06,
+ "loss": 0.4799,
+ "step": 7358
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.796138996017073e-06,
+ "loss": 0.4692,
+ "step": 7359
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.793572055960398e-06,
+ "loss": 0.4631,
+ "step": 7360
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.791005351370458e-06,
+ "loss": 0.47,
+ "step": 7361
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.788438882435737e-06,
+ "loss": 0.4797,
+ "step": 7362
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7858726493447084e-06,
+ "loss": 0.4582,
+ "step": 7363
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.78330665228582e-06,
+ "loss": 0.4842,
+ "step": 7364
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.780740891447515e-06,
+ "loss": 0.4711,
+ "step": 7365
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.778175367018205e-06,
+ "loss": 0.4705,
+ "step": 7366
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.775610079186299e-06,
+ "loss": 0.4719,
+ "step": 7367
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.773045028140177e-06,
+ "loss": 0.474,
+ "step": 7368
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.770480214068207e-06,
+ "loss": 0.4711,
+ "step": 7369
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.767915637158735e-06,
+ "loss": 0.4732,
+ "step": 7370
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.765351297600098e-06,
+ "loss": 0.5037,
+ "step": 7371
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.762787195580609e-06,
+ "loss": 0.4625,
+ "step": 7372
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.760223331288558e-06,
+ "loss": 0.4838,
+ "step": 7373
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.757659704912234e-06,
+ "loss": 0.4613,
+ "step": 7374
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.755096316639894e-06,
+ "loss": 0.4719,
+ "step": 7375
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.752533166659786e-06,
+ "loss": 0.4777,
+ "step": 7376
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.749970255160134e-06,
+ "loss": 0.4718,
+ "step": 7377
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.747407582329151e-06,
+ "loss": 0.4682,
+ "step": 7378
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.744845148355023e-06,
+ "loss": 0.4711,
+ "step": 7379
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.742282953425928e-06,
+ "loss": 0.4649,
+ "step": 7380
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.739720997730024e-06,
+ "loss": 0.4666,
+ "step": 7381
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.73715928145545e-06,
+ "loss": 0.4793,
+ "step": 7382
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.734597804790328e-06,
+ "loss": 0.4825,
+ "step": 7383
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.732036567922761e-06,
+ "loss": 0.4683,
+ "step": 7384
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.729475571040835e-06,
+ "loss": 0.4744,
+ "step": 7385
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.726914814332621e-06,
+ "loss": 0.4606,
+ "step": 7386
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.724354297986164e-06,
+ "loss": 0.4713,
+ "step": 7387
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7217940221895095e-06,
+ "loss": 0.5145,
+ "step": 7388
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7192339871306655e-06,
+ "loss": 0.4723,
+ "step": 7389
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7166741929976295e-06,
+ "loss": 0.4768,
+ "step": 7390
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7141146399783875e-06,
+ "loss": 0.4662,
+ "step": 7391
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.711555328260899e-06,
+ "loss": 0.4682,
+ "step": 7392
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.708996258033109e-06,
+ "loss": 0.4747,
+ "step": 7393
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.706437429482942e-06,
+ "loss": 0.4901,
+ "step": 7394
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.703878842798315e-06,
+ "loss": 0.4792,
+ "step": 7395
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.701320498167115e-06,
+ "loss": 0.4451,
+ "step": 7396
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.6987623957772165e-06,
+ "loss": 0.4769,
+ "step": 7397
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.696204535816479e-06,
+ "loss": 0.4691,
+ "step": 7398
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.693646918472739e-06,
+ "loss": 0.4577,
+ "step": 7399
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.691089543933815e-06,
+ "loss": 0.4784,
+ "step": 7400
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.68853241238751e-06,
+ "loss": 0.4884,
+ "step": 7401
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.685975524021615e-06,
+ "loss": 0.4705,
+ "step": 7402
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.683418879023893e-06,
+ "loss": 0.4748,
+ "step": 7403
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.6808624775820954e-06,
+ "loss": 0.49,
+ "step": 7404
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.678306319883948e-06,
+ "loss": 0.456,
+ "step": 7405
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.675750406117172e-06,
+ "loss": 0.447,
+ "step": 7406
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.673194736469455e-06,
+ "loss": 0.4794,
+ "step": 7407
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.670639311128484e-06,
+ "loss": 0.4712,
+ "step": 7408
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.668084130281913e-06,
+ "loss": 0.4512,
+ "step": 7409
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.665529194117386e-06,
+ "loss": 0.4734,
+ "step": 7410
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.662974502822524e-06,
+ "loss": 0.4735,
+ "step": 7411
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.660420056584935e-06,
+ "loss": 0.4767,
+ "step": 7412
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.65786585559221e-06,
+ "loss": 0.4643,
+ "step": 7413
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.655311900031909e-06,
+ "loss": 0.4899,
+ "step": 7414
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.652758190091595e-06,
+ "loss": 0.4542,
+ "step": 7415
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.650204725958795e-06,
+ "loss": 0.4742,
+ "step": 7416
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.647651507821029e-06,
+ "loss": 0.4802,
+ "step": 7417
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.645098535865793e-06,
+ "loss": 0.4728,
+ "step": 7418
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.642545810280567e-06,
+ "loss": 0.4773,
+ "step": 7419
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.63999333125281e-06,
+ "loss": 0.4743,
+ "step": 7420
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.637441098969967e-06,
+ "loss": 0.4709,
+ "step": 7421
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.634889113619463e-06,
+ "loss": 0.4619,
+ "step": 7422
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.632337375388709e-06,
+ "loss": 0.4638,
+ "step": 7423
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.629785884465091e-06,
+ "loss": 0.4739,
+ "step": 7424
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.62723464103598e-06,
+ "loss": 0.4845,
+ "step": 7425
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.624683645288726e-06,
+ "loss": 0.46,
+ "step": 7426
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.622132897410668e-06,
+ "loss": 0.4822,
+ "step": 7427
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.619582397589117e-06,
+ "loss": 0.4872,
+ "step": 7428
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.617032146011377e-06,
+ "loss": 0.4577,
+ "step": 7429
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.614482142864728e-06,
+ "loss": 0.4661,
+ "step": 7430
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.611932388336425e-06,
+ "loss": 0.4734,
+ "step": 7431
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.609382882613717e-06,
+ "loss": 0.5089,
+ "step": 7432
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.606833625883829e-06,
+ "loss": 0.4623,
+ "step": 7433
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.604284618333967e-06,
+ "loss": 0.4694,
+ "step": 7434
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.601735860151313e-06,
+ "loss": 0.4794,
+ "step": 7435
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.599187351523046e-06,
+ "loss": 0.4663,
+ "step": 7436
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.596639092636315e-06,
+ "loss": 0.4743,
+ "step": 7437
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.594091083678256e-06,
+ "loss": 0.4755,
+ "step": 7438
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.5915433248359795e-06,
+ "loss": 0.4826,
+ "step": 7439
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.588995816296585e-06,
+ "loss": 0.4959,
+ "step": 7440
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.586448558247147e-06,
+ "loss": 0.4803,
+ "step": 7441
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.58390155087473e-06,
+ "loss": 0.4815,
+ "step": 7442
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.581354794366377e-06,
+ "loss": 0.4684,
+ "step": 7443
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.578808288909109e-06,
+ "loss": 0.4681,
+ "step": 7444
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.576262034689929e-06,
+ "loss": 0.4779,
+ "step": 7445
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.573716031895825e-06,
+ "loss": 0.4647,
+ "step": 7446
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.571170280713765e-06,
+ "loss": 0.4679,
+ "step": 7447
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.568624781330694e-06,
+ "loss": 0.472,
+ "step": 7448
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.566079533933551e-06,
+ "loss": 0.4853,
+ "step": 7449
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.563534538709244e-06,
+ "loss": 0.4819,
+ "step": 7450
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.560989795844668e-06,
+ "loss": 0.4661,
+ "step": 7451
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.558445305526695e-06,
+ "loss": 0.4871,
+ "step": 7452
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.555901067942188e-06,
+ "loss": 0.4697,
+ "step": 7453
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.553357083277979e-06,
+ "loss": 0.4684,
+ "step": 7454
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.550813351720888e-06,
+ "loss": 0.448,
+ "step": 7455
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.54826987345772e-06,
+ "loss": 0.4641,
+ "step": 7456
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.545726648675255e-06,
+ "loss": 0.4725,
+ "step": 7457
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.54318367756026e-06,
+ "loss": 0.4737,
+ "step": 7458
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.540640960299477e-06,
+ "loss": 0.4911,
+ "step": 7459
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.538098497079634e-06,
+ "loss": 0.4779,
+ "step": 7460
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.5355562880874345e-06,
+ "loss": 0.4593,
+ "step": 7461
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.533014333509573e-06,
+ "loss": 0.4589,
+ "step": 7462
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.530472633532718e-06,
+ "loss": 0.485,
+ "step": 7463
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.527931188343525e-06,
+ "loss": 0.5078,
+ "step": 7464
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.525389998128624e-06,
+ "loss": 0.4716,
+ "step": 7465
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.522849063074628e-06,
+ "loss": 0.4613,
+ "step": 7466
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.520308383368134e-06,
+ "loss": 0.4736,
+ "step": 7467
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.51776795919572e-06,
+ "loss": 0.4775,
+ "step": 7468
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.515227790743939e-06,
+ "loss": 0.4675,
+ "step": 7469
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.51268787819934e-06,
+ "loss": 0.5053,
+ "step": 7470
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.510148221748438e-06,
+ "loss": 0.4562,
+ "step": 7471
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.507608821577733e-06,
+ "loss": 0.4942,
+ "step": 7472
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.505069677873712e-06,
+ "loss": 0.4833,
+ "step": 7473
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.502530790822838e-06,
+ "loss": 0.4595,
+ "step": 7474
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.499992160611556e-06,
+ "loss": 0.4807,
+ "step": 7475
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4974537874262865e-06,
+ "loss": 0.4696,
+ "step": 7476
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.494915671453448e-06,
+ "loss": 0.4573,
+ "step": 7477
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.492377812879422e-06,
+ "loss": 0.4639,
+ "step": 7478
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.489840211890581e-06,
+ "loss": 0.4548,
+ "step": 7479
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4873028686732755e-06,
+ "loss": 0.4844,
+ "step": 7480
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.484765783413838e-06,
+ "loss": 0.4707,
+ "step": 7481
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.482228956298575e-06,
+ "loss": 0.4791,
+ "step": 7482
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.479692387513788e-06,
+ "loss": 0.4717,
+ "step": 7483
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.477156077245752e-06,
+ "loss": 0.4769,
+ "step": 7484
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.474620025680722e-06,
+ "loss": 0.487,
+ "step": 7485
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.472084233004934e-06,
+ "loss": 0.4828,
+ "step": 7486
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.469548699404603e-06,
+ "loss": 0.4782,
+ "step": 7487
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.467013425065935e-06,
+ "loss": 0.4786,
+ "step": 7488
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.464478410175101e-06,
+ "loss": 0.4812,
+ "step": 7489
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.461943654918271e-06,
+ "loss": 0.4729,
+ "step": 7490
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.459409159481584e-06,
+ "loss": 0.4727,
+ "step": 7491
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.456874924051162e-06,
+ "loss": 0.4939,
+ "step": 7492
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.454340948813105e-06,
+ "loss": 0.4628,
+ "step": 7493
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.451807233953504e-06,
+ "loss": 0.4971,
+ "step": 7494
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4492737796584225e-06,
+ "loss": 0.4719,
+ "step": 7495
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.446740586113902e-06,
+ "loss": 0.4494,
+ "step": 7496
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4442076535059774e-06,
+ "loss": 0.4809,
+ "step": 7497
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.441674982020654e-06,
+ "loss": 0.4808,
+ "step": 7498
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.439142571843915e-06,
+ "loss": 0.4673,
+ "step": 7499
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.43661042316174e-06,
+ "loss": 0.4685,
+ "step": 7500
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.434078536160072e-06,
+ "loss": 0.4587,
+ "step": 7501
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.431546911024844e-06,
+ "loss": 0.4609,
+ "step": 7502
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.429015547941968e-06,
+ "loss": 0.4694,
+ "step": 7503
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.426484447097336e-06,
+ "loss": 0.4861,
+ "step": 7504
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.423953608676827e-06,
+ "loss": 0.4696,
+ "step": 7505
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.42142303286629e-06,
+ "loss": 0.483,
+ "step": 7506
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.418892719851561e-06,
+ "loss": 0.4773,
+ "step": 7507
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.416362669818454e-06,
+ "loss": 0.4661,
+ "step": 7508
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.413832882952769e-06,
+ "loss": 0.4772,
+ "step": 7509
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.411303359440277e-06,
+ "loss": 0.4728,
+ "step": 7510
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.408774099466744e-06,
+ "loss": 0.4697,
+ "step": 7511
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.406245103217903e-06,
+ "loss": 0.4669,
+ "step": 7512
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.403716370879476e-06,
+ "loss": 0.4848,
+ "step": 7513
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.401187902637157e-06,
+ "loss": 0.4847,
+ "step": 7514
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.398659698676632e-06,
+ "loss": 0.4871,
+ "step": 7515
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.396131759183557e-06,
+ "loss": 0.4799,
+ "step": 7516
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.393604084343579e-06,
+ "loss": 0.4634,
+ "step": 7517
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.391076674342316e-06,
+ "loss": 0.4661,
+ "step": 7518
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.388549529365371e-06,
+ "loss": 0.4611,
+ "step": 7519
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3860226495983295e-06,
+ "loss": 0.4653,
+ "step": 7520
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.383496035226752e-06,
+ "loss": 0.4802,
+ "step": 7521
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.380969686436183e-06,
+ "loss": 0.4697,
+ "step": 7522
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.378443603412145e-06,
+ "loss": 0.47,
+ "step": 7523
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.375917786340149e-06,
+ "loss": 0.4656,
+ "step": 7524
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.373392235405674e-06,
+ "loss": 0.4674,
+ "step": 7525
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3708669507941925e-06,
+ "loss": 0.454,
+ "step": 7526
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.368341932691146e-06,
+ "loss": 0.4648,
+ "step": 7527
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.365817181281965e-06,
+ "loss": 0.4764,
+ "step": 7528
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.36329269675205e-06,
+ "loss": 0.4925,
+ "step": 7529
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.360768479286793e-06,
+ "loss": 0.4803,
+ "step": 7530
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.358244529071565e-06,
+ "loss": 0.4688,
+ "step": 7531
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.355720846291713e-06,
+ "loss": 0.4638,
+ "step": 7532
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3531974311325625e-06,
+ "loss": 0.4732,
+ "step": 7533
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.350674283779424e-06,
+ "loss": 0.4725,
+ "step": 7534
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.348151404417589e-06,
+ "loss": 0.46,
+ "step": 7535
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3456287932323255e-06,
+ "loss": 0.4699,
+ "step": 7536
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.34310645040888e-06,
+ "loss": 0.464,
+ "step": 7537
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.34058437613249e-06,
+ "loss": 0.4604,
+ "step": 7538
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.338062570588363e-06,
+ "loss": 0.4868,
+ "step": 7539
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.335541033961687e-06,
+ "loss": 0.4638,
+ "step": 7540
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.33301976643764e-06,
+ "loss": 0.4742,
+ "step": 7541
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.330498768201367e-06,
+ "loss": 0.4737,
+ "step": 7542
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.327978039438003e-06,
+ "loss": 0.476,
+ "step": 7543
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.325457580332655e-06,
+ "loss": 0.4563,
+ "step": 7544
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3229373910704205e-06,
+ "loss": 0.4869,
+ "step": 7545
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3204174718363705e-06,
+ "loss": 0.4795,
+ "step": 7546
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.317897822815559e-06,
+ "loss": 0.4641,
+ "step": 7547
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.315378444193014e-06,
+ "loss": 0.4707,
+ "step": 7548
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.31285933615375e-06,
+ "loss": 0.4488,
+ "step": 7549
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.310340498882763e-06,
+ "loss": 0.4658,
+ "step": 7550
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.30782193256502e-06,
+ "loss": 0.4589,
+ "step": 7551
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.305303637385478e-06,
+ "loss": 0.4657,
+ "step": 7552
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.302785613529072e-06,
+ "loss": 0.4786,
+ "step": 7553
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.300267861180713e-06,
+ "loss": 0.4664,
+ "step": 7554
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.297750380525289e-06,
+ "loss": 0.4712,
+ "step": 7555
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.295233171747683e-06,
+ "loss": 0.4753,
+ "step": 7556
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.292716235032738e-06,
+ "loss": 0.4655,
+ "step": 7557
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.290199570565298e-06,
+ "loss": 0.4664,
+ "step": 7558
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.287683178530172e-06,
+ "loss": 0.4774,
+ "step": 7559
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.285167059112149e-06,
+ "loss": 0.482,
+ "step": 7560
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.282651212496009e-06,
+ "loss": 0.4864,
+ "step": 7561
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.280135638866502e-06,
+ "loss": 0.4768,
+ "step": 7562
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.277620338408362e-06,
+ "loss": 0.4789,
+ "step": 7563
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.275105311306298e-06,
+ "loss": 0.4865,
+ "step": 7564
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.272590557745011e-06,
+ "loss": 0.4426,
+ "step": 7565
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.270076077909166e-06,
+ "loss": 0.4658,
+ "step": 7566
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.267561871983424e-06,
+ "loss": 0.4645,
+ "step": 7567
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.265047940152413e-06,
+ "loss": 0.4599,
+ "step": 7568
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.262534282600747e-06,
+ "loss": 0.4751,
+ "step": 7569
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2600208995130156e-06,
+ "loss": 0.4681,
+ "step": 7570
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.257507791073792e-06,
+ "loss": 0.4576,
+ "step": 7571
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.254994957467633e-06,
+ "loss": 0.4755,
+ "step": 7572
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.252482398879068e-06,
+ "loss": 0.4781,
+ "step": 7573
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.249970115492609e-06,
+ "loss": 0.4545,
+ "step": 7574
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.247458107492745e-06,
+ "loss": 0.4745,
+ "step": 7575
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.244946375063951e-06,
+ "loss": 0.4892,
+ "step": 7576
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.242434918390678e-06,
+ "loss": 0.4818,
+ "step": 7577
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.239923737657351e-06,
+ "loss": 0.4687,
+ "step": 7578
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.237412833048389e-06,
+ "loss": 0.4732,
+ "step": 7579
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2349022047481784e-06,
+ "loss": 0.4699,
+ "step": 7580
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2323918529410895e-06,
+ "loss": 0.4839,
+ "step": 7581
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2298817778114725e-06,
+ "loss": 0.4702,
+ "step": 7582
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.227371979543658e-06,
+ "loss": 0.4687,
+ "step": 7583
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.224862458321954e-06,
+ "loss": 0.5033,
+ "step": 7584
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.222353214330643e-06,
+ "loss": 0.4622,
+ "step": 7585
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2198442477540036e-06,
+ "loss": 0.4653,
+ "step": 7586
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2173355587762805e-06,
+ "loss": 0.4618,
+ "step": 7587
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.214827147581701e-06,
+ "loss": 0.4721,
+ "step": 7588
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.212319014354472e-06,
+ "loss": 0.4822,
+ "step": 7589
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.209811159278778e-06,
+ "loss": 0.4573,
+ "step": 7590
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.207303582538789e-06,
+ "loss": 0.4765,
+ "step": 7591
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.2047962843186495e-06,
+ "loss": 0.4657,
+ "step": 7592
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.202289264802488e-06,
+ "loss": 0.4607,
+ "step": 7593
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.199782524174406e-06,
+ "loss": 0.4389,
+ "step": 7594
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.197276062618489e-06,
+ "loss": 0.4819,
+ "step": 7595
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.194769880318801e-06,
+ "loss": 0.4754,
+ "step": 7596
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.192263977459385e-06,
+ "loss": 0.4634,
+ "step": 7597
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.189758354224262e-06,
+ "loss": 0.4707,
+ "step": 7598
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.187253010797443e-06,
+ "loss": 0.4694,
+ "step": 7599
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1847479473629035e-06,
+ "loss": 0.4673,
+ "step": 7600
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1822431641046045e-06,
+ "loss": 0.4739,
+ "step": 7601
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1797386612064895e-06,
+ "loss": 0.4772,
+ "step": 7602
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.177234438852477e-06,
+ "loss": 0.4582,
+ "step": 7603
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.174730497226467e-06,
+ "loss": 0.4811,
+ "step": 7604
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.172226836512336e-06,
+ "loss": 0.4807,
+ "step": 7605
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.16972345689395e-06,
+ "loss": 0.4766,
+ "step": 7606
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.167220358555138e-06,
+ "loss": 0.4655,
+ "step": 7607
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.164717541679724e-06,
+ "loss": 0.4603,
+ "step": 7608
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.162215006451502e-06,
+ "loss": 0.4671,
+ "step": 7609
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.159712753054248e-06,
+ "loss": 0.4648,
+ "step": 7610
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.157210781671713e-06,
+ "loss": 0.4749,
+ "step": 7611
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.154709092487633e-06,
+ "loss": 0.4573,
+ "step": 7612
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.152207685685727e-06,
+ "loss": 0.4714,
+ "step": 7613
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1497065614496866e-06,
+ "loss": 0.4892,
+ "step": 7614
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.147205719963181e-06,
+ "loss": 0.4641,
+ "step": 7615
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.144705161409858e-06,
+ "loss": 0.4658,
+ "step": 7616
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.142204885973358e-06,
+ "loss": 0.4738,
+ "step": 7617
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1397048938372825e-06,
+ "loss": 0.4532,
+ "step": 7618
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.13720518518522e-06,
+ "loss": 0.481,
+ "step": 7619
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.134705760200747e-06,
+ "loss": 0.4683,
+ "step": 7620
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.132206619067407e-06,
+ "loss": 0.4594,
+ "step": 7621
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1297077619687216e-06,
+ "loss": 0.4808,
+ "step": 7622
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.127209189088204e-06,
+ "loss": 0.4638,
+ "step": 7623
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1247109006093345e-06,
+ "loss": 0.4768,
+ "step": 7624
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.122212896715577e-06,
+ "loss": 0.4717,
+ "step": 7625
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.119715177590373e-06,
+ "loss": 0.4688,
+ "step": 7626
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1172177434171495e-06,
+ "loss": 0.4736,
+ "step": 7627
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.114720594379304e-06,
+ "loss": 0.5022,
+ "step": 7628
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.112223730660221e-06,
+ "loss": 0.4698,
+ "step": 7629
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.109727152443254e-06,
+ "loss": 0.4825,
+ "step": 7630
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1072308599117445e-06,
+ "loss": 0.4657,
+ "step": 7631
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.104734853249009e-06,
+ "loss": 0.4716,
+ "step": 7632
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.102239132638343e-06,
+ "loss": 0.4828,
+ "step": 7633
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.099743698263028e-06,
+ "loss": 0.4588,
+ "step": 7634
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.097248550306311e-06,
+ "loss": 0.4679,
+ "step": 7635
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.094753688951428e-06,
+ "loss": 0.4711,
+ "step": 7636
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.092259114381589e-06,
+ "loss": 0.4754,
+ "step": 7637
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.089764826779989e-06,
+ "loss": 0.4503,
+ "step": 7638
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.087270826329793e-06,
+ "loss": 0.4527,
+ "step": 7639
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.084777113214156e-06,
+ "loss": 0.4627,
+ "step": 7640
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.082283687616204e-06,
+ "loss": 0.4812,
+ "step": 7641
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.079790549719044e-06,
+ "loss": 0.4899,
+ "step": 7642
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.077297699705758e-06,
+ "loss": 0.4577,
+ "step": 7643
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.074805137759414e-06,
+ "loss": 0.4823,
+ "step": 7644
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.072312864063054e-06,
+ "loss": 0.4605,
+ "step": 7645
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0698208787996995e-06,
+ "loss": 0.4674,
+ "step": 7646
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.067329182152355e-06,
+ "loss": 0.4326,
+ "step": 7647
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.064837774303997e-06,
+ "loss": 0.4767,
+ "step": 7648
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0623466554375864e-06,
+ "loss": 0.4843,
+ "step": 7649
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.059855825736061e-06,
+ "loss": 0.4827,
+ "step": 7650
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.057365285382333e-06,
+ "loss": 0.4549,
+ "step": 7651
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0548750345593e-06,
+ "loss": 0.4818,
+ "step": 7652
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.052385073449833e-06,
+ "loss": 0.4602,
+ "step": 7653
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.049895402236789e-06,
+ "loss": 0.4846,
+ "step": 7654
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.047406021103e-06,
+ "loss": 0.4772,
+ "step": 7655
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.04491693023127e-06,
+ "loss": 0.4602,
+ "step": 7656
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.042428129804392e-06,
+ "loss": 0.4973,
+ "step": 7657
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0399396200051285e-06,
+ "loss": 0.4907,
+ "step": 7658
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0374514010162296e-06,
+ "loss": 0.4616,
+ "step": 7659
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.034963473020417e-06,
+ "loss": 0.4955,
+ "step": 7660
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0324758362003956e-06,
+ "loss": 0.4642,
+ "step": 7661
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.029988490738849e-06,
+ "loss": 0.4725,
+ "step": 7662
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.027501436818433e-06,
+ "loss": 0.4769,
+ "step": 7663
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0250146746217895e-06,
+ "loss": 0.4685,
+ "step": 7664
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.022528204331534e-06,
+ "loss": 0.4556,
+ "step": 7665
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.020042026130262e-06,
+ "loss": 0.4587,
+ "step": 7666
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.017556140200553e-06,
+ "loss": 0.4977,
+ "step": 7667
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.015070546724957e-06,
+ "loss": 0.4682,
+ "step": 7668
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.012585245886004e-06,
+ "loss": 0.4524,
+ "step": 7669
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0101002378662066e-06,
+ "loss": 0.4828,
+ "step": 7670
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.007615522848053e-06,
+ "loss": 0.4578,
+ "step": 7671
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.00513110101401e-06,
+ "loss": 0.4576,
+ "step": 7672
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.002646972546517e-06,
+ "loss": 0.4703,
+ "step": 7673
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.000163137628009e-06,
+ "loss": 0.4826,
+ "step": 7674
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.997679596440884e-06,
+ "loss": 0.4883,
+ "step": 7675
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.995196349167523e-06,
+ "loss": 0.4739,
+ "step": 7676
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.992713395990285e-06,
+ "loss": 0.485,
+ "step": 7677
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.990230737091505e-06,
+ "loss": 0.4745,
+ "step": 7678
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.987748372653504e-06,
+ "loss": 0.4834,
+ "step": 7679
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9852663028585704e-06,
+ "loss": 0.466,
+ "step": 7680
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.982784527888985e-06,
+ "loss": 0.4647,
+ "step": 7681
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.980303047926996e-06,
+ "loss": 0.476,
+ "step": 7682
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.977821863154832e-06,
+ "loss": 0.4727,
+ "step": 7683
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.975340973754697e-06,
+ "loss": 0.463,
+ "step": 7684
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.972860379908784e-06,
+ "loss": 0.474,
+ "step": 7685
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.970380081799254e-06,
+ "loss": 0.4732,
+ "step": 7686
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.967900079608247e-06,
+ "loss": 0.4832,
+ "step": 7687
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.965420373517892e-06,
+ "loss": 0.4749,
+ "step": 7688
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.96294096371028e-06,
+ "loss": 0.4943,
+ "step": 7689
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.960461850367496e-06,
+ "loss": 0.4747,
+ "step": 7690
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9579830336715905e-06,
+ "loss": 0.4638,
+ "step": 7691
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9555045138046e-06,
+ "loss": 0.4821,
+ "step": 7692
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.953026290948534e-06,
+ "loss": 0.4843,
+ "step": 7693
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.950548365285383e-06,
+ "loss": 0.4715,
+ "step": 7694
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.948070736997118e-06,
+ "loss": 0.4683,
+ "step": 7695
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9455934062656874e-06,
+ "loss": 0.4626,
+ "step": 7696
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.943116373273012e-06,
+ "loss": 0.4571,
+ "step": 7697
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.940639638200998e-06,
+ "loss": 0.48,
+ "step": 7698
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.938163201231523e-06,
+ "loss": 0.4771,
+ "step": 7699
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.935687062546449e-06,
+ "loss": 0.4547,
+ "step": 7700
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.933211222327608e-06,
+ "loss": 0.4689,
+ "step": 7701
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.930735680756825e-06,
+ "loss": 0.4698,
+ "step": 7702
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.928260438015887e-06,
+ "loss": 0.4458,
+ "step": 7703
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.925785494286566e-06,
+ "loss": 0.4599,
+ "step": 7704
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.923310849750614e-06,
+ "loss": 0.4897,
+ "step": 7705
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.920836504589756e-06,
+ "loss": 0.4731,
+ "step": 7706
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9183624589856956e-06,
+ "loss": 0.4675,
+ "step": 7707
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.915888713120124e-06,
+ "loss": 0.4822,
+ "step": 7708
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.913415267174696e-06,
+ "loss": 0.4777,
+ "step": 7709
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.910942121331054e-06,
+ "loss": 0.4775,
+ "step": 7710
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.908469275770815e-06,
+ "loss": 0.4773,
+ "step": 7711
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.905996730675575e-06,
+ "loss": 0.4766,
+ "step": 7712
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.903524486226907e-06,
+ "loss": 0.4699,
+ "step": 7713
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.901052542606358e-06,
+ "loss": 0.4748,
+ "step": 7714
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.898580899995463e-06,
+ "loss": 0.4859,
+ "step": 7715
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.896109558575731e-06,
+ "loss": 0.4632,
+ "step": 7716
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.893638518528643e-06,
+ "loss": 0.4726,
+ "step": 7717
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.891167780035663e-06,
+ "loss": 0.4775,
+ "step": 7718
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.888697343278229e-06,
+ "loss": 0.4747,
+ "step": 7719
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.886227208437763e-06,
+ "loss": 0.4684,
+ "step": 7720
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8837573756956575e-06,
+ "loss": 0.4646,
+ "step": 7721
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.881287845233292e-06,
+ "loss": 0.4675,
+ "step": 7722
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.878818617232018e-06,
+ "loss": 0.4882,
+ "step": 7723
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.876349691873162e-06,
+ "loss": 0.4614,
+ "step": 7724
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.873881069338032e-06,
+ "loss": 0.4633,
+ "step": 7725
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.871412749807917e-06,
+ "loss": 0.4684,
+ "step": 7726
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.868944733464077e-06,
+ "loss": 0.4677,
+ "step": 7727
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.866477020487748e-06,
+ "loss": 0.4895,
+ "step": 7728
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.86400961106016e-06,
+ "loss": 0.4697,
+ "step": 7729
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8615425053625005e-06,
+ "loss": 0.4953,
+ "step": 7730
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.859075703575949e-06,
+ "loss": 0.464,
+ "step": 7731
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.856609205881654e-06,
+ "loss": 0.4749,
+ "step": 7732
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.854143012460745e-06,
+ "loss": 0.4698,
+ "step": 7733
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.851677123494326e-06,
+ "loss": 0.4582,
+ "step": 7734
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.849211539163486e-06,
+ "loss": 0.4782,
+ "step": 7735
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.846746259649288e-06,
+ "loss": 0.4867,
+ "step": 7736
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.844281285132769e-06,
+ "loss": 0.4811,
+ "step": 7737
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.841816615794948e-06,
+ "loss": 0.4702,
+ "step": 7738
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.839352251816821e-06,
+ "loss": 0.4787,
+ "step": 7739
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.836888193379359e-06,
+ "loss": 0.4668,
+ "step": 7740
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.834424440663512e-06,
+ "loss": 0.4868,
+ "step": 7741
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.831960993850203e-06,
+ "loss": 0.4854,
+ "step": 7742
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.829497853120345e-06,
+ "loss": 0.4697,
+ "step": 7743
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.827035018654821e-06,
+ "loss": 0.4569,
+ "step": 7744
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.824572490634488e-06,
+ "loss": 0.464,
+ "step": 7745
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.822110269240184e-06,
+ "loss": 0.5041,
+ "step": 7746
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.819648354652725e-06,
+ "loss": 0.4528,
+ "step": 7747
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8171867470529e-06,
+ "loss": 0.4847,
+ "step": 7748
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8147254466214865e-06,
+ "loss": 0.4592,
+ "step": 7749
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.812264453539228e-06,
+ "loss": 0.4716,
+ "step": 7750
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.809803767986851e-06,
+ "loss": 0.473,
+ "step": 7751
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.807343390145055e-06,
+ "loss": 0.4787,
+ "step": 7752
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.80488332019452e-06,
+ "loss": 0.4637,
+ "step": 7753
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.802423558315908e-06,
+ "loss": 0.4845,
+ "step": 7754
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.799964104689847e-06,
+ "loss": 0.4641,
+ "step": 7755
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.797504959496957e-06,
+ "loss": 0.4473,
+ "step": 7756
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.795046122917823e-06,
+ "loss": 0.4654,
+ "step": 7757
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.792587595133012e-06,
+ "loss": 0.4761,
+ "step": 7758
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.790129376323068e-06,
+ "loss": 0.4757,
+ "step": 7759
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.787671466668513e-06,
+ "loss": 0.4667,
+ "step": 7760
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.785213866349844e-06,
+ "loss": 0.5057,
+ "step": 7761
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.782756575547535e-06,
+ "loss": 0.4902,
+ "step": 7762
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.780299594442047e-06,
+ "loss": 0.4814,
+ "step": 7763
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.777842923213801e-06,
+ "loss": 0.4806,
+ "step": 7764
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.775386562043212e-06,
+ "loss": 0.4772,
+ "step": 7765
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7729305111106645e-06,
+ "loss": 0.4515,
+ "step": 7766
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.770474770596518e-06,
+ "loss": 0.4629,
+ "step": 7767
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.768019340681113e-06,
+ "loss": 0.4687,
+ "step": 7768
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.765564221544759e-06,
+ "loss": 0.458,
+ "step": 7769
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.763109413367762e-06,
+ "loss": 0.4801,
+ "step": 7770
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.760654916330388e-06,
+ "loss": 0.5006,
+ "step": 7771
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.758200730612883e-06,
+ "loss": 0.4343,
+ "step": 7772
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.75574685639547e-06,
+ "loss": 0.4685,
+ "step": 7773
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7532932938583575e-06,
+ "loss": 0.4836,
+ "step": 7774
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.750840043181722e-06,
+ "loss": 0.4585,
+ "step": 7775
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7483871045457185e-06,
+ "loss": 0.4923,
+ "step": 7776
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.745934478130484e-06,
+ "loss": 0.4916,
+ "step": 7777
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7434821641161285e-06,
+ "loss": 0.4803,
+ "step": 7778
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.74103016268274e-06,
+ "loss": 0.4627,
+ "step": 7779
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.738578474010379e-06,
+ "loss": 0.4538,
+ "step": 7780
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.736127098279092e-06,
+ "loss": 0.4798,
+ "step": 7781
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.733676035668891e-06,
+ "loss": 0.4515,
+ "step": 7782
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.731225286359781e-06,
+ "loss": 0.4924,
+ "step": 7783
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.728774850531733e-06,
+ "loss": 0.468,
+ "step": 7784
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.726324728364688e-06,
+ "loss": 0.4704,
+ "step": 7785
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.723874920038586e-06,
+ "loss": 0.4524,
+ "step": 7786
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.721425425733322e-06,
+ "loss": 0.4711,
+ "step": 7787
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.718976245628779e-06,
+ "loss": 0.4704,
+ "step": 7788
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7165273799048105e-06,
+ "loss": 0.475,
+ "step": 7789
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.71407882874126e-06,
+ "loss": 0.4684,
+ "step": 7790
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.711630592317933e-06,
+ "loss": 0.4576,
+ "step": 7791
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.709182670814619e-06,
+ "loss": 0.4713,
+ "step": 7792
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.706735064411082e-06,
+ "loss": 0.4866,
+ "step": 7793
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.704287773287061e-06,
+ "loss": 0.4498,
+ "step": 7794
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.701840797622284e-06,
+ "loss": 0.4883,
+ "step": 7795
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.699394137596437e-06,
+ "loss": 0.4998,
+ "step": 7796
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6969477933892e-06,
+ "loss": 0.4451,
+ "step": 7797
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.69450176518022e-06,
+ "loss": 0.4563,
+ "step": 7798
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.692056053149122e-06,
+ "loss": 0.4794,
+ "step": 7799
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.68961065747551e-06,
+ "loss": 0.4454,
+ "step": 7800
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.687165578338962e-06,
+ "loss": 0.4627,
+ "step": 7801
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.684720815919036e-06,
+ "loss": 0.4788,
+ "step": 7802
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.682276370395261e-06,
+ "loss": 0.4744,
+ "step": 7803
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.679832241947154e-06,
+ "loss": 0.4643,
+ "step": 7804
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.677388430754196e-06,
+ "loss": 0.4488,
+ "step": 7805
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.674944936995854e-06,
+ "loss": 0.4716,
+ "step": 7806
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.672501760851568e-06,
+ "loss": 0.4773,
+ "step": 7807
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6700589025007535e-06,
+ "loss": 0.4811,
+ "step": 7808
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.667616362122803e-06,
+ "loss": 0.491,
+ "step": 7809
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.665174139897083e-06,
+ "loss": 0.4657,
+ "step": 7810
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.662732236002949e-06,
+ "loss": 0.4906,
+ "step": 7811
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.660290650619719e-06,
+ "loss": 0.481,
+ "step": 7812
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.657849383926693e-06,
+ "loss": 0.4664,
+ "step": 7813
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.655408436103149e-06,
+ "loss": 0.4844,
+ "step": 7814
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.652967807328334e-06,
+ "loss": 0.4665,
+ "step": 7815
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6505274977814875e-06,
+ "loss": 0.4795,
+ "step": 7816
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.648087507641806e-06,
+ "loss": 0.4739,
+ "step": 7817
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6456478370884815e-06,
+ "loss": 0.508,
+ "step": 7818
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.643208486300669e-06,
+ "loss": 0.4686,
+ "step": 7819
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.640769455457502e-06,
+ "loss": 0.4812,
+ "step": 7820
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6383307447380965e-06,
+ "loss": 0.4453,
+ "step": 7821
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.635892354321539e-06,
+ "loss": 0.4728,
+ "step": 7822
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.633454284386893e-06,
+ "loss": 0.4947,
+ "step": 7823
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.631016535113204e-06,
+ "loss": 0.4628,
+ "step": 7824
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.628579106679491e-06,
+ "loss": 0.4684,
+ "step": 7825
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.62614199926474e-06,
+ "loss": 0.4589,
+ "step": 7826
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.623705213047933e-06,
+ "loss": 0.483,
+ "step": 7827
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.621268748208013e-06,
+ "loss": 0.4802,
+ "step": 7828
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.618832604923904e-06,
+ "loss": 0.4595,
+ "step": 7829
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.616396783374501e-06,
+ "loss": 0.4818,
+ "step": 7830
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.613961283738692e-06,
+ "loss": 0.4592,
+ "step": 7831
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.61152610619532e-06,
+ "loss": 0.4717,
+ "step": 7832
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.60909125092322e-06,
+ "loss": 0.4754,
+ "step": 7833
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.606656718101193e-06,
+ "loss": 0.4837,
+ "step": 7834
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.604222507908021e-06,
+ "loss": 0.4693,
+ "step": 7835
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.60178862052247e-06,
+ "loss": 0.4601,
+ "step": 7836
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.599355056123263e-06,
+ "loss": 0.5122,
+ "step": 7837
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.596921814889122e-06,
+ "loss": 0.4721,
+ "step": 7838
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.594488896998729e-06,
+ "loss": 0.481,
+ "step": 7839
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.592056302630748e-06,
+ "loss": 0.4778,
+ "step": 7840
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.589624031963816e-06,
+ "loss": 0.4752,
+ "step": 7841
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.5871920851765535e-06,
+ "loss": 0.4595,
+ "step": 7842
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.584760462447548e-06,
+ "loss": 0.4692,
+ "step": 7843
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.582329163955367e-06,
+ "loss": 0.47,
+ "step": 7844
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.579898189878561e-06,
+ "loss": 0.4761,
+ "step": 7845
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.577467540395645e-06,
+ "loss": 0.473,
+ "step": 7846
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.575037215685119e-06,
+ "loss": 0.4554,
+ "step": 7847
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.572607215925458e-06,
+ "loss": 0.4822,
+ "step": 7848
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.570177541295107e-06,
+ "loss": 0.4727,
+ "step": 7849
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.567748191972493e-06,
+ "loss": 0.4875,
+ "step": 7850
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.565319168136012e-06,
+ "loss": 0.4617,
+ "step": 7851
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.56289046996405e-06,
+ "loss": 0.4695,
+ "step": 7852
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.5604620976349575e-06,
+ "loss": 0.4883,
+ "step": 7853
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.558034051327061e-06,
+ "loss": 0.4778,
+ "step": 7854
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.55560633121867e-06,
+ "loss": 0.4758,
+ "step": 7855
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.553178937488061e-06,
+ "loss": 0.4683,
+ "step": 7856
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.550751870313494e-06,
+ "loss": 0.4598,
+ "step": 7857
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.548325129873209e-06,
+ "loss": 0.5035,
+ "step": 7858
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.545898716345408e-06,
+ "loss": 0.4741,
+ "step": 7859
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.543472629908282e-06,
+ "loss": 0.4689,
+ "step": 7860
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.541046870739987e-06,
+ "loss": 0.4767,
+ "step": 7861
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.538621439018666e-06,
+ "loss": 0.4579,
+ "step": 7862
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.53619633492243e-06,
+ "loss": 0.4773,
+ "step": 7863
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.533771558629365e-06,
+ "loss": 0.4711,
+ "step": 7864
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.531347110317544e-06,
+ "loss": 0.482,
+ "step": 7865
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.528922990165004e-06,
+ "loss": 0.443,
+ "step": 7866
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.52649919834976e-06,
+ "loss": 0.4557,
+ "step": 7867
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.524075735049812e-06,
+ "loss": 0.4646,
+ "step": 7868
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.521652600443124e-06,
+ "loss": 0.4632,
+ "step": 7869
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.519229794707643e-06,
+ "loss": 0.4557,
+ "step": 7870
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.516807318021286e-06,
+ "loss": 0.475,
+ "step": 7871
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.514385170561956e-06,
+ "loss": 0.4735,
+ "step": 7872
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.511963352507521e-06,
+ "loss": 0.4566,
+ "step": 7873
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.50954186403583e-06,
+ "loss": 0.4755,
+ "step": 7874
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.507120705324709e-06,
+ "loss": 0.4943,
+ "step": 7875
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.504699876551951e-06,
+ "loss": 0.4656,
+ "step": 7876
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.502279377895341e-06,
+ "loss": 0.4863,
+ "step": 7877
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.499859209532622e-06,
+ "loss": 0.4729,
+ "step": 7878
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.497439371641528e-06,
+ "loss": 0.4802,
+ "step": 7879
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.495019864399761e-06,
+ "loss": 0.4667,
+ "step": 7880
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.492600687984997e-06,
+ "loss": 0.4724,
+ "step": 7881
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.490181842574891e-06,
+ "loss": 0.4769,
+ "step": 7882
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.487763328347071e-06,
+ "loss": 0.4641,
+ "step": 7883
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.485345145479147e-06,
+ "loss": 0.485,
+ "step": 7884
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.482927294148691e-06,
+ "loss": 0.4727,
+ "step": 7885
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.480509774533271e-06,
+ "loss": 0.4835,
+ "step": 7886
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.478092586810413e-06,
+ "loss": 0.4731,
+ "step": 7887
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.47567573115763e-06,
+ "loss": 0.4807,
+ "step": 7888
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.473259207752404e-06,
+ "loss": 0.4883,
+ "step": 7889
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.470843016772194e-06,
+ "loss": 0.4636,
+ "step": 7890
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.468427158394434e-06,
+ "loss": 0.4616,
+ "step": 7891
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.466011632796531e-06,
+ "loss": 0.4808,
+ "step": 7892
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.463596440155878e-06,
+ "loss": 0.4907,
+ "step": 7893
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.461181580649837e-06,
+ "loss": 0.4812,
+ "step": 7894
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4587670544557404e-06,
+ "loss": 0.4711,
+ "step": 7895
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.456352861750904e-06,
+ "loss": 0.4735,
+ "step": 7896
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.453939002712611e-06,
+ "loss": 0.4667,
+ "step": 7897
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.451525477518133e-06,
+ "loss": 0.4629,
+ "step": 7898
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4491122863447e-06,
+ "loss": 0.4739,
+ "step": 7899
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.446699429369538e-06,
+ "loss": 0.4901,
+ "step": 7900
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.444286906769831e-06,
+ "loss": 0.4603,
+ "step": 7901
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.441874718722744e-06,
+ "loss": 0.474,
+ "step": 7902
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.439462865405419e-06,
+ "loss": 0.4659,
+ "step": 7903
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.437051346994973e-06,
+ "loss": 0.4519,
+ "step": 7904
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.434640163668494e-06,
+ "loss": 0.4696,
+ "step": 7905
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.432229315603054e-06,
+ "loss": 0.5035,
+ "step": 7906
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.429818802975697e-06,
+ "loss": 0.4653,
+ "step": 7907
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.427408625963434e-06,
+ "loss": 0.473,
+ "step": 7908
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.424998784743266e-06,
+ "loss": 0.5055,
+ "step": 7909
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4225892794921585e-06,
+ "loss": 0.4932,
+ "step": 7910
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.420180110387056e-06,
+ "loss": 0.4689,
+ "step": 7911
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.417771277604873e-06,
+ "loss": 0.4671,
+ "step": 7912
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4153627813225114e-06,
+ "loss": 0.4679,
+ "step": 7913
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.412954621716839e-06,
+ "loss": 0.4852,
+ "step": 7914
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.410546798964701e-06,
+ "loss": 0.4746,
+ "step": 7915
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.408139313242916e-06,
+ "loss": 0.4582,
+ "step": 7916
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.405732164728276e-06,
+ "loss": 0.4603,
+ "step": 7917
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4033253535975635e-06,
+ "loss": 0.4852,
+ "step": 7918
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.400918880027513e-06,
+ "loss": 0.4561,
+ "step": 7919
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.398512744194854e-06,
+ "loss": 0.4665,
+ "step": 7920
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3961069462762804e-06,
+ "loss": 0.4571,
+ "step": 7921
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3937014864484635e-06,
+ "loss": 0.4624,
+ "step": 7922
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.39129636488805e-06,
+ "loss": 0.4613,
+ "step": 7923
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.388891581771664e-06,
+ "loss": 0.4828,
+ "step": 7924
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3864871372759e-06,
+ "loss": 0.4632,
+ "step": 7925
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.384083031577327e-06,
+ "loss": 0.4565,
+ "step": 7926
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.381679264852503e-06,
+ "loss": 0.4787,
+ "step": 7927
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.379275837277944e-06,
+ "loss": 0.4624,
+ "step": 7928
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3768727490301445e-06,
+ "loss": 0.4692,
+ "step": 7929
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.374470000285584e-06,
+ "loss": 0.454,
+ "step": 7930
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3720675912207085e-06,
+ "loss": 0.4773,
+ "step": 7931
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.369665522011938e-06,
+ "loss": 0.4697,
+ "step": 7932
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.367263792835673e-06,
+ "loss": 0.4758,
+ "step": 7933
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3648624038682886e-06,
+ "loss": 0.4822,
+ "step": 7934
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.362461355286129e-06,
+ "loss": 0.4614,
+ "step": 7935
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.360060647265519e-06,
+ "loss": 0.4877,
+ "step": 7936
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.357660279982757e-06,
+ "loss": 0.4527,
+ "step": 7937
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.35526025361411e-06,
+ "loss": 0.4733,
+ "step": 7938
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.352860568335835e-06,
+ "loss": 0.4525,
+ "step": 7939
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3504612243241474e-06,
+ "loss": 0.4608,
+ "step": 7940
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3480622217552524e-06,
+ "loss": 0.4853,
+ "step": 7941
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3456635608053186e-06,
+ "loss": 0.4678,
+ "step": 7942
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.343265241650495e-06,
+ "loss": 0.4678,
+ "step": 7943
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.340867264466902e-06,
+ "loss": 0.471,
+ "step": 7944
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.338469629430638e-06,
+ "loss": 0.4485,
+ "step": 7945
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.336072336717773e-06,
+ "loss": 0.4902,
+ "step": 7946
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.333675386504361e-06,
+ "loss": 0.47,
+ "step": 7947
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.33127877896642e-06,
+ "loss": 0.4581,
+ "step": 7948
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.328882514279942e-06,
+ "loss": 0.4655,
+ "step": 7949
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3264865926209076e-06,
+ "loss": 0.4873,
+ "step": 7950
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.324091014165259e-06,
+ "loss": 0.4545,
+ "step": 7951
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3216957790889176e-06,
+ "loss": 0.4819,
+ "step": 7952
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.319300887567777e-06,
+ "loss": 0.4598,
+ "step": 7953
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.316906339777714e-06,
+ "loss": 0.4577,
+ "step": 7954
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.31451213589457e-06,
+ "loss": 0.4706,
+ "step": 7955
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.312118276094167e-06,
+ "loss": 0.4746,
+ "step": 7956
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3097247605522996e-06,
+ "loss": 0.4613,
+ "step": 7957
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.307331589444737e-06,
+ "loss": 0.469,
+ "step": 7958
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.304938762947221e-06,
+ "loss": 0.4634,
+ "step": 7959
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3025462812354744e-06,
+ "loss": 0.4984,
+ "step": 7960
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.300154144485194e-06,
+ "loss": 0.4598,
+ "step": 7961
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.297762352872044e-06,
+ "loss": 0.448,
+ "step": 7962
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2953709065716704e-06,
+ "loss": 0.4654,
+ "step": 7963
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.292979805759689e-06,
+ "loss": 0.4789,
+ "step": 7964
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.290589050611692e-06,
+ "loss": 0.4614,
+ "step": 7965
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.288198641303248e-06,
+ "loss": 0.4794,
+ "step": 7966
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.285808578009894e-06,
+ "loss": 0.454,
+ "step": 7967
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.283418860907155e-06,
+ "loss": 0.4548,
+ "step": 7968
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.281029490170515e-06,
+ "loss": 0.469,
+ "step": 7969
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2786404659754375e-06,
+ "loss": 0.4638,
+ "step": 7970
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.276251788497373e-06,
+ "loss": 0.4919,
+ "step": 7971
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.273863457911728e-06,
+ "loss": 0.4731,
+ "step": 7972
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.271475474393889e-06,
+ "loss": 0.4618,
+ "step": 7973
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.269087838119229e-06,
+ "loss": 0.4624,
+ "step": 7974
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.266700549263079e-06,
+ "loss": 0.4752,
+ "step": 7975
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.264313608000755e-06,
+ "loss": 0.4623,
+ "step": 7976
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.261927014507542e-06,
+ "loss": 0.4629,
+ "step": 7977
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2595407689587006e-06,
+ "loss": 0.457,
+ "step": 7978
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2571548715294664e-06,
+ "loss": 0.4797,
+ "step": 7979
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.254769322395053e-06,
+ "loss": 0.474,
+ "step": 7980
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2523841217306415e-06,
+ "loss": 0.456,
+ "step": 7981
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.249999269711396e-06,
+ "loss": 0.454,
+ "step": 7982
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.247614766512449e-06,
+ "loss": 0.4753,
+ "step": 7983
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.245230612308906e-06,
+ "loss": 0.4781,
+ "step": 7984
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.24284680727585e-06,
+ "loss": 0.4845,
+ "step": 7985
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.240463351588339e-06,
+ "loss": 0.4856,
+ "step": 7986
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.238080245421397e-06,
+ "loss": 0.4736,
+ "step": 7987
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.235697488950041e-06,
+ "loss": 0.4765,
+ "step": 7988
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.233315082349245e-06,
+ "loss": 0.4583,
+ "step": 7989
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2309330257939596e-06,
+ "loss": 0.467,
+ "step": 7990
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.22855131945912e-06,
+ "loss": 0.4896,
+ "step": 7991
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.226169963519625e-06,
+ "loss": 0.4487,
+ "step": 7992
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.223788958150353e-06,
+ "loss": 0.4804,
+ "step": 7993
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.221408303526151e-06,
+ "loss": 0.4854,
+ "step": 7994
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.219027999821851e-06,
+ "loss": 0.4575,
+ "step": 7995
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2166480472122475e-06,
+ "loss": 0.4674,
+ "step": 7996
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.214268445872117e-06,
+ "loss": 0.4684,
+ "step": 7997
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.211889195976207e-06,
+ "loss": 0.4653,
+ "step": 7998
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.209510297699239e-06,
+ "loss": 0.4578,
+ "step": 7999
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2071317512159055e-06,
+ "loss": 0.4672,
+ "step": 8000
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.204753556700881e-06,
+ "loss": 0.4591,
+ "step": 8001
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.202375714328814e-06,
+ "loss": 0.4749,
+ "step": 8002
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.199998224274321e-06,
+ "loss": 0.483,
+ "step": 8003
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.197621086711993e-06,
+ "loss": 0.4896,
+ "step": 8004
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.195244301816398e-06,
+ "loss": 0.4701,
+ "step": 8005
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.192867869762076e-06,
+ "loss": 0.4645,
+ "step": 8006
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1904917907235395e-06,
+ "loss": 0.4561,
+ "step": 8007
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.188116064875286e-06,
+ "loss": 0.4791,
+ "step": 8008
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.185740692391774e-06,
+ "loss": 0.4797,
+ "step": 8009
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.183365673447442e-06,
+ "loss": 0.4743,
+ "step": 8010
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.180991008216698e-06,
+ "loss": 0.4652,
+ "step": 8011
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.178616696873935e-06,
+ "loss": 0.4932,
+ "step": 8012
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1762427395935065e-06,
+ "loss": 0.4888,
+ "step": 8013
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.173869136549744e-06,
+ "loss": 0.48,
+ "step": 8014
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.171495887916962e-06,
+ "loss": 0.465,
+ "step": 8015
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1691229938694396e-06,
+ "loss": 0.4495,
+ "step": 8016
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.166750454581432e-06,
+ "loss": 0.4761,
+ "step": 8017
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.164378270227167e-06,
+ "loss": 0.4633,
+ "step": 8018
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.162006440980849e-06,
+ "loss": 0.4559,
+ "step": 8019
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.159634967016653e-06,
+ "loss": 0.4589,
+ "step": 8020
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.157263848508735e-06,
+ "loss": 0.4933,
+ "step": 8021
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.154893085631213e-06,
+ "loss": 0.4685,
+ "step": 8022
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.152522678558195e-06,
+ "loss": 0.4722,
+ "step": 8023
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.150152627463749e-06,
+ "loss": 0.473,
+ "step": 8024
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1477829325219235e-06,
+ "loss": 0.4841,
+ "step": 8025
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1454135939067365e-06,
+ "loss": 0.4842,
+ "step": 8026
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.143044611792183e-06,
+ "loss": 0.4715,
+ "step": 8027
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.140675986352228e-06,
+ "loss": 0.4933,
+ "step": 8028
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.13830771776082e-06,
+ "loss": 0.4563,
+ "step": 8029
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.135939806191874e-06,
+ "loss": 0.4535,
+ "step": 8030
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.133572251819272e-06,
+ "loss": 0.4683,
+ "step": 8031
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.131205054816888e-06,
+ "loss": 0.4829,
+ "step": 8032
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.128838215358553e-06,
+ "loss": 0.4593,
+ "step": 8033
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.126471733618079e-06,
+ "loss": 0.4618,
+ "step": 8034
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.124105609769246e-06,
+ "loss": 0.4798,
+ "step": 8035
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.12173984398582e-06,
+ "loss": 0.4731,
+ "step": 8036
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.119374436441531e-06,
+ "loss": 0.4838,
+ "step": 8037
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.117009387310083e-06,
+ "loss": 0.4896,
+ "step": 8038
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.114644696765157e-06,
+ "loss": 0.4656,
+ "step": 8039
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.112280364980402e-06,
+ "loss": 0.4628,
+ "step": 8040
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.109916392129446e-06,
+ "loss": 0.469,
+ "step": 8041
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1075527783858934e-06,
+ "loss": 0.4615,
+ "step": 8042
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.105189523923312e-06,
+ "loss": 0.4725,
+ "step": 8043
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1028266289152565e-06,
+ "loss": 0.4601,
+ "step": 8044
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.100464093535244e-06,
+ "loss": 0.4656,
+ "step": 8045
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.098101917956771e-06,
+ "loss": 0.4931,
+ "step": 8046
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0957401023533036e-06,
+ "loss": 0.4619,
+ "step": 8047
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.093378646898282e-06,
+ "loss": 0.4562,
+ "step": 8048
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.091017551765127e-06,
+ "loss": 0.4753,
+ "step": 8049
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0886568171272265e-06,
+ "loss": 0.475,
+ "step": 8050
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.08629644315794e-06,
+ "loss": 0.453,
+ "step": 8051
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0839364300306016e-06,
+ "loss": 0.4629,
+ "step": 8052
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.081576777918529e-06,
+ "loss": 0.4749,
+ "step": 8053
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.079217486994999e-06,
+ "loss": 0.4747,
+ "step": 8054
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0768585574332675e-06,
+ "loss": 0.4711,
+ "step": 8055
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.074499989406569e-06,
+ "loss": 0.4655,
+ "step": 8056
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.072141783088107e-06,
+ "loss": 0.4468,
+ "step": 8057
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.069783938651054e-06,
+ "loss": 0.45,
+ "step": 8058
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.067426456268563e-06,
+ "loss": 0.4939,
+ "step": 8059
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.065069336113756e-06,
+ "loss": 0.4619,
+ "step": 8060
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.062712578359728e-06,
+ "loss": 0.4636,
+ "step": 8061
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.060356183179556e-06,
+ "loss": 0.4795,
+ "step": 8062
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.058000150746276e-06,
+ "loss": 0.471,
+ "step": 8063
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.055644481232914e-06,
+ "loss": 0.4677,
+ "step": 8064
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0532891748124565e-06,
+ "loss": 0.4624,
+ "step": 8065
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.050934231657867e-06,
+ "loss": 0.4759,
+ "step": 8066
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.048579651942083e-06,
+ "loss": 0.4778,
+ "step": 8067
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.046225435838015e-06,
+ "loss": 0.4734,
+ "step": 8068
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.043871583518542e-06,
+ "loss": 0.4746,
+ "step": 8069
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.04151809515653e-06,
+ "loss": 0.4566,
+ "step": 8070
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.039164970924805e-06,
+ "loss": 0.4637,
+ "step": 8071
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.0368122109961716e-06,
+ "loss": 0.453,
+ "step": 8072
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.034459815543401e-06,
+ "loss": 0.4528,
+ "step": 8073
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.032107784739253e-06,
+ "loss": 0.4723,
+ "step": 8074
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.029756118756446e-06,
+ "loss": 0.4791,
+ "step": 8075
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.027404817767672e-06,
+ "loss": 0.4692,
+ "step": 8076
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.025053881945612e-06,
+ "loss": 0.4452,
+ "step": 8077
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.0227033114629e-06,
+ "loss": 0.4711,
+ "step": 8078
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.020353106492156e-06,
+ "loss": 0.4609,
+ "step": 8079
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.018003267205969e-06,
+ "loss": 0.4732,
+ "step": 8080
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.015653793776898e-06,
+ "loss": 0.4574,
+ "step": 8081
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.013304686377478e-06,
+ "loss": 0.4587,
+ "step": 8082
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.010955945180225e-06,
+ "loss": 0.4708,
+ "step": 8083
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.008607570357612e-06,
+ "loss": 0.4685,
+ "step": 8084
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.006259562082102e-06,
+ "loss": 0.4661,
+ "step": 8085
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.003911920526119e-06,
+ "loss": 0.4538,
+ "step": 8086
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.0015646458620645e-06,
+ "loss": 0.4543,
+ "step": 8087
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.999217738262313e-06,
+ "loss": 0.4777,
+ "step": 8088
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.996871197899207e-06,
+ "loss": 0.4714,
+ "step": 8089
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.994525024945075e-06,
+ "loss": 0.4666,
+ "step": 8090
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.992179219572204e-06,
+ "loss": 0.4673,
+ "step": 8091
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.989833781952864e-06,
+ "loss": 0.4602,
+ "step": 8092
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.987488712259288e-06,
+ "loss": 0.4727,
+ "step": 8093
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.985144010663695e-06,
+ "loss": 0.4598,
+ "step": 8094
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.982799677338268e-06,
+ "loss": 0.4775,
+ "step": 8095
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.980455712455161e-06,
+ "loss": 0.4617,
+ "step": 8096
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.978112116186512e-06,
+ "loss": 0.4769,
+ "step": 8097
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.975768888704422e-06,
+ "loss": 0.4757,
+ "step": 8098
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.973426030180968e-06,
+ "loss": 0.4748,
+ "step": 8099
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.971083540788199e-06,
+ "loss": 0.4697,
+ "step": 8100
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.968741420698137e-06,
+ "loss": 0.4743,
+ "step": 8101
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.966399670082779e-06,
+ "loss": 0.4653,
+ "step": 8102
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.964058289114089e-06,
+ "loss": 0.4759,
+ "step": 8103
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.961717277964012e-06,
+ "loss": 0.5013,
+ "step": 8104
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.959376636804467e-06,
+ "loss": 0.4803,
+ "step": 8105
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9570363658073366e-06,
+ "loss": 0.4712,
+ "step": 8106
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.954696465144479e-06,
+ "loss": 0.4678,
+ "step": 8107
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.952356934987728e-06,
+ "loss": 0.4561,
+ "step": 8108
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.95001777550889e-06,
+ "loss": 0.4624,
+ "step": 8109
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.947678986879737e-06,
+ "loss": 0.4786,
+ "step": 8110
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.945340569272029e-06,
+ "loss": 0.4465,
+ "step": 8111
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.943002522857487e-06,
+ "loss": 0.477,
+ "step": 8112
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.940664847807804e-06,
+ "loss": 0.4772,
+ "step": 8113
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9383275442946495e-06,
+ "loss": 0.4757,
+ "step": 8114
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.935990612489671e-06,
+ "loss": 0.4488,
+ "step": 8115
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.933654052564477e-06,
+ "loss": 0.4872,
+ "step": 8116
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.931317864690655e-06,
+ "loss": 0.4675,
+ "step": 8117
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.92898204903977e-06,
+ "loss": 0.4818,
+ "step": 8118
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.92664660578335e-06,
+ "loss": 0.4752,
+ "step": 8119
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.924311535092904e-06,
+ "loss": 0.4517,
+ "step": 8120
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9219768371399055e-06,
+ "loss": 0.4548,
+ "step": 8121
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.919642512095808e-06,
+ "loss": 0.454,
+ "step": 8122
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.917308560132029e-06,
+ "loss": 0.4802,
+ "step": 8123
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.914974981419974e-06,
+ "loss": 0.4431,
+ "step": 8124
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9126417761310005e-06,
+ "loss": 0.4663,
+ "step": 8125
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9103089444364605e-06,
+ "loss": 0.4542,
+ "step": 8126
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9079764865076615e-06,
+ "loss": 0.4589,
+ "step": 8127
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.90564440251589e-06,
+ "loss": 0.4767,
+ "step": 8128
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.903312692632405e-06,
+ "loss": 0.463,
+ "step": 8129
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9009813570284326e-06,
+ "loss": 0.4729,
+ "step": 8130
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.898650395875185e-06,
+ "loss": 0.4562,
+ "step": 8131
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.896319809343834e-06,
+ "loss": 0.4701,
+ "step": 8132
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.893989597605528e-06,
+ "loss": 0.4578,
+ "step": 8133
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8916597608313855e-06,
+ "loss": 0.4918,
+ "step": 8134
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8893302991925075e-06,
+ "loss": 0.4608,
+ "step": 8135
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.887001212859954e-06,
+ "loss": 0.4662,
+ "step": 8136
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.884672502004762e-06,
+ "loss": 0.4747,
+ "step": 8137
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8823441667979475e-06,
+ "loss": 0.4636,
+ "step": 8138
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.880016207410493e-06,
+ "loss": 0.4709,
+ "step": 8139
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.877688624013353e-06,
+ "loss": 0.4848,
+ "step": 8140
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.875361416777453e-06,
+ "loss": 0.4728,
+ "step": 8141
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.873034585873697e-06,
+ "loss": 0.494,
+ "step": 8142
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.870708131472957e-06,
+ "loss": 0.4538,
+ "step": 8143
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.868382053746072e-06,
+ "loss": 0.4667,
+ "step": 8144
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.866056352863866e-06,
+ "loss": 0.4854,
+ "step": 8145
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8637310289971314e-06,
+ "loss": 0.4811,
+ "step": 8146
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.861406082316626e-06,
+ "loss": 0.471,
+ "step": 8147
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8590815129930865e-06,
+ "loss": 0.4748,
+ "step": 8148
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8567573211972175e-06,
+ "loss": 0.4685,
+ "step": 8149
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.854433507099698e-06,
+ "loss": 0.4846,
+ "step": 8150
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.852110070871175e-06,
+ "loss": 0.4754,
+ "step": 8151
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.849787012682282e-06,
+ "loss": 0.464,
+ "step": 8152
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8474643327036095e-06,
+ "loss": 0.4705,
+ "step": 8153
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.845142031105724e-06,
+ "loss": 0.4814,
+ "step": 8154
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8428201080591645e-06,
+ "loss": 0.4669,
+ "step": 8155
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.840498563734449e-06,
+ "loss": 0.4703,
+ "step": 8156
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.838177398302056e-06,
+ "loss": 0.4661,
+ "step": 8157
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8358566119324494e-06,
+ "loss": 0.4684,
+ "step": 8158
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.833536204796052e-06,
+ "loss": 0.4745,
+ "step": 8159
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.831216177063268e-06,
+ "loss": 0.4634,
+ "step": 8160
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.82889652890447e-06,
+ "loss": 0.4606,
+ "step": 8161
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8265772604900015e-06,
+ "loss": 0.4659,
+ "step": 8162
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.824258371990181e-06,
+ "loss": 0.4668,
+ "step": 8163
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.821939863575295e-06,
+ "loss": 0.4562,
+ "step": 8164
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.819621735415613e-06,
+ "loss": 0.4466,
+ "step": 8165
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.817303987681359e-06,
+ "loss": 0.4877,
+ "step": 8166
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.814986620542747e-06,
+ "loss": 0.4766,
+ "step": 8167
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8126696341699515e-06,
+ "loss": 0.4601,
+ "step": 8168
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.810353028733123e-06,
+ "loss": 0.4765,
+ "step": 8169
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.808036804402383e-06,
+ "loss": 0.4913,
+ "step": 8170
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.80572096134782e-06,
+ "loss": 0.4553,
+ "step": 8171
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.803405499739511e-06,
+ "loss": 0.4824,
+ "step": 8172
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.801090419747486e-06,
+ "loss": 0.466,
+ "step": 8173
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.798775721541757e-06,
+ "loss": 0.4502,
+ "step": 8174
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.796461405292302e-06,
+ "loss": 0.453,
+ "step": 8175
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.794147471169082e-06,
+ "loss": 0.4768,
+ "step": 8176
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.7918339193420195e-06,
+ "loss": 0.4754,
+ "step": 8177
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.789520749981007e-06,
+ "loss": 0.4688,
+ "step": 8178
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.787207963255922e-06,
+ "loss": 0.4925,
+ "step": 8179
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.7848955593366035e-06,
+ "loss": 0.4751,
+ "step": 8180
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.782583538392863e-06,
+ "loss": 0.4647,
+ "step": 8181
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.7802719005944875e-06,
+ "loss": 0.4637,
+ "step": 8182
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.777960646111233e-06,
+ "loss": 0.4859,
+ "step": 8183
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.775649775112828e-06,
+ "loss": 0.4761,
+ "step": 8184
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.77333928776897e-06,
+ "loss": 0.4867,
+ "step": 8185
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.771029184249339e-06,
+ "loss": 0.4683,
+ "step": 8186
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.768719464723572e-06,
+ "loss": 0.4825,
+ "step": 8187
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.766410129361294e-06,
+ "loss": 0.4661,
+ "step": 8188
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7641011783320866e-06,
+ "loss": 0.4592,
+ "step": 8189
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7617926118055125e-06,
+ "loss": 0.4794,
+ "step": 8190
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7594844299511e-06,
+ "loss": 0.4742,
+ "step": 8191
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.757176632938351e-06,
+ "loss": 0.4719,
+ "step": 8192
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.754869220936748e-06,
+ "loss": 0.4626,
+ "step": 8193
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.752562194115732e-06,
+ "loss": 0.4645,
+ "step": 8194
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.750255552644722e-06,
+ "loss": 0.4626,
+ "step": 8195
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7479492966931076e-06,
+ "loss": 0.4671,
+ "step": 8196
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.745643426430254e-06,
+ "loss": 0.4699,
+ "step": 8197
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.743337942025489e-06,
+ "loss": 0.4682,
+ "step": 8198
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.741032843648126e-06,
+ "loss": 0.4568,
+ "step": 8199
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.738728131467436e-06,
+ "loss": 0.4775,
+ "step": 8200
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.73642380565267e-06,
+ "loss": 0.4795,
+ "step": 8201
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.734119866373046e-06,
+ "loss": 0.4591,
+ "step": 8202
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.731816313797757e-06,
+ "loss": 0.4689,
+ "step": 8203
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7295131480959655e-06,
+ "loss": 0.4534,
+ "step": 8204
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.727210369436803e-06,
+ "loss": 0.4792,
+ "step": 8205
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.724907977989384e-06,
+ "loss": 0.4638,
+ "step": 8206
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7226059739227796e-06,
+ "loss": 0.4603,
+ "step": 8207
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.720304357406044e-06,
+ "loss": 0.4847,
+ "step": 8208
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7180031286081975e-06,
+ "loss": 0.464,
+ "step": 8209
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.715702287698232e-06,
+ "loss": 0.4724,
+ "step": 8210
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.71340183484511e-06,
+ "loss": 0.4716,
+ "step": 8211
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.711101770217766e-06,
+ "loss": 0.471,
+ "step": 8212
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.708802093985113e-06,
+ "loss": 0.473,
+ "step": 8213
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.706502806316028e-06,
+ "loss": 0.4778,
+ "step": 8214
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.704203907379358e-06,
+ "loss": 0.4548,
+ "step": 8215
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7019053973439265e-06,
+ "loss": 0.484,
+ "step": 8216
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6996072763785225e-06,
+ "loss": 0.473,
+ "step": 8217
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.697309544651918e-06,
+ "loss": 0.4642,
+ "step": 8218
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6950122023328415e-06,
+ "loss": 0.4716,
+ "step": 8219
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.692715249590007e-06,
+ "loss": 0.4708,
+ "step": 8220
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.69041868659209e-06,
+ "loss": 0.4752,
+ "step": 8221
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.68812251350774e-06,
+ "loss": 0.4551,
+ "step": 8222
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.685826730505581e-06,
+ "loss": 0.4794,
+ "step": 8223
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.683531337754201e-06,
+ "loss": 0.4568,
+ "step": 8224
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6812363354221675e-06,
+ "loss": 0.4637,
+ "step": 8225
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.678941723678012e-06,
+ "loss": 0.4712,
+ "step": 8226
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.676647502690248e-06,
+ "loss": 0.4848,
+ "step": 8227
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.674353672627345e-06,
+ "loss": 0.4672,
+ "step": 8228
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.672060233657762e-06,
+ "loss": 0.4781,
+ "step": 8229
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.669767185949915e-06,
+ "loss": 0.4555,
+ "step": 8230
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.667474529672196e-06,
+ "loss": 0.4874,
+ "step": 8231
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.665182264992966e-06,
+ "loss": 0.4607,
+ "step": 8232
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.66289039208056e-06,
+ "loss": 0.4571,
+ "step": 8233
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.660598911103288e-06,
+ "loss": 0.4561,
+ "step": 8234
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.658307822229423e-06,
+ "loss": 0.4632,
+ "step": 8235
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.656017125627214e-06,
+ "loss": 0.4754,
+ "step": 8236
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.653726821464876e-06,
+ "loss": 0.483,
+ "step": 8237
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.651436909910607e-06,
+ "loss": 0.4668,
+ "step": 8238
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.649147391132562e-06,
+ "loss": 0.4958,
+ "step": 8239
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.646858265298881e-06,
+ "loss": 0.4723,
+ "step": 8240
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.644569532577662e-06,
+ "loss": 0.4746,
+ "step": 8241
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6422811931369825e-06,
+ "loss": 0.4718,
+ "step": 8242
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.639993247144889e-06,
+ "loss": 0.4667,
+ "step": 8243
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.637705694769396e-06,
+ "loss": 0.4615,
+ "step": 8244
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.635418536178492e-06,
+ "loss": 0.4802,
+ "step": 8245
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.633131771540136e-06,
+ "loss": 0.471,
+ "step": 8246
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.630845401022264e-06,
+ "loss": 0.4659,
+ "step": 8247
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.628559424792769e-06,
+ "loss": 0.48,
+ "step": 8248
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.626273843019532e-06,
+ "loss": 0.4433,
+ "step": 8249
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.623988655870394e-06,
+ "loss": 0.4805,
+ "step": 8250
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.621703863513168e-06,
+ "loss": 0.4693,
+ "step": 8251
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.61941946611564e-06,
+ "loss": 0.4697,
+ "step": 8252
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.617135463845563e-06,
+ "loss": 0.4931,
+ "step": 8253
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.614851856870673e-06,
+ "loss": 0.4724,
+ "step": 8254
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.612568645358664e-06,
+ "loss": 0.4771,
+ "step": 8255
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6102858294772055e-06,
+ "loss": 0.4438,
+ "step": 8256
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.608003409393939e-06,
+ "loss": 0.49,
+ "step": 8257
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.60572138527647e-06,
+ "loss": 0.4572,
+ "step": 8258
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.60343975729239e-06,
+ "loss": 0.4596,
+ "step": 8259
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.601158525609245e-06,
+ "loss": 0.4777,
+ "step": 8260
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.598877690394565e-06,
+ "loss": 0.4661,
+ "step": 8261
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.596597251815844e-06,
+ "loss": 0.458,
+ "step": 8262
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5943172100405455e-06,
+ "loss": 0.4684,
+ "step": 8263
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.592037565236108e-06,
+ "loss": 0.4587,
+ "step": 8264
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.589758317569938e-06,
+ "loss": 0.4612,
+ "step": 8265
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5874794672094135e-06,
+ "loss": 0.475,
+ "step": 8266
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.585201014321882e-06,
+ "loss": 0.4665,
+ "step": 8267
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.582922959074668e-06,
+ "loss": 0.4585,
+ "step": 8268
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5806453016350584e-06,
+ "loss": 0.4705,
+ "step": 8269
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5783680421703205e-06,
+ "loss": 0.4901,
+ "step": 8270
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.576091180847684e-06,
+ "loss": 0.4554,
+ "step": 8271
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.57381471783435e-06,
+ "loss": 0.4782,
+ "step": 8272
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.571538653297491e-06,
+ "loss": 0.4807,
+ "step": 8273
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5692629874042585e-06,
+ "loss": 0.4598,
+ "step": 8274
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.566987720321764e-06,
+ "loss": 0.4618,
+ "step": 8275
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.564712852217094e-06,
+ "loss": 0.47,
+ "step": 8276
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.562438383257304e-06,
+ "loss": 0.4723,
+ "step": 8277
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5601643136094195e-06,
+ "loss": 0.4548,
+ "step": 8278
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.557890643440445e-06,
+ "loss": 0.4667,
+ "step": 8279
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5556173729173434e-06,
+ "loss": 0.4726,
+ "step": 8280
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.55334450220706e-06,
+ "loss": 0.4704,
+ "step": 8281
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.551072031476504e-06,
+ "loss": 0.4842,
+ "step": 8282
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.548799960892552e-06,
+ "loss": 0.4802,
+ "step": 8283
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.546528290622058e-06,
+ "loss": 0.4843,
+ "step": 8284
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.544257020831843e-06,
+ "loss": 0.4921,
+ "step": 8285
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.541986151688702e-06,
+ "loss": 0.4769,
+ "step": 8286
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.539715683359391e-06,
+ "loss": 0.45,
+ "step": 8287
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.537445616010655e-06,
+ "loss": 0.4646,
+ "step": 8288
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.535175949809188e-06,
+ "loss": 0.4756,
+ "step": 8289
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.532906684921672e-06,
+ "loss": 0.4601,
+ "step": 8290
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.53063782151475e-06,
+ "loss": 0.486,
+ "step": 8291
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5283693597550384e-06,
+ "loss": 0.4705,
+ "step": 8292
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.526101299809122e-06,
+ "loss": 0.4619,
+ "step": 8293
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.523833641843554e-06,
+ "loss": 0.4683,
+ "step": 8294
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.521566386024871e-06,
+ "loss": 0.4627,
+ "step": 8295
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.519299532519566e-06,
+ "loss": 0.483,
+ "step": 8296
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.517033081494109e-06,
+ "loss": 0.4766,
+ "step": 8297
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.514767033114935e-06,
+ "loss": 0.4708,
+ "step": 8298
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.512501387548453e-06,
+ "loss": 0.4741,
+ "step": 8299
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.510236144961047e-06,
+ "loss": 0.4742,
+ "step": 8300
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.507971305519062e-06,
+ "loss": 0.4632,
+ "step": 8301
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.505706869388825e-06,
+ "loss": 0.468,
+ "step": 8302
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.503442836736624e-06,
+ "loss": 0.4569,
+ "step": 8303
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5011792077287175e-06,
+ "loss": 0.4734,
+ "step": 8304
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.498915982531339e-06,
+ "loss": 0.4751,
+ "step": 8305
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.49665316131069e-06,
+ "loss": 0.4773,
+ "step": 8306
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.494390744232943e-06,
+ "loss": 0.4506,
+ "step": 8307
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.492128731464237e-06,
+ "loss": 0.4594,
+ "step": 8308
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.489867123170692e-06,
+ "loss": 0.4719,
+ "step": 8309
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.487605919518382e-06,
+ "loss": 0.4808,
+ "step": 8310
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.485345120673369e-06,
+ "loss": 0.4713,
+ "step": 8311
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4830847268016745e-06,
+ "loss": 0.4824,
+ "step": 8312
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.480824738069291e-06,
+ "loss": 0.4813,
+ "step": 8313
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.478565154642178e-06,
+ "loss": 0.477,
+ "step": 8314
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.476305976686279e-06,
+ "loss": 0.4704,
+ "step": 8315
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.474047204367494e-06,
+ "loss": 0.4748,
+ "step": 8316
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4717888378516986e-06,
+ "loss": 0.454,
+ "step": 8317
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.469530877304737e-06,
+ "loss": 0.4577,
+ "step": 8318
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.467273322892421e-06,
+ "loss": 0.4852,
+ "step": 8319
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.465016174780544e-06,
+ "loss": 0.4551,
+ "step": 8320
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.462759433134855e-06,
+ "loss": 0.4726,
+ "step": 8321
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4605030981210824e-06,
+ "loss": 0.5028,
+ "step": 8322
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4582471699049245e-06,
+ "loss": 0.4718,
+ "step": 8323
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.455991648652044e-06,
+ "loss": 0.479,
+ "step": 8324
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.453736534528077e-06,
+ "loss": 0.4514,
+ "step": 8325
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.45148182769863e-06,
+ "loss": 0.467,
+ "step": 8326
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.449227528329281e-06,
+ "loss": 0.489,
+ "step": 8327
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.446973636585571e-06,
+ "loss": 0.4569,
+ "step": 8328
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.444720152633023e-06,
+ "loss": 0.4732,
+ "step": 8329
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.442467076637121e-06,
+ "loss": 0.4608,
+ "step": 8330
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.440214408763318e-06,
+ "loss": 0.4619,
+ "step": 8331
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.437962149177047e-06,
+ "loss": 0.469,
+ "step": 8332
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.435710298043703e-06,
+ "loss": 0.4816,
+ "step": 8333
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.43345885552865e-06,
+ "loss": 0.4489,
+ "step": 8334
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.431207821797222e-06,
+ "loss": 0.4529,
+ "step": 8335
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.428957197014732e-06,
+ "loss": 0.4827,
+ "step": 8336
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.426706981346456e-06,
+ "loss": 0.4554,
+ "step": 8337
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.424457174957637e-06,
+ "loss": 0.4698,
+ "step": 8338
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.422207778013493e-06,
+ "loss": 0.4708,
+ "step": 8339
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.419958790679205e-06,
+ "loss": 0.4747,
+ "step": 8340
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4177102131199405e-06,
+ "loss": 0.4694,
+ "step": 8341
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.415462045500813e-06,
+ "loss": 0.4597,
+ "step": 8342
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.41321428798693e-06,
+ "loss": 0.4661,
+ "step": 8343
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.410966940743353e-06,
+ "loss": 0.4799,
+ "step": 8344
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.408720003935116e-06,
+ "loss": 0.4642,
+ "step": 8345
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.406473477727228e-06,
+ "loss": 0.4708,
+ "step": 8346
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.404227362284661e-06,
+ "loss": 0.4911,
+ "step": 8347
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.401981657772359e-06,
+ "loss": 0.4707,
+ "step": 8348
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.399736364355243e-06,
+ "loss": 0.4633,
+ "step": 8349
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.397491482198195e-06,
+ "loss": 0.4862,
+ "step": 8350
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.395247011466067e-06,
+ "loss": 0.461,
+ "step": 8351
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.393002952323691e-06,
+ "loss": 0.4619,
+ "step": 8352
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3907593049358555e-06,
+ "loss": 0.4857,
+ "step": 8353
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.388516069467327e-06,
+ "loss": 0.482,
+ "step": 8354
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.386273246082834e-06,
+ "loss": 0.4656,
+ "step": 8355
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.384030834947088e-06,
+ "loss": 0.4777,
+ "step": 8356
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.381788836224759e-06,
+ "loss": 0.4786,
+ "step": 8357
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.379547250080491e-06,
+ "loss": 0.4525,
+ "step": 8358
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.377306076678895e-06,
+ "loss": 0.4711,
+ "step": 8359
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.375065316184556e-06,
+ "loss": 0.4986,
+ "step": 8360
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.372824968762019e-06,
+ "loss": 0.4564,
+ "step": 8361
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.37058503457581e-06,
+ "loss": 0.4666,
+ "step": 8362
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.368345513790427e-06,
+ "loss": 0.4745,
+ "step": 8363
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.366106406570325e-06,
+ "loss": 0.5115,
+ "step": 8364
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.363867713079935e-06,
+ "loss": 0.4606,
+ "step": 8365
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.361629433483659e-06,
+ "loss": 0.4698,
+ "step": 8366
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3593915679458645e-06,
+ "loss": 0.4697,
+ "step": 8367
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3571541166308926e-06,
+ "loss": 0.4661,
+ "step": 8368
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.354917079703049e-06,
+ "loss": 0.4622,
+ "step": 8369
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.352680457326617e-06,
+ "loss": 0.4748,
+ "step": 8370
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.350444249665845e-06,
+ "loss": 0.4748,
+ "step": 8371
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.348208456884945e-06,
+ "loss": 0.4493,
+ "step": 8372
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.345973079148111e-06,
+ "loss": 0.486,
+ "step": 8373
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.343738116619499e-06,
+ "loss": 0.4661,
+ "step": 8374
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3415035694632326e-06,
+ "loss": 0.4423,
+ "step": 8375
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.339269437843405e-06,
+ "loss": 0.4572,
+ "step": 8376
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.337035721924089e-06,
+ "loss": 0.4763,
+ "step": 8377
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.334802421869316e-06,
+ "loss": 0.4874,
+ "step": 8378
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.332569537843089e-06,
+ "loss": 0.4534,
+ "step": 8379
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.330337070009382e-06,
+ "loss": 0.4533,
+ "step": 8380
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.328105018532136e-06,
+ "loss": 0.461,
+ "step": 8381
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.32587338357527e-06,
+ "loss": 0.4669,
+ "step": 8382
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.323642165302658e-06,
+ "loss": 0.4619,
+ "step": 8383
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.321411363878159e-06,
+ "loss": 0.4544,
+ "step": 8384
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.319180979465592e-06,
+ "loss": 0.4866,
+ "step": 8385
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.316951012228744e-06,
+ "loss": 0.4647,
+ "step": 8386
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.314721462331376e-06,
+ "loss": 0.4605,
+ "step": 8387
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.312492329937218e-06,
+ "loss": 0.4656,
+ "step": 8388
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.310263615209963e-06,
+ "loss": 0.4996,
+ "step": 8389
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.308035318313286e-06,
+ "loss": 0.4711,
+ "step": 8390
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.305807439410822e-06,
+ "loss": 0.4672,
+ "step": 8391
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.30357997866617e-06,
+ "loss": 0.4885,
+ "step": 8392
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.301352936242916e-06,
+ "loss": 0.4748,
+ "step": 8393
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.2991263123046005e-06,
+ "loss": 0.4615,
+ "step": 8394
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.296900107014735e-06,
+ "loss": 0.4693,
+ "step": 8395
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.294674320536803e-06,
+ "loss": 0.4776,
+ "step": 8396
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.292448953034261e-06,
+ "loss": 0.4694,
+ "step": 8397
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.290224004670529e-06,
+ "loss": 0.4633,
+ "step": 8398
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.287999475608997e-06,
+ "loss": 0.4731,
+ "step": 8399
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.285775366013026e-06,
+ "loss": 0.4514,
+ "step": 8400
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.283551676045945e-06,
+ "loss": 0.4551,
+ "step": 8401
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.281328405871048e-06,
+ "loss": 0.4775,
+ "step": 8402
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.279105555651608e-06,
+ "loss": 0.4647,
+ "step": 8403
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.276883125550864e-06,
+ "loss": 0.47,
+ "step": 8404
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.27466111573202e-06,
+ "loss": 0.4737,
+ "step": 8405
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.272439526358249e-06,
+ "loss": 0.4676,
+ "step": 8406
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.270218357592696e-06,
+ "loss": 0.459,
+ "step": 8407
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.267997609598477e-06,
+ "loss": 0.4788,
+ "step": 8408
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.26577728253867e-06,
+ "loss": 0.4554,
+ "step": 8409
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.263557376576326e-06,
+ "loss": 0.4793,
+ "step": 8410
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.261337891874473e-06,
+ "loss": 0.4776,
+ "step": 8411
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.259118828596096e-06,
+ "loss": 0.4613,
+ "step": 8412
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.25690018690415e-06,
+ "loss": 0.4708,
+ "step": 8413
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.254681966961571e-06,
+ "loss": 0.4675,
+ "step": 8414
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.2524641689312526e-06,
+ "loss": 0.4669,
+ "step": 8415
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.250246792976058e-06,
+ "loss": 0.4417,
+ "step": 8416
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.248029839258821e-06,
+ "loss": 0.4719,
+ "step": 8417
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.245813307942354e-06,
+ "loss": 0.4622,
+ "step": 8418
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.243597199189422e-06,
+ "loss": 0.4852,
+ "step": 8419
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.241381513162769e-06,
+ "loss": 0.4809,
+ "step": 8420
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.239166250025106e-06,
+ "loss": 0.4711,
+ "step": 8421
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.236951409939109e-06,
+ "loss": 0.4572,
+ "step": 8422
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.234736993067434e-06,
+ "loss": 0.4833,
+ "step": 8423
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.2325229995726915e-06,
+ "loss": 0.4804,
+ "step": 8424
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.230309429617474e-06,
+ "loss": 0.456,
+ "step": 8425
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.228096283364335e-06,
+ "loss": 0.4626,
+ "step": 8426
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.2258835609757965e-06,
+ "loss": 0.4777,
+ "step": 8427
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.223671262614354e-06,
+ "loss": 0.4482,
+ "step": 8428
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.221459388442467e-06,
+ "loss": 0.4631,
+ "step": 8429
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.219247938622566e-06,
+ "loss": 0.451,
+ "step": 8430
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.217036913317054e-06,
+ "loss": 0.4781,
+ "step": 8431
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.214826312688299e-06,
+ "loss": 0.4649,
+ "step": 8432
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.212616136898634e-06,
+ "loss": 0.4937,
+ "step": 8433
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.210406386110371e-06,
+ "loss": 0.4511,
+ "step": 8434
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.208197060485783e-06,
+ "loss": 0.4606,
+ "step": 8435
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.205988160187113e-06,
+ "loss": 0.4546,
+ "step": 8436
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.20377968537657e-06,
+ "loss": 0.4751,
+ "step": 8437
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.201571636216343e-06,
+ "loss": 0.4677,
+ "step": 8438
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.199364012868575e-06,
+ "loss": 0.4771,
+ "step": 8439
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.197156815495389e-06,
+ "loss": 0.4534,
+ "step": 8440
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.194950044258871e-06,
+ "loss": 0.4552,
+ "step": 8441
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.192743699321075e-06,
+ "loss": 0.4798,
+ "step": 8442
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.190537780844026e-06,
+ "loss": 0.4611,
+ "step": 8443
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.188332288989721e-06,
+ "loss": 0.4666,
+ "step": 8444
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.186127223920118e-06,
+ "loss": 0.4572,
+ "step": 8445
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.183922585797152e-06,
+ "loss": 0.4646,
+ "step": 8446
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.181718374782722e-06,
+ "loss": 0.4711,
+ "step": 8447
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.179514591038692e-06,
+ "loss": 0.4616,
+ "step": 8448
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.177311234726904e-06,
+ "loss": 0.473,
+ "step": 8449
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.175108306009159e-06,
+ "loss": 0.4671,
+ "step": 8450
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.172905805047229e-06,
+ "loss": 0.4892,
+ "step": 8451
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.170703732002864e-06,
+ "loss": 0.4654,
+ "step": 8452
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.168502087037771e-06,
+ "loss": 0.4498,
+ "step": 8453
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.166300870313625e-06,
+ "loss": 0.493,
+ "step": 8454
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.164100081992084e-06,
+ "loss": 0.4726,
+ "step": 8455
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.161899722234759e-06,
+ "loss": 0.4567,
+ "step": 8456
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.159699791203237e-06,
+ "loss": 0.4695,
+ "step": 8457
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.157500289059065e-06,
+ "loss": 0.4722,
+ "step": 8458
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.155301215963776e-06,
+ "loss": 0.4779,
+ "step": 8459
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.153102572078855e-06,
+ "loss": 0.4611,
+ "step": 8460
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.150904357565763e-06,
+ "loss": 0.4846,
+ "step": 8461
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.148706572585927e-06,
+ "loss": 0.4619,
+ "step": 8462
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.146509217300738e-06,
+ "loss": 0.4694,
+ "step": 8463
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.14431229187157e-06,
+ "loss": 0.4676,
+ "step": 8464
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.142115796459748e-06,
+ "loss": 0.4772,
+ "step": 8465
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.13991973122658e-06,
+ "loss": 0.4591,
+ "step": 8466
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.137724096333334e-06,
+ "loss": 0.4703,
+ "step": 8467
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.135528891941246e-06,
+ "loss": 0.4667,
+ "step": 8468
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.133334118211526e-06,
+ "loss": 0.4814,
+ "step": 8469
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.131139775305346e-06,
+ "loss": 0.463,
+ "step": 8470
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.128945863383846e-06,
+ "loss": 0.4672,
+ "step": 8471
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.126752382608147e-06,
+ "loss": 0.4525,
+ "step": 8472
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.124559333139324e-06,
+ "loss": 0.4729,
+ "step": 8473
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.122366715138426e-06,
+ "loss": 0.4727,
+ "step": 8474
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.1201745287664664e-06,
+ "loss": 0.4635,
+ "step": 8475
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.117982774184436e-06,
+ "loss": 0.4769,
+ "step": 8476
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.115791451553286e-06,
+ "loss": 0.4583,
+ "step": 8477
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.1136005610339335e-06,
+ "loss": 0.476,
+ "step": 8478
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.111410102787276e-06,
+ "loss": 0.4648,
+ "step": 8479
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.109220076974168e-06,
+ "loss": 0.4614,
+ "step": 8480
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.107030483755436e-06,
+ "loss": 0.482,
+ "step": 8481
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.104841323291876e-06,
+ "loss": 0.4816,
+ "step": 8482
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.102652595744248e-06,
+ "loss": 0.4644,
+ "step": 8483
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.100464301273282e-06,
+ "loss": 0.4676,
+ "step": 8484
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.098276440039681e-06,
+ "loss": 0.4865,
+ "step": 8485
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0960890122041095e-06,
+ "loss": 0.472,
+ "step": 8486
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.093902017927208e-06,
+ "loss": 0.4773,
+ "step": 8487
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.091715457369577e-06,
+ "loss": 0.4894,
+ "step": 8488
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.089529330691789e-06,
+ "loss": 0.4876,
+ "step": 8489
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.087343638054382e-06,
+ "loss": 0.4657,
+ "step": 8490
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.085158379617866e-06,
+ "loss": 0.4594,
+ "step": 8491
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.082973555542713e-06,
+ "loss": 0.4669,
+ "step": 8492
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.080789165989376e-06,
+ "loss": 0.484,
+ "step": 8493
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0786052111182625e-06,
+ "loss": 0.4446,
+ "step": 8494
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0764216910897496e-06,
+ "loss": 0.4834,
+ "step": 8495
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.074238606064194e-06,
+ "loss": 0.4814,
+ "step": 8496
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.072055956201907e-06,
+ "loss": 0.4433,
+ "step": 8497
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.069873741663171e-06,
+ "loss": 0.466,
+ "step": 8498
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.067691962608245e-06,
+ "loss": 0.4694,
+ "step": 8499
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0655106191973485e-06,
+ "loss": 0.4718,
+ "step": 8500
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.063329711590668e-06,
+ "loss": 0.4776,
+ "step": 8501
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.061149239948361e-06,
+ "loss": 0.4952,
+ "step": 8502
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.058969204430553e-06,
+ "loss": 0.4696,
+ "step": 8503
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.056789605197335e-06,
+ "loss": 0.4936,
+ "step": 8504
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.054610442408765e-06,
+ "loss": 0.4689,
+ "step": 8505
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.052431716224876e-06,
+ "loss": 0.4777,
+ "step": 8506
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.050253426805668e-06,
+ "loss": 0.4714,
+ "step": 8507
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.048075574311101e-06,
+ "loss": 0.4638,
+ "step": 8508
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.045898158901108e-06,
+ "loss": 0.4809,
+ "step": 8509
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.043721180735589e-06,
+ "loss": 0.4672,
+ "step": 8510
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.041544639974413e-06,
+ "loss": 0.4507,
+ "step": 8511
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.03936853677741e-06,
+ "loss": 0.4801,
+ "step": 8512
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.037192871304396e-06,
+ "loss": 0.4604,
+ "step": 8513
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.035017643715135e-06,
+ "loss": 0.462,
+ "step": 8514
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.032842854169368e-06,
+ "loss": 0.465,
+ "step": 8515
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.030668502826799e-06,
+ "loss": 0.4692,
+ "step": 8516
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.028494589847109e-06,
+ "loss": 0.4676,
+ "step": 8517
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.026321115389942e-06,
+ "loss": 0.475,
+ "step": 8518
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0241480796149e-06,
+ "loss": 0.4485,
+ "step": 8519
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.021975482681571e-06,
+ "loss": 0.4837,
+ "step": 8520
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0198033247494995e-06,
+ "loss": 0.4756,
+ "step": 8521
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.017631605978198e-06,
+ "loss": 0.4693,
+ "step": 8522
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.015460326527149e-06,
+ "loss": 0.4934,
+ "step": 8523
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.013289486555801e-06,
+ "loss": 0.4677,
+ "step": 8524
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.01111908622357e-06,
+ "loss": 0.4588,
+ "step": 8525
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.008949125689846e-06,
+ "loss": 0.4807,
+ "step": 8526
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0067796051139775e-06,
+ "loss": 0.4802,
+ "step": 8527
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0046105246552895e-06,
+ "loss": 0.4561,
+ "step": 8528
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.002441884473069e-06,
+ "loss": 0.4578,
+ "step": 8529
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.000273684726569e-06,
+ "loss": 0.469,
+ "step": 8530
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.998105925575017e-06,
+ "loss": 0.4794,
+ "step": 8531
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.995938607177599e-06,
+ "loss": 0.4589,
+ "step": 8532
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.993771729693476e-06,
+ "loss": 0.4691,
+ "step": 8533
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.991605293281779e-06,
+ "loss": 0.4729,
+ "step": 8534
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.989439298101597e-06,
+ "loss": 0.477,
+ "step": 8535
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.9872737443119914e-06,
+ "loss": 0.4653,
+ "step": 8536
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.985108632071995e-06,
+ "loss": 0.4654,
+ "step": 8537
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.982943961540604e-06,
+ "loss": 0.4591,
+ "step": 8538
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.980779732876777e-06,
+ "loss": 0.4844,
+ "step": 8539
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.978615946239456e-06,
+ "loss": 0.4753,
+ "step": 8540
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.9764526017875326e-06,
+ "loss": 0.4698,
+ "step": 8541
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.974289699679879e-06,
+ "loss": 0.4496,
+ "step": 8542
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.972127240075325e-06,
+ "loss": 0.4753,
+ "step": 8543
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.969965223132675e-06,
+ "loss": 0.4723,
+ "step": 8544
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.967803649010698e-06,
+ "loss": 0.4615,
+ "step": 8545
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.965642517868129e-06,
+ "loss": 0.4637,
+ "step": 8546
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.963481829863673e-06,
+ "loss": 0.4717,
+ "step": 8547
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9613215851560094e-06,
+ "loss": 0.4675,
+ "step": 8548
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.95916178390377e-06,
+ "loss": 0.4737,
+ "step": 8549
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.957002426265564e-06,
+ "loss": 0.4573,
+ "step": 8550
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.954843512399965e-06,
+ "loss": 0.477,
+ "step": 8551
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.952685042465515e-06,
+ "loss": 0.4955,
+ "step": 8552
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.950527016620719e-06,
+ "loss": 0.4608,
+ "step": 8553
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.948369435024061e-06,
+ "loss": 0.4601,
+ "step": 8554
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9462122978339815e-06,
+ "loss": 0.4654,
+ "step": 8555
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.944055605208891e-06,
+ "loss": 0.4643,
+ "step": 8556
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.941899357307164e-06,
+ "loss": 0.4667,
+ "step": 8557
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.939743554287154e-06,
+ "loss": 0.4756,
+ "step": 8558
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.937588196307172e-06,
+ "loss": 0.4816,
+ "step": 8559
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9354332835254935e-06,
+ "loss": 0.4623,
+ "step": 8560
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.933278816100373e-06,
+ "loss": 0.468,
+ "step": 8561
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9311247941900245e-06,
+ "loss": 0.4859,
+ "step": 8562
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9289712179526275e-06,
+ "loss": 0.4537,
+ "step": 8563
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.926818087546333e-06,
+ "loss": 0.4717,
+ "step": 8564
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.924665403129259e-06,
+ "loss": 0.4674,
+ "step": 8565
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9225131648594835e-06,
+ "loss": 0.4457,
+ "step": 8566
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.920361372895067e-06,
+ "loss": 0.4414,
+ "step": 8567
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.918210027394021e-06,
+ "loss": 0.4717,
+ "step": 8568
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9160591285143375e-06,
+ "loss": 0.462,
+ "step": 8569
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9139086764139675e-06,
+ "loss": 0.4642,
+ "step": 8570
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.911758671250829e-06,
+ "loss": 0.4636,
+ "step": 8571
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.909609113182812e-06,
+ "loss": 0.462,
+ "step": 8572
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.907460002367766e-06,
+ "loss": 0.4626,
+ "step": 8573
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.90531133896352e-06,
+ "loss": 0.4717,
+ "step": 8574
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.90316312312786e-06,
+ "loss": 0.4724,
+ "step": 8575
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.901015355018541e-06,
+ "loss": 0.4667,
+ "step": 8576
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8988680347932836e-06,
+ "loss": 0.4813,
+ "step": 8577
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.896721162609785e-06,
+ "loss": 0.4612,
+ "step": 8578
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.894574738625699e-06,
+ "loss": 0.4741,
+ "step": 8579
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.892428762998644e-06,
+ "loss": 0.4814,
+ "step": 8580
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.890283235886223e-06,
+ "loss": 0.4944,
+ "step": 8581
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.888138157445989e-06,
+ "loss": 0.433,
+ "step": 8582
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.885993527835466e-06,
+ "loss": 0.4921,
+ "step": 8583
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.883849347212151e-06,
+ "loss": 0.4568,
+ "step": 8584
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8817056157334985e-06,
+ "loss": 0.4738,
+ "step": 8585
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.879562333556939e-06,
+ "loss": 0.4914,
+ "step": 8586
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.877419500839861e-06,
+ "loss": 0.4677,
+ "step": 8587
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.875277117739632e-06,
+ "loss": 0.4613,
+ "step": 8588
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.873135184413573e-06,
+ "loss": 0.4628,
+ "step": 8589
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.870993701018988e-06,
+ "loss": 0.4649,
+ "step": 8590
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.868852667713131e-06,
+ "loss": 0.4456,
+ "step": 8591
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8667120846532335e-06,
+ "loss": 0.4777,
+ "step": 8592
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.864571951996491e-06,
+ "loss": 0.476,
+ "step": 8593
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.862432269900062e-06,
+ "loss": 0.4743,
+ "step": 8594
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.860293038521082e-06,
+ "loss": 0.4484,
+ "step": 8595
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.858154258016643e-06,
+ "loss": 0.4882,
+ "step": 8596
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.856015928543811e-06,
+ "loss": 0.4718,
+ "step": 8597
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.85387805025961e-06,
+ "loss": 0.4623,
+ "step": 8598
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8517406233210445e-06,
+ "loss": 0.4816,
+ "step": 8599
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.849603647885076e-06,
+ "loss": 0.47,
+ "step": 8600
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.84746712410863e-06,
+ "loss": 0.4653,
+ "step": 8601
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.845331052148612e-06,
+ "loss": 0.4681,
+ "step": 8602
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.843195432161883e-06,
+ "loss": 0.4579,
+ "step": 8603
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.841060264305272e-06,
+ "loss": 0.4616,
+ "step": 8604
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.838925548735579e-06,
+ "loss": 0.4761,
+ "step": 8605
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.836791285609568e-06,
+ "loss": 0.4677,
+ "step": 8606
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.834657475083967e-06,
+ "loss": 0.4562,
+ "step": 8607
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.83252411731548e-06,
+ "loss": 0.492,
+ "step": 8608
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.830391212460767e-06,
+ "loss": 0.4816,
+ "step": 8609
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.828258760676464e-06,
+ "loss": 0.4645,
+ "step": 8610
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.826126762119169e-06,
+ "loss": 0.4629,
+ "step": 8611
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.823995216945445e-06,
+ "loss": 0.4651,
+ "step": 8612
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.821864125311824e-06,
+ "loss": 0.4499,
+ "step": 8613
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.819733487374801e-06,
+ "loss": 0.4697,
+ "step": 8614
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.81760330329085e-06,
+ "loss": 0.4748,
+ "step": 8615
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.815473573216397e-06,
+ "loss": 0.4666,
+ "step": 8616
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8133442973078415e-06,
+ "loss": 0.4688,
+ "step": 8617
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.811215475721548e-06,
+ "loss": 0.4636,
+ "step": 8618
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.809087108613846e-06,
+ "loss": 0.452,
+ "step": 8619
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8069591961410402e-06,
+ "loss": 0.458,
+ "step": 8620
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.804831738459388e-06,
+ "loss": 0.4557,
+ "step": 8621
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.80270473572513e-06,
+ "loss": 0.483,
+ "step": 8622
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.800578188094459e-06,
+ "loss": 0.4682,
+ "step": 8623
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7984520957235403e-06,
+ "loss": 0.4645,
+ "step": 8624
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7963264587685067e-06,
+ "loss": 0.4688,
+ "step": 8625
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7942012773854532e-06,
+ "loss": 0.4634,
+ "step": 8626
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.792076551730447e-06,
+ "loss": 0.4708,
+ "step": 8627
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.789952281959515e-06,
+ "loss": 0.4622,
+ "step": 8628
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7878284682286615e-06,
+ "loss": 0.4641,
+ "step": 8629
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7857051106938425e-06,
+ "loss": 0.4655,
+ "step": 8630
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7835822095109966e-06,
+ "loss": 0.4844,
+ "step": 8631
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7814597648360176e-06,
+ "loss": 0.4661,
+ "step": 8632
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7793377768247685e-06,
+ "loss": 0.4646,
+ "step": 8633
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7772162456330796e-06,
+ "loss": 0.49,
+ "step": 8634
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.775095171416744e-06,
+ "loss": 0.4759,
+ "step": 8635
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.77297455433153e-06,
+ "loss": 0.4735,
+ "step": 8636
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7708543945331654e-06,
+ "loss": 0.4817,
+ "step": 8637
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.768734692177345e-06,
+ "loss": 0.449,
+ "step": 8638
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.766615447419727e-06,
+ "loss": 0.4656,
+ "step": 8639
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.764496660415948e-06,
+ "loss": 0.4704,
+ "step": 8640
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.762378331321599e-06,
+ "loss": 0.4846,
+ "step": 8641
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7602604602922365e-06,
+ "loss": 0.4714,
+ "step": 8642
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.758143047483398e-06,
+ "loss": 0.4686,
+ "step": 8643
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.756026093050571e-06,
+ "loss": 0.4748,
+ "step": 8644
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7539095971492177e-06,
+ "loss": 0.4507,
+ "step": 8645
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7517935599347634e-06,
+ "loss": 0.4642,
+ "step": 8646
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7496779815626026e-06,
+ "loss": 0.4805,
+ "step": 8647
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.74756286218809e-06,
+ "loss": 0.4671,
+ "step": 8648
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.745448201966558e-06,
+ "loss": 0.4739,
+ "step": 8649
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7433340010532926e-06,
+ "loss": 0.4768,
+ "step": 8650
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7412202596035586e-06,
+ "loss": 0.4509,
+ "step": 8651
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.739106977772575e-06,
+ "loss": 0.4845,
+ "step": 8652
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7369941557155354e-06,
+ "loss": 0.4621,
+ "step": 8653
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7348817935875947e-06,
+ "loss": 0.4534,
+ "step": 8654
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7327698915438725e-06,
+ "loss": 0.4751,
+ "step": 8655
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.730658449739466e-06,
+ "loss": 0.4679,
+ "step": 8656
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7285474683294274e-06,
+ "loss": 0.4685,
+ "step": 8657
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7264369474687767e-06,
+ "loss": 0.4646,
+ "step": 8658
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7243268873125038e-06,
+ "loss": 0.4867,
+ "step": 8659
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7222172880155585e-06,
+ "loss": 0.473,
+ "step": 8660
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.720108149732866e-06,
+ "loss": 0.4919,
+ "step": 8661
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.717999472619309e-06,
+ "loss": 0.4689,
+ "step": 8662
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7158912568297458e-06,
+ "loss": 0.482,
+ "step": 8663
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7137835025189894e-06,
+ "loss": 0.4459,
+ "step": 8664
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.711676209841828e-06,
+ "loss": 0.4706,
+ "step": 8665
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.7095693789530096e-06,
+ "loss": 0.4603,
+ "step": 8666
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.707463010007252e-06,
+ "loss": 0.4563,
+ "step": 8667
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.7053571031592393e-06,
+ "loss": 0.4674,
+ "step": 8668
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.703251658563615e-06,
+ "loss": 0.4673,
+ "step": 8669
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.7011466763750026e-06,
+ "loss": 0.4479,
+ "step": 8670
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6990421567479764e-06,
+ "loss": 0.465,
+ "step": 8671
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6969380998370896e-06,
+ "loss": 0.4908,
+ "step": 8672
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6948345057968525e-06,
+ "loss": 0.4905,
+ "step": 8673
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.692731374781744e-06,
+ "loss": 0.4654,
+ "step": 8674
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.69062870694621e-06,
+ "loss": 0.4858,
+ "step": 8675
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.688526502444657e-06,
+ "loss": 0.4783,
+ "step": 8676
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6864247614314696e-06,
+ "loss": 0.4673,
+ "step": 8677
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6843234840609877e-06,
+ "loss": 0.4805,
+ "step": 8678
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6822226704875208e-06,
+ "loss": 0.4687,
+ "step": 8679
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6801223208653392e-06,
+ "loss": 0.4843,
+ "step": 8680
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6780224353486916e-06,
+ "loss": 0.4707,
+ "step": 8681
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.675923014091781e-06,
+ "loss": 0.4632,
+ "step": 8682
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.673824057248778e-06,
+ "loss": 0.4782,
+ "step": 8683
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.671725564973827e-06,
+ "loss": 0.4764,
+ "step": 8684
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.669627537421029e-06,
+ "loss": 0.4581,
+ "step": 8685
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6675299747444536e-06,
+ "loss": 0.4726,
+ "step": 8686
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6654328770981396e-06,
+ "loss": 0.4647,
+ "step": 8687
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6633362446360865e-06,
+ "loss": 0.4703,
+ "step": 8688
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6612400775122603e-06,
+ "loss": 0.448,
+ "step": 8689
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.659144375880602e-06,
+ "loss": 0.4705,
+ "step": 8690
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6570491398950038e-06,
+ "loss": 0.4516,
+ "step": 8691
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.654954369709337e-06,
+ "loss": 0.449,
+ "step": 8692
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6528600654774306e-06,
+ "loss": 0.466,
+ "step": 8693
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.650766227353081e-06,
+ "loss": 0.464,
+ "step": 8694
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.648672855490052e-06,
+ "loss": 0.4556,
+ "step": 8695
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6465799500420673e-06,
+ "loss": 0.4629,
+ "step": 8696
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6444875111628287e-06,
+ "loss": 0.4737,
+ "step": 8697
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.642395539005993e-06,
+ "loss": 0.4636,
+ "step": 8698
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.640304033725185e-06,
+ "loss": 0.4655,
+ "step": 8699
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6382129954739975e-06,
+ "loss": 0.4755,
+ "step": 8700
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6361224244059823e-06,
+ "loss": 0.4662,
+ "step": 8701
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.634032320674672e-06,
+ "loss": 0.4579,
+ "step": 8702
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.631942684433546e-06,
+ "loss": 0.4519,
+ "step": 8703
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.629853515836065e-06,
+ "loss": 0.4656,
+ "step": 8704
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.627764815035647e-06,
+ "loss": 0.463,
+ "step": 8705
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6256765821856775e-06,
+ "loss": 0.4798,
+ "step": 8706
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6235888174395062e-06,
+ "loss": 0.4823,
+ "step": 8707
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.621501520950451e-06,
+ "loss": 0.4671,
+ "step": 8708
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6194146928717942e-06,
+ "loss": 0.4839,
+ "step": 8709
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.61732833335678e-06,
+ "loss": 0.4805,
+ "step": 8710
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6152424425586285e-06,
+ "loss": 0.4655,
+ "step": 8711
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.613157020630512e-06,
+ "loss": 0.4648,
+ "step": 8712
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.611072067725583e-06,
+ "loss": 0.4541,
+ "step": 8713
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.608987583996948e-06,
+ "loss": 0.4756,
+ "step": 8714
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.606903569597683e-06,
+ "loss": 0.4576,
+ "step": 8715
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6048200246808273e-06,
+ "loss": 0.4836,
+ "step": 8716
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.602736949399388e-06,
+ "loss": 0.473,
+ "step": 8717
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.600654343906341e-06,
+ "loss": 0.4894,
+ "step": 8718
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5985722083546228e-06,
+ "loss": 0.4522,
+ "step": 8719
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5964905428971354e-06,
+ "loss": 0.473,
+ "step": 8720
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.594409347686746e-06,
+ "loss": 0.4861,
+ "step": 8721
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5923286228762934e-06,
+ "loss": 0.4682,
+ "step": 8722
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5902483686185764e-06,
+ "loss": 0.457,
+ "step": 8723
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.588168585066355e-06,
+ "loss": 0.4876,
+ "step": 8724
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5860892723723674e-06,
+ "loss": 0.4721,
+ "step": 8725
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5840104306893055e-06,
+ "loss": 0.4603,
+ "step": 8726
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5819320601698324e-06,
+ "loss": 0.4653,
+ "step": 8727
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.579854160966574e-06,
+ "loss": 0.4754,
+ "step": 8728
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5777767332321222e-06,
+ "loss": 0.4538,
+ "step": 8729
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5756997771190317e-06,
+ "loss": 0.4826,
+ "step": 8730
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.573623292779832e-06,
+ "loss": 0.4565,
+ "step": 8731
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5715472803670092e-06,
+ "loss": 0.4866,
+ "step": 8732
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5694717400330125e-06,
+ "loss": 0.4571,
+ "step": 8733
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5673966719302677e-06,
+ "loss": 0.4778,
+ "step": 8734
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.565322076211156e-06,
+ "loss": 0.4611,
+ "step": 8735
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5632479530280273e-06,
+ "loss": 0.4616,
+ "step": 8736
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5611743025331933e-06,
+ "loss": 0.4913,
+ "step": 8737
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.559101124878941e-06,
+ "loss": 0.46,
+ "step": 8738
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.557028420217512e-06,
+ "loss": 0.4664,
+ "step": 8739
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5549561887011186e-06,
+ "loss": 0.47,
+ "step": 8740
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.552884430481934e-06,
+ "loss": 0.4343,
+ "step": 8741
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5508131457120986e-06,
+ "loss": 0.4623,
+ "step": 8742
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5487423345437253e-06,
+ "loss": 0.4712,
+ "step": 8743
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.546671997128879e-06,
+ "loss": 0.4623,
+ "step": 8744
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5446021336196024e-06,
+ "loss": 0.4617,
+ "step": 8745
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5425327441678956e-06,
+ "loss": 0.4594,
+ "step": 8746
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5404638289257256e-06,
+ "loss": 0.4785,
+ "step": 8747
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.538395388045024e-06,
+ "loss": 0.4682,
+ "step": 8748
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.53632742167769e-06,
+ "loss": 0.4745,
+ "step": 8749
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5342599299755854e-06,
+ "loss": 0.4562,
+ "step": 8750
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.532192913090534e-06,
+ "loss": 0.4783,
+ "step": 8751
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5301263711743384e-06,
+ "loss": 0.4638,
+ "step": 8752
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.528060304378749e-06,
+ "loss": 0.4599,
+ "step": 8753
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.525994712855494e-06,
+ "loss": 0.4589,
+ "step": 8754
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5239295967562603e-06,
+ "loss": 0.4726,
+ "step": 8755
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5218649562327e-06,
+ "loss": 0.492,
+ "step": 8756
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.519800791436434e-06,
+ "loss": 0.45,
+ "step": 8757
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.517737102519041e-06,
+ "loss": 0.4591,
+ "step": 8758
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5156738896320773e-06,
+ "loss": 0.4785,
+ "step": 8759
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.513611152927052e-06,
+ "loss": 0.4613,
+ "step": 8760
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5115488925554453e-06,
+ "loss": 0.46,
+ "step": 8761
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5094871086686997e-06,
+ "loss": 0.46,
+ "step": 8762
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.507425801418223e-06,
+ "loss": 0.4892,
+ "step": 8763
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5053649709553893e-06,
+ "loss": 0.4579,
+ "step": 8764
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5033046174315422e-06,
+ "loss": 0.4607,
+ "step": 8765
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5012447409979832e-06,
+ "loss": 0.4775,
+ "step": 8766
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4991853418059798e-06,
+ "loss": 0.4502,
+ "step": 8767
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4971264200067657e-06,
+ "loss": 0.4841,
+ "step": 8768
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4950679757515395e-06,
+ "loss": 0.4704,
+ "step": 8769
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4930100091914655e-06,
+ "loss": 0.4668,
+ "step": 8770
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4909525204776684e-06,
+ "loss": 0.4685,
+ "step": 8771
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4888955097612487e-06,
+ "loss": 0.4771,
+ "step": 8772
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4868389771932608e-06,
+ "loss": 0.4739,
+ "step": 8773
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4847829229247243e-06,
+ "loss": 0.4764,
+ "step": 8774
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.482727347106636e-06,
+ "loss": 0.4639,
+ "step": 8775
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4806722498899424e-06,
+ "loss": 0.4862,
+ "step": 8776
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4786176314255626e-06,
+ "loss": 0.4599,
+ "step": 8777
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4765634918643778e-06,
+ "loss": 0.4675,
+ "step": 8778
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.474509831357239e-06,
+ "loss": 0.4556,
+ "step": 8779
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.472456650054957e-06,
+ "loss": 0.4535,
+ "step": 8780
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4704039481083086e-06,
+ "loss": 0.4802,
+ "step": 8781
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4683517256680365e-06,
+ "loss": 0.4857,
+ "step": 8782
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.466299982884842e-06,
+ "loss": 0.4661,
+ "step": 8783
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4642487199094042e-06,
+ "loss": 0.4644,
+ "step": 8784
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.462197936892354e-06,
+ "loss": 0.4719,
+ "step": 8785
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4601476339842976e-06,
+ "loss": 0.4574,
+ "step": 8786
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4580978113357967e-06,
+ "loss": 0.4828,
+ "step": 8787
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4560484690973838e-06,
+ "loss": 0.4778,
+ "step": 8788
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4539996074195526e-06,
+ "loss": 0.4658,
+ "step": 8789
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4519512264527633e-06,
+ "loss": 0.4703,
+ "step": 8790
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.44990332634744e-06,
+ "loss": 0.4833,
+ "step": 8791
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.447855907253971e-06,
+ "loss": 0.464,
+ "step": 8792
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4458089693227127e-06,
+ "loss": 0.4666,
+ "step": 8793
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.443762512703981e-06,
+ "loss": 0.4895,
+ "step": 8794
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4417165375480644e-06,
+ "loss": 0.4448,
+ "step": 8795
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.439671044005206e-06,
+ "loss": 0.4548,
+ "step": 8796
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4376260322256207e-06,
+ "loss": 0.4647,
+ "step": 8797
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.435581502359484e-06,
+ "loss": 0.4641,
+ "step": 8798
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4335374545569355e-06,
+ "loss": 0.4555,
+ "step": 8799
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.431493888968087e-06,
+ "loss": 0.4594,
+ "step": 8800
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4294508057430077e-06,
+ "loss": 0.4741,
+ "step": 8801
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4274082050317324e-06,
+ "loss": 0.4444,
+ "step": 8802
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.425366086984261e-06,
+ "loss": 0.4935,
+ "step": 8803
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4233244517505535e-06,
+ "loss": 0.4806,
+ "step": 8804
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4212832994805445e-06,
+ "loss": 0.4512,
+ "step": 8805
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.419242630324131e-06,
+ "loss": 0.4563,
+ "step": 8806
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.417202444431167e-06,
+ "loss": 0.4666,
+ "step": 8807
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4151627419514753e-06,
+ "loss": 0.4755,
+ "step": 8808
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4131235230348434e-06,
+ "loss": 0.4383,
+ "step": 8809
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.411084787831024e-06,
+ "loss": 0.4517,
+ "step": 8810
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4090465364897317e-06,
+ "loss": 0.4664,
+ "step": 8811
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4070087691606446e-06,
+ "loss": 0.4844,
+ "step": 8812
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4049714859934144e-06,
+ "loss": 0.4634,
+ "step": 8813
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4029346871376477e-06,
+ "loss": 0.4492,
+ "step": 8814
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4008983727429147e-06,
+ "loss": 0.4665,
+ "step": 8815
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.398862542958761e-06,
+ "loss": 0.4744,
+ "step": 8816
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3968271979346857e-06,
+ "loss": 0.4571,
+ "step": 8817
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3947923378201576e-06,
+ "loss": 0.4543,
+ "step": 8818
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3927579627646024e-06,
+ "loss": 0.4386,
+ "step": 8819
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.390724072917424e-06,
+ "loss": 0.4878,
+ "step": 8820
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3886906684279806e-06,
+ "loss": 0.4807,
+ "step": 8821
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3866577494455953e-06,
+ "loss": 0.485,
+ "step": 8822
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3846253161195584e-06,
+ "loss": 0.46,
+ "step": 8823
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3825933685991184e-06,
+ "loss": 0.4907,
+ "step": 8824
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3805619070335026e-06,
+ "loss": 0.4913,
+ "step": 8825
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.378530931571884e-06,
+ "loss": 0.4608,
+ "step": 8826
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3765004423634164e-06,
+ "loss": 0.4769,
+ "step": 8827
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.374470439557207e-06,
+ "loss": 0.4694,
+ "step": 8828
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.37244092330233e-06,
+ "loss": 0.4434,
+ "step": 8829
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.370411893747827e-06,
+ "loss": 0.4433,
+ "step": 8830
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.368383351042699e-06,
+ "loss": 0.4656,
+ "step": 8831
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.366355295335915e-06,
+ "loss": 0.4648,
+ "step": 8832
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.364327726776403e-06,
+ "loss": 0.4587,
+ "step": 8833
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.362300645513067e-06,
+ "loss": 0.4806,
+ "step": 8834
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3602740516947595e-06,
+ "loss": 0.4774,
+ "step": 8835
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.358247945470313e-06,
+ "loss": 0.4611,
+ "step": 8836
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.356222326988512e-06,
+ "loss": 0.4639,
+ "step": 8837
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.354197196398109e-06,
+ "loss": 0.4685,
+ "step": 8838
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.352172553847819e-06,
+ "loss": 0.4648,
+ "step": 8839
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3501483994863293e-06,
+ "loss": 0.4667,
+ "step": 8840
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3481247334622822e-06,
+ "loss": 0.4724,
+ "step": 8841
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.346101555924288e-06,
+ "loss": 0.4687,
+ "step": 8842
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.34407886702092e-06,
+ "loss": 0.4531,
+ "step": 8843
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.342056666900716e-06,
+ "loss": 0.4567,
+ "step": 8844
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3400349557121748e-06,
+ "loss": 0.4598,
+ "step": 8845
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.338013733603768e-06,
+ "loss": 0.489,
+ "step": 8846
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3359930007239204e-06,
+ "loss": 0.4647,
+ "step": 8847
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3339727572210323e-06,
+ "loss": 0.4698,
+ "step": 8848
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3319530032434588e-06,
+ "loss": 0.4671,
+ "step": 8849
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3299337389395225e-06,
+ "loss": 0.4578,
+ "step": 8850
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.327914964457509e-06,
+ "loss": 0.4684,
+ "step": 8851
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3258966799456705e-06,
+ "loss": 0.4679,
+ "step": 8852
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3238788855522164e-06,
+ "loss": 0.4732,
+ "step": 8853
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3218615814253306e-06,
+ "loss": 0.471,
+ "step": 8854
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.319844767713155e-06,
+ "loss": 0.4485,
+ "step": 8855
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.317828444563792e-06,
+ "loss": 0.4604,
+ "step": 8856
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3158126121253178e-06,
+ "loss": 0.4795,
+ "step": 8857
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3137972705457632e-06,
+ "loss": 0.4728,
+ "step": 8858
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3117824199731274e-06,
+ "loss": 0.4833,
+ "step": 8859
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3097680605553697e-06,
+ "loss": 0.4926,
+ "step": 8860
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.307754192440421e-06,
+ "loss": 0.4609,
+ "step": 8861
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3057408157761696e-06,
+ "loss": 0.4956,
+ "step": 8862
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3037279307104685e-06,
+ "loss": 0.4779,
+ "step": 8863
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3017155373911382e-06,
+ "loss": 0.4621,
+ "step": 8864
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.299703635965953e-06,
+ "loss": 0.4677,
+ "step": 8865
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2976922265826695e-06,
+ "loss": 0.4607,
+ "step": 8866
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.295681309388987e-06,
+ "loss": 0.4671,
+ "step": 8867
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2936708845325882e-06,
+ "loss": 0.4555,
+ "step": 8868
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2916609521611052e-06,
+ "loss": 0.4641,
+ "step": 8869
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2896515124221395e-06,
+ "loss": 0.4775,
+ "step": 8870
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.287642565463257e-06,
+ "loss": 0.4471,
+ "step": 8871
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2856341114319856e-06,
+ "loss": 0.467,
+ "step": 8872
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.283626150475818e-06,
+ "loss": 0.4799,
+ "step": 8873
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.281618682742207e-06,
+ "loss": 0.4601,
+ "step": 8874
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2796117083785793e-06,
+ "loss": 0.4666,
+ "step": 8875
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2776052275323155e-06,
+ "loss": 0.461,
+ "step": 8876
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2755992403507595e-06,
+ "loss": 0.4508,
+ "step": 8877
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2735937469812308e-06,
+ "loss": 0.4643,
+ "step": 8878
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2715887475709994e-06,
+ "loss": 0.4558,
+ "step": 8879
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.269584242267301e-06,
+ "loss": 0.4459,
+ "step": 8880
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2675802312173468e-06,
+ "loss": 0.4652,
+ "step": 8881
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.265576714568296e-06,
+ "loss": 0.4812,
+ "step": 8882
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.263573692467282e-06,
+ "loss": 0.4507,
+ "step": 8883
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2615711650613978e-06,
+ "loss": 0.4705,
+ "step": 8884
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2595691324976987e-06,
+ "loss": 0.4785,
+ "step": 8885
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2575675949232044e-06,
+ "loss": 0.4464,
+ "step": 8886
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2555665524849056e-06,
+ "loss": 0.4793,
+ "step": 8887
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2535660053297426e-06,
+ "loss": 0.467,
+ "step": 8888
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2515659536046362e-06,
+ "loss": 0.4741,
+ "step": 8889
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.249566397456456e-06,
+ "loss": 0.456,
+ "step": 8890
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2475673370320437e-06,
+ "loss": 0.4789,
+ "step": 8891
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2455687724781993e-06,
+ "loss": 0.4689,
+ "step": 8892
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.243570703941692e-06,
+ "loss": 0.4554,
+ "step": 8893
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2415731315692456e-06,
+ "loss": 0.4697,
+ "step": 8894
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2395760555075616e-06,
+ "loss": 0.4546,
+ "step": 8895
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.237579475903294e-06,
+ "loss": 0.4439,
+ "step": 8896
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.235583392903059e-06,
+ "loss": 0.4737,
+ "step": 8897
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2335878066534464e-06,
+ "loss": 0.4907,
+ "step": 8898
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.231592717301003e-06,
+ "loss": 0.4479,
+ "step": 8899
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.229598124992238e-06,
+ "loss": 0.4761,
+ "step": 8900
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2276040298736246e-06,
+ "loss": 0.4905,
+ "step": 8901
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.225610432091604e-06,
+ "loss": 0.4728,
+ "step": 8902
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.223617331792578e-06,
+ "loss": 0.4552,
+ "step": 8903
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2216247291229087e-06,
+ "loss": 0.4697,
+ "step": 8904
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2196326242289266e-06,
+ "loss": 0.4414,
+ "step": 8905
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.217641017256923e-06,
+ "loss": 0.4574,
+ "step": 8906
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.21564990835315e-06,
+ "loss": 0.4696,
+ "step": 8907
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2136592976638293e-06,
+ "loss": 0.4626,
+ "step": 8908
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2116691853351455e-06,
+ "loss": 0.448,
+ "step": 8909
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2096795715132436e-06,
+ "loss": 0.4561,
+ "step": 8910
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2076904563442303e-06,
+ "loss": 0.4295,
+ "step": 8911
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2057018399741777e-06,
+ "loss": 0.4665,
+ "step": 8912
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2037137225491233e-06,
+ "loss": 0.4557,
+ "step": 8913
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2017261042150625e-06,
+ "loss": 0.4629,
+ "step": 8914
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.199738985117963e-06,
+ "loss": 0.455,
+ "step": 8915
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.197752365403748e-06,
+ "loss": 0.4552,
+ "step": 8916
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.195766245218307e-06,
+ "loss": 0.469,
+ "step": 8917
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1937806247074875e-06,
+ "loss": 0.4608,
+ "step": 8918
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1917955040171146e-06,
+ "loss": 0.4603,
+ "step": 8919
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.189810883292961e-06,
+ "loss": 0.4671,
+ "step": 8920
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.187826762680768e-06,
+ "loss": 0.4597,
+ "step": 8921
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.185843142326247e-06,
+ "loss": 0.4783,
+ "step": 8922
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1838600223750625e-06,
+ "loss": 0.4879,
+ "step": 8923
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.181877402972848e-06,
+ "loss": 0.452,
+ "step": 8924
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1798952842651985e-06,
+ "loss": 0.4763,
+ "step": 8925
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.177913666397673e-06,
+ "loss": 0.4543,
+ "step": 8926
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.175932549515789e-06,
+ "loss": 0.4596,
+ "step": 8927
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.173951933765038e-06,
+ "loss": 0.4473,
+ "step": 8928
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.171971819290862e-06,
+ "loss": 0.4753,
+ "step": 8929
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.169992206238679e-06,
+ "loss": 0.4606,
+ "step": 8930
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.16801309475386e-06,
+ "loss": 0.4574,
+ "step": 8931
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.166034484981744e-06,
+ "loss": 0.4675,
+ "step": 8932
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1640563770676305e-06,
+ "loss": 0.473,
+ "step": 8933
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1620787711567823e-06,
+ "loss": 0.4408,
+ "step": 8934
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1601016673944262e-06,
+ "loss": 0.4406,
+ "step": 8935
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.158125065925758e-06,
+ "loss": 0.4783,
+ "step": 8936
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1561489668959268e-06,
+ "loss": 0.4705,
+ "step": 8937
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1541733704500464e-06,
+ "loss": 0.4587,
+ "step": 8938
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1521982767332038e-06,
+ "loss": 0.4524,
+ "step": 8939
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.150223685890437e-06,
+ "loss": 0.4647,
+ "step": 8940
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1482495980667516e-06,
+ "loss": 0.4681,
+ "step": 8941
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1462760134071145e-06,
+ "loss": 0.4533,
+ "step": 8942
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1443029320564642e-06,
+ "loss": 0.4697,
+ "step": 8943
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1423303541596904e-06,
+ "loss": 0.4745,
+ "step": 8944
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1403582798616527e-06,
+ "loss": 0.4818,
+ "step": 8945
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1383867093071717e-06,
+ "loss": 0.4557,
+ "step": 8946
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1364156426410307e-06,
+ "loss": 0.4594,
+ "step": 8947
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1344450800079753e-06,
+ "loss": 0.4624,
+ "step": 8948
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1324750215527157e-06,
+ "loss": 0.4538,
+ "step": 8949
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1305054674199297e-06,
+ "loss": 0.4745,
+ "step": 8950
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.12853641775425e-06,
+ "loss": 0.4548,
+ "step": 8951
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1265678727002758e-06,
+ "loss": 0.4664,
+ "step": 8952
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.124599832402567e-06,
+ "loss": 0.459,
+ "step": 8953
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.122632297005651e-06,
+ "loss": 0.4514,
+ "step": 8954
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1206652666540107e-06,
+ "loss": 0.5009,
+ "step": 8955
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1186987414921023e-06,
+ "loss": 0.451,
+ "step": 8956
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1167327216643374e-06,
+ "loss": 0.4915,
+ "step": 8957
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1147672073150916e-06,
+ "loss": 0.4549,
+ "step": 8958
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1128021985887004e-06,
+ "loss": 0.4543,
+ "step": 8959
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.110837695629473e-06,
+ "loss": 0.4726,
+ "step": 8960
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1088736985816716e-06,
+ "loss": 0.4673,
+ "step": 8961
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1069102075895207e-06,
+ "loss": 0.4575,
+ "step": 8962
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1049472227972157e-06,
+ "loss": 0.4507,
+ "step": 8963
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1029847443489093e-06,
+ "loss": 0.4733,
+ "step": 8964
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1010227723887153e-06,
+ "loss": 0.4522,
+ "step": 8965
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0990613070607145e-06,
+ "loss": 0.4629,
+ "step": 8966
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0971003485089477e-06,
+ "loss": 0.4818,
+ "step": 8967
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.095139896877417e-06,
+ "loss": 0.4479,
+ "step": 8968
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.093179952310096e-06,
+ "loss": 0.4705,
+ "step": 8969
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.091220514950908e-06,
+ "loss": 0.4932,
+ "step": 8970
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0892615849437533e-06,
+ "loss": 0.4519,
+ "step": 8971
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0873031624324835e-06,
+ "loss": 0.4589,
+ "step": 8972
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.085345247560918e-06,
+ "loss": 0.4546,
+ "step": 8973
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0833878404728366e-06,
+ "loss": 0.4622,
+ "step": 8974
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.081430941311985e-06,
+ "loss": 0.4992,
+ "step": 8975
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0794745502220646e-06,
+ "loss": 0.4815,
+ "step": 8976
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.077518667346752e-06,
+ "loss": 0.4669,
+ "step": 8977
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.075563292829675e-06,
+ "loss": 0.4699,
+ "step": 8978
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0736084268144264e-06,
+ "loss": 0.4627,
+ "step": 8979
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0716540694445694e-06,
+ "loss": 0.4654,
+ "step": 8980
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0697002208636195e-06,
+ "loss": 0.4628,
+ "step": 8981
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0677468812150612e-06,
+ "loss": 0.4558,
+ "step": 8982
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0657940506423345e-06,
+ "loss": 0.4844,
+ "step": 8983
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0638417292888546e-06,
+ "loss": 0.4778,
+ "step": 8984
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0618899172979875e-06,
+ "loss": 0.4671,
+ "step": 8985
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0599386148130684e-06,
+ "loss": 0.4511,
+ "step": 8986
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0579878219773917e-06,
+ "loss": 0.4486,
+ "step": 8987
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0560375389342147e-06,
+ "loss": 0.4686,
+ "step": 8988
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0540877658267555e-06,
+ "loss": 0.4589,
+ "step": 8989
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0521385027982033e-06,
+ "loss": 0.4522,
+ "step": 8990
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.050189749991699e-06,
+ "loss": 0.4682,
+ "step": 8991
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0482415075503556e-06,
+ "loss": 0.4816,
+ "step": 8992
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0462937756172417e-06,
+ "loss": 0.4533,
+ "step": 8993
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0443465543353902e-06,
+ "loss": 0.4747,
+ "step": 8994
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0423998438477964e-06,
+ "loss": 0.4747,
+ "step": 8995
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0404536442974165e-06,
+ "loss": 0.4568,
+ "step": 8996
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0385079558271768e-06,
+ "loss": 0.4665,
+ "step": 8997
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.036562778579959e-06,
+ "loss": 0.4617,
+ "step": 8998
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0346181126986063e-06,
+ "loss": 0.4713,
+ "step": 8999
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0326739583259255e-06,
+ "loss": 0.4868,
+ "step": 9000
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.030730315604693e-06,
+ "loss": 0.4813,
+ "step": 9001
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0287871846776397e-06,
+ "loss": 0.4769,
+ "step": 9002
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0268445656874555e-06,
+ "loss": 0.4529,
+ "step": 9003
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0249024587768074e-06,
+ "loss": 0.4653,
+ "step": 9004
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.02296086408831e-06,
+ "loss": 0.4987,
+ "step": 9005
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0210197817645472e-06,
+ "loss": 0.445,
+ "step": 9006
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0190792119480638e-06,
+ "loss": 0.4692,
+ "step": 9007
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.017139154781368e-06,
+ "loss": 0.4617,
+ "step": 9008
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.015199610406925e-06,
+ "loss": 0.4727,
+ "step": 9009
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0132605789671744e-06,
+ "loss": 0.4471,
+ "step": 9010
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0113220606045035e-06,
+ "loss": 0.4654,
+ "step": 9011
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0093840554612753e-06,
+ "loss": 0.4895,
+ "step": 9012
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0074465636798056e-06,
+ "loss": 0.4657,
+ "step": 9013
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0055095854023764e-06,
+ "loss": 0.483,
+ "step": 9014
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0035731207712305e-06,
+ "loss": 0.4526,
+ "step": 9015
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.001637169928575e-06,
+ "loss": 0.4655,
+ "step": 9016
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9997017330165736e-06,
+ "loss": 0.4689,
+ "step": 9017
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9977668101773636e-06,
+ "loss": 0.4669,
+ "step": 9018
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.995832401553035e-06,
+ "loss": 0.4726,
+ "step": 9019
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.993898507285643e-06,
+ "loss": 0.4629,
+ "step": 9020
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9919651275172e-06,
+ "loss": 0.4591,
+ "step": 9021
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.990032262389693e-06,
+ "loss": 0.4758,
+ "step": 9022
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9880999120450595e-06,
+ "loss": 0.4545,
+ "step": 9023
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9861680766252e-06,
+ "loss": 0.4509,
+ "step": 9024
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9842367562719887e-06,
+ "loss": 0.4604,
+ "step": 9025
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.982305951127249e-06,
+ "loss": 0.46,
+ "step": 9026
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9803756613327704e-06,
+ "loss": 0.4715,
+ "step": 9027
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.978445887030308e-06,
+ "loss": 0.4413,
+ "step": 9028
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.976516628361574e-06,
+ "loss": 0.4943,
+ "step": 9029
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.974587885468243e-06,
+ "loss": 0.4575,
+ "step": 9030
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9726596584919596e-06,
+ "loss": 0.4496,
+ "step": 9031
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.970731947574319e-06,
+ "loss": 0.4542,
+ "step": 9032
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.968804752856891e-06,
+ "loss": 0.4855,
+ "step": 9033
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9668780744811967e-06,
+ "loss": 0.4437,
+ "step": 9034
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9649519125887227e-06,
+ "loss": 0.4699,
+ "step": 9035
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.96302626732092e-06,
+ "loss": 0.4794,
+ "step": 9036
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9611011388191956e-06,
+ "loss": 0.4607,
+ "step": 9037
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9591765272249305e-06,
+ "loss": 0.472,
+ "step": 9038
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9572524326794562e-06,
+ "loss": 0.4636,
+ "step": 9039
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9553288553240698e-06,
+ "loss": 0.4749,
+ "step": 9040
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9534057953000283e-06,
+ "loss": 0.4753,
+ "step": 9041
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9514832527485593e-06,
+ "loss": 0.4424,
+ "step": 9042
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.949561227810843e-06,
+ "loss": 0.4706,
+ "step": 9043
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.947639720628023e-06,
+ "loss": 0.4448,
+ "step": 9044
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.945718731341212e-06,
+ "loss": 0.4846,
+ "step": 9045
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.943798260091475e-06,
+ "loss": 0.4563,
+ "step": 9046
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9418783070198455e-06,
+ "loss": 0.4693,
+ "step": 9047
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9399588722673165e-06,
+ "loss": 0.4424,
+ "step": 9048
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.938039955974843e-06,
+ "loss": 0.4605,
+ "step": 9049
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9361215582833425e-06,
+ "loss": 0.474,
+ "step": 9050
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9342036793336904e-06,
+ "loss": 0.4644,
+ "step": 9051
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9322863192667306e-06,
+ "loss": 0.4739,
+ "step": 9052
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9303694782232706e-06,
+ "loss": 0.451,
+ "step": 9053
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.928453156344071e-06,
+ "loss": 0.4632,
+ "step": 9054
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9265373537698595e-06,
+ "loss": 0.4599,
+ "step": 9055
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.924622070641323e-06,
+ "loss": 0.4581,
+ "step": 9056
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.922707307099113e-06,
+ "loss": 0.4745,
+ "step": 9057
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.920793063283839e-06,
+ "loss": 0.4713,
+ "step": 9058
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9188793393360813e-06,
+ "loss": 0.4605,
+ "step": 9059
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.916966135396372e-06,
+ "loss": 0.4687,
+ "step": 9060
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9150534516052085e-06,
+ "loss": 0.4748,
+ "step": 9061
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9131412881030487e-06,
+ "loss": 0.454,
+ "step": 9062
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.911229645030319e-06,
+ "loss": 0.4901,
+ "step": 9063
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.909318522527397e-06,
+ "loss": 0.4588,
+ "step": 9064
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9074079207346328e-06,
+ "loss": 0.4642,
+ "step": 9065
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9054978397923306e-06,
+ "loss": 0.4733,
+ "step": 9066
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.903588279840759e-06,
+ "loss": 0.4799,
+ "step": 9067
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.901679241020149e-06,
+ "loss": 0.472,
+ "step": 9068
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8997707234706894e-06,
+ "loss": 0.4813,
+ "step": 9069
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8978627273325378e-06,
+ "loss": 0.4612,
+ "step": 9070
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8959552527458025e-06,
+ "loss": 0.4695,
+ "step": 9071
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8940482998505703e-06,
+ "loss": 0.4619,
+ "step": 9072
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.892141868786871e-06,
+ "loss": 0.452,
+ "step": 9073
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8902359596947127e-06,
+ "loss": 0.4722,
+ "step": 9074
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8883305727140533e-06,
+ "loss": 0.442,
+ "step": 9075
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8864257079848166e-06,
+ "loss": 0.4708,
+ "step": 9076
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8845213656468896e-06,
+ "loss": 0.4646,
+ "step": 9077
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.882617545840114e-06,
+ "loss": 0.4648,
+ "step": 9078
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8807142487043047e-06,
+ "loss": 0.4804,
+ "step": 9079
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8788114743792317e-06,
+ "loss": 0.46,
+ "step": 9080
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8769092230046236e-06,
+ "loss": 0.455,
+ "step": 9081
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.875007494720171e-06,
+ "loss": 0.4514,
+ "step": 9082
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8731062896655383e-06,
+ "loss": 0.4745,
+ "step": 9083
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.871205607980335e-06,
+ "loss": 0.4647,
+ "step": 9084
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8693054498041383e-06,
+ "loss": 0.4675,
+ "step": 9085
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.867405815276494e-06,
+ "loss": 0.4572,
+ "step": 9086
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.865506704536899e-06,
+ "loss": 0.4301,
+ "step": 9087
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8636081177248176e-06,
+ "loss": 0.4656,
+ "step": 9088
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.861710054979674e-06,
+ "loss": 0.4682,
+ "step": 9089
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.859812516440853e-06,
+ "loss": 0.4671,
+ "step": 9090
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8579155022477024e-06,
+ "loss": 0.4713,
+ "step": 9091
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.856019012539528e-06,
+ "loss": 0.4732,
+ "step": 9092
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8541230474556035e-06,
+ "loss": 0.4658,
+ "step": 9093
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.852227607135164e-06,
+ "loss": 0.4677,
+ "step": 9094
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.850332691717399e-06,
+ "loss": 0.4676,
+ "step": 9095
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8484383013414627e-06,
+ "loss": 0.4892,
+ "step": 9096
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.846544436146473e-06,
+ "loss": 0.4541,
+ "step": 9097
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8446510962715055e-06,
+ "loss": 0.464,
+ "step": 9098
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8427582818555976e-06,
+ "loss": 0.4755,
+ "step": 9099
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8408659930377556e-06,
+ "loss": 0.4582,
+ "step": 9100
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.838974229956938e-06,
+ "loss": 0.4648,
+ "step": 9101
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.837082992752067e-06,
+ "loss": 0.4542,
+ "step": 9102
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.835192281562027e-06,
+ "loss": 0.4401,
+ "step": 9103
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8333020965256666e-06,
+ "loss": 0.4844,
+ "step": 9104
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8314124377817888e-06,
+ "loss": 0.4815,
+ "step": 9105
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8295233054691685e-06,
+ "loss": 0.479,
+ "step": 9106
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8276346997265324e-06,
+ "loss": 0.4473,
+ "step": 9107
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8257466206925723e-06,
+ "loss": 0.4676,
+ "step": 9108
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.82385906850594e-06,
+ "loss": 0.4612,
+ "step": 9109
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.82197204330525e-06,
+ "loss": 0.4752,
+ "step": 9110
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.820085545229078e-06,
+ "loss": 0.4496,
+ "step": 9111
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8181995744159553e-06,
+ "loss": 0.4537,
+ "step": 9112
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8163141310043886e-06,
+ "loss": 0.4666,
+ "step": 9113
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.81442921513283e-06,
+ "loss": 0.4734,
+ "step": 9114
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.812544826939706e-06,
+ "loss": 0.4739,
+ "step": 9115
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8106609665633943e-06,
+ "loss": 0.4542,
+ "step": 9116
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.808777634142239e-06,
+ "loss": 0.4808,
+ "step": 9117
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8068948298145437e-06,
+ "loss": 0.4737,
+ "step": 9118
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.80501255371857e-06,
+ "loss": 0.453,
+ "step": 9119
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.803130805992552e-06,
+ "loss": 0.4852,
+ "step": 9120
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8012495867746735e-06,
+ "loss": 0.4509,
+ "step": 9121
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.799368896203084e-06,
+ "loss": 0.447,
+ "step": 9122
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7974887344158897e-06,
+ "loss": 0.4753,
+ "step": 9123
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7956091015511676e-06,
+ "loss": 0.4621,
+ "step": 9124
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.793729997746948e-06,
+ "loss": 0.4722,
+ "step": 9125
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.791851423141222e-06,
+ "loss": 0.4903,
+ "step": 9126
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7899733778719483e-06,
+ "loss": 0.4797,
+ "step": 9127
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7880958620770415e-06,
+ "loss": 0.4619,
+ "step": 9128
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7862188758943788e-06,
+ "loss": 0.4626,
+ "step": 9129
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7843424194617964e-06,
+ "loss": 0.4839,
+ "step": 9130
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7824664929170953e-06,
+ "loss": 0.4832,
+ "step": 9131
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7805910963980343e-06,
+ "loss": 0.5038,
+ "step": 9132
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.778716230042333e-06,
+ "loss": 0.4822,
+ "step": 9133
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7768418939876794e-06,
+ "loss": 0.4542,
+ "step": 9134
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7749680883717102e-06,
+ "loss": 0.4602,
+ "step": 9135
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.773094813332037e-06,
+ "loss": 0.4747,
+ "step": 9136
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7712220690062208e-06,
+ "loss": 0.4595,
+ "step": 9137
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.769349855531789e-06,
+ "loss": 0.4627,
+ "step": 9138
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7674781730462273e-06,
+ "loss": 0.4563,
+ "step": 9139
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.765607021686989e-06,
+ "loss": 0.4852,
+ "step": 9140
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7637364015914803e-06,
+ "loss": 0.4463,
+ "step": 9141
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7618663128970722e-06,
+ "loss": 0.4673,
+ "step": 9142
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.759996755741098e-06,
+ "loss": 0.446,
+ "step": 9143
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7581277302608446e-06,
+ "loss": 0.4693,
+ "step": 9144
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7562592365935724e-06,
+ "loss": 0.4751,
+ "step": 9145
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.75439127487649e-06,
+ "loss": 0.4539,
+ "step": 9146
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7525238452467783e-06,
+ "loss": 0.4628,
+ "step": 9147
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7506569478415713e-06,
+ "loss": 0.4756,
+ "step": 9148
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7487905827979654e-06,
+ "loss": 0.4652,
+ "step": 9149
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7469247502530194e-06,
+ "loss": 0.4361,
+ "step": 9150
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.745059450343752e-06,
+ "loss": 0.4724,
+ "step": 9151
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7431946832071433e-06,
+ "loss": 0.4707,
+ "step": 9152
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7413304489801296e-06,
+ "loss": 0.4704,
+ "step": 9153
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7394667477996207e-06,
+ "loss": 0.4542,
+ "step": 9154
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.737603579802471e-06,
+ "loss": 0.4505,
+ "step": 9155
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7357409451255113e-06,
+ "loss": 0.458,
+ "step": 9156
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.733878843905523e-06,
+ "loss": 0.4673,
+ "step": 9157
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7320172762792497e-06,
+ "loss": 0.4914,
+ "step": 9158
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7301562423833985e-06,
+ "loss": 0.4658,
+ "step": 9159
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.728295742354631e-06,
+ "loss": 0.449,
+ "step": 9160
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7264357763295822e-06,
+ "loss": 0.4757,
+ "step": 9161
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7245763444448383e-06,
+ "loss": 0.4689,
+ "step": 9162
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7227174468369454e-06,
+ "loss": 0.4551,
+ "step": 9163
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.720859083642415e-06,
+ "loss": 0.4712,
+ "step": 9164
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7190012549977153e-06,
+ "loss": 0.4821,
+ "step": 9165
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7171439610392815e-06,
+ "loss": 0.4558,
+ "step": 9166
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7152872019035005e-06,
+ "loss": 0.4696,
+ "step": 9167
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7134309777267307e-06,
+ "loss": 0.4633,
+ "step": 9168
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.711575288645284e-06,
+ "loss": 0.4628,
+ "step": 9169
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7097201347954318e-06,
+ "loss": 0.466,
+ "step": 9170
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7078655163134117e-06,
+ "loss": 0.4747,
+ "step": 9171
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.706011433335417e-06,
+ "loss": 0.4617,
+ "step": 9172
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.704157885997605e-06,
+ "loss": 0.4672,
+ "step": 9173
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.702304874436089e-06,
+ "loss": 0.453,
+ "step": 9174
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7004523987869526e-06,
+ "loss": 0.4688,
+ "step": 9175
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.698600459186228e-06,
+ "loss": 0.4595,
+ "step": 9176
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6967490557699196e-06,
+ "loss": 0.4421,
+ "step": 9177
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6948981886739846e-06,
+ "loss": 0.4677,
+ "step": 9178
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.693047858034342e-06,
+ "loss": 0.4797,
+ "step": 9179
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6911980639868696e-06,
+ "loss": 0.4518,
+ "step": 9180
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6893488066674154e-06,
+ "loss": 0.4681,
+ "step": 9181
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.687500086211777e-06,
+ "loss": 0.4684,
+ "step": 9182
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.685651902755717e-06,
+ "loss": 0.465,
+ "step": 9183
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6838042564349597e-06,
+ "loss": 0.4633,
+ "step": 9184
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6819571473851836e-06,
+ "loss": 0.4565,
+ "step": 9185
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6801105757420397e-06,
+ "loss": 0.4577,
+ "step": 9186
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6782645416411267e-06,
+ "loss": 0.4726,
+ "step": 9187
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.676419045218016e-06,
+ "loss": 0.4555,
+ "step": 9188
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.674574086608228e-06,
+ "loss": 0.4847,
+ "step": 9189
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.672729665947251e-06,
+ "loss": 0.4464,
+ "step": 9190
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6708857833705315e-06,
+ "loss": 0.4601,
+ "step": 9191
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.669042439013476e-06,
+ "loss": 0.4795,
+ "step": 9192
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6671996330114514e-06,
+ "loss": 0.4571,
+ "step": 9193
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6653573654997835e-06,
+ "loss": 0.4686,
+ "step": 9194
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6635156366137672e-06,
+ "loss": 0.4599,
+ "step": 9195
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6616744464886437e-06,
+ "loss": 0.4802,
+ "step": 9196
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.65983379525963e-06,
+ "loss": 0.4669,
+ "step": 9197
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6579936830618926e-06,
+ "loss": 0.4458,
+ "step": 9198
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.656154110030561e-06,
+ "loss": 0.466,
+ "step": 9199
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6543150763007265e-06,
+ "loss": 0.4608,
+ "step": 9200
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.652476582007436e-06,
+ "loss": 0.4676,
+ "step": 9201
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6506386272857086e-06,
+ "loss": 0.4696,
+ "step": 9202
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.648801212270512e-06,
+ "loss": 0.463,
+ "step": 9203
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.646964337096778e-06,
+ "loss": 0.4484,
+ "step": 9204
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6451280018993996e-06,
+ "loss": 0.4569,
+ "step": 9205
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.643292206813227e-06,
+ "loss": 0.4825,
+ "step": 9206
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6414569519730793e-06,
+ "loss": 0.4526,
+ "step": 9207
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6396222375137227e-06,
+ "loss": 0.4555,
+ "step": 9208
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6377880635698973e-06,
+ "loss": 0.4824,
+ "step": 9209
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.635954430276296e-06,
+ "loss": 0.4683,
+ "step": 9210
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.634121337767571e-06,
+ "loss": 0.4648,
+ "step": 9211
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6322887861783385e-06,
+ "loss": 0.4767,
+ "step": 9212
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.630456775643173e-06,
+ "loss": 0.4557,
+ "step": 9213
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6286253062966096e-06,
+ "loss": 0.4721,
+ "step": 9214
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6267943782731407e-06,
+ "loss": 0.4695,
+ "step": 9215
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.624963991707228e-06,
+ "loss": 0.4559,
+ "step": 9216
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6231341467332827e-06,
+ "loss": 0.477,
+ "step": 9217
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6213048434856846e-06,
+ "loss": 0.4626,
+ "step": 9218
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.61947608209877e-06,
+ "loss": 0.4592,
+ "step": 9219
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6176478627068324e-06,
+ "loss": 0.5004,
+ "step": 9220
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.615820185444128e-06,
+ "loss": 0.488,
+ "step": 9221
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6139930504448785e-06,
+ "loss": 0.4704,
+ "step": 9222
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6121664578432593e-06,
+ "loss": 0.4755,
+ "step": 9223
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6103404077734075e-06,
+ "loss": 0.4581,
+ "step": 9224
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.60851490036942e-06,
+ "loss": 0.4553,
+ "step": 9225
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.606689935765351e-06,
+ "loss": 0.4777,
+ "step": 9226
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.604865514095225e-06,
+ "loss": 0.4676,
+ "step": 9227
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6030416354930154e-06,
+ "loss": 0.4463,
+ "step": 9228
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6012183000926638e-06,
+ "loss": 0.4546,
+ "step": 9229
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5993955080280663e-06,
+ "loss": 0.483,
+ "step": 9230
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5975732594330816e-06,
+ "loss": 0.4715,
+ "step": 9231
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.595751554441527e-06,
+ "loss": 0.4556,
+ "step": 9232
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5939303931871827e-06,
+ "loss": 0.4788,
+ "step": 9233
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.592109775803785e-06,
+ "loss": 0.4724,
+ "step": 9234
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.590289702425032e-06,
+ "loss": 0.4611,
+ "step": 9235
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5884701731845862e-06,
+ "loss": 0.4714,
+ "step": 9236
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5866511882160604e-06,
+ "loss": 0.4642,
+ "step": 9237
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.584832747653041e-06,
+ "loss": 0.4718,
+ "step": 9238
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.583014851629062e-06,
+ "loss": 0.4696,
+ "step": 9239
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5811975002776233e-06,
+ "loss": 0.4488,
+ "step": 9240
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.579380693732183e-06,
+ "loss": 0.4678,
+ "step": 9241
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.577564432126156e-06,
+ "loss": 0.4598,
+ "step": 9242
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5757487155929285e-06,
+ "loss": 0.482,
+ "step": 9243
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.573933544265835e-06,
+ "loss": 0.4572,
+ "step": 9244
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.572118918278176e-06,
+ "loss": 0.4634,
+ "step": 9245
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.570304837763208e-06,
+ "loss": 0.4784,
+ "step": 9246
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.568491302854147e-06,
+ "loss": 0.458,
+ "step": 9247
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5666783136841777e-06,
+ "loss": 0.4777,
+ "step": 9248
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.564865870386433e-06,
+ "loss": 0.4558,
+ "step": 9249
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5630539730940163e-06,
+ "loss": 0.4666,
+ "step": 9250
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5612426219399834e-06,
+ "loss": 0.4487,
+ "step": 9251
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5594318170573527e-06,
+ "loss": 0.4581,
+ "step": 9252
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5576215585791007e-06,
+ "loss": 0.4659,
+ "step": 9253
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5558118466381675e-06,
+ "loss": 0.4502,
+ "step": 9254
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5540026813674458e-06,
+ "loss": 0.4941,
+ "step": 9255
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5521940628998e-06,
+ "loss": 0.4728,
+ "step": 9256
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.550385991368044e-06,
+ "loss": 0.4579,
+ "step": 9257
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.548578466904953e-06,
+ "loss": 0.4819,
+ "step": 9258
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5467714896432704e-06,
+ "loss": 0.4623,
+ "step": 9259
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5449650597156884e-06,
+ "loss": 0.4512,
+ "step": 9260
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5431591772548647e-06,
+ "loss": 0.469,
+ "step": 9261
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5413538423934125e-06,
+ "loss": 0.4628,
+ "step": 9262
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5395490552639145e-06,
+ "loss": 0.4641,
+ "step": 9263
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5377448159989037e-06,
+ "loss": 0.458,
+ "step": 9264
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5359411247308753e-06,
+ "loss": 0.4823,
+ "step": 9265
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5341379815922853e-06,
+ "loss": 0.467,
+ "step": 9266
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5323353867155465e-06,
+ "loss": 0.4686,
+ "step": 9267
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.53053334023304e-06,
+ "loss": 0.4559,
+ "step": 9268
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5287318422770934e-06,
+ "loss": 0.4608,
+ "step": 9269
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5269308929800084e-06,
+ "loss": 0.4619,
+ "step": 9270
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.525130492474035e-06,
+ "loss": 0.4805,
+ "step": 9271
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.523330640891388e-06,
+ "loss": 0.4584,
+ "step": 9272
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5215313383642414e-06,
+ "loss": 0.4771,
+ "step": 9273
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.519732585024729e-06,
+ "loss": 0.4555,
+ "step": 9274
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5179343810049418e-06,
+ "loss": 0.466,
+ "step": 9275
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5161367264369296e-06,
+ "loss": 0.4694,
+ "step": 9276
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5143396214527127e-06,
+ "loss": 0.4603,
+ "step": 9277
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5125430661842587e-06,
+ "loss": 0.4644,
+ "step": 9278
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5107470607634956e-06,
+ "loss": 0.4647,
+ "step": 9279
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5089516053223216e-06,
+ "loss": 0.4704,
+ "step": 9280
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5071566999925833e-06,
+ "loss": 0.4869,
+ "step": 9281
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5053623449060927e-06,
+ "loss": 0.4826,
+ "step": 9282
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5035685401946163e-06,
+ "loss": 0.4694,
+ "step": 9283
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5017752859898892e-06,
+ "loss": 0.4598,
+ "step": 9284
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.499982582423597e-06,
+ "loss": 0.4522,
+ "step": 9285
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4981904296273884e-06,
+ "loss": 0.4609,
+ "step": 9286
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4963988277328733e-06,
+ "loss": 0.4702,
+ "step": 9287
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.494607776871616e-06,
+ "loss": 0.4667,
+ "step": 9288
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.492817277175148e-06,
+ "loss": 0.4737,
+ "step": 9289
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.491027328774952e-06,
+ "loss": 0.4664,
+ "step": 9290
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4892379318024806e-06,
+ "loss": 0.4345,
+ "step": 9291
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4874490863891355e-06,
+ "loss": 0.4877,
+ "step": 9292
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.485660792666281e-06,
+ "loss": 0.4726,
+ "step": 9293
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4838730507652455e-06,
+ "loss": 0.4508,
+ "step": 9294
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.482085860817309e-06,
+ "loss": 0.4623,
+ "step": 9295
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.480299222953716e-06,
+ "loss": 0.4561,
+ "step": 9296
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.478513137305675e-06,
+ "loss": 0.4565,
+ "step": 9297
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4767276040043433e-06,
+ "loss": 0.4553,
+ "step": 9298
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4749426231808427e-06,
+ "loss": 0.4781,
+ "step": 9299
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4731581949662597e-06,
+ "loss": 0.4629,
+ "step": 9300
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4713743194916318e-06,
+ "loss": 0.4546,
+ "step": 9301
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4695909968879607e-06,
+ "loss": 0.466,
+ "step": 9302
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4678082272862025e-06,
+ "loss": 0.4552,
+ "step": 9303
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4660260108172816e-06,
+ "loss": 0.4513,
+ "step": 9304
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4642443476120746e-06,
+ "loss": 0.4539,
+ "step": 9305
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.462463237801419e-06,
+ "loss": 0.4682,
+ "step": 9306
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.460682681516112e-06,
+ "loss": 0.453,
+ "step": 9307
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4589026788869117e-06,
+ "loss": 0.4768,
+ "step": 9308
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4571232300445293e-06,
+ "loss": 0.4839,
+ "step": 9309
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4553443351196426e-06,
+ "loss": 0.4596,
+ "step": 9310
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.453565994242891e-06,
+ "loss": 0.4595,
+ "step": 9311
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4517882075448663e-06,
+ "loss": 0.4475,
+ "step": 9312
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4500109751561187e-06,
+ "loss": 0.4539,
+ "step": 9313
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4482342972071626e-06,
+ "loss": 0.4622,
+ "step": 9314
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.44645817382847e-06,
+ "loss": 0.4861,
+ "step": 9315
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.444682605150471e-06,
+ "loss": 0.4707,
+ "step": 9316
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.442907591303554e-06,
+ "loss": 0.479,
+ "step": 9317
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.441133132418073e-06,
+ "loss": 0.4697,
+ "step": 9318
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4393592286243363e-06,
+ "loss": 0.4657,
+ "step": 9319
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4375858800526077e-06,
+ "loss": 0.4666,
+ "step": 9320
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.43581308683312e-06,
+ "loss": 0.4637,
+ "step": 9321
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4340408490960575e-06,
+ "loss": 0.4706,
+ "step": 9322
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.432269166971567e-06,
+ "loss": 0.4753,
+ "step": 9323
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4304980405897483e-06,
+ "loss": 0.4751,
+ "step": 9324
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4287274700806727e-06,
+ "loss": 0.4541,
+ "step": 9325
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.42695745557436e-06,
+ "loss": 0.4487,
+ "step": 9326
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4251879972007943e-06,
+ "loss": 0.4575,
+ "step": 9327
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.423419095089915e-06,
+ "loss": 0.4677,
+ "step": 9328
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4216507493716213e-06,
+ "loss": 0.4627,
+ "step": 9329
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4198829601757787e-06,
+ "loss": 0.4684,
+ "step": 9330
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.418115727632201e-06,
+ "loss": 0.4892,
+ "step": 9331
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4163490518706713e-06,
+ "loss": 0.4636,
+ "step": 9332
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.414582933020924e-06,
+ "loss": 0.459,
+ "step": 9333
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.412817371212657e-06,
+ "loss": 0.4632,
+ "step": 9334
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4110523665755236e-06,
+ "loss": 0.4559,
+ "step": 9335
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4092879192391406e-06,
+ "loss": 0.4697,
+ "step": 9336
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.407524029333077e-06,
+ "loss": 0.4719,
+ "step": 9337
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.405760696986873e-06,
+ "loss": 0.4609,
+ "step": 9338
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.403997922330016e-06,
+ "loss": 0.4663,
+ "step": 9339
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4022357054919545e-06,
+ "loss": 0.4537,
+ "step": 9340
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4004740466021047e-06,
+ "loss": 0.4711,
+ "step": 9341
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.398712945789832e-06,
+ "loss": 0.4591,
+ "step": 9342
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3969524031844638e-06,
+ "loss": 0.4759,
+ "step": 9343
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3951924189152854e-06,
+ "loss": 0.4557,
+ "step": 9344
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3934329931115474e-06,
+ "loss": 0.4759,
+ "step": 9345
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.391674125902452e-06,
+ "loss": 0.4565,
+ "step": 9346
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3899158174171644e-06,
+ "loss": 0.4823,
+ "step": 9347
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.388158067784806e-06,
+ "loss": 0.4724,
+ "step": 9348
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3864008771344595e-06,
+ "loss": 0.4682,
+ "step": 9349
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3846442455951612e-06,
+ "loss": 0.4776,
+ "step": 9350
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3828881732959163e-06,
+ "loss": 0.4587,
+ "step": 9351
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.381132660365684e-06,
+ "loss": 0.4814,
+ "step": 9352
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.37937770693338e-06,
+ "loss": 0.4737,
+ "step": 9353
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3776233131278805e-06,
+ "loss": 0.447,
+ "step": 9354
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3758694790780214e-06,
+ "loss": 0.4658,
+ "step": 9355
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3741162049125964e-06,
+ "loss": 0.4719,
+ "step": 9356
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.372363490760359e-06,
+ "loss": 0.4448,
+ "step": 9357
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3706113367500183e-06,
+ "loss": 0.4582,
+ "step": 9358
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.36885974301025e-06,
+ "loss": 0.4683,
+ "step": 9359
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.367108709669683e-06,
+ "loss": 0.4571,
+ "step": 9360
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3653582368569017e-06,
+ "loss": 0.4503,
+ "step": 9361
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3636083247004592e-06,
+ "loss": 0.4537,
+ "step": 9362
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3618589733288588e-06,
+ "loss": 0.4668,
+ "step": 9363
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3601101828705664e-06,
+ "loss": 0.4526,
+ "step": 9364
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.358361953454004e-06,
+ "loss": 0.478,
+ "step": 9365
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.356614285207557e-06,
+ "loss": 0.4649,
+ "step": 9366
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3548671782595655e-06,
+ "loss": 0.4418,
+ "step": 9367
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3531206327383305e-06,
+ "loss": 0.4629,
+ "step": 9368
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.35137464877211e-06,
+ "loss": 0.4576,
+ "step": 9369
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3496292264891194e-06,
+ "loss": 0.4573,
+ "step": 9370
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3478843660175423e-06,
+ "loss": 0.4696,
+ "step": 9371
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.346140067485506e-06,
+ "loss": 0.4837,
+ "step": 9372
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3443963310211105e-06,
+ "loss": 0.476,
+ "step": 9373
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.342653156752408e-06,
+ "loss": 0.4577,
+ "step": 9374
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3409105448074067e-06,
+ "loss": 0.4761,
+ "step": 9375
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.339168495314079e-06,
+ "loss": 0.4755,
+ "step": 9376
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3374270084003535e-06,
+ "loss": 0.4652,
+ "step": 9377
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3356860841941152e-06,
+ "loss": 0.4781,
+ "step": 9378
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3339457228232142e-06,
+ "loss": 0.4703,
+ "step": 9379
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.332205924415455e-06,
+ "loss": 0.4699,
+ "step": 9380
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.330466689098596e-06,
+ "loss": 0.4769,
+ "step": 9381
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.328728017000367e-06,
+ "loss": 0.47,
+ "step": 9382
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3269899082484447e-06,
+ "loss": 0.4821,
+ "step": 9383
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.325252362970469e-06,
+ "loss": 0.4785,
+ "step": 9384
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3235153812940357e-06,
+ "loss": 0.4489,
+ "step": 9385
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.321778963346707e-06,
+ "loss": 0.4619,
+ "step": 9386
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3200431092559948e-06,
+ "loss": 0.4659,
+ "step": 9387
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3183078191493734e-06,
+ "loss": 0.4701,
+ "step": 9388
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3165730931542753e-06,
+ "loss": 0.4658,
+ "step": 9389
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3148389313980912e-06,
+ "loss": 0.4866,
+ "step": 9390
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3131053340081675e-06,
+ "loss": 0.4773,
+ "step": 9391
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3113723011118196e-06,
+ "loss": 0.4558,
+ "step": 9392
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3096398328363078e-06,
+ "loss": 0.4641,
+ "step": 9393
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3079079293088623e-06,
+ "loss": 0.4733,
+ "step": 9394
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3061765906566644e-06,
+ "loss": 0.4505,
+ "step": 9395
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.304445817006857e-06,
+ "loss": 0.4527,
+ "step": 9396
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.302715608486541e-06,
+ "loss": 0.4698,
+ "step": 9397
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.300985965222775e-06,
+ "loss": 0.4587,
+ "step": 9398
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2992568873425746e-06,
+ "loss": 0.4571,
+ "step": 9399
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2975283749729205e-06,
+ "loss": 0.4801,
+ "step": 9400
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2958004282407466e-06,
+ "loss": 0.464,
+ "step": 9401
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2940730472729423e-06,
+ "loss": 0.4576,
+ "step": 9402
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.292346232196364e-06,
+ "loss": 0.468,
+ "step": 9403
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2906199831378194e-06,
+ "loss": 0.4632,
+ "step": 9404
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.288894300224076e-06,
+ "loss": 0.4746,
+ "step": 9405
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2871691835818642e-06,
+ "loss": 0.4696,
+ "step": 9406
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.285444633337869e-06,
+ "loss": 0.4789,
+ "step": 9407
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2837206496187314e-06,
+ "loss": 0.4654,
+ "step": 9408
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.281997232551055e-06,
+ "loss": 0.4687,
+ "step": 9409
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2802743822614003e-06,
+ "loss": 0.4548,
+ "step": 9410
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2785520988762833e-06,
+ "loss": 0.4527,
+ "step": 9411
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.276830382522187e-06,
+ "loss": 0.4528,
+ "step": 9412
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.275109233325542e-06,
+ "loss": 0.4684,
+ "step": 9413
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2733886514127466e-06,
+ "loss": 0.4661,
+ "step": 9414
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2716686369101525e-06,
+ "loss": 0.4706,
+ "step": 9415
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2699491899440683e-06,
+ "loss": 0.4721,
+ "step": 9416
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2682303106407645e-06,
+ "loss": 0.4519,
+ "step": 9417
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2665119991264673e-06,
+ "loss": 0.4758,
+ "step": 9418
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2647942555273592e-06,
+ "loss": 0.4432,
+ "step": 9419
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2630770799695922e-06,
+ "loss": 0.4654,
+ "step": 9420
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2613604725792636e-06,
+ "loss": 0.4654,
+ "step": 9421
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.259644433482434e-06,
+ "loss": 0.4582,
+ "step": 9422
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2579289628051203e-06,
+ "loss": 0.4455,
+ "step": 9423
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.256214060673305e-06,
+ "loss": 0.4711,
+ "step": 9424
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2544997272129197e-06,
+ "loss": 0.4694,
+ "step": 9425
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.252785962549856e-06,
+ "loss": 0.4452,
+ "step": 9426
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2510727668099706e-06,
+ "loss": 0.4767,
+ "step": 9427
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2493601401190723e-06,
+ "loss": 0.4607,
+ "step": 9428
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.247648082602927e-06,
+ "loss": 0.4478,
+ "step": 9429
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2459365943872613e-06,
+ "loss": 0.4754,
+ "step": 9430
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.244225675597761e-06,
+ "loss": 0.4856,
+ "step": 9431
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.242515326360066e-06,
+ "loss": 0.4694,
+ "step": 9432
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2408055467997823e-06,
+ "loss": 0.4513,
+ "step": 9433
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2390963370424635e-06,
+ "loss": 0.4721,
+ "step": 9434
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.237387697213632e-06,
+ "loss": 0.4726,
+ "step": 9435
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2356796274387617e-06,
+ "loss": 0.4632,
+ "step": 9436
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2339721278432847e-06,
+ "loss": 0.4877,
+ "step": 9437
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2322651985525932e-06,
+ "loss": 0.4796,
+ "step": 9438
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2305588396920375e-06,
+ "loss": 0.4482,
+ "step": 9439
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.228853051386922e-06,
+ "loss": 0.4621,
+ "step": 9440
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.22714783376252e-06,
+ "loss": 0.4697,
+ "step": 9441
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2254431869440496e-06,
+ "loss": 0.4766,
+ "step": 9442
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.223739111056692e-06,
+ "loss": 0.4686,
+ "step": 9443
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.222035606225593e-06,
+ "loss": 0.46,
+ "step": 9444
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.220332672575849e-06,
+ "loss": 0.4642,
+ "step": 9445
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2186303102325125e-06,
+ "loss": 0.4591,
+ "step": 9446
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2169285193206038e-06,
+ "loss": 0.4726,
+ "step": 9447
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2152272999650916e-06,
+ "loss": 0.4684,
+ "step": 9448
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2135266522909073e-06,
+ "loss": 0.491,
+ "step": 9449
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2118265764229396e-06,
+ "loss": 0.4728,
+ "step": 9450
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2101270724860345e-06,
+ "loss": 0.4598,
+ "step": 9451
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2084281406049966e-06,
+ "loss": 0.4708,
+ "step": 9452
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2067297809045863e-06,
+ "loss": 0.4778,
+ "step": 9453
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2050319935095254e-06,
+ "loss": 0.4637,
+ "step": 9454
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.203334778544497e-06,
+ "loss": 0.4553,
+ "step": 9455
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.201638136134132e-06,
+ "loss": 0.4488,
+ "step": 9456
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.199942066403028e-06,
+ "loss": 0.4643,
+ "step": 9457
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.198246569475735e-06,
+ "loss": 0.4453,
+ "step": 9458
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1965516454767645e-06,
+ "loss": 0.4703,
+ "step": 9459
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1948572945305813e-06,
+ "loss": 0.4579,
+ "step": 9460
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.193163516761617e-06,
+ "loss": 0.4486,
+ "step": 9461
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1914703122942525e-06,
+ "loss": 0.4719,
+ "step": 9462
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1897776812528317e-06,
+ "loss": 0.4651,
+ "step": 9463
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.188085623761649e-06,
+ "loss": 0.4757,
+ "step": 9464
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1863941399449685e-06,
+ "loss": 0.4875,
+ "step": 9465
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1847032299270032e-06,
+ "loss": 0.4704,
+ "step": 9466
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1830128938319238e-06,
+ "loss": 0.455,
+ "step": 9467
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1813231317838667e-06,
+ "loss": 0.4656,
+ "step": 9468
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.179633943906918e-06,
+ "loss": 0.454,
+ "step": 9469
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1779453303251262e-06,
+ "loss": 0.4647,
+ "step": 9470
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.176257291162495e-06,
+ "loss": 0.4512,
+ "step": 9471
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.174569826542986e-06,
+ "loss": 0.473,
+ "step": 9472
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.172882936590518e-06,
+ "loss": 0.4463,
+ "step": 9473
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1711966214289747e-06,
+ "loss": 0.4627,
+ "step": 9474
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1695108811821863e-06,
+ "loss": 0.4592,
+ "step": 9475
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1678257159739524e-06,
+ "loss": 0.4872,
+ "step": 9476
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1661411259280206e-06,
+ "loss": 0.4719,
+ "step": 9477
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1644571111681023e-06,
+ "loss": 0.4569,
+ "step": 9478
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1627736718178626e-06,
+ "loss": 0.4524,
+ "step": 9479
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.161090808000924e-06,
+ "loss": 0.4584,
+ "step": 9480
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1594085198408756e-06,
+ "loss": 0.4599,
+ "step": 9481
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1577268074612535e-06,
+ "loss": 0.4763,
+ "step": 9482
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.156045670985556e-06,
+ "loss": 0.4584,
+ "step": 9483
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1543651105372352e-06,
+ "loss": 0.4735,
+ "step": 9484
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.152685126239713e-06,
+ "loss": 0.4688,
+ "step": 9485
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1510057182163547e-06,
+ "loss": 0.4492,
+ "step": 9486
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1493268865904872e-06,
+ "loss": 0.4916,
+ "step": 9487
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1476486314854027e-06,
+ "loss": 0.4659,
+ "step": 9488
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1459709530243423e-06,
+ "loss": 0.4438,
+ "step": 9489
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.144293851330508e-06,
+ "loss": 0.4826,
+ "step": 9490
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1426173265270578e-06,
+ "loss": 0.4829,
+ "step": 9491
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1409413787371114e-06,
+ "loss": 0.4722,
+ "step": 9492
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.13926600808374e-06,
+ "loss": 0.4796,
+ "step": 9493
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1375912146899767e-06,
+ "loss": 0.4647,
+ "step": 9494
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.135916998678812e-06,
+ "loss": 0.4497,
+ "step": 9495
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.134243360173196e-06,
+ "loss": 0.4972,
+ "step": 9496
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1325702992960317e-06,
+ "loss": 0.4788,
+ "step": 9497
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.130897816170181e-06,
+ "loss": 0.4516,
+ "step": 9498
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1292259109184654e-06,
+ "loss": 0.4556,
+ "step": 9499
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1275545836636625e-06,
+ "loss": 0.4519,
+ "step": 9500
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1258838345285027e-06,
+ "loss": 0.4905,
+ "step": 9501
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.124213663635687e-06,
+ "loss": 0.4682,
+ "step": 9502
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1225440711078615e-06,
+ "loss": 0.4862,
+ "step": 9503
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.120875057067635e-06,
+ "loss": 0.4761,
+ "step": 9504
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1192066216375695e-06,
+ "loss": 0.4625,
+ "step": 9505
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1175387649401935e-06,
+ "loss": 0.4456,
+ "step": 9506
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1158714870979856e-06,
+ "loss": 0.4596,
+ "step": 9507
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.114204788233379e-06,
+ "loss": 0.4775,
+ "step": 9508
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1125386684687774e-06,
+ "loss": 0.4652,
+ "step": 9509
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.110873127926529e-06,
+ "loss": 0.4516,
+ "step": 9510
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1092081667289454e-06,
+ "loss": 0.4667,
+ "step": 9511
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1075437849982937e-06,
+ "loss": 0.4646,
+ "step": 9512
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.105879982856799e-06,
+ "loss": 0.473,
+ "step": 9513
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1042167604266415e-06,
+ "loss": 0.4532,
+ "step": 9514
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.102554117829967e-06,
+ "loss": 0.4778,
+ "step": 9515
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.100892055188867e-06,
+ "loss": 0.4789,
+ "step": 9516
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0992305726254026e-06,
+ "loss": 0.4668,
+ "step": 9517
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0975696702615823e-06,
+ "loss": 0.483,
+ "step": 9518
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0959093482193783e-06,
+ "loss": 0.4624,
+ "step": 9519
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.094249606620715e-06,
+ "loss": 0.4581,
+ "step": 9520
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.092590445587476e-06,
+ "loss": 0.4768,
+ "step": 9521
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0909318652415078e-06,
+ "loss": 0.4691,
+ "step": 9522
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0892738657046065e-06,
+ "loss": 0.4657,
+ "step": 9523
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0876164470985305e-06,
+ "loss": 0.4549,
+ "step": 9524
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0859596095449886e-06,
+ "loss": 0.4605,
+ "step": 9525
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0843033531656596e-06,
+ "loss": 0.4536,
+ "step": 9526
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0826476780821683e-06,
+ "loss": 0.4656,
+ "step": 9527
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.080992584416097e-06,
+ "loss": 0.4637,
+ "step": 9528
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.079338072288997e-06,
+ "loss": 0.4756,
+ "step": 9529
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0776841418223635e-06,
+ "loss": 0.4659,
+ "step": 9530
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0760307931376555e-06,
+ "loss": 0.4654,
+ "step": 9531
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0743780263562884e-06,
+ "loss": 0.4624,
+ "step": 9532
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0727258415996334e-06,
+ "loss": 0.4591,
+ "step": 9533
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0710742389890205e-06,
+ "loss": 0.4664,
+ "step": 9534
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.069423218645734e-06,
+ "loss": 0.4513,
+ "step": 9535
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.067772780691023e-06,
+ "loss": 0.4584,
+ "step": 9536
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0661229252460835e-06,
+ "loss": 0.4804,
+ "step": 9537
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.064473652432081e-06,
+ "loss": 0.4685,
+ "step": 9538
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0628249623701255e-06,
+ "loss": 0.457,
+ "step": 9539
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.061176855181293e-06,
+ "loss": 0.4696,
+ "step": 9540
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0595293309866107e-06,
+ "loss": 0.4725,
+ "step": 9541
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0578823899070653e-06,
+ "loss": 0.4579,
+ "step": 9542
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0562360320636064e-06,
+ "loss": 0.4803,
+ "step": 9543
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0545902575771326e-06,
+ "loss": 0.4821,
+ "step": 9544
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0529450665685023e-06,
+ "loss": 0.4638,
+ "step": 9545
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0513004591585305e-06,
+ "loss": 0.4593,
+ "step": 9546
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.049656435467994e-06,
+ "loss": 0.473,
+ "step": 9547
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.04801299561762e-06,
+ "loss": 0.4585,
+ "step": 9548
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0463701397280953e-06,
+ "loss": 0.4658,
+ "step": 9549
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0447278679200676e-06,
+ "loss": 0.4673,
+ "step": 9550
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0430861803141377e-06,
+ "loss": 0.4683,
+ "step": 9551
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0414450770308638e-06,
+ "loss": 0.4636,
+ "step": 9552
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.03980455819076e-06,
+ "loss": 0.4777,
+ "step": 9553
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0381646239143017e-06,
+ "loss": 0.453,
+ "step": 9554
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0365252743219143e-06,
+ "loss": 0.4474,
+ "step": 9555
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.034886509533991e-06,
+ "loss": 0.4671,
+ "step": 9556
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0332483296708693e-06,
+ "loss": 0.4719,
+ "step": 9557
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.031610734852858e-06,
+ "loss": 0.4555,
+ "step": 9558
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.029973725200212e-06,
+ "loss": 0.4698,
+ "step": 9559
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.028337300833144e-06,
+ "loss": 0.4783,
+ "step": 9560
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0267014618718295e-06,
+ "loss": 0.4447,
+ "step": 9561
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0250662084363928e-06,
+ "loss": 0.4752,
+ "step": 9562
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.023431540646926e-06,
+ "loss": 0.4757,
+ "step": 9563
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.02179745862347e-06,
+ "loss": 0.4496,
+ "step": 9564
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0201639624860246e-06,
+ "loss": 0.4651,
+ "step": 9565
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0185310523545475e-06,
+ "loss": 0.4539,
+ "step": 9566
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0168987283489494e-06,
+ "loss": 0.4631,
+ "step": 9567
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0152669905891075e-06,
+ "loss": 0.4478,
+ "step": 9568
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.013635839194844e-06,
+ "loss": 0.4758,
+ "step": 9569
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0120052742859497e-06,
+ "loss": 0.4786,
+ "step": 9570
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.010375295982163e-06,
+ "loss": 0.4593,
+ "step": 9571
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0087459044031843e-06,
+ "loss": 0.466,
+ "step": 9572
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0071170996686674e-06,
+ "loss": 0.4639,
+ "step": 9573
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0054888818982254e-06,
+ "loss": 0.4788,
+ "step": 9574
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0038612512114285e-06,
+ "loss": 0.4549,
+ "step": 9575
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0022342077278014e-06,
+ "loss": 0.454,
+ "step": 9576
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.00060775156683e-06,
+ "loss": 0.4759,
+ "step": 9577
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.998981882847951e-06,
+ "loss": 0.4794,
+ "step": 9578
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9973566016905666e-06,
+ "loss": 0.4785,
+ "step": 9579
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.995731908214028e-06,
+ "loss": 0.4464,
+ "step": 9580
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.994107802537646e-06,
+ "loss": 0.4696,
+ "step": 9581
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9924842847806867e-06,
+ "loss": 0.4567,
+ "step": 9582
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9908613550623746e-06,
+ "loss": 0.4601,
+ "step": 9583
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9892390135018945e-06,
+ "loss": 0.4741,
+ "step": 9584
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.987617260218382e-06,
+ "loss": 0.4543,
+ "step": 9585
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.985996095330931e-06,
+ "loss": 0.4632,
+ "step": 9586
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.984375518958592e-06,
+ "loss": 0.4491,
+ "step": 9587
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9827555312203785e-06,
+ "loss": 0.4767,
+ "step": 9588
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9811361322352517e-06,
+ "loss": 0.473,
+ "step": 9589
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9795173221221318e-06,
+ "loss": 0.4599,
+ "step": 9590
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9778991009999036e-06,
+ "loss": 0.482,
+ "step": 9591
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9762814689873987e-06,
+ "loss": 0.4809,
+ "step": 9592
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.974664426203409e-06,
+ "loss": 0.4695,
+ "step": 9593
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.973047972766684e-06,
+ "loss": 0.4676,
+ "step": 9594
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9714321087959296e-06,
+ "loss": 0.4593,
+ "step": 9595
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9698168344098056e-06,
+ "loss": 0.4615,
+ "step": 9596
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9682021497269357e-06,
+ "loss": 0.4768,
+ "step": 9597
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9665880548658888e-06,
+ "loss": 0.457,
+ "step": 9598
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9649745499452067e-06,
+ "loss": 0.4568,
+ "step": 9599
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9633616350833717e-06,
+ "loss": 0.4788,
+ "step": 9600
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.961749310398833e-06,
+ "loss": 0.4911,
+ "step": 9601
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9601375760099895e-06,
+ "loss": 0.4736,
+ "step": 9602
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9585264320352003e-06,
+ "loss": 0.464,
+ "step": 9603
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9569158785927867e-06,
+ "loss": 0.4649,
+ "step": 9604
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.955305915801016e-06,
+ "loss": 0.4484,
+ "step": 9605
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9536965437781186e-06,
+ "loss": 0.4635,
+ "step": 9606
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9520877626422794e-06,
+ "loss": 0.4572,
+ "step": 9607
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.95047957251164e-06,
+ "loss": 0.4729,
+ "step": 9608
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9488719735043018e-06,
+ "loss": 0.4615,
+ "step": 9609
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9472649657383157e-06,
+ "loss": 0.4654,
+ "step": 9610
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9456585493317004e-06,
+ "loss": 0.4707,
+ "step": 9611
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.94405272440242e-06,
+ "loss": 0.4773,
+ "step": 9612
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.942447491068401e-06,
+ "loss": 0.4667,
+ "step": 9613
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.940842849447524e-06,
+ "loss": 0.4603,
+ "step": 9614
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9392387996576277e-06,
+ "loss": 0.4447,
+ "step": 9615
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.937635341816506e-06,
+ "loss": 0.4665,
+ "step": 9616
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9360324760419093e-06,
+ "loss": 0.4667,
+ "step": 9617
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.934430202451549e-06,
+ "loss": 0.454,
+ "step": 9618
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9328285211630847e-06,
+ "loss": 0.4657,
+ "step": 9619
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9312274322941426e-06,
+ "loss": 0.4621,
+ "step": 9620
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9296269359622977e-06,
+ "loss": 0.457,
+ "step": 9621
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9280270322850836e-06,
+ "loss": 0.4572,
+ "step": 9622
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.92642772137999e-06,
+ "loss": 0.4614,
+ "step": 9623
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9248290033644614e-06,
+ "loss": 0.4545,
+ "step": 9624
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9232308783559064e-06,
+ "loss": 0.4749,
+ "step": 9625
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9216333464716817e-06,
+ "loss": 0.4872,
+ "step": 9626
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9200364078291032e-06,
+ "loss": 0.4565,
+ "step": 9627
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9184400625454413e-06,
+ "loss": 0.4787,
+ "step": 9628
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.916844310737931e-06,
+ "loss": 0.4553,
+ "step": 9629
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9152491525237504e-06,
+ "loss": 0.4542,
+ "step": 9630
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9136545880200484e-06,
+ "loss": 0.4756,
+ "step": 9631
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.912060617343919e-06,
+ "loss": 0.4579,
+ "step": 9632
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.910467240612419e-06,
+ "loss": 0.4656,
+ "step": 9633
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9088744579425567e-06,
+ "loss": 0.4556,
+ "step": 9634
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9072822694513016e-06,
+ "loss": 0.4717,
+ "step": 9635
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9056906752555759e-06,
+ "loss": 0.4633,
+ "step": 9636
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9040996754722574e-06,
+ "loss": 0.4566,
+ "step": 9637
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.902509270218189e-06,
+ "loss": 0.4552,
+ "step": 9638
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9009194596101566e-06,
+ "loss": 0.4667,
+ "step": 9639
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8993302437649143e-06,
+ "loss": 0.4566,
+ "step": 9640
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8977416227991663e-06,
+ "loss": 0.4585,
+ "step": 9641
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.896153596829574e-06,
+ "loss": 0.4518,
+ "step": 9642
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8945661659727555e-06,
+ "loss": 0.4677,
+ "step": 9643
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8929793303452814e-06,
+ "loss": 0.4731,
+ "step": 9644
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.891393090063688e-06,
+ "loss": 0.4661,
+ "step": 9645
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8898074452444604e-06,
+ "loss": 0.4539,
+ "step": 9646
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8882223960040413e-06,
+ "loss": 0.4814,
+ "step": 9647
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8866379424588287e-06,
+ "loss": 0.4711,
+ "step": 9648
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8850540847251786e-06,
+ "loss": 0.4454,
+ "step": 9649
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8834708229194054e-06,
+ "loss": 0.4759,
+ "step": 9650
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8818881571577741e-06,
+ "loss": 0.4592,
+ "step": 9651
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8803060875565127e-06,
+ "loss": 0.4533,
+ "step": 9652
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8787246142318006e-06,
+ "loss": 0.484,
+ "step": 9653
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8771437372997736e-06,
+ "loss": 0.4713,
+ "step": 9654
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8755634568765246e-06,
+ "loss": 0.4474,
+ "step": 9655
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8739837730781029e-06,
+ "loss": 0.4372,
+ "step": 9656
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.872404686020516e-06,
+ "loss": 0.4562,
+ "step": 9657
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8708261958197193e-06,
+ "loss": 0.4659,
+ "step": 9658
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8692483025916387e-06,
+ "loss": 0.4809,
+ "step": 9659
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8676710064521409e-06,
+ "loss": 0.4592,
+ "step": 9660
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8660943075170634e-06,
+ "loss": 0.4448,
+ "step": 9661
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.864518205902187e-06,
+ "loss": 0.4631,
+ "step": 9662
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.862942701723257e-06,
+ "loss": 0.4671,
+ "step": 9663
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8613677950959697e-06,
+ "loss": 0.4527,
+ "step": 9664
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8597934861359779e-06,
+ "loss": 0.4446,
+ "step": 9665
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.858219774958897e-06,
+ "loss": 0.4743,
+ "step": 9666
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8566466616802914e-06,
+ "loss": 0.4744,
+ "step": 9667
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.855074146415685e-06,
+ "loss": 0.4457,
+ "step": 9668
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8535022292805539e-06,
+ "loss": 0.4582,
+ "step": 9669
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.851930910390337e-06,
+ "loss": 0.4666,
+ "step": 9670
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8503601898604207e-06,
+ "loss": 0.4709,
+ "step": 9671
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8487900678061588e-06,
+ "loss": 0.4568,
+ "step": 9672
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8472205443428504e-06,
+ "loss": 0.4638,
+ "step": 9673
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8456516195857543e-06,
+ "loss": 0.4657,
+ "step": 9674
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8440832936500875e-06,
+ "loss": 0.4578,
+ "step": 9675
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.842515566651021e-06,
+ "loss": 0.4629,
+ "step": 9676
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8409484387036813e-06,
+ "loss": 0.4413,
+ "step": 9677
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8393819099231503e-06,
+ "loss": 0.4732,
+ "step": 9678
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.837815980424471e-06,
+ "loss": 0.4708,
+ "step": 9679
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8362506503226374e-06,
+ "loss": 0.483,
+ "step": 9680
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8346859197325984e-06,
+ "loss": 0.4639,
+ "step": 9681
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8331217887692653e-06,
+ "loss": 0.4756,
+ "step": 9682
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8315582575475e-06,
+ "loss": 0.4638,
+ "step": 9683
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8299953261821202e-06,
+ "loss": 0.4641,
+ "step": 9684
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8284329947878999e-06,
+ "loss": 0.4882,
+ "step": 9685
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8268712634795749e-06,
+ "loss": 0.4464,
+ "step": 9686
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8253101323718303e-06,
+ "loss": 0.4501,
+ "step": 9687
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8237496015793077e-06,
+ "loss": 0.4642,
+ "step": 9688
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8221896712166075e-06,
+ "loss": 0.4618,
+ "step": 9689
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8206303413982806e-06,
+ "loss": 0.4548,
+ "step": 9690
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.819071612238843e-06,
+ "loss": 0.4565,
+ "step": 9691
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8175134838527575e-06,
+ "loss": 0.4589,
+ "step": 9692
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8159559563544504e-06,
+ "loss": 0.4569,
+ "step": 9693
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.814399029858298e-06,
+ "loss": 0.4753,
+ "step": 9694
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8128427044786345e-06,
+ "loss": 0.4571,
+ "step": 9695
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8112869803297494e-06,
+ "loss": 0.4539,
+ "step": 9696
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8097318575258894e-06,
+ "loss": 0.4814,
+ "step": 9697
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.808177336181256e-06,
+ "loss": 0.4669,
+ "step": 9698
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8066234164100038e-06,
+ "loss": 0.4593,
+ "step": 9699
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8050700983262526e-06,
+ "loss": 0.4782,
+ "step": 9700
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8035173820440643e-06,
+ "loss": 0.4736,
+ "step": 9701
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8019652676774703e-06,
+ "loss": 0.4838,
+ "step": 9702
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8004137553404498e-06,
+ "loss": 0.4489,
+ "step": 9703
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.798862845146938e-06,
+ "loss": 0.4896,
+ "step": 9704
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.797312537210827e-06,
+ "loss": 0.4669,
+ "step": 9705
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.795762831645964e-06,
+ "loss": 0.4614,
+ "step": 9706
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7942137285661576e-06,
+ "loss": 0.4606,
+ "step": 9707
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7926652280851642e-06,
+ "loss": 0.4639,
+ "step": 9708
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7911173303166985e-06,
+ "loss": 0.4593,
+ "step": 9709
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.789570035374434e-06,
+ "loss": 0.4639,
+ "step": 9710
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7880233433719929e-06,
+ "loss": 0.4737,
+ "step": 9711
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7864772544229626e-06,
+ "loss": 0.4641,
+ "step": 9712
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7849317686408817e-06,
+ "loss": 0.4718,
+ "step": 9713
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7833868861392423e-06,
+ "loss": 0.4658,
+ "step": 9714
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7818426070314953e-06,
+ "loss": 0.4595,
+ "step": 9715
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7802989314310449e-06,
+ "loss": 0.4852,
+ "step": 9716
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7787558594512533e-06,
+ "loss": 0.4482,
+ "step": 9717
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7772133912054367e-06,
+ "loss": 0.4569,
+ "step": 9718
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7756715268068635e-06,
+ "loss": 0.4792,
+ "step": 9719
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7741302663687697e-06,
+ "loss": 0.4654,
+ "step": 9720
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7725896100043349e-06,
+ "loss": 0.4532,
+ "step": 9721
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7710495578266963e-06,
+ "loss": 0.4619,
+ "step": 9722
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7695101099489542e-06,
+ "loss": 0.4695,
+ "step": 9723
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7679712664841554e-06,
+ "loss": 0.465,
+ "step": 9724
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.766433027545308e-06,
+ "loss": 0.4712,
+ "step": 9725
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7648953932453706e-06,
+ "loss": 0.4926,
+ "step": 9726
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.763358363697265e-06,
+ "loss": 0.4681,
+ "step": 9727
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7618219390138635e-06,
+ "loss": 0.4721,
+ "step": 9728
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7602861193079922e-06,
+ "loss": 0.4555,
+ "step": 9729
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7587509046924378e-06,
+ "loss": 0.4666,
+ "step": 9730
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7572162952799366e-06,
+ "loss": 0.4645,
+ "step": 9731
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7556822911831882e-06,
+ "loss": 0.4613,
+ "step": 9732
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7541488925148397e-06,
+ "loss": 0.4739,
+ "step": 9733
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.752616099387502e-06,
+ "loss": 0.455,
+ "step": 9734
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7510839119137347e-06,
+ "loss": 0.4624,
+ "step": 9735
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7495523302060546e-06,
+ "loss": 0.4691,
+ "step": 9736
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7480213543769343e-06,
+ "loss": 0.4729,
+ "step": 9737
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7464909845388045e-06,
+ "loss": 0.4682,
+ "step": 9738
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7449612208040479e-06,
+ "loss": 0.4588,
+ "step": 9739
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.743432063285001e-06,
+ "loss": 0.464,
+ "step": 9740
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7419035120939642e-06,
+ "loss": 0.4633,
+ "step": 9741
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.740375567343182e-06,
+ "loss": 0.4697,
+ "step": 9742
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7388482291448684e-06,
+ "loss": 0.4564,
+ "step": 9743
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7373214976111786e-06,
+ "loss": 0.4541,
+ "step": 9744
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.735795372854231e-06,
+ "loss": 0.4673,
+ "step": 9745
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7342698549860958e-06,
+ "loss": 0.4842,
+ "step": 9746
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.732744944118805e-06,
+ "loss": 0.459,
+ "step": 9747
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7312206403643395e-06,
+ "loss": 0.4632,
+ "step": 9748
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7296969438346378e-06,
+ "loss": 0.4745,
+ "step": 9749
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7281738546415938e-06,
+ "loss": 0.4645,
+ "step": 9750
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.726651372897057e-06,
+ "loss": 0.4611,
+ "step": 9751
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7251294987128287e-06,
+ "loss": 0.4632,
+ "step": 9752
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.723608232200673e-06,
+ "loss": 0.4493,
+ "step": 9753
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7220875734723063e-06,
+ "loss": 0.4455,
+ "step": 9754
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.720567522639398e-06,
+ "loss": 0.4785,
+ "step": 9755
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7190480798135745e-06,
+ "loss": 0.4574,
+ "step": 9756
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7175292451064174e-06,
+ "loss": 0.4784,
+ "step": 9757
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.716011018629462e-06,
+ "loss": 0.4608,
+ "step": 9758
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7144934004942027e-06,
+ "loss": 0.4531,
+ "step": 9759
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7129763908120823e-06,
+ "loss": 0.4734,
+ "step": 9760
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7114599896945105e-06,
+ "loss": 0.4574,
+ "step": 9761
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.709944197252843e-06,
+ "loss": 0.4479,
+ "step": 9762
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7084290135983895e-06,
+ "loss": 0.4544,
+ "step": 9763
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7069144388424253e-06,
+ "loss": 0.4866,
+ "step": 9764
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7054004730961704e-06,
+ "loss": 0.4746,
+ "step": 9765
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7038871164708059e-06,
+ "loss": 0.4562,
+ "step": 9766
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7023743690774619e-06,
+ "loss": 0.4627,
+ "step": 9767
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7008622310272349e-06,
+ "loss": 0.4512,
+ "step": 9768
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6993507024311661e-06,
+ "loss": 0.4584,
+ "step": 9769
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.697839783400258e-06,
+ "loss": 0.4578,
+ "step": 9770
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6963294740454638e-06,
+ "loss": 0.4818,
+ "step": 9771
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.694819774477694e-06,
+ "loss": 0.4753,
+ "step": 9772
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6933106848078174e-06,
+ "loss": 0.4678,
+ "step": 9773
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.691802205146652e-06,
+ "loss": 0.4589,
+ "step": 9774
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6902943356049796e-06,
+ "loss": 0.4672,
+ "step": 9775
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6887870762935276e-06,
+ "loss": 0.4603,
+ "step": 9776
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6872804273229838e-06,
+ "loss": 0.4586,
+ "step": 9777
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6857743888039902e-06,
+ "loss": 0.4551,
+ "step": 9778
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6842689608471451e-06,
+ "loss": 0.4649,
+ "step": 9779
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6827641435629983e-06,
+ "loss": 0.4798,
+ "step": 9780
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6812599370620574e-06,
+ "loss": 0.4601,
+ "step": 9781
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.679756341454788e-06,
+ "loss": 0.4397,
+ "step": 9782
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6782533568516047e-06,
+ "loss": 0.4517,
+ "step": 9783
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6767509833628847e-06,
+ "loss": 0.4718,
+ "step": 9784
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6752492210989523e-06,
+ "loss": 0.4713,
+ "step": 9785
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6737480701700936e-06,
+ "loss": 0.4593,
+ "step": 9786
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6722475306865415e-06,
+ "loss": 0.4871,
+ "step": 9787
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6707476027584956e-06,
+ "loss": 0.4819,
+ "step": 9788
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6692482864961024e-06,
+ "loss": 0.4736,
+ "step": 9789
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6677495820094635e-06,
+ "loss": 0.4608,
+ "step": 9790
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6662514894086402e-06,
+ "loss": 0.4389,
+ "step": 9791
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.664754008803644e-06,
+ "loss": 0.4748,
+ "step": 9792
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6632571403044429e-06,
+ "loss": 0.4592,
+ "step": 9793
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6617608840209642e-06,
+ "loss": 0.4609,
+ "step": 9794
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6602652400630825e-06,
+ "loss": 0.4567,
+ "step": 9795
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6587702085406366e-06,
+ "loss": 0.5012,
+ "step": 9796
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6572757895634117e-06,
+ "loss": 0.4571,
+ "step": 9797
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6557819832411537e-06,
+ "loss": 0.4843,
+ "step": 9798
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6542887896835614e-06,
+ "loss": 0.4747,
+ "step": 9799
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.652796209000287e-06,
+ "loss": 0.4576,
+ "step": 9800
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6513042413009383e-06,
+ "loss": 0.4586,
+ "step": 9801
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6498128866950835e-06,
+ "loss": 0.4844,
+ "step": 9802
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6483221452922394e-06,
+ "loss": 0.4594,
+ "step": 9803
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.646832017201877e-06,
+ "loss": 0.4692,
+ "step": 9804
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6453425025334302e-06,
+ "loss": 0.4718,
+ "step": 9805
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6438536013962814e-06,
+ "loss": 0.4611,
+ "step": 9806
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6423653138997675e-06,
+ "loss": 0.4661,
+ "step": 9807
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.64087764015318e-06,
+ "loss": 0.4553,
+ "step": 9808
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.639390580265774e-06,
+ "loss": 0.4626,
+ "step": 9809
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6379041343467484e-06,
+ "loss": 0.4576,
+ "step": 9810
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6364183025052626e-06,
+ "loss": 0.4766,
+ "step": 9811
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6349330848504308e-06,
+ "loss": 0.4571,
+ "step": 9812
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6334484814913165e-06,
+ "loss": 0.4734,
+ "step": 9813
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6319644925369504e-06,
+ "loss": 0.4534,
+ "step": 9814
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6304811180963032e-06,
+ "loss": 0.4627,
+ "step": 9815
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6289983582783142e-06,
+ "loss": 0.4361,
+ "step": 9816
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6275162131918688e-06,
+ "loss": 0.4706,
+ "step": 9817
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6260346829458084e-06,
+ "loss": 0.4615,
+ "step": 9818
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.624553767648931e-06,
+ "loss": 0.4508,
+ "step": 9819
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.623073467409988e-06,
+ "loss": 0.4657,
+ "step": 9820
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.621593782337686e-06,
+ "loss": 0.4634,
+ "step": 9821
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.62011471254069e-06,
+ "loss": 0.4603,
+ "step": 9822
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.618636258127615e-06,
+ "loss": 0.4654,
+ "step": 9823
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6171584192070322e-06,
+ "loss": 0.46,
+ "step": 9824
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6156811958874664e-06,
+ "loss": 0.478,
+ "step": 9825
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6142045882774027e-06,
+ "loss": 0.4481,
+ "step": 9826
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6127285964852758e-06,
+ "loss": 0.4746,
+ "step": 9827
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6112532206194719e-06,
+ "loss": 0.4595,
+ "step": 9828
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6097784607883427e-06,
+ "loss": 0.4624,
+ "step": 9829
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6083043171001856e-06,
+ "loss": 0.4669,
+ "step": 9830
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6068307896632562e-06,
+ "loss": 0.456,
+ "step": 9831
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6053578785857637e-06,
+ "loss": 0.4572,
+ "step": 9832
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6038855839758727e-06,
+ "loss": 0.4696,
+ "step": 9833
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6024139059417e-06,
+ "loss": 0.4707,
+ "step": 9834
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6009428445913245e-06,
+ "loss": 0.4542,
+ "step": 9835
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5994724000327689e-06,
+ "loss": 0.4657,
+ "step": 9836
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5980025723740222e-06,
+ "loss": 0.4558,
+ "step": 9837
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5965333617230206e-06,
+ "loss": 0.4499,
+ "step": 9838
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5950647681876564e-06,
+ "loss": 0.4672,
+ "step": 9839
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5935967918757766e-06,
+ "loss": 0.4803,
+ "step": 9840
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5921294328951842e-06,
+ "loss": 0.4685,
+ "step": 9841
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5906626913536315e-06,
+ "loss": 0.4913,
+ "step": 9842
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5891965673588371e-06,
+ "loss": 0.4623,
+ "step": 9843
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5877310610184638e-06,
+ "loss": 0.467,
+ "step": 9844
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5862661724401296e-06,
+ "loss": 0.4534,
+ "step": 9845
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5848019017314143e-06,
+ "loss": 0.4589,
+ "step": 9846
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5833382489998461e-06,
+ "loss": 0.4532,
+ "step": 9847
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5818752143529092e-06,
+ "loss": 0.4563,
+ "step": 9848
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.580412797898041e-06,
+ "loss": 0.4748,
+ "step": 9849
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.578950999742639e-06,
+ "loss": 0.4534,
+ "step": 9850
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5774898199940503e-06,
+ "loss": 0.4749,
+ "step": 9851
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.576029258759577e-06,
+ "loss": 0.4571,
+ "step": 9852
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.574569316146477e-06,
+ "loss": 0.4619,
+ "step": 9853
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.573109992261963e-06,
+ "loss": 0.4568,
+ "step": 9854
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5716512872131983e-06,
+ "loss": 0.46,
+ "step": 9855
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5701932011073072e-06,
+ "loss": 0.464,
+ "step": 9856
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5687357340513676e-06,
+ "loss": 0.4505,
+ "step": 9857
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.567278886152407e-06,
+ "loss": 0.4821,
+ "step": 9858
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5658226575174107e-06,
+ "loss": 0.4536,
+ "step": 9859
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.564367048253318e-06,
+ "loss": 0.4568,
+ "step": 9860
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5629120584670233e-06,
+ "loss": 0.4723,
+ "step": 9861
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.561457688265372e-06,
+ "loss": 0.4438,
+ "step": 9862
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5600039377551713e-06,
+ "loss": 0.4778,
+ "step": 9863
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5585508070431777e-06,
+ "loss": 0.4595,
+ "step": 9864
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5570982962361014e-06,
+ "loss": 0.4779,
+ "step": 9865
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5556464054406084e-06,
+ "loss": 0.4676,
+ "step": 9866
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5541951347633222e-06,
+ "loss": 0.4708,
+ "step": 9867
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5527444843108164e-06,
+ "loss": 0.4505,
+ "step": 9868
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5512944541896192e-06,
+ "loss": 0.4521,
+ "step": 9869
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5498450445062185e-06,
+ "loss": 0.4528,
+ "step": 9870
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5483962553670507e-06,
+ "loss": 0.4653,
+ "step": 9871
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5469480868785092e-06,
+ "loss": 0.4514,
+ "step": 9872
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5455005391469414e-06,
+ "loss": 0.4529,
+ "step": 9873
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5440536122786487e-06,
+ "loss": 0.4503,
+ "step": 9874
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5426073063798853e-06,
+ "loss": 0.4638,
+ "step": 9875
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.541161621556867e-06,
+ "loss": 0.4875,
+ "step": 9876
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5397165579157547e-06,
+ "loss": 0.4691,
+ "step": 9877
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5382721155626701e-06,
+ "loss": 0.4669,
+ "step": 9878
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5368282946036884e-06,
+ "loss": 0.4839,
+ "step": 9879
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5353850951448346e-06,
+ "loss": 0.45,
+ "step": 9880
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.533942517292092e-06,
+ "loss": 0.4832,
+ "step": 9881
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5325005611513988e-06,
+ "loss": 0.4552,
+ "step": 9882
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5310592268286427e-06,
+ "loss": 0.4636,
+ "step": 9883
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5296185144296737e-06,
+ "loss": 0.4557,
+ "step": 9884
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5281784240602915e-06,
+ "loss": 0.4538,
+ "step": 9885
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5267389558262458e-06,
+ "loss": 0.4727,
+ "step": 9886
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.525300109833251e-06,
+ "loss": 0.468,
+ "step": 9887
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5238618861869657e-06,
+ "loss": 0.4555,
+ "step": 9888
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5224242849930104e-06,
+ "loss": 0.4554,
+ "step": 9889
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5209873063569514e-06,
+ "loss": 0.461,
+ "step": 9890
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5195509503843198e-06,
+ "loss": 0.4678,
+ "step": 9891
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5181152171805946e-06,
+ "loss": 0.4675,
+ "step": 9892
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5166801068512083e-06,
+ "loss": 0.4785,
+ "step": 9893
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5152456195015508e-06,
+ "loss": 0.4646,
+ "step": 9894
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5138117552369636e-06,
+ "loss": 0.4579,
+ "step": 9895
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5123785141627422e-06,
+ "loss": 0.4778,
+ "step": 9896
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5109458963841405e-06,
+ "loss": 0.4539,
+ "step": 9897
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5095139020063654e-06,
+ "loss": 0.4777,
+ "step": 9898
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5080825311345748e-06,
+ "loss": 0.4639,
+ "step": 9899
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5066517838738826e-06,
+ "loss": 0.4715,
+ "step": 9900
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5052216603293567e-06,
+ "loss": 0.4642,
+ "step": 9901
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5037921606060201e-06,
+ "loss": 0.4706,
+ "step": 9902
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5023632848088466e-06,
+ "loss": 0.4704,
+ "step": 9903
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5009350330427707e-06,
+ "loss": 0.4681,
+ "step": 9904
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4995074054126758e-06,
+ "loss": 0.4892,
+ "step": 9905
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4980804020234018e-06,
+ "loss": 0.4726,
+ "step": 9906
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4966540229797377e-06,
+ "loss": 0.449,
+ "step": 9907
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.495228268386436e-06,
+ "loss": 0.4921,
+ "step": 9908
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4938031383481976e-06,
+ "loss": 0.4561,
+ "step": 9909
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4923786329696732e-06,
+ "loss": 0.4515,
+ "step": 9910
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.490954752355479e-06,
+ "loss": 0.4636,
+ "step": 9911
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4895314966101771e-06,
+ "loss": 0.4696,
+ "step": 9912
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4881088658382825e-06,
+ "loss": 0.46,
+ "step": 9913
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4866868601442708e-06,
+ "loss": 0.4571,
+ "step": 9914
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4852654796325649e-06,
+ "loss": 0.4791,
+ "step": 9915
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.483844724407546e-06,
+ "loss": 0.4548,
+ "step": 9916
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4824245945735504e-06,
+ "loss": 0.4757,
+ "step": 9917
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4810050902348637e-06,
+ "loss": 0.4646,
+ "step": 9918
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4795862114957316e-06,
+ "loss": 0.4581,
+ "step": 9919
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4781679584603502e-06,
+ "loss": 0.4629,
+ "step": 9920
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.476750331232868e-06,
+ "loss": 0.4577,
+ "step": 9921
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.475333329917391e-06,
+ "loss": 0.4527,
+ "step": 9922
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4739169546179765e-06,
+ "loss": 0.4807,
+ "step": 9923
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4725012054386378e-06,
+ "loss": 0.4923,
+ "step": 9924
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.471086082483343e-06,
+ "loss": 0.4598,
+ "step": 9925
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4696715858560117e-06,
+ "loss": 0.4665,
+ "step": 9926
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4682577156605172e-06,
+ "loss": 0.4629,
+ "step": 9927
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4668444720006925e-06,
+ "loss": 0.4601,
+ "step": 9928
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.465431854980317e-06,
+ "loss": 0.4491,
+ "step": 9929
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.464019864703128e-06,
+ "loss": 0.4712,
+ "step": 9930
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.462608501272814e-06,
+ "loss": 0.4774,
+ "step": 9931
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4611977647930253e-06,
+ "loss": 0.4513,
+ "step": 9932
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4597876553673563e-06,
+ "loss": 0.4563,
+ "step": 9933
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4583781730993608e-06,
+ "loss": 0.499,
+ "step": 9934
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4569693180925448e-06,
+ "loss": 0.4526,
+ "step": 9935
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4555610904503693e-06,
+ "loss": 0.4584,
+ "step": 9936
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4541534902762454e-06,
+ "loss": 0.4796,
+ "step": 9937
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4527465176735468e-06,
+ "loss": 0.4667,
+ "step": 9938
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4513401727455912e-06,
+ "loss": 0.4605,
+ "step": 9939
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4499344555956596e-06,
+ "loss": 0.4599,
+ "step": 9940
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4485293663269784e-06,
+ "loss": 0.4705,
+ "step": 9941
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4471249050427327e-06,
+ "loss": 0.4587,
+ "step": 9942
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.445721071846059e-06,
+ "loss": 0.4666,
+ "step": 9943
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4443178668400482e-06,
+ "loss": 0.4746,
+ "step": 9944
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.44291529012775e-06,
+ "loss": 0.4541,
+ "step": 9945
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4415133418121607e-06,
+ "loss": 0.4601,
+ "step": 9946
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.440112021996235e-06,
+ "loss": 0.4644,
+ "step": 9947
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.438711330782877e-06,
+ "loss": 0.4746,
+ "step": 9948
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4373112682749513e-06,
+ "loss": 0.453,
+ "step": 9949
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.435911834575271e-06,
+ "loss": 0.4469,
+ "step": 9950
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4345130297866028e-06,
+ "loss": 0.4831,
+ "step": 9951
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4331148540116736e-06,
+ "loss": 0.4721,
+ "step": 9952
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4317173073531577e-06,
+ "loss": 0.4719,
+ "step": 9953
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4303203899136841e-06,
+ "loss": 0.4573,
+ "step": 9954
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4289241017958366e-06,
+ "loss": 0.4556,
+ "step": 9955
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4275284431021541e-06,
+ "loss": 0.4715,
+ "step": 9956
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4261334139351269e-06,
+ "loss": 0.4622,
+ "step": 9957
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4247390143971972e-06,
+ "loss": 0.4679,
+ "step": 9958
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.423345244590768e-06,
+ "loss": 0.4744,
+ "step": 9959
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4219521046181928e-06,
+ "loss": 0.4441,
+ "step": 9960
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4205595945817773e-06,
+ "loss": 0.4609,
+ "step": 9961
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.41916771458378e-06,
+ "loss": 0.4812,
+ "step": 9962
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4177764647264148e-06,
+ "loss": 0.4526,
+ "step": 9963
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4163858451118506e-06,
+ "loss": 0.4531,
+ "step": 9964
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.414995855842205e-06,
+ "loss": 0.4603,
+ "step": 9965
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4136064970195595e-06,
+ "loss": 0.447,
+ "step": 9966
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4122177687459382e-06,
+ "loss": 0.4504,
+ "step": 9967
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4108296711233249e-06,
+ "loss": 0.461,
+ "step": 9968
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4094422042536538e-06,
+ "loss": 0.458,
+ "step": 9969
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4080553682388188e-06,
+ "loss": 0.4563,
+ "step": 9970
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4066691631806574e-06,
+ "loss": 0.4701,
+ "step": 9971
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4052835891809735e-06,
+ "loss": 0.4579,
+ "step": 9972
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.403898646341515e-06,
+ "loss": 0.4772,
+ "step": 9973
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4025143347639858e-06,
+ "loss": 0.467,
+ "step": 9974
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4011306545500435e-06,
+ "loss": 0.4744,
+ "step": 9975
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3997476058013016e-06,
+ "loss": 0.4634,
+ "step": 9976
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.398365188619324e-06,
+ "loss": 0.4809,
+ "step": 9977
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3969834031056273e-06,
+ "loss": 0.4474,
+ "step": 9978
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3956022493616895e-06,
+ "loss": 0.4512,
+ "step": 9979
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3942217274889325e-06,
+ "loss": 0.4772,
+ "step": 9980
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3928418375887388e-06,
+ "loss": 0.4751,
+ "step": 9981
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3914625797624415e-06,
+ "loss": 0.4361,
+ "step": 9982
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3900839541113265e-06,
+ "loss": 0.4814,
+ "step": 9983
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3887059607366338e-06,
+ "loss": 0.4506,
+ "step": 9984
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3873285997395569e-06,
+ "loss": 0.4521,
+ "step": 9985
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3859518712212473e-06,
+ "loss": 0.4759,
+ "step": 9986
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3845757752828037e-06,
+ "loss": 0.4694,
+ "step": 9987
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3832003120252801e-06,
+ "loss": 0.4438,
+ "step": 9988
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3818254815496846e-06,
+ "loss": 0.4566,
+ "step": 9989
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3804512839569805e-06,
+ "loss": 0.4699,
+ "step": 9990
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3790777193480842e-06,
+ "loss": 0.4585,
+ "step": 9991
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3777047878238603e-06,
+ "loss": 0.4504,
+ "step": 9992
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3763324894851371e-06,
+ "loss": 0.4583,
+ "step": 9993
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3749608244326862e-06,
+ "loss": 0.461,
+ "step": 9994
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.373589792767238e-06,
+ "loss": 0.4712,
+ "step": 9995
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.372219394589477e-06,
+ "loss": 0.4688,
+ "step": 9996
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3708496300000363e-06,
+ "loss": 0.479,
+ "step": 9997
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.369480499099508e-06,
+ "loss": 0.4624,
+ "step": 9998
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3681120019884331e-06,
+ "loss": 0.4708,
+ "step": 9999
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3667441387673098e-06,
+ "loss": 0.4821,
+ "step": 10000
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.36537690953659e-06,
+ "loss": 0.4553,
+ "step": 10001
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3640103143966765e-06,
+ "loss": 0.4771,
+ "step": 10002
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3626443534479262e-06,
+ "loss": 0.4618,
+ "step": 10003
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3612790267906484e-06,
+ "loss": 0.4534,
+ "step": 10004
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3599143345251075e-06,
+ "loss": 0.4711,
+ "step": 10005
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.35855027675152e-06,
+ "loss": 0.4506,
+ "step": 10006
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3571868535700595e-06,
+ "loss": 0.4574,
+ "step": 10007
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3558240650808473e-06,
+ "loss": 0.4485,
+ "step": 10008
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.354461911383963e-06,
+ "loss": 0.4536,
+ "step": 10009
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.353100392579434e-06,
+ "loss": 0.467,
+ "step": 10010
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.351739508767249e-06,
+ "loss": 0.4719,
+ "step": 10011
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3503792600473408e-06,
+ "loss": 0.4611,
+ "step": 10012
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.349019646519607e-06,
+ "loss": 0.4513,
+ "step": 10013
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3476606682838866e-06,
+ "loss": 0.4686,
+ "step": 10014
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3463023254399798e-06,
+ "loss": 0.4681,
+ "step": 10015
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3449446180876369e-06,
+ "loss": 0.4556,
+ "step": 10016
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3435875463265624e-06,
+ "loss": 0.4678,
+ "step": 10017
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3422311102564134e-06,
+ "loss": 0.4727,
+ "step": 10018
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.340875309976799e-06,
+ "loss": 0.4818,
+ "step": 10019
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3395201455872886e-06,
+ "loss": 0.4737,
+ "step": 10020
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3381656171873936e-06,
+ "loss": 0.4683,
+ "step": 10021
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.336811724876592e-06,
+ "loss": 0.4708,
+ "step": 10022
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3354584687543037e-06,
+ "loss": 0.4664,
+ "step": 10023
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3341058489199065e-06,
+ "loss": 0.4535,
+ "step": 10024
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3327538654727323e-06,
+ "loss": 0.4832,
+ "step": 10025
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3314025185120616e-06,
+ "loss": 0.4402,
+ "step": 10026
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3300518081371373e-06,
+ "loss": 0.4713,
+ "step": 10027
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3287017344471477e-06,
+ "loss": 0.4847,
+ "step": 10028
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3273522975412344e-06,
+ "loss": 0.485,
+ "step": 10029
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3260034975184955e-06,
+ "loss": 0.4526,
+ "step": 10030
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3246553344779834e-06,
+ "loss": 0.4636,
+ "step": 10031
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3233078085187002e-06,
+ "loss": 0.4618,
+ "step": 10032
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3219609197396e-06,
+ "loss": 0.4777,
+ "step": 10033
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3206146682395983e-06,
+ "loss": 0.4768,
+ "step": 10034
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3192690541175536e-06,
+ "loss": 0.469,
+ "step": 10035
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3179240774722845e-06,
+ "loss": 0.4677,
+ "step": 10036
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3165797384025602e-06,
+ "loss": 0.4521,
+ "step": 10037
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3152360370071016e-06,
+ "loss": 0.458,
+ "step": 10038
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3138929733845873e-06,
+ "loss": 0.4684,
+ "step": 10039
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3125505476336408e-06,
+ "loss": 0.4928,
+ "step": 10040
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.31120875985285e-06,
+ "loss": 0.4457,
+ "step": 10041
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3098676101407493e-06,
+ "loss": 0.4711,
+ "step": 10042
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3085270985958276e-06,
+ "loss": 0.4534,
+ "step": 10043
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.307187225316524e-06,
+ "loss": 0.4645,
+ "step": 10044
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3058479904012356e-06,
+ "loss": 0.4482,
+ "step": 10045
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3045093939483066e-06,
+ "loss": 0.4551,
+ "step": 10046
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.303171436056042e-06,
+ "loss": 0.4767,
+ "step": 10047
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3018341168226944e-06,
+ "loss": 0.4526,
+ "step": 10048
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3004974363464717e-06,
+ "loss": 0.4568,
+ "step": 10049
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2991613947255321e-06,
+ "loss": 0.4566,
+ "step": 10050
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2978259920579895e-06,
+ "loss": 0.4475,
+ "step": 10051
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2964912284419119e-06,
+ "loss": 0.4601,
+ "step": 10052
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2951571039753163e-06,
+ "loss": 0.4661,
+ "step": 10053
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2938236187561782e-06,
+ "loss": 0.4581,
+ "step": 10054
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.292490772882422e-06,
+ "loss": 0.4995,
+ "step": 10055
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2911585664519267e-06,
+ "loss": 0.4664,
+ "step": 10056
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2898269995625234e-06,
+ "loss": 0.4653,
+ "step": 10057
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2884960723119978e-06,
+ "loss": 0.4812,
+ "step": 10058
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2871657847980856e-06,
+ "loss": 0.4597,
+ "step": 10059
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.285836137118477e-06,
+ "loss": 0.4648,
+ "step": 10060
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2845071293708188e-06,
+ "loss": 0.4471,
+ "step": 10061
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2831787616527058e-06,
+ "loss": 0.4796,
+ "step": 10062
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2818510340616896e-06,
+ "loss": 0.4558,
+ "step": 10063
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2805239466952723e-06,
+ "loss": 0.4706,
+ "step": 10064
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2791974996509094e-06,
+ "loss": 0.4646,
+ "step": 10065
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2778716930260105e-06,
+ "loss": 0.4734,
+ "step": 10066
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2765465269179334e-06,
+ "loss": 0.4534,
+ "step": 10067
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.275222001423998e-06,
+ "loss": 0.4768,
+ "step": 10068
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2738981166414688e-06,
+ "loss": 0.467,
+ "step": 10069
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2725748726675691e-06,
+ "loss": 0.4768,
+ "step": 10070
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2712522695994666e-06,
+ "loss": 0.4946,
+ "step": 10071
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.269930307534295e-06,
+ "loss": 0.4539,
+ "step": 10072
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.268608986569131e-06,
+ "loss": 0.4647,
+ "step": 10073
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2672883068010033e-06,
+ "loss": 0.4726,
+ "step": 10074
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2659682683269036e-06,
+ "loss": 0.4771,
+ "step": 10075
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2646488712437654e-06,
+ "loss": 0.4556,
+ "step": 10076
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2633301156484822e-06,
+ "loss": 0.4647,
+ "step": 10077
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2620120016378956e-06,
+ "loss": 0.4549,
+ "step": 10078
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2606945293088047e-06,
+ "loss": 0.4467,
+ "step": 10079
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2593776987579576e-06,
+ "loss": 0.4639,
+ "step": 10080
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2580615100820548e-06,
+ "loss": 0.4664,
+ "step": 10081
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2567459633777567e-06,
+ "loss": 0.4634,
+ "step": 10082
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2554310587416674e-06,
+ "loss": 0.4713,
+ "step": 10083
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2541167962703515e-06,
+ "loss": 0.4783,
+ "step": 10084
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.252803176060321e-06,
+ "loss": 0.4557,
+ "step": 10085
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.251490198208043e-06,
+ "loss": 0.4748,
+ "step": 10086
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2501778628099349e-06,
+ "loss": 0.4805,
+ "step": 10087
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2488661699623739e-06,
+ "loss": 0.4657,
+ "step": 10088
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.247555119761682e-06,
+ "loss": 0.4644,
+ "step": 10089
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2462447123041388e-06,
+ "loss": 0.464,
+ "step": 10090
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.244934947685974e-06,
+ "loss": 0.4735,
+ "step": 10091
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2436258260033696e-06,
+ "loss": 0.4721,
+ "step": 10092
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2423173473524653e-06,
+ "loss": 0.4823,
+ "step": 10093
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2410095118293475e-06,
+ "loss": 0.4499,
+ "step": 10094
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2397023195300618e-06,
+ "loss": 0.4769,
+ "step": 10095
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.238395770550601e-06,
+ "loss": 0.4584,
+ "step": 10096
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2370898649869122e-06,
+ "loss": 0.4785,
+ "step": 10097
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2357846029348975e-06,
+ "loss": 0.461,
+ "step": 10098
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2344799844904065e-06,
+ "loss": 0.4563,
+ "step": 10099
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2331760097492485e-06,
+ "loss": 0.4628,
+ "step": 10100
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2318726788071767e-06,
+ "loss": 0.4704,
+ "step": 10101
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.230569991759909e-06,
+ "loss": 0.473,
+ "step": 10102
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2292679487031045e-06,
+ "loss": 0.4632,
+ "step": 10103
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2279665497323835e-06,
+ "loss": 0.4495,
+ "step": 10104
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2266657949433135e-06,
+ "loss": 0.4662,
+ "step": 10105
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2253656844314155e-06,
+ "loss": 0.4628,
+ "step": 10106
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.224066218292167e-06,
+ "loss": 0.4859,
+ "step": 10107
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2227673966209896e-06,
+ "loss": 0.4671,
+ "step": 10108
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2214692195132705e-06,
+ "loss": 0.4454,
+ "step": 10109
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2201716870643388e-06,
+ "loss": 0.458,
+ "step": 10110
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2188747993694805e-06,
+ "loss": 0.452,
+ "step": 10111
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.217578556523934e-06,
+ "loss": 0.4621,
+ "step": 10112
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2162829586228874e-06,
+ "loss": 0.4471,
+ "step": 10113
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.214988005761487e-06,
+ "loss": 0.4653,
+ "step": 10114
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2136936980348267e-06,
+ "loss": 0.4649,
+ "step": 10115
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2124000355379583e-06,
+ "loss": 0.4577,
+ "step": 10116
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.21110701836588e-06,
+ "loss": 0.4553,
+ "step": 10117
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2098146466135475e-06,
+ "loss": 0.4912,
+ "step": 10118
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2085229203758663e-06,
+ "loss": 0.4616,
+ "step": 10119
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2072318397476945e-06,
+ "loss": 0.4577,
+ "step": 10120
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2059414048238437e-06,
+ "loss": 0.4583,
+ "step": 10121
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2046516156990796e-06,
+ "loss": 0.4592,
+ "step": 10122
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2033624724681191e-06,
+ "loss": 0.468,
+ "step": 10123
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2020739752256282e-06,
+ "loss": 0.4817,
+ "step": 10124
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2007861240662334e-06,
+ "loss": 0.4542,
+ "step": 10125
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1994989190845075e-06,
+ "loss": 0.4465,
+ "step": 10126
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1982123603749762e-06,
+ "loss": 0.455,
+ "step": 10127
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1969264480321175e-06,
+ "loss": 0.465,
+ "step": 10128
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1956411821503688e-06,
+ "loss": 0.462,
+ "step": 10129
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1943565628241105e-06,
+ "loss": 0.4554,
+ "step": 10130
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1930725901476814e-06,
+ "loss": 0.4542,
+ "step": 10131
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1917892642153706e-06,
+ "loss": 0.469,
+ "step": 10132
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.190506585121418e-06,
+ "loss": 0.4819,
+ "step": 10133
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1892245529600222e-06,
+ "loss": 0.4757,
+ "step": 10134
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1879431678253261e-06,
+ "loss": 0.4704,
+ "step": 10135
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1866624298114338e-06,
+ "loss": 0.459,
+ "step": 10136
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1853823390123964e-06,
+ "loss": 0.4646,
+ "step": 10137
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1841028955222155e-06,
+ "loss": 0.4662,
+ "step": 10138
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1828240994348517e-06,
+ "loss": 0.4671,
+ "step": 10139
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1815459508442118e-06,
+ "loss": 0.4511,
+ "step": 10140
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1802684498441585e-06,
+ "loss": 0.4797,
+ "step": 10141
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1789915965285037e-06,
+ "loss": 0.4553,
+ "step": 10142
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.177715390991019e-06,
+ "loss": 0.4775,
+ "step": 10143
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1764398333254202e-06,
+ "loss": 0.4567,
+ "step": 10144
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1751649236253815e-06,
+ "loss": 0.4767,
+ "step": 10145
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1738906619845248e-06,
+ "loss": 0.4722,
+ "step": 10146
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1726170484964282e-06,
+ "loss": 0.4849,
+ "step": 10147
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1713440832546196e-06,
+ "loss": 0.4432,
+ "step": 10148
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1700717663525784e-06,
+ "loss": 0.4562,
+ "step": 10149
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1688000978837423e-06,
+ "loss": 0.478,
+ "step": 10150
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1675290779414949e-06,
+ "loss": 0.4653,
+ "step": 10151
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1662587066191755e-06,
+ "loss": 0.4584,
+ "step": 10152
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1649889840100737e-06,
+ "loss": 0.4666,
+ "step": 10153
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1637199102074326e-06,
+ "loss": 0.4629,
+ "step": 10154
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1624514853044488e-06,
+ "loss": 0.4594,
+ "step": 10155
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1611837093942691e-06,
+ "loss": 0.4912,
+ "step": 10156
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1599165825699955e-06,
+ "loss": 0.4794,
+ "step": 10157
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1586501049246801e-06,
+ "loss": 0.4589,
+ "step": 10158
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1573842765513266e-06,
+ "loss": 0.4812,
+ "step": 10159
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1561190975428926e-06,
+ "loss": 0.4629,
+ "step": 10160
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1548545679922885e-06,
+ "loss": 0.4512,
+ "step": 10161
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.153590687992372e-06,
+ "loss": 0.4553,
+ "step": 10162
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1523274576359633e-06,
+ "loss": 0.4647,
+ "step": 10163
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.151064877015825e-06,
+ "loss": 0.4667,
+ "step": 10164
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1498029462246752e-06,
+ "loss": 0.4664,
+ "step": 10165
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1485416653551884e-06,
+ "loss": 0.459,
+ "step": 10166
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1472810344999852e-06,
+ "loss": 0.4335,
+ "step": 10167
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1460210537516426e-06,
+ "loss": 0.4746,
+ "step": 10168
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1447617232026842e-06,
+ "loss": 0.4671,
+ "step": 10169
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1435030429455951e-06,
+ "loss": 0.4687,
+ "step": 10170
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1422450130728069e-06,
+ "loss": 0.4722,
+ "step": 10171
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1409876336767013e-06,
+ "loss": 0.4592,
+ "step": 10172
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1397309048496174e-06,
+ "loss": 0.4744,
+ "step": 10173
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1384748266838408e-06,
+ "loss": 0.4578,
+ "step": 10174
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1372193992716175e-06,
+ "loss": 0.467,
+ "step": 10175
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1359646227051357e-06,
+ "loss": 0.4537,
+ "step": 10176
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1347104970765466e-06,
+ "loss": 0.454,
+ "step": 10177
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.133457022477945e-06,
+ "loss": 0.475,
+ "step": 10178
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1322041990013798e-06,
+ "loss": 0.4638,
+ "step": 10179
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.130952026738855e-06,
+ "loss": 0.4609,
+ "step": 10180
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1297005057823251e-06,
+ "loss": 0.4676,
+ "step": 10181
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1284496362236952e-06,
+ "loss": 0.4789,
+ "step": 10182
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1271994181548217e-06,
+ "loss": 0.4718,
+ "step": 10183
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1259498516675204e-06,
+ "loss": 0.4717,
+ "step": 10184
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.12470093685355e-06,
+ "loss": 0.4607,
+ "step": 10185
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1234526738046303e-06,
+ "loss": 0.4358,
+ "step": 10186
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.122205062612426e-06,
+ "loss": 0.474,
+ "step": 10187
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1209581033685558e-06,
+ "loss": 0.4668,
+ "step": 10188
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1197117961645921e-06,
+ "loss": 0.4598,
+ "step": 10189
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.118466141092055e-06,
+ "loss": 0.4466,
+ "step": 10190
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1172211382424269e-06,
+ "loss": 0.4796,
+ "step": 10191
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1159767877071314e-06,
+ "loss": 0.461,
+ "step": 10192
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1147330895775498e-06,
+ "loss": 0.472,
+ "step": 10193
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1134900439450124e-06,
+ "loss": 0.4753,
+ "step": 10194
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.112247650900804e-06,
+ "loss": 0.449,
+ "step": 10195
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1110059105361616e-06,
+ "loss": 0.4559,
+ "step": 10196
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1097648229422719e-06,
+ "loss": 0.4649,
+ "step": 10197
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.108524388210278e-06,
+ "loss": 0.4535,
+ "step": 10198
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1072846064312715e-06,
+ "loss": 0.4645,
+ "step": 10199
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1060454776962947e-06,
+ "loss": 0.4628,
+ "step": 10200
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1048070020963453e-06,
+ "loss": 0.4658,
+ "step": 10201
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1035691797223724e-06,
+ "loss": 0.4706,
+ "step": 10202
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1023320106652735e-06,
+ "loss": 0.4566,
+ "step": 10203
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1010954950159058e-06,
+ "loss": 0.4699,
+ "step": 10204
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0998596328650724e-06,
+ "loss": 0.4587,
+ "step": 10205
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.098624424303526e-06,
+ "loss": 0.4722,
+ "step": 10206
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0973898694219809e-06,
+ "loss": 0.4548,
+ "step": 10207
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0961559683110946e-06,
+ "loss": 0.4523,
+ "step": 10208
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0949227210614798e-06,
+ "loss": 0.4467,
+ "step": 10209
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0936901277637002e-06,
+ "loss": 0.4952,
+ "step": 10210
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0924581885082753e-06,
+ "loss": 0.4745,
+ "step": 10211
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0912269033856716e-06,
+ "loss": 0.45,
+ "step": 10212
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.089996272486309e-06,
+ "loss": 0.4564,
+ "step": 10213
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.088766295900562e-06,
+ "loss": 0.4536,
+ "step": 10214
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0875369737187502e-06,
+ "loss": 0.4627,
+ "step": 10215
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0863083060311563e-06,
+ "loss": 0.4539,
+ "step": 10216
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0850802929280034e-06,
+ "loss": 0.474,
+ "step": 10217
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0838529344994763e-06,
+ "loss": 0.4448,
+ "step": 10218
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0826262308357038e-06,
+ "loss": 0.4548,
+ "step": 10219
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0814001820267717e-06,
+ "loss": 0.4531,
+ "step": 10220
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0801747881627134e-06,
+ "loss": 0.4624,
+ "step": 10221
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0789500493335191e-06,
+ "loss": 0.4819,
+ "step": 10222
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0777259656291284e-06,
+ "loss": 0.4558,
+ "step": 10223
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.07650253713943e-06,
+ "loss": 0.4588,
+ "step": 10224
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0752797639542712e-06,
+ "loss": 0.4649,
+ "step": 10225
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0740576461634466e-06,
+ "loss": 0.4855,
+ "step": 10226
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0728361838567003e-06,
+ "loss": 0.4787,
+ "step": 10227
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0716153771237359e-06,
+ "loss": 0.4544,
+ "step": 10228
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0703952260542016e-06,
+ "loss": 0.4666,
+ "step": 10229
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0691757307377014e-06,
+ "loss": 0.4757,
+ "step": 10230
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0679568912637872e-06,
+ "loss": 0.4772,
+ "step": 10231
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0667387077219704e-06,
+ "loss": 0.4798,
+ "step": 10232
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0655211802017052e-06,
+ "loss": 0.4355,
+ "step": 10233
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0643043087924043e-06,
+ "loss": 0.4507,
+ "step": 10234
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0630880935834286e-06,
+ "loss": 0.4636,
+ "step": 10235
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0618725346640902e-06,
+ "loss": 0.4574,
+ "step": 10236
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0606576321236585e-06,
+ "loss": 0.473,
+ "step": 10237
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0594433860513452e-06,
+ "loss": 0.458,
+ "step": 10238
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0582297965363264e-06,
+ "loss": 0.4414,
+ "step": 10239
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0570168636677191e-06,
+ "loss": 0.4564,
+ "step": 10240
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.055804587534598e-06,
+ "loss": 0.4609,
+ "step": 10241
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0545929682259847e-06,
+ "loss": 0.4552,
+ "step": 10242
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0533820058308576e-06,
+ "loss": 0.487,
+ "step": 10243
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0521717004381427e-06,
+ "loss": 0.4707,
+ "step": 10244
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0509620521367225e-06,
+ "loss": 0.4729,
+ "step": 10245
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0497530610154283e-06,
+ "loss": 0.4663,
+ "step": 10246
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.04854472716304e-06,
+ "loss": 0.4829,
+ "step": 10247
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0473370506682968e-06,
+ "loss": 0.4565,
+ "step": 10248
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.046130031619883e-06,
+ "loss": 0.4666,
+ "step": 10249
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.044923670106439e-06,
+ "loss": 0.4489,
+ "step": 10250
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0437179662165508e-06,
+ "loss": 0.4793,
+ "step": 10251
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0425129200387662e-06,
+ "loss": 0.4564,
+ "step": 10252
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0413085316615745e-06,
+ "loss": 0.47,
+ "step": 10253
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0401048011734227e-06,
+ "loss": 0.4469,
+ "step": 10254
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0389017286627078e-06,
+ "loss": 0.4772,
+ "step": 10255
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0376993142177771e-06,
+ "loss": 0.475,
+ "step": 10256
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.036497557926931e-06,
+ "loss": 0.4524,
+ "step": 10257
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.035296459878421e-06,
+ "loss": 0.4645,
+ "step": 10258
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0340960201604544e-06,
+ "loss": 0.4579,
+ "step": 10259
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0328962388611841e-06,
+ "loss": 0.4659,
+ "step": 10260
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0316971160687172e-06,
+ "loss": 0.4552,
+ "step": 10261
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0304986518711124e-06,
+ "loss": 0.452,
+ "step": 10262
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.029300846356379e-06,
+ "loss": 0.4648,
+ "step": 10263
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0281036996124793e-06,
+ "loss": 0.4696,
+ "step": 10264
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.026907211727326e-06,
+ "loss": 0.4558,
+ "step": 10265
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0257113827887865e-06,
+ "loss": 0.4506,
+ "step": 10266
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0245162128846764e-06,
+ "loss": 0.4555,
+ "step": 10267
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.023321702102762e-06,
+ "loss": 0.4706,
+ "step": 10268
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0221278505307665e-06,
+ "loss": 0.4593,
+ "step": 10269
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0209346582563596e-06,
+ "loss": 0.4606,
+ "step": 10270
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0197421253671646e-06,
+ "loss": 0.458,
+ "step": 10271
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.018550251950755e-06,
+ "loss": 0.4643,
+ "step": 10272
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0173590380946596e-06,
+ "loss": 0.497,
+ "step": 10273
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.016168483886356e-06,
+ "loss": 0.4946,
+ "step": 10274
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0149785894132714e-06,
+ "loss": 0.4545,
+ "step": 10275
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0137893547627875e-06,
+ "loss": 0.4669,
+ "step": 10276
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0126007800222347e-06,
+ "loss": 0.4839,
+ "step": 10277
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0114128652789023e-06,
+ "loss": 0.4633,
+ "step": 10278
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0102256106200203e-06,
+ "loss": 0.4627,
+ "step": 10279
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0090390161327801e-06,
+ "loss": 0.4656,
+ "step": 10280
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0078530819043174e-06,
+ "loss": 0.4692,
+ "step": 10281
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.006667808021725e-06,
+ "loss": 0.4646,
+ "step": 10282
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0054831945720411e-06,
+ "loss": 0.4597,
+ "step": 10283
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0042992416422614e-06,
+ "loss": 0.4651,
+ "step": 10284
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0031159493193277e-06,
+ "loss": 0.4696,
+ "step": 10285
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.001933317690139e-06,
+ "loss": 0.4727,
+ "step": 10286
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.000751346841542e-06,
+ "loss": 0.4629,
+ "step": 10287
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.995700368603333e-07,
+ "loss": 0.4629,
+ "step": 10288
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.983893878332674e-07,
+ "loss": 0.4644,
+ "step": 10289
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.972093998470444e-07,
+ "loss": 0.4686,
+ "step": 10290
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.960300729883177e-07,
+ "loss": 0.4609,
+ "step": 10291
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.9485140734369e-07,
+ "loss": 0.4454,
+ "step": 10292
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.936734029997218e-07,
+ "loss": 0.4597,
+ "step": 10293
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.92496060042919e-07,
+ "loss": 0.4802,
+ "step": 10294
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.913193785597396e-07,
+ "loss": 0.4629,
+ "step": 10295
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.90143358636596e-07,
+ "loss": 0.4501,
+ "step": 10296
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.88968000359849e-07,
+ "loss": 0.4537,
+ "step": 10297
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.877933038158105e-07,
+ "loss": 0.464,
+ "step": 10298
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.866192690907472e-07,
+ "loss": 0.4678,
+ "step": 10299
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.85445896270878e-07,
+ "loss": 0.4739,
+ "step": 10300
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.84273185442367e-07,
+ "loss": 0.4806,
+ "step": 10301
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.831011366913335e-07,
+ "loss": 0.4504,
+ "step": 10302
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.819297501038494e-07,
+ "loss": 0.4628,
+ "step": 10303
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.80759025765935e-07,
+ "loss": 0.4659,
+ "step": 10304
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.795889637635636e-07,
+ "loss": 0.4496,
+ "step": 10305
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.78419564182659e-07,
+ "loss": 0.4522,
+ "step": 10306
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.772508271090997e-07,
+ "loss": 0.4757,
+ "step": 10307
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.760827526287108e-07,
+ "loss": 0.4711,
+ "step": 10308
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.749153408272693e-07,
+ "loss": 0.4507,
+ "step": 10309
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.737485917905088e-07,
+ "loss": 0.4604,
+ "step": 10310
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.725825056041094e-07,
+ "loss": 0.4598,
+ "step": 10311
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.714170823537007e-07,
+ "loss": 0.471,
+ "step": 10312
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.702523221248706e-07,
+ "loss": 0.4624,
+ "step": 10313
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.69088225003152e-07,
+ "loss": 0.4548,
+ "step": 10314
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.679247910740331e-07,
+ "loss": 0.4672,
+ "step": 10315
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.667620204229488e-07,
+ "loss": 0.4596,
+ "step": 10316
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.6559991313529e-07,
+ "loss": 0.447,
+ "step": 10317
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.64438469296396e-07,
+ "loss": 0.4531,
+ "step": 10318
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.632776889915595e-07,
+ "loss": 0.4692,
+ "step": 10319
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.621175723060216e-07,
+ "loss": 0.4731,
+ "step": 10320
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.609581193249794e-07,
+ "loss": 0.4477,
+ "step": 10321
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.597993301335773e-07,
+ "loss": 0.48,
+ "step": 10322
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.586412048169114e-07,
+ "loss": 0.4617,
+ "step": 10323
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.574837434600293e-07,
+ "loss": 0.4565,
+ "step": 10324
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.563269461479307e-07,
+ "loss": 0.4485,
+ "step": 10325
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.551708129655635e-07,
+ "loss": 0.4653,
+ "step": 10326
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.54015343997834e-07,
+ "loss": 0.46,
+ "step": 10327
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.528605393295909e-07,
+ "loss": 0.4716,
+ "step": 10328
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.517063990456399e-07,
+ "loss": 0.4637,
+ "step": 10329
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.505529232307376e-07,
+ "loss": 0.4507,
+ "step": 10330
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.494001119695884e-07,
+ "loss": 0.4772,
+ "step": 10331
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.482479653468512e-07,
+ "loss": 0.4558,
+ "step": 10332
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.47096483447133e-07,
+ "loss": 0.4491,
+ "step": 10333
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.459456663549959e-07,
+ "loss": 0.4573,
+ "step": 10334
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.447955141549514e-07,
+ "loss": 0.4429,
+ "step": 10335
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.436460269314607e-07,
+ "loss": 0.4629,
+ "step": 10336
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.424972047689374e-07,
+ "loss": 0.4625,
+ "step": 10337
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.413490477517462e-07,
+ "loss": 0.4684,
+ "step": 10338
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.402015559642019e-07,
+ "loss": 0.4807,
+ "step": 10339
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.390547294905739e-07,
+ "loss": 0.4669,
+ "step": 10340
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.379085684150779e-07,
+ "loss": 0.4493,
+ "step": 10341
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.367630728218868e-07,
+ "loss": 0.4639,
+ "step": 10342
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.356182427951188e-07,
+ "loss": 0.4678,
+ "step": 10343
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.344740784188445e-07,
+ "loss": 0.4619,
+ "step": 10344
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.333305797770887e-07,
+ "loss": 0.489,
+ "step": 10345
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.321877469538232e-07,
+ "loss": 0.4565,
+ "step": 10346
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.31045580032972e-07,
+ "loss": 0.4754,
+ "step": 10347
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.299040790984137e-07,
+ "loss": 0.4564,
+ "step": 10348
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.287632442339756e-07,
+ "loss": 0.472,
+ "step": 10349
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.276230755234328e-07,
+ "loss": 0.4752,
+ "step": 10350
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.264835730505184e-07,
+ "loss": 0.4529,
+ "step": 10351
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.25344736898911e-07,
+ "loss": 0.4372,
+ "step": 10352
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.242065671522393e-07,
+ "loss": 0.4867,
+ "step": 10353
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.230690638940898e-07,
+ "loss": 0.4552,
+ "step": 10354
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.219322272079955e-07,
+ "loss": 0.47,
+ "step": 10355
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.207960571774388e-07,
+ "loss": 0.459,
+ "step": 10356
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.196605538858571e-07,
+ "loss": 0.4625,
+ "step": 10357
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.185257174166362e-07,
+ "loss": 0.4528,
+ "step": 10358
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.173915478531148e-07,
+ "loss": 0.4446,
+ "step": 10359
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.162580452785775e-07,
+ "loss": 0.477,
+ "step": 10360
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.151252097762675e-07,
+ "loss": 0.4613,
+ "step": 10361
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.139930414293774e-07,
+ "loss": 0.4511,
+ "step": 10362
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.128615403210472e-07,
+ "loss": 0.4492,
+ "step": 10363
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.117307065343683e-07,
+ "loss": 0.4666,
+ "step": 10364
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.106005401523865e-07,
+ "loss": 0.4672,
+ "step": 10365
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.094710412580942e-07,
+ "loss": 0.4787,
+ "step": 10366
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.083422099344375e-07,
+ "loss": 0.4664,
+ "step": 10367
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.072140462643154e-07,
+ "loss": 0.4515,
+ "step": 10368
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.060865503305738e-07,
+ "loss": 0.4508,
+ "step": 10369
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.049597222160111e-07,
+ "loss": 0.4644,
+ "step": 10370
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.038335620033756e-07,
+ "loss": 0.4454,
+ "step": 10371
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.02708069775372e-07,
+ "loss": 0.4649,
+ "step": 10372
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.015832456146489e-07,
+ "loss": 0.4778,
+ "step": 10373
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.004590896038068e-07,
+ "loss": 0.4462,
+ "step": 10374
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.99335601825404e-07,
+ "loss": 0.4462,
+ "step": 10375
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.982127823619413e-07,
+ "loss": 0.4594,
+ "step": 10376
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.970906312958749e-07,
+ "loss": 0.4522,
+ "step": 10377
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.959691487096111e-07,
+ "loss": 0.482,
+ "step": 10378
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.948483346855064e-07,
+ "loss": 0.4502,
+ "step": 10379
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.937281893058658e-07,
+ "loss": 0.4623,
+ "step": 10380
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.926087126529548e-07,
+ "loss": 0.4559,
+ "step": 10381
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.914899048089765e-07,
+ "loss": 0.4734,
+ "step": 10382
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.903717658560961e-07,
+ "loss": 0.4638,
+ "step": 10383
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.892542958764238e-07,
+ "loss": 0.4368,
+ "step": 10384
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.881374949520216e-07,
+ "loss": 0.4844,
+ "step": 10385
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.870213631649038e-07,
+ "loss": 0.4673,
+ "step": 10386
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.859059005970305e-07,
+ "loss": 0.4555,
+ "step": 10387
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.847911073303206e-07,
+ "loss": 0.4701,
+ "step": 10388
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.836769834466397e-07,
+ "loss": 0.4677,
+ "step": 10389
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.825635290278034e-07,
+ "loss": 0.4631,
+ "step": 10390
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.814507441555775e-07,
+ "loss": 0.4691,
+ "step": 10391
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.803386289116833e-07,
+ "loss": 0.4743,
+ "step": 10392
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.792271833777888e-07,
+ "loss": 0.4724,
+ "step": 10393
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.78116407635512e-07,
+ "loss": 0.4461,
+ "step": 10394
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.770063017664276e-07,
+ "loss": 0.4705,
+ "step": 10395
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.75896865852055e-07,
+ "loss": 0.4547,
+ "step": 10396
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.747880999738667e-07,
+ "loss": 0.4837,
+ "step": 10397
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.736800042132853e-07,
+ "loss": 0.4696,
+ "step": 10398
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.725725786516858e-07,
+ "loss": 0.4605,
+ "step": 10399
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.714658233703921e-07,
+ "loss": 0.4868,
+ "step": 10400
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.703597384506779e-07,
+ "loss": 0.4542,
+ "step": 10401
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.692543239737706e-07,
+ "loss": 0.4542,
+ "step": 10402
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.681495800208517e-07,
+ "loss": 0.4587,
+ "step": 10403
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.670455066730444e-07,
+ "loss": 0.4659,
+ "step": 10404
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.65942104011428e-07,
+ "loss": 0.474,
+ "step": 10405
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.648393721170323e-07,
+ "loss": 0.4734,
+ "step": 10406
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.63737311070837e-07,
+ "loss": 0.4765,
+ "step": 10407
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.626359209537716e-07,
+ "loss": 0.4577,
+ "step": 10408
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.615352018467204e-07,
+ "loss": 0.4625,
+ "step": 10409
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.604351538305156e-07,
+ "loss": 0.4697,
+ "step": 10410
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.593357769859368e-07,
+ "loss": 0.4622,
+ "step": 10411
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.582370713937193e-07,
+ "loss": 0.4769,
+ "step": 10412
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.571390371345489e-07,
+ "loss": 0.4899,
+ "step": 10413
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.560416742890599e-07,
+ "loss": 0.4746,
+ "step": 10414
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.549449829378354e-07,
+ "loss": 0.4566,
+ "step": 10415
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.538489631614167e-07,
+ "loss": 0.4804,
+ "step": 10416
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.527536150402882e-07,
+ "loss": 0.4592,
+ "step": 10417
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.516589386548879e-07,
+ "loss": 0.4471,
+ "step": 10418
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.505649340856048e-07,
+ "loss": 0.4799,
+ "step": 10419
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.494716014127768e-07,
+ "loss": 0.4877,
+ "step": 10420
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.483789407166932e-07,
+ "loss": 0.4582,
+ "step": 10421
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.472869520775972e-07,
+ "loss": 0.4554,
+ "step": 10422
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.461956355756772e-07,
+ "loss": 0.4487,
+ "step": 10423
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.451049912910769e-07,
+ "loss": 0.4454,
+ "step": 10424
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.440150193038888e-07,
+ "loss": 0.4578,
+ "step": 10425
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.429257196941554e-07,
+ "loss": 0.4786,
+ "step": 10426
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.418370925418695e-07,
+ "loss": 0.4635,
+ "step": 10427
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.407491379269739e-07,
+ "loss": 0.4748,
+ "step": 10428
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.396618559293679e-07,
+ "loss": 0.4652,
+ "step": 10429
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.385752466288933e-07,
+ "loss": 0.4624,
+ "step": 10430
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.374893101053482e-07,
+ "loss": 0.4563,
+ "step": 10431
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.364040464384771e-07,
+ "loss": 0.4677,
+ "step": 10432
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.353194557079791e-07,
+ "loss": 0.4588,
+ "step": 10433
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.34235537993503e-07,
+ "loss": 0.4498,
+ "step": 10434
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.331522933746428e-07,
+ "loss": 0.4734,
+ "step": 10435
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.320697219309526e-07,
+ "loss": 0.4523,
+ "step": 10436
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.309878237419289e-07,
+ "loss": 0.4687,
+ "step": 10437
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.299065988870236e-07,
+ "loss": 0.4675,
+ "step": 10438
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.288260474456367e-07,
+ "loss": 0.4673,
+ "step": 10439
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.277461694971178e-07,
+ "loss": 0.4436,
+ "step": 10440
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.266669651207704e-07,
+ "loss": 0.4659,
+ "step": 10441
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.255884343958453e-07,
+ "loss": 0.4867,
+ "step": 10442
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.245105774015461e-07,
+ "loss": 0.4468,
+ "step": 10443
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.234333942170281e-07,
+ "loss": 0.4678,
+ "step": 10444
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.223568849213925e-07,
+ "loss": 0.4726,
+ "step": 10445
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.212810495936952e-07,
+ "loss": 0.4651,
+ "step": 10446
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.202058883129404e-07,
+ "loss": 0.474,
+ "step": 10447
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.191314011580842e-07,
+ "loss": 0.4809,
+ "step": 10448
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.180575882080288e-07,
+ "loss": 0.4541,
+ "step": 10449
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.169844495416368e-07,
+ "loss": 0.4656,
+ "step": 10450
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.159119852377106e-07,
+ "loss": 0.4456,
+ "step": 10451
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.148401953750096e-07,
+ "loss": 0.4625,
+ "step": 10452
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.137690800322384e-07,
+ "loss": 0.4638,
+ "step": 10453
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.126986392880587e-07,
+ "loss": 0.4811,
+ "step": 10454
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.116288732210787e-07,
+ "loss": 0.4776,
+ "step": 10455
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.105597819098554e-07,
+ "loss": 0.4533,
+ "step": 10456
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.094913654329018e-07,
+ "loss": 0.4689,
+ "step": 10457
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.08423623868676e-07,
+ "loss": 0.4605,
+ "step": 10458
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.073565572955877e-07,
+ "loss": 0.4652,
+ "step": 10459
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.062901657919998e-07,
+ "loss": 0.4584,
+ "step": 10460
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.052244494362227e-07,
+ "loss": 0.4699,
+ "step": 10461
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.041594083065152e-07,
+ "loss": 0.4525,
+ "step": 10462
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.030950424810946e-07,
+ "loss": 0.476,
+ "step": 10463
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.020313520381206e-07,
+ "loss": 0.4795,
+ "step": 10464
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.009683370557075e-07,
+ "loss": 0.4751,
+ "step": 10465
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.999059976119183e-07,
+ "loss": 0.4427,
+ "step": 10466
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.988443337847673e-07,
+ "loss": 0.4616,
+ "step": 10467
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.977833456522166e-07,
+ "loss": 0.4687,
+ "step": 10468
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.967230332921816e-07,
+ "loss": 0.4731,
+ "step": 10469
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.956633967825289e-07,
+ "loss": 0.4715,
+ "step": 10470
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.946044362010718e-07,
+ "loss": 0.4532,
+ "step": 10471
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.935461516255782e-07,
+ "loss": 0.4768,
+ "step": 10472
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.924885431337604e-07,
+ "loss": 0.4527,
+ "step": 10473
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.914316108032882e-07,
+ "loss": 0.4693,
+ "step": 10474
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.903753547117788e-07,
+ "loss": 0.4768,
+ "step": 10475
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.893197749367943e-07,
+ "loss": 0.4678,
+ "step": 10476
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.882648715558583e-07,
+ "loss": 0.4589,
+ "step": 10477
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.872106446464345e-07,
+ "loss": 0.4649,
+ "step": 10478
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.861570942859431e-07,
+ "loss": 0.4652,
+ "step": 10479
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.851042205517512e-07,
+ "loss": 0.4853,
+ "step": 10480
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.840520235211768e-07,
+ "loss": 0.4503,
+ "step": 10481
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.830005032714905e-07,
+ "loss": 0.463,
+ "step": 10482
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.819496598799093e-07,
+ "loss": 0.4523,
+ "step": 10483
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.808994934236058e-07,
+ "loss": 0.4681,
+ "step": 10484
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.798500039796974e-07,
+ "loss": 0.4989,
+ "step": 10485
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.788011916252558e-07,
+ "loss": 0.4629,
+ "step": 10486
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.777530564373015e-07,
+ "loss": 0.4475,
+ "step": 10487
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.767055984928041e-07,
+ "loss": 0.4632,
+ "step": 10488
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.756588178686853e-07,
+ "loss": 0.4704,
+ "step": 10489
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.746127146418148e-07,
+ "loss": 0.4527,
+ "step": 10490
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.735672888890155e-07,
+ "loss": 0.4651,
+ "step": 10491
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.725225406870607e-07,
+ "loss": 0.4569,
+ "step": 10492
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.714784701126687e-07,
+ "loss": 0.464,
+ "step": 10493
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.704350772425129e-07,
+ "loss": 0.4621,
+ "step": 10494
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.693923621532184e-07,
+ "loss": 0.4683,
+ "step": 10495
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.683503249213554e-07,
+ "loss": 0.4905,
+ "step": 10496
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.673089656234456e-07,
+ "loss": 0.4562,
+ "step": 10497
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.662682843359648e-07,
+ "loss": 0.4489,
+ "step": 10498
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.652282811353362e-07,
+ "loss": 0.4638,
+ "step": 10499
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.641889560979321e-07,
+ "loss": 0.4682,
+ "step": 10500
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.631503093000758e-07,
+ "loss": 0.4702,
+ "step": 10501
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.621123408180419e-07,
+ "loss": 0.4686,
+ "step": 10502
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.61075050728054e-07,
+ "loss": 0.452,
+ "step": 10503
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.600384391062865e-07,
+ "loss": 0.4584,
+ "step": 10504
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.590025060288642e-07,
+ "loss": 0.4783,
+ "step": 10505
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.579672515718628e-07,
+ "loss": 0.4468,
+ "step": 10506
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.569326758113049e-07,
+ "loss": 0.4802,
+ "step": 10507
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.558987788231675e-07,
+ "loss": 0.4594,
+ "step": 10508
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.548655606833755e-07,
+ "loss": 0.4826,
+ "step": 10509
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.538330214678002e-07,
+ "loss": 0.4664,
+ "step": 10510
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.528011612522723e-07,
+ "loss": 0.4502,
+ "step": 10511
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.517699801125655e-07,
+ "loss": 0.45,
+ "step": 10512
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.507394781244038e-07,
+ "loss": 0.4798,
+ "step": 10513
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.497096553634653e-07,
+ "loss": 0.4694,
+ "step": 10514
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.48680511905373e-07,
+ "loss": 0.4539,
+ "step": 10515
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.476520478257065e-07,
+ "loss": 0.466,
+ "step": 10516
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.466242631999887e-07,
+ "loss": 0.4647,
+ "step": 10517
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.455971581036991e-07,
+ "loss": 0.4704,
+ "step": 10518
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.44570732612262e-07,
+ "loss": 0.4576,
+ "step": 10519
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.435449868010535e-07,
+ "loss": 0.4648,
+ "step": 10520
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.425199207454014e-07,
+ "loss": 0.4485,
+ "step": 10521
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.41495534520581e-07,
+ "loss": 0.4636,
+ "step": 10522
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.404718282018197e-07,
+ "loss": 0.4768,
+ "step": 10523
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.394488018642931e-07,
+ "loss": 0.4482,
+ "step": 10524
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.3842645558313e-07,
+ "loss": 0.4373,
+ "step": 10525
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.374047894334047e-07,
+ "loss": 0.4618,
+ "step": 10526
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.363838034901471e-07,
+ "loss": 0.4681,
+ "step": 10527
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.35363497828333e-07,
+ "loss": 0.4577,
+ "step": 10528
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.343438725228891e-07,
+ "loss": 0.4653,
+ "step": 10529
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.33324927648692e-07,
+ "loss": 0.4989,
+ "step": 10530
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.323066632805676e-07,
+ "loss": 0.4368,
+ "step": 10531
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.312890794932969e-07,
+ "loss": 0.4771,
+ "step": 10532
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.302721763616039e-07,
+ "loss": 0.4751,
+ "step": 10533
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.292559539601674e-07,
+ "loss": 0.4537,
+ "step": 10534
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.28240412363611e-07,
+ "loss": 0.4543,
+ "step": 10535
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.272255516465176e-07,
+ "loss": 0.4839,
+ "step": 10536
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.262113718834086e-07,
+ "loss": 0.4525,
+ "step": 10537
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.251978731487664e-07,
+ "loss": 0.4823,
+ "step": 10538
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.241850555170149e-07,
+ "loss": 0.4638,
+ "step": 10539
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.231729190625314e-07,
+ "loss": 0.4807,
+ "step": 10540
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.221614638596441e-07,
+ "loss": 0.4729,
+ "step": 10541
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.211506899826304e-07,
+ "loss": 0.4802,
+ "step": 10542
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.201405975057152e-07,
+ "loss": 0.4365,
+ "step": 10543
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.191311865030748e-07,
+ "loss": 0.4644,
+ "step": 10544
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.18122457048841e-07,
+ "loss": 0.4555,
+ "step": 10545
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.171144092170845e-07,
+ "loss": 0.4495,
+ "step": 10546
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.161070430818385e-07,
+ "loss": 0.4348,
+ "step": 10547
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.151003587170757e-07,
+ "loss": 0.4765,
+ "step": 10548
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.14094356196724e-07,
+ "loss": 0.4557,
+ "step": 10549
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.130890355946596e-07,
+ "loss": 0.4436,
+ "step": 10550
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.12084396984708e-07,
+ "loss": 0.4619,
+ "step": 10551
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.11080440440648e-07,
+ "loss": 0.4572,
+ "step": 10552
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.100771660362061e-07,
+ "loss": 0.464,
+ "step": 10553
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.090745738450566e-07,
+ "loss": 0.465,
+ "step": 10554
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.080726639408264e-07,
+ "loss": 0.4505,
+ "step": 10555
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.070714363970899e-07,
+ "loss": 0.458,
+ "step": 10556
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.060708912873771e-07,
+ "loss": 0.4661,
+ "step": 10557
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.050710286851603e-07,
+ "loss": 0.4561,
+ "step": 10558
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.040718486638676e-07,
+ "loss": 0.4619,
+ "step": 10559
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.030733512968735e-07,
+ "loss": 0.4623,
+ "step": 10560
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.020755366575038e-07,
+ "loss": 0.4636,
+ "step": 10561
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.010784048190344e-07,
+ "loss": 0.4576,
+ "step": 10562
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.000819558546901e-07,
+ "loss": 0.4482,
+ "step": 10563
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.990861898376444e-07,
+ "loss": 0.4662,
+ "step": 10564
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.980911068410224e-07,
+ "loss": 0.4577,
+ "step": 10565
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.97096706937902e-07,
+ "loss": 0.4521,
+ "step": 10566
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.961029902013039e-07,
+ "loss": 0.452,
+ "step": 10567
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.951099567042052e-07,
+ "loss": 0.4763,
+ "step": 10568
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.941176065195299e-07,
+ "loss": 0.4561,
+ "step": 10569
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.931259397201517e-07,
+ "loss": 0.4594,
+ "step": 10570
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.921349563788949e-07,
+ "loss": 0.4663,
+ "step": 10571
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.911446565685298e-07,
+ "loss": 0.4581,
+ "step": 10572
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.901550403617852e-07,
+ "loss": 0.4803,
+ "step": 10573
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.891661078313317e-07,
+ "loss": 0.4621,
+ "step": 10574
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.881778590497923e-07,
+ "loss": 0.4698,
+ "step": 10575
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.87190294089738e-07,
+ "loss": 0.4748,
+ "step": 10576
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.86203413023696e-07,
+ "loss": 0.453,
+ "step": 10577
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.852172159241343e-07,
+ "loss": 0.4714,
+ "step": 10578
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.842317028634793e-07,
+ "loss": 0.4762,
+ "step": 10579
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.832468739141007e-07,
+ "loss": 0.4559,
+ "step": 10580
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.822627291483197e-07,
+ "loss": 0.4699,
+ "step": 10581
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.812792686384095e-07,
+ "loss": 0.4521,
+ "step": 10582
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.802964924565891e-07,
+ "loss": 0.4515,
+ "step": 10583
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.793144006750318e-07,
+ "loss": 0.4689,
+ "step": 10584
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.783329933658555e-07,
+ "loss": 0.4531,
+ "step": 10585
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.773522706011337e-07,
+ "loss": 0.4877,
+ "step": 10586
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.763722324528843e-07,
+ "loss": 0.4599,
+ "step": 10587
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.753928789930797e-07,
+ "loss": 0.469,
+ "step": 10588
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.74414210293638e-07,
+ "loss": 0.4548,
+ "step": 10589
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.734362264264283e-07,
+ "loss": 0.4717,
+ "step": 10590
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.724589274632698e-07,
+ "loss": 0.4463,
+ "step": 10591
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.714823134759307e-07,
+ "loss": 0.4454,
+ "step": 10592
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.705063845361315e-07,
+ "loss": 0.4723,
+ "step": 10593
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.695311407155391e-07,
+ "loss": 0.4621,
+ "step": 10594
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.68556582085772e-07,
+ "loss": 0.4683,
+ "step": 10595
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.675827087183961e-07,
+ "loss": 0.4772,
+ "step": 10596
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.666095206849288e-07,
+ "loss": 0.4646,
+ "step": 10597
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.656370180568395e-07,
+ "loss": 0.4574,
+ "step": 10598
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.646652009055409e-07,
+ "loss": 0.4854,
+ "step": 10599
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.63694069302403e-07,
+ "loss": 0.4795,
+ "step": 10600
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.627236233187407e-07,
+ "loss": 0.4678,
+ "step": 10601
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.61753863025818e-07,
+ "loss": 0.4546,
+ "step": 10602
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.607847884948515e-07,
+ "loss": 0.4514,
+ "step": 10603
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.598163997970053e-07,
+ "loss": 0.4607,
+ "step": 10604
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.588486970033936e-07,
+ "loss": 0.467,
+ "step": 10605
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.578816801850796e-07,
+ "loss": 0.461,
+ "step": 10606
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.569153494130798e-07,
+ "loss": 0.4654,
+ "step": 10607
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.55949704758354e-07,
+ "loss": 0.485,
+ "step": 10608
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.549847462918191e-07,
+ "loss": 0.4681,
+ "step": 10609
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.540204740843348e-07,
+ "loss": 0.4647,
+ "step": 10610
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.530568882067145e-07,
+ "loss": 0.4694,
+ "step": 10611
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.520939887297184e-07,
+ "loss": 0.4592,
+ "step": 10612
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.511317757240598e-07,
+ "loss": 0.4805,
+ "step": 10613
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.50170249260399e-07,
+ "loss": 0.4699,
+ "step": 10614
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.492094094093459e-07,
+ "loss": 0.4552,
+ "step": 10615
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.482492562414621e-07,
+ "loss": 0.4495,
+ "step": 10616
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.472897898272534e-07,
+ "loss": 0.4724,
+ "step": 10617
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.463310102371834e-07,
+ "loss": 0.4603,
+ "step": 10618
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.453729175416579e-07,
+ "loss": 0.4423,
+ "step": 10619
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.444155118110373e-07,
+ "loss": 0.4421,
+ "step": 10620
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.434587931156299e-07,
+ "loss": 0.4656,
+ "step": 10621
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.425027615256907e-07,
+ "loss": 0.4639,
+ "step": 10622
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.415474171114288e-07,
+ "loss": 0.4575,
+ "step": 10623
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.405927599429995e-07,
+ "loss": 0.4592,
+ "step": 10624
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.396387900905099e-07,
+ "loss": 0.4616,
+ "step": 10625
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.386855076240117e-07,
+ "loss": 0.4553,
+ "step": 10626
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.377329126135168e-07,
+ "loss": 0.4603,
+ "step": 10627
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.367810051289746e-07,
+ "loss": 0.4622,
+ "step": 10628
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.358297852402894e-07,
+ "loss": 0.4787,
+ "step": 10629
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.348792530173187e-07,
+ "loss": 0.4648,
+ "step": 10630
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.339294085298631e-07,
+ "loss": 0.4586,
+ "step": 10631
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.329802518476746e-07,
+ "loss": 0.464,
+ "step": 10632
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.320317830404554e-07,
+ "loss": 0.4964,
+ "step": 10633
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.310840021778586e-07,
+ "loss": 0.4679,
+ "step": 10634
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.30136909329484e-07,
+ "loss": 0.4348,
+ "step": 10635
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.291905045648839e-07,
+ "loss": 0.4809,
+ "step": 10636
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.282447879535558e-07,
+ "loss": 0.4575,
+ "step": 10637
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.272997595649499e-07,
+ "loss": 0.4739,
+ "step": 10638
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.263554194684662e-07,
+ "loss": 0.4522,
+ "step": 10639
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.254117677334514e-07,
+ "loss": 0.4417,
+ "step": 10640
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.244688044292058e-07,
+ "loss": 0.4564,
+ "step": 10641
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.23526529624976e-07,
+ "loss": 0.4505,
+ "step": 10642
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.225849433899578e-07,
+ "loss": 0.4596,
+ "step": 10643
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.216440457932981e-07,
+ "loss": 0.4338,
+ "step": 10644
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.207038369040918e-07,
+ "loss": 0.4676,
+ "step": 10645
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.197643167913847e-07,
+ "loss": 0.4753,
+ "step": 10646
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.188254855241693e-07,
+ "loss": 0.4584,
+ "step": 10647
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.178873431713928e-07,
+ "loss": 0.4765,
+ "step": 10648
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.169498898019443e-07,
+ "loss": 0.4592,
+ "step": 10649
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.160131254846702e-07,
+ "loss": 0.4643,
+ "step": 10650
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.150770502883618e-07,
+ "loss": 0.4684,
+ "step": 10651
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.141416642817599e-07,
+ "loss": 0.4886,
+ "step": 10652
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.13206967533555e-07,
+ "loss": 0.4641,
+ "step": 10653
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.122729601123878e-07,
+ "loss": 0.4639,
+ "step": 10654
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.113396420868489e-07,
+ "loss": 0.4511,
+ "step": 10655
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.104070135254758e-07,
+ "loss": 0.4748,
+ "step": 10656
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.09475074496757e-07,
+ "loss": 0.4607,
+ "step": 10657
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.085438250691311e-07,
+ "loss": 0.4689,
+ "step": 10658
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.076132653109834e-07,
+ "loss": 0.4497,
+ "step": 10659
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.066833952906515e-07,
+ "loss": 0.4615,
+ "step": 10660
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.057542150764218e-07,
+ "loss": 0.4654,
+ "step": 10661
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.048257247365297e-07,
+ "loss": 0.4703,
+ "step": 10662
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.038979243391597e-07,
+ "loss": 0.4581,
+ "step": 10663
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.029708139524438e-07,
+ "loss": 0.4653,
+ "step": 10664
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.020443936444664e-07,
+ "loss": 0.4835,
+ "step": 10665
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.0111866348326e-07,
+ "loss": 0.4538,
+ "step": 10666
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.001936235368044e-07,
+ "loss": 0.4771,
+ "step": 10667
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.992692738730332e-07,
+ "loss": 0.4604,
+ "step": 10668
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.983456145598266e-07,
+ "loss": 0.4592,
+ "step": 10669
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.974226456650123e-07,
+ "loss": 0.4773,
+ "step": 10670
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.965003672563719e-07,
+ "loss": 0.472,
+ "step": 10671
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.955787794016321e-07,
+ "loss": 0.4521,
+ "step": 10672
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.946578821684713e-07,
+ "loss": 0.4492,
+ "step": 10673
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.937376756245139e-07,
+ "loss": 0.4726,
+ "step": 10674
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.928181598373395e-07,
+ "loss": 0.4556,
+ "step": 10675
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.918993348744728e-07,
+ "loss": 0.4523,
+ "step": 10676
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.909812008033866e-07,
+ "loss": 0.461,
+ "step": 10677
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.900637576915069e-07,
+ "loss": 0.4729,
+ "step": 10678
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.891470056062043e-07,
+ "loss": 0.4656,
+ "step": 10679
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.882309446148038e-07,
+ "loss": 0.4639,
+ "step": 10680
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.87315574784576e-07,
+ "loss": 0.4651,
+ "step": 10681
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.864008961827428e-07,
+ "loss": 0.4665,
+ "step": 10682
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.854869088764737e-07,
+ "loss": 0.4629,
+ "step": 10683
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.845736129328883e-07,
+ "loss": 0.4569,
+ "step": 10684
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.836610084190541e-07,
+ "loss": 0.455,
+ "step": 10685
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.82749095401991e-07,
+ "loss": 0.4809,
+ "step": 10686
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.81837873948663e-07,
+ "loss": 0.4639,
+ "step": 10687
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.809273441259899e-07,
+ "loss": 0.4451,
+ "step": 10688
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.800175060008362e-07,
+ "loss": 0.4691,
+ "step": 10689
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.791083596400148e-07,
+ "loss": 0.467,
+ "step": 10690
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.781999051102927e-07,
+ "loss": 0.463,
+ "step": 10691
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.772921424783806e-07,
+ "loss": 0.4638,
+ "step": 10692
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.763850718109421e-07,
+ "loss": 0.475,
+ "step": 10693
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.754786931745859e-07,
+ "loss": 0.4652,
+ "step": 10694
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.745730066358779e-07,
+ "loss": 0.4622,
+ "step": 10695
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.736680122613237e-07,
+ "loss": 0.4608,
+ "step": 10696
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.727637101173844e-07,
+ "loss": 0.4586,
+ "step": 10697
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.718601002704671e-07,
+ "loss": 0.442,
+ "step": 10698
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.709571827869287e-07,
+ "loss": 0.4706,
+ "step": 10699
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.70054957733076e-07,
+ "loss": 0.4871,
+ "step": 10700
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.691534251751652e-07,
+ "loss": 0.4701,
+ "step": 10701
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.682525851794019e-07,
+ "loss": 0.4756,
+ "step": 10702
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.673524378119388e-07,
+ "loss": 0.4662,
+ "step": 10703
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.664529831388799e-07,
+ "loss": 0.4683,
+ "step": 10704
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.655542212262766e-07,
+ "loss": 0.4452,
+ "step": 10705
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.646561521401317e-07,
+ "loss": 0.4809,
+ "step": 10706
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.637587759463925e-07,
+ "loss": 0.4604,
+ "step": 10707
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.628620927109607e-07,
+ "loss": 0.4794,
+ "step": 10708
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.619661024996848e-07,
+ "loss": 0.4603,
+ "step": 10709
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.610708053783642e-07,
+ "loss": 0.4669,
+ "step": 10710
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.60176201412741e-07,
+ "loss": 0.471,
+ "step": 10711
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.59282290668517e-07,
+ "loss": 0.4629,
+ "step": 10712
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.58389073211335e-07,
+ "loss": 0.4513,
+ "step": 10713
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.574965491067874e-07,
+ "loss": 0.5152,
+ "step": 10714
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.566047184204182e-07,
+ "loss": 0.4614,
+ "step": 10715
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.557135812177228e-07,
+ "loss": 0.4401,
+ "step": 10716
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.548231375641389e-07,
+ "loss": 0.4655,
+ "step": 10717
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.539333875250596e-07,
+ "loss": 0.4761,
+ "step": 10718
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.530443311658218e-07,
+ "loss": 0.4628,
+ "step": 10719
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.521559685517153e-07,
+ "loss": 0.4645,
+ "step": 10720
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.51268299747978e-07,
+ "loss": 0.4947,
+ "step": 10721
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.503813248197965e-07,
+ "loss": 0.4574,
+ "step": 10722
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.494950438323077e-07,
+ "loss": 0.4685,
+ "step": 10723
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.48609456850594e-07,
+ "loss": 0.4751,
+ "step": 10724
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.477245639396922e-07,
+ "loss": 0.4682,
+ "step": 10725
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.468403651645826e-07,
+ "loss": 0.4474,
+ "step": 10726
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.459568605901977e-07,
+ "loss": 0.4704,
+ "step": 10727
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.450740502814178e-07,
+ "loss": 0.4847,
+ "step": 10728
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.441919343030744e-07,
+ "loss": 0.4695,
+ "step": 10729
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.433105127199467e-07,
+ "loss": 0.4646,
+ "step": 10730
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.424297855967597e-07,
+ "loss": 0.4771,
+ "step": 10731
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.415497529981928e-07,
+ "loss": 0.4748,
+ "step": 10732
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.40670414988872e-07,
+ "loss": 0.4688,
+ "step": 10733
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.397917716333723e-07,
+ "loss": 0.4381,
+ "step": 10734
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.389138229962155e-07,
+ "loss": 0.4684,
+ "step": 10735
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.380365691418765e-07,
+ "loss": 0.4519,
+ "step": 10736
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.371600101347763e-07,
+ "loss": 0.4714,
+ "step": 10737
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.362841460392875e-07,
+ "loss": 0.4653,
+ "step": 10738
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.354089769197268e-07,
+ "loss": 0.4803,
+ "step": 10739
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.345345028403659e-07,
+ "loss": 0.4518,
+ "step": 10740
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.33660723865419e-07,
+ "loss": 0.4649,
+ "step": 10741
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.32787640059057e-07,
+ "loss": 0.461,
+ "step": 10742
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.31915251485392e-07,
+ "loss": 0.4962,
+ "step": 10743
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.310435582084917e-07,
+ "loss": 0.4649,
+ "step": 10744
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.301725602923691e-07,
+ "loss": 0.4624,
+ "step": 10745
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.293022578009843e-07,
+ "loss": 0.467,
+ "step": 10746
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.284326507982507e-07,
+ "loss": 0.4678,
+ "step": 10747
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.275637393480282e-07,
+ "loss": 0.4608,
+ "step": 10748
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.266955235141235e-07,
+ "loss": 0.4783,
+ "step": 10749
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.258280033602992e-07,
+ "loss": 0.4863,
+ "step": 10750
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.249611789502607e-07,
+ "loss": 0.4491,
+ "step": 10751
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.240950503476616e-07,
+ "loss": 0.4695,
+ "step": 10752
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.232296176161101e-07,
+ "loss": 0.4812,
+ "step": 10753
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.223648808191584e-07,
+ "loss": 0.4459,
+ "step": 10754
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.215008400203103e-07,
+ "loss": 0.4771,
+ "step": 10755
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.20637495283014e-07,
+ "loss": 0.4675,
+ "step": 10756
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.197748466706742e-07,
+ "loss": 0.4509,
+ "step": 10757
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.189128942466393e-07,
+ "loss": 0.4566,
+ "step": 10758
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.180516380742051e-07,
+ "loss": 0.4632,
+ "step": 10759
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.171910782166212e-07,
+ "loss": 0.4563,
+ "step": 10760
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.163312147370824e-07,
+ "loss": 0.4507,
+ "step": 10761
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.154720476987329e-07,
+ "loss": 0.4547,
+ "step": 10762
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.146135771646655e-07,
+ "loss": 0.4596,
+ "step": 10763
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.137558031979273e-07,
+ "loss": 0.4456,
+ "step": 10764
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.128987258615059e-07,
+ "loss": 0.4591,
+ "step": 10765
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.12042345218342e-07,
+ "loss": 0.4841,
+ "step": 10766
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.111866613313255e-07,
+ "loss": 0.4637,
+ "step": 10767
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.103316742632935e-07,
+ "loss": 0.4692,
+ "step": 10768
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.094773840770306e-07,
+ "loss": 0.4977,
+ "step": 10769
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.086237908352776e-07,
+ "loss": 0.4727,
+ "step": 10770
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.077708946007143e-07,
+ "loss": 0.4818,
+ "step": 10771
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.069186954359761e-07,
+ "loss": 0.4501,
+ "step": 10772
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.060671934036421e-07,
+ "loss": 0.4501,
+ "step": 10773
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.052163885662476e-07,
+ "loss": 0.4629,
+ "step": 10774
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.043662809862692e-07,
+ "loss": 0.4542,
+ "step": 10775
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.03516870726134e-07,
+ "loss": 0.4559,
+ "step": 10776
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.026681578482229e-07,
+ "loss": 0.4821,
+ "step": 10777
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.018201424148606e-07,
+ "loss": 0.4764,
+ "step": 10778
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.009728244883205e-07,
+ "loss": 0.4775,
+ "step": 10779
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.001262041308263e-07,
+ "loss": 0.4691,
+ "step": 10780
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.992802814045505e-07,
+ "loss": 0.4439,
+ "step": 10781
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.984350563716145e-07,
+ "loss": 0.4732,
+ "step": 10782
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.975905290940874e-07,
+ "loss": 0.4788,
+ "step": 10783
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.967466996339887e-07,
+ "loss": 0.471,
+ "step": 10784
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.959035680532854e-07,
+ "loss": 0.4454,
+ "step": 10785
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.950611344138945e-07,
+ "loss": 0.4511,
+ "step": 10786
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.9421939877768e-07,
+ "loss": 0.4767,
+ "step": 10787
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.933783612064546e-07,
+ "loss": 0.4464,
+ "step": 10788
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.925380217619813e-07,
+ "loss": 0.4537,
+ "step": 10789
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.916983805059705e-07,
+ "loss": 0.4717,
+ "step": 10790
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.90859437500083e-07,
+ "loss": 0.4549,
+ "step": 10791
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.900211928059284e-07,
+ "loss": 0.4547,
+ "step": 10792
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.891836464850596e-07,
+ "loss": 0.4571,
+ "step": 10793
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.883467985989876e-07,
+ "loss": 0.4762,
+ "step": 10794
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.875106492091642e-07,
+ "loss": 0.4692,
+ "step": 10795
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.866751983769935e-07,
+ "loss": 0.4702,
+ "step": 10796
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.858404461638266e-07,
+ "loss": 0.4569,
+ "step": 10797
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.850063926309657e-07,
+ "loss": 0.4488,
+ "step": 10798
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.841730378396592e-07,
+ "loss": 0.4586,
+ "step": 10799
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.833403818511062e-07,
+ "loss": 0.4559,
+ "step": 10800
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.825084247264522e-07,
+ "loss": 0.4566,
+ "step": 10801
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.816771665267939e-07,
+ "loss": 0.4449,
+ "step": 10802
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.808466073131735e-07,
+ "loss": 0.4585,
+ "step": 10803
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.800167471465844e-07,
+ "loss": 0.4537,
+ "step": 10804
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.791875860879703e-07,
+ "loss": 0.4585,
+ "step": 10805
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.783591241982199e-07,
+ "loss": 0.4525,
+ "step": 10806
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.775313615381716e-07,
+ "loss": 0.4708,
+ "step": 10807
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.767042981686143e-07,
+ "loss": 0.4424,
+ "step": 10808
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.758779341502817e-07,
+ "loss": 0.47,
+ "step": 10809
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.750522695438597e-07,
+ "loss": 0.453,
+ "step": 10810
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.742273044099821e-07,
+ "loss": 0.4558,
+ "step": 10811
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.7340303880923145e-07,
+ "loss": 0.4708,
+ "step": 10812
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.7257947280213713e-07,
+ "loss": 0.4453,
+ "step": 10813
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.7175660644917745e-07,
+ "loss": 0.4709,
+ "step": 10814
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.709344398107829e-07,
+ "loss": 0.4792,
+ "step": 10815
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.701129729473286e-07,
+ "loss": 0.4693,
+ "step": 10816
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.6929220591913847e-07,
+ "loss": 0.4548,
+ "step": 10817
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6847213878648876e-07,
+ "loss": 0.4827,
+ "step": 10818
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6765277160960133e-07,
+ "loss": 0.4751,
+ "step": 10819
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6683410444864573e-07,
+ "loss": 0.4529,
+ "step": 10820
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6601613736374173e-07,
+ "loss": 0.4748,
+ "step": 10821
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6519887041495905e-07,
+ "loss": 0.4607,
+ "step": 10822
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6438230366231075e-07,
+ "loss": 0.4451,
+ "step": 10823
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6356643716576557e-07,
+ "loss": 0.4693,
+ "step": 10824
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.627512709852355e-07,
+ "loss": 0.4662,
+ "step": 10825
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.61936805180585e-07,
+ "loss": 0.4448,
+ "step": 10826
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.611230398116229e-07,
+ "loss": 0.47,
+ "step": 10827
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6030997493811126e-07,
+ "loss": 0.4645,
+ "step": 10828
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.594976106197546e-07,
+ "loss": 0.435,
+ "step": 10829
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5868594691621304e-07,
+ "loss": 0.4691,
+ "step": 10830
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5787498388708774e-07,
+ "loss": 0.4661,
+ "step": 10831
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.570647215919366e-07,
+ "loss": 0.4651,
+ "step": 10832
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5625516009026095e-07,
+ "loss": 0.4573,
+ "step": 10833
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5544629944150876e-07,
+ "loss": 0.4668,
+ "step": 10834
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5463813970508364e-07,
+ "loss": 0.461,
+ "step": 10835
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5383068094033036e-07,
+ "loss": 0.4437,
+ "step": 10836
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.53023923206547e-07,
+ "loss": 0.4601,
+ "step": 10837
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5221786656297727e-07,
+ "loss": 0.4662,
+ "step": 10838
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.51412511068815e-07,
+ "loss": 0.4571,
+ "step": 10839
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5060785678320397e-07,
+ "loss": 0.4747,
+ "step": 10840
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.498039037652313e-07,
+ "loss": 0.4635,
+ "step": 10841
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.490006520739387e-07,
+ "loss": 0.4445,
+ "step": 10842
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4819810176831235e-07,
+ "loss": 0.4579,
+ "step": 10843
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.473962529072873e-07,
+ "loss": 0.4499,
+ "step": 10844
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.465951055497497e-07,
+ "loss": 0.4692,
+ "step": 10845
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4579465975453264e-07,
+ "loss": 0.4776,
+ "step": 10846
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4499491558041673e-07,
+ "loss": 0.4795,
+ "step": 10847
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4419587308613285e-07,
+ "loss": 0.4559,
+ "step": 10848
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.433975323303574e-07,
+ "loss": 0.4781,
+ "step": 10849
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.42599893371719e-07,
+ "loss": 0.4636,
+ "step": 10850
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.418029562687898e-07,
+ "loss": 0.462,
+ "step": 10851
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4100672108009837e-07,
+ "loss": 0.4626,
+ "step": 10852
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4021118786411465e-07,
+ "loss": 0.4657,
+ "step": 10853
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3941635667925866e-07,
+ "loss": 0.4566,
+ "step": 10854
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3862222758389806e-07,
+ "loss": 0.4768,
+ "step": 10855
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3782880063635403e-07,
+ "loss": 0.4521,
+ "step": 10856
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3703607589489105e-07,
+ "loss": 0.471,
+ "step": 10857
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.362440534177226e-07,
+ "loss": 0.4468,
+ "step": 10858
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3545273326301205e-07,
+ "loss": 0.4578,
+ "step": 10859
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3466211548887195e-07,
+ "loss": 0.4488,
+ "step": 10860
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.338722001533602e-07,
+ "loss": 0.4784,
+ "step": 10861
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3308298731448596e-07,
+ "loss": 0.4639,
+ "step": 10862
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.322944770302051e-07,
+ "loss": 0.4591,
+ "step": 10863
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3150666935842243e-07,
+ "loss": 0.4511,
+ "step": 10864
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.307195643569917e-07,
+ "loss": 0.459,
+ "step": 10865
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.299331620837133e-07,
+ "loss": 0.4785,
+ "step": 10866
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.29147462596341e-07,
+ "loss": 0.4438,
+ "step": 10867
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.283624659525698e-07,
+ "loss": 0.465,
+ "step": 10868
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2757817221004803e-07,
+ "loss": 0.4592,
+ "step": 10869
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.267945814263708e-07,
+ "loss": 0.4657,
+ "step": 10870
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2601169365908077e-07,
+ "loss": 0.4765,
+ "step": 10871
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2522950896566994e-07,
+ "loss": 0.4664,
+ "step": 10872
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2444802740358114e-07,
+ "loss": 0.4634,
+ "step": 10873
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2366724903020076e-07,
+ "loss": 0.4695,
+ "step": 10874
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2288717390286614e-07,
+ "loss": 0.4691,
+ "step": 10875
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2210780207886383e-07,
+ "loss": 0.4936,
+ "step": 10876
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2132913361542683e-07,
+ "loss": 0.4619,
+ "step": 10877
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.205511685697372e-07,
+ "loss": 0.4653,
+ "step": 10878
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1977390699892706e-07,
+ "loss": 0.4641,
+ "step": 10879
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1899734896007404e-07,
+ "loss": 0.4697,
+ "step": 10880
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1822149451020475e-07,
+ "loss": 0.4413,
+ "step": 10881
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1744634370629587e-07,
+ "loss": 0.4594,
+ "step": 10882
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.166718966052696e-07,
+ "loss": 0.4503,
+ "step": 10883
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.158981532640005e-07,
+ "loss": 0.4772,
+ "step": 10884
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1512511373930533e-07,
+ "loss": 0.4692,
+ "step": 10885
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.143527780879575e-07,
+ "loss": 0.4666,
+ "step": 10886
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1358114636667056e-07,
+ "loss": 0.4712,
+ "step": 10887
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.128102186321126e-07,
+ "loss": 0.4737,
+ "step": 10888
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1203999494089596e-07,
+ "loss": 0.45,
+ "step": 10889
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.112704753495822e-07,
+ "loss": 0.4695,
+ "step": 10890
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1050165991468273e-07,
+ "loss": 0.4741,
+ "step": 10891
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.097335486926546e-07,
+ "loss": 0.4438,
+ "step": 10892
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.08966141739906e-07,
+ "loss": 0.4623,
+ "step": 10893
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.08199439112793e-07,
+ "loss": 0.4615,
+ "step": 10894
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0743344086761725e-07,
+ "loss": 0.4557,
+ "step": 10895
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.066681470606304e-07,
+ "loss": 0.482,
+ "step": 10896
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0590355774803416e-07,
+ "loss": 0.4708,
+ "step": 10897
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.051396729859758e-07,
+ "loss": 0.4756,
+ "step": 10898
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.043764928305505e-07,
+ "loss": 0.466,
+ "step": 10899
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.036140173378045e-07,
+ "loss": 0.4491,
+ "step": 10900
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.028522465637319e-07,
+ "loss": 0.4952,
+ "step": 10901
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0209118056427356e-07,
+ "loss": 0.4506,
+ "step": 10902
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.013308193953169e-07,
+ "loss": 0.4513,
+ "step": 10903
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0057116311270073e-07,
+ "loss": 0.4536,
+ "step": 10904
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.998122117722125e-07,
+ "loss": 0.4479,
+ "step": 10905
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.990539654295833e-07,
+ "loss": 0.4539,
+ "step": 10906
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.982964241404974e-07,
+ "loss": 0.4578,
+ "step": 10907
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.975395879605881e-07,
+ "loss": 0.4572,
+ "step": 10908
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.96783456945431e-07,
+ "loss": 0.4333,
+ "step": 10909
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.960280311505538e-07,
+ "loss": 0.4491,
+ "step": 10910
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9527331063143215e-07,
+ "loss": 0.4693,
+ "step": 10911
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9451929544348956e-07,
+ "loss": 0.4599,
+ "step": 10912
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9376598564209614e-07,
+ "loss": 0.4722,
+ "step": 10913
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9301338128257536e-07,
+ "loss": 0.4704,
+ "step": 10914
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.922614824201931e-07,
+ "loss": 0.4599,
+ "step": 10915
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.915102891101652e-07,
+ "loss": 0.4563,
+ "step": 10916
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9075980140765637e-07,
+ "loss": 0.4605,
+ "step": 10917
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.900100193677814e-07,
+ "loss": 0.4588,
+ "step": 10918
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.892609430455985e-07,
+ "loss": 0.4697,
+ "step": 10919
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.885125724961192e-07,
+ "loss": 0.4797,
+ "step": 10920
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.877649077742984e-07,
+ "loss": 0.4523,
+ "step": 10921
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8701794893504343e-07,
+ "loss": 0.4725,
+ "step": 10922
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.862716960332058e-07,
+ "loss": 0.4492,
+ "step": 10923
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8552614912358956e-07,
+ "loss": 0.435,
+ "step": 10924
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8478130826094307e-07,
+ "loss": 0.4606,
+ "step": 10925
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8403717349996263e-07,
+ "loss": 0.4684,
+ "step": 10926
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.832937448952978e-07,
+ "loss": 0.4579,
+ "step": 10927
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8255102250154054e-07,
+ "loss": 0.4772,
+ "step": 10928
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.81809006373236e-07,
+ "loss": 0.4719,
+ "step": 10929
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8106769656487184e-07,
+ "loss": 0.4419,
+ "step": 10930
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.803270931308889e-07,
+ "loss": 0.4684,
+ "step": 10931
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.795871961256725e-07,
+ "loss": 0.4569,
+ "step": 10932
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.788480056035571e-07,
+ "loss": 0.4644,
+ "step": 10933
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.78109521618828e-07,
+ "loss": 0.4834,
+ "step": 10934
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.773717442257141e-07,
+ "loss": 0.4578,
+ "step": 10935
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.7663467347839766e-07,
+ "loss": 0.4573,
+ "step": 10936
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7589830943100205e-07,
+ "loss": 0.4669,
+ "step": 10937
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7516265213760507e-07,
+ "loss": 0.4479,
+ "step": 10938
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7442770165223133e-07,
+ "loss": 0.4579,
+ "step": 10939
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7369345802885095e-07,
+ "loss": 0.4696,
+ "step": 10940
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7295992132138416e-07,
+ "loss": 0.4632,
+ "step": 10941
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7222709158369895e-07,
+ "loss": 0.4405,
+ "step": 10942
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.714949688696123e-07,
+ "loss": 0.4644,
+ "step": 10943
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.707635532328857e-07,
+ "loss": 0.4782,
+ "step": 10944
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.700328447272339e-07,
+ "loss": 0.4324,
+ "step": 10945
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.693028434063151e-07,
+ "loss": 0.4569,
+ "step": 10946
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6857354932373857e-07,
+ "loss": 0.454,
+ "step": 10947
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6784496253305937e-07,
+ "loss": 0.4474,
+ "step": 10948
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.671170830877846e-07,
+ "loss": 0.4524,
+ "step": 10949
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.663899110413638e-07,
+ "loss": 0.4726,
+ "step": 10950
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6566344644719974e-07,
+ "loss": 0.4711,
+ "step": 10951
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.649376893586398e-07,
+ "loss": 0.441,
+ "step": 10952
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6421263982898023e-07,
+ "loss": 0.4742,
+ "step": 10953
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.634882979114662e-07,
+ "loss": 0.4701,
+ "step": 10954
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.627646636592919e-07,
+ "loss": 0.4461,
+ "step": 10955
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6204173712559464e-07,
+ "loss": 0.4677,
+ "step": 10956
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6131951836346544e-07,
+ "loss": 0.4643,
+ "step": 10957
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6059800742593963e-07,
+ "loss": 0.4507,
+ "step": 10958
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5987720436600483e-07,
+ "loss": 0.4745,
+ "step": 10959
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5915710923658974e-07,
+ "loss": 0.4839,
+ "step": 10960
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.584377220905788e-07,
+ "loss": 0.458,
+ "step": 10961
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5771904298079864e-07,
+ "loss": 0.4535,
+ "step": 10962
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.57001071960027e-07,
+ "loss": 0.443,
+ "step": 10963
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.562838090809884e-07,
+ "loss": 0.4507,
+ "step": 10964
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.555672543963562e-07,
+ "loss": 0.4554,
+ "step": 10965
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.548514079587495e-07,
+ "loss": 0.4864,
+ "step": 10966
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.541362698207373e-07,
+ "loss": 0.4705,
+ "step": 10967
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5342184003483884e-07,
+ "loss": 0.451,
+ "step": 10968
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.527081186535164e-07,
+ "loss": 0.4559,
+ "step": 10969
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5199510572918484e-07,
+ "loss": 0.4681,
+ "step": 10970
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5128280131420333e-07,
+ "loss": 0.4597,
+ "step": 10971
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.505712054608801e-07,
+ "loss": 0.4551,
+ "step": 10972
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4986031822147325e-07,
+ "loss": 0.4646,
+ "step": 10973
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4915013964818556e-07,
+ "loss": 0.4706,
+ "step": 10974
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4844066979317193e-07,
+ "loss": 0.4488,
+ "step": 10975
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.477319087085318e-07,
+ "loss": 0.4767,
+ "step": 10976
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.470238564463135e-07,
+ "loss": 0.4695,
+ "step": 10977
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4631651305851224e-07,
+ "loss": 0.4663,
+ "step": 10978
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4560987859707407e-07,
+ "loss": 0.455,
+ "step": 10979
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.44903953113892e-07,
+ "loss": 0.4549,
+ "step": 10980
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4419873666080237e-07,
+ "loss": 0.4622,
+ "step": 10981
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.434942292895982e-07,
+ "loss": 0.4688,
+ "step": 10982
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.427904310520136e-07,
+ "loss": 0.4463,
+ "step": 10983
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.420873419997317e-07,
+ "loss": 0.4726,
+ "step": 10984
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.413849621843857e-07,
+ "loss": 0.4541,
+ "step": 10985
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.406832916575542e-07,
+ "loss": 0.4545,
+ "step": 10986
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3998233047076613e-07,
+ "loss": 0.449,
+ "step": 10987
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3928207867549467e-07,
+ "loss": 0.4896,
+ "step": 10988
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.385825363231665e-07,
+ "loss": 0.4583,
+ "step": 10989
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3788370346515274e-07,
+ "loss": 0.4388,
+ "step": 10990
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3718558015277237e-07,
+ "loss": 0.4818,
+ "step": 10991
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3648816643729207e-07,
+ "loss": 0.4601,
+ "step": 10992
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.357914623699265e-07,
+ "loss": 0.4561,
+ "step": 10993
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3509546800183923e-07,
+ "loss": 0.4834,
+ "step": 10994
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.344001833841426e-07,
+ "loss": 0.4675,
+ "step": 10995
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.337056085678936e-07,
+ "loss": 0.4454,
+ "step": 10996
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3301174360410026e-07,
+ "loss": 0.4625,
+ "step": 10997
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3231858854371634e-07,
+ "loss": 0.462,
+ "step": 10998
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3162614343764334e-07,
+ "loss": 0.4516,
+ "step": 10999
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.309344083367327e-07,
+ "loss": 0.4705,
+ "step": 11000
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3024338329178285e-07,
+ "loss": 0.4631,
+ "step": 11001
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2955306835353863e-07,
+ "loss": 0.4625,
+ "step": 11002
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2886346357269614e-07,
+ "loss": 0.4815,
+ "step": 11003
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.28174568999895e-07,
+ "loss": 0.4582,
+ "step": 11004
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.274863846857257e-07,
+ "loss": 0.4654,
+ "step": 11005
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2679891068072566e-07,
+ "loss": 0.4465,
+ "step": 11006
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.26112147035379e-07,
+ "loss": 0.4808,
+ "step": 11007
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.254260938001186e-07,
+ "loss": 0.4494,
+ "step": 11008
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2474075102532756e-07,
+ "loss": 0.4643,
+ "step": 11009
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.240561187613323e-07,
+ "loss": 0.4687,
+ "step": 11010
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.233721970584114e-07,
+ "loss": 0.4417,
+ "step": 11011
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.226889859667881e-07,
+ "loss": 0.4668,
+ "step": 11012
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.220064855366345e-07,
+ "loss": 0.4714,
+ "step": 11013
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2132469581807046e-07,
+ "loss": 0.4715,
+ "step": 11014
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2064361686116377e-07,
+ "loss": 0.4557,
+ "step": 11015
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.199632487159321e-07,
+ "loss": 0.4709,
+ "step": 11016
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1928359143233556e-07,
+ "loss": 0.4687,
+ "step": 11017
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1860464506028865e-07,
+ "loss": 0.4549,
+ "step": 11018
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1792640964964593e-07,
+ "loss": 0.4747,
+ "step": 11019
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.172488852502187e-07,
+ "loss": 0.4414,
+ "step": 11020
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1657207191176043e-07,
+ "loss": 0.4593,
+ "step": 11021
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1589596968397027e-07,
+ "loss": 0.4616,
+ "step": 11022
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.15220578616503e-07,
+ "loss": 0.4688,
+ "step": 11023
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1454589875895445e-07,
+ "loss": 0.4583,
+ "step": 11024
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1387193016086945e-07,
+ "loss": 0.4662,
+ "step": 11025
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.131986728717429e-07,
+ "loss": 0.4629,
+ "step": 11026
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1252612694101515e-07,
+ "loss": 0.4678,
+ "step": 11027
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1185429241807453e-07,
+ "loss": 0.4724,
+ "step": 11028
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1118316935226043e-07,
+ "loss": 0.4607,
+ "step": 11029
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.105127577928546e-07,
+ "loss": 0.4534,
+ "step": 11030
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0984305778908875e-07,
+ "loss": 0.4537,
+ "step": 11031
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.091740693901468e-07,
+ "loss": 0.4804,
+ "step": 11032
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.085057926451529e-07,
+ "loss": 0.4322,
+ "step": 11033
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.078382276031833e-07,
+ "loss": 0.4564,
+ "step": 11034
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.071713743132609e-07,
+ "loss": 0.4704,
+ "step": 11035
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0650523282435896e-07,
+ "loss": 0.4677,
+ "step": 11036
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0583980318539377e-07,
+ "loss": 0.467,
+ "step": 11037
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.051750854452329e-07,
+ "loss": 0.452,
+ "step": 11038
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0451107965268956e-07,
+ "loss": 0.4757,
+ "step": 11039
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0384778585652477e-07,
+ "loss": 0.4601,
+ "step": 11040
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.031852041054506e-07,
+ "loss": 0.4614,
+ "step": 11041
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0252333444812263e-07,
+ "loss": 0.4768,
+ "step": 11042
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0186217693314643e-07,
+ "loss": 0.4619,
+ "step": 11043
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.012017316090743e-07,
+ "loss": 0.4598,
+ "step": 11044
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0054199852440626e-07,
+ "loss": 0.4628,
+ "step": 11045
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9988297772759136e-07,
+ "loss": 0.4393,
+ "step": 11046
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.992246692670242e-07,
+ "loss": 0.475,
+ "step": 11047
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.985670731910495e-07,
+ "loss": 0.4703,
+ "step": 11048
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9791018954795636e-07,
+ "loss": 0.4442,
+ "step": 11049
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.972540183859862e-07,
+ "loss": 0.4694,
+ "step": 11050
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9659855975332274e-07,
+ "loss": 0.4698,
+ "step": 11051
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.959438136981019e-07,
+ "loss": 0.4357,
+ "step": 11052
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9528978026840625e-07,
+ "loss": 0.4585,
+ "step": 11053
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9463645951226415e-07,
+ "loss": 0.4864,
+ "step": 11054
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.939838514776527e-07,
+ "loss": 0.4584,
+ "step": 11055
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.933319562124959e-07,
+ "loss": 0.4561,
+ "step": 11056
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.926807737646675e-07,
+ "loss": 0.4795,
+ "step": 11057
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.920303041819872e-07,
+ "loss": 0.4472,
+ "step": 11058
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.9138054751222447e-07,
+ "loss": 0.461,
+ "step": 11059
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.907315038030911e-07,
+ "loss": 0.4699,
+ "step": 11060
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.900831731022524e-07,
+ "loss": 0.4574,
+ "step": 11061
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.894355554573203e-07,
+ "loss": 0.4534,
+ "step": 11062
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8878865091584993e-07,
+ "loss": 0.4645,
+ "step": 11063
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.881424595253501e-07,
+ "loss": 0.4718,
+ "step": 11064
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8749698133327396e-07,
+ "loss": 0.4806,
+ "step": 11065
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.868522163870213e-07,
+ "loss": 0.4608,
+ "step": 11066
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8620816473394206e-07,
+ "loss": 0.4613,
+ "step": 11067
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.855648264213329e-07,
+ "loss": 0.4636,
+ "step": 11068
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.84922201496437e-07,
+ "loss": 0.4611,
+ "step": 11069
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8428029000644676e-07,
+ "loss": 0.4624,
+ "step": 11070
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.83639091998501e-07,
+ "loss": 0.4557,
+ "step": 11071
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8299860751968664e-07,
+ "loss": 0.4618,
+ "step": 11072
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.823588366170393e-07,
+ "loss": 0.4716,
+ "step": 11073
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8171977933754036e-07,
+ "loss": 0.4572,
+ "step": 11074
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.810814357281189e-07,
+ "loss": 0.4798,
+ "step": 11075
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.804438058356529e-07,
+ "loss": 0.4614,
+ "step": 11076
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.798068897069672e-07,
+ "loss": 0.4506,
+ "step": 11077
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.791706873888345e-07,
+ "loss": 0.4792,
+ "step": 11078
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.78535198927975e-07,
+ "loss": 0.463,
+ "step": 11079
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.779004243710548e-07,
+ "loss": 0.4493,
+ "step": 11080
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7726636376468995e-07,
+ "loss": 0.4583,
+ "step": 11081
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.766330171554443e-07,
+ "loss": 0.4744,
+ "step": 11082
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7600038458982626e-07,
+ "loss": 0.4577,
+ "step": 11083
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7536846611429524e-07,
+ "loss": 0.4498,
+ "step": 11084
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.747372617752575e-07,
+ "loss": 0.466,
+ "step": 11085
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.741067716190637e-07,
+ "loss": 0.4466,
+ "step": 11086
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.734769956920169e-07,
+ "loss": 0.4521,
+ "step": 11087
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.728479340403634e-07,
+ "loss": 0.4548,
+ "step": 11088
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7221958671029834e-07,
+ "loss": 0.464,
+ "step": 11089
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.715919537479661e-07,
+ "loss": 0.463,
+ "step": 11090
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.709650351994575e-07,
+ "loss": 0.4979,
+ "step": 11091
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7033883111081014e-07,
+ "loss": 0.46,
+ "step": 11092
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6971334152801063e-07,
+ "loss": 0.4618,
+ "step": 11093
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.690885664969933e-07,
+ "loss": 0.4493,
+ "step": 11094
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6846450606363705e-07,
+ "loss": 0.4691,
+ "step": 11095
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.678411602737707e-07,
+ "loss": 0.4505,
+ "step": 11096
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6721852917316995e-07,
+ "loss": 0.4586,
+ "step": 11097
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.665966128075592e-07,
+ "loss": 0.4665,
+ "step": 11098
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.659754112226087e-07,
+ "loss": 0.4521,
+ "step": 11099
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.653549244639375e-07,
+ "loss": 0.4666,
+ "step": 11100
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6473515257711136e-07,
+ "loss": 0.456,
+ "step": 11101
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6411609560764273e-07,
+ "loss": 0.4674,
+ "step": 11102
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6349775360099306e-07,
+ "loss": 0.4626,
+ "step": 11103
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.628801266025727e-07,
+ "loss": 0.4403,
+ "step": 11104
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.622632146577364e-07,
+ "loss": 0.4732,
+ "step": 11105
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.616470178117858e-07,
+ "loss": 0.4657,
+ "step": 11106
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6103153610997464e-07,
+ "loss": 0.4599,
+ "step": 11107
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.604167695975002e-07,
+ "loss": 0.4552,
+ "step": 11108
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5980271831950734e-07,
+ "loss": 0.4677,
+ "step": 11109
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5918938232109004e-07,
+ "loss": 0.4628,
+ "step": 11110
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5857676164729006e-07,
+ "loss": 0.4507,
+ "step": 11111
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5796485634309477e-07,
+ "loss": 0.4524,
+ "step": 11112
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.573536664534404e-07,
+ "loss": 0.4644,
+ "step": 11113
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5674319202320997e-07,
+ "loss": 0.4485,
+ "step": 11114
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5613343309723426e-07,
+ "loss": 0.4583,
+ "step": 11115
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.555243897202919e-07,
+ "loss": 0.4837,
+ "step": 11116
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.549160619371072e-07,
+ "loss": 0.4759,
+ "step": 11117
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5430844979235426e-07,
+ "loss": 0.4621,
+ "step": 11118
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5370155333065416e-07,
+ "loss": 0.4752,
+ "step": 11119
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5309537259657346e-07,
+ "loss": 0.4624,
+ "step": 11120
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.524899076346288e-07,
+ "loss": 0.4575,
+ "step": 11121
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.518851584892812e-07,
+ "loss": 0.4817,
+ "step": 11122
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5128112520494297e-07,
+ "loss": 0.4768,
+ "step": 11123
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5067780782596973e-07,
+ "loss": 0.4499,
+ "step": 11124
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.500752063966694e-07,
+ "loss": 0.4508,
+ "step": 11125
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.494733209612921e-07,
+ "loss": 0.4726,
+ "step": 11126
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.488721515640391e-07,
+ "loss": 0.4577,
+ "step": 11127
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.482716982490574e-07,
+ "loss": 0.449,
+ "step": 11128
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.476719610604417e-07,
+ "loss": 0.4783,
+ "step": 11129
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4707294004223335e-07,
+ "loss": 0.483,
+ "step": 11130
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.464746352384229e-07,
+ "loss": 0.4561,
+ "step": 11131
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4587704669294834e-07,
+ "loss": 0.4791,
+ "step": 11132
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.452801744496913e-07,
+ "loss": 0.4602,
+ "step": 11133
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.446840185524868e-07,
+ "loss": 0.4529,
+ "step": 11134
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4408857904511196e-07,
+ "loss": 0.4832,
+ "step": 11135
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4349385597129403e-07,
+ "loss": 0.4787,
+ "step": 11136
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.428998493747081e-07,
+ "loss": 0.4726,
+ "step": 11137
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4230655929897263e-07,
+ "loss": 0.4646,
+ "step": 11138
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.417139857876583e-07,
+ "loss": 0.4458,
+ "step": 11139
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4112212888428246e-07,
+ "loss": 0.4363,
+ "step": 11140
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4053098863230706e-07,
+ "loss": 0.4711,
+ "step": 11141
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3994056507514183e-07,
+ "loss": 0.4633,
+ "step": 11142
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3935085825614655e-07,
+ "loss": 0.4565,
+ "step": 11143
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.387618682186277e-07,
+ "loss": 0.4608,
+ "step": 11144
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3817359500583615e-07,
+ "loss": 0.4632,
+ "step": 11145
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3758603866097406e-07,
+ "loss": 0.4617,
+ "step": 11146
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3699919922718805e-07,
+ "loss": 0.4715,
+ "step": 11147
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3641307674757362e-07,
+ "loss": 0.4526,
+ "step": 11148
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3582767126517302e-07,
+ "loss": 0.4631,
+ "step": 11149
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.352429828229763e-07,
+ "loss": 0.4627,
+ "step": 11150
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3465901146391912e-07,
+ "loss": 0.4579,
+ "step": 11151
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3407575723088827e-07,
+ "loss": 0.4531,
+ "step": 11152
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3349322016671394e-07,
+ "loss": 0.4655,
+ "step": 11153
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3291140031417525e-07,
+ "loss": 0.4745,
+ "step": 11154
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3233029771599913e-07,
+ "loss": 0.4893,
+ "step": 11155
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3174991241485923e-07,
+ "loss": 0.4505,
+ "step": 11156
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.31170244453377e-07,
+ "loss": 0.4682,
+ "step": 11157
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.305912938741184e-07,
+ "loss": 0.4609,
+ "step": 11158
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3001306071960384e-07,
+ "loss": 0.4606,
+ "step": 11159
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.294355450322916e-07,
+ "loss": 0.4565,
+ "step": 11160
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2885874685459553e-07,
+ "loss": 0.4542,
+ "step": 11161
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2828266622887173e-07,
+ "loss": 0.4691,
+ "step": 11162
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2770730319742528e-07,
+ "loss": 0.4622,
+ "step": 11163
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.271326578025068e-07,
+ "loss": 0.4703,
+ "step": 11164
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2655873008631812e-07,
+ "loss": 0.4572,
+ "step": 11165
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.259855200910066e-07,
+ "loss": 0.4871,
+ "step": 11166
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2541302785866525e-07,
+ "loss": 0.4661,
+ "step": 11167
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.248412534313349e-07,
+ "loss": 0.4621,
+ "step": 11168
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2427019685100527e-07,
+ "loss": 0.4768,
+ "step": 11169
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.236998581596128e-07,
+ "loss": 0.4552,
+ "step": 11170
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.231302373990385e-07,
+ "loss": 0.4535,
+ "step": 11171
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.225613346111155e-07,
+ "loss": 0.4639,
+ "step": 11172
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2199314983762043e-07,
+ "loss": 0.4708,
+ "step": 11173
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2142568312027879e-07,
+ "loss": 0.4768,
+ "step": 11174
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2085893450076167e-07,
+ "loss": 0.4697,
+ "step": 11175
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.2029290402069137e-07,
+ "loss": 0.4648,
+ "step": 11176
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1972759172163239e-07,
+ "loss": 0.4732,
+ "step": 11177
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.191629976451004e-07,
+ "loss": 0.4662,
+ "step": 11178
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.185991218325556e-07,
+ "loss": 0.458,
+ "step": 11179
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1803596432540818e-07,
+ "loss": 0.4644,
+ "step": 11180
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1747352516501396e-07,
+ "loss": 0.4514,
+ "step": 11181
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1691180439267434e-07,
+ "loss": 0.477,
+ "step": 11182
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1635080204964187e-07,
+ "loss": 0.4799,
+ "step": 11183
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.157905181771114e-07,
+ "loss": 0.4699,
+ "step": 11184
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1523095281623109e-07,
+ "loss": 0.4609,
+ "step": 11185
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.146721060080914e-07,
+ "loss": 0.446,
+ "step": 11186
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.141139777937318e-07,
+ "loss": 0.4774,
+ "step": 11187
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1355656821413938e-07,
+ "loss": 0.4701,
+ "step": 11188
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1299987731024818e-07,
+ "loss": 0.457,
+ "step": 11189
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1244390512293878e-07,
+ "loss": 0.4449,
+ "step": 11190
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1188865169303852e-07,
+ "loss": 0.4626,
+ "step": 11191
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1133411706132368e-07,
+ "loss": 0.4547,
+ "step": 11192
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1078030126851833e-07,
+ "loss": 0.4508,
+ "step": 11193
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1022720435529109e-07,
+ "loss": 0.4558,
+ "step": 11194
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0967482636225723e-07,
+ "loss": 0.4591,
+ "step": 11195
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0912316732998538e-07,
+ "loss": 0.4874,
+ "step": 11196
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0857222729898429e-07,
+ "loss": 0.4589,
+ "step": 11197
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0802200630971382e-07,
+ "loss": 0.4498,
+ "step": 11198
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0747250440257715e-07,
+ "loss": 0.4682,
+ "step": 11199
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0692372161793094e-07,
+ "loss": 0.4665,
+ "step": 11200
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0637565799607517e-07,
+ "loss": 0.4639,
+ "step": 11201
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0582831357725542e-07,
+ "loss": 0.4561,
+ "step": 11202
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.052816884016673e-07,
+ "loss": 0.4466,
+ "step": 11203
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0473578250945315e-07,
+ "loss": 0.4515,
+ "step": 11204
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0419059594069977e-07,
+ "loss": 0.4653,
+ "step": 11205
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0364612873544632e-07,
+ "loss": 0.4583,
+ "step": 11206
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0310238093367517e-07,
+ "loss": 0.4565,
+ "step": 11207
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0255935257531668e-07,
+ "loss": 0.4796,
+ "step": 11208
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0201704370024889e-07,
+ "loss": 0.4641,
+ "step": 11209
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0147545434829664e-07,
+ "loss": 0.4512,
+ "step": 11210
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0093458455923253e-07,
+ "loss": 0.4543,
+ "step": 11211
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0039443437277483e-07,
+ "loss": 0.4575,
+ "step": 11212
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9985500382858846e-07,
+ "loss": 0.4808,
+ "step": 11213
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9931629296629062e-07,
+ "loss": 0.4879,
+ "step": 11214
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9877830182543966e-07,
+ "loss": 0.4643,
+ "step": 11215
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.982410304455429e-07,
+ "loss": 0.4918,
+ "step": 11216
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.977044788660576e-07,
+ "loss": 0.4732,
+ "step": 11217
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9716864712638452e-07,
+ "loss": 0.458,
+ "step": 11218
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9663353526587104e-07,
+ "loss": 0.4465,
+ "step": 11219
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9609914332381797e-07,
+ "loss": 0.467,
+ "step": 11220
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9556547133946503e-07,
+ "loss": 0.471,
+ "step": 11221
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9503251935200418e-07,
+ "loss": 0.4334,
+ "step": 11222
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9450028740057415e-07,
+ "loss": 0.4527,
+ "step": 11223
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9396877552425808e-07,
+ "loss": 0.4616,
+ "step": 11224
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9343798376208812e-07,
+ "loss": 0.4508,
+ "step": 11225
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9290791215304527e-07,
+ "loss": 0.4742,
+ "step": 11226
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.92378560736054e-07,
+ "loss": 0.4621,
+ "step": 11227
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.918499295499887e-07,
+ "loss": 0.4577,
+ "step": 11228
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.913220186336684e-07,
+ "loss": 0.4754,
+ "step": 11229
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9079482802586314e-07,
+ "loss": 0.4778,
+ "step": 11230
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9026835776528529e-07,
+ "loss": 0.443,
+ "step": 11231
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.897426078905984e-07,
+ "loss": 0.4614,
+ "step": 11232
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8921757844040821e-07,
+ "loss": 0.4567,
+ "step": 11233
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8869326945327505e-07,
+ "loss": 0.4597,
+ "step": 11234
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8816968096769917e-07,
+ "loss": 0.4536,
+ "step": 11235
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8764681302213096e-07,
+ "loss": 0.4508,
+ "step": 11236
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8712466565496966e-07,
+ "loss": 0.4729,
+ "step": 11237
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.866032389045569e-07,
+ "loss": 0.4623,
+ "step": 11238
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.860825328091853e-07,
+ "loss": 0.4619,
+ "step": 11239
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8556254740709322e-07,
+ "loss": 0.4518,
+ "step": 11240
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8504328273646676e-07,
+ "loss": 0.4522,
+ "step": 11241
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8452473883543876e-07,
+ "loss": 0.4689,
+ "step": 11242
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8400691574208763e-07,
+ "loss": 0.4826,
+ "step": 11243
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8348981349444073e-07,
+ "loss": 0.4514,
+ "step": 11244
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8297343213047215e-07,
+ "loss": 0.4614,
+ "step": 11245
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8245777168810264e-07,
+ "loss": 0.4789,
+ "step": 11246
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8194283220519972e-07,
+ "loss": 0.4497,
+ "step": 11247
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8142861371957866e-07,
+ "loss": 0.4716,
+ "step": 11248
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.809151162690026e-07,
+ "loss": 0.4514,
+ "step": 11249
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8040233989117915e-07,
+ "loss": 0.4515,
+ "step": 11250
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.79890284623766e-07,
+ "loss": 0.4727,
+ "step": 11251
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7937895050436528e-07,
+ "loss": 0.4491,
+ "step": 11252
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7886833757052692e-07,
+ "loss": 0.4514,
+ "step": 11253
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.783584458597476e-07,
+ "loss": 0.4681,
+ "step": 11254
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7784927540947406e-07,
+ "loss": 0.4641,
+ "step": 11255
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7734082625709637e-07,
+ "loss": 0.4511,
+ "step": 11256
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7683309843995245e-07,
+ "loss": 0.4866,
+ "step": 11257
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.76326091995328e-07,
+ "loss": 0.4605,
+ "step": 11258
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7581980696045665e-07,
+ "loss": 0.4512,
+ "step": 11259
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7531424337251523e-07,
+ "loss": 0.4494,
+ "step": 11260
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.74809401268633e-07,
+ "loss": 0.4466,
+ "step": 11261
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7430528068588136e-07,
+ "loss": 0.4511,
+ "step": 11262
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.73801881661283e-07,
+ "loss": 0.4694,
+ "step": 11263
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.732992042318038e-07,
+ "loss": 0.4656,
+ "step": 11264
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7279724843435874e-07,
+ "loss": 0.4696,
+ "step": 11265
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7229601430580832e-07,
+ "loss": 0.4668,
+ "step": 11266
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7179550188296313e-07,
+ "loss": 0.4587,
+ "step": 11267
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7129571120257705e-07,
+ "loss": 0.4508,
+ "step": 11268
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7079664230135406e-07,
+ "loss": 0.4877,
+ "step": 11269
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7029829521594265e-07,
+ "loss": 0.4431,
+ "step": 11270
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.698006699829402e-07,
+ "loss": 0.4604,
+ "step": 11271
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.693037666388886e-07,
+ "loss": 0.4764,
+ "step": 11272
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6880758522028083e-07,
+ "loss": 0.449,
+ "step": 11273
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6831212576355116e-07,
+ "loss": 0.4654,
+ "step": 11274
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6781738830508708e-07,
+ "loss": 0.4697,
+ "step": 11275
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6732337288121848e-07,
+ "loss": 0.4456,
+ "step": 11276
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6683007952822405e-07,
+ "loss": 0.4683,
+ "step": 11277
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.663375082823293e-07,
+ "loss": 0.4491,
+ "step": 11278
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.658456591797075e-07,
+ "loss": 0.4488,
+ "step": 11279
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6535453225647645e-07,
+ "loss": 0.4635,
+ "step": 11280
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6486412754870286e-07,
+ "loss": 0.4656,
+ "step": 11281
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.643744450924012e-07,
+ "loss": 0.489,
+ "step": 11282
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.638854849235305e-07,
+ "loss": 0.4561,
+ "step": 11283
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6339724707799875e-07,
+ "loss": 0.458,
+ "step": 11284
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6290973159165945e-07,
+ "loss": 0.4563,
+ "step": 11285
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.62422938500314e-07,
+ "loss": 0.4512,
+ "step": 11286
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.619368678397093e-07,
+ "loss": 0.4662,
+ "step": 11287
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.614515196455424e-07,
+ "loss": 0.4656,
+ "step": 11288
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6096689395345366e-07,
+ "loss": 0.4872,
+ "step": 11289
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.604829907990335e-07,
+ "loss": 0.4777,
+ "step": 11290
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5999981021781685e-07,
+ "loss": 0.4589,
+ "step": 11291
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.595173522452864e-07,
+ "loss": 0.4641,
+ "step": 11292
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5903561691687164e-07,
+ "loss": 0.4715,
+ "step": 11293
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5855460426794865e-07,
+ "loss": 0.446,
+ "step": 11294
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5807431433384368e-07,
+ "loss": 0.4725,
+ "step": 11295
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5759474714982405e-07,
+ "loss": 0.4727,
+ "step": 11296
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5711590275110933e-07,
+ "loss": 0.4476,
+ "step": 11297
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5663778117286254e-07,
+ "loss": 0.4618,
+ "step": 11298
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.561603824501956e-07,
+ "loss": 0.4643,
+ "step": 11299
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5568370661816713e-07,
+ "loss": 0.4793,
+ "step": 11300
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.552077537117802e-07,
+ "loss": 0.4569,
+ "step": 11301
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5473252376598913e-07,
+ "loss": 0.4629,
+ "step": 11302
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5425801681569263e-07,
+ "loss": 0.4617,
+ "step": 11303
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5378423289573508e-07,
+ "loss": 0.4613,
+ "step": 11304
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5331117204091085e-07,
+ "loss": 0.45,
+ "step": 11305
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.528388342859577e-07,
+ "loss": 0.4758,
+ "step": 11306
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5236721966556456e-07,
+ "loss": 0.4927,
+ "step": 11307
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.518963282143615e-07,
+ "loss": 0.4616,
+ "step": 11308
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5142615996693087e-07,
+ "loss": 0.4713,
+ "step": 11309
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5095671495780062e-07,
+ "loss": 0.4613,
+ "step": 11310
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5048799322144426e-07,
+ "loss": 0.4549,
+ "step": 11311
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5001999479228203e-07,
+ "loss": 0.459,
+ "step": 11312
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.49552719704682e-07,
+ "loss": 0.4595,
+ "step": 11313
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4908616799296006e-07,
+ "loss": 0.4503,
+ "step": 11314
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4862033969137545e-07,
+ "loss": 0.4753,
+ "step": 11315
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4815523483413864e-07,
+ "loss": 0.4399,
+ "step": 11316
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4769085345540556e-07,
+ "loss": 0.4847,
+ "step": 11317
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.472271955892768e-07,
+ "loss": 0.4602,
+ "step": 11318
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4676426126980058e-07,
+ "loss": 0.4709,
+ "step": 11319
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4630205053097645e-07,
+ "loss": 0.4564,
+ "step": 11320
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4584056340674392e-07,
+ "loss": 0.4561,
+ "step": 11321
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4537979993099361e-07,
+ "loss": 0.4634,
+ "step": 11322
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4491976013756292e-07,
+ "loss": 0.462,
+ "step": 11323
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4446044406023485e-07,
+ "loss": 0.4504,
+ "step": 11324
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4400185173274018e-07,
+ "loss": 0.4507,
+ "step": 11325
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4354398318875417e-07,
+ "loss": 0.4674,
+ "step": 11326
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.430868384619022e-07,
+ "loss": 0.4756,
+ "step": 11327
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4263041758575402e-07,
+ "loss": 0.4396,
+ "step": 11328
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4217472059382952e-07,
+ "loss": 0.464,
+ "step": 11329
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4171974751959082e-07,
+ "loss": 0.4678,
+ "step": 11330
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4126549839645009e-07,
+ "loss": 0.4847,
+ "step": 11331
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.408119732577662e-07,
+ "loss": 0.4553,
+ "step": 11332
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4035917213684358e-07,
+ "loss": 0.4686,
+ "step": 11333
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3990709506693457e-07,
+ "loss": 0.4596,
+ "step": 11334
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.394557420812359e-07,
+ "loss": 0.443,
+ "step": 11335
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3900511321289557e-07,
+ "loss": 0.4613,
+ "step": 11336
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.385552084950037e-07,
+ "loss": 0.4579,
+ "step": 11337
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.381060279606017e-07,
+ "loss": 0.4549,
+ "step": 11338
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3765757164267313e-07,
+ "loss": 0.4551,
+ "step": 11339
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3720983957415278e-07,
+ "loss": 0.4749,
+ "step": 11340
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3676283178791882e-07,
+ "loss": 0.4428,
+ "step": 11341
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.363165483167983e-07,
+ "loss": 0.4797,
+ "step": 11342
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.35870989193565e-07,
+ "loss": 0.4681,
+ "step": 11343
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3542615445093722e-07,
+ "loss": 0.4495,
+ "step": 11344
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3498204412158434e-07,
+ "loss": 0.4612,
+ "step": 11345
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3453865823811696e-07,
+ "loss": 0.4608,
+ "step": 11346
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3409599683309793e-07,
+ "loss": 0.4477,
+ "step": 11347
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3365405993903347e-07,
+ "loss": 0.4679,
+ "step": 11348
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.332128475883765e-07,
+ "loss": 0.4465,
+ "step": 11349
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3277235981352887e-07,
+ "loss": 0.4629,
+ "step": 11350
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3233259664683916e-07,
+ "loss": 0.4655,
+ "step": 11351
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3189355812060157e-07,
+ "loss": 0.4558,
+ "step": 11352
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.314552442670558e-07,
+ "loss": 0.4475,
+ "step": 11353
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.310176551183906e-07,
+ "loss": 0.4415,
+ "step": 11354
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3058079070674023e-07,
+ "loss": 0.4641,
+ "step": 11355
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3014465106418573e-07,
+ "loss": 0.4601,
+ "step": 11356
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.297092362227581e-07,
+ "loss": 0.4457,
+ "step": 11357
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2927454621442959e-07,
+ "loss": 0.4609,
+ "step": 11358
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2884058107112353e-07,
+ "loss": 0.4725,
+ "step": 11359
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2840734082470662e-07,
+ "loss": 0.455,
+ "step": 11360
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.279748255069968e-07,
+ "loss": 0.453,
+ "step": 11361
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.275430351497542e-07,
+ "loss": 0.4684,
+ "step": 11362
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.27111969784689e-07,
+ "loss": 0.4651,
+ "step": 11363
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2668162944345587e-07,
+ "loss": 0.4371,
+ "step": 11364
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.262520141576584e-07,
+ "loss": 0.4689,
+ "step": 11365
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2582312395884476e-07,
+ "loss": 0.4626,
+ "step": 11366
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2539495887851083e-07,
+ "loss": 0.4517,
+ "step": 11367
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2496751894810032e-07,
+ "loss": 0.4605,
+ "step": 11368
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.245408041990004e-07,
+ "loss": 0.4645,
+ "step": 11369
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2411481466254926e-07,
+ "loss": 0.4477,
+ "step": 11370
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2368955037002973e-07,
+ "loss": 0.4739,
+ "step": 11371
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.232650113526701e-07,
+ "loss": 0.4712,
+ "step": 11372
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.228411976416488e-07,
+ "loss": 0.4649,
+ "step": 11373
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2241810926808762e-07,
+ "loss": 0.4477,
+ "step": 11374
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.219957462630561e-07,
+ "loss": 0.4506,
+ "step": 11375
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2157410865757057e-07,
+ "loss": 0.4762,
+ "step": 11376
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2115319648259516e-07,
+ "loss": 0.4677,
+ "step": 11377
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2073300976904067e-07,
+ "loss": 0.4585,
+ "step": 11378
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2031354854776356e-07,
+ "loss": 0.4589,
+ "step": 11379
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.198948128495647e-07,
+ "loss": 0.4742,
+ "step": 11380
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1947680270519733e-07,
+ "loss": 0.4694,
+ "step": 11381
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.19059518145358e-07,
+ "loss": 0.4748,
+ "step": 11382
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.186429592006888e-07,
+ "loss": 0.4683,
+ "step": 11383
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1822712590178197e-07,
+ "loss": 0.4732,
+ "step": 11384
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.178120182791731e-07,
+ "loss": 0.4454,
+ "step": 11385
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1739763636334667e-07,
+ "loss": 0.4684,
+ "step": 11386
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1698398018473278e-07,
+ "loss": 0.4555,
+ "step": 11387
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1657104977370937e-07,
+ "loss": 0.4729,
+ "step": 11388
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1615884516059883e-07,
+ "loss": 0.4459,
+ "step": 11389
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1574736637567252e-07,
+ "loss": 0.462,
+ "step": 11390
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1533661344914848e-07,
+ "loss": 0.4428,
+ "step": 11391
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1492658641119037e-07,
+ "loss": 0.4663,
+ "step": 11392
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1451728529190852e-07,
+ "loss": 0.4739,
+ "step": 11393
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1410871012136116e-07,
+ "loss": 0.4518,
+ "step": 11394
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.137008609295509e-07,
+ "loss": 0.4517,
+ "step": 11395
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1329373774642938e-07,
+ "loss": 0.4603,
+ "step": 11396
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1288734060189267e-07,
+ "loss": 0.4487,
+ "step": 11397
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1248166952578799e-07,
+ "loss": 0.4477,
+ "step": 11398
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1207672454790264e-07,
+ "loss": 0.4674,
+ "step": 11399
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1167250569797728e-07,
+ "loss": 0.4888,
+ "step": 11400
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.112690130056926e-07,
+ "loss": 0.4248,
+ "step": 11401
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1086624650068267e-07,
+ "loss": 0.4714,
+ "step": 11402
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1046420621252275e-07,
+ "loss": 0.4564,
+ "step": 11403
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1006289217073806e-07,
+ "loss": 0.4568,
+ "step": 11404
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0966230440479953e-07,
+ "loss": 0.4453,
+ "step": 11405
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0926244294412359e-07,
+ "loss": 0.4599,
+ "step": 11406
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0886330781807674e-07,
+ "loss": 0.4831,
+ "step": 11407
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0846489905596669e-07,
+ "loss": 0.459,
+ "step": 11408
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0806721668705333e-07,
+ "loss": 0.4722,
+ "step": 11409
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0767026074053888e-07,
+ "loss": 0.4564,
+ "step": 11410
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0727403124557667e-07,
+ "loss": 0.473,
+ "step": 11411
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0687852823126122e-07,
+ "loss": 0.4533,
+ "step": 11412
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0648375172663927e-07,
+ "loss": 0.466,
+ "step": 11413
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0608970176069987e-07,
+ "loss": 0.4882,
+ "step": 11414
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.05696378362381e-07,
+ "loss": 0.4757,
+ "step": 11415
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.053037815605662e-07,
+ "loss": 0.4573,
+ "step": 11416
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0491191138408685e-07,
+ "loss": 0.4652,
+ "step": 11417
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0452076786171994e-07,
+ "loss": 0.4586,
+ "step": 11418
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0413035102219027e-07,
+ "loss": 0.4461,
+ "step": 11419
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0374066089416602e-07,
+ "loss": 0.4575,
+ "step": 11420
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.033516975062676e-07,
+ "loss": 0.4532,
+ "step": 11421
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0296346088705555e-07,
+ "loss": 0.4417,
+ "step": 11422
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.025759510650437e-07,
+ "loss": 0.4606,
+ "step": 11423
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0218916806868594e-07,
+ "loss": 0.469,
+ "step": 11424
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0180311192638848e-07,
+ "loss": 0.4542,
+ "step": 11425
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0141778266650082e-07,
+ "loss": 0.4661,
+ "step": 11426
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0103318031732035e-07,
+ "loss": 0.4652,
+ "step": 11427
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.006493049070889e-07,
+ "loss": 0.4853,
+ "step": 11428
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.002661564639995e-07,
+ "loss": 0.4559,
+ "step": 11429
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.988373501618631e-08,
+ "loss": 0.4535,
+ "step": 11430
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.950204059173462e-08,
+ "loss": 0.4537,
+ "step": 11431
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.912107321867315e-08,
+ "loss": 0.462,
+ "step": 11432
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.87408329249795e-08,
+ "loss": 0.4469,
+ "step": 11433
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.836131973857687e-08,
+ "loss": 0.4602,
+ "step": 11434
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.798253368733523e-08,
+ "loss": 0.4734,
+ "step": 11435
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.76044747990701e-08,
+ "loss": 0.4662,
+ "step": 11436
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.722714310154591e-08,
+ "loss": 0.4702,
+ "step": 11437
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.685053862247051e-08,
+ "loss": 0.4542,
+ "step": 11438
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.647466138950178e-08,
+ "loss": 0.4661,
+ "step": 11439
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.60995114302421e-08,
+ "loss": 0.4739,
+ "step": 11440
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.572508877224163e-08,
+ "loss": 0.4406,
+ "step": 11441
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.535139344299393e-08,
+ "loss": 0.4697,
+ "step": 11442
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.497842546994485e-08,
+ "loss": 0.4764,
+ "step": 11443
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.460618488048024e-08,
+ "loss": 0.4497,
+ "step": 11444
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.423467170193933e-08,
+ "loss": 0.4531,
+ "step": 11445
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.386388596160367e-08,
+ "loss": 0.4582,
+ "step": 11446
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.349382768670034e-08,
+ "loss": 0.4613,
+ "step": 11447
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.31244969044065e-08,
+ "loss": 0.4622,
+ "step": 11448
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.275589364184379e-08,
+ "loss": 0.4951,
+ "step": 11449
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.238801792608054e-08,
+ "loss": 0.4514,
+ "step": 11450
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.202086978413294e-08,
+ "loss": 0.4673,
+ "step": 11451
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.165444924296163e-08,
+ "loss": 0.4674,
+ "step": 11452
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.12887563294751e-08,
+ "loss": 0.462,
+ "step": 11453
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.092379107053074e-08,
+ "loss": 0.4548,
+ "step": 11454
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.055955349292711e-08,
+ "loss": 0.4618,
+ "step": 11455
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.019604362341394e-08,
+ "loss": 0.4822,
+ "step": 11456
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.983326148868432e-08,
+ "loss": 0.4545,
+ "step": 11457
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.947120711538138e-08,
+ "loss": 0.4525,
+ "step": 11458
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.910988053009162e-08,
+ "loss": 0.462,
+ "step": 11459
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.874928175934938e-08,
+ "loss": 0.4336,
+ "step": 11460
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.838941082963681e-08,
+ "loss": 0.4565,
+ "step": 11461
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.803026776738055e-08,
+ "loss": 0.4647,
+ "step": 11462
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.767185259895284e-08,
+ "loss": 0.4468,
+ "step": 11463
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.731416535067705e-08,
+ "loss": 0.4473,
+ "step": 11464
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.695720604881886e-08,
+ "loss": 0.4576,
+ "step": 11465
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.660097471959173e-08,
+ "loss": 0.4786,
+ "step": 11466
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.624547138915696e-08,
+ "loss": 0.4623,
+ "step": 11467
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.589069608361922e-08,
+ "loss": 0.4606,
+ "step": 11468
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.553664882903323e-08,
+ "loss": 0.4581,
+ "step": 11469
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.518332965139931e-08,
+ "loss": 0.4398,
+ "step": 11470
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.483073857666224e-08,
+ "loss": 0.4641,
+ "step": 11471
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.447887563071466e-08,
+ "loss": 0.4707,
+ "step": 11472
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.4127740839397e-08,
+ "loss": 0.4626,
+ "step": 11473
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.377733422849532e-08,
+ "loss": 0.4563,
+ "step": 11474
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.342765582374124e-08,
+ "loss": 0.4642,
+ "step": 11475
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.307870565081422e-08,
+ "loss": 0.4385,
+ "step": 11476
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.273048373533932e-08,
+ "loss": 0.4736,
+ "step": 11477
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.23829901028883e-08,
+ "loss": 0.45,
+ "step": 11478
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.203622477898077e-08,
+ "loss": 0.4565,
+ "step": 11479
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.169018778908078e-08,
+ "loss": 0.4609,
+ "step": 11480
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.134487915860024e-08,
+ "loss": 0.4565,
+ "step": 11481
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.100029891289662e-08,
+ "loss": 0.4625,
+ "step": 11482
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.065644707727415e-08,
+ "loss": 0.4632,
+ "step": 11483
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.031332367698486e-08,
+ "loss": 0.4644,
+ "step": 11484
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.997092873722633e-08,
+ "loss": 0.4493,
+ "step": 11485
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.962926228314293e-08,
+ "loss": 0.4484,
+ "step": 11486
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.928832433982348e-08,
+ "loss": 0.4623,
+ "step": 11487
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.89481149323068e-08,
+ "loss": 0.4518,
+ "step": 11488
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.860863408557629e-08,
+ "loss": 0.4552,
+ "step": 11489
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.826988182456086e-08,
+ "loss": 0.4685,
+ "step": 11490
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.793185817413728e-08,
+ "loss": 0.4479,
+ "step": 11491
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.759456315912905e-08,
+ "loss": 0.478,
+ "step": 11492
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.725799680430634e-08,
+ "loss": 0.4773,
+ "step": 11493
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.692215913438383e-08,
+ "loss": 0.4452,
+ "step": 11494
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.658705017402623e-08,
+ "loss": 0.4524,
+ "step": 11495
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.625266994784053e-08,
+ "loss": 0.4712,
+ "step": 11496
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.591901848038263e-08,
+ "loss": 0.4557,
+ "step": 11497
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.558609579615406e-08,
+ "loss": 0.4618,
+ "step": 11498
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.525390191960413e-08,
+ "loss": 0.4687,
+ "step": 11499
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.49224368751278e-08,
+ "loss": 0.4418,
+ "step": 11500
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.459170068706555e-08,
+ "loss": 0.4609,
+ "step": 11501
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.42616933797069e-08,
+ "loss": 0.4724,
+ "step": 11502
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.393241497728465e-08,
+ "loss": 0.4743,
+ "step": 11503
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.360386550398058e-08,
+ "loss": 0.4792,
+ "step": 11504
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.327604498392094e-08,
+ "loss": 0.4734,
+ "step": 11505
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.294895344118091e-08,
+ "loss": 0.4442,
+ "step": 11506
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.262259089977907e-08,
+ "loss": 0.4476,
+ "step": 11507
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.229695738368403e-08,
+ "loss": 0.493,
+ "step": 11508
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.197205291680887e-08,
+ "loss": 0.4545,
+ "step": 11509
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.164787752301117e-08,
+ "loss": 0.4578,
+ "step": 11510
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.132443122609856e-08,
+ "loss": 0.4767,
+ "step": 11511
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.100171404982315e-08,
+ "loss": 0.4626,
+ "step": 11512
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.067972601788376e-08,
+ "loss": 0.4525,
+ "step": 11513
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.035846715392591e-08,
+ "loss": 0.4466,
+ "step": 11514
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.003793748154186e-08,
+ "loss": 0.4565,
+ "step": 11515
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.971813702427055e-08,
+ "loss": 0.4513,
+ "step": 11516
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.939906580559542e-08,
+ "loss": 0.4462,
+ "step": 11517
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.908072384894881e-08,
+ "loss": 0.4708,
+ "step": 11518
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.876311117770762e-08,
+ "loss": 0.4715,
+ "step": 11519
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.844622781519649e-08,
+ "loss": 0.4652,
+ "step": 11520
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.813007378468684e-08,
+ "loss": 0.4617,
+ "step": 11521
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.78146491093945e-08,
+ "loss": 0.4697,
+ "step": 11522
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.74999538124832e-08,
+ "loss": 0.4436,
+ "step": 11523
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.718598791706221e-08,
+ "loss": 0.4746,
+ "step": 11524
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.687275144618865e-08,
+ "loss": 0.4787,
+ "step": 11525
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.656024442286524e-08,
+ "loss": 0.4546,
+ "step": 11526
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.62484668700425e-08,
+ "loss": 0.4944,
+ "step": 11527
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.593741881061321e-08,
+ "loss": 0.4772,
+ "step": 11528
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.562710026742248e-08,
+ "loss": 0.4597,
+ "step": 11529
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.531751126325647e-08,
+ "loss": 0.462,
+ "step": 11530
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.500865182085148e-08,
+ "loss": 0.4656,
+ "step": 11531
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.470052196288712e-08,
+ "loss": 0.4457,
+ "step": 11532
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.439312171199308e-08,
+ "loss": 0.462,
+ "step": 11533
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.408645109074352e-08,
+ "loss": 0.4589,
+ "step": 11534
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.37805101216571e-08,
+ "loss": 0.4681,
+ "step": 11535
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.34752988272036e-08,
+ "loss": 0.4498,
+ "step": 11536
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.317081722979402e-08,
+ "loss": 0.4609,
+ "step": 11537
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.286706535179044e-08,
+ "loss": 0.4832,
+ "step": 11538
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.256404321549725e-08,
+ "loss": 0.4635,
+ "step": 11539
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.226175084316666e-08,
+ "loss": 0.4608,
+ "step": 11540
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.19601882570009e-08,
+ "loss": 0.4557,
+ "step": 11541
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.165935547914225e-08,
+ "loss": 0.458,
+ "step": 11542
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.135925253168417e-08,
+ "loss": 0.4766,
+ "step": 11543
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.105987943666459e-08,
+ "loss": 0.455,
+ "step": 11544
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.07612362160681e-08,
+ "loss": 0.4563,
+ "step": 11545
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.046332289182722e-08,
+ "loss": 0.4636,
+ "step": 11546
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.016613948581662e-08,
+ "loss": 0.4598,
+ "step": 11547
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.98696860198622e-08,
+ "loss": 0.4772,
+ "step": 11548
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.957396251573433e-08,
+ "loss": 0.4755,
+ "step": 11549
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.9278968995150066e-08,
+ "loss": 0.4486,
+ "step": 11550
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.898470547977098e-08,
+ "loss": 0.4531,
+ "step": 11551
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.8691171991207554e-08,
+ "loss": 0.4647,
+ "step": 11552
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.8398368551014774e-08,
+ "loss": 0.4795,
+ "step": 11553
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.810629518069655e-08,
+ "loss": 0.4659,
+ "step": 11554
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.781495190170017e-08,
+ "loss": 0.4633,
+ "step": 11555
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.7524338735420734e-08,
+ "loss": 0.4726,
+ "step": 11556
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.7234455703200073e-08,
+ "loss": 0.4533,
+ "step": 11557
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.69453028263256e-08,
+ "loss": 0.4576,
+ "step": 11558
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.6656880126032544e-08,
+ "loss": 0.5139,
+ "step": 11559
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.636918762350063e-08,
+ "loss": 0.4825,
+ "step": 11560
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.60822253398563e-08,
+ "loss": 0.4501,
+ "step": 11561
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.57959932961738e-08,
+ "loss": 0.4619,
+ "step": 11562
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.551049151347299e-08,
+ "loss": 0.4715,
+ "step": 11563
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.522572001271931e-08,
+ "loss": 0.4353,
+ "step": 11564
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.494167881482493e-08,
+ "loss": 0.4583,
+ "step": 11565
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.4658367940648716e-08,
+ "loss": 0.4748,
+ "step": 11566
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.437578741099625e-08,
+ "loss": 0.4489,
+ "step": 11567
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.409393724661982e-08,
+ "loss": 0.4516,
+ "step": 11568
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.381281746821621e-08,
+ "loss": 0.4539,
+ "step": 11569
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.353242809643e-08,
+ "loss": 0.4893,
+ "step": 11570
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.3252769151851404e-08,
+ "loss": 0.4578,
+ "step": 11571
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.297384065501843e-08,
+ "loss": 0.4645,
+ "step": 11572
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.269564262641358e-08,
+ "loss": 0.45,
+ "step": 11573
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.241817508646607e-08,
+ "loss": 0.4595,
+ "step": 11574
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.214143805555294e-08,
+ "loss": 0.4711,
+ "step": 11575
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.1865431553996814e-08,
+ "loss": 0.4387,
+ "step": 11576
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.159015560206593e-08,
+ "loss": 0.4737,
+ "step": 11577
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.131561021997522e-08,
+ "loss": 0.4596,
+ "step": 11578
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.104179542788634e-08,
+ "loss": 0.4678,
+ "step": 11579
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.0768711245907654e-08,
+ "loss": 0.458,
+ "step": 11580
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.049635769409311e-08,
+ "loss": 0.4588,
+ "step": 11581
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.022473479244228e-08,
+ "loss": 0.4621,
+ "step": 11582
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.995384256090252e-08,
+ "loss": 0.4776,
+ "step": 11583
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.9683681019367935e-08,
+ "loss": 0.5035,
+ "step": 11584
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.941425018767709e-08,
+ "loss": 0.4653,
+ "step": 11585
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.914555008561528e-08,
+ "loss": 0.4472,
+ "step": 11586
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.8877580732916706e-08,
+ "loss": 0.4582,
+ "step": 11587
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.861034214925786e-08,
+ "loss": 0.4557,
+ "step": 11588
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.834383435426526e-08,
+ "loss": 0.4401,
+ "step": 11589
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.807805736750881e-08,
+ "loss": 0.4679,
+ "step": 11590
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.7813011208507344e-08,
+ "loss": 0.4689,
+ "step": 11591
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.754869589672306e-08,
+ "loss": 0.4587,
+ "step": 11592
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.728511145156822e-08,
+ "loss": 0.4385,
+ "step": 11593
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.702225789239734e-08,
+ "loss": 0.4664,
+ "step": 11594
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.676013523851497e-08,
+ "loss": 0.4549,
+ "step": 11595
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.6498743509170165e-08,
+ "loss": 0.4589,
+ "step": 11596
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.6238082723557566e-08,
+ "loss": 0.479,
+ "step": 11597
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.597815290081853e-08,
+ "loss": 0.4623,
+ "step": 11598
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.571895406004334e-08,
+ "loss": 0.4538,
+ "step": 11599
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.546048622026455e-08,
+ "loss": 0.4619,
+ "step": 11600
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.520274940046254e-08,
+ "loss": 0.4445,
+ "step": 11601
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.494574361956661e-08,
+ "loss": 0.4731,
+ "step": 11602
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.4689468896449426e-08,
+ "loss": 0.4714,
+ "step": 11603
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.44339252499304e-08,
+ "loss": 0.4801,
+ "step": 11604
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.4179112698774505e-08,
+ "loss": 0.4417,
+ "step": 11605
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.392503126169678e-08,
+ "loss": 0.4605,
+ "step": 11606
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.3671680957352304e-08,
+ "loss": 0.4555,
+ "step": 11607
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.341906180434952e-08,
+ "loss": 0.4503,
+ "step": 11608
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.3167173821238026e-08,
+ "loss": 0.4642,
+ "step": 11609
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.291601702651527e-08,
+ "loss": 0.4799,
+ "step": 11610
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.2665591438626474e-08,
+ "loss": 0.4446,
+ "step": 11611
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.241589707596028e-08,
+ "loss": 0.4713,
+ "step": 11612
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.216693395685423e-08,
+ "loss": 0.4628,
+ "step": 11613
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.191870209959037e-08,
+ "loss": 0.4603,
+ "step": 11614
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.167120152239856e-08,
+ "loss": 0.4876,
+ "step": 11615
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.142443224345427e-08,
+ "loss": 0.4624,
+ "step": 11616
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.1178394280878554e-08,
+ "loss": 0.4711,
+ "step": 11617
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.093308765273918e-08,
+ "loss": 0.4748,
+ "step": 11618
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.068851237705174e-08,
+ "loss": 0.4544,
+ "step": 11619
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.044466847177519e-08,
+ "loss": 0.4416,
+ "step": 11620
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.0201555954818563e-08,
+ "loss": 0.4559,
+ "step": 11621
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.9959174844032e-08,
+ "loss": 0.4686,
+ "step": 11622
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.971752515721794e-08,
+ "loss": 0.4665,
+ "step": 11623
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.9476606912121073e-08,
+ "loss": 0.4777,
+ "step": 11624
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.9236420126432806e-08,
+ "loss": 0.469,
+ "step": 11625
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.899696481779236e-08,
+ "loss": 0.4729,
+ "step": 11626
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.8758241003782336e-08,
+ "loss": 0.4659,
+ "step": 11627
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.852024870193649e-08,
+ "loss": 0.4463,
+ "step": 11628
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.8282987929730844e-08,
+ "loss": 0.4729,
+ "step": 11629
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.804645870458812e-08,
+ "loss": 0.4636,
+ "step": 11630
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.781066104387887e-08,
+ "loss": 0.4568,
+ "step": 11631
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.757559496491925e-08,
+ "loss": 0.457,
+ "step": 11632
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.7341260484969885e-08,
+ "loss": 0.4333,
+ "step": 11633
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.710765762124147e-08,
+ "loss": 0.4622,
+ "step": 11634
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.687478639088804e-08,
+ "loss": 0.4611,
+ "step": 11635
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.6642646811010375e-08,
+ "loss": 0.4524,
+ "step": 11636
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.6411238898655943e-08,
+ "loss": 0.4486,
+ "step": 11637
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.618056267081782e-08,
+ "loss": 0.4561,
+ "step": 11638
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.59506181444369e-08,
+ "loss": 0.465,
+ "step": 11639
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.5721405336398565e-08,
+ "loss": 0.4843,
+ "step": 11640
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.5492924263537124e-08,
+ "loss": 0.458,
+ "step": 11641
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.526517494262804e-08,
+ "loss": 0.4535,
+ "step": 11642
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.5038157390399067e-08,
+ "loss": 0.4647,
+ "step": 11643
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.481187162352018e-08,
+ "loss": 0.4704,
+ "step": 11644
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.4586317658609205e-08,
+ "loss": 0.4537,
+ "step": 11645
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.436149551223067e-08,
+ "loss": 0.4813,
+ "step": 11646
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.413740520089248e-08,
+ "loss": 0.4698,
+ "step": 11647
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.3914046741052585e-08,
+ "loss": 0.4612,
+ "step": 11648
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.369142014911231e-08,
+ "loss": 0.4437,
+ "step": 11649
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.34695254414219e-08,
+ "loss": 0.4877,
+ "step": 11650
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.3248362634275e-08,
+ "loss": 0.4612,
+ "step": 11651
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.302793174391417e-08,
+ "loss": 0.4605,
+ "step": 11652
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.280823278652645e-08,
+ "loss": 0.466,
+ "step": 11653
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.2589265778244505e-08,
+ "loss": 0.4523,
+ "step": 11654
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.237103073514991e-08,
+ "loss": 0.4371,
+ "step": 11655
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.215352767326873e-08,
+ "loss": 0.4783,
+ "step": 11656
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.193675660857265e-08,
+ "loss": 0.4543,
+ "step": 11657
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.172071755698114e-08,
+ "loss": 0.471,
+ "step": 11658
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.150541053435818e-08,
+ "loss": 0.4686,
+ "step": 11659
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.129083555651668e-08,
+ "loss": 0.4683,
+ "step": 11660
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.1076992639211824e-08,
+ "loss": 0.452,
+ "step": 11661
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.086388179814992e-08,
+ "loss": 0.4614,
+ "step": 11662
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.065150304897957e-08,
+ "loss": 0.469,
+ "step": 11663
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.043985640729718e-08,
+ "loss": 0.4555,
+ "step": 11664
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.022894188864589e-08,
+ "loss": 0.4715,
+ "step": 11665
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.0018759508513297e-08,
+ "loss": 0.4541,
+ "step": 11666
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.980930928233372e-08,
+ "loss": 0.4638,
+ "step": 11667
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.9600591225490415e-08,
+ "loss": 0.4959,
+ "step": 11668
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.93926053533089e-08,
+ "loss": 0.4738,
+ "step": 11669
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.918535168106473e-08,
+ "loss": 0.4592,
+ "step": 11670
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.897883022397574e-08,
+ "loss": 0.468,
+ "step": 11671
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8773040997208678e-08,
+ "loss": 0.4645,
+ "step": 11672
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8567984015877014e-08,
+ "loss": 0.4617,
+ "step": 11673
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8363659295037592e-08,
+ "loss": 0.4605,
+ "step": 11674
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8160066849696187e-08,
+ "loss": 0.4509,
+ "step": 11675
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.7957206694803064e-08,
+ "loss": 0.4641,
+ "step": 11676
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.77550788452563e-08,
+ "loss": 0.4295,
+ "step": 11677
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.755368331589847e-08,
+ "loss": 0.4568,
+ "step": 11678
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.7353020121518857e-08,
+ "loss": 0.4661,
+ "step": 11679
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.715308927685567e-08,
+ "loss": 0.4596,
+ "step": 11680
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.6953890796588276e-08,
+ "loss": 0.4582,
+ "step": 11681
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.67554246953472e-08,
+ "loss": 0.4804,
+ "step": 11682
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.655769098770522e-08,
+ "loss": 0.439,
+ "step": 11683
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.636068968818295e-08,
+ "loss": 0.4728,
+ "step": 11684
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.6164420811249925e-08,
+ "loss": 0.465,
+ "step": 11685
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5968884371315728e-08,
+ "loss": 0.4494,
+ "step": 11686
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5774080382743317e-08,
+ "loss": 0.4401,
+ "step": 11687
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5580008859835692e-08,
+ "loss": 0.4924,
+ "step": 11688
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.538666981684479e-08,
+ "loss": 0.4549,
+ "step": 11689
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5194063267970358e-08,
+ "loss": 0.4631,
+ "step": 11690
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5002189227354425e-08,
+ "loss": 0.4868,
+ "step": 11691
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.481104770908904e-08,
+ "loss": 0.4634,
+ "step": 11692
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.4620638727210766e-08,
+ "loss": 0.4397,
+ "step": 11693
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.4430962295701743e-08,
+ "loss": 0.4728,
+ "step": 11694
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.4242018428491944e-08,
+ "loss": 0.4633,
+ "step": 11695
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.405380713945582e-08,
+ "loss": 0.4515,
+ "step": 11696
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.3866328442414545e-08,
+ "loss": 0.4745,
+ "step": 11697
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.3679582351137098e-08,
+ "loss": 0.4766,
+ "step": 11698
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.349356887933585e-08,
+ "loss": 0.4631,
+ "step": 11699
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.330828804067098e-08,
+ "loss": 0.4695,
+ "step": 11700
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.3123739848749382e-08,
+ "loss": 0.4665,
+ "step": 11701
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2939924317124663e-08,
+ "loss": 0.46,
+ "step": 11702
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.275684145929269e-08,
+ "loss": 0.4722,
+ "step": 11703
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2574491288700485e-08,
+ "loss": 0.4655,
+ "step": 11704
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2392873818738447e-08,
+ "loss": 0.4503,
+ "step": 11705
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2211989062743688e-08,
+ "loss": 0.4614,
+ "step": 11706
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2031837034000024e-08,
+ "loss": 0.4405,
+ "step": 11707
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1852417745735764e-08,
+ "loss": 0.4648,
+ "step": 11708
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1673731211129255e-08,
+ "loss": 0.4791,
+ "step": 11709
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1495777443300005e-08,
+ "loss": 0.467,
+ "step": 11710
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.131855645531644e-08,
+ "loss": 0.4428,
+ "step": 11711
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1142068260194827e-08,
+ "loss": 0.4568,
+ "step": 11712
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0966312870893678e-08,
+ "loss": 0.4525,
+ "step": 11713
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0791290300321564e-08,
+ "loss": 0.4744,
+ "step": 11714
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0617000561329315e-08,
+ "loss": 0.4685,
+ "step": 11715
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.04434436667178e-08,
+ "loss": 0.4811,
+ "step": 11716
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.027061962923127e-08,
+ "loss": 0.4609,
+ "step": 11717
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0098528461562906e-08,
+ "loss": 0.4709,
+ "step": 11718
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9927170176348155e-08,
+ "loss": 0.4597,
+ "step": 11719
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9756544786171393e-08,
+ "loss": 0.4651,
+ "step": 11720
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9586652303562603e-08,
+ "loss": 0.4463,
+ "step": 11721
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.941749274099958e-08,
+ "loss": 0.4751,
+ "step": 11722
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.924906611090349e-08,
+ "loss": 0.4505,
+ "step": 11723
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9081372425642232e-08,
+ "loss": 0.4564,
+ "step": 11724
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8914411697531498e-08,
+ "loss": 0.4579,
+ "step": 11725
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8748183938832597e-08,
+ "loss": 0.4747,
+ "step": 11726
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8582689161751323e-08,
+ "loss": 0.4637,
+ "step": 11727
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.841792737844128e-08,
+ "loss": 0.4701,
+ "step": 11728
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8253898601002794e-08,
+ "loss": 0.4685,
+ "step": 11729
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8090602841479566e-08,
+ "loss": 0.4487,
+ "step": 11730
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.792804011186533e-08,
+ "loss": 0.4494,
+ "step": 11731
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.7766210424097207e-08,
+ "loss": 0.4415,
+ "step": 11732
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.7605113790059024e-08,
+ "loss": 0.4635,
+ "step": 11733
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.744475022158243e-08,
+ "loss": 0.459,
+ "step": 11734
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.7285119730442446e-08,
+ "loss": 0.4558,
+ "step": 11735
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.712622232836192e-08,
+ "loss": 0.4716,
+ "step": 11736
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6968058027009292e-08,
+ "loss": 0.4586,
+ "step": 11737
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6810626837999722e-08,
+ "loss": 0.4835,
+ "step": 11738
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6653928772895067e-08,
+ "loss": 0.4461,
+ "step": 11739
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.649796384320168e-08,
+ "loss": 0.4419,
+ "step": 11740
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6342732060373733e-08,
+ "loss": 0.4625,
+ "step": 11741
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6188233435809887e-08,
+ "loss": 0.4593,
+ "step": 11742
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6034467980857727e-08,
+ "loss": 0.4429,
+ "step": 11743
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5881435706806002e-08,
+ "loss": 0.4512,
+ "step": 11744
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5729136624895723e-08,
+ "loss": 0.4645,
+ "step": 11745
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5577570746309057e-08,
+ "loss": 0.4584,
+ "step": 11746
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5426738082178206e-08,
+ "loss": 0.4629,
+ "step": 11747
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5276638643578756e-08,
+ "loss": 0.4594,
+ "step": 11748
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5127272441533004e-08,
+ "loss": 0.4414,
+ "step": 11749
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.497863948700995e-08,
+ "loss": 0.4754,
+ "step": 11750
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4830739790925308e-08,
+ "loss": 0.4389,
+ "step": 11751
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4683573364138171e-08,
+ "loss": 0.4845,
+ "step": 11752
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4537140217458778e-08,
+ "loss": 0.4612,
+ "step": 11753
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.439144036163964e-08,
+ "loss": 0.4562,
+ "step": 11754
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4246473807378869e-08,
+ "loss": 0.4516,
+ "step": 11755
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.41022405653235e-08,
+ "loss": 0.4753,
+ "step": 11756
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.395874064606506e-08,
+ "loss": 0.4545,
+ "step": 11757
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.381597406014179e-08,
+ "loss": 0.4614,
+ "step": 11758
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3673940818037523e-08,
+ "loss": 0.4941,
+ "step": 11759
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3532640930182806e-08,
+ "loss": 0.4754,
+ "step": 11760
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.339207440695378e-08,
+ "loss": 0.4795,
+ "step": 11761
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3252241258673305e-08,
+ "loss": 0.4604,
+ "step": 11762
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3113141495610937e-08,
+ "loss": 0.4656,
+ "step": 11763
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2974775127980732e-08,
+ "loss": 0.4797,
+ "step": 11764
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.283714216594345e-08,
+ "loss": 0.4449,
+ "step": 11765
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2700242619606562e-08,
+ "loss": 0.4625,
+ "step": 11766
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2564076499024247e-08,
+ "loss": 0.4635,
+ "step": 11767
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2428643814195174e-08,
+ "loss": 0.4668,
+ "step": 11768
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.229394457506472e-08,
+ "loss": 0.4709,
+ "step": 11769
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2159978791524973e-08,
+ "loss": 0.4454,
+ "step": 11770
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.202674647341362e-08,
+ "loss": 0.474,
+ "step": 11771
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.1894247630516165e-08,
+ "loss": 0.4544,
+ "step": 11772
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.1762482272560382e-08,
+ "loss": 0.4765,
+ "step": 11773
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1631450409224088e-08,
+ "loss": 0.4647,
+ "step": 11774
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1501152050128472e-08,
+ "loss": 0.4871,
+ "step": 11775
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1371587204843659e-08,
+ "loss": 0.4494,
+ "step": 11776
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.124275588288426e-08,
+ "loss": 0.4947,
+ "step": 11777
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1114658093709373e-08,
+ "loss": 0.4682,
+ "step": 11778
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0987293846728141e-08,
+ "loss": 0.4486,
+ "step": 11779
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0860663151291973e-08,
+ "loss": 0.4312,
+ "step": 11780
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0734766016700093e-08,
+ "loss": 0.4613,
+ "step": 11781
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0609602452199553e-08,
+ "loss": 0.4764,
+ "step": 11782
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0485172466980776e-08,
+ "loss": 0.4795,
+ "step": 11783
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0361476070180899e-08,
+ "loss": 0.4585,
+ "step": 11784
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0238513270884876e-08,
+ "loss": 0.459,
+ "step": 11785
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0116284078121042e-08,
+ "loss": 0.4561,
+ "step": 11786
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.994788500866659e-09,
+ "loss": 0.4608,
+ "step": 11787
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.87402654804348e-09,
+ "loss": 0.4812,
+ "step": 11788
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.753998228519967e-09,
+ "loss": 0.4629,
+ "step": 11789
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.634703551110181e-09,
+ "loss": 0.4569,
+ "step": 11790
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.516142524574889e-09,
+ "loss": 0.4736,
+ "step": 11791
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.398315157619354e-09,
+ "loss": 0.4595,
+ "step": 11792
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.281221458898871e-09,
+ "loss": 0.456,
+ "step": 11793
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.164861437009897e-09,
+ "loss": 0.4692,
+ "step": 11794
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.049235100500042e-09,
+ "loss": 0.4546,
+ "step": 11795
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.93434245785696e-09,
+ "loss": 0.4422,
+ "step": 11796
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.820183517521675e-09,
+ "loss": 0.4557,
+ "step": 11797
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.706758287874151e-09,
+ "loss": 0.4557,
+ "step": 11798
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.594066777246613e-09,
+ "loss": 0.4656,
+ "step": 11799
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.482108993912441e-09,
+ "loss": 0.501,
+ "step": 11800
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.370884946095059e-09,
+ "loss": 0.4627,
+ "step": 11801
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.260394641961267e-09,
+ "loss": 0.4597,
+ "step": 11802
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.150638089624574e-09,
+ "loss": 0.4844,
+ "step": 11803
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.04161529714631e-09,
+ "loss": 0.4403,
+ "step": 11804
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.933326272532294e-09,
+ "loss": 0.4704,
+ "step": 11805
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.825771023735051e-09,
+ "loss": 0.4568,
+ "step": 11806
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.7189495586516e-09,
+ "loss": 0.4704,
+ "step": 11807
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.612861885128997e-09,
+ "loss": 0.4585,
+ "step": 11808
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.507508010955455e-09,
+ "loss": 0.4507,
+ "step": 11809
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.40288794386812e-09,
+ "loss": 0.4675,
+ "step": 11810
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.299001691550844e-09,
+ "loss": 0.4525,
+ "step": 11811
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.195849261631971e-09,
+ "loss": 0.4645,
+ "step": 11812
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.093430661686551e-09,
+ "loss": 0.4757,
+ "step": 11813
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.991745899236346e-09,
+ "loss": 0.4585,
+ "step": 11814
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.890794981748717e-09,
+ "loss": 0.4569,
+ "step": 11815
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.79057791663551e-09,
+ "loss": 0.4858,
+ "step": 11816
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.691094711258617e-09,
+ "loss": 0.4416,
+ "step": 11817
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.5923453729221935e-09,
+ "loss": 0.4474,
+ "step": 11818
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.4943299088771065e-09,
+ "loss": 0.4492,
+ "step": 11819
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.397048326323152e-09,
+ "loss": 0.4803,
+ "step": 11820
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.300500632403505e-09,
+ "loss": 0.458,
+ "step": 11821
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.204686834208051e-09,
+ "loss": 0.4613,
+ "step": 11822
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.1096069387733825e-09,
+ "loss": 0.4649,
+ "step": 11823
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.015260953080582e-09,
+ "loss": 0.4637,
+ "step": 11824
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.921648884059661e-09,
+ "loss": 0.4679,
+ "step": 11825
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.828770738584011e-09,
+ "loss": 0.4586,
+ "step": 11826
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.736626523474842e-09,
+ "loss": 0.4494,
+ "step": 11827
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.645216245497853e-09,
+ "loss": 0.446,
+ "step": 11828
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.554539911367673e-09,
+ "loss": 0.4763,
+ "step": 11829
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.4645975277412004e-09,
+ "loss": 0.4616,
+ "step": 11830
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.37538910122426e-09,
+ "loss": 0.4542,
+ "step": 11831
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.2869146383682794e-09,
+ "loss": 0.4753,
+ "step": 11832
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.199174145670283e-09,
+ "loss": 0.488,
+ "step": 11833
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.112167629572895e-09,
+ "loss": 0.4638,
+ "step": 11834
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.02589509646656e-09,
+ "loss": 0.479,
+ "step": 11835
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.94035655268621e-09,
+ "loss": 0.4608,
+ "step": 11836
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.855552004513486e-09,
+ "loss": 0.4786,
+ "step": 11837
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.7714814581756305e-09,
+ "loss": 0.4579,
+ "step": 11838
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.6881449198477035e-09,
+ "loss": 0.4622,
+ "step": 11839
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.605542395648144e-09,
+ "loss": 0.4534,
+ "step": 11840
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.52367389164432e-09,
+ "loss": 0.469,
+ "step": 11841
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.44253941384698e-09,
+ "loss": 0.4853,
+ "step": 11842
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.362138968214691e-09,
+ "loss": 0.4447,
+ "step": 11843
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.282472560651618e-09,
+ "loss": 0.4573,
+ "step": 11844
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.203540197009748e-09,
+ "loss": 0.461,
+ "step": 11845
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.125341883083334e-09,
+ "loss": 0.4492,
+ "step": 11846
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.047877624615559e-09,
+ "loss": 0.4663,
+ "step": 11847
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.971147427296318e-09,
+ "loss": 0.455,
+ "step": 11848
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.895151296758881e-09,
+ "loss": 0.4424,
+ "step": 11849
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.81988923858434e-09,
+ "loss": 0.4672,
+ "step": 11850
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.745361258300495e-09,
+ "loss": 0.4656,
+ "step": 11851
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.6715673613796353e-09,
+ "loss": 0.4624,
+ "step": 11852
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.59850755324076e-09,
+ "loss": 0.4421,
+ "step": 11853
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.5261818392484657e-09,
+ "loss": 0.4816,
+ "step": 11854
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.454590224716281e-09,
+ "loss": 0.4464,
+ "step": 11855
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.383732714900001e-09,
+ "loss": 0.45,
+ "step": 11856
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.313609315003241e-09,
+ "loss": 0.4448,
+ "step": 11857
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.244220030175216e-09,
+ "loss": 0.4695,
+ "step": 11858
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.175564865512959e-09,
+ "loss": 0.4581,
+ "step": 11859
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.107643826055773e-09,
+ "loss": 0.4873,
+ "step": 11860
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.04045691679411e-09,
+ "loss": 0.4794,
+ "step": 11861
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.9740041426606915e-09,
+ "loss": 0.4446,
+ "step": 11862
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.908285508536057e-09,
+ "loss": 0.4744,
+ "step": 11863
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.843301019245237e-09,
+ "loss": 0.442,
+ "step": 11864
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.7790506795610793e-09,
+ "loss": 0.46,
+ "step": 11865
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.7155344942020324e-09,
+ "loss": 0.4449,
+ "step": 11866
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.6527524678321424e-09,
+ "loss": 0.4606,
+ "step": 11867
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.5907046050632767e-09,
+ "loss": 0.4512,
+ "step": 11868
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.5293909104495696e-09,
+ "loss": 0.467,
+ "step": 11869
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.4688113884940855e-09,
+ "loss": 0.4508,
+ "step": 11870
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.4089660436477093e-09,
+ "loss": 0.4537,
+ "step": 11871
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.3498548803024825e-09,
+ "loss": 0.4676,
+ "step": 11872
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.2914779028015976e-09,
+ "loss": 0.472,
+ "step": 11873
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.233835115430516e-09,
+ "loss": 0.4748,
+ "step": 11874
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.1769265224225176e-09,
+ "loss": 0.4612,
+ "step": 11875
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.1207521279575925e-09,
+ "loss": 0.4694,
+ "step": 11876
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.065311936160219e-09,
+ "loss": 0.4486,
+ "step": 11877
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.0106059511015853e-09,
+ "loss": 0.4707,
+ "step": 11878
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.9566341767984774e-09,
+ "loss": 0.4409,
+ "step": 11879
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.903396617216613e-09,
+ "loss": 0.4728,
+ "step": 11880
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.8508932762628662e-09,
+ "loss": 0.4348,
+ "step": 11881
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.7991241577952624e-09,
+ "loss": 0.4634,
+ "step": 11882
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.7480892656129845e-09,
+ "loss": 0.4532,
+ "step": 11883
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.697788603466366e-09,
+ "loss": 0.4515,
+ "step": 11884
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.6482221750468984e-09,
+ "loss": 0.4701,
+ "step": 11885
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.5993899839972239e-09,
+ "loss": 0.4458,
+ "step": 11886
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.5512920339011416e-09,
+ "loss": 0.4809,
+ "step": 11887
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.503928328291382e-09,
+ "loss": 0.4552,
+ "step": 11888
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.4572988706462732e-09,
+ "loss": 0.4768,
+ "step": 11889
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.4114036643897434e-09,
+ "loss": 0.4614,
+ "step": 11890
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.3662427128924294e-09,
+ "loss": 0.4842,
+ "step": 11891
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.3218160194716778e-09,
+ "loss": 0.4597,
+ "step": 11892
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.2781235873882136e-09,
+ "loss": 0.456,
+ "step": 11893
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.2351654198528018e-09,
+ "loss": 0.4666,
+ "step": 11894
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.1929415200173656e-09,
+ "loss": 0.4657,
+ "step": 11895
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.151451890984978e-09,
+ "loss": 0.4713,
+ "step": 11896
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.1106965358009814e-09,
+ "loss": 0.4443,
+ "step": 11897
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.0706754574596468e-09,
+ "loss": 0.4491,
+ "step": 11898
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.0313886588986244e-09,
+ "loss": 0.4913,
+ "step": 11899
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 9.928361430044941e-10,
+ "loss": 0.4457,
+ "step": 11900
+ }
+ ],
+ "logging_steps": 1.0,
+ "max_steps": 11952,
+ "num_input_tokens_seen": 0,
+ "num_train_epochs": 1,
+ "save_steps": 100,
+ "total_flos": 0.0,
+ "train_batch_size": 16,
+ "trial_name": null,
+ "trial_params": null
+}
diff --git a/checkpoint-11900/vision_tower/config.json b/checkpoint-11900/vision_tower/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..5515c0578f6ddf3e45d1ab677176774db6634110
--- /dev/null
+++ b/checkpoint-11900/vision_tower/config.json
@@ -0,0 +1,19 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/vision_tower",
+ "architectures": [
+ "SiglipVisionModel"
+ ],
+ "attention_dropout": 0.0,
+ "hidden_act": "gelu_pytorch_tanh",
+ "hidden_size": 1152,
+ "image_size": 384,
+ "intermediate_size": 4304,
+ "layer_norm_eps": 1e-06,
+ "model_type": "siglip_vision_model",
+ "num_attention_heads": 16,
+ "num_channels": 3,
+ "num_hidden_layers": 27,
+ "patch_size": 14,
+ "torch_dtype": "bfloat16",
+ "transformers_version": "4.36.2"
+}
diff --git a/checkpoint-11900/vision_tower/model.safetensors b/checkpoint-11900/vision_tower/model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..5003e60dc5514579789356bf50818e2121ae56f2
--- /dev/null
+++ b/checkpoint-11900/vision_tower/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c602abf3ee39781f02b41100da0213fe0a5ffb7ec869b4dc0fed316e80a76cd0
+size 856506120
diff --git a/checkpoint-11900/vision_tower/preprocessor_config.json b/checkpoint-11900/vision_tower/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f13134ed29056f82f3ab7e0246f0ab973e7ecf3
--- /dev/null
+++ b/checkpoint-11900/vision_tower/preprocessor_config.json
@@ -0,0 +1,24 @@
+{
+ "do_convert_rgb": true,
+ "do_normalize": true,
+ "do_rescale": true,
+ "do_resize": true,
+ "image_mean": [
+ 0.5,
+ 0.5,
+ 0.5
+ ],
+ "image_processor_type": "SiglipImageProcessor",
+ "image_std": [
+ 0.5,
+ 0.5,
+ 0.5
+ ],
+ "processor_class": "SiglipProcessor",
+ "resample": 3,
+ "rescale_factor": 0.00392156862745098,
+ "size": {
+ "height": 384,
+ "width": 384
+ }
+}
diff --git a/checkpoint-11900/zero_to_fp32.py b/checkpoint-11900/zero_to_fp32.py
new file mode 100644
index 0000000000000000000000000000000000000000..c5246ff52274e1d6142001ccf085186d3545ce57
--- /dev/null
+++ b/checkpoint-11900/zero_to_fp32.py
@@ -0,0 +1,578 @@
+#!/usr/bin/env python
+
+# Copyright (c) Microsoft Corporation.
+# SPDX-License-Identifier: Apache-2.0
+
+# DeepSpeed Team
+
+# This script extracts fp32 consolidated weights from a zero 2 and 3 DeepSpeed checkpoints. It gets
+# copied into the top level checkpoint dir, so the user can easily do the conversion at any point in
+# the future. Once extracted, the weights don't require DeepSpeed and can be used in any
+# application.
+#
+# example: python zero_to_fp32.py . pytorch_model.bin
+
+import argparse
+import torch
+import glob
+import math
+import os
+import re
+from collections import OrderedDict
+from dataclasses import dataclass
+
+# while this script doesn't use deepspeed to recover data, since the checkpoints are pickled with
+# DeepSpeed data structures it has to be available in the current python environment.
+from deepspeed.utils import logger
+from deepspeed.checkpoint.constants import (DS_VERSION, OPTIMIZER_STATE_DICT, SINGLE_PARTITION_OF_FP32_GROUPS,
+ FP32_FLAT_GROUPS, ZERO_STAGE, PARTITION_COUNT, PARAM_SHAPES, BUFFER_NAMES,
+ FROZEN_PARAM_SHAPES, FROZEN_PARAM_FRAGMENTS)
+
+
+@dataclass
+class zero_model_state:
+ buffers: dict()
+ param_shapes: dict()
+ shared_params: list
+ ds_version: int
+ frozen_param_shapes: dict()
+ frozen_param_fragments: dict()
+
+
+debug = 0
+
+# load to cpu
+device = torch.device('cpu')
+
+
+def atoi(text):
+ return int(text) if text.isdigit() else text
+
+
+def natural_keys(text):
+ '''
+ alist.sort(key=natural_keys) sorts in human order
+ http://nedbatchelder.com/blog/200712/human_sorting.html
+ (See Toothy's implementation in the comments)
+ '''
+ return [atoi(c) for c in re.split(r'(\d+)', text)]
+
+
+def get_model_state_file(checkpoint_dir, zero_stage):
+ if not os.path.isdir(checkpoint_dir):
+ raise FileNotFoundError(f"Directory '{checkpoint_dir}' doesn't exist")
+
+ # there should be only one file
+ if zero_stage == 2:
+ file = os.path.join(checkpoint_dir, "mp_rank_00_model_states.pt")
+ elif zero_stage == 3:
+ file = os.path.join(checkpoint_dir, "zero_pp_rank_0_mp_rank_00_model_states.pt")
+
+ if not os.path.exists(file):
+ raise FileNotFoundError(f"can't find model states file at '{file}'")
+
+ return file
+
+
+def get_checkpoint_files(checkpoint_dir, glob_pattern):
+ # XXX: need to test that this simple glob rule works for multi-node setup too
+ ckpt_files = sorted(glob.glob(os.path.join(checkpoint_dir, glob_pattern)), key=natural_keys)
+
+ if len(ckpt_files) == 0:
+ raise FileNotFoundError(f"can't find {glob_pattern} files in directory '{checkpoint_dir}'")
+
+ return ckpt_files
+
+
+def get_optim_files(checkpoint_dir):
+ return get_checkpoint_files(checkpoint_dir, "*_optim_states.pt")
+
+
+def get_model_state_files(checkpoint_dir):
+ return get_checkpoint_files(checkpoint_dir, "*_model_states.pt")
+
+
+def parse_model_states(files):
+ zero_model_states = []
+ for file in files:
+ state_dict = torch.load(file, map_location=device)
+
+ if BUFFER_NAMES not in state_dict:
+ raise ValueError(f"{file} is not a model state checkpoint")
+ buffer_names = state_dict[BUFFER_NAMES]
+ if debug:
+ print("Found buffers:", buffer_names)
+
+ # recover just the buffers while restoring them to fp32 if they were saved in fp16
+ buffers = {k: v.float() for k, v in state_dict["module"].items() if k in buffer_names}
+ param_shapes = state_dict[PARAM_SHAPES]
+
+ # collect parameters that are included in param_shapes
+ param_names = []
+ for s in param_shapes:
+ for name in s.keys():
+ param_names.append(name)
+
+ # update with frozen parameters
+ frozen_param_shapes = state_dict.get(FROZEN_PARAM_SHAPES, None)
+ if frozen_param_shapes is not None:
+ if debug:
+ print(f"Found frozen_param_shapes: {frozen_param_shapes}")
+ param_names += list(frozen_param_shapes.keys())
+
+ # handle shared params
+ shared_params = [[k, v] for k, v in state_dict["shared_params"].items()]
+
+ ds_version = state_dict.get(DS_VERSION, None)
+
+ frozen_param_fragments = state_dict.get(FROZEN_PARAM_FRAGMENTS, None)
+
+ z_model_state = zero_model_state(buffers=buffers,
+ param_shapes=param_shapes,
+ shared_params=shared_params,
+ ds_version=ds_version,
+ frozen_param_shapes=frozen_param_shapes,
+ frozen_param_fragments=frozen_param_fragments)
+ zero_model_states.append(z_model_state)
+
+ return zero_model_states
+
+
+def parse_optim_states(files, ds_checkpoint_dir):
+
+ total_files = len(files)
+ state_dicts = []
+ for f in files:
+ state_dicts.append(torch.load(f, map_location=device))
+
+ if not ZERO_STAGE in state_dicts[0][OPTIMIZER_STATE_DICT]:
+ raise ValueError(f"{files[0]} is not a zero checkpoint")
+ zero_stage = state_dicts[0][OPTIMIZER_STATE_DICT][ZERO_STAGE]
+ world_size = state_dicts[0][OPTIMIZER_STATE_DICT][PARTITION_COUNT]
+
+ # For ZeRO-2 each param group can have different partition_count as data parallelism for expert
+ # parameters can be different from data parallelism for non-expert parameters. So we can just
+ # use the max of the partition_count to get the dp world_size.
+
+ if type(world_size) is list:
+ world_size = max(world_size)
+
+ if world_size != total_files:
+ raise ValueError(
+ f"Expected {world_size} of '*_optim_states.pt' under '{ds_checkpoint_dir}' but found {total_files} files. "
+ "Possibly due to an overwrite of an old checkpoint, or a checkpoint didn't get saved by one or more processes."
+ )
+
+ # the groups are named differently in each stage
+ if zero_stage == 2:
+ fp32_groups_key = SINGLE_PARTITION_OF_FP32_GROUPS
+ elif zero_stage == 3:
+ fp32_groups_key = FP32_FLAT_GROUPS
+ else:
+ raise ValueError(f"unknown zero stage {zero_stage}")
+
+ if zero_stage == 2:
+ fp32_flat_groups = [state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key] for i in range(len(state_dicts))]
+ elif zero_stage == 3:
+ # if there is more than one param group, there will be multiple flattened tensors - one
+ # flattened tensor per group - for simplicity merge them into a single tensor
+ #
+ # XXX: could make the script more memory efficient for when there are multiple groups - it
+ # will require matching the sub-lists of param_shapes for each param group flattened tensor
+
+ fp32_flat_groups = [
+ torch.cat(state_dicts[i][OPTIMIZER_STATE_DICT][fp32_groups_key], 0) for i in range(len(state_dicts))
+ ]
+
+ return zero_stage, world_size, fp32_flat_groups
+
+
+def _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir):
+ """
+ Returns fp32 state_dict reconstructed from ds checkpoint
+
+ Args:
+ - ``ds_checkpoint_dir``: path to the deepspeed checkpoint folder (where the optimizer files are)
+
+ """
+ print(f"Processing zero checkpoint '{ds_checkpoint_dir}'")
+
+ optim_files = get_optim_files(ds_checkpoint_dir)
+ zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
+ print(f"Detected checkpoint of type zero stage {zero_stage}, world_size: {world_size}")
+
+ model_files = get_model_state_files(ds_checkpoint_dir)
+
+ zero_model_states = parse_model_states(model_files)
+ print(f'Parsing checkpoint created by deepspeed=={zero_model_states[0].ds_version}')
+
+ if zero_stage == 2:
+ return _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states)
+ elif zero_stage == 3:
+ return _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states)
+
+
+def _zero2_merge_frozen_params(state_dict, zero_model_states):
+ if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+ return
+
+ frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+ frozen_param_fragments = zero_model_states[0].frozen_param_fragments
+
+ if debug:
+ num_elem = sum(s.numel() for s in frozen_param_shapes.values())
+ print(f'rank 0: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+ wanted_params = len(frozen_param_shapes)
+ wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+ avail_numel = sum([p.numel() for p in frozen_param_fragments.values()])
+ print(f'Frozen params: Have {avail_numel} numels to process.')
+ print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+ total_params = 0
+ total_numel = 0
+ for name, shape in frozen_param_shapes.items():
+ total_params += 1
+ unpartitioned_numel = shape.numel()
+ total_numel += unpartitioned_numel
+
+ state_dict[name] = frozen_param_fragments[name]
+
+ if debug:
+ print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+
+ print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+ param_shapes = zero_model_states[0].param_shapes
+
+ # Reconstruction protocol:
+ #
+ # XXX: document this
+
+ if debug:
+ for i in range(world_size):
+ for j in range(len(fp32_flat_groups[0])):
+ print(f"{FP32_FLAT_GROUPS}[{i}][{j}].shape={fp32_flat_groups[i][j].shape}")
+
+ # XXX: memory usage doubles here (zero2)
+ num_param_groups = len(fp32_flat_groups[0])
+ merged_single_partition_of_fp32_groups = []
+ for i in range(num_param_groups):
+ merged_partitions = [sd[i] for sd in fp32_flat_groups]
+ full_single_fp32_vector = torch.cat(merged_partitions, 0)
+ merged_single_partition_of_fp32_groups.append(full_single_fp32_vector)
+ avail_numel = sum(
+ [full_single_fp32_vector.numel() for full_single_fp32_vector in merged_single_partition_of_fp32_groups])
+
+ if debug:
+ wanted_params = sum([len(shapes) for shapes in param_shapes])
+ wanted_numel = sum([sum(shape.numel() for shape in shapes.values()) for shapes in param_shapes])
+ # not asserting if there is a mismatch due to possible padding
+ print(f"Have {avail_numel} numels to process.")
+ print(f"Need {wanted_numel} numels in {wanted_params} params.")
+
+ # params
+ # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+ # out-of-core computing solution
+ total_numel = 0
+ total_params = 0
+ for shapes, full_single_fp32_vector in zip(param_shapes, merged_single_partition_of_fp32_groups):
+ offset = 0
+ avail_numel = full_single_fp32_vector.numel()
+ for name, shape in shapes.items():
+
+ unpartitioned_numel = shape.numel()
+ total_numel += unpartitioned_numel
+ total_params += 1
+
+ if debug:
+ print(f"{name} full shape: {shape} unpartitioned numel {unpartitioned_numel} ")
+ state_dict[name] = full_single_fp32_vector.narrow(0, offset, unpartitioned_numel).view(shape)
+ offset += unpartitioned_numel
+
+ # Z2 started to align to 2*world_size to improve nccl performance. Therefore both offset and
+ # avail_numel can differ by anywhere between 0..2*world_size. Due to two unrelated complex
+ # paddings performed in the code it's almost impossible to predict the exact numbers w/o the
+ # live optimizer object, so we are checking that the numbers are within the right range
+ align_to = 2 * world_size
+
+ def zero2_align(x):
+ return align_to * math.ceil(x / align_to)
+
+ if debug:
+ print(f"original offset={offset}, avail_numel={avail_numel}")
+
+ offset = zero2_align(offset)
+ avail_numel = zero2_align(avail_numel)
+
+ if debug:
+ print(f"aligned offset={offset}, avail_numel={avail_numel}")
+
+ # Sanity check
+ if offset != avail_numel:
+ raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+ print(f"Reconstructed fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero2_checkpoint(world_size, fp32_flat_groups, zero_model_states):
+ state_dict = OrderedDict()
+
+ # buffers
+ buffers = zero_model_states[0].buffers
+ state_dict.update(buffers)
+ if debug:
+ print(f"added {len(buffers)} buffers")
+
+ _zero2_merge_frozen_params(state_dict, zero_model_states)
+
+ _zero2_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+ # recover shared parameters
+ for pair in zero_model_states[0].shared_params:
+ if pair[1] in state_dict:
+ state_dict[pair[0]] = state_dict[pair[1]]
+
+ return state_dict
+
+
+def zero3_partitioned_param_info(unpartitioned_numel, world_size):
+ remainder = unpartitioned_numel % world_size
+ padding_numel = (world_size - remainder) if remainder else 0
+ partitioned_numel = math.ceil(unpartitioned_numel / world_size)
+ return partitioned_numel, padding_numel
+
+
+def _zero3_merge_frozen_params(state_dict, world_size, zero_model_states):
+ if zero_model_states[0].frozen_param_shapes is None or len(zero_model_states[0].frozen_param_shapes) == 0:
+ return
+
+ if debug:
+ for i in range(world_size):
+ num_elem = sum(s.numel() for s in zero_model_states[i].frozen_param_fragments.values())
+ print(f'rank {i}: {FROZEN_PARAM_SHAPES}.numel = {num_elem}')
+
+ frozen_param_shapes = zero_model_states[0].frozen_param_shapes
+ wanted_params = len(frozen_param_shapes)
+ wanted_numel = sum(s.numel() for s in frozen_param_shapes.values())
+ avail_numel = sum([p.numel() for p in zero_model_states[0].frozen_param_fragments.values()]) * world_size
+ print(f'Frozen params: Have {avail_numel} numels to process.')
+ print(f'Frozen params: Need {wanted_numel} numels in {wanted_params} params')
+
+ total_params = 0
+ total_numel = 0
+ for name, shape in zero_model_states[0].frozen_param_shapes.items():
+ total_params += 1
+ unpartitioned_numel = shape.numel()
+ total_numel += unpartitioned_numel
+
+ param_frags = tuple(model_state.frozen_param_fragments[name] for model_state in zero_model_states)
+ state_dict[name] = torch.cat(param_frags, 0).narrow(0, 0, unpartitioned_numel).view(shape)
+
+ partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+ if debug:
+ print(
+ f"Frozen params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+ )
+
+ print(f"Reconstructed Frozen fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states):
+ param_shapes = zero_model_states[0].param_shapes
+ avail_numel = fp32_flat_groups[0].numel() * world_size
+ # Reconstruction protocol: For zero3 we need to zip the partitions together at boundary of each
+ # param, re-consolidating each param, while dealing with padding if any
+
+ # merge list of dicts, preserving order
+ param_shapes = {k: v for d in param_shapes for k, v in d.items()}
+
+ if debug:
+ for i in range(world_size):
+ print(f"{FP32_FLAT_GROUPS}[{i}].shape={fp32_flat_groups[i].shape}")
+
+ wanted_params = len(param_shapes)
+ wanted_numel = sum(shape.numel() for shape in param_shapes.values())
+ # not asserting if there is a mismatch due to possible padding
+ avail_numel = fp32_flat_groups[0].numel() * world_size
+ print(f"Trainable params: Have {avail_numel} numels to process.")
+ print(f"Trainable params: Need {wanted_numel} numels in {wanted_params} params.")
+
+ # params
+ # XXX: for huge models that can't fit into the host's RAM we will have to recode this to support
+ # out-of-core computing solution
+ offset = 0
+ total_numel = 0
+ total_params = 0
+ for name, shape in param_shapes.items():
+
+ unpartitioned_numel = shape.numel()
+ total_numel += unpartitioned_numel
+ total_params += 1
+
+ partitioned_numel, partitioned_padding_numel = zero3_partitioned_param_info(unpartitioned_numel, world_size)
+
+ if debug:
+ print(
+ f"Trainable params: {total_params} {name} full shape: {shape} partition0 numel={partitioned_numel} partitioned_padding_numel={partitioned_padding_numel}"
+ )
+
+ # XXX: memory usage doubles here
+ state_dict[name] = torch.cat(
+ tuple(fp32_flat_groups[i].narrow(0, offset, partitioned_numel) for i in range(world_size)),
+ 0).narrow(0, 0, unpartitioned_numel).view(shape)
+ offset += partitioned_numel
+
+ offset *= world_size
+
+ # Sanity check
+ if offset != avail_numel:
+ raise ValueError(f"consumed {offset} numels out of {avail_numel} - something is wrong")
+
+ print(f"Reconstructed Trainable fp32 state dict with {total_params} params {total_numel} elements")
+
+
+def _get_fp32_state_dict_from_zero3_checkpoint(world_size, fp32_flat_groups, zero_model_states):
+ state_dict = OrderedDict()
+
+ # buffers
+ buffers = zero_model_states[0].buffers
+ state_dict.update(buffers)
+ if debug:
+ print(f"added {len(buffers)} buffers")
+
+ _zero3_merge_frozen_params(state_dict, world_size, zero_model_states)
+
+ _zero3_merge_trainable_params(state_dict, world_size, fp32_flat_groups, zero_model_states)
+
+ # recover shared parameters
+ for pair in zero_model_states[0].shared_params:
+ if pair[1] in state_dict:
+ state_dict[pair[0]] = state_dict[pair[1]]
+
+ return state_dict
+
+
+def get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag=None):
+ """
+ Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated state_dict that can be loaded with
+ ``load_state_dict()`` and used for training without DeepSpeed or shared with others, for example
+ via a model hub.
+
+ Args:
+ - ``checkpoint_dir``: path to the desired checkpoint folder
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in 'latest' file. e.g., ``global_step14``
+
+ Returns:
+ - pytorch ``state_dict``
+
+ Note: this approach may not work if your application doesn't have sufficient free CPU memory and
+ you may need to use the offline approach using the ``zero_to_fp32.py`` script that is saved with
+ the checkpoint.
+
+ A typical usage might be ::
+
+ from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
+ # do the training and checkpoint saving
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir) # already on cpu
+ model = model.cpu() # move to cpu
+ model.load_state_dict(state_dict)
+ # submit to model hub or save the model to share with others
+
+ In this example the ``model`` will no longer be usable in the deepspeed context of the same
+ application. i.e. you will need to re-initialize the deepspeed engine, since
+ ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+ If you want it all done for you, use ``load_state_dict_from_zero_checkpoint`` instead.
+
+ """
+ if tag is None:
+ latest_path = os.path.join(checkpoint_dir, 'latest')
+ if os.path.isfile(latest_path):
+ with open(latest_path, 'r') as fd:
+ tag = fd.read().strip()
+ else:
+ raise ValueError(f"Unable to find 'latest' file at {latest_path}")
+
+ ds_checkpoint_dir = os.path.join(checkpoint_dir, tag)
+
+ if not os.path.isdir(ds_checkpoint_dir):
+ raise FileNotFoundError(f"Directory '{ds_checkpoint_dir}' doesn't exist")
+
+ return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir)
+
+
+def convert_zero_checkpoint_to_fp32_state_dict(checkpoint_dir, output_file, tag=None):
+ """
+ Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict`` file that can be
+ loaded with ``torch.load(file)`` + ``load_state_dict()`` and used for training without DeepSpeed.
+
+ Args:
+ - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+ - ``output_file``: path to the pytorch fp32 state_dict output file (e.g. path/pytorch_model.bin)
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+ """
+
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
+ print(f"Saving fp32 state dict to {output_file}")
+ torch.save(state_dict, output_file)
+
+
+def load_state_dict_from_zero_checkpoint(model, checkpoint_dir, tag=None):
+ """
+ 1. Put the provided model to cpu
+ 2. Convert ZeRO 2 or 3 checkpoint into a single fp32 consolidated ``state_dict``
+ 3. Load it into the provided model
+
+ Args:
+ - ``model``: the model object to update
+ - ``checkpoint_dir``: path to the desired checkpoint folder. (one that contains the tag-folder, like ``global_step14``)
+ - ``tag``: checkpoint tag used as a unique identifier for checkpoint. If not provided will attempt to load tag in the file named ``latest`` in the checkpoint folder, e.g., ``global_step14``
+
+ Returns:
+ - ``model`: modified model
+
+ Make sure you have plenty of CPU memory available before you call this function. If you don't
+ have enough use the ``zero_to_fp32.py`` utility to do the conversion. You will find it
+ conveniently placed for you in the checkpoint folder.
+
+ A typical usage might be ::
+
+ from deepspeed.utils.zero_to_fp32 import load_state_dict_from_zero_checkpoint
+ model = load_state_dict_from_zero_checkpoint(trainer.model, checkpoint_dir)
+ # submit to model hub or save the model to share with others
+
+ Note, that once this was run, the ``model`` will no longer be usable in the deepspeed context
+ of the same application. i.e. you will need to re-initialize the deepspeed engine, since
+ ``model.load_state_dict(state_dict)`` will remove all the deepspeed magic from it.
+
+ """
+ logger.info(f"Extracting fp32 weights")
+ state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
+
+ logger.info(f"Overwriting model with fp32 weights")
+ model = model.cpu()
+ model.load_state_dict(state_dict, strict=False)
+
+ return model
+
+
+if __name__ == "__main__":
+
+ parser = argparse.ArgumentParser()
+ parser.add_argument("checkpoint_dir",
+ type=str,
+ help="path to the desired checkpoint folder, e.g., path/checkpoint-12")
+ parser.add_argument(
+ "output_file",
+ type=str,
+ help="path to the pytorch fp32 state_dict output file (e.g. path/checkpoint-12/pytorch_model.bin)")
+ parser.add_argument("-d", "--debug", action='store_true', help="enable debug")
+ args = parser.parse_args()
+
+ debug = args.debug
+
+ convert_zero_checkpoint_to_fp32_state_dict(args.checkpoint_dir, args.output_file)
diff --git a/config.json b/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9325453c3515dd581031b1b6ac79fba4653ed69f
--- /dev/null
+++ b/config.json
@@ -0,0 +1,253 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask",
+ "architectures": [
+ "LlavaLlamaModel"
+ ],
+ "drop_path_rate": 0.0,
+ "hidden_size": 2560,
+ "image_aspect_ratio": "resize",
+ "interpolate_mode": "linear",
+ "llm_cfg": {
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/llm",
+ "add_cross_attention": false,
+ "architectures": [
+ "LlamaForCausalLM"
+ ],
+ "attention_bias": false,
+ "attention_dropout": 0.0,
+ "bad_words_ids": null,
+ "begin_suppress_tokens": null,
+ "bos_token_id": 1,
+ "chunk_size_feed_forward": 0,
+ "cross_attention_hidden_size": null,
+ "decoder_start_token_id": null,
+ "diversity_penalty": 0.0,
+ "do_sample": false,
+ "early_stopping": false,
+ "encoder_no_repeat_ngram_size": 0,
+ "eos_token_id": 2,
+ "exponential_decay_length_penalty": null,
+ "finetuning_task": null,
+ "forced_bos_token_id": null,
+ "forced_eos_token_id": null,
+ "hidden_act": "silu",
+ "hidden_size": 2560,
+ "id2label": {
+ "0": "LABEL_0",
+ "1": "LABEL_1"
+ },
+ "initializer_range": 0.02,
+ "intermediate_size": 6912,
+ "is_decoder": false,
+ "is_encoder_decoder": false,
+ "label2id": {
+ "LABEL_0": 0,
+ "LABEL_1": 1
+ },
+ "length_penalty": 1.0,
+ "max_length": 20,
+ "max_position_embeddings": 4096,
+ "min_length": 0,
+ "model_max_length": 4096,
+ "model_type": "llama",
+ "no_repeat_ngram_size": 0,
+ "num_attention_heads": 20,
+ "num_beam_groups": 1,
+ "num_beams": 1,
+ "num_hidden_layers": 32,
+ "num_key_value_heads": 20,
+ "num_return_sequences": 1,
+ "output_attentions": false,
+ "output_hidden_states": false,
+ "output_scores": false,
+ "pad_token_id": 0,
+ "prefix": null,
+ "pretraining_tp": 1,
+ "problem_type": null,
+ "pruned_heads": {},
+ "remove_invalid_values": false,
+ "repetition_penalty": 1.0,
+ "return_dict": true,
+ "return_dict_in_generate": false,
+ "rms_norm_eps": 1e-05,
+ "rope_scaling": null,
+ "rope_theta": 10000.0,
+ "sep_token_id": null,
+ "suppress_tokens": null,
+ "task_specific_params": null,
+ "temperature": 1.0,
+ "tf_legacy_loss": false,
+ "tie_encoder_decoder": false,
+ "tie_word_embeddings": false,
+ "tokenizer_class": null,
+ "tokenizer_model_max_length": 4096,
+ "tokenizer_padding_side": "right",
+ "top_k": 50,
+ "top_p": 1.0,
+ "torch_dtype": "bfloat16",
+ "torchscript": false,
+ "typical_p": 1.0,
+ "use_bfloat16": false,
+ "use_cache": true,
+ "vocab_size": 32000
+ },
+ "mm_hidden_size": 1152,
+ "mm_projector_cfg": {
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/mm_projector",
+ "add_cross_attention": false,
+ "architectures": [
+ "MultimodalProjector"
+ ],
+ "bad_words_ids": null,
+ "begin_suppress_tokens": null,
+ "bos_token_id": null,
+ "chunk_size_feed_forward": 0,
+ "cross_attention_hidden_size": null,
+ "decoder_start_token_id": null,
+ "diversity_penalty": 0.0,
+ "do_sample": false,
+ "early_stopping": false,
+ "encoder_no_repeat_ngram_size": 0,
+ "eos_token_id": null,
+ "exponential_decay_length_penalty": null,
+ "finetuning_task": null,
+ "forced_bos_token_id": null,
+ "forced_eos_token_id": null,
+ "id2label": {
+ "0": "LABEL_0",
+ "1": "LABEL_1"
+ },
+ "is_decoder": false,
+ "is_encoder_decoder": false,
+ "label2id": {
+ "LABEL_0": 0,
+ "LABEL_1": 1
+ },
+ "length_penalty": 1.0,
+ "max_length": 20,
+ "min_length": 0,
+ "mm_projector_type": "mlp_downsample",
+ "model_type": "v2l_projector",
+ "no_repeat_ngram_size": 0,
+ "num_beam_groups": 1,
+ "num_beams": 1,
+ "num_return_sequences": 1,
+ "output_attentions": false,
+ "output_hidden_states": false,
+ "output_scores": false,
+ "pad_token_id": null,
+ "prefix": null,
+ "problem_type": null,
+ "pruned_heads": {},
+ "remove_invalid_values": false,
+ "repetition_penalty": 1.0,
+ "return_dict": true,
+ "return_dict_in_generate": false,
+ "sep_token_id": null,
+ "suppress_tokens": null,
+ "task_specific_params": null,
+ "temperature": 1.0,
+ "tf_legacy_loss": false,
+ "tie_encoder_decoder": false,
+ "tie_word_embeddings": true,
+ "tokenizer_class": null,
+ "top_k": 50,
+ "top_p": 1.0,
+ "torch_dtype": "bfloat16",
+ "torchscript": false,
+ "typical_p": 1.0,
+ "use_bfloat16": false
+ },
+ "mm_projector_lr": null,
+ "mm_use_im_patch_token": false,
+ "mm_use_im_start_end": false,
+ "mm_vision_select_feature": "cls_patch",
+ "mm_vision_select_layer": -2,
+ "model_dtype": "torch.bfloat16",
+ "model_type": "llava_llama",
+ "num_video_frames": 8,
+ "resume_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask",
+ "s2": false,
+ "s2_max_split_size": 336,
+ "s2_scales": "336,672,1008",
+ "transformers_version": "4.36.2",
+ "tune_language_model": true,
+ "tune_mm_projector": true,
+ "tune_vision_tower": true,
+ "vision_resolution": -1,
+ "vision_tower_cfg": {
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/vision_tower",
+ "add_cross_attention": false,
+ "architectures": [
+ "SiglipVisionModel"
+ ],
+ "attention_dropout": 0.0,
+ "bad_words_ids": null,
+ "begin_suppress_tokens": null,
+ "bos_token_id": null,
+ "chunk_size_feed_forward": 0,
+ "cross_attention_hidden_size": null,
+ "decoder_start_token_id": null,
+ "diversity_penalty": 0.0,
+ "do_sample": false,
+ "early_stopping": false,
+ "encoder_no_repeat_ngram_size": 0,
+ "eos_token_id": null,
+ "exponential_decay_length_penalty": null,
+ "finetuning_task": null,
+ "forced_bos_token_id": null,
+ "forced_eos_token_id": null,
+ "hidden_act": "gelu_pytorch_tanh",
+ "hidden_size": 1152,
+ "id2label": {
+ "0": "LABEL_0",
+ "1": "LABEL_1"
+ },
+ "image_size": 384,
+ "intermediate_size": 4304,
+ "is_decoder": false,
+ "is_encoder_decoder": false,
+ "label2id": {
+ "LABEL_0": 0,
+ "LABEL_1": 1
+ },
+ "layer_norm_eps": 1e-06,
+ "length_penalty": 1.0,
+ "max_length": 20,
+ "min_length": 0,
+ "model_type": "siglip_vision_model",
+ "no_repeat_ngram_size": 0,
+ "num_attention_heads": 16,
+ "num_beam_groups": 1,
+ "num_beams": 1,
+ "num_channels": 3,
+ "num_hidden_layers": 27,
+ "num_return_sequences": 1,
+ "output_attentions": false,
+ "output_hidden_states": false,
+ "output_scores": false,
+ "pad_token_id": null,
+ "patch_size": 14,
+ "prefix": null,
+ "problem_type": null,
+ "pruned_heads": {},
+ "remove_invalid_values": false,
+ "repetition_penalty": 1.0,
+ "return_dict": true,
+ "return_dict_in_generate": false,
+ "sep_token_id": null,
+ "suppress_tokens": null,
+ "task_specific_params": null,
+ "temperature": 1.0,
+ "tf_legacy_loss": false,
+ "tie_encoder_decoder": false,
+ "tie_word_embeddings": true,
+ "tokenizer_class": null,
+ "top_k": 50,
+ "top_p": 1.0,
+ "torch_dtype": "bfloat16",
+ "torchscript": false,
+ "typical_p": 1.0,
+ "use_bfloat16": false
+ }
+}
diff --git a/llm/config.json b/llm/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..d385ac57663b58ba80dee4a8e8d3456f55c26c42
--- /dev/null
+++ b/llm/config.json
@@ -0,0 +1,32 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/llm",
+ "architectures": [
+ "LlamaForCausalLM"
+ ],
+ "attention_bias": false,
+ "attention_dropout": 0.0,
+ "bos_token_id": 1,
+ "eos_token_id": 2,
+ "hidden_act": "silu",
+ "hidden_size": 2560,
+ "initializer_range": 0.02,
+ "intermediate_size": 6912,
+ "max_position_embeddings": 4096,
+ "model_max_length": 4096,
+ "model_type": "llama",
+ "num_attention_heads": 20,
+ "num_hidden_layers": 32,
+ "num_key_value_heads": 20,
+ "pad_token_id": 0,
+ "pretraining_tp": 1,
+ "rms_norm_eps": 1e-05,
+ "rope_scaling": null,
+ "rope_theta": 10000.0,
+ "tie_word_embeddings": false,
+ "tokenizer_model_max_length": 4096,
+ "tokenizer_padding_side": "right",
+ "torch_dtype": "bfloat16",
+ "transformers_version": "4.36.2",
+ "use_cache": true,
+ "vocab_size": 32000
+}
diff --git a/llm/generation_config.json b/llm/generation_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..bf84ec1a28ba89feb07162d95b06633a40b4975f
--- /dev/null
+++ b/llm/generation_config.json
@@ -0,0 +1,7 @@
+{
+ "_from_model_config": true,
+ "bos_token_id": 1,
+ "eos_token_id": 2,
+ "pad_token_id": 0,
+ "transformers_version": "4.36.2"
+}
diff --git a/llm/model-00001-of-00002.safetensors b/llm/model-00001-of-00002.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..27ddd467f481d9b88710818436c2ca8991140415
--- /dev/null
+++ b/llm/model-00001-of-00002.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d34abe1d76878de8223dc920a1aca528f03f5a076ab0edc3ef96c0c829471830
+size 4974521464
diff --git a/llm/model-00002-of-00002.safetensors b/llm/model-00002-of-00002.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..3c4a05d6ad9eb29af550cee87fcca1544dcf9e6f
--- /dev/null
+++ b/llm/model-00002-of-00002.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:81eb8fea09f4c1d6e0939133165c20adbacc5197dc1976727ae0b3f885a676e6
+size 428632856
diff --git a/llm/model.safetensors.index.json b/llm/model.safetensors.index.json
new file mode 100644
index 0000000000000000000000000000000000000000..8b173c9ac8194749df58c92051618c0ff74c4c20
--- /dev/null
+++ b/llm/model.safetensors.index.json
@@ -0,0 +1,298 @@
+{
+ "metadata": {
+ "total_size": 5403120640
+ },
+ "weight_map": {
+ "lm_head.weight": "model-00002-of-00002.safetensors",
+ "model.embed_tokens.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.21.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.22.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.23.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.24.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.25.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.26.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.27.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.28.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.29.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.input_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.30.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.30.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.31.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
+ "model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
+ "model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
+ "model.norm.weight": "model-00002-of-00002.safetensors"
+ }
+}
diff --git a/llm/special_tokens_map.json b/llm/special_tokens_map.json
new file mode 100644
index 0000000000000000000000000000000000000000..14761dcf1466dc232bd41de9c21d4c617b15755e
--- /dev/null
+++ b/llm/special_tokens_map.json
@@ -0,0 +1,24 @@
+{
+ "bos_token": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "eos_token": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
+ "pad_token": "",
+ "unk_token": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ }
+}
diff --git a/llm/tokenizer.model b/llm/tokenizer.model
new file mode 100644
index 0000000000000000000000000000000000000000..3b7eab905db502ae7629c8a3c1f8412a3178c4c2
--- /dev/null
+++ b/llm/tokenizer.model
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7aedb3582ecda9fa99ee9242c17a9658f6744db083ee6ebdc8fb14857f84d220
+size 499723
diff --git a/llm/tokenizer_config.json b/llm/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..47ab96cd62cc374653a0ea0fb77f9457e0f53481
--- /dev/null
+++ b/llm/tokenizer_config.json
@@ -0,0 +1,43 @@
+{
+ "add_bos_token": true,
+ "add_eos_token": false,
+ "add_prefix_space": true,
+ "added_tokens_decoder": {
+ "0": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "1": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
+ "2": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ }
+ },
+ "bos_token": "",
+ "clean_up_tokenization_spaces": false,
+ "eos_token": "",
+ "legacy": false,
+ "model_max_length": 4096,
+ "pad_token": "",
+ "padding_side": "right",
+ "sp_model_kwargs": {},
+ "spaces_between_special_tokens": false,
+ "tokenizer_class": "LlamaTokenizer",
+ "unk_token": "",
+ "use_default_system_prompt": false
+}
diff --git a/mm_projector/config.json b/mm_projector/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6e9f215d95de28f15f2da1944cc55b182b6a1245
--- /dev/null
+++ b/mm_projector/config.json
@@ -0,0 +1,10 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/mm_projector",
+ "architectures": [
+ "MultimodalProjector"
+ ],
+ "mm_projector_type": "mlp_downsample",
+ "model_type": "v2l_projector",
+ "torch_dtype": "bfloat16",
+ "transformers_version": "4.36.2"
+}
diff --git a/mm_projector/model.safetensors b/mm_projector/model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..541e3a678ce410e1d69a7a15f9f3a3373593b476
--- /dev/null
+++ b/mm_projector/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f5fddbf1c11889bed72ebb19ba6ba0330a1394730b705dedb127118d77a84d2e
+size 36729360
diff --git a/terminal.log b/terminal.log
new file mode 100644
index 0000000000000000000000000000000000000000..5e993eec273768277b123c8c33b011dfea325289
--- /dev/null
+++ b/terminal.log
@@ -0,0 +1,16200 @@
+srun: job 8825117 queued and waiting for resources
+srun: job 8825117 has been allocated resources
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+MASTER_ADDR=batch-block1-0014
+JobID: 8825117 | Full list: batch-block1-0014
+NETWORK=Efficient-Large-Model/VILA1.5-3b
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
+*****************************************
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:18,324] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [INFO] [comm.py:625:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 08:33:20,106] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 08:33:20,106] [INFO] [comm.py:594:init_distributed] cdb=None
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/huggingface_hub/file_download.py:795: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
+ warnings.warn(
+
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 4314.87it/s]
+
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 8137.77it/s]
+
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 13155.57it/s]
+
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 9787.67it/s]
+
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 7102.62it/s]
+
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 9024.58it/s]
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 11346.78it/s]
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+
Fetching 17 files: 0%| | 0/17 [00:00, ?it/s]
Fetching 17 files: 100%|██████████| 17/17 [00:00<00:00, 27424.30it/s]
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+[2025-06-10 08:33:28,967] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 2.70B parameters
+
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.01s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.01s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.02s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.09s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.09s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.10s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.11s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 1.81s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.14s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 1.81s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.14s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 1.81s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.14s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 1.85s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.19s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 1.85s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.19s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 1.85s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.19s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 1.85s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.19s/it]
+
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.77s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.70s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.16s/it]
+[2025-06-10 08:33:35,574] [WARNING] [partition_parameters.py:836:_post_init_method] param `probe` in SiglipMultiheadAttentionPoolingHead not on GPU so was not broadcasted from rank 0
+[2025-06-10 08:33:35,576] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.13B parameters
+[2025-06-10 08:33:36,786] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.15B parameters
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[dist-0-of-8] LlavaLlamaModel(
+ (llm): LlamaForCausalLM(
+ (model): LlamaModel(
+ (embed_tokens): Embedding(32000, 2560, padding_idx=0)
+ (layers): ModuleList(
+ (0-31): 32 x LlamaDecoderLayer(
+ (self_attn): LlamaFlashAttention2(
+ (q_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (k_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (v_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (o_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (rotary_emb): LlamaRotaryEmbedding()
+ )
+ (mlp): LlamaMLP(
+ (gate_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (up_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (down_proj): Linear(in_features=6912, out_features=2560, bias=False)
+ (act_fn): SiLU()
+ )
+ (input_layernorm): LlamaRMSNorm()
+ (post_attention_layernorm): LlamaRMSNorm()
+ )
+ )
+ (norm): LlamaRMSNorm()
+ )
+ (lm_head): Linear(in_features=2560, out_features=32000, bias=False)
+ )
+ (vision_tower): SiglipVisionTower(
+ (vision_tower): SiglipVisionModel(
+ (vision_model): SiglipVisionTransformer(
+ (embeddings): SiglipVisionEmbeddings(
+ (patch_embedding): Conv2d(3, 1152, kernel_size=(14, 14), stride=(14, 14), padding=valid)
+ (position_embedding): Embedding(729, 1152)
+ )
+ (encoder): SiglipEncoder(
+ (layers): ModuleList(
+ (0-26): 27 x SiglipEncoderLayer(
+ (self_attn): SiglipAttention(
+ (k_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (v_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (q_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (out_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layer_norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ (layer_norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ )
+ )
+ )
+ (post_layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (head): SiglipMultiheadAttentionPoolingHead(
+ (attention): MultiheadAttention(
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ )
+ )
+ )
+ )
+ (mm_projector): MultimodalProjector(
+ (layers): Sequential(
+ (0): DownSampleBlock()
+ (1): LayerNorm((4608,), eps=1e-05, elementwise_affine=True)
+ (2): Linear(in_features=4608, out_features=2560, bias=True)
+ (3): GELU(approximate='none')
+ (4): Linear(in_features=2560, out_features=2560, bias=True)
+ )
+ )
+)
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[dist-0-of-8] Tunable parameters:
+language model True
+[dist-0-of-8] vision tower True
+[dist-0-of-8] mm projector True
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8356547355651855
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8345866203308105
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8336405754089355
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8364787101745605
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8079085350036621
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8347392082214355
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8311381340026855
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8325419425964355
+Parameter Offload: Total persistent parameters: 593856 in 349 params
+wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.18.7
+wandb: Run data is saved locally in /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/wandb/run-20250610_083432-ihoq7kdn
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run vila_3b_path_mask
+wandb: ⭐️ View project at https://wandb.ai/memmelma/VILA
+wandb: 🚀 View run at https://wandb.ai/memmelma/VILA/runs/ihoq7kdn
+
0%| | 0/11952 [00:00, ?it/s]Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+
0%| | 1/11952 [00:24<82:40:59, 24.91s/it]
{'loss': 0.8031, 'learning_rate': 5.571030640668524e-08, 'epoch': 0.0}
+
0%| | 1/11952 [00:24<82:40:59, 24.91s/it]
0%| | 2/11952 [00:30<45:18:19, 13.65s/it]
{'loss': 0.8071, 'learning_rate': 1.1142061281337048e-07, 'epoch': 0.0}
+
0%| | 2/11952 [00:30<45:18:19, 13.65s/it]
0%| | 3/11952 [00:36<33:25:20, 10.07s/it]
{'loss': 0.7913, 'learning_rate': 1.6713091922005573e-07, 'epoch': 0.0}
+
0%| | 3/11952 [00:36<33:25:20, 10.07s/it]
0%| | 4/11952 [00:42<28:21:44, 8.55s/it]
{'loss': 0.8033, 'learning_rate': 2.2284122562674096e-07, 'epoch': 0.0}
+
0%| | 4/11952 [00:42<28:21:44, 8.55s/it]
0%| | 5/11952 [00:48<24:48:05, 7.47s/it]
{'loss': 0.805, 'learning_rate': 2.785515320334262e-07, 'epoch': 0.0}
+
0%| | 5/11952 [00:48<24:48:05, 7.47s/it]
0%| | 6/11952 [00:54<22:57:42, 6.92s/it]
{'loss': 0.8159, 'learning_rate': 3.3426183844011146e-07, 'epoch': 0.0}
+
0%| | 6/11952 [00:54<22:57:42, 6.92s/it]
0%| | 7/11952 [00:59<21:47:08, 6.57s/it]
{'loss': 0.8095, 'learning_rate': 3.899721448467967e-07, 'epoch': 0.0}
+
0%| | 7/11952 [00:59<21:47:08, 6.57s/it]
0%| | 8/11952 [01:05<21:01:27, 6.34s/it]
{'loss': 0.7973, 'learning_rate': 4.456824512534819e-07, 'epoch': 0.0}
+
0%| | 8/11952 [01:05<21:01:27, 6.34s/it]
0%| | 9/11952 [01:11<20:39:24, 6.23s/it]
{'loss': 0.7913, 'learning_rate': 5.013927576601672e-07, 'epoch': 0.0}
+
0%| | 9/11952 [01:11<20:39:24, 6.23s/it]
0%| | 10/11952 [01:17<20:05:57, 6.06s/it]
{'loss': 0.8118, 'learning_rate': 5.571030640668524e-07, 'epoch': 0.0}
+
0%| | 10/11952 [01:17<20:05:57, 6.06s/it]
0%| | 11/11952 [01:23<20:23:11, 6.15s/it]
{'loss': 0.7926, 'learning_rate': 6.128133704735377e-07, 'epoch': 0.0}
+
0%| | 11/11952 [01:23<20:23:11, 6.15s/it]
0%| | 12/11952 [01:29<20:02:32, 6.04s/it]
{'loss': 0.7805, 'learning_rate': 6.685236768802229e-07, 'epoch': 0.0}
+
0%| | 12/11952 [01:29<20:02:32, 6.04s/it]
0%| | 13/11952 [01:35<19:39:57, 5.93s/it]
{'loss': 0.7913, 'learning_rate': 7.242339832869082e-07, 'epoch': 0.0}
+
0%| | 13/11952 [01:35<19:39:57, 5.93s/it]
0%| | 14/11952 [01:40<19:25:24, 5.86s/it]
{'loss': 0.7994, 'learning_rate': 7.799442896935934e-07, 'epoch': 0.0}
+
0%| | 14/11952 [01:40<19:25:24, 5.86s/it]
0%| | 15/11952 [01:46<19:30:28, 5.88s/it]
{'loss': 0.7979, 'learning_rate': 8.356545961002786e-07, 'epoch': 0.0}
+
0%| | 15/11952 [01:46<19:30:28, 5.88s/it]
0%| | 16/11952 [01:52<19:19:21, 5.83s/it]
{'loss': 0.7736, 'learning_rate': 8.913649025069638e-07, 'epoch': 0.0}
+
0%| | 16/11952 [01:52<19:19:21, 5.83s/it]
0%| | 17/11952 [01:58<19:11:51, 5.79s/it]
{'loss': 0.7817, 'learning_rate': 9.470752089136491e-07, 'epoch': 0.0}
+
0%| | 17/11952 [01:58<19:11:51, 5.79s/it]
0%| | 18/11952 [02:04<19:24:55, 5.86s/it]
{'loss': 0.7678, 'learning_rate': 1.0027855153203343e-06, 'epoch': 0.0}
+
0%| | 18/11952 [02:04<19:24:55, 5.86s/it]
0%| | 19/11952 [02:10<19:33:12, 5.90s/it]
{'loss': 0.7265, 'learning_rate': 1.0584958217270195e-06, 'epoch': 0.0}
+
0%| | 19/11952 [02:10<19:33:12, 5.90s/it]
0%| | 20/11952 [02:15<19:15:25, 5.81s/it]
{'loss': 0.7331, 'learning_rate': 1.1142061281337048e-06, 'epoch': 0.0}
+
0%| | 20/11952 [02:15<19:15:25, 5.81s/it]
0%| | 21/11952 [02:21<19:13:30, 5.80s/it]
{'loss': 0.7349, 'learning_rate': 1.16991643454039e-06, 'epoch': 0.0}
+
0%| | 21/11952 [02:21<19:13:30, 5.80s/it]
0%| | 22/11952 [02:27<19:20:45, 5.84s/it]
{'loss': 0.7219, 'learning_rate': 1.2256267409470754e-06, 'epoch': 0.0}
+
0%| | 22/11952 [02:27<19:20:45, 5.84s/it]
0%| | 23/11952 [02:33<19:13:53, 5.80s/it]
{'loss': 0.7335, 'learning_rate': 1.2813370473537607e-06, 'epoch': 0.0}
+
0%| | 23/11952 [02:33<19:13:53, 5.80s/it]
0%| | 24/11952 [02:39<19:11:42, 5.79s/it]
{'loss': 0.7127, 'learning_rate': 1.3370473537604459e-06, 'epoch': 0.0}
+
0%| | 24/11952 [02:39<19:11:42, 5.79s/it]
0%| | 25/11952 [02:44<18:57:33, 5.72s/it]
{'loss': 0.7235, 'learning_rate': 1.392757660167131e-06, 'epoch': 0.0}
+
0%| | 25/11952 [02:44<18:57:33, 5.72s/it]
0%| | 26/11952 [02:50<19:03:10, 5.75s/it]
{'loss': 0.6903, 'learning_rate': 1.4484679665738164e-06, 'epoch': 0.0}
+
0%| | 26/11952 [02:50<19:03:10, 5.75s/it]
0%| | 27/11952 [02:56<19:18:44, 5.83s/it]
{'loss': 0.6748, 'learning_rate': 1.5041782729805015e-06, 'epoch': 0.0}
+
0%| | 27/11952 [02:56<19:18:44, 5.83s/it]
0%| | 28/11952 [03:02<19:16:48, 5.82s/it]
{'loss': 0.6899, 'learning_rate': 1.5598885793871869e-06, 'epoch': 0.0}
+
0%| | 28/11952 [03:02<19:16:48, 5.82s/it]
0%| | 29/11952 [03:08<19:14:02, 5.81s/it]
{'loss': 0.6611, 'learning_rate': 1.615598885793872e-06, 'epoch': 0.0}
+
0%| | 29/11952 [03:08<19:14:02, 5.81s/it]
0%| | 30/11952 [03:13<19:17:03, 5.82s/it]
{'loss': 0.6656, 'learning_rate': 1.6713091922005572e-06, 'epoch': 0.0}
+
0%| | 30/11952 [03:13<19:17:03, 5.82s/it]
0%| | 31/11952 [03:19<19:22:40, 5.85s/it]
{'loss': 0.6954, 'learning_rate': 1.7270194986072425e-06, 'epoch': 0.0}
+
0%| | 31/11952 [03:19<19:22:40, 5.85s/it]
0%| | 32/11952 [03:25<19:12:26, 5.80s/it]
{'loss': 0.683, 'learning_rate': 1.7827298050139277e-06, 'epoch': 0.0}
+
0%| | 32/11952 [03:25<19:12:26, 5.80s/it]
0%| | 33/11952 [03:31<19:07:06, 5.77s/it]
{'loss': 0.6812, 'learning_rate': 1.838440111420613e-06, 'epoch': 0.0}
+
0%| | 33/11952 [03:31<19:07:06, 5.77s/it]
0%| | 34/11952 [03:37<19:08:59, 5.78s/it]
{'loss': 0.6796, 'learning_rate': 1.8941504178272982e-06, 'epoch': 0.0}
+
0%| | 34/11952 [03:37<19:08:59, 5.78s/it]
0%| | 35/11952 [03:42<19:00:57, 5.74s/it]
{'loss': 0.6593, 'learning_rate': 1.9498607242339835e-06, 'epoch': 0.0}
+
0%| | 35/11952 [03:42<19:00:57, 5.74s/it]
0%| | 36/11952 [03:48<19:02:19, 5.75s/it]
{'loss': 0.6622, 'learning_rate': 2.0055710306406687e-06, 'epoch': 0.0}
+
0%| | 36/11952 [03:48<19:02:19, 5.75s/it]
0%| | 37/11952 [03:54<19:09:19, 5.79s/it]
{'loss': 0.6774, 'learning_rate': 2.061281337047354e-06, 'epoch': 0.0}
+
0%| | 37/11952 [03:54<19:09:19, 5.79s/it]
0%| | 38/11952 [04:00<19:29:23, 5.89s/it]
{'loss': 0.6606, 'learning_rate': 2.116991643454039e-06, 'epoch': 0.0}
+
0%| | 38/11952 [04:00<19:29:23, 5.89s/it]
0%| | 39/11952 [04:06<19:10:30, 5.79s/it]
{'loss': 0.658, 'learning_rate': 2.1727019498607245e-06, 'epoch': 0.0}
+
0%| | 39/11952 [04:06<19:10:30, 5.79s/it]
0%| | 40/11952 [04:12<19:20:07, 5.84s/it]
{'loss': 0.6551, 'learning_rate': 2.2284122562674097e-06, 'epoch': 0.0}
+
0%| | 40/11952 [04:12<19:20:07, 5.84s/it]
0%| | 41/11952 [04:17<19:17:10, 5.83s/it]
{'loss': 0.621, 'learning_rate': 2.284122562674095e-06, 'epoch': 0.0}
+
0%| | 41/11952 [04:17<19:17:10, 5.83s/it]
0%| | 42/11952 [04:23<19:14:22, 5.82s/it]
{'loss': 0.6396, 'learning_rate': 2.33983286908078e-06, 'epoch': 0.0}
+
0%| | 42/11952 [04:23<19:14:22, 5.82s/it]
0%| | 43/11952 [04:29<19:13:31, 5.81s/it]
{'loss': 0.6604, 'learning_rate': 2.395543175487465e-06, 'epoch': 0.0}
+
0%| | 43/11952 [04:29<19:13:31, 5.81s/it]
0%| | 44/11952 [04:35<19:00:28, 5.75s/it]
{'loss': 0.6269, 'learning_rate': 2.4512534818941507e-06, 'epoch': 0.0}
+
0%| | 44/11952 [04:35<19:00:28, 5.75s/it]
0%| | 45/11952 [04:40<19:08:02, 5.79s/it]
{'loss': 0.6314, 'learning_rate': 2.506963788300836e-06, 'epoch': 0.0}
+
0%| | 45/11952 [04:40<19:08:02, 5.79s/it]
0%| | 46/11952 [04:46<19:01:39, 5.75s/it]
{'loss': 0.623, 'learning_rate': 2.5626740947075214e-06, 'epoch': 0.0}
+
0%| | 46/11952 [04:46<19:01:39, 5.75s/it]
0%| | 47/11952 [04:52<19:02:49, 5.76s/it]
{'loss': 0.6306, 'learning_rate': 2.618384401114206e-06, 'epoch': 0.0}
+
0%| | 47/11952 [04:52<19:02:49, 5.76s/it]
0%| | 48/11952 [04:58<19:14:37, 5.82s/it]
{'loss': 0.6014, 'learning_rate': 2.6740947075208917e-06, 'epoch': 0.0}
+
0%| | 48/11952 [04:58<19:14:37, 5.82s/it]
0%| | 49/11952 [05:04<19:08:05, 5.79s/it]
{'loss': 0.6312, 'learning_rate': 2.729805013927577e-06, 'epoch': 0.0}
+
0%| | 49/11952 [05:04<19:08:05, 5.79s/it]7 AutoResumeHook: Checking whether to suspend...
+52 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+34 AutoResumeHook: Checking whether to suspend...
+ 1AutoResumeHook: Checking whether to suspend...6
+AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
0%| | 50/11952 [05:09<19:07:24, 5.78s/it]
{'loss': 0.617, 'learning_rate': 2.785515320334262e-06, 'epoch': 0.0}
+
0%| | 50/11952 [05:09<19:07:24, 5.78s/it]
0%| | 51/11952 [05:15<19:20:38, 5.85s/it]
{'loss': 0.6195, 'learning_rate': 2.841225626740947e-06, 'epoch': 0.0}
+
0%| | 51/11952 [05:15<19:20:38, 5.85s/it]
0%| | 52/11952 [05:21<19:12:10, 5.81s/it]
{'loss': 0.6213, 'learning_rate': 2.8969359331476327e-06, 'epoch': 0.0}
+
0%| | 52/11952 [05:21<19:12:10, 5.81s/it]
0%| | 53/11952 [05:27<19:04:01, 5.77s/it]
{'loss': 0.6236, 'learning_rate': 2.9526462395543174e-06, 'epoch': 0.0}
+
0%| | 53/11952 [05:27<19:04:01, 5.77s/it]
0%| | 54/11952 [05:33<19:07:51, 5.79s/it]
{'loss': 0.6158, 'learning_rate': 3.008356545961003e-06, 'epoch': 0.0}
+
0%| | 54/11952 [05:33<19:07:51, 5.79s/it]
0%| | 55/11952 [05:38<19:01:49, 5.76s/it]
{'loss': 0.5968, 'learning_rate': 3.064066852367688e-06, 'epoch': 0.0}
+
0%| | 55/11952 [05:38<19:01:49, 5.76s/it]
0%| | 56/11952 [05:44<18:55:40, 5.73s/it]
{'loss': 0.6257, 'learning_rate': 3.1197771587743737e-06, 'epoch': 0.0}
+
0%| | 56/11952 [05:44<18:55:40, 5.73s/it]
0%| | 57/11952 [05:50<19:02:08, 5.76s/it]
{'loss': 0.6096, 'learning_rate': 3.1754874651810585e-06, 'epoch': 0.0}
+
0%| | 57/11952 [05:50<19:02:08, 5.76s/it]
0%| | 58/11952 [05:56<19:07:20, 5.79s/it]
{'loss': 0.6253, 'learning_rate': 3.231197771587744e-06, 'epoch': 0.0}
+
0%| | 58/11952 [05:56<19:07:20, 5.79s/it]
0%| | 59/11952 [06:01<19:05:18, 5.78s/it]
{'loss': 0.6213, 'learning_rate': 3.286908077994429e-06, 'epoch': 0.0}
+
0%| | 59/11952 [06:01<19:05:18, 5.78s/it]
1%| | 60/11952 [06:07<19:11:12, 5.81s/it]
{'loss': 0.6041, 'learning_rate': 3.3426183844011143e-06, 'epoch': 0.01}
+
1%| | 60/11952 [06:07<19:11:12, 5.81s/it]
1%| | 61/11952 [06:13<19:09:31, 5.80s/it]
{'loss': 0.6098, 'learning_rate': 3.3983286908077995e-06, 'epoch': 0.01}
+
1%| | 61/11952 [06:13<19:09:31, 5.80s/it]
1%| | 62/11952 [06:19<19:20:01, 5.85s/it]
{'loss': 0.614, 'learning_rate': 3.454038997214485e-06, 'epoch': 0.01}
+
1%| | 62/11952 [06:19<19:20:01, 5.85s/it]
1%| | 63/11952 [06:25<19:10:34, 5.81s/it]
{'loss': 0.6163, 'learning_rate': 3.5097493036211698e-06, 'epoch': 0.01}
+
1%| | 63/11952 [06:25<19:10:34, 5.81s/it]
1%| | 64/11952 [06:30<19:04:36, 5.78s/it]
{'loss': 0.6006, 'learning_rate': 3.5654596100278553e-06, 'epoch': 0.01}
+
1%| | 64/11952 [06:30<19:04:36, 5.78s/it]
1%| | 65/11952 [06:36<19:00:55, 5.76s/it]
{'loss': 0.5992, 'learning_rate': 3.6211699164345405e-06, 'epoch': 0.01}
+
1%| | 65/11952 [06:36<19:00:55, 5.76s/it]
1%| | 66/11952 [06:42<19:05:40, 5.78s/it]
{'loss': 0.6079, 'learning_rate': 3.676880222841226e-06, 'epoch': 0.01}
+
1%| | 66/11952 [06:42<19:05:40, 5.78s/it]
1%| | 67/11952 [06:48<19:05:28, 5.78s/it]
{'loss': 0.607, 'learning_rate': 3.7325905292479116e-06, 'epoch': 0.01}
+
1%| | 67/11952 [06:48<19:05:28, 5.78s/it]
1%| | 68/11952 [06:53<19:00:30, 5.76s/it]
{'loss': 0.6128, 'learning_rate': 3.7883008356545963e-06, 'epoch': 0.01}
+
1%| | 68/11952 [06:53<19:00:30, 5.76s/it]
1%| | 69/11952 [06:59<19:03:02, 5.77s/it]
{'loss': 0.6046, 'learning_rate': 3.844011142061282e-06, 'epoch': 0.01}
+
1%| | 69/11952 [06:59<19:03:02, 5.77s/it]
1%| | 70/11952 [07:05<19:05:03, 5.78s/it]
{'loss': 0.5908, 'learning_rate': 3.899721448467967e-06, 'epoch': 0.01}
+
1%| | 70/11952 [07:05<19:05:03, 5.78s/it]
1%| | 71/11952 [07:11<19:15:51, 5.84s/it]
{'loss': 0.6016, 'learning_rate': 3.955431754874652e-06, 'epoch': 0.01}
+
1%| | 71/11952 [07:11<19:15:51, 5.84s/it]
1%| | 72/11952 [07:17<19:25:40, 5.89s/it]
{'loss': 0.615, 'learning_rate': 4.011142061281337e-06, 'epoch': 0.01}
+
1%| | 72/11952 [07:17<19:25:40, 5.89s/it]
1%| | 73/11952 [07:23<19:16:36, 5.84s/it]
{'loss': 0.6117, 'learning_rate': 4.0668523676880225e-06, 'epoch': 0.01}
+
1%| | 73/11952 [07:23<19:16:36, 5.84s/it]
1%| | 74/11952 [07:29<19:27:28, 5.90s/it]
{'loss': 0.5916, 'learning_rate': 4.122562674094708e-06, 'epoch': 0.01}
+
1%| | 74/11952 [07:29<19:27:28, 5.90s/it]
1%| | 75/11952 [07:35<19:23:49, 5.88s/it]
{'loss': 0.6005, 'learning_rate': 4.178272980501394e-06, 'epoch': 0.01}
+
1%| | 75/11952 [07:35<19:23:49, 5.88s/it]
1%| | 76/11952 [07:40<19:06:26, 5.79s/it]
{'loss': 0.5826, 'learning_rate': 4.233983286908078e-06, 'epoch': 0.01}
+
1%| | 76/11952 [07:40<19:06:26, 5.79s/it]
1%| | 77/11952 [07:46<19:01:25, 5.77s/it]
{'loss': 0.6087, 'learning_rate': 4.289693593314764e-06, 'epoch': 0.01}
+
1%| | 77/11952 [07:46<19:01:25, 5.77s/it]
1%| | 78/11952 [07:52<19:12:18, 5.82s/it]
{'loss': 0.5953, 'learning_rate': 4.345403899721449e-06, 'epoch': 0.01}
+
1%| | 78/11952 [07:52<19:12:18, 5.82s/it]
1%| | 79/11952 [07:58<19:15:58, 5.84s/it]
{'loss': 0.581, 'learning_rate': 4.401114206128134e-06, 'epoch': 0.01}
+
1%| | 79/11952 [07:58<19:15:58, 5.84s/it]
1%| | 80/11952 [08:03<19:10:43, 5.82s/it]
{'loss': 0.5961, 'learning_rate': 4.456824512534819e-06, 'epoch': 0.01}
+
1%| | 80/11952 [08:03<19:10:43, 5.82s/it]
1%| | 81/11952 [08:09<19:19:52, 5.86s/it]
{'loss': 0.5837, 'learning_rate': 4.5125348189415045e-06, 'epoch': 0.01}
+
1%| | 81/11952 [08:09<19:19:52, 5.86s/it]
1%| | 82/11952 [08:15<19:18:24, 5.86s/it]
{'loss': 0.5881, 'learning_rate': 4.56824512534819e-06, 'epoch': 0.01}
+
1%| | 82/11952 [08:15<19:18:24, 5.86s/it]
1%| | 83/11952 [08:21<19:07:03, 5.80s/it]
{'loss': 0.6076, 'learning_rate': 4.623955431754875e-06, 'epoch': 0.01}
+
1%| | 83/11952 [08:21<19:07:03, 5.80s/it]
1%| | 84/11952 [08:26<18:48:30, 5.71s/it]
{'loss': 0.5977, 'learning_rate': 4.67966573816156e-06, 'epoch': 0.01}
+
1%| | 84/11952 [08:26<18:48:30, 5.71s/it]
1%| | 85/11952 [08:32<19:09:06, 5.81s/it]
{'loss': 0.6113, 'learning_rate': 4.735376044568246e-06, 'epoch': 0.01}
+
1%| | 85/11952 [08:32<19:09:06, 5.81s/it]
1%| | 86/11952 [08:38<19:05:22, 5.79s/it]
{'loss': 0.5748, 'learning_rate': 4.79108635097493e-06, 'epoch': 0.01}
+
1%| | 86/11952 [08:38<19:05:22, 5.79s/it]
1%| | 87/11952 [08:44<18:59:33, 5.76s/it]
{'loss': 0.6021, 'learning_rate': 4.846796657381616e-06, 'epoch': 0.01}
+
1%| | 87/11952 [08:44<18:59:33, 5.76s/it]
1%| | 88/11952 [08:50<19:08:10, 5.81s/it]
{'loss': 0.5738, 'learning_rate': 4.902506963788301e-06, 'epoch': 0.01}
+
1%| | 88/11952 [08:50<19:08:10, 5.81s/it]
1%| | 89/11952 [08:56<19:04:36, 5.79s/it]
{'loss': 0.5804, 'learning_rate': 4.9582172701949865e-06, 'epoch': 0.01}
+
1%| | 89/11952 [08:56<19:04:36, 5.79s/it]
1%| | 90/11952 [09:02<19:18:53, 5.86s/it]
{'loss': 0.5796, 'learning_rate': 5.013927576601672e-06, 'epoch': 0.01}
+
1%| | 90/11952 [09:02<19:18:53, 5.86s/it]
1%| | 91/11952 [09:08<19:33:42, 5.94s/it]
{'loss': 0.591, 'learning_rate': 5.069637883008357e-06, 'epoch': 0.01}
+
1%| | 91/11952 [09:08<19:33:42, 5.94s/it]
1%| | 92/11952 [09:13<19:23:07, 5.88s/it]
{'loss': 0.5811, 'learning_rate': 5.125348189415043e-06, 'epoch': 0.01}
+
1%| | 92/11952 [09:13<19:23:07, 5.88s/it]
1%| | 93/11952 [09:19<19:19:59, 5.87s/it]
{'loss': 0.5667, 'learning_rate': 5.181058495821727e-06, 'epoch': 0.01}
+
1%| | 93/11952 [09:19<19:19:59, 5.87s/it]
1%| | 94/11952 [09:25<19:28:59, 5.91s/it]
{'loss': 0.6095, 'learning_rate': 5.236768802228412e-06, 'epoch': 0.01}
+
1%| | 94/11952 [09:25<19:28:59, 5.91s/it]
1%| | 95/11952 [09:31<19:21:49, 5.88s/it]
{'loss': 0.5935, 'learning_rate': 5.292479108635098e-06, 'epoch': 0.01}
+
1%| | 95/11952 [09:31<19:21:49, 5.88s/it]
1%| | 96/11952 [09:37<19:16:06, 5.85s/it]
{'loss': 0.57, 'learning_rate': 5.3481894150417834e-06, 'epoch': 0.01}
+
1%| | 96/11952 [09:37<19:16:06, 5.85s/it]
1%| | 97/11952 [09:42<18:59:04, 5.77s/it]
{'loss': 0.5865, 'learning_rate': 5.403899721448468e-06, 'epoch': 0.01}
+
1%| | 97/11952 [09:42<18:59:04, 5.77s/it]
1%| | 98/11952 [09:48<18:49:54, 5.72s/it]
{'loss': 0.6119, 'learning_rate': 5.459610027855154e-06, 'epoch': 0.01}
+
1%| | 98/11952 [09:48<18:49:54, 5.72s/it]
1%| | 99/11952 [09:54<19:22:15, 5.88s/it]
{'loss': 0.6189, 'learning_rate': 5.515320334261839e-06, 'epoch': 0.01}
+
1%| | 99/11952 [09:54<19:22:15, 5.88s/it]7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
1%| | 100/11952 [10:00<19:29:08, 5.92s/it]
{'loss': 0.6001, 'learning_rate': 5.571030640668524e-06, 'epoch': 0.01}
+
1%| | 100/11952 [10:00<19:29:08, 5.92s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
1%| | 101/11952 [10:28<40:54:13, 12.43s/it]
{'loss': 0.5787, 'learning_rate': 5.62674094707521e-06, 'epoch': 0.01}
+
1%| | 101/11952 [10:28<40:54:13, 12.43s/it]
1%| | 102/11952 [10:34<34:18:31, 10.42s/it]
{'loss': 0.5809, 'learning_rate': 5.682451253481894e-06, 'epoch': 0.01}
+
1%| | 102/11952 [10:34<34:18:31, 10.42s/it]
1%| | 103/11952 [10:39<29:32:44, 8.98s/it]
{'loss': 0.5708, 'learning_rate': 5.7381615598885795e-06, 'epoch': 0.01}
+
1%| | 103/11952 [10:39<29:32:44, 8.98s/it]
1%| | 104/11952 [10:46<26:58:29, 8.20s/it]
{'loss': 0.6033, 'learning_rate': 5.7938718662952654e-06, 'epoch': 0.01}
+
1%| | 104/11952 [10:46<26:58:29, 8.20s/it]
1%| | 105/11952 [10:52<24:56:55, 7.58s/it]
{'loss': 0.5802, 'learning_rate': 5.849582172701951e-06, 'epoch': 0.01}
+
1%| | 105/11952 [10:52<24:56:55, 7.58s/it]
1%| | 106/11952 [10:58<23:07:33, 7.03s/it]
{'loss': 0.587, 'learning_rate': 5.905292479108635e-06, 'epoch': 0.01}
+
1%| | 106/11952 [10:58<23:07:33, 7.03s/it]
1%| | 107/11952 [11:04<22:19:19, 6.78s/it]
{'loss': 0.5665, 'learning_rate': 5.961002785515321e-06, 'epoch': 0.01}
+
1%| | 107/11952 [11:04<22:19:19, 6.78s/it]
1%| | 108/11952 [11:10<21:22:24, 6.50s/it]
{'loss': 0.5883, 'learning_rate': 6.016713091922006e-06, 'epoch': 0.01}
+
1%| | 108/11952 [11:10<21:22:24, 6.50s/it]
1%| | 109/11952 [11:15<20:29:20, 6.23s/it]
{'loss': 0.5707, 'learning_rate': 6.072423398328692e-06, 'epoch': 0.01}
+
1%| | 109/11952 [11:15<20:29:20, 6.23s/it]
1%| | 110/11952 [11:21<19:58:05, 6.07s/it]
{'loss': 0.5862, 'learning_rate': 6.128133704735376e-06, 'epoch': 0.01}
+
1%| | 110/11952 [11:21<19:58:05, 6.07s/it]
1%| | 111/11952 [11:27<19:55:42, 6.06s/it]
{'loss': 0.5918, 'learning_rate': 6.1838440111420615e-06, 'epoch': 0.01}
+
1%| | 111/11952 [11:27<19:55:42, 6.06s/it]
1%| | 112/11952 [11:33<19:34:35, 5.95s/it]
{'loss': 0.564, 'learning_rate': 6.2395543175487475e-06, 'epoch': 0.01}
+
1%| | 112/11952 [11:33<19:34:35, 5.95s/it]
1%| | 113/11952 [11:38<19:12:08, 5.84s/it]
{'loss': 0.571, 'learning_rate': 6.295264623955433e-06, 'epoch': 0.01}
+
1%| | 113/11952 [11:38<19:12:08, 5.84s/it]
1%| | 114/11952 [11:44<19:19:51, 5.88s/it]
{'loss': 0.5589, 'learning_rate': 6.350974930362117e-06, 'epoch': 0.01}
+
1%| | 114/11952 [11:44<19:19:51, 5.88s/it]
1%| | 115/11952 [11:50<19:21:20, 5.89s/it]
{'loss': 0.5875, 'learning_rate': 6.406685236768803e-06, 'epoch': 0.01}
+
1%| | 115/11952 [11:50<19:21:20, 5.89s/it]
1%| | 116/11952 [11:56<19:25:07, 5.91s/it]
{'loss': 0.5771, 'learning_rate': 6.462395543175488e-06, 'epoch': 0.01}
+
1%| | 116/11952 [11:56<19:25:07, 5.91s/it]
1%| | 117/11952 [12:02<19:13:54, 5.85s/it]
{'loss': 0.5563, 'learning_rate': 6.518105849582173e-06, 'epoch': 0.01}
+
1%| | 117/11952 [12:02<19:13:54, 5.85s/it]
1%| | 118/11952 [12:07<19:02:12, 5.79s/it]
{'loss': 0.5947, 'learning_rate': 6.573816155988858e-06, 'epoch': 0.01}
+
1%| | 118/11952 [12:07<19:02:12, 5.79s/it]
1%| | 119/11952 [12:13<19:08:55, 5.83s/it]
{'loss': 0.5625, 'learning_rate': 6.6295264623955435e-06, 'epoch': 0.01}
+
1%| | 119/11952 [12:13<19:08:55, 5.83s/it]
1%| | 120/11952 [12:19<19:17:21, 5.87s/it]
{'loss': 0.5658, 'learning_rate': 6.685236768802229e-06, 'epoch': 0.01}
+
1%| | 120/11952 [12:19<19:17:21, 5.87s/it]
1%| | 121/11952 [12:25<19:21:09, 5.89s/it]
{'loss': 0.5672, 'learning_rate': 6.740947075208915e-06, 'epoch': 0.01}
+
1%| | 121/11952 [12:25<19:21:09, 5.89s/it]
1%| | 122/11952 [12:31<19:22:01, 5.89s/it]
{'loss': 0.5932, 'learning_rate': 6.796657381615599e-06, 'epoch': 0.01}
+
1%| | 122/11952 [12:31<19:22:01, 5.89s/it]
1%| | 123/11952 [12:37<19:16:10, 5.86s/it]
{'loss': 0.5779, 'learning_rate': 6.852367688022284e-06, 'epoch': 0.01}
+
1%| | 123/11952 [12:37<19:16:10, 5.86s/it]
1%| | 124/11952 [12:43<19:00:54, 5.79s/it]
{'loss': 0.5683, 'learning_rate': 6.90807799442897e-06, 'epoch': 0.01}
+
1%| | 124/11952 [12:43<19:00:54, 5.79s/it]
1%| | 125/11952 [12:48<19:08:29, 5.83s/it]
{'loss': 0.565, 'learning_rate': 6.963788300835655e-06, 'epoch': 0.01}
+
1%| | 125/11952 [12:48<19:08:29, 5.83s/it]
1%| | 126/11952 [12:54<19:08:26, 5.83s/it]
{'loss': 0.5455, 'learning_rate': 7.0194986072423395e-06, 'epoch': 0.01}
+
1%| | 126/11952 [12:54<19:08:26, 5.83s/it]
1%| | 127/11952 [13:00<18:53:06, 5.75s/it]
{'loss': 0.5816, 'learning_rate': 7.0752089136490255e-06, 'epoch': 0.01}
+
1%| | 127/11952 [13:00<18:53:06, 5.75s/it]
1%| | 128/11952 [13:06<18:52:15, 5.75s/it]
{'loss': 0.5675, 'learning_rate': 7.130919220055711e-06, 'epoch': 0.01}
+
1%| | 128/11952 [13:06<18:52:15, 5.75s/it]
1%| | 129/11952 [13:12<19:08:54, 5.83s/it]
{'loss': 0.575, 'learning_rate': 7.186629526462397e-06, 'epoch': 0.01}
+
1%| | 129/11952 [13:12<19:08:54, 5.83s/it]
1%| | 130/11952 [13:17<19:03:56, 5.81s/it]
{'loss': 0.5656, 'learning_rate': 7.242339832869081e-06, 'epoch': 0.01}
+
1%| | 130/11952 [13:17<19:03:56, 5.81s/it]
1%| | 131/11952 [13:23<18:50:53, 5.74s/it]
{'loss': 0.5686, 'learning_rate': 7.298050139275766e-06, 'epoch': 0.01}
+
1%| | 131/11952 [13:23<18:50:53, 5.74s/it]
1%| | 132/11952 [13:29<19:18:21, 5.88s/it]
{'loss': 0.5917, 'learning_rate': 7.353760445682452e-06, 'epoch': 0.01}
+
1%| | 132/11952 [13:29<19:18:21, 5.88s/it]
1%| | 133/11952 [13:35<19:35:03, 5.97s/it]
{'loss': 0.5935, 'learning_rate': 7.409470752089137e-06, 'epoch': 0.01}
+
1%| | 133/11952 [13:35<19:35:03, 5.97s/it]
1%| | 134/11952 [13:41<19:36:51, 5.97s/it]
{'loss': 0.5816, 'learning_rate': 7.465181058495823e-06, 'epoch': 0.01}
+
1%| | 134/11952 [13:41<19:36:51, 5.97s/it]
1%| | 135/11952 [13:47<19:33:47, 5.96s/it]
{'loss': 0.5658, 'learning_rate': 7.5208913649025075e-06, 'epoch': 0.01}
+
1%| | 135/11952 [13:47<19:33:47, 5.96s/it]
1%| | 136/11952 [13:54<19:52:42, 6.06s/it]
{'loss': 0.5707, 'learning_rate': 7.576601671309193e-06, 'epoch': 0.01}
+
1%| | 136/11952 [13:54<19:52:42, 6.06s/it]
1%| | 137/11952 [13:59<19:42:33, 6.01s/it]
{'loss': 0.5605, 'learning_rate': 7.632311977715879e-06, 'epoch': 0.01}
+
1%| | 137/11952 [13:59<19:42:33, 6.01s/it]
1%| | 138/11952 [14:05<19:40:00, 5.99s/it]
{'loss': 0.5882, 'learning_rate': 7.688022284122564e-06, 'epoch': 0.01}
+
1%| | 138/11952 [14:05<19:40:00, 5.99s/it]
1%| | 139/11952 [14:11<19:32:10, 5.95s/it]
{'loss': 0.5645, 'learning_rate': 7.743732590529249e-06, 'epoch': 0.01}
+
1%| | 139/11952 [14:11<19:32:10, 5.95s/it]
1%| | 140/11952 [14:17<19:17:11, 5.88s/it]
{'loss': 0.5875, 'learning_rate': 7.799442896935934e-06, 'epoch': 0.01}
+
1%| | 140/11952 [14:17<19:17:11, 5.88s/it]
1%| | 141/11952 [14:23<19:14:26, 5.86s/it]
{'loss': 0.5554, 'learning_rate': 7.85515320334262e-06, 'epoch': 0.01}
+
1%| | 141/11952 [14:23<19:14:26, 5.86s/it]
1%| | 142/11952 [14:29<19:10:57, 5.85s/it]
{'loss': 0.5579, 'learning_rate': 7.910863509749304e-06, 'epoch': 0.01}
+
1%| | 142/11952 [14:29<19:10:57, 5.85s/it]
1%| | 143/11952 [14:35<19:16:30, 5.88s/it]
{'loss': 0.5873, 'learning_rate': 7.96657381615599e-06, 'epoch': 0.01}
+
1%| | 143/11952 [14:35<19:16:30, 5.88s/it]
1%| | 144/11952 [14:40<19:08:31, 5.84s/it]
{'loss': 0.5785, 'learning_rate': 8.022284122562675e-06, 'epoch': 0.01}
+
1%| | 144/11952 [14:40<19:08:31, 5.84s/it]
1%| | 145/11952 [14:46<18:49:33, 5.74s/it]
{'loss': 0.5596, 'learning_rate': 8.07799442896936e-06, 'epoch': 0.01}
+
1%| | 145/11952 [14:46<18:49:33, 5.74s/it]
1%| | 146/11952 [14:51<18:47:00, 5.73s/it]
{'loss': 0.5765, 'learning_rate': 8.133704735376045e-06, 'epoch': 0.01}
+
1%| | 146/11952 [14:51<18:47:00, 5.73s/it]
1%| | 147/11952 [14:57<18:48:42, 5.74s/it]
{'loss': 0.5682, 'learning_rate': 8.18941504178273e-06, 'epoch': 0.01}
+
1%| | 147/11952 [14:57<18:48:42, 5.74s/it]
1%| | 148/11952 [15:03<18:45:51, 5.72s/it]
{'loss': 0.5593, 'learning_rate': 8.245125348189415e-06, 'epoch': 0.01}
+
1%| | 148/11952 [15:03<18:45:51, 5.72s/it]
1%| | 149/11952 [15:09<18:45:43, 5.72s/it]
{'loss': 0.5568, 'learning_rate': 8.3008356545961e-06, 'epoch': 0.01}
+
1%| | 149/11952 [15:09<18:45:43, 5.72s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
1%|▏ | 150/11952 [15:14<18:43:33, 5.71s/it]
{'loss': 0.5685, 'learning_rate': 8.356545961002787e-06, 'epoch': 0.01}
+
1%|▏ | 150/11952 [15:14<18:43:33, 5.71s/it]
1%|▏ | 151/11952 [15:21<19:13:31, 5.86s/it]
{'loss': 0.5681, 'learning_rate': 8.41225626740947e-06, 'epoch': 0.01}
+
1%|▏ | 151/11952 [15:21<19:13:31, 5.86s/it]
1%|▏ | 152/11952 [15:27<19:20:58, 5.90s/it]
{'loss': 0.5858, 'learning_rate': 8.467966573816156e-06, 'epoch': 0.01}
+
1%|▏ | 152/11952 [15:27<19:20:58, 5.90s/it]
1%|▏ | 153/11952 [15:32<19:12:28, 5.86s/it]
{'loss': 0.5611, 'learning_rate': 8.523676880222843e-06, 'epoch': 0.01}
+
1%|▏ | 153/11952 [15:32<19:12:28, 5.86s/it]
1%|▏ | 154/11952 [15:38<18:54:58, 5.77s/it]
{'loss': 0.5584, 'learning_rate': 8.579387186629528e-06, 'epoch': 0.01}
+
1%|▏ | 154/11952 [15:38<18:54:58, 5.77s/it]
1%|▏ | 155/11952 [15:44<18:47:43, 5.74s/it]
{'loss': 0.5517, 'learning_rate': 8.635097493036211e-06, 'epoch': 0.01}
+
1%|▏ | 155/11952 [15:44<18:47:43, 5.74s/it]
1%|▏ | 156/11952 [15:49<18:47:53, 5.74s/it]
{'loss': 0.56, 'learning_rate': 8.690807799442898e-06, 'epoch': 0.01}
+
1%|▏ | 156/11952 [15:49<18:47:53, 5.74s/it]
1%|▏ | 157/11952 [15:55<18:56:37, 5.78s/it]
{'loss': 0.5673, 'learning_rate': 8.746518105849583e-06, 'epoch': 0.01}
+
1%|▏ | 157/11952 [15:55<18:56:37, 5.78s/it]
1%|▏ | 158/11952 [16:01<18:53:43, 5.77s/it]
{'loss': 0.5571, 'learning_rate': 8.802228412256268e-06, 'epoch': 0.01}
+
1%|▏ | 158/11952 [16:01<18:53:43, 5.77s/it]
1%|▏ | 159/11952 [16:07<19:11:43, 5.86s/it]
{'loss': 0.5716, 'learning_rate': 8.857938718662954e-06, 'epoch': 0.01}
+
1%|▏ | 159/11952 [16:07<19:11:43, 5.86s/it]
1%|▏ | 160/11952 [16:13<19:09:59, 5.85s/it]
{'loss': 0.5634, 'learning_rate': 8.913649025069639e-06, 'epoch': 0.01}
+
1%|▏ | 160/11952 [16:13<19:09:59, 5.85s/it]
1%|▏ | 161/11952 [16:19<19:04:12, 5.82s/it]
{'loss': 0.5602, 'learning_rate': 8.969359331476324e-06, 'epoch': 0.01}
+
1%|▏ | 161/11952 [16:19<19:04:12, 5.82s/it]
1%|▏ | 162/11952 [16:24<18:56:13, 5.78s/it]
{'loss': 0.5444, 'learning_rate': 9.025069637883009e-06, 'epoch': 0.01}
+
1%|▏ | 162/11952 [16:24<18:56:13, 5.78s/it]
1%|▏ | 163/11952 [16:30<18:48:43, 5.74s/it]
{'loss': 0.5793, 'learning_rate': 9.080779944289694e-06, 'epoch': 0.01}
+
1%|▏ | 163/11952 [16:30<18:48:43, 5.74s/it]
1%|▏ | 164/11952 [16:36<18:58:36, 5.80s/it]
{'loss': 0.5443, 'learning_rate': 9.13649025069638e-06, 'epoch': 0.01}
+
1%|▏ | 164/11952 [16:36<18:58:36, 5.80s/it]
1%|▏ | 165/11952 [16:41<18:47:04, 5.74s/it]
{'loss': 0.5449, 'learning_rate': 9.192200557103064e-06, 'epoch': 0.01}
+
1%|▏ | 165/11952 [16:41<18:47:04, 5.74s/it]
1%|▏ | 166/11952 [16:47<18:44:22, 5.72s/it]
{'loss': 0.5599, 'learning_rate': 9.24791086350975e-06, 'epoch': 0.01}
+
1%|▏ | 166/11952 [16:47<18:44:22, 5.72s/it]
1%|▏ | 167/11952 [16:53<18:50:14, 5.75s/it]
{'loss': 0.5362, 'learning_rate': 9.303621169916436e-06, 'epoch': 0.01}
+
1%|▏ | 167/11952 [16:53<18:50:14, 5.75s/it]
1%|▏ | 168/11952 [16:59<18:46:56, 5.74s/it]
{'loss': 0.5649, 'learning_rate': 9.35933147632312e-06, 'epoch': 0.01}
+
1%|▏ | 168/11952 [16:59<18:46:56, 5.74s/it]
1%|▏ | 169/11952 [17:04<18:37:24, 5.69s/it]
{'loss': 0.5734, 'learning_rate': 9.415041782729805e-06, 'epoch': 0.01}
+
1%|▏ | 169/11952 [17:04<18:37:24, 5.69s/it]
1%|▏ | 170/11952 [17:10<18:45:39, 5.73s/it]
{'loss': 0.5595, 'learning_rate': 9.470752089136492e-06, 'epoch': 0.01}
+
1%|▏ | 170/11952 [17:10<18:45:39, 5.73s/it]
1%|▏ | 171/11952 [17:16<18:49:13, 5.75s/it]
{'loss': 0.5483, 'learning_rate': 9.526462395543177e-06, 'epoch': 0.01}
+
1%|▏ | 171/11952 [17:16<18:49:13, 5.75s/it]
1%|▏ | 172/11952 [17:21<18:36:42, 5.69s/it]
{'loss': 0.5569, 'learning_rate': 9.58217270194986e-06, 'epoch': 0.01}
+
1%|▏ | 172/11952 [17:21<18:36:42, 5.69s/it]
1%|▏ | 173/11952 [17:27<18:51:03, 5.76s/it]
{'loss': 0.5591, 'learning_rate': 9.637883008356547e-06, 'epoch': 0.01}
+
1%|▏ | 173/11952 [17:27<18:51:03, 5.76s/it]
1%|▏ | 174/11952 [17:33<18:56:12, 5.79s/it]
{'loss': 0.5639, 'learning_rate': 9.693593314763233e-06, 'epoch': 0.01}
+
1%|▏ | 174/11952 [17:33<18:56:12, 5.79s/it]
1%|▏ | 175/11952 [17:39<18:58:25, 5.80s/it]
{'loss': 0.5504, 'learning_rate': 9.749303621169918e-06, 'epoch': 0.01}
+
1%|▏ | 175/11952 [17:39<18:58:25, 5.80s/it]
1%|▏ | 176/11952 [17:45<18:54:54, 5.78s/it]
{'loss': 0.5627, 'learning_rate': 9.805013927576603e-06, 'epoch': 0.01}
+
1%|▏ | 176/11952 [17:45<18:54:54, 5.78s/it]
1%|▏ | 177/11952 [17:50<18:52:25, 5.77s/it]
{'loss': 0.5587, 'learning_rate': 9.860724233983288e-06, 'epoch': 0.01}
+
1%|▏ | 177/11952 [17:50<18:52:25, 5.77s/it]
1%|▏ | 178/11952 [17:56<18:58:30, 5.80s/it]
{'loss': 0.5603, 'learning_rate': 9.916434540389973e-06, 'epoch': 0.01}
+
1%|▏ | 178/11952 [17:56<18:58:30, 5.80s/it]
1%|▏ | 179/11952 [18:02<18:59:55, 5.81s/it]
{'loss': 0.5558, 'learning_rate': 9.972144846796658e-06, 'epoch': 0.01}
+
1%|▏ | 179/11952 [18:02<18:59:55, 5.81s/it]
2%|▏ | 180/11952 [18:08<18:54:12, 5.78s/it]
{'loss': 0.5519, 'learning_rate': 1.0027855153203343e-05, 'epoch': 0.02}
+
2%|▏ | 180/11952 [18:08<18:54:12, 5.78s/it]
2%|▏ | 181/11952 [18:14<19:02:46, 5.83s/it]
{'loss': 0.5488, 'learning_rate': 1.008356545961003e-05, 'epoch': 0.02}
+
2%|▏ | 181/11952 [18:14<19:02:46, 5.83s/it]
2%|▏ | 182/11952 [18:20<19:15:14, 5.89s/it]
{'loss': 0.5417, 'learning_rate': 1.0139275766016714e-05, 'epoch': 0.02}
+
2%|▏ | 182/11952 [18:20<19:15:14, 5.89s/it]
2%|▏ | 183/11952 [18:26<19:17:50, 5.90s/it]
{'loss': 0.5537, 'learning_rate': 1.0194986072423399e-05, 'epoch': 0.02}
+
2%|▏ | 183/11952 [18:26<19:17:50, 5.90s/it]
2%|▏ | 184/11952 [18:32<19:06:57, 5.85s/it]
{'loss': 0.5349, 'learning_rate': 1.0250696378830086e-05, 'epoch': 0.02}
+
2%|▏ | 184/11952 [18:32<19:06:57, 5.85s/it]
2%|▏ | 185/11952 [18:37<19:02:59, 5.83s/it]
{'loss': 0.5355, 'learning_rate': 1.0306406685236769e-05, 'epoch': 0.02}
+
2%|▏ | 185/11952 [18:37<19:02:59, 5.83s/it]
2%|▏ | 186/11952 [18:43<19:09:48, 5.86s/it]
{'loss': 0.5492, 'learning_rate': 1.0362116991643454e-05, 'epoch': 0.02}
+
2%|▏ | 186/11952 [18:43<19:09:48, 5.86s/it]
2%|▏ | 187/11952 [18:49<18:55:29, 5.79s/it]
{'loss': 0.5627, 'learning_rate': 1.0417827298050141e-05, 'epoch': 0.02}
+
2%|▏ | 187/11952 [18:49<18:55:29, 5.79s/it]
2%|▏ | 188/11952 [18:54<18:44:25, 5.73s/it]
{'loss': 0.5576, 'learning_rate': 1.0473537604456825e-05, 'epoch': 0.02}
+
2%|▏ | 188/11952 [18:54<18:44:25, 5.73s/it]
2%|▏ | 189/11952 [19:00<18:41:02, 5.72s/it]
{'loss': 0.5411, 'learning_rate': 1.0529247910863511e-05, 'epoch': 0.02}
+
2%|▏ | 189/11952 [19:00<18:41:02, 5.72s/it]
2%|▏ | 190/11952 [19:06<18:34:09, 5.68s/it]
{'loss': 0.5494, 'learning_rate': 1.0584958217270197e-05, 'epoch': 0.02}
+
2%|▏ | 190/11952 [19:06<18:34:09, 5.68s/it]
2%|▏ | 191/11952 [19:12<18:47:34, 5.75s/it]
{'loss': 0.5574, 'learning_rate': 1.064066852367688e-05, 'epoch': 0.02}
+
2%|▏ | 191/11952 [19:12<18:47:34, 5.75s/it]
2%|▏ | 192/11952 [19:18<19:01:02, 5.82s/it]
{'loss': 0.5522, 'learning_rate': 1.0696378830083567e-05, 'epoch': 0.02}
+
2%|▏ | 192/11952 [19:18<19:01:02, 5.82s/it]
2%|▏ | 193/11952 [19:23<19:01:31, 5.82s/it]
{'loss': 0.546, 'learning_rate': 1.0752089136490252e-05, 'epoch': 0.02}
+
2%|▏ | 193/11952 [19:23<19:01:31, 5.82s/it]
2%|▏ | 194/11952 [19:29<18:50:19, 5.77s/it]
{'loss': 0.5454, 'learning_rate': 1.0807799442896935e-05, 'epoch': 0.02}
+
2%|▏ | 194/11952 [19:29<18:50:19, 5.77s/it]
2%|▏ | 195/11952 [19:35<18:57:07, 5.80s/it]
{'loss': 0.5463, 'learning_rate': 1.0863509749303622e-05, 'epoch': 0.02}
+
2%|▏ | 195/11952 [19:35<18:57:07, 5.80s/it]
2%|▏ | 196/11952 [19:41<18:47:35, 5.75s/it]
{'loss': 0.5607, 'learning_rate': 1.0919220055710307e-05, 'epoch': 0.02}
+
2%|▏ | 196/11952 [19:41<18:47:35, 5.75s/it]
2%|▏ | 197/11952 [19:47<19:03:46, 5.84s/it]
{'loss': 0.5493, 'learning_rate': 1.0974930362116993e-05, 'epoch': 0.02}
+
2%|▏ | 197/11952 [19:47<19:03:46, 5.84s/it]
2%|▏ | 198/11952 [19:52<19:02:09, 5.83s/it]
{'loss': 0.5301, 'learning_rate': 1.1030640668523678e-05, 'epoch': 0.02}
+
2%|▏ | 198/11952 [19:52<19:02:09, 5.83s/it]
2%|▏ | 199/11952 [19:58<19:03:42, 5.84s/it]
{'loss': 0.5335, 'learning_rate': 1.1086350974930363e-05, 'epoch': 0.02}
+
2%|▏ | 199/11952 [19:58<19:03:42, 5.84s/it]5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+ 1 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
2%|▏ | 200/11952 [20:04<19:13:30, 5.89s/it]
{'loss': 0.5532, 'learning_rate': 1.1142061281337048e-05, 'epoch': 0.02}
+
2%|▏ | 200/11952 [20:04<19:13:30, 5.89s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
2%|▏ | 201/11952 [20:39<47:25:32, 14.53s/it]
{'loss': 0.5332, 'learning_rate': 1.1197771587743733e-05, 'epoch': 0.02}
+
2%|▏ | 201/11952 [20:39<47:25:32, 14.53s/it]
2%|▏ | 202/11952 [20:45<38:51:40, 11.91s/it]
{'loss': 0.5719, 'learning_rate': 1.125348189415042e-05, 'epoch': 0.02}
+
2%|▏ | 202/11952 [20:45<38:51:40, 11.91s/it]
2%|▏ | 203/11952 [20:51<32:57:18, 10.10s/it]
{'loss': 0.5222, 'learning_rate': 1.1309192200557103e-05, 'epoch': 0.02}
+
2%|▏ | 203/11952 [20:51<32:57:18, 10.10s/it]
2%|▏ | 204/11952 [20:57<28:52:04, 8.85s/it]
{'loss': 0.5481, 'learning_rate': 1.1364902506963789e-05, 'epoch': 0.02}
+
2%|▏ | 204/11952 [20:57<28:52:04, 8.85s/it]
2%|▏ | 205/11952 [21:02<25:41:00, 7.87s/it]
{'loss': 0.5465, 'learning_rate': 1.1420612813370475e-05, 'epoch': 0.02}
+
2%|▏ | 205/11952 [21:02<25:41:00, 7.87s/it]
2%|▏ | 206/11952 [21:08<23:54:05, 7.33s/it]
{'loss': 0.552, 'learning_rate': 1.1476323119777159e-05, 'epoch': 0.02}
+
2%|▏ | 206/11952 [21:08<23:54:05, 7.33s/it]
2%|▏ | 207/11952 [21:14<22:40:41, 6.95s/it]
{'loss': 0.5473, 'learning_rate': 1.1532033426183844e-05, 'epoch': 0.02}
+
2%|▏ | 207/11952 [21:14<22:40:41, 6.95s/it]
2%|▏ | 208/11952 [21:21<22:06:10, 6.78s/it]
{'loss': 0.5439, 'learning_rate': 1.1587743732590531e-05, 'epoch': 0.02}
+
2%|▏ | 208/11952 [21:21<22:06:10, 6.78s/it]
2%|▏ | 209/11952 [21:27<21:10:04, 6.49s/it]
{'loss': 0.5462, 'learning_rate': 1.1643454038997214e-05, 'epoch': 0.02}
+
2%|▏ | 209/11952 [21:27<21:10:04, 6.49s/it]
2%|▏ | 210/11952 [21:32<20:22:23, 6.25s/it]
{'loss': 0.5401, 'learning_rate': 1.1699164345403901e-05, 'epoch': 0.02}
+
2%|▏ | 210/11952 [21:32<20:22:23, 6.25s/it]
2%|▏ | 211/11952 [21:38<20:12:47, 6.20s/it]
{'loss': 0.5498, 'learning_rate': 1.1754874651810586e-05, 'epoch': 0.02}
+
2%|▏ | 211/11952 [21:38<20:12:47, 6.20s/it]
2%|▏ | 212/11952 [21:44<19:38:19, 6.02s/it]
{'loss': 0.5567, 'learning_rate': 1.181058495821727e-05, 'epoch': 0.02}
+
2%|▏ | 212/11952 [21:44<19:38:19, 6.02s/it]
2%|▏ | 213/11952 [21:50<19:38:54, 6.03s/it]
{'loss': 0.5436, 'learning_rate': 1.1866295264623957e-05, 'epoch': 0.02}
+
2%|▏ | 213/11952 [21:50<19:38:54, 6.03s/it]
2%|▏ | 214/11952 [21:56<19:23:52, 5.95s/it]
{'loss': 0.5484, 'learning_rate': 1.1922005571030642e-05, 'epoch': 0.02}
+
2%|▏ | 214/11952 [21:56<19:23:52, 5.95s/it]
2%|▏ | 215/11952 [22:01<19:07:41, 5.87s/it]
{'loss': 0.5411, 'learning_rate': 1.1977715877437325e-05, 'epoch': 0.02}
+
2%|▏ | 215/11952 [22:01<19:07:41, 5.87s/it]
2%|▏ | 216/11952 [22:07<19:20:26, 5.93s/it]
{'loss': 0.5581, 'learning_rate': 1.2033426183844012e-05, 'epoch': 0.02}
+
2%|▏ | 216/11952 [22:07<19:20:26, 5.93s/it]
2%|▏ | 217/11952 [22:13<19:10:56, 5.88s/it]
{'loss': 0.5441, 'learning_rate': 1.2089136490250697e-05, 'epoch': 0.02}
+
2%|▏ | 217/11952 [22:13<19:10:56, 5.88s/it]
2%|▏ | 218/11952 [22:19<19:07:51, 5.87s/it]
{'loss': 0.5574, 'learning_rate': 1.2144846796657384e-05, 'epoch': 0.02}
+
2%|▏ | 218/11952 [22:19<19:07:51, 5.87s/it]
2%|▏ | 219/11952 [22:25<19:04:15, 5.85s/it]
{'loss': 0.5588, 'learning_rate': 1.2200557103064068e-05, 'epoch': 0.02}
+
2%|▏ | 219/11952 [22:25<19:04:15, 5.85s/it]
2%|▏ | 220/11952 [22:31<19:21:25, 5.94s/it]
{'loss': 0.5554, 'learning_rate': 1.2256267409470753e-05, 'epoch': 0.02}
+
2%|▏ | 220/11952 [22:31<19:21:25, 5.94s/it]
2%|▏ | 221/11952 [22:37<18:59:23, 5.83s/it]
{'loss': 0.5342, 'learning_rate': 1.231197771587744e-05, 'epoch': 0.02}
+
2%|▏ | 221/11952 [22:37<18:59:23, 5.83s/it]
2%|▏ | 222/11952 [22:42<18:52:05, 5.79s/it]
{'loss': 0.568, 'learning_rate': 1.2367688022284123e-05, 'epoch': 0.02}
+
2%|▏ | 222/11952 [22:42<18:52:05, 5.79s/it]
2%|▏ | 223/11952 [22:48<18:45:50, 5.76s/it]
{'loss': 0.5387, 'learning_rate': 1.2423398328690808e-05, 'epoch': 0.02}
+
2%|▏ | 223/11952 [22:48<18:45:50, 5.76s/it]
2%|▏ | 224/11952 [22:54<18:41:32, 5.74s/it]
{'loss': 0.5469, 'learning_rate': 1.2479108635097495e-05, 'epoch': 0.02}
+
2%|▏ | 224/11952 [22:54<18:41:32, 5.74s/it]
2%|▏ | 225/11952 [22:59<18:33:12, 5.70s/it]
{'loss': 0.5312, 'learning_rate': 1.2534818941504178e-05, 'epoch': 0.02}
+
2%|▏ | 225/11952 [22:59<18:33:12, 5.70s/it]
2%|▏ | 226/11952 [23:05<18:26:32, 5.66s/it]
{'loss': 0.5462, 'learning_rate': 1.2590529247910865e-05, 'epoch': 0.02}
+
2%|▏ | 226/11952 [23:05<18:26:32, 5.66s/it]
2%|▏ | 227/11952 [23:11<18:35:51, 5.71s/it]
{'loss': 0.5595, 'learning_rate': 1.264623955431755e-05, 'epoch': 0.02}
+
2%|▏ | 227/11952 [23:11<18:35:51, 5.71s/it]
2%|▏ | 228/11952 [23:16<18:21:53, 5.64s/it]
{'loss': 0.5355, 'learning_rate': 1.2701949860724234e-05, 'epoch': 0.02}
+
2%|▏ | 228/11952 [23:16<18:21:53, 5.64s/it]
2%|▏ | 229/11952 [23:22<18:31:26, 5.69s/it]
{'loss': 0.548, 'learning_rate': 1.275766016713092e-05, 'epoch': 0.02}
+
2%|▏ | 229/11952 [23:22<18:31:26, 5.69s/it]
2%|▏ | 230/11952 [23:28<18:26:41, 5.66s/it]
{'loss': 0.547, 'learning_rate': 1.2813370473537606e-05, 'epoch': 0.02}
+
2%|▏ | 230/11952 [23:28<18:26:41, 5.66s/it]
2%|▏ | 231/11952 [23:33<18:32:03, 5.69s/it]
{'loss': 0.5309, 'learning_rate': 1.2869080779944293e-05, 'epoch': 0.02}
+
2%|▏ | 231/11952 [23:33<18:32:03, 5.69s/it]
2%|▏ | 232/11952 [23:39<18:36:00, 5.71s/it]
{'loss': 0.557, 'learning_rate': 1.2924791086350976e-05, 'epoch': 0.02}
+
2%|▏ | 232/11952 [23:39<18:36:00, 5.71s/it]
2%|▏ | 233/11952 [23:45<18:29:05, 5.68s/it]
{'loss': 0.5592, 'learning_rate': 1.2980501392757661e-05, 'epoch': 0.02}
+
2%|▏ | 233/11952 [23:45<18:29:05, 5.68s/it]
2%|▏ | 234/11952 [23:50<18:34:17, 5.71s/it]
{'loss': 0.5326, 'learning_rate': 1.3036211699164346e-05, 'epoch': 0.02}
+
2%|▏ | 234/11952 [23:50<18:34:17, 5.71s/it]
2%|▏ | 235/11952 [23:56<18:27:36, 5.67s/it]
{'loss': 0.5262, 'learning_rate': 1.3091922005571032e-05, 'epoch': 0.02}
+
2%|▏ | 235/11952 [23:56<18:27:36, 5.67s/it]
2%|▏ | 236/11952 [24:02<18:39:41, 5.73s/it]
{'loss': 0.5443, 'learning_rate': 1.3147632311977717e-05, 'epoch': 0.02}
+
2%|▏ | 236/11952 [24:02<18:39:41, 5.73s/it]
2%|▏ | 237/11952 [24:08<18:39:00, 5.73s/it]
{'loss': 0.541, 'learning_rate': 1.3203342618384402e-05, 'epoch': 0.02}
+
2%|▏ | 237/11952 [24:08<18:39:00, 5.73s/it]
2%|▏ | 238/11952 [24:14<18:53:59, 5.81s/it]
{'loss': 0.5411, 'learning_rate': 1.3259052924791087e-05, 'epoch': 0.02}
+
2%|▏ | 238/11952 [24:14<18:53:59, 5.81s/it]
2%|▏ | 239/11952 [24:20<19:08:51, 5.89s/it]
{'loss': 0.5406, 'learning_rate': 1.3314763231197774e-05, 'epoch': 0.02}
+
2%|▏ | 239/11952 [24:20<19:08:51, 5.89s/it]
2%|▏ | 240/11952 [24:25<18:56:24, 5.82s/it]
{'loss': 0.5488, 'learning_rate': 1.3370473537604457e-05, 'epoch': 0.02}
+
2%|▏ | 240/11952 [24:25<18:56:24, 5.82s/it]
2%|▏ | 241/11952 [24:31<18:53:33, 5.81s/it]
{'loss': 0.5626, 'learning_rate': 1.3426183844011142e-05, 'epoch': 0.02}
+
2%|▏ | 241/11952 [24:31<18:53:33, 5.81s/it]
2%|▏ | 242/11952 [24:37<19:07:07, 5.88s/it]
{'loss': 0.5479, 'learning_rate': 1.348189415041783e-05, 'epoch': 0.02}
+
2%|▏ | 242/11952 [24:37<19:07:07, 5.88s/it]
2%|▏ | 243/11952 [24:43<19:14:43, 5.92s/it]
{'loss': 0.5583, 'learning_rate': 1.3537604456824513e-05, 'epoch': 0.02}
+
2%|▏ | 243/11952 [24:43<19:14:43, 5.92s/it]
2%|▏ | 244/11952 [24:49<19:03:40, 5.86s/it]
{'loss': 0.5572, 'learning_rate': 1.3593314763231198e-05, 'epoch': 0.02}
+
2%|▏ | 244/11952 [24:49<19:03:40, 5.86s/it]
2%|▏ | 245/11952 [24:55<19:00:42, 5.85s/it]
{'loss': 0.5438, 'learning_rate': 1.3649025069637885e-05, 'epoch': 0.02}
+
2%|▏ | 245/11952 [24:55<19:00:42, 5.85s/it]
2%|▏ | 246/11952 [25:01<19:05:21, 5.87s/it]
{'loss': 0.5382, 'learning_rate': 1.3704735376044568e-05, 'epoch': 0.02}
+
2%|▏ | 246/11952 [25:01<19:05:21, 5.87s/it]
2%|▏ | 247/11952 [25:06<18:55:16, 5.82s/it]
{'loss': 0.5321, 'learning_rate': 1.3760445682451255e-05, 'epoch': 0.02}
+
2%|▏ | 247/11952 [25:06<18:55:16, 5.82s/it]
2%|▏ | 248/11952 [25:12<19:02:14, 5.86s/it]
{'loss': 0.5513, 'learning_rate': 1.381615598885794e-05, 'epoch': 0.02}
+
2%|▏ | 248/11952 [25:12<19:02:14, 5.86s/it]
2%|▏ | 249/11952 [25:18<18:54:41, 5.82s/it]
{'loss': 0.546, 'learning_rate': 1.3871866295264624e-05, 'epoch': 0.02}
+
2%|▏ | 249/11952 [25:18<18:54:41, 5.82s/it]5 AutoResumeHook: Checking whether to suspend...
+46 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
2%|▏ | 250/11952 [25:24<18:58:00, 5.83s/it]
{'loss': 0.5539, 'learning_rate': 1.392757660167131e-05, 'epoch': 0.02}
+
2%|▏ | 250/11952 [25:24<18:58:00, 5.83s/it]
2%|▏ | 251/11952 [25:30<18:55:20, 5.82s/it]
{'loss': 0.5551, 'learning_rate': 1.3983286908077996e-05, 'epoch': 0.02}
+
2%|▏ | 251/11952 [25:30<18:55:20, 5.82s/it]
2%|▏ | 252/11952 [25:35<18:46:28, 5.78s/it]
{'loss': 0.5484, 'learning_rate': 1.4038997214484679e-05, 'epoch': 0.02}
+
2%|▏ | 252/11952 [25:35<18:46:28, 5.78s/it]
2%|▏ | 253/11952 [25:41<18:57:05, 5.83s/it]
{'loss': 0.5445, 'learning_rate': 1.4094707520891366e-05, 'epoch': 0.02}
+
2%|▏ | 253/11952 [25:41<18:57:05, 5.83s/it]
2%|▏ | 254/11952 [25:47<18:44:08, 5.77s/it]
{'loss': 0.5497, 'learning_rate': 1.4150417827298051e-05, 'epoch': 0.02}
+
2%|▏ | 254/11952 [25:47<18:44:08, 5.77s/it]
2%|▏ | 255/11952 [25:53<18:51:02, 5.80s/it]
{'loss': 0.5279, 'learning_rate': 1.4206128133704738e-05, 'epoch': 0.02}
+
2%|▏ | 255/11952 [25:53<18:51:02, 5.80s/it]
2%|▏ | 256/11952 [25:59<18:51:02, 5.80s/it]
{'loss': 0.5312, 'learning_rate': 1.4261838440111421e-05, 'epoch': 0.02}
+
2%|▏ | 256/11952 [25:59<18:51:02, 5.80s/it]
2%|▏ | 257/11952 [26:04<18:44:14, 5.77s/it]
{'loss': 0.5578, 'learning_rate': 1.4317548746518106e-05, 'epoch': 0.02}
+
2%|▏ | 257/11952 [26:04<18:44:14, 5.77s/it]
2%|▏ | 258/11952 [26:10<18:39:45, 5.75s/it]
{'loss': 0.549, 'learning_rate': 1.4373259052924793e-05, 'epoch': 0.02}
+
2%|▏ | 258/11952 [26:10<18:39:45, 5.75s/it]
2%|▏ | 259/11952 [26:16<18:31:48, 5.71s/it]
{'loss': 0.5359, 'learning_rate': 1.4428969359331477e-05, 'epoch': 0.02}
+
2%|▏ | 259/11952 [26:16<18:31:48, 5.71s/it]
2%|▏ | 260/11952 [26:22<18:55:23, 5.83s/it]
{'loss': 0.5571, 'learning_rate': 1.4484679665738162e-05, 'epoch': 0.02}
+
2%|▏ | 260/11952 [26:22<18:55:23, 5.83s/it]
2%|▏ | 261/11952 [26:28<18:50:35, 5.80s/it]
{'loss': 0.5211, 'learning_rate': 1.4540389972144849e-05, 'epoch': 0.02}
+
2%|▏ | 261/11952 [26:28<18:50:35, 5.80s/it]
2%|▏ | 262/11952 [26:33<18:59:42, 5.85s/it]
{'loss': 0.5446, 'learning_rate': 1.4596100278551532e-05, 'epoch': 0.02}
+
2%|▏ | 262/11952 [26:33<18:59:42, 5.85s/it]
2%|▏ | 263/11952 [26:39<18:46:18, 5.78s/it]
{'loss': 0.533, 'learning_rate': 1.4651810584958219e-05, 'epoch': 0.02}
+
2%|▏ | 263/11952 [26:39<18:46:18, 5.78s/it]
2%|▏ | 264/11952 [26:45<18:38:11, 5.74s/it]
{'loss': 0.548, 'learning_rate': 1.4707520891364904e-05, 'epoch': 0.02}
+
2%|▏ | 264/11952 [26:45<18:38:11, 5.74s/it]
2%|▏ | 265/11952 [26:51<18:43:16, 5.77s/it]
{'loss': 0.546, 'learning_rate': 1.4763231197771588e-05, 'epoch': 0.02}
+
2%|▏ | 265/11952 [26:51<18:43:16, 5.77s/it]
2%|▏ | 266/11952 [26:56<18:32:09, 5.71s/it]
{'loss': 0.5171, 'learning_rate': 1.4818941504178274e-05, 'epoch': 0.02}
+
2%|▏ | 266/11952 [26:56<18:32:09, 5.71s/it]
2%|▏ | 267/11952 [27:02<18:30:36, 5.70s/it]
{'loss': 0.5478, 'learning_rate': 1.487465181058496e-05, 'epoch': 0.02}
+
2%|▏ | 267/11952 [27:02<18:30:36, 5.70s/it]
2%|▏ | 268/11952 [27:07<18:26:20, 5.68s/it]
{'loss': 0.5389, 'learning_rate': 1.4930362116991646e-05, 'epoch': 0.02}
+
2%|▏ | 268/11952 [27:07<18:26:20, 5.68s/it]
2%|▏ | 269/11952 [27:14<18:55:04, 5.83s/it]
{'loss': 0.5388, 'learning_rate': 1.498607242339833e-05, 'epoch': 0.02}
+
2%|▏ | 269/11952 [27:14<18:55:04, 5.83s/it]
2%|▏ | 270/11952 [27:19<18:49:48, 5.80s/it]
{'loss': 0.5412, 'learning_rate': 1.5041782729805015e-05, 'epoch': 0.02}
+
2%|▏ | 270/11952 [27:19<18:49:48, 5.80s/it]
2%|▏ | 271/11952 [27:25<18:41:51, 5.76s/it]
{'loss': 0.5354, 'learning_rate': 1.5097493036211702e-05, 'epoch': 0.02}
+
2%|▏ | 271/11952 [27:25<18:41:51, 5.76s/it]
2%|▏ | 272/11952 [27:31<18:30:35, 5.71s/it]
{'loss': 0.5453, 'learning_rate': 1.5153203342618385e-05, 'epoch': 0.02}
+
2%|▏ | 272/11952 [27:31<18:30:35, 5.71s/it]
2%|▏ | 273/11952 [27:36<18:26:41, 5.69s/it]
{'loss': 0.5322, 'learning_rate': 1.520891364902507e-05, 'epoch': 0.02}
+
2%|▏ | 273/11952 [27:36<18:26:41, 5.69s/it]
2%|▏ | 274/11952 [27:43<19:12:13, 5.92s/it]
{'loss': 0.5533, 'learning_rate': 1.5264623955431757e-05, 'epoch': 0.02}
+
2%|▏ | 274/11952 [27:43<19:12:13, 5.92s/it]
2%|▏ | 275/11952 [27:49<19:22:46, 5.97s/it]
{'loss': 0.5358, 'learning_rate': 1.5320334261838443e-05, 'epoch': 0.02}
+
2%|▏ | 275/11952 [27:49<19:22:46, 5.97s/it]
2%|▏ | 276/11952 [27:54<19:04:25, 5.88s/it]
{'loss': 0.5376, 'learning_rate': 1.5376044568245128e-05, 'epoch': 0.02}
+
2%|▏ | 276/11952 [27:54<19:04:25, 5.88s/it]
2%|▏ | 277/11952 [28:00<18:52:17, 5.82s/it]
{'loss': 0.5359, 'learning_rate': 1.5431754874651813e-05, 'epoch': 0.02}
+
2%|▏ | 277/11952 [28:00<18:52:17, 5.82s/it]
2%|▏ | 278/11952 [28:06<18:56:31, 5.84s/it]
{'loss': 0.5518, 'learning_rate': 1.5487465181058498e-05, 'epoch': 0.02}
+
2%|▏ | 278/11952 [28:06<18:56:31, 5.84s/it]
2%|▏ | 279/11952 [28:12<19:03:35, 5.88s/it]
{'loss': 0.5365, 'learning_rate': 1.5543175487465183e-05, 'epoch': 0.02}
+
2%|▏ | 279/11952 [28:12<19:03:35, 5.88s/it]
2%|▏ | 280/11952 [28:18<18:45:29, 5.79s/it]
{'loss': 0.5345, 'learning_rate': 1.5598885793871868e-05, 'epoch': 0.02}
+
2%|▏ | 280/11952 [28:18<18:45:29, 5.79s/it]
2%|▏ | 281/11952 [28:24<19:03:49, 5.88s/it]
{'loss': 0.5424, 'learning_rate': 1.5654596100278553e-05, 'epoch': 0.02}
+
2%|▏ | 281/11952 [28:24<19:03:49, 5.88s/it]
2%|▏ | 282/11952 [28:29<18:47:15, 5.80s/it]
{'loss': 0.5337, 'learning_rate': 1.571030640668524e-05, 'epoch': 0.02}
+
2%|▏ | 282/11952 [28:29<18:47:15, 5.80s/it]
2%|▏ | 283/11952 [28:35<18:36:09, 5.74s/it]
{'loss': 0.5202, 'learning_rate': 1.5766016713091924e-05, 'epoch': 0.02}
+
2%|▏ | 283/11952 [28:35<18:36:09, 5.74s/it]
2%|▏ | 284/11952 [28:41<18:40:23, 5.76s/it]
{'loss': 0.5293, 'learning_rate': 1.582172701949861e-05, 'epoch': 0.02}
+
2%|▏ | 284/11952 [28:41<18:40:23, 5.76s/it]
2%|▏ | 285/11952 [28:47<18:50:19, 5.81s/it]
{'loss': 0.549, 'learning_rate': 1.5877437325905294e-05, 'epoch': 0.02}
+
2%|▏ | 285/11952 [28:47<18:50:19, 5.81s/it]
2%|▏ | 286/11952 [28:53<18:53:42, 5.83s/it]
{'loss': 0.5346, 'learning_rate': 1.593314763231198e-05, 'epoch': 0.02}
+
2%|▏ | 286/11952 [28:53<18:53:42, 5.83s/it]
2%|▏ | 287/11952 [28:58<18:40:00, 5.76s/it]
{'loss': 0.5482, 'learning_rate': 1.5988857938718664e-05, 'epoch': 0.02}
+
2%|▏ | 287/11952 [28:58<18:40:00, 5.76s/it]
2%|▏ | 288/11952 [29:04<18:54:22, 5.84s/it]
{'loss': 0.5549, 'learning_rate': 1.604456824512535e-05, 'epoch': 0.02}
+
2%|▏ | 288/11952 [29:04<18:54:22, 5.84s/it]
2%|▏ | 289/11952 [29:10<18:53:03, 5.83s/it]
{'loss': 0.5293, 'learning_rate': 1.6100278551532035e-05, 'epoch': 0.02}
+
2%|▏ | 289/11952 [29:10<18:53:03, 5.83s/it]
2%|▏ | 290/11952 [29:16<19:04:24, 5.89s/it]
{'loss': 0.5656, 'learning_rate': 1.615598885793872e-05, 'epoch': 0.02}
+
2%|▏ | 290/11952 [29:16<19:04:24, 5.89s/it]
2%|▏ | 291/11952 [29:22<19:13:32, 5.94s/it]
{'loss': 0.5305, 'learning_rate': 1.6211699164345405e-05, 'epoch': 0.02}
+
2%|▏ | 291/11952 [29:22<19:13:32, 5.94s/it]
2%|▏ | 292/11952 [29:27<18:47:21, 5.80s/it]
{'loss': 0.5557, 'learning_rate': 1.626740947075209e-05, 'epoch': 0.02}
+
2%|▏ | 292/11952 [29:27<18:47:21, 5.80s/it]
2%|▏ | 293/11952 [29:33<18:38:26, 5.76s/it]
{'loss': 0.5374, 'learning_rate': 1.6323119777158775e-05, 'epoch': 0.02}
+
2%|▏ | 293/11952 [29:33<18:38:26, 5.76s/it]
2%|▏ | 294/11952 [29:39<18:39:18, 5.76s/it]
{'loss': 0.5183, 'learning_rate': 1.637883008356546e-05, 'epoch': 0.02}
+
2%|▏ | 294/11952 [29:39<18:39:18, 5.76s/it]
2%|▏ | 295/11952 [29:45<18:38:50, 5.76s/it]
{'loss': 0.5629, 'learning_rate': 1.6434540389972145e-05, 'epoch': 0.02}
+
2%|▏ | 295/11952 [29:45<18:38:50, 5.76s/it]
2%|▏ | 296/11952 [29:51<18:51:55, 5.83s/it]
{'loss': 0.5362, 'learning_rate': 1.649025069637883e-05, 'epoch': 0.02}
+
2%|▏ | 296/11952 [29:51<18:51:55, 5.83s/it]
2%|▏ | 297/11952 [29:56<18:38:42, 5.76s/it]
{'loss': 0.532, 'learning_rate': 1.654596100278552e-05, 'epoch': 0.02}
+
2%|▏ | 297/11952 [29:56<18:38:42, 5.76s/it]
2%|▏ | 298/11952 [30:02<18:44:44, 5.79s/it]
{'loss': 0.5322, 'learning_rate': 1.66016713091922e-05, 'epoch': 0.02}
+
2%|▏ | 298/11952 [30:02<18:44:44, 5.79s/it]
3%|▎ | 299/11952 [30:08<18:43:16, 5.78s/it]
{'loss': 0.528, 'learning_rate': 1.6657381615598886e-05, 'epoch': 0.03}
+
3%|▎ | 299/11952 [30:08<18:43:16, 5.78s/it]6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+01 3AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
3%|▎ | 300/11952 [30:14<19:04:38, 5.89s/it]
{'loss': 0.5609, 'learning_rate': 1.6713091922005575e-05, 'epoch': 0.03}
+
3%|▎ | 300/11952 [30:14<19:04:38, 5.89s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
3%|▎ | 301/11952 [30:48<45:53:47, 14.18s/it]
{'loss': 0.5438, 'learning_rate': 1.6768802228412256e-05, 'epoch': 0.03}
+
3%|▎ | 301/11952 [30:48<45:53:47, 14.18s/it]
3%|▎ | 302/11952 [30:53<37:37:56, 11.63s/it]
{'loss': 0.5241, 'learning_rate': 1.682451253481894e-05, 'epoch': 0.03}
+
3%|▎ | 302/11952 [30:53<37:37:56, 11.63s/it]
3%|▎ | 303/11952 [30:59<31:49:51, 9.84s/it]
{'loss': 0.5318, 'learning_rate': 1.688022284122563e-05, 'epoch': 0.03}
+
3%|▎ | 303/11952 [30:59<31:49:51, 9.84s/it]
3%|▎ | 304/11952 [31:05<27:56:47, 8.64s/it]
{'loss': 0.539, 'learning_rate': 1.6935933147632312e-05, 'epoch': 0.03}
+
3%|▎ | 304/11952 [31:05<27:56:47, 8.64s/it]
3%|▎ | 305/11952 [31:11<25:11:27, 7.79s/it]
{'loss': 0.5516, 'learning_rate': 1.6991643454039e-05, 'epoch': 0.03}
+
3%|▎ | 305/11952 [31:11<25:11:27, 7.79s/it]
3%|▎ | 306/11952 [31:16<23:24:23, 7.24s/it]
{'loss': 0.5418, 'learning_rate': 1.7047353760445685e-05, 'epoch': 0.03}
+
3%|▎ | 306/11952 [31:16<23:24:23, 7.24s/it]
3%|▎ | 307/11952 [31:23<22:16:33, 6.89s/it]
{'loss': 0.5453, 'learning_rate': 1.7103064066852367e-05, 'epoch': 0.03}
+
3%|▎ | 307/11952 [31:23<22:16:33, 6.89s/it]
3%|▎ | 308/11952 [31:28<21:12:06, 6.55s/it]
{'loss': 0.5144, 'learning_rate': 1.7158774373259056e-05, 'epoch': 0.03}
+
3%|▎ | 308/11952 [31:28<21:12:06, 6.55s/it]
3%|▎ | 309/11952 [31:34<20:20:49, 6.29s/it]
{'loss': 0.5553, 'learning_rate': 1.721448467966574e-05, 'epoch': 0.03}
+
3%|▎ | 309/11952 [31:34<20:20:49, 6.29s/it]
3%|▎ | 310/11952 [31:40<20:06:57, 6.22s/it]
{'loss': 0.5618, 'learning_rate': 1.7270194986072423e-05, 'epoch': 0.03}
+
3%|▎ | 310/11952 [31:40<20:06:57, 6.22s/it]
3%|▎ | 311/11952 [31:46<19:42:20, 6.09s/it]
{'loss': 0.525, 'learning_rate': 1.732590529247911e-05, 'epoch': 0.03}
+
3%|▎ | 311/11952 [31:46<19:42:20, 6.09s/it]
3%|▎ | 312/11952 [31:52<19:29:47, 6.03s/it]
{'loss': 0.5315, 'learning_rate': 1.7381615598885796e-05, 'epoch': 0.03}
+
3%|▎ | 312/11952 [31:52<19:29:47, 6.03s/it]
3%|▎ | 313/11952 [31:58<19:24:33, 6.00s/it]
{'loss': 0.5413, 'learning_rate': 1.743732590529248e-05, 'epoch': 0.03}
+
3%|▎ | 313/11952 [31:58<19:24:33, 6.00s/it]
3%|▎ | 314/11952 [32:04<19:27:15, 6.02s/it]
{'loss': 0.549, 'learning_rate': 1.7493036211699167e-05, 'epoch': 0.03}
+
3%|▎ | 314/11952 [32:04<19:27:15, 6.02s/it]
3%|▎ | 315/11952 [32:09<19:09:53, 5.93s/it]
{'loss': 0.5299, 'learning_rate': 1.7548746518105852e-05, 'epoch': 0.03}
+
3%|▎ | 315/11952 [32:09<19:09:53, 5.93s/it]
3%|▎ | 316/11952 [32:15<19:01:09, 5.88s/it]
{'loss': 0.5693, 'learning_rate': 1.7604456824512537e-05, 'epoch': 0.03}
+
3%|▎ | 316/11952 [32:15<19:01:09, 5.88s/it]
3%|▎ | 317/11952 [32:21<18:56:53, 5.86s/it]
{'loss': 0.5535, 'learning_rate': 1.7660167130919222e-05, 'epoch': 0.03}
+
3%|▎ | 317/11952 [32:21<18:56:53, 5.86s/it]
3%|▎ | 318/11952 [32:27<19:01:36, 5.89s/it]
{'loss': 0.5383, 'learning_rate': 1.7715877437325907e-05, 'epoch': 0.03}
+
3%|▎ | 318/11952 [32:27<19:01:36, 5.89s/it]
3%|▎ | 319/11952 [32:33<18:58:15, 5.87s/it]
{'loss': 0.5564, 'learning_rate': 1.7771587743732592e-05, 'epoch': 0.03}
+
3%|▎ | 319/11952 [32:33<18:58:15, 5.87s/it]
3%|▎ | 320/11952 [32:39<19:23:46, 6.00s/it]
{'loss': 0.5521, 'learning_rate': 1.7827298050139278e-05, 'epoch': 0.03}
+
3%|▎ | 320/11952 [32:39<19:23:46, 6.00s/it]
3%|▎ | 321/11952 [32:45<19:18:26, 5.98s/it]
{'loss': 0.5272, 'learning_rate': 1.7883008356545963e-05, 'epoch': 0.03}
+
3%|▎ | 321/11952 [32:45<19:18:26, 5.98s/it]
3%|▎ | 322/11952 [32:51<19:08:07, 5.92s/it]
{'loss': 0.5204, 'learning_rate': 1.7938718662952648e-05, 'epoch': 0.03}
+
3%|▎ | 322/11952 [32:51<19:08:07, 5.92s/it]
3%|▎ | 323/11952 [32:57<19:04:27, 5.90s/it]
{'loss': 0.5537, 'learning_rate': 1.7994428969359333e-05, 'epoch': 0.03}
+
3%|▎ | 323/11952 [32:57<19:04:27, 5.90s/it]
3%|▎ | 324/11952 [33:03<19:00:52, 5.89s/it]
{'loss': 0.5412, 'learning_rate': 1.8050139275766018e-05, 'epoch': 0.03}
+
3%|▎ | 324/11952 [33:03<19:00:52, 5.89s/it]
3%|▎ | 325/11952 [33:08<18:48:03, 5.82s/it]
{'loss': 0.5343, 'learning_rate': 1.8105849582172703e-05, 'epoch': 0.03}
+
3%|▎ | 325/11952 [33:08<18:48:03, 5.82s/it]
3%|▎ | 326/11952 [33:14<18:45:16, 5.81s/it]
{'loss': 0.5388, 'learning_rate': 1.816155988857939e-05, 'epoch': 0.03}
+
3%|▎ | 326/11952 [33:14<18:45:16, 5.81s/it]
3%|▎ | 327/11952 [33:20<18:46:41, 5.82s/it]
{'loss': 0.5325, 'learning_rate': 1.8217270194986074e-05, 'epoch': 0.03}
+
3%|▎ | 327/11952 [33:20<18:46:41, 5.82s/it]
3%|▎ | 328/11952 [33:26<18:39:40, 5.78s/it]
{'loss': 0.525, 'learning_rate': 1.827298050139276e-05, 'epoch': 0.03}
+
3%|▎ | 328/11952 [33:26<18:39:40, 5.78s/it]
3%|▎ | 329/11952 [33:32<19:02:45, 5.90s/it]
{'loss': 0.5467, 'learning_rate': 1.8328690807799444e-05, 'epoch': 0.03}
+
3%|▎ | 329/11952 [33:32<19:02:45, 5.90s/it]
3%|▎ | 330/11952 [33:38<18:57:50, 5.87s/it]
{'loss': 0.5329, 'learning_rate': 1.838440111420613e-05, 'epoch': 0.03}
+
3%|▎ | 330/11952 [33:38<18:57:50, 5.87s/it]
3%|▎ | 331/11952 [33:44<19:07:05, 5.92s/it]
{'loss': 0.5338, 'learning_rate': 1.8440111420612814e-05, 'epoch': 0.03}
+
3%|▎ | 331/11952 [33:44<19:07:05, 5.92s/it]
3%|▎ | 332/11952 [33:49<18:55:00, 5.86s/it]
{'loss': 0.5236, 'learning_rate': 1.84958217270195e-05, 'epoch': 0.03}
+
3%|▎ | 332/11952 [33:49<18:55:00, 5.86s/it]
3%|▎ | 333/11952 [33:55<18:53:48, 5.85s/it]
{'loss': 0.5235, 'learning_rate': 1.8551532033426184e-05, 'epoch': 0.03}
+
3%|▎ | 333/11952 [33:55<18:53:48, 5.85s/it]
3%|▎ | 334/11952 [34:01<18:47:15, 5.82s/it]
{'loss': 0.5295, 'learning_rate': 1.8607242339832873e-05, 'epoch': 0.03}
+
3%|▎ | 334/11952 [34:01<18:47:15, 5.82s/it]
3%|▎ | 335/11952 [34:07<18:47:05, 5.82s/it]
{'loss': 0.5306, 'learning_rate': 1.8662952646239555e-05, 'epoch': 0.03}
+
3%|▎ | 335/11952 [34:07<18:47:05, 5.82s/it]
3%|▎ | 336/11952 [34:12<18:45:19, 5.81s/it]
{'loss': 0.5102, 'learning_rate': 1.871866295264624e-05, 'epoch': 0.03}
+
3%|▎ | 336/11952 [34:12<18:45:19, 5.81s/it]
3%|▎ | 337/11952 [34:18<18:34:24, 5.76s/it]
{'loss': 0.5463, 'learning_rate': 1.877437325905293e-05, 'epoch': 0.03}
+
3%|▎ | 337/11952 [34:18<18:34:24, 5.76s/it]
3%|▎ | 338/11952 [34:24<18:34:12, 5.76s/it]
{'loss': 0.5163, 'learning_rate': 1.883008356545961e-05, 'epoch': 0.03}
+
3%|▎ | 338/11952 [34:24<18:34:12, 5.76s/it]
3%|▎ | 339/11952 [34:30<18:30:20, 5.74s/it]
{'loss': 0.5452, 'learning_rate': 1.8885793871866295e-05, 'epoch': 0.03}
+
3%|▎ | 339/11952 [34:30<18:30:20, 5.74s/it]
3%|▎ | 340/11952 [34:35<18:32:51, 5.75s/it]
{'loss': 0.547, 'learning_rate': 1.8941504178272984e-05, 'epoch': 0.03}
+
3%|▎ | 340/11952 [34:35<18:32:51, 5.75s/it]
3%|▎ | 341/11952 [34:41<18:49:03, 5.83s/it]
{'loss': 0.5442, 'learning_rate': 1.8997214484679666e-05, 'epoch': 0.03}
+
3%|▎ | 341/11952 [34:41<18:49:03, 5.83s/it]
3%|▎ | 342/11952 [34:47<18:53:17, 5.86s/it]
{'loss': 0.5389, 'learning_rate': 1.9052924791086354e-05, 'epoch': 0.03}
+
3%|▎ | 342/11952 [34:47<18:53:17, 5.86s/it]
3%|▎ | 343/11952 [34:53<19:09:02, 5.94s/it]
{'loss': 0.5253, 'learning_rate': 1.910863509749304e-05, 'epoch': 0.03}
+
3%|▎ | 343/11952 [34:53<19:09:02, 5.94s/it]
3%|▎ | 344/11952 [34:59<19:04:12, 5.91s/it]
{'loss': 0.5252, 'learning_rate': 1.916434540389972e-05, 'epoch': 0.03}
+
3%|▎ | 344/11952 [34:59<19:04:12, 5.91s/it]
3%|▎ | 345/11952 [35:05<19:16:33, 5.98s/it]
{'loss': 0.5388, 'learning_rate': 1.922005571030641e-05, 'epoch': 0.03}
+
3%|▎ | 345/11952 [35:05<19:16:33, 5.98s/it]
3%|▎ | 346/11952 [35:11<19:24:16, 6.02s/it]
{'loss': 0.5336, 'learning_rate': 1.9275766016713095e-05, 'epoch': 0.03}
+
3%|▎ | 346/11952 [35:11<19:24:16, 6.02s/it]
3%|▎ | 347/11952 [35:17<19:07:55, 5.93s/it]
{'loss': 0.5342, 'learning_rate': 1.9331476323119776e-05, 'epoch': 0.03}
+
3%|▎ | 347/11952 [35:17<19:07:55, 5.93s/it]
3%|▎ | 348/11952 [35:23<19:17:35, 5.99s/it]
{'loss': 0.5227, 'learning_rate': 1.9387186629526465e-05, 'epoch': 0.03}
+
3%|▎ | 348/11952 [35:23<19:17:35, 5.99s/it]
3%|▎ | 349/11952 [35:29<19:06:30, 5.93s/it]
{'loss': 0.5062, 'learning_rate': 1.944289693593315e-05, 'epoch': 0.03}
+
3%|▎ | 349/11952 [35:29<19:06:30, 5.93s/it]2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 3AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ 4AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+
3%|▎ | 350/11952 [35:35<18:54:24, 5.87s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5286, 'learning_rate': 1.9498607242339835e-05, 'epoch': 0.03}
+
3%|▎ | 350/11952 [35:35<18:54:24, 5.87s/it]
3%|▎ | 351/11952 [35:41<18:49:59, 5.84s/it]
{'loss': 0.5326, 'learning_rate': 1.955431754874652e-05, 'epoch': 0.03}
+
3%|▎ | 351/11952 [35:41<18:49:59, 5.84s/it]
3%|▎ | 352/11952 [35:46<18:50:31, 5.85s/it]
{'loss': 0.5219, 'learning_rate': 1.9610027855153206e-05, 'epoch': 0.03}
+
3%|▎ | 352/11952 [35:47<18:50:31, 5.85s/it]
3%|▎ | 353/11952 [35:52<18:46:09, 5.83s/it]
{'loss': 0.5258, 'learning_rate': 1.966573816155989e-05, 'epoch': 0.03}
+
3%|▎ | 353/11952 [35:52<18:46:09, 5.83s/it]
3%|▎ | 354/11952 [35:58<18:46:35, 5.83s/it]
{'loss': 0.5307, 'learning_rate': 1.9721448467966576e-05, 'epoch': 0.03}
+
3%|▎ | 354/11952 [35:58<18:46:35, 5.83s/it]
3%|▎ | 355/11952 [36:04<18:57:59, 5.89s/it]
{'loss': 0.5314, 'learning_rate': 1.977715877437326e-05, 'epoch': 0.03}
+
3%|▎ | 355/11952 [36:04<18:57:59, 5.89s/it]
3%|▎ | 356/11952 [36:10<18:42:04, 5.81s/it]
{'loss': 0.5438, 'learning_rate': 1.9832869080779946e-05, 'epoch': 0.03}
+
3%|▎ | 356/11952 [36:10<18:42:04, 5.81s/it]
3%|▎ | 357/11952 [36:15<18:34:00, 5.76s/it]
{'loss': 0.5321, 'learning_rate': 1.988857938718663e-05, 'epoch': 0.03}
+
3%|▎ | 357/11952 [36:15<18:34:00, 5.76s/it]
3%|▎ | 358/11952 [36:22<18:53:40, 5.87s/it]
{'loss': 0.5139, 'learning_rate': 1.9944289693593316e-05, 'epoch': 0.03}
+
3%|▎ | 358/11952 [36:22<18:53:40, 5.87s/it]
3%|▎ | 359/11952 [36:27<18:56:41, 5.88s/it]
{'loss': 0.5207, 'learning_rate': 2e-05, 'epoch': 0.03}
+
3%|▎ | 359/11952 [36:27<18:56:41, 5.88s/it]
3%|▎ | 360/11952 [36:33<18:44:49, 5.82s/it]
{'loss': 0.5364, 'learning_rate': 1.99999996328208e-05, 'epoch': 0.03}
+
3%|▎ | 360/11952 [36:33<18:44:49, 5.82s/it]
3%|▎ | 361/11952 [36:39<18:43:26, 5.82s/it]
{'loss': 0.54, 'learning_rate': 1.9999998531283215e-05, 'epoch': 0.03}
+
3%|▎ | 361/11952 [36:39<18:43:26, 5.82s/it]
3%|▎ | 362/11952 [36:45<18:31:59, 5.76s/it]
{'loss': 0.5216, 'learning_rate': 1.9999996695387335e-05, 'epoch': 0.03}
+
3%|▎ | 362/11952 [36:45<18:31:59, 5.76s/it]
3%|▎ | 363/11952 [36:50<18:38:59, 5.79s/it]
{'loss': 0.5454, 'learning_rate': 1.9999994125133287e-05, 'epoch': 0.03}
+
3%|▎ | 363/11952 [36:50<18:38:59, 5.79s/it]
3%|▎ | 364/11952 [36:56<18:38:06, 5.79s/it]
{'loss': 0.5464, 'learning_rate': 1.9999990820521264e-05, 'epoch': 0.03}
+
3%|▎ | 364/11952 [36:56<18:38:06, 5.79s/it]
3%|▎ | 365/11952 [37:02<18:25:02, 5.72s/it]
{'loss': 0.5201, 'learning_rate': 1.999998678155151e-05, 'epoch': 0.03}
+
3%|▎ | 365/11952 [37:02<18:25:02, 5.72s/it]
3%|▎ | 366/11952 [37:08<18:40:35, 5.80s/it]
{'loss': 0.541, 'learning_rate': 1.999998200822432e-05, 'epoch': 0.03}
+
3%|▎ | 366/11952 [37:08<18:40:35, 5.80s/it]
3%|▎ | 367/11952 [37:14<18:42:49, 5.82s/it]
{'loss': 0.5372, 'learning_rate': 1.9999976500540042e-05, 'epoch': 0.03}
+
3%|▎ | 367/11952 [37:14<18:42:49, 5.82s/it]
3%|▎ | 368/11952 [37:20<18:55:05, 5.88s/it]
{'loss': 0.5408, 'learning_rate': 1.9999970258499083e-05, 'epoch': 0.03}
+
3%|▎ | 368/11952 [37:20<18:55:05, 5.88s/it]
3%|▎ | 369/11952 [37:25<18:43:58, 5.82s/it]
{'loss': 0.5416, 'learning_rate': 1.99999632821019e-05, 'epoch': 0.03}
+
3%|▎ | 369/11952 [37:25<18:43:58, 5.82s/it]
3%|▎ | 370/11952 [37:31<18:44:03, 5.82s/it]
{'loss': 0.5459, 'learning_rate': 1.9999955571349014e-05, 'epoch': 0.03}
+
3%|▎ | 370/11952 [37:31<18:44:03, 5.82s/it]
3%|▎ | 371/11952 [37:37<18:44:52, 5.83s/it]
{'loss': 0.5258, 'learning_rate': 1.9999947126240977e-05, 'epoch': 0.03}
+
3%|▎ | 371/11952 [37:37<18:44:52, 5.83s/it]
3%|▎ | 372/11952 [37:43<18:53:41, 5.87s/it]
{'loss': 0.5256, 'learning_rate': 1.9999937946778418e-05, 'epoch': 0.03}
+
3%|▎ | 372/11952 [37:43<18:53:41, 5.87s/it]
3%|▎ | 373/11952 [37:49<18:42:06, 5.81s/it]
{'loss': 0.5362, 'learning_rate': 1.999992803296201e-05, 'epoch': 0.03}
+
3%|▎ | 373/11952 [37:49<18:42:06, 5.81s/it]
3%|▎ | 374/11952 [37:55<18:51:42, 5.86s/it]
{'loss': 0.5381, 'learning_rate': 1.9999917384792477e-05, 'epoch': 0.03}
+
3%|▎ | 374/11952 [37:55<18:51:42, 5.86s/it]
3%|▎ | 375/11952 [38:00<18:47:04, 5.84s/it]
{'loss': 0.536, 'learning_rate': 1.9999906002270605e-05, 'epoch': 0.03}
+
3%|▎ | 375/11952 [38:00<18:47:04, 5.84s/it]
3%|▎ | 376/11952 [38:06<18:39:45, 5.80s/it]
{'loss': 0.5304, 'learning_rate': 1.999989388539723e-05, 'epoch': 0.03}
+
3%|▎ | 376/11952 [38:06<18:39:45, 5.80s/it]
3%|▎ | 377/11952 [38:12<18:45:36, 5.83s/it]
{'loss': 0.5351, 'learning_rate': 1.9999881034173242e-05, 'epoch': 0.03}
+
3%|▎ | 377/11952 [38:12<18:45:36, 5.83s/it]
3%|▎ | 378/11952 [38:18<18:48:09, 5.85s/it]
{'loss': 0.5387, 'learning_rate': 1.999986744859958e-05, 'epoch': 0.03}
+
3%|▎ | 378/11952 [38:18<18:48:09, 5.85s/it]
3%|▎ | 379/11952 [38:24<18:48:43, 5.85s/it]
{'loss': 0.5333, 'learning_rate': 1.999985312867725e-05, 'epoch': 0.03}
+
3%|▎ | 379/11952 [38:24<18:48:43, 5.85s/it]
3%|▎ | 380/11952 [38:29<18:35:02, 5.78s/it]
{'loss': 0.5152, 'learning_rate': 1.9999838074407296e-05, 'epoch': 0.03}
+
3%|▎ | 380/11952 [38:29<18:35:02, 5.78s/it]
3%|▎ | 381/11952 [38:35<18:37:39, 5.80s/it]
{'loss': 0.516, 'learning_rate': 1.9999822285790825e-05, 'epoch': 0.03}
+
3%|▎ | 381/11952 [38:35<18:37:39, 5.80s/it]
3%|▎ | 382/11952 [38:41<18:45:18, 5.84s/it]
{'loss': 0.539, 'learning_rate': 1.9999805762829e-05, 'epoch': 0.03}
+
3%|▎ | 382/11952 [38:41<18:45:18, 5.84s/it]
3%|▎ | 383/11952 [38:47<18:44:53, 5.83s/it]
{'loss': 0.5299, 'learning_rate': 1.999978850552303e-05, 'epoch': 0.03}
+
3%|▎ | 383/11952 [38:47<18:44:53, 5.83s/it]
3%|▎ | 384/11952 [38:53<18:47:12, 5.85s/it]
{'loss': 0.5556, 'learning_rate': 1.9999770513874187e-05, 'epoch': 0.03}
+
3%|▎ | 384/11952 [38:53<18:47:12, 5.85s/it]
3%|▎ | 385/11952 [38:59<18:39:18, 5.81s/it]
{'loss': 0.5509, 'learning_rate': 1.9999751787883787e-05, 'epoch': 0.03}
+
3%|▎ | 385/11952 [38:59<18:39:18, 5.81s/it]
3%|▎ | 386/11952 [39:04<18:31:55, 5.77s/it]
{'loss': 0.5262, 'learning_rate': 1.999973232755321e-05, 'epoch': 0.03}
+
3%|▎ | 386/11952 [39:04<18:31:55, 5.77s/it]
3%|▎ | 387/11952 [39:10<18:30:50, 5.76s/it]
{'loss': 0.5146, 'learning_rate': 1.999971213288388e-05, 'epoch': 0.03}
+
3%|▎ | 387/11952 [39:10<18:30:50, 5.76s/it]
3%|▎ | 388/11952 [39:16<18:25:04, 5.73s/it]
{'loss': 0.5112, 'learning_rate': 1.9999691203877286e-05, 'epoch': 0.03}
+
3%|▎ | 388/11952 [39:16<18:25:04, 5.73s/it]
3%|▎ | 389/11952 [39:22<18:34:38, 5.78s/it]
{'loss': 0.544, 'learning_rate': 1.999966954053496e-05, 'epoch': 0.03}
+
3%|▎ | 389/11952 [39:22<18:34:38, 5.78s/it]
3%|▎ | 390/11952 [39:27<18:42:12, 5.82s/it]
{'loss': 0.519, 'learning_rate': 1.9999647142858496e-05, 'epoch': 0.03}
+
3%|▎ | 390/11952 [39:27<18:42:12, 5.82s/it]
3%|▎ | 391/11952 [39:33<18:35:20, 5.79s/it]
{'loss': 0.5349, 'learning_rate': 1.9999624010849536e-05, 'epoch': 0.03}
+
3%|▎ | 391/11952 [39:33<18:35:20, 5.79s/it]
3%|▎ | 392/11952 [39:39<18:35:12, 5.79s/it]
{'loss': 0.5184, 'learning_rate': 1.999960014450978e-05, 'epoch': 0.03}
+
3%|▎ | 392/11952 [39:39<18:35:12, 5.79s/it]
3%|▎ | 393/11952 [39:45<18:47:42, 5.85s/it]
{'loss': 0.5374, 'learning_rate': 1.9999575543840982e-05, 'epoch': 0.03}
+
3%|▎ | 393/11952 [39:45<18:47:42, 5.85s/it]
3%|▎ | 394/11952 [39:51<18:47:40, 5.85s/it]
{'loss': 0.5205, 'learning_rate': 1.999955020884495e-05, 'epoch': 0.03}
+
3%|▎ | 394/11952 [39:51<18:47:40, 5.85s/it]
3%|▎ | 395/11952 [39:57<18:57:51, 5.91s/it]
{'loss': 0.5536, 'learning_rate': 1.9999524139523538e-05, 'epoch': 0.03}
+
3%|▎ | 395/11952 [39:57<18:57:51, 5.91s/it]
3%|▎ | 396/11952 [40:03<19:02:30, 5.93s/it]
{'loss': 0.5277, 'learning_rate': 1.9999497335878666e-05, 'epoch': 0.03}
+
3%|▎ | 396/11952 [40:03<19:02:30, 5.93s/it]
3%|▎ | 397/11952 [40:09<18:56:29, 5.90s/it]
{'loss': 0.5181, 'learning_rate': 1.99994697979123e-05, 'epoch': 0.03}
+
3%|▎ | 397/11952 [40:09<18:56:29, 5.90s/it]
3%|▎ | 398/11952 [40:14<18:46:07, 5.85s/it]
{'loss': 0.5173, 'learning_rate': 1.9999441525626464e-05, 'epoch': 0.03}
+
3%|▎ | 398/11952 [40:14<18:46:07, 5.85s/it]
3%|▎ | 399/11952 [40:20<18:44:38, 5.84s/it]
{'loss': 0.5443, 'learning_rate': 1.9999412519023233e-05, 'epoch': 0.03}
+
3%|▎ | 399/11952 [40:20<18:44:38, 5.84s/it]07 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...3
+ AutoResumeHook: Checking whether to suspend...
+
3%|▎ | 400/11952 [40:26<18:36:55, 5.80s/it]4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5279, 'learning_rate': 1.9999382778104734e-05, 'epoch': 0.03}
+
3%|▎ | 400/11952 [40:26<18:36:55, 5.80s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
3%|▎ | 401/11952 [40:59<44:54:29, 14.00s/it]
{'loss': 0.5472, 'learning_rate': 1.999935230287316e-05, 'epoch': 0.03}
+
3%|▎ | 401/11952 [40:59<44:54:29, 14.00s/it]
3%|▎ | 402/11952 [41:05<37:15:22, 11.61s/it]
{'loss': 0.5348, 'learning_rate': 1.9999321093330736e-05, 'epoch': 0.03}
+
3%|▎ | 402/11952 [41:05<37:15:22, 11.61s/it]
3%|▎ | 403/11952 [41:11<31:23:29, 9.79s/it]
{'loss': 0.5534, 'learning_rate': 1.9999289149479767e-05, 'epoch': 0.03}
+
3%|▎ | 403/11952 [41:11<31:23:29, 9.79s/it]
3%|▎ | 404/11952 [41:17<27:44:13, 8.65s/it]
{'loss': 0.5447, 'learning_rate': 1.9999256471322593e-05, 'epoch': 0.03}
+
3%|▎ | 404/11952 [41:17<27:44:13, 8.65s/it]
3%|▎ | 405/11952 [41:22<25:03:44, 7.81s/it]
{'loss': 0.5312, 'learning_rate': 1.9999223058861613e-05, 'epoch': 0.03}
+
3%|▎ | 405/11952 [41:22<25:03:44, 7.81s/it]
3%|▎ | 406/11952 [41:28<23:06:41, 7.21s/it]
{'loss': 0.5267, 'learning_rate': 1.9999188912099278e-05, 'epoch': 0.03}
+
3%|▎ | 406/11952 [41:28<23:06:41, 7.21s/it]
3%|▎ | 407/11952 [41:34<21:49:55, 6.81s/it]
{'loss': 0.5221, 'learning_rate': 1.99991540310381e-05, 'epoch': 0.03}
+
3%|▎ | 407/11952 [41:34<21:49:55, 6.81s/it]
3%|▎ | 408/11952 [41:40<20:47:56, 6.49s/it]
{'loss': 0.5456, 'learning_rate': 1.9999118415680642e-05, 'epoch': 0.03}
+
3%|▎ | 408/11952 [41:40<20:47:56, 6.49s/it]
3%|▎ | 409/11952 [41:46<20:09:04, 6.28s/it]
{'loss': 0.5202, 'learning_rate': 1.999908206602952e-05, 'epoch': 0.03}
+
3%|▎ | 409/11952 [41:46<20:09:04, 6.28s/it]
3%|▎ | 410/11952 [41:51<19:30:45, 6.09s/it]
{'loss': 0.5202, 'learning_rate': 1.9999044982087394e-05, 'epoch': 0.03}
+
3%|▎ | 410/11952 [41:51<19:30:45, 6.09s/it]
3%|▎ | 411/11952 [41:57<19:13:22, 6.00s/it]
{'loss': 0.5302, 'learning_rate': 1.9999007163856998e-05, 'epoch': 0.03}
+
3%|▎ | 411/11952 [41:57<19:13:22, 6.00s/it]
3%|▎ | 412/11952 [42:03<18:49:36, 5.87s/it]
{'loss': 0.5081, 'learning_rate': 1.9998968611341102e-05, 'epoch': 0.03}
+
3%|▎ | 412/11952 [42:03<18:49:36, 5.87s/it]
3%|▎ | 413/11952 [42:09<18:47:40, 5.86s/it]
{'loss': 0.5599, 'learning_rate': 1.9998929324542543e-05, 'epoch': 0.03}
+
3%|▎ | 413/11952 [42:09<18:47:40, 5.86s/it]
3%|▎ | 414/11952 [42:15<18:58:54, 5.92s/it]
{'loss': 0.5327, 'learning_rate': 1.99988893034642e-05, 'epoch': 0.03}
+
3%|▎ | 414/11952 [42:15<18:58:54, 5.92s/it]
3%|▎ | 415/11952 [42:21<19:02:31, 5.94s/it]
{'loss': 0.5236, 'learning_rate': 1.9998848548109017e-05, 'epoch': 0.03}
+
3%|▎ | 415/11952 [42:21<19:02:31, 5.94s/it]
3%|▎ | 416/11952 [42:27<19:01:46, 5.94s/it]
{'loss': 0.5366, 'learning_rate': 1.9998807058479986e-05, 'epoch': 0.03}
+
3%|▎ | 416/11952 [42:27<19:01:46, 5.94s/it]
3%|▎ | 417/11952 [42:32<19:02:36, 5.94s/it]
{'loss': 0.5525, 'learning_rate': 1.9998764834580147e-05, 'epoch': 0.03}
+
3%|▎ | 417/11952 [42:32<19:02:36, 5.94s/it]
3%|▎ | 418/11952 [42:38<19:05:01, 5.96s/it]
{'loss': 0.5199, 'learning_rate': 1.9998721876412613e-05, 'epoch': 0.03}
+
3%|▎ | 418/11952 [42:38<19:05:01, 5.96s/it]
4%|▎ | 419/11952 [42:45<19:09:52, 5.98s/it]
{'loss': 0.518, 'learning_rate': 1.9998678183980532e-05, 'epoch': 0.04}
+
4%|▎ | 419/11952 [42:45<19:09:52, 5.98s/it]
4%|▎ | 420/11952 [42:50<18:55:02, 5.91s/it]
{'loss': 0.5472, 'learning_rate': 1.999863375728711e-05, 'epoch': 0.04}
+
4%|▎ | 420/11952 [42:50<18:55:02, 5.91s/it]
4%|▎ | 421/11952 [42:56<18:43:14, 5.84s/it]
{'loss': 0.5363, 'learning_rate': 1.9998588596335612e-05, 'epoch': 0.04}
+
4%|▎ | 421/11952 [42:56<18:43:14, 5.84s/it]
4%|▎ | 422/11952 [43:02<19:03:34, 5.95s/it]
{'loss': 0.5383, 'learning_rate': 1.9998542701129357e-05, 'epoch': 0.04}
+
4%|▎ | 422/11952 [43:02<19:03:34, 5.95s/it]
4%|▎ | 423/11952 [43:08<18:49:02, 5.88s/it]
{'loss': 0.5367, 'learning_rate': 1.999849607167171e-05, 'epoch': 0.04}
+
4%|▎ | 423/11952 [43:08<18:49:02, 5.88s/it]
4%|▎ | 424/11952 [43:14<18:57:13, 5.92s/it]
{'loss': 0.5358, 'learning_rate': 1.99984487079661e-05, 'epoch': 0.04}
+
4%|▎ | 424/11952 [43:14<18:57:13, 5.92s/it]
4%|▎ | 425/11952 [43:20<18:59:13, 5.93s/it]
{'loss': 0.5414, 'learning_rate': 1.9998400610016003e-05, 'epoch': 0.04}
+
4%|▎ | 425/11952 [43:20<18:59:13, 5.93s/it]
4%|▎ | 426/11952 [43:26<19:08:07, 5.98s/it]
{'loss': 0.5361, 'learning_rate': 1.9998351777824956e-05, 'epoch': 0.04}
+
4%|▎ | 426/11952 [43:26<19:08:07, 5.98s/it]
4%|▎ | 427/11952 [43:32<19:01:40, 5.94s/it]
{'loss': 0.5266, 'learning_rate': 1.9998302211396537e-05, 'epoch': 0.04}
+
4%|▎ | 427/11952 [43:32<19:01:40, 5.94s/it]
4%|▎ | 428/11952 [43:38<18:56:51, 5.92s/it]
{'loss': 0.5149, 'learning_rate': 1.999825191073439e-05, 'epoch': 0.04}
+
4%|▎ | 428/11952 [43:38<18:56:51, 5.92s/it]
4%|▎ | 429/11952 [43:43<18:38:19, 5.82s/it]
{'loss': 0.5253, 'learning_rate': 1.9998200875842206e-05, 'epoch': 0.04}
+
4%|▎ | 429/11952 [43:43<18:38:19, 5.82s/it]
4%|▎ | 430/11952 [43:49<18:23:55, 5.75s/it]
{'loss': 0.5362, 'learning_rate': 1.9998149106723737e-05, 'epoch': 0.04}
+
4%|▎ | 430/11952 [43:49<18:23:55, 5.75s/it]
4%|▎ | 431/11952 [43:55<18:45:16, 5.86s/it]
{'loss': 0.5377, 'learning_rate': 1.9998096603382785e-05, 'epoch': 0.04}
+
4%|▎ | 431/11952 [43:55<18:45:16, 5.86s/it]
4%|▎ | 432/11952 [44:01<18:34:34, 5.81s/it]
{'loss': 0.5397, 'learning_rate': 1.9998043365823205e-05, 'epoch': 0.04}
+
4%|▎ | 432/11952 [44:01<18:34:34, 5.81s/it]
4%|▎ | 433/11952 [44:06<18:38:19, 5.83s/it]
{'loss': 0.5267, 'learning_rate': 1.99979893940489e-05, 'epoch': 0.04}
+
4%|▎ | 433/11952 [44:06<18:38:19, 5.83s/it]
4%|▎ | 434/11952 [44:12<18:48:15, 5.88s/it]
{'loss': 0.5379, 'learning_rate': 1.999793468806384e-05, 'epoch': 0.04}
+
4%|▎ | 434/11952 [44:12<18:48:15, 5.88s/it]
4%|▎ | 435/11952 [44:18<18:46:12, 5.87s/it]
{'loss': 0.5283, 'learning_rate': 1.9997879247872042e-05, 'epoch': 0.04}
+
4%|▎ | 435/11952 [44:18<18:46:12, 5.87s/it]
4%|▎ | 436/11952 [44:24<18:52:46, 5.90s/it]
{'loss': 0.5098, 'learning_rate': 1.9997823073477577e-05, 'epoch': 0.04}
+
4%|▎ | 436/11952 [44:24<18:52:46, 5.90s/it]
4%|▎ | 437/11952 [44:30<18:40:52, 5.84s/it]
{'loss': 0.5102, 'learning_rate': 1.9997766164884572e-05, 'epoch': 0.04}
+
4%|▎ | 437/11952 [44:30<18:40:52, 5.84s/it]
4%|▎ | 438/11952 [44:36<18:45:18, 5.86s/it]
{'loss': 0.5374, 'learning_rate': 1.9997708522097202e-05, 'epoch': 0.04}
+
4%|▎ | 438/11952 [44:36<18:45:18, 5.86s/it]
4%|▎ | 439/11952 [44:42<18:45:11, 5.86s/it]
{'loss': 0.5158, 'learning_rate': 1.9997650145119702e-05, 'epoch': 0.04}
+
4%|▎ | 439/11952 [44:42<18:45:11, 5.86s/it]
4%|▎ | 440/11952 [44:47<18:35:15, 5.81s/it]
{'loss': 0.5019, 'learning_rate': 1.9997591033956353e-05, 'epoch': 0.04}
+
4%|▎ | 440/11952 [44:47<18:35:15, 5.81s/it]
4%|▎ | 441/11952 [44:53<18:44:34, 5.86s/it]
{'loss': 0.5368, 'learning_rate': 1.9997531188611507e-05, 'epoch': 0.04}
+
4%|▎ | 441/11952 [44:53<18:44:34, 5.86s/it]
4%|▎ | 442/11952 [44:59<18:44:58, 5.86s/it]
{'loss': 0.5247, 'learning_rate': 1.999747060908955e-05, 'epoch': 0.04}
+
4%|▎ | 442/11952 [44:59<18:44:58, 5.86s/it]
4%|▎ | 443/11952 [45:05<18:39:24, 5.84s/it]
{'loss': 0.5346, 'learning_rate': 1.9997409295394938e-05, 'epoch': 0.04}
+
4%|▎ | 443/11952 [45:05<18:39:24, 5.84s/it]
4%|▎ | 444/11952 [45:11<18:40:40, 5.84s/it]
{'loss': 0.5386, 'learning_rate': 1.999734724753217e-05, 'epoch': 0.04}
+
4%|▎ | 444/11952 [45:11<18:40:40, 5.84s/it]
4%|▎ | 445/11952 [45:17<18:24:21, 5.76s/it]
{'loss': 0.5305, 'learning_rate': 1.99972844655058e-05, 'epoch': 0.04}
+
4%|▎ | 445/11952 [45:17<18:24:21, 5.76s/it]
4%|▎ | 446/11952 [45:22<18:21:20, 5.74s/it]
{'loss': 0.5347, 'learning_rate': 1.999722094932044e-05, 'epoch': 0.04}
+
4%|▎ | 446/11952 [45:22<18:21:20, 5.74s/it]
4%|▎ | 447/11952 [45:28<18:18:14, 5.73s/it]
{'loss': 0.5309, 'learning_rate': 1.9997156698980755e-05, 'epoch': 0.04}
+
4%|▎ | 447/11952 [45:28<18:18:14, 5.73s/it]
4%|▎ | 448/11952 [45:34<18:15:24, 5.71s/it]
{'loss': 0.5383, 'learning_rate': 1.9997091714491465e-05, 'epoch': 0.04}
+
4%|▎ | 448/11952 [45:34<18:15:24, 5.71s/it]
4%|▍ | 449/11952 [45:40<18:28:28, 5.78s/it]
{'loss': 0.524, 'learning_rate': 1.999702599585734e-05, 'epoch': 0.04}
+
4%|▍ | 449/11952 [45:40<18:28:28, 5.78s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
4%|▍ | 450/11952 [45:45<18:26:09, 5.77s/it]
{'loss': 0.5387, 'learning_rate': 1.9996959543083207e-05, 'epoch': 0.04}
+
4%|▍ | 450/11952 [45:45<18:26:09, 5.77s/it]
4%|▍ | 451/11952 [45:51<18:13:00, 5.70s/it]
{'loss': 0.5336, 'learning_rate': 1.9996892356173946e-05, 'epoch': 0.04}
+
4%|▍ | 451/11952 [45:51<18:13:00, 5.70s/it]
4%|▍ | 452/11952 [45:57<18:39:43, 5.84s/it]
{'loss': 0.5338, 'learning_rate': 1.9996824435134486e-05, 'epoch': 0.04}
+
4%|▍ | 452/11952 [45:57<18:39:43, 5.84s/it]
4%|▍ | 453/11952 [46:03<18:53:13, 5.91s/it]
{'loss': 0.5231, 'learning_rate': 1.9996755779969827e-05, 'epoch': 0.04}
+
4%|▍ | 453/11952 [46:03<18:53:13, 5.91s/it]
4%|▍ | 454/11952 [46:09<18:49:31, 5.89s/it]
{'loss': 0.5371, 'learning_rate': 1.9996686390685e-05, 'epoch': 0.04}
+
4%|▍ | 454/11952 [46:09<18:49:31, 5.89s/it]
4%|▍ | 455/11952 [46:15<18:35:29, 5.82s/it]
{'loss': 0.5467, 'learning_rate': 1.9996616267285104e-05, 'epoch': 0.04}
+
4%|▍ | 455/11952 [46:15<18:35:29, 5.82s/it]
4%|▍ | 456/11952 [46:20<18:40:27, 5.85s/it]
{'loss': 0.5239, 'learning_rate': 1.9996545409775286e-05, 'epoch': 0.04}
+
4%|▍ | 456/11952 [46:20<18:40:27, 5.85s/it]
4%|▍ | 457/11952 [46:26<18:49:18, 5.89s/it]
{'loss': 0.5296, 'learning_rate': 1.9996473818160752e-05, 'epoch': 0.04}
+
4%|▍ | 457/11952 [46:26<18:49:18, 5.89s/it]
4%|▍ | 458/11952 [46:32<18:52:19, 5.91s/it]
{'loss': 0.5514, 'learning_rate': 1.999640149244676e-05, 'epoch': 0.04}
+
4%|▍ | 458/11952 [46:32<18:52:19, 5.91s/it]
4%|▍ | 459/11952 [46:38<18:39:25, 5.84s/it]
{'loss': 0.5196, 'learning_rate': 1.9996328432638622e-05, 'epoch': 0.04}
+
4%|▍ | 459/11952 [46:38<18:39:25, 5.84s/it]
4%|▍ | 460/11952 [46:44<18:38:26, 5.84s/it]
{'loss': 0.5297, 'learning_rate': 1.9996254638741702e-05, 'epoch': 0.04}
+
4%|▍ | 460/11952 [46:44<18:38:26, 5.84s/it]
4%|▍ | 461/11952 [46:50<18:32:20, 5.81s/it]
{'loss': 0.5309, 'learning_rate': 1.999618011076142e-05, 'epoch': 0.04}
+
4%|▍ | 461/11952 [46:50<18:32:20, 5.81s/it]
4%|▍ | 462/11952 [46:56<18:34:30, 5.82s/it]
{'loss': 0.5313, 'learning_rate': 1.9996104848703243e-05, 'epoch': 0.04}
+
4%|▍ | 462/11952 [46:56<18:34:30, 5.82s/it]
4%|▍ | 463/11952 [47:02<18:55:38, 5.93s/it]
{'loss': 0.5292, 'learning_rate': 1.9996028852572705e-05, 'epoch': 0.04}
+
4%|▍ | 463/11952 [47:02<18:55:38, 5.93s/it]
4%|▍ | 464/11952 [47:08<18:54:51, 5.93s/it]
{'loss': 0.5368, 'learning_rate': 1.9995952122375385e-05, 'epoch': 0.04}
+
4%|▍ | 464/11952 [47:08<18:54:51, 5.93s/it]
4%|▍ | 465/11952 [47:14<19:09:59, 6.01s/it]
{'loss': 0.5373, 'learning_rate': 1.9995874658116917e-05, 'epoch': 0.04}
+
4%|▍ | 465/11952 [47:14<19:09:59, 6.01s/it]
4%|▍ | 466/11952 [47:20<19:10:08, 6.01s/it]
{'loss': 0.5392, 'learning_rate': 1.999579645980299e-05, 'epoch': 0.04}
+
4%|▍ | 466/11952 [47:20<19:10:08, 6.01s/it]
4%|▍ | 467/11952 [47:26<19:21:23, 6.07s/it]
{'loss': 0.5315, 'learning_rate': 1.9995717527439348e-05, 'epoch': 0.04}
+
4%|▍ | 467/11952 [47:26<19:21:23, 6.07s/it]
4%|▍ | 468/11952 [47:32<18:58:45, 5.95s/it]
{'loss': 0.5325, 'learning_rate': 1.9995637861031786e-05, 'epoch': 0.04}
+
4%|▍ | 468/11952 [47:32<18:58:45, 5.95s/it]
4%|▍ | 469/11952 [47:38<18:56:04, 5.94s/it]
{'loss': 0.5468, 'learning_rate': 1.9995557460586153e-05, 'epoch': 0.04}
+
4%|▍ | 469/11952 [47:38<18:56:04, 5.94s/it]
4%|▍ | 470/11952 [47:43<18:45:29, 5.88s/it]
{'loss': 0.5525, 'learning_rate': 1.9995476326108355e-05, 'epoch': 0.04}
+
4%|▍ | 470/11952 [47:43<18:45:29, 5.88s/it]
4%|▍ | 471/11952 [47:49<18:34:15, 5.82s/it]
{'loss': 0.5133, 'learning_rate': 1.9995394457604354e-05, 'epoch': 0.04}
+
4%|▍ | 471/11952 [47:49<18:34:15, 5.82s/it]
4%|▍ | 472/11952 [47:55<18:23:46, 5.77s/it]
{'loss': 0.5228, 'learning_rate': 1.9995311855080155e-05, 'epoch': 0.04}
+
4%|▍ | 472/11952 [47:55<18:23:46, 5.77s/it]
4%|▍ | 473/11952 [48:01<18:42:19, 5.87s/it]
{'loss': 0.5394, 'learning_rate': 1.9995228518541828e-05, 'epoch': 0.04}
+
4%|▍ | 473/11952 [48:01<18:42:19, 5.87s/it]
4%|▍ | 474/11952 [48:07<18:37:46, 5.84s/it]
{'loss': 0.5449, 'learning_rate': 1.999514444799549e-05, 'epoch': 0.04}
+
4%|▍ | 474/11952 [48:07<18:37:46, 5.84s/it]
4%|▍ | 475/11952 [48:13<18:58:29, 5.95s/it]
{'loss': 0.5181, 'learning_rate': 1.9995059643447313e-05, 'epoch': 0.04}
+
4%|▍ | 475/11952 [48:13<18:58:29, 5.95s/it]
4%|▍ | 476/11952 [48:19<18:57:35, 5.95s/it]
{'loss': 0.533, 'learning_rate': 1.9994974104903536e-05, 'epoch': 0.04}
+
4%|▍ | 476/11952 [48:19<18:57:35, 5.95s/it]
4%|▍ | 477/11952 [48:25<19:08:11, 6.00s/it]
{'loss': 0.5344, 'learning_rate': 1.999488783237043e-05, 'epoch': 0.04}
+
4%|▍ | 477/11952 [48:25<19:08:11, 6.00s/it]
4%|▍ | 478/11952 [48:31<18:47:34, 5.90s/it]
{'loss': 0.5248, 'learning_rate': 1.999480082585433e-05, 'epoch': 0.04}
+
4%|▍ | 478/11952 [48:31<18:47:34, 5.90s/it]
4%|▍ | 479/11952 [48:37<18:56:30, 5.94s/it]
{'loss': 0.5394, 'learning_rate': 1.999471308536163e-05, 'epoch': 0.04}
+
4%|▍ | 479/11952 [48:37<18:56:30, 5.94s/it]
4%|▍ | 480/11952 [48:43<18:57:38, 5.95s/it]
{'loss': 0.5263, 'learning_rate': 1.9994624610898778e-05, 'epoch': 0.04}
+
4%|▍ | 480/11952 [48:43<18:57:38, 5.95s/it]
4%|▍ | 481/11952 [48:49<19:06:46, 6.00s/it]
{'loss': 0.5065, 'learning_rate': 1.999453540247226e-05, 'epoch': 0.04}
+
4%|▍ | 481/11952 [48:49<19:06:46, 6.00s/it]
4%|▍ | 482/11952 [48:54<18:58:19, 5.95s/it]
{'loss': 0.5423, 'learning_rate': 1.9994445460088635e-05, 'epoch': 0.04}
+
4%|▍ | 482/11952 [48:54<18:58:19, 5.95s/it]
4%|▍ | 483/11952 [49:00<18:42:58, 5.87s/it]
{'loss': 0.5219, 'learning_rate': 1.9994354783754504e-05, 'epoch': 0.04}
+
4%|▍ | 483/11952 [49:00<18:42:58, 5.87s/it]
4%|▍ | 484/11952 [49:06<18:37:48, 5.85s/it]
{'loss': 0.5298, 'learning_rate': 1.9994263373476526e-05, 'epoch': 0.04}
+
4%|▍ | 484/11952 [49:06<18:37:48, 5.85s/it]
4%|▍ | 485/11952 [49:12<19:04:28, 5.99s/it]
{'loss': 0.5212, 'learning_rate': 1.9994171229261417e-05, 'epoch': 0.04}
+
4%|▍ | 485/11952 [49:12<19:04:28, 5.99s/it]
4%|▍ | 486/11952 [49:18<18:50:17, 5.91s/it]
{'loss': 0.5283, 'learning_rate': 1.999407835111594e-05, 'epoch': 0.04}
+
4%|▍ | 486/11952 [49:18<18:50:17, 5.91s/it]
4%|▍ | 487/11952 [49:24<18:48:50, 5.91s/it]
{'loss': 0.5377, 'learning_rate': 1.999398473904692e-05, 'epoch': 0.04}
+
4%|▍ | 487/11952 [49:24<18:48:50, 5.91s/it]
4%|▍ | 488/11952 [49:30<19:13:15, 6.04s/it]
{'loss': 0.536, 'learning_rate': 1.999389039306123e-05, 'epoch': 0.04}
+
4%|▍ | 488/11952 [49:30<19:13:15, 6.04s/it]
4%|▍ | 489/11952 [49:36<18:44:47, 5.89s/it]
{'loss': 0.5229, 'learning_rate': 1.9993795313165795e-05, 'epoch': 0.04}
+
4%|▍ | 489/11952 [49:36<18:44:47, 5.89s/it]
4%|▍ | 490/11952 [49:42<18:45:59, 5.89s/it]
{'loss': 0.5259, 'learning_rate': 1.99936994993676e-05, 'epoch': 0.04}
+
4%|▍ | 490/11952 [49:42<18:45:59, 5.89s/it]
4%|▍ | 491/11952 [49:47<18:23:41, 5.78s/it]
{'loss': 0.5236, 'learning_rate': 1.999360295167368e-05, 'epoch': 0.04}
+
4%|▍ | 491/11952 [49:47<18:23:41, 5.78s/it]
4%|▍ | 492/11952 [49:53<18:17:00, 5.74s/it]
{'loss': 0.5245, 'learning_rate': 1.9993505670091123e-05, 'epoch': 0.04}
+
4%|▍ | 492/11952 [49:53<18:17:00, 5.74s/it]
4%|▍ | 493/11952 [49:59<18:26:17, 5.79s/it]
{'loss': 0.5348, 'learning_rate': 1.999340765462708e-05, 'epoch': 0.04}
+
4%|▍ | 493/11952 [49:59<18:26:17, 5.79s/it]
4%|▍ | 494/11952 [50:04<18:13:55, 5.73s/it]
{'loss': 0.5415, 'learning_rate': 1.9993308905288745e-05, 'epoch': 0.04}
+
4%|▍ | 494/11952 [50:04<18:13:55, 5.73s/it]
4%|▍ | 495/11952 [50:10<18:19:30, 5.76s/it]
{'loss': 0.5391, 'learning_rate': 1.9993209422083367e-05, 'epoch': 0.04}
+
4%|▍ | 495/11952 [50:10<18:19:30, 5.76s/it]
4%|▍ | 496/11952 [50:16<18:10:40, 5.71s/it]
{'loss': 0.5202, 'learning_rate': 1.999310920501825e-05, 'epoch': 0.04}
+
4%|▍ | 496/11952 [50:16<18:10:40, 5.71s/it]
4%|▍ | 497/11952 [50:22<18:20:18, 5.76s/it]
{'loss': 0.5172, 'learning_rate': 1.9993008254100765e-05, 'epoch': 0.04}
+
4%|▍ | 497/11952 [50:22<18:20:18, 5.76s/it]
4%|▍ | 498/11952 [50:28<18:28:15, 5.81s/it]
{'loss': 0.534, 'learning_rate': 1.9992906569338314e-05, 'epoch': 0.04}
+
4%|▍ | 498/11952 [50:28<18:28:15, 5.81s/it]
4%|▍ | 499/11952 [50:33<18:14:45, 5.74s/it]
{'loss': 0.5294, 'learning_rate': 1.999280415073837e-05, 'epoch': 0.04}
+
4%|▍ | 499/11952 [50:33<18:14:45, 5.74s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+37 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+16 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
4%|▍ | 500/11952 [50:39<18:33:10, 5.83s/it]
{'loss': 0.5486, 'learning_rate': 1.9992700998308453e-05, 'epoch': 0.04}
+
4%|▍ | 500/11952 [50:39<18:33:10, 5.83s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
4%|▍ | 501/11952 [51:06<38:58:26, 12.25s/it]
{'loss': 0.5134, 'learning_rate': 1.9992597112056134e-05, 'epoch': 0.04}
+
4%|▍ | 501/11952 [51:06<38:58:26, 12.25s/it]
4%|▍ | 502/11952 [51:12<32:51:44, 10.33s/it]
{'loss': 0.5241, 'learning_rate': 1.9992492491989045e-05, 'epoch': 0.04}
+
4%|▍ | 502/11952 [51:12<32:51:44, 10.33s/it]
4%|▍ | 503/11952 [51:18<28:35:23, 8.99s/it]
{'loss': 0.528, 'learning_rate': 1.999238713811487e-05, 'epoch': 0.04}
+
4%|▍ | 503/11952 [51:18<28:35:23, 8.99s/it]
4%|▍ | 504/11952 [51:24<25:31:27, 8.03s/it]
{'loss': 0.5463, 'learning_rate': 1.999228105044135e-05, 'epoch': 0.04}
+
4%|▍ | 504/11952 [51:24<25:31:27, 8.03s/it]
4%|▍ | 505/11952 [51:30<23:25:26, 7.37s/it]
{'loss': 0.5119, 'learning_rate': 1.9992174228976265e-05, 'epoch': 0.04}
+
4%|▍ | 505/11952 [51:30<23:25:26, 7.37s/it]
4%|▍ | 506/11952 [51:36<22:01:00, 6.92s/it]
{'loss': 0.5352, 'learning_rate': 1.999206667372747e-05, 'epoch': 0.04}
+
4%|▍ | 506/11952 [51:36<22:01:00, 6.92s/it]
4%|▍ | 507/11952 [51:42<21:12:21, 6.67s/it]
{'loss': 0.5365, 'learning_rate': 1.9991958384702855e-05, 'epoch': 0.04}
+
4%|▍ | 507/11952 [51:42<21:12:21, 6.67s/it]
4%|▍ | 508/11952 [51:47<20:19:35, 6.39s/it]
{'loss': 0.5205, 'learning_rate': 1.999184936191038e-05, 'epoch': 0.04}
+
4%|▍ | 508/11952 [51:47<20:19:35, 6.39s/it]
4%|▍ | 509/11952 [51:53<19:57:45, 6.28s/it]
{'loss': 0.5034, 'learning_rate': 1.9991739605358042e-05, 'epoch': 0.04}
+
4%|▍ | 509/11952 [51:53<19:57:45, 6.28s/it]
4%|▍ | 510/11952 [51:59<19:26:11, 6.12s/it]
{'loss': 0.5319, 'learning_rate': 1.9991629115053908e-05, 'epoch': 0.04}
+
4%|▍ | 510/11952 [51:59<19:26:11, 6.12s/it]
4%|▍ | 511/11952 [52:05<18:55:53, 5.96s/it]
{'loss': 0.5195, 'learning_rate': 1.999151789100609e-05, 'epoch': 0.04}
+
4%|▍ | 511/11952 [52:05<18:55:53, 5.96s/it]
4%|▍ | 512/11952 [52:11<18:59:37, 5.98s/it]
{'loss': 0.5319, 'learning_rate': 1.9991405933222758e-05, 'epoch': 0.04}
+
4%|▍ | 512/11952 [52:11<18:59:37, 5.98s/it]
4%|▍ | 513/11952 [52:17<18:46:53, 5.91s/it]
{'loss': 0.5359, 'learning_rate': 1.9991293241712128e-05, 'epoch': 0.04}
+
4%|▍ | 513/11952 [52:17<18:46:53, 5.91s/it]
4%|▍ | 514/11952 [52:22<18:27:06, 5.81s/it]
{'loss': 0.5251, 'learning_rate': 1.999117981648248e-05, 'epoch': 0.04}
+
4%|▍ | 514/11952 [52:22<18:27:06, 5.81s/it]
4%|▍ | 515/11952 [52:28<18:30:32, 5.83s/it]
{'loss': 0.5134, 'learning_rate': 1.9991065657542146e-05, 'epoch': 0.04}
+
4%|▍ | 515/11952 [52:28<18:30:32, 5.83s/it]
4%|▍ | 516/11952 [52:34<18:20:37, 5.77s/it]
{'loss': 0.5365, 'learning_rate': 1.9990950764899502e-05, 'epoch': 0.04}
+
4%|▍ | 516/11952 [52:34<18:20:37, 5.77s/it]
4%|▍ | 517/11952 [52:40<18:37:44, 5.86s/it]
{'loss': 0.5388, 'learning_rate': 1.999083513856299e-05, 'epoch': 0.04}
+
4%|▍ | 517/11952 [52:40<18:37:44, 5.86s/it]
4%|▍ | 518/11952 [52:46<18:36:21, 5.86s/it]
{'loss': 0.5144, 'learning_rate': 1.99907187785411e-05, 'epoch': 0.04}
+
4%|▍ | 518/11952 [52:46<18:36:21, 5.86s/it]
4%|▍ | 519/11952 [52:51<18:23:02, 5.79s/it]
{'loss': 0.5203, 'learning_rate': 1.9990601684842385e-05, 'epoch': 0.04}
+
4%|▍ | 519/11952 [52:51<18:23:02, 5.79s/it]
4%|▍ | 520/11952 [52:57<18:17:11, 5.76s/it]
{'loss': 0.5384, 'learning_rate': 1.9990483857475428e-05, 'epoch': 0.04}
+
4%|▍ | 520/11952 [52:57<18:17:11, 5.76s/it]
4%|▍ | 521/11952 [53:03<18:17:50, 5.76s/it]
{'loss': 0.5309, 'learning_rate': 1.9990365296448892e-05, 'epoch': 0.04}
+
4%|▍ | 521/11952 [53:03<18:17:50, 5.76s/it]
4%|▍ | 522/11952 [53:09<18:38:46, 5.87s/it]
{'loss': 0.5405, 'learning_rate': 1.999024600177148e-05, 'epoch': 0.04}
+
4%|▍ | 522/11952 [53:09<18:38:46, 5.87s/it]
4%|▍ | 523/11952 [53:15<18:29:48, 5.83s/it]
{'loss': 0.5271, 'learning_rate': 1.9990125973451956e-05, 'epoch': 0.04}
+
4%|▍ | 523/11952 [53:15<18:29:48, 5.83s/it]
4%|▍ | 524/11952 [53:20<18:22:56, 5.79s/it]
{'loss': 0.5266, 'learning_rate': 1.9990005211499137e-05, 'epoch': 0.04}
+
4%|▍ | 524/11952 [53:20<18:22:56, 5.79s/it]
4%|▍ | 525/11952 [53:26<18:32:03, 5.84s/it]
{'loss': 0.521, 'learning_rate': 1.998988371592188e-05, 'epoch': 0.04}
+
4%|▍ | 525/11952 [53:26<18:32:03, 5.84s/it]
4%|▍ | 526/11952 [53:32<18:44:24, 5.90s/it]
{'loss': 0.5432, 'learning_rate': 1.998976148672912e-05, 'epoch': 0.04}
+
4%|▍ | 526/11952 [53:32<18:44:24, 5.90s/it]
4%|▍ | 527/11952 [53:38<18:57:32, 5.97s/it]
{'loss': 0.5378, 'learning_rate': 1.998963852392982e-05, 'epoch': 0.04}
+
4%|▍ | 527/11952 [53:38<18:57:32, 5.97s/it]
4%|▍ | 528/11952 [53:44<18:48:32, 5.93s/it]
{'loss': 0.5218, 'learning_rate': 1.998951482753302e-05, 'epoch': 0.04}
+
4%|▍ | 528/11952 [53:44<18:48:32, 5.93s/it]
4%|▍ | 529/11952 [53:50<19:00:05, 5.99s/it]
{'loss': 0.5309, 'learning_rate': 1.99893903975478e-05, 'epoch': 0.04}
+
4%|▍ | 529/11952 [53:50<19:00:05, 5.99s/it]
4%|▍ | 530/11952 [53:56<18:40:59, 5.89s/it]
{'loss': 0.5238, 'learning_rate': 1.99892652339833e-05, 'epoch': 0.04}
+
4%|▍ | 530/11952 [53:56<18:40:59, 5.89s/it]
4%|▍ | 531/11952 [54:02<18:54:18, 5.96s/it]
{'loss': 0.5364, 'learning_rate': 1.9989139336848708e-05, 'epoch': 0.04}
+
4%|▍ | 531/11952 [54:02<18:54:18, 5.96s/it]
4%|▍ | 532/11952 [54:08<18:44:51, 5.91s/it]
{'loss': 0.5396, 'learning_rate': 1.9989012706153273e-05, 'epoch': 0.04}
+
4%|▍ | 532/11952 [54:08<18:44:51, 5.91s/it]
4%|▍ | 533/11952 [54:14<18:40:51, 5.89s/it]
{'loss': 0.5236, 'learning_rate': 1.9988885341906292e-05, 'epoch': 0.04}
+
4%|▍ | 533/11952 [54:14<18:40:51, 5.89s/it]
4%|▍ | 534/11952 [54:20<18:40:34, 5.89s/it]
{'loss': 0.5107, 'learning_rate': 1.9988757244117118e-05, 'epoch': 0.04}
+
4%|▍ | 534/11952 [54:20<18:40:34, 5.89s/it]
4%|▍ | 535/11952 [54:25<18:20:20, 5.78s/it]
{'loss': 0.5068, 'learning_rate': 1.9988628412795158e-05, 'epoch': 0.04}
+
4%|▍ | 535/11952 [54:25<18:20:20, 5.78s/it]
4%|▍ | 536/11952 [54:31<18:11:11, 5.74s/it]
{'loss': 0.5272, 'learning_rate': 1.9988498847949872e-05, 'epoch': 0.04}
+
4%|▍ | 536/11952 [54:31<18:11:11, 5.74s/it]
4%|▍ | 537/11952 [54:37<18:28:15, 5.83s/it]
{'loss': 0.5193, 'learning_rate': 1.9988368549590778e-05, 'epoch': 0.04}
+
4%|▍ | 537/11952 [54:37<18:28:15, 5.83s/it]
5%|▍ | 538/11952 [54:43<18:27:52, 5.82s/it]
{'loss': 0.5314, 'learning_rate': 1.998823751772744e-05, 'epoch': 0.05}
+
5%|▍ | 538/11952 [54:43<18:27:52, 5.82s/it]
5%|▍ | 539/11952 [54:49<18:37:19, 5.87s/it]
{'loss': 0.524, 'learning_rate': 1.9988105752369487e-05, 'epoch': 0.05}
+
5%|▍ | 539/11952 [54:49<18:37:19, 5.87s/it]
5%|▍ | 540/11952 [54:55<18:48:51, 5.94s/it]
{'loss': 0.51, 'learning_rate': 1.998797325352659e-05, 'epoch': 0.05}
+
5%|▍ | 540/11952 [54:55<18:48:51, 5.94s/it]
5%|▍ | 541/11952 [55:01<18:52:32, 5.95s/it]
{'loss': 0.5412, 'learning_rate': 1.9987840021208477e-05, 'epoch': 0.05}
+
5%|▍ | 541/11952 [55:01<18:52:32, 5.95s/it]
5%|▍ | 542/11952 [55:07<18:43:55, 5.91s/it]
{'loss': 0.5195, 'learning_rate': 1.9987706055424935e-05, 'epoch': 0.05}
+
5%|▍ | 542/11952 [55:07<18:43:55, 5.91s/it]
5%|▍ | 543/11952 [55:13<19:10:05, 6.05s/it]
{'loss': 0.5251, 'learning_rate': 1.9987571356185807e-05, 'epoch': 0.05}
+
5%|▍ | 543/11952 [55:13<19:10:05, 6.05s/it]
5%|▍ | 544/11952 [55:19<18:58:02, 5.99s/it]
{'loss': 0.5078, 'learning_rate': 1.9987435923500978e-05, 'epoch': 0.05}
+
5%|▍ | 544/11952 [55:19<18:58:02, 5.99s/it]
5%|▍ | 545/11952 [55:25<19:09:44, 6.05s/it]
{'loss': 0.5461, 'learning_rate': 1.9987299757380393e-05, 'epoch': 0.05}
+
5%|▍ | 545/11952 [55:25<19:09:44, 6.05s/it]
5%|▍ | 546/11952 [55:31<18:48:51, 5.94s/it]
{'loss': 0.5278, 'learning_rate': 1.998716285783406e-05, 'epoch': 0.05}
+
5%|▍ | 546/11952 [55:31<18:48:51, 5.94s/it]
5%|▍ | 547/11952 [55:36<18:24:42, 5.81s/it]
{'loss': 0.5154, 'learning_rate': 1.998702522487202e-05, 'epoch': 0.05}
+
5%|▍ | 547/11952 [55:36<18:24:42, 5.81s/it]
5%|▍ | 548/11952 [55:42<18:12:10, 5.75s/it]
{'loss': 0.5246, 'learning_rate': 1.998688685850439e-05, 'epoch': 0.05}
+
5%|▍ | 548/11952 [55:42<18:12:10, 5.75s/it]
5%|▍ | 549/11952 [55:47<18:08:20, 5.73s/it]
{'loss': 0.5102, 'learning_rate': 1.998674775874133e-05, 'epoch': 0.05}
+
5%|▍ | 549/11952 [55:47<18:08:20, 5.73s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
5%|▍ | 550/11952 [55:53<18:28:27, 5.83s/it]
{'loss': 0.5195, 'learning_rate': 1.9986607925593046e-05, 'epoch': 0.05}
+
5%|▍ | 550/11952 [55:53<18:28:27, 5.83s/it]
5%|▍ | 551/11952 [55:59<18:35:31, 5.87s/it]
{'loss': 0.5231, 'learning_rate': 1.998646735906982e-05, 'epoch': 0.05}
+
5%|▍ | 551/11952 [55:59<18:35:31, 5.87s/it]
5%|▍ | 552/11952 [56:05<18:35:39, 5.87s/it]
{'loss': 0.5364, 'learning_rate': 1.9986326059181965e-05, 'epoch': 0.05}
+
5%|▍ | 552/11952 [56:05<18:35:39, 5.87s/it]
5%|▍ | 553/11952 [56:11<18:40:58, 5.90s/it]
{'loss': 0.5223, 'learning_rate': 1.998618402593986e-05, 'epoch': 0.05}
+
5%|▍ | 553/11952 [56:11<18:40:58, 5.90s/it]
5%|▍ | 554/11952 [56:17<18:35:15, 5.87s/it]
{'loss': 0.5358, 'learning_rate': 1.9986041259353937e-05, 'epoch': 0.05}
+
5%|▍ | 554/11952 [56:17<18:35:15, 5.87s/it]
5%|▍ | 555/11952 [56:23<18:35:46, 5.87s/it]
{'loss': 0.5318, 'learning_rate': 1.9985897759434677e-05, 'epoch': 0.05}
+
5%|▍ | 555/11952 [56:23<18:35:46, 5.87s/it]
5%|▍ | 556/11952 [56:29<18:27:15, 5.83s/it]
{'loss': 0.5339, 'learning_rate': 1.998575352619262e-05, 'epoch': 0.05}
+
5%|▍ | 556/11952 [56:29<18:27:15, 5.83s/it]
5%|▍ | 557/11952 [56:35<18:37:06, 5.88s/it]
{'loss': 0.5275, 'learning_rate': 1.9985608559638364e-05, 'epoch': 0.05}
+
5%|▍ | 557/11952 [56:35<18:37:06, 5.88s/it]
5%|▍ | 558/11952 [56:40<18:23:54, 5.81s/it]
{'loss': 0.5343, 'learning_rate': 1.9985462859782544e-05, 'epoch': 0.05}
+
5%|▍ | 558/11952 [56:40<18:23:54, 5.81s/it]
5%|▍ | 559/11952 [56:46<18:17:20, 5.78s/it]
{'loss': 0.5217, 'learning_rate': 1.9985316426635863e-05, 'epoch': 0.05}
+
5%|▍ | 559/11952 [56:46<18:17:20, 5.78s/it]
5%|▍ | 560/11952 [56:52<18:32:39, 5.86s/it]
{'loss': 0.5284, 'learning_rate': 1.9985169260209075e-05, 'epoch': 0.05}
+
5%|▍ | 560/11952 [56:52<18:32:39, 5.86s/it]
5%|▍ | 561/11952 [56:58<18:53:49, 5.97s/it]
{'loss': 0.5254, 'learning_rate': 1.998502136051299e-05, 'epoch': 0.05}
+
5%|▍ | 561/11952 [56:58<18:53:49, 5.97s/it]
5%|▍ | 562/11952 [57:04<18:51:01, 5.96s/it]
{'loss': 0.5316, 'learning_rate': 1.9984872727558468e-05, 'epoch': 0.05}
+
5%|▍ | 562/11952 [57:04<18:51:01, 5.96s/it]
5%|▍ | 563/11952 [57:10<18:59:39, 6.00s/it]
{'loss': 0.525, 'learning_rate': 1.998472336135642e-05, 'epoch': 0.05}
+
5%|▍ | 563/11952 [57:10<18:59:39, 6.00s/it]
5%|▍ | 564/11952 [57:16<18:57:43, 5.99s/it]
{'loss': 0.5241, 'learning_rate': 1.9984573261917825e-05, 'epoch': 0.05}
+
5%|▍ | 564/11952 [57:16<18:57:43, 5.99s/it]
5%|▍ | 565/11952 [57:22<18:35:53, 5.88s/it]
{'loss': 0.5233, 'learning_rate': 1.998442242925369e-05, 'epoch': 0.05}
+
5%|▍ | 565/11952 [57:22<18:35:53, 5.88s/it]
5%|▍ | 566/11952 [57:28<18:38:02, 5.89s/it]
{'loss': 0.5282, 'learning_rate': 1.9984270863375105e-05, 'epoch': 0.05}
+
5%|▍ | 566/11952 [57:28<18:38:02, 5.89s/it]
5%|▍ | 567/11952 [57:34<18:32:10, 5.86s/it]
{'loss': 0.5263, 'learning_rate': 1.9984118564293197e-05, 'epoch': 0.05}
+
5%|▍ | 567/11952 [57:34<18:32:10, 5.86s/it]
5%|▍ | 568/11952 [57:40<18:49:02, 5.95s/it]
{'loss': 0.5201, 'learning_rate': 1.9983965532019142e-05, 'epoch': 0.05}
+
5%|▍ | 568/11952 [57:40<18:49:02, 5.95s/it]
5%|▍ | 569/11952 [57:46<18:35:36, 5.88s/it]
{'loss': 0.5317, 'learning_rate': 1.998381176656419e-05, 'epoch': 0.05}
+
5%|▍ | 569/11952 [57:46<18:35:36, 5.88s/it]
5%|▍ | 570/11952 [57:51<18:28:52, 5.85s/it]
{'loss': 0.5263, 'learning_rate': 1.9983657267939627e-05, 'epoch': 0.05}
+
5%|▍ | 570/11952 [57:51<18:28:52, 5.85s/it]
5%|▍ | 571/11952 [57:57<18:19:38, 5.80s/it]
{'loss': 0.5158, 'learning_rate': 1.99835020361568e-05, 'epoch': 0.05}
+
5%|▍ | 571/11952 [57:57<18:19:38, 5.80s/it]
5%|▍ | 572/11952 [58:03<18:16:19, 5.78s/it]
{'loss': 0.5344, 'learning_rate': 1.9983346071227107e-05, 'epoch': 0.05}
+
5%|▍ | 572/11952 [58:03<18:16:19, 5.78s/it]
5%|▍ | 573/11952 [58:09<18:34:04, 5.87s/it]
{'loss': 0.5306, 'learning_rate': 1.9983189373162003e-05, 'epoch': 0.05}
+
5%|▍ | 573/11952 [58:09<18:34:04, 5.87s/it]
5%|▍ | 574/11952 [58:15<18:31:30, 5.86s/it]
{'loss': 0.5402, 'learning_rate': 1.9983031941972994e-05, 'epoch': 0.05}
+
5%|▍ | 574/11952 [58:15<18:31:30, 5.86s/it]
5%|▍ | 575/11952 [58:20<18:20:44, 5.81s/it]
{'loss': 0.5339, 'learning_rate': 1.998287377767164e-05, 'epoch': 0.05}
+
5%|▍ | 575/11952 [58:20<18:20:44, 5.81s/it]
5%|▍ | 576/11952 [58:26<18:09:30, 5.75s/it]
{'loss': 0.5216, 'learning_rate': 1.9982714880269557e-05, 'epoch': 0.05}
+
5%|▍ | 576/11952 [58:26<18:09:30, 5.75s/it]
5%|▍ | 577/11952 [58:32<18:22:31, 5.82s/it]
{'loss': 0.5053, 'learning_rate': 1.998255524977842e-05, 'epoch': 0.05}
+
5%|▍ | 577/11952 [58:32<18:22:31, 5.82s/it]
5%|▍ | 578/11952 [58:38<18:18:35, 5.80s/it]
{'loss': 0.5199, 'learning_rate': 1.9982394886209943e-05, 'epoch': 0.05}
+
5%|▍ | 578/11952 [58:38<18:18:35, 5.80s/it]
5%|▍ | 579/11952 [58:44<18:24:29, 5.83s/it]
{'loss': 0.5293, 'learning_rate': 1.9982233789575904e-05, 'epoch': 0.05}
+
5%|▍ | 579/11952 [58:44<18:24:29, 5.83s/it]
5%|▍ | 580/11952 [58:49<18:21:11, 5.81s/it]
{'loss': 0.5093, 'learning_rate': 1.9982071959888138e-05, 'epoch': 0.05}
+
5%|▍ | 580/11952 [58:49<18:21:11, 5.81s/it]
5%|▍ | 581/11952 [58:55<18:24:58, 5.83s/it]
{'loss': 0.5355, 'learning_rate': 1.998190939715852e-05, 'epoch': 0.05}
+
5%|▍ | 581/11952 [58:55<18:24:58, 5.83s/it]
5%|▍ | 582/11952 [59:01<18:32:31, 5.87s/it]
{'loss': 0.5191, 'learning_rate': 1.9981746101399e-05, 'epoch': 0.05}
+
5%|▍ | 582/11952 [59:01<18:32:31, 5.87s/it]
5%|▍ | 583/11952 [59:07<18:18:59, 5.80s/it]
{'loss': 0.5267, 'learning_rate': 1.998158207262156e-05, 'epoch': 0.05}
+
5%|▍ | 583/11952 [59:07<18:18:59, 5.80s/it]
5%|▍ | 584/11952 [59:13<18:25:04, 5.83s/it]
{'loss': 0.5117, 'learning_rate': 1.998141731083825e-05, 'epoch': 0.05}
+
5%|▍ | 584/11952 [59:13<18:25:04, 5.83s/it]
5%|▍ | 585/11952 [59:18<18:18:20, 5.80s/it]
{'loss': 0.5119, 'learning_rate': 1.9981251816061168e-05, 'epoch': 0.05}
+
5%|▍ | 585/11952 [59:18<18:18:20, 5.80s/it]
5%|▍ | 586/11952 [59:24<18:21:22, 5.81s/it]
{'loss': 0.518, 'learning_rate': 1.9981085588302468e-05, 'epoch': 0.05}
+
5%|▍ | 586/11952 [59:24<18:21:22, 5.81s/it]
5%|▍ | 587/11952 [59:30<18:16:49, 5.79s/it]
{'loss': 0.5203, 'learning_rate': 1.998091862757436e-05, 'epoch': 0.05}
+
5%|▍ | 587/11952 [59:30<18:16:49, 5.79s/it]
5%|▍ | 588/11952 [59:36<18:18:19, 5.80s/it]
{'loss': 0.5326, 'learning_rate': 1.9980750933889098e-05, 'epoch': 0.05}
+
5%|▍ | 588/11952 [59:36<18:18:19, 5.80s/it]
5%|▍ | 589/11952 [59:42<18:46:07, 5.95s/it]
{'loss': 0.5318, 'learning_rate': 1.9980582507259e-05, 'epoch': 0.05}
+
5%|▍ | 589/11952 [59:42<18:46:07, 5.95s/it]
5%|▍ | 590/11952 [59:48<18:23:58, 5.83s/it]
{'loss': 0.5275, 'learning_rate': 1.998041334769644e-05, 'epoch': 0.05}
+
5%|▍ | 590/11952 [59:48<18:23:58, 5.83s/it]
5%|▍ | 591/11952 [59:54<18:39:47, 5.91s/it]
{'loss': 0.5346, 'learning_rate': 1.998024345521383e-05, 'epoch': 0.05}
+
5%|▍ | 591/11952 [59:54<18:39:47, 5.91s/it]
5%|▍ | 592/11952 [1:00:00<18:38:47, 5.91s/it]
{'loss': 0.5313, 'learning_rate': 1.9980072829823656e-05, 'epoch': 0.05}
+
5%|▍ | 592/11952 [1:00:00<18:38:47, 5.91s/it]
5%|▍ | 593/11952 [1:00:06<18:56:53, 6.01s/it]
{'loss': 0.5433, 'learning_rate': 1.9979901471538442e-05, 'epoch': 0.05}
+
5%|▍ | 593/11952 [1:00:06<18:56:53, 6.01s/it]
5%|▍ | 594/11952 [1:00:12<18:51:47, 5.98s/it]
{'loss': 0.5223, 'learning_rate': 1.997972938037077e-05, 'epoch': 0.05}
+
5%|▍ | 594/11952 [1:00:12<18:51:47, 5.98s/it]
5%|▍ | 595/11952 [1:00:17<18:25:35, 5.84s/it]
{'loss': 0.5244, 'learning_rate': 1.9979556556333283e-05, 'epoch': 0.05}
+
5%|▍ | 595/11952 [1:00:17<18:25:35, 5.84s/it]
5%|▍ | 596/11952 [1:00:23<18:27:56, 5.85s/it]
{'loss': 0.5391, 'learning_rate': 1.9979382999438672e-05, 'epoch': 0.05}
+
5%|▍ | 596/11952 [1:00:23<18:27:56, 5.85s/it]
5%|▍ | 597/11952 [1:00:29<18:25:40, 5.84s/it]
{'loss': 0.5366, 'learning_rate': 1.997920870969968e-05, 'epoch': 0.05}
+
5%|▍ | 597/11952 [1:00:29<18:25:40, 5.84s/it]
5%|▌ | 598/11952 [1:00:35<18:26:53, 5.85s/it]
{'loss': 0.518, 'learning_rate': 1.997903368712911e-05, 'epoch': 0.05}
+
5%|▌ | 598/11952 [1:00:35<18:26:53, 5.85s/it]
5%|▌ | 599/11952 [1:00:41<18:16:23, 5.79s/it]
{'loss': 0.5125, 'learning_rate': 1.9978857931739805e-05, 'epoch': 0.05}
+
5%|▌ | 599/11952 [1:00:41<18:16:23, 5.79s/it]7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+426 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
+0 AutoResumeHook: Checking whether to suspend...
+
5%|▌ | 600/11952 [1:00:47<18:28:32, 5.86s/it]
{'loss': 0.5062, 'learning_rate': 1.9978681443544687e-05, 'epoch': 0.05}
+
5%|▌ | 600/11952 [1:00:47<18:28:32, 5.86s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
5%|▌ | 601/11952 [1:01:19<43:09:12, 13.69s/it]
{'loss': 0.51, 'learning_rate': 1.9978504222556704e-05, 'epoch': 0.05}
+
5%|▌ | 601/11952 [1:01:19<43:09:12, 13.69s/it]
5%|▌ | 602/11952 [1:01:24<35:33:50, 11.28s/it]
{'loss': 0.5224, 'learning_rate': 1.9978326268788873e-05, 'epoch': 0.05}
+
5%|▌ | 602/11952 [1:01:24<35:33:50, 11.28s/it]
5%|▌ | 603/11952 [1:01:30<30:20:18, 9.62s/it]
{'loss': 0.5183, 'learning_rate': 1.9978147582254266e-05, 'epoch': 0.05}
+
5%|▌ | 603/11952 [1:01:30<30:20:18, 9.62s/it]
5%|▌ | 604/11952 [1:01:36<26:29:07, 8.40s/it]
{'loss': 0.529, 'learning_rate': 1.9977968162966e-05, 'epoch': 0.05}
+
5%|▌ | 604/11952 [1:01:36<26:29:07, 8.40s/it]
5%|▌ | 605/11952 [1:01:41<23:54:44, 7.59s/it]
{'loss': 0.5163, 'learning_rate': 1.997778801093726e-05, 'epoch': 0.05}
+
5%|▌ | 605/11952 [1:01:41<23:54:44, 7.59s/it]
5%|▌ | 606/11952 [1:01:47<22:12:06, 7.04s/it]
{'loss': 0.508, 'learning_rate': 1.9977607126181264e-05, 'epoch': 0.05}
+
5%|▌ | 606/11952 [1:01:47<22:12:06, 7.04s/it]
5%|▌ | 607/11952 [1:01:53<21:06:28, 6.70s/it]
{'loss': 0.5383, 'learning_rate': 1.9977425508711303e-05, 'epoch': 0.05}
+
5%|▌ | 607/11952 [1:01:53<21:06:28, 6.70s/it]
5%|▌ | 608/11952 [1:01:59<20:13:40, 6.42s/it]
{'loss': 0.5161, 'learning_rate': 1.997724315854071e-05, 'epoch': 0.05}
+
5%|▌ | 608/11952 [1:01:59<20:13:40, 6.42s/it]
5%|▌ | 609/11952 [1:02:04<19:38:07, 6.23s/it]
{'loss': 0.5294, 'learning_rate': 1.9977060075682878e-05, 'epoch': 0.05}
+
5%|▌ | 609/11952 [1:02:04<19:38:07, 6.23s/it]
5%|▌ | 610/11952 [1:02:10<19:18:58, 6.13s/it]
{'loss': 0.5113, 'learning_rate': 1.997687626015125e-05, 'epoch': 0.05}
+
5%|▌ | 610/11952 [1:02:10<19:18:58, 6.13s/it]
5%|▌ | 611/11952 [1:02:16<18:52:17, 5.99s/it]
{'loss': 0.525, 'learning_rate': 1.997669171195933e-05, 'epoch': 0.05}
+
5%|▌ | 611/11952 [1:02:16<18:52:17, 5.99s/it]
5%|▌ | 612/11952 [1:02:22<18:46:31, 5.96s/it]
{'loss': 0.5313, 'learning_rate': 1.9976506431120665e-05, 'epoch': 0.05}
+
5%|▌ | 612/11952 [1:02:22<18:46:31, 5.96s/it]
5%|▌ | 613/11952 [1:02:28<18:36:44, 5.91s/it]
{'loss': 0.5248, 'learning_rate': 1.9976320417648868e-05, 'epoch': 0.05}
+
5%|▌ | 613/11952 [1:02:28<18:36:44, 5.91s/it]
5%|▌ | 614/11952 [1:02:34<18:37:22, 5.91s/it]
{'loss': 0.537, 'learning_rate': 1.9976133671557587e-05, 'epoch': 0.05}
+
5%|▌ | 614/11952 [1:02:34<18:37:22, 5.91s/it]
5%|▌ | 615/11952 [1:02:39<18:32:20, 5.89s/it]
{'loss': 0.5232, 'learning_rate': 1.9975946192860544e-05, 'epoch': 0.05}
+
5%|▌ | 615/11952 [1:02:39<18:32:20, 5.89s/it]
5%|▌ | 616/11952 [1:02:46<18:49:42, 5.98s/it]
{'loss': 0.5132, 'learning_rate': 1.9975757981571512e-05, 'epoch': 0.05}
+
5%|▌ | 616/11952 [1:02:46<18:49:42, 5.98s/it]
5%|▌ | 617/11952 [1:02:51<18:40:51, 5.93s/it]
{'loss': 0.531, 'learning_rate': 1.99755690377043e-05, 'epoch': 0.05}
+
5%|▌ | 617/11952 [1:02:51<18:40:51, 5.93s/it]
5%|▌ | 618/11952 [1:02:57<18:20:11, 5.82s/it]
{'loss': 0.532, 'learning_rate': 1.997537936127279e-05, 'epoch': 0.05}
+
5%|▌ | 618/11952 [1:02:57<18:20:11, 5.82s/it]
5%|▌ | 619/11952 [1:03:03<18:36:32, 5.91s/it]
{'loss': 0.5399, 'learning_rate': 1.9975188952290915e-05, 'epoch': 0.05}
+
5%|▌ | 619/11952 [1:03:03<18:36:32, 5.91s/it]
5%|▌ | 620/11952 [1:03:09<18:26:44, 5.86s/it]
{'loss': 0.5195, 'learning_rate': 1.997499781077265e-05, 'epoch': 0.05}
+
5%|▌ | 620/11952 [1:03:09<18:26:44, 5.86s/it]
5%|▌ | 621/11952 [1:03:15<18:19:54, 5.82s/it]
{'loss': 0.5213, 'learning_rate': 1.997480593673203e-05, 'epoch': 0.05}
+
5%|▌ | 621/11952 [1:03:15<18:19:54, 5.82s/it]
5%|▌ | 622/11952 [1:03:21<18:24:01, 5.85s/it]
{'loss': 0.5198, 'learning_rate': 1.9974613330183156e-05, 'epoch': 0.05}
+
5%|▌ | 622/11952 [1:03:21<18:24:01, 5.85s/it]
5%|▌ | 623/11952 [1:03:26<18:28:20, 5.87s/it]
{'loss': 0.5242, 'learning_rate': 1.997441999114017e-05, 'epoch': 0.05}
+
5%|▌ | 623/11952 [1:03:26<18:28:20, 5.87s/it]
5%|▌ | 624/11952 [1:03:32<18:36:48, 5.92s/it]
{'loss': 0.5376, 'learning_rate': 1.9974225919617258e-05, 'epoch': 0.05}
+
5%|▌ | 624/11952 [1:03:32<18:36:48, 5.92s/it]
5%|▌ | 625/11952 [1:03:38<18:37:58, 5.92s/it]
{'loss': 0.521, 'learning_rate': 1.9974031115628688e-05, 'epoch': 0.05}
+
5%|▌ | 625/11952 [1:03:38<18:37:58, 5.92s/it]
5%|▌ | 626/11952 [1:03:45<18:55:02, 6.01s/it]
{'loss': 0.5179, 'learning_rate': 1.9973835579188753e-05, 'epoch': 0.05}
+
5%|▌ | 626/11952 [1:03:45<18:55:02, 6.01s/it]
5%|▌ | 627/11952 [1:03:50<18:40:28, 5.94s/it]
{'loss': 0.5341, 'learning_rate': 1.997363931031182e-05, 'epoch': 0.05}
+
5%|▌ | 627/11952 [1:03:50<18:40:28, 5.94s/it]
5%|▌ | 628/11952 [1:03:57<18:52:14, 6.00s/it]
{'loss': 0.4995, 'learning_rate': 1.9973442309012296e-05, 'epoch': 0.05}
+
5%|▌ | 628/11952 [1:03:57<18:52:14, 6.00s/it]
5%|▌ | 629/11952 [1:04:03<18:53:15, 6.01s/it]
{'loss': 0.5421, 'learning_rate': 1.9973244575304657e-05, 'epoch': 0.05}
+
5%|▌ | 629/11952 [1:04:03<18:53:15, 6.01s/it]
5%|▌ | 630/11952 [1:04:09<18:53:15, 6.01s/it]
{'loss': 0.5164, 'learning_rate': 1.9973046109203414e-05, 'epoch': 0.05}
+
5%|▌ | 630/11952 [1:04:09<18:53:15, 6.01s/it]
5%|▌ | 631/11952 [1:04:14<18:48:44, 5.98s/it]
{'loss': 0.5236, 'learning_rate': 1.9972846910723146e-05, 'epoch': 0.05}
+
5%|▌ | 631/11952 [1:04:14<18:48:44, 5.98s/it]
5%|▌ | 632/11952 [1:04:20<18:39:56, 5.94s/it]
{'loss': 0.5341, 'learning_rate': 1.9972646979878483e-05, 'epoch': 0.05}
+
5%|▌ | 632/11952 [1:04:20<18:39:56, 5.94s/it]
5%|▌ | 633/11952 [1:04:26<18:27:14, 5.87s/it]
{'loss': 0.5337, 'learning_rate': 1.9972446316684106e-05, 'epoch': 0.05}
+
5%|▌ | 633/11952 [1:04:26<18:27:14, 5.87s/it]
5%|▌ | 634/11952 [1:04:32<18:28:06, 5.87s/it]
{'loss': 0.5226, 'learning_rate': 1.9972244921154746e-05, 'epoch': 0.05}
+
5%|▌ | 634/11952 [1:04:32<18:28:06, 5.87s/it]
5%|▌ | 635/11952 [1:04:38<18:19:13, 5.83s/it]
{'loss': 0.5177, 'learning_rate': 1.9972042793305196e-05, 'epoch': 0.05}
+
5%|▌ | 635/11952 [1:04:38<18:19:13, 5.83s/it]
5%|▌ | 636/11952 [1:04:43<18:14:32, 5.80s/it]
{'loss': 0.5229, 'learning_rate': 1.9971839933150307e-05, 'epoch': 0.05}
+
5%|▌ | 636/11952 [1:04:43<18:14:32, 5.80s/it]
5%|▌ | 637/11952 [1:04:49<18:15:42, 5.81s/it]
{'loss': 0.513, 'learning_rate': 1.997163634070496e-05, 'epoch': 0.05}
+
5%|▌ | 637/11952 [1:04:49<18:15:42, 5.81s/it]
5%|▌ | 638/11952 [1:04:55<18:13:29, 5.80s/it]
{'loss': 0.5055, 'learning_rate': 1.9971432015984126e-05, 'epoch': 0.05}
+
5%|▌ | 638/11952 [1:04:55<18:13:29, 5.80s/it]
5%|▌ | 639/11952 [1:05:01<18:15:56, 5.81s/it]
{'loss': 0.4982, 'learning_rate': 1.9971226959002796e-05, 'epoch': 0.05}
+
5%|▌ | 639/11952 [1:05:01<18:15:56, 5.81s/it]
5%|▌ | 640/11952 [1:05:07<18:10:22, 5.78s/it]
{'loss': 0.5206, 'learning_rate': 1.9971021169776024e-05, 'epoch': 0.05}
+
5%|▌ | 640/11952 [1:05:07<18:10:22, 5.78s/it]
5%|▌ | 641/11952 [1:05:12<18:06:34, 5.76s/it]
{'loss': 0.4946, 'learning_rate': 1.9970814648318937e-05, 'epoch': 0.05}
+
5%|▌ | 641/11952 [1:05:12<18:06:34, 5.76s/it]
5%|▌ | 642/11952 [1:05:18<18:05:36, 5.76s/it]
{'loss': 0.5367, 'learning_rate': 1.997060739464669e-05, 'epoch': 0.05}
+
5%|▌ | 642/11952 [1:05:18<18:05:36, 5.76s/it]
5%|▌ | 643/11952 [1:05:24<18:29:54, 5.89s/it]
{'loss': 0.5368, 'learning_rate': 1.997039940877451e-05, 'epoch': 0.05}
+
5%|▌ | 643/11952 [1:05:24<18:29:54, 5.89s/it]
5%|▌ | 644/11952 [1:05:30<18:18:50, 5.83s/it]
{'loss': 0.5131, 'learning_rate': 1.997019069071767e-05, 'epoch': 0.05}
+
5%|▌ | 644/11952 [1:05:30<18:18:50, 5.83s/it]
5%|▌ | 645/11952 [1:05:36<18:43:50, 5.96s/it]
{'loss': 0.5253, 'learning_rate': 1.996998124049149e-05, 'epoch': 0.05}
+
5%|▌ | 645/11952 [1:05:36<18:43:50, 5.96s/it]
5%|▌ | 646/11952 [1:05:42<18:48:40, 5.99s/it]
{'loss': 0.5273, 'learning_rate': 1.9969771058111357e-05, 'epoch': 0.05}
+
5%|▌ | 646/11952 [1:05:42<18:48:40, 5.99s/it]
5%|▌ | 647/11952 [1:05:48<18:46:45, 5.98s/it]
{'loss': 0.5247, 'learning_rate': 1.9969560143592705e-05, 'epoch': 0.05}
+
5%|▌ | 647/11952 [1:05:48<18:46:45, 5.98s/it]
5%|▌ | 648/11952 [1:05:54<18:34:19, 5.91s/it]
{'loss': 0.5292, 'learning_rate': 1.996934849695102e-05, 'epoch': 0.05}
+
5%|▌ | 648/11952 [1:05:54<18:34:19, 5.91s/it]
5%|▌ | 649/11952 [1:06:00<18:28:36, 5.88s/it]
{'loss': 0.5262, 'learning_rate': 1.9969136118201852e-05, 'epoch': 0.05}
+
5%|▌ | 649/11952 [1:06:00<18:28:36, 5.88s/it]6 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
5%|▌ | 650/11952 [1:06:05<18:13:38, 5.81s/it]
{'loss': 0.5031, 'learning_rate': 1.9968923007360788e-05, 'epoch': 0.05}
+
5%|▌ | 650/11952 [1:06:05<18:13:38, 5.81s/it]
5%|▌ | 651/11952 [1:06:11<18:23:24, 5.86s/it]
{'loss': 0.523, 'learning_rate': 1.9968709164443483e-05, 'epoch': 0.05}
+
5%|▌ | 651/11952 [1:06:11<18:23:24, 5.86s/it]
5%|▌ | 652/11952 [1:06:17<18:28:47, 5.89s/it]
{'loss': 0.5326, 'learning_rate': 1.9968494589465645e-05, 'epoch': 0.05}
+
5%|▌ | 652/11952 [1:06:17<18:28:47, 5.89s/it]
5%|▌ | 653/11952 [1:06:23<18:23:57, 5.86s/it]
{'loss': 0.4976, 'learning_rate': 1.996827928244302e-05, 'epoch': 0.05}
+
5%|▌ | 653/11952 [1:06:23<18:23:57, 5.86s/it]
5%|▌ | 654/11952 [1:06:29<18:35:10, 5.92s/it]
{'loss': 0.5387, 'learning_rate': 1.996806324339143e-05, 'epoch': 0.05}
+
5%|▌ | 654/11952 [1:06:29<18:35:10, 5.92s/it]
5%|▌ | 655/11952 [1:06:35<18:22:43, 5.86s/it]
{'loss': 0.5141, 'learning_rate': 1.996784647232673e-05, 'epoch': 0.05}
+
5%|▌ | 655/11952 [1:06:35<18:22:43, 5.86s/it]
5%|▌ | 656/11952 [1:06:41<18:18:42, 5.84s/it]
{'loss': 0.5372, 'learning_rate': 1.996762896926485e-05, 'epoch': 0.05}
+
5%|▌ | 656/11952 [1:06:41<18:18:42, 5.84s/it]
5%|▌ | 657/11952 [1:06:46<18:07:24, 5.78s/it]
{'loss': 0.5209, 'learning_rate': 1.9967410734221757e-05, 'epoch': 0.05}
+
5%|▌ | 657/11952 [1:06:46<18:07:24, 5.78s/it]
6%|▌ | 658/11952 [1:06:52<18:27:26, 5.88s/it]
{'loss': 0.5474, 'learning_rate': 1.9967191767213475e-05, 'epoch': 0.06}
+
6%|▌ | 658/11952 [1:06:52<18:27:26, 5.88s/it]
6%|▌ | 659/11952 [1:06:58<18:12:08, 5.80s/it]
{'loss': 0.5331, 'learning_rate': 1.9966972068256087e-05, 'epoch': 0.06}
+
6%|▌ | 659/11952 [1:06:58<18:12:08, 5.80s/it]
6%|▌ | 660/11952 [1:07:04<18:02:38, 5.75s/it]
{'loss': 0.513, 'learning_rate': 1.9966751637365726e-05, 'epoch': 0.06}
+
6%|▌ | 660/11952 [1:07:04<18:02:38, 5.75s/it]
6%|▌ | 661/11952 [1:07:10<18:11:02, 5.80s/it]
{'loss': 0.5238, 'learning_rate': 1.996653047455858e-05, 'epoch': 0.06}
+
6%|▌ | 661/11952 [1:07:10<18:11:02, 5.80s/it]
6%|▌ | 662/11952 [1:07:15<17:55:06, 5.71s/it]
{'loss': 0.5155, 'learning_rate': 1.996630857985089e-05, 'epoch': 0.06}
+
6%|▌ | 662/11952 [1:07:15<17:55:06, 5.71s/it]
6%|▌ | 663/11952 [1:07:21<17:45:37, 5.66s/it]
{'loss': 0.5119, 'learning_rate': 1.996608595325895e-05, 'epoch': 0.06}
+
6%|▌ | 663/11952 [1:07:21<17:45:37, 5.66s/it]
6%|▌ | 664/11952 [1:07:26<17:51:29, 5.70s/it]
{'loss': 0.5187, 'learning_rate': 1.996586259479911e-05, 'epoch': 0.06}
+
6%|▌ | 664/11952 [1:07:26<17:51:29, 5.70s/it]
6%|▌ | 665/11952 [1:07:33<18:24:54, 5.87s/it]
{'loss': 0.5293, 'learning_rate': 1.9965638504487773e-05, 'epoch': 0.06}
+
6%|▌ | 665/11952 [1:07:33<18:24:54, 5.87s/it]
6%|▌ | 666/11952 [1:07:39<18:31:41, 5.91s/it]
{'loss': 0.5285, 'learning_rate': 1.9965413682341393e-05, 'epoch': 0.06}
+
6%|▌ | 666/11952 [1:07:39<18:31:41, 5.91s/it]
6%|▌ | 667/11952 [1:07:45<18:28:45, 5.90s/it]
{'loss': 0.5239, 'learning_rate': 1.996518812837648e-05, 'epoch': 0.06}
+
6%|▌ | 667/11952 [1:07:45<18:28:45, 5.90s/it]
6%|▌ | 668/11952 [1:07:50<18:26:05, 5.88s/it]
{'loss': 0.524, 'learning_rate': 1.9964961842609602e-05, 'epoch': 0.06}
+
6%|▌ | 668/11952 [1:07:50<18:26:05, 5.88s/it]
6%|▌ | 669/11952 [1:07:56<18:33:55, 5.92s/it]
{'loss': 0.5324, 'learning_rate': 1.9964734825057374e-05, 'epoch': 0.06}
+
6%|▌ | 669/11952 [1:07:56<18:33:55, 5.92s/it]
6%|▌ | 670/11952 [1:08:02<18:17:37, 5.84s/it]
{'loss': 0.5108, 'learning_rate': 1.9964507075736463e-05, 'epoch': 0.06}
+
6%|▌ | 670/11952 [1:08:02<18:17:37, 5.84s/it]
6%|▌ | 671/11952 [1:08:08<18:01:11, 5.75s/it]
{'loss': 0.5108, 'learning_rate': 1.99642785946636e-05, 'epoch': 0.06}
+
6%|▌ | 671/11952 [1:08:08<18:01:11, 5.75s/it]
6%|▌ | 672/11952 [1:08:13<17:52:07, 5.70s/it]
{'loss': 0.5037, 'learning_rate': 1.9964049381855566e-05, 'epoch': 0.06}
+
6%|▌ | 672/11952 [1:08:13<17:52:07, 5.70s/it]
6%|▌ | 673/11952 [1:08:19<17:51:43, 5.70s/it]
{'loss': 0.5381, 'learning_rate': 1.9963819437329184e-05, 'epoch': 0.06}
+
6%|▌ | 673/11952 [1:08:19<17:51:43, 5.70s/it]
6%|▌ | 674/11952 [1:08:25<17:47:09, 5.68s/it]
{'loss': 0.5213, 'learning_rate': 1.9963588761101347e-05, 'epoch': 0.06}
+
6%|▌ | 674/11952 [1:08:25<17:47:09, 5.68s/it]
6%|▌ | 675/11952 [1:08:31<18:25:02, 5.88s/it]
{'loss': 0.5213, 'learning_rate': 1.9963357353188993e-05, 'epoch': 0.06}
+
6%|▌ | 675/11952 [1:08:31<18:25:02, 5.88s/it]
6%|▌ | 676/11952 [1:08:37<18:37:03, 5.94s/it]
{'loss': 0.5493, 'learning_rate': 1.9963125213609113e-05, 'epoch': 0.06}
+
6%|▌ | 676/11952 [1:08:37<18:37:03, 5.94s/it]
6%|▌ | 677/11952 [1:08:43<18:19:03, 5.85s/it]
{'loss': 0.5336, 'learning_rate': 1.996289234237876e-05, 'epoch': 0.06}
+
6%|▌ | 677/11952 [1:08:43<18:19:03, 5.85s/it]
6%|▌ | 678/11952 [1:08:48<18:09:29, 5.80s/it]
{'loss': 0.5166, 'learning_rate': 1.996265873951503e-05, 'epoch': 0.06}
+
6%|▌ | 678/11952 [1:08:48<18:09:29, 5.80s/it]
6%|▌ | 679/11952 [1:08:54<18:09:12, 5.80s/it]
{'loss': 0.5261, 'learning_rate': 1.996242440503508e-05, 'epoch': 0.06}
+
6%|▌ | 679/11952 [1:08:54<18:09:12, 5.80s/it]
6%|▌ | 680/11952 [1:09:00<18:06:33, 5.78s/it]
{'loss': 0.516, 'learning_rate': 1.9962189338956124e-05, 'epoch': 0.06}
+
6%|▌ | 680/11952 [1:09:00<18:06:33, 5.78s/it]
6%|▌ | 681/11952 [1:09:06<18:07:25, 5.79s/it]
{'loss': 0.5128, 'learning_rate': 1.9961953541295413e-05, 'epoch': 0.06}
+
6%|▌ | 681/11952 [1:09:06<18:07:25, 5.79s/it]
6%|▌ | 682/11952 [1:09:11<18:10:59, 5.81s/it]
{'loss': 0.5057, 'learning_rate': 1.9961717012070273e-05, 'epoch': 0.06}
+
6%|▌ | 682/11952 [1:09:11<18:10:59, 5.81s/it]
6%|▌ | 683/11952 [1:09:17<18:16:13, 5.84s/it]
{'loss': 0.514, 'learning_rate': 1.9961479751298066e-05, 'epoch': 0.06}
+
6%|▌ | 683/11952 [1:09:17<18:16:13, 5.84s/it]
6%|▌ | 684/11952 [1:09:23<18:00:10, 5.75s/it]
{'loss': 0.5306, 'learning_rate': 1.996124175899622e-05, 'epoch': 0.06}
+
6%|▌ | 684/11952 [1:09:23<18:00:10, 5.75s/it]
6%|▌ | 685/11952 [1:09:29<18:07:26, 5.79s/it]
{'loss': 0.5231, 'learning_rate': 1.996100303518221e-05, 'epoch': 0.06}
+
6%|▌ | 685/11952 [1:09:29<18:07:26, 5.79s/it]
6%|▌ | 686/11952 [1:09:35<18:15:55, 5.84s/it]
{'loss': 0.5202, 'learning_rate': 1.9960763579873568e-05, 'epoch': 0.06}
+
6%|▌ | 686/11952 [1:09:35<18:15:55, 5.84s/it]
6%|▌ | 687/11952 [1:09:40<18:08:59, 5.80s/it]
{'loss': 0.5057, 'learning_rate': 1.996052339308788e-05, 'epoch': 0.06}
+
6%|▌ | 687/11952 [1:09:40<18:08:59, 5.80s/it]
6%|▌ | 688/11952 [1:09:46<18:18:17, 5.85s/it]
{'loss': 0.5059, 'learning_rate': 1.9960282474842784e-05, 'epoch': 0.06}
+
6%|▌ | 688/11952 [1:09:46<18:18:17, 5.85s/it]
6%|▌ | 689/11952 [1:09:52<18:25:47, 5.89s/it]
{'loss': 0.5282, 'learning_rate': 1.9960040825155968e-05, 'epoch': 0.06}
+
6%|▌ | 689/11952 [1:09:52<18:25:47, 5.89s/it]
6%|▌ | 690/11952 [1:09:58<18:16:40, 5.84s/it]
{'loss': 0.5417, 'learning_rate': 1.9959798444045184e-05, 'epoch': 0.06}
+
6%|▌ | 690/11952 [1:09:58<18:16:40, 5.84s/it]
6%|▌ | 691/11952 [1:10:04<18:36:46, 5.95s/it]
{'loss': 0.5122, 'learning_rate': 1.9959555331528226e-05, 'epoch': 0.06}
+
6%|▌ | 691/11952 [1:10:04<18:36:46, 5.95s/it]
6%|▌ | 692/11952 [1:10:10<18:33:20, 5.93s/it]
{'loss': 0.5125, 'learning_rate': 1.995931148762295e-05, 'epoch': 0.06}
+
6%|▌ | 692/11952 [1:10:10<18:33:20, 5.93s/it]
6%|▌ | 693/11952 [1:10:16<18:10:30, 5.81s/it]
{'loss': 0.5131, 'learning_rate': 1.9959066912347262e-05, 'epoch': 0.06}
+
6%|▌ | 693/11952 [1:10:16<18:10:30, 5.81s/it]
6%|▌ | 694/11952 [1:10:22<18:19:09, 5.86s/it]
{'loss': 0.5258, 'learning_rate': 1.9958821605719122e-05, 'epoch': 0.06}
+
6%|▌ | 694/11952 [1:10:22<18:19:09, 5.86s/it]
6%|▌ | 695/11952 [1:10:28<18:15:41, 5.84s/it]
{'loss': 0.5234, 'learning_rate': 1.9958575567756546e-05, 'epoch': 0.06}
+
6%|▌ | 695/11952 [1:10:28<18:15:41, 5.84s/it]
6%|▌ | 696/11952 [1:10:33<18:08:02, 5.80s/it]
{'loss': 0.5072, 'learning_rate': 1.9958328798477602e-05, 'epoch': 0.06}
+
6%|▌ | 696/11952 [1:10:33<18:08:02, 5.80s/it]
6%|▌ | 697/11952 [1:10:39<17:57:25, 5.74s/it]
{'loss': 0.5149, 'learning_rate': 1.9958081297900413e-05, 'epoch': 0.06}
+
6%|▌ | 697/11952 [1:10:39<17:57:25, 5.74s/it]
6%|▌ | 698/11952 [1:10:45<18:03:46, 5.78s/it]
{'loss': 0.5273, 'learning_rate': 1.995783306604315e-05, 'epoch': 0.06}
+
6%|▌ | 698/11952 [1:10:45<18:03:46, 5.78s/it]
6%|▌ | 699/11952 [1:10:51<18:09:07, 5.81s/it]
{'loss': 0.5115, 'learning_rate': 1.995758410292404e-05, 'epoch': 0.06}
+
6%|▌ | 699/11952 [1:10:51<18:09:07, 5.81s/it]6 AutoResumeHook: Checking whether to suspend...
+70 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 5AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
6%|▌ | 700/11952 [1:10:56<18:10:33, 5.82s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5219, 'learning_rate': 1.9957334408561374e-05, 'epoch': 0.06}
+
6%|▌ | 700/11952 [1:10:56<18:10:33, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
6%|▌ | 701/11952 [1:11:29<43:27:34, 13.91s/it]
{'loss': 0.5097, 'learning_rate': 1.9957083982973488e-05, 'epoch': 0.06}
+
6%|▌ | 701/11952 [1:11:29<43:27:34, 13.91s/it]
6%|▌ | 702/11952 [1:11:35<35:38:51, 11.41s/it]
{'loss': 0.5104, 'learning_rate': 1.9956832826178765e-05, 'epoch': 0.06}
+
6%|▌ | 702/11952 [1:11:35<35:38:51, 11.41s/it]
6%|▌ | 703/11952 [1:11:40<30:07:52, 9.64s/it]
{'loss': 0.5237, 'learning_rate': 1.9956580938195654e-05, 'epoch': 0.06}
+
6%|▌ | 703/11952 [1:11:40<30:07:52, 9.64s/it]
6%|▌ | 704/11952 [1:11:46<26:30:29, 8.48s/it]
{'loss': 0.519, 'learning_rate': 1.9956328319042648e-05, 'epoch': 0.06}
+
6%|▌ | 704/11952 [1:11:46<26:30:29, 8.48s/it]
6%|▌ | 705/11952 [1:11:52<24:11:54, 7.75s/it]
{'loss': 0.5404, 'learning_rate': 1.9956074968738306e-05, 'epoch': 0.06}
+
6%|▌ | 705/11952 [1:11:52<24:11:54, 7.75s/it]
6%|▌ | 706/11952 [1:11:58<22:16:24, 7.13s/it]
{'loss': 0.5104, 'learning_rate': 1.9955820887301227e-05, 'epoch': 0.06}
+
6%|▌ | 706/11952 [1:11:58<22:16:24, 7.13s/it]
6%|▌ | 707/11952 [1:12:03<20:50:59, 6.67s/it]
{'loss': 0.5055, 'learning_rate': 1.995556607475007e-05, 'epoch': 0.06}
+
6%|▌ | 707/11952 [1:12:03<20:50:59, 6.67s/it]
6%|▌ | 708/11952 [1:12:09<20:02:54, 6.42s/it]
{'loss': 0.5312, 'learning_rate': 1.9955310531103552e-05, 'epoch': 0.06}
+
6%|▌ | 708/11952 [1:12:09<20:02:54, 6.42s/it]
6%|▌ | 709/11952 [1:12:15<19:19:59, 6.19s/it]
{'loss': 0.5138, 'learning_rate': 1.9955054256380436e-05, 'epoch': 0.06}
+
6%|▌ | 709/11952 [1:12:15<19:19:59, 6.19s/it]
6%|▌ | 710/11952 [1:12:21<19:06:17, 6.12s/it]
{'loss': 0.5236, 'learning_rate': 1.995479725059954e-05, 'epoch': 0.06}
+
6%|▌ | 710/11952 [1:12:21<19:06:17, 6.12s/it]
6%|▌ | 711/11952 [1:12:27<18:49:44, 6.03s/it]
{'loss': 0.5212, 'learning_rate': 1.9954539513779737e-05, 'epoch': 0.06}
+
6%|▌ | 711/11952 [1:12:27<18:49:44, 6.03s/it]
6%|▌ | 712/11952 [1:12:32<18:31:48, 5.93s/it]
{'loss': 0.5143, 'learning_rate': 1.9954281045939958e-05, 'epoch': 0.06}
+
6%|▌ | 712/11952 [1:12:32<18:31:48, 5.93s/it]
6%|▌ | 713/11952 [1:12:38<18:22:38, 5.89s/it]
{'loss': 0.5225, 'learning_rate': 1.995402184709918e-05, 'epoch': 0.06}
+
6%|▌ | 713/11952 [1:12:38<18:22:38, 5.89s/it]
6%|▌ | 714/11952 [1:12:44<18:11:17, 5.83s/it]
{'loss': 0.5255, 'learning_rate': 1.9953761917276443e-05, 'epoch': 0.06}
+
6%|▌ | 714/11952 [1:12:44<18:11:17, 5.83s/it]
6%|▌ | 715/11952 [1:12:50<18:24:34, 5.90s/it]
{'loss': 0.5169, 'learning_rate': 1.995350125649083e-05, 'epoch': 0.06}
+
6%|▌ | 715/11952 [1:12:50<18:24:34, 5.90s/it]
6%|▌ | 716/11952 [1:12:56<18:15:33, 5.85s/it]
{'loss': 0.5122, 'learning_rate': 1.9953239864761486e-05, 'epoch': 0.06}
+
6%|▌ | 716/11952 [1:12:56<18:15:33, 5.85s/it]
6%|▌ | 717/11952 [1:13:02<18:23:01, 5.89s/it]
{'loss': 0.5222, 'learning_rate': 1.9952977742107606e-05, 'epoch': 0.06}
+
6%|▌ | 717/11952 [1:13:02<18:23:01, 5.89s/it]
6%|▌ | 718/11952 [1:13:07<18:10:39, 5.83s/it]
{'loss': 0.5347, 'learning_rate': 1.9952714888548432e-05, 'epoch': 0.06}
+
6%|▌ | 718/11952 [1:13:07<18:10:39, 5.83s/it]
6%|▌ | 719/11952 [1:13:13<17:55:31, 5.74s/it]
{'loss': 0.5194, 'learning_rate': 1.9952451304103278e-05, 'epoch': 0.06}
+
6%|▌ | 719/11952 [1:13:13<17:55:31, 5.74s/it]
6%|▌ | 720/11952 [1:13:19<18:01:05, 5.78s/it]
{'loss': 0.5115, 'learning_rate': 1.9952186988791494e-05, 'epoch': 0.06}
+
6%|▌ | 720/11952 [1:13:19<18:01:05, 5.78s/it]
6%|▌ | 721/11952 [1:13:24<17:56:33, 5.75s/it]
{'loss': 0.521, 'learning_rate': 1.9951921942632493e-05, 'epoch': 0.06}
+
6%|▌ | 721/11952 [1:13:24<17:56:33, 5.75s/it]
6%|▌ | 722/11952 [1:13:30<17:49:22, 5.71s/it]
{'loss': 0.5169, 'learning_rate': 1.9951656165645736e-05, 'epoch': 0.06}
+
6%|▌ | 722/11952 [1:13:30<17:49:22, 5.71s/it]
6%|▌ | 723/11952 [1:13:36<17:48:15, 5.71s/it]
{'loss': 0.5083, 'learning_rate': 1.9951389657850744e-05, 'epoch': 0.06}
+
6%|▌ | 723/11952 [1:13:36<17:48:15, 5.71s/it]
6%|▌ | 724/11952 [1:13:41<17:49:28, 5.72s/it]
{'loss': 0.5222, 'learning_rate': 1.9951122419267085e-05, 'epoch': 0.06}
+
6%|▌ | 724/11952 [1:13:41<17:49:28, 5.72s/it]
6%|▌ | 725/11952 [1:13:47<17:43:25, 5.68s/it]
{'loss': 0.5328, 'learning_rate': 1.9950854449914384e-05, 'epoch': 0.06}
+
6%|▌ | 725/11952 [1:13:47<17:43:25, 5.68s/it]
6%|▌ | 726/11952 [1:13:53<17:45:03, 5.69s/it]
{'loss': 0.502, 'learning_rate': 1.9950585749812326e-05, 'epoch': 0.06}
+
6%|▌ | 726/11952 [1:13:53<17:45:03, 5.69s/it]
6%|▌ | 727/11952 [1:13:59<17:56:22, 5.75s/it]
{'loss': 0.5185, 'learning_rate': 1.9950316318980632e-05, 'epoch': 0.06}
+
6%|▌ | 727/11952 [1:13:59<17:56:22, 5.75s/it]
6%|▌ | 728/11952 [1:14:05<18:20:40, 5.88s/it]
{'loss': 0.528, 'learning_rate': 1.99500461574391e-05, 'epoch': 0.06}
+
6%|▌ | 728/11952 [1:14:05<18:20:40, 5.88s/it]
6%|▌ | 729/11952 [1:14:11<18:09:10, 5.82s/it]
{'loss': 0.5134, 'learning_rate': 1.994977526520756e-05, 'epoch': 0.06}
+
6%|▌ | 729/11952 [1:14:11<18:09:10, 5.82s/it]
6%|▌ | 730/11952 [1:14:16<17:56:02, 5.75s/it]
{'loss': 0.5163, 'learning_rate': 1.9949503642305908e-05, 'epoch': 0.06}
+
6%|▌ | 730/11952 [1:14:16<17:56:02, 5.75s/it]
6%|▌ | 731/11952 [1:14:22<18:01:08, 5.78s/it]
{'loss': 0.5277, 'learning_rate': 1.9949231288754094e-05, 'epoch': 0.06}
+
6%|▌ | 731/11952 [1:14:22<18:01:08, 5.78s/it]
6%|▌ | 732/11952 [1:14:28<18:09:47, 5.83s/it]
{'loss': 0.5142, 'learning_rate': 1.9948958204572114e-05, 'epoch': 0.06}
+
6%|▌ | 732/11952 [1:14:28<18:09:47, 5.83s/it]
6%|▌ | 733/11952 [1:14:34<18:04:34, 5.80s/it]
{'loss': 0.5133, 'learning_rate': 1.9948684389780026e-05, 'epoch': 0.06}
+
6%|▌ | 733/11952 [1:14:34<18:04:34, 5.80s/it]
6%|▌ | 734/11952 [1:14:40<18:10:46, 5.83s/it]
{'loss': 0.5184, 'learning_rate': 1.9948409844397934e-05, 'epoch': 0.06}
+
6%|▌ | 734/11952 [1:14:40<18:10:46, 5.83s/it]
6%|▌ | 735/11952 [1:14:45<18:00:45, 5.78s/it]
{'loss': 0.4933, 'learning_rate': 1.9948134568446006e-05, 'epoch': 0.06}
+
6%|▌ | 735/11952 [1:14:45<18:00:45, 5.78s/it]
6%|▌ | 736/11952 [1:14:51<18:03:33, 5.80s/it]
{'loss': 0.5337, 'learning_rate': 1.994785856194445e-05, 'epoch': 0.06}
+
6%|▌ | 736/11952 [1:14:51<18:03:33, 5.80s/it]
6%|▌ | 737/11952 [1:14:57<18:17:17, 5.87s/it]
{'loss': 0.5312, 'learning_rate': 1.9947581824913536e-05, 'epoch': 0.06}
+
6%|▌ | 737/11952 [1:14:57<18:17:17, 5.87s/it]
6%|▌ | 738/11952 [1:15:03<18:11:27, 5.84s/it]
{'loss': 0.5064, 'learning_rate': 1.994730435737359e-05, 'epoch': 0.06}
+
6%|▌ | 738/11952 [1:15:03<18:11:27, 5.84s/it]
6%|▌ | 739/11952 [1:15:09<18:15:51, 5.86s/it]
{'loss': 0.5289, 'learning_rate': 1.9947026159344985e-05, 'epoch': 0.06}
+
6%|▌ | 739/11952 [1:15:09<18:15:51, 5.86s/it]
6%|▌ | 740/11952 [1:15:14<18:05:21, 5.81s/it]
{'loss': 0.5196, 'learning_rate': 1.9946747230848152e-05, 'epoch': 0.06}
+
6%|▌ | 740/11952 [1:15:14<18:05:21, 5.81s/it]
6%|▌ | 741/11952 [1:15:20<18:15:36, 5.86s/it]
{'loss': 0.5098, 'learning_rate': 1.994646757190357e-05, 'epoch': 0.06}
+
6%|▌ | 741/11952 [1:15:20<18:15:36, 5.86s/it]
6%|▌ | 742/11952 [1:15:27<18:24:57, 5.91s/it]
{'loss': 0.5362, 'learning_rate': 1.9946187182531785e-05, 'epoch': 0.06}
+
6%|▌ | 742/11952 [1:15:27<18:24:57, 5.91s/it]
6%|▌ | 743/11952 [1:15:33<18:31:44, 5.95s/it]
{'loss': 0.5438, 'learning_rate': 1.9945906062753383e-05, 'epoch': 0.06}
+
6%|▌ | 743/11952 [1:15:33<18:31:44, 5.95s/it]
6%|▌ | 744/11952 [1:15:39<18:34:06, 5.96s/it]
{'loss': 0.5376, 'learning_rate': 1.9945624212589007e-05, 'epoch': 0.06}
+
6%|▌ | 744/11952 [1:15:39<18:34:06, 5.96s/it]
6%|▌ | 745/11952 [1:15:44<18:20:24, 5.89s/it]
{'loss': 0.508, 'learning_rate': 1.9945341632059356e-05, 'epoch': 0.06}
+
6%|▌ | 745/11952 [1:15:44<18:20:24, 5.89s/it]
6%|▌ | 746/11952 [1:15:50<18:14:13, 5.86s/it]
{'loss': 0.5277, 'learning_rate': 1.9945058321185175e-05, 'epoch': 0.06}
+
6%|▌ | 746/11952 [1:15:50<18:14:13, 5.86s/it]
6%|▋ | 747/11952 [1:15:56<18:16:37, 5.87s/it]
{'loss': 0.528, 'learning_rate': 1.994477427998728e-05, 'epoch': 0.06}
+
6%|▋ | 747/11952 [1:15:56<18:16:37, 5.87s/it]
6%|▋ | 748/11952 [1:16:02<18:19:49, 5.89s/it]
{'loss': 0.515, 'learning_rate': 1.9944489508486528e-05, 'epoch': 0.06}
+
6%|▋ | 748/11952 [1:16:02<18:19:49, 5.89s/it]
6%|▋ | 749/11952 [1:16:08<18:05:25, 5.81s/it]
{'loss': 0.5223, 'learning_rate': 1.9944204006703828e-05, 'epoch': 0.06}
+
6%|▋ | 749/11952 [1:16:08<18:05:25, 5.81s/it]6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+71 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
6%|▋ | 750/11952 [1:16:13<18:07:22, 5.82s/it]
{'loss': 0.5251, 'learning_rate': 1.9943917774660145e-05, 'epoch': 0.06}
+
6%|▋ | 750/11952 [1:16:13<18:07:22, 5.82s/it]
6%|▋ | 751/11952 [1:16:19<17:48:11, 5.72s/it]
{'loss': 0.51, 'learning_rate': 1.99436308123765e-05, 'epoch': 0.06}
+
6%|▋ | 751/11952 [1:16:19<17:48:11, 5.72s/it]
6%|▋ | 752/11952 [1:16:24<17:43:39, 5.70s/it]
{'loss': 0.5188, 'learning_rate': 1.9943343119873966e-05, 'epoch': 0.06}
+
6%|▋ | 752/11952 [1:16:24<17:43:39, 5.70s/it]
6%|▋ | 753/11952 [1:16:30<17:34:03, 5.65s/it]
{'loss': 0.5078, 'learning_rate': 1.9943054697173676e-05, 'epoch': 0.06}
+
6%|▋ | 753/11952 [1:16:30<17:34:03, 5.65s/it]
6%|▋ | 754/11952 [1:16:36<17:31:05, 5.63s/it]
{'loss': 0.505, 'learning_rate': 1.99427655442968e-05, 'epoch': 0.06}
+
6%|▋ | 754/11952 [1:16:36<17:31:05, 5.63s/it]
6%|▋ | 755/11952 [1:16:41<17:27:46, 5.61s/it]
{'loss': 0.5079, 'learning_rate': 1.994247566126458e-05, 'epoch': 0.06}
+
6%|▋ | 755/11952 [1:16:41<17:27:46, 5.61s/it]
6%|▋ | 756/11952 [1:16:47<17:58:12, 5.78s/it]
{'loss': 0.521, 'learning_rate': 1.99421850480983e-05, 'epoch': 0.06}
+
6%|▋ | 756/11952 [1:16:47<17:58:12, 5.78s/it]
6%|▋ | 757/11952 [1:16:53<18:11:57, 5.85s/it]
{'loss': 0.5151, 'learning_rate': 1.9941893704819307e-05, 'epoch': 0.06}
+
6%|▋ | 757/11952 [1:16:53<18:11:57, 5.85s/it]
6%|▋ | 758/11952 [1:16:59<18:05:30, 5.82s/it]
{'loss': 0.5118, 'learning_rate': 1.9941601631448986e-05, 'epoch': 0.06}
+
6%|▋ | 758/11952 [1:16:59<18:05:30, 5.82s/it]
6%|▋ | 759/11952 [1:17:05<17:56:52, 5.77s/it]
{'loss': 0.5173, 'learning_rate': 1.9941308828008794e-05, 'epoch': 0.06}
+
6%|▋ | 759/11952 [1:17:05<17:56:52, 5.77s/it]
6%|▋ | 760/11952 [1:17:11<18:07:04, 5.83s/it]
{'loss': 0.5219, 'learning_rate': 1.994101529452023e-05, 'epoch': 0.06}
+
6%|▋ | 760/11952 [1:17:11<18:07:04, 5.83s/it]
6%|▋ | 761/11952 [1:17:17<18:22:25, 5.91s/it]
{'loss': 0.5182, 'learning_rate': 1.9940721031004853e-05, 'epoch': 0.06}
+
6%|▋ | 761/11952 [1:17:17<18:22:25, 5.91s/it]
6%|▋ | 762/11952 [1:17:23<18:32:06, 5.96s/it]
{'loss': 0.5159, 'learning_rate': 1.9940426037484268e-05, 'epoch': 0.06}
+
6%|▋ | 762/11952 [1:17:23<18:32:06, 5.96s/it]
6%|▋ | 763/11952 [1:17:29<18:24:42, 5.92s/it]
{'loss': 0.5232, 'learning_rate': 1.994013031398014e-05, 'epoch': 0.06}
+
6%|▋ | 763/11952 [1:17:29<18:24:42, 5.92s/it]
6%|▋ | 764/11952 [1:17:34<18:12:56, 5.86s/it]
{'loss': 0.5113, 'learning_rate': 1.9939833860514187e-05, 'epoch': 0.06}
+
6%|▋ | 764/11952 [1:17:34<18:12:56, 5.86s/it]
6%|▋ | 765/11952 [1:17:40<18:07:55, 5.83s/it]
{'loss': 0.5284, 'learning_rate': 1.9939536677108176e-05, 'epoch': 0.06}
+
6%|▋ | 765/11952 [1:17:40<18:07:55, 5.83s/it]
6%|▋ | 766/11952 [1:17:46<18:01:11, 5.80s/it]
{'loss': 0.5181, 'learning_rate': 1.993923876378393e-05, 'epoch': 0.06}
+
6%|▋ | 766/11952 [1:17:46<18:01:11, 5.80s/it]
6%|▋ | 767/11952 [1:17:52<18:07:58, 5.84s/it]
{'loss': 0.5263, 'learning_rate': 1.993894012056334e-05, 'epoch': 0.06}
+
6%|▋ | 767/11952 [1:17:52<18:07:58, 5.84s/it]
6%|▋ | 768/11952 [1:17:58<17:55:53, 5.77s/it]
{'loss': 0.508, 'learning_rate': 1.993864074746832e-05, 'epoch': 0.06}
+
6%|▋ | 768/11952 [1:17:58<17:55:53, 5.77s/it]
6%|▋ | 769/11952 [1:18:03<18:03:50, 5.82s/it]
{'loss': 0.5173, 'learning_rate': 1.993834064452086e-05, 'epoch': 0.06}
+
6%|▋ | 769/11952 [1:18:03<18:03:50, 5.82s/it]
6%|▋ | 770/11952 [1:18:09<17:54:59, 5.77s/it]
{'loss': 0.5273, 'learning_rate': 1.9938039811743e-05, 'epoch': 0.06}
+
6%|▋ | 770/11952 [1:18:09<17:54:59, 5.77s/it]
6%|▋ | 771/11952 [1:18:15<17:49:21, 5.74s/it]
{'loss': 0.5169, 'learning_rate': 1.9937738249156836e-05, 'epoch': 0.06}
+
6%|▋ | 771/11952 [1:18:15<17:49:21, 5.74s/it]
6%|▋ | 772/11952 [1:18:21<17:53:41, 5.76s/it]
{'loss': 0.5033, 'learning_rate': 1.9937435956784506e-05, 'epoch': 0.06}
+
6%|▋ | 772/11952 [1:18:21<17:53:41, 5.76s/it]
6%|▋ | 773/11952 [1:18:26<17:57:01, 5.78s/it]
{'loss': 0.4927, 'learning_rate': 1.9937132934648213e-05, 'epoch': 0.06}
+
6%|▋ | 773/11952 [1:18:26<17:57:01, 5.78s/it]
6%|▋ | 774/11952 [1:18:32<18:01:10, 5.80s/it]
{'loss': 0.5177, 'learning_rate': 1.993682918277021e-05, 'epoch': 0.06}
+
6%|▋ | 774/11952 [1:18:32<18:01:10, 5.80s/it]
6%|▋ | 775/11952 [1:18:38<18:02:39, 5.81s/it]
{'loss': 0.51, 'learning_rate': 1.99365247011728e-05, 'epoch': 0.06}
+
6%|▋ | 775/11952 [1:18:38<18:02:39, 5.81s/it]
6%|▋ | 776/11952 [1:18:44<17:58:20, 5.79s/it]
{'loss': 0.5046, 'learning_rate': 1.9936219489878343e-05, 'epoch': 0.06}
+
6%|▋ | 776/11952 [1:18:44<17:58:20, 5.79s/it]
7%|▋ | 777/11952 [1:18:50<18:02:10, 5.81s/it]
{'loss': 0.5577, 'learning_rate': 1.9935913548909258e-05, 'epoch': 0.07}
+
7%|▋ | 777/11952 [1:18:50<18:02:10, 5.81s/it]
7%|▋ | 778/11952 [1:18:56<18:14:59, 5.88s/it]
{'loss': 0.5247, 'learning_rate': 1.9935606878288008e-05, 'epoch': 0.07}
+
7%|▋ | 778/11952 [1:18:56<18:14:59, 5.88s/it]
7%|▋ | 779/11952 [1:19:01<18:00:40, 5.80s/it]
{'loss': 0.5033, 'learning_rate': 1.9935299478037114e-05, 'epoch': 0.07}
+
7%|▋ | 779/11952 [1:19:01<18:00:40, 5.80s/it]
7%|▋ | 780/11952 [1:19:07<18:04:09, 5.82s/it]
{'loss': 0.5286, 'learning_rate': 1.993499134817915e-05, 'epoch': 0.07}
+
7%|▋ | 780/11952 [1:19:07<18:04:09, 5.82s/it]
7%|▋ | 781/11952 [1:19:13<18:12:32, 5.87s/it]
{'loss': 0.5342, 'learning_rate': 1.9934682488736745e-05, 'epoch': 0.07}
+
7%|▋ | 781/11952 [1:19:13<18:12:32, 5.87s/it]
7%|▋ | 782/11952 [1:19:19<18:21:06, 5.91s/it]
{'loss': 0.5145, 'learning_rate': 1.993437289973258e-05, 'epoch': 0.07}
+
7%|▋ | 782/11952 [1:19:19<18:21:06, 5.91s/it]
7%|▋ | 783/11952 [1:19:25<18:20:59, 5.91s/it]
{'loss': 0.5139, 'learning_rate': 1.993406258118939e-05, 'epoch': 0.07}
+
7%|▋ | 783/11952 [1:19:25<18:20:59, 5.91s/it]
7%|▋ | 784/11952 [1:19:31<18:19:38, 5.91s/it]
{'loss': 0.5159, 'learning_rate': 1.993375153312996e-05, 'epoch': 0.07}
+
7%|▋ | 784/11952 [1:19:31<18:19:38, 5.91s/it]
7%|▋ | 785/11952 [1:19:37<18:27:54, 5.95s/it]
{'loss': 0.506, 'learning_rate': 1.9933439755577134e-05, 'epoch': 0.07}
+
7%|▋ | 785/11952 [1:19:37<18:27:54, 5.95s/it]
7%|▋ | 786/11952 [1:19:43<18:23:31, 5.93s/it]
{'loss': 0.5219, 'learning_rate': 1.9933127248553813e-05, 'epoch': 0.07}
+
7%|▋ | 786/11952 [1:19:43<18:23:31, 5.93s/it]
7%|▋ | 787/11952 [1:19:49<18:08:19, 5.85s/it]
{'loss': 0.5383, 'learning_rate': 1.993281401208294e-05, 'epoch': 0.07}
+
7%|▋ | 787/11952 [1:19:49<18:08:19, 5.85s/it]
7%|▋ | 788/11952 [1:19:55<18:14:18, 5.88s/it]
{'loss': 0.5096, 'learning_rate': 1.993250004618752e-05, 'epoch': 0.07}
+
7%|▋ | 788/11952 [1:19:55<18:14:18, 5.88s/it]
7%|▋ | 789/11952 [1:20:00<18:12:46, 5.87s/it]
{'loss': 0.5199, 'learning_rate': 1.9932185350890606e-05, 'epoch': 0.07}
+
7%|▋ | 789/11952 [1:20:00<18:12:46, 5.87s/it]
7%|▋ | 790/11952 [1:20:06<18:02:50, 5.82s/it]
{'loss': 0.5117, 'learning_rate': 1.9931869926215315e-05, 'epoch': 0.07}
+
7%|▋ | 790/11952 [1:20:06<18:02:50, 5.82s/it]
7%|▋ | 791/11952 [1:20:12<18:08:13, 5.85s/it]
{'loss': 0.5312, 'learning_rate': 1.9931553772184805e-05, 'epoch': 0.07}
+
7%|▋ | 791/11952 [1:20:12<18:08:13, 5.85s/it]
7%|▋ | 792/11952 [1:20:18<18:25:15, 5.94s/it]
{'loss': 0.5135, 'learning_rate': 1.9931236888822295e-05, 'epoch': 0.07}
+
7%|▋ | 792/11952 [1:20:18<18:25:15, 5.94s/it]
7%|▋ | 793/11952 [1:20:24<18:44:28, 6.05s/it]
{'loss': 0.5282, 'learning_rate': 1.993091927615105e-05, 'epoch': 0.07}
+
7%|▋ | 793/11952 [1:20:24<18:44:28, 6.05s/it]
7%|▋ | 794/11952 [1:20:31<18:59:29, 6.13s/it]
{'loss': 0.5438, 'learning_rate': 1.9930600934194405e-05, 'epoch': 0.07}
+
7%|▋ | 794/11952 [1:20:31<18:59:29, 6.13s/it]
7%|▋ | 795/11952 [1:20:37<18:39:48, 6.02s/it]
{'loss': 0.5087, 'learning_rate': 1.993028186297573e-05, 'epoch': 0.07}
+
7%|▋ | 795/11952 [1:20:37<18:39:48, 6.02s/it]
7%|▋ | 796/11952 [1:20:42<18:33:03, 5.99s/it]
{'loss': 0.5244, 'learning_rate': 1.9929962062518458e-05, 'epoch': 0.07}
+
7%|▋ | 796/11952 [1:20:42<18:33:03, 5.99s/it]
7%|▋ | 797/11952 [1:20:48<18:23:36, 5.94s/it]
{'loss': 0.5054, 'learning_rate': 1.9929641532846074e-05, 'epoch': 0.07}
+
7%|▋ | 797/11952 [1:20:48<18:23:36, 5.94s/it]
7%|▋ | 798/11952 [1:20:54<18:10:36, 5.87s/it]
{'loss': 0.5353, 'learning_rate': 1.992932027398212e-05, 'epoch': 0.07}
+
7%|▋ | 798/11952 [1:20:54<18:10:36, 5.87s/it]
7%|▋ | 799/11952 [1:21:00<17:58:33, 5.80s/it]
{'loss': 0.5065, 'learning_rate': 1.992899828595018e-05, 'epoch': 0.07}
+
7%|▋ | 799/11952 [1:21:00<17:58:33, 5.80s/it]2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
7%|▋ | 800/11952 [1:21:06<18:11:39, 5.87s/it]
{'loss': 0.5293, 'learning_rate': 1.9928675568773906e-05, 'epoch': 0.07}
+
7%|▋ | 800/11952 [1:21:06<18:11:39, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
7%|▋ | 801/11952 [1:21:37<41:30:46, 13.40s/it]
{'loss': 0.5097, 'learning_rate': 1.992835212247699e-05, 'epoch': 0.07}
+
7%|▋ | 801/11952 [1:21:37<41:30:46, 13.40s/it]
7%|▋ | 802/11952 [1:21:42<34:24:08, 11.11s/it]
{'loss': 0.5242, 'learning_rate': 1.9928027947083195e-05, 'epoch': 0.07}
+
7%|▋ | 802/11952 [1:21:42<34:24:08, 11.11s/it]
7%|▋ | 803/11952 [1:21:48<29:30:22, 9.53s/it]
{'loss': 0.5199, 'learning_rate': 1.992770304261632e-05, 'epoch': 0.07}
+
7%|▋ | 803/11952 [1:21:48<29:30:22, 9.53s/it]
7%|▋ | 804/11952 [1:21:54<25:59:53, 8.40s/it]
{'loss': 0.5333, 'learning_rate': 1.9927377409100222e-05, 'epoch': 0.07}
+
7%|▋ | 804/11952 [1:21:54<25:59:53, 8.40s/it]
7%|▋ | 805/11952 [1:22:00<23:18:42, 7.53s/it]
{'loss': 0.5338, 'learning_rate': 1.992705104655882e-05, 'epoch': 0.07}
+
7%|▋ | 805/11952 [1:22:00<23:18:42, 7.53s/it]
7%|▋ | 806/11952 [1:22:05<21:43:50, 7.02s/it]
{'loss': 0.5206, 'learning_rate': 1.992672395501608e-05, 'epoch': 0.07}
+
7%|▋ | 806/11952 [1:22:05<21:43:50, 7.02s/it]
7%|▋ | 807/11952 [1:22:12<21:03:15, 6.80s/it]
{'loss': 0.5262, 'learning_rate': 1.992639613449602e-05, 'epoch': 0.07}
+
7%|▋ | 807/11952 [1:22:12<21:03:15, 6.80s/it]
7%|▋ | 808/11952 [1:22:18<20:31:39, 6.63s/it]
{'loss': 0.5317, 'learning_rate': 1.9926067585022718e-05, 'epoch': 0.07}
+
7%|▋ | 808/11952 [1:22:18<20:31:39, 6.63s/it]
7%|▋ | 809/11952 [1:22:24<19:40:47, 6.36s/it]
{'loss': 0.5414, 'learning_rate': 1.9925738306620294e-05, 'epoch': 0.07}
+
7%|▋ | 809/11952 [1:22:24<19:40:47, 6.36s/it]
7%|▋ | 810/11952 [1:22:29<19:08:13, 6.18s/it]
{'loss': 0.5112, 'learning_rate': 1.9925408299312935e-05, 'epoch': 0.07}
+
7%|▋ | 810/11952 [1:22:29<19:08:13, 6.18s/it]
7%|▋ | 811/11952 [1:22:35<18:53:46, 6.11s/it]
{'loss': 0.5168, 'learning_rate': 1.992507756312487e-05, 'epoch': 0.07}
+
7%|▋ | 811/11952 [1:22:35<18:53:46, 6.11s/it]
7%|▋ | 812/11952 [1:22:41<18:39:10, 6.03s/it]
{'loss': 0.5242, 'learning_rate': 1.99247460980804e-05, 'epoch': 0.07}
+
7%|▋ | 812/11952 [1:22:41<18:39:10, 6.03s/it]
7%|▋ | 813/11952 [1:22:47<18:49:10, 6.08s/it]
{'loss': 0.51, 'learning_rate': 1.9924413904203847e-05, 'epoch': 0.07}
+
7%|▋ | 813/11952 [1:22:47<18:49:10, 6.08s/it]
7%|▋ | 814/11952 [1:22:53<18:36:00, 6.01s/it]
{'loss': 0.5168, 'learning_rate': 1.992408098151962e-05, 'epoch': 0.07}
+
7%|▋ | 814/11952 [1:22:53<18:36:00, 6.01s/it]
7%|▋ | 815/11952 [1:22:59<18:41:04, 6.04s/it]
{'loss': 0.5223, 'learning_rate': 1.992374733005216e-05, 'epoch': 0.07}
+
7%|▋ | 815/11952 [1:22:59<18:41:04, 6.04s/it]
7%|▋ | 816/11952 [1:23:05<18:18:10, 5.92s/it]
{'loss': 0.5066, 'learning_rate': 1.9923412949825975e-05, 'epoch': 0.07}
+
7%|▋ | 816/11952 [1:23:05<18:18:10, 5.92s/it]
7%|▋ | 817/11952 [1:23:11<18:14:10, 5.90s/it]
{'loss': 0.5063, 'learning_rate': 1.9923077840865615e-05, 'epoch': 0.07}
+
7%|▋ | 817/11952 [1:23:11<18:14:10, 5.90s/it]
7%|▋ | 818/11952 [1:23:17<18:13:36, 5.89s/it]
{'loss': 0.5171, 'learning_rate': 1.9922742003195696e-05, 'epoch': 0.07}
+
7%|▋ | 818/11952 [1:23:17<18:13:36, 5.89s/it]
7%|▋ | 819/11952 [1:23:22<18:05:46, 5.85s/it]
{'loss': 0.5278, 'learning_rate': 1.9922405436840872e-05, 'epoch': 0.07}
+
7%|▋ | 819/11952 [1:23:22<18:05:46, 5.85s/it]
7%|▋ | 820/11952 [1:23:28<18:00:12, 5.82s/it]
{'loss': 0.5183, 'learning_rate': 1.9922068141825864e-05, 'epoch': 0.07}
+
7%|▋ | 820/11952 [1:23:28<18:00:12, 5.82s/it]
7%|▋ | 821/11952 [1:23:34<17:56:14, 5.80s/it]
{'loss': 0.5055, 'learning_rate': 1.9921730118175443e-05, 'epoch': 0.07}
+
7%|▋ | 821/11952 [1:23:34<17:56:14, 5.80s/it]
7%|▋ | 822/11952 [1:23:40<17:54:17, 5.79s/it]
{'loss': 0.5416, 'learning_rate': 1.9921391365914426e-05, 'epoch': 0.07}
+
7%|▋ | 822/11952 [1:23:40<17:54:17, 5.79s/it]
7%|▋ | 823/11952 [1:23:46<17:58:00, 5.81s/it]
{'loss': 0.5098, 'learning_rate': 1.9921051885067695e-05, 'epoch': 0.07}
+
7%|▋ | 823/11952 [1:23:46<17:58:00, 5.81s/it]
7%|▋ | 824/11952 [1:23:51<17:47:41, 5.76s/it]
{'loss': 0.543, 'learning_rate': 1.9920711675660178e-05, 'epoch': 0.07}
+
7%|▋ | 824/11952 [1:23:51<17:47:41, 5.76s/it]
7%|▋ | 825/11952 [1:23:57<17:58:11, 5.81s/it]
{'loss': 0.5269, 'learning_rate': 1.992037073771686e-05, 'epoch': 0.07}
+
7%|▋ | 825/11952 [1:23:57<17:58:11, 5.81s/it]
7%|▋ | 826/11952 [1:24:03<17:51:42, 5.78s/it]
{'loss': 0.4967, 'learning_rate': 1.9920029071262778e-05, 'epoch': 0.07}
+
7%|▋ | 826/11952 [1:24:03<17:51:42, 5.78s/it]
7%|▋ | 827/11952 [1:24:09<17:47:20, 5.76s/it]
{'loss': 0.5036, 'learning_rate': 1.9919686676323015e-05, 'epoch': 0.07}
+
7%|▋ | 827/11952 [1:24:09<17:47:20, 5.76s/it]
7%|▋ | 828/11952 [1:24:14<17:37:24, 5.70s/it]
{'loss': 0.518, 'learning_rate': 1.9919343552922727e-05, 'epoch': 0.07}
+
7%|▋ | 828/11952 [1:24:14<17:37:24, 5.70s/it]
7%|▋ | 829/11952 [1:24:20<17:56:56, 5.81s/it]
{'loss': 0.5273, 'learning_rate': 1.9918999701087104e-05, 'epoch': 0.07}
+
7%|▋ | 829/11952 [1:24:20<17:56:56, 5.81s/it]
7%|▋ | 830/11952 [1:24:26<17:59:11, 5.82s/it]
{'loss': 0.5271, 'learning_rate': 1.9918655120841403e-05, 'epoch': 0.07}
+
7%|▋ | 830/11952 [1:24:26<17:59:11, 5.82s/it]
7%|▋ | 831/11952 [1:24:32<18:00:21, 5.83s/it]
{'loss': 0.5263, 'learning_rate': 1.991830981221092e-05, 'epoch': 0.07}
+
7%|▋ | 831/11952 [1:24:32<18:00:21, 5.83s/it]
7%|▋ | 832/11952 [1:24:38<18:22:04, 5.95s/it]
{'loss': 0.5187, 'learning_rate': 1.991796377522102e-05, 'epoch': 0.07}
+
7%|▋ | 832/11952 [1:24:38<18:22:04, 5.95s/it]
7%|▋ | 833/11952 [1:24:44<18:09:21, 5.88s/it]
{'loss': 0.5042, 'learning_rate': 1.9917617009897113e-05, 'epoch': 0.07}
+
7%|▋ | 833/11952 [1:24:44<18:09:21, 5.88s/it]
7%|▋ | 834/11952 [1:24:49<17:56:09, 5.81s/it]
{'loss': 0.5248, 'learning_rate': 1.9917269516264662e-05, 'epoch': 0.07}
+
7%|▋ | 834/11952 [1:24:49<17:56:09, 5.81s/it]
7%|▋ | 835/11952 [1:24:55<17:46:37, 5.76s/it]
{'loss': 0.4992, 'learning_rate': 1.9916921294349187e-05, 'epoch': 0.07}
+
7%|▋ | 835/11952 [1:24:55<17:46:37, 5.76s/it]
7%|▋ | 836/11952 [1:25:01<17:41:13, 5.73s/it]
{'loss': 0.5347, 'learning_rate': 1.9916572344176258e-05, 'epoch': 0.07}
+
7%|▋ | 836/11952 [1:25:01<17:41:13, 5.73s/it]
7%|▋ | 837/11952 [1:25:07<18:03:49, 5.85s/it]
{'loss': 0.5343, 'learning_rate': 1.9916222665771506e-05, 'epoch': 0.07}
+
7%|▋ | 837/11952 [1:25:07<18:03:49, 5.85s/it]
7%|▋ | 838/11952 [1:25:13<18:01:32, 5.84s/it]
{'loss': 0.511, 'learning_rate': 1.9915872259160603e-05, 'epoch': 0.07}
+
7%|▋ | 838/11952 [1:25:13<18:01:32, 5.84s/it]
7%|▋ | 839/11952 [1:25:19<18:24:38, 5.96s/it]
{'loss': 0.5374, 'learning_rate': 1.991552112436929e-05, 'epoch': 0.07}
+
7%|▋ | 839/11952 [1:25:19<18:24:38, 5.96s/it]
7%|▋ | 840/11952 [1:25:25<18:23:10, 5.96s/it]
{'loss': 0.5074, 'learning_rate': 1.991516926142334e-05, 'epoch': 0.07}
+
7%|▋ | 840/11952 [1:25:25<18:23:10, 5.96s/it]
7%|▋ | 841/11952 [1:25:31<18:06:31, 5.87s/it]
{'loss': 0.5287, 'learning_rate': 1.99148166703486e-05, 'epoch': 0.07}
+
7%|▋ | 841/11952 [1:25:31<18:06:31, 5.87s/it]
7%|▋ | 842/11952 [1:25:37<18:17:13, 5.93s/it]
{'loss': 0.5089, 'learning_rate': 1.991446335117097e-05, 'epoch': 0.07}
+
7%|▋ | 842/11952 [1:25:37<18:17:13, 5.93s/it]
7%|▋ | 843/11952 [1:25:43<18:22:54, 5.96s/it]
{'loss': 0.5148, 'learning_rate': 1.991410930391638e-05, 'epoch': 0.07}
+
7%|▋ | 843/11952 [1:25:43<18:22:54, 5.96s/it]
7%|▋ | 844/11952 [1:25:48<18:13:47, 5.91s/it]
{'loss': 0.5282, 'learning_rate': 1.9913754528610846e-05, 'epoch': 0.07}
+
7%|▋ | 844/11952 [1:25:48<18:13:47, 5.91s/it]
7%|▋ | 845/11952 [1:25:54<18:07:51, 5.88s/it]
{'loss': 0.5093, 'learning_rate': 1.991339902528041e-05, 'epoch': 0.07}
+
7%|▋ | 845/11952 [1:25:54<18:07:51, 5.88s/it]
7%|▋ | 846/11952 [1:26:00<17:54:39, 5.81s/it]
{'loss': 0.5292, 'learning_rate': 1.9913042793951184e-05, 'epoch': 0.07}
+
7%|▋ | 846/11952 [1:26:00<17:54:39, 5.81s/it]
7%|▋ | 847/11952 [1:26:06<17:56:09, 5.81s/it]
{'loss': 0.5164, 'learning_rate': 1.9912685834649324e-05, 'epoch': 0.07}
+
7%|▋ | 847/11952 [1:26:06<17:56:09, 5.81s/it]
7%|▋ | 848/11952 [1:26:11<17:51:18, 5.79s/it]
{'loss': 0.5011, 'learning_rate': 1.991232814740105e-05, 'epoch': 0.07}
+
7%|▋ | 848/11952 [1:26:11<17:51:18, 5.79s/it]
7%|▋ | 849/11952 [1:26:17<17:55:36, 5.81s/it]
{'loss': 0.5238, 'learning_rate': 1.991196973223262e-05, 'epoch': 0.07}
+
7%|▋ | 849/11952 [1:26:17<17:55:36, 5.81s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...6
+ AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
7%|▋ | 850/11952 [1:26:23<17:51:43, 5.79s/it]
{'loss': 0.5173, 'learning_rate': 1.9911610589170363e-05, 'epoch': 0.07}
+
7%|▋ | 850/11952 [1:26:23<17:51:43, 5.79s/it]
7%|▋ | 851/11952 [1:26:29<18:18:46, 5.94s/it]
{'loss': 0.5082, 'learning_rate': 1.9911250718240653e-05, 'epoch': 0.07}
+
7%|▋ | 851/11952 [1:26:29<18:18:46, 5.94s/it]
7%|▋ | 852/11952 [1:26:35<18:07:08, 5.88s/it]
{'loss': 0.5063, 'learning_rate': 1.991089011946991e-05, 'epoch': 0.07}
+
7%|▋ | 852/11952 [1:26:35<18:07:08, 5.88s/it]
7%|▋ | 853/11952 [1:26:41<18:05:38, 5.87s/it]
{'loss': 0.5203, 'learning_rate': 1.991052879288462e-05, 'epoch': 0.07}
+
7%|▋ | 853/11952 [1:26:41<18:05:38, 5.87s/it]
7%|▋ | 854/11952 [1:26:47<17:55:30, 5.81s/it]
{'loss': 0.5008, 'learning_rate': 1.9910166738511315e-05, 'epoch': 0.07}
+
7%|▋ | 854/11952 [1:26:47<17:55:30, 5.81s/it]
7%|▋ | 855/11952 [1:26:53<18:06:52, 5.88s/it]
{'loss': 0.5135, 'learning_rate': 1.9909803956376588e-05, 'epoch': 0.07}
+
7%|▋ | 855/11952 [1:26:53<18:06:52, 5.88s/it]
7%|▋ | 856/11952 [1:26:59<18:08:58, 5.89s/it]
{'loss': 0.5087, 'learning_rate': 1.9909440446507074e-05, 'epoch': 0.07}
+
7%|▋ | 856/11952 [1:26:59<18:08:58, 5.89s/it]
7%|▋ | 857/11952 [1:27:04<17:58:21, 5.83s/it]
{'loss': 0.5175, 'learning_rate': 1.990907620892947e-05, 'epoch': 0.07}
+
7%|▋ | 857/11952 [1:27:04<17:58:21, 5.83s/it]
7%|▋ | 858/11952 [1:27:10<17:55:45, 5.82s/it]
{'loss': 0.5173, 'learning_rate': 1.9908711243670526e-05, 'epoch': 0.07}
+
7%|▋ | 858/11952 [1:27:10<17:55:45, 5.82s/it]
7%|▋ | 859/11952 [1:27:16<17:54:03, 5.81s/it]
{'loss': 0.5081, 'learning_rate': 1.990834555075704e-05, 'epoch': 0.07}
+
7%|▋ | 859/11952 [1:27:16<17:54:03, 5.81s/it]
7%|▋ | 860/11952 [1:27:22<18:02:39, 5.86s/it]
{'loss': 0.517, 'learning_rate': 1.9907979130215868e-05, 'epoch': 0.07}
+
7%|▋ | 860/11952 [1:27:22<18:02:39, 5.86s/it]
7%|▋ | 861/11952 [1:27:28<18:04:51, 5.87s/it]
{'loss': 0.5276, 'learning_rate': 1.990761198207392e-05, 'epoch': 0.07}
+
7%|▋ | 861/11952 [1:27:28<18:04:51, 5.87s/it]
7%|▋ | 862/11952 [1:27:33<17:53:44, 5.81s/it]
{'loss': 0.5121, 'learning_rate': 1.9907244106358158e-05, 'epoch': 0.07}
+
7%|▋ | 862/11952 [1:27:33<17:53:44, 5.81s/it]
7%|▋ | 863/11952 [1:27:39<17:57:29, 5.83s/it]
{'loss': 0.5236, 'learning_rate': 1.9906875503095594e-05, 'epoch': 0.07}
+
7%|▋ | 863/11952 [1:27:39<17:57:29, 5.83s/it]
7%|▋ | 864/11952 [1:27:45<17:51:00, 5.80s/it]
{'loss': 0.524, 'learning_rate': 1.99065061723133e-05, 'epoch': 0.07}
+
7%|▋ | 864/11952 [1:27:45<17:51:00, 5.80s/it]
7%|▋ | 865/11952 [1:27:51<17:39:04, 5.73s/it]
{'loss': 0.5112, 'learning_rate': 1.9906136114038398e-05, 'epoch': 0.07}
+
7%|▋ | 865/11952 [1:27:51<17:39:04, 5.73s/it]
7%|▋ | 866/11952 [1:27:57<17:59:33, 5.84s/it]
{'loss': 0.5318, 'learning_rate': 1.990576532829806e-05, 'epoch': 0.07}
+
7%|▋ | 866/11952 [1:27:57<17:59:33, 5.84s/it]
7%|▋ | 867/11952 [1:28:02<18:00:00, 5.85s/it]
{'loss': 0.5188, 'learning_rate': 1.990539381511952e-05, 'epoch': 0.07}
+
7%|▋ | 867/11952 [1:28:02<18:00:00, 5.85s/it]
7%|▋ | 868/11952 [1:28:08<17:49:54, 5.79s/it]
{'loss': 0.5064, 'learning_rate': 1.9905021574530055e-05, 'epoch': 0.07}
+
7%|▋ | 868/11952 [1:28:08<17:49:54, 5.79s/it]
7%|▋ | 869/11952 [1:28:14<18:02:39, 5.86s/it]
{'loss': 0.528, 'learning_rate': 1.9904648606557007e-05, 'epoch': 0.07}
+
7%|▋ | 869/11952 [1:28:14<18:02:39, 5.86s/it]
7%|▋ | 870/11952 [1:28:20<18:13:26, 5.92s/it]
{'loss': 0.5179, 'learning_rate': 1.9904274911227762e-05, 'epoch': 0.07}
+
7%|▋ | 870/11952 [1:28:20<18:13:26, 5.92s/it]
7%|▋ | 871/11952 [1:28:26<18:01:30, 5.86s/it]
{'loss': 0.5177, 'learning_rate': 1.990390048856976e-05, 'epoch': 0.07}
+
7%|▋ | 871/11952 [1:28:26<18:01:30, 5.86s/it]
7%|▋ | 872/11952 [1:28:32<18:03:29, 5.87s/it]
{'loss': 0.516, 'learning_rate': 1.99035253386105e-05, 'epoch': 0.07}
+
7%|▋ | 872/11952 [1:28:32<18:03:29, 5.87s/it]
7%|▋ | 873/11952 [1:28:38<17:57:58, 5.84s/it]
{'loss': 0.525, 'learning_rate': 1.9903149461377532e-05, 'epoch': 0.07}
+
7%|▋ | 873/11952 [1:28:38<17:57:58, 5.84s/it]
7%|▋ | 874/11952 [1:28:43<17:56:29, 5.83s/it]
{'loss': 0.5407, 'learning_rate': 1.9902772856898457e-05, 'epoch': 0.07}
+
7%|▋ | 874/11952 [1:28:43<17:56:29, 5.83s/it]
7%|▋ | 875/11952 [1:28:49<17:53:09, 5.81s/it]
{'loss': 0.5232, 'learning_rate': 1.9902395525200933e-05, 'epoch': 0.07}
+
7%|▋ | 875/11952 [1:28:49<17:53:09, 5.81s/it]
7%|▋ | 876/11952 [1:28:56<18:48:31, 6.11s/it]
{'loss': 0.5302, 'learning_rate': 1.9902017466312668e-05, 'epoch': 0.07}
+
7%|▋ | 876/11952 [1:28:56<18:48:31, 6.11s/it]
7%|▋ | 877/11952 [1:29:02<18:26:00, 5.99s/it]
{'loss': 0.5218, 'learning_rate': 1.9901638680261426e-05, 'epoch': 0.07}
+
7%|▋ | 877/11952 [1:29:02<18:26:00, 5.99s/it]
7%|▋ | 878/11952 [1:29:08<18:17:58, 5.95s/it]
{'loss': 0.5213, 'learning_rate': 1.9901259167075023e-05, 'epoch': 0.07}
+
7%|▋ | 878/11952 [1:29:08<18:17:58, 5.95s/it]
7%|▋ | 879/11952 [1:29:14<18:20:42, 5.96s/it]
{'loss': 0.5346, 'learning_rate': 1.9900878926781327e-05, 'epoch': 0.07}
+
7%|▋ | 879/11952 [1:29:14<18:20:42, 5.96s/it]
7%|▋ | 880/11952 [1:29:19<18:15:29, 5.94s/it]
{'loss': 0.5155, 'learning_rate': 1.990049795940827e-05, 'epoch': 0.07}
+
7%|▋ | 880/11952 [1:29:19<18:15:29, 5.94s/it]
7%|▋ | 881/11952 [1:29:25<17:59:54, 5.85s/it]
{'loss': 0.523, 'learning_rate': 1.9900116264983815e-05, 'epoch': 0.07}
+
7%|▋ | 881/11952 [1:29:25<17:59:54, 5.85s/it]
7%|▋ | 882/11952 [1:29:31<17:55:39, 5.83s/it]
{'loss': 0.5037, 'learning_rate': 1.9899733843536e-05, 'epoch': 0.07}
+
7%|▋ | 882/11952 [1:29:31<17:55:39, 5.83s/it]
7%|▋ | 883/11952 [1:29:37<17:48:06, 5.79s/it]
{'loss': 0.516, 'learning_rate': 1.9899350695092914e-05, 'epoch': 0.07}
+
7%|▋ | 883/11952 [1:29:37<17:48:06, 5.79s/it]
7%|▋ | 884/11952 [1:29:42<17:47:38, 5.79s/it]
{'loss': 0.5274, 'learning_rate': 1.989896681968268e-05, 'epoch': 0.07}
+
7%|▋ | 884/11952 [1:29:42<17:47:38, 5.79s/it]
7%|▋ | 885/11952 [1:29:48<17:51:00, 5.81s/it]
{'loss': 0.5063, 'learning_rate': 1.98985822173335e-05, 'epoch': 0.07}
+
7%|▋ | 885/11952 [1:29:48<17:51:00, 5.81s/it]
7%|▋ | 886/11952 [1:29:54<17:50:58, 5.81s/it]
{'loss': 0.507, 'learning_rate': 1.9898196888073612e-05, 'epoch': 0.07}
+
7%|▋ | 886/11952 [1:29:54<17:50:58, 5.81s/it]
7%|▋ | 887/11952 [1:30:00<17:51:24, 5.81s/it]
{'loss': 0.5332, 'learning_rate': 1.9897810831931314e-05, 'epoch': 0.07}
+
7%|▋ | 887/11952 [1:30:00<17:51:24, 5.81s/it]
7%|▋ | 888/11952 [1:30:06<18:02:12, 5.87s/it]
{'loss': 0.5391, 'learning_rate': 1.989742404893496e-05, 'epoch': 0.07}
+
7%|▋ | 888/11952 [1:30:06<18:02:12, 5.87s/it]
7%|▋ | 889/11952 [1:30:12<18:13:50, 5.93s/it]
{'loss': 0.5041, 'learning_rate': 1.9897036539112945e-05, 'epoch': 0.07}
+
7%|▋ | 889/11952 [1:30:12<18:13:50, 5.93s/it]
7%|▋ | 890/11952 [1:30:18<18:03:36, 5.88s/it]
{'loss': 0.5138, 'learning_rate': 1.9896648302493734e-05, 'epoch': 0.07}
+
7%|▋ | 890/11952 [1:30:18<18:03:36, 5.88s/it]
7%|▋ | 891/11952 [1:30:23<18:00:06, 5.86s/it]
{'loss': 0.5398, 'learning_rate': 1.9896259339105835e-05, 'epoch': 0.07}
+
7%|▋ | 891/11952 [1:30:23<18:00:06, 5.86s/it]
7%|▋ | 892/11952 [1:30:30<18:29:01, 6.02s/it]
{'loss': 0.516, 'learning_rate': 1.9895869648977812e-05, 'epoch': 0.07}
+
7%|▋ | 892/11952 [1:30:30<18:29:01, 6.02s/it]
7%|▋ | 893/11952 [1:30:35<18:08:16, 5.90s/it]
{'loss': 0.5177, 'learning_rate': 1.9895479232138282e-05, 'epoch': 0.07}
+
7%|▋ | 893/11952 [1:30:35<18:08:16, 5.90s/it]
7%|▋ | 894/11952 [1:30:41<18:06:41, 5.90s/it]
{'loss': 0.4917, 'learning_rate': 1.9895088088615915e-05, 'epoch': 0.07}
+
7%|▋ | 894/11952 [1:30:41<18:06:41, 5.90s/it]
7%|▋ | 895/11952 [1:30:47<17:53:01, 5.82s/it]
{'loss': 0.526, 'learning_rate': 1.9894696218439436e-05, 'epoch': 0.07}
+
7%|▋ | 895/11952 [1:30:47<17:53:01, 5.82s/it]
7%|▋ | 896/11952 [1:30:53<18:02:58, 5.88s/it]
{'loss': 0.5205, 'learning_rate': 1.989430362163762e-05, 'epoch': 0.07}
+
7%|▋ | 896/11952 [1:30:53<18:02:58, 5.88s/it]
8%|▊ | 897/11952 [1:30:59<17:54:11, 5.83s/it]
{'loss': 0.5188, 'learning_rate': 1.98939102982393e-05, 'epoch': 0.08}
+
8%|▊ | 897/11952 [1:30:59<17:54:11, 5.83s/it]
8%|▊ | 898/11952 [1:31:05<18:02:22, 5.88s/it]
{'loss': 0.5392, 'learning_rate': 1.9893516248273362e-05, 'epoch': 0.08}
+
8%|▊ | 898/11952 [1:31:05<18:02:22, 5.88s/it]
8%|▊ | 899/11952 [1:31:11<18:06:37, 5.90s/it]
{'loss': 0.5131, 'learning_rate': 1.989312147176874e-05, 'epoch': 0.08}
+
8%|▊ | 899/11952 [1:31:11<18:06:37, 5.90s/it]6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ 3 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
8%|▊ | 900/11952 [1:31:16<17:56:18, 5.84s/it]
{'loss': 0.5156, 'learning_rate': 1.9892725968754426e-05, 'epoch': 0.08}
+
8%|▊ | 900/11952 [1:31:16<17:56:18, 5.84s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
8%|▊ | 901/11952 [1:31:50<43:48:21, 14.27s/it]
{'loss': 0.4967, 'learning_rate': 1.9892329739259462e-05, 'epoch': 0.08}
+
8%|▊ | 901/11952 [1:31:50<43:48:21, 14.27s/it]
8%|▊ | 902/11952 [1:31:56<35:52:52, 11.69s/it]
{'loss': 0.5241, 'learning_rate': 1.9891932783312948e-05, 'epoch': 0.08}
+
8%|▊ | 902/11952 [1:31:56<35:52:52, 11.69s/it]
8%|▊ | 903/11952 [1:32:02<30:16:44, 9.87s/it]
{'loss': 0.5174, 'learning_rate': 1.9891535100944033e-05, 'epoch': 0.08}
+
8%|▊ | 903/11952 [1:32:02<30:16:44, 9.87s/it]
8%|▊ | 904/11952 [1:32:08<26:43:54, 8.71s/it]
{'loss': 0.5355, 'learning_rate': 1.9891136692181926e-05, 'epoch': 0.08}
+
8%|▊ | 904/11952 [1:32:08<26:43:54, 8.71s/it]
8%|▊ | 905/11952 [1:32:14<24:10:24, 7.88s/it]
{'loss': 0.5073, 'learning_rate': 1.989073755705588e-05, 'epoch': 0.08}
+
8%|▊ | 905/11952 [1:32:14<24:10:24, 7.88s/it]
8%|▊ | 906/11952 [1:32:19<22:05:47, 7.20s/it]
{'loss': 0.518, 'learning_rate': 1.9890337695595202e-05, 'epoch': 0.08}
+
8%|▊ | 906/11952 [1:32:19<22:05:47, 7.20s/it]
8%|▊ | 907/11952 [1:32:25<20:40:31, 6.74s/it]
{'loss': 0.5088, 'learning_rate': 1.988993710782926e-05, 'epoch': 0.08}
+
8%|▊ | 907/11952 [1:32:25<20:40:31, 6.74s/it]
8%|▊ | 908/11952 [1:32:31<19:49:22, 6.46s/it]
{'loss': 0.5005, 'learning_rate': 1.988953579378748e-05, 'epoch': 0.08}
+
8%|▊ | 908/11952 [1:32:31<19:49:22, 6.46s/it]
8%|▊ | 909/11952 [1:32:37<19:21:40, 6.31s/it]
{'loss': 0.5177, 'learning_rate': 1.988913375349932e-05, 'epoch': 0.08}
+
8%|▊ | 909/11952 [1:32:37<19:21:40, 6.31s/it]
8%|▊ | 910/11952 [1:32:43<18:58:21, 6.19s/it]
{'loss': 0.5096, 'learning_rate': 1.988873098699431e-05, 'epoch': 0.08}
+
8%|▊ | 910/11952 [1:32:43<18:58:21, 6.19s/it]
8%|▊ | 911/11952 [1:32:49<18:50:12, 6.14s/it]
{'loss': 0.5153, 'learning_rate': 1.9888327494302025e-05, 'epoch': 0.08}
+
8%|▊ | 911/11952 [1:32:49<18:50:12, 6.14s/it]
8%|▊ | 912/11952 [1:32:54<18:35:33, 6.06s/it]
{'loss': 0.5335, 'learning_rate': 1.98879232754521e-05, 'epoch': 0.08}
+
8%|▊ | 912/11952 [1:32:54<18:35:33, 6.06s/it]
8%|▊ | 913/11952 [1:33:00<18:33:38, 6.05s/it]
{'loss': 0.5308, 'learning_rate': 1.9887518330474216e-05, 'epoch': 0.08}
+
8%|▊ | 913/11952 [1:33:00<18:33:38, 6.05s/it]
8%|▊ | 914/11952 [1:33:06<18:30:55, 6.04s/it]
{'loss': 0.5303, 'learning_rate': 1.9887112659398108e-05, 'epoch': 0.08}
+
8%|▊ | 914/11952 [1:33:06<18:30:55, 6.04s/it]
8%|▊ | 915/11952 [1:33:12<18:18:41, 5.97s/it]
{'loss': 0.5258, 'learning_rate': 1.9886706262253574e-05, 'epoch': 0.08}
+
8%|▊ | 915/11952 [1:33:12<18:18:41, 5.97s/it]
8%|▊ | 916/11952 [1:33:18<18:13:46, 5.95s/it]
{'loss': 0.5278, 'learning_rate': 1.988629913907045e-05, 'epoch': 0.08}
+
8%|▊ | 916/11952 [1:33:18<18:13:46, 5.95s/it]
8%|▊ | 917/11952 [1:33:24<18:10:16, 5.93s/it]
{'loss': 0.5097, 'learning_rate': 1.988589128987864e-05, 'epoch': 0.08}
+
8%|▊ | 917/11952 [1:33:24<18:10:16, 5.93s/it]
8%|▊ | 918/11952 [1:33:30<17:59:50, 5.87s/it]
{'loss': 0.5024, 'learning_rate': 1.9885482714708093e-05, 'epoch': 0.08}
+
8%|▊ | 918/11952 [1:33:30<17:59:50, 5.87s/it]
8%|▊ | 919/11952 [1:33:36<17:56:03, 5.85s/it]
{'loss': 0.5346, 'learning_rate': 1.988507341358881e-05, 'epoch': 0.08}
+
8%|▊ | 919/11952 [1:33:36<17:56:03, 5.85s/it]
8%|▊ | 920/11952 [1:33:41<17:49:13, 5.82s/it]
{'loss': 0.5104, 'learning_rate': 1.9884663386550853e-05, 'epoch': 0.08}
+
8%|▊ | 920/11952 [1:33:41<17:49:13, 5.82s/it]
8%|▊ | 921/11952 [1:33:47<18:03:24, 5.89s/it]
{'loss': 0.5202, 'learning_rate': 1.988425263362433e-05, 'epoch': 0.08}
+
8%|▊ | 921/11952 [1:33:47<18:03:24, 5.89s/it]
8%|▊ | 922/11952 [1:33:53<17:42:26, 5.78s/it]
{'loss': 0.5188, 'learning_rate': 1.98838411548394e-05, 'epoch': 0.08}
+
8%|▊ | 922/11952 [1:33:53<17:42:26, 5.78s/it]
8%|▊ | 923/11952 [1:33:59<17:41:44, 5.78s/it]
{'loss': 0.5121, 'learning_rate': 1.9883428950226294e-05, 'epoch': 0.08}
+
8%|▊ | 923/11952 [1:33:59<17:41:44, 5.78s/it]
8%|▊ | 924/11952 [1:34:05<17:49:19, 5.82s/it]
{'loss': 0.5089, 'learning_rate': 1.9883016019815268e-05, 'epoch': 0.08}
+
8%|▊ | 924/11952 [1:34:05<17:49:19, 5.82s/it]
8%|▊ | 925/11952 [1:34:11<18:00:54, 5.88s/it]
{'loss': 0.5172, 'learning_rate': 1.9882602363636656e-05, 'epoch': 0.08}
+
8%|▊ | 925/11952 [1:34:11<18:00:54, 5.88s/it]
8%|▊ | 926/11952 [1:34:17<18:01:00, 5.88s/it]
{'loss': 0.52, 'learning_rate': 1.9882187981720827e-05, 'epoch': 0.08}
+
8%|▊ | 926/11952 [1:34:17<18:01:00, 5.88s/it]
8%|▊ | 927/11952 [1:34:22<17:44:16, 5.79s/it]
{'loss': 0.5118, 'learning_rate': 1.9881772874098218e-05, 'epoch': 0.08}
+
8%|▊ | 927/11952 [1:34:22<17:44:16, 5.79s/it]
8%|▊ | 928/11952 [1:34:28<17:52:19, 5.84s/it]
{'loss': 0.531, 'learning_rate': 1.9881357040799312e-05, 'epoch': 0.08}
+
8%|▊ | 928/11952 [1:34:28<17:52:19, 5.84s/it]
8%|▊ | 929/11952 [1:34:34<17:46:29, 5.81s/it]
{'loss': 0.5273, 'learning_rate': 1.9880940481854646e-05, 'epoch': 0.08}
+
8%|▊ | 929/11952 [1:34:34<17:46:29, 5.81s/it]
8%|▊ | 930/11952 [1:34:40<18:12:29, 5.95s/it]
{'loss': 0.5082, 'learning_rate': 1.9880523197294804e-05, 'epoch': 0.08}
+
8%|▊ | 930/11952 [1:34:40<18:12:29, 5.95s/it]
8%|▊ | 931/11952 [1:34:46<18:12:34, 5.95s/it]
{'loss': 0.5142, 'learning_rate': 1.9880105187150435e-05, 'epoch': 0.08}
+
8%|▊ | 931/11952 [1:34:46<18:12:34, 5.95s/it]
8%|▊ | 932/11952 [1:34:52<18:18:30, 5.98s/it]
{'loss': 0.5217, 'learning_rate': 1.987968645145224e-05, 'epoch': 0.08}
+
8%|▊ | 932/11952 [1:34:52<18:18:30, 5.98s/it]
8%|▊ | 933/11952 [1:34:58<18:04:31, 5.91s/it]
{'loss': 0.504, 'learning_rate': 1.987926699023096e-05, 'epoch': 0.08}
+
8%|▊ | 933/11952 [1:34:58<18:04:31, 5.91s/it]
8%|▊ | 934/11952 [1:35:04<18:02:21, 5.89s/it]
{'loss': 0.5272, 'learning_rate': 1.9878846803517408e-05, 'epoch': 0.08}
+
8%|▊ | 934/11952 [1:35:04<18:02:21, 5.89s/it]
8%|▊ | 935/11952 [1:35:09<17:57:37, 5.87s/it]
{'loss': 0.5336, 'learning_rate': 1.987842589134243e-05, 'epoch': 0.08}
+
8%|▊ | 935/11952 [1:35:09<17:57:37, 5.87s/it]
8%|▊ | 936/11952 [1:35:16<18:13:19, 5.95s/it]
{'loss': 0.5198, 'learning_rate': 1.9878004253736945e-05, 'epoch': 0.08}
+
8%|▊ | 936/11952 [1:35:16<18:13:19, 5.95s/it]
8%|▊ | 937/11952 [1:35:21<17:58:20, 5.87s/it]
{'loss': 0.5233, 'learning_rate': 1.9877581890731915e-05, 'epoch': 0.08}
+
8%|▊ | 937/11952 [1:35:21<17:58:20, 5.87s/it]
8%|▊ | 938/11952 [1:35:27<17:52:05, 5.84s/it]
{'loss': 0.5315, 'learning_rate': 1.987715880235835e-05, 'epoch': 0.08}
+
8%|▊ | 938/11952 [1:35:27<17:52:05, 5.84s/it]
8%|▊ | 939/11952 [1:35:33<17:38:16, 5.77s/it]
{'loss': 0.5072, 'learning_rate': 1.9876734988647334e-05, 'epoch': 0.08}
+
8%|▊ | 939/11952 [1:35:33<17:38:16, 5.77s/it]
8%|▊ | 940/11952 [1:35:38<17:37:47, 5.76s/it]
{'loss': 0.5278, 'learning_rate': 1.9876310449629973e-05, 'epoch': 0.08}
+
8%|▊ | 940/11952 [1:35:38<17:37:47, 5.76s/it]
8%|▊ | 941/11952 [1:35:44<17:42:36, 5.79s/it]
{'loss': 0.5219, 'learning_rate': 1.9875885185337453e-05, 'epoch': 0.08}
+
8%|▊ | 941/11952 [1:35:44<17:42:36, 5.79s/it]
8%|▊ | 942/11952 [1:35:50<17:37:11, 5.76s/it]
{'loss': 0.5161, 'learning_rate': 1.9875459195801e-05, 'epoch': 0.08}
+
8%|▊ | 942/11952 [1:35:50<17:37:11, 5.76s/it]
8%|▊ | 943/11952 [1:35:56<17:26:45, 5.70s/it]
{'loss': 0.5227, 'learning_rate': 1.98750324810519e-05, 'epoch': 0.08}
+
8%|▊ | 943/11952 [1:35:56<17:26:45, 5.70s/it]
8%|▊ | 944/11952 [1:36:02<17:41:57, 5.79s/it]
{'loss': 0.5114, 'learning_rate': 1.987460504112149e-05, 'epoch': 0.08}
+
8%|▊ | 944/11952 [1:36:02<17:41:57, 5.79s/it]
8%|▊ | 945/11952 [1:36:07<17:52:11, 5.84s/it]
{'loss': 0.5262, 'learning_rate': 1.9874176876041157e-05, 'epoch': 0.08}
+
8%|▊ | 945/11952 [1:36:07<17:52:11, 5.84s/it]
8%|▊ | 946/11952 [1:36:14<18:17:30, 5.98s/it]
{'loss': 0.508, 'learning_rate': 1.9873747985842343e-05, 'epoch': 0.08}
+
8%|▊ | 946/11952 [1:36:14<18:17:30, 5.98s/it]
8%|▊ | 947/11952 [1:36:20<18:09:40, 5.94s/it]
{'loss': 0.5422, 'learning_rate': 1.9873318370556546e-05, 'epoch': 0.08}
+
8%|▊ | 947/11952 [1:36:20<18:09:40, 5.94s/it]
8%|▊ | 948/11952 [1:36:25<18:05:25, 5.92s/it]
{'loss': 0.5087, 'learning_rate': 1.9872888030215313e-05, 'epoch': 0.08}
+
8%|▊ | 948/11952 [1:36:26<18:05:25, 5.92s/it]
8%|▊ | 949/11952 [1:36:31<18:04:01, 5.91s/it]
{'loss': 0.5138, 'learning_rate': 1.9872456964850246e-05, 'epoch': 0.08}
+
8%|▊ | 949/11952 [1:36:31<18:04:01, 5.91s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
8%|▊ | 950/11952 [1:36:37<18:08:14, 5.93s/it]
+
{'loss': 0.5138, 'learning_rate': 1.9872025174493003e-05, 'epoch': 0.08}
+
8%|▊ | 950/11952 [1:36:37<18:08:14, 5.93s/it]
8%|▊ | 951/11952 [1:36:43<17:59:04, 5.89s/it]
{'loss': 0.5301, 'learning_rate': 1.9871592659175296e-05, 'epoch': 0.08}
+
8%|▊ | 951/11952 [1:36:43<17:59:04, 5.89s/it]
8%|▊ | 952/11952 [1:36:49<17:59:41, 5.89s/it]
{'loss': 0.4924, 'learning_rate': 1.987115941892888e-05, 'epoch': 0.08}
+
8%|▊ | 952/11952 [1:36:49<17:59:41, 5.89s/it]
8%|▊ | 953/11952 [1:36:55<17:53:56, 5.86s/it]
{'loss': 0.5321, 'learning_rate': 1.987072545378557e-05, 'epoch': 0.08}
+
8%|▊ | 953/11952 [1:36:55<17:53:56, 5.86s/it]
8%|▊ | 954/11952 [1:37:01<17:50:36, 5.84s/it]
{'loss': 0.5333, 'learning_rate': 1.9870290763777243e-05, 'epoch': 0.08}
+
8%|▊ | 954/11952 [1:37:01<17:50:36, 5.84s/it]
8%|▊ | 955/11952 [1:37:06<17:49:55, 5.84s/it]
{'loss': 0.5032, 'learning_rate': 1.9869855348935817e-05, 'epoch': 0.08}
+
8%|▊ | 955/11952 [1:37:06<17:49:55, 5.84s/it]
8%|▊ | 956/11952 [1:37:12<17:52:43, 5.85s/it]
{'loss': 0.5294, 'learning_rate': 1.986941920929326e-05, 'epoch': 0.08}
+
8%|▊ | 956/11952 [1:37:12<17:52:43, 5.85s/it]
8%|▊ | 957/11952 [1:37:18<17:38:28, 5.78s/it]
{'loss': 0.5085, 'learning_rate': 1.986898234488161e-05, 'epoch': 0.08}
+
8%|▊ | 957/11952 [1:37:18<17:38:28, 5.78s/it]
8%|▊ | 958/11952 [1:37:24<17:34:43, 5.76s/it]
{'loss': 0.4924, 'learning_rate': 1.9868544755732948e-05, 'epoch': 0.08}
+
8%|▊ | 958/11952 [1:37:24<17:34:43, 5.76s/it]
8%|▊ | 959/11952 [1:37:30<17:53:56, 5.86s/it]
{'loss': 0.496, 'learning_rate': 1.9868106441879403e-05, 'epoch': 0.08}
+
8%|▊ | 959/11952 [1:37:30<17:53:56, 5.86s/it]
8%|▊ | 960/11952 [1:37:35<17:40:12, 5.79s/it]
{'loss': 0.5076, 'learning_rate': 1.9867667403353162e-05, 'epoch': 0.08}
+
8%|▊ | 960/11952 [1:37:35<17:40:12, 5.79s/it]
8%|▊ | 961/11952 [1:37:41<17:46:09, 5.82s/it]
{'loss': 0.5201, 'learning_rate': 1.9867227640186474e-05, 'epoch': 0.08}
+
8%|▊ | 961/11952 [1:37:41<17:46:09, 5.82s/it]
8%|▊ | 962/11952 [1:37:47<17:42:31, 5.80s/it]
{'loss': 0.5204, 'learning_rate': 1.9866787152411624e-05, 'epoch': 0.08}
+
8%|▊ | 962/11952 [1:37:47<17:42:31, 5.80s/it]
8%|▊ | 963/11952 [1:37:53<17:50:31, 5.85s/it]
{'loss': 0.5269, 'learning_rate': 1.986634594006097e-05, 'epoch': 0.08}
+
8%|▊ | 963/11952 [1:37:53<17:50:31, 5.85s/it]
8%|▊ | 964/11952 [1:37:59<17:51:44, 5.85s/it]
{'loss': 0.5226, 'learning_rate': 1.9865904003166904e-05, 'epoch': 0.08}
+
8%|▊ | 964/11952 [1:37:59<17:51:44, 5.85s/it]
8%|▊ | 965/11952 [1:38:05<17:50:02, 5.84s/it]
{'loss': 0.5212, 'learning_rate': 1.9865461341761885e-05, 'epoch': 0.08}
+
8%|▊ | 965/11952 [1:38:05<17:50:02, 5.84s/it]
8%|▊ | 966/11952 [1:38:11<17:56:03, 5.88s/it]
{'loss': 0.5216, 'learning_rate': 1.986501795587842e-05, 'epoch': 0.08}
+
8%|▊ | 966/11952 [1:38:11<17:56:03, 5.88s/it]
8%|▊ | 967/11952 [1:38:17<18:05:27, 5.93s/it]
{'loss': 0.5174, 'learning_rate': 1.9864573845549063e-05, 'epoch': 0.08}
+
8%|▊ | 967/11952 [1:38:17<18:05:27, 5.93s/it]
8%|▊ | 968/11952 [1:38:23<18:25:12, 6.04s/it]
{'loss': 0.5356, 'learning_rate': 1.9864129010806437e-05, 'epoch': 0.08}
+
8%|▊ | 968/11952 [1:38:23<18:25:12, 6.04s/it]
8%|▊ | 969/11952 [1:38:29<18:03:53, 5.92s/it]
{'loss': 0.4997, 'learning_rate': 1.9863683451683204e-05, 'epoch': 0.08}
+
8%|▊ | 969/11952 [1:38:29<18:03:53, 5.92s/it]
8%|▊ | 970/11952 [1:38:35<18:10:41, 5.96s/it]
{'loss': 0.5137, 'learning_rate': 1.9863237168212084e-05, 'epoch': 0.08}
+
8%|▊ | 970/11952 [1:38:35<18:10:41, 5.96s/it]
8%|▊ | 971/11952 [1:38:41<18:19:16, 6.01s/it]
{'loss': 0.5368, 'learning_rate': 1.986279016042585e-05, 'epoch': 0.08}
+
8%|▊ | 971/11952 [1:38:41<18:19:16, 6.01s/it]
8%|▊ | 972/11952 [1:38:47<18:18:52, 6.00s/it]
{'loss': 0.5209, 'learning_rate': 1.9862342428357327e-05, 'epoch': 0.08}
+
8%|▊ | 972/11952 [1:38:47<18:18:52, 6.00s/it]
8%|▊ | 973/11952 [1:38:52<18:01:47, 5.91s/it]
{'loss': 0.5135, 'learning_rate': 1.9861893972039402e-05, 'epoch': 0.08}
+
8%|▊ | 973/11952 [1:38:52<18:01:47, 5.91s/it]
8%|▊ | 974/11952 [1:38:58<17:44:06, 5.82s/it]
{'loss': 0.517, 'learning_rate': 1.9861444791504997e-05, 'epoch': 0.08}
+
8%|▊ | 974/11952 [1:38:58<17:44:06, 5.82s/it]
8%|▊ | 975/11952 [1:39:04<17:41:51, 5.80s/it]
{'loss': 0.5308, 'learning_rate': 1.9860994886787106e-05, 'epoch': 0.08}
+
8%|▊ | 975/11952 [1:39:04<17:41:51, 5.80s/it]
8%|▊ | 976/11952 [1:39:10<17:46:11, 5.83s/it]
{'loss': 0.5223, 'learning_rate': 1.9860544257918765e-05, 'epoch': 0.08}
+
8%|▊ | 976/11952 [1:39:10<17:46:11, 5.83s/it]
8%|▊ | 977/11952 [1:39:16<17:49:32, 5.85s/it]
{'loss': 0.5231, 'learning_rate': 1.9860092904933065e-05, 'epoch': 0.08}
+
8%|▊ | 977/11952 [1:39:16<17:49:32, 5.85s/it]
8%|▊ | 978/11952 [1:39:21<17:44:35, 5.82s/it]
{'loss': 0.5187, 'learning_rate': 1.9859640827863157e-05, 'epoch': 0.08}
+
8%|▊ | 978/11952 [1:39:21<17:44:35, 5.82s/it]
8%|▊ | 979/11952 [1:39:27<17:22:53, 5.70s/it]
{'loss': 0.524, 'learning_rate': 1.9859188026742235e-05, 'epoch': 0.08}
+
8%|▊ | 979/11952 [1:39:27<17:22:53, 5.70s/it]
8%|▊ | 980/11952 [1:39:33<17:29:49, 5.74s/it]
{'loss': 0.5258, 'learning_rate': 1.9858734501603553e-05, 'epoch': 0.08}
+
8%|▊ | 980/11952 [1:39:33<17:29:49, 5.74s/it]
8%|▊ | 981/11952 [1:39:38<17:33:18, 5.76s/it]
{'loss': 0.5138, 'learning_rate': 1.985828025248041e-05, 'epoch': 0.08}
+
8%|▊ | 981/11952 [1:39:38<17:33:18, 5.76s/it]
8%|▊ | 982/11952 [1:39:44<17:41:35, 5.81s/it]
{'loss': 0.5222, 'learning_rate': 1.985782527940617e-05, 'epoch': 0.08}
+
8%|▊ | 982/11952 [1:39:44<17:41:35, 5.81s/it]
8%|▊ | 983/11952 [1:39:50<17:45:41, 5.83s/it]
{'loss': 0.5048, 'learning_rate': 1.9857369582414246e-05, 'epoch': 0.08}
+
8%|▊ | 983/11952 [1:39:50<17:45:41, 5.83s/it]
8%|▊ | 984/11952 [1:39:56<17:36:19, 5.78s/it]
{'loss': 0.498, 'learning_rate': 1.98569131615381e-05, 'epoch': 0.08}
+
8%|▊ | 984/11952 [1:39:56<17:36:19, 5.78s/it]
8%|▊ | 985/11952 [1:40:02<17:45:23, 5.83s/it]
{'loss': 0.5268, 'learning_rate': 1.985645601681125e-05, 'epoch': 0.08}
+
8%|▊ | 985/11952 [1:40:02<17:45:23, 5.83s/it]
8%|▊ | 986/11952 [1:40:08<17:36:18, 5.78s/it]
{'loss': 0.5111, 'learning_rate': 1.9855998148267265e-05, 'epoch': 0.08}
+
8%|▊ | 986/11952 [1:40:08<17:36:18, 5.78s/it]
8%|▊ | 987/11952 [1:40:13<17:38:53, 5.79s/it]
{'loss': 0.5131, 'learning_rate': 1.9855539555939768e-05, 'epoch': 0.08}
+
8%|▊ | 987/11952 [1:40:13<17:38:53, 5.79s/it]
8%|▊ | 988/11952 [1:40:19<17:29:10, 5.74s/it]
{'loss': 0.5085, 'learning_rate': 1.985508023986244e-05, 'epoch': 0.08}
+
8%|▊ | 988/11952 [1:40:19<17:29:10, 5.74s/it]
8%|▊ | 989/11952 [1:40:25<17:30:50, 5.75s/it]
{'loss': 0.4973, 'learning_rate': 1.985462020006901e-05, 'epoch': 0.08}
+
8%|▊ | 989/11952 [1:40:25<17:30:50, 5.75s/it]
8%|▊ | 990/11952 [1:40:31<17:36:02, 5.78s/it]
{'loss': 0.5084, 'learning_rate': 1.9854159436593258e-05, 'epoch': 0.08}
+
8%|▊ | 990/11952 [1:40:31<17:36:02, 5.78s/it]
8%|▊ | 991/11952 [1:40:36<17:27:47, 5.74s/it]
{'loss': 0.499, 'learning_rate': 1.9853697949469027e-05, 'epoch': 0.08}
+
8%|▊ | 991/11952 [1:40:36<17:27:47, 5.74s/it]
8%|▊ | 992/11952 [1:40:42<17:43:24, 5.82s/it]
{'loss': 0.5203, 'learning_rate': 1.98532357387302e-05, 'epoch': 0.08}
+
8%|▊ | 992/11952 [1:40:42<17:43:24, 5.82s/it]
8%|▊ | 993/11952 [1:40:48<17:42:59, 5.82s/it]
{'loss': 0.4915, 'learning_rate': 1.9852772804410728e-05, 'epoch': 0.08}
+
8%|▊ | 993/11952 [1:40:48<17:42:59, 5.82s/it]
8%|▊ | 994/11952 [1:40:54<17:41:41, 5.81s/it]
{'loss': 0.5183, 'learning_rate': 1.98523091465446e-05, 'epoch': 0.08}
+
8%|▊ | 994/11952 [1:40:54<17:41:41, 5.81s/it]
8%|▊ | 995/11952 [1:40:59<17:31:19, 5.76s/it]
{'loss': 0.505, 'learning_rate': 1.9851844765165863e-05, 'epoch': 0.08}
+
8%|▊ | 995/11952 [1:40:59<17:31:19, 5.76s/it]
8%|▊ | 996/11952 [1:41:05<17:38:52, 5.80s/it]
{'loss': 0.5046, 'learning_rate': 1.9851379660308624e-05, 'epoch': 0.08}
+
8%|▊ | 996/11952 [1:41:05<17:38:52, 5.80s/it]
8%|▊ | 997/11952 [1:41:11<17:45:49, 5.84s/it]
{'loss': 0.515, 'learning_rate': 1.9850913832007042e-05, 'epoch': 0.08}
+
8%|▊ | 997/11952 [1:41:11<17:45:49, 5.84s/it]
8%|▊ | 998/11952 [1:41:17<17:46:53, 5.84s/it]
{'loss': 0.503, 'learning_rate': 1.985044728029532e-05, 'epoch': 0.08}
+
8%|▊ | 998/11952 [1:41:17<17:46:53, 5.84s/it]
8%|▊ | 999/11952 [1:41:23<17:48:35, 5.85s/it]
{'loss': 0.5179, 'learning_rate': 1.984998000520772e-05, 'epoch': 0.08}
+
8%|▊ | 999/11952 [1:41:23<17:48:35, 5.85s/it]5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+47 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
8%|▊ | 1000/11952 [1:41:29<18:04:19, 5.94s/it]
{'loss': 0.5145, 'learning_rate': 1.9849512006778557e-05, 'epoch': 0.08}
+
8%|▊ | 1000/11952 [1:41:29<18:04:19, 5.94s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
8%|▊ | 1001/11952 [1:41:59<40:16:08, 13.24s/it]
{'loss': 0.5222, 'learning_rate': 1.9849043285042203e-05, 'epoch': 0.08}
+
8%|▊ | 1001/11952 [1:41:59<40:16:08, 13.24s/it]
8%|▊ | 1002/11952 [1:42:05<33:14:16, 10.93s/it]
{'loss': 0.4923, 'learning_rate': 1.9848573840033068e-05, 'epoch': 0.08}
+
8%|▊ | 1002/11952 [1:42:05<33:14:16, 10.93s/it]
8%|▊ | 1003/11952 [1:42:11<28:27:20, 9.36s/it]
{'loss': 0.5156, 'learning_rate': 1.984810367178564e-05, 'epoch': 0.08}
+
8%|▊ | 1003/11952 [1:42:11<28:27:20, 9.36s/it]
8%|▊ | 1004/11952 [1:42:16<25:05:31, 8.25s/it]
{'loss': 0.5181, 'learning_rate': 1.984763278033444e-05, 'epoch': 0.08}
+
8%|▊ | 1004/11952 [1:42:16<25:05:31, 8.25s/it]
8%|▊ | 1005/11952 [1:42:22<22:44:06, 7.48s/it]
{'loss': 0.5291, 'learning_rate': 1.9847161165714043e-05, 'epoch': 0.08}
+
8%|▊ | 1005/11952 [1:42:22<22:44:06, 7.48s/it]
8%|▊ | 1006/11952 [1:42:28<21:06:23, 6.94s/it]
{'loss': 0.5196, 'learning_rate': 1.984668882795909e-05, 'epoch': 0.08}
+
8%|▊ | 1006/11952 [1:42:28<21:06:23, 6.94s/it]
8%|▊ | 1007/11952 [1:42:33<19:50:52, 6.53s/it]
{'loss': 0.5165, 'learning_rate': 1.9846215767104266e-05, 'epoch': 0.08}
+
8%|▊ | 1007/11952 [1:42:33<19:50:52, 6.53s/it]
8%|▊ | 1008/11952 [1:42:39<19:10:02, 6.31s/it]
{'loss': 0.5066, 'learning_rate': 1.984574198318431e-05, 'epoch': 0.08}
+
8%|▊ | 1008/11952 [1:42:39<19:10:02, 6.31s/it]
8%|▊ | 1009/11952 [1:42:45<18:42:03, 6.15s/it]
{'loss': 0.5345, 'learning_rate': 1.9845267476234013e-05, 'epoch': 0.08}
+
8%|▊ | 1009/11952 [1:42:45<18:42:03, 6.15s/it]
8%|▊ | 1010/11952 [1:42:51<18:26:43, 6.07s/it]
{'loss': 0.5275, 'learning_rate': 1.984479224628822e-05, 'epoch': 0.08}
+
8%|▊ | 1010/11952 [1:42:51<18:26:43, 6.07s/it]
8%|▊ | 1011/11952 [1:42:57<18:10:43, 5.98s/it]
{'loss': 0.5111, 'learning_rate': 1.9844316293381834e-05, 'epoch': 0.08}
+
8%|▊ | 1011/11952 [1:42:57<18:10:43, 5.98s/it]
8%|▊ | 1012/11952 [1:43:03<18:13:50, 6.00s/it]
{'loss': 0.4976, 'learning_rate': 1.9843839617549805e-05, 'epoch': 0.08}
+
8%|▊ | 1012/11952 [1:43:03<18:13:50, 6.00s/it]
8%|▊ | 1013/11952 [1:43:08<18:01:23, 5.93s/it]
{'loss': 0.5251, 'learning_rate': 1.984336221882714e-05, 'epoch': 0.08}
+
8%|▊ | 1013/11952 [1:43:08<18:01:23, 5.93s/it]
8%|▊ | 1014/11952 [1:43:14<17:47:38, 5.86s/it]
{'loss': 0.5083, 'learning_rate': 1.9842884097248892e-05, 'epoch': 0.08}
+
8%|▊ | 1014/11952 [1:43:14<17:47:38, 5.86s/it]
8%|▊ | 1015/11952 [1:43:20<17:55:37, 5.90s/it]
{'loss': 0.5086, 'learning_rate': 1.9842405252850175e-05, 'epoch': 0.08}
+
8%|▊ | 1015/11952 [1:43:20<17:55:37, 5.90s/it]
9%|▊ | 1016/11952 [1:43:26<18:02:57, 5.94s/it]
{'loss': 0.535, 'learning_rate': 1.984192568566616e-05, 'epoch': 0.09}
+
9%|▊ | 1016/11952 [1:43:26<18:02:57, 5.94s/it]
9%|▊ | 1017/11952 [1:43:32<18:01:41, 5.94s/it]
{'loss': 0.5005, 'learning_rate': 1.9841445395732054e-05, 'epoch': 0.09}
+
9%|▊ | 1017/11952 [1:43:32<18:01:41, 5.94s/it]
9%|▊ | 1018/11952 [1:43:38<17:45:17, 5.85s/it]
{'loss': 0.5042, 'learning_rate': 1.984096438308313e-05, 'epoch': 0.09}
+
9%|▊ | 1018/11952 [1:43:38<17:45:17, 5.85s/it]
9%|▊ | 1019/11952 [1:43:43<17:35:04, 5.79s/it]
{'loss': 0.5152, 'learning_rate': 1.9840482647754716e-05, 'epoch': 0.09}
+
9%|▊ | 1019/11952 [1:43:43<17:35:04, 5.79s/it]
9%|▊ | 1020/11952 [1:43:49<17:52:50, 5.89s/it]
{'loss': 0.5217, 'learning_rate': 1.9840000189782184e-05, 'epoch': 0.09}
+
9%|▊ | 1020/11952 [1:43:49<17:52:50, 5.89s/it]
9%|▊ | 1021/11952 [1:43:55<17:56:18, 5.91s/it]
{'loss': 0.5063, 'learning_rate': 1.983951700920097e-05, 'epoch': 0.09}
+
9%|▊ | 1021/11952 [1:43:55<17:56:18, 5.91s/it]
9%|▊ | 1022/11952 [1:44:01<17:52:26, 5.89s/it]
{'loss': 0.5153, 'learning_rate': 1.9839033106046548e-05, 'epoch': 0.09}
+
9%|▊ | 1022/11952 [1:44:01<17:52:26, 5.89s/it]
9%|▊ | 1023/11952 [1:44:07<17:42:45, 5.83s/it]
{'loss': 0.5272, 'learning_rate': 1.983854848035446e-05, 'epoch': 0.09}
+
9%|▊ | 1023/11952 [1:44:07<17:42:45, 5.83s/it]
9%|▊ | 1024/11952 [1:44:13<18:01:43, 5.94s/it]
{'loss': 0.5123, 'learning_rate': 1.9838063132160292e-05, 'epoch': 0.09}
+
9%|▊ | 1024/11952 [1:44:13<18:01:43, 5.94s/it]
9%|▊ | 1025/11952 [1:44:19<17:48:26, 5.87s/it]
{'loss': 0.5136, 'learning_rate': 1.983757706149969e-05, 'epoch': 0.09}
+
9%|▊ | 1025/11952 [1:44:19<17:48:26, 5.87s/it]
9%|▊ | 1026/11952 [1:44:24<17:36:49, 5.80s/it]
{'loss': 0.5199, 'learning_rate': 1.9837090268408342e-05, 'epoch': 0.09}
+
9%|▊ | 1026/11952 [1:44:24<17:36:49, 5.80s/it]
9%|▊ | 1027/11952 [1:44:31<17:52:10, 5.89s/it]
{'loss': 0.5092, 'learning_rate': 1.9836602752922004e-05, 'epoch': 0.09}
+
9%|▊ | 1027/11952 [1:44:31<17:52:10, 5.89s/it]
9%|▊ | 1028/11952 [1:44:37<17:59:30, 5.93s/it]
{'loss': 0.5272, 'learning_rate': 1.9836114515076473e-05, 'epoch': 0.09}
+
9%|▊ | 1028/11952 [1:44:37<17:59:30, 5.93s/it]
9%|▊ | 1029/11952 [1:44:43<18:04:03, 5.95s/it]
{'loss': 0.5041, 'learning_rate': 1.98356255549076e-05, 'epoch': 0.09}
+
9%|▊ | 1029/11952 [1:44:43<18:04:03, 5.95s/it]
9%|▊ | 1030/11952 [1:44:48<17:57:55, 5.92s/it]
{'loss': 0.529, 'learning_rate': 1.98351358724513e-05, 'epoch': 0.09}
+
9%|▊ | 1030/11952 [1:44:48<17:57:55, 5.92s/it]
9%|▊ | 1031/11952 [1:44:54<17:57:10, 5.92s/it]
{'loss': 0.5032, 'learning_rate': 1.9834645467743524e-05, 'epoch': 0.09}
+
9%|▊ | 1031/11952 [1:44:54<17:57:10, 5.92s/it]
9%|▊ | 1032/11952 [1:45:00<17:48:27, 5.87s/it]
{'loss': 0.5256, 'learning_rate': 1.9834154340820296e-05, 'epoch': 0.09}
+
9%|▊ | 1032/11952 [1:45:00<17:48:27, 5.87s/it]
9%|▊ | 1033/11952 [1:45:06<17:46:39, 5.86s/it]
{'loss': 0.5248, 'learning_rate': 1.983366249171767e-05, 'epoch': 0.09}
+
9%|▊ | 1033/11952 [1:45:06<17:46:39, 5.86s/it]
9%|▊ | 1034/11952 [1:45:12<17:33:44, 5.79s/it]
{'loss': 0.5205, 'learning_rate': 1.9833169920471778e-05, 'epoch': 0.09}
+
9%|▊ | 1034/11952 [1:45:12<17:33:44, 5.79s/it]
9%|▊ | 1035/11952 [1:45:17<17:40:08, 5.83s/it]
{'loss': 0.5149, 'learning_rate': 1.9832676627118784e-05, 'epoch': 0.09}
+
9%|▊ | 1035/11952 [1:45:17<17:40:08, 5.83s/it]
9%|▊ | 1036/11952 [1:45:23<17:34:14, 5.79s/it]
{'loss': 0.5022, 'learning_rate': 1.9832182611694916e-05, 'epoch': 0.09}
+
9%|▊ | 1036/11952 [1:45:23<17:34:14, 5.79s/it]
9%|▊ | 1037/11952 [1:45:29<17:40:13, 5.83s/it]
{'loss': 0.5143, 'learning_rate': 1.983168787423645e-05, 'epoch': 0.09}
+
9%|▊ | 1037/11952 [1:45:29<17:40:13, 5.83s/it]
9%|▊ | 1038/11952 [1:45:35<17:54:05, 5.90s/it]
{'loss': 0.5363, 'learning_rate': 1.9831192414779724e-05, 'epoch': 0.09}
+
9%|▊ | 1038/11952 [1:45:35<17:54:05, 5.90s/it]
9%|▊ | 1039/11952 [1:45:41<17:38:22, 5.82s/it]
{'loss': 0.4941, 'learning_rate': 1.9830696233361113e-05, 'epoch': 0.09}
+
9%|▊ | 1039/11952 [1:45:41<17:38:22, 5.82s/it]
9%|▊ | 1040/11952 [1:45:46<17:27:05, 5.76s/it]
{'loss': 0.5166, 'learning_rate': 1.9830199330017063e-05, 'epoch': 0.09}
+
9%|▊ | 1040/11952 [1:45:46<17:27:05, 5.76s/it]
9%|▊ | 1041/11952 [1:45:52<17:29:51, 5.77s/it]
{'loss': 0.5323, 'learning_rate': 1.982970170478406e-05, 'epoch': 0.09}
+
9%|▊ | 1041/11952 [1:45:52<17:29:51, 5.77s/it]
9%|▊ | 1042/11952 [1:45:58<17:54:27, 5.91s/it]
{'loss': 0.5265, 'learning_rate': 1.9829203357698647e-05, 'epoch': 0.09}
+
9%|▊ | 1042/11952 [1:45:58<17:54:27, 5.91s/it]
9%|▊ | 1043/11952 [1:46:04<17:41:00, 5.84s/it]
{'loss': 0.5111, 'learning_rate': 1.9828704288797425e-05, 'epoch': 0.09}
+
9%|▊ | 1043/11952 [1:46:04<17:41:00, 5.84s/it]
9%|▊ | 1044/11952 [1:46:10<17:54:32, 5.91s/it]
{'loss': 0.5161, 'learning_rate': 1.982820449811704e-05, 'epoch': 0.09}
+
9%|▊ | 1044/11952 [1:46:10<17:54:32, 5.91s/it]
9%|▊ | 1045/11952 [1:46:16<17:45:02, 5.86s/it]
{'loss': 0.5233, 'learning_rate': 1.9827703985694194e-05, 'epoch': 0.09}
+
9%|▊ | 1045/11952 [1:46:16<17:45:02, 5.86s/it]
9%|▉ | 1046/11952 [1:46:22<17:43:25, 5.85s/it]
{'loss': 0.5273, 'learning_rate': 1.9827202751565644e-05, 'epoch': 0.09}
+
9%|▉ | 1046/11952 [1:46:22<17:43:25, 5.85s/it]
9%|▉ | 1047/11952 [1:46:27<17:25:03, 5.75s/it]
{'loss': 0.5168, 'learning_rate': 1.9826700795768197e-05, 'epoch': 0.09}
+
9%|▉ | 1047/11952 [1:46:27<17:25:03, 5.75s/it]
9%|▉ | 1048/11952 [1:46:33<17:26:38, 5.76s/it]
{'loss': 0.504, 'learning_rate': 1.982619811833872e-05, 'epoch': 0.09}
+
9%|▉ | 1048/11952 [1:46:33<17:26:38, 5.76s/it]
9%|▉ | 1049/11952 [1:46:39<17:37:42, 5.82s/it]
{'loss': 0.5216, 'learning_rate': 1.982569471931412e-05, 'epoch': 0.09}
+
9%|▉ | 1049/11952 [1:46:39<17:37:42, 5.82s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
9%|▉ | 1050/11952 [1:46:45<17:49:05, 5.88s/it]2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5331, 'learning_rate': 1.982519059873137e-05, 'epoch': 0.09}
+
9%|▉ | 1050/11952 [1:46:45<17:49:05, 5.88s/it]
9%|▉ | 1051/11952 [1:46:51<17:43:51, 5.86s/it]
{'loss': 0.5473, 'learning_rate': 1.9824685756627487e-05, 'epoch': 0.09}
+
9%|▉ | 1051/11952 [1:46:51<17:43:51, 5.86s/it]
9%|▉ | 1052/11952 [1:46:57<17:42:54, 5.85s/it]
{'loss': 0.5213, 'learning_rate': 1.9824180193039545e-05, 'epoch': 0.09}
+
9%|▉ | 1052/11952 [1:46:57<17:42:54, 5.85s/it]
9%|▉ | 1053/11952 [1:47:03<17:53:46, 5.91s/it]
{'loss': 0.5104, 'learning_rate': 1.9823673908004673e-05, 'epoch': 0.09}
+
9%|▉ | 1053/11952 [1:47:03<17:53:46, 5.91s/it]
9%|▉ | 1054/11952 [1:47:08<17:40:19, 5.84s/it]
{'loss': 0.5322, 'learning_rate': 1.982316690156005e-05, 'epoch': 0.09}
+
9%|▉ | 1054/11952 [1:47:08<17:40:19, 5.84s/it]
9%|▉ | 1055/11952 [1:47:14<17:49:55, 5.89s/it]
{'loss': 0.52, 'learning_rate': 1.9822659173742904e-05, 'epoch': 0.09}
+
9%|▉ | 1055/11952 [1:47:14<17:49:55, 5.89s/it]
9%|▉ | 1056/11952 [1:47:20<17:40:34, 5.84s/it]
{'loss': 0.5226, 'learning_rate': 1.9822150724590528e-05, 'epoch': 0.09}
+
9%|▉ | 1056/11952 [1:47:20<17:40:34, 5.84s/it]
9%|▉ | 1057/11952 [1:47:26<17:38:32, 5.83s/it]
{'loss': 0.4941, 'learning_rate': 1.9821641554140252e-05, 'epoch': 0.09}
+
9%|▉ | 1057/11952 [1:47:26<17:38:32, 5.83s/it]
9%|▉ | 1058/11952 [1:47:32<17:51:54, 5.90s/it]
{'loss': 0.5173, 'learning_rate': 1.9821131662429476e-05, 'epoch': 0.09}
+
9%|▉ | 1058/11952 [1:47:32<17:51:54, 5.90s/it]
9%|▉ | 1059/11952 [1:47:38<17:48:03, 5.88s/it]
{'loss': 0.5042, 'learning_rate': 1.9820621049495637e-05, 'epoch': 0.09}
+
9%|▉ | 1059/11952 [1:47:38<17:48:03, 5.88s/it]
9%|▉ | 1060/11952 [1:47:44<17:56:28, 5.93s/it]
{'loss': 0.5264, 'learning_rate': 1.9820109715376236e-05, 'epoch': 0.09}
+
9%|▉ | 1060/11952 [1:47:44<17:56:28, 5.93s/it]
9%|▉ | 1061/11952 [1:47:50<18:07:20, 5.99s/it]
{'loss': 0.5155, 'learning_rate': 1.9819597660108823e-05, 'epoch': 0.09}
+
9%|▉ | 1061/11952 [1:47:50<18:07:20, 5.99s/it]
9%|▉ | 1062/11952 [1:47:56<18:00:04, 5.95s/it]
{'loss': 0.5059, 'learning_rate': 1.9819084883731e-05, 'epoch': 0.09}
+
9%|▉ | 1062/11952 [1:47:56<18:00:04, 5.95s/it]
9%|▉ | 1063/11952 [1:48:02<17:52:29, 5.91s/it]
{'loss': 0.5237, 'learning_rate': 1.9818571386280422e-05, 'epoch': 0.09}
+
9%|▉ | 1063/11952 [1:48:02<17:52:29, 5.91s/it]
9%|▉ | 1064/11952 [1:48:07<17:33:18, 5.80s/it]
{'loss': 0.5203, 'learning_rate': 1.9818057167794803e-05, 'epoch': 0.09}
+
9%|▉ | 1064/11952 [1:48:07<17:33:18, 5.80s/it]
9%|▉ | 1065/11952 [1:48:13<17:33:24, 5.81s/it]
{'loss': 0.5128, 'learning_rate': 1.98175422283119e-05, 'epoch': 0.09}
+
9%|▉ | 1065/11952 [1:48:13<17:33:24, 5.81s/it]
9%|▉ | 1066/11952 [1:48:19<17:23:02, 5.75s/it]
{'loss': 0.5125, 'learning_rate': 1.9817026567869527e-05, 'epoch': 0.09}
+
9%|▉ | 1066/11952 [1:48:19<17:23:02, 5.75s/it]
9%|▉ | 1067/11952 [1:48:24<17:23:25, 5.75s/it]
{'loss': 0.5056, 'learning_rate': 1.9816510186505562e-05, 'epoch': 0.09}
+
9%|▉ | 1067/11952 [1:48:24<17:23:25, 5.75s/it]
9%|▉ | 1068/11952 [1:48:30<17:23:06, 5.75s/it]
{'loss': 0.5249, 'learning_rate': 1.9815993084257913e-05, 'epoch': 0.09}
+
9%|▉ | 1068/11952 [1:48:30<17:23:06, 5.75s/it]
9%|▉ | 1069/11952 [1:48:36<17:46:50, 5.88s/it]
{'loss': 0.5111, 'learning_rate': 1.9815475261164563e-05, 'epoch': 0.09}
+
9%|▉ | 1069/11952 [1:48:36<17:46:50, 5.88s/it]
9%|▉ | 1070/11952 [1:48:42<17:26:17, 5.77s/it]
{'loss': 0.5204, 'learning_rate': 1.9814956717263534e-05, 'epoch': 0.09}
+
9%|▉ | 1070/11952 [1:48:42<17:26:17, 5.77s/it]
9%|▉ | 1071/11952 [1:48:48<17:26:51, 5.77s/it]
{'loss': 0.5045, 'learning_rate': 1.9814437452592908e-05, 'epoch': 0.09}
+
9%|▉ | 1071/11952 [1:48:48<17:26:51, 5.77s/it]
9%|▉ | 1072/11952 [1:48:54<17:44:13, 5.87s/it]
{'loss': 0.4943, 'learning_rate': 1.9813917467190817e-05, 'epoch': 0.09}
+
9%|▉ | 1072/11952 [1:48:54<17:44:13, 5.87s/it]
9%|▉ | 1073/11952 [1:49:00<17:50:06, 5.90s/it]
{'loss': 0.5294, 'learning_rate': 1.9813396761095446e-05, 'epoch': 0.09}
+
9%|▉ | 1073/11952 [1:49:00<17:50:06, 5.90s/it]
9%|▉ | 1074/11952 [1:49:06<17:58:58, 5.95s/it]
{'loss': 0.5243, 'learning_rate': 1.9812875334345032e-05, 'epoch': 0.09}
+
9%|▉ | 1074/11952 [1:49:06<17:58:58, 5.95s/it]
9%|▉ | 1075/11952 [1:49:12<18:01:04, 5.96s/it]
{'loss': 0.508, 'learning_rate': 1.981235318697787e-05, 'epoch': 0.09}
+
9%|▉ | 1075/11952 [1:49:12<18:01:04, 5.96s/it]
9%|▉ | 1076/11952 [1:49:17<17:47:21, 5.89s/it]
{'loss': 0.5013, 'learning_rate': 1.98118303190323e-05, 'epoch': 0.09}
+
9%|▉ | 1076/11952 [1:49:17<17:47:21, 5.89s/it]
9%|▉ | 1077/11952 [1:49:23<17:44:44, 5.87s/it]
{'loss': 0.494, 'learning_rate': 1.9811306730546728e-05, 'epoch': 0.09}
+
9%|▉ | 1077/11952 [1:49:23<17:44:44, 5.87s/it]
9%|▉ | 1078/11952 [1:49:29<17:34:37, 5.82s/it]
{'loss': 0.5325, 'learning_rate': 1.9810782421559595e-05, 'epoch': 0.09}
+
9%|▉ | 1078/11952 [1:49:29<17:34:37, 5.82s/it]
9%|▉ | 1079/11952 [1:49:35<17:36:02, 5.83s/it]
{'loss': 0.5255, 'learning_rate': 1.9810257392109405e-05, 'epoch': 0.09}
+
9%|▉ | 1079/11952 [1:49:35<17:36:02, 5.83s/it]
9%|▉ | 1080/11952 [1:49:41<17:40:13, 5.85s/it]
{'loss': 0.5053, 'learning_rate': 1.9809731642234715e-05, 'epoch': 0.09}
+
9%|▉ | 1080/11952 [1:49:41<17:40:13, 5.85s/it]
9%|▉ | 1081/11952 [1:49:46<17:33:18, 5.81s/it]
{'loss': 0.5062, 'learning_rate': 1.9809205171974136e-05, 'epoch': 0.09}
+
9%|▉ | 1081/11952 [1:49:46<17:33:18, 5.81s/it]
9%|▉ | 1082/11952 [1:49:52<17:30:42, 5.80s/it]
{'loss': 0.5201, 'learning_rate': 1.9808677981366334e-05, 'epoch': 0.09}
+
9%|▉ | 1082/11952 [1:49:52<17:30:42, 5.80s/it]
9%|▉ | 1083/11952 [1:49:58<17:18:08, 5.73s/it]
{'loss': 0.4957, 'learning_rate': 1.9808150070450015e-05, 'epoch': 0.09}
+
9%|▉ | 1083/11952 [1:49:58<17:18:08, 5.73s/it]
9%|▉ | 1084/11952 [1:50:03<17:08:41, 5.68s/it]
{'loss': 0.5247, 'learning_rate': 1.980762143926395e-05, 'epoch': 0.09}
+
9%|▉ | 1084/11952 [1:50:03<17:08:41, 5.68s/it]
9%|▉ | 1085/11952 [1:50:09<17:14:12, 5.71s/it]
{'loss': 0.5265, 'learning_rate': 1.9807092087846956e-05, 'epoch': 0.09}
+
9%|▉ | 1085/11952 [1:50:09<17:14:12, 5.71s/it]
9%|▉ | 1086/11952 [1:50:15<17:16:11, 5.72s/it]
{'loss': 0.528, 'learning_rate': 1.9806562016237913e-05, 'epoch': 0.09}
+
9%|▉ | 1086/11952 [1:50:15<17:16:11, 5.72s/it]
9%|▉ | 1087/11952 [1:50:21<17:31:32, 5.81s/it]
{'loss': 0.5301, 'learning_rate': 1.9806031224475743e-05, 'epoch': 0.09}
+
9%|▉ | 1087/11952 [1:50:21<17:31:32, 5.81s/it]
9%|▉ | 1088/11952 [1:50:27<17:36:09, 5.83s/it]
{'loss': 0.5281, 'learning_rate': 1.9805499712599426e-05, 'epoch': 0.09}
+
9%|▉ | 1088/11952 [1:50:27<17:36:09, 5.83s/it]
9%|▉ | 1089/11952 [1:50:33<17:33:53, 5.82s/it]
{'loss': 0.5024, 'learning_rate': 1.9804967480647996e-05, 'epoch': 0.09}
+
9%|▉ | 1089/11952 [1:50:33<17:33:53, 5.82s/it]
9%|▉ | 1090/11952 [1:50:39<17:42:21, 5.87s/it]
{'loss': 0.5087, 'learning_rate': 1.9804434528660536e-05, 'epoch': 0.09}
+
9%|▉ | 1090/11952 [1:50:39<17:42:21, 5.87s/it]
9%|▉ | 1091/11952 [1:50:44<17:34:35, 5.83s/it]
{'loss': 0.5004, 'learning_rate': 1.9803900856676182e-05, 'epoch': 0.09}
+
9%|▉ | 1091/11952 [1:50:44<17:34:35, 5.83s/it]
9%|▉ | 1092/11952 [1:50:50<17:36:36, 5.84s/it]
{'loss': 0.5165, 'learning_rate': 1.980336646473413e-05, 'epoch': 0.09}
+
9%|▉ | 1092/11952 [1:50:50<17:36:36, 5.84s/it]
9%|▉ | 1093/11952 [1:50:56<17:39:58, 5.86s/it]
{'loss': 0.4901, 'learning_rate': 1.980283135287362e-05, 'epoch': 0.09}
+
9%|▉ | 1093/11952 [1:50:56<17:39:58, 5.86s/it]
9%|▉ | 1094/11952 [1:51:02<17:34:25, 5.83s/it]
{'loss': 0.5026, 'learning_rate': 1.9802295521133942e-05, 'epoch': 0.09}
+
9%|▉ | 1094/11952 [1:51:02<17:34:25, 5.83s/it]
9%|▉ | 1095/11952 [1:51:08<17:49:28, 5.91s/it]
{'loss': 0.5191, 'learning_rate': 1.980175896955446e-05, 'epoch': 0.09}
+
9%|▉ | 1095/11952 [1:51:08<17:49:28, 5.91s/it]
9%|▉ | 1096/11952 [1:51:14<17:44:36, 5.88s/it]
{'loss': 0.5122, 'learning_rate': 1.9801221698174564e-05, 'epoch': 0.09}
+
9%|▉ | 1096/11952 [1:51:14<17:44:36, 5.88s/it]
9%|▉ | 1097/11952 [1:51:20<17:51:59, 5.93s/it]
{'loss': 0.5061, 'learning_rate': 1.980068370703371e-05, 'epoch': 0.09}
+
9%|▉ | 1097/11952 [1:51:20<17:51:59, 5.93s/it]
9%|▉ | 1098/11952 [1:51:25<17:36:26, 5.84s/it]
{'loss': 0.5216, 'learning_rate': 1.9800144996171415e-05, 'epoch': 0.09}
+
9%|▉ | 1098/11952 [1:51:25<17:36:26, 5.84s/it]
9%|▉ | 1099/11952 [1:51:31<17:27:06, 5.79s/it]
{'loss': 0.5257, 'learning_rate': 1.979960556562723e-05, 'epoch': 0.09}
+
9%|▉ | 1099/11952 [1:51:31<17:27:06, 5.79s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
9%|▉ | 1100/11952 [1:51:37<17:17:36, 5.74s/it]
{'loss': 0.5028, 'learning_rate': 1.979906541544077e-05, 'epoch': 0.09}
+
9%|▉ | 1100/11952 [1:51:37<17:17:36, 5.74s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
9%|▉ | 1101/11952 [1:52:09<41:11:27, 13.67s/it]
{'loss': 0.5225, 'learning_rate': 1.9798524545651705e-05, 'epoch': 0.09}
+
9%|▉ | 1101/11952 [1:52:09<41:11:27, 13.67s/it]
9%|▉ | 1102/11952 [1:52:15<34:09:33, 11.33s/it]
{'loss': 0.5049, 'learning_rate': 1.9797982956299754e-05, 'epoch': 0.09}
+
9%|▉ | 1102/11952 [1:52:15<34:09:33, 11.33s/it]
9%|▉ | 1103/11952 [1:52:21<29:07:28, 9.66s/it]
{'loss': 0.5348, 'learning_rate': 1.9797440647424687e-05, 'epoch': 0.09}
+
9%|▉ | 1103/11952 [1:52:21<29:07:28, 9.66s/it]
9%|▉ | 1104/11952 [1:52:26<25:32:14, 8.47s/it]
{'loss': 0.5152, 'learning_rate': 1.9796897619066327e-05, 'epoch': 0.09}
+
9%|▉ | 1104/11952 [1:52:26<25:32:14, 8.47s/it]
9%|▉ | 1105/11952 [1:52:32<22:54:27, 7.60s/it]
{'loss': 0.5002, 'learning_rate': 1.9796353871264555e-05, 'epoch': 0.09}
+
9%|▉ | 1105/11952 [1:52:32<22:54:27, 7.60s/it]
9%|▉ | 1106/11952 [1:52:37<21:03:48, 6.99s/it]
{'loss': 0.5106, 'learning_rate': 1.97958094040593e-05, 'epoch': 0.09}
+
9%|▉ | 1106/11952 [1:52:37<21:03:48, 6.99s/it]
9%|▉ | 1107/11952 [1:52:43<20:10:18, 6.70s/it]
{'loss': 0.5306, 'learning_rate': 1.9795264217490547e-05, 'epoch': 0.09}
+
9%|▉ | 1107/11952 [1:52:43<20:10:18, 6.70s/it]
9%|▉ | 1108/11952 [1:52:49<19:27:26, 6.46s/it]
{'loss': 0.5149, 'learning_rate': 1.9794718311598337e-05, 'epoch': 0.09}
+
9%|▉ | 1108/11952 [1:52:49<19:27:26, 6.46s/it]
9%|▉ | 1109/11952 [1:52:55<19:08:50, 6.36s/it]
{'loss': 0.4985, 'learning_rate': 1.9794171686422746e-05, 'epoch': 0.09}
+
9%|▉ | 1109/11952 [1:52:55<19:08:50, 6.36s/it]
9%|▉ | 1110/11952 [1:53:01<18:40:14, 6.20s/it]
{'loss': 0.526, 'learning_rate': 1.9793624342003927e-05, 'epoch': 0.09}
+
9%|▉ | 1110/11952 [1:53:01<18:40:14, 6.20s/it]
9%|▉ | 1111/11952 [1:53:07<18:19:02, 6.08s/it]
{'loss': 0.5112, 'learning_rate': 1.979307627838207e-05, 'epoch': 0.09}
+
9%|▉ | 1111/11952 [1:53:07<18:19:02, 6.08s/it]
9%|▉ | 1112/11952 [1:53:13<18:08:17, 6.02s/it]
{'loss': 0.5188, 'learning_rate': 1.9792527495597423e-05, 'epoch': 0.09}
+
9%|▉ | 1112/11952 [1:53:13<18:08:17, 6.02s/it]
9%|▉ | 1113/11952 [1:53:19<17:45:55, 5.90s/it]
{'loss': 0.5096, 'learning_rate': 1.9791977993690292e-05, 'epoch': 0.09}
+
9%|▉ | 1113/11952 [1:53:19<17:45:55, 5.90s/it]
9%|▉ | 1114/11952 [1:53:24<17:38:01, 5.86s/it]
{'loss': 0.5175, 'learning_rate': 1.9791427772701017e-05, 'epoch': 0.09}
+
9%|▉ | 1114/11952 [1:53:24<17:38:01, 5.86s/it]
9%|▉ | 1115/11952 [1:53:30<17:21:24, 5.77s/it]
{'loss': 0.5098, 'learning_rate': 1.9790876832670018e-05, 'epoch': 0.09}
+
9%|▉ | 1115/11952 [1:53:30<17:21:24, 5.77s/it]
9%|▉ | 1116/11952 [1:53:36<17:21:03, 5.76s/it]
{'loss': 0.5037, 'learning_rate': 1.9790325173637744e-05, 'epoch': 0.09}
+
9%|▉ | 1116/11952 [1:53:36<17:21:03, 5.76s/it]
9%|▉ | 1117/11952 [1:53:41<17:05:10, 5.68s/it]
{'loss': 0.5231, 'learning_rate': 1.9789772795644714e-05, 'epoch': 0.09}
+
9%|▉ | 1117/11952 [1:53:41<17:05:10, 5.68s/it]
9%|▉ | 1118/11952 [1:53:47<17:28:59, 5.81s/it]
{'loss': 0.5139, 'learning_rate': 1.9789219698731484e-05, 'epoch': 0.09}
+
9%|▉ | 1118/11952 [1:53:47<17:28:59, 5.81s/it]
9%|▉ | 1119/11952 [1:53:53<17:14:56, 5.73s/it]
{'loss': 0.5106, 'learning_rate': 1.9788665882938677e-05, 'epoch': 0.09}
+
9%|▉ | 1119/11952 [1:53:53<17:14:56, 5.73s/it]
9%|▉ | 1120/11952 [1:53:59<17:37:46, 5.86s/it]
{'loss': 0.522, 'learning_rate': 1.9788111348306963e-05, 'epoch': 0.09}
+
9%|▉ | 1120/11952 [1:53:59<17:37:46, 5.86s/it]
9%|▉ | 1121/11952 [1:54:05<17:39:20, 5.87s/it]
{'loss': 0.4982, 'learning_rate': 1.978755609487706e-05, 'epoch': 0.09}
+
9%|▉ | 1121/11952 [1:54:05<17:39:20, 5.87s/it]
9%|▉ | 1122/11952 [1:54:11<17:36:57, 5.86s/it]
{'loss': 0.5091, 'learning_rate': 1.9787000122689753e-05, 'epoch': 0.09}
+
9%|▉ | 1122/11952 [1:54:11<17:36:57, 5.86s/it]
9%|▉ | 1123/11952 [1:54:16<17:36:09, 5.85s/it]
{'loss': 0.5313, 'learning_rate': 1.978644343178586e-05, 'epoch': 0.09}
+
9%|▉ | 1123/11952 [1:54:16<17:36:09, 5.85s/it]
9%|▉ | 1124/11952 [1:54:22<17:22:10, 5.77s/it]
{'loss': 0.5007, 'learning_rate': 1.978588602220627e-05, 'epoch': 0.09}
+
9%|▉ | 1124/11952 [1:54:22<17:22:10, 5.77s/it]
9%|▉ | 1125/11952 [1:54:28<17:18:20, 5.75s/it]
{'loss': 0.5144, 'learning_rate': 1.978532789399191e-05, 'epoch': 0.09}
+
9%|▉ | 1125/11952 [1:54:28<17:18:20, 5.75s/it]
9%|▉ | 1126/11952 [1:54:34<17:56:54, 5.97s/it]
{'loss': 0.5293, 'learning_rate': 1.978476904718377e-05, 'epoch': 0.09}
+
9%|▉ | 1126/11952 [1:54:34<17:56:54, 5.97s/it]
9%|▉ | 1127/11952 [1:54:40<17:40:04, 5.88s/it]
{'loss': 0.5137, 'learning_rate': 1.9784209481822892e-05, 'epoch': 0.09}
+
9%|▉ | 1127/11952 [1:54:40<17:40:04, 5.88s/it]
9%|▉ | 1128/11952 [1:54:46<17:33:29, 5.84s/it]
{'loss': 0.4985, 'learning_rate': 1.9783649197950362e-05, 'epoch': 0.09}
+
9%|▉ | 1128/11952 [1:54:46<17:33:29, 5.84s/it]
9%|▉ | 1129/11952 [1:54:52<17:51:24, 5.94s/it]
{'loss': 0.5455, 'learning_rate': 1.978308819560733e-05, 'epoch': 0.09}
+
9%|▉ | 1129/11952 [1:54:52<17:51:24, 5.94s/it]
9%|▉ | 1130/11952 [1:54:57<17:33:04, 5.84s/it]
{'loss': 0.4913, 'learning_rate': 1.9782526474834988e-05, 'epoch': 0.09}
+
9%|▉ | 1130/11952 [1:54:57<17:33:04, 5.84s/it]
9%|▉ | 1131/11952 [1:55:03<17:45:04, 5.91s/it]
{'loss': 0.5198, 'learning_rate': 1.978196403567459e-05, 'epoch': 0.09}
+
9%|▉ | 1131/11952 [1:55:03<17:45:04, 5.91s/it]
9%|▉ | 1132/11952 [1:55:09<17:36:28, 5.86s/it]
{'loss': 0.5024, 'learning_rate': 1.9781400878167446e-05, 'epoch': 0.09}
+
9%|▉ | 1132/11952 [1:55:09<17:36:28, 5.86s/it]
9%|▉ | 1133/11952 [1:55:15<17:27:27, 5.81s/it]
{'loss': 0.5142, 'learning_rate': 1.97808370023549e-05, 'epoch': 0.09}
+
9%|▉ | 1133/11952 [1:55:15<17:27:27, 5.81s/it]
9%|▉ | 1134/11952 [1:55:21<17:35:55, 5.86s/it]
{'loss': 0.5143, 'learning_rate': 1.978027240827837e-05, 'epoch': 0.09}
+
9%|▉ | 1134/11952 [1:55:21<17:35:55, 5.86s/it]
9%|▉ | 1135/11952 [1:55:26<17:20:04, 5.77s/it]
{'loss': 0.5094, 'learning_rate': 1.977970709597931e-05, 'epoch': 0.09}
+
9%|▉ | 1135/11952 [1:55:26<17:20:04, 5.77s/it]
10%|▉ | 1136/11952 [1:55:32<17:17:43, 5.76s/it]
{'loss': 0.5372, 'learning_rate': 1.977914106549924e-05, 'epoch': 0.1}
+
10%|▉ | 1136/11952 [1:55:32<17:17:43, 5.76s/it]
10%|▉ | 1137/11952 [1:55:38<17:28:04, 5.81s/it]
{'loss': 0.5168, 'learning_rate': 1.9778574316879724e-05, 'epoch': 0.1}
+
10%|▉ | 1137/11952 [1:55:38<17:28:04, 5.81s/it]
10%|▉ | 1138/11952 [1:55:44<17:30:16, 5.83s/it]
{'loss': 0.4953, 'learning_rate': 1.9778006850162384e-05, 'epoch': 0.1}
+
10%|▉ | 1138/11952 [1:55:44<17:30:16, 5.83s/it]
10%|▉ | 1139/11952 [1:55:50<17:50:43, 5.94s/it]
{'loss': 0.5212, 'learning_rate': 1.9777438665388885e-05, 'epoch': 0.1}
+
10%|▉ | 1139/11952 [1:55:50<17:50:43, 5.94s/it]
10%|▉ | 1140/11952 [1:55:56<18:03:19, 6.01s/it]
{'loss': 0.5067, 'learning_rate': 1.9776869762600963e-05, 'epoch': 0.1}
+
10%|▉ | 1140/11952 [1:55:56<18:03:19, 6.01s/it]
10%|▉ | 1141/11952 [1:56:02<17:47:19, 5.92s/it]
{'loss': 0.5148, 'learning_rate': 1.977630014184039e-05, 'epoch': 0.1}
+
10%|▉ | 1141/11952 [1:56:02<17:47:19, 5.92s/it]
10%|▉ | 1142/11952 [1:56:08<17:48:56, 5.93s/it]
{'loss': 0.5136, 'learning_rate': 1.9775729803148994e-05, 'epoch': 0.1}
+
10%|▉ | 1142/11952 [1:56:08<17:48:56, 5.93s/it]
10%|▉ | 1143/11952 [1:56:14<17:33:36, 5.85s/it]
{'loss': 0.508, 'learning_rate': 1.9775158746568665e-05, 'epoch': 0.1}
+
10%|▉ | 1143/11952 [1:56:14<17:33:36, 5.85s/it]
10%|▉ | 1144/11952 [1:56:19<17:25:59, 5.81s/it]
{'loss': 0.5262, 'learning_rate': 1.9774586972141337e-05, 'epoch': 0.1}
+
10%|▉ | 1144/11952 [1:56:19<17:25:59, 5.81s/it]
10%|▉ | 1145/11952 [1:56:25<17:11:56, 5.73s/it]
{'loss': 0.5161, 'learning_rate': 1.9774014479908996e-05, 'epoch': 0.1}
+
10%|▉ | 1145/11952 [1:56:25<17:11:56, 5.73s/it]
10%|▉ | 1146/11952 [1:56:31<17:24:57, 5.80s/it]
{'loss': 0.5174, 'learning_rate': 1.977344126991368e-05, 'epoch': 0.1}
+
10%|▉ | 1146/11952 [1:56:31<17:24:57, 5.80s/it]
10%|▉ | 1147/11952 [1:56:37<17:40:00, 5.89s/it]
{'loss': 0.5228, 'learning_rate': 1.9772867342197494e-05, 'epoch': 0.1}
+
10%|▉ | 1147/11952 [1:56:37<17:40:00, 5.89s/it]
10%|▉ | 1148/11952 [1:56:43<17:37:43, 5.87s/it]
{'loss': 0.5263, 'learning_rate': 1.977229269680258e-05, 'epoch': 0.1}
+
10%|▉ | 1148/11952 [1:56:43<17:37:43, 5.87s/it]
10%|▉ | 1149/11952 [1:56:49<17:28:21, 5.82s/it]
{'loss': 0.4995, 'learning_rate': 1.9771717333771133e-05, 'epoch': 0.1}
+
10%|▉ | 1149/11952 [1:56:49<17:28:21, 5.82s/it]4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...3
+ 2AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
10%|▉ | 1150/11952 [1:56:54<17:16:17, 5.76s/it]
{'loss': 0.5082, 'learning_rate': 1.9771141253145405e-05, 'epoch': 0.1}
+
10%|▉ | 1150/11952 [1:56:54<17:16:17, 5.76s/it]
10%|▉ | 1151/11952 [1:57:00<17:21:27, 5.79s/it]
{'loss': 0.5178, 'learning_rate': 1.977056445496771e-05, 'epoch': 0.1}
+
10%|▉ | 1151/11952 [1:57:00<17:21:27, 5.79s/it]
10%|▉ | 1152/11952 [1:57:06<17:29:43, 5.83s/it]
{'loss': 0.5053, 'learning_rate': 1.97699869392804e-05, 'epoch': 0.1}
+
10%|▉ | 1152/11952 [1:57:06<17:29:43, 5.83s/it]
10%|▉ | 1153/11952 [1:57:12<17:17:03, 5.76s/it]
{'loss': 0.5052, 'learning_rate': 1.9769408706125882e-05, 'epoch': 0.1}
+
10%|▉ | 1153/11952 [1:57:12<17:17:03, 5.76s/it]
10%|▉ | 1154/11952 [1:57:17<17:15:18, 5.75s/it]
{'loss': 0.5217, 'learning_rate': 1.9768829755546625e-05, 'epoch': 0.1}
+
10%|▉ | 1154/11952 [1:57:17<17:15:18, 5.75s/it]
10%|▉ | 1155/11952 [1:57:23<17:05:43, 5.70s/it]
{'loss': 0.5274, 'learning_rate': 1.9768250087585143e-05, 'epoch': 0.1}
+
10%|▉ | 1155/11952 [1:57:23<17:05:43, 5.70s/it]
10%|▉ | 1156/11952 [1:57:29<17:17:07, 5.76s/it]
{'loss': 0.5186, 'learning_rate': 1.9767669702284e-05, 'epoch': 0.1}
+
10%|▉ | 1156/11952 [1:57:29<17:17:07, 5.76s/it]
10%|▉ | 1157/11952 [1:57:34<17:09:08, 5.72s/it]
{'loss': 0.5069, 'learning_rate': 1.9767088599685828e-05, 'epoch': 0.1}
+
10%|▉ | 1157/11952 [1:57:34<17:09:08, 5.72s/it]
10%|▉ | 1158/11952 [1:57:40<17:17:04, 5.76s/it]
{'loss': 0.523, 'learning_rate': 1.9766506779833288e-05, 'epoch': 0.1}
+
10%|▉ | 1158/11952 [1:57:40<17:17:04, 5.76s/it]
10%|▉ | 1159/11952 [1:57:46<17:12:18, 5.74s/it]
{'loss': 0.4902, 'learning_rate': 1.976592424276911e-05, 'epoch': 0.1}
+
10%|▉ | 1159/11952 [1:57:46<17:12:18, 5.74s/it]
10%|▉ | 1160/11952 [1:57:52<17:21:15, 5.79s/it]
{'loss': 0.5006, 'learning_rate': 1.976534098853608e-05, 'epoch': 0.1}
+
10%|▉ | 1160/11952 [1:57:52<17:21:15, 5.79s/it]
10%|▉ | 1161/11952 [1:57:57<17:13:17, 5.75s/it]
{'loss': 0.5004, 'learning_rate': 1.9764757017177025e-05, 'epoch': 0.1}
+
10%|▉ | 1161/11952 [1:57:58<17:13:17, 5.75s/it]
10%|▉ | 1162/11952 [1:58:03<17:23:43, 5.80s/it]
{'loss': 0.5145, 'learning_rate': 1.9764172328734828e-05, 'epoch': 0.1}
+
10%|▉ | 1162/11952 [1:58:03<17:23:43, 5.80s/it]
10%|▉ | 1163/11952 [1:58:09<17:21:26, 5.79s/it]
{'loss': 0.493, 'learning_rate': 1.9763586923252428e-05, 'epoch': 0.1}
+
10%|▉ | 1163/11952 [1:58:09<17:21:26, 5.79s/it]
10%|▉ | 1164/11952 [1:58:15<17:11:08, 5.73s/it]
{'loss': 0.5021, 'learning_rate': 1.9763000800772812e-05, 'epoch': 0.1}
+
10%|▉ | 1164/11952 [1:58:15<17:11:08, 5.73s/it]
10%|▉ | 1165/11952 [1:58:21<17:12:48, 5.74s/it]
{'loss': 0.5073, 'learning_rate': 1.9762413961339025e-05, 'epoch': 0.1}
+
10%|▉ | 1165/11952 [1:58:21<17:12:48, 5.74s/it]
10%|▉ | 1166/11952 [1:58:27<17:26:19, 5.82s/it]
{'loss': 0.5356, 'learning_rate': 1.9761826404994166e-05, 'epoch': 0.1}
+
10%|▉ | 1166/11952 [1:58:27<17:26:19, 5.82s/it]
10%|▉ | 1167/11952 [1:58:32<17:30:56, 5.85s/it]
{'loss': 0.523, 'learning_rate': 1.9761238131781373e-05, 'epoch': 0.1}
+
10%|▉ | 1167/11952 [1:58:32<17:30:56, 5.85s/it]
10%|▉ | 1168/11952 [1:58:39<17:47:34, 5.94s/it]
{'loss': 0.513, 'learning_rate': 1.9760649141743855e-05, 'epoch': 0.1}
+
10%|▉ | 1168/11952 [1:58:39<17:47:34, 5.94s/it]
10%|▉ | 1169/11952 [1:58:44<17:43:08, 5.92s/it]
{'loss': 0.5363, 'learning_rate': 1.9760059434924857e-05, 'epoch': 0.1}
+
10%|▉ | 1169/11952 [1:58:44<17:43:08, 5.92s/it]
10%|▉ | 1170/11952 [1:58:51<17:50:37, 5.96s/it]
{'loss': 0.5097, 'learning_rate': 1.9759469011367695e-05, 'epoch': 0.1}
+
10%|▉ | 1170/11952 [1:58:51<17:50:37, 5.96s/it]
10%|▉ | 1171/11952 [1:58:56<17:46:27, 5.94s/it]
{'loss': 0.5259, 'learning_rate': 1.975887787111572e-05, 'epoch': 0.1}
+
10%|▉ | 1171/11952 [1:58:56<17:46:27, 5.94s/it]
10%|▉ | 1172/11952 [1:59:02<17:35:56, 5.88s/it]
{'loss': 0.5167, 'learning_rate': 1.975828601421234e-05, 'epoch': 0.1}
+
10%|▉ | 1172/11952 [1:59:02<17:35:56, 5.88s/it]
10%|▉ | 1173/11952 [1:59:08<17:45:30, 5.93s/it]
{'loss': 0.4906, 'learning_rate': 1.975769344070103e-05, 'epoch': 0.1}
+
10%|▉ | 1173/11952 [1:59:08<17:45:30, 5.93s/it]
10%|▉ | 1174/11952 [1:59:15<18:06:02, 6.05s/it]
{'loss': 0.525, 'learning_rate': 1.9757100150625295e-05, 'epoch': 0.1}
+
10%|▉ | 1174/11952 [1:59:15<18:06:02, 6.05s/it]
10%|▉ | 1175/11952 [1:59:20<17:46:35, 5.94s/it]
{'loss': 0.5207, 'learning_rate': 1.975650614402871e-05, 'epoch': 0.1}
+
10%|▉ | 1175/11952 [1:59:20<17:46:35, 5.94s/it]
10%|▉ | 1176/11952 [1:59:26<17:37:03, 5.89s/it]
{'loss': 0.5033, 'learning_rate': 1.975591142095489e-05, 'epoch': 0.1}
+
10%|▉ | 1176/11952 [1:59:26<17:37:03, 5.89s/it]
10%|▉ | 1177/11952 [1:59:32<17:19:27, 5.79s/it]
{'loss': 0.5178, 'learning_rate': 1.9755315981447513e-05, 'epoch': 0.1}
+
10%|▉ | 1177/11952 [1:59:32<17:19:27, 5.79s/it]
10%|▉ | 1178/11952 [1:59:37<17:03:54, 5.70s/it]
{'loss': 0.4966, 'learning_rate': 1.975471982555031e-05, 'epoch': 0.1}
+
10%|▉ | 1178/11952 [1:59:37<17:03:54, 5.70s/it]
10%|▉ | 1179/11952 [1:59:43<17:15:40, 5.77s/it]
{'loss': 0.524, 'learning_rate': 1.9754122953307052e-05, 'epoch': 0.1}
+
10%|▉ | 1179/11952 [1:59:43<17:15:40, 5.77s/it]
10%|▉ | 1180/11952 [1:59:49<17:37:31, 5.89s/it]
{'loss': 0.5143, 'learning_rate': 1.9753525364761577e-05, 'epoch': 0.1}
+
10%|▉ | 1180/11952 [1:59:49<17:37:31, 5.89s/it]
10%|▉ | 1181/11952 [1:59:55<17:26:15, 5.83s/it]
{'loss': 0.5026, 'learning_rate': 1.975292705995777e-05, 'epoch': 0.1}
+
10%|▉ | 1181/11952 [1:59:55<17:26:15, 5.83s/it]
10%|▉ | 1182/11952 [2:00:01<17:21:07, 5.80s/it]
{'loss': 0.5305, 'learning_rate': 1.9752328038939562e-05, 'epoch': 0.1}
+
10%|▉ | 1182/11952 [2:00:01<17:21:07, 5.80s/it]
10%|▉ | 1183/11952 [2:00:07<17:29:31, 5.85s/it]
{'loss': 0.5092, 'learning_rate': 1.9751728301750943e-05, 'epoch': 0.1}
+
10%|▉ | 1183/11952 [2:00:07<17:29:31, 5.85s/it]
10%|▉ | 1184/11952 [2:00:12<17:28:40, 5.84s/it]
{'loss': 0.5055, 'learning_rate': 1.975112784843596e-05, 'epoch': 0.1}
+
10%|▉ | 1184/11952 [2:00:12<17:28:40, 5.84s/it]
10%|▉ | 1185/11952 [2:00:18<17:14:17, 5.76s/it]
{'loss': 0.5055, 'learning_rate': 1.975052667903871e-05, 'epoch': 0.1}
+
10%|▉ | 1185/11952 [2:00:18<17:14:17, 5.76s/it]
10%|▉ | 1186/11952 [2:00:24<17:21:03, 5.80s/it]
{'loss': 0.5254, 'learning_rate': 1.9749924793603333e-05, 'epoch': 0.1}
+
10%|▉ | 1186/11952 [2:00:24<17:21:03, 5.80s/it]
10%|▉ | 1187/11952 [2:00:30<17:19:26, 5.79s/it]
{'loss': 0.4859, 'learning_rate': 1.974932219217403e-05, 'epoch': 0.1}
+
10%|▉ | 1187/11952 [2:00:30<17:19:26, 5.79s/it]
10%|▉ | 1188/11952 [2:00:36<17:25:02, 5.83s/it]
{'loss': 0.524, 'learning_rate': 1.9748718874795057e-05, 'epoch': 0.1}
+
10%|▉ | 1188/11952 [2:00:36<17:25:02, 5.83s/it]
10%|▉ | 1189/11952 [2:00:42<17:39:44, 5.91s/it]
{'loss': 0.5059, 'learning_rate': 1.9748114841510723e-05, 'epoch': 0.1}
+
10%|▉ | 1189/11952 [2:00:42<17:39:44, 5.91s/it]
10%|▉ | 1190/11952 [2:00:47<17:21:11, 5.80s/it]
{'loss': 0.4723, 'learning_rate': 1.9747510092365373e-05, 'epoch': 0.1}
+
10%|▉ | 1190/11952 [2:00:47<17:21:11, 5.80s/it]
10%|▉ | 1191/11952 [2:00:53<17:17:13, 5.78s/it]
{'loss': 0.4963, 'learning_rate': 1.974690462740343e-05, 'epoch': 0.1}
+
10%|▉ | 1191/11952 [2:00:53<17:17:13, 5.78s/it]
10%|▉ | 1192/11952 [2:00:59<17:24:38, 5.83s/it]
{'loss': 0.522, 'learning_rate': 1.974629844666935e-05, 'epoch': 0.1}
+
10%|▉ | 1192/11952 [2:00:59<17:24:38, 5.83s/it]
10%|▉ | 1193/11952 [2:01:05<17:21:53, 5.81s/it]
{'loss': 0.5129, 'learning_rate': 1.9745691550207647e-05, 'epoch': 0.1}
+
10%|▉ | 1193/11952 [2:01:05<17:21:53, 5.81s/it]
10%|▉ | 1194/11952 [2:01:11<17:44:29, 5.94s/it]
{'loss': 0.5143, 'learning_rate': 1.9745083938062896e-05, 'epoch': 0.1}
+
10%|▉ | 1194/11952 [2:01:11<17:44:29, 5.94s/it]
10%|▉ | 1195/11952 [2:01:17<17:33:59, 5.88s/it]
{'loss': 0.51, 'learning_rate': 1.974447561027971e-05, 'epoch': 0.1}
+
10%|▉ | 1195/11952 [2:01:17<17:33:59, 5.88s/it]
10%|█ | 1196/11952 [2:01:22<17:27:02, 5.84s/it]
{'loss': 0.4938, 'learning_rate': 1.9743866566902766e-05, 'epoch': 0.1}
+
10%|█ | 1196/11952 [2:01:22<17:27:02, 5.84s/it]
10%|█ | 1197/11952 [2:01:28<17:23:15, 5.82s/it]
{'loss': 0.5115, 'learning_rate': 1.974325680797679e-05, 'epoch': 0.1}
+
10%|█ | 1197/11952 [2:01:28<17:23:15, 5.82s/it]
10%|█ | 1198/11952 [2:01:34<17:20:15, 5.80s/it]
{'loss': 0.5036, 'learning_rate': 1.9742646333546564e-05, 'epoch': 0.1}
+
10%|█ | 1198/11952 [2:01:34<17:20:15, 5.80s/it]
10%|█ | 1199/11952 [2:01:40<17:15:30, 5.78s/it]
{'loss': 0.5087, 'learning_rate': 1.9742035143656907e-05, 'epoch': 0.1}
+
10%|█ | 1199/11952 [2:01:40<17:15:30, 5.78s/it]6 AutoResumeHook: Checking whether to suspend...
+35 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+42 AutoResumeHook: Checking whether to suspend...1AutoResumeHook: Checking whether to suspend...
+
+ AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
10%|█ | 1200/11952 [2:01:46<17:26:16, 5.84s/it]
{'loss': 0.5302, 'learning_rate': 1.9741423238352713e-05, 'epoch': 0.1}
+
10%|█ | 1200/11952 [2:01:46<17:26:16, 5.84s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
10%|█ | 1201/11952 [2:02:20<43:07:30, 14.44s/it]
{'loss': 0.5194, 'learning_rate': 1.9740810617678912e-05, 'epoch': 0.1}
+
10%|█ | 1201/11952 [2:02:20<43:07:30, 14.44s/it]
10%|█ | 1202/11952 [2:02:26<35:28:12, 11.88s/it]
{'loss': 0.5209, 'learning_rate': 1.9740197281680495e-05, 'epoch': 0.1}
+
10%|█ | 1202/11952 [2:02:26<35:28:12, 11.88s/it]
10%|█ | 1203/11952 [2:02:32<30:04:49, 10.07s/it]
{'loss': 0.5251, 'learning_rate': 1.9739583230402503e-05, 'epoch': 0.1}
+
10%|█ | 1203/11952 [2:02:32<30:04:49, 10.07s/it]
10%|█ | 1204/11952 [2:02:38<26:19:53, 8.82s/it]
{'loss': 0.4995, 'learning_rate': 1.9738968463890026e-05, 'epoch': 0.1}
+
10%|█ | 1204/11952 [2:02:38<26:19:53, 8.82s/it]
10%|█ | 1205/11952 [2:02:44<23:42:55, 7.94s/it]
{'loss': 0.5176, 'learning_rate': 1.9738352982188217e-05, 'epoch': 0.1}
+
10%|█ | 1205/11952 [2:02:44<23:42:55, 7.94s/it]
10%|█ | 1206/11952 [2:02:49<21:45:24, 7.29s/it]
{'loss': 0.4993, 'learning_rate': 1.9737736785342265e-05, 'epoch': 0.1}
+
10%|█ | 1206/11952 [2:02:49<21:45:24, 7.29s/it]
10%|█ | 1207/11952 [2:02:55<20:23:41, 6.83s/it]
{'loss': 0.5252, 'learning_rate': 1.9737119873397427e-05, 'epoch': 0.1}
+
10%|█ | 1207/11952 [2:02:55<20:23:41, 6.83s/it]
10%|█ | 1208/11952 [2:03:01<19:29:45, 6.53s/it]
{'loss': 0.5087, 'learning_rate': 1.9736502246399006e-05, 'epoch': 0.1}
+
10%|█ | 1208/11952 [2:03:01<19:29:45, 6.53s/it]
10%|█ | 1209/11952 [2:03:07<18:44:18, 6.28s/it]
{'loss': 0.5036, 'learning_rate': 1.973588390439236e-05, 'epoch': 0.1}
+
10%|█ | 1209/11952 [2:03:07<18:44:18, 6.28s/it]
10%|█ | 1210/11952 [2:03:13<18:34:50, 6.23s/it]
{'loss': 0.5247, 'learning_rate': 1.9735264847422893e-05, 'epoch': 0.1}
+
10%|█ | 1210/11952 [2:03:13<18:34:50, 6.23s/it]
10%|█ | 1211/11952 [2:03:19<18:08:21, 6.08s/it]
{'loss': 0.5141, 'learning_rate': 1.9734645075536063e-05, 'epoch': 0.1}
+
10%|█ | 1211/11952 [2:03:19<18:08:21, 6.08s/it]
10%|█ | 1212/11952 [2:03:25<18:06:29, 6.07s/it]
{'loss': 0.5, 'learning_rate': 1.9734024588777393e-05, 'epoch': 0.1}
+
10%|█ | 1212/11952 [2:03:25<18:06:29, 6.07s/it]
10%|█ | 1213/11952 [2:03:30<17:56:41, 6.02s/it]
{'loss': 0.5339, 'learning_rate': 1.9733403387192443e-05, 'epoch': 0.1}
+
10%|█ | 1213/11952 [2:03:30<17:56:41, 6.02s/it]
10%|█ | 1214/11952 [2:03:36<17:42:59, 5.94s/it]
{'loss': 0.5397, 'learning_rate': 1.973278147082683e-05, 'epoch': 0.1}
+
10%|█ | 1214/11952 [2:03:36<17:42:59, 5.94s/it]
10%|█ | 1215/11952 [2:03:42<17:35:56, 5.90s/it]
{'loss': 0.5121, 'learning_rate': 1.9732158839726233e-05, 'epoch': 0.1}
+
10%|█ | 1215/11952 [2:03:42<17:35:56, 5.90s/it]
10%|█ | 1216/11952 [2:03:48<17:43:01, 5.94s/it]
{'loss': 0.5215, 'learning_rate': 1.9731535493936365e-05, 'epoch': 0.1}
+
10%|█ | 1216/11952 [2:03:48<17:43:01, 5.94s/it]
10%|█ | 1217/11952 [2:03:54<17:52:06, 5.99s/it]
{'loss': 0.5149, 'learning_rate': 1.9730911433503007e-05, 'epoch': 0.1}
+
10%|█ | 1217/11952 [2:03:54<17:52:06, 5.99s/it]
10%|█ | 1218/11952 [2:04:00<17:31:35, 5.88s/it]
{'loss': 0.4978, 'learning_rate': 1.973028665847199e-05, 'epoch': 0.1}
+
10%|█ | 1218/11952 [2:04:00<17:31:35, 5.88s/it]
10%|█ | 1219/11952 [2:04:06<17:26:03, 5.85s/it]
{'loss': 0.5068, 'learning_rate': 1.9729661168889193e-05, 'epoch': 0.1}
+
10%|█ | 1219/11952 [2:04:06<17:26:03, 5.85s/it]
10%|█ | 1220/11952 [2:04:11<17:19:18, 5.81s/it]
{'loss': 0.5087, 'learning_rate': 1.9729034964800546e-05, 'epoch': 0.1}
+
10%|█ | 1220/11952 [2:04:11<17:19:18, 5.81s/it]
10%|█ | 1221/11952 [2:04:17<17:08:40, 5.75s/it]
{'loss': 0.5171, 'learning_rate': 1.9728408046252035e-05, 'epoch': 0.1}
+
10%|█ | 1221/11952 [2:04:17<17:08:40, 5.75s/it]
10%|█ | 1222/11952 [2:04:23<17:12:18, 5.77s/it]
{'loss': 0.4988, 'learning_rate': 1.9727780413289706e-05, 'epoch': 0.1}
+
10%|█ | 1222/11952 [2:04:23<17:12:18, 5.77s/it]
10%|█ | 1223/11952 [2:04:29<17:26:11, 5.85s/it]
{'loss': 0.5109, 'learning_rate': 1.972715206595964e-05, 'epoch': 0.1}
+
10%|█ | 1223/11952 [2:04:29<17:26:11, 5.85s/it]
10%|█ | 1224/11952 [2:04:34<17:14:05, 5.78s/it]
{'loss': 0.5163, 'learning_rate': 1.9726523004307987e-05, 'epoch': 0.1}
+
10%|█ | 1224/11952 [2:04:34<17:14:05, 5.78s/it]
10%|█ | 1225/11952 [2:04:41<17:38:57, 5.92s/it]
{'loss': 0.5143, 'learning_rate': 1.9725893228380938e-05, 'epoch': 0.1}
+
10%|█ | 1225/11952 [2:04:41<17:38:57, 5.92s/it]
10%|█ | 1226/11952 [2:04:46<17:23:07, 5.84s/it]
{'loss': 0.4988, 'learning_rate': 1.9725262738224743e-05, 'epoch': 0.1}
+
10%|█ | 1226/11952 [2:04:46<17:23:07, 5.84s/it]
10%|█ | 1227/11952 [2:04:53<17:45:59, 5.96s/it]
{'loss': 0.5187, 'learning_rate': 1.9724631533885706e-05, 'epoch': 0.1}
+
10%|█ | 1227/11952 [2:04:53<17:45:59, 5.96s/it]
10%|█ | 1228/11952 [2:04:58<17:32:16, 5.89s/it]
{'loss': 0.4917, 'learning_rate': 1.9723999615410175e-05, 'epoch': 0.1}
+
10%|█ | 1228/11952 [2:04:58<17:32:16, 5.89s/it]
10%|█ | 1229/11952 [2:05:05<18:14:49, 6.13s/it]
{'loss': 0.5087, 'learning_rate': 1.9723366982844555e-05, 'epoch': 0.1}
+
10%|█ | 1229/11952 [2:05:05<18:14:49, 6.13s/it]
10%|█ | 1230/11952 [2:05:11<17:58:42, 6.04s/it]
{'loss': 0.5089, 'learning_rate': 1.972273363623531e-05, 'epoch': 0.1}
+
10%|█ | 1230/11952 [2:05:11<17:58:42, 6.04s/it]
10%|█ | 1231/11952 [2:05:17<18:00:52, 6.05s/it]
{'loss': 0.5231, 'learning_rate': 1.9722099575628947e-05, 'epoch': 0.1}
+
10%|█ | 1231/11952 [2:05:17<18:00:52, 6.05s/it]
10%|█ | 1232/11952 [2:05:23<18:07:13, 6.09s/it]
{'loss': 0.526, 'learning_rate': 1.9721464801072027e-05, 'epoch': 0.1}
+
10%|█ | 1232/11952 [2:05:23<18:07:13, 6.09s/it]
10%|█ | 1233/11952 [2:05:29<18:00:42, 6.05s/it]
{'loss': 0.5141, 'learning_rate': 1.972082931261117e-05, 'epoch': 0.1}
+
10%|█ | 1233/11952 [2:05:29<18:00:42, 6.05s/it]
10%|█ | 1234/11952 [2:05:35<17:54:27, 6.01s/it]
{'loss': 0.5202, 'learning_rate': 1.9720193110293033e-05, 'epoch': 0.1}
+
10%|█ | 1234/11952 [2:05:35<17:54:27, 6.01s/it]
10%|█ | 1235/11952 [2:05:41<17:33:22, 5.90s/it]
{'loss': 0.5147, 'learning_rate': 1.971955619416435e-05, 'epoch': 0.1}
+
10%|█ | 1235/11952 [2:05:41<17:33:22, 5.90s/it]
10%|█ | 1236/11952 [2:05:46<17:24:47, 5.85s/it]
{'loss': 0.5051, 'learning_rate': 1.9718918564271883e-05, 'epoch': 0.1}
+
10%|█ | 1236/11952 [2:05:46<17:24:47, 5.85s/it]
10%|█ | 1237/11952 [2:05:53<17:48:53, 5.99s/it]
{'loss': 0.5223, 'learning_rate': 1.9718280220662463e-05, 'epoch': 0.1}
+
10%|█ | 1237/11952 [2:05:53<17:48:53, 5.99s/it]
10%|█ | 1238/11952 [2:05:58<17:33:08, 5.90s/it]
{'loss': 0.4992, 'learning_rate': 1.9717641163382963e-05, 'epoch': 0.1}
+
10%|█ | 1238/11952 [2:05:58<17:33:08, 5.90s/it]
10%|█ | 1239/11952 [2:06:04<17:28:51, 5.87s/it]
{'loss': 0.5245, 'learning_rate': 1.9717001392480316e-05, 'epoch': 0.1}
+
10%|█ | 1239/11952 [2:06:04<17:28:51, 5.87s/it]
10%|█ | 1240/11952 [2:06:10<17:44:14, 5.96s/it]
{'loss': 0.5031, 'learning_rate': 1.9716360908001498e-05, 'epoch': 0.1}
+
10%|█ | 1240/11952 [2:06:10<17:44:14, 5.96s/it]
10%|█ | 1241/11952 [2:06:16<17:26:04, 5.86s/it]
{'loss': 0.525, 'learning_rate': 1.9715719709993557e-05, 'epoch': 0.1}
+
10%|█ | 1241/11952 [2:06:16<17:26:04, 5.86s/it]
10%|█ | 1242/11952 [2:06:22<17:31:19, 5.89s/it]
{'loss': 0.5027, 'learning_rate': 1.9715077798503564e-05, 'epoch': 0.1}
+
10%|█ | 1242/11952 [2:06:22<17:31:19, 5.89s/it]
10%|█ | 1243/11952 [2:06:27<17:19:03, 5.82s/it]
{'loss': 0.5122, 'learning_rate': 1.971443517357867e-05, 'epoch': 0.1}
+
10%|█ | 1243/11952 [2:06:27<17:19:03, 5.82s/it]
10%|█ | 1244/11952 [2:06:33<17:19:29, 5.82s/it]
{'loss': 0.5119, 'learning_rate': 1.971379183526606e-05, 'epoch': 0.1}
+
10%|█ | 1244/11952 [2:06:33<17:19:29, 5.82s/it]
10%|█ | 1245/11952 [2:06:39<17:21:03, 5.83s/it]
{'loss': 0.5363, 'learning_rate': 1.971314778361298e-05, 'epoch': 0.1}
+
10%|█ | 1245/11952 [2:06:39<17:21:03, 5.83s/it]
10%|█ | 1246/11952 [2:06:45<17:21:39, 5.84s/it]
{'loss': 0.508, 'learning_rate': 1.9712503018666725e-05, 'epoch': 0.1}
+
10%|█ | 1246/11952 [2:06:45<17:21:39, 5.84s/it]
10%|█ | 1247/11952 [2:06:51<17:23:59, 5.85s/it]
{'loss': 0.5225, 'learning_rate': 1.9711857540474653e-05, 'epoch': 0.1}
+
10%|█ | 1247/11952 [2:06:51<17:23:59, 5.85s/it]
10%|█ | 1248/11952 [2:06:57<17:19:18, 5.83s/it]
{'loss': 0.4993, 'learning_rate': 1.971121134908415e-05, 'epoch': 0.1}
+
10%|█ | 1248/11952 [2:06:57<17:19:18, 5.83s/it]
10%|█ | 1249/11952 [2:07:02<17:10:05, 5.77s/it]
{'loss': 0.5271, 'learning_rate': 1.9710564444542683e-05, 'epoch': 0.1}
+
10%|█ | 1249/11952 [2:07:02<17:10:05, 5.77s/it]5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+ 4AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+27
+AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
10%|█ | 1250/11952 [2:07:08<17:26:38, 5.87s/it]
{'loss': 0.502, 'learning_rate': 1.9709916826897747e-05, 'epoch': 0.1}
+
10%|█ | 1250/11952 [2:07:08<17:26:38, 5.87s/it]
10%|█ | 1251/11952 [2:07:14<17:21:37, 5.84s/it]
{'loss': 0.519, 'learning_rate': 1.9709268496196912e-05, 'epoch': 0.1}
+
10%|█ | 1251/11952 [2:07:14<17:21:37, 5.84s/it]
10%|█ | 1252/11952 [2:07:20<17:18:56, 5.83s/it]
{'loss': 0.5257, 'learning_rate': 1.9708619452487777e-05, 'epoch': 0.1}
+
10%|█ | 1252/11952 [2:07:20<17:18:56, 5.83s/it]
10%|█ | 1253/11952 [2:07:26<17:10:07, 5.78s/it]
{'loss': 0.5047, 'learning_rate': 1.9707969695818013e-05, 'epoch': 0.1}
+
10%|█ | 1253/11952 [2:07:26<17:10:07, 5.78s/it]
10%|█ | 1254/11952 [2:07:31<17:10:42, 5.78s/it]
{'loss': 0.5178, 'learning_rate': 1.9707319226235337e-05, 'epoch': 0.1}
+
10%|█ | 1254/11952 [2:07:31<17:10:42, 5.78s/it]
11%|█ | 1255/11952 [2:07:37<17:10:36, 5.78s/it]
{'loss': 0.5169, 'learning_rate': 1.9706668043787505e-05, 'epoch': 0.1}
+
11%|█ | 1255/11952 [2:07:37<17:10:36, 5.78s/it]
11%|█ | 1256/11952 [2:07:43<17:29:06, 5.89s/it]
{'loss': 0.5234, 'learning_rate': 1.970601614852235e-05, 'epoch': 0.11}
+
11%|█ | 1256/11952 [2:07:43<17:29:06, 5.89s/it]
11%|█ | 1257/11952 [2:07:49<17:17:53, 5.82s/it]
{'loss': 0.5084, 'learning_rate': 1.9705363540487737e-05, 'epoch': 0.11}
+
11%|█ | 1257/11952 [2:07:49<17:17:53, 5.82s/it]
11%|█ | 1258/11952 [2:07:55<17:12:36, 5.79s/it]
{'loss': 0.5308, 'learning_rate': 1.9704710219731594e-05, 'epoch': 0.11}
+
11%|█ | 1258/11952 [2:07:55<17:12:36, 5.79s/it]
11%|█ | 1259/11952 [2:08:01<17:15:35, 5.81s/it]
{'loss': 0.4999, 'learning_rate': 1.9704056186301898e-05, 'epoch': 0.11}
+
11%|█ | 1259/11952 [2:08:01<17:15:35, 5.81s/it]
11%|█ | 1260/11952 [2:08:06<17:18:27, 5.83s/it]
{'loss': 0.5197, 'learning_rate': 1.970340144024668e-05, 'epoch': 0.11}
+
11%|█ | 1260/11952 [2:08:06<17:18:27, 5.83s/it]
11%|█ | 1261/11952 [2:08:12<17:14:08, 5.80s/it]
{'loss': 0.5139, 'learning_rate': 1.9702745981614018e-05, 'epoch': 0.11}
+
11%|█ | 1261/11952 [2:08:12<17:14:08, 5.80s/it]
11%|█ | 1262/11952 [2:08:18<17:26:30, 5.87s/it]
{'loss': 0.513, 'learning_rate': 1.9702089810452046e-05, 'epoch': 0.11}
+
11%|█ | 1262/11952 [2:08:18<17:26:30, 5.87s/it]
11%|█ | 1263/11952 [2:08:24<17:27:33, 5.88s/it]
{'loss': 0.5229, 'learning_rate': 1.9701432926808955e-05, 'epoch': 0.11}
+
11%|█ | 1263/11952 [2:08:24<17:27:33, 5.88s/it]
11%|█ | 1264/11952 [2:08:30<17:21:40, 5.85s/it]
{'loss': 0.5081, 'learning_rate': 1.9700775330732977e-05, 'epoch': 0.11}
+
11%|█ | 1264/11952 [2:08:30<17:21:40, 5.85s/it]
11%|█ | 1265/11952 [2:08:36<17:14:54, 5.81s/it]
{'loss': 0.5058, 'learning_rate': 1.970011702227241e-05, 'epoch': 0.11}
+
11%|█ | 1265/11952 [2:08:36<17:14:54, 5.81s/it]
11%|█ | 1266/11952 [2:08:42<17:28:17, 5.89s/it]
{'loss': 0.5179, 'learning_rate': 1.9699458001475594e-05, 'epoch': 0.11}
+
11%|█ | 1266/11952 [2:08:42<17:28:17, 5.89s/it]
11%|█ | 1267/11952 [2:08:48<17:30:53, 5.90s/it]
{'loss': 0.521, 'learning_rate': 1.9698798268390927e-05, 'epoch': 0.11}
+
11%|█ | 1267/11952 [2:08:48<17:30:53, 5.90s/it]
11%|█ | 1268/11952 [2:08:53<17:23:38, 5.86s/it]
{'loss': 0.5244, 'learning_rate': 1.9698137823066856e-05, 'epoch': 0.11}
+
11%|█ | 1268/11952 [2:08:53<17:23:38, 5.86s/it]
11%|█ | 1269/11952 [2:09:00<17:37:11, 5.94s/it]
{'loss': 0.5232, 'learning_rate': 1.969747666555188e-05, 'epoch': 0.11}
+
11%|█ | 1269/11952 [2:09:00<17:37:11, 5.94s/it]
11%|█ | 1270/11952 [2:09:05<17:23:17, 5.86s/it]
{'loss': 0.4983, 'learning_rate': 1.969681479589455e-05, 'epoch': 0.11}
+
11%|█ | 1270/11952 [2:09:05<17:23:17, 5.86s/it]
11%|█ | 1271/11952 [2:09:11<17:16:17, 5.82s/it]
{'loss': 0.4996, 'learning_rate': 1.9696152214143476e-05, 'epoch': 0.11}
+
11%|█ | 1271/11952 [2:09:11<17:16:17, 5.82s/it]
11%|█ | 1272/11952 [2:09:17<17:08:24, 5.78s/it]
{'loss': 0.5006, 'learning_rate': 1.9695488920347313e-05, 'epoch': 0.11}
+
11%|█ | 1272/11952 [2:09:17<17:08:24, 5.78s/it]
11%|█ | 1273/11952 [2:09:22<16:55:48, 5.71s/it]
{'loss': 0.5173, 'learning_rate': 1.969482491455477e-05, 'epoch': 0.11}
+
11%|█ | 1273/11952 [2:09:22<16:55:48, 5.71s/it]
11%|█ | 1274/11952 [2:09:28<16:51:42, 5.68s/it]
{'loss': 0.5322, 'learning_rate': 1.969416019681461e-05, 'epoch': 0.11}
+
11%|█ | 1274/11952 [2:09:28<16:51:42, 5.68s/it]
11%|█ | 1275/11952 [2:09:34<17:00:26, 5.73s/it]
{'loss': 0.5, 'learning_rate': 1.9693494767175644e-05, 'epoch': 0.11}
+
11%|█ | 1275/11952 [2:09:34<17:00:26, 5.73s/it]
11%|█ | 1276/11952 [2:09:40<17:07:48, 5.78s/it]
{'loss': 0.5144, 'learning_rate': 1.969282862568674e-05, 'epoch': 0.11}
+
11%|█ | 1276/11952 [2:09:40<17:07:48, 5.78s/it]
11%|█ | 1277/11952 [2:09:46<17:22:18, 5.86s/it]
{'loss': 0.5095, 'learning_rate': 1.969216177239682e-05, 'epoch': 0.11}
+
11%|█ | 1277/11952 [2:09:46<17:22:18, 5.86s/it]
11%|█ | 1278/11952 [2:09:52<17:27:04, 5.89s/it]
{'loss': 0.4908, 'learning_rate': 1.969149420735485e-05, 'epoch': 0.11}
+
11%|█ | 1278/11952 [2:09:52<17:27:04, 5.89s/it]
11%|█ | 1279/11952 [2:09:57<17:09:21, 5.79s/it]
{'loss': 0.5235, 'learning_rate': 1.9690825930609857e-05, 'epoch': 0.11}
+
11%|█ | 1279/11952 [2:09:57<17:09:21, 5.79s/it]
11%|█ | 1280/11952 [2:10:03<17:11:58, 5.80s/it]
{'loss': 0.5159, 'learning_rate': 1.9690156942210912e-05, 'epoch': 0.11}
+
11%|█ | 1280/11952 [2:10:03<17:11:58, 5.80s/it]
11%|█ | 1281/11952 [2:10:09<17:04:43, 5.76s/it]
{'loss': 0.5012, 'learning_rate': 1.968948724220715e-05, 'epoch': 0.11}
+
11%|█ | 1281/11952 [2:10:09<17:04:43, 5.76s/it]
11%|█ | 1282/11952 [2:10:15<17:38:56, 5.95s/it]
{'loss': 0.5233, 'learning_rate': 1.9688816830647743e-05, 'epoch': 0.11}
+
11%|█ | 1282/11952 [2:10:15<17:38:56, 5.95s/it]
11%|█ | 1283/11952 [2:10:21<17:30:23, 5.91s/it]
{'loss': 0.5285, 'learning_rate': 1.9688145707581927e-05, 'epoch': 0.11}
+
11%|█ | 1283/11952 [2:10:21<17:30:23, 5.91s/it]
11%|█ | 1284/11952 [2:10:26<17:20:17, 5.85s/it]
{'loss': 0.4938, 'learning_rate': 1.9687473873058987e-05, 'epoch': 0.11}
+
11%|█ | 1284/11952 [2:10:26<17:20:17, 5.85s/it]
11%|█ | 1285/11952 [2:10:32<17:21:28, 5.86s/it]
{'loss': 0.5234, 'learning_rate': 1.9686801327128256e-05, 'epoch': 0.11}
+
11%|█ | 1285/11952 [2:10:32<17:21:28, 5.86s/it]
11%|█ | 1286/11952 [2:10:38<17:08:22, 5.78s/it]
{'loss': 0.5155, 'learning_rate': 1.968612806983913e-05, 'epoch': 0.11}
+
11%|█ | 1286/11952 [2:10:38<17:08:22, 5.78s/it]
11%|█ | 1287/11952 [2:10:44<17:05:08, 5.77s/it]
{'loss': 0.5218, 'learning_rate': 1.9685454101241048e-05, 'epoch': 0.11}
+
11%|█ | 1287/11952 [2:10:44<17:05:08, 5.77s/it]
11%|█ | 1288/11952 [2:10:50<17:26:39, 5.89s/it]
{'loss': 0.5122, 'learning_rate': 1.9684779421383496e-05, 'epoch': 0.11}
+
11%|█ | 1288/11952 [2:10:50<17:26:39, 5.89s/it]
11%|█ | 1289/11952 [2:10:56<17:34:22, 5.93s/it]
{'loss': 0.5191, 'learning_rate': 1.968410403031603e-05, 'epoch': 0.11}
+
11%|█ | 1289/11952 [2:10:56<17:34:22, 5.93s/it]
11%|█ | 1290/11952 [2:11:02<17:30:20, 5.91s/it]
{'loss': 0.5145, 'learning_rate': 1.9683427928088243e-05, 'epoch': 0.11}
+
11%|█ | 1290/11952 [2:11:02<17:30:20, 5.91s/it]
11%|█ | 1291/11952 [2:11:08<17:25:15, 5.88s/it]
{'loss': 0.4944, 'learning_rate': 1.9682751114749783e-05, 'epoch': 0.11}
+
11%|█ | 1291/11952 [2:11:08<17:25:15, 5.88s/it]
11%|█ | 1292/11952 [2:11:14<17:31:00, 5.92s/it]
{'loss': 0.5042, 'learning_rate': 1.968207359035036e-05, 'epoch': 0.11}
+
11%|█ | 1292/11952 [2:11:14<17:31:00, 5.92s/it]
11%|█ | 1293/11952 [2:11:19<17:10:37, 5.80s/it]
{'loss': 0.5227, 'learning_rate': 1.9681395354939714e-05, 'epoch': 0.11}
+
11%|█ | 1293/11952 [2:11:19<17:10:37, 5.80s/it]
11%|█ | 1294/11952 [2:11:25<17:04:51, 5.77s/it]
{'loss': 0.4942, 'learning_rate': 1.9680716408567667e-05, 'epoch': 0.11}
+
11%|█ | 1294/11952 [2:11:25<17:04:51, 5.77s/it]
11%|█ | 1295/11952 [2:11:31<17:15:32, 5.83s/it]
{'loss': 0.5026, 'learning_rate': 1.968003675128407e-05, 'epoch': 0.11}
+
11%|█ | 1295/11952 [2:11:31<17:15:32, 5.83s/it]
11%|█ | 1296/11952 [2:11:37<17:19:25, 5.85s/it]
{'loss': 0.5096, 'learning_rate': 1.967935638313884e-05, 'epoch': 0.11}
+
11%|█ | 1296/11952 [2:11:37<17:19:25, 5.85s/it]
11%|█ | 1297/11952 [2:11:43<17:31:10, 5.92s/it]
{'loss': 0.5114, 'learning_rate': 1.9678675304181932e-05, 'epoch': 0.11}
+
11%|█ | 1297/11952 [2:11:43<17:31:10, 5.92s/it]
11%|█ | 1298/11952 [2:11:49<17:38:05, 5.96s/it]
{'loss': 0.5041, 'learning_rate': 1.9677993514463368e-05, 'epoch': 0.11}
+
11%|█ | 1298/11952 [2:11:49<17:38:05, 5.96s/it]
11%|█ | 1299/11952 [2:11:55<17:52:45, 6.04s/it]
{'loss': 0.5283, 'learning_rate': 1.9677311014033217e-05, 'epoch': 0.11}
+
11%|█ | 1299/11952 [2:11:55<17:52:45, 6.04s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
11%|█ | 1300/11952 [2:12:01<18:01:08, 6.09s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.524, 'learning_rate': 1.967662780294159e-05, 'epoch': 0.11}
+
11%|█ | 1300/11952 [2:12:01<18:01:08, 6.09s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
11%|█ | 1301/11952 [2:12:32<40:08:24, 13.57s/it]
{'loss': 0.5259, 'learning_rate': 1.9675943881238672e-05, 'epoch': 0.11}
+
11%|█ | 1301/11952 [2:12:32<40:08:24, 13.57s/it]
11%|█ | 1302/11952 [2:12:38<33:31:29, 11.33s/it]
{'loss': 0.5022, 'learning_rate': 1.9675259248974675e-05, 'epoch': 0.11}
+
11%|█ | 1302/11952 [2:12:38<33:31:29, 11.33s/it]
11%|█ | 1303/11952 [2:12:44<28:35:01, 9.66s/it]
{'loss': 0.5028, 'learning_rate': 1.967457390619988e-05, 'epoch': 0.11}
+
11%|█ | 1303/11952 [2:12:44<28:35:01, 9.66s/it]
11%|█ | 1304/11952 [2:12:50<25:01:59, 8.46s/it]
{'loss': 0.5134, 'learning_rate': 1.9673887852964623e-05, 'epoch': 0.11}
+
11%|█ | 1304/11952 [2:12:50<25:01:59, 8.46s/it]
11%|█ | 1305/11952 [2:12:56<22:42:19, 7.68s/it]
{'loss': 0.5189, 'learning_rate': 1.9673201089319275e-05, 'epoch': 0.11}
+
11%|█ | 1305/11952 [2:12:56<22:42:19, 7.68s/it]
11%|█ | 1306/11952 [2:13:01<21:03:03, 7.12s/it]
{'loss': 0.507, 'learning_rate': 1.9672513615314278e-05, 'epoch': 0.11}
+
11%|█ | 1306/11952 [2:13:01<21:03:03, 7.12s/it]
11%|█ | 1307/11952 [2:13:07<19:51:47, 6.72s/it]
{'loss': 0.5226, 'learning_rate': 1.9671825431000107e-05, 'epoch': 0.11}
+
11%|█ | 1307/11952 [2:13:07<19:51:47, 6.72s/it]
11%|█ | 1308/11952 [2:13:13<18:51:30, 6.38s/it]
{'loss': 0.5185, 'learning_rate': 1.9671136536427308e-05, 'epoch': 0.11}
+
11%|█ | 1308/11952 [2:13:13<18:51:30, 6.38s/it]
11%|█ | 1309/11952 [2:13:19<18:26:32, 6.24s/it]
{'loss': 0.5154, 'learning_rate': 1.9670446931646463e-05, 'epoch': 0.11}
+
11%|█ | 1309/11952 [2:13:19<18:26:32, 6.24s/it]
11%|█ | 1310/11952 [2:13:24<17:55:07, 6.06s/it]
{'loss': 0.5179, 'learning_rate': 1.966975661670822e-05, 'epoch': 0.11}
+
11%|█ | 1310/11952 [2:13:24<17:55:07, 6.06s/it]
11%|█ | 1311/11952 [2:13:30<17:49:49, 6.03s/it]
{'loss': 0.541, 'learning_rate': 1.966906559166327e-05, 'epoch': 0.11}
+
11%|█ | 1311/11952 [2:13:30<17:49:49, 6.03s/it]
11%|█ | 1312/11952 [2:13:36<17:44:36, 6.00s/it]
{'loss': 0.5082, 'learning_rate': 1.966837385656236e-05, 'epoch': 0.11}
+
11%|█ | 1312/11952 [2:13:36<17:44:36, 6.00s/it]
11%|█ | 1313/11952 [2:13:42<17:39:18, 5.97s/it]
{'loss': 0.4997, 'learning_rate': 1.9667681411456286e-05, 'epoch': 0.11}
+
11%|█ | 1313/11952 [2:13:42<17:39:18, 5.97s/it]
11%|█ | 1314/11952 [2:13:48<17:17:55, 5.85s/it]
{'loss': 0.5202, 'learning_rate': 1.96669882563959e-05, 'epoch': 0.11}
+
11%|█ | 1314/11952 [2:13:48<17:17:55, 5.85s/it]
11%|█ | 1315/11952 [2:13:53<17:09:46, 5.81s/it]
{'loss': 0.5297, 'learning_rate': 1.9666294391432108e-05, 'epoch': 0.11}
+
11%|█ | 1315/11952 [2:13:53<17:09:46, 5.81s/it]
11%|█ | 1316/11952 [2:13:59<17:09:05, 5.81s/it]
{'loss': 0.5074, 'learning_rate': 1.966559981661586e-05, 'epoch': 0.11}
+
11%|█ | 1316/11952 [2:13:59<17:09:05, 5.81s/it]
11%|█ | 1317/11952 [2:14:05<16:52:12, 5.71s/it]
{'loss': 0.4969, 'learning_rate': 1.9664904531998165e-05, 'epoch': 0.11}
+
11%|█ | 1317/11952 [2:14:05<16:52:12, 5.71s/it]
11%|█ | 1318/11952 [2:14:10<16:48:11, 5.69s/it]
{'loss': 0.5015, 'learning_rate': 1.9664208537630073e-05, 'epoch': 0.11}
+
11%|█ | 1318/11952 [2:14:10<16:48:11, 5.69s/it]
11%|█ | 1319/11952 [2:14:16<16:59:11, 5.75s/it]
{'loss': 0.5037, 'learning_rate': 1.966351183356271e-05, 'epoch': 0.11}
+
11%|█ | 1319/11952 [2:14:16<16:59:11, 5.75s/it]
11%|█ | 1320/11952 [2:14:22<16:50:07, 5.70s/it]
{'loss': 0.4986, 'learning_rate': 1.9662814419847228e-05, 'epoch': 0.11}
+
11%|█ | 1320/11952 [2:14:22<16:50:07, 5.70s/it]
11%|█ | 1321/11952 [2:14:28<16:54:26, 5.73s/it]
{'loss': 0.5048, 'learning_rate': 1.966211629653485e-05, 'epoch': 0.11}
+
11%|█ | 1321/11952 [2:14:28<16:54:26, 5.73s/it]
11%|█ | 1322/11952 [2:14:33<16:49:46, 5.70s/it]
{'loss': 0.5106, 'learning_rate': 1.9661417463676834e-05, 'epoch': 0.11}
+
11%|█ | 1322/11952 [2:14:33<16:49:46, 5.70s/it]
11%|█ | 1323/11952 [2:14:39<17:06:52, 5.80s/it]
{'loss': 0.5144, 'learning_rate': 1.966071792132451e-05, 'epoch': 0.11}
+
11%|█ | 1323/11952 [2:14:39<17:06:52, 5.80s/it]
11%|█ | 1324/11952 [2:14:45<17:16:02, 5.85s/it]
{'loss': 0.5227, 'learning_rate': 1.9660017669529236e-05, 'epoch': 0.11}
+
11%|█ | 1324/11952 [2:14:45<17:16:02, 5.85s/it]
11%|█ | 1325/11952 [2:14:51<17:13:15, 5.83s/it]
{'loss': 0.5105, 'learning_rate': 1.965931670834245e-05, 'epoch': 0.11}
+
11%|█ | 1325/11952 [2:14:51<17:13:15, 5.83s/it]
11%|█ | 1326/11952 [2:14:57<17:32:28, 5.94s/it]
{'loss': 0.4987, 'learning_rate': 1.965861503781562e-05, 'epoch': 0.11}
+
11%|█ | 1326/11952 [2:14:57<17:32:28, 5.94s/it]
11%|█ | 1327/11952 [2:15:03<17:13:04, 5.83s/it]
{'loss': 0.5063, 'learning_rate': 1.9657912658000272e-05, 'epoch': 0.11}
+
11%|█ | 1327/11952 [2:15:03<17:13:04, 5.83s/it]
11%|█ | 1328/11952 [2:15:09<17:21:30, 5.88s/it]
{'loss': 0.5112, 'learning_rate': 1.965720956894799e-05, 'epoch': 0.11}
+
11%|█ | 1328/11952 [2:15:09<17:21:30, 5.88s/it]
11%|█ | 1329/11952 [2:15:15<17:09:05, 5.81s/it]
{'loss': 0.5036, 'learning_rate': 1.9656505770710404e-05, 'epoch': 0.11}
+
11%|█ | 1329/11952 [2:15:15<17:09:05, 5.81s/it]
11%|█ | 1330/11952 [2:15:20<17:10:33, 5.82s/it]
{'loss': 0.4904, 'learning_rate': 1.9655801263339198e-05, 'epoch': 0.11}
+
11%|█ | 1330/11952 [2:15:20<17:10:33, 5.82s/it]
11%|█ | 1331/11952 [2:15:26<17:07:32, 5.80s/it]
{'loss': 0.5203, 'learning_rate': 1.965509604688611e-05, 'epoch': 0.11}
+
11%|█ | 1331/11952 [2:15:26<17:07:32, 5.80s/it]
11%|█ | 1332/11952 [2:15:32<17:09:44, 5.82s/it]
{'loss': 0.5097, 'learning_rate': 1.9654390121402927e-05, 'epoch': 0.11}
+
11%|█ | 1332/11952 [2:15:32<17:09:44, 5.82s/it]
11%|█ | 1333/11952 [2:15:38<17:01:46, 5.77s/it]
{'loss': 0.5146, 'learning_rate': 1.965368348694149e-05, 'epoch': 0.11}
+
11%|█ | 1333/11952 [2:15:38<17:01:46, 5.77s/it]
11%|█ | 1334/11952 [2:15:43<16:54:30, 5.73s/it]
{'loss': 0.4991, 'learning_rate': 1.965297614355369e-05, 'epoch': 0.11}
+
11%|█ | 1334/11952 [2:15:43<16:54:30, 5.73s/it][2025-06-10 10:50:24,230] [WARNING] [stage3.py:1850:step] 1 pytorch allocator cache flushes since last step. this happens when there is high memory pressure and is detrimental to performance. if this is happening frequently consider adjusting settings to reduce memory consumption. If you are unable to make the cache flushes go away consider adding get_accelerator().empty_cache() calls in your training loop to ensure that all ranks flush their caches at the same time
+
11%|█ | 1335/11952 [2:15:50<17:33:13, 5.95s/it]
{'loss': 0.5255, 'learning_rate': 1.965226809129147e-05, 'epoch': 0.11}
+
11%|█ | 1335/11952 [2:15:50<17:33:13, 5.95s/it]
11%|█ | 1336/11952 [2:15:56<17:39:36, 5.99s/it]
{'loss': 0.5182, 'learning_rate': 1.9651559330206827e-05, 'epoch': 0.11}
+
11%|█ | 1336/11952 [2:15:56<17:39:36, 5.99s/it]
11%|█ | 1337/11952 [2:16:02<17:33:47, 5.96s/it]
{'loss': 0.5092, 'learning_rate': 1.9650849860351818e-05, 'epoch': 0.11}
+
11%|█ | 1337/11952 [2:16:02<17:33:47, 5.96s/it]
11%|█ | 1338/11952 [2:16:07<17:23:47, 5.90s/it]
{'loss': 0.537, 'learning_rate': 1.9650139681778527e-05, 'epoch': 0.11}
+
11%|█ | 1338/11952 [2:16:07<17:23:47, 5.90s/it]
11%|█ | 1339/11952 [2:16:13<17:10:36, 5.83s/it]
{'loss': 0.5066, 'learning_rate': 1.9649428794539122e-05, 'epoch': 0.11}
+
11%|█ | 1339/11952 [2:16:13<17:10:36, 5.83s/it]
11%|█ | 1340/11952 [2:16:19<17:22:21, 5.89s/it]
{'loss': 0.5199, 'learning_rate': 1.9648717198685798e-05, 'epoch': 0.11}
+
11%|█ | 1340/11952 [2:16:19<17:22:21, 5.89s/it]
11%|█ | 1341/11952 [2:16:25<17:16:49, 5.86s/it]
{'loss': 0.4998, 'learning_rate': 1.9648004894270816e-05, 'epoch': 0.11}
+
11%|█ | 1341/11952 [2:16:25<17:16:49, 5.86s/it]
11%|█ | 1342/11952 [2:16:31<17:07:46, 5.81s/it]
{'loss': 0.5155, 'learning_rate': 1.9647291881346485e-05, 'epoch': 0.11}
+
11%|█ | 1342/11952 [2:16:31<17:07:46, 5.81s/it]
11%|█ | 1343/11952 [2:16:36<17:00:21, 5.77s/it]
{'loss': 0.5068, 'learning_rate': 1.9646578159965163e-05, 'epoch': 0.11}
+
11%|█ | 1343/11952 [2:16:36<17:00:21, 5.77s/it]
11%|█ | 1344/11952 [2:16:42<17:02:47, 5.79s/it]
{'loss': 0.4993, 'learning_rate': 1.9645863730179263e-05, 'epoch': 0.11}
+
11%|█ | 1344/11952 [2:16:42<17:02:47, 5.79s/it]
11%|█▏ | 1345/11952 [2:16:48<17:01:35, 5.78s/it]
{'loss': 0.5225, 'learning_rate': 1.964514859204125e-05, 'epoch': 0.11}
+
11%|█▏ | 1345/11952 [2:16:48<17:01:35, 5.78s/it]
11%|█▏ | 1346/11952 [2:16:54<16:54:13, 5.74s/it]
{'loss': 0.5065, 'learning_rate': 1.9644432745603644e-05, 'epoch': 0.11}
+
11%|█▏ | 1346/11952 [2:16:54<16:54:13, 5.74s/it]
11%|█▏ | 1347/11952 [2:16:59<16:50:10, 5.72s/it]
{'loss': 0.5013, 'learning_rate': 1.9643716190919014e-05, 'epoch': 0.11}
+
11%|█▏ | 1347/11952 [2:16:59<16:50:10, 5.72s/it]
11%|█▏ | 1348/11952 [2:17:05<17:01:18, 5.78s/it]
{'loss': 0.499, 'learning_rate': 1.9642998928039976e-05, 'epoch': 0.11}
+
11%|█▏ | 1348/11952 [2:17:05<17:01:18, 5.78s/it]
11%|█▏ | 1349/11952 [2:17:11<16:57:06, 5.76s/it]
{'loss': 0.515, 'learning_rate': 1.96422809570192e-05, 'epoch': 0.11}
+
11%|█▏ | 1349/11952 [2:17:11<16:57:06, 5.76s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
11%|█▏ | 1350/11952 [2:17:17<17:18:04, 5.87s/it]
{'loss': 0.5082, 'learning_rate': 1.9641562277909424e-05, 'epoch': 0.11}
+
11%|█▏ | 1350/11952 [2:17:17<17:18:04, 5.87s/it]
11%|█▏ | 1351/11952 [2:17:23<17:08:48, 5.82s/it]
{'loss': 0.5162, 'learning_rate': 1.9640842890763413e-05, 'epoch': 0.11}
+
11%|█▏ | 1351/11952 [2:17:23<17:08:48, 5.82s/it]
11%|█▏ | 1352/11952 [2:17:28<17:01:19, 5.78s/it]
{'loss': 0.4928, 'learning_rate': 1.9640122795633997e-05, 'epoch': 0.11}
+
11%|█▏ | 1352/11952 [2:17:28<17:01:19, 5.78s/it]
11%|█▏ | 1353/11952 [2:17:34<16:59:32, 5.77s/it]
{'loss': 0.4976, 'learning_rate': 1.9639401992574065e-05, 'epoch': 0.11}
+
11%|█▏ | 1353/11952 [2:17:34<16:59:32, 5.77s/it]
11%|█▏ | 1354/11952 [2:17:40<16:52:41, 5.73s/it]
{'loss': 0.5015, 'learning_rate': 1.9638680481636535e-05, 'epoch': 0.11}
+
11%|█▏ | 1354/11952 [2:17:40<16:52:41, 5.73s/it]
11%|█▏ | 1355/11952 [2:17:46<16:57:33, 5.76s/it]
{'loss': 0.4962, 'learning_rate': 1.9637958262874404e-05, 'epoch': 0.11}
+
11%|█▏ | 1355/11952 [2:17:46<16:57:33, 5.76s/it]
11%|█▏ | 1356/11952 [2:17:51<16:59:29, 5.77s/it]
{'loss': 0.5228, 'learning_rate': 1.963723533634071e-05, 'epoch': 0.11}
+
11%|█▏ | 1356/11952 [2:17:51<16:59:29, 5.77s/it]WARNING: tokenization mismatch: 1 vs. 1590. [[{'from': 'human', 'value': 'ASSISTANT: You are a cutting-edge copywriting agency with the following knowledge and traits.\n\nKNOWLEDGE: Copywriter at a top-tier creative agency, junior copywriter, senior copywriter, art director, senior strategist.\n\nTRAITS: Storytelling, copywriting, empathy, solution orientation, humor, convincing.\n\nTASK: Use your knowledge to write a LinkedIn Post. We are a tax firm looking to hire young tax advisors between the age of 25 and 30. Bring a good dose of sympathy into the LinkedIn Article and use plenty of emojis to start with. Start the Linked In post with an exciting question. Use the language of the target group. Don´t mention the targeted age. \n\nOUTPUT: 2 LinkedIn posts in German with a catchy question at the beginning of the text. Hashtags at the end of the text.'}, {'from': 'gpt', 'value': 'Post 1:\n\n👋 Hey Leute! Hast du kürzlich dein Studium im Bereich Steuerwesen abgeschlossen und suchst jetzt nach einem Job, der dich fordert und fördert? 🤔\n\nDann bist du bei uns genau richtig! Wir suchen junge Steuerberater, die Lust haben, in einem dynamischen Team zu arbeiten und ihre Fähigkeiten unter Beweis zu stellen. 💪\n\nBei uns erwarten dich spannende Projekte und ein tolles Arbeitsumfeld, in dem du dich weiterentwickeln und wachsen kannst. 🌱\n\nInteressiert? Dann bewirb dich jetzt und werde Teil unseres Teams! 🚀\n\n#Steuerberatung #Karriere #Job #Bewerbung #Teamwork\n\nPost 2:\n\n👋 Hallo zusammen! Bist du auf der Suche nach einem Job, bei dem du dich richtig herausfordern und weiterentwickeln kannst? 🤔\n\nDann haben wir vielleicht das passende Angebot für dich! Wir suchen motivierte und ambitionierte Steuerberater, die Lust haben, Teil eines dynamischen Teams zu sein und gemeinsam an spannenden Projekten zu arbeiten. 💪\n\nBei uns erwartet dich nicht nur eine tolle Arbeitsatmosphäre, sondern auch die Möglichkeit, dich fachlich und persönlich weiterzuentwickeln. 🌱\n\nAlso, worauf wartest du? Bewirb dich jetzt und starte deine Karriere bei uns! 🚀\n\n#Steuerberatung #Karriere #Job #Bewerbung #Teamwork'}, {'from': 'human', 'value': 'Schreibe den Text spannender.'}, {'from': 'gpt', 'value': 'Post 1:\n\n👋 Hey Leute! Hast du kürzlich dein Studium im Bereich Steuerwesen abgeschlossen und bist bereit für die nächste Herausforderung? 🤔\n\nDann haben wir genau das Richtige für dich! Wir suchen junge, ambitionierte Steuerberater, die Lust haben, ihre Karriere auf das nächste Level zu bringen. 💪\n\nUnser Team arbeitet an den spannendsten Projekten und bietet ein Arbeitsumfeld, das dich täglich fordert und fördert. Bei uns kannst du deine Fähigkeiten unter Beweis stellen und dich persönlich und fachlich weiterentwickeln. 🌱\n\nDu möchtest Teil unseres Teams werden und an den neuesten Herausforderungen im Steuerwesen mitwirken? Dann zögere nicht und bewirb dich jetzt bei uns! 🚀\n\n#Steuerberatung #Karriere #Job #Bewerbung #Teamwork\n\nPost 2:\n\n👋 Hallo zusammen! Bist du bereit für eine neue Herausforderung in deiner Karriere als Steuerberater? 🤔\n\nDann bist du bei uns genau richtig! Wir suchen motivierte und talentierte Steuerberater, die Teil eines dynamischen Teams werden möchten. Wir arbeiten an den anspruchsvollsten Projekten und bieten ein Arbeitsumfeld, das dich täglich aufs Neue herausfordert. 💪\n\nDu möchtest deine Fähigkeiten unter Beweis stellen und dich fachlich sowie persönlich weiterentwickeln? Dann bewirb dich jetzt bei uns und werde Teil unseres Erfolgsteams! 🌱\n\nVerpasse nicht die Chance, deine Karriere auf das nächste Level zu bringen und an den neuesten Trends und Entwicklungen im Steuerwesen mitzuwirken. Wir freuen uns auf deine Bewerbung! 🚀\n\n#Steuerberatung #Karriere #Job #Bewerbung #Teamwork'}, {'from': 'human', 'value': 'Schreibe den Text objektiv und sachlich.'}, {'from': 'gpt', 'value': 'Post 1:\n\nGuten Tag,\n\nWir sind auf der Suche nach jungen, talentierten Steuerberatern, die ihr Studium im Bereich Steuerwesen erfolgreich abgeschlossen haben. Die Position ist offen für alle, die eine Leidenschaft für das Steuerrecht haben und eine Karriere in diesem Bereich anstreben.\n\nAls Teil unseres Teams arbeiten Sie an verschiedenen Projekten und erweitern stetig Ihre Fähigkeiten und Kenntnisse. Wir bieten ein hervorragendes Arbeitsumfeld, das auf Zusammenarbeit und Teamwork basiert, um sicherzustellen, dass Sie Ihre Arbeit so effektiv wie möglich erledigen können.\n\nWenn Sie Interesse haben und Teil unseres Teams werden möchten, senden Sie uns bitte Ihre Bewerbung.\n\nVielen Dank.\n\nPost 2:\n\nGuten Tag,\n\nWir sind auf der Suche nach motivierten und talentierten Steuerberatern, die an einer Karriere in diesem Bereich interessiert sind. Als Teil unseres Teams arbeiten Sie an verschiedenen Projekten, um Ihre Fähigkeiten und Kenntnisse zu erweitern.\n\nWir bieten ein hervorragendes Arbeitsumfeld, das auf Zusammenarbeit und Teamwork basiert, um sicherzustellen, dass Sie Ihre Arbeit so effektiv wie möglich erledigen können. Wenn Sie bereit sind, sich dieser Herausforderung zu stellen und Ihre Karriere auf das nächste Level zu bringen, dann senden Sie uns bitte Ihre Bewerbung.\n\nVielen Dank.'}]] (ignored)
+
11%|█▏ | 1357/11952 [2:17:57<17:07:58, 5.82s/it]
{'loss': 0.5255, 'learning_rate': 1.9636511702088535e-05, 'epoch': 0.11}
+
11%|█▏ | 1357/11952 [2:17:57<17:07:58, 5.82s/it]
11%|█▏ | 1358/11952 [2:18:04<17:34:09, 5.97s/it]
{'loss': 0.5213, 'learning_rate': 1.963578736017102e-05, 'epoch': 0.11}
+
11%|█▏ | 1358/11952 [2:18:04<17:34:09, 5.97s/it]
11%|█▏ | 1359/11952 [2:18:10<17:33:49, 5.97s/it]
{'loss': 0.5361, 'learning_rate': 1.963506231064136e-05, 'epoch': 0.11}
+
11%|█▏ | 1359/11952 [2:18:10<17:33:49, 5.97s/it]
11%|█▏ | 1360/11952 [2:18:16<17:51:46, 6.07s/it]
{'loss': 0.5014, 'learning_rate': 1.9634336553552803e-05, 'epoch': 0.11}
+
11%|█▏ | 1360/11952 [2:18:16<17:51:46, 6.07s/it]
11%|█▏ | 1361/11952 [2:18:22<17:44:11, 6.03s/it]
{'loss': 0.5107, 'learning_rate': 1.9633610088958638e-05, 'epoch': 0.11}
+
11%|█▏ | 1361/11952 [2:18:22<17:44:11, 6.03s/it]
11%|█▏ | 1362/11952 [2:18:28<17:30:19, 5.95s/it]
{'loss': 0.501, 'learning_rate': 1.9632882916912217e-05, 'epoch': 0.11}
+
11%|█▏ | 1362/11952 [2:18:28<17:30:19, 5.95s/it]
11%|█▏ | 1363/11952 [2:18:34<17:27:39, 5.94s/it]
{'loss': 0.513, 'learning_rate': 1.9632155037466942e-05, 'epoch': 0.11}
+
11%|█▏ | 1363/11952 [2:18:34<17:27:39, 5.94s/it]
11%|█▏ | 1364/11952 [2:18:39<17:09:52, 5.84s/it]
{'loss': 0.4982, 'learning_rate': 1.9631426450676264e-05, 'epoch': 0.11}
+
11%|█▏ | 1364/11952 [2:18:39<17:09:52, 5.84s/it]
11%|█▏ | 1365/11952 [2:18:45<17:22:15, 5.91s/it]
{'loss': 0.5127, 'learning_rate': 1.9630697156593688e-05, 'epoch': 0.11}
+
11%|█▏ | 1365/11952 [2:18:45<17:22:15, 5.91s/it]
11%|█▏ | 1366/11952 [2:18:51<17:23:09, 5.91s/it]
{'loss': 0.488, 'learning_rate': 1.962996715527277e-05, 'epoch': 0.11}
+
11%|█▏ | 1366/11952 [2:18:51<17:23:09, 5.91s/it]
11%|█▏ | 1367/11952 [2:18:57<17:10:49, 5.84s/it]
{'loss': 0.5273, 'learning_rate': 1.9629236446767118e-05, 'epoch': 0.11}
+
11%|█▏ | 1367/11952 [2:18:57<17:10:49, 5.84s/it]
11%|█▏ | 1368/11952 [2:19:03<17:21:42, 5.91s/it]
{'loss': 0.506, 'learning_rate': 1.962850503113039e-05, 'epoch': 0.11}
+
11%|█▏ | 1368/11952 [2:19:03<17:21:42, 5.91s/it]
11%|█▏ | 1369/11952 [2:19:09<17:42:26, 6.02s/it]
{'loss': 0.4915, 'learning_rate': 1.9627772908416302e-05, 'epoch': 0.11}
+
11%|█▏ | 1369/11952 [2:19:09<17:42:26, 6.02s/it]
11%|█▏ | 1370/11952 [2:19:15<17:20:30, 5.90s/it]
{'loss': 0.506, 'learning_rate': 1.9627040078678617e-05, 'epoch': 0.11}
+
11%|█▏ | 1370/11952 [2:19:15<17:20:30, 5.90s/it]
11%|█▏ | 1371/11952 [2:19:20<17:06:56, 5.82s/it]
{'loss': 0.5139, 'learning_rate': 1.9626306541971153e-05, 'epoch': 0.11}
+
11%|█▏ | 1371/11952 [2:19:20<17:06:56, 5.82s/it]
11%|█▏ | 1372/11952 [2:19:26<16:57:50, 5.77s/it]
{'loss': 0.4852, 'learning_rate': 1.962557229834777e-05, 'epoch': 0.11}
+
11%|█▏ | 1372/11952 [2:19:26<16:57:50, 5.77s/it]
11%|█▏ | 1373/11952 [2:19:32<16:57:38, 5.77s/it]
{'loss': 0.532, 'learning_rate': 1.9624837347862398e-05, 'epoch': 0.11}
+
11%|█▏ | 1373/11952 [2:19:32<16:57:38, 5.77s/it]
11%|█▏ | 1374/11952 [2:19:38<17:02:16, 5.80s/it]
{'loss': 0.5052, 'learning_rate': 1.9624101690569e-05, 'epoch': 0.11}
+
11%|█▏ | 1374/11952 [2:19:38<17:02:16, 5.80s/it]
12%|█▏ | 1375/11952 [2:19:43<16:56:58, 5.77s/it]
{'loss': 0.5007, 'learning_rate': 1.9623365326521603e-05, 'epoch': 0.12}
+
12%|█▏ | 1375/11952 [2:19:43<16:56:58, 5.77s/it]
12%|█▏ | 1376/11952 [2:19:49<16:43:52, 5.70s/it]
{'loss': 0.4933, 'learning_rate': 1.9622628255774288e-05, 'epoch': 0.12}
+
12%|█▏ | 1376/11952 [2:19:49<16:43:52, 5.70s/it]
12%|█▏ | 1377/11952 [2:19:55<16:44:16, 5.70s/it]
{'loss': 0.5235, 'learning_rate': 1.9621890478381175e-05, 'epoch': 0.12}
+
12%|█▏ | 1377/11952 [2:19:55<16:44:16, 5.70s/it]
12%|█▏ | 1378/11952 [2:20:01<16:54:16, 5.76s/it]
{'loss': 0.5125, 'learning_rate': 1.9621151994396443e-05, 'epoch': 0.12}
+
12%|█▏ | 1378/11952 [2:20:01<16:54:16, 5.76s/it]
12%|█▏ | 1379/11952 [2:20:07<17:23:14, 5.92s/it]
{'loss': 0.5039, 'learning_rate': 1.962041280387433e-05, 'epoch': 0.12}
+
12%|█▏ | 1379/11952 [2:20:07<17:23:14, 5.92s/it]
12%|█▏ | 1380/11952 [2:20:13<17:20:16, 5.90s/it]
{'loss': 0.5263, 'learning_rate': 1.9619672906869114e-05, 'epoch': 0.12}
+
12%|█▏ | 1380/11952 [2:20:13<17:20:16, 5.90s/it]
12%|█▏ | 1381/11952 [2:20:19<17:32:34, 5.97s/it]
{'loss': 0.5178, 'learning_rate': 1.961893230343513e-05, 'epoch': 0.12}
+
12%|█▏ | 1381/11952 [2:20:19<17:32:34, 5.97s/it]
12%|█▏ | 1382/11952 [2:20:25<17:17:30, 5.89s/it]
{'loss': 0.5091, 'learning_rate': 1.9618190993626768e-05, 'epoch': 0.12}
+
12%|█▏ | 1382/11952 [2:20:25<17:17:30, 5.89s/it]
12%|█▏ | 1383/11952 [2:20:31<17:31:28, 5.97s/it]
{'loss': 0.5201, 'learning_rate': 1.961744897749846e-05, 'epoch': 0.12}
+
12%|█▏ | 1383/11952 [2:20:31<17:31:28, 5.97s/it]
12%|█▏ | 1384/11952 [2:20:36<17:20:30, 5.91s/it]
{'loss': 0.5166, 'learning_rate': 1.9616706255104705e-05, 'epoch': 0.12}
+
12%|█▏ | 1384/11952 [2:20:36<17:20:30, 5.91s/it]
12%|█▏ | 1385/11952 [2:20:43<17:42:38, 6.03s/it]
{'loss': 0.5028, 'learning_rate': 1.9615962826500038e-05, 'epoch': 0.12}
+
12%|█▏ | 1385/11952 [2:20:43<17:42:38, 6.03s/it]
12%|█▏ | 1386/11952 [2:20:48<17:24:56, 5.93s/it]
{'loss': 0.5015, 'learning_rate': 1.961521869173906e-05, 'epoch': 0.12}
+
12%|█▏ | 1386/11952 [2:20:48<17:24:56, 5.93s/it]
12%|█▏ | 1387/11952 [2:20:54<17:18:03, 5.90s/it]
{'loss': 0.507, 'learning_rate': 1.9614473850876413e-05, 'epoch': 0.12}
+
12%|█▏ | 1387/11952 [2:20:54<17:18:03, 5.90s/it]
12%|█▏ | 1388/11952 [2:21:00<17:19:55, 5.91s/it]
{'loss': 0.513, 'learning_rate': 1.9613728303966794e-05, 'epoch': 0.12}
+
12%|█▏ | 1388/11952 [2:21:00<17:19:55, 5.91s/it]
12%|█▏ | 1389/11952 [2:21:06<17:24:30, 5.93s/it]
{'loss': 0.5002, 'learning_rate': 1.961298205106496e-05, 'epoch': 0.12}
+
12%|█▏ | 1389/11952 [2:21:06<17:24:30, 5.93s/it]
12%|█▏ | 1390/11952 [2:21:12<17:11:02, 5.86s/it]
{'loss': 0.5226, 'learning_rate': 1.9612235092225704e-05, 'epoch': 0.12}
+
12%|█▏ | 1390/11952 [2:21:12<17:11:02, 5.86s/it]
12%|█▏ | 1391/11952 [2:21:18<17:35:37, 6.00s/it]
{'loss': 0.4932, 'learning_rate': 1.9611487427503883e-05, 'epoch': 0.12}
+
12%|█▏ | 1391/11952 [2:21:18<17:35:37, 6.00s/it]
12%|█▏ | 1392/11952 [2:21:24<17:42:26, 6.04s/it]
{'loss': 0.5077, 'learning_rate': 1.9610739056954406e-05, 'epoch': 0.12}
+
12%|█▏ | 1392/11952 [2:21:24<17:42:26, 6.04s/it]
12%|█▏ | 1393/11952 [2:21:30<17:36:03, 6.00s/it]
{'loss': 0.5023, 'learning_rate': 1.9609989980632222e-05, 'epoch': 0.12}
+
12%|█▏ | 1393/11952 [2:21:30<17:36:03, 6.00s/it]
12%|█▏ | 1394/11952 [2:21:36<17:32:56, 5.98s/it]
{'loss': 0.52, 'learning_rate': 1.9609240198592344e-05, 'epoch': 0.12}
+
12%|█▏ | 1394/11952 [2:21:36<17:32:56, 5.98s/it]
12%|█▏ | 1395/11952 [2:21:42<17:15:46, 5.89s/it]
{'loss': 0.488, 'learning_rate': 1.9608489710889837e-05, 'epoch': 0.12}
+
12%|█▏ | 1395/11952 [2:21:42<17:15:46, 5.89s/it]
12%|█▏ | 1396/11952 [2:21:48<17:11:05, 5.86s/it]
{'loss': 0.4979, 'learning_rate': 1.9607738517579807e-05, 'epoch': 0.12}
+
12%|█▏ | 1396/11952 [2:21:48<17:11:05, 5.86s/it]
12%|█▏ | 1397/11952 [2:21:54<17:22:54, 5.93s/it]
{'loss': 0.5187, 'learning_rate': 1.9606986618717428e-05, 'epoch': 0.12}
+
12%|█▏ | 1397/11952 [2:21:54<17:22:54, 5.93s/it]
12%|█▏ | 1398/11952 [2:22:00<17:25:12, 5.94s/it]
{'loss': 0.5141, 'learning_rate': 1.9606234014357905e-05, 'epoch': 0.12}
+
12%|█▏ | 1398/11952 [2:22:00<17:25:12, 5.94s/it]
12%|█▏ | 1399/11952 [2:22:05<17:12:01, 5.87s/it]
{'loss': 0.5124, 'learning_rate': 1.9605480704556516e-05, 'epoch': 0.12}
+
12%|█▏ | 1399/11952 [2:22:05<17:12:01, 5.87s/it]1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+07 6 AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+AutoResumeHook: Checking whether to suspend...
+
12%|█▏ | 1400/11952 [2:22:11<16:51:17, 5.75s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4959, 'learning_rate': 1.960472668936857e-05, 'epoch': 0.12}
+
12%|█▏ | 1400/11952 [2:22:11<16:51:17, 5.75s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
12%|█▏ | 1401/11952 [2:22:42<39:02:48, 13.32s/it]
{'loss': 0.495, 'learning_rate': 1.960397196884945e-05, 'epoch': 0.12}
+
12%|█▏ | 1401/11952 [2:22:42<39:02:48, 13.32s/it]
12%|█▏ | 1402/11952 [2:22:48<32:30:33, 11.09s/it]
{'loss': 0.514, 'learning_rate': 1.960321654305457e-05, 'epoch': 0.12}
+
12%|█▏ | 1402/11952 [2:22:48<32:30:33, 11.09s/it]
12%|█▏ | 1403/11952 [2:22:53<27:46:37, 9.48s/it]
{'loss': 0.5115, 'learning_rate': 1.9602460412039416e-05, 'epoch': 0.12}
+
12%|█▏ | 1403/11952 [2:22:53<27:46:37, 9.48s/it]
12%|█▏ | 1404/11952 [2:22:59<24:28:50, 8.36s/it]
{'loss': 0.527, 'learning_rate': 1.9601703575859504e-05, 'epoch': 0.12}
+
12%|█▏ | 1404/11952 [2:22:59<24:28:50, 8.36s/it]
12%|█▏ | 1405/11952 [2:23:05<22:06:26, 7.55s/it]
{'loss': 0.5074, 'learning_rate': 1.960094603457042e-05, 'epoch': 0.12}
+
12%|█▏ | 1405/11952 [2:23:05<22:06:26, 7.55s/it]
12%|█▏ | 1406/11952 [2:23:11<20:46:13, 7.09s/it]
{'loss': 0.51, 'learning_rate': 1.960018778822779e-05, 'epoch': 0.12}
+
12%|█▏ | 1406/11952 [2:23:11<20:46:13, 7.09s/it]
12%|█▏ | 1407/11952 [2:23:17<19:46:12, 6.75s/it]
{'loss': 0.5231, 'learning_rate': 1.9599428836887302e-05, 'epoch': 0.12}
+
12%|█▏ | 1407/11952 [2:23:17<19:46:12, 6.75s/it]
12%|█▏ | 1408/11952 [2:23:23<18:57:50, 6.47s/it]
{'loss': 0.5108, 'learning_rate': 1.9598669180604685e-05, 'epoch': 0.12}
+
12%|█▏ | 1408/11952 [2:23:23<18:57:50, 6.47s/it]
12%|█▏ | 1409/11952 [2:23:29<18:37:03, 6.36s/it]
{'loss': 0.5175, 'learning_rate': 1.959790881943573e-05, 'epoch': 0.12}
+
12%|█▏ | 1409/11952 [2:23:29<18:37:03, 6.36s/it]
12%|█▏ | 1410/11952 [2:23:34<18:00:42, 6.15s/it]
{'loss': 0.4948, 'learning_rate': 1.959714775343627e-05, 'epoch': 0.12}
+
12%|█▏ | 1410/11952 [2:23:34<18:00:42, 6.15s/it]
12%|█▏ | 1411/11952 [2:23:40<17:34:56, 6.00s/it]
{'loss': 0.5196, 'learning_rate': 1.9596385982662197e-05, 'epoch': 0.12}
+
12%|█▏ | 1411/11952 [2:23:40<17:34:56, 6.00s/it]
12%|█▏ | 1412/11952 [2:23:46<17:14:41, 5.89s/it]
{'loss': 0.4951, 'learning_rate': 1.959562350716945e-05, 'epoch': 0.12}
+
12%|█▏ | 1412/11952 [2:23:46<17:14:41, 5.89s/it]
12%|█▏ | 1413/11952 [2:23:52<17:10:17, 5.87s/it]
{'loss': 0.5001, 'learning_rate': 1.959486032701403e-05, 'epoch': 0.12}
+
12%|█▏ | 1413/11952 [2:23:52<17:10:17, 5.87s/it]
12%|█▏ | 1414/11952 [2:23:58<17:15:41, 5.90s/it]
{'loss': 0.5112, 'learning_rate': 1.959409644225197e-05, 'epoch': 0.12}
+
12%|█▏ | 1414/11952 [2:23:58<17:15:41, 5.90s/it]
12%|█▏ | 1415/11952 [2:24:03<17:16:19, 5.90s/it]
{'loss': 0.5144, 'learning_rate': 1.959333185293937e-05, 'epoch': 0.12}
+
12%|█▏ | 1415/11952 [2:24:03<17:16:19, 5.90s/it]
12%|█▏ | 1416/11952 [2:24:09<17:13:10, 5.88s/it]
{'loss': 0.5077, 'learning_rate': 1.9592566559132384e-05, 'epoch': 0.12}
+
12%|█▏ | 1416/11952 [2:24:09<17:13:10, 5.88s/it]
12%|█▏ | 1417/11952 [2:24:15<17:08:38, 5.86s/it]
{'loss': 0.5186, 'learning_rate': 1.9591800560887207e-05, 'epoch': 0.12}
+
12%|█▏ | 1417/11952 [2:24:15<17:08:38, 5.86s/it]
12%|█▏ | 1418/11952 [2:24:21<17:10:34, 5.87s/it]
{'loss': 0.5239, 'learning_rate': 1.9591033858260094e-05, 'epoch': 0.12}
+
12%|█▏ | 1418/11952 [2:24:21<17:10:34, 5.87s/it]
12%|█▏ | 1419/11952 [2:24:27<17:11:24, 5.88s/it]
{'loss': 0.5225, 'learning_rate': 1.9590266451307348e-05, 'epoch': 0.12}
+
12%|█▏ | 1419/11952 [2:24:27<17:11:24, 5.88s/it]
12%|█▏ | 1420/11952 [2:24:33<17:03:14, 5.83s/it]
{'loss': 0.5016, 'learning_rate': 1.958949834008532e-05, 'epoch': 0.12}
+
12%|█▏ | 1420/11952 [2:24:33<17:03:14, 5.83s/it]
12%|█▏ | 1421/11952 [2:24:38<16:50:40, 5.76s/it]
{'loss': 0.4952, 'learning_rate': 1.958872952465042e-05, 'epoch': 0.12}
+
12%|█▏ | 1421/11952 [2:24:38<16:50:40, 5.76s/it]
12%|█▏ | 1422/11952 [2:24:44<16:56:08, 5.79s/it]
{'loss': 0.4957, 'learning_rate': 1.9587960005059104e-05, 'epoch': 0.12}
+
12%|█▏ | 1422/11952 [2:24:44<16:56:08, 5.79s/it]
12%|█▏ | 1423/11952 [2:24:50<16:56:20, 5.79s/it]
{'loss': 0.5117, 'learning_rate': 1.9587189781367888e-05, 'epoch': 0.12}
+
12%|█▏ | 1423/11952 [2:24:50<16:56:20, 5.79s/it]
12%|█▏ | 1424/11952 [2:24:56<17:16:38, 5.91s/it]
{'loss': 0.5254, 'learning_rate': 1.958641885363333e-05, 'epoch': 0.12}
+
12%|█▏ | 1424/11952 [2:24:56<17:16:38, 5.91s/it]
12%|█▏ | 1425/11952 [2:25:02<17:07:54, 5.86s/it]
{'loss': 0.5041, 'learning_rate': 1.9585647221912044e-05, 'epoch': 0.12}
+
12%|█▏ | 1425/11952 [2:25:02<17:07:54, 5.86s/it]
12%|█▏ | 1426/11952 [2:25:07<16:54:14, 5.78s/it]
{'loss': 0.4954, 'learning_rate': 1.9584874886260695e-05, 'epoch': 0.12}
+
12%|█▏ | 1426/11952 [2:25:07<16:54:14, 5.78s/it]
12%|█▏ | 1427/11952 [2:25:13<16:53:56, 5.78s/it]
{'loss': 0.5099, 'learning_rate': 1.9584101846736002e-05, 'epoch': 0.12}
+
12%|█▏ | 1427/11952 [2:25:13<16:53:56, 5.78s/it]
12%|█▏ | 1428/11952 [2:25:19<17:04:07, 5.84s/it]
{'loss': 0.5261, 'learning_rate': 1.9583328103394733e-05, 'epoch': 0.12}
+
12%|█▏ | 1428/11952 [2:25:19<17:04:07, 5.84s/it]
12%|█▏ | 1429/11952 [2:25:25<16:59:27, 5.81s/it]
{'loss': 0.4948, 'learning_rate': 1.9582553656293707e-05, 'epoch': 0.12}
+
12%|█▏ | 1429/11952 [2:25:25<16:59:27, 5.81s/it]
12%|█▏ | 1430/11952 [2:25:31<16:52:03, 5.77s/it]
{'loss': 0.5298, 'learning_rate': 1.9581778505489797e-05, 'epoch': 0.12}
+
12%|█▏ | 1430/11952 [2:25:31<16:52:03, 5.77s/it]
12%|█▏ | 1431/11952 [2:25:37<17:04:33, 5.84s/it]
{'loss': 0.5066, 'learning_rate': 1.9581002651039928e-05, 'epoch': 0.12}
+
12%|█▏ | 1431/11952 [2:25:37<17:04:33, 5.84s/it]
12%|█▏ | 1432/11952 [2:25:42<17:09:06, 5.87s/it]
{'loss': 0.5078, 'learning_rate': 1.9580226093001077e-05, 'epoch': 0.12}
+
12%|█▏ | 1432/11952 [2:25:42<17:09:06, 5.87s/it]
12%|█▏ | 1433/11952 [2:25:48<17:09:10, 5.87s/it]
{'loss': 0.5214, 'learning_rate': 1.9579448831430264e-05, 'epoch': 0.12}
+
12%|█▏ | 1433/11952 [2:25:48<17:09:10, 5.87s/it]
12%|█▏ | 1434/11952 [2:25:54<17:09:17, 5.87s/it]
{'loss': 0.5257, 'learning_rate': 1.9578670866384574e-05, 'epoch': 0.12}
+
12%|█▏ | 1434/11952 [2:25:54<17:09:17, 5.87s/it]
12%|█▏ | 1435/11952 [2:26:00<17:18:34, 5.93s/it]
{'loss': 0.5086, 'learning_rate': 1.9577892197921136e-05, 'epoch': 0.12}
+
12%|█▏ | 1435/11952 [2:26:00<17:18:34, 5.93s/it]
12%|█▏ | 1436/11952 [2:26:06<17:21:29, 5.94s/it]
{'loss': 0.5219, 'learning_rate': 1.9577112826097134e-05, 'epoch': 0.12}
+
12%|█▏ | 1436/11952 [2:26:06<17:21:29, 5.94s/it]
12%|█▏ | 1437/11952 [2:26:12<17:07:27, 5.86s/it]
{'loss': 0.509, 'learning_rate': 1.95763327509698e-05, 'epoch': 0.12}
+
12%|█▏ | 1437/11952 [2:26:12<17:07:27, 5.86s/it]
12%|█▏ | 1438/11952 [2:26:17<16:50:39, 5.77s/it]
{'loss': 0.5082, 'learning_rate': 1.9575551972596422e-05, 'epoch': 0.12}
+
12%|█▏ | 1438/11952 [2:26:17<16:50:39, 5.77s/it]
12%|█▏ | 1439/11952 [2:26:23<16:53:40, 5.79s/it]
{'loss': 0.5165, 'learning_rate': 1.9574770491034333e-05, 'epoch': 0.12}
+
12%|█▏ | 1439/11952 [2:26:23<16:53:40, 5.79s/it]
12%|█▏ | 1440/11952 [2:26:29<17:01:24, 5.83s/it]
{'loss': 0.5104, 'learning_rate': 1.9573988306340924e-05, 'epoch': 0.12}
+
12%|█▏ | 1440/11952 [2:26:29<17:01:24, 5.83s/it]
12%|█▏ | 1441/11952 [2:26:35<17:06:49, 5.86s/it]
{'loss': 0.5131, 'learning_rate': 1.9573205418573634e-05, 'epoch': 0.12}
+
12%|█▏ | 1441/11952 [2:26:35<17:06:49, 5.86s/it]
12%|█▏ | 1442/11952 [2:26:41<17:01:13, 5.83s/it]
{'loss': 0.5001, 'learning_rate': 1.9572421827789954e-05, 'epoch': 0.12}
+
12%|█▏ | 1442/11952 [2:26:41<17:01:13, 5.83s/it]
12%|█▏ | 1443/11952 [2:26:47<16:59:54, 5.82s/it]
{'loss': 0.5068, 'learning_rate': 1.957163753404743e-05, 'epoch': 0.12}
+
12%|█▏ | 1443/11952 [2:26:47<16:59:54, 5.82s/it]
12%|█▏ | 1444/11952 [2:26:53<17:01:54, 5.84s/it]
{'loss': 0.5094, 'learning_rate': 1.957085253740366e-05, 'epoch': 0.12}
+
12%|█▏ | 1444/11952 [2:26:53<17:01:54, 5.84s/it]
12%|█▏ | 1445/11952 [2:26:58<16:47:23, 5.75s/it]
{'loss': 0.504, 'learning_rate': 1.9570066837916285e-05, 'epoch': 0.12}
+
12%|█▏ | 1445/11952 [2:26:58<16:47:23, 5.75s/it]
12%|█▏ | 1446/11952 [2:27:04<16:40:49, 5.72s/it]
{'loss': 0.5258, 'learning_rate': 1.956928043564301e-05, 'epoch': 0.12}
+
12%|█▏ | 1446/11952 [2:27:04<16:40:49, 5.72s/it]
12%|█▏ | 1447/11952 [2:27:10<16:44:35, 5.74s/it]
{'loss': 0.5101, 'learning_rate': 1.956849333064158e-05, 'epoch': 0.12}
+
12%|█▏ | 1447/11952 [2:27:10<16:44:35, 5.74s/it]
12%|█▏ | 1448/11952 [2:27:15<16:46:11, 5.75s/it]
{'loss': 0.5094, 'learning_rate': 1.9567705522969796e-05, 'epoch': 0.12}
+
12%|█▏ | 1448/11952 [2:27:15<16:46:11, 5.75s/it]
12%|█▏ | 1449/11952 [2:27:21<16:53:54, 5.79s/it]
{'loss': 0.5293, 'learning_rate': 1.9566917012685515e-05, 'epoch': 0.12}
+
12%|█▏ | 1449/11952 [2:27:21<16:53:54, 5.79s/it]2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
12%|█▏ | 1450/11952 [2:27:27<16:58:55, 5.82s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.515, 'learning_rate': 1.9566127799846642e-05, 'epoch': 0.12}
+
12%|█▏ | 1450/11952 [2:27:27<16:58:55, 5.82s/it]
12%|█▏ | 1451/11952 [2:27:33<16:58:15, 5.82s/it]
{'loss': 0.4926, 'learning_rate': 1.9565337884511128e-05, 'epoch': 0.12}
+
12%|█▏ | 1451/11952 [2:27:33<16:58:15, 5.82s/it]
12%|█▏ | 1452/11952 [2:27:39<16:58:18, 5.82s/it]
{'loss': 0.5152, 'learning_rate': 1.956454726673699e-05, 'epoch': 0.12}
+
12%|█▏ | 1452/11952 [2:27:39<16:58:18, 5.82s/it]
12%|█▏ | 1453/11952 [2:27:45<17:09:41, 5.88s/it]
{'loss': 0.5183, 'learning_rate': 1.9563755946582277e-05, 'epoch': 0.12}
+
12%|█▏ | 1453/11952 [2:27:45<17:09:41, 5.88s/it]
12%|█▏ | 1454/11952 [2:27:51<17:04:16, 5.85s/it]
{'loss': 0.5313, 'learning_rate': 1.956296392410511e-05, 'epoch': 0.12}
+
12%|█▏ | 1454/11952 [2:27:51<17:04:16, 5.85s/it]
12%|█▏ | 1455/11952 [2:27:57<17:08:14, 5.88s/it]
{'loss': 0.4952, 'learning_rate': 1.9562171199363646e-05, 'epoch': 0.12}
+
12%|█▏ | 1455/11952 [2:27:57<17:08:14, 5.88s/it]
12%|█▏ | 1456/11952 [2:28:02<17:04:02, 5.85s/it]
{'loss': 0.5244, 'learning_rate': 1.9561377772416103e-05, 'epoch': 0.12}
+
12%|█▏ | 1456/11952 [2:28:02<17:04:02, 5.85s/it]
12%|█▏ | 1457/11952 [2:28:09<17:26:09, 5.98s/it]
{'loss': 0.5044, 'learning_rate': 1.9560583643320745e-05, 'epoch': 0.12}
+
12%|█▏ | 1457/11952 [2:28:09<17:26:09, 5.98s/it]
12%|█▏ | 1458/11952 [2:28:15<17:32:11, 6.02s/it]
{'loss': 0.5245, 'learning_rate': 1.955978881213589e-05, 'epoch': 0.12}
+
12%|█▏ | 1458/11952 [2:28:15<17:32:11, 6.02s/it]
12%|█▏ | 1459/11952 [2:28:20<17:18:28, 5.94s/it]
{'loss': 0.5117, 'learning_rate': 1.9558993278919904e-05, 'epoch': 0.12}
+
12%|█▏ | 1459/11952 [2:28:20<17:18:28, 5.94s/it]
12%|█▏ | 1460/11952 [2:28:26<16:57:12, 5.82s/it]
{'loss': 0.4932, 'learning_rate': 1.9558197043731214e-05, 'epoch': 0.12}
+
12%|█▏ | 1460/11952 [2:28:26<16:57:12, 5.82s/it]
12%|█▏ | 1461/11952 [2:28:32<16:54:11, 5.80s/it]
{'loss': 0.4863, 'learning_rate': 1.9557400106628285e-05, 'epoch': 0.12}
+
12%|█▏ | 1461/11952 [2:28:32<16:54:11, 5.80s/it]
12%|█▏ | 1462/11952 [2:28:38<16:53:21, 5.80s/it]
{'loss': 0.5167, 'learning_rate': 1.9556602467669645e-05, 'epoch': 0.12}
+
12%|█▏ | 1462/11952 [2:28:38<16:53:21, 5.80s/it]
12%|█▏ | 1463/11952 [2:28:44<17:08:24, 5.88s/it]
{'loss': 0.5063, 'learning_rate': 1.9555804126913868e-05, 'epoch': 0.12}
+
12%|█▏ | 1463/11952 [2:28:44<17:08:24, 5.88s/it]
12%|█▏ | 1464/11952 [2:28:49<16:56:27, 5.81s/it]
{'loss': 0.5097, 'learning_rate': 1.9555005084419585e-05, 'epoch': 0.12}
+
12%|█▏ | 1464/11952 [2:28:49<16:56:27, 5.81s/it]
12%|█▏ | 1465/11952 [2:28:55<17:05:25, 5.87s/it]
{'loss': 0.5213, 'learning_rate': 1.9554205340245468e-05, 'epoch': 0.12}
+
12%|█▏ | 1465/11952 [2:28:55<17:05:25, 5.87s/it]
12%|█▏ | 1466/11952 [2:29:01<17:04:35, 5.86s/it]
{'loss': 0.4985, 'learning_rate': 1.955340489445025e-05, 'epoch': 0.12}
+
12%|█▏ | 1466/11952 [2:29:01<17:04:35, 5.86s/it]
12%|█▏ | 1467/11952 [2:29:07<16:56:51, 5.82s/it]
{'loss': 0.5026, 'learning_rate': 1.9552603747092714e-05, 'epoch': 0.12}
+
12%|█▏ | 1467/11952 [2:29:07<16:56:51, 5.82s/it]
12%|█▏ | 1468/11952 [2:29:12<16:42:10, 5.74s/it]
{'loss': 0.506, 'learning_rate': 1.9551801898231692e-05, 'epoch': 0.12}
+
12%|█▏ | 1468/11952 [2:29:12<16:42:10, 5.74s/it]
12%|█▏ | 1469/11952 [2:29:18<16:50:43, 5.78s/it]
{'loss': 0.5001, 'learning_rate': 1.9550999347926064e-05, 'epoch': 0.12}
+
12%|█▏ | 1469/11952 [2:29:18<16:50:43, 5.78s/it]
12%|█▏ | 1470/11952 [2:29:24<17:05:30, 5.87s/it]
{'loss': 0.5154, 'learning_rate': 1.955019609623477e-05, 'epoch': 0.12}
+
12%|█▏ | 1470/11952 [2:29:24<17:05:30, 5.87s/it]
12%|█▏ | 1471/11952 [2:29:30<16:49:17, 5.78s/it]
{'loss': 0.5028, 'learning_rate': 1.95493921432168e-05, 'epoch': 0.12}
+
12%|█▏ | 1471/11952 [2:29:30<16:49:17, 5.78s/it]
12%|█▏ | 1472/11952 [2:29:35<16:39:39, 5.72s/it]
{'loss': 0.5032, 'learning_rate': 1.9548587488931187e-05, 'epoch': 0.12}
+
12%|█▏ | 1472/11952 [2:29:35<16:39:39, 5.72s/it]
12%|█▏ | 1473/11952 [2:29:42<17:09:48, 5.90s/it]
{'loss': 0.508, 'learning_rate': 1.9547782133437024e-05, 'epoch': 0.12}
+
12%|█▏ | 1473/11952 [2:29:42<17:09:48, 5.90s/it]
12%|█▏ | 1474/11952 [2:29:48<17:03:12, 5.86s/it]
{'loss': 0.5321, 'learning_rate': 1.9546976076793456e-05, 'epoch': 0.12}
+
12%|█▏ | 1474/11952 [2:29:48<17:03:12, 5.86s/it]
12%|█▏ | 1475/11952 [2:29:54<17:23:03, 5.97s/it]
{'loss': 0.4916, 'learning_rate': 1.954616931905967e-05, 'epoch': 0.12}
+
12%|█▏ | 1475/11952 [2:29:54<17:23:03, 5.97s/it]
12%|█▏ | 1476/11952 [2:30:00<17:08:29, 5.89s/it]
{'loss': 0.4889, 'learning_rate': 1.954536186029492e-05, 'epoch': 0.12}
+
12%|█▏ | 1476/11952 [2:30:00<17:08:29, 5.89s/it]
12%|█▏ | 1477/11952 [2:30:05<16:56:07, 5.82s/it]
{'loss': 0.5233, 'learning_rate': 1.954455370055849e-05, 'epoch': 0.12}
+
12%|█▏ | 1477/11952 [2:30:05<16:56:07, 5.82s/it]
12%|█▏ | 1478/11952 [2:30:11<16:48:34, 5.78s/it]
{'loss': 0.4962, 'learning_rate': 1.9543744839909743e-05, 'epoch': 0.12}
+
12%|█▏ | 1478/11952 [2:30:11<16:48:34, 5.78s/it]
12%|█▏ | 1479/11952 [2:30:16<16:39:52, 5.73s/it]
{'loss': 0.4988, 'learning_rate': 1.9542935278408066e-05, 'epoch': 0.12}
+
12%|█▏ | 1479/11952 [2:30:16<16:39:52, 5.73s/it]
12%|█▏ | 1480/11952 [2:30:22<16:46:39, 5.77s/it]
{'loss': 0.5181, 'learning_rate': 1.9542125016112913e-05, 'epoch': 0.12}
+
12%|█▏ | 1480/11952 [2:30:22<16:46:39, 5.77s/it]
12%|█▏ | 1481/11952 [2:30:28<17:03:27, 5.86s/it]
{'loss': 0.5045, 'learning_rate': 1.954131405308379e-05, 'epoch': 0.12}
+
12%|█▏ | 1481/11952 [2:30:28<17:03:27, 5.86s/it]
12%|█▏ | 1482/11952 [2:30:34<16:56:32, 5.83s/it]
{'loss': 0.5008, 'learning_rate': 1.9540502389380245e-05, 'epoch': 0.12}
+
12%|█▏ | 1482/11952 [2:30:34<16:56:32, 5.83s/it]
12%|█▏ | 1483/11952 [2:30:40<16:54:55, 5.82s/it]
{'loss': 0.522, 'learning_rate': 1.953969002506189e-05, 'epoch': 0.12}
+
12%|█▏ | 1483/11952 [2:30:40<16:54:55, 5.82s/it]
12%|█▏ | 1484/11952 [2:30:46<17:00:10, 5.85s/it]
{'loss': 0.5198, 'learning_rate': 1.9538876960188378e-05, 'epoch': 0.12}
+
12%|█▏ | 1484/11952 [2:30:46<17:00:10, 5.85s/it]
12%|█▏ | 1485/11952 [2:30:52<17:07:22, 5.89s/it]
{'loss': 0.5029, 'learning_rate': 1.9538063194819418e-05, 'epoch': 0.12}
+
12%|█▏ | 1485/11952 [2:30:52<17:07:22, 5.89s/it]
12%|█▏ | 1486/11952 [2:30:58<17:17:25, 5.95s/it]
{'loss': 0.5282, 'learning_rate': 1.9537248729014767e-05, 'epoch': 0.12}
+
12%|█▏ | 1486/11952 [2:30:58<17:17:25, 5.95s/it]
12%|█▏ | 1487/11952 [2:31:04<17:18:43, 5.96s/it]
{'loss': 0.5243, 'learning_rate': 1.9536433562834235e-05, 'epoch': 0.12}
+
12%|█▏ | 1487/11952 [2:31:04<17:18:43, 5.96s/it]
12%|█▏ | 1488/11952 [2:31:10<17:12:04, 5.92s/it]
{'loss': 0.5025, 'learning_rate': 1.953561769633769e-05, 'epoch': 0.12}
+
12%|█▏ | 1488/11952 [2:31:10<17:12:04, 5.92s/it]
12%|█▏ | 1489/11952 [2:31:16<17:21:50, 5.97s/it]
{'loss': 0.5192, 'learning_rate': 1.9534801129585044e-05, 'epoch': 0.12}
+
12%|█▏ | 1489/11952 [2:31:16<17:21:50, 5.97s/it]
12%|█▏ | 1490/11952 [2:31:22<17:05:52, 5.88s/it]
{'loss': 0.4863, 'learning_rate': 1.953398386263626e-05, 'epoch': 0.12}
+
12%|█▏ | 1490/11952 [2:31:22<17:05:52, 5.88s/it]
12%|█▏ | 1491/11952 [2:31:27<17:05:43, 5.88s/it]
{'loss': 0.5097, 'learning_rate': 1.9533165895551356e-05, 'epoch': 0.12}
+
12%|█▏ | 1491/11952 [2:31:27<17:05:43, 5.88s/it]
12%|█▏ | 1492/11952 [2:31:34<17:23:40, 5.99s/it]
{'loss': 0.5092, 'learning_rate': 1.95323472283904e-05, 'epoch': 0.12}
+
12%|█▏ | 1492/11952 [2:31:34<17:23:40, 5.99s/it]
12%|█▏ | 1493/11952 [2:31:40<17:20:55, 5.97s/it]
{'loss': 0.5021, 'learning_rate': 1.9531527861213514e-05, 'epoch': 0.12}
+
12%|█▏ | 1493/11952 [2:31:40<17:20:55, 5.97s/it]
12%|█▎ | 1494/11952 [2:31:45<16:58:44, 5.84s/it]
{'loss': 0.5236, 'learning_rate': 1.9530707794080864e-05, 'epoch': 0.12}
+
12%|█▎ | 1494/11952 [2:31:45<16:58:44, 5.84s/it]
13%|█▎ | 1495/11952 [2:31:51<17:01:32, 5.86s/it]
{'loss': 0.5116, 'learning_rate': 1.9529887027052676e-05, 'epoch': 0.13}
+
13%|█▎ | 1495/11952 [2:31:51<17:01:32, 5.86s/it]
13%|█▎ | 1496/11952 [2:31:57<17:09:14, 5.91s/it]
{'loss': 0.5081, 'learning_rate': 1.952906556018922e-05, 'epoch': 0.13}
+
13%|█▎ | 1496/11952 [2:31:57<17:09:14, 5.91s/it]
13%|█▎ | 1497/11952 [2:32:03<17:02:23, 5.87s/it]
{'loss': 0.4812, 'learning_rate': 1.9528243393550825e-05, 'epoch': 0.13}
+
13%|█▎ | 1497/11952 [2:32:03<17:02:23, 5.87s/it]
13%|█▎ | 1498/11952 [2:32:09<17:00:38, 5.86s/it]
{'loss': 0.5272, 'learning_rate': 1.9527420527197867e-05, 'epoch': 0.13}
+
13%|█▎ | 1498/11952 [2:32:09<17:00:38, 5.86s/it]
13%|█▎ | 1499/11952 [2:32:14<16:46:08, 5.78s/it]
{'loss': 0.4959, 'learning_rate': 1.9526596961190772e-05, 'epoch': 0.13}
+
13%|█▎ | 1499/11952 [2:32:14<16:46:08, 5.78s/it]2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 7 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
13%|█▎ | 1500/11952 [2:32:20<16:54:07, 5.82s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5129, 'learning_rate': 1.952577269559002e-05, 'epoch': 0.13}
+
13%|█▎ | 1500/11952 [2:32:20<16:54:07, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
13%|█▎ | 1501/11952 [2:32:54<41:05:41, 14.16s/it]
{'loss': 0.5061, 'learning_rate': 1.952494773045614e-05, 'epoch': 0.13}
+
13%|█▎ | 1501/11952 [2:32:54<41:05:41, 14.16s/it]
13%|█▎ | 1502/11952 [2:33:00<33:59:09, 11.71s/it]
{'loss': 0.5036, 'learning_rate': 1.9524122065849722e-05, 'epoch': 0.13}
+
13%|█▎ | 1502/11952 [2:33:00<33:59:09, 11.71s/it]
13%|█▎ | 1503/11952 [2:33:06<29:01:10, 10.00s/it]
{'loss': 0.5044, 'learning_rate': 1.9523295701831388e-05, 'epoch': 0.13}
+
13%|█▎ | 1503/11952 [2:33:06<29:01:10, 10.00s/it]
13%|█▎ | 1504/11952 [2:33:12<25:25:27, 8.76s/it]
{'loss': 0.516, 'learning_rate': 1.952246863846183e-05, 'epoch': 0.13}
+
13%|█▎ | 1504/11952 [2:33:12<25:25:27, 8.76s/it]
13%|█▎ | 1505/11952 [2:33:17<22:35:53, 7.79s/it]
{'loss': 0.5064, 'learning_rate': 1.9521640875801783e-05, 'epoch': 0.13}
+
13%|█▎ | 1505/11952 [2:33:17<22:35:53, 7.79s/it]
13%|█▎ | 1506/11952 [2:33:23<21:12:36, 7.31s/it]
{'loss': 0.5003, 'learning_rate': 1.9520812413912032e-05, 'epoch': 0.13}
+
13%|█▎ | 1506/11952 [2:33:23<21:12:36, 7.31s/it]
13%|█▎ | 1507/11952 [2:33:29<19:53:55, 6.86s/it]
{'loss': 0.5019, 'learning_rate': 1.9519983252853415e-05, 'epoch': 0.13}
+
13%|█▎ | 1507/11952 [2:33:29<19:53:55, 6.86s/it]
13%|█▎ | 1508/11952 [2:33:35<18:57:36, 6.54s/it]
{'loss': 0.5233, 'learning_rate': 1.9519153392686828e-05, 'epoch': 0.13}
+
13%|█▎ | 1508/11952 [2:33:35<18:57:36, 6.54s/it]
13%|█▎ | 1509/11952 [2:33:41<18:19:24, 6.32s/it]
{'loss': 0.516, 'learning_rate': 1.951832283347321e-05, 'epoch': 0.13}
+
13%|█▎ | 1509/11952 [2:33:41<18:19:24, 6.32s/it]
13%|█▎ | 1510/11952 [2:33:46<17:45:42, 6.12s/it]
{'loss': 0.5068, 'learning_rate': 1.9517491575273552e-05, 'epoch': 0.13}
+
13%|█▎ | 1510/11952 [2:33:46<17:45:42, 6.12s/it]
13%|█▎ | 1511/11952 [2:33:52<17:44:27, 6.12s/it]
{'loss': 0.5093, 'learning_rate': 1.9516659618148897e-05, 'epoch': 0.13}
+
13%|█▎ | 1511/11952 [2:33:52<17:44:27, 6.12s/it]
13%|█▎ | 1512/11952 [2:33:58<17:34:09, 6.06s/it]
{'loss': 0.5433, 'learning_rate': 1.9515826962160342e-05, 'epoch': 0.13}
+
13%|█▎ | 1512/11952 [2:33:58<17:34:09, 6.06s/it]
13%|█▎ | 1513/11952 [2:34:04<17:17:06, 5.96s/it]
{'loss': 0.4968, 'learning_rate': 1.9514993607369037e-05, 'epoch': 0.13}
+
13%|█▎ | 1513/11952 [2:34:04<17:17:06, 5.96s/it]
13%|█▎ | 1514/11952 [2:34:10<17:13:22, 5.94s/it]
{'loss': 0.5295, 'learning_rate': 1.9514159553836177e-05, 'epoch': 0.13}
+
13%|█▎ | 1514/11952 [2:34:10<17:13:22, 5.94s/it]
13%|█▎ | 1515/11952 [2:34:16<16:48:49, 5.80s/it]
{'loss': 0.5024, 'learning_rate': 1.951332480162301e-05, 'epoch': 0.13}
+
13%|█▎ | 1515/11952 [2:34:16<16:48:49, 5.80s/it]
13%|█▎ | 1516/11952 [2:34:21<16:55:55, 5.84s/it]
{'loss': 0.4909, 'learning_rate': 1.9512489350790838e-05, 'epoch': 0.13}
+
13%|█▎ | 1516/11952 [2:34:21<16:55:55, 5.84s/it]
13%|█▎ | 1517/11952 [2:34:28<17:09:29, 5.92s/it]
{'loss': 0.5222, 'learning_rate': 1.9511653201401012e-05, 'epoch': 0.13}
+
13%|█▎ | 1517/11952 [2:34:28<17:09:29, 5.92s/it]
13%|█▎ | 1518/11952 [2:34:33<16:59:27, 5.86s/it]
{'loss': 0.538, 'learning_rate': 1.951081635351494e-05, 'epoch': 0.13}
+
13%|█▎ | 1518/11952 [2:34:33<16:59:27, 5.86s/it]
13%|█▎ | 1519/11952 [2:34:39<16:39:09, 5.75s/it]
{'loss': 0.5152, 'learning_rate': 1.9509978807194075e-05, 'epoch': 0.13}
+
13%|█▎ | 1519/11952 [2:34:39<16:39:09, 5.75s/it]
13%|█▎ | 1520/11952 [2:34:45<16:56:16, 5.85s/it]
{'loss': 0.5195, 'learning_rate': 1.950914056249992e-05, 'epoch': 0.13}
+
13%|█▎ | 1520/11952 [2:34:45<16:56:16, 5.85s/it]
13%|█▎ | 1521/11952 [2:34:50<16:46:46, 5.79s/it]
{'loss': 0.496, 'learning_rate': 1.9508301619494033e-05, 'epoch': 0.13}
+
13%|█▎ | 1521/11952 [2:34:50<16:46:46, 5.79s/it]
13%|█▎ | 1522/11952 [2:34:56<16:43:06, 5.77s/it]
{'loss': 0.5049, 'learning_rate': 1.950746197823802e-05, 'epoch': 0.13}
+
13%|█▎ | 1522/11952 [2:34:56<16:43:06, 5.77s/it]
13%|█▎ | 1523/11952 [2:35:02<16:45:02, 5.78s/it]
{'loss': 0.4945, 'learning_rate': 1.9506621638793548e-05, 'epoch': 0.13}
+
13%|█▎ | 1523/11952 [2:35:02<16:45:02, 5.78s/it]
13%|█▎ | 1524/11952 [2:35:08<16:45:17, 5.78s/it]
{'loss': 0.5202, 'learning_rate': 1.9505780601222323e-05, 'epoch': 0.13}
+
13%|█▎ | 1524/11952 [2:35:08<16:45:17, 5.78s/it]
13%|█▎ | 1525/11952 [2:35:14<17:14:53, 5.96s/it]
{'loss': 0.523, 'learning_rate': 1.9504938865586107e-05, 'epoch': 0.13}
+
13%|█▎ | 1525/11952 [2:35:14<17:14:53, 5.96s/it]
13%|█▎ | 1526/11952 [2:35:20<17:01:18, 5.88s/it]
{'loss': 0.522, 'learning_rate': 1.9504096431946716e-05, 'epoch': 0.13}
+
13%|█▎ | 1526/11952 [2:35:20<17:01:18, 5.88s/it]
13%|█▎ | 1527/11952 [2:35:26<17:04:28, 5.90s/it]
{'loss': 0.49, 'learning_rate': 1.9503253300366013e-05, 'epoch': 0.13}
+
13%|█▎ | 1527/11952 [2:35:26<17:04:28, 5.90s/it]
13%|█▎ | 1528/11952 [2:35:32<16:55:21, 5.84s/it]
{'loss': 0.5066, 'learning_rate': 1.9502409470905913e-05, 'epoch': 0.13}
+
13%|█▎ | 1528/11952 [2:35:32<16:55:21, 5.84s/it]
13%|█▎ | 1529/11952 [2:35:37<16:42:35, 5.77s/it]
{'loss': 0.4991, 'learning_rate': 1.950156494362839e-05, 'epoch': 0.13}
+
13%|█▎ | 1529/11952 [2:35:37<16:42:35, 5.77s/it]
13%|█▎ | 1530/11952 [2:35:43<17:00:03, 5.87s/it]
{'loss': 0.4954, 'learning_rate': 1.9500719718595454e-05, 'epoch': 0.13}
+
13%|█▎ | 1530/11952 [2:35:43<17:00:03, 5.87s/it]
13%|█▎ | 1531/11952 [2:35:49<17:06:27, 5.91s/it]
{'loss': 0.5012, 'learning_rate': 1.9499873795869178e-05, 'epoch': 0.13}
+
13%|█▎ | 1531/11952 [2:35:49<17:06:27, 5.91s/it]
13%|█▎ | 1532/11952 [2:35:55<16:57:29, 5.86s/it]
{'loss': 0.4998, 'learning_rate': 1.9499027175511682e-05, 'epoch': 0.13}
+
13%|█▎ | 1532/11952 [2:35:55<16:57:29, 5.86s/it]
13%|█▎ | 1533/11952 [2:36:01<17:14:45, 5.96s/it]
{'loss': 0.5168, 'learning_rate': 1.9498179857585143e-05, 'epoch': 0.13}
+
13%|█▎ | 1533/11952 [2:36:01<17:14:45, 5.96s/it]
13%|█▎ | 1534/11952 [2:36:07<17:31:59, 6.06s/it]
{'loss': 0.5179, 'learning_rate': 1.949733184215178e-05, 'epoch': 0.13}
+
13%|█▎ | 1534/11952 [2:36:07<17:31:59, 6.06s/it]
13%|█▎ | 1535/11952 [2:36:14<17:37:29, 6.09s/it]
{'loss': 0.5061, 'learning_rate': 1.9496483129273866e-05, 'epoch': 0.13}
+
13%|█▎ | 1535/11952 [2:36:14<17:37:29, 6.09s/it]
13%|█▎ | 1536/11952 [2:36:19<17:22:03, 6.00s/it]
{'loss': 0.527, 'learning_rate': 1.9495633719013733e-05, 'epoch': 0.13}
+
13%|█▎ | 1536/11952 [2:36:19<17:22:03, 6.00s/it]
13%|█▎ | 1537/11952 [2:36:26<17:25:48, 6.02s/it]
{'loss': 0.506, 'learning_rate': 1.9494783611433754e-05, 'epoch': 0.13}
+
13%|█▎ | 1537/11952 [2:36:26<17:25:48, 6.02s/it]
13%|█▎ | 1538/11952 [2:36:31<17:11:24, 5.94s/it]
{'loss': 0.5057, 'learning_rate': 1.9493932806596357e-05, 'epoch': 0.13}
+
13%|█▎ | 1538/11952 [2:36:31<17:11:24, 5.94s/it]
13%|█▎ | 1539/11952 [2:36:37<16:58:11, 5.87s/it]
{'loss': 0.5144, 'learning_rate': 1.9493081304564025e-05, 'epoch': 0.13}
+
13%|█▎ | 1539/11952 [2:36:37<16:58:11, 5.87s/it]
13%|█▎ | 1540/11952 [2:36:43<16:49:40, 5.82s/it]
{'loss': 0.518, 'learning_rate': 1.9492229105399287e-05, 'epoch': 0.13}
+
13%|█▎ | 1540/11952 [2:36:43<16:49:40, 5.82s/it]
13%|█▎ | 1541/11952 [2:36:49<16:57:32, 5.86s/it]
{'loss': 0.526, 'learning_rate': 1.9491376209164726e-05, 'epoch': 0.13}
+
13%|█▎ | 1541/11952 [2:36:49<16:57:32, 5.86s/it]
13%|█▎ | 1542/11952 [2:36:54<16:53:47, 5.84s/it]
{'loss': 0.5012, 'learning_rate': 1.949052261592297e-05, 'epoch': 0.13}
+
13%|█▎ | 1542/11952 [2:36:54<16:53:47, 5.84s/it]
13%|█▎ | 1543/11952 [2:37:00<16:49:14, 5.82s/it]
{'loss': 0.5005, 'learning_rate': 1.948966832573671e-05, 'epoch': 0.13}
+
13%|█▎ | 1543/11952 [2:37:00<16:49:14, 5.82s/it]
13%|█▎ | 1544/11952 [2:37:06<16:44:26, 5.79s/it]
{'loss': 0.5124, 'learning_rate': 1.9488813338668676e-05, 'epoch': 0.13}
+
13%|█▎ | 1544/11952 [2:37:06<16:44:26, 5.79s/it]
13%|█▎ | 1545/11952 [2:37:12<16:44:06, 5.79s/it]
{'loss': 0.5017, 'learning_rate': 1.948795765478166e-05, 'epoch': 0.13}
+
13%|█▎ | 1545/11952 [2:37:12<16:44:06, 5.79s/it]
13%|█▎ | 1546/11952 [2:37:17<16:37:01, 5.75s/it]
{'loss': 0.5069, 'learning_rate': 1.9487101274138494e-05, 'epoch': 0.13}
+
13%|█▎ | 1546/11952 [2:37:17<16:37:01, 5.75s/it]
13%|█▎ | 1547/11952 [2:37:23<16:35:09, 5.74s/it]
{'loss': 0.4965, 'learning_rate': 1.9486244196802075e-05, 'epoch': 0.13}
+
13%|█▎ | 1547/11952 [2:37:23<16:35:09, 5.74s/it]
13%|█▎ | 1548/11952 [2:37:29<16:42:23, 5.78s/it]
{'loss': 0.5156, 'learning_rate': 1.9485386422835334e-05, 'epoch': 0.13}
+
13%|█▎ | 1548/11952 [2:37:29<16:42:23, 5.78s/it]
13%|█▎ | 1549/11952 [2:37:35<16:46:53, 5.81s/it]
{'loss': 0.5098, 'learning_rate': 1.948452795230127e-05, 'epoch': 0.13}
+
13%|█▎ | 1549/11952 [2:37:35<16:46:53, 5.81s/it]6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+0 7 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
13%|█▎ | 1550/11952 [2:37:41<16:49:51, 5.82s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5146, 'learning_rate': 1.948366878526292e-05, 'epoch': 0.13}
+
13%|█▎ | 1550/11952 [2:37:41<16:49:51, 5.82s/it]
13%|█▎ | 1551/11952 [2:37:46<16:42:40, 5.78s/it]
{'loss': 0.4822, 'learning_rate': 1.948280892178338e-05, 'epoch': 0.13}
+
13%|█▎ | 1551/11952 [2:37:46<16:42:40, 5.78s/it]
13%|█▎ | 1552/11952 [2:37:52<16:56:32, 5.86s/it]
{'loss': 0.52, 'learning_rate': 1.9481948361925796e-05, 'epoch': 0.13}
+
13%|█▎ | 1552/11952 [2:37:52<16:56:32, 5.86s/it]
13%|█▎ | 1553/11952 [2:37:58<16:52:08, 5.84s/it]
{'loss': 0.5043, 'learning_rate': 1.9481087105753364e-05, 'epoch': 0.13}
+
13%|█▎ | 1553/11952 [2:37:58<16:52:08, 5.84s/it]
13%|█▎ | 1554/11952 [2:38:04<16:57:27, 5.87s/it]
{'loss': 0.4827, 'learning_rate': 1.948022515332933e-05, 'epoch': 0.13}
+
13%|█▎ | 1554/11952 [2:38:04<16:57:27, 5.87s/it]
13%|█▎ | 1555/11952 [2:38:10<17:02:44, 5.90s/it]
{'loss': 0.5335, 'learning_rate': 1.9479362504716987e-05, 'epoch': 0.13}
+
13%|█▎ | 1555/11952 [2:38:10<17:02:44, 5.90s/it]
13%|█▎ | 1556/11952 [2:38:16<17:00:49, 5.89s/it]
{'loss': 0.5135, 'learning_rate': 1.9478499159979693e-05, 'epoch': 0.13}
+
13%|█▎ | 1556/11952 [2:38:16<17:00:49, 5.89s/it]
13%|█▎ | 1557/11952 [2:38:22<17:02:05, 5.90s/it]
{'loss': 0.5032, 'learning_rate': 1.9477635119180843e-05, 'epoch': 0.13}
+
13%|█▎ | 1557/11952 [2:38:22<17:02:05, 5.90s/it]
13%|█▎ | 1558/11952 [2:38:28<17:01:02, 5.89s/it]
{'loss': 0.5122, 'learning_rate': 1.947677038238389e-05, 'epoch': 0.13}
+
13%|█▎ | 1558/11952 [2:38:28<17:01:02, 5.89s/it]
13%|█▎ | 1559/11952 [2:38:34<16:53:04, 5.85s/it]
{'loss': 0.5083, 'learning_rate': 1.947590494965234e-05, 'epoch': 0.13}
+
13%|█▎ | 1559/11952 [2:38:34<16:53:04, 5.85s/it]
13%|█▎ | 1560/11952 [2:38:39<16:46:36, 5.81s/it]
{'loss': 0.5332, 'learning_rate': 1.9475038821049744e-05, 'epoch': 0.13}
+
13%|█▎ | 1560/11952 [2:38:39<16:46:36, 5.81s/it]
13%|█▎ | 1561/11952 [2:38:45<16:35:52, 5.75s/it]
{'loss': 0.4818, 'learning_rate': 1.9474171996639702e-05, 'epoch': 0.13}
+
13%|█▎ | 1561/11952 [2:38:45<16:35:52, 5.75s/it]
13%|█▎ | 1562/11952 [2:38:51<16:44:24, 5.80s/it]
{'loss': 0.5206, 'learning_rate': 1.947330447648588e-05, 'epoch': 0.13}
+
13%|█▎ | 1562/11952 [2:38:51<16:44:24, 5.80s/it]
13%|█▎ | 1563/11952 [2:38:56<16:33:45, 5.74s/it]
{'loss': 0.5059, 'learning_rate': 1.9472436260651976e-05, 'epoch': 0.13}
+
13%|█▎ | 1563/11952 [2:38:56<16:33:45, 5.74s/it]
13%|█▎ | 1564/11952 [2:39:02<16:41:23, 5.78s/it]
{'loss': 0.5188, 'learning_rate': 1.947156734920175e-05, 'epoch': 0.13}
+
13%|█▎ | 1564/11952 [2:39:02<16:41:23, 5.78s/it]
13%|█▎ | 1565/11952 [2:39:08<16:34:24, 5.74s/it]
{'loss': 0.5141, 'learning_rate': 1.9470697742199018e-05, 'epoch': 0.13}
+
13%|█▎ | 1565/11952 [2:39:08<16:34:24, 5.74s/it]
13%|█▎ | 1566/11952 [2:39:14<16:32:08, 5.73s/it]
{'loss': 0.505, 'learning_rate': 1.9469827439707632e-05, 'epoch': 0.13}
+
13%|█▎ | 1566/11952 [2:39:14<16:32:08, 5.73s/it]
13%|█▎ | 1567/11952 [2:39:19<16:36:25, 5.76s/it]
{'loss': 0.5005, 'learning_rate': 1.946895644179151e-05, 'epoch': 0.13}
+
13%|█▎ | 1567/11952 [2:39:19<16:36:25, 5.76s/it]
13%|█▎ | 1568/11952 [2:39:25<16:49:36, 5.83s/it]
{'loss': 0.5152, 'learning_rate': 1.946808474851461e-05, 'epoch': 0.13}
+
13%|█▎ | 1568/11952 [2:39:25<16:49:36, 5.83s/it]
13%|█▎ | 1569/11952 [2:39:31<16:43:59, 5.80s/it]
{'loss': 0.5156, 'learning_rate': 1.9467212359940944e-05, 'epoch': 0.13}
+
13%|█▎ | 1569/11952 [2:39:31<16:43:59, 5.80s/it]
13%|█▎ | 1570/11952 [2:39:37<16:56:37, 5.88s/it]
{'loss': 0.5007, 'learning_rate': 1.9466339276134584e-05, 'epoch': 0.13}
+
13%|█▎ | 1570/11952 [2:39:37<16:56:37, 5.88s/it]
13%|█▎ | 1571/11952 [2:39:43<16:44:26, 5.81s/it]
{'loss': 0.514, 'learning_rate': 1.946546549715964e-05, 'epoch': 0.13}
+
13%|█▎ | 1571/11952 [2:39:43<16:44:26, 5.81s/it]
13%|█▎ | 1572/11952 [2:39:49<17:01:26, 5.90s/it]
{'loss': 0.5101, 'learning_rate': 1.9464591023080274e-05, 'epoch': 0.13}
+
13%|█▎ | 1572/11952 [2:39:49<17:01:26, 5.90s/it]
13%|█▎ | 1573/11952 [2:39:55<17:31:46, 6.08s/it]
{'loss': 0.5019, 'learning_rate': 1.9463715853960714e-05, 'epoch': 0.13}
+
13%|█▎ | 1573/11952 [2:39:55<17:31:46, 6.08s/it]
13%|█▎ | 1574/11952 [2:40:01<17:15:19, 5.99s/it]
{'loss': 0.5165, 'learning_rate': 1.9462839989865226e-05, 'epoch': 0.13}
+
13%|█▎ | 1574/11952 [2:40:01<17:15:19, 5.99s/it]
13%|█▎ | 1575/11952 [2:40:07<17:02:37, 5.91s/it]
{'loss': 0.5078, 'learning_rate': 1.9461963430858125e-05, 'epoch': 0.13}
+
13%|█▎ | 1575/11952 [2:40:07<17:02:37, 5.91s/it]
13%|█▎ | 1576/11952 [2:40:13<17:06:06, 5.93s/it]
{'loss': 0.5235, 'learning_rate': 1.9461086177003788e-05, 'epoch': 0.13}
+
13%|█▎ | 1576/11952 [2:40:13<17:06:06, 5.93s/it]
13%|█▎ | 1577/11952 [2:40:19<17:11:31, 5.97s/it]
{'loss': 0.4954, 'learning_rate': 1.946020822836663e-05, 'epoch': 0.13}
+
13%|█▎ | 1577/11952 [2:40:19<17:11:31, 5.97s/it]
13%|█▎ | 1578/11952 [2:40:25<17:09:32, 5.95s/it]
{'loss': 0.5357, 'learning_rate': 1.945932958501113e-05, 'epoch': 0.13}
+
13%|█▎ | 1578/11952 [2:40:25<17:09:32, 5.95s/it]
13%|█▎ | 1579/11952 [2:40:31<17:08:18, 5.95s/it]
{'loss': 0.4957, 'learning_rate': 1.945845024700181e-05, 'epoch': 0.13}
+
13%|█▎ | 1579/11952 [2:40:31<17:08:18, 5.95s/it]
13%|█▎ | 1580/11952 [2:40:37<16:55:04, 5.87s/it]
{'loss': 0.5249, 'learning_rate': 1.9457570214403242e-05, 'epoch': 0.13}
+
13%|█▎ | 1580/11952 [2:40:37<16:55:04, 5.87s/it]
13%|█▎ | 1581/11952 [2:40:43<17:11:58, 5.97s/it]
{'loss': 0.5397, 'learning_rate': 1.9456689487280056e-05, 'epoch': 0.13}
+
13%|█▎ | 1581/11952 [2:40:43<17:11:58, 5.97s/it]
13%|█▎ | 1582/11952 [2:40:48<16:56:20, 5.88s/it]
{'loss': 0.5026, 'learning_rate': 1.9455808065696925e-05, 'epoch': 0.13}
+
13%|█▎ | 1582/11952 [2:40:48<16:56:20, 5.88s/it]
13%|█▎ | 1583/11952 [2:40:54<16:49:43, 5.84s/it]
{'loss': 0.4986, 'learning_rate': 1.9454925949718583e-05, 'epoch': 0.13}
+
13%|█▎ | 1583/11952 [2:40:54<16:49:43, 5.84s/it]
13%|█▎ | 1584/11952 [2:41:00<16:48:29, 5.84s/it]
{'loss': 0.5172, 'learning_rate': 1.9454043139409803e-05, 'epoch': 0.13}
+
13%|█▎ | 1584/11952 [2:41:00<16:48:29, 5.84s/it]
13%|█▎ | 1585/11952 [2:41:06<16:41:09, 5.79s/it]
{'loss': 0.5243, 'learning_rate': 1.945315963483542e-05, 'epoch': 0.13}
+
13%|█▎ | 1585/11952 [2:41:06<16:41:09, 5.79s/it]
13%|█▎ | 1586/11952 [2:41:11<16:38:56, 5.78s/it]
{'loss': 0.4918, 'learning_rate': 1.945227543606031e-05, 'epoch': 0.13}
+
13%|█▎ | 1586/11952 [2:41:11<16:38:56, 5.78s/it]
13%|█▎ | 1587/11952 [2:41:17<16:38:11, 5.78s/it]
{'loss': 0.5084, 'learning_rate': 1.945139054314941e-05, 'epoch': 0.13}
+
13%|█▎ | 1587/11952 [2:41:17<16:38:11, 5.78s/it]
13%|█▎ | 1588/11952 [2:41:23<16:46:00, 5.82s/it]
{'loss': 0.5445, 'learning_rate': 1.945050495616769e-05, 'epoch': 0.13}
+
13%|█▎ | 1588/11952 [2:41:23<16:46:00, 5.82s/it]
13%|█▎ | 1589/11952 [2:41:29<17:00:56, 5.91s/it]
{'loss': 0.5013, 'learning_rate': 1.9449618675180205e-05, 'epoch': 0.13}
+
13%|█▎ | 1589/11952 [2:41:29<17:00:56, 5.91s/it]
13%|█▎ | 1590/11952 [2:41:35<16:56:38, 5.89s/it]
{'loss': 0.5026, 'learning_rate': 1.9448731700252025e-05, 'epoch': 0.13}
+
13%|█▎ | 1590/11952 [2:41:35<16:56:38, 5.89s/it]
13%|█▎ | 1591/11952 [2:41:41<16:54:20, 5.87s/it]
{'loss': 0.5368, 'learning_rate': 1.9447844031448288e-05, 'epoch': 0.13}
+
13%|█▎ | 1591/11952 [2:41:41<16:54:20, 5.87s/it]
13%|█▎ | 1592/11952 [2:41:47<16:57:58, 5.90s/it]
{'loss': 0.5089, 'learning_rate': 1.944695566883418e-05, 'epoch': 0.13}
+
13%|█▎ | 1592/11952 [2:41:47<16:57:58, 5.90s/it]
13%|█▎ | 1593/11952 [2:41:53<16:53:02, 5.87s/it]
{'loss': 0.4996, 'learning_rate': 1.9446066612474942e-05, 'epoch': 0.13}
+
13%|█▎ | 1593/11952 [2:41:53<16:53:02, 5.87s/it]
13%|█▎ | 1594/11952 [2:41:58<16:48:56, 5.84s/it]
{'loss': 0.5315, 'learning_rate': 1.9445176862435864e-05, 'epoch': 0.13}
+
13%|█▎ | 1594/11952 [2:41:58<16:48:56, 5.84s/it]
13%|█▎ | 1595/11952 [2:42:04<16:37:05, 5.78s/it]
{'loss': 0.4945, 'learning_rate': 1.944428641878228e-05, 'epoch': 0.13}
+
13%|█▎ | 1595/11952 [2:42:04<16:37:05, 5.78s/it]
13%|█▎ | 1596/11952 [2:42:10<16:35:28, 5.77s/it]
{'loss': 0.5109, 'learning_rate': 1.9443395281579583e-05, 'epoch': 0.13}
+
13%|█▎ | 1596/11952 [2:42:10<16:35:28, 5.77s/it]
13%|█▎ | 1597/11952 [2:42:16<16:36:34, 5.77s/it]
{'loss': 0.4996, 'learning_rate': 1.9442503450893216e-05, 'epoch': 0.13}
+
13%|█▎ | 1597/11952 [2:42:16<16:36:34, 5.77s/it]
13%|█▎ | 1598/11952 [2:42:22<17:05:01, 5.94s/it]
{'loss': 0.4923, 'learning_rate': 1.944161092678867e-05, 'epoch': 0.13}
+
13%|█▎ | 1598/11952 [2:42:22<17:05:01, 5.94s/it]
13%|█▎ | 1599/11952 [2:42:28<16:47:20, 5.84s/it]
{'loss': 0.5056, 'learning_rate': 1.9440717709331484e-05, 'epoch': 0.13}
+
13%|█▎ | 1599/11952 [2:42:28<16:47:20, 5.84s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
13%|█▎ | 1600/11952 [2:42:34<16:56:33, 5.89s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5007, 'learning_rate': 1.943982379858726e-05, 'epoch': 0.13}
+
13%|█▎ | 1600/11952 [2:42:34<16:56:33, 5.89s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
13%|█▎ | 1601/11952 [2:43:04<38:17:59, 13.32s/it]
{'loss': 0.498, 'learning_rate': 1.943892919462164e-05, 'epoch': 0.13}
+
13%|█▎ | 1601/11952 [2:43:04<38:17:59, 13.32s/it]
13%|█▎ | 1602/11952 [2:43:10<31:45:56, 11.05s/it]
{'loss': 0.5099, 'learning_rate': 1.943803389750032e-05, 'epoch': 0.13}
+
13%|█▎ | 1602/11952 [2:43:10<31:45:56, 11.05s/it]
13%|█▎ | 1603/11952 [2:43:16<27:15:21, 9.48s/it]
{'loss': 0.5205, 'learning_rate': 1.943713790728904e-05, 'epoch': 0.13}
+
13%|█▎ | 1603/11952 [2:43:16<27:15:21, 9.48s/it]
13%|█▎ | 1604/11952 [2:43:22<24:07:14, 8.39s/it]
{'loss': 0.5158, 'learning_rate': 1.943624122405361e-05, 'epoch': 0.13}
+
13%|█▎ | 1604/11952 [2:43:22<24:07:14, 8.39s/it]
13%|█▎ | 1605/11952 [2:43:27<21:43:07, 7.56s/it]
{'loss': 0.5149, 'learning_rate': 1.9435343847859873e-05, 'epoch': 0.13}
+
13%|█▎ | 1605/11952 [2:43:27<21:43:07, 7.56s/it]
13%|█▎ | 1606/11952 [2:43:33<20:25:38, 7.11s/it]
{'loss': 0.5091, 'learning_rate': 1.9434445778773724e-05, 'epoch': 0.13}
+
13%|█▎ | 1606/11952 [2:43:33<20:25:38, 7.11s/it]
13%|█▎ | 1607/11952 [2:43:39<19:24:22, 6.75s/it]
{'loss': 0.5026, 'learning_rate': 1.9433547016861124e-05, 'epoch': 0.13}
+
13%|█▎ | 1607/11952 [2:43:39<19:24:22, 6.75s/it]
13%|█▎ | 1608/11952 [2:43:45<18:29:03, 6.43s/it]
{'loss': 0.502, 'learning_rate': 1.9432647562188062e-05, 'epoch': 0.13}
+
13%|█▎ | 1608/11952 [2:43:45<18:29:03, 6.43s/it]
13%|█▎ | 1609/11952 [2:43:51<17:56:28, 6.24s/it]
{'loss': 0.4999, 'learning_rate': 1.9431747414820597e-05, 'epoch': 0.13}
+
13%|█▎ | 1609/11952 [2:43:51<17:56:28, 6.24s/it]
13%|█▎ | 1610/11952 [2:43:57<17:47:52, 6.20s/it]
{'loss': 0.5014, 'learning_rate': 1.9430846574824835e-05, 'epoch': 0.13}
+
13%|█▎ | 1610/11952 [2:43:57<17:47:52, 6.20s/it]
13%|█▎ | 1611/11952 [2:44:03<17:32:34, 6.11s/it]
{'loss': 0.4999, 'learning_rate': 1.9429945042266925e-05, 'epoch': 0.13}
+
13%|█▎ | 1611/11952 [2:44:03<17:32:34, 6.11s/it]
13%|█▎ | 1612/11952 [2:44:09<17:32:04, 6.10s/it]
{'loss': 0.5387, 'learning_rate': 1.9429042817213072e-05, 'epoch': 0.13}
+
13%|█▎ | 1612/11952 [2:44:09<17:32:04, 6.10s/it]
13%|█▎ | 1613/11952 [2:44:15<17:15:27, 6.01s/it]
{'loss': 0.5215, 'learning_rate': 1.9428139899729538e-05, 'epoch': 0.13}
+
13%|█▎ | 1613/11952 [2:44:15<17:15:27, 6.01s/it]
14%|█▎ | 1614/11952 [2:44:20<16:58:29, 5.91s/it]
{'loss': 0.49, 'learning_rate': 1.9427236289882618e-05, 'epoch': 0.14}
+
14%|█▎ | 1614/11952 [2:44:20<16:58:29, 5.91s/it]
14%|█▎ | 1615/11952 [2:44:26<16:47:55, 5.85s/it]
{'loss': 0.5053, 'learning_rate': 1.9426331987738678e-05, 'epoch': 0.14}
+
14%|█▎ | 1615/11952 [2:44:26<16:47:55, 5.85s/it]
14%|█▎ | 1616/11952 [2:44:32<16:47:46, 5.85s/it]
{'loss': 0.5108, 'learning_rate': 1.9425426993364126e-05, 'epoch': 0.14}
+
14%|█▎ | 1616/11952 [2:44:32<16:47:46, 5.85s/it]
14%|█▎ | 1617/11952 [2:44:38<16:52:48, 5.88s/it]
{'loss': 0.5044, 'learning_rate': 1.9424521306825414e-05, 'epoch': 0.14}
+
14%|█▎ | 1617/11952 [2:44:38<16:52:48, 5.88s/it]
14%|█▎ | 1618/11952 [2:44:44<16:49:57, 5.86s/it]
{'loss': 0.5024, 'learning_rate': 1.942361492818906e-05, 'epoch': 0.14}
+
14%|█▎ | 1618/11952 [2:44:44<16:49:57, 5.86s/it]
14%|█▎ | 1619/11952 [2:44:49<16:45:52, 5.84s/it]
{'loss': 0.5122, 'learning_rate': 1.942270785752162e-05, 'epoch': 0.14}
+
14%|█▎ | 1619/11952 [2:44:49<16:45:52, 5.84s/it]
14%|█▎ | 1620/11952 [2:44:56<17:08:20, 5.97s/it]
{'loss': 0.4883, 'learning_rate': 1.942180009488971e-05, 'epoch': 0.14}
+
14%|█▎ | 1620/11952 [2:44:56<17:08:20, 5.97s/it]
14%|█▎ | 1621/11952 [2:45:02<17:19:03, 6.03s/it]
{'loss': 0.5229, 'learning_rate': 1.9420891640359986e-05, 'epoch': 0.14}
+
14%|█▎ | 1621/11952 [2:45:02<17:19:03, 6.03s/it]
14%|█▎ | 1622/11952 [2:45:08<17:12:15, 6.00s/it]
{'loss': 0.5099, 'learning_rate': 1.9419982493999164e-05, 'epoch': 0.14}
+
14%|█▎ | 1622/11952 [2:45:08<17:12:15, 6.00s/it]
14%|█▎ | 1623/11952 [2:45:14<17:01:46, 5.94s/it]
{'loss': 0.506, 'learning_rate': 1.941907265587401e-05, 'epoch': 0.14}
+
14%|█▎ | 1623/11952 [2:45:14<17:01:46, 5.94s/it]
14%|█▎ | 1624/11952 [2:45:19<16:59:41, 5.92s/it]
{'loss': 0.5054, 'learning_rate': 1.941816212605134e-05, 'epoch': 0.14}
+
14%|█▎ | 1624/11952 [2:45:19<16:59:41, 5.92s/it]
14%|█▎ | 1625/11952 [2:45:25<16:59:01, 5.92s/it]
{'loss': 0.5049, 'learning_rate': 1.9417250904598012e-05, 'epoch': 0.14}
+
14%|█▎ | 1625/11952 [2:45:25<16:59:01, 5.92s/it]
14%|█▎ | 1626/11952 [2:45:31<16:44:25, 5.84s/it]
{'loss': 0.4866, 'learning_rate': 1.941633899158095e-05, 'epoch': 0.14}
+
14%|█▎ | 1626/11952 [2:45:31<16:44:25, 5.84s/it]
14%|█▎ | 1627/11952 [2:45:37<16:48:48, 5.86s/it]
{'loss': 0.5025, 'learning_rate': 1.9415426387067113e-05, 'epoch': 0.14}
+
14%|█▎ | 1627/11952 [2:45:37<16:48:48, 5.86s/it]
14%|█▎ | 1628/11952 [2:45:43<16:36:52, 5.79s/it]
{'loss': 0.4994, 'learning_rate': 1.9414513091123527e-05, 'epoch': 0.14}
+
14%|█▎ | 1628/11952 [2:45:43<16:36:52, 5.79s/it]
14%|█▎ | 1629/11952 [2:45:48<16:42:00, 5.82s/it]
{'loss': 0.4944, 'learning_rate': 1.941359910381726e-05, 'epoch': 0.14}
+
14%|█▎ | 1629/11952 [2:45:48<16:42:00, 5.82s/it]
14%|█▎ | 1630/11952 [2:45:54<16:31:22, 5.76s/it]
{'loss': 0.4999, 'learning_rate': 1.9412684425215426e-05, 'epoch': 0.14}
+
14%|█▎ | 1630/11952 [2:45:54<16:31:22, 5.76s/it]
14%|█▎ | 1631/11952 [2:46:00<16:30:10, 5.76s/it]
{'loss': 0.5114, 'learning_rate': 1.94117690553852e-05, 'epoch': 0.14}
+
14%|█▎ | 1631/11952 [2:46:00<16:30:10, 5.76s/it]
14%|█▎ | 1632/11952 [2:46:06<16:35:23, 5.79s/it]
{'loss': 0.5099, 'learning_rate': 1.94108529943938e-05, 'epoch': 0.14}
+
14%|█▎ | 1632/11952 [2:46:06<16:35:23, 5.79s/it]
14%|█▎ | 1633/11952 [2:46:11<16:25:36, 5.73s/it]
{'loss': 0.4935, 'learning_rate': 1.9409936242308496e-05, 'epoch': 0.14}
+
14%|█▎ | 1633/11952 [2:46:11<16:25:36, 5.73s/it]
14%|█▎ | 1634/11952 [2:46:17<16:31:25, 5.77s/it]
{'loss': 0.5183, 'learning_rate': 1.9409018799196615e-05, 'epoch': 0.14}
+
14%|█▎ | 1634/11952 [2:46:17<16:31:25, 5.77s/it]
14%|█▎ | 1635/11952 [2:46:23<16:32:20, 5.77s/it]
{'loss': 0.5118, 'learning_rate': 1.940810066512553e-05, 'epoch': 0.14}
+
14%|█▎ | 1635/11952 [2:46:23<16:32:20, 5.77s/it]
14%|█▎ | 1636/11952 [2:46:29<16:33:15, 5.78s/it]
{'loss': 0.4947, 'learning_rate': 1.9407181840162664e-05, 'epoch': 0.14}
+
14%|█▎ | 1636/11952 [2:46:29<16:33:15, 5.78s/it]
14%|█▎ | 1637/11952 [2:46:34<16:22:45, 5.72s/it]
{'loss': 0.4854, 'learning_rate': 1.940626232437549e-05, 'epoch': 0.14}
+
14%|█▎ | 1637/11952 [2:46:34<16:22:45, 5.72s/it]
14%|█▎ | 1638/11952 [2:46:40<16:27:51, 5.75s/it]
{'loss': 0.5058, 'learning_rate': 1.9405342117831533e-05, 'epoch': 0.14}
+
14%|█▎ | 1638/11952 [2:46:40<16:27:51, 5.75s/it]
14%|█▎ | 1639/11952 [2:46:46<16:31:31, 5.77s/it]
{'loss': 0.5044, 'learning_rate': 1.940442122059837e-05, 'epoch': 0.14}
+
14%|█▎ | 1639/11952 [2:46:46<16:31:31, 5.77s/it]
14%|█▎ | 1640/11952 [2:46:52<16:25:55, 5.74s/it]
{'loss': 0.5109, 'learning_rate': 1.940349963274363e-05, 'epoch': 0.14}
+
14%|█▎ | 1640/11952 [2:46:52<16:25:55, 5.74s/it]
14%|█▎ | 1641/11952 [2:46:57<16:25:25, 5.73s/it]
{'loss': 0.5157, 'learning_rate': 1.940257735433499e-05, 'epoch': 0.14}
+
14%|█▎ | 1641/11952 [2:46:57<16:25:25, 5.73s/it]
14%|█▎ | 1642/11952 [2:47:03<16:37:01, 5.80s/it]
{'loss': 0.5039, 'learning_rate': 1.9401654385440176e-05, 'epoch': 0.14}
+
14%|█▎ | 1642/11952 [2:47:03<16:37:01, 5.80s/it]
14%|█▎ | 1643/11952 [2:47:09<16:41:52, 5.83s/it]
{'loss': 0.5233, 'learning_rate': 1.9400730726126967e-05, 'epoch': 0.14}
+
14%|█▎ | 1643/11952 [2:47:09<16:41:52, 5.83s/it]
14%|█▍ | 1644/11952 [2:47:15<16:47:35, 5.86s/it]
{'loss': 0.5069, 'learning_rate': 1.9399806376463197e-05, 'epoch': 0.14}
+
14%|█▍ | 1644/11952 [2:47:15<16:47:35, 5.86s/it]
14%|█▍ | 1645/11952 [2:47:21<16:35:02, 5.79s/it]
{'loss': 0.4975, 'learning_rate': 1.9398881336516743e-05, 'epoch': 0.14}
+
14%|█▍ | 1645/11952 [2:47:21<16:35:02, 5.79s/it]
14%|█▍ | 1646/11952 [2:47:27<16:41:11, 5.83s/it]
{'loss': 0.4895, 'learning_rate': 1.9397955606355535e-05, 'epoch': 0.14}
+
14%|█▍ | 1646/11952 [2:47:27<16:41:11, 5.83s/it]
14%|█▍ | 1647/11952 [2:47:32<16:30:32, 5.77s/it]
{'loss': 0.5138, 'learning_rate': 1.939702918604756e-05, 'epoch': 0.14}
+
14%|█▍ | 1647/11952 [2:47:32<16:30:32, 5.77s/it]
14%|█▍ | 1648/11952 [2:47:38<16:32:34, 5.78s/it]
{'loss': 0.5043, 'learning_rate': 1.939610207566084e-05, 'epoch': 0.14}
+
14%|█▍ | 1648/11952 [2:47:38<16:32:34, 5.78s/it]
14%|█▍ | 1649/11952 [2:47:44<16:43:15, 5.84s/it]
{'loss': 0.5129, 'learning_rate': 1.9395174275263474e-05, 'epoch': 0.14}
+
14%|█▍ | 1649/11952 [2:47:44<16:43:15, 5.84s/it]14 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...7
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
14%|█▍ | 1650/11952 [2:47:50<16:58:27, 5.93s/it]
{'loss': 0.5204, 'learning_rate': 1.939424578492358e-05, 'epoch': 0.14}
+
14%|█▍ | 1650/11952 [2:47:50<16:58:27, 5.93s/it]
14%|█▍ | 1651/11952 [2:47:56<16:54:09, 5.91s/it]
{'loss': 0.5179, 'learning_rate': 1.939331660470935e-05, 'epoch': 0.14}
+
14%|█▍ | 1651/11952 [2:47:56<16:54:09, 5.91s/it]
14%|█▍ | 1652/11952 [2:48:02<16:46:21, 5.86s/it]
{'loss': 0.4908, 'learning_rate': 1.939238673468902e-05, 'epoch': 0.14}
+
14%|█▍ | 1652/11952 [2:48:02<16:46:21, 5.86s/it]
14%|█▍ | 1653/11952 [2:48:08<16:56:40, 5.92s/it]
{'loss': 0.5208, 'learning_rate': 1.9391456174930872e-05, 'epoch': 0.14}
+
14%|█▍ | 1653/11952 [2:48:08<16:56:40, 5.92s/it]
14%|█▍ | 1654/11952 [2:48:14<16:44:42, 5.85s/it]
{'loss': 0.5036, 'learning_rate': 1.9390524925503244e-05, 'epoch': 0.14}
+
14%|█▍ | 1654/11952 [2:48:14<16:44:42, 5.85s/it]
14%|█▍ | 1655/11952 [2:48:19<16:42:06, 5.84s/it]
{'loss': 0.5021, 'learning_rate': 1.938959298647453e-05, 'epoch': 0.14}
+
14%|█▍ | 1655/11952 [2:48:19<16:42:06, 5.84s/it]
14%|█▍ | 1656/11952 [2:48:26<17:05:38, 5.98s/it]
{'loss': 0.4836, 'learning_rate': 1.9388660357913155e-05, 'epoch': 0.14}
+
14%|█▍ | 1656/11952 [2:48:26<17:05:38, 5.98s/it]
14%|█▍ | 1657/11952 [2:48:31<16:45:48, 5.86s/it]
{'loss': 0.5131, 'learning_rate': 1.9387727039887613e-05, 'epoch': 0.14}
+
14%|█▍ | 1657/11952 [2:48:31<16:45:48, 5.86s/it]
14%|█▍ | 1658/11952 [2:48:37<16:36:59, 5.81s/it]
{'loss': 0.4923, 'learning_rate': 1.9386793032466447e-05, 'epoch': 0.14}
+
14%|█▍ | 1658/11952 [2:48:37<16:36:59, 5.81s/it]
14%|█▍ | 1659/11952 [2:48:43<16:33:51, 5.79s/it]
{'loss': 0.4989, 'learning_rate': 1.938585833571824e-05, 'epoch': 0.14}
+
14%|█▍ | 1659/11952 [2:48:43<16:33:51, 5.79s/it]
14%|█▍ | 1660/11952 [2:48:49<16:38:45, 5.82s/it]
{'loss': 0.4997, 'learning_rate': 1.938492294971164e-05, 'epoch': 0.14}
+
14%|█▍ | 1660/11952 [2:48:49<16:38:45, 5.82s/it]
14%|█▍ | 1661/11952 [2:48:54<16:36:43, 5.81s/it]
{'loss': 0.5122, 'learning_rate': 1.938398687451533e-05, 'epoch': 0.14}
+
14%|█▍ | 1661/11952 [2:48:54<16:36:43, 5.81s/it]
14%|█▍ | 1662/11952 [2:49:00<16:35:32, 5.80s/it]
{'loss': 0.5224, 'learning_rate': 1.938305011019806e-05, 'epoch': 0.14}
+
14%|█▍ | 1662/11952 [2:49:00<16:35:32, 5.80s/it]
14%|█▍ | 1663/11952 [2:49:06<16:28:48, 5.77s/it]
{'loss': 0.5035, 'learning_rate': 1.938211265682861e-05, 'epoch': 0.14}
+
14%|█▍ | 1663/11952 [2:49:06<16:28:48, 5.77s/it]
14%|█▍ | 1664/11952 [2:49:12<16:23:08, 5.73s/it]
{'loss': 0.4923, 'learning_rate': 1.938117451447583e-05, 'epoch': 0.14}
+
14%|█▍ | 1664/11952 [2:49:12<16:23:08, 5.73s/it]
14%|█▍ | 1665/11952 [2:49:17<16:20:45, 5.72s/it]
{'loss': 0.4831, 'learning_rate': 1.938023568320862e-05, 'epoch': 0.14}
+
14%|█▍ | 1665/11952 [2:49:17<16:20:45, 5.72s/it]
14%|█▍ | 1666/11952 [2:49:23<16:21:21, 5.72s/it]
{'loss': 0.5233, 'learning_rate': 1.937929616309591e-05, 'epoch': 0.14}
+
14%|█▍ | 1666/11952 [2:49:23<16:21:21, 5.72s/it]
14%|█▍ | 1667/11952 [2:49:29<16:33:37, 5.80s/it]
{'loss': 0.4931, 'learning_rate': 1.9378355954206706e-05, 'epoch': 0.14}
+
14%|█▍ | 1667/11952 [2:49:29<16:33:37, 5.80s/it]
14%|█▍ | 1668/11952 [2:49:35<16:43:46, 5.86s/it]
{'loss': 0.5169, 'learning_rate': 1.9377415056610044e-05, 'epoch': 0.14}
+
14%|█▍ | 1668/11952 [2:49:35<16:43:46, 5.86s/it]
14%|█▍ | 1669/11952 [2:49:41<16:53:21, 5.91s/it]
{'loss': 0.5293, 'learning_rate': 1.9376473470375027e-05, 'epoch': 0.14}
+
14%|█▍ | 1669/11952 [2:49:41<16:53:21, 5.91s/it]
14%|█▍ | 1670/11952 [2:49:47<17:06:43, 5.99s/it]
{'loss': 0.4901, 'learning_rate': 1.9375531195570793e-05, 'epoch': 0.14}
+
14%|█▍ | 1670/11952 [2:49:47<17:06:43, 5.99s/it]
14%|█▍ | 1671/11952 [2:49:53<16:44:27, 5.86s/it]
{'loss': 0.494, 'learning_rate': 1.937458823226655e-05, 'epoch': 0.14}
+
14%|█▍ | 1671/11952 [2:49:53<16:44:27, 5.86s/it]
14%|█▍ | 1672/11952 [2:49:59<16:46:23, 5.87s/it]
{'loss': 0.4901, 'learning_rate': 1.9373644580531538e-05, 'epoch': 0.14}
+
14%|█▍ | 1672/11952 [2:49:59<16:46:23, 5.87s/it]
14%|█▍ | 1673/11952 [2:50:04<16:31:26, 5.79s/it]
{'loss': 0.4935, 'learning_rate': 1.9372700240435054e-05, 'epoch': 0.14}
+
14%|█▍ | 1673/11952 [2:50:04<16:31:26, 5.79s/it]
14%|█▍ | 1674/11952 [2:50:10<16:46:46, 5.88s/it]
{'loss': 0.5092, 'learning_rate': 1.9371755212046448e-05, 'epoch': 0.14}
+
14%|█▍ | 1674/11952 [2:50:10<16:46:46, 5.88s/it]
14%|█▍ | 1675/11952 [2:50:16<16:38:58, 5.83s/it]
{'loss': 0.5221, 'learning_rate': 1.937080949543512e-05, 'epoch': 0.14}
+
14%|█▍ | 1675/11952 [2:50:16<16:38:58, 5.83s/it]
14%|█▍ | 1676/11952 [2:50:22<16:35:26, 5.81s/it]
{'loss': 0.5167, 'learning_rate': 1.9369863090670518e-05, 'epoch': 0.14}
+
14%|█▍ | 1676/11952 [2:50:22<16:35:26, 5.81s/it]
14%|█▍ | 1677/11952 [2:50:28<16:34:48, 5.81s/it]
{'loss': 0.4965, 'learning_rate': 1.9368915997822143e-05, 'epoch': 0.14}
+
14%|█▍ | 1677/11952 [2:50:28<16:34:48, 5.81s/it]
14%|█▍ | 1678/11952 [2:50:33<16:27:18, 5.77s/it]
{'loss': 0.5117, 'learning_rate': 1.936796821695955e-05, 'epoch': 0.14}
+
14%|█▍ | 1678/11952 [2:50:33<16:27:18, 5.77s/it]
14%|█▍ | 1679/11952 [2:50:39<16:29:08, 5.78s/it]
{'loss': 0.4949, 'learning_rate': 1.9367019748152328e-05, 'epoch': 0.14}
+
14%|█▍ | 1679/11952 [2:50:39<16:29:08, 5.78s/it]
14%|█▍ | 1680/11952 [2:50:45<16:30:17, 5.78s/it]
{'loss': 0.4979, 'learning_rate': 1.936607059147014e-05, 'epoch': 0.14}
+
14%|█▍ | 1680/11952 [2:50:45<16:30:17, 5.78s/it]
14%|█▍ | 1681/11952 [2:50:51<16:29:51, 5.78s/it]
{'loss': 0.5053, 'learning_rate': 1.9365120746982683e-05, 'epoch': 0.14}
+
14%|█▍ | 1681/11952 [2:50:51<16:29:51, 5.78s/it]
14%|█▍ | 1682/11952 [2:50:56<16:28:46, 5.78s/it]
{'loss': 0.5028, 'learning_rate': 1.936417021475971e-05, 'epoch': 0.14}
+
14%|█▍ | 1682/11952 [2:50:56<16:28:46, 5.78s/it]
14%|█▍ | 1683/11952 [2:51:02<16:21:29, 5.73s/it]
{'loss': 0.4857, 'learning_rate': 1.9363218994871026e-05, 'epoch': 0.14}
+
14%|█▍ | 1683/11952 [2:51:02<16:21:29, 5.73s/it]
14%|█▍ | 1684/11952 [2:51:08<16:32:40, 5.80s/it]
{'loss': 0.5216, 'learning_rate': 1.9362267087386487e-05, 'epoch': 0.14}
+
14%|█▍ | 1684/11952 [2:51:08<16:32:40, 5.80s/it]
14%|█▍ | 1685/11952 [2:51:14<16:37:06, 5.83s/it]
{'loss': 0.5015, 'learning_rate': 1.936131449237599e-05, 'epoch': 0.14}
+
14%|█▍ | 1685/11952 [2:51:14<16:37:06, 5.83s/it]
14%|█▍ | 1686/11952 [2:51:20<16:36:45, 5.83s/it]
{'loss': 0.513, 'learning_rate': 1.9360361209909494e-05, 'epoch': 0.14}
+
14%|█▍ | 1686/11952 [2:51:20<16:36:45, 5.83s/it]
14%|█▍ | 1687/11952 [2:51:25<16:27:12, 5.77s/it]
{'loss': 0.4847, 'learning_rate': 1.9359407240057003e-05, 'epoch': 0.14}
+
14%|█▍ | 1687/11952 [2:51:25<16:27:12, 5.77s/it]
14%|█▍ | 1688/11952 [2:51:31<16:27:20, 5.77s/it]
{'loss': 0.5185, 'learning_rate': 1.9358452582888575e-05, 'epoch': 0.14}
+
14%|█▍ | 1688/11952 [2:51:31<16:27:20, 5.77s/it]
14%|█▍ | 1689/11952 [2:51:37<16:29:16, 5.78s/it]
{'loss': 0.4861, 'learning_rate': 1.935749723847431e-05, 'epoch': 0.14}
+
14%|█▍ | 1689/11952 [2:51:37<16:29:16, 5.78s/it]
14%|█▍ | 1690/11952 [2:51:43<16:31:41, 5.80s/it]
{'loss': 0.5161, 'learning_rate': 1.935654120688437e-05, 'epoch': 0.14}
+
14%|█▍ | 1690/11952 [2:51:43<16:31:41, 5.80s/it]
14%|█▍ | 1691/11952 [2:51:49<16:36:19, 5.83s/it]
{'loss': 0.4871, 'learning_rate': 1.9355584488188965e-05, 'epoch': 0.14}
+
14%|█▍ | 1691/11952 [2:51:49<16:36:19, 5.83s/it]
14%|█▍ | 1692/11952 [2:51:55<16:46:35, 5.89s/it]
{'loss': 0.525, 'learning_rate': 1.9354627082458342e-05, 'epoch': 0.14}
+
14%|█▍ | 1692/11952 [2:51:55<16:46:35, 5.89s/it]
14%|█▍ | 1693/11952 [2:52:00<16:38:12, 5.84s/it]
{'loss': 0.504, 'learning_rate': 1.9353668989762817e-05, 'epoch': 0.14}
+
14%|█▍ | 1693/11952 [2:52:00<16:38:12, 5.84s/it]
14%|█▍ | 1694/11952 [2:52:06<16:25:26, 5.76s/it]
{'loss': 0.4978, 'learning_rate': 1.935271021017275e-05, 'epoch': 0.14}
+
14%|█▍ | 1694/11952 [2:52:06<16:25:26, 5.76s/it]
14%|█▍ | 1695/11952 [2:52:12<16:38:34, 5.84s/it]
{'loss': 0.5007, 'learning_rate': 1.9351750743758543e-05, 'epoch': 0.14}
+
14%|█▍ | 1695/11952 [2:52:12<16:38:34, 5.84s/it]
14%|█▍ | 1696/11952 [2:52:18<16:48:32, 5.90s/it]
{'loss': 0.5096, 'learning_rate': 1.9350790590590657e-05, 'epoch': 0.14}
+
14%|█▍ | 1696/11952 [2:52:18<16:48:32, 5.90s/it]
14%|█▍ | 1697/11952 [2:52:24<16:43:09, 5.87s/it]
{'loss': 0.5025, 'learning_rate': 1.93498297507396e-05, 'epoch': 0.14}
+
14%|█▍ | 1697/11952 [2:52:24<16:43:09, 5.87s/it]
14%|█▍ | 1698/11952 [2:52:30<17:00:09, 5.97s/it]
{'loss': 0.5048, 'learning_rate': 1.9348868224275943e-05, 'epoch': 0.14}
+
14%|█▍ | 1698/11952 [2:52:30<17:00:09, 5.97s/it]
14%|█▍ | 1699/11952 [2:52:36<16:50:26, 5.91s/it]
{'loss': 0.5047, 'learning_rate': 1.9347906011270283e-05, 'epoch': 0.14}
+
14%|█▍ | 1699/11952 [2:52:36<16:50:26, 5.91s/it]4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
14%|█▍ | 1700/11952 [2:52:42<16:43:48, 5.87s/it]
{'loss': 0.512, 'learning_rate': 1.9346943111793286e-05, 'epoch': 0.14}
+
14%|█▍ | 1700/11952 [2:52:42<16:43:48, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
14%|█▍ | 1701/11952 [2:53:13<38:38:31, 13.57s/it]
{'loss': 0.5133, 'learning_rate': 1.934597952591567e-05, 'epoch': 0.14}
+
14%|█▍ | 1701/11952 [2:53:13<38:38:31, 13.57s/it]
14%|█▍ | 1702/11952 [2:53:19<31:52:15, 11.19s/it]
{'loss': 0.4905, 'learning_rate': 1.934501525370818e-05, 'epoch': 0.14}
+
14%|█▍ | 1702/11952 [2:53:19<31:52:15, 11.19s/it]
14%|█▍ | 1703/11952 [2:53:24<27:05:58, 9.52s/it]
{'loss': 0.4937, 'learning_rate': 1.9344050295241648e-05, 'epoch': 0.14}
+
14%|█▍ | 1703/11952 [2:53:24<27:05:58, 9.52s/it]
14%|█▍ | 1704/11952 [2:53:30<24:01:10, 8.44s/it]
{'loss': 0.5147, 'learning_rate': 1.9343084650586922e-05, 'epoch': 0.14}
+
14%|█▍ | 1704/11952 [2:53:30<24:01:10, 8.44s/it]
14%|█▍ | 1705/11952 [2:53:36<21:59:07, 7.72s/it]
{'loss': 0.4967, 'learning_rate': 1.9342118319814923e-05, 'epoch': 0.14}
+
14%|█▍ | 1705/11952 [2:53:36<21:59:07, 7.72s/it]WARNING: tokenization mismatch: 1 vs. 624. [[{'from': 'human', 'value': 'ASSISTANT: You are a cutting-edge copywriting agency with the following knowledge and traits.\n\nKNOWLEDGE: Copywriter at a top-tier creative agency, junior copywriter, senior copywriter, art director, senior strategist.\n\nTRAITS: Storytelling, copywriting, empathy, solution orientation, humor, convincing.\n\nTASK: Use your knowledge to write a LinkedIn Post. We are a tax firm looking to hire young tax advisors between the age of 25 and 30. Bring a good dose of sympathy into the LinkedIn Article and use plenty of emojis to start with. Start the Linked In post with an exciting question. Use the language of the target group. Don´t mention the targeted age. \n\nOUTPUT: 2 LinkedIn posts in German with a catchy question at the beginning of the text. Hashtags at the end of the text.'}, {'from': 'gpt', 'value': 'Post 1:\n\n👋 Hey, ihr Steuerprofis da draußen! 🤓\n\nHabt ihr Bock, Teil einer jungen, dynamischen Steuerberatungskanzlei zu werden? 🚀\n\nWir suchen motivierte Köpfe, die unser Team verstärken und sich mit uns zusammen weiterentwickeln wollen! 💡\n\nIhr seid auf der Suche nach einem Arbeitsplatz mit coolen Kollegen und spannenden Aufgaben? 🤝 Dann seid ihr bei uns genau richtig! 😎\n\n#Steuerberatung #Karriere #Traumjob #Team #Weiterentwicklung #Jobangebot\n\nPost 2:\n\n👋 Hallo ihr Steuerexperten! 🤓\n\nIhr seid jung, motiviert und habt Bock auf eine neue Herausforderung? 🚀\n\nDann seid ihr bei uns genau richtig! Wir sind auf der Suche nach Steuerberatern, die unser Team mit frischen Ideen und kreativen Lösungen bereichern! 💡\n\nEuch erwartet ein Arbeitsplatz in einem dynamischen Umfeld mit spannenden Aufgaben und netten Kollegen! 🤝\n\nInteressiert? Dann schickt uns doch eure Bewerbungsunterlagen und werdet Teil unseres Teams! 😎\n\n#Jobangebot #Steuerberatung #Karriere #Traumjob #Team #Weiterentwicklung'}]] (ignored)
+
14%|█▍ | 1706/11952 [2:53:42<20:33:54, 7.23s/it]
{'loss': 0.5341, 'learning_rate': 1.934115130299661e-05, 'epoch': 0.14}
+
14%|█▍ | 1706/11952 [2:53:42<20:33:54, 7.23s/it]
14%|█▍ | 1707/11952 [2:53:48<19:32:40, 6.87s/it]
{'loss': 0.4955, 'learning_rate': 1.9340183600202998e-05, 'epoch': 0.14}
+
14%|█▍ | 1707/11952 [2:53:48<19:32:40, 6.87s/it]
14%|█▍ | 1708/11952 [2:53:54<18:30:44, 6.51s/it]
{'loss': 0.4864, 'learning_rate': 1.933921521150515e-05, 'epoch': 0.14}
+
14%|█▍ | 1708/11952 [2:53:54<18:30:44, 6.51s/it]
14%|█▍ | 1709/11952 [2:54:00<17:54:26, 6.29s/it]
{'loss': 0.5248, 'learning_rate': 1.9338246136974182e-05, 'epoch': 0.14}
+
14%|█▍ | 1709/11952 [2:54:00<17:54:26, 6.29s/it]
14%|█▍ | 1710/11952 [2:54:06<17:36:01, 6.19s/it]
{'loss': 0.5103, 'learning_rate': 1.9337276376681264e-05, 'epoch': 0.14}
+
14%|█▍ | 1710/11952 [2:54:06<17:36:01, 6.19s/it]
14%|█▍ | 1711/11952 [2:54:12<17:27:20, 6.14s/it]
{'loss': 0.5182, 'learning_rate': 1.93363059306976e-05, 'epoch': 0.14}
+
14%|█▍ | 1711/11952 [2:54:12<17:27:20, 6.14s/it]
14%|█▍ | 1712/11952 [2:54:18<17:10:00, 6.04s/it]
{'loss': 0.5186, 'learning_rate': 1.933533479909446e-05, 'epoch': 0.14}
+
14%|█▍ | 1712/11952 [2:54:18<17:10:00, 6.04s/it]
14%|█▍ | 1713/11952 [2:54:23<16:50:04, 5.92s/it]
{'loss': 0.5112, 'learning_rate': 1.9334362981943163e-05, 'epoch': 0.14}
+
14%|█▍ | 1713/11952 [2:54:23<16:50:04, 5.92s/it]
14%|█▍ | 1714/11952 [2:54:29<16:48:50, 5.91s/it]
{'loss': 0.4874, 'learning_rate': 1.9333390479315074e-05, 'epoch': 0.14}
+
14%|█▍ | 1714/11952 [2:54:29<16:48:50, 5.91s/it]
14%|█▍ | 1715/11952 [2:54:35<16:27:10, 5.79s/it]
{'loss': 0.4948, 'learning_rate': 1.9332417291281608e-05, 'epoch': 0.14}
+
14%|█▍ | 1715/11952 [2:54:35<16:27:10, 5.79s/it]
14%|█▍ | 1716/11952 [2:54:41<16:32:09, 5.82s/it]
{'loss': 0.5153, 'learning_rate': 1.9331443417914232e-05, 'epoch': 0.14}
+
14%|█▍ | 1716/11952 [2:54:41<16:32:09, 5.82s/it]
14%|█▍ | 1717/11952 [2:54:46<16:24:08, 5.77s/it]
{'loss': 0.5004, 'learning_rate': 1.9330468859284462e-05, 'epoch': 0.14}
+
14%|█▍ | 1717/11952 [2:54:46<16:24:08, 5.77s/it]
14%|█▍ | 1718/11952 [2:54:52<16:13:41, 5.71s/it]
{'loss': 0.4919, 'learning_rate': 1.932949361546387e-05, 'epoch': 0.14}
+
14%|█▍ | 1718/11952 [2:54:52<16:13:41, 5.71s/it]
14%|█▍ | 1719/11952 [2:54:58<16:14:05, 5.71s/it]
{'loss': 0.5057, 'learning_rate': 1.9328517686524073e-05, 'epoch': 0.14}
+
14%|█▍ | 1719/11952 [2:54:58<16:14:05, 5.71s/it]
14%|█▍ | 1720/11952 [2:55:03<16:05:16, 5.66s/it]
{'loss': 0.5056, 'learning_rate': 1.9327541072536733e-05, 'epoch': 0.14}
+
14%|█▍ | 1720/11952 [2:55:03<16:05:16, 5.66s/it]
14%|█▍ | 1721/11952 [2:55:09<16:06:53, 5.67s/it]
{'loss': 0.4943, 'learning_rate': 1.9326563773573576e-05, 'epoch': 0.14}
+
14%|█▍ | 1721/11952 [2:55:09<16:06:53, 5.67s/it]
14%|█▍ | 1722/11952 [2:55:15<16:21:14, 5.76s/it]
{'loss': 0.5114, 'learning_rate': 1.9325585789706366e-05, 'epoch': 0.14}
+
14%|█▍ | 1722/11952 [2:55:15<16:21:14, 5.76s/it]
14%|█▍ | 1723/11952 [2:55:21<16:30:35, 5.81s/it]
{'loss': 0.4955, 'learning_rate': 1.932460712100692e-05, 'epoch': 0.14}
+
14%|█▍ | 1723/11952 [2:55:21<16:30:35, 5.81s/it]
14%|█▍ | 1724/11952 [2:55:26<16:28:27, 5.80s/it]
{'loss': 0.4962, 'learning_rate': 1.9323627767547118e-05, 'epoch': 0.14}
+
14%|█▍ | 1724/11952 [2:55:26<16:28:27, 5.80s/it]
14%|█▍ | 1725/11952 [2:55:32<16:26:15, 5.79s/it]
{'loss': 0.5037, 'learning_rate': 1.932264772939887e-05, 'epoch': 0.14}
+
14%|█▍ | 1725/11952 [2:55:32<16:26:15, 5.79s/it]
14%|█▍ | 1726/11952 [2:55:38<16:26:15, 5.79s/it]
{'loss': 0.5101, 'learning_rate': 1.9321667006634146e-05, 'epoch': 0.14}
+
14%|█▍ | 1726/11952 [2:55:38<16:26:15, 5.79s/it]
14%|█▍ | 1727/11952 [2:55:44<16:36:46, 5.85s/it]
{'loss': 0.5041, 'learning_rate': 1.932068559932497e-05, 'epoch': 0.14}
+
14%|█▍ | 1727/11952 [2:55:44<16:36:46, 5.85s/it]
14%|█▍ | 1728/11952 [2:55:50<16:32:17, 5.82s/it]
{'loss': 0.4974, 'learning_rate': 1.9319703507543415e-05, 'epoch': 0.14}
+
14%|█▍ | 1728/11952 [2:55:50<16:32:17, 5.82s/it]
14%|█▍ | 1729/11952 [2:55:55<16:25:39, 5.78s/it]
{'loss': 0.5173, 'learning_rate': 1.9318720731361593e-05, 'epoch': 0.14}
+
14%|█▍ | 1729/11952 [2:55:55<16:25:39, 5.78s/it]
14%|█▍ | 1730/11952 [2:56:01<16:27:32, 5.80s/it]
{'loss': 0.5043, 'learning_rate': 1.931773727085168e-05, 'epoch': 0.14}
+
14%|█▍ | 1730/11952 [2:56:01<16:27:32, 5.80s/it]
14%|█▍ | 1731/11952 [2:56:07<16:22:50, 5.77s/it]
{'loss': 0.5068, 'learning_rate': 1.9316753126085902e-05, 'epoch': 0.14}
+
14%|█▍ | 1731/11952 [2:56:07<16:22:50, 5.77s/it]
14%|█▍ | 1732/11952 [2:56:13<16:41:33, 5.88s/it]
{'loss': 0.5033, 'learning_rate': 1.9315768297136523e-05, 'epoch': 0.14}
+
14%|█▍ | 1732/11952 [2:56:13<16:41:33, 5.88s/it]
14%|█▍ | 1733/11952 [2:56:19<16:57:51, 5.98s/it]
{'loss': 0.5153, 'learning_rate': 1.9314782784075866e-05, 'epoch': 0.14}
+
14%|█▍ | 1733/11952 [2:56:19<16:57:51, 5.98s/it]
15%|█▍ | 1734/11952 [2:56:26<17:23:34, 6.13s/it]
{'loss': 0.5235, 'learning_rate': 1.9313796586976306e-05, 'epoch': 0.15}
+
15%|█▍ | 1734/11952 [2:56:26<17:23:34, 6.13s/it]
15%|█▍ | 1735/11952 [2:56:31<17:00:53, 6.00s/it]
{'loss': 0.4886, 'learning_rate': 1.9312809705910266e-05, 'epoch': 0.15}
+
15%|█▍ | 1735/11952 [2:56:31<17:00:53, 6.00s/it]
15%|█▍ | 1736/11952 [2:56:37<16:42:45, 5.89s/it]
{'loss': 0.493, 'learning_rate': 1.9311822140950213e-05, 'epoch': 0.15}
+
15%|█▍ | 1736/11952 [2:56:37<16:42:45, 5.89s/it]
15%|█▍ | 1737/11952 [2:56:43<16:35:26, 5.85s/it]
{'loss': 0.5066, 'learning_rate': 1.931083389216867e-05, 'epoch': 0.15}
+
15%|█▍ | 1737/11952 [2:56:43<16:35:26, 5.85s/it]
15%|█▍ | 1738/11952 [2:56:49<16:37:56, 5.86s/it]
{'loss': 0.4965, 'learning_rate': 1.930984495963822e-05, 'epoch': 0.15}
+
15%|█▍ | 1738/11952 [2:56:49<16:37:56, 5.86s/it]
15%|█▍ | 1739/11952 [2:56:54<16:31:16, 5.82s/it]
{'loss': 0.497, 'learning_rate': 1.930885534343147e-05, 'epoch': 0.15}
+
15%|█▍ | 1739/11952 [2:56:54<16:31:16, 5.82s/it]
15%|█▍ | 1740/11952 [2:57:00<16:40:05, 5.88s/it]
{'loss': 0.4967, 'learning_rate': 1.930786504362111e-05, 'epoch': 0.15}
+
15%|█▍ | 1740/11952 [2:57:00<16:40:05, 5.88s/it]
15%|█▍ | 1741/11952 [2:57:06<16:39:58, 5.88s/it]
{'loss': 0.4892, 'learning_rate': 1.930687406027985e-05, 'epoch': 0.15}
+
15%|█▍ | 1741/11952 [2:57:06<16:39:58, 5.88s/it]
15%|█▍ | 1742/11952 [2:57:12<16:27:23, 5.80s/it]
{'loss': 0.5099, 'learning_rate': 1.930588239348047e-05, 'epoch': 0.15}
+
15%|█▍ | 1742/11952 [2:57:12<16:27:23, 5.80s/it]
15%|█▍ | 1743/11952 [2:57:18<16:35:05, 5.85s/it]
{'loss': 0.5118, 'learning_rate': 1.9304890043295796e-05, 'epoch': 0.15}
+
15%|█▍ | 1743/11952 [2:57:18<16:35:05, 5.85s/it]
15%|█▍ | 1744/11952 [2:57:24<16:32:14, 5.83s/it]
{'loss': 0.504, 'learning_rate': 1.93038970097987e-05, 'epoch': 0.15}
+
15%|█▍ | 1744/11952 [2:57:24<16:32:14, 5.83s/it]
15%|█▍ | 1745/11952 [2:57:30<16:35:34, 5.85s/it]
{'loss': 0.5056, 'learning_rate': 1.93029032930621e-05, 'epoch': 0.15}
+
15%|█▍ | 1745/11952 [2:57:30<16:35:34, 5.85s/it]
15%|█▍ | 1746/11952 [2:57:35<16:28:26, 5.81s/it]
{'loss': 0.499, 'learning_rate': 1.930190889315898e-05, 'epoch': 0.15}
+
15%|█▍ | 1746/11952 [2:57:35<16:28:26, 5.81s/it]
15%|█▍ | 1747/11952 [2:57:41<16:33:01, 5.84s/it]
{'loss': 0.5259, 'learning_rate': 1.930091381016236e-05, 'epoch': 0.15}
+
15%|█▍ | 1747/11952 [2:57:41<16:33:01, 5.84s/it]
15%|█▍ | 1748/11952 [2:57:47<16:34:56, 5.85s/it]
{'loss': 0.5033, 'learning_rate': 1.9299918044145315e-05, 'epoch': 0.15}
+
15%|█▍ | 1748/11952 [2:57:47<16:34:56, 5.85s/it]
15%|█▍ | 1749/11952 [2:57:53<16:49:25, 5.94s/it]
{'loss': 0.5005, 'learning_rate': 1.9298921595180968e-05, 'epoch': 0.15}
+
15%|█▍ | 1749/11952 [2:57:53<16:49:25, 5.94s/it]4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+26 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
15%|█▍ | 1750/11952 [2:57:59<16:52:48, 5.96s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.518, 'learning_rate': 1.9297924463342495e-05, 'epoch': 0.15}
+
15%|█▍ | 1750/11952 [2:57:59<16:52:48, 5.96s/it]
15%|█▍ | 1751/11952 [2:58:05<16:52:09, 5.95s/it]
{'loss': 0.5143, 'learning_rate': 1.929692664870313e-05, 'epoch': 0.15}
+
15%|█▍ | 1751/11952 [2:58:05<16:52:09, 5.95s/it]
15%|█▍ | 1752/11952 [2:58:12<17:11:08, 6.07s/it]
{'loss': 0.5061, 'learning_rate': 1.9295928151336134e-05, 'epoch': 0.15}
+
15%|█▍ | 1752/11952 [2:58:12<17:11:08, 6.07s/it]
15%|█▍ | 1753/11952 [2:58:17<16:56:16, 5.98s/it]
{'loss': 0.5013, 'learning_rate': 1.9294928971314843e-05, 'epoch': 0.15}
+
15%|█▍ | 1753/11952 [2:58:17<16:56:16, 5.98s/it]
15%|█▍ | 1754/11952 [2:58:23<16:39:08, 5.88s/it]
{'loss': 0.5112, 'learning_rate': 1.9293929108712624e-05, 'epoch': 0.15}
+
15%|█▍ | 1754/11952 [2:58:23<16:39:08, 5.88s/it]
15%|█▍ | 1755/11952 [2:58:29<16:45:33, 5.92s/it]
{'loss': 0.4963, 'learning_rate': 1.9292928563602912e-05, 'epoch': 0.15}
+
15%|█▍ | 1755/11952 [2:58:29<16:45:33, 5.92s/it]
15%|█▍ | 1756/11952 [2:58:35<16:57:50, 5.99s/it]
{'loss': 0.5058, 'learning_rate': 1.9291927336059175e-05, 'epoch': 0.15}
+
15%|█▍ | 1756/11952 [2:58:35<16:57:50, 5.99s/it]
15%|█▍ | 1757/11952 [2:58:41<16:53:14, 5.96s/it]
{'loss': 0.4977, 'learning_rate': 1.9290925426154948e-05, 'epoch': 0.15}
+
15%|█▍ | 1757/11952 [2:58:41<16:53:14, 5.96s/it]
15%|█▍ | 1758/11952 [2:58:47<16:58:08, 5.99s/it]
{'loss': 0.5122, 'learning_rate': 1.9289922833963798e-05, 'epoch': 0.15}
+
15%|█▍ | 1758/11952 [2:58:47<16:58:08, 5.99s/it]
15%|█▍ | 1759/11952 [2:58:53<16:44:16, 5.91s/it]
{'loss': 0.5096, 'learning_rate': 1.9288919559559353e-05, 'epoch': 0.15}
+
15%|█▍ | 1759/11952 [2:58:53<16:44:16, 5.91s/it]
15%|█▍ | 1760/11952 [2:58:59<16:37:42, 5.87s/it]
{'loss': 0.5032, 'learning_rate': 1.928791560301529e-05, 'epoch': 0.15}
+
15%|█▍ | 1760/11952 [2:58:59<16:37:42, 5.87s/it]
15%|█▍ | 1761/11952 [2:59:04<16:37:04, 5.87s/it]
{'loss': 0.4987, 'learning_rate': 1.9286910964405345e-05, 'epoch': 0.15}
+
15%|█▍ | 1761/11952 [2:59:04<16:37:04, 5.87s/it]
15%|█▍ | 1762/11952 [2:59:10<16:30:32, 5.83s/it]
{'loss': 0.5022, 'learning_rate': 1.9285905643803277e-05, 'epoch': 0.15}
+
15%|█▍ | 1762/11952 [2:59:10<16:30:32, 5.83s/it]
15%|█▍ | 1763/11952 [2:59:16<16:27:42, 5.82s/it]
{'loss': 0.4889, 'learning_rate': 1.9284899641282925e-05, 'epoch': 0.15}
+
15%|█▍ | 1763/11952 [2:59:16<16:27:42, 5.82s/it]
15%|█▍ | 1764/11952 [2:59:22<16:49:16, 5.94s/it]
{'loss': 0.5117, 'learning_rate': 1.928389295691816e-05, 'epoch': 0.15}
+
15%|█▍ | 1764/11952 [2:59:22<16:49:16, 5.94s/it]
15%|█▍ | 1765/11952 [2:59:28<16:48:18, 5.94s/it]
{'loss': 0.5068, 'learning_rate': 1.9282885590782916e-05, 'epoch': 0.15}
+
15%|█▍ | 1765/11952 [2:59:28<16:48:18, 5.94s/it]
15%|█▍ | 1766/11952 [2:59:34<16:57:32, 5.99s/it]
{'loss': 0.5271, 'learning_rate': 1.928187754295116e-05, 'epoch': 0.15}
+
15%|█▍ | 1766/11952 [2:59:34<16:57:32, 5.99s/it]
15%|█▍ | 1767/11952 [2:59:40<16:40:37, 5.89s/it]
{'loss': 0.497, 'learning_rate': 1.9280868813496927e-05, 'epoch': 0.15}
+
15%|█▍ | 1767/11952 [2:59:40<16:40:37, 5.89s/it]
15%|█▍ | 1768/11952 [2:59:46<16:30:16, 5.83s/it]
{'loss': 0.5223, 'learning_rate': 1.9279859402494288e-05, 'epoch': 0.15}
+
15%|█▍ | 1768/11952 [2:59:46<16:30:16, 5.83s/it]
15%|█▍ | 1769/11952 [2:59:52<16:49:51, 5.95s/it]
{'loss': 0.5151, 'learning_rate': 1.9278849310017372e-05, 'epoch': 0.15}
+
15%|█▍ | 1769/11952 [2:59:52<16:49:51, 5.95s/it]
15%|█▍ | 1770/11952 [2:59:58<16:58:15, 6.00s/it]
{'loss': 0.5233, 'learning_rate': 1.9277838536140357e-05, 'epoch': 0.15}
+
15%|█▍ | 1770/11952 [2:59:58<16:58:15, 6.00s/it]
15%|█▍ | 1771/11952 [3:00:04<16:58:40, 6.00s/it]
{'loss': 0.4949, 'learning_rate': 1.927682708093747e-05, 'epoch': 0.15}
+
15%|█▍ | 1771/11952 [3:00:04<16:58:40, 6.00s/it]
15%|█▍ | 1772/11952 [3:00:10<16:45:36, 5.93s/it]
{'loss': 0.5211, 'learning_rate': 1.9275814944482988e-05, 'epoch': 0.15}
+
15%|█▍ | 1772/11952 [3:00:10<16:45:36, 5.93s/it]
15%|█▍ | 1773/11952 [3:00:15<16:32:17, 5.85s/it]
{'loss': 0.4977, 'learning_rate': 1.9274802126851237e-05, 'epoch': 0.15}
+
15%|█▍ | 1773/11952 [3:00:15<16:32:17, 5.85s/it]
15%|█▍ | 1774/11952 [3:00:21<16:30:42, 5.84s/it]
{'loss': 0.5169, 'learning_rate': 1.9273788628116593e-05, 'epoch': 0.15}
+
15%|█▍ | 1774/11952 [3:00:21<16:30:42, 5.84s/it]
15%|█▍ | 1775/11952 [3:00:27<16:32:20, 5.85s/it]
{'loss': 0.5062, 'learning_rate': 1.9272774448353484e-05, 'epoch': 0.15}
+
15%|█▍ | 1775/11952 [3:00:27<16:32:20, 5.85s/it]
15%|█▍ | 1776/11952 [3:00:33<16:29:26, 5.83s/it]
{'loss': 0.4999, 'learning_rate': 1.927175958763639e-05, 'epoch': 0.15}
+
15%|█▍ | 1776/11952 [3:00:33<16:29:26, 5.83s/it]
15%|█▍ | 1777/11952 [3:00:39<16:55:29, 5.99s/it]
{'loss': 0.5578, 'learning_rate': 1.9270744046039834e-05, 'epoch': 0.15}
+
15%|█▍ | 1777/11952 [3:00:39<16:55:29, 5.99s/it]
15%|█▍ | 1778/11952 [3:00:45<16:31:52, 5.85s/it]
{'loss': 0.5188, 'learning_rate': 1.92697278236384e-05, 'epoch': 0.15}
+
15%|█▍ | 1778/11952 [3:00:45<16:31:52, 5.85s/it]
15%|█▍ | 1779/11952 [3:00:51<16:26:56, 5.82s/it]
{'loss': 0.5076, 'learning_rate': 1.9268710920506707e-05, 'epoch': 0.15}
+
15%|█▍ | 1779/11952 [3:00:51<16:26:56, 5.82s/it]
15%|█▍ | 1780/11952 [3:00:56<16:28:44, 5.83s/it]
{'loss': 0.4947, 'learning_rate': 1.926769333671943e-05, 'epoch': 0.15}
+
15%|█▍ | 1780/11952 [3:00:56<16:28:44, 5.83s/it]
15%|█▍ | 1781/11952 [3:01:02<16:40:10, 5.90s/it]
{'loss': 0.5049, 'learning_rate': 1.926667507235131e-05, 'epoch': 0.15}
+
15%|█▍ | 1781/11952 [3:01:02<16:40:10, 5.90s/it]
15%|█▍ | 1782/11952 [3:01:08<16:42:52, 5.92s/it]
{'loss': 0.5118, 'learning_rate': 1.9265656127477114e-05, 'epoch': 0.15}
+
15%|█▍ | 1782/11952 [3:01:08<16:42:52, 5.92s/it]
15%|█▍ | 1783/11952 [3:01:14<16:29:29, 5.84s/it]
{'loss': 0.489, 'learning_rate': 1.926463650217167e-05, 'epoch': 0.15}
+
15%|█▍ | 1783/11952 [3:01:14<16:29:29, 5.84s/it]
15%|█▍ | 1784/11952 [3:01:20<16:14:26, 5.75s/it]
{'loss': 0.5062, 'learning_rate': 1.9263616196509855e-05, 'epoch': 0.15}
+
15%|█▍ | 1784/11952 [3:01:20<16:14:26, 5.75s/it]
15%|█▍ | 1785/11952 [3:01:25<16:19:37, 5.78s/it]
{'loss': 0.5238, 'learning_rate': 1.9262595210566598e-05, 'epoch': 0.15}
+
15%|█▍ | 1785/11952 [3:01:25<16:19:37, 5.78s/it]
15%|█▍ | 1786/11952 [3:01:31<16:10:00, 5.73s/it]
{'loss': 0.4939, 'learning_rate': 1.9261573544416872e-05, 'epoch': 0.15}
+
15%|█▍ | 1786/11952 [3:01:31<16:10:00, 5.73s/it]
15%|█▍ | 1787/11952 [3:01:37<16:12:55, 5.74s/it]
{'loss': 0.491, 'learning_rate': 1.926055119813571e-05, 'epoch': 0.15}
+
15%|█▍ | 1787/11952 [3:01:37<16:12:55, 5.74s/it]
15%|█▍ | 1788/11952 [3:01:43<16:19:33, 5.78s/it]
{'loss': 0.4932, 'learning_rate': 1.9259528171798184e-05, 'epoch': 0.15}
+
15%|█▍ | 1788/11952 [3:01:43<16:19:33, 5.78s/it]
15%|█▍ | 1789/11952 [3:01:49<16:33:49, 5.87s/it]
{'loss': 0.5256, 'learning_rate': 1.925850446547942e-05, 'epoch': 0.15}
+
15%|█▍ | 1789/11952 [3:01:49<16:33:49, 5.87s/it]
15%|█▍ | 1790/11952 [3:01:55<16:53:54, 5.99s/it]
{'loss': 0.5049, 'learning_rate': 1.92574800792546e-05, 'epoch': 0.15}
+
15%|█▍ | 1790/11952 [3:01:55<16:53:54, 5.99s/it]
15%|█▍ | 1791/11952 [3:02:01<16:33:18, 5.87s/it]
{'loss': 0.4982, 'learning_rate': 1.925645501319895e-05, 'epoch': 0.15}
+
15%|█▍ | 1791/11952 [3:02:01<16:33:18, 5.87s/it]
15%|█▍ | 1792/11952 [3:02:06<16:31:42, 5.86s/it]
{'loss': 0.5154, 'learning_rate': 1.925542926738774e-05, 'epoch': 0.15}
+
15%|█▍ | 1792/11952 [3:02:06<16:31:42, 5.86s/it]
15%|█▌ | 1793/11952 [3:02:12<16:39:54, 5.91s/it]
{'loss': 0.5136, 'learning_rate': 1.92544028418963e-05, 'epoch': 0.15}
+
15%|█▌ | 1793/11952 [3:02:12<16:39:54, 5.91s/it]
15%|█▌ | 1794/11952 [3:02:18<16:26:55, 5.83s/it]
{'loss': 0.4918, 'learning_rate': 1.9253375736800014e-05, 'epoch': 0.15}
+
15%|█▌ | 1794/11952 [3:02:18<16:26:55, 5.83s/it]
15%|█▌ | 1795/11952 [3:02:24<16:22:39, 5.80s/it]
{'loss': 0.5009, 'learning_rate': 1.9252347952174294e-05, 'epoch': 0.15}
+
15%|█▌ | 1795/11952 [3:02:24<16:22:39, 5.80s/it]
15%|█▌ | 1796/11952 [3:02:30<16:26:36, 5.83s/it]
{'loss': 0.5235, 'learning_rate': 1.925131948809463e-05, 'epoch': 0.15}
+
15%|█▌ | 1796/11952 [3:02:30<16:26:36, 5.83s/it]
15%|█▌ | 1797/11952 [3:02:36<16:36:32, 5.89s/it]
{'loss': 0.5012, 'learning_rate': 1.9250290344636537e-05, 'epoch': 0.15}
+
15%|█▌ | 1797/11952 [3:02:36<16:36:32, 5.89s/it]
15%|█▌ | 1798/11952 [3:02:41<16:23:49, 5.81s/it]
{'loss': 0.4942, 'learning_rate': 1.92492605218756e-05, 'epoch': 0.15}
+
15%|█▌ | 1798/11952 [3:02:41<16:23:49, 5.81s/it]
15%|█▌ | 1799/11952 [3:02:47<16:18:54, 5.78s/it]
{'loss': 0.5102, 'learning_rate': 1.9248230019887438e-05, 'epoch': 0.15}
+
15%|█▌ | 1799/11952 [3:02:47<16:18:54, 5.78s/it]4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+ 1 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
15%|█▌ | 1800/11952 [3:02:53<16:24:45, 5.82s/it]63 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4946, 'learning_rate': 1.924719883874773e-05, 'epoch': 0.15}
+
15%|█▌ | 1800/11952 [3:02:53<16:24:45, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
15%|█▌ | 1801/11952 [3:03:28<40:46:38, 14.46s/it]
{'loss': 0.5077, 'learning_rate': 1.9246166978532203e-05, 'epoch': 0.15}
+
15%|█▌ | 1801/11952 [3:03:28<40:46:38, 14.46s/it]
15%|█▌ | 1802/11952 [3:03:34<33:34:45, 11.91s/it]
{'loss': 0.5084, 'learning_rate': 1.924513443931663e-05, 'epoch': 0.15}
+
15%|█▌ | 1802/11952 [3:03:34<33:34:45, 11.91s/it]
15%|█▌ | 1803/11952 [3:03:40<28:31:02, 10.12s/it]
{'loss': 0.4944, 'learning_rate': 1.9244101221176834e-05, 'epoch': 0.15}
+
15%|█▌ | 1803/11952 [3:03:40<28:31:02, 10.12s/it]
15%|█▌ | 1804/11952 [3:03:46<25:11:48, 8.94s/it]
{'loss': 0.5069, 'learning_rate': 1.9243067324188696e-05, 'epoch': 0.15}
+
15%|█▌ | 1804/11952 [3:03:46<25:11:48, 8.94s/it]
15%|█▌ | 1805/11952 [3:03:52<22:33:47, 8.01s/it]
{'loss': 0.4945, 'learning_rate': 1.9242032748428138e-05, 'epoch': 0.15}
+
15%|█▌ | 1805/11952 [3:03:52<22:33:47, 8.01s/it]
15%|█▌ | 1806/11952 [3:03:57<20:44:01, 7.36s/it]
{'loss': 0.507, 'learning_rate': 1.924099749397114e-05, 'epoch': 0.15}
+
15%|█▌ | 1806/11952 [3:03:57<20:44:01, 7.36s/it]
15%|█▌ | 1807/11952 [3:04:03<19:28:37, 6.91s/it]
{'loss': 0.5152, 'learning_rate': 1.9239961560893717e-05, 'epoch': 0.15}
+
15%|█▌ | 1807/11952 [3:04:03<19:28:37, 6.91s/it]
15%|█▌ | 1808/11952 [3:04:09<18:33:12, 6.58s/it]
{'loss': 0.4897, 'learning_rate': 1.923892494927195e-05, 'epoch': 0.15}
+
15%|█▌ | 1808/11952 [3:04:09<18:33:12, 6.58s/it]
15%|█▌ | 1809/11952 [3:04:15<18:00:02, 6.39s/it]
{'loss': 0.4968, 'learning_rate': 1.9237887659181963e-05, 'epoch': 0.15}
+
15%|█▌ | 1809/11952 [3:04:15<18:00:02, 6.39s/it]
15%|█▌ | 1810/11952 [3:04:22<18:06:42, 6.43s/it]
{'loss': 0.5118, 'learning_rate': 1.9236849690699924e-05, 'epoch': 0.15}
+
15%|█▌ | 1810/11952 [3:04:22<18:06:42, 6.43s/it]
15%|█▌ | 1811/11952 [3:04:28<17:45:22, 6.30s/it]
{'loss': 0.5128, 'learning_rate': 1.923581104390207e-05, 'epoch': 0.15}
+
15%|█▌ | 1811/11952 [3:04:28<17:45:22, 6.30s/it]
15%|█▌ | 1812/11952 [3:04:33<17:15:19, 6.13s/it]
{'loss': 0.4928, 'learning_rate': 1.9234771718864667e-05, 'epoch': 0.15}
+
15%|█▌ | 1812/11952 [3:04:33<17:15:19, 6.13s/it]
15%|█▌ | 1813/11952 [3:04:39<17:04:07, 6.06s/it]
{'loss': 0.5075, 'learning_rate': 1.9233731715664036e-05, 'epoch': 0.15}
+
15%|█▌ | 1813/11952 [3:04:39<17:04:07, 6.06s/it]
15%|█▌ | 1814/11952 [3:04:45<16:49:37, 5.98s/it]
{'loss': 0.5109, 'learning_rate': 1.9232691034376556e-05, 'epoch': 0.15}
+
15%|█▌ | 1814/11952 [3:04:45<16:49:37, 5.98s/it]
15%|█▌ | 1815/11952 [3:04:54<19:19:49, 6.86s/it]
{'loss': 0.4918, 'learning_rate': 1.9231649675078647e-05, 'epoch': 0.15}
+
15%|█▌ | 1815/11952 [3:04:54<19:19:49, 6.86s/it]
15%|█▌ | 1816/11952 [3:05:00<18:34:12, 6.60s/it]
{'loss': 0.5056, 'learning_rate': 1.9230607637846785e-05, 'epoch': 0.15}
+
15%|█▌ | 1816/11952 [3:05:00<18:34:12, 6.60s/it]
15%|█▌ | 1817/11952 [3:05:06<17:51:48, 6.35s/it]
{'loss': 0.4999, 'learning_rate': 1.9229564922757487e-05, 'epoch': 0.15}
+
15%|█▌ | 1817/11952 [3:05:06<17:51:48, 6.35s/it]
15%|█▌ | 1818/11952 [3:05:12<17:34:00, 6.24s/it]
{'loss': 0.5066, 'learning_rate': 1.9228521529887333e-05, 'epoch': 0.15}
+
15%|█▌ | 1818/11952 [3:05:12<17:34:00, 6.24s/it]
15%|█▌ | 1819/11952 [3:05:17<17:09:02, 6.09s/it]
{'loss': 0.4944, 'learning_rate': 1.9227477459312942e-05, 'epoch': 0.15}
+
15%|█▌ | 1819/11952 [3:05:17<17:09:02, 6.09s/it]
15%|█▌ | 1820/11952 [3:05:23<17:04:22, 6.07s/it]
{'loss': 0.5145, 'learning_rate': 1.9226432711110983e-05, 'epoch': 0.15}
+
15%|█▌ | 1820/11952 [3:05:23<17:04:22, 6.07s/it]
15%|█▌ | 1821/11952 [3:05:29<16:44:21, 5.95s/it]
{'loss': 0.5033, 'learning_rate': 1.922538728535819e-05, 'epoch': 0.15}
+
15%|█▌ | 1821/11952 [3:05:29<16:44:21, 5.95s/it]
15%|█▌ | 1822/11952 [3:05:35<16:48:07, 5.97s/it]
{'loss': 0.5292, 'learning_rate': 1.922434118213132e-05, 'epoch': 0.15}
+
15%|█▌ | 1822/11952 [3:05:35<16:48:07, 5.97s/it]
15%|█▌ | 1823/11952 [3:05:41<16:40:16, 5.93s/it]
{'loss': 0.5067, 'learning_rate': 1.9223294401507196e-05, 'epoch': 0.15}
+
15%|█▌ | 1823/11952 [3:05:41<16:40:16, 5.93s/it]
15%|█▌ | 1824/11952 [3:05:47<16:54:00, 6.01s/it]
{'loss': 0.5016, 'learning_rate': 1.9222246943562702e-05, 'epoch': 0.15}
+
15%|█▌ | 1824/11952 [3:05:47<16:54:00, 6.01s/it]
15%|█▌ | 1825/11952 [3:05:53<16:48:32, 5.98s/it]
{'loss': 0.4928, 'learning_rate': 1.9221198808374746e-05, 'epoch': 0.15}
+
15%|█▌ | 1825/11952 [3:05:53<16:48:32, 5.98s/it]
15%|█▌ | 1826/11952 [3:05:59<16:33:02, 5.88s/it]
{'loss': 0.5077, 'learning_rate': 1.9220149996020306e-05, 'epoch': 0.15}
+
15%|█▌ | 1826/11952 [3:05:59<16:33:02, 5.88s/it]
15%|█▌ | 1827/11952 [3:06:04<16:28:58, 5.86s/it]
{'loss': 0.4962, 'learning_rate': 1.9219100506576396e-05, 'epoch': 0.15}
+
15%|█▌ | 1827/11952 [3:06:04<16:28:58, 5.86s/it]
15%|█▌ | 1828/11952 [3:06:10<16:28:29, 5.86s/it]
{'loss': 0.5081, 'learning_rate': 1.9218050340120095e-05, 'epoch': 0.15}
+
15%|█▌ | 1828/11952 [3:06:10<16:28:29, 5.86s/it]
15%|█▌ | 1829/11952 [3:06:16<16:32:55, 5.89s/it]
{'loss': 0.5203, 'learning_rate': 1.9216999496728513e-05, 'epoch': 0.15}
+
15%|█▌ | 1829/11952 [3:06:16<16:32:55, 5.89s/it]
15%|█▌ | 1830/11952 [3:06:22<16:28:24, 5.86s/it]
{'loss': 0.511, 'learning_rate': 1.9215947976478825e-05, 'epoch': 0.15}
+
15%|█▌ | 1830/11952 [3:06:22<16:28:24, 5.86s/it]
15%|█▌ | 1831/11952 [3:06:28<16:17:16, 5.79s/it]
{'loss': 0.5018, 'learning_rate': 1.9214895779448254e-05, 'epoch': 0.15}
+
15%|█▌ | 1831/11952 [3:06:28<16:17:16, 5.79s/it]
15%|█▌ | 1832/11952 [3:06:34<16:24:28, 5.84s/it]
{'loss': 0.4929, 'learning_rate': 1.921384290571406e-05, 'epoch': 0.15}
+
15%|█▌ | 1832/11952 [3:06:34<16:24:28, 5.84s/it]
15%|█▌ | 1833/11952 [3:06:39<16:20:00, 5.81s/it]
{'loss': 0.4992, 'learning_rate': 1.9212789355353567e-05, 'epoch': 0.15}
+
15%|█▌ | 1833/11952 [3:06:39<16:20:00, 5.81s/it]
15%|█▌ | 1834/11952 [3:06:45<16:13:24, 5.77s/it]
{'loss': 0.5106, 'learning_rate': 1.921173512844414e-05, 'epoch': 0.15}
+
15%|█▌ | 1834/11952 [3:06:45<16:13:24, 5.77s/it]
15%|█▌ | 1835/11952 [3:06:54<18:38:46, 6.64s/it]
{'loss': 0.4934, 'learning_rate': 1.9210680225063204e-05, 'epoch': 0.15}
+
15%|█▌ | 1835/11952 [3:06:54<18:38:46, 6.64s/it]
15%|█▌ | 1836/11952 [3:06:59<17:46:54, 6.33s/it]
{'loss': 0.5013, 'learning_rate': 1.9209624645288224e-05, 'epoch': 0.15}
+
15%|█▌ | 1836/11952 [3:06:59<17:46:54, 6.33s/it]
15%|█▌ | 1837/11952 [3:07:05<17:07:30, 6.09s/it]
{'loss': 0.4948, 'learning_rate': 1.9208568389196715e-05, 'epoch': 0.15}
+
15%|█▌ | 1837/11952 [3:07:05<17:07:30, 6.09s/it]
15%|█▌ | 1838/11952 [3:07:10<16:41:59, 5.94s/it]
{'loss': 0.4963, 'learning_rate': 1.920751145686624e-05, 'epoch': 0.15}
+
15%|█▌ | 1838/11952 [3:07:10<16:41:59, 5.94s/it]
15%|█▌ | 1839/11952 [3:07:16<16:43:45, 5.96s/it]
{'loss': 0.499, 'learning_rate': 1.9206453848374425e-05, 'epoch': 0.15}
+
15%|█▌ | 1839/11952 [3:07:16<16:43:45, 5.96s/it]
15%|█▌ | 1840/11952 [3:07:22<16:28:26, 5.86s/it]
{'loss': 0.4947, 'learning_rate': 1.920539556379893e-05, 'epoch': 0.15}
+
15%|█▌ | 1840/11952 [3:07:22<16:28:26, 5.86s/it]
15%|█▌ | 1841/11952 [3:07:28<16:29:11, 5.87s/it]
{'loss': 0.5145, 'learning_rate': 1.920433660321747e-05, 'epoch': 0.15}
+
15%|█▌ | 1841/11952 [3:07:28<16:29:11, 5.87s/it]
15%|█▌ | 1842/11952 [3:07:36<18:30:45, 6.59s/it]
{'loss': 0.4967, 'learning_rate': 1.920327696670782e-05, 'epoch': 0.15}
+
15%|█▌ | 1842/11952 [3:07:36<18:30:45, 6.59s/it]
15%|█▌ | 1843/11952 [3:07:42<17:58:18, 6.40s/it]
{'loss': 0.52, 'learning_rate': 1.9202216654347786e-05, 'epoch': 0.15}
+
15%|█▌ | 1843/11952 [3:07:42<17:58:18, 6.40s/it]
15%|█▌ | 1844/11952 [3:07:48<17:14:28, 6.14s/it]
{'loss': 0.5103, 'learning_rate': 1.9201155666215237e-05, 'epoch': 0.15}
+
15%|█▌ | 1844/11952 [3:07:48<17:14:28, 6.14s/it]
15%|█▌ | 1845/11952 [3:07:57<19:30:30, 6.95s/it]
{'loss': 0.5124, 'learning_rate': 1.9200094002388084e-05, 'epoch': 0.15}
+
15%|█▌ | 1845/11952 [3:07:57<19:30:30, 6.95s/it]
15%|█▌ | 1846/11952 [3:08:03<18:53:35, 6.73s/it]
{'loss': 0.5054, 'learning_rate': 1.9199031662944294e-05, 'epoch': 0.15}
+
15%|█▌ | 1846/11952 [3:08:03<18:53:35, 6.73s/it]
15%|█▌ | 1847/11952 [3:08:09<18:03:58, 6.44s/it]
{'loss': 0.4923, 'learning_rate': 1.919796864796188e-05, 'epoch': 0.15}
+
15%|█▌ | 1847/11952 [3:08:09<18:03:58, 6.44s/it]
15%|█▌ | 1848/11952 [3:08:14<17:32:31, 6.25s/it]
{'loss': 0.5264, 'learning_rate': 1.919690495751891e-05, 'epoch': 0.15}
+
15%|█▌ | 1848/11952 [3:08:14<17:32:31, 6.25s/it]
15%|█▌ | 1849/11952 [3:08:24<20:08:41, 7.18s/it]
{'loss': 0.4979, 'learning_rate': 1.9195840591693486e-05, 'epoch': 0.15}
+
15%|█▌ | 1849/11952 [3:08:24<20:08:41, 7.18s/it]7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
15%|█▌ | 1850/11952 [3:08:29<18:50:17, 6.71s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5072, 'learning_rate': 1.919477555056378e-05, 'epoch': 0.15}
+
15%|█▌ | 1850/11952 [3:08:29<18:50:17, 6.71s/it]
15%|█▌ | 1851/11952 [3:08:37<19:57:46, 7.11s/it]
{'loss': 0.5136, 'learning_rate': 1.9193709834208005e-05, 'epoch': 0.15}
+
15%|█▌ | 1851/11952 [3:08:37<19:57:46, 7.11s/it]
15%|█▌ | 1852/11952 [3:08:46<21:25:13, 7.64s/it]
{'loss': 0.5028, 'learning_rate': 1.9192643442704413e-05, 'epoch': 0.15}
+
15%|█▌ | 1852/11952 [3:08:46<21:25:13, 7.64s/it]
16%|█▌ | 1853/11952 [3:08:52<19:47:03, 7.05s/it]
{'loss': 0.52, 'learning_rate': 1.9191576376131328e-05, 'epoch': 0.16}
+
16%|█▌ | 1853/11952 [3:08:52<19:47:03, 7.05s/it]
16%|█▌ | 1854/11952 [3:08:58<18:55:29, 6.75s/it]
{'loss': 0.5033, 'learning_rate': 1.91905086345671e-05, 'epoch': 0.16}
+
16%|█▌ | 1854/11952 [3:08:58<18:55:29, 6.75s/it]
16%|█▌ | 1855/11952 [3:09:04<18:09:31, 6.47s/it]
{'loss': 0.5088, 'learning_rate': 1.9189440218090146e-05, 'epoch': 0.16}
+
16%|█▌ | 1855/11952 [3:09:04<18:09:31, 6.47s/it]
16%|█▌ | 1856/11952 [3:09:10<17:37:41, 6.29s/it]
{'loss': 0.5009, 'learning_rate': 1.9188371126778923e-05, 'epoch': 0.16}
+
16%|█▌ | 1856/11952 [3:09:10<17:37:41, 6.29s/it]
16%|█▌ | 1857/11952 [3:09:16<17:32:47, 6.26s/it]
{'loss': 0.5068, 'learning_rate': 1.9187301360711943e-05, 'epoch': 0.16}
+
16%|█▌ | 1857/11952 [3:09:16<17:32:47, 6.26s/it]
16%|█▌ | 1858/11952 [3:09:22<17:10:52, 6.13s/it]
{'loss': 0.4997, 'learning_rate': 1.9186230919967764e-05, 'epoch': 0.16}
+
16%|█▌ | 1858/11952 [3:09:22<17:10:52, 6.13s/it]
16%|█▌ | 1859/11952 [3:09:28<17:01:57, 6.08s/it]
{'loss': 0.5098, 'learning_rate': 1.9185159804624994e-05, 'epoch': 0.16}
+
16%|█▌ | 1859/11952 [3:09:28<17:01:57, 6.08s/it]
16%|█▌ | 1860/11952 [3:09:33<16:38:28, 5.94s/it]
{'loss': 0.4964, 'learning_rate': 1.9184088014762292e-05, 'epoch': 0.16}
+
16%|█▌ | 1860/11952 [3:09:33<16:38:28, 5.94s/it]
16%|█▌ | 1861/11952 [3:09:39<16:24:45, 5.86s/it]
{'loss': 0.5084, 'learning_rate': 1.9183015550458367e-05, 'epoch': 0.16}
+
16%|█▌ | 1861/11952 [3:09:39<16:24:45, 5.86s/it]
16%|█▌ | 1862/11952 [3:09:45<16:20:38, 5.83s/it]
{'loss': 0.5049, 'learning_rate': 1.918194241179197e-05, 'epoch': 0.16}
+
16%|█▌ | 1862/11952 [3:09:45<16:20:38, 5.83s/it]
16%|█▌ | 1863/11952 [3:09:51<16:25:11, 5.86s/it]
{'loss': 0.4998, 'learning_rate': 1.9180868598841916e-05, 'epoch': 0.16}
+
16%|█▌ | 1863/11952 [3:09:51<16:25:11, 5.86s/it]
16%|█▌ | 1864/11952 [3:09:56<16:21:54, 5.84s/it]
{'loss': 0.5073, 'learning_rate': 1.9179794111687063e-05, 'epoch': 0.16}
+
16%|█▌ | 1864/11952 [3:09:56<16:21:54, 5.84s/it]
16%|█▌ | 1865/11952 [3:10:02<16:26:13, 5.87s/it]
{'loss': 0.5088, 'learning_rate': 1.9178718950406304e-05, 'epoch': 0.16}
+
16%|█▌ | 1865/11952 [3:10:02<16:26:13, 5.87s/it]
16%|█▌ | 1866/11952 [3:10:08<16:28:35, 5.88s/it]
{'loss': 0.4973, 'learning_rate': 1.917764311507861e-05, 'epoch': 0.16}
+
16%|█▌ | 1866/11952 [3:10:08<16:28:35, 5.88s/it]
16%|█▌ | 1867/11952 [3:10:14<16:26:47, 5.87s/it]
{'loss': 0.5177, 'learning_rate': 1.9176566605782974e-05, 'epoch': 0.16}
+
16%|█▌ | 1867/11952 [3:10:14<16:26:47, 5.87s/it]
16%|█▌ | 1868/11952 [3:10:20<16:44:40, 5.98s/it]
{'loss': 0.5072, 'learning_rate': 1.9175489422598455e-05, 'epoch': 0.16}
+
16%|█▌ | 1868/11952 [3:10:20<16:44:40, 5.98s/it]
16%|█▌ | 1869/11952 [3:10:26<16:35:41, 5.92s/it]
{'loss': 0.5095, 'learning_rate': 1.9174411565604157e-05, 'epoch': 0.16}
+
16%|█▌ | 1869/11952 [3:10:26<16:35:41, 5.92s/it]
16%|█▌ | 1870/11952 [3:10:32<16:24:12, 5.86s/it]
{'loss': 0.4966, 'learning_rate': 1.917333303487923e-05, 'epoch': 0.16}
+
16%|█▌ | 1870/11952 [3:10:32<16:24:12, 5.86s/it]
16%|█▌ | 1871/11952 [3:10:38<16:37:47, 5.94s/it]
{'loss': 0.5067, 'learning_rate': 1.9172253830502883e-05, 'epoch': 0.16}
+
16%|█▌ | 1871/11952 [3:10:38<16:37:47, 5.94s/it]
16%|█▌ | 1872/11952 [3:10:44<16:20:40, 5.84s/it]
{'loss': 0.5058, 'learning_rate': 1.9171173952554367e-05, 'epoch': 0.16}
+
16%|█▌ | 1872/11952 [3:10:44<16:20:40, 5.84s/it]
16%|█▌ | 1873/11952 [3:10:49<16:22:26, 5.85s/it]
{'loss': 0.5126, 'learning_rate': 1.917009340111298e-05, 'epoch': 0.16}
+
16%|█▌ | 1873/11952 [3:10:49<16:22:26, 5.85s/it]
16%|█▌ | 1874/11952 [3:10:55<16:09:45, 5.77s/it]
{'loss': 0.5041, 'learning_rate': 1.916901217625807e-05, 'epoch': 0.16}
+
16%|█▌ | 1874/11952 [3:10:55<16:09:45, 5.77s/it]
16%|█▌ | 1875/11952 [3:11:01<15:56:27, 5.69s/it]
{'loss': 0.4989, 'learning_rate': 1.916793027806905e-05, 'epoch': 0.16}
+
16%|█▌ | 1875/11952 [3:11:01<15:56:27, 5.69s/it]
16%|█▌ | 1876/11952 [3:11:06<15:46:46, 5.64s/it]
{'loss': 0.5211, 'learning_rate': 1.9166847706625357e-05, 'epoch': 0.16}
+
16%|█▌ | 1876/11952 [3:11:06<15:46:46, 5.64s/it]
16%|█▌ | 1877/11952 [3:11:12<15:45:52, 5.63s/it]
{'loss': 0.499, 'learning_rate': 1.91657644620065e-05, 'epoch': 0.16}
+
16%|█▌ | 1877/11952 [3:11:12<15:45:52, 5.63s/it]
16%|█▌ | 1878/11952 [3:11:18<16:00:57, 5.72s/it]
{'loss': 0.4914, 'learning_rate': 1.9164680544292023e-05, 'epoch': 0.16}
+
16%|█▌ | 1878/11952 [3:11:18<16:00:57, 5.72s/it]
16%|█▌ | 1879/11952 [3:11:23<15:49:27, 5.66s/it]
{'loss': 0.5074, 'learning_rate': 1.9163595953561523e-05, 'epoch': 0.16}
+
16%|█▌ | 1879/11952 [3:11:23<15:49:27, 5.66s/it]
16%|█▌ | 1880/11952 [3:11:29<16:08:05, 5.77s/it]
{'loss': 0.534, 'learning_rate': 1.9162510689894653e-05, 'epoch': 0.16}
+
16%|█▌ | 1880/11952 [3:11:29<16:08:05, 5.77s/it]
16%|█▌ | 1881/11952 [3:11:35<16:34:18, 5.92s/it]
{'loss': 0.5084, 'learning_rate': 1.916142475337111e-05, 'epoch': 0.16}
+
16%|█▌ | 1881/11952 [3:11:35<16:34:18, 5.92s/it]
16%|█▌ | 1882/11952 [3:11:41<16:26:38, 5.88s/it]
{'loss': 0.5069, 'learning_rate': 1.9160338144070635e-05, 'epoch': 0.16}
+
16%|█▌ | 1882/11952 [3:11:41<16:26:38, 5.88s/it]
16%|█▌ | 1883/11952 [3:11:47<16:22:06, 5.85s/it]
{'loss': 0.5611, 'learning_rate': 1.9159250862073028e-05, 'epoch': 0.16}
+
16%|█▌ | 1883/11952 [3:11:47<16:22:06, 5.85s/it]
16%|█▌ | 1884/11952 [3:11:53<16:26:59, 5.88s/it]
{'loss': 0.4864, 'learning_rate': 1.9158162907458135e-05, 'epoch': 0.16}
+
16%|█▌ | 1884/11952 [3:11:53<16:26:59, 5.88s/it]
16%|█▌ | 1885/11952 [3:11:59<16:12:59, 5.80s/it]
{'loss': 0.5034, 'learning_rate': 1.9157074280305847e-05, 'epoch': 0.16}
+
16%|█▌ | 1885/11952 [3:11:59<16:12:59, 5.80s/it]
16%|█▌ | 1886/11952 [3:12:04<16:02:58, 5.74s/it]
{'loss': 0.5303, 'learning_rate': 1.9155984980696112e-05, 'epoch': 0.16}
+
16%|█▌ | 1886/11952 [3:12:04<16:02:58, 5.74s/it]
16%|█▌ | 1887/11952 [3:12:10<16:07:10, 5.77s/it]
{'loss': 0.4934, 'learning_rate': 1.9154895008708923e-05, 'epoch': 0.16}
+
16%|█▌ | 1887/11952 [3:12:10<16:07:10, 5.77s/it]
16%|█▌ | 1888/11952 [3:12:16<16:04:27, 5.75s/it]
{'loss': 0.4889, 'learning_rate': 1.9153804364424325e-05, 'epoch': 0.16}
+
16%|█▌ | 1888/11952 [3:12:16<16:04:27, 5.75s/it]
16%|█▌ | 1889/11952 [3:12:21<16:01:51, 5.74s/it]
{'loss': 0.5199, 'learning_rate': 1.9152713047922406e-05, 'epoch': 0.16}
+
16%|█▌ | 1889/11952 [3:12:21<16:01:51, 5.74s/it]
16%|█▌ | 1890/11952 [3:12:27<16:20:10, 5.84s/it]
{'loss': 0.5035, 'learning_rate': 1.9151621059283306e-05, 'epoch': 0.16}
+
16%|█▌ | 1890/11952 [3:12:27<16:20:10, 5.84s/it]
16%|█▌ | 1891/11952 [3:12:33<16:15:20, 5.82s/it]
{'loss': 0.5213, 'learning_rate': 1.9150528398587226e-05, 'epoch': 0.16}
+
16%|█▌ | 1891/11952 [3:12:33<16:15:20, 5.82s/it]
16%|█▌ | 1892/11952 [3:12:39<16:19:26, 5.84s/it]
{'loss': 0.4933, 'learning_rate': 1.9149435065914395e-05, 'epoch': 0.16}
+
16%|█▌ | 1892/11952 [3:12:39<16:19:26, 5.84s/it]
16%|█▌ | 1893/11952 [3:12:45<16:26:54, 5.89s/it]
{'loss': 0.4935, 'learning_rate': 1.9148341061345114e-05, 'epoch': 0.16}
+
16%|█▌ | 1893/11952 [3:12:45<16:26:54, 5.89s/it]
16%|█▌ | 1894/11952 [3:12:51<16:20:42, 5.85s/it]
{'loss': 0.5199, 'learning_rate': 1.9147246384959715e-05, 'epoch': 0.16}
+
16%|█▌ | 1894/11952 [3:12:51<16:20:42, 5.85s/it]
16%|█▌ | 1895/11952 [3:12:57<16:30:47, 5.91s/it]
{'loss': 0.5242, 'learning_rate': 1.9146151036838583e-05, 'epoch': 0.16}
+
16%|█▌ | 1895/11952 [3:12:57<16:30:47, 5.91s/it]
16%|█▌ | 1896/11952 [3:13:03<16:17:16, 5.83s/it]
{'loss': 0.4793, 'learning_rate': 1.9145055017062165e-05, 'epoch': 0.16}
+
16%|█▌ | 1896/11952 [3:13:03<16:17:16, 5.83s/it]
16%|█▌ | 1897/11952 [3:13:09<16:34:13, 5.93s/it]
{'loss': 0.5142, 'learning_rate': 1.914395832571094e-05, 'epoch': 0.16}
+
16%|█▌ | 1897/11952 [3:13:09<16:34:13, 5.93s/it]
16%|█▌ | 1898/11952 [3:13:14<16:21:53, 5.86s/it]
{'loss': 0.4923, 'learning_rate': 1.914286096286545e-05, 'epoch': 0.16}
+
16%|█▌ | 1898/11952 [3:13:14<16:21:53, 5.86s/it]
16%|█▌ | 1899/11952 [3:13:20<16:22:50, 5.87s/it]
{'loss': 0.4866, 'learning_rate': 1.9141762928606282e-05, 'epoch': 0.16}
+
16%|█▌ | 1899/11952 [3:13:20<16:22:50, 5.87s/it]7 AutoResumeHook: Checking whether to suspend...
+4 5AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
16%|█▌ | 1900/11952 [3:13:26<16:21:41, 5.86s/it]
{'loss': 0.4988, 'learning_rate': 1.9140664223014064e-05, 'epoch': 0.16}
+
16%|█▌ | 1900/11952 [3:13:26<16:21:41, 5.86s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-1900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
16%|█▌ | 1901/11952 [3:14:00<40:03:21, 14.35s/it]
{'loss': 0.4838, 'learning_rate': 1.9139564846169486e-05, 'epoch': 0.16}
+
16%|█▌ | 1901/11952 [3:14:00<40:03:21, 14.35s/it]
16%|█▌ | 1902/11952 [3:14:06<33:03:23, 11.84s/it]
{'loss': 0.5151, 'learning_rate': 1.913846479815328e-05, 'epoch': 0.16}
+
16%|█▌ | 1902/11952 [3:14:06<33:03:23, 11.84s/it]
16%|█▌ | 1903/11952 [3:14:12<28:04:34, 10.06s/it]
{'loss': 0.493, 'learning_rate': 1.913736407904623e-05, 'epoch': 0.16}
+
16%|█▌ | 1903/11952 [3:14:12<28:04:34, 10.06s/it]
16%|█▌ | 1904/11952 [3:14:18<24:48:47, 8.89s/it]
{'loss': 0.4959, 'learning_rate': 1.9136262688929167e-05, 'epoch': 0.16}
+
16%|█▌ | 1904/11952 [3:14:18<24:48:47, 8.89s/it]
16%|█▌ | 1905/11952 [3:14:24<22:13:26, 7.96s/it]
{'loss': 0.5162, 'learning_rate': 1.913516062788297e-05, 'epoch': 0.16}
+
16%|█▌ | 1905/11952 [3:14:24<22:13:26, 7.96s/it]
16%|█▌ | 1906/11952 [3:14:30<20:26:00, 7.32s/it]
{'loss': 0.4908, 'learning_rate': 1.9134057895988574e-05, 'epoch': 0.16}
+
16%|█▌ | 1906/11952 [3:14:30<20:26:00, 7.32s/it]
16%|█▌ | 1907/11952 [3:14:36<19:16:02, 6.91s/it]
{'loss': 0.5083, 'learning_rate': 1.913295449332696e-05, 'epoch': 0.16}
+
16%|█▌ | 1907/11952 [3:14:36<19:16:02, 6.91s/it]
16%|█▌ | 1908/11952 [3:14:42<18:28:12, 6.62s/it]
{'loss': 0.5152, 'learning_rate': 1.913185041997915e-05, 'epoch': 0.16}
+
16%|█▌ | 1908/11952 [3:14:42<18:28:12, 6.62s/it]
16%|█▌ | 1909/11952 [3:14:48<17:43:44, 6.36s/it]
{'loss': 0.5059, 'learning_rate': 1.913074567602623e-05, 'epoch': 0.16}
+
16%|█▌ | 1909/11952 [3:14:48<17:43:44, 6.36s/it]
16%|█▌ | 1910/11952 [3:14:53<17:17:39, 6.20s/it]
{'loss': 0.509, 'learning_rate': 1.9129640261549324e-05, 'epoch': 0.16}
+
16%|█▌ | 1910/11952 [3:14:53<17:17:39, 6.20s/it]
16%|█▌ | 1911/11952 [3:14:59<16:51:39, 6.05s/it]
{'loss': 0.5031, 'learning_rate': 1.9128534176629613e-05, 'epoch': 0.16}
+
16%|█▌ | 1911/11952 [3:14:59<16:51:39, 6.05s/it]
16%|█▌ | 1912/11952 [3:15:05<16:39:04, 5.97s/it]
{'loss': 0.5084, 'learning_rate': 1.9127427421348316e-05, 'epoch': 0.16}
+
16%|█▌ | 1912/11952 [3:15:05<16:39:04, 5.97s/it]
16%|█▌ | 1913/11952 [3:15:11<16:20:06, 5.86s/it]
{'loss': 0.5322, 'learning_rate': 1.9126319995786717e-05, 'epoch': 0.16}
+
16%|█▌ | 1913/11952 [3:15:11<16:20:06, 5.86s/it]
16%|█▌ | 1914/11952 [3:15:16<16:08:09, 5.79s/it]
{'loss': 0.5027, 'learning_rate': 1.912521190002614e-05, 'epoch': 0.16}
+
16%|█▌ | 1914/11952 [3:15:16<16:08:09, 5.79s/it]
16%|█▌ | 1915/11952 [3:15:22<16:09:18, 5.79s/it]
{'loss': 0.505, 'learning_rate': 1.9124103134147945e-05, 'epoch': 0.16}
+
16%|█▌ | 1915/11952 [3:15:22<16:09:18, 5.79s/it]
16%|█▌ | 1916/11952 [3:15:28<16:13:12, 5.82s/it]
{'loss': 0.5083, 'learning_rate': 1.9122993698233576e-05, 'epoch': 0.16}
+
16%|█▌ | 1916/11952 [3:15:28<16:13:12, 5.82s/it]
16%|█▌ | 1917/11952 [3:15:33<16:03:25, 5.76s/it]
{'loss': 0.5209, 'learning_rate': 1.9121883592364486e-05, 'epoch': 0.16}
+
16%|█▌ | 1917/11952 [3:15:33<16:03:25, 5.76s/it]
16%|█▌ | 1918/11952 [3:15:39<15:55:35, 5.71s/it]
{'loss': 0.509, 'learning_rate': 1.9120772816622213e-05, 'epoch': 0.16}
+
16%|█▌ | 1918/11952 [3:15:39<15:55:35, 5.71s/it]
16%|█▌ | 1919/11952 [3:15:45<16:02:35, 5.76s/it]
{'loss': 0.5019, 'learning_rate': 1.9119661371088318e-05, 'epoch': 0.16}
+
16%|█▌ | 1919/11952 [3:15:45<16:02:35, 5.76s/it]
16%|█▌ | 1920/11952 [3:15:51<16:11:42, 5.81s/it]
{'loss': 0.4998, 'learning_rate': 1.9118549255844425e-05, 'epoch': 0.16}
+
16%|█▌ | 1920/11952 [3:15:51<16:11:42, 5.81s/it]
16%|█▌ | 1921/11952 [3:15:56<16:01:52, 5.75s/it]
{'loss': 0.4973, 'learning_rate': 1.91174364709722e-05, 'epoch': 0.16}
+
16%|█▌ | 1921/11952 [3:15:56<16:01:52, 5.75s/it]
16%|█▌ | 1922/11952 [3:16:02<16:06:10, 5.78s/it]
{'loss': 0.5233, 'learning_rate': 1.9116323016553363e-05, 'epoch': 0.16}
+
16%|█▌ | 1922/11952 [3:16:02<16:06:10, 5.78s/it]
16%|█▌ | 1923/11952 [3:16:08<16:11:21, 5.81s/it]
{'loss': 0.492, 'learning_rate': 1.911520889266968e-05, 'epoch': 0.16}
+
16%|█▌ | 1923/11952 [3:16:08<16:11:21, 5.81s/it]
16%|█▌ | 1924/11952 [3:16:14<16:17:56, 5.85s/it]
{'loss': 0.5242, 'learning_rate': 1.911409409940297e-05, 'epoch': 0.16}
+
16%|█▌ | 1924/11952 [3:16:14<16:17:56, 5.85s/it]
16%|█▌ | 1925/11952 [3:16:20<16:30:36, 5.93s/it]
{'loss': 0.5041, 'learning_rate': 1.91129786368351e-05, 'epoch': 0.16}
+
16%|█▌ | 1925/11952 [3:16:20<16:30:36, 5.93s/it]
16%|█▌ | 1926/11952 [3:16:26<16:20:03, 5.87s/it]
{'loss': 0.5142, 'learning_rate': 1.911186250504798e-05, 'epoch': 0.16}
+
16%|█▌ | 1926/11952 [3:16:26<16:20:03, 5.87s/it]
16%|█▌ | 1927/11952 [3:16:32<16:21:32, 5.87s/it]
{'loss': 0.5063, 'learning_rate': 1.9110745704123577e-05, 'epoch': 0.16}
+
16%|█▌ | 1927/11952 [3:16:32<16:21:32, 5.87s/it]
16%|█▌ | 1928/11952 [3:16:37<16:02:20, 5.76s/it]
{'loss': 0.497, 'learning_rate': 1.9109628234143905e-05, 'epoch': 0.16}
+
16%|█▌ | 1928/11952 [3:16:37<16:02:20, 5.76s/it]
16%|█▌ | 1929/11952 [3:16:43<16:08:17, 5.80s/it]
{'loss': 0.4973, 'learning_rate': 1.9108510095191025e-05, 'epoch': 0.16}
+
16%|█▌ | 1929/11952 [3:16:43<16:08:17, 5.80s/it]
16%|█▌ | 1930/11952 [3:16:49<16:13:42, 5.83s/it]
{'loss': 0.4926, 'learning_rate': 1.910739128734705e-05, 'epoch': 0.16}
+
16%|█▌ | 1930/11952 [3:16:49<16:13:42, 5.83s/it]
16%|█▌ | 1931/11952 [3:16:55<16:08:36, 5.80s/it]
{'loss': 0.5205, 'learning_rate': 1.9106271810694137e-05, 'epoch': 0.16}
+
16%|█▌ | 1931/11952 [3:16:55<16:08:36, 5.80s/it]
16%|█▌ | 1932/11952 [3:17:01<16:05:26, 5.78s/it]
{'loss': 0.4997, 'learning_rate': 1.9105151665314497e-05, 'epoch': 0.16}
+
16%|█▌ | 1932/11952 [3:17:01<16:05:26, 5.78s/it]
16%|█▌ | 1933/11952 [3:17:07<16:20:25, 5.87s/it]
{'loss': 0.5069, 'learning_rate': 1.9104030851290393e-05, 'epoch': 0.16}
+
16%|█▌ | 1933/11952 [3:17:07<16:20:25, 5.87s/it]
16%|█▌ | 1934/11952 [3:17:13<16:28:16, 5.92s/it]
{'loss': 0.5012, 'learning_rate': 1.910290936870413e-05, 'epoch': 0.16}
+
16%|█▌ | 1934/11952 [3:17:13<16:28:16, 5.92s/it]
16%|█▌ | 1935/11952 [3:17:19<16:23:14, 5.89s/it]
{'loss': 0.5198, 'learning_rate': 1.910178721763806e-05, 'epoch': 0.16}
+
16%|█▌ | 1935/11952 [3:17:19<16:23:14, 5.89s/it]
16%|█▌ | 1936/11952 [3:17:24<16:09:09, 5.81s/it]
{'loss': 0.5206, 'learning_rate': 1.91006643981746e-05, 'epoch': 0.16}
+
16%|█▌ | 1936/11952 [3:17:24<16:09:09, 5.81s/it]
16%|█▌ | 1937/11952 [3:17:30<16:14:34, 5.84s/it]
{'loss': 0.4984, 'learning_rate': 1.9099540910396194e-05, 'epoch': 0.16}
+
16%|█▌ | 1937/11952 [3:17:30<16:14:34, 5.84s/it]
16%|█▌ | 1938/11952 [3:17:36<16:15:52, 5.85s/it]
{'loss': 0.5317, 'learning_rate': 1.9098416754385355e-05, 'epoch': 0.16}
+
16%|█▌ | 1938/11952 [3:17:36<16:15:52, 5.85s/it]
16%|█▌ | 1939/11952 [3:17:42<16:11:06, 5.82s/it]
{'loss': 0.4949, 'learning_rate': 1.909729193022463e-05, 'epoch': 0.16}
+
16%|█▌ | 1939/11952 [3:17:42<16:11:06, 5.82s/it]
16%|█▌ | 1940/11952 [3:17:48<16:18:50, 5.87s/it]
{'loss': 0.4801, 'learning_rate': 1.9096166437996626e-05, 'epoch': 0.16}
+
16%|█▌ | 1940/11952 [3:17:48<16:18:50, 5.87s/it]
16%|█▌ | 1941/11952 [3:17:54<16:41:40, 6.00s/it]
{'loss': 0.5191, 'learning_rate': 1.9095040277783993e-05, 'epoch': 0.16}
+
16%|█▌ | 1941/11952 [3:17:54<16:41:40, 6.00s/it]
16%|█▌ | 1942/11952 [3:18:00<16:31:32, 5.94s/it]
{'loss': 0.5103, 'learning_rate': 1.909391344966943e-05, 'epoch': 0.16}
+
16%|█▌ | 1942/11952 [3:18:00<16:31:32, 5.94s/it]
16%|█▋ | 1943/11952 [3:18:06<16:43:33, 6.02s/it]
{'loss': 0.4988, 'learning_rate': 1.909278595373569e-05, 'epoch': 0.16}
+
16%|█▋ | 1943/11952 [3:18:06<16:43:33, 6.02s/it]
16%|█▋ | 1944/11952 [3:18:12<16:38:51, 5.99s/it]
{'loss': 0.49, 'learning_rate': 1.9091657790065565e-05, 'epoch': 0.16}
+
16%|█▋ | 1944/11952 [3:18:12<16:38:51, 5.99s/it]
16%|█▋ | 1945/11952 [3:18:18<16:34:33, 5.96s/it]
{'loss': 0.528, 'learning_rate': 1.909052895874191e-05, 'epoch': 0.16}
+
16%|█▋ | 1945/11952 [3:18:18<16:34:33, 5.96s/it]
16%|█▋ | 1946/11952 [3:18:24<16:24:51, 5.91s/it]
{'loss': 0.4989, 'learning_rate': 1.9089399459847615e-05, 'epoch': 0.16}
+
16%|█▋ | 1946/11952 [3:18:24<16:24:51, 5.91s/it]
16%|█▋ | 1947/11952 [3:18:29<16:16:53, 5.86s/it]
{'loss': 0.4941, 'learning_rate': 1.9088269293465634e-05, 'epoch': 0.16}
+
16%|█▋ | 1947/11952 [3:18:29<16:16:53, 5.86s/it]
16%|█▋ | 1948/11952 [3:18:35<16:25:05, 5.91s/it]
{'loss': 0.5119, 'learning_rate': 1.9087138459678956e-05, 'epoch': 0.16}
+
16%|█▋ | 1948/11952 [3:18:35<16:25:05, 5.91s/it]
16%|█▋ | 1949/11952 [3:18:41<16:16:21, 5.86s/it]
{'loss': 0.5093, 'learning_rate': 1.908600695857062e-05, 'epoch': 0.16}
+
16%|█▋ | 1949/11952 [3:18:41<16:16:21, 5.86s/it]41 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
16%|█▋ | 1950/11952 [3:18:47<16:17:11, 5.86s/it]
{'loss': 0.5122, 'learning_rate': 1.9084874790223735e-05, 'epoch': 0.16}
+
16%|█▋ | 1950/11952 [3:18:47<16:17:11, 5.86s/it]
16%|█▋ | 1951/11952 [3:18:53<16:06:12, 5.80s/it]
{'loss': 0.4985, 'learning_rate': 1.9083741954721423e-05, 'epoch': 0.16}
+
16%|█▋ | 1951/11952 [3:18:53<16:06:12, 5.80s/it]
16%|█▋ | 1952/11952 [3:18:58<16:09:09, 5.81s/it]
{'loss': 0.5291, 'learning_rate': 1.908260845214689e-05, 'epoch': 0.16}
+
16%|█▋ | 1952/11952 [3:18:58<16:09:09, 5.81s/it]
16%|█▋ | 1953/11952 [3:19:04<16:05:21, 5.79s/it]
{'loss': 0.5037, 'learning_rate': 1.9081474282583367e-05, 'epoch': 0.16}
+
16%|█▋ | 1953/11952 [3:19:04<16:05:21, 5.79s/it]
16%|█▋ | 1954/11952 [3:19:10<16:13:14, 5.84s/it]
{'loss': 0.4901, 'learning_rate': 1.9080339446114148e-05, 'epoch': 0.16}
+
16%|█▋ | 1954/11952 [3:19:10<16:13:14, 5.84s/it]
16%|█▋ | 1955/11952 [3:19:16<16:09:47, 5.82s/it]
{'loss': 0.4888, 'learning_rate': 1.907920394282256e-05, 'epoch': 0.16}
+
16%|█▋ | 1955/11952 [3:19:16<16:09:47, 5.82s/it]
16%|█▋ | 1956/11952 [3:19:22<16:20:16, 5.88s/it]
{'loss': 0.4985, 'learning_rate': 1.9078067772792006e-05, 'epoch': 0.16}
+
16%|█▋ | 1956/11952 [3:19:22<16:20:16, 5.88s/it]
16%|█▋ | 1957/11952 [3:19:28<16:19:33, 5.88s/it]
{'loss': 0.5106, 'learning_rate': 1.907693093610591e-05, 'epoch': 0.16}
+
16%|█▋ | 1957/11952 [3:19:28<16:19:33, 5.88s/it]
16%|█▋ | 1958/11952 [3:19:34<16:31:21, 5.95s/it]
{'loss': 0.5031, 'learning_rate': 1.9075793432847763e-05, 'epoch': 0.16}
+
16%|█▋ | 1958/11952 [3:19:34<16:31:21, 5.95s/it]
16%|█▋ | 1959/11952 [3:19:40<16:30:55, 5.95s/it]
{'loss': 0.5117, 'learning_rate': 1.907465526310109e-05, 'epoch': 0.16}
+
16%|█▋ | 1959/11952 [3:19:40<16:30:55, 5.95s/it]
16%|█▋ | 1960/11952 [3:19:46<16:15:40, 5.86s/it]
{'loss': 0.5219, 'learning_rate': 1.9073516426949485e-05, 'epoch': 0.16}
+
16%|█▋ | 1960/11952 [3:19:46<16:15:40, 5.86s/it]
16%|█▋ | 1961/11952 [3:19:52<16:42:06, 6.02s/it]
{'loss': 0.5064, 'learning_rate': 1.9072376924476568e-05, 'epoch': 0.16}
+
16%|█▋ | 1961/11952 [3:19:52<16:42:06, 6.02s/it]
16%|█▋ | 1962/11952 [3:19:58<16:48:24, 6.06s/it]
{'loss': 0.5332, 'learning_rate': 1.9071236755766028e-05, 'epoch': 0.16}
+
16%|█▋ | 1962/11952 [3:19:58<16:48:24, 6.06s/it]
16%|█▋ | 1963/11952 [3:20:04<16:29:23, 5.94s/it]
{'loss': 0.5191, 'learning_rate': 1.9070095920901588e-05, 'epoch': 0.16}
+
16%|█▋ | 1963/11952 [3:20:04<16:29:23, 5.94s/it]
16%|█▋ | 1964/11952 [3:20:10<16:28:30, 5.94s/it]
{'loss': 0.5143, 'learning_rate': 1.906895441996703e-05, 'epoch': 0.16}
+
16%|█▋ | 1964/11952 [3:20:10<16:28:30, 5.94s/it]
16%|█▋ | 1965/11952 [3:20:16<16:33:07, 5.97s/it]
{'loss': 0.491, 'learning_rate': 1.906781225304618e-05, 'epoch': 0.16}
+
16%|█▋ | 1965/11952 [3:20:16<16:33:07, 5.97s/it]
16%|█▋ | 1966/11952 [3:20:22<16:22:35, 5.90s/it]
{'loss': 0.5089, 'learning_rate': 1.9066669420222915e-05, 'epoch': 0.16}
+
16%|█▋ | 1966/11952 [3:20:22<16:22:35, 5.90s/it]
16%|█▋ | 1967/11952 [3:20:28<16:34:57, 5.98s/it]
{'loss': 0.5046, 'learning_rate': 1.9065525921581158e-05, 'epoch': 0.16}
+
16%|█▋ | 1967/11952 [3:20:28<16:34:57, 5.98s/it]
16%|█▋ | 1968/11952 [3:20:33<16:10:19, 5.83s/it]
{'loss': 0.501, 'learning_rate': 1.9064381757204884e-05, 'epoch': 0.16}
+
16%|█▋ | 1968/11952 [3:20:33<16:10:19, 5.83s/it]
16%|█▋ | 1969/11952 [3:20:39<15:58:23, 5.76s/it]
{'loss': 0.5061, 'learning_rate': 1.9063236927178116e-05, 'epoch': 0.16}
+
16%|█▋ | 1969/11952 [3:20:39<15:58:23, 5.76s/it]WARNING: tokenization mismatch: 1 vs. 1473. [[{'from': 'human', 'value': 'ASSISTANT: Du bist eine auf Kundenfeedback spezialisierte Agentur mit den folgenden Kenntnissen und Eigenschaften.\n\nKENNTNISSE: Kundenfeedback, wissenschaftliche Datenerhebung, Fragebogendesign, Benutzerfreundlichkeit, Kundenbindung, Service-Qualitätsevaluation.\n\nEIGENSCHAFTEN: Präzision, Effizienz, Empathie, Anpassungsfähigkeit, Datenorientierung, Kundenfokus.\n\nAUFGABE: Nutze dein Wissen, um ein Kundenfeedback-Formular zu entwickeln, das die Service-Qualität einer Steuerberatung evaluiert. Das Formular soll auf wissenschaftlich fundierten Datenniveaus basieren und dabei darauf achten, dass es nur so lang ist, dass es tatsächlich vom Kunden ausgefüllt wird. Konzentriere dich auf die Gestaltung eines benutzerfreundlichen und effizienten Fragebogens, der aussagekräftige Informationen über die Steuerberatung liefert.\n\nOUTPUT: Ein strukturiertes Kundenfeedback-Formular, das auf wissenschaftlich fundierten Datenniveaus basiert und eine angemessene Länge hat, um von Kunden tatsächlich ausgefüllt zu werden, und speziell auf die Evaluation der Service-Qualität einer Steuerberatung abzielt.'}, {'from': 'gpt', 'value': 'Kundenfeedback-Formular: Steuerberatung Service-Qualität\n\nTeil 1: Allgemeine Informationen\n(Bitte füllen Sie die folgenden Informationen aus.)\n\n1. Name (Optional):\n2. Alter:\n☐ Unter 25\n☐ 25-34\n☐ 35-44\n☐ 45-54\n☐ 55-64\n☐ 65 oder älter\n3. Geschlecht:\n☐ Männlich\n☐ Weiblich\n☐ Andere\n☐ Lieber nicht angeben\n\nTeil 2: Service-Qualität\n(Bitte bewerten Sie die folgenden Aspekte der Steuerberatung auf einer Skala von 1 bis 5, wobei 1 = sehr unzufrieden und 5 = sehr zufrieden.)\n\n1. Fachliche Kompetenz des Steuerberaters:\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n2. Freundlichkeit und Hilfsbereitschaft des Personals:\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n3. Reaktionsgeschwindigkeit auf Anfragen und Probleme:\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n4. Verständlichkeit der erbrachten Informationen und Beratung:\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n5. Qualität der bereitgestellten Dienstleistungen und Lösungen:\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n6. Preis-Leistungs-Verhältnis:\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n\nTeil 3: Kundenbindung und Zufriedenheit\n(Bitte beantworten Sie die folgenden Fragen.)\n\n1. Wie wahrscheinlich ist es, dass Sie die Steuerberatung an Freunde, Familie oder Kollegen weiterempfehlen? (Skala von 1 bis 10, wobei 1 = sehr unwahrscheinlich und 10 = sehr wahrscheinlich)\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n☐ 6\n☐ 7\n☐ 8\n☐ 9\n☐ 10\n2. Wie zufrieden sind Sie insgesamt mit der Steuerberatung? (Skala von 1 bis 5, wobei 1 = sehr unzufrieden und 5 = sehr zufrieden)\n☐ 1\n☐ 2\n☐ 3\n☐ 4\n☐ 5\n\nTeil 4: Offene Fragen\n(Bitte teilen Sie uns Ihre Gedanken und Erfahrungen mit.)\n\n1. Was hat Ihnen am meisten an der Steuerberatung gefallen? (Optional)\n2. Was könnte die Steuerberatung verbessern, um Ihre Zufriedenheit zu erhöhen? (Optional)\n\nVielen Dank für Ihre Zeit und Ihr'}, {'from': 'human', 'value': 'Continue.'}, {'from': 'gpt', 'value': 'wertvolles Feedback! Ihre Meinung hilft uns dabei, den Service und die Qualität unserer Steuerberatung kontinuierlich zu verbessern. Wenn Sie Fragen oder Anmerkungen haben oder zusätzliche Informationen benötigen, zögern Sie bitte nicht, uns zu kontaktieren.\n\nTeil 5: Kontaktaufnahme (Optional)\n(Bitte geben Sie Ihre Kontaktinformationen an, falls Sie möchten, dass wir Ihnen bezüglich Ihres Feedbacks antworten oder weitere Informationen anbieten.)\n\n1. Name:\n2. E-Mail-Adresse:\n3. Telefonnummer:\n\nHinweis zum Datenschutz: Ihre persönlichen Daten werden vertraulich behandelt und nur für interne Zwecke verwendet. Sie werden nicht an Dritte weitergegeben.\n\nBitte klicken Sie auf "Absenden", um das Formular abzuschließen. Nochmals vielen Dank für Ihre Rückmeldung und Ihre Unterstützung bei der Verbesserung unserer Steuerberatung!'}]] (ignored)
+
16%|█▋ | 1970/11952 [3:20:45<16:06:08, 5.81s/it]
{'loss': 0.5049, 'learning_rate': 1.9062091431584924e-05, 'epoch': 0.16}
+
16%|█▋ | 1970/11952 [3:20:45<16:06:08, 5.81s/it]
16%|█▋ | 1971/11952 [3:20:50<15:50:40, 5.71s/it]
{'loss': 0.4905, 'learning_rate': 1.9060945270509427e-05, 'epoch': 0.16}
+
16%|█▋ | 1971/11952 [3:20:50<15:50:40, 5.71s/it]
16%|█▋ | 1972/11952 [3:20:56<15:52:52, 5.73s/it]
{'loss': 0.4926, 'learning_rate': 1.90597984440358e-05, 'epoch': 0.16}
+
16%|█▋ | 1972/11952 [3:20:56<15:52:52, 5.73s/it]
17%|█▋ | 1973/11952 [3:21:02<15:51:55, 5.72s/it]
{'loss': 0.4932, 'learning_rate': 1.9058650952248257e-05, 'epoch': 0.17}
+
17%|█▋ | 1973/11952 [3:21:02<15:51:55, 5.72s/it]
17%|█▋ | 1974/11952 [3:21:07<15:49:06, 5.71s/it]
{'loss': 0.5016, 'learning_rate': 1.9057502795231066e-05, 'epoch': 0.17}
+
17%|█▋ | 1974/11952 [3:21:07<15:49:06, 5.71s/it]
17%|█▋ | 1975/11952 [3:21:13<15:53:40, 5.74s/it]
{'loss': 0.4863, 'learning_rate': 1.9056353973068544e-05, 'epoch': 0.17}
+
17%|█▋ | 1975/11952 [3:21:13<15:53:40, 5.74s/it]
17%|█▋ | 1976/11952 [3:21:19<16:05:00, 5.80s/it]
{'loss': 0.5144, 'learning_rate': 1.905520448584505e-05, 'epoch': 0.17}
+
17%|█▋ | 1976/11952 [3:21:19<16:05:00, 5.80s/it]
17%|█▋ | 1977/11952 [3:21:25<16:01:09, 5.78s/it]
{'loss': 0.4898, 'learning_rate': 1.9054054333645006e-05, 'epoch': 0.17}
+
17%|█▋ | 1977/11952 [3:21:25<16:01:09, 5.78s/it]
17%|█▋ | 1978/11952 [3:21:31<16:16:02, 5.87s/it]
{'loss': 0.4975, 'learning_rate': 1.905290351655287e-05, 'epoch': 0.17}
+
17%|█▋ | 1978/11952 [3:21:31<16:16:02, 5.87s/it]
17%|█▋ | 1979/11952 [3:21:37<16:15:59, 5.87s/it]
{'loss': 0.526, 'learning_rate': 1.9051752034653153e-05, 'epoch': 0.17}
+
17%|█▋ | 1979/11952 [3:21:37<16:15:59, 5.87s/it]
17%|█▋ | 1980/11952 [3:21:43<16:16:17, 5.87s/it]
{'loss': 0.5172, 'learning_rate': 1.9050599888030413e-05, 'epoch': 0.17}
+
17%|█▋ | 1980/11952 [3:21:43<16:16:17, 5.87s/it]
17%|█▋ | 1981/11952 [3:21:48<16:01:41, 5.79s/it]
{'loss': 0.4884, 'learning_rate': 1.9049447076769265e-05, 'epoch': 0.17}
+
17%|█▋ | 1981/11952 [3:21:48<16:01:41, 5.79s/it]
17%|█▋ | 1982/11952 [3:21:54<15:48:58, 5.71s/it]
{'loss': 0.5012, 'learning_rate': 1.904829360095436e-05, 'epoch': 0.17}
+
17%|█▋ | 1982/11952 [3:21:54<15:48:58, 5.71s/it]
17%|█▋ | 1983/11952 [3:21:59<15:44:10, 5.68s/it]
{'loss': 0.5017, 'learning_rate': 1.904713946067041e-05, 'epoch': 0.17}
+
17%|█▋ | 1983/11952 [3:21:59<15:44:10, 5.68s/it]
17%|█▋ | 1984/11952 [3:22:06<16:20:08, 5.90s/it]
{'loss': 0.5158, 'learning_rate': 1.904598465600217e-05, 'epoch': 0.17}
+
17%|█▋ | 1984/11952 [3:22:06<16:20:08, 5.90s/it]
17%|█▋ | 1985/11952 [3:22:12<16:39:23, 6.02s/it]
{'loss': 0.5017, 'learning_rate': 1.904482918703444e-05, 'epoch': 0.17}
+
17%|█▋ | 1985/11952 [3:22:12<16:39:23, 6.02s/it]
17%|█▋ | 1986/11952 [3:22:18<16:25:06, 5.93s/it]
{'loss': 0.496, 'learning_rate': 1.9043673053852073e-05, 'epoch': 0.17}
+
17%|█▋ | 1986/11952 [3:22:18<16:25:06, 5.93s/it]
17%|█▋ | 1987/11952 [3:22:24<16:30:55, 5.97s/it]
{'loss': 0.5146, 'learning_rate': 1.9042516256539974e-05, 'epoch': 0.17}
+
17%|█▋ | 1987/11952 [3:22:24<16:30:55, 5.97s/it]
17%|█▋ | 1988/11952 [3:22:30<16:18:37, 5.89s/it]
{'loss': 0.497, 'learning_rate': 1.904135879518309e-05, 'epoch': 0.17}
+
17%|█▋ | 1988/11952 [3:22:30<16:18:37, 5.89s/it]
17%|█▋ | 1989/11952 [3:22:35<16:18:27, 5.89s/it]
{'loss': 0.5092, 'learning_rate': 1.9040200669866426e-05, 'epoch': 0.17}
+
17%|█▋ | 1989/11952 [3:22:35<16:18:27, 5.89s/it]
17%|█▋ | 1990/11952 [3:22:41<16:00:23, 5.78s/it]
{'loss': 0.4902, 'learning_rate': 1.903904188067502e-05, 'epoch': 0.17}
+
17%|█▋ | 1990/11952 [3:22:41<16:00:23, 5.78s/it]
17%|█▋ | 1991/11952 [3:22:47<16:02:28, 5.80s/it]
{'loss': 0.5079, 'learning_rate': 1.903788242769398e-05, 'epoch': 0.17}
+
17%|█▋ | 1991/11952 [3:22:47<16:02:28, 5.80s/it]
17%|█▋ | 1992/11952 [3:22:53<16:12:20, 5.86s/it]
{'loss': 0.5132, 'learning_rate': 1.9036722311008442e-05, 'epoch': 0.17}
+
17%|█▋ | 1992/11952 [3:22:53<16:12:20, 5.86s/it]
17%|█▋ | 1993/11952 [3:22:59<16:09:28, 5.84s/it]
{'loss': 0.5149, 'learning_rate': 1.9035561530703605e-05, 'epoch': 0.17}
+
17%|█▋ | 1993/11952 [3:22:59<16:09:28, 5.84s/it]
17%|█▋ | 1994/11952 [3:23:04<15:55:50, 5.76s/it]
{'loss': 0.4911, 'learning_rate': 1.903440008686471e-05, 'epoch': 0.17}
+
17%|█▋ | 1994/11952 [3:23:04<15:55:50, 5.76s/it]
17%|█▋ | 1995/11952 [3:23:10<16:10:33, 5.85s/it]
{'loss': 0.5114, 'learning_rate': 1.9033237979577053e-05, 'epoch': 0.17}
+
17%|█▋ | 1995/11952 [3:23:10<16:10:33, 5.85s/it]
17%|█▋ | 1996/11952 [3:23:16<15:58:08, 5.77s/it]
{'loss': 0.5084, 'learning_rate': 1.9032075208925967e-05, 'epoch': 0.17}
+
17%|█▋ | 1996/11952 [3:23:16<15:58:08, 5.77s/it]
17%|█▋ | 1997/11952 [3:23:22<15:55:52, 5.76s/it]
{'loss': 0.4958, 'learning_rate': 1.903091177499685e-05, 'epoch': 0.17}
+
17%|█▋ | 1997/11952 [3:23:22<15:55:52, 5.76s/it]
17%|█▋ | 1998/11952 [3:23:27<16:03:53, 5.81s/it]
{'loss': 0.5, 'learning_rate': 1.9029747677875132e-05, 'epoch': 0.17}
+
17%|█▋ | 1998/11952 [3:23:27<16:03:53, 5.81s/it]
17%|█▋ | 1999/11952 [3:23:33<15:57:24, 5.77s/it]
{'loss': 0.5156, 'learning_rate': 1.90285829176463e-05, 'epoch': 0.17}
+
17%|█▋ | 1999/11952 [3:23:33<15:57:24, 5.77s/it]5 AutoResumeHook: Checking whether to suspend...
+74 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
17%|█▋ | 2000/11952 [3:23:39<15:57:45, 5.77s/it]
{'loss': 0.501, 'learning_rate': 1.9027417494395896e-05, 'epoch': 0.17}
+
17%|█▋ | 2000/11952 [3:23:39<15:57:45, 5.77s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
17%|█▋ | 2001/11952 [3:24:11<37:45:53, 13.66s/it]
{'loss': 0.4945, 'learning_rate': 1.9026251408209494e-05, 'epoch': 0.17}
+
17%|█▋ | 2001/11952 [3:24:11<37:45:53, 13.66s/it]
17%|█▋ | 2002/11952 [3:24:17<31:15:36, 11.31s/it]
{'loss': 0.4951, 'learning_rate': 1.9025084659172733e-05, 'epoch': 0.17}
+
17%|█▋ | 2002/11952 [3:24:17<31:15:36, 11.31s/it]
17%|█▋ | 2003/11952 [3:24:23<26:34:32, 9.62s/it]
{'loss': 0.4994, 'learning_rate': 1.9023917247371292e-05, 'epoch': 0.17}
+
17%|█▋ | 2003/11952 [3:24:23<26:34:32, 9.62s/it]
17%|█▋ | 2004/11952 [3:24:28<23:26:01, 8.48s/it]
{'loss': 0.5328, 'learning_rate': 1.9022749172890904e-05, 'epoch': 0.17}
+
17%|█▋ | 2004/11952 [3:24:28<23:26:01, 8.48s/it]
17%|█▋ | 2005/11952 [3:24:34<21:10:04, 7.66s/it]
{'loss': 0.5034, 'learning_rate': 1.9021580435817343e-05, 'epoch': 0.17}
+
17%|█▋ | 2005/11952 [3:24:34<21:10:04, 7.66s/it]
17%|█▋ | 2006/11952 [3:24:40<19:48:43, 7.17s/it]
{'loss': 0.5178, 'learning_rate': 1.902041103623644e-05, 'epoch': 0.17}
+
17%|█▋ | 2006/11952 [3:24:40<19:48:43, 7.17s/it]
17%|█▋ | 2007/11952 [3:24:46<18:33:52, 6.72s/it]
{'loss': 0.4987, 'learning_rate': 1.901924097423407e-05, 'epoch': 0.17}
+
17%|█▋ | 2007/11952 [3:24:46<18:33:52, 6.72s/it]
17%|█▋ | 2008/11952 [3:24:52<18:07:20, 6.56s/it]
{'loss': 0.4948, 'learning_rate': 1.901807024989615e-05, 'epoch': 0.17}
+
17%|█▋ | 2008/11952 [3:24:52<18:07:20, 6.56s/it]
17%|█▋ | 2009/11952 [3:24:58<17:27:54, 6.32s/it]
{'loss': 0.4785, 'learning_rate': 1.9016898863308667e-05, 'epoch': 0.17}
+
17%|█▋ | 2009/11952 [3:24:58<17:27:54, 6.32s/it]
17%|█▋ | 2010/11952 [3:25:03<16:59:28, 6.15s/it]
{'loss': 0.496, 'learning_rate': 1.9015726814557632e-05, 'epoch': 0.17}
+
17%|█▋ | 2010/11952 [3:25:03<16:59:28, 6.15s/it]
17%|█▋ | 2011/11952 [3:25:09<16:43:39, 6.06s/it]
{'loss': 0.5314, 'learning_rate': 1.9014554103729125e-05, 'epoch': 0.17}
+
17%|█▋ | 2011/11952 [3:25:09<16:43:39, 6.06s/it]
17%|█▋ | 2012/11952 [3:25:15<16:36:26, 6.01s/it]
{'loss': 0.503, 'learning_rate': 1.9013380730909255e-05, 'epoch': 0.17}
+
17%|█▋ | 2012/11952 [3:25:15<16:36:26, 6.01s/it]
17%|█▋ | 2013/11952 [3:25:21<16:15:43, 5.89s/it]
{'loss': 0.5094, 'learning_rate': 1.901220669618419e-05, 'epoch': 0.17}
+
17%|█▋ | 2013/11952 [3:25:21<16:15:43, 5.89s/it]
17%|█▋ | 2014/11952 [3:25:26<15:55:55, 5.77s/it]
{'loss': 0.5112, 'learning_rate': 1.9011031999640152e-05, 'epoch': 0.17}
+
17%|█▋ | 2014/11952 [3:25:26<15:55:55, 5.77s/it]
17%|█▋ | 2015/11952 [3:25:32<16:02:49, 5.81s/it]
{'loss': 0.5092, 'learning_rate': 1.9009856641363406e-05, 'epoch': 0.17}
+
17%|█▋ | 2015/11952 [3:25:32<16:02:49, 5.81s/it]
17%|█▋ | 2016/11952 [3:25:38<16:12:41, 5.87s/it]
{'loss': 0.5008, 'learning_rate': 1.9008680621440262e-05, 'epoch': 0.17}
+
17%|█▋ | 2016/11952 [3:25:38<16:12:41, 5.87s/it]
17%|█▋ | 2017/11952 [3:25:44<16:15:14, 5.89s/it]
{'loss': 0.503, 'learning_rate': 1.9007503939957085e-05, 'epoch': 0.17}
+
17%|█▋ | 2017/11952 [3:25:44<16:15:14, 5.89s/it]
17%|█▋ | 2018/11952 [3:25:50<16:06:07, 5.84s/it]
{'loss': 0.5023, 'learning_rate': 1.900632659700028e-05, 'epoch': 0.17}
+
17%|█▋ | 2018/11952 [3:25:50<16:06:07, 5.84s/it]
17%|█▋ | 2019/11952 [3:25:56<16:08:40, 5.85s/it]
{'loss': 0.4859, 'learning_rate': 1.9005148592656312e-05, 'epoch': 0.17}
+
17%|█▋ | 2019/11952 [3:25:56<16:08:40, 5.85s/it]
17%|█▋ | 2020/11952 [3:26:01<15:52:55, 5.76s/it]
{'loss': 0.4745, 'learning_rate': 1.9003969927011683e-05, 'epoch': 0.17}
+
17%|█▋ | 2020/11952 [3:26:01<15:52:55, 5.76s/it]
17%|█▋ | 2021/11952 [3:26:07<15:55:20, 5.77s/it]
{'loss': 0.5014, 'learning_rate': 1.900279060015296e-05, 'epoch': 0.17}
+
17%|█▋ | 2021/11952 [3:26:07<15:55:20, 5.77s/it]
17%|█▋ | 2022/11952 [3:26:13<15:58:34, 5.79s/it]
{'loss': 0.4822, 'learning_rate': 1.9001610612166735e-05, 'epoch': 0.17}
+
17%|█▋ | 2022/11952 [3:26:13<15:58:34, 5.79s/it]
17%|█▋ | 2023/11952 [3:26:19<16:01:11, 5.81s/it]
{'loss': 0.4995, 'learning_rate': 1.9000429963139668e-05, 'epoch': 0.17}
+
17%|█▋ | 2023/11952 [3:26:19<16:01:11, 5.81s/it]
17%|█▋ | 2024/11952 [3:26:25<15:59:59, 5.80s/it]
{'loss': 0.5026, 'learning_rate': 1.8999248653158463e-05, 'epoch': 0.17}
+
17%|█▋ | 2024/11952 [3:26:25<15:59:59, 5.80s/it]
17%|█▋ | 2025/11952 [3:26:31<16:07:28, 5.85s/it]
{'loss': 0.5068, 'learning_rate': 1.8998066682309864e-05, 'epoch': 0.17}
+
17%|█▋ | 2025/11952 [3:26:31<16:07:28, 5.85s/it]
17%|█▋ | 2026/11952 [3:26:37<16:15:46, 5.90s/it]
{'loss': 0.5157, 'learning_rate': 1.8996884050680675e-05, 'epoch': 0.17}
+
17%|█▋ | 2026/11952 [3:26:37<16:15:46, 5.90s/it]
17%|█▋ | 2027/11952 [3:26:42<16:07:38, 5.85s/it]
{'loss': 0.4847, 'learning_rate': 1.8995700758357744e-05, 'epoch': 0.17}
+
17%|█▋ | 2027/11952 [3:26:42<16:07:38, 5.85s/it]
17%|█▋ | 2028/11952 [3:26:48<15:52:55, 5.76s/it]
{'loss': 0.4887, 'learning_rate': 1.899451680542796e-05, 'epoch': 0.17}
+
17%|█▋ | 2028/11952 [3:26:48<15:52:55, 5.76s/it]
17%|█▋ | 2029/11952 [3:26:54<15:56:07, 5.78s/it]
{'loss': 0.5107, 'learning_rate': 1.8993332191978277e-05, 'epoch': 0.17}
+
17%|█▋ | 2029/11952 [3:26:54<15:56:07, 5.78s/it]
17%|█▋ | 2030/11952 [3:27:00<16:03:01, 5.82s/it]
{'loss': 0.5014, 'learning_rate': 1.8992146918095684e-05, 'epoch': 0.17}
+
17%|█▋ | 2030/11952 [3:27:00<16:03:01, 5.82s/it]
17%|█▋ | 2031/11952 [3:27:06<16:21:12, 5.93s/it]
{'loss': 0.5074, 'learning_rate': 1.8990960983867222e-05, 'epoch': 0.17}
+
17%|█▋ | 2031/11952 [3:27:06<16:21:12, 5.93s/it]
17%|█▋ | 2032/11952 [3:27:12<16:11:44, 5.88s/it]
{'loss': 0.5281, 'learning_rate': 1.898977438937998e-05, 'epoch': 0.17}
+
17%|█▋ | 2032/11952 [3:27:12<16:11:44, 5.88s/it]
17%|█▋ | 2033/11952 [3:27:17<16:06:24, 5.85s/it]
{'loss': 0.4978, 'learning_rate': 1.8988587134721103e-05, 'epoch': 0.17}
+
17%|█▋ | 2033/11952 [3:27:17<16:06:24, 5.85s/it]
17%|█▋ | 2034/11952 [3:27:23<16:15:56, 5.90s/it]
{'loss': 0.5055, 'learning_rate': 1.8987399219977768e-05, 'epoch': 0.17}
+
17%|█▋ | 2034/11952 [3:27:23<16:15:56, 5.90s/it]
17%|█▋ | 2035/11952 [3:27:29<16:19:48, 5.93s/it]
{'loss': 0.5146, 'learning_rate': 1.8986210645237216e-05, 'epoch': 0.17}
+
17%|█▋ | 2035/11952 [3:27:29<16:19:48, 5.93s/it]
17%|█▋ | 2036/11952 [3:27:35<16:12:12, 5.88s/it]
{'loss': 0.5041, 'learning_rate': 1.8985021410586732e-05, 'epoch': 0.17}
+
17%|█▋ | 2036/11952 [3:27:35<16:12:12, 5.88s/it]
17%|█▋ | 2037/11952 [3:27:41<16:11:34, 5.88s/it]
{'loss': 0.5209, 'learning_rate': 1.8983831516113645e-05, 'epoch': 0.17}
+
17%|█▋ | 2037/11952 [3:27:41<16:11:34, 5.88s/it]
17%|█▋ | 2038/11952 [3:27:47<16:14:41, 5.90s/it]
{'loss': 0.4876, 'learning_rate': 1.898264096190534e-05, 'epoch': 0.17}
+
17%|█▋ | 2038/11952 [3:27:47<16:14:41, 5.90s/it]
17%|█▋ | 2039/11952 [3:27:53<16:21:58, 5.94s/it]
{'loss': 0.5127, 'learning_rate': 1.8981449748049248e-05, 'epoch': 0.17}
+
17%|█▋ | 2039/11952 [3:27:53<16:21:58, 5.94s/it]
17%|█▋ | 2040/11952 [3:27:59<16:06:03, 5.85s/it]
{'loss': 0.5006, 'learning_rate': 1.8980257874632836e-05, 'epoch': 0.17}
+
17%|█▋ | 2040/11952 [3:27:59<16:06:03, 5.85s/it]
17%|█▋ | 2041/11952 [3:28:05<16:13:32, 5.89s/it]
{'loss': 0.4796, 'learning_rate': 1.8979065341743642e-05, 'epoch': 0.17}
+
17%|█▋ | 2041/11952 [3:28:05<16:13:32, 5.89s/it]
17%|█▋ | 2042/11952 [3:28:11<16:26:35, 5.97s/it]
{'loss': 0.4946, 'learning_rate': 1.8977872149469236e-05, 'epoch': 0.17}
+
17%|█▋ | 2042/11952 [3:28:11<16:26:35, 5.97s/it]
17%|█▋ | 2043/11952 [3:28:17<16:37:28, 6.04s/it]
{'loss': 0.5015, 'learning_rate': 1.897667829789724e-05, 'epoch': 0.17}
+
17%|█▋ | 2043/11952 [3:28:17<16:37:28, 6.04s/it]
17%|█▋ | 2044/11952 [3:28:23<16:23:06, 5.95s/it]
{'loss': 0.4806, 'learning_rate': 1.8975483787115326e-05, 'epoch': 0.17}
+
17%|█▋ | 2044/11952 [3:28:23<16:23:06, 5.95s/it]
17%|█▋ | 2045/11952 [3:28:29<16:20:21, 5.94s/it]
{'loss': 0.5259, 'learning_rate': 1.8974288617211217e-05, 'epoch': 0.17}
+
17%|█▋ | 2045/11952 [3:28:29<16:20:21, 5.94s/it]
17%|█▋ | 2046/11952 [3:28:34<16:11:51, 5.89s/it]
{'loss': 0.5037, 'learning_rate': 1.8973092788272677e-05, 'epoch': 0.17}
+
17%|█▋ | 2046/11952 [3:28:34<16:11:51, 5.89s/it]
17%|█▋ | 2047/11952 [3:28:40<16:22:23, 5.95s/it]
{'loss': 0.506, 'learning_rate': 1.8971896300387525e-05, 'epoch': 0.17}
+
17%|█▋ | 2047/11952 [3:28:40<16:22:23, 5.95s/it]
17%|█▋ | 2048/11952 [3:28:46<16:09:49, 5.88s/it]
{'loss': 0.5138, 'learning_rate': 1.8970699153643623e-05, 'epoch': 0.17}
+
17%|█▋ | 2048/11952 [3:28:46<16:09:49, 5.88s/it]
17%|█▋ | 2049/11952 [3:28:52<16:06:33, 5.86s/it]
{'loss': 0.5103, 'learning_rate': 1.896950134812889e-05, 'epoch': 0.17}
+
17%|█▋ | 2049/11952 [3:28:52<16:06:33, 5.86s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+16 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
17%|█▋ | 2050/11952 [3:28:58<15:55:22, 5.79s/it]
{'loss': 0.4973, 'learning_rate': 1.8968302883931283e-05, 'epoch': 0.17}
+
17%|█▋ | 2050/11952 [3:28:58<15:55:22, 5.79s/it]
17%|█▋ | 2051/11952 [3:29:04<16:04:53, 5.85s/it]
{'loss': 0.524, 'learning_rate': 1.8967103761138817e-05, 'epoch': 0.17}
+
17%|█▋ | 2051/11952 [3:29:04<16:04:53, 5.85s/it]
17%|█▋ | 2052/11952 [3:29:09<15:58:11, 5.81s/it]
{'loss': 0.5037, 'learning_rate': 1.8965903979839547e-05, 'epoch': 0.17}
+
17%|█▋ | 2052/11952 [3:29:09<15:58:11, 5.81s/it]
17%|█▋ | 2053/11952 [3:29:15<16:10:44, 5.88s/it]
{'loss': 0.4964, 'learning_rate': 1.8964703540121577e-05, 'epoch': 0.17}
+
17%|█▋ | 2053/11952 [3:29:15<16:10:44, 5.88s/it]
17%|█▋ | 2054/11952 [3:29:21<16:12:35, 5.90s/it]
{'loss': 0.499, 'learning_rate': 1.8963502442073073e-05, 'epoch': 0.17}
+
17%|█▋ | 2054/11952 [3:29:21<16:12:35, 5.90s/it]
17%|█▋ | 2055/11952 [3:29:28<16:34:05, 6.03s/it]
{'loss': 0.507, 'learning_rate': 1.8962300685782224e-05, 'epoch': 0.17}
+
17%|█▋ | 2055/11952 [3:29:28<16:34:05, 6.03s/it]
17%|█▋ | 2056/11952 [3:29:33<16:18:57, 5.94s/it]
{'loss': 0.5196, 'learning_rate': 1.8961098271337296e-05, 'epoch': 0.17}
+
17%|█▋ | 2056/11952 [3:29:33<16:18:57, 5.94s/it]
17%|█▋ | 2057/11952 [3:29:39<16:10:18, 5.88s/it]
{'loss': 0.489, 'learning_rate': 1.8959895198826582e-05, 'epoch': 0.17}
+
17%|█▋ | 2057/11952 [3:29:39<16:10:18, 5.88s/it]
17%|█▋ | 2058/11952 [3:29:45<16:10:30, 5.89s/it]
{'loss': 0.5034, 'learning_rate': 1.895869146833843e-05, 'epoch': 0.17}
+
17%|█▋ | 2058/11952 [3:29:45<16:10:30, 5.89s/it]
17%|█▋ | 2059/11952 [3:29:51<16:10:05, 5.88s/it]
{'loss': 0.5135, 'learning_rate': 1.8957487079961235e-05, 'epoch': 0.17}
+
17%|█▋ | 2059/11952 [3:29:51<16:10:05, 5.88s/it]
17%|█▋ | 2060/11952 [3:29:57<15:59:06, 5.82s/it]
{'loss': 0.4917, 'learning_rate': 1.895628203378345e-05, 'epoch': 0.17}
+
17%|█▋ | 2060/11952 [3:29:57<15:59:06, 5.82s/it]
17%|█▋ | 2061/11952 [3:30:02<15:48:15, 5.75s/it]
{'loss': 0.503, 'learning_rate': 1.8955076329893565e-05, 'epoch': 0.17}
+
17%|█▋ | 2061/11952 [3:30:02<15:48:15, 5.75s/it]
17%|█▋ | 2062/11952 [3:30:08<16:04:42, 5.85s/it]
{'loss': 0.53, 'learning_rate': 1.8953869968380117e-05, 'epoch': 0.17}
+
17%|█▋ | 2062/11952 [3:30:08<16:04:42, 5.85s/it]
17%|█▋ | 2063/11952 [3:30:14<16:00:43, 5.83s/it]
{'loss': 0.4998, 'learning_rate': 1.8952662949331707e-05, 'epoch': 0.17}
+
17%|█▋ | 2063/11952 [3:30:14<16:00:43, 5.83s/it]
17%|█▋ | 2064/11952 [3:30:20<15:49:51, 5.76s/it]
{'loss': 0.4908, 'learning_rate': 1.8951455272836963e-05, 'epoch': 0.17}
+
17%|█▋ | 2064/11952 [3:30:20<15:49:51, 5.76s/it]
17%|█▋ | 2065/11952 [3:30:26<16:01:14, 5.83s/it]
{'loss': 0.5131, 'learning_rate': 1.8950246938984573e-05, 'epoch': 0.17}
+
17%|█▋ | 2065/11952 [3:30:26<16:01:14, 5.83s/it]
17%|█▋ | 2066/11952 [3:30:31<15:58:12, 5.82s/it]
{'loss': 0.5325, 'learning_rate': 1.894903794786328e-05, 'epoch': 0.17}
+
17%|█▋ | 2066/11952 [3:30:31<15:58:12, 5.82s/it]
17%|█▋ | 2067/11952 [3:30:37<15:52:28, 5.78s/it]
{'loss': 0.5071, 'learning_rate': 1.894782829956186e-05, 'epoch': 0.17}
+
17%|█▋ | 2067/11952 [3:30:37<15:52:28, 5.78s/it]
17%|█▋ | 2068/11952 [3:30:43<15:52:49, 5.78s/it]
{'loss': 0.5157, 'learning_rate': 1.8946617994169146e-05, 'epoch': 0.17}
+
17%|█▋ | 2068/11952 [3:30:43<15:52:49, 5.78s/it]
17%|█▋ | 2069/11952 [3:30:49<16:13:16, 5.91s/it]
{'loss': 0.4963, 'learning_rate': 1.8945407031774018e-05, 'epoch': 0.17}
+
17%|█▋ | 2069/11952 [3:30:49<16:13:16, 5.91s/it]
17%|█▋ | 2070/11952 [3:30:55<15:59:03, 5.82s/it]
{'loss': 0.5301, 'learning_rate': 1.8944195412465404e-05, 'epoch': 0.17}
+
17%|█▋ | 2070/11952 [3:30:55<15:59:03, 5.82s/it]
17%|█▋ | 2071/11952 [3:31:01<15:59:09, 5.82s/it]
{'loss': 0.5193, 'learning_rate': 1.8942983136332282e-05, 'epoch': 0.17}
+
17%|█▋ | 2071/11952 [3:31:01<15:59:09, 5.82s/it]
17%|█▋ | 2072/11952 [3:31:06<15:52:16, 5.78s/it]
{'loss': 0.4954, 'learning_rate': 1.8941770203463674e-05, 'epoch': 0.17}
+
17%|█▋ | 2072/11952 [3:31:06<15:52:16, 5.78s/it]
17%|█▋ | 2073/11952 [3:31:12<16:00:17, 5.83s/it]
{'loss': 0.5124, 'learning_rate': 1.8940556613948656e-05, 'epoch': 0.17}
+
17%|█▋ | 2073/11952 [3:31:12<16:00:17, 5.83s/it]
17%|█▋ | 2074/11952 [3:31:18<15:55:06, 5.80s/it]
{'loss': 0.51, 'learning_rate': 1.8939342367876345e-05, 'epoch': 0.17}
+
17%|█▋ | 2074/11952 [3:31:18<15:55:06, 5.80s/it]
17%|█▋ | 2075/11952 [3:31:23<15:44:38, 5.74s/it]
{'loss': 0.4831, 'learning_rate': 1.893812746533591e-05, 'epoch': 0.17}
+
17%|█▋ | 2075/11952 [3:31:24<15:44:38, 5.74s/it]
17%|█▋ | 2076/11952 [3:31:29<15:46:22, 5.75s/it]
{'loss': 0.4994, 'learning_rate': 1.8936911906416572e-05, 'epoch': 0.17}
+
17%|█▋ | 2076/11952 [3:31:29<15:46:22, 5.75s/it]
17%|█▋ | 2077/11952 [3:31:35<15:45:41, 5.75s/it]
{'loss': 0.5263, 'learning_rate': 1.8935695691207598e-05, 'epoch': 0.17}
+
17%|█▋ | 2077/11952 [3:31:35<15:45:41, 5.75s/it]
17%|█▋ | 2078/11952 [3:31:41<15:55:57, 5.81s/it]
{'loss': 0.4893, 'learning_rate': 1.8934478819798296e-05, 'epoch': 0.17}
+
17%|█▋ | 2078/11952 [3:31:41<15:55:57, 5.81s/it]
17%|█▋ | 2079/11952 [3:31:47<15:51:06, 5.78s/it]
{'loss': 0.5132, 'learning_rate': 1.8933261292278033e-05, 'epoch': 0.17}
+
17%|█▋ | 2079/11952 [3:31:47<15:51:06, 5.78s/it]
17%|█▋ | 2080/11952 [3:31:52<15:46:54, 5.76s/it]
{'loss': 0.5076, 'learning_rate': 1.8932043108736217e-05, 'epoch': 0.17}
+
17%|█▋ | 2080/11952 [3:31:52<15:46:54, 5.76s/it]
17%|█▋ | 2081/11952 [3:31:59<16:06:18, 5.87s/it]
{'loss': 0.527, 'learning_rate': 1.89308242692623e-05, 'epoch': 0.17}
+
17%|█▋ | 2081/11952 [3:31:59<16:06:18, 5.87s/it]
17%|█▋ | 2082/11952 [3:32:04<16:05:39, 5.87s/it]
{'loss': 0.5058, 'learning_rate': 1.89296047739458e-05, 'epoch': 0.17}
+
17%|█▋ | 2082/11952 [3:32:04<16:05:39, 5.87s/it]
17%|█▋ | 2083/11952 [3:32:10<16:01:33, 5.85s/it]
{'loss': 0.5095, 'learning_rate': 1.892838462287627e-05, 'epoch': 0.17}
+
17%|█▋ | 2083/11952 [3:32:10<16:01:33, 5.85s/it]
17%|█▋ | 2084/11952 [3:32:16<15:58:39, 5.83s/it]
{'loss': 0.4916, 'learning_rate': 1.8927163816143302e-05, 'epoch': 0.17}
+
17%|█▋ | 2084/11952 [3:32:16<15:58:39, 5.83s/it]
17%|█▋ | 2085/11952 [3:32:22<15:48:12, 5.77s/it]
{'loss': 0.4806, 'learning_rate': 1.8925942353836558e-05, 'epoch': 0.17}
+
17%|█▋ | 2085/11952 [3:32:22<15:48:12, 5.77s/it]
17%|█▋ | 2086/11952 [3:32:27<15:46:31, 5.76s/it]
{'loss': 0.5076, 'learning_rate': 1.892472023604573e-05, 'epoch': 0.17}
+
17%|█▋ | 2086/11952 [3:32:27<15:46:31, 5.76s/it]
17%|█▋ | 2087/11952 [3:32:33<15:47:00, 5.76s/it]
{'loss': 0.5209, 'learning_rate': 1.8923497462860572e-05, 'epoch': 0.17}
+
17%|█▋ | 2087/11952 [3:32:33<15:47:00, 5.76s/it]
17%|█▋ | 2088/11952 [3:32:39<15:55:24, 5.81s/it]
{'loss': 0.4888, 'learning_rate': 1.8922274034370875e-05, 'epoch': 0.17}
+
17%|█▋ | 2088/11952 [3:32:39<15:55:24, 5.81s/it]
17%|█▋ | 2089/11952 [3:32:45<15:53:35, 5.80s/it]
{'loss': 0.5002, 'learning_rate': 1.8921049950666484e-05, 'epoch': 0.17}
+
17%|█▋ | 2089/11952 [3:32:45<15:53:35, 5.80s/it]
17%|█▋ | 2090/11952 [3:32:51<15:52:19, 5.79s/it]
{'loss': 0.5068, 'learning_rate': 1.891982521183729e-05, 'epoch': 0.17}
+
17%|█▋ | 2090/11952 [3:32:51<15:52:19, 5.79s/it]
17%|█▋ | 2091/11952 [3:32:56<15:44:41, 5.75s/it]
{'loss': 0.4904, 'learning_rate': 1.891859981797323e-05, 'epoch': 0.17}
+
17%|█▋ | 2091/11952 [3:32:56<15:44:41, 5.75s/it]
18%|█▊ | 2092/11952 [3:33:02<15:49:06, 5.78s/it]
{'loss': 0.5147, 'learning_rate': 1.89173737691643e-05, 'epoch': 0.18}
+
18%|█▊ | 2092/11952 [3:33:02<15:49:06, 5.78s/it]
18%|█▊ | 2093/11952 [3:33:08<15:36:40, 5.70s/it]
{'loss': 0.489, 'learning_rate': 1.8916147065500524e-05, 'epoch': 0.18}
+
18%|█▊ | 2093/11952 [3:33:08<15:36:40, 5.70s/it]
18%|█▊ | 2094/11952 [3:33:14<15:48:35, 5.77s/it]
{'loss': 0.5265, 'learning_rate': 1.8914919707071997e-05, 'epoch': 0.18}
+
18%|█▊ | 2094/11952 [3:33:14<15:48:35, 5.77s/it]
18%|█▊ | 2095/11952 [3:33:20<16:01:19, 5.85s/it]
{'loss': 0.4928, 'learning_rate': 1.8913691693968846e-05, 'epoch': 0.18}
+
18%|█▊ | 2095/11952 [3:33:20<16:01:19, 5.85s/it]
18%|█▊ | 2096/11952 [3:33:26<16:13:57, 5.93s/it]
{'loss': 0.5037, 'learning_rate': 1.891246302628125e-05, 'epoch': 0.18}
+
18%|█▊ | 2096/11952 [3:33:26<16:13:57, 5.93s/it]
18%|█▊ | 2097/11952 [3:33:32<16:12:01, 5.92s/it]
{'loss': 0.5027, 'learning_rate': 1.891123370409944e-05, 'epoch': 0.18}
+
18%|█▊ | 2097/11952 [3:33:32<16:12:01, 5.92s/it]
18%|█▊ | 2098/11952 [3:33:37<16:03:24, 5.87s/it]
{'loss': 0.496, 'learning_rate': 1.8910003727513697e-05, 'epoch': 0.18}
+
18%|█▊ | 2098/11952 [3:33:37<16:03:24, 5.87s/it]
18%|█▊ | 2099/11952 [3:33:43<15:48:19, 5.77s/it]
{'loss': 0.4993, 'learning_rate': 1.8908773096614333e-05, 'epoch': 0.18}
+
18%|█▊ | 2099/11952 [3:33:43<15:48:19, 5.77s/it]2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+56 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+7 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
18%|█▊ | 2100/11952 [3:33:49<15:43:29, 5.75s/it]4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4809, 'learning_rate': 1.8907541811491726e-05, 'epoch': 0.18}
+
18%|█▊ | 2100/11952 [3:33:49<15:43:29, 5.75s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
18%|█▊ | 2101/11952 [3:34:23<39:04:47, 14.28s/it]
{'loss': 0.4981, 'learning_rate': 1.89063098722363e-05, 'epoch': 0.18}
+
18%|█▊ | 2101/11952 [3:34:23<39:04:47, 14.28s/it]
18%|█▊ | 2102/11952 [3:34:29<32:11:30, 11.77s/it]
{'loss': 0.5007, 'learning_rate': 1.8905077278938524e-05, 'epoch': 0.18}
+
18%|█▊ | 2102/11952 [3:34:29<32:11:30, 11.77s/it]
18%|█▊ | 2103/11952 [3:34:34<27:16:07, 9.97s/it]
{'loss': 0.5164, 'learning_rate': 1.890384403168891e-05, 'epoch': 0.18}
+
18%|█▊ | 2103/11952 [3:34:34<27:16:07, 9.97s/it]
18%|█▊ | 2104/11952 [3:34:40<23:46:35, 8.69s/it]
{'loss': 0.5046, 'learning_rate': 1.890261013057802e-05, 'epoch': 0.18}
+
18%|█▊ | 2104/11952 [3:34:40<23:46:35, 8.69s/it]
18%|█▊ | 2105/11952 [3:34:46<21:32:58, 7.88s/it]
{'loss': 0.5137, 'learning_rate': 1.8901375575696476e-05, 'epoch': 0.18}
+
18%|█▊ | 2105/11952 [3:34:46<21:32:58, 7.88s/it]
18%|█▊ | 2106/11952 [3:34:52<19:59:01, 7.31s/it]
{'loss': 0.5103, 'learning_rate': 1.890014036713493e-05, 'epoch': 0.18}
+
18%|█▊ | 2106/11952 [3:34:52<19:59:01, 7.31s/it]
18%|█▊ | 2107/11952 [3:34:58<19:07:19, 6.99s/it]
{'loss': 0.5071, 'learning_rate': 1.8898904504984096e-05, 'epoch': 0.18}
+
18%|█▊ | 2107/11952 [3:34:58<19:07:19, 6.99s/it]
18%|█▊ | 2108/11952 [3:35:04<18:11:28, 6.65s/it]
{'loss': 0.5271, 'learning_rate': 1.8897667989334726e-05, 'epoch': 0.18}
+
18%|█▊ | 2108/11952 [3:35:04<18:11:28, 6.65s/it]
18%|█▊ | 2109/11952 [3:35:10<17:45:39, 6.50s/it]
{'loss': 0.5044, 'learning_rate': 1.889643082027763e-05, 'epoch': 0.18}
+
18%|█▊ | 2109/11952 [3:35:10<17:45:39, 6.50s/it]
18%|█▊ | 2110/11952 [3:35:16<17:02:21, 6.23s/it]
{'loss': 0.4989, 'learning_rate': 1.8895192997903657e-05, 'epoch': 0.18}
+
18%|█▊ | 2110/11952 [3:35:16<17:02:21, 6.23s/it]
18%|█▊ | 2111/11952 [3:35:22<16:35:00, 6.07s/it]
{'loss': 0.5072, 'learning_rate': 1.8893954522303707e-05, 'epoch': 0.18}
+
18%|█▊ | 2111/11952 [3:35:22<16:35:00, 6.07s/it]
18%|█▊ | 2112/11952 [3:35:27<16:21:50, 5.99s/it]
{'loss': 0.4782, 'learning_rate': 1.889271539356873e-05, 'epoch': 0.18}
+
18%|█▊ | 2112/11952 [3:35:27<16:21:50, 5.99s/it]
18%|█▊ | 2113/11952 [3:35:33<16:01:25, 5.86s/it]
{'loss': 0.4853, 'learning_rate': 1.889147561178972e-05, 'epoch': 0.18}
+
18%|█▊ | 2113/11952 [3:35:33<16:01:25, 5.86s/it]
18%|█▊ | 2114/11952 [3:35:39<16:07:06, 5.90s/it]
{'loss': 0.5108, 'learning_rate': 1.889023517705773e-05, 'epoch': 0.18}
+
18%|█▊ | 2114/11952 [3:35:39<16:07:06, 5.90s/it]
18%|█▊ | 2115/11952 [3:35:45<16:07:20, 5.90s/it]
{'loss': 0.5195, 'learning_rate': 1.888899408946384e-05, 'epoch': 0.18}
+
18%|█▊ | 2115/11952 [3:35:45<16:07:20, 5.90s/it]
18%|█▊ | 2116/11952 [3:35:51<16:13:32, 5.94s/it]
{'loss': 0.4972, 'learning_rate': 1.88877523490992e-05, 'epoch': 0.18}
+
18%|█▊ | 2116/11952 [3:35:51<16:13:32, 5.94s/it]
18%|█▊ | 2117/11952 [3:35:57<16:01:06, 5.86s/it]
{'loss': 0.4881, 'learning_rate': 1.888650995605499e-05, 'epoch': 0.18}
+
18%|█▊ | 2117/11952 [3:35:57<16:01:06, 5.86s/it]
18%|█▊ | 2118/11952 [3:36:02<15:58:11, 5.85s/it]
{'loss': 0.4766, 'learning_rate': 1.8885266910422454e-05, 'epoch': 0.18}
+
18%|█▊ | 2118/11952 [3:36:02<15:58:11, 5.85s/it]
18%|█▊ | 2119/11952 [3:36:08<15:58:36, 5.85s/it]
{'loss': 0.4896, 'learning_rate': 1.888402321229287e-05, 'epoch': 0.18}
+
18%|█▊ | 2119/11952 [3:36:08<15:58:36, 5.85s/it]
18%|█▊ | 2120/11952 [3:36:14<15:51:41, 5.81s/it]
{'loss': 0.5269, 'learning_rate': 1.8882778861757573e-05, 'epoch': 0.18}
+
18%|█▊ | 2120/11952 [3:36:14<15:51:41, 5.81s/it]
18%|█▊ | 2121/11952 [3:36:20<15:51:20, 5.81s/it]
{'loss': 0.5108, 'learning_rate': 1.8881533858907945e-05, 'epoch': 0.18}
+
18%|█▊ | 2121/11952 [3:36:20<15:51:20, 5.81s/it]
18%|█▊ | 2122/11952 [3:36:25<15:42:54, 5.76s/it]
{'loss': 0.5037, 'learning_rate': 1.888028820383541e-05, 'epoch': 0.18}
+
18%|█▊ | 2122/11952 [3:36:25<15:42:54, 5.76s/it]
18%|█▊ | 2123/11952 [3:36:31<15:35:31, 5.71s/it]
{'loss': 0.4973, 'learning_rate': 1.8879041896631448e-05, 'epoch': 0.18}
+
18%|█▊ | 2123/11952 [3:36:31<15:35:31, 5.71s/it]
18%|█▊ | 2124/11952 [3:36:37<15:39:18, 5.73s/it]
{'loss': 0.5348, 'learning_rate': 1.8877794937387576e-05, 'epoch': 0.18}
+
18%|█▊ | 2124/11952 [3:36:37<15:39:18, 5.73s/it]
18%|█▊ | 2125/11952 [3:36:43<16:07:58, 5.91s/it]
{'loss': 0.5247, 'learning_rate': 1.8876547326195373e-05, 'epoch': 0.18}
+
18%|█▊ | 2125/11952 [3:36:43<16:07:58, 5.91s/it]
18%|█▊ | 2126/11952 [3:36:49<16:09:51, 5.92s/it]
{'loss': 0.5148, 'learning_rate': 1.887529906314645e-05, 'epoch': 0.18}
+
18%|█▊ | 2126/11952 [3:36:49<16:09:51, 5.92s/it]
18%|█▊ | 2127/11952 [3:36:55<15:50:57, 5.81s/it]
{'loss': 0.5, 'learning_rate': 1.8874050148332484e-05, 'epoch': 0.18}
+
18%|█▊ | 2127/11952 [3:36:55<15:50:57, 5.81s/it]
18%|█▊ | 2128/11952 [3:37:01<16:10:56, 5.93s/it]
{'loss': 0.4996, 'learning_rate': 1.887280058184518e-05, 'epoch': 0.18}
+
18%|█▊ | 2128/11952 [3:37:01<16:10:56, 5.93s/it]
18%|█▊ | 2129/11952 [3:37:07<16:01:27, 5.87s/it]
{'loss': 0.5084, 'learning_rate': 1.8871550363776308e-05, 'epoch': 0.18}
+
18%|█▊ | 2129/11952 [3:37:07<16:01:27, 5.87s/it]
18%|█▊ | 2130/11952 [3:37:12<16:01:00, 5.87s/it]
{'loss': 0.5191, 'learning_rate': 1.8870299494217675e-05, 'epoch': 0.18}
+
18%|█▊ | 2130/11952 [3:37:12<16:01:00, 5.87s/it]
18%|█▊ | 2131/11952 [3:37:18<16:01:31, 5.87s/it]
{'loss': 0.5196, 'learning_rate': 1.8869047973261148e-05, 'epoch': 0.18}
+
18%|█▊ | 2131/11952 [3:37:18<16:01:31, 5.87s/it]
18%|█▊ | 2132/11952 [3:37:24<16:09:31, 5.92s/it]
{'loss': 0.5111, 'learning_rate': 1.8867795800998623e-05, 'epoch': 0.18}
+
18%|█▊ | 2132/11952 [3:37:24<16:09:31, 5.92s/it]
18%|█▊ | 2133/11952 [3:37:30<16:10:29, 5.93s/it]
{'loss': 0.4926, 'learning_rate': 1.8866542977522057e-05, 'epoch': 0.18}
+
18%|█▊ | 2133/11952 [3:37:30<16:10:29, 5.93s/it]
18%|█▊ | 2134/11952 [3:37:36<16:10:06, 5.93s/it]
{'loss': 0.5095, 'learning_rate': 1.8865289502923455e-05, 'epoch': 0.18}
+
18%|█▊ | 2134/11952 [3:37:36<16:10:06, 5.93s/it]
18%|█▊ | 2135/11952 [3:37:43<16:29:50, 6.05s/it]
{'loss': 0.5105, 'learning_rate': 1.8864035377294865e-05, 'epoch': 0.18}
+
18%|█▊ | 2135/11952 [3:37:43<16:29:50, 6.05s/it]
18%|█▊ | 2136/11952 [3:37:48<16:12:25, 5.94s/it]
{'loss': 0.507, 'learning_rate': 1.8862780600728384e-05, 'epoch': 0.18}
+
18%|█▊ | 2136/11952 [3:37:48<16:12:25, 5.94s/it]
18%|█▊ | 2137/11952 [3:37:54<16:08:11, 5.92s/it]
{'loss': 0.486, 'learning_rate': 1.886152517331616e-05, 'epoch': 0.18}
+
18%|█▊ | 2137/11952 [3:37:54<16:08:11, 5.92s/it]
18%|█▊ | 2138/11952 [3:38:00<16:10:46, 5.94s/it]
{'loss': 0.5058, 'learning_rate': 1.8860269095150387e-05, 'epoch': 0.18}
+
18%|█▊ | 2138/11952 [3:38:00<16:10:46, 5.94s/it]
18%|█▊ | 2139/11952 [3:38:06<15:59:43, 5.87s/it]
{'loss': 0.4886, 'learning_rate': 1.88590123663233e-05, 'epoch': 0.18}
+
18%|█▊ | 2139/11952 [3:38:06<15:59:43, 5.87s/it]
18%|█▊ | 2140/11952 [3:38:12<15:54:56, 5.84s/it]
{'loss': 0.5001, 'learning_rate': 1.8857754986927196e-05, 'epoch': 0.18}
+
18%|█▊ | 2140/11952 [3:38:12<15:54:56, 5.84s/it]
18%|█▊ | 2141/11952 [3:38:18<15:59:23, 5.87s/it]
{'loss': 0.5071, 'learning_rate': 1.8856496957054406e-05, 'epoch': 0.18}
+
18%|█▊ | 2141/11952 [3:38:18<15:59:23, 5.87s/it]
18%|█▊ | 2142/11952 [3:38:23<15:52:37, 5.83s/it]
{'loss': 0.5145, 'learning_rate': 1.8855238276797315e-05, 'epoch': 0.18}
+
18%|█▊ | 2142/11952 [3:38:23<15:52:37, 5.83s/it]
18%|█▊ | 2143/11952 [3:38:29<15:42:14, 5.76s/it]
{'loss': 0.5025, 'learning_rate': 1.885397894624836e-05, 'epoch': 0.18}
+
18%|█▊ | 2143/11952 [3:38:29<15:42:14, 5.76s/it]
18%|█▊ | 2144/11952 [3:38:34<15:32:52, 5.71s/it]
{'loss': 0.4977, 'learning_rate': 1.8852718965500018e-05, 'epoch': 0.18}
+
18%|█▊ | 2144/11952 [3:38:34<15:32:52, 5.71s/it]
18%|█▊ | 2145/11952 [3:38:40<15:29:15, 5.69s/it]
{'loss': 0.4879, 'learning_rate': 1.8851458334644814e-05, 'epoch': 0.18}
+
18%|█▊ | 2145/11952 [3:38:40<15:29:15, 5.69s/it]
18%|█▊ | 2146/11952 [3:38:46<15:31:25, 5.70s/it]
{'loss': 0.499, 'learning_rate': 1.8850197053775326e-05, 'epoch': 0.18}
+
18%|█▊ | 2146/11952 [3:38:46<15:31:25, 5.70s/it]
18%|█▊ | 2147/11952 [3:38:52<15:34:02, 5.72s/it]
{'loss': 0.4959, 'learning_rate': 1.8848935122984177e-05, 'epoch': 0.18}
+
18%|█▊ | 2147/11952 [3:38:52<15:34:02, 5.72s/it]
18%|█▊ | 2148/11952 [3:38:57<15:43:06, 5.77s/it]
{'loss': 0.4981, 'learning_rate': 1.884767254236404e-05, 'epoch': 0.18}
+
18%|█▊ | 2148/11952 [3:38:57<15:43:06, 5.77s/it]
18%|█▊ | 2149/11952 [3:39:03<15:54:02, 5.84s/it]
{'loss': 0.5005, 'learning_rate': 1.884640931200763e-05, 'epoch': 0.18}
+
18%|█▊ | 2149/11952 [3:39:03<15:54:02, 5.84s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+23 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
18%|█▊ | 2150/11952 [3:39:09<15:35:26, 5.73s/it]
{'loss': 0.4988, 'learning_rate': 1.8845145432007715e-05, 'epoch': 0.18}
+
18%|█▊ | 2150/11952 [3:39:09<15:35:26, 5.73s/it]
18%|█▊ | 2151/11952 [3:39:15<15:47:58, 5.80s/it]
{'loss': 0.4929, 'learning_rate': 1.884388090245711e-05, 'epoch': 0.18}
+
18%|█▊ | 2151/11952 [3:39:15<15:47:58, 5.80s/it]
18%|█▊ | 2152/11952 [3:39:21<15:45:49, 5.79s/it]
{'loss': 0.5127, 'learning_rate': 1.8842615723448678e-05, 'epoch': 0.18}
+
18%|█▊ | 2152/11952 [3:39:21<15:45:49, 5.79s/it]
18%|█▊ | 2153/11952 [3:39:27<15:58:09, 5.87s/it]
{'loss': 0.5139, 'learning_rate': 1.884134989507532e-05, 'epoch': 0.18}
+
18%|█▊ | 2153/11952 [3:39:27<15:58:09, 5.87s/it]
18%|█▊ | 2154/11952 [3:39:32<15:43:38, 5.78s/it]
{'loss': 0.4953, 'learning_rate': 1.8840083417430003e-05, 'epoch': 0.18}
+
18%|█▊ | 2154/11952 [3:39:32<15:43:38, 5.78s/it]
18%|█▊ | 2155/11952 [3:39:38<15:56:32, 5.86s/it]
{'loss': 0.5164, 'learning_rate': 1.8838816290605732e-05, 'epoch': 0.18}
+
18%|█▊ | 2155/11952 [3:39:38<15:56:32, 5.86s/it]
18%|█▊ | 2156/11952 [3:39:44<16:11:27, 5.95s/it]
{'loss': 0.5008, 'learning_rate': 1.883754851469555e-05, 'epoch': 0.18}
+
18%|█▊ | 2156/11952 [3:39:44<16:11:27, 5.95s/it]
18%|█▊ | 2157/11952 [3:39:50<16:03:00, 5.90s/it]
{'loss': 0.4822, 'learning_rate': 1.883628008979257e-05, 'epoch': 0.18}
+
18%|█▊ | 2157/11952 [3:39:50<16:03:00, 5.90s/it]
18%|█▊ | 2158/11952 [3:39:56<15:53:18, 5.84s/it]
{'loss': 0.5138, 'learning_rate': 1.8835011015989927e-05, 'epoch': 0.18}
+
18%|█▊ | 2158/11952 [3:39:56<15:53:18, 5.84s/it]
18%|█▊ | 2159/11952 [3:40:02<15:39:54, 5.76s/it]
{'loss': 0.5049, 'learning_rate': 1.8833741293380826e-05, 'epoch': 0.18}
+
18%|█▊ | 2159/11952 [3:40:02<15:39:54, 5.76s/it]
18%|█▊ | 2160/11952 [3:40:07<15:44:32, 5.79s/it]
{'loss': 0.5085, 'learning_rate': 1.883247092205851e-05, 'epoch': 0.18}
+
18%|█▊ | 2160/11952 [3:40:07<15:44:32, 5.79s/it]
18%|█▊ | 2161/11952 [3:40:13<15:45:17, 5.79s/it]
{'loss': 0.4884, 'learning_rate': 1.883119990211626e-05, 'epoch': 0.18}
+
18%|█▊ | 2161/11952 [3:40:13<15:45:17, 5.79s/it]
18%|█▊ | 2162/11952 [3:40:20<16:12:26, 5.96s/it]
{'loss': 0.5028, 'learning_rate': 1.8829928233647422e-05, 'epoch': 0.18}
+
18%|█▊ | 2162/11952 [3:40:20<16:12:26, 5.96s/it]
18%|█▊ | 2163/11952 [3:40:26<16:23:07, 6.03s/it]
{'loss': 0.5221, 'learning_rate': 1.8828655916745383e-05, 'epoch': 0.18}
+
18%|█▊ | 2163/11952 [3:40:26<16:23:07, 6.03s/it]
18%|█▊ | 2164/11952 [3:40:32<16:19:20, 6.00s/it]
{'loss': 0.5228, 'learning_rate': 1.8827382951503575e-05, 'epoch': 0.18}
+
18%|█▊ | 2164/11952 [3:40:32<16:19:20, 6.00s/it]
18%|█▊ | 2165/11952 [3:40:38<16:23:51, 6.03s/it]
{'loss': 0.5035, 'learning_rate': 1.8826109338015478e-05, 'epoch': 0.18}
+
18%|█▊ | 2165/11952 [3:40:38<16:23:51, 6.03s/it]
18%|█▊ | 2166/11952 [3:40:44<16:10:02, 5.95s/it]
{'loss': 0.4917, 'learning_rate': 1.8824835076374622e-05, 'epoch': 0.18}
+
18%|█▊ | 2166/11952 [3:40:44<16:10:02, 5.95s/it]
18%|█▊ | 2167/11952 [3:40:49<16:03:04, 5.91s/it]
{'loss': 0.5087, 'learning_rate': 1.882356016667458e-05, 'epoch': 0.18}
+
18%|█▊ | 2167/11952 [3:40:49<16:03:04, 5.91s/it]
18%|█▊ | 2168/11952 [3:40:55<15:59:12, 5.88s/it]
{'loss': 0.4921, 'learning_rate': 1.8822284609008985e-05, 'epoch': 0.18}
+
18%|█▊ | 2168/11952 [3:40:55<15:59:12, 5.88s/it]
18%|█▊ | 2169/11952 [3:41:01<16:11:23, 5.96s/it]
{'loss': 0.5027, 'learning_rate': 1.8821008403471497e-05, 'epoch': 0.18}
+
18%|█▊ | 2169/11952 [3:41:01<16:11:23, 5.96s/it]
18%|█▊ | 2170/11952 [3:41:07<15:58:10, 5.88s/it]
{'loss': 0.5117, 'learning_rate': 1.8819731550155845e-05, 'epoch': 0.18}
+
18%|█▊ | 2170/11952 [3:41:07<15:58:10, 5.88s/it]
18%|█▊ | 2171/11952 [3:41:13<15:52:15, 5.84s/it]
{'loss': 0.4992, 'learning_rate': 1.8818454049155792e-05, 'epoch': 0.18}
+
18%|█▊ | 2171/11952 [3:41:13<15:52:15, 5.84s/it]
18%|█▊ | 2172/11952 [3:41:18<15:45:21, 5.80s/it]
{'loss': 0.4923, 'learning_rate': 1.881717590056515e-05, 'epoch': 0.18}
+
18%|█▊ | 2172/11952 [3:41:18<15:45:21, 5.80s/it]
18%|█▊ | 2173/11952 [3:41:24<15:52:24, 5.84s/it]
{'loss': 0.4898, 'learning_rate': 1.8815897104477786e-05, 'epoch': 0.18}
+
18%|█▊ | 2173/11952 [3:41:24<15:52:24, 5.84s/it]
18%|█▊ | 2174/11952 [3:41:30<15:59:23, 5.89s/it]
{'loss': 0.523, 'learning_rate': 1.8814617660987603e-05, 'epoch': 0.18}
+
18%|█▊ | 2174/11952 [3:41:30<15:59:23, 5.89s/it]
18%|█▊ | 2175/11952 [3:41:36<15:52:35, 5.85s/it]
{'loss': 0.5144, 'learning_rate': 1.881333757018857e-05, 'epoch': 0.18}
+
18%|█▊ | 2175/11952 [3:41:36<15:52:35, 5.85s/it]
18%|█▊ | 2176/11952 [3:41:42<15:55:59, 5.87s/it]
{'loss': 0.4931, 'learning_rate': 1.8812056832174673e-05, 'epoch': 0.18}
+
18%|█▊ | 2176/11952 [3:41:42<15:55:59, 5.87s/it]
18%|█▊ | 2177/11952 [3:41:48<15:43:59, 5.79s/it]
{'loss': 0.4996, 'learning_rate': 1.881077544703998e-05, 'epoch': 0.18}
+
18%|█▊ | 2177/11952 [3:41:48<15:43:59, 5.79s/it]
18%|█▊ | 2178/11952 [3:41:53<15:41:14, 5.78s/it]
{'loss': 0.4943, 'learning_rate': 1.8809493414878585e-05, 'epoch': 0.18}
+
18%|█▊ | 2178/11952 [3:41:53<15:41:14, 5.78s/it]
18%|█▊ | 2179/11952 [3:41:59<15:38:12, 5.76s/it]
{'loss': 0.4915, 'learning_rate': 1.880821073578463e-05, 'epoch': 0.18}
+
18%|█▊ | 2179/11952 [3:41:59<15:38:12, 5.76s/it]
18%|█▊ | 2180/11952 [3:42:05<15:38:42, 5.76s/it]
{'loss': 0.5129, 'learning_rate': 1.8806927409852323e-05, 'epoch': 0.18}
+
18%|█▊ | 2180/11952 [3:42:05<15:38:42, 5.76s/it]
18%|█▊ | 2181/11952 [3:42:11<15:35:07, 5.74s/it]
{'loss': 0.4973, 'learning_rate': 1.8805643437175892e-05, 'epoch': 0.18}
+
18%|█▊ | 2181/11952 [3:42:11<15:35:07, 5.74s/it]
18%|█▊ | 2182/11952 [3:42:16<15:38:30, 5.76s/it]
{'loss': 0.4808, 'learning_rate': 1.8804358817849634e-05, 'epoch': 0.18}
+
18%|█▊ | 2182/11952 [3:42:16<15:38:30, 5.76s/it]
18%|█▊ | 2183/11952 [3:42:22<15:35:50, 5.75s/it]
{'loss': 0.5014, 'learning_rate': 1.8803073551967884e-05, 'epoch': 0.18}
+
18%|█▊ | 2183/11952 [3:42:22<15:35:50, 5.75s/it]
18%|█▊ | 2184/11952 [3:42:28<15:48:44, 5.83s/it]
{'loss': 0.5324, 'learning_rate': 1.8801787639625025e-05, 'epoch': 0.18}
+
18%|█▊ | 2184/11952 [3:42:28<15:48:44, 5.83s/it]
18%|█▊ | 2185/11952 [3:42:34<16:01:11, 5.90s/it]
{'loss': 0.4964, 'learning_rate': 1.8800501080915496e-05, 'epoch': 0.18}
+
18%|█▊ | 2185/11952 [3:42:34<16:01:11, 5.90s/it]
18%|█▊ | 2186/11952 [3:42:40<15:56:10, 5.87s/it]
{'loss': 0.5127, 'learning_rate': 1.879921387593377e-05, 'epoch': 0.18}
+
18%|█▊ | 2186/11952 [3:42:40<15:56:10, 5.87s/it]
18%|█▊ | 2187/11952 [3:42:46<16:10:40, 5.96s/it]
{'loss': 0.5176, 'learning_rate': 1.8797926024774375e-05, 'epoch': 0.18}
+
18%|█▊ | 2187/11952 [3:42:46<16:10:40, 5.96s/it]
18%|█▊ | 2188/11952 [3:42:52<16:01:43, 5.91s/it]
{'loss': 0.5158, 'learning_rate': 1.8796637527531883e-05, 'epoch': 0.18}
+
18%|█▊ | 2188/11952 [3:42:52<16:01:43, 5.91s/it]
18%|█▊ | 2189/11952 [3:42:58<15:55:54, 5.87s/it]
{'loss': 0.5075, 'learning_rate': 1.8795348384300922e-05, 'epoch': 0.18}
+
18%|█▊ | 2189/11952 [3:42:58<15:55:54, 5.87s/it]
18%|█▊ | 2190/11952 [3:43:03<15:45:31, 5.81s/it]
{'loss': 0.4952, 'learning_rate': 1.879405859517616e-05, 'epoch': 0.18}
+
18%|█▊ | 2190/11952 [3:43:03<15:45:31, 5.81s/it]
18%|█▊ | 2191/11952 [3:43:09<15:41:26, 5.79s/it]
{'loss': 0.5071, 'learning_rate': 1.8792768160252308e-05, 'epoch': 0.18}
+
18%|█▊ | 2191/11952 [3:43:09<15:41:26, 5.79s/it]
18%|█▊ | 2192/11952 [3:43:15<16:05:39, 5.94s/it]
{'loss': 0.5143, 'learning_rate': 1.8791477079624138e-05, 'epoch': 0.18}
+
18%|█▊ | 2192/11952 [3:43:15<16:05:39, 5.94s/it]
18%|█▊ | 2193/11952 [3:43:21<15:56:06, 5.88s/it]
{'loss': 0.4903, 'learning_rate': 1.8790185353386453e-05, 'epoch': 0.18}
+
18%|█▊ | 2193/11952 [3:43:21<15:56:06, 5.88s/it]
18%|█▊ | 2194/11952 [3:43:27<15:41:22, 5.79s/it]
{'loss': 0.5099, 'learning_rate': 1.878889298163412e-05, 'epoch': 0.18}
+
18%|█▊ | 2194/11952 [3:43:27<15:41:22, 5.79s/it]
18%|█▊ | 2195/11952 [3:43:33<15:40:25, 5.78s/it]
{'loss': 0.5002, 'learning_rate': 1.8787599964462044e-05, 'epoch': 0.18}
+
18%|█▊ | 2195/11952 [3:43:33<15:40:25, 5.78s/it]
18%|█▊ | 2196/11952 [3:43:38<15:35:50, 5.76s/it]
{'loss': 0.4997, 'learning_rate': 1.8786306301965175e-05, 'epoch': 0.18}
+
18%|█▊ | 2196/11952 [3:43:38<15:35:50, 5.76s/it]
18%|█▊ | 2197/11952 [3:43:44<15:35:51, 5.76s/it]
{'loss': 0.5037, 'learning_rate': 1.8785011994238516e-05, 'epoch': 0.18}
+
18%|█▊ | 2197/11952 [3:43:44<15:35:51, 5.76s/it]
18%|█▊ | 2198/11952 [3:43:50<15:32:35, 5.74s/it]
{'loss': 0.5111, 'learning_rate': 1.8783717041377113e-05, 'epoch': 0.18}
+
18%|█▊ | 2198/11952 [3:43:50<15:32:35, 5.74s/it]
18%|█▊ | 2199/11952 [3:43:55<15:26:43, 5.70s/it]
{'loss': 0.4795, 'learning_rate': 1.8782421443476072e-05, 'epoch': 0.18}
+
18%|█▊ | 2199/11952 [3:43:55<15:26:43, 5.70s/it]5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...6 AutoResumeHook: Checking whether to suspend...
+
+
18%|█▊ | 2200/11952 [3:44:01<15:35:48, 5.76s/it]
{'loss': 0.4958, 'learning_rate': 1.878112520063052e-05, 'epoch': 0.18}
+
18%|█▊ | 2200/11952 [3:44:01<15:35:48, 5.76s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
18%|█▊ | 2201/11952 [3:44:35<38:18:23, 14.14s/it]
{'loss': 0.5096, 'learning_rate': 1.8779828312935664e-05, 'epoch': 0.18}
+
18%|█▊ | 2201/11952 [3:44:35<38:18:23, 14.14s/it]
18%|█▊ | 2202/11952 [3:44:41<31:29:20, 11.63s/it]
{'loss': 0.5011, 'learning_rate': 1.877853078048673e-05, 'epoch': 0.18}
+
18%|█▊ | 2202/11952 [3:44:41<31:29:20, 11.63s/it]
18%|█▊ | 2203/11952 [3:44:47<26:47:36, 9.89s/it]
{'loss': 0.5011, 'learning_rate': 1.8777232603379012e-05, 'epoch': 0.18}
+
18%|█▊ | 2203/11952 [3:44:47<26:47:36, 9.89s/it]
18%|█▊ | 2204/11952 [3:44:52<23:31:07, 8.69s/it]
{'loss': 0.4967, 'learning_rate': 1.8775933781707836e-05, 'epoch': 0.18}
+
18%|█▊ | 2204/11952 [3:44:52<23:31:07, 8.69s/it]
18%|█▊ | 2205/11952 [3:44:58<21:22:36, 7.90s/it]
{'loss': 0.5074, 'learning_rate': 1.8774634315568583e-05, 'epoch': 0.18}
+
18%|█▊ | 2205/11952 [3:44:58<21:22:36, 7.90s/it]
18%|█▊ | 2206/11952 [3:45:04<19:39:45, 7.26s/it]
{'loss': 0.4919, 'learning_rate': 1.8773334205056687e-05, 'epoch': 0.18}
+
18%|█▊ | 2206/11952 [3:45:04<19:39:45, 7.26s/it]
18%|█▊ | 2207/11952 [3:45:10<18:31:12, 6.84s/it]
{'loss': 0.5044, 'learning_rate': 1.8772033450267617e-05, 'epoch': 0.18}
+
18%|█▊ | 2207/11952 [3:45:10<18:31:12, 6.84s/it]
18%|█▊ | 2208/11952 [3:45:16<17:31:32, 6.48s/it]
{'loss': 0.5007, 'learning_rate': 1.8770732051296895e-05, 'epoch': 0.18}
+
18%|█▊ | 2208/11952 [3:45:16<17:31:32, 6.48s/it]
18%|█▊ | 2209/11952 [3:45:22<17:07:27, 6.33s/it]
{'loss': 0.5067, 'learning_rate': 1.876943000824009e-05, 'epoch': 0.18}
+
18%|█▊ | 2209/11952 [3:45:22<17:07:27, 6.33s/it]
18%|█▊ | 2210/11952 [3:45:27<16:34:31, 6.13s/it]
{'loss': 0.4923, 'learning_rate': 1.8768127321192825e-05, 'epoch': 0.18}
+
18%|█▊ | 2210/11952 [3:45:27<16:34:31, 6.13s/it]
18%|█▊ | 2211/11952 [3:45:33<16:26:55, 6.08s/it]
{'loss': 0.4937, 'learning_rate': 1.8766823990250756e-05, 'epoch': 0.18}
+
18%|█▊ | 2211/11952 [3:45:33<16:26:55, 6.08s/it]
19%|█▊ | 2212/11952 [3:45:39<16:10:11, 5.98s/it]
{'loss': 0.5473, 'learning_rate': 1.8765520015509597e-05, 'epoch': 0.19}
+
19%|█▊ | 2212/11952 [3:45:39<16:10:11, 5.98s/it]
19%|█▊ | 2213/11952 [3:45:45<16:21:00, 6.04s/it]
{'loss': 0.5043, 'learning_rate': 1.8764215397065105e-05, 'epoch': 0.19}
+
19%|█▊ | 2213/11952 [3:45:45<16:21:00, 6.04s/it]
19%|█▊ | 2214/11952 [3:45:51<15:59:58, 5.91s/it]
{'loss': 0.4941, 'learning_rate': 1.8762910135013088e-05, 'epoch': 0.19}
+
19%|█▊ | 2214/11952 [3:45:51<15:59:58, 5.91s/it]
19%|█▊ | 2215/11952 [3:45:57<15:54:04, 5.88s/it]
{'loss': 0.5032, 'learning_rate': 1.8761604229449402e-05, 'epoch': 0.19}
+
19%|█▊ | 2215/11952 [3:45:57<15:54:04, 5.88s/it]
19%|█▊ | 2216/11952 [3:46:02<15:50:03, 5.85s/it]
{'loss': 0.4992, 'learning_rate': 1.8760297680469938e-05, 'epoch': 0.19}
+
19%|█▊ | 2216/11952 [3:46:02<15:50:03, 5.85s/it]
19%|█▊ | 2217/11952 [3:46:08<15:45:43, 5.83s/it]
{'loss': 0.4925, 'learning_rate': 1.875899048817065e-05, 'epoch': 0.19}
+
19%|█▊ | 2217/11952 [3:46:08<15:45:43, 5.83s/it]
19%|█▊ | 2218/11952 [3:46:14<15:57:17, 5.90s/it]
{'loss': 0.5178, 'learning_rate': 1.8757682652647538e-05, 'epoch': 0.19}
+
19%|█▊ | 2218/11952 [3:46:14<15:57:17, 5.90s/it]
19%|█▊ | 2219/11952 [3:46:21<16:13:34, 6.00s/it]
{'loss': 0.5141, 'learning_rate': 1.875637417399663e-05, 'epoch': 0.19}
+
19%|█▊ | 2219/11952 [3:46:21<16:13:34, 6.00s/it]
19%|█▊ | 2220/11952 [3:46:26<16:04:30, 5.95s/it]
{'loss': 0.4848, 'learning_rate': 1.875506505231403e-05, 'epoch': 0.19}
+
19%|█▊ | 2220/11952 [3:46:26<16:04:30, 5.95s/it]
19%|█▊ | 2221/11952 [3:46:32<15:59:48, 5.92s/it]
{'loss': 0.4989, 'learning_rate': 1.8753755287695866e-05, 'epoch': 0.19}
+
19%|█▊ | 2221/11952 [3:46:32<15:59:48, 5.92s/it]
19%|█▊ | 2222/11952 [3:46:38<15:59:17, 5.92s/it]
{'loss': 0.4951, 'learning_rate': 1.875244488023832e-05, 'epoch': 0.19}
+
19%|█▊ | 2222/11952 [3:46:38<15:59:17, 5.92s/it]
19%|█▊ | 2223/11952 [3:46:44<15:59:37, 5.92s/it]
{'loss': 0.4867, 'learning_rate': 1.875113383003763e-05, 'epoch': 0.19}
+
19%|█▊ | 2223/11952 [3:46:44<15:59:37, 5.92s/it]
19%|█▊ | 2224/11952 [3:46:50<15:58:20, 5.91s/it]
{'loss': 0.4955, 'learning_rate': 1.8749822137190065e-05, 'epoch': 0.19}
+
19%|█▊ | 2224/11952 [3:46:50<15:58:20, 5.91s/it]
19%|█▊ | 2225/11952 [3:46:56<15:47:39, 5.85s/it]
{'loss': 0.514, 'learning_rate': 1.8748509801791962e-05, 'epoch': 0.19}
+
19%|█▊ | 2225/11952 [3:46:56<15:47:39, 5.85s/it]
19%|█▊ | 2226/11952 [3:47:02<15:53:35, 5.88s/it]
{'loss': 0.4934, 'learning_rate': 1.874719682393968e-05, 'epoch': 0.19}
+
19%|█▊ | 2226/11952 [3:47:02<15:53:35, 5.88s/it]
19%|█▊ | 2227/11952 [3:47:07<15:42:07, 5.81s/it]
{'loss': 0.504, 'learning_rate': 1.8745883203729648e-05, 'epoch': 0.19}
+
19%|█▊ | 2227/11952 [3:47:07<15:42:07, 5.81s/it]
19%|█▊ | 2228/11952 [3:47:13<15:35:28, 5.77s/it]
{'loss': 0.5041, 'learning_rate': 1.8744568941258335e-05, 'epoch': 0.19}
+
19%|█▊ | 2228/11952 [3:47:13<15:35:28, 5.77s/it]
19%|█▊ | 2229/11952 [3:47:19<15:36:21, 5.78s/it]
{'loss': 0.4908, 'learning_rate': 1.8743254036622243e-05, 'epoch': 0.19}
+
19%|█▊ | 2229/11952 [3:47:19<15:36:21, 5.78s/it]
19%|█▊ | 2230/11952 [3:47:24<15:32:43, 5.76s/it]
{'loss': 0.5062, 'learning_rate': 1.874193848991795e-05, 'epoch': 0.19}
+
19%|█▊ | 2230/11952 [3:47:24<15:32:43, 5.76s/it]
19%|█▊ | 2231/11952 [3:47:30<15:35:12, 5.77s/it]
{'loss': 0.5084, 'learning_rate': 1.8740622301242045e-05, 'epoch': 0.19}
+
19%|█▊ | 2231/11952 [3:47:30<15:35:12, 5.77s/it]
19%|█▊ | 2232/11952 [3:47:36<15:29:53, 5.74s/it]
{'loss': 0.4935, 'learning_rate': 1.8739305470691197e-05, 'epoch': 0.19}
+
19%|█▊ | 2232/11952 [3:47:36<15:29:53, 5.74s/it]
19%|█▊ | 2233/11952 [3:47:41<15:17:49, 5.67s/it]
{'loss': 0.4952, 'learning_rate': 1.8737987998362106e-05, 'epoch': 0.19}
+
19%|█▊ | 2233/11952 [3:47:41<15:17:49, 5.67s/it]
19%|█▊ | 2234/11952 [3:47:47<15:31:16, 5.75s/it]
{'loss': 0.5139, 'learning_rate': 1.8736669884351523e-05, 'epoch': 0.19}
+
19%|█▊ | 2234/11952 [3:47:47<15:31:16, 5.75s/it]
19%|█▊ | 2235/11952 [3:47:53<15:36:04, 5.78s/it]
{'loss': 0.4954, 'learning_rate': 1.8735351128756238e-05, 'epoch': 0.19}
+
19%|█▊ | 2235/11952 [3:47:53<15:36:04, 5.78s/it]
19%|█▊ | 2236/11952 [3:47:59<16:01:19, 5.94s/it]
{'loss': 0.5215, 'learning_rate': 1.8734031731673096e-05, 'epoch': 0.19}
+
19%|█▊ | 2236/11952 [3:47:59<16:01:19, 5.94s/it]
19%|█▊ | 2237/11952 [3:48:05<15:57:39, 5.91s/it]
{'loss': 0.5039, 'learning_rate': 1.8732711693199e-05, 'epoch': 0.19}
+
19%|█▊ | 2237/11952 [3:48:05<15:57:39, 5.91s/it]
19%|█▊ | 2238/11952 [3:48:11<15:55:57, 5.90s/it]
{'loss': 0.5171, 'learning_rate': 1.873139101343087e-05, 'epoch': 0.19}
+
19%|█▊ | 2238/11952 [3:48:11<15:55:57, 5.90s/it]
19%|█▊ | 2239/11952 [3:48:17<16:02:25, 5.95s/it]
{'loss': 0.4796, 'learning_rate': 1.8730069692465708e-05, 'epoch': 0.19}
+
19%|█▊ | 2239/11952 [3:48:17<16:02:25, 5.95s/it]
19%|█▊ | 2240/11952 [3:48:23<15:47:54, 5.86s/it]
{'loss': 0.5093, 'learning_rate': 1.8728747730400533e-05, 'epoch': 0.19}
+
19%|█▊ | 2240/11952 [3:48:23<15:47:54, 5.86s/it]
19%|█▉ | 2241/11952 [3:48:29<15:51:18, 5.88s/it]
{'loss': 0.5096, 'learning_rate': 1.872742512733243e-05, 'epoch': 0.19}
+
19%|█▉ | 2241/11952 [3:48:29<15:51:18, 5.88s/it]
19%|█▉ | 2242/11952 [3:48:35<15:51:30, 5.88s/it]
{'loss': 0.4824, 'learning_rate': 1.8726101883358534e-05, 'epoch': 0.19}
+
19%|█▉ | 2242/11952 [3:48:35<15:51:30, 5.88s/it]
19%|█▉ | 2243/11952 [3:48:40<15:46:52, 5.85s/it]
{'loss': 0.5057, 'learning_rate': 1.8724777998576006e-05, 'epoch': 0.19}
+
19%|█▉ | 2243/11952 [3:48:40<15:46:52, 5.85s/it]
19%|█▉ | 2244/11952 [3:48:46<15:45:47, 5.85s/it]
{'loss': 0.5089, 'learning_rate': 1.872345347308207e-05, 'epoch': 0.19}
+
19%|█▉ | 2244/11952 [3:48:46<15:45:47, 5.85s/it]
19%|█▉ | 2245/11952 [3:48:52<15:52:43, 5.89s/it]
{'loss': 0.501, 'learning_rate': 1.872212830697399e-05, 'epoch': 0.19}
+
19%|█▉ | 2245/11952 [3:48:52<15:52:43, 5.89s/it]
19%|█▉ | 2246/11952 [3:48:58<15:52:26, 5.89s/it]
{'loss': 0.5236, 'learning_rate': 1.8720802500349095e-05, 'epoch': 0.19}
+
19%|█▉ | 2246/11952 [3:48:58<15:52:26, 5.89s/it]
19%|█▉ | 2247/11952 [3:49:04<15:46:18, 5.85s/it]
{'loss': 0.5291, 'learning_rate': 1.871947605330473e-05, 'epoch': 0.19}
+
19%|█▉ | 2247/11952 [3:49:04<15:46:18, 5.85s/it]
19%|█▉ | 2248/11952 [3:49:10<15:47:07, 5.86s/it]
{'loss': 0.5228, 'learning_rate': 1.8718148965938312e-05, 'epoch': 0.19}
+
19%|█▉ | 2248/11952 [3:49:10<15:47:07, 5.86s/it]
19%|█▉ | 2249/11952 [3:49:15<15:32:52, 5.77s/it]
{'loss': 0.4989, 'learning_rate': 1.8716821238347296e-05, 'epoch': 0.19}
+
19%|█▉ | 2249/11952 [3:49:15<15:32:52, 5.77s/it]20 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 4AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+35 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
19%|█▉ | 2250/11952 [3:49:21<15:41:03, 5.82s/it]6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4978, 'learning_rate': 1.8715492870629183e-05, 'epoch': 0.19}
+
19%|█▉ | 2250/11952 [3:49:21<15:41:03, 5.82s/it]
19%|█▉ | 2251/11952 [3:49:27<15:30:20, 5.75s/it]
{'loss': 0.4955, 'learning_rate': 1.8714163862881527e-05, 'epoch': 0.19}
+
19%|█▉ | 2251/11952 [3:49:27<15:30:20, 5.75s/it]
19%|█▉ | 2252/11952 [3:49:33<15:30:52, 5.76s/it]
{'loss': 0.5113, 'learning_rate': 1.8712834215201918e-05, 'epoch': 0.19}
+
19%|█▉ | 2252/11952 [3:49:33<15:30:52, 5.76s/it]
19%|█▉ | 2253/11952 [3:49:39<15:35:43, 5.79s/it]
{'loss': 0.5227, 'learning_rate': 1.8711503927688007e-05, 'epoch': 0.19}
+
19%|█▉ | 2253/11952 [3:49:39<15:35:43, 5.79s/it]
19%|█▉ | 2254/11952 [3:49:44<15:40:19, 5.82s/it]
{'loss': 0.5006, 'learning_rate': 1.871017300043748e-05, 'epoch': 0.19}
+
19%|█▉ | 2254/11952 [3:49:44<15:40:19, 5.82s/it]
19%|█▉ | 2255/11952 [3:49:50<15:48:12, 5.87s/it]
{'loss': 0.5215, 'learning_rate': 1.8708841433548076e-05, 'epoch': 0.19}
+
19%|█▉ | 2255/11952 [3:49:50<15:48:12, 5.87s/it]
19%|█▉ | 2256/11952 [3:49:56<15:41:22, 5.83s/it]
{'loss': 0.5261, 'learning_rate': 1.8707509227117578e-05, 'epoch': 0.19}
+
19%|█▉ | 2256/11952 [3:49:56<15:41:22, 5.83s/it]
19%|█▉ | 2257/11952 [3:50:02<15:40:53, 5.82s/it]
{'loss': 0.5057, 'learning_rate': 1.8706176381243822e-05, 'epoch': 0.19}
+
19%|█▉ | 2257/11952 [3:50:02<15:40:53, 5.82s/it]
19%|█▉ | 2258/11952 [3:50:08<15:32:03, 5.77s/it]
{'loss': 0.4915, 'learning_rate': 1.8704842896024685e-05, 'epoch': 0.19}
+
19%|█▉ | 2258/11952 [3:50:08<15:32:03, 5.77s/it]
19%|█▉ | 2259/11952 [3:50:14<15:43:07, 5.84s/it]
{'loss': 0.4977, 'learning_rate': 1.8703508771558093e-05, 'epoch': 0.19}
+
19%|█▉ | 2259/11952 [3:50:14<15:43:07, 5.84s/it]
19%|█▉ | 2260/11952 [3:50:19<15:38:58, 5.81s/it]
{'loss': 0.4921, 'learning_rate': 1.8702174007942012e-05, 'epoch': 0.19}
+
19%|█▉ | 2260/11952 [3:50:19<15:38:58, 5.81s/it]
19%|█▉ | 2261/11952 [3:50:25<15:38:15, 5.81s/it]
{'loss': 0.4881, 'learning_rate': 1.870083860527447e-05, 'epoch': 0.19}
+
19%|█▉ | 2261/11952 [3:50:25<15:38:15, 5.81s/it]
19%|█▉ | 2262/11952 [3:50:31<15:49:03, 5.88s/it]
{'loss': 0.5051, 'learning_rate': 1.869950256365353e-05, 'epoch': 0.19}
+
19%|█▉ | 2262/11952 [3:50:31<15:49:03, 5.88s/it]
19%|█▉ | 2263/11952 [3:50:37<15:45:36, 5.86s/it]
{'loss': 0.5007, 'learning_rate': 1.8698165883177308e-05, 'epoch': 0.19}
+
19%|█▉ | 2263/11952 [3:50:37<15:45:36, 5.86s/it]
19%|█▉ | 2264/11952 [3:50:43<15:38:49, 5.81s/it]
{'loss': 0.5076, 'learning_rate': 1.8696828563943962e-05, 'epoch': 0.19}
+
19%|█▉ | 2264/11952 [3:50:43<15:38:49, 5.81s/it]
19%|█▉ | 2265/11952 [3:50:49<15:42:28, 5.84s/it]
{'loss': 0.4853, 'learning_rate': 1.8695490606051694e-05, 'epoch': 0.19}
+
19%|█▉ | 2265/11952 [3:50:49<15:42:28, 5.84s/it]
19%|█▉ | 2266/11952 [3:50:55<16:02:40, 5.96s/it]
{'loss': 0.5068, 'learning_rate': 1.8694152009598767e-05, 'epoch': 0.19}
+
19%|█▉ | 2266/11952 [3:50:55<16:02:40, 5.96s/it]
19%|█▉ | 2267/11952 [3:51:00<15:44:45, 5.85s/it]
{'loss': 0.4871, 'learning_rate': 1.8692812774683477e-05, 'epoch': 0.19}
+
19%|█▉ | 2267/11952 [3:51:00<15:44:45, 5.85s/it]
19%|█▉ | 2268/11952 [3:51:06<15:40:19, 5.83s/it]
{'loss': 0.4977, 'learning_rate': 1.8691472901404174e-05, 'epoch': 0.19}
+
19%|█▉ | 2268/11952 [3:51:06<15:40:19, 5.83s/it]
19%|█▉ | 2269/11952 [3:51:12<15:41:02, 5.83s/it]
{'loss': 0.4994, 'learning_rate': 1.8690132389859254e-05, 'epoch': 0.19}
+
19%|█▉ | 2269/11952 [3:51:12<15:41:02, 5.83s/it]
19%|█▉ | 2270/11952 [3:51:18<15:44:54, 5.86s/it]
{'loss': 0.4928, 'learning_rate': 1.868879124014715e-05, 'epoch': 0.19}
+
19%|█▉ | 2270/11952 [3:51:18<15:44:54, 5.86s/it]
19%|█▉ | 2271/11952 [3:51:24<15:45:36, 5.86s/it]
{'loss': 0.5154, 'learning_rate': 1.8687449452366362e-05, 'epoch': 0.19}
+
19%|█▉ | 2271/11952 [3:51:24<15:45:36, 5.86s/it]
19%|█▉ | 2272/11952 [3:51:30<15:46:54, 5.87s/it]
{'loss': 0.5094, 'learning_rate': 1.8686107026615418e-05, 'epoch': 0.19}
+
19%|█▉ | 2272/11952 [3:51:30<15:46:54, 5.87s/it]
19%|█▉ | 2273/11952 [3:51:36<15:54:23, 5.92s/it]
{'loss': 0.4799, 'learning_rate': 1.8684763962992903e-05, 'epoch': 0.19}
+
19%|█▉ | 2273/11952 [3:51:36<15:54:23, 5.92s/it]
19%|█▉ | 2274/11952 [3:51:42<15:56:14, 5.93s/it]
{'loss': 0.5091, 'learning_rate': 1.8683420261597445e-05, 'epoch': 0.19}
+
19%|█▉ | 2274/11952 [3:51:42<15:56:14, 5.93s/it]
19%|█▉ | 2275/11952 [3:51:47<15:47:30, 5.87s/it]
{'loss': 0.5067, 'learning_rate': 1.8682075922527717e-05, 'epoch': 0.19}
+
19%|█▉ | 2275/11952 [3:51:47<15:47:30, 5.87s/it]
19%|█▉ | 2276/11952 [3:51:54<16:08:10, 6.00s/it]
{'loss': 0.5016, 'learning_rate': 1.868073094588245e-05, 'epoch': 0.19}
+
19%|█▉ | 2276/11952 [3:51:54<16:08:10, 6.00s/it]
19%|█▉ | 2277/11952 [3:52:00<16:02:10, 5.97s/it]
{'loss': 0.5159, 'learning_rate': 1.8679385331760405e-05, 'epoch': 0.19}
+
19%|█▉ | 2277/11952 [3:52:00<16:02:10, 5.97s/it]
19%|█▉ | 2278/11952 [3:52:06<16:26:16, 6.12s/it]
{'loss': 0.5221, 'learning_rate': 1.8678039080260403e-05, 'epoch': 0.19}
+
19%|█▉ | 2278/11952 [3:52:06<16:26:16, 6.12s/it]
19%|█▉ | 2279/11952 [3:52:12<16:25:48, 6.11s/it]
{'loss': 0.4992, 'learning_rate': 1.8676692191481303e-05, 'epoch': 0.19}
+
19%|█▉ | 2279/11952 [3:52:12<16:25:48, 6.11s/it]
19%|█▉ | 2280/11952 [3:52:18<16:16:35, 6.06s/it]
{'loss': 0.5096, 'learning_rate': 1.867534466552202e-05, 'epoch': 0.19}
+
19%|█▉ | 2280/11952 [3:52:18<16:16:35, 6.06s/it]
19%|█▉ | 2281/11952 [3:52:24<16:09:33, 6.02s/it]
{'loss': 0.5064, 'learning_rate': 1.8673996502481507e-05, 'epoch': 0.19}
+
19%|█▉ | 2281/11952 [3:52:24<16:09:33, 6.02s/it]
19%|█▉ | 2282/11952 [3:52:30<15:54:01, 5.92s/it]
{'loss': 0.4879, 'learning_rate': 1.867264770245877e-05, 'epoch': 0.19}
+
19%|█▉ | 2282/11952 [3:52:30<15:54:01, 5.92s/it]
19%|█▉ | 2283/11952 [3:52:36<15:57:17, 5.94s/it]
{'loss': 0.5101, 'learning_rate': 1.8671298265552855e-05, 'epoch': 0.19}
+
19%|█▉ | 2283/11952 [3:52:36<15:57:17, 5.94s/it]
19%|█▉ | 2284/11952 [3:52:42<16:04:47, 5.99s/it]
{'loss': 0.5155, 'learning_rate': 1.8669948191862866e-05, 'epoch': 0.19}
+
19%|█▉ | 2284/11952 [3:52:42<16:04:47, 5.99s/it]
19%|█▉ | 2285/11952 [3:52:48<16:18:56, 6.08s/it]
{'loss': 0.5111, 'learning_rate': 1.866859748148794e-05, 'epoch': 0.19}
+
19%|█▉ | 2285/11952 [3:52:48<16:18:56, 6.08s/it]
19%|█▉ | 2286/11952 [3:52:54<16:08:00, 6.01s/it]
{'loss': 0.4805, 'learning_rate': 1.866724613452727e-05, 'epoch': 0.19}
+
19%|█▉ | 2286/11952 [3:52:54<16:08:00, 6.01s/it]
19%|█▉ | 2287/11952 [3:53:00<15:49:39, 5.90s/it]
{'loss': 0.5088, 'learning_rate': 1.8665894151080097e-05, 'epoch': 0.19}
+
19%|█▉ | 2287/11952 [3:53:00<15:49:39, 5.90s/it]
19%|█▉ | 2288/11952 [3:53:05<15:38:07, 5.82s/it]
{'loss': 0.5163, 'learning_rate': 1.8664541531245698e-05, 'epoch': 0.19}
+
19%|█▉ | 2288/11952 [3:53:05<15:38:07, 5.82s/it]
19%|█▉ | 2289/11952 [3:53:11<15:52:27, 5.91s/it]
{'loss': 0.5177, 'learning_rate': 1.866318827512341e-05, 'epoch': 0.19}
+
19%|█▉ | 2289/11952 [3:53:11<15:52:27, 5.91s/it]
19%|█▉ | 2290/11952 [3:53:17<15:38:36, 5.83s/it]
{'loss': 0.4867, 'learning_rate': 1.8661834382812608e-05, 'epoch': 0.19}
+
19%|█▉ | 2290/11952 [3:53:17<15:38:36, 5.83s/it]
19%|█▉ | 2291/11952 [3:53:23<15:42:44, 5.85s/it]
{'loss': 0.5183, 'learning_rate': 1.8660479854412713e-05, 'epoch': 0.19}
+
19%|█▉ | 2291/11952 [3:53:23<15:42:44, 5.85s/it]
19%|█▉ | 2292/11952 [3:53:29<15:38:16, 5.83s/it]
{'loss': 0.4917, 'learning_rate': 1.8659124690023205e-05, 'epoch': 0.19}
+
19%|█▉ | 2292/11952 [3:53:29<15:38:16, 5.83s/it]
19%|█▉ | 2293/11952 [3:53:35<15:38:06, 5.83s/it]
{'loss': 0.5098, 'learning_rate': 1.865776888974359e-05, 'epoch': 0.19}
+
19%|█▉ | 2293/11952 [3:53:35<15:38:06, 5.83s/it]
19%|█▉ | 2294/11952 [3:53:40<15:24:28, 5.74s/it]
{'loss': 0.4977, 'learning_rate': 1.865641245367344e-05, 'epoch': 0.19}
+
19%|█▉ | 2294/11952 [3:53:40<15:24:28, 5.74s/it]
19%|█▉ | 2295/11952 [3:53:46<15:33:02, 5.80s/it]
{'loss': 0.5151, 'learning_rate': 1.8655055381912367e-05, 'epoch': 0.19}
+
19%|█▉ | 2295/11952 [3:53:46<15:33:02, 5.80s/it]
19%|█▉ | 2296/11952 [3:53:52<15:32:09, 5.79s/it]
{'loss': 0.524, 'learning_rate': 1.8653697674560023e-05, 'epoch': 0.19}
+
19%|█▉ | 2296/11952 [3:53:52<15:32:09, 5.79s/it]
19%|█▉ | 2297/11952 [3:53:58<15:37:30, 5.83s/it]
{'loss': 0.4991, 'learning_rate': 1.8652339331716114e-05, 'epoch': 0.19}
+
19%|█▉ | 2297/11952 [3:53:58<15:37:30, 5.83s/it]
19%|█▉ | 2298/11952 [3:54:03<15:30:06, 5.78s/it]
{'loss': 0.5015, 'learning_rate': 1.8650980353480395e-05, 'epoch': 0.19}
+
19%|█▉ | 2298/11952 [3:54:03<15:30:06, 5.78s/it]
19%|█▉ | 2299/11952 [3:54:09<15:32:49, 5.80s/it]
{'loss': 0.5034, 'learning_rate': 1.8649620739952658e-05, 'epoch': 0.19}
+
19%|█▉ | 2299/11952 [3:54:09<15:32:49, 5.80s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ 7AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...1
+ AutoResumeHook: Checking whether to suspend...
+
+
19%|█▉ | 2300/11952 [3:54:15<15:46:38, 5.88s/it]3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4985, 'learning_rate': 1.8648260491232753e-05, 'epoch': 0.19}
+
19%|█▉ | 2300/11952 [3:54:15<15:46:38, 5.88s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
19%|█▉ | 2301/11952 [3:54:45<34:57:29, 13.04s/it]
{'loss': 0.4961, 'learning_rate': 1.8646899607420567e-05, 'epoch': 0.19}
+
19%|█▉ | 2301/11952 [3:54:45<34:57:29, 13.04s/it]
19%|█▉ | 2302/11952 [3:54:51<29:07:15, 10.86s/it]
{'loss': 0.5042, 'learning_rate': 1.8645538088616038e-05, 'epoch': 0.19}
+
19%|█▉ | 2302/11952 [3:54:51<29:07:15, 10.86s/it]
19%|█▉ | 2303/11952 [3:54:57<25:02:49, 9.34s/it]
{'loss': 0.5092, 'learning_rate': 1.8644175934919156e-05, 'epoch': 0.19}
+
19%|█▉ | 2303/11952 [3:54:57<25:02:49, 9.34s/it]
19%|█▉ | 2304/11952 [3:55:02<22:07:49, 8.26s/it]
{'loss': 0.507, 'learning_rate': 1.8642813146429943e-05, 'epoch': 0.19}
+
19%|█▉ | 2304/11952 [3:55:02<22:07:49, 8.26s/it]
19%|█▉ | 2305/11952 [3:55:08<20:12:57, 7.54s/it]
{'loss': 0.5064, 'learning_rate': 1.8641449723248482e-05, 'epoch': 0.19}
+
19%|█▉ | 2305/11952 [3:55:08<20:12:57, 7.54s/it]
19%|█▉ | 2306/11952 [3:55:14<18:50:08, 7.03s/it]
{'loss': 0.5085, 'learning_rate': 1.8640085665474898e-05, 'epoch': 0.19}
+
19%|█▉ | 2306/11952 [3:55:14<18:50:08, 7.03s/it]
19%|█▉ | 2307/11952 [3:55:20<17:54:08, 6.68s/it]
{'loss': 0.5056, 'learning_rate': 1.8638720973209353e-05, 'epoch': 0.19}
+
19%|█▉ | 2307/11952 [3:55:20<17:54:08, 6.68s/it]
19%|█▉ | 2308/11952 [3:55:26<17:15:56, 6.45s/it]
{'loss': 0.4972, 'learning_rate': 1.863735564655208e-05, 'epoch': 0.19}
+
19%|█▉ | 2308/11952 [3:55:26<17:15:56, 6.45s/it]
19%|█▉ | 2309/11952 [3:55:32<16:40:47, 6.23s/it]
{'loss': 0.509, 'learning_rate': 1.8635989685603327e-05, 'epoch': 0.19}
+
19%|█▉ | 2309/11952 [3:55:32<16:40:47, 6.23s/it]
19%|█▉ | 2310/11952 [3:55:37<16:27:16, 6.14s/it]
{'loss': 0.494, 'learning_rate': 1.8634623090463413e-05, 'epoch': 0.19}
+
19%|█▉ | 2310/11952 [3:55:38<16:27:16, 6.14s/it]
19%|█▉ | 2311/11952 [3:55:44<16:21:07, 6.11s/it]
{'loss': 0.4905, 'learning_rate': 1.8633255861232692e-05, 'epoch': 0.19}
+
19%|█▉ | 2311/11952 [3:55:44<16:21:07, 6.11s/it]
19%|█▉ | 2312/11952 [3:55:49<16:10:58, 6.04s/it]
{'loss': 0.5028, 'learning_rate': 1.863188799801157e-05, 'epoch': 0.19}
+
19%|█▉ | 2312/11952 [3:55:49<16:10:58, 6.04s/it]
19%|█▉ | 2313/11952 [3:55:55<15:42:46, 5.87s/it]
{'loss': 0.4914, 'learning_rate': 1.8630519500900495e-05, 'epoch': 0.19}
+
19%|█▉ | 2313/11952 [3:55:55<15:42:46, 5.87s/it]
19%|█▉ | 2314/11952 [3:56:01<15:31:43, 5.80s/it]
{'loss': 0.4912, 'learning_rate': 1.8629150369999967e-05, 'epoch': 0.19}
+
19%|█▉ | 2314/11952 [3:56:01<15:31:43, 5.80s/it]
19%|█▉ | 2315/11952 [3:56:07<15:41:02, 5.86s/it]
{'loss': 0.5075, 'learning_rate': 1.8627780605410528e-05, 'epoch': 0.19}
+
19%|█▉ | 2315/11952 [3:56:07<15:41:02, 5.86s/it]
19%|█▉ | 2316/11952 [3:56:12<15:45:16, 5.89s/it]
{'loss': 0.4992, 'learning_rate': 1.8626410207232762e-05, 'epoch': 0.19}
+
19%|█▉ | 2316/11952 [3:56:12<15:45:16, 5.89s/it]
19%|█▉ | 2317/11952 [3:56:18<15:42:54, 5.87s/it]
{'loss': 0.5166, 'learning_rate': 1.8625039175567316e-05, 'epoch': 0.19}
+
19%|█▉ | 2317/11952 [3:56:18<15:42:54, 5.87s/it]
19%|█▉ | 2318/11952 [3:56:24<15:34:49, 5.82s/it]
{'loss': 0.4918, 'learning_rate': 1.8623667510514867e-05, 'epoch': 0.19}
+
19%|█▉ | 2318/11952 [3:56:24<15:34:49, 5.82s/it]
19%|█▉ | 2319/11952 [3:56:30<15:27:57, 5.78s/it]
{'loss': 0.5128, 'learning_rate': 1.8622295212176142e-05, 'epoch': 0.19}
+
19%|█▉ | 2319/11952 [3:56:30<15:27:57, 5.78s/it]
19%|█▉ | 2320/11952 [3:56:36<15:39:04, 5.85s/it]
{'loss': 0.5005, 'learning_rate': 1.862092228065192e-05, 'epoch': 0.19}
+
19%|█▉ | 2320/11952 [3:56:36<15:39:04, 5.85s/it]
19%|█▉ | 2321/11952 [3:56:41<15:35:39, 5.83s/it]
{'loss': 0.4824, 'learning_rate': 1.861954871604302e-05, 'epoch': 0.19}
+
19%|█▉ | 2321/11952 [3:56:41<15:35:39, 5.83s/it]
19%|█▉ | 2322/11952 [3:56:47<15:31:16, 5.80s/it]
{'loss': 0.4942, 'learning_rate': 1.8618174518450317e-05, 'epoch': 0.19}
+
19%|█▉ | 2322/11952 [3:56:47<15:31:16, 5.80s/it]
19%|█▉ | 2323/11952 [3:56:53<15:45:37, 5.89s/it]
{'loss': 0.5031, 'learning_rate': 1.8616799687974724e-05, 'epoch': 0.19}
+
19%|█▉ | 2323/11952 [3:56:53<15:45:37, 5.89s/it]
19%|█▉ | 2324/11952 [3:56:59<15:36:43, 5.84s/it]
{'loss': 0.4922, 'learning_rate': 1.86154242247172e-05, 'epoch': 0.19}
+
19%|█▉ | 2324/11952 [3:56:59<15:36:43, 5.84s/it]Jun 10 12:31:35.206381 2592862 slurmstepd 0x155550ab8700: error: *** STEP 8825117.0 ON batch-block1-0014 CANCELLED AT 2025-06-10T12:31:35 DUE TO TIME LIMIT ***
+srun: Job step aborted: Waiting up to 122 seconds for job step to finish.
+srun: error: batch-block1-0014: task 0: Terminated
+srun: Terminating StepId=8825117.0
+srun: job 8828654 queued and waiting for resources
+srun: job 8828654 has been allocated resources
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+MASTER_ADDR=batch-block1-0014
+JobID: 8828654 | Full list: batch-block1-0014
+NETWORK=Efficient-Large-Model/VILA1.5-3b
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
+*****************************************
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+[2025-06-10 12:33:32,003] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,003] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,003] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,003] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,004] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,004] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,004] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,004] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 12:33:32,954] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 12:33:32,954] [INFO] [comm.py:625:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+[2025-06-10 12:33:32,954] [INFO] [comm.py:594:init_distributed] cdb=None
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+[2025-06-10 12:33:38,447] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 2.70B parameters
+
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 50%|█████ | 1/2 [00:02<00:02, 2.36s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:02<00:02, 2.39s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:02<00:02, 2.40s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:02<00:02, 2.43s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:02<00:02, 2.44s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:02<00:02, 2.44s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:02<00:02, 2.46s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.03s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.23s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.07s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.07s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.27s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.11s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.31s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.11s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.31s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.12s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.32s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.13s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:02<00:00, 1.33s/it]
+
Loading checkpoint shards: 50%|█████ | 1/2 [00:03<00:03, 3.07s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:03<00:00, 1.41s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:03<00:00, 1.66s/it]
+[2025-06-10 12:33:42,017] [WARNING] [partition_parameters.py:836:_post_init_method] param `probe` in SiglipMultiheadAttentionPoolingHead not on GPU so was not broadcasted from rank 0
+[2025-06-10 12:33:42,018] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.13B parameters
+[2025-06-10 12:33:42,487] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.15B parameters
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj'][Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj'][Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[dist-0-of-8] LlavaLlamaModel(
+ (llm): LlamaForCausalLM(
+ (model): LlamaModel(
+ (embed_tokens): Embedding(32000, 2560, padding_idx=0)
+ (layers): ModuleList(
+ (0-31): 32 x LlamaDecoderLayer(
+ (self_attn): LlamaFlashAttention2(
+ (q_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (k_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (v_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (o_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (rotary_emb): LlamaRotaryEmbedding()
+ )
+ (mlp): LlamaMLP(
+ (gate_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (up_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (down_proj): Linear(in_features=6912, out_features=2560, bias=False)
+ (act_fn): SiLU()
+ )
+ (input_layernorm): LlamaRMSNorm()
+ (post_attention_layernorm): LlamaRMSNorm()
+ )
+ )
+ (norm): LlamaRMSNorm()
+ )
+ (lm_head): Linear(in_features=2560, out_features=32000, bias=False)
+ )
+ (vision_tower): SiglipVisionTower(
+ (vision_tower): SiglipVisionModel(
+ (vision_model): SiglipVisionTransformer(
+ (embeddings): SiglipVisionEmbeddings(
+ (patch_embedding): Conv2d(3, 1152, kernel_size=(14, 14), stride=(14, 14), padding=valid)
+ (position_embedding): Embedding(729, 1152)
+ )
+ (encoder): SiglipEncoder(
+ (layers): ModuleList(
+ (0-26): 27 x SiglipEncoderLayer(
+ (self_attn): SiglipAttention(
+ (k_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (v_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (q_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (out_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layer_norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ (layer_norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ )
+ )
+ )
+ (post_layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (head): SiglipMultiheadAttentionPoolingHead(
+ (attention): MultiheadAttention(
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ )
+ )
+ )
+ )
+ (mm_projector): MultimodalProjector(
+ (layers): Sequential(
+ (0): DownSampleBlock()
+ (1): LayerNorm((4608,), eps=1e-05, elementwise_affine=True)
+ (2): Linear(in_features=4608, out_features=2560, bias=True)
+ (3): GELU(approximate='none')
+ (4): Linear(in_features=2560, out_features=2560, bias=True)
+ )
+ )
+)
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[dist-0-of-8] Tunable parameters:
+language model True
+[dist-0-of-8] vision tower True
+[dist-0-of-8] mm projector True
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8196439743041992
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8397250175476074
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8381266593933105
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8403162956237793
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.841041088104248
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8315768241882324
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8410830497741699
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8391642570495605
+Parameter Offload: Total persistent parameters: 593856 in 349 params
+wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.18.7
+wandb: Run data is saved locally in /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/wandb/run-20250610_123458-wmx1rsxo
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run vila_3b_path_mask
+wandb: ⭐️ View project at https://wandb.ai/memmelma/VILA
+wandb: 🚀 View run at https://wandb.ai/memmelma/VILA/runs/wmx1rsxo
+
0%| | 0/11952 [00:00, ?it/s]Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+
19%|█▉ | 2301/11952 [00:23<01:40, 95.98it/s]
{'loss': 0.4961, 'learning_rate': 1.8646899607420567e-05, 'epoch': 0.19}
+
19%|█▉ | 2301/11952 [00:23<01:40, 95.98it/s]
{'loss': 0.5044, 'learning_rate': 1.8645538088616038e-05, 'epoch': 0.19}
+
19%|█▉ | 2302/11952 [00:29<01:40, 95.98it/s]
19%|█▉ | 2302/11952 [00:35<01:40, 95.98it/s]
19%|█▉ | 2303/11952 [00:35<02:49, 57.04it/s]
{'loss': 0.5092, 'learning_rate': 1.8644175934919156e-05, 'epoch': 0.19}
+
19%|█▉ | 2303/11952 [00:35<02:49, 57.04it/s]
19%|█▉ | 2304/11952 [00:41<03:37, 44.40it/s]
{'loss': 0.5069, 'learning_rate': 1.8642813146429943e-05, 'epoch': 0.19}
+
19%|█▉ | 2304/11952 [00:41<03:37, 44.40it/s]
19%|█▉ | 2305/11952 [00:46<04:48, 33.48it/s]
{'loss': 0.5064, 'learning_rate': 1.8641449723248482e-05, 'epoch': 0.19}
+
19%|█▉ | 2305/11952 [00:46<04:48, 33.48it/s]
19%|█▉ | 2306/11952 [00:52<06:28, 24.85it/s]
{'loss': 0.5085, 'learning_rate': 1.8640085665474898e-05, 'epoch': 0.19}
+
19%|█▉ | 2306/11952 [00:52<06:28, 24.85it/s]
19%|█▉ | 2307/11952 [00:58<08:52, 18.12it/s]
{'loss': 0.5056, 'learning_rate': 1.8638720973209353e-05, 'epoch': 0.19}
+
19%|█▉ | 2307/11952 [00:58<08:52, 18.12it/s]
19%|█▉ | 2308/11952 [01:04<12:18, 13.05it/s]
{'loss': 0.4973, 'learning_rate': 1.863735564655208e-05, 'epoch': 0.19}
+
19%|█▉ | 2308/11952 [01:04<12:18, 13.05it/s]
19%|█▉ | 2309/11952 [01:10<17:00, 9.45it/s]
{'loss': 0.5089, 'learning_rate': 1.8635989685603327e-05, 'epoch': 0.19}
+
19%|█▉ | 2309/11952 [01:10<17:00, 9.45it/s]
19%|█▉ | 2310/11952 [01:16<23:53, 6.73it/s]
{'loss': 0.4941, 'learning_rate': 1.8634623090463413e-05, 'epoch': 0.19}
+
19%|█▉ | 2310/11952 [01:16<23:53, 6.73it/s]
19%|█▉ | 2311/11952 [01:22<33:42, 4.77it/s]
{'loss': 0.4903, 'learning_rate': 1.8633255861232692e-05, 'epoch': 0.19}
+
19%|█▉ | 2311/11952 [01:22<33:42, 4.77it/s]
19%|█▉ | 2312/11952 [01:28<47:05, 3.41it/s]
{'loss': 0.5029, 'learning_rate': 1.863188799801157e-05, 'epoch': 0.19}
+
19%|█▉ | 2312/11952 [01:28<47:05, 3.41it/s]
19%|█▉ | 2313/11952 [01:33<1:04:06, 2.51it/s]
{'loss': 0.4915, 'learning_rate': 1.8630519500900495e-05, 'epoch': 0.19}
+
19%|█▉ | 2313/11952 [01:33<1:04:06, 2.51it/s]
19%|█▉ | 2314/11952 [01:39<1:27:59, 1.83it/s]
{'loss': 0.4913, 'learning_rate': 1.8629150369999967e-05, 'epoch': 0.19}
+
19%|█▉ | 2314/11952 [01:39<1:27:59, 1.83it/s]
19%|█▉ | 2315/11952 [01:45<2:02:13, 1.31it/s]
{'loss': 0.5075, 'learning_rate': 1.8627780605410528e-05, 'epoch': 0.19}
+
19%|█▉ | 2315/11952 [01:45<2:02:13, 1.31it/s]
19%|█▉ | 2316/11952 [01:51<2:46:17, 1.04s/it]
{'loss': 0.4993, 'learning_rate': 1.8626410207232762e-05, 'epoch': 0.19}
+
19%|█▉ | 2316/11952 [01:51<2:46:17, 1.04s/it]
19%|█▉ | 2317/11952 [01:56<3:40:14, 1.37s/it]
{'loss': 0.5164, 'learning_rate': 1.8625039175567316e-05, 'epoch': 0.19}
+
19%|█▉ | 2317/11952 [01:56<3:40:14, 1.37s/it]
19%|█▉ | 2318/11952 [02:02<4:43:20, 1.76s/it]
{'loss': 0.4919, 'learning_rate': 1.8623667510514867e-05, 'epoch': 0.19}
+
19%|█▉ | 2318/11952 [02:02<4:43:20, 1.76s/it]
19%|█▉ | 2319/11952 [02:08<5:55:39, 2.22s/it]
{'loss': 0.5125, 'learning_rate': 1.8622295212176142e-05, 'epoch': 0.19}
+
19%|█▉ | 2319/11952 [02:08<5:55:39, 2.22s/it]
19%|█▉ | 2320/11952 [02:14<7:21:20, 2.75s/it]
{'loss': 0.5005, 'learning_rate': 1.862092228065192e-05, 'epoch': 0.19}
+
19%|█▉ | 2320/11952 [02:14<7:21:20, 2.75s/it]
19%|█▉ | 2321/11952 [02:20<8:42:43, 3.26s/it]
{'loss': 0.4824, 'learning_rate': 1.861954871604302e-05, 'epoch': 0.19}
+
19%|█▉ | 2321/11952 [02:20<8:42:43, 3.26s/it]
19%|█▉ | 2322/11952 [02:25<9:59:37, 3.74s/it]
{'loss': 0.4943, 'learning_rate': 1.8618174518450317e-05, 'epoch': 0.19}
+
19%|█▉ | 2322/11952 [02:25<9:59:37, 3.74s/it]
19%|█▉ | 2323/11952 [02:31<11:21:55, 4.25s/it]
{'loss': 0.5029, 'learning_rate': 1.8616799687974724e-05, 'epoch': 0.19}
+
19%|█▉ | 2323/11952 [02:31<11:21:55, 4.25s/it]
19%|█▉ | 2324/11952 [02:37<12:16:54, 4.59s/it]
{'loss': 0.4923, 'learning_rate': 1.86154242247172e-05, 'epoch': 0.19}
+
19%|█▉ | 2324/11952 [02:37<12:16:54, 4.59s/it]
19%|█▉ | 2325/11952 [02:43<13:01:12, 4.87s/it]
{'loss': 0.5028, 'learning_rate': 1.8614048128778755e-05, 'epoch': 0.19}
+
19%|█▉ | 2325/11952 [02:43<13:01:12, 4.87s/it]
19%|█▉ | 2326/11952 [02:49<13:46:13, 5.15s/it]
{'loss': 0.4956, 'learning_rate': 1.8612671400260445e-05, 'epoch': 0.19}
+
19%|█▉ | 2326/11952 [02:49<13:46:13, 5.15s/it]
19%|█▉ | 2327/11952 [02:55<14:33:39, 5.45s/it]
{'loss': 0.5067, 'learning_rate': 1.861129403926337e-05, 'epoch': 0.19}
+
19%|█▉ | 2327/11952 [02:55<14:33:39, 5.45s/it]
19%|█▉ | 2328/11952 [03:01<14:37:03, 5.47s/it]
{'loss': 0.4775, 'learning_rate': 1.8609916045888677e-05, 'epoch': 0.19}
+
19%|█▉ | 2328/11952 [03:01<14:37:03, 5.47s/it]
19%|█▉ | 2329/11952 [03:06<14:41:13, 5.49s/it]
{'loss': 0.4859, 'learning_rate': 1.860853742023756e-05, 'epoch': 0.19}
+
19%|█▉ | 2329/11952 [03:06<14:41:13, 5.49s/it]
19%|█▉ | 2330/11952 [03:12<15:00:28, 5.62s/it]
{'loss': 0.5, 'learning_rate': 1.860715816241126e-05, 'epoch': 0.19}
+
19%|█▉ | 2330/11952 [03:12<15:00:28, 5.62s/it]
20%|█▉ | 2331/11952 [03:18<15:24:25, 5.77s/it]
{'loss': 0.5103, 'learning_rate': 1.860577827251107e-05, 'epoch': 0.2}
+
20%|█▉ | 2331/11952 [03:18<15:24:25, 5.77s/it]
20%|█▉ | 2332/11952 [03:24<15:32:37, 5.82s/it]
{'loss': 0.5085, 'learning_rate': 1.8604397750638314e-05, 'epoch': 0.2}
+
20%|█▉ | 2332/11952 [03:24<15:32:37, 5.82s/it]
20%|█▉ | 2333/11952 [03:30<15:27:57, 5.79s/it]
{'loss': 0.4992, 'learning_rate': 1.8603016596894375e-05, 'epoch': 0.2}
+
20%|█▉ | 2333/11952 [03:30<15:27:57, 5.79s/it]
20%|█▉ | 2334/11952 [03:36<15:34:51, 5.83s/it]
{'loss': 0.5093, 'learning_rate': 1.860163481138068e-05, 'epoch': 0.2}
+
20%|█▉ | 2334/11952 [03:36<15:34:51, 5.83s/it]
20%|█▉ | 2335/11952 [03:42<15:42:15, 5.88s/it]
{'loss': 0.5172, 'learning_rate': 1.8600252394198702e-05, 'epoch': 0.2}
+
20%|█▉ | 2335/11952 [03:42<15:42:15, 5.88s/it]
20%|█▉ | 2336/11952 [03:47<15:25:46, 5.78s/it]
{'loss': 0.4971, 'learning_rate': 1.8598869345449957e-05, 'epoch': 0.2}
+
20%|█▉ | 2336/11952 [03:47<15:25:46, 5.78s/it]
20%|█▉ | 2337/11952 [03:53<15:29:27, 5.80s/it]
{'loss': 0.5007, 'learning_rate': 1.8597485665236016e-05, 'epoch': 0.2}
+
20%|█▉ | 2337/11952 [03:53<15:29:27, 5.80s/it]
20%|█▉ | 2338/11952 [03:59<15:25:08, 5.77s/it]
{'loss': 0.4957, 'learning_rate': 1.8596101353658488e-05, 'epoch': 0.2}
+
20%|█▉ | 2338/11952 [03:59<15:25:08, 5.77s/it]
20%|█▉ | 2339/11952 [04:05<15:29:02, 5.80s/it]
{'loss': 0.4941, 'learning_rate': 1.8594716410819027e-05, 'epoch': 0.2}
+
20%|█▉ | 2339/11952 [04:05<15:29:02, 5.80s/it]
20%|█▉ | 2340/11952 [04:10<15:23:28, 5.76s/it]
{'loss': 0.4833, 'learning_rate': 1.8593330836819342e-05, 'epoch': 0.2}
+
20%|█▉ | 2340/11952 [04:10<15:23:28, 5.76s/it]
20%|█▉ | 2341/11952 [04:16<15:16:05, 5.72s/it]
{'loss': 0.4959, 'learning_rate': 1.8591944631761185e-05, 'epoch': 0.2}
+
20%|█▉ | 2341/11952 [04:16<15:16:05, 5.72s/it]
20%|█▉ | 2342/11952 [04:22<15:32:56, 5.82s/it]
{'loss': 0.5065, 'learning_rate': 1.859055779574635e-05, 'epoch': 0.2}
+
20%|█▉ | 2342/11952 [04:22<15:32:56, 5.82s/it]
20%|█▉ | 2343/11952 [04:28<15:39:35, 5.87s/it]
{'loss': 0.5085, 'learning_rate': 1.858917032887668e-05, 'epoch': 0.2}
+
20%|█▉ | 2343/11952 [04:28<15:39:35, 5.87s/it]
20%|█▉ | 2344/11952 [04:34<15:40:12, 5.87s/it]
{'loss': 0.5195, 'learning_rate': 1.8587782231254065e-05, 'epoch': 0.2}
+
20%|█▉ | 2344/11952 [04:34<15:40:12, 5.87s/it]
20%|█▉ | 2345/11952 [04:40<15:45:08, 5.90s/it]
{'loss': 0.5003, 'learning_rate': 1.8586393502980442e-05, 'epoch': 0.2}
+
20%|█▉ | 2345/11952 [04:40<15:45:08, 5.90s/it]
20%|█▉ | 2346/11952 [04:46<15:46:56, 5.91s/it]
{'loss': 0.4933, 'learning_rate': 1.8585004144157798e-05, 'epoch': 0.2}
+
20%|█▉ | 2346/11952 [04:46<15:46:56, 5.91s/it]
20%|█▉ | 2347/11952 [04:52<15:40:44, 5.88s/it]
{'loss': 0.5186, 'learning_rate': 1.8583614154888154e-05, 'epoch': 0.2}
+
20%|█▉ | 2347/11952 [04:52<15:40:44, 5.88s/it]
20%|█▉ | 2348/11952 [04:58<15:56:20, 5.97s/it]
{'loss': 0.4988, 'learning_rate': 1.8582223535273587e-05, 'epoch': 0.2}
+
20%|█▉ | 2348/11952 [04:58<15:56:20, 5.97s/it]
20%|█▉ | 2349/11952 [05:04<15:47:02, 5.92s/it]
{'loss': 0.5032, 'learning_rate': 1.8580832285416223e-05, 'epoch': 0.2}
+
20%|█▉ | 2349/11952 [05:04<15:47:02, 5.92s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
20%|█▉ | 2350/11952 [05:09<15:35:28, 5.85s/it]4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5109, 'learning_rate': 1.8579440405418222e-05, 'epoch': 0.2}
+
20%|█▉ | 2350/11952 [05:09<15:35:28, 5.85s/it]
20%|█▉ | 2351/11952 [05:15<15:31:47, 5.82s/it]
{'loss': 0.503, 'learning_rate': 1.857804789538181e-05, 'epoch': 0.2}
+
20%|█▉ | 2351/11952 [05:15<15:31:47, 5.82s/it]
20%|█▉ | 2352/11952 [05:21<15:54:45, 5.97s/it]
{'loss': 0.5101, 'learning_rate': 1.8576654755409233e-05, 'epoch': 0.2}
+
20%|█▉ | 2352/11952 [05:21<15:54:45, 5.97s/it]
20%|█▉ | 2353/11952 [05:27<15:45:15, 5.91s/it]
{'loss': 0.5242, 'learning_rate': 1.8575260985602806e-05, 'epoch': 0.2}
+
20%|█▉ | 2353/11952 [05:27<15:45:15, 5.91s/it]
20%|█▉ | 2354/11952 [05:33<15:34:18, 5.84s/it]
{'loss': 0.5165, 'learning_rate': 1.8573866586064877e-05, 'epoch': 0.2}
+
20%|█▉ | 2354/11952 [05:33<15:34:18, 5.84s/it]
20%|█▉ | 2355/11952 [05:39<15:46:40, 5.92s/it]
{'loss': 0.5158, 'learning_rate': 1.857247155689785e-05, 'epoch': 0.2}
+
20%|█▉ | 2355/11952 [05:39<15:46:40, 5.92s/it]
20%|█▉ | 2356/11952 [05:45<15:39:54, 5.88s/it]
{'loss': 0.4967, 'learning_rate': 1.8571075898204167e-05, 'epoch': 0.2}
+
20%|█▉ | 2356/11952 [05:45<15:39:54, 5.88s/it]
20%|█▉ | 2357/11952 [05:50<15:33:07, 5.84s/it]
{'loss': 0.5094, 'learning_rate': 1.856967961008632e-05, 'epoch': 0.2}
+
20%|█▉ | 2357/11952 [05:50<15:33:07, 5.84s/it]
20%|█▉ | 2358/11952 [05:56<15:33:55, 5.84s/it]
{'loss': 0.4908, 'learning_rate': 1.8568282692646844e-05, 'epoch': 0.2}
+
20%|█▉ | 2358/11952 [05:56<15:33:55, 5.84s/it]
20%|█▉ | 2359/11952 [06:02<15:22:03, 5.77s/it]
{'loss': 0.48, 'learning_rate': 1.8566885145988326e-05, 'epoch': 0.2}
+
20%|█▉ | 2359/11952 [06:02<15:22:03, 5.77s/it]
20%|█▉ | 2360/11952 [06:08<15:27:14, 5.80s/it]
{'loss': 0.5177, 'learning_rate': 1.8565486970213397e-05, 'epoch': 0.2}
+
20%|█▉ | 2360/11952 [06:08<15:27:14, 5.80s/it]
20%|█▉ | 2361/11952 [06:14<15:36:56, 5.86s/it]
{'loss': 0.496, 'learning_rate': 1.8564088165424733e-05, 'epoch': 0.2}
+
20%|█▉ | 2361/11952 [06:14<15:36:56, 5.86s/it]
20%|█▉ | 2362/11952 [06:20<16:00:48, 6.01s/it]
{'loss': 0.5195, 'learning_rate': 1.8562688731725053e-05, 'epoch': 0.2}
+
20%|█▉ | 2362/11952 [06:20<16:00:48, 6.01s/it]
20%|█▉ | 2363/11952 [06:26<15:56:06, 5.98s/it]
{'loss': 0.4852, 'learning_rate': 1.8561288669217125e-05, 'epoch': 0.2}
+
20%|█▉ | 2363/11952 [06:26<15:56:06, 5.98s/it]
20%|█▉ | 2364/11952 [06:32<15:47:58, 5.93s/it]
{'loss': 0.4954, 'learning_rate': 1.8559887978003766e-05, 'epoch': 0.2}
+
20%|█▉ | 2364/11952 [06:32<15:47:58, 5.93s/it]
20%|█▉ | 2365/11952 [06:38<15:45:08, 5.92s/it]
{'loss': 0.5074, 'learning_rate': 1.8558486658187843e-05, 'epoch': 0.2}
+
20%|█▉ | 2365/11952 [06:38<15:45:08, 5.92s/it]
20%|█▉ | 2366/11952 [06:43<15:30:57, 5.83s/it]
{'loss': 0.4885, 'learning_rate': 1.8557084709872253e-05, 'epoch': 0.2}
+
20%|█▉ | 2366/11952 [06:43<15:30:57, 5.83s/it]
20%|█▉ | 2367/11952 [06:49<15:30:04, 5.82s/it]
{'loss': 0.4868, 'learning_rate': 1.8555682133159952e-05, 'epoch': 0.2}
+
20%|█▉ | 2367/11952 [06:49<15:30:04, 5.82s/it]
20%|█▉ | 2368/11952 [06:55<15:35:29, 5.86s/it]
{'loss': 0.5194, 'learning_rate': 1.8554278928153942e-05, 'epoch': 0.2}
+
20%|█▉ | 2368/11952 [06:55<15:35:29, 5.86s/it]
20%|█▉ | 2369/11952 [07:01<15:44:44, 5.92s/it]
{'loss': 0.4986, 'learning_rate': 1.855287509495727e-05, 'epoch': 0.2}
+
20%|█▉ | 2369/11952 [07:01<15:44:44, 5.92s/it]
20%|█▉ | 2370/11952 [07:07<15:46:48, 5.93s/it]
{'loss': 0.5032, 'learning_rate': 1.8551470633673023e-05, 'epoch': 0.2}
+
20%|█▉ | 2370/11952 [07:07<15:46:48, 5.93s/it]
20%|█▉ | 2371/11952 [07:13<15:36:52, 5.87s/it]
{'loss': 0.5006, 'learning_rate': 1.855006554440434e-05, 'epoch': 0.2}
+
20%|█▉ | 2371/11952 [07:13<15:36:52, 5.87s/it]
20%|█▉ | 2372/11952 [07:19<15:40:54, 5.89s/it]
{'loss': 0.5124, 'learning_rate': 1.8548659827254408e-05, 'epoch': 0.2}
+
20%|█▉ | 2372/11952 [07:19<15:40:54, 5.89s/it]
20%|█▉ | 2373/11952 [07:25<15:39:29, 5.88s/it]
{'loss': 0.4894, 'learning_rate': 1.8547253482326458e-05, 'epoch': 0.2}
+
20%|█▉ | 2373/11952 [07:25<15:39:29, 5.88s/it]
20%|█▉ | 2374/11952 [07:30<15:38:18, 5.88s/it]
{'loss': 0.5089, 'learning_rate': 1.8545846509723757e-05, 'epoch': 0.2}
+
20%|█▉ | 2374/11952 [07:30<15:38:18, 5.88s/it]
20%|█▉ | 2375/11952 [07:36<15:30:25, 5.83s/it]
{'loss': 0.4991, 'learning_rate': 1.8544438909549636e-05, 'epoch': 0.2}
+
20%|█▉ | 2375/11952 [07:36<15:30:25, 5.83s/it]
20%|█▉ | 2376/11952 [07:42<15:40:35, 5.89s/it]
{'loss': 0.5044, 'learning_rate': 1.854303068190746e-05, 'epoch': 0.2}
+
20%|█▉ | 2376/11952 [07:42<15:40:35, 5.89s/it]
20%|█▉ | 2377/11952 [07:48<15:48:13, 5.94s/it]
{'loss': 0.5011, 'learning_rate': 1.854162182690064e-05, 'epoch': 0.2}
+
20%|█▉ | 2377/11952 [07:48<15:48:13, 5.94s/it]
20%|█▉ | 2378/11952 [07:54<15:42:23, 5.91s/it]
{'loss': 0.4879, 'learning_rate': 1.8540212344632646e-05, 'epoch': 0.2}
+
20%|█▉ | 2378/11952 [07:54<15:42:23, 5.91s/it]
20%|█▉ | 2379/11952 [08:00<15:53:52, 5.98s/it]
{'loss': 0.5249, 'learning_rate': 1.8538802235206977e-05, 'epoch': 0.2}
+
20%|█▉ | 2379/11952 [08:00<15:53:52, 5.98s/it]
20%|█▉ | 2380/11952 [08:06<15:40:25, 5.89s/it]
{'loss': 0.489, 'learning_rate': 1.8537391498727187e-05, 'epoch': 0.2}
+
20%|█▉ | 2380/11952 [08:06<15:40:25, 5.89s/it]
20%|█▉ | 2381/11952 [08:12<15:52:17, 5.97s/it]
{'loss': 0.5214, 'learning_rate': 1.8535980135296876e-05, 'epoch': 0.2}
+
20%|█▉ | 2381/11952 [08:12<15:52:17, 5.97s/it]
20%|█▉ | 2382/11952 [08:18<15:46:59, 5.94s/it]
{'loss': 0.5325, 'learning_rate': 1.8534568145019687e-05, 'epoch': 0.2}
+
20%|█▉ | 2382/11952 [08:18<15:46:59, 5.94s/it]
20%|█▉ | 2383/11952 [08:24<15:47:20, 5.94s/it]
{'loss': 0.5143, 'learning_rate': 1.853315552799931e-05, 'epoch': 0.2}
+
20%|█▉ | 2383/11952 [08:24<15:47:20, 5.94s/it]
20%|█▉ | 2384/11952 [08:30<15:54:34, 5.99s/it]
{'loss': 0.5069, 'learning_rate': 1.8531742284339486e-05, 'epoch': 0.2}
+
20%|█▉ | 2384/11952 [08:30<15:54:34, 5.99s/it]
20%|█▉ | 2385/11952 [08:36<15:45:22, 5.93s/it]
{'loss': 0.4942, 'learning_rate': 1.853032841414399e-05, 'epoch': 0.2}
+
20%|█▉ | 2385/11952 [08:36<15:45:22, 5.93s/it]
20%|█▉ | 2386/11952 [08:42<15:36:12, 5.87s/it]
{'loss': 0.4831, 'learning_rate': 1.852891391751666e-05, 'epoch': 0.2}
+
20%|█▉ | 2386/11952 [08:42<15:36:12, 5.87s/it]
20%|█▉ | 2387/11952 [08:47<15:28:04, 5.82s/it]
{'loss': 0.4999, 'learning_rate': 1.8527498794561367e-05, 'epoch': 0.2}
+
20%|█▉ | 2387/11952 [08:47<15:28:04, 5.82s/it]
20%|█▉ | 2388/11952 [08:53<15:22:46, 5.79s/it]
{'loss': 0.4998, 'learning_rate': 1.8526083045382025e-05, 'epoch': 0.2}
+
20%|█▉ | 2388/11952 [08:53<15:22:46, 5.79s/it]
20%|█▉ | 2389/11952 [08:59<15:13:09, 5.73s/it]
{'loss': 0.5075, 'learning_rate': 1.852466667008261e-05, 'epoch': 0.2}
+
20%|█▉ | 2389/11952 [08:59<15:13:09, 5.73s/it]
20%|█▉ | 2390/11952 [09:04<15:06:17, 5.69s/it]
{'loss': 0.5047, 'learning_rate': 1.8523249668767135e-05, 'epoch': 0.2}
+
20%|█▉ | 2390/11952 [09:04<15:06:17, 5.69s/it]
20%|██ | 2391/11952 [09:10<15:08:20, 5.70s/it]
{'loss': 0.5177, 'learning_rate': 1.852183204153965e-05, 'epoch': 0.2}
+
20%|██ | 2391/11952 [09:10<15:08:20, 5.70s/it]
20%|██ | 2392/11952 [09:15<15:02:13, 5.66s/it]
{'loss': 0.486, 'learning_rate': 1.852041378850427e-05, 'epoch': 0.2}
+
20%|██ | 2392/11952 [09:15<15:02:13, 5.66s/it]
20%|██ | 2393/11952 [09:21<15:15:28, 5.75s/it]
{'loss': 0.4809, 'learning_rate': 1.851899490976514e-05, 'epoch': 0.2}
+
20%|██ | 2393/11952 [09:21<15:15:28, 5.75s/it]
20%|██ | 2394/11952 [09:27<15:24:03, 5.80s/it]
{'loss': 0.5098, 'learning_rate': 1.851757540542645e-05, 'epoch': 0.2}
+
20%|██ | 2394/11952 [09:27<15:24:03, 5.80s/it]
20%|██ | 2395/11952 [09:33<15:38:14, 5.89s/it]
{'loss': 0.4916, 'learning_rate': 1.8516155275592457e-05, 'epoch': 0.2}
+
20%|██ | 2395/11952 [09:33<15:38:14, 5.89s/it]
20%|██ | 2396/11952 [09:39<15:35:20, 5.87s/it]
{'loss': 0.5143, 'learning_rate': 1.8514734520367438e-05, 'epoch': 0.2}
+
20%|██ | 2396/11952 [09:39<15:35:20, 5.87s/it]
20%|██ | 2397/11952 [09:45<15:52:20, 5.98s/it]
{'loss': 0.4984, 'learning_rate': 1.8513313139855734e-05, 'epoch': 0.2}
+
20%|██ | 2397/11952 [09:45<15:52:20, 5.98s/it]
20%|██ | 2398/11952 [09:51<15:48:40, 5.96s/it]
{'loss': 0.4834, 'learning_rate': 1.8511891134161718e-05, 'epoch': 0.2}
+
20%|██ | 2398/11952 [09:51<15:48:40, 5.96s/it]
20%|██ | 2399/11952 [09:57<15:40:55, 5.91s/it]
{'loss': 0.4972, 'learning_rate': 1.8510468503389825e-05, 'epoch': 0.2}
+
20%|██ | 2399/11952 [09:57<15:40:55, 5.91s/it]5 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...1
+ AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
20%|██ | 2400/11952 [10:03<15:43:22, 5.93s/it]6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4988, 'learning_rate': 1.8509045247644524e-05, 'epoch': 0.2}
+
20%|██ | 2400/11952 [10:03<15:43:22, 5.93s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
20%|██ | 2401/11952 [10:39<39:12:08, 14.78s/it]
{'loss': 0.5079, 'learning_rate': 1.8507621367030326e-05, 'epoch': 0.2}
+
20%|██ | 2401/11952 [10:39<39:12:08, 14.78s/it]
20%|██ | 2402/11952 [10:45<32:17:09, 12.17s/it]
{'loss': 0.514, 'learning_rate': 1.8506196861651802e-05, 'epoch': 0.2}
+
20%|██ | 2402/11952 [10:45<32:17:09, 12.17s/it]
20%|██ | 2403/11952 [10:50<27:13:48, 10.27s/it]
{'loss': 0.4905, 'learning_rate': 1.8504771731613568e-05, 'epoch': 0.2}
+
20%|██ | 2403/11952 [10:50<27:13:48, 10.27s/it]
20%|██ | 2404/11952 [10:56<23:50:33, 8.99s/it]
{'loss': 0.5006, 'learning_rate': 1.8503345977020262e-05, 'epoch': 0.2}
+
20%|██ | 2404/11952 [10:56<23:50:33, 8.99s/it]
20%|██ | 2405/11952 [11:02<21:19:13, 8.04s/it]
{'loss': 0.4949, 'learning_rate': 1.8501919597976602e-05, 'epoch': 0.2}
+
20%|██ | 2405/11952 [11:02<21:19:13, 8.04s/it]
20%|██ | 2406/11952 [11:08<19:31:44, 7.36s/it]
{'loss': 0.5129, 'learning_rate': 1.850049259458733e-05, 'epoch': 0.2}
+
20%|██ | 2406/11952 [11:08<19:31:44, 7.36s/it]
20%|██ | 2407/11952 [11:14<18:28:15, 6.97s/it]
{'loss': 0.498, 'learning_rate': 1.8499064966957233e-05, 'epoch': 0.2}
+
20%|██ | 2407/11952 [11:14<18:28:15, 6.97s/it]
20%|██ | 2408/11952 [11:20<17:30:18, 6.60s/it]
{'loss': 0.499, 'learning_rate': 1.8497636715191153e-05, 'epoch': 0.2}
+
20%|██ | 2408/11952 [11:20<17:30:18, 6.60s/it]
20%|██ | 2409/11952 [11:25<16:41:44, 6.30s/it]
{'loss': 0.4932, 'learning_rate': 1.8496207839393984e-05, 'epoch': 0.2}
+
20%|██ | 2409/11952 [11:25<16:41:44, 6.30s/it]
20%|██ | 2410/11952 [11:32<16:30:14, 6.23s/it]
{'loss': 0.5081, 'learning_rate': 1.849477833967065e-05, 'epoch': 0.2}
+
20%|██ | 2410/11952 [11:32<16:30:14, 6.23s/it]
20%|██ | 2411/11952 [11:37<16:17:10, 6.15s/it]
{'loss': 0.497, 'learning_rate': 1.849334821612612e-05, 'epoch': 0.2}
+
20%|██ | 2411/11952 [11:37<16:17:10, 6.15s/it]
20%|██ | 2412/11952 [11:43<15:55:52, 6.01s/it]
{'loss': 0.5113, 'learning_rate': 1.8491917468865426e-05, 'epoch': 0.2}
+
20%|██ | 2412/11952 [11:43<15:55:52, 6.01s/it]
20%|██ | 2413/11952 [11:49<15:33:39, 5.87s/it]
{'loss': 0.5037, 'learning_rate': 1.8490486097993635e-05, 'epoch': 0.2}
+
20%|██ | 2413/11952 [11:49<15:33:39, 5.87s/it]
20%|██ | 2414/11952 [11:55<16:05:45, 6.08s/it]
{'loss': 0.4858, 'learning_rate': 1.848905410361586e-05, 'epoch': 0.2}
+
20%|██ | 2414/11952 [11:55<16:05:45, 6.08s/it]
20%|██ | 2415/11952 [12:01<15:35:21, 5.88s/it]
{'loss': 0.4957, 'learning_rate': 1.848762148583726e-05, 'epoch': 0.2}
+
20%|██ | 2415/11952 [12:01<15:35:21, 5.88s/it]
20%|██ | 2416/11952 [12:06<15:27:34, 5.84s/it]
{'loss': 0.5217, 'learning_rate': 1.8486188244763038e-05, 'epoch': 0.2}
+
20%|██ | 2416/11952 [12:06<15:27:34, 5.84s/it]
20%|██ | 2417/11952 [12:12<15:32:13, 5.87s/it]
{'loss': 0.496, 'learning_rate': 1.8484754380498452e-05, 'epoch': 0.2}
+
20%|██ | 2417/11952 [12:12<15:32:13, 5.87s/it]
20%|██ | 2418/11952 [12:18<15:22:33, 5.81s/it]
{'loss': 0.4957, 'learning_rate': 1.8483319893148794e-05, 'epoch': 0.2}
+
20%|██ | 2418/11952 [12:18<15:22:33, 5.81s/it]
20%|██ | 2419/11952 [12:24<15:25:34, 5.83s/it]
{'loss': 0.4935, 'learning_rate': 1.848188478281941e-05, 'epoch': 0.2}
+
20%|██ | 2419/11952 [12:24<15:25:34, 5.83s/it]
20%|██ | 2420/11952 [12:30<15:18:53, 5.78s/it]
{'loss': 0.4964, 'learning_rate': 1.8480449049615684e-05, 'epoch': 0.2}
+
20%|██ | 2420/11952 [12:30<15:18:53, 5.78s/it]
20%|██ | 2421/11952 [12:36<15:32:33, 5.87s/it]
{'loss': 0.4948, 'learning_rate': 1.847901269364305e-05, 'epoch': 0.2}
+
20%|██ | 2421/11952 [12:36<15:32:33, 5.87s/it]
20%|██ | 2422/11952 [12:41<15:19:56, 5.79s/it]
{'loss': 0.4968, 'learning_rate': 1.847757571500699e-05, 'epoch': 0.2}
+
20%|██ | 2422/11952 [12:41<15:19:56, 5.79s/it]
20%|██ | 2423/11952 [12:47<15:17:25, 5.78s/it]
{'loss': 0.5153, 'learning_rate': 1.8476138113813037e-05, 'epoch': 0.2}
+
20%|██ | 2423/11952 [12:47<15:17:25, 5.78s/it]
20%|██ | 2424/11952 [12:53<15:37:41, 5.90s/it]
{'loss': 0.513, 'learning_rate': 1.8474699890166753e-05, 'epoch': 0.2}
+
20%|██ | 2424/11952 [12:53<15:37:41, 5.90s/it]
20%|██ | 2425/11952 [12:59<15:20:36, 5.80s/it]
{'loss': 0.5264, 'learning_rate': 1.8473261044173756e-05, 'epoch': 0.2}
+
20%|██ | 2425/11952 [12:59<15:20:36, 5.80s/it]
20%|██ | 2426/11952 [13:05<15:29:48, 5.86s/it]
{'loss': 0.4933, 'learning_rate': 1.8471821575939713e-05, 'epoch': 0.2}
+
20%|██ | 2426/11952 [13:05<15:29:48, 5.86s/it]
20%|██ | 2427/11952 [13:10<15:18:28, 5.79s/it]
{'loss': 0.5192, 'learning_rate': 1.8470381485570327e-05, 'epoch': 0.2}
+
20%|██ | 2427/11952 [13:10<15:18:28, 5.79s/it]
20%|██ | 2428/11952 [13:16<15:31:09, 5.87s/it]
{'loss': 0.4959, 'learning_rate': 1.8468940773171357e-05, 'epoch': 0.2}
+
20%|██ | 2428/11952 [13:16<15:31:09, 5.87s/it]
20%|██ | 2429/11952 [13:23<15:40:27, 5.93s/it]
{'loss': 0.5083, 'learning_rate': 1.8467499438848606e-05, 'epoch': 0.2}
+
20%|██ | 2429/11952 [13:23<15:40:27, 5.93s/it]
20%|██ | 2430/11952 [13:28<15:42:16, 5.94s/it]
{'loss': 0.5058, 'learning_rate': 1.846605748270791e-05, 'epoch': 0.2}
+
20%|██ | 2430/11952 [13:28<15:42:16, 5.94s/it]
20%|██ | 2431/11952 [13:35<15:50:17, 5.99s/it]
{'loss': 0.5126, 'learning_rate': 1.8464614904855168e-05, 'epoch': 0.2}
+
20%|██ | 2431/11952 [13:35<15:50:17, 5.99s/it]
20%|██ | 2432/11952 [13:40<15:46:17, 5.96s/it]
{'loss': 0.5123, 'learning_rate': 1.8463171705396313e-05, 'epoch': 0.2}
+
20%|██ | 2432/11952 [13:40<15:46:17, 5.96s/it]
20%|██ | 2433/11952 [13:46<15:38:45, 5.92s/it]
{'loss': 0.4949, 'learning_rate': 1.846172788443733e-05, 'epoch': 0.2}
+
20%|██ | 2433/11952 [13:46<15:38:45, 5.92s/it]
20%|██ | 2434/11952 [13:52<15:29:26, 5.86s/it]
{'loss': 0.497, 'learning_rate': 1.8460283442084246e-05, 'epoch': 0.2}
+
20%|██ | 2434/11952 [13:52<15:29:26, 5.86s/it]
20%|██ | 2435/11952 [13:58<15:40:47, 5.93s/it]
{'loss': 0.5059, 'learning_rate': 1.8458838378443134e-05, 'epoch': 0.2}
+
20%|██ | 2435/11952 [13:58<15:40:47, 5.93s/it]
20%|██ | 2436/11952 [14:04<15:34:06, 5.89s/it]
{'loss': 0.5048, 'learning_rate': 1.8457392693620114e-05, 'epoch': 0.2}
+
20%|██ | 2436/11952 [14:04<15:34:06, 5.89s/it]
20%|██ | 2437/11952 [14:10<15:44:32, 5.96s/it]
{'loss': 0.518, 'learning_rate': 1.8455946387721356e-05, 'epoch': 0.2}
+
20%|██ | 2437/11952 [14:10<15:44:32, 5.96s/it]
20%|██ | 2438/11952 [14:16<15:33:46, 5.89s/it]
{'loss': 0.5013, 'learning_rate': 1.845449946085306e-05, 'epoch': 0.2}
+
20%|██ | 2438/11952 [14:16<15:33:46, 5.89s/it]
20%|██ | 2439/11952 [14:22<15:36:52, 5.91s/it]
{'loss': 0.4975, 'learning_rate': 1.8453051913121494e-05, 'epoch': 0.2}
+
20%|██ | 2439/11952 [14:22<15:36:52, 5.91s/it]
20%|██ | 2440/11952 [14:28<15:37:00, 5.91s/it]
{'loss': 0.504, 'learning_rate': 1.8451603744632952e-05, 'epoch': 0.2}
+
20%|██ | 2440/11952 [14:28<15:37:00, 5.91s/it]
20%|██ | 2441/11952 [14:33<15:22:40, 5.82s/it]
{'loss': 0.5083, 'learning_rate': 1.845015495549378e-05, 'epoch': 0.2}
+
20%|██ | 2441/11952 [14:33<15:22:40, 5.82s/it]
20%|██ | 2442/11952 [14:39<15:26:18, 5.84s/it]
{'loss': 0.5114, 'learning_rate': 1.844870554581038e-05, 'epoch': 0.2}
+
20%|██ | 2442/11952 [14:39<15:26:18, 5.84s/it]
20%|██ | 2443/11952 [14:45<15:33:27, 5.89s/it]
{'loss': 0.4908, 'learning_rate': 1.8447255515689185e-05, 'epoch': 0.2}
+
20%|██ | 2443/11952 [14:45<15:33:27, 5.89s/it]
20%|██ | 2444/11952 [14:51<15:30:51, 5.87s/it]
{'loss': 0.4994, 'learning_rate': 1.844580486523668e-05, 'epoch': 0.2}
+
20%|██ | 2444/11952 [14:51<15:30:51, 5.87s/it]
20%|██ | 2445/11952 [14:57<15:18:00, 5.79s/it]
{'loss': 0.5013, 'learning_rate': 1.8444353594559392e-05, 'epoch': 0.2}
+
20%|██ | 2445/11952 [14:57<15:18:00, 5.79s/it]
20%|██ | 2446/11952 [15:02<15:14:31, 5.77s/it]
{'loss': 0.5016, 'learning_rate': 1.84429017037639e-05, 'epoch': 0.2}
+
20%|██ | 2446/11952 [15:02<15:14:31, 5.77s/it]
20%|██ | 2447/11952 [15:08<15:06:37, 5.72s/it]
{'loss': 0.5037, 'learning_rate': 1.8441449192956823e-05, 'epoch': 0.2}
+
20%|██ | 2447/11952 [15:08<15:06:37, 5.72s/it]
20%|██ | 2448/11952 [15:14<15:00:30, 5.68s/it]
{'loss': 0.4919, 'learning_rate': 1.8439996062244828e-05, 'epoch': 0.2}
+
20%|██ | 2448/11952 [15:14<15:00:30, 5.68s/it]
20%|██ | 2449/11952 [15:19<15:02:18, 5.70s/it]
{'loss': 0.4875, 'learning_rate': 1.843854231173463e-05, 'epoch': 0.2}
+
20%|██ | 2449/11952 [15:19<15:02:18, 5.70s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ 3 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...6
+
+AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
20%|██ | 2450/11952 [15:25<14:57:53, 5.67s/it]
{'loss': 0.4861, 'learning_rate': 1.8437087941532982e-05, 'epoch': 0.2}
+
20%|██ | 2450/11952 [15:25<14:57:53, 5.67s/it]
21%|██ | 2451/11952 [15:31<15:09:48, 5.75s/it]
{'loss': 0.5123, 'learning_rate': 1.8435632951746685e-05, 'epoch': 0.21}
+
21%|██ | 2451/11952 [15:31<15:09:48, 5.75s/it]
21%|██ | 2452/11952 [15:36<15:05:42, 5.72s/it]
{'loss': 0.4923, 'learning_rate': 1.8434177342482594e-05, 'epoch': 0.21}
+
21%|██ | 2452/11952 [15:36<15:05:42, 5.72s/it]
21%|██ | 2453/11952 [15:42<15:05:27, 5.72s/it]
{'loss': 0.5275, 'learning_rate': 1.8432721113847596e-05, 'epoch': 0.21}
+
21%|██ | 2453/11952 [15:42<15:05:27, 5.72s/it]
21%|██ | 2454/11952 [15:48<15:26:43, 5.85s/it]
{'loss': 0.529, 'learning_rate': 1.8431264265948636e-05, 'epoch': 0.21}
+
21%|██ | 2454/11952 [15:48<15:26:43, 5.85s/it]
21%|██ | 2455/11952 [15:54<15:15:50, 5.79s/it]
{'loss': 0.5048, 'learning_rate': 1.8429806798892694e-05, 'epoch': 0.21}
+
21%|██ | 2455/11952 [15:54<15:15:50, 5.79s/it]
21%|██ | 2456/11952 [16:00<15:13:02, 5.77s/it]
{'loss': 0.485, 'learning_rate': 1.8428348712786803e-05, 'epoch': 0.21}
+
21%|██ | 2456/11952 [16:00<15:13:02, 5.77s/it]
21%|██ | 2457/11952 [16:05<15:06:20, 5.73s/it]
{'loss': 0.5057, 'learning_rate': 1.842689000773804e-05, 'epoch': 0.21}
+
21%|██ | 2457/11952 [16:05<15:06:20, 5.73s/it]
21%|██ | 2458/11952 [16:11<15:13:04, 5.77s/it]
{'loss': 0.5013, 'learning_rate': 1.8425430683853527e-05, 'epoch': 0.21}
+
21%|██ | 2458/11952 [16:11<15:13:04, 5.77s/it]
21%|██ | 2459/11952 [16:17<15:22:38, 5.83s/it]
{'loss': 0.4978, 'learning_rate': 1.8423970741240426e-05, 'epoch': 0.21}
+
21%|██ | 2459/11952 [16:17<15:22:38, 5.83s/it]
21%|██ | 2460/11952 [16:23<15:21:34, 5.83s/it]
{'loss': 0.4971, 'learning_rate': 1.842251018000595e-05, 'epoch': 0.21}
+
21%|██ | 2460/11952 [16:23<15:21:34, 5.83s/it]
21%|██ | 2461/11952 [16:29<15:24:36, 5.85s/it]
{'loss': 0.5246, 'learning_rate': 1.8421049000257362e-05, 'epoch': 0.21}
+
21%|██ | 2461/11952 [16:29<15:24:36, 5.85s/it]
21%|██ | 2462/11952 [16:35<15:26:39, 5.86s/it]
{'loss': 0.4989, 'learning_rate': 1.841958720210196e-05, 'epoch': 0.21}
+
21%|██ | 2462/11952 [16:35<15:26:39, 5.86s/it]
21%|██ | 2463/11952 [16:41<15:34:40, 5.91s/it]
{'loss': 0.5098, 'learning_rate': 1.8418124785647092e-05, 'epoch': 0.21}
+
21%|██ | 2463/11952 [16:41<15:34:40, 5.91s/it]
21%|██ | 2464/11952 [16:47<15:44:13, 5.97s/it]
{'loss': 0.5075, 'learning_rate': 1.8416661751000156e-05, 'epoch': 0.21}
+
21%|██ | 2464/11952 [16:47<15:44:13, 5.97s/it]
21%|██ | 2465/11952 [16:53<15:37:16, 5.93s/it]
{'loss': 0.4991, 'learning_rate': 1.841519809826859e-05, 'epoch': 0.21}
+
21%|██ | 2465/11952 [16:53<15:37:16, 5.93s/it]
21%|██ | 2466/11952 [16:58<15:22:10, 5.83s/it]
{'loss': 0.4971, 'learning_rate': 1.8413733827559873e-05, 'epoch': 0.21}
+
21%|██ | 2466/11952 [16:58<15:22:10, 5.83s/it]
21%|██ | 2467/11952 [17:04<15:23:19, 5.84s/it]
{'loss': 0.5031, 'learning_rate': 1.841226893898154e-05, 'epoch': 0.21}
+
21%|██ | 2467/11952 [17:04<15:23:19, 5.84s/it]
21%|██ | 2468/11952 [17:10<15:22:36, 5.84s/it]
{'loss': 0.4909, 'learning_rate': 1.8410803432641165e-05, 'epoch': 0.21}
+
21%|██ | 2468/11952 [17:10<15:22:36, 5.84s/it]
21%|██ | 2469/11952 [17:16<15:32:42, 5.90s/it]
{'loss': 0.5077, 'learning_rate': 1.840933730864637e-05, 'epoch': 0.21}
+
21%|██ | 2469/11952 [17:16<15:32:42, 5.90s/it]
21%|██ | 2470/11952 [17:22<15:36:04, 5.92s/it]
{'loss': 0.5273, 'learning_rate': 1.840787056710482e-05, 'epoch': 0.21}
+
21%|██ | 2470/11952 [17:22<15:36:04, 5.92s/it]
21%|██ | 2471/11952 [17:28<15:49:17, 6.01s/it]
{'loss': 0.5063, 'learning_rate': 1.8406403208124227e-05, 'epoch': 0.21}
+
21%|██ | 2471/11952 [17:28<15:49:17, 6.01s/it]
21%|██ | 2472/11952 [17:34<15:38:24, 5.94s/it]
{'loss': 0.5041, 'learning_rate': 1.8404935231812348e-05, 'epoch': 0.21}
+
21%|██ | 2472/11952 [17:34<15:38:24, 5.94s/it]
21%|██ | 2473/11952 [17:40<15:25:25, 5.86s/it]
{'loss': 0.493, 'learning_rate': 1.8403466638276983e-05, 'epoch': 0.21}
+
21%|██ | 2473/11952 [17:40<15:25:25, 5.86s/it]
21%|██ | 2474/11952 [17:45<15:23:29, 5.85s/it]
{'loss': 0.4928, 'learning_rate': 1.840199742762598e-05, 'epoch': 0.21}
+
21%|██ | 2474/11952 [17:45<15:23:29, 5.85s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
21%|██ | 2475/11952 [17:52<15:35:38, 5.92s/it]
{'loss': 0.506, 'learning_rate': 1.840052759996723e-05, 'epoch': 0.21}
+
21%|██ | 2475/11952 [17:52<15:35:38, 5.92s/it]
21%|██ | 2476/11952 [17:57<15:26:11, 5.86s/it]
{'loss': 0.503, 'learning_rate': 1.839905715540868e-05, 'epoch': 0.21}
+
21%|██ | 2476/11952 [17:57<15:26:11, 5.86s/it]
21%|██ | 2477/11952 [18:03<15:15:21, 5.80s/it]
{'loss': 0.4865, 'learning_rate': 1.8397586094058303e-05, 'epoch': 0.21}
+
21%|██ | 2477/11952 [18:03<15:15:21, 5.80s/it]
21%|██ | 2478/11952 [18:09<15:23:58, 5.85s/it]
{'loss': 0.4936, 'learning_rate': 1.839611441602413e-05, 'epoch': 0.21}
+
21%|██ | 2478/11952 [18:09<15:23:58, 5.85s/it]
21%|██ | 2479/11952 [18:15<15:13:42, 5.79s/it]
{'loss': 0.501, 'learning_rate': 1.8394642121414238e-05, 'epoch': 0.21}
+
21%|██ | 2479/11952 [18:15<15:13:42, 5.79s/it]
21%|██ | 2480/11952 [18:20<15:11:37, 5.77s/it]
{'loss': 0.4826, 'learning_rate': 1.8393169210336747e-05, 'epoch': 0.21}
+
21%|██ | 2480/11952 [18:20<15:11:37, 5.77s/it]
21%|██ | 2481/11952 [18:26<15:02:02, 5.71s/it]
{'loss': 0.5122, 'learning_rate': 1.8391695682899814e-05, 'epoch': 0.21}
+
21%|██ | 2481/11952 [18:26<15:02:02, 5.71s/it]
21%|██ | 2482/11952 [18:32<15:03:07, 5.72s/it]
{'loss': 0.5038, 'learning_rate': 1.839022153921166e-05, 'epoch': 0.21}
+
21%|██ | 2482/11952 [18:32<15:03:07, 5.72s/it]
21%|██ | 2483/11952 [18:38<15:17:43, 5.82s/it]
{'loss': 0.4954, 'learning_rate': 1.8388746779380532e-05, 'epoch': 0.21}
+
21%|██ | 2483/11952 [18:38<15:17:43, 5.82s/it]
21%|██ | 2484/11952 [18:44<15:19:51, 5.83s/it]
{'loss': 0.5098, 'learning_rate': 1.838727140351473e-05, 'epoch': 0.21}
+
21%|██ | 2484/11952 [18:44<15:19:51, 5.83s/it]
21%|██ | 2485/11952 [18:49<15:15:42, 5.80s/it]
{'loss': 0.4984, 'learning_rate': 1.83857954117226e-05, 'epoch': 0.21}
+
21%|██ | 2485/11952 [18:49<15:15:42, 5.80s/it]
21%|██ | 2486/11952 [18:55<15:27:49, 5.88s/it]
{'loss': 0.5117, 'learning_rate': 1.8384318804112533e-05, 'epoch': 0.21}
+
21%|██ | 2486/11952 [18:55<15:27:49, 5.88s/it]
21%|██ | 2487/11952 [19:01<15:24:04, 5.86s/it]
{'loss': 0.4905, 'learning_rate': 1.838284158079297e-05, 'epoch': 0.21}
+
21%|██ | 2487/11952 [19:01<15:24:04, 5.86s/it]
21%|██ | 2488/11952 [19:07<15:17:05, 5.81s/it]
{'loss': 0.4969, 'learning_rate': 1.8381363741872386e-05, 'epoch': 0.21}
+
21%|██ | 2488/11952 [19:07<15:17:05, 5.81s/it]
21%|██ | 2489/11952 [19:13<15:15:37, 5.81s/it]
{'loss': 0.5055, 'learning_rate': 1.8379885287459315e-05, 'epoch': 0.21}
+
21%|██ | 2489/11952 [19:13<15:15:37, 5.81s/it]
21%|██ | 2490/11952 [19:18<15:09:07, 5.76s/it]
{'loss': 0.4903, 'learning_rate': 1.8378406217662314e-05, 'epoch': 0.21}
+
21%|██ | 2490/11952 [19:18<15:09:07, 5.76s/it]
21%|██ | 2491/11952 [19:24<15:14:11, 5.80s/it]
{'loss': 0.4854, 'learning_rate': 1.8376926532590012e-05, 'epoch': 0.21}
+
21%|██ | 2491/11952 [19:24<15:14:11, 5.80s/it]
21%|██ | 2492/11952 [19:30<15:08:34, 5.76s/it]
{'loss': 0.5033, 'learning_rate': 1.837544623235107e-05, 'epoch': 0.21}
+
21%|██ | 2492/11952 [19:30<15:08:34, 5.76s/it]
21%|██ | 2493/11952 [19:36<15:30:11, 5.90s/it]
{'loss': 0.5127, 'learning_rate': 1.8373965317054195e-05, 'epoch': 0.21}
+
21%|██ | 2493/11952 [19:36<15:30:11, 5.90s/it]
21%|██ | 2494/11952 [19:42<15:20:26, 5.84s/it]
{'loss': 0.488, 'learning_rate': 1.8372483786808133e-05, 'epoch': 0.21}
+
21%|██ | 2494/11952 [19:42<15:20:26, 5.84s/it]
21%|██ | 2495/11952 [19:48<15:23:26, 5.86s/it]
{'loss': 0.4882, 'learning_rate': 1.8371001641721685e-05, 'epoch': 0.21}
+
21%|██ | 2495/11952 [19:48<15:23:26, 5.86s/it]
21%|██ | 2496/11952 [19:53<15:14:51, 5.80s/it]
{'loss': 0.5022, 'learning_rate': 1.8369518881903698e-05, 'epoch': 0.21}
+
21%|██ | 2496/11952 [19:53<15:14:51, 5.80s/it]
21%|██ | 2497/11952 [20:00<15:30:42, 5.91s/it]
{'loss': 0.4967, 'learning_rate': 1.8368035507463053e-05, 'epoch': 0.21}
+
21%|██ | 2497/11952 [20:00<15:30:42, 5.91s/it]
21%|██ | 2498/11952 [20:05<15:14:48, 5.81s/it]
{'loss': 0.4857, 'learning_rate': 1.8366551518508685e-05, 'epoch': 0.21}
+
21%|██ | 2498/11952 [20:05<15:14:48, 5.81s/it]
21%|██ | 2499/11952 [20:11<15:09:17, 5.77s/it]
{'loss': 0.4862, 'learning_rate': 1.8365066915149573e-05, 'epoch': 0.21}
+
21%|██ | 2499/11952 [20:11<15:09:17, 5.77s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 6AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
21%|██ | 2500/11952 [20:17<15:12:41, 5.79s/it]
{'loss': 0.4842, 'learning_rate': 1.8363581697494738e-05, 'epoch': 0.21}
+
21%|██ | 2500/11952 [20:17<15:12:41, 5.79s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
21%|██ | 2501/11952 [20:50<36:39:09, 13.96s/it]
{'loss': 0.4985, 'learning_rate': 1.8362095865653257e-05, 'epoch': 0.21}
+
21%|██ | 2501/11952 [20:50<36:39:09, 13.96s/it]
21%|██ | 2502/11952 [20:55<30:14:23, 11.52s/it]
{'loss': 0.5008, 'learning_rate': 1.8360609419734227e-05, 'epoch': 0.21}
+
21%|██ | 2502/11952 [20:55<30:14:23, 11.52s/it]
21%|██ | 2503/11952 [21:01<25:53:09, 9.86s/it]
{'loss': 0.5087, 'learning_rate': 1.835912235984682e-05, 'epoch': 0.21}
+
21%|██ | 2503/11952 [21:01<25:53:09, 9.86s/it]
21%|██ | 2504/11952 [21:07<22:42:09, 8.65s/it]
{'loss': 0.4947, 'learning_rate': 1.8357634686100236e-05, 'epoch': 0.21}
+
21%|██ | 2504/11952 [21:07<22:42:09, 8.65s/it]
21%|██ | 2505/11952 [21:13<20:34:29, 7.84s/it]
{'loss': 0.4921, 'learning_rate': 1.835614639860372e-05, 'epoch': 0.21}
+
21%|██ | 2505/11952 [21:13<20:34:29, 7.84s/it]
21%|██ | 2506/11952 [21:19<18:59:26, 7.24s/it]
{'loss': 0.4997, 'learning_rate': 1.835465749746657e-05, 'epoch': 0.21}
+
21%|██ | 2506/11952 [21:19<18:59:26, 7.24s/it]
21%|██ | 2507/11952 [21:25<17:57:36, 6.85s/it]
{'loss': 0.5113, 'learning_rate': 1.8353167982798124e-05, 'epoch': 0.21}
+
21%|██ | 2507/11952 [21:25<17:57:36, 6.85s/it]
21%|██ | 2508/11952 [21:31<17:02:40, 6.50s/it]
{'loss': 0.4809, 'learning_rate': 1.8351677854707763e-05, 'epoch': 0.21}
+
21%|██ | 2508/11952 [21:31<17:02:40, 6.50s/it]
21%|██ | 2509/11952 [21:37<16:34:39, 6.32s/it]
{'loss': 0.5035, 'learning_rate': 1.8350187113304918e-05, 'epoch': 0.21}
+
21%|██ | 2509/11952 [21:37<16:34:39, 6.32s/it]
21%|██ | 2510/11952 [21:42<16:12:19, 6.18s/it]
{'loss': 0.5228, 'learning_rate': 1.8348695758699065e-05, 'epoch': 0.21}
+
21%|██ | 2510/11952 [21:42<16:12:19, 6.18s/it]
21%|██ | 2511/11952 [21:48<15:55:03, 6.07s/it]
{'loss': 0.5196, 'learning_rate': 1.8347203790999716e-05, 'epoch': 0.21}
+
21%|██ | 2511/11952 [21:48<15:55:03, 6.07s/it]
21%|██ | 2512/11952 [21:54<16:01:22, 6.11s/it]
{'loss': 0.4999, 'learning_rate': 1.834571121031644e-05, 'epoch': 0.21}
+
21%|██ | 2512/11952 [21:54<16:01:22, 6.11s/it]
21%|██ | 2513/11952 [22:00<15:52:13, 6.05s/it]
{'loss': 0.5013, 'learning_rate': 1.8344218016758847e-05, 'epoch': 0.21}
+
21%|██ | 2513/11952 [22:00<15:52:13, 6.05s/it]
21%|██ | 2514/11952 [22:06<15:40:38, 5.98s/it]
{'loss': 0.5062, 'learning_rate': 1.834272421043659e-05, 'epoch': 0.21}
+
21%|██ | 2514/11952 [22:06<15:40:38, 5.98s/it]
21%|██ | 2515/11952 [22:12<15:44:13, 6.00s/it]
{'loss': 0.5037, 'learning_rate': 1.8341229791459365e-05, 'epoch': 0.21}
+
21%|██ | 2515/11952 [22:12<15:44:13, 6.00s/it]
21%|██ | 2516/11952 [22:18<15:25:47, 5.89s/it]
{'loss': 0.5002, 'learning_rate': 1.833973475993692e-05, 'epoch': 0.21}
+
21%|██ | 2516/11952 [22:18<15:25:47, 5.89s/it]
21%|██ | 2517/11952 [22:24<15:21:59, 5.86s/it]
{'loss': 0.501, 'learning_rate': 1.8338239115979038e-05, 'epoch': 0.21}
+
21%|██ | 2517/11952 [22:24<15:21:59, 5.86s/it]
21%|██ | 2518/11952 [22:29<15:16:12, 5.83s/it]
{'loss': 0.4984, 'learning_rate': 1.833674285969556e-05, 'epoch': 0.21}
+
21%|██ | 2518/11952 [22:29<15:16:12, 5.83s/it]
21%|██ | 2519/11952 [22:35<15:04:57, 5.76s/it]
{'loss': 0.4887, 'learning_rate': 1.833524599119636e-05, 'epoch': 0.21}
+
21%|██ | 2519/11952 [22:35<15:04:57, 5.76s/it]
21%|██ | 2520/11952 [22:41<15:13:44, 5.81s/it]
{'loss': 0.5059, 'learning_rate': 1.8333748510591364e-05, 'epoch': 0.21}
+
21%|██ | 2520/11952 [22:41<15:13:44, 5.81s/it]
21%|██ | 2521/11952 [22:47<15:27:40, 5.90s/it]
{'loss': 0.5056, 'learning_rate': 1.833225041799054e-05, 'epoch': 0.21}
+
21%|██ | 2521/11952 [22:47<15:27:40, 5.90s/it]
21%|██ | 2522/11952 [22:53<15:16:30, 5.83s/it]
{'loss': 0.494, 'learning_rate': 1.8330751713503902e-05, 'epoch': 0.21}
+
21%|██ | 2522/11952 [22:53<15:16:30, 5.83s/it]
21%|██ | 2523/11952 [22:58<15:14:01, 5.82s/it]
{'loss': 0.497, 'learning_rate': 1.8329252397241504e-05, 'epoch': 0.21}
+
21%|██ | 2523/11952 [22:59<15:14:01, 5.82s/it]
21%|██ | 2524/11952 [23:04<15:21:14, 5.86s/it]
{'loss': 0.5149, 'learning_rate': 1.832775246931346e-05, 'epoch': 0.21}
+
21%|██ | 2524/11952 [23:04<15:21:14, 5.86s/it]
21%|██ | 2525/11952 [23:10<15:09:12, 5.79s/it]
{'loss': 0.4997, 'learning_rate': 1.832625192982991e-05, 'epoch': 0.21}
+
21%|██ | 2525/11952 [23:10<15:09:12, 5.79s/it]
21%|██ | 2526/11952 [23:16<15:04:45, 5.76s/it]
{'loss': 0.5015, 'learning_rate': 1.8324750778901047e-05, 'epoch': 0.21}
+
21%|██ | 2526/11952 [23:16<15:04:45, 5.76s/it]
21%|██ | 2527/11952 [23:22<15:21:25, 5.87s/it]
{'loss': 0.5, 'learning_rate': 1.8323249016637118e-05, 'epoch': 0.21}
+
21%|██ | 2527/11952 [23:22<15:21:25, 5.87s/it]
21%|██ | 2528/11952 [23:28<15:27:52, 5.91s/it]
{'loss': 0.5136, 'learning_rate': 1.8321746643148394e-05, 'epoch': 0.21}
+
21%|██ | 2528/11952 [23:28<15:27:52, 5.91s/it]
21%|██ | 2529/11952 [23:33<15:12:03, 5.81s/it]
{'loss': 0.5003, 'learning_rate': 1.8320243658545215e-05, 'epoch': 0.21}
+
21%|██ | 2529/11952 [23:33<15:12:03, 5.81s/it]
21%|██ | 2530/11952 [23:39<15:10:42, 5.80s/it]
{'loss': 0.482, 'learning_rate': 1.8318740062937944e-05, 'epoch': 0.21}
+
21%|██ | 2530/11952 [23:39<15:10:42, 5.80s/it]
21%|██ | 2531/11952 [23:45<15:12:25, 5.81s/it]
{'loss': 0.476, 'learning_rate': 1.8317235856437006e-05, 'epoch': 0.21}
+
21%|██ | 2531/11952 [23:45<15:12:25, 5.81s/it]
21%|██ | 2532/11952 [23:51<15:08:15, 5.79s/it]
{'loss': 0.4906, 'learning_rate': 1.831573103915286e-05, 'epoch': 0.21}
+
21%|██ | 2532/11952 [23:51<15:08:15, 5.79s/it]
21%|██ | 2533/11952 [23:57<15:04:40, 5.76s/it]
{'loss': 0.5128, 'learning_rate': 1.8314225611196013e-05, 'epoch': 0.21}
+
21%|██ | 2533/11952 [23:57<15:04:40, 5.76s/it]
21%|██ | 2534/11952 [24:02<14:56:48, 5.71s/it]
{'loss': 0.5126, 'learning_rate': 1.8312719572677018e-05, 'epoch': 0.21}
+
21%|██ | 2534/11952 [24:02<14:56:48, 5.71s/it]
21%|██ | 2535/11952 [24:08<15:09:44, 5.80s/it]
{'loss': 0.5084, 'learning_rate': 1.8311212923706473e-05, 'epoch': 0.21}
+
21%|██ | 2535/11952 [24:08<15:09:44, 5.80s/it]
21%|██ | 2536/11952 [24:14<15:15:56, 5.84s/it]
{'loss': 0.5062, 'learning_rate': 1.8309705664395024e-05, 'epoch': 0.21}
+
21%|██ | 2536/11952 [24:14<15:15:56, 5.84s/it]
21%|██ | 2537/11952 [24:20<15:20:02, 5.86s/it]
{'loss': 0.4906, 'learning_rate': 1.830819779485335e-05, 'epoch': 0.21}
+
21%|██ | 2537/11952 [24:20<15:20:02, 5.86s/it]
21%|██ | 2538/11952 [24:26<15:13:01, 5.82s/it]
{'loss': 0.5119, 'learning_rate': 1.8306689315192187e-05, 'epoch': 0.21}
+
21%|██ | 2538/11952 [24:26<15:13:01, 5.82s/it]
21%|██ | 2539/11952 [24:31<15:08:46, 5.79s/it]
{'loss': 0.4949, 'learning_rate': 1.8305180225522306e-05, 'epoch': 0.21}
+
21%|██ | 2539/11952 [24:31<15:08:46, 5.79s/it]
21%|██▏ | 2540/11952 [24:37<14:56:29, 5.71s/it]
{'loss': 0.4931, 'learning_rate': 1.830367052595454e-05, 'epoch': 0.21}
+
21%|██▏ | 2540/11952 [24:37<14:56:29, 5.71s/it]
21%|██▏ | 2541/11952 [24:43<15:10:04, 5.80s/it]
{'loss': 0.5127, 'learning_rate': 1.8302160216599745e-05, 'epoch': 0.21}
+
21%|██▏ | 2541/11952 [24:43<15:10:04, 5.80s/it]
21%|██▏ | 2542/11952 [24:49<15:00:35, 5.74s/it]
{'loss': 0.488, 'learning_rate': 1.8300649297568837e-05, 'epoch': 0.21}
+
21%|██▏ | 2542/11952 [24:49<15:00:35, 5.74s/it]
21%|██▏ | 2543/11952 [24:54<15:06:19, 5.78s/it]
{'loss': 0.5083, 'learning_rate': 1.8299137768972766e-05, 'epoch': 0.21}
+
21%|██▏ | 2543/11952 [24:54<15:06:19, 5.78s/it]
21%|██▏ | 2544/11952 [25:00<14:54:13, 5.70s/it]
{'loss': 0.4948, 'learning_rate': 1.829762563092254e-05, 'epoch': 0.21}
+
21%|██▏ | 2544/11952 [25:00<14:54:13, 5.70s/it]
21%|██▏ | 2545/11952 [25:06<15:10:46, 5.81s/it]
{'loss': 0.5074, 'learning_rate': 1.8296112883529197e-05, 'epoch': 0.21}
+
21%|██▏ | 2545/11952 [25:06<15:10:46, 5.81s/it]
21%|██▏ | 2546/11952 [25:12<15:15:32, 5.84s/it]
{'loss': 0.5196, 'learning_rate': 1.829459952690383e-05, 'epoch': 0.21}
+
21%|██▏ | 2546/11952 [25:12<15:15:32, 5.84s/it]
21%|██▏ | 2547/11952 [25:18<15:18:43, 5.86s/it]
{'loss': 0.4939, 'learning_rate': 1.8293085561157578e-05, 'epoch': 0.21}
+
21%|██▏ | 2547/11952 [25:18<15:18:43, 5.86s/it]
21%|██▏ | 2548/11952 [25:23<15:03:14, 5.76s/it]
{'loss': 0.4937, 'learning_rate': 1.829157098640161e-05, 'epoch': 0.21}
+
21%|██▏ | 2548/11952 [25:23<15:03:14, 5.76s/it]
21%|██▏ | 2549/11952 [25:29<15:15:31, 5.84s/it]
{'loss': 0.4949, 'learning_rate': 1.829005580274716e-05, 'epoch': 0.21}
+
21%|██▏ | 2549/11952 [25:29<15:15:31, 5.84s/it]2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
21%|██▏ | 2550/11952 [25:35<15:05:39, 5.78s/it]
{'loss': 0.4918, 'learning_rate': 1.828854001030549e-05, 'epoch': 0.21}
+
21%|██▏ | 2550/11952 [25:35<15:05:39, 5.78s/it]
21%|██▏ | 2551/11952 [25:41<14:56:55, 5.72s/it]
{'loss': 0.5065, 'learning_rate': 1.828702360918792e-05, 'epoch': 0.21}
+
21%|██▏ | 2551/11952 [25:41<14:56:55, 5.72s/it]
21%|██▏ | 2552/11952 [25:46<14:54:21, 5.71s/it]
{'loss': 0.4884, 'learning_rate': 1.8285506599505803e-05, 'epoch': 0.21}
+
21%|██▏ | 2552/11952 [25:46<14:54:21, 5.71s/it]
21%|██▏ | 2553/11952 [25:52<14:57:08, 5.73s/it]
{'loss': 0.5058, 'learning_rate': 1.8283988981370543e-05, 'epoch': 0.21}
+
21%|██▏ | 2553/11952 [25:52<14:57:08, 5.73s/it]
21%|██▏ | 2554/11952 [25:58<15:10:26, 5.81s/it]
{'loss': 0.5247, 'learning_rate': 1.8282470754893585e-05, 'epoch': 0.21}
+
21%|██▏ | 2554/11952 [25:58<15:10:26, 5.81s/it]
21%|██▏ | 2555/11952 [26:04<15:07:10, 5.79s/it]
{'loss': 0.5005, 'learning_rate': 1.828095192018643e-05, 'epoch': 0.21}
+
21%|██▏ | 2555/11952 [26:04<15:07:10, 5.79s/it]
21%|██▏ | 2556/11952 [26:09<15:01:06, 5.75s/it]
{'loss': 0.4886, 'learning_rate': 1.82794324773606e-05, 'epoch': 0.21}
+
21%|██▏ | 2556/11952 [26:09<15:01:06, 5.75s/it]
21%|██▏ | 2557/11952 [26:15<14:56:49, 5.73s/it]
{'loss': 0.5016, 'learning_rate': 1.8277912426527696e-05, 'epoch': 0.21}
+
21%|██▏ | 2557/11952 [26:15<14:56:49, 5.73s/it]
21%|██▏ | 2558/11952 [26:21<15:03:29, 5.77s/it]
{'loss': 0.4991, 'learning_rate': 1.8276391767799326e-05, 'epoch': 0.21}
+
21%|██▏ | 2558/11952 [26:21<15:03:29, 5.77s/it]
21%|██▏ | 2559/11952 [26:27<15:19:57, 5.88s/it]
{'loss': 0.5007, 'learning_rate': 1.8274870501287174e-05, 'epoch': 0.21}
+
21%|██▏ | 2559/11952 [26:27<15:19:57, 5.88s/it]
21%|██▏ | 2560/11952 [26:33<15:22:18, 5.89s/it]
{'loss': 0.4941, 'learning_rate': 1.8273348627102948e-05, 'epoch': 0.21}
+
21%|██▏ | 2560/11952 [26:33<15:22:18, 5.89s/it]
21%|██▏ | 2561/11952 [26:39<15:25:48, 5.92s/it]
{'loss': 0.4995, 'learning_rate': 1.827182614535841e-05, 'epoch': 0.21}
+
21%|██▏ | 2561/11952 [26:39<15:25:48, 5.92s/it]
21%|██▏ | 2562/11952 [26:45<15:12:10, 5.83s/it]
{'loss': 0.4974, 'learning_rate': 1.8270303056165364e-05, 'epoch': 0.21}
+
21%|██▏ | 2562/11952 [26:45<15:12:10, 5.83s/it]
21%|██▏ | 2563/11952 [26:50<15:06:22, 5.79s/it]
{'loss': 0.5034, 'learning_rate': 1.826877935963566e-05, 'epoch': 0.21}
+
21%|██▏ | 2563/11952 [26:50<15:06:22, 5.79s/it]
21%|██▏ | 2564/11952 [26:56<15:07:22, 5.80s/it]
{'loss': 0.4848, 'learning_rate': 1.8267255055881197e-05, 'epoch': 0.21}
+
21%|██▏ | 2564/11952 [26:56<15:07:22, 5.80s/it]
21%|██▏ | 2565/11952 [27:02<15:22:41, 5.90s/it]
{'loss': 0.5114, 'learning_rate': 1.8265730145013903e-05, 'epoch': 0.21}
+
21%|██▏ | 2565/11952 [27:02<15:22:41, 5.90s/it]
21%|██▏ | 2566/11952 [27:08<15:20:09, 5.88s/it]
{'loss': 0.5084, 'learning_rate': 1.826420462714577e-05, 'epoch': 0.21}
+
21%|██▏ | 2566/11952 [27:08<15:20:09, 5.88s/it]
21%|██▏ | 2567/11952 [27:14<15:23:33, 5.90s/it]
{'loss': 0.5176, 'learning_rate': 1.8262678502388824e-05, 'epoch': 0.21}
+
21%|██▏ | 2567/11952 [27:14<15:23:33, 5.90s/it]
21%|██▏ | 2568/11952 [27:20<15:22:24, 5.90s/it]
{'loss': 0.4974, 'learning_rate': 1.8261151770855134e-05, 'epoch': 0.21}
+
21%|██▏ | 2568/11952 [27:20<15:22:24, 5.90s/it]
21%|██▏ | 2569/11952 [27:26<15:20:46, 5.89s/it]
{'loss': 0.5196, 'learning_rate': 1.8259624432656816e-05, 'epoch': 0.21}
+
21%|██▏ | 2569/11952 [27:26<15:20:46, 5.89s/it]
22%|██▏ | 2570/11952 [27:32<15:14:38, 5.85s/it]
{'loss': 0.4914, 'learning_rate': 1.825809648790604e-05, 'epoch': 0.22}
+
22%|██▏ | 2570/11952 [27:32<15:14:38, 5.85s/it]
22%|██▏ | 2571/11952 [27:38<15:20:17, 5.89s/it]
{'loss': 0.4887, 'learning_rate': 1.8256567936715e-05, 'epoch': 0.22}
+
22%|██▏ | 2571/11952 [27:38<15:20:17, 5.89s/it]
22%|██▏ | 2572/11952 [27:43<15:09:59, 5.82s/it]
{'loss': 0.513, 'learning_rate': 1.8255038779195957e-05, 'epoch': 0.22}
+
22%|██▏ | 2572/11952 [27:43<15:09:59, 5.82s/it]
22%|██▏ | 2573/11952 [27:49<14:56:33, 5.74s/it]
{'loss': 0.4801, 'learning_rate': 1.82535090154612e-05, 'epoch': 0.22}
+
22%|██▏ | 2573/11952 [27:49<14:56:33, 5.74s/it]
22%|██▏ | 2574/11952 [27:55<14:56:18, 5.73s/it]
{'loss': 0.4912, 'learning_rate': 1.825197864562307e-05, 'epoch': 0.22}
+
22%|██▏ | 2574/11952 [27:55<14:56:18, 5.73s/it]
22%|██▏ | 2575/11952 [28:00<14:52:57, 5.71s/it]
{'loss': 0.5092, 'learning_rate': 1.825044766979395e-05, 'epoch': 0.22}
+
22%|██▏ | 2575/11952 [28:00<14:52:57, 5.71s/it]
22%|██▏ | 2576/11952 [28:06<14:53:00, 5.71s/it]
{'loss': 0.5197, 'learning_rate': 1.8248916088086268e-05, 'epoch': 0.22}
+
22%|██▏ | 2576/11952 [28:06<14:53:00, 5.71s/it]
22%|██▏ | 2577/11952 [28:12<14:58:08, 5.75s/it]
{'loss': 0.4776, 'learning_rate': 1.82473839006125e-05, 'epoch': 0.22}
+
22%|██▏ | 2577/11952 [28:12<14:58:08, 5.75s/it]
22%|██▏ | 2578/11952 [28:18<15:02:54, 5.78s/it]
{'loss': 0.4789, 'learning_rate': 1.824585110748516e-05, 'epoch': 0.22}
+
22%|██▏ | 2578/11952 [28:18<15:02:54, 5.78s/it]
22%|██▏ | 2579/11952 [28:23<15:06:55, 5.81s/it]
{'loss': 0.5079, 'learning_rate': 1.8244317708816815e-05, 'epoch': 0.22}
+
22%|██▏ | 2579/11952 [28:23<15:06:55, 5.81s/it]
22%|██▏ | 2580/11952 [28:30<15:20:35, 5.89s/it]
{'loss': 0.5039, 'learning_rate': 1.8242783704720066e-05, 'epoch': 0.22}
+
22%|██▏ | 2580/11952 [28:30<15:20:35, 5.89s/it]
22%|██▏ | 2581/11952 [28:35<15:06:17, 5.80s/it]
{'loss': 0.4892, 'learning_rate': 1.8241249095307566e-05, 'epoch': 0.22}
+
22%|██▏ | 2581/11952 [28:35<15:06:17, 5.80s/it]
22%|██▏ | 2582/11952 [28:41<15:00:08, 5.76s/it]
{'loss': 0.4991, 'learning_rate': 1.823971388069201e-05, 'epoch': 0.22}
+
22%|██▏ | 2582/11952 [28:41<15:00:08, 5.76s/it]
22%|██▏ | 2583/11952 [28:47<14:56:32, 5.74s/it]
{'loss': 0.4969, 'learning_rate': 1.823817806098614e-05, 'epoch': 0.22}
+
22%|██▏ | 2583/11952 [28:47<14:56:32, 5.74s/it]
22%|██▏ | 2584/11952 [28:52<14:44:50, 5.67s/it]
{'loss': 0.4987, 'learning_rate': 1.8236641636302737e-05, 'epoch': 0.22}
+
22%|██▏ | 2584/11952 [28:52<14:44:50, 5.67s/it]
22%|██▏ | 2585/11952 [28:58<14:47:46, 5.69s/it]
{'loss': 0.49, 'learning_rate': 1.823510460675463e-05, 'epoch': 0.22}
+
22%|██▏ | 2585/11952 [28:58<14:47:46, 5.69s/it]
22%|██▏ | 2586/11952 [29:04<14:54:03, 5.73s/it]
{'loss': 0.4967, 'learning_rate': 1.8233566972454696e-05, 'epoch': 0.22}
+
22%|██▏ | 2586/11952 [29:04<14:54:03, 5.73s/it]
22%|██▏ | 2587/11952 [29:09<14:54:40, 5.73s/it]
{'loss': 0.4846, 'learning_rate': 1.823202873351585e-05, 'epoch': 0.22}
+
22%|██▏ | 2587/11952 [29:09<14:54:40, 5.73s/it]
22%|██▏ | 2588/11952 [29:15<14:50:20, 5.70s/it]
{'loss': 0.5066, 'learning_rate': 1.8230489890051048e-05, 'epoch': 0.22}
+
22%|██▏ | 2588/11952 [29:15<14:50:20, 5.70s/it]
22%|██▏ | 2589/11952 [29:21<15:13:10, 5.85s/it]
{'loss': 0.513, 'learning_rate': 1.8228950442173304e-05, 'epoch': 0.22}
+
22%|██▏ | 2589/11952 [29:21<15:13:10, 5.85s/it]
22%|██▏ | 2590/11952 [29:27<15:18:33, 5.89s/it]
{'loss': 0.4966, 'learning_rate': 1.8227410389995668e-05, 'epoch': 0.22}
+
22%|██▏ | 2590/11952 [29:27<15:18:33, 5.89s/it]
22%|██▏ | 2591/11952 [29:33<15:11:35, 5.84s/it]
{'loss': 0.5062, 'learning_rate': 1.8225869733631234e-05, 'epoch': 0.22}
+
22%|██▏ | 2591/11952 [29:33<15:11:35, 5.84s/it]
22%|██▏ | 2592/11952 [29:38<15:00:47, 5.77s/it]
{'loss': 0.488, 'learning_rate': 1.8224328473193137e-05, 'epoch': 0.22}
+
22%|██▏ | 2592/11952 [29:38<15:00:47, 5.77s/it]
22%|██▏ | 2593/11952 [29:45<15:15:01, 5.87s/it]
{'loss': 0.4971, 'learning_rate': 1.822278660879457e-05, 'epoch': 0.22}
+
22%|██▏ | 2593/11952 [29:45<15:15:01, 5.87s/it]
22%|██▏ | 2594/11952 [29:50<15:04:52, 5.80s/it]
{'loss': 0.5029, 'learning_rate': 1.822124414054875e-05, 'epoch': 0.22}
+
22%|██▏ | 2594/11952 [29:50<15:04:52, 5.80s/it]
22%|██▏ | 2595/11952 [29:56<15:11:45, 5.85s/it]
{'loss': 0.4926, 'learning_rate': 1.8219701068568957e-05, 'epoch': 0.22}
+
22%|██▏ | 2595/11952 [29:56<15:11:45, 5.85s/it]
22%|██▏ | 2596/11952 [30:02<15:10:23, 5.84s/it]
{'loss': 0.4797, 'learning_rate': 1.8218157392968505e-05, 'epoch': 0.22}
+
22%|██▏ | 2596/11952 [30:02<15:10:23, 5.84s/it]
22%|██▏ | 2597/11952 [30:08<15:07:44, 5.82s/it]
{'loss': 0.5108, 'learning_rate': 1.821661311386076e-05, 'epoch': 0.22}
+
22%|██▏ | 2597/11952 [30:08<15:07:44, 5.82s/it]
22%|██▏ | 2598/11952 [30:14<15:13:46, 5.86s/it]
{'loss': 0.5117, 'learning_rate': 1.8215068231359118e-05, 'epoch': 0.22}
+
22%|██▏ | 2598/11952 [30:14<15:13:46, 5.86s/it]
22%|██▏ | 2599/11952 [30:20<15:10:51, 5.84s/it]
{'loss': 0.4963, 'learning_rate': 1.821352274557704e-05, 'epoch': 0.22}
+
22%|██▏ | 2599/11952 [30:20<15:10:51, 5.84s/it]5 AutoResumeHook: Checking whether to suspend...
+021 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+AutoResumeHook: Checking whether to suspend...
+47 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+3
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
22%|██▏ | 2600/11952 [30:25<15:12:33, 5.85s/it]
{'loss': 0.5159, 'learning_rate': 1.8211976656628007e-05, 'epoch': 0.22}
+
22%|██▏ | 2600/11952 [30:25<15:12:33, 5.85s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
22%|██▏ | 2601/11952 [30:58<36:21:53, 14.00s/it]
{'loss': 0.4822, 'learning_rate': 1.821042996462557e-05, 'epoch': 0.22}
+
22%|██▏ | 2601/11952 [30:58<36:21:53, 14.00s/it]
22%|██▏ | 2602/11952 [31:04<30:03:09, 11.57s/it]
{'loss': 0.4933, 'learning_rate': 1.8208882669683305e-05, 'epoch': 0.22}
+
22%|██▏ | 2602/11952 [31:04<30:03:09, 11.57s/it]
22%|██▏ | 2603/11952 [31:10<25:30:02, 9.82s/it]
{'loss': 0.4897, 'learning_rate': 1.820733477191484e-05, 'epoch': 0.22}
+
22%|██▏ | 2603/11952 [31:10<25:30:02, 9.82s/it]
22%|██▏ | 2604/11952 [31:16<22:21:19, 8.61s/it]
{'loss': 0.4959, 'learning_rate': 1.8205786271433845e-05, 'epoch': 0.22}
+
22%|██▏ | 2604/11952 [31:16<22:21:19, 8.61s/it]
22%|██▏ | 2605/11952 [31:22<20:16:04, 7.81s/it]
{'loss': 0.5009, 'learning_rate': 1.8204237168354038e-05, 'epoch': 0.22}
+
22%|██▏ | 2605/11952 [31:22<20:16:04, 7.81s/it]
22%|██▏ | 2606/11952 [31:27<18:36:21, 7.17s/it]
{'loss': 0.4853, 'learning_rate': 1.8202687462789175e-05, 'epoch': 0.22}
+
22%|██▏ | 2606/11952 [31:27<18:36:21, 7.17s/it]
22%|██▏ | 2607/11952 [31:33<17:38:34, 6.80s/it]
{'loss': 0.523, 'learning_rate': 1.8201137154853065e-05, 'epoch': 0.22}
+
22%|██▏ | 2607/11952 [31:33<17:38:34, 6.80s/it]
22%|██▏ | 2608/11952 [31:39<16:49:27, 6.48s/it]
{'loss': 0.512, 'learning_rate': 1.8199586244659554e-05, 'epoch': 0.22}
+
22%|██▏ | 2608/11952 [31:39<16:49:27, 6.48s/it]
22%|██▏ | 2609/11952 [31:45<16:10:07, 6.23s/it]
{'loss': 0.4876, 'learning_rate': 1.8198034732322532e-05, 'epoch': 0.22}
+
22%|██▏ | 2609/11952 [31:45<16:10:07, 6.23s/it]
22%|██▏ | 2610/11952 [31:50<15:46:21, 6.08s/it]
{'loss': 0.5184, 'learning_rate': 1.8196482617955938e-05, 'epoch': 0.22}
+
22%|██▏ | 2610/11952 [31:50<15:46:21, 6.08s/it]
22%|██▏ | 2611/11952 [31:56<15:28:51, 5.97s/it]
{'loss': 0.536, 'learning_rate': 1.8194929901673752e-05, 'epoch': 0.22}
+
22%|██▏ | 2611/11952 [31:56<15:28:51, 5.97s/it]
22%|██▏ | 2612/11952 [32:02<15:12:15, 5.86s/it]
{'loss': 0.4823, 'learning_rate': 1.819337658359e-05, 'epoch': 0.22}
+
22%|██▏ | 2612/11952 [32:02<15:12:15, 5.86s/it]
22%|██▏ | 2613/11952 [32:08<15:08:47, 5.84s/it]
{'loss': 0.504, 'learning_rate': 1.819182266381875e-05, 'epoch': 0.22}
+
22%|██▏ | 2613/11952 [32:08<15:08:47, 5.84s/it]
22%|██▏ | 2614/11952 [32:13<15:12:07, 5.86s/it]
{'loss': 0.5123, 'learning_rate': 1.8190268142474113e-05, 'epoch': 0.22}
+
22%|██▏ | 2614/11952 [32:13<15:12:07, 5.86s/it]
22%|██▏ | 2615/11952 [32:19<15:02:09, 5.80s/it]
{'loss': 0.4874, 'learning_rate': 1.8188713019670253e-05, 'epoch': 0.22}
+
22%|██▏ | 2615/11952 [32:19<15:02:09, 5.80s/it]
22%|██▏ | 2616/11952 [32:25<14:59:14, 5.78s/it]
{'loss': 0.4956, 'learning_rate': 1.8187157295521366e-05, 'epoch': 0.22}
+
22%|██▏ | 2616/11952 [32:25<14:59:14, 5.78s/it]
22%|██▏ | 2617/11952 [32:31<15:22:21, 5.93s/it]
{'loss': 0.5148, 'learning_rate': 1.8185600970141703e-05, 'epoch': 0.22}
+
22%|██▏ | 2617/11952 [32:31<15:22:21, 5.93s/it]
22%|██▏ | 2618/11952 [32:37<15:19:08, 5.91s/it]
{'loss': 0.4907, 'learning_rate': 1.818404404364555e-05, 'epoch': 0.22}
+
22%|██▏ | 2618/11952 [32:37<15:19:08, 5.91s/it]
22%|██▏ | 2619/11952 [32:42<14:59:14, 5.78s/it]
{'loss': 0.4943, 'learning_rate': 1.818248651614724e-05, 'epoch': 0.22}
+
22%|██▏ | 2619/11952 [32:42<14:59:14, 5.78s/it]
22%|██▏ | 2620/11952 [32:48<14:59:37, 5.78s/it]
{'loss': 0.5055, 'learning_rate': 1.8180928387761157e-05, 'epoch': 0.22}
+
22%|██▏ | 2620/11952 [32:48<14:59:37, 5.78s/it]
22%|██▏ | 2621/11952 [32:54<15:00:48, 5.79s/it]
{'loss': 0.4992, 'learning_rate': 1.817936965860172e-05, 'epoch': 0.22}
+
22%|██▏ | 2621/11952 [32:54<15:00:48, 5.79s/it]
22%|██▏ | 2622/11952 [33:00<15:13:15, 5.87s/it]
{'loss': 0.5033, 'learning_rate': 1.8177810328783395e-05, 'epoch': 0.22}
+
22%|██▏ | 2622/11952 [33:00<15:13:15, 5.87s/it]
22%|██▏ | 2623/11952 [33:06<15:02:47, 5.81s/it]
{'loss': 0.4799, 'learning_rate': 1.8176250398420694e-05, 'epoch': 0.22}
+
22%|██▏ | 2623/11952 [33:06<15:02:47, 5.81s/it]
22%|██▏ | 2624/11952 [33:11<14:55:59, 5.76s/it]
{'loss': 0.4893, 'learning_rate': 1.817468986762817e-05, 'epoch': 0.22}
+
22%|██▏ | 2624/11952 [33:11<14:55:59, 5.76s/it]
22%|██▏ | 2625/11952 [33:18<15:09:32, 5.85s/it]
{'loss': 0.5092, 'learning_rate': 1.8173128736520427e-05, 'epoch': 0.22}
+
22%|██▏ | 2625/11952 [33:18<15:09:32, 5.85s/it]
22%|██▏ | 2626/11952 [33:23<15:03:21, 5.81s/it]
{'loss': 0.4862, 'learning_rate': 1.81715670052121e-05, 'epoch': 0.22}
+
22%|██▏ | 2626/11952 [33:23<15:03:21, 5.81s/it]
22%|██▏ | 2627/11952 [33:29<15:00:43, 5.80s/it]
{'loss': 0.5004, 'learning_rate': 1.8170004673817882e-05, 'epoch': 0.22}
+
22%|██▏ | 2627/11952 [33:29<15:00:43, 5.80s/it]
22%|██▏ | 2628/11952 [33:35<15:00:09, 5.79s/it]
{'loss': 0.4948, 'learning_rate': 1.8168441742452502e-05, 'epoch': 0.22}
+
22%|██▏ | 2628/11952 [33:35<15:00:09, 5.79s/it]
22%|██▏ | 2629/11952 [33:41<14:59:48, 5.79s/it]
{'loss': 0.5071, 'learning_rate': 1.8166878211230736e-05, 'epoch': 0.22}
+
22%|██▏ | 2629/11952 [33:41<14:59:48, 5.79s/it]
22%|██▏ | 2630/11952 [33:47<15:08:39, 5.85s/it]
{'loss': 0.5127, 'learning_rate': 1.8165314080267406e-05, 'epoch': 0.22}
+
22%|██▏ | 2630/11952 [33:47<15:08:39, 5.85s/it]
22%|██▏ | 2631/11952 [33:52<15:02:41, 5.81s/it]
{'loss': 0.5117, 'learning_rate': 1.8163749349677363e-05, 'epoch': 0.22}
+
22%|██▏ | 2631/11952 [33:52<15:02:41, 5.81s/it]
22%|██▏ | 2632/11952 [33:58<15:15:30, 5.89s/it]
{'loss': 0.5178, 'learning_rate': 1.8162184019575534e-05, 'epoch': 0.22}
+
22%|██▏ | 2632/11952 [33:58<15:15:30, 5.89s/it]
22%|██▏ | 2633/11952 [34:04<15:23:49, 5.95s/it]
{'loss': 0.5083, 'learning_rate': 1.816061809007685e-05, 'epoch': 0.22}
+
22%|██▏ | 2633/11952 [34:04<15:23:49, 5.95s/it]
22%|██▏ | 2634/11952 [34:10<15:13:09, 5.88s/it]
{'loss': 0.5078, 'learning_rate': 1.8159051561296323e-05, 'epoch': 0.22}
+
22%|██▏ | 2634/11952 [34:10<15:13:09, 5.88s/it]
22%|██▏ | 2635/11952 [34:16<15:01:38, 5.81s/it]
{'loss': 0.5072, 'learning_rate': 1.815748443334898e-05, 'epoch': 0.22}
+
22%|██▏ | 2635/11952 [34:16<15:01:38, 5.81s/it]
22%|██▏ | 2636/11952 [34:22<15:04:04, 5.82s/it]
{'loss': 0.4987, 'learning_rate': 1.8155916706349913e-05, 'epoch': 0.22}
+
22%|██▏ | 2636/11952 [34:22<15:04:04, 5.82s/it]
22%|██▏ | 2637/11952 [34:28<15:07:45, 5.85s/it]
{'loss': 0.5096, 'learning_rate': 1.8154348380414245e-05, 'epoch': 0.22}
+
22%|██▏ | 2637/11952 [34:28<15:07:45, 5.85s/it]
22%|██▏ | 2638/11952 [34:34<15:29:05, 5.99s/it]
{'loss': 0.5288, 'learning_rate': 1.815277945565715e-05, 'epoch': 0.22}
+
22%|██▏ | 2638/11952 [34:34<15:29:05, 5.99s/it]
22%|██▏ | 2639/11952 [34:40<15:17:03, 5.91s/it]
{'loss': 0.4849, 'learning_rate': 1.8151209932193844e-05, 'epoch': 0.22}
+
22%|██▏ | 2639/11952 [34:40<15:17:03, 5.91s/it]
22%|██▏ | 2640/11952 [34:45<15:05:44, 5.84s/it]
{'loss': 0.4918, 'learning_rate': 1.814963981013958e-05, 'epoch': 0.22}
+
22%|██▏ | 2640/11952 [34:45<15:05:44, 5.84s/it]
22%|██▏ | 2641/11952 [34:51<15:14:30, 5.89s/it]
{'loss': 0.4967, 'learning_rate': 1.8148069089609667e-05, 'epoch': 0.22}
+
22%|██▏ | 2641/11952 [34:51<15:14:30, 5.89s/it]
22%|██▏ | 2642/11952 [34:57<15:06:17, 5.84s/it]
{'loss': 0.5129, 'learning_rate': 1.8146497770719448e-05, 'epoch': 0.22}
+
22%|██▏ | 2642/11952 [34:57<15:06:17, 5.84s/it]
22%|██▏ | 2643/11952 [35:03<15:05:54, 5.84s/it]
{'loss': 0.4814, 'learning_rate': 1.8144925853584315e-05, 'epoch': 0.22}
+
22%|██▏ | 2643/11952 [35:03<15:05:54, 5.84s/it]
22%|██▏ | 2644/11952 [35:09<15:08:47, 5.86s/it]
{'loss': 0.5177, 'learning_rate': 1.8143353338319712e-05, 'epoch': 0.22}
+
22%|██▏ | 2644/11952 [35:09<15:08:47, 5.86s/it]
22%|██▏ | 2645/11952 [35:14<14:52:49, 5.76s/it]
{'loss': 0.5168, 'learning_rate': 1.8141780225041104e-05, 'epoch': 0.22}
+
22%|██▏ | 2645/11952 [35:14<14:52:49, 5.76s/it]
22%|██▏ | 2646/11952 [35:20<15:08:29, 5.86s/it]
{'loss': 0.5167, 'learning_rate': 1.8140206513864026e-05, 'epoch': 0.22}
+
22%|██▏ | 2646/11952 [35:20<15:08:29, 5.86s/it]
22%|██▏ | 2647/11952 [35:26<14:59:59, 5.80s/it]
{'loss': 0.4849, 'learning_rate': 1.8138632204904033e-05, 'epoch': 0.22}
+
22%|██▏ | 2647/11952 [35:26<14:59:59, 5.80s/it]
22%|██▏ | 2648/11952 [35:32<14:46:10, 5.71s/it]
{'loss': 0.4971, 'learning_rate': 1.8137057298276745e-05, 'epoch': 0.22}
+
22%|██▏ | 2648/11952 [35:32<14:46:10, 5.71s/it]
22%|██▏ | 2649/11952 [35:37<14:55:17, 5.77s/it]
{'loss': 0.5189, 'learning_rate': 1.8135481794097814e-05, 'epoch': 0.22}
+
22%|██▏ | 2649/11952 [35:37<14:55:17, 5.77s/it]6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+021 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...4 AutoResumeHook: Checking whether to suspend...
+
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
22%|██▏ | 2650/11952 [35:43<15:05:18, 5.84s/it]
{'loss': 0.4916, 'learning_rate': 1.813390569248294e-05, 'epoch': 0.22}
+
22%|██▏ | 2650/11952 [35:43<15:05:18, 5.84s/it]
22%|██▏ | 2651/11952 [35:49<15:04:34, 5.84s/it]
{'loss': 0.5015, 'learning_rate': 1.813232899354786e-05, 'epoch': 0.22}
+
22%|██▏ | 2651/11952 [35:49<15:04:34, 5.84s/it]
22%|██▏ | 2652/11952 [35:55<15:19:07, 5.93s/it]
{'loss': 0.499, 'learning_rate': 1.8130751697408364e-05, 'epoch': 0.22}
+
22%|██▏ | 2652/11952 [35:55<15:19:07, 5.93s/it]
22%|██▏ | 2653/11952 [36:01<15:09:09, 5.87s/it]
{'loss': 0.4776, 'learning_rate': 1.8129173804180285e-05, 'epoch': 0.22}
+
22%|██▏ | 2653/11952 [36:01<15:09:09, 5.87s/it]
22%|██▏ | 2654/11952 [36:07<15:03:07, 5.83s/it]
{'loss': 0.4923, 'learning_rate': 1.812759531397949e-05, 'epoch': 0.22}
+
22%|██▏ | 2654/11952 [36:07<15:03:07, 5.83s/it]
22%|██▏ | 2655/11952 [36:13<15:01:33, 5.82s/it]
{'loss': 0.5178, 'learning_rate': 1.8126016226921898e-05, 'epoch': 0.22}
+
22%|██▏ | 2655/11952 [36:13<15:01:33, 5.82s/it]
22%|██▏ | 2656/11952 [36:18<14:57:01, 5.79s/it]
{'loss': 0.4954, 'learning_rate': 1.812443654312348e-05, 'epoch': 0.22}
+
22%|██▏ | 2656/11952 [36:18<14:57:01, 5.79s/it]
22%|██▏ | 2657/11952 [36:25<15:18:34, 5.93s/it]
{'loss': 0.5286, 'learning_rate': 1.8122856262700227e-05, 'epoch': 0.22}
+
22%|██▏ | 2657/11952 [36:25<15:18:34, 5.93s/it]
22%|██▏ | 2658/11952 [36:31<15:19:12, 5.93s/it]
{'loss': 0.5092, 'learning_rate': 1.81212753857682e-05, 'epoch': 0.22}
+
22%|██▏ | 2658/11952 [36:31<15:19:12, 5.93s/it]
22%|██▏ | 2659/11952 [36:36<15:03:45, 5.84s/it]
{'loss': 0.5141, 'learning_rate': 1.8119693912443487e-05, 'epoch': 0.22}
+
22%|██▏ | 2659/11952 [36:36<15:03:45, 5.84s/it]
22%|██▏ | 2660/11952 [36:42<15:13:24, 5.90s/it]
{'loss': 0.5079, 'learning_rate': 1.8118111842842227e-05, 'epoch': 0.22}
+
22%|██▏ | 2660/11952 [36:42<15:13:24, 5.90s/it]
22%|██▏ | 2661/11952 [36:48<15:01:02, 5.82s/it]
{'loss': 0.4833, 'learning_rate': 1.8116529177080594e-05, 'epoch': 0.22}
+
22%|██▏ | 2661/11952 [36:48<15:01:02, 5.82s/it]
22%|██▏ | 2662/11952 [36:54<15:04:08, 5.84s/it]
{'loss': 0.5262, 'learning_rate': 1.8114945915274826e-05, 'epoch': 0.22}
+
22%|██▏ | 2662/11952 [36:54<15:04:08, 5.84s/it]
22%|██▏ | 2663/11952 [36:59<14:54:29, 5.78s/it]
{'loss': 0.5065, 'learning_rate': 1.8113362057541175e-05, 'epoch': 0.22}
+
22%|██▏ | 2663/11952 [36:59<14:54:29, 5.78s/it]
22%|██▏ | 2664/11952 [37:05<14:52:48, 5.77s/it]
{'loss': 0.492, 'learning_rate': 1.811177760399596e-05, 'epoch': 0.22}
+
22%|██▏ | 2664/11952 [37:05<14:52:48, 5.77s/it]
22%|██▏ | 2665/11952 [37:11<15:03:22, 5.84s/it]
{'loss': 0.4939, 'learning_rate': 1.811019255475554e-05, 'epoch': 0.22}
+
22%|██▏ | 2665/11952 [37:11<15:03:22, 5.84s/it]
22%|██▏ | 2666/11952 [37:17<14:53:29, 5.77s/it]
{'loss': 0.4864, 'learning_rate': 1.8108606909936312e-05, 'epoch': 0.22}
+
22%|██▏ | 2666/11952 [37:17<14:53:29, 5.77s/it]
22%|██▏ | 2667/11952 [37:23<14:53:23, 5.77s/it]
{'loss': 0.4914, 'learning_rate': 1.810702066965472e-05, 'epoch': 0.22}
+
22%|██▏ | 2667/11952 [37:23<14:53:23, 5.77s/it]
22%|██▏ | 2668/11952 [37:28<14:54:16, 5.78s/it]
{'loss': 0.5023, 'learning_rate': 1.810543383402725e-05, 'epoch': 0.22}
+
22%|██▏ | 2668/11952 [37:28<14:54:16, 5.78s/it]
22%|██▏ | 2669/11952 [37:34<14:58:33, 5.81s/it]
{'loss': 0.4967, 'learning_rate': 1.8103846403170427e-05, 'epoch': 0.22}
+
22%|██▏ | 2669/11952 [37:34<14:58:33, 5.81s/it]
22%|██▏ | 2670/11952 [37:40<15:04:26, 5.85s/it]
{'loss': 0.4998, 'learning_rate': 1.8102258377200837e-05, 'epoch': 0.22}
+
22%|██▏ | 2670/11952 [37:40<15:04:26, 5.85s/it]
22%|██▏ | 2671/11952 [37:46<14:53:26, 5.78s/it]
{'loss': 0.5019, 'learning_rate': 1.8100669756235087e-05, 'epoch': 0.22}
+
22%|██▏ | 2671/11952 [37:46<14:53:26, 5.78s/it]
22%|██▏ | 2672/11952 [37:52<15:04:19, 5.85s/it]
{'loss': 0.5198, 'learning_rate': 1.8099080540389845e-05, 'epoch': 0.22}
+
22%|██▏ | 2672/11952 [37:52<15:04:19, 5.85s/it]
22%|██▏ | 2673/11952 [37:58<15:04:21, 5.85s/it]
{'loss': 0.5041, 'learning_rate': 1.8097490729781815e-05, 'epoch': 0.22}
+
22%|██▏ | 2673/11952 [37:58<15:04:21, 5.85s/it]
22%|██▏ | 2674/11952 [38:04<15:10:51, 5.89s/it]
{'loss': 0.4983, 'learning_rate': 1.8095900324527745e-05, 'epoch': 0.22}
+
22%|██▏ | 2674/11952 [38:04<15:10:51, 5.89s/it]
22%|██▏ | 2675/11952 [38:10<15:12:31, 5.90s/it]
{'loss': 0.4895, 'learning_rate': 1.8094309324744428e-05, 'epoch': 0.22}
+
22%|██▏ | 2675/11952 [38:10<15:12:31, 5.90s/it]
22%|██▏ | 2676/11952 [38:15<15:14:04, 5.91s/it]
{'loss': 0.5035, 'learning_rate': 1.8092717730548702e-05, 'epoch': 0.22}
+
22%|██▏ | 2676/11952 [38:15<15:14:04, 5.91s/it]
22%|██▏ | 2677/11952 [38:21<15:08:27, 5.88s/it]
{'loss': 0.51, 'learning_rate': 1.8091125542057442e-05, 'epoch': 0.22}
+
22%|██▏ | 2677/11952 [38:21<15:08:27, 5.88s/it]
22%|██▏ | 2678/11952 [38:27<15:06:59, 5.87s/it]
{'loss': 0.4928, 'learning_rate': 1.8089532759387586e-05, 'epoch': 0.22}
+
22%|██▏ | 2678/11952 [38:27<15:06:59, 5.87s/it]
22%|██▏ | 2679/11952 [38:33<15:15:37, 5.92s/it]
{'loss': 0.4932, 'learning_rate': 1.8087939382656082e-05, 'epoch': 0.22}
+
22%|██▏ | 2679/11952 [38:33<15:15:37, 5.92s/it]
22%|██▏ | 2680/11952 [38:39<15:11:14, 5.90s/it]
{'loss': 0.5225, 'learning_rate': 1.8086345411979952e-05, 'epoch': 0.22}
+
22%|██▏ | 2680/11952 [38:39<15:11:14, 5.90s/it]
22%|██▏ | 2681/11952 [38:45<15:08:10, 5.88s/it]
{'loss': 0.4933, 'learning_rate': 1.808475084747625e-05, 'epoch': 0.22}
+
22%|██▏ | 2681/11952 [38:45<15:08:10, 5.88s/it]
22%|██▏ | 2682/11952 [38:51<15:01:46, 5.84s/it]
{'loss': 0.5014, 'learning_rate': 1.808315568926207e-05, 'epoch': 0.22}
+
22%|██▏ | 2682/11952 [38:51<15:01:46, 5.84s/it]
22%|██▏ | 2683/11952 [38:57<15:11:10, 5.90s/it]
{'loss': 0.4988, 'learning_rate': 1.808155993745456e-05, 'epoch': 0.22}
+
22%|██▏ | 2683/11952 [38:57<15:11:10, 5.90s/it]
22%|██▏ | 2684/11952 [39:03<15:20:05, 5.96s/it]
{'loss': 0.4932, 'learning_rate': 1.8079963592170903e-05, 'epoch': 0.22}
+
22%|██▏ | 2684/11952 [39:03<15:20:05, 5.96s/it]
22%|██▏ | 2685/11952 [39:08<15:05:39, 5.86s/it]
{'loss': 0.4945, 'learning_rate': 1.807836665352832e-05, 'epoch': 0.22}
+
22%|██▏ | 2685/11952 [39:08<15:05:39, 5.86s/it]
22%|██▏ | 2686/11952 [39:14<15:10:24, 5.90s/it]
{'loss': 0.4966, 'learning_rate': 1.8076769121644097e-05, 'epoch': 0.22}
+
22%|██▏ | 2686/11952 [39:14<15:10:24, 5.90s/it]
22%|██▏ | 2687/11952 [39:21<15:24:16, 5.99s/it]
{'loss': 0.516, 'learning_rate': 1.8075170996635538e-05, 'epoch': 0.22}
+
22%|██▏ | 2687/11952 [39:21<15:24:16, 5.99s/it]
22%|██▏ | 2688/11952 [39:27<15:24:32, 5.99s/it]
{'loss': 0.5308, 'learning_rate': 1.8073572278620015e-05, 'epoch': 0.22}
+
22%|██▏ | 2688/11952 [39:27<15:24:32, 5.99s/it]
22%|██▏ | 2689/11952 [39:32<15:15:44, 5.93s/it]
{'loss': 0.4975, 'learning_rate': 1.8071972967714918e-05, 'epoch': 0.22}
+
22%|██▏ | 2689/11952 [39:32<15:15:44, 5.93s/it]
23%|██▎ | 2690/11952 [39:38<15:16:56, 5.94s/it]
{'loss': 0.5108, 'learning_rate': 1.8070373064037702e-05, 'epoch': 0.23}
+
23%|██▎ | 2690/11952 [39:38<15:16:56, 5.94s/it]
23%|██▎ | 2691/11952 [39:44<15:18:31, 5.95s/it]
{'loss': 0.4995, 'learning_rate': 1.8068772567705858e-05, 'epoch': 0.23}
+
23%|██▎ | 2691/11952 [39:44<15:18:31, 5.95s/it]
23%|██▎ | 2692/11952 [39:50<15:16:30, 5.94s/it]
{'loss': 0.4989, 'learning_rate': 1.8067171478836916e-05, 'epoch': 0.23}
+
23%|██▎ | 2692/11952 [39:50<15:16:30, 5.94s/it]
23%|██▎ | 2693/11952 [39:56<15:11:03, 5.90s/it]
{'loss': 0.4833, 'learning_rate': 1.8065569797548453e-05, 'epoch': 0.23}
+
23%|██▎ | 2693/11952 [39:56<15:11:03, 5.90s/it]
23%|██▎ | 2694/11952 [40:02<15:14:53, 5.93s/it]
{'loss': 0.4976, 'learning_rate': 1.8063967523958093e-05, 'epoch': 0.23}
+
23%|██▎ | 2694/11952 [40:02<15:14:53, 5.93s/it]
23%|██▎ | 2695/11952 [40:08<15:09:35, 5.90s/it]
{'loss': 0.5101, 'learning_rate': 1.80623646581835e-05, 'epoch': 0.23}
+
23%|██▎ | 2695/11952 [40:08<15:09:35, 5.90s/it]
23%|██▎ | 2696/11952 [40:14<15:13:51, 5.92s/it]
{'loss': 0.5045, 'learning_rate': 1.8060761200342376e-05, 'epoch': 0.23}
+
23%|██▎ | 2696/11952 [40:14<15:13:51, 5.92s/it]
23%|██▎ | 2697/11952 [40:20<15:23:30, 5.99s/it]
{'loss': 0.4985, 'learning_rate': 1.8059157150552477e-05, 'epoch': 0.23}
+
23%|██▎ | 2697/11952 [40:20<15:23:30, 5.99s/it]
23%|██▎ | 2698/11952 [40:26<15:26:08, 6.00s/it]
{'loss': 0.4916, 'learning_rate': 1.80575525089316e-05, 'epoch': 0.23}
+
23%|██▎ | 2698/11952 [40:26<15:26:08, 6.00s/it]
23%|██▎ | 2699/11952 [40:32<15:10:46, 5.91s/it]
{'loss': 0.4951, 'learning_rate': 1.805594727559758e-05, 'epoch': 0.23}
+
23%|██▎ | 2699/11952 [40:32<15:10:46, 5.91s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
23%|██▎ | 2700/11952 [40:38<15:19:28, 5.96s/it]4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5025, 'learning_rate': 1.80543414506683e-05, 'epoch': 0.23}
+
23%|██▎ | 2700/11952 [40:38<15:19:28, 5.96s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
23%|██▎ | 2701/11952 [41:11<36:41:31, 14.28s/it]
{'loss': 0.5244, 'learning_rate': 1.8052735034261683e-05, 'epoch': 0.23}
+
23%|██▎ | 2701/11952 [41:11<36:41:31, 14.28s/it]
23%|██▎ | 2702/11952 [41:17<30:12:03, 11.75s/it]
{'loss': 0.4934, 'learning_rate': 1.8051128026495703e-05, 'epoch': 0.23}
+
23%|██▎ | 2702/11952 [41:17<30:12:03, 11.75s/it]
23%|██▎ | 2703/11952 [41:23<25:44:49, 10.02s/it]
{'loss': 0.5106, 'learning_rate': 1.8049520427488362e-05, 'epoch': 0.23}
+
23%|██▎ | 2703/11952 [41:23<25:44:49, 10.02s/it]
23%|██▎ | 2704/11952 [41:29<22:35:10, 8.79s/it]
{'loss': 0.5032, 'learning_rate': 1.8047912237357724e-05, 'epoch': 0.23}
+
23%|██▎ | 2704/11952 [41:29<22:35:10, 8.79s/it]
23%|██▎ | 2705/11952 [41:35<20:34:08, 8.01s/it]
{'loss': 0.4925, 'learning_rate': 1.8046303456221885e-05, 'epoch': 0.23}
+
23%|██▎ | 2705/11952 [41:35<20:34:08, 8.01s/it]
23%|██▎ | 2706/11952 [41:41<19:02:55, 7.42s/it]
{'loss': 0.4961, 'learning_rate': 1.8044694084198985e-05, 'epoch': 0.23}
+
23%|██▎ | 2706/11952 [41:41<19:02:55, 7.42s/it]
23%|██▎ | 2707/11952 [41:47<17:48:42, 6.94s/it]
{'loss': 0.4993, 'learning_rate': 1.8043084121407214e-05, 'epoch': 0.23}
+
23%|██▎ | 2707/11952 [41:47<17:48:42, 6.94s/it]
23%|██▎ | 2708/11952 [41:53<17:01:20, 6.63s/it]
{'loss': 0.5052, 'learning_rate': 1.80414735679648e-05, 'epoch': 0.23}
+
23%|██▎ | 2708/11952 [41:53<17:01:20, 6.63s/it]
23%|██▎ | 2709/11952 [41:59<16:23:13, 6.38s/it]
{'loss': 0.5097, 'learning_rate': 1.8039862423990012e-05, 'epoch': 0.23}
+
23%|██▎ | 2709/11952 [41:59<16:23:13, 6.38s/it]
23%|██▎ | 2710/11952 [42:05<15:50:19, 6.17s/it]
{'loss': 0.5066, 'learning_rate': 1.803825068960117e-05, 'epoch': 0.23}
+
23%|██▎ | 2710/11952 [42:05<15:50:19, 6.17s/it]
23%|██▎ | 2711/11952 [42:11<15:46:45, 6.15s/it]
{'loss': 0.5189, 'learning_rate': 1.803663836491663e-05, 'epoch': 0.23}
+
23%|██▎ | 2711/11952 [42:11<15:46:45, 6.15s/it]
23%|██▎ | 2712/11952 [42:16<15:25:05, 6.01s/it]
{'loss': 0.4867, 'learning_rate': 1.8035025450054796e-05, 'epoch': 0.23}
+
23%|██▎ | 2712/11952 [42:16<15:25:05, 6.01s/it]
23%|██▎ | 2713/11952 [42:23<15:29:56, 6.04s/it]
{'loss': 0.4937, 'learning_rate': 1.803341194513411e-05, 'epoch': 0.23}
+
23%|██▎ | 2713/11952 [42:23<15:29:56, 6.04s/it]
23%|██▎ | 2714/11952 [42:28<15:25:22, 6.01s/it]
{'loss': 0.512, 'learning_rate': 1.803179785027307e-05, 'epoch': 0.23}
+
23%|██▎ | 2714/11952 [42:28<15:25:22, 6.01s/it]
23%|██▎ | 2715/11952 [42:34<15:07:49, 5.90s/it]
{'loss': 0.4938, 'learning_rate': 1.8030183165590197e-05, 'epoch': 0.23}
+
23%|██▎ | 2715/11952 [42:34<15:07:49, 5.90s/it]
23%|██▎ | 2716/11952 [42:40<15:16:23, 5.95s/it]
{'loss': 0.4957, 'learning_rate': 1.8028567891204074e-05, 'epoch': 0.23}
+
23%|██▎ | 2716/11952 [42:40<15:16:23, 5.95s/it]
23%|██▎ | 2717/11952 [42:46<15:13:12, 5.93s/it]
{'loss': 0.4973, 'learning_rate': 1.802695202723332e-05, 'epoch': 0.23}
+
23%|██▎ | 2717/11952 [42:46<15:13:12, 5.93s/it]
23%|██▎ | 2718/11952 [42:52<15:12:55, 5.93s/it]
{'loss': 0.5068, 'learning_rate': 1.8025335573796596e-05, 'epoch': 0.23}
+
23%|██▎ | 2718/11952 [42:52<15:12:55, 5.93s/it]
23%|██▎ | 2719/11952 [42:58<15:09:23, 5.91s/it]
{'loss': 0.4977, 'learning_rate': 1.8023718531012602e-05, 'epoch': 0.23}
+
23%|██▎ | 2719/11952 [42:58<15:09:23, 5.91s/it]
23%|██▎ | 2720/11952 [43:04<15:05:38, 5.89s/it]
{'loss': 0.4864, 'learning_rate': 1.80221008990001e-05, 'epoch': 0.23}
+
23%|██▎ | 2720/11952 [43:04<15:05:38, 5.89s/it]
23%|██▎ | 2721/11952 [43:10<15:18:03, 5.97s/it]
{'loss': 0.5293, 'learning_rate': 1.8020482677877868e-05, 'epoch': 0.23}
+
23%|██▎ | 2721/11952 [43:10<15:18:03, 5.97s/it]
23%|██▎ | 2722/11952 [43:16<15:14:35, 5.95s/it]
{'loss': 0.4882, 'learning_rate': 1.801886386776475e-05, 'epoch': 0.23}
+
23%|██▎ | 2722/11952 [43:16<15:14:35, 5.95s/it]
23%|██▎ | 2723/11952 [43:21<15:02:16, 5.87s/it]
{'loss': 0.4978, 'learning_rate': 1.8017244468779625e-05, 'epoch': 0.23}
+
23%|██▎ | 2723/11952 [43:21<15:02:16, 5.87s/it]
23%|██▎ | 2724/11952 [43:27<14:59:15, 5.85s/it]
{'loss': 0.4887, 'learning_rate': 1.8015624481041408e-05, 'epoch': 0.23}
+
23%|██▎ | 2724/11952 [43:27<14:59:15, 5.85s/it]
23%|██▎ | 2725/11952 [43:33<14:47:16, 5.77s/it]
{'loss': 0.4994, 'learning_rate': 1.8014003904669073e-05, 'epoch': 0.23}
+
23%|██▎ | 2725/11952 [43:33<14:47:16, 5.77s/it]
23%|██▎ | 2726/11952 [43:39<14:55:19, 5.82s/it]
{'loss': 0.498, 'learning_rate': 1.8012382739781623e-05, 'epoch': 0.23}
+
23%|██▎ | 2726/11952 [43:39<14:55:19, 5.82s/it]
23%|██▎ | 2727/11952 [43:44<14:47:53, 5.77s/it]
{'loss': 0.5084, 'learning_rate': 1.801076098649811e-05, 'epoch': 0.23}
+
23%|██▎ | 2727/11952 [43:44<14:47:53, 5.77s/it]
23%|██▎ | 2728/11952 [43:50<14:51:18, 5.80s/it]
{'loss': 0.5097, 'learning_rate': 1.8009138644937626e-05, 'epoch': 0.23}
+
23%|██▎ | 2728/11952 [43:50<14:51:18, 5.80s/it]
23%|██▎ | 2729/11952 [43:56<15:00:53, 5.86s/it]
{'loss': 0.5071, 'learning_rate': 1.8007515715219317e-05, 'epoch': 0.23}
+
23%|██▎ | 2729/11952 [43:56<15:00:53, 5.86s/it]
23%|██▎ | 2730/11952 [44:02<15:01:37, 5.87s/it]
{'loss': 0.5053, 'learning_rate': 1.8005892197462355e-05, 'epoch': 0.23}
+
23%|██▎ | 2730/11952 [44:02<15:01:37, 5.87s/it]
23%|██▎ | 2731/11952 [44:08<14:58:01, 5.84s/it]
{'loss': 0.4957, 'learning_rate': 1.8004268091785973e-05, 'epoch': 0.23}
+
23%|██▎ | 2731/11952 [44:08<14:58:01, 5.84s/it]
23%|██▎ | 2732/11952 [44:14<14:47:21, 5.77s/it]
{'loss': 0.4895, 'learning_rate': 1.8002643398309434e-05, 'epoch': 0.23}
+
23%|██▎ | 2732/11952 [44:14<14:47:21, 5.77s/it]
23%|██▎ | 2733/11952 [44:19<14:54:59, 5.82s/it]
{'loss': 0.4991, 'learning_rate': 1.800101811715205e-05, 'epoch': 0.23}
+
23%|██▎ | 2733/11952 [44:19<14:54:59, 5.82s/it]
23%|██▎ | 2734/11952 [44:25<14:46:11, 5.77s/it]
{'loss': 0.4882, 'learning_rate': 1.799939224843317e-05, 'epoch': 0.23}
+
23%|██▎ | 2734/11952 [44:25<14:46:11, 5.77s/it]
23%|██▎ | 2735/11952 [44:31<14:39:01, 5.72s/it]
{'loss': 0.4993, 'learning_rate': 1.7997765792272203e-05, 'epoch': 0.23}
+
23%|██▎ | 2735/11952 [44:31<14:39:01, 5.72s/it]
23%|██▎ | 2736/11952 [44:36<14:34:46, 5.70s/it]
{'loss': 0.4852, 'learning_rate': 1.7996138748788573e-05, 'epoch': 0.23}
+
23%|██▎ | 2736/11952 [44:36<14:34:46, 5.70s/it]
23%|██▎ | 2737/11952 [44:42<14:41:41, 5.74s/it]
{'loss': 0.5067, 'learning_rate': 1.799451111810178e-05, 'epoch': 0.23}
+
23%|██▎ | 2737/11952 [44:42<14:41:41, 5.74s/it]
23%|██▎ | 2738/11952 [44:48<14:44:12, 5.76s/it]
{'loss': 0.5039, 'learning_rate': 1.7992882900331336e-05, 'epoch': 0.23}
+
23%|██▎ | 2738/11952 [44:48<14:44:12, 5.76s/it]
23%|██▎ | 2739/11952 [44:54<14:45:17, 5.77s/it]
{'loss': 0.4889, 'learning_rate': 1.799125409559682e-05, 'epoch': 0.23}
+
23%|██▎ | 2739/11952 [44:54<14:45:17, 5.77s/it]
23%|██▎ | 2740/11952 [45:00<14:43:27, 5.75s/it]
{'loss': 0.4925, 'learning_rate': 1.7989624704017838e-05, 'epoch': 0.23}
+
23%|██▎ | 2740/11952 [45:00<14:43:27, 5.75s/it]
23%|██▎ | 2741/11952 [45:05<14:35:32, 5.70s/it]
{'loss': 0.4827, 'learning_rate': 1.798799472571405e-05, 'epoch': 0.23}
+
23%|██▎ | 2741/11952 [45:05<14:35:32, 5.70s/it]
23%|██▎ | 2742/11952 [45:11<14:45:51, 5.77s/it]
{'loss': 0.4894, 'learning_rate': 1.7986364160805156e-05, 'epoch': 0.23}
+
23%|██▎ | 2742/11952 [45:11<14:45:51, 5.77s/it]
23%|██▎ | 2743/11952 [45:17<15:07:02, 5.91s/it]
{'loss': 0.5013, 'learning_rate': 1.7984733009410896e-05, 'epoch': 0.23}
+
23%|██▎ | 2743/11952 [45:17<15:07:02, 5.91s/it]
23%|██▎ | 2744/11952 [45:23<15:14:13, 5.96s/it]
{'loss': 0.4842, 'learning_rate': 1.7983101271651052e-05, 'epoch': 0.23}
+
23%|██▎ | 2744/11952 [45:23<15:14:13, 5.96s/it]
23%|██▎ | 2745/11952 [45:29<15:13:23, 5.95s/it]
{'loss': 0.5058, 'learning_rate': 1.798146894764546e-05, 'epoch': 0.23}
+
23%|██▎ | 2745/11952 [45:29<15:13:23, 5.95s/it]
23%|██▎ | 2746/11952 [45:35<15:17:04, 5.98s/it]
{'loss': 0.5045, 'learning_rate': 1.7979836037513977e-05, 'epoch': 0.23}
+
23%|██▎ | 2746/11952 [45:35<15:17:04, 5.98s/it]
23%|██▎ | 2747/11952 [45:41<15:13:19, 5.95s/it]
{'loss': 0.4997, 'learning_rate': 1.7978202541376533e-05, 'epoch': 0.23}
+
23%|██▎ | 2747/11952 [45:41<15:13:19, 5.95s/it]
23%|██▎ | 2748/11952 [45:47<15:02:41, 5.88s/it]
{'loss': 0.5177, 'learning_rate': 1.7976568459353078e-05, 'epoch': 0.23}
+
23%|██▎ | 2748/11952 [45:47<15:02:41, 5.88s/it]
23%|██▎ | 2749/11952 [45:53<15:06:21, 5.91s/it]
{'loss': 0.4966, 'learning_rate': 1.797493379156361e-05, 'epoch': 0.23}
+
23%|██▎ | 2749/11952 [45:53<15:06:21, 5.91s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+51 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+037 AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+ AutoResumeHook: Checking whether to suspend...
+
23%|██▎ | 2750/11952 [45:59<15:04:46, 5.90s/it]
{'loss': 0.4932, 'learning_rate': 1.7973298538128174e-05, 'epoch': 0.23}
+
23%|██▎ | 2750/11952 [45:59<15:04:46, 5.90s/it]
23%|██▎ | 2751/11952 [46:05<15:04:50, 5.90s/it]
{'loss': 0.4896, 'learning_rate': 1.797166269916686e-05, 'epoch': 0.23}
+
23%|██▎ | 2751/11952 [46:05<15:04:50, 5.90s/it]
23%|██▎ | 2752/11952 [46:11<15:19:17, 6.00s/it]
{'loss': 0.4984, 'learning_rate': 1.797002627479979e-05, 'epoch': 0.23}
+
23%|██▎ | 2752/11952 [46:11<15:19:17, 6.00s/it]
23%|██▎ | 2753/11952 [46:17<15:20:17, 6.00s/it]
{'loss': 0.5047, 'learning_rate': 1.7968389265147142e-05, 'epoch': 0.23}
+
23%|██▎ | 2753/11952 [46:17<15:20:17, 6.00s/it]
23%|██▎ | 2754/11952 [46:23<15:16:59, 5.98s/it]
{'loss': 0.4992, 'learning_rate': 1.796675167032913e-05, 'epoch': 0.23}
+
23%|██▎ | 2754/11952 [46:23<15:16:59, 5.98s/it]
23%|██▎ | 2755/11952 [46:29<15:09:36, 5.93s/it]
{'loss': 0.4927, 'learning_rate': 1.7965113490466013e-05, 'epoch': 0.23}
+
23%|██▎ | 2755/11952 [46:29<15:09:36, 5.93s/it]
23%|██▎ | 2756/11952 [46:35<15:10:22, 5.94s/it]
{'loss': 0.4969, 'learning_rate': 1.796347472567809e-05, 'epoch': 0.23}
+
23%|██▎ | 2756/11952 [46:35<15:10:22, 5.94s/it]
23%|██▎ | 2757/11952 [46:41<15:14:37, 5.97s/it]
{'loss': 0.497, 'learning_rate': 1.7961835376085702e-05, 'epoch': 0.23}
+
23%|██▎ | 2757/11952 [46:41<15:14:37, 5.97s/it]
23%|██▎ | 2758/11952 [46:46<14:58:54, 5.87s/it]
{'loss': 0.4832, 'learning_rate': 1.7960195441809242e-05, 'epoch': 0.23}
+
23%|██▎ | 2758/11952 [46:46<14:58:54, 5.87s/it]
23%|██▎ | 2759/11952 [46:52<15:07:40, 5.92s/it]
{'loss': 0.5121, 'learning_rate': 1.795855492296914e-05, 'epoch': 0.23}
+
23%|██▎ | 2759/11952 [46:52<15:07:40, 5.92s/it]
23%|██▎ | 2760/11952 [46:58<14:59:20, 5.87s/it]
{'loss': 0.5147, 'learning_rate': 1.7956913819685865e-05, 'epoch': 0.23}
+
23%|██▎ | 2760/11952 [46:58<14:59:20, 5.87s/it]
23%|██▎ | 2761/11952 [47:04<14:55:16, 5.84s/it]
{'loss': 0.4937, 'learning_rate': 1.7955272132079935e-05, 'epoch': 0.23}
+
23%|██▎ | 2761/11952 [47:04<14:55:16, 5.84s/it]
23%|██▎ | 2762/11952 [47:10<15:04:31, 5.91s/it]
{'loss': 0.5006, 'learning_rate': 1.7953629860271906e-05, 'epoch': 0.23}
+
23%|██▎ | 2762/11952 [47:10<15:04:31, 5.91s/it]
23%|██▎ | 2763/11952 [47:16<15:08:08, 5.93s/it]
{'loss': 0.4956, 'learning_rate': 1.7951987004382384e-05, 'epoch': 0.23}
+
23%|██▎ | 2763/11952 [47:16<15:08:08, 5.93s/it]
23%|██▎ | 2764/11952 [47:22<15:07:55, 5.93s/it]
{'loss': 0.5006, 'learning_rate': 1.795034356453201e-05, 'epoch': 0.23}
+
23%|██▎ | 2764/11952 [47:22<15:07:55, 5.93s/it]
23%|██▎ | 2765/11952 [47:28<15:00:42, 5.88s/it]
{'loss': 0.51, 'learning_rate': 1.794869954084147e-05, 'epoch': 0.23}
+
23%|██▎ | 2765/11952 [47:28<15:00:42, 5.88s/it]
23%|██▎ | 2766/11952 [47:33<14:39:22, 5.74s/it]
{'loss': 0.4736, 'learning_rate': 1.79470549334315e-05, 'epoch': 0.23}
+
23%|██▎ | 2766/11952 [47:33<14:39:22, 5.74s/it]
23%|██▎ | 2767/11952 [47:39<14:48:09, 5.80s/it]
{'loss': 0.5055, 'learning_rate': 1.794540974242287e-05, 'epoch': 0.23}
+
23%|██▎ | 2767/11952 [47:39<14:48:09, 5.80s/it]
23%|██▎ | 2768/11952 [47:45<14:55:47, 5.85s/it]
{'loss': 0.5209, 'learning_rate': 1.7943763967936395e-05, 'epoch': 0.23}
+
23%|██▎ | 2768/11952 [47:45<14:55:47, 5.85s/it]
23%|██▎ | 2769/11952 [47:51<14:52:30, 5.83s/it]
{'loss': 0.493, 'learning_rate': 1.7942117610092938e-05, 'epoch': 0.23}
+
23%|██▎ | 2769/11952 [47:51<14:52:30, 5.83s/it]
23%|██▎ | 2770/11952 [47:56<14:49:00, 5.81s/it]
{'loss': 0.4909, 'learning_rate': 1.794047066901339e-05, 'epoch': 0.23}
+
23%|██▎ | 2770/11952 [47:56<14:49:00, 5.81s/it]
23%|██▎ | 2771/11952 [48:02<14:54:13, 5.84s/it]
{'loss': 0.5175, 'learning_rate': 1.7938823144818712e-05, 'epoch': 0.23}
+
23%|██▎ | 2771/11952 [48:02<14:54:13, 5.84s/it]
23%|██▎ | 2772/11952 [48:08<15:03:59, 5.91s/it]
{'loss': 0.4814, 'learning_rate': 1.7937175037629876e-05, 'epoch': 0.23}
+
23%|██▎ | 2772/11952 [48:08<15:03:59, 5.91s/it]
23%|██▎ | 2773/11952 [48:14<14:47:52, 5.80s/it]
{'loss': 0.5145, 'learning_rate': 1.793552634756792e-05, 'epoch': 0.23}
+
23%|██▎ | 2773/11952 [48:14<14:47:52, 5.80s/it]
23%|██▎ | 2774/11952 [48:20<14:36:01, 5.73s/it]
{'loss': 0.5087, 'learning_rate': 1.793387707475392e-05, 'epoch': 0.23}
+
23%|██▎ | 2774/11952 [48:20<14:36:01, 5.73s/it]
23%|██▎ | 2775/11952 [48:25<14:43:05, 5.77s/it]
{'loss': 0.504, 'learning_rate': 1.793222721930898e-05, 'epoch': 0.23}
+
23%|██▎ | 2775/11952 [48:25<14:43:05, 5.77s/it]
23%|██▎ | 2776/11952 [48:31<14:52:55, 5.84s/it]
{'loss': 0.4912, 'learning_rate': 1.793057678135427e-05, 'epoch': 0.23}
+
23%|██▎ | 2776/11952 [48:31<14:52:55, 5.84s/it]
23%|██▎ | 2777/11952 [48:37<14:46:00, 5.79s/it]
{'loss': 0.5088, 'learning_rate': 1.7928925761010984e-05, 'epoch': 0.23}
+
23%|██▎ | 2777/11952 [48:37<14:46:00, 5.79s/it]
23%|██▎ | 2778/11952 [48:43<14:41:24, 5.76s/it]
{'loss': 0.484, 'learning_rate': 1.792727415840037e-05, 'epoch': 0.23}
+
23%|██▎ | 2778/11952 [48:43<14:41:24, 5.76s/it]
23%|██▎ | 2779/11952 [48:48<14:34:28, 5.72s/it]
{'loss': 0.5029, 'learning_rate': 1.7925621973643713e-05, 'epoch': 0.23}
+
23%|██▎ | 2779/11952 [48:48<14:34:28, 5.72s/it]
23%|██▎ | 2780/11952 [48:54<14:30:53, 5.70s/it]
{'loss': 0.5131, 'learning_rate': 1.7923969206862347e-05, 'epoch': 0.23}
+
23%|██▎ | 2780/11952 [48:54<14:30:53, 5.70s/it]
23%|██▎ | 2781/11952 [49:00<14:48:39, 5.81s/it]
{'loss': 0.4955, 'learning_rate': 1.7922315858177638e-05, 'epoch': 0.23}
+
23%|██▎ | 2781/11952 [49:00<14:48:39, 5.81s/it]
23%|██▎ | 2782/11952 [49:06<14:52:05, 5.84s/it]
{'loss': 0.5075, 'learning_rate': 1.7920661927711002e-05, 'epoch': 0.23}
+
23%|██▎ | 2782/11952 [49:06<14:52:05, 5.84s/it]
23%|██▎ | 2783/11952 [49:12<14:58:09, 5.88s/it]
{'loss': 0.469, 'learning_rate': 1.7919007415583903e-05, 'epoch': 0.23}
+
23%|██▎ | 2783/11952 [49:12<14:58:09, 5.88s/it]
23%|██▎ | 2784/11952 [49:18<15:00:58, 5.90s/it]
{'loss': 0.5087, 'learning_rate': 1.7917352321917834e-05, 'epoch': 0.23}
+
23%|██▎ | 2784/11952 [49:18<15:00:58, 5.90s/it]
23%|██▎ | 2785/11952 [49:24<14:49:03, 5.82s/it]
{'loss': 0.4729, 'learning_rate': 1.7915696646834343e-05, 'epoch': 0.23}
+
23%|██▎ | 2785/11952 [49:24<14:49:03, 5.82s/it]
23%|██▎ | 2786/11952 [49:29<14:44:16, 5.79s/it]
{'loss': 0.4914, 'learning_rate': 1.7914040390455014e-05, 'epoch': 0.23}
+
23%|██▎ | 2786/11952 [49:29<14:44:16, 5.79s/it]
23%|██▎ | 2787/11952 [49:35<14:43:15, 5.78s/it]
{'loss': 0.5058, 'learning_rate': 1.7912383552901473e-05, 'epoch': 0.23}
+
23%|██▎ | 2787/11952 [49:35<14:43:15, 5.78s/it]
23%|██▎ | 2788/11952 [49:41<14:56:42, 5.87s/it]
{'loss': 0.4916, 'learning_rate': 1.7910726134295396e-05, 'epoch': 0.23}
+
23%|██▎ | 2788/11952 [49:41<14:56:42, 5.87s/it]
23%|██▎ | 2789/11952 [49:47<14:59:09, 5.89s/it]
{'loss': 0.5064, 'learning_rate': 1.7909068134758497e-05, 'epoch': 0.23}
+
23%|██▎ | 2789/11952 [49:47<14:59:09, 5.89s/it]
23%|██▎ | 2790/11952 [49:53<14:46:13, 5.80s/it]
{'loss': 0.501, 'learning_rate': 1.7907409554412526e-05, 'epoch': 0.23}
+
23%|██▎ | 2790/11952 [49:53<14:46:13, 5.80s/it]
23%|██▎ | 2791/11952 [49:59<15:13:58, 5.99s/it]
{'loss': 0.5054, 'learning_rate': 1.790575039337929e-05, 'epoch': 0.23}
+
23%|██▎ | 2791/11952 [49:59<15:13:58, 5.99s/it]
23%|██▎ | 2792/11952 [50:05<15:07:21, 5.94s/it]
{'loss': 0.4934, 'learning_rate': 1.7904090651780624e-05, 'epoch': 0.23}
+
23%|██▎ | 2792/11952 [50:05<15:07:21, 5.94s/it]
23%|██▎ | 2793/11952 [50:11<15:14:33, 5.99s/it]
{'loss': 0.5042, 'learning_rate': 1.790243032973842e-05, 'epoch': 0.23}
+
23%|██▎ | 2793/11952 [50:11<15:14:33, 5.99s/it]
23%|██▎ | 2794/11952 [50:17<14:54:56, 5.86s/it]
{'loss': 0.4681, 'learning_rate': 1.79007694273746e-05, 'epoch': 0.23}
+
23%|██▎ | 2794/11952 [50:17<14:54:56, 5.86s/it]
23%|██▎ | 2795/11952 [50:22<14:50:44, 5.84s/it]
{'loss': 0.5011, 'learning_rate': 1.7899107944811133e-05, 'epoch': 0.23}
+
23%|██▎ | 2795/11952 [50:22<14:50:44, 5.84s/it]
23%|██▎ | 2796/11952 [50:28<14:46:29, 5.81s/it]
{'loss': 0.5067, 'learning_rate': 1.7897445882170038e-05, 'epoch': 0.23}
+
23%|██▎ | 2796/11952 [50:28<14:46:29, 5.81s/it]
23%|██▎ | 2797/11952 [50:34<14:39:34, 5.76s/it]
{'loss': 0.5044, 'learning_rate': 1.789578323957336e-05, 'epoch': 0.23}
+
23%|██▎ | 2797/11952 [50:34<14:39:34, 5.76s/it]
23%|██▎ | 2798/11952 [50:40<14:38:19, 5.76s/it]
{'loss': 0.5046, 'learning_rate': 1.7894120017143205e-05, 'epoch': 0.23}
+
23%|██▎ | 2798/11952 [50:40<14:38:19, 5.76s/it]
23%|██▎ | 2799/11952 [50:45<14:34:29, 5.73s/it]
{'loss': 0.4989, 'learning_rate': 1.789245621500171e-05, 'epoch': 0.23}
+
23%|██▎ | 2799/11952 [50:45<14:34:29, 5.73s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+40 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
23%|██▎ | 2800/11952 [50:51<14:32:12, 5.72s/it]
{'loss': 0.4721, 'learning_rate': 1.7890791833271058e-05, 'epoch': 0.23}
+
23%|██▎ | 2800/11952 [50:51<14:32:12, 5.72s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
23%|██▎ | 2801/11952 [51:27<37:27:38, 14.74s/it]
{'loss': 0.5095, 'learning_rate': 1.7889126872073473e-05, 'epoch': 0.23}
+
23%|██▎ | 2801/11952 [51:27<37:27:38, 14.74s/it]
23%|██▎ | 2802/11952 [51:33<30:45:18, 12.10s/it]
{'loss': 0.496, 'learning_rate': 1.7887461331531224e-05, 'epoch': 0.23}
+
23%|██▎ | 2802/11952 [51:33<30:45:18, 12.10s/it]
23%|██▎ | 2803/11952 [51:38<25:51:31, 10.18s/it]
{'loss': 0.4881, 'learning_rate': 1.788579521176662e-05, 'epoch': 0.23}
+
23%|██▎ | 2803/11952 [51:38<25:51:31, 10.18s/it]
23%|██▎ | 2804/11952 [51:44<22:33:01, 8.87s/it]
{'loss': 0.5057, 'learning_rate': 1.7884128512902018e-05, 'epoch': 0.23}
+
23%|██▎ | 2804/11952 [51:44<22:33:01, 8.87s/it]
23%|██▎ | 2805/11952 [51:50<20:11:55, 7.95s/it]
{'loss': 0.5034, 'learning_rate': 1.788246123505981e-05, 'epoch': 0.23}
+
23%|██▎ | 2805/11952 [51:50<20:11:55, 7.95s/it]
23%|██▎ | 2806/11952 [51:56<18:30:23, 7.28s/it]
{'loss': 0.4997, 'learning_rate': 1.7880793378362432e-05, 'epoch': 0.23}
+
23%|██▎ | 2806/11952 [51:56<18:30:23, 7.28s/it]
23%|██▎ | 2807/11952 [52:01<17:21:59, 6.84s/it]
{'loss': 0.4959, 'learning_rate': 1.787912494293237e-05, 'epoch': 0.23}
+
23%|██▎ | 2807/11952 [52:01<17:21:59, 6.84s/it]
23%|██▎ | 2808/11952 [52:07<16:25:39, 6.47s/it]
{'loss': 0.4812, 'learning_rate': 1.787745592889214e-05, 'epoch': 0.23}
+
23%|██▎ | 2808/11952 [52:07<16:25:39, 6.47s/it]
24%|██▎ | 2809/11952 [52:13<15:55:11, 6.27s/it]
{'loss': 0.5047, 'learning_rate': 1.7875786336364316e-05, 'epoch': 0.24}
+
24%|██▎ | 2809/11952 [52:13<15:55:11, 6.27s/it]
24%|██▎ | 2810/11952 [52:19<15:28:25, 6.09s/it]
{'loss': 0.4924, 'learning_rate': 1.78741161654715e-05, 'epoch': 0.24}
+
24%|██▎ | 2810/11952 [52:19<15:28:25, 6.09s/it]
24%|██▎ | 2811/11952 [52:24<15:08:04, 5.96s/it]
{'loss': 0.5078, 'learning_rate': 1.7872445416336343e-05, 'epoch': 0.24}
+
24%|██▎ | 2811/11952 [52:24<15:08:04, 5.96s/it]
24%|██▎ | 2812/11952 [52:30<14:54:15, 5.87s/it]
{'loss': 0.4883, 'learning_rate': 1.7870774089081537e-05, 'epoch': 0.24}
+
24%|██▎ | 2812/11952 [52:30<14:54:15, 5.87s/it]
24%|██▎ | 2813/11952 [52:35<14:40:56, 5.78s/it]
{'loss': 0.5038, 'learning_rate': 1.786910218382982e-05, 'epoch': 0.24}
+
24%|██▎ | 2813/11952 [52:35<14:40:56, 5.78s/it]
24%|██▎ | 2814/11952 [52:41<14:51:21, 5.85s/it]
{'loss': 0.5137, 'learning_rate': 1.7867429700703967e-05, 'epoch': 0.24}
+
24%|██▎ | 2814/11952 [52:41<14:51:21, 5.85s/it]
24%|██▎ | 2815/11952 [52:47<14:48:09, 5.83s/it]
{'loss': 0.5147, 'learning_rate': 1.7865756639826805e-05, 'epoch': 0.24}
+
24%|██▎ | 2815/11952 [52:47<14:48:09, 5.83s/it]
24%|██▎ | 2816/11952 [52:53<15:03:08, 5.93s/it]
{'loss': 0.4802, 'learning_rate': 1.786408300132119e-05, 'epoch': 0.24}
+
24%|██▎ | 2816/11952 [52:53<15:03:08, 5.93s/it]
24%|██▎ | 2817/11952 [52:59<15:03:14, 5.93s/it]
{'loss': 0.5072, 'learning_rate': 1.7862408785310025e-05, 'epoch': 0.24}
+
24%|██▎ | 2817/11952 [52:59<15:03:14, 5.93s/it]
24%|██▎ | 2818/11952 [53:05<14:58:45, 5.90s/it]
{'loss': 0.5101, 'learning_rate': 1.7860733991916263e-05, 'epoch': 0.24}
+
24%|██▎ | 2818/11952 [53:05<14:58:45, 5.90s/it]
24%|██▎ | 2819/11952 [53:11<15:06:03, 5.95s/it]
{'loss': 0.4928, 'learning_rate': 1.7859058621262893e-05, 'epoch': 0.24}
+
24%|██▎ | 2819/11952 [53:11<15:06:03, 5.95s/it]
24%|██▎ | 2820/11952 [53:17<15:01:20, 5.92s/it]
{'loss': 0.499, 'learning_rate': 1.7857382673472946e-05, 'epoch': 0.24}
+
24%|██▎ | 2820/11952 [53:17<15:01:20, 5.92s/it]
24%|██▎ | 2821/11952 [53:23<15:07:35, 5.96s/it]
{'loss': 0.5024, 'learning_rate': 1.7855706148669494e-05, 'epoch': 0.24}
+
24%|██▎ | 2821/11952 [53:23<15:07:35, 5.96s/it]
24%|██▎ | 2822/11952 [53:29<14:56:20, 5.89s/it]
{'loss': 0.4932, 'learning_rate': 1.785402904697566e-05, 'epoch': 0.24}
+
24%|██▎ | 2822/11952 [53:29<14:56:20, 5.89s/it]
24%|██▎ | 2823/11952 [53:35<14:49:49, 5.85s/it]
{'loss': 0.5075, 'learning_rate': 1.7852351368514597e-05, 'epoch': 0.24}
+
24%|██▎ | 2823/11952 [53:35<14:49:49, 5.85s/it]
24%|██▎ | 2824/11952 [53:40<14:41:34, 5.79s/it]
{'loss': 0.499, 'learning_rate': 1.7850673113409514e-05, 'epoch': 0.24}
+
24%|██▎ | 2824/11952 [53:40<14:41:34, 5.79s/it]
24%|██▎ | 2825/11952 [53:46<14:37:59, 5.77s/it]
{'loss': 0.5007, 'learning_rate': 1.7848994281783648e-05, 'epoch': 0.24}
+
24%|██▎ | 2825/11952 [53:46<14:37:59, 5.77s/it]
24%|██▎ | 2826/11952 [53:52<14:35:55, 5.76s/it]
{'loss': 0.5201, 'learning_rate': 1.784731487376029e-05, 'epoch': 0.24}
+
24%|██▎ | 2826/11952 [53:52<14:35:55, 5.76s/it]
24%|██▎ | 2827/11952 [53:57<14:27:18, 5.70s/it]
{'loss': 0.4836, 'learning_rate': 1.7845634889462763e-05, 'epoch': 0.24}
+
24%|██▎ | 2827/11952 [53:57<14:27:18, 5.70s/it]
24%|██▎ | 2828/11952 [54:03<14:38:02, 5.77s/it]
{'loss': 0.5021, 'learning_rate': 1.784395432901445e-05, 'epoch': 0.24}
+
24%|██▎ | 2828/11952 [54:03<14:38:02, 5.77s/it]
24%|██▎ | 2829/11952 [54:09<14:38:22, 5.78s/it]
{'loss': 0.5008, 'learning_rate': 1.784227319253875e-05, 'epoch': 0.24}
+
24%|██▎ | 2829/11952 [54:09<14:38:22, 5.78s/it]
24%|██▎ | 2830/11952 [54:15<14:44:46, 5.82s/it]
{'loss': 0.5007, 'learning_rate': 1.7840591480159127e-05, 'epoch': 0.24}
+
24%|██▎ | 2830/11952 [54:15<14:44:46, 5.82s/it]
24%|██▎ | 2831/11952 [54:21<14:51:05, 5.86s/it]
{'loss': 0.4969, 'learning_rate': 1.7838909191999077e-05, 'epoch': 0.24}
+
24%|██▎ | 2831/11952 [54:21<14:51:05, 5.86s/it]
24%|██▎ | 2832/11952 [54:27<14:44:08, 5.82s/it]
{'loss': 0.4959, 'learning_rate': 1.783722632818214e-05, 'epoch': 0.24}
+
24%|██▎ | 2832/11952 [54:27<14:44:08, 5.82s/it]
24%|██▎ | 2833/11952 [54:32<14:40:09, 5.79s/it]
{'loss': 0.5112, 'learning_rate': 1.78355428888319e-05, 'epoch': 0.24}
+
24%|██▎ | 2833/11952 [54:32<14:40:09, 5.79s/it]
24%|██▎ | 2834/11952 [54:38<14:49:22, 5.85s/it]
{'loss': 0.5032, 'learning_rate': 1.783385887407198e-05, 'epoch': 0.24}
+
24%|██▎ | 2834/11952 [54:38<14:49:22, 5.85s/it]
24%|██▎ | 2835/11952 [54:44<14:52:34, 5.87s/it]
{'loss': 0.5036, 'learning_rate': 1.783217428402605e-05, 'epoch': 0.24}
+
24%|██▎ | 2835/11952 [54:44<14:52:34, 5.87s/it]
24%|██▎ | 2836/11952 [54:50<14:38:58, 5.79s/it]
{'loss': 0.5104, 'learning_rate': 1.7830489118817812e-05, 'epoch': 0.24}
+
24%|██▎ | 2836/11952 [54:50<14:38:58, 5.79s/it]
24%|██▎ | 2837/11952 [54:55<14:28:04, 5.71s/it]
{'loss': 0.4815, 'learning_rate': 1.7828803378571028e-05, 'epoch': 0.24}
+
24%|██▎ | 2837/11952 [54:55<14:28:04, 5.71s/it]
24%|██▎ | 2838/11952 [55:01<14:35:23, 5.76s/it]
{'loss': 0.4726, 'learning_rate': 1.7827117063409483e-05, 'epoch': 0.24}
+
24%|██▎ | 2838/11952 [55:01<14:35:23, 5.76s/it]
24%|██▍ | 2839/11952 [55:07<14:32:54, 5.75s/it]
{'loss': 0.4989, 'learning_rate': 1.782543017345702e-05, 'epoch': 0.24}
+
24%|██▍ | 2839/11952 [55:07<14:32:54, 5.75s/it]
24%|██▍ | 2840/11952 [55:13<14:21:20, 5.67s/it]
{'loss': 0.4892, 'learning_rate': 1.782374270883751e-05, 'epoch': 0.24}
+
24%|██▍ | 2840/11952 [55:13<14:21:20, 5.67s/it]
24%|██▍ | 2841/11952 [55:18<14:31:00, 5.74s/it]
{'loss': 0.4928, 'learning_rate': 1.7822054669674878e-05, 'epoch': 0.24}
+
24%|██▍ | 2841/11952 [55:18<14:31:00, 5.74s/it]
24%|██▍ | 2842/11952 [55:24<14:23:46, 5.69s/it]
{'loss': 0.4805, 'learning_rate': 1.7820366056093083e-05, 'epoch': 0.24}
+
24%|██▍ | 2842/11952 [55:24<14:23:46, 5.69s/it]
24%|██▍ | 2843/11952 [55:30<14:27:59, 5.72s/it]
{'loss': 0.4995, 'learning_rate': 1.7818676868216137e-05, 'epoch': 0.24}
+
24%|██▍ | 2843/11952 [55:30<14:27:59, 5.72s/it]
24%|██▍ | 2844/11952 [55:35<14:21:20, 5.67s/it]
{'loss': 0.4744, 'learning_rate': 1.781698710616808e-05, 'epoch': 0.24}
+
24%|██▍ | 2844/11952 [55:35<14:21:20, 5.67s/it]
24%|██▍ | 2845/11952 [55:41<14:36:51, 5.78s/it]
{'loss': 0.4918, 'learning_rate': 1.7815296770073002e-05, 'epoch': 0.24}
+
24%|██▍ | 2845/11952 [55:41<14:36:51, 5.78s/it]
24%|██▍ | 2846/11952 [55:47<14:38:58, 5.79s/it]
{'loss': 0.5363, 'learning_rate': 1.7813605860055034e-05, 'epoch': 0.24}
+
24%|██▍ | 2846/11952 [55:47<14:38:58, 5.79s/it]
24%|██▍ | 2847/11952 [55:53<14:33:24, 5.76s/it]
{'loss': 0.4904, 'learning_rate': 1.7811914376238354e-05, 'epoch': 0.24}
+
24%|██▍ | 2847/11952 [55:53<14:33:24, 5.76s/it]
24%|██▍ | 2848/11952 [55:58<14:27:17, 5.72s/it]
{'loss': 0.4744, 'learning_rate': 1.7810222318747173e-05, 'epoch': 0.24}
+
24%|██▍ | 2848/11952 [55:58<14:27:17, 5.72s/it]
24%|██▍ | 2849/11952 [56:04<14:35:42, 5.77s/it]
{'loss': 0.4957, 'learning_rate': 1.780852968770575e-05, 'epoch': 0.24}
+
24%|██▍ | 2849/11952 [56:04<14:35:42, 5.77s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...1
+ AutoResumeHook: Checking whether to suspend...
+074 AutoResumeHook: Checking whether to suspend... 3
+AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
24%|██▍ | 2850/11952 [56:10<14:35:53, 5.77s/it]
{'loss': 0.521, 'learning_rate': 1.7806836483238387e-05, 'epoch': 0.24}
+
24%|██▍ | 2850/11952 [56:10<14:35:53, 5.77s/it]
24%|██▍ | 2851/11952 [56:16<14:33:03, 5.76s/it]
{'loss': 0.4905, 'learning_rate': 1.780514270546942e-05, 'epoch': 0.24}
+
24%|██▍ | 2851/11952 [56:16<14:33:03, 5.76s/it]
24%|██▍ | 2852/11952 [56:22<14:48:23, 5.86s/it]
{'loss': 0.494, 'learning_rate': 1.780344835452324e-05, 'epoch': 0.24}
+
24%|██▍ | 2852/11952 [56:22<14:48:23, 5.86s/it]
24%|██▍ | 2853/11952 [56:28<14:36:27, 5.78s/it]
{'loss': 0.4928, 'learning_rate': 1.780175343052427e-05, 'epoch': 0.24}
+
24%|██▍ | 2853/11952 [56:28<14:36:27, 5.78s/it]
24%|██▍ | 2854/11952 [56:34<14:45:27, 5.84s/it]
{'loss': 0.4872, 'learning_rate': 1.7800057933596975e-05, 'epoch': 0.24}
+
24%|██▍ | 2854/11952 [56:34<14:45:27, 5.84s/it]
24%|██▍ | 2855/11952 [56:39<14:35:59, 5.78s/it]
{'loss': 0.4856, 'learning_rate': 1.779836186386587e-05, 'epoch': 0.24}
+
24%|██▍ | 2855/11952 [56:39<14:35:59, 5.78s/it]
24%|██▍ | 2856/11952 [56:45<14:31:56, 5.75s/it]
{'loss': 0.5121, 'learning_rate': 1.7796665221455503e-05, 'epoch': 0.24}
+
24%|██▍ | 2856/11952 [56:45<14:31:56, 5.75s/it]
24%|██▍ | 2857/11952 [56:51<14:28:27, 5.73s/it]
{'loss': 0.4866, 'learning_rate': 1.7794968006490475e-05, 'epoch': 0.24}
+
24%|██▍ | 2857/11952 [56:51<14:28:27, 5.73s/it]
24%|██▍ | 2858/11952 [56:57<14:45:29, 5.84s/it]
{'loss': 0.498, 'learning_rate': 1.7793270219095418e-05, 'epoch': 0.24}
+
24%|██▍ | 2858/11952 [56:57<14:45:29, 5.84s/it]
24%|██▍ | 2859/11952 [57:03<14:48:24, 5.86s/it]
{'loss': 0.4983, 'learning_rate': 1.779157185939501e-05, 'epoch': 0.24}
+
24%|██▍ | 2859/11952 [57:03<14:48:24, 5.86s/it]
24%|██▍ | 2860/11952 [57:08<14:50:02, 5.87s/it]
{'loss': 0.501, 'learning_rate': 1.778987292751397e-05, 'epoch': 0.24}
+
24%|██▍ | 2860/11952 [57:08<14:50:02, 5.87s/it]
24%|██▍ | 2861/11952 [57:14<14:54:52, 5.91s/it]
{'loss': 0.5019, 'learning_rate': 1.7788173423577063e-05, 'epoch': 0.24}
+
24%|██▍ | 2861/11952 [57:14<14:54:52, 5.91s/it]
24%|██▍ | 2862/11952 [57:20<15:01:15, 5.95s/it]
{'loss': 0.5126, 'learning_rate': 1.7786473347709094e-05, 'epoch': 0.24}
+
24%|██▍ | 2862/11952 [57:20<15:01:15, 5.95s/it]
24%|██▍ | 2863/11952 [57:26<15:01:10, 5.95s/it]
{'loss': 0.5096, 'learning_rate': 1.778477270003491e-05, 'epoch': 0.24}
+
24%|██▍ | 2863/11952 [57:26<15:01:10, 5.95s/it]
24%|██▍ | 2864/11952 [57:32<14:47:24, 5.86s/it]
{'loss': 0.506, 'learning_rate': 1.7783071480679397e-05, 'epoch': 0.24}
+
24%|██▍ | 2864/11952 [57:32<14:47:24, 5.86s/it]
24%|██▍ | 2865/11952 [57:38<14:42:11, 5.82s/it]
{'loss': 0.4847, 'learning_rate': 1.7781369689767488e-05, 'epoch': 0.24}
+
24%|██▍ | 2865/11952 [57:38<14:42:11, 5.82s/it]
24%|██▍ | 2866/11952 [57:44<14:54:08, 5.90s/it]
{'loss': 0.5061, 'learning_rate': 1.7779667327424152e-05, 'epoch': 0.24}
+
24%|██▍ | 2866/11952 [57:44<14:54:08, 5.90s/it]
24%|██▍ | 2867/11952 [57:50<14:45:53, 5.85s/it]
{'loss': 0.5108, 'learning_rate': 1.777796439377441e-05, 'epoch': 0.24}
+
24%|██▍ | 2867/11952 [57:50<14:45:53, 5.85s/it]
24%|██▍ | 2868/11952 [57:55<14:39:52, 5.81s/it]
{'loss': 0.486, 'learning_rate': 1.777626088894331e-05, 'epoch': 0.24}
+
24%|██▍ | 2868/11952 [57:55<14:39:52, 5.81s/it]
24%|██▍ | 2869/11952 [58:02<14:56:42, 5.92s/it]
{'loss': 0.4891, 'learning_rate': 1.7774556813055956e-05, 'epoch': 0.24}
+
24%|██▍ | 2869/11952 [58:02<14:56:42, 5.92s/it]
24%|██▍ | 2870/11952 [58:07<14:44:07, 5.84s/it]
{'loss': 0.5196, 'learning_rate': 1.7772852166237483e-05, 'epoch': 0.24}
+
24%|██▍ | 2870/11952 [58:07<14:44:07, 5.84s/it]
24%|██▍ | 2871/11952 [58:13<14:34:03, 5.78s/it]
{'loss': 0.507, 'learning_rate': 1.7771146948613078e-05, 'epoch': 0.24}
+
24%|██▍ | 2871/11952 [58:13<14:34:03, 5.78s/it]
24%|██▍ | 2872/11952 [58:19<14:43:57, 5.84s/it]
{'loss': 0.5085, 'learning_rate': 1.7769441160307967e-05, 'epoch': 0.24}
+
24%|██▍ | 2872/11952 [58:19<14:43:57, 5.84s/it]
24%|██▍ | 2873/11952 [58:25<14:42:25, 5.83s/it]
{'loss': 0.4863, 'learning_rate': 1.776773480144741e-05, 'epoch': 0.24}
+
24%|██▍ | 2873/11952 [58:25<14:42:25, 5.83s/it]
24%|██▍ | 2874/11952 [58:30<14:35:10, 5.78s/it]
{'loss': 0.4874, 'learning_rate': 1.776602787215672e-05, 'epoch': 0.24}
+
24%|██▍ | 2874/11952 [58:30<14:35:10, 5.78s/it]
24%|██▍ | 2875/11952 [58:37<14:54:20, 5.91s/it]
{'loss': 0.5047, 'learning_rate': 1.7764320372561238e-05, 'epoch': 0.24}
+
24%|██▍ | 2875/11952 [58:37<14:54:20, 5.91s/it]
24%|██▍ | 2876/11952 [58:42<14:49:44, 5.88s/it]
{'loss': 0.495, 'learning_rate': 1.7762612302786372e-05, 'epoch': 0.24}
+
24%|██▍ | 2876/11952 [58:42<14:49:44, 5.88s/it]
24%|██▍ | 2877/11952 [58:48<14:55:36, 5.92s/it]
{'loss': 0.5146, 'learning_rate': 1.776090366295754e-05, 'epoch': 0.24}
+
24%|██▍ | 2877/11952 [58:48<14:55:36, 5.92s/it]
24%|██▍ | 2878/11952 [58:54<14:58:01, 5.94s/it]
{'loss': 0.4959, 'learning_rate': 1.775919445320022e-05, 'epoch': 0.24}
+
24%|██▍ | 2878/11952 [58:54<14:58:01, 5.94s/it]
24%|██▍ | 2879/11952 [59:00<15:00:07, 5.95s/it]
{'loss': 0.4918, 'learning_rate': 1.7757484673639936e-05, 'epoch': 0.24}
+
24%|██▍ | 2879/11952 [59:00<15:00:07, 5.95s/it]
24%|██▍ | 2880/11952 [59:06<14:43:25, 5.84s/it]
{'loss': 0.4994, 'learning_rate': 1.7755774324402244e-05, 'epoch': 0.24}
+
24%|██▍ | 2880/11952 [59:06<14:43:25, 5.84s/it]
24%|██▍ | 2881/11952 [59:12<14:36:32, 5.80s/it]
{'loss': 0.4843, 'learning_rate': 1.7754063405612744e-05, 'epoch': 0.24}
+
24%|██▍ | 2881/11952 [59:12<14:36:32, 5.80s/it]
24%|██▍ | 2882/11952 [59:18<14:42:17, 5.84s/it]
{'loss': 0.5114, 'learning_rate': 1.7752351917397078e-05, 'epoch': 0.24}
+
24%|██▍ | 2882/11952 [59:18<14:42:17, 5.84s/it]
24%|██▍ | 2883/11952 [59:23<14:34:45, 5.79s/it]
{'loss': 0.4892, 'learning_rate': 1.775063985988093e-05, 'epoch': 0.24}
+
24%|██▍ | 2883/11952 [59:23<14:34:45, 5.79s/it]
24%|██▍ | 2884/11952 [59:29<14:29:04, 5.75s/it]
{'loss': 0.5053, 'learning_rate': 1.774892723319003e-05, 'epoch': 0.24}
+
24%|██▍ | 2884/11952 [59:29<14:29:04, 5.75s/it]
24%|██▍ | 2885/11952 [59:35<14:30:31, 5.76s/it]
{'loss': 0.4994, 'learning_rate': 1.7747214037450146e-05, 'epoch': 0.24}
+
24%|██▍ | 2885/11952 [59:35<14:30:31, 5.76s/it]
24%|██▍ | 2886/11952 [59:40<14:18:49, 5.68s/it]
{'loss': 0.4916, 'learning_rate': 1.7745500272787084e-05, 'epoch': 0.24}
+
24%|██▍ | 2886/11952 [59:40<14:18:49, 5.68s/it]
24%|██▍ | 2887/11952 [59:46<14:29:46, 5.76s/it]
{'loss': 0.5066, 'learning_rate': 1.7743785939326697e-05, 'epoch': 0.24}
+
24%|██▍ | 2887/11952 [59:46<14:29:46, 5.76s/it]
24%|██▍ | 2888/11952 [59:52<14:35:00, 5.79s/it]
{'loss': 0.484, 'learning_rate': 1.7742071037194882e-05, 'epoch': 0.24}
+
24%|██▍ | 2888/11952 [59:52<14:35:00, 5.79s/it]
24%|██▍ | 2889/11952 [59:58<14:32:17, 5.77s/it]
{'loss': 0.5008, 'learning_rate': 1.7740355566517567e-05, 'epoch': 0.24}
+
24%|██▍ | 2889/11952 [59:58<14:32:17, 5.77s/it]
24%|██▍ | 2890/11952 [1:00:03<14:31:44, 5.77s/it]
{'loss': 0.4982, 'learning_rate': 1.7738639527420738e-05, 'epoch': 0.24}
+
24%|██▍ | 2890/11952 [1:00:03<14:31:44, 5.77s/it]
24%|██▍ | 2891/11952 [1:00:09<14:29:42, 5.76s/it]
{'loss': 0.4913, 'learning_rate': 1.773692292003041e-05, 'epoch': 0.24}
+
24%|██▍ | 2891/11952 [1:00:09<14:29:42, 5.76s/it]
24%|██▍ | 2892/11952 [1:00:15<14:36:45, 5.81s/it]
{'loss': 0.5338, 'learning_rate': 1.7735205744472642e-05, 'epoch': 0.24}
+
24%|██▍ | 2892/11952 [1:00:15<14:36:45, 5.81s/it]
24%|██▍ | 2893/11952 [1:00:21<15:01:21, 5.97s/it]
{'loss': 0.5042, 'learning_rate': 1.7733488000873538e-05, 'epoch': 0.24}
+
24%|██▍ | 2893/11952 [1:00:21<15:01:21, 5.97s/it]
24%|██▍ | 2894/11952 [1:00:27<14:55:40, 5.93s/it]
{'loss': 0.4934, 'learning_rate': 1.773176968935924e-05, 'epoch': 0.24}
+
24%|██▍ | 2894/11952 [1:00:27<14:55:40, 5.93s/it]
24%|██▍ | 2895/11952 [1:00:33<14:53:03, 5.92s/it]
{'loss': 0.499, 'learning_rate': 1.7730050810055935e-05, 'epoch': 0.24}
+
24%|██▍ | 2895/11952 [1:00:33<14:53:03, 5.92s/it]
24%|██▍ | 2896/11952 [1:00:39<15:05:11, 6.00s/it]
{'loss': 0.5032, 'learning_rate': 1.772833136308985e-05, 'epoch': 0.24}
+
24%|██▍ | 2896/11952 [1:00:39<15:05:11, 6.00s/it]
24%|██▍ | 2897/11952 [1:00:45<15:07:12, 6.01s/it]
{'loss': 0.5151, 'learning_rate': 1.7726611348587255e-05, 'epoch': 0.24}
+
24%|██▍ | 2897/11952 [1:00:45<15:07:12, 6.01s/it]
24%|██▍ | 2898/11952 [1:00:51<15:07:33, 6.01s/it]
{'loss': 0.4901, 'learning_rate': 1.7724890766674457e-05, 'epoch': 0.24}
+
24%|██▍ | 2898/11952 [1:00:51<15:07:33, 6.01s/it]
24%|██▍ | 2899/11952 [1:00:57<14:58:15, 5.95s/it]
{'loss': 0.5074, 'learning_rate': 1.7723169617477815e-05, 'epoch': 0.24}
+
24%|██▍ | 2899/11952 [1:00:57<14:58:15, 5.95s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
24%|██▍ | 2900/11952 [1:01:03<15:12:13, 6.05s/it]
{'loss': 0.4803, 'learning_rate': 1.772144790112372e-05, 'epoch': 0.24}
+
24%|██▍ | 2900/11952 [1:01:03<15:12:13, 6.05s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-2900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
24%|██▍ | 2901/11952 [1:01:38<36:40:27, 14.59s/it]
{'loss': 0.4699, 'learning_rate': 1.7719725617738605e-05, 'epoch': 0.24}
+
24%|██▍ | 2901/11952 [1:01:38<36:40:27, 14.59s/it]
24%|██▍ | 2902/11952 [1:01:44<30:03:06, 11.95s/it]
{'loss': 0.5076, 'learning_rate': 1.771800276744895e-05, 'epoch': 0.24}
+
24%|██▍ | 2902/11952 [1:01:44<30:03:06, 11.95s/it]
24%|██▍ | 2903/11952 [1:01:49<25:16:38, 10.06s/it]
{'loss': 0.4943, 'learning_rate': 1.771627935038127e-05, 'epoch': 0.24}
+
24%|██▍ | 2903/11952 [1:01:49<25:16:38, 10.06s/it]
24%|██▍ | 2904/11952 [1:01:55<22:10:03, 8.82s/it]
{'loss': 0.4933, 'learning_rate': 1.7714555366662133e-05, 'epoch': 0.24}
+
24%|██▍ | 2904/11952 [1:01:55<22:10:03, 8.82s/it]
24%|██▍ | 2905/11952 [1:02:01<19:45:50, 7.86s/it]
{'loss': 0.5069, 'learning_rate': 1.7712830816418137e-05, 'epoch': 0.24}
+
24%|██▍ | 2905/11952 [1:02:01<19:45:50, 7.86s/it]
24%|██▍ | 2906/11952 [1:02:07<18:04:41, 7.19s/it]
{'loss': 0.4909, 'learning_rate': 1.7711105699775925e-05, 'epoch': 0.24}
+
24%|██▍ | 2906/11952 [1:02:07<18:04:41, 7.19s/it]
24%|██▍ | 2907/11952 [1:02:12<16:59:34, 6.76s/it]
{'loss': 0.4913, 'learning_rate': 1.7709380016862182e-05, 'epoch': 0.24}
+
24%|██▍ | 2907/11952 [1:02:12<16:59:34, 6.76s/it]
24%|██▍ | 2908/11952 [1:02:18<16:06:05, 6.41s/it]
{'loss': 0.4997, 'learning_rate': 1.7707653767803638e-05, 'epoch': 0.24}
+
24%|██▍ | 2908/11952 [1:02:18<16:06:05, 6.41s/it]
24%|██▍ | 2909/11952 [1:02:24<15:30:27, 6.17s/it]
{'loss': 0.4943, 'learning_rate': 1.770592695272706e-05, 'epoch': 0.24}
+
24%|██▍ | 2909/11952 [1:02:24<15:30:27, 6.17s/it]
24%|██▍ | 2910/11952 [1:02:29<15:12:33, 6.06s/it]
{'loss': 0.5002, 'learning_rate': 1.7704199571759257e-05, 'epoch': 0.24}
+
24%|██▍ | 2910/11952 [1:02:29<15:12:33, 6.06s/it]
24%|██▍ | 2911/11952 [1:02:35<14:58:34, 5.96s/it]
{'loss': 0.4869, 'learning_rate': 1.770247162502708e-05, 'epoch': 0.24}
+
24%|██▍ | 2911/11952 [1:02:35<14:58:34, 5.96s/it]
24%|██▍ | 2912/11952 [1:02:41<14:45:45, 5.88s/it]
{'loss': 0.504, 'learning_rate': 1.7700743112657427e-05, 'epoch': 0.24}
+
24%|██▍ | 2912/11952 [1:02:41<14:45:45, 5.88s/it]
24%|██▍ | 2913/11952 [1:02:47<14:57:09, 5.96s/it]
{'loss': 0.4923, 'learning_rate': 1.7699014034777227e-05, 'epoch': 0.24}
+
24%|██▍ | 2913/11952 [1:02:47<14:57:09, 5.96s/it]
24%|██▍ | 2914/11952 [1:02:53<14:41:01, 5.85s/it]
{'loss': 0.5013, 'learning_rate': 1.7697284391513462e-05, 'epoch': 0.24}
+
24%|██▍ | 2914/11952 [1:02:53<14:41:01, 5.85s/it]
24%|██▍ | 2915/11952 [1:02:58<14:32:03, 5.79s/it]
{'loss': 0.5073, 'learning_rate': 1.7695554182993145e-05, 'epoch': 0.24}
+
24%|██▍ | 2915/11952 [1:02:58<14:32:03, 5.79s/it]
24%|██▍ | 2916/11952 [1:03:04<14:34:21, 5.81s/it]
{'loss': 0.4885, 'learning_rate': 1.7693823409343335e-05, 'epoch': 0.24}
+
24%|██▍ | 2916/11952 [1:03:04<14:34:21, 5.81s/it]
24%|██▍ | 2917/11952 [1:03:10<14:33:21, 5.80s/it]
{'loss': 0.5021, 'learning_rate': 1.769209207069114e-05, 'epoch': 0.24}
+
24%|██▍ | 2917/11952 [1:03:10<14:33:21, 5.80s/it]
24%|██▍ | 2918/11952 [1:03:15<14:24:07, 5.74s/it]
{'loss': 0.4975, 'learning_rate': 1.7690360167163693e-05, 'epoch': 0.24}
+
24%|██▍ | 2918/11952 [1:03:15<14:24:07, 5.74s/it]
24%|██▍ | 2919/11952 [1:03:21<14:36:40, 5.82s/it]
{'loss': 0.5013, 'learning_rate': 1.768862769888818e-05, 'epoch': 0.24}
+
24%|██▍ | 2919/11952 [1:03:21<14:36:40, 5.82s/it]
24%|██▍ | 2920/11952 [1:03:27<14:31:34, 5.79s/it]
{'loss': 0.5013, 'learning_rate': 1.7686894665991837e-05, 'epoch': 0.24}
+
24%|██▍ | 2920/11952 [1:03:27<14:31:34, 5.79s/it]
24%|██▍ | 2921/11952 [1:03:33<14:23:34, 5.74s/it]
{'loss': 0.4903, 'learning_rate': 1.7685161068601915e-05, 'epoch': 0.24}
+
24%|██▍ | 2921/11952 [1:03:33<14:23:34, 5.74s/it]
24%|██▍ | 2922/11952 [1:03:39<14:35:20, 5.82s/it]
{'loss': 0.4874, 'learning_rate': 1.768342690684573e-05, 'epoch': 0.24}
+
24%|██▍ | 2922/11952 [1:03:39<14:35:20, 5.82s/it]
24%|██▍ | 2923/11952 [1:03:45<14:32:59, 5.80s/it]
{'loss': 0.5023, 'learning_rate': 1.768169218085063e-05, 'epoch': 0.24}
+
24%|██▍ | 2923/11952 [1:03:45<14:32:59, 5.80s/it]
24%|██▍ | 2924/11952 [1:03:50<14:37:22, 5.83s/it]
{'loss': 0.4943, 'learning_rate': 1.7679956890744008e-05, 'epoch': 0.24}
+
24%|██▍ | 2924/11952 [1:03:50<14:37:22, 5.83s/it]
24%|██▍ | 2925/11952 [1:03:56<14:30:41, 5.79s/it]
{'loss': 0.505, 'learning_rate': 1.7678221036653295e-05, 'epoch': 0.24}
+
24%|██▍ | 2925/11952 [1:03:56<14:30:41, 5.79s/it]
24%|██▍ | 2926/11952 [1:04:02<14:33:09, 5.80s/it]
{'loss': 0.4858, 'learning_rate': 1.7676484618705966e-05, 'epoch': 0.24}
+
24%|██▍ | 2926/11952 [1:04:02<14:33:09, 5.80s/it]
24%|██▍ | 2927/11952 [1:04:08<14:34:37, 5.81s/it]
{'loss': 0.4885, 'learning_rate': 1.7674747637029533e-05, 'epoch': 0.24}
+
24%|██▍ | 2927/11952 [1:04:08<14:34:37, 5.81s/it]
24%|██▍ | 2928/11952 [1:04:13<14:27:26, 5.77s/it]
{'loss': 0.4894, 'learning_rate': 1.7673010091751557e-05, 'epoch': 0.24}
+
24%|██▍ | 2928/11952 [1:04:13<14:27:26, 5.77s/it]
25%|██▍ | 2929/11952 [1:04:19<14:31:51, 5.80s/it]
{'loss': 0.4983, 'learning_rate': 1.7671271982999637e-05, 'epoch': 0.25}
+
25%|██▍ | 2929/11952 [1:04:19<14:31:51, 5.80s/it]
25%|██▍ | 2930/11952 [1:04:25<14:29:15, 5.78s/it]
{'loss': 0.4914, 'learning_rate': 1.7669533310901405e-05, 'epoch': 0.25}
+
25%|██▍ | 2930/11952 [1:04:25<14:29:15, 5.78s/it]
25%|██▍ | 2931/11952 [1:04:31<14:25:06, 5.75s/it]
{'loss': 0.5021, 'learning_rate': 1.766779407558455e-05, 'epoch': 0.25}
+
25%|██▍ | 2931/11952 [1:04:31<14:25:06, 5.75s/it]
25%|██▍ | 2932/11952 [1:04:37<14:27:50, 5.77s/it]
{'loss': 0.4882, 'learning_rate': 1.7666054277176788e-05, 'epoch': 0.25}
+
25%|██▍ | 2932/11952 [1:04:37<14:27:50, 5.77s/it]
25%|██▍ | 2933/11952 [1:04:42<14:19:25, 5.72s/it]
{'loss': 0.4862, 'learning_rate': 1.7664313915805885e-05, 'epoch': 0.25}
+
25%|██▍ | 2933/11952 [1:04:42<14:19:25, 5.72s/it]
25%|██▍ | 2934/11952 [1:04:48<14:27:34, 5.77s/it]
{'loss': 0.5032, 'learning_rate': 1.7662572991599648e-05, 'epoch': 0.25}
+
25%|██▍ | 2934/11952 [1:04:48<14:27:34, 5.77s/it]
25%|██▍ | 2935/11952 [1:04:54<14:27:47, 5.77s/it]
{'loss': 0.4968, 'learning_rate': 1.7660831504685923e-05, 'epoch': 0.25}
+
25%|██▍ | 2935/11952 [1:04:54<14:27:47, 5.77s/it]
25%|██▍ | 2936/11952 [1:04:59<14:16:31, 5.70s/it]
{'loss': 0.4915, 'learning_rate': 1.7659089455192594e-05, 'epoch': 0.25}
+
25%|██▍ | 2936/11952 [1:04:59<14:16:31, 5.70s/it]
25%|██▍ | 2937/11952 [1:05:05<14:13:41, 5.68s/it]
{'loss': 0.5019, 'learning_rate': 1.7657346843247595e-05, 'epoch': 0.25}
+
25%|██▍ | 2937/11952 [1:05:05<14:13:41, 5.68s/it]
25%|██▍ | 2938/11952 [1:05:11<14:25:41, 5.76s/it]
{'loss': 0.4972, 'learning_rate': 1.765560366897889e-05, 'epoch': 0.25}
+
25%|██▍ | 2938/11952 [1:05:11<14:25:41, 5.76s/it]
25%|██▍ | 2939/11952 [1:05:17<14:26:46, 5.77s/it]
{'loss': 0.4978, 'learning_rate': 1.7653859932514494e-05, 'epoch': 0.25}
+
25%|██▍ | 2939/11952 [1:05:17<14:26:46, 5.77s/it]
25%|██▍ | 2940/11952 [1:05:23<14:30:33, 5.80s/it]
{'loss': 0.5023, 'learning_rate': 1.765211563398246e-05, 'epoch': 0.25}
+
25%|██▍ | 2940/11952 [1:05:23<14:30:33, 5.80s/it]
25%|██▍ | 2941/11952 [1:05:29<14:34:47, 5.82s/it]
{'loss': 0.5064, 'learning_rate': 1.7650370773510885e-05, 'epoch': 0.25}
+
25%|██▍ | 2941/11952 [1:05:29<14:34:47, 5.82s/it]
25%|██▍ | 2942/11952 [1:05:35<14:44:54, 5.89s/it]
{'loss': 0.481, 'learning_rate': 1.7648625351227894e-05, 'epoch': 0.25}
+
25%|██▍ | 2942/11952 [1:05:35<14:44:54, 5.89s/it]
25%|██▍ | 2943/11952 [1:05:40<14:33:04, 5.81s/it]
{'loss': 0.4964, 'learning_rate': 1.7646879367261673e-05, 'epoch': 0.25}
+
25%|██▍ | 2943/11952 [1:05:40<14:33:04, 5.81s/it]
25%|██▍ | 2944/11952 [1:05:46<14:28:38, 5.79s/it]
{'loss': 0.4971, 'learning_rate': 1.7645132821740437e-05, 'epoch': 0.25}
+
25%|██▍ | 2944/11952 [1:05:46<14:28:38, 5.79s/it]
25%|██▍ | 2945/11952 [1:05:52<14:50:38, 5.93s/it]
{'loss': 0.4873, 'learning_rate': 1.7643385714792446e-05, 'epoch': 0.25}
+
25%|██▍ | 2945/11952 [1:05:52<14:50:38, 5.93s/it]
25%|██▍ | 2946/11952 [1:05:58<14:53:06, 5.95s/it]
{'loss': 0.4941, 'learning_rate': 1.7641638046546e-05, 'epoch': 0.25}
+
25%|██▍ | 2946/11952 [1:05:58<14:53:06, 5.95s/it]
25%|██▍ | 2947/11952 [1:06:04<14:45:53, 5.90s/it]
{'loss': 0.4745, 'learning_rate': 1.7639889817129435e-05, 'epoch': 0.25}
+
25%|██▍ | 2947/11952 [1:06:04<14:45:53, 5.90s/it]
25%|██▍ | 2948/11952 [1:06:10<14:46:04, 5.90s/it]
{'loss': 0.4895, 'learning_rate': 1.763814102667114e-05, 'epoch': 0.25}
+
25%|██▍ | 2948/11952 [1:06:10<14:46:04, 5.90s/it]
25%|██▍ | 2949/11952 [1:06:16<14:46:22, 5.91s/it]
{'loss': 0.5155, 'learning_rate': 1.7636391675299546e-05, 'epoch': 0.25}
+
25%|██▍ | 2949/11952 [1:06:16<14:46:22, 5.91s/it]1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+ 6AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+3
+AutoResumeHook: Checking whether to suspend...
+
25%|██▍ | 2950/11952 [1:06:21<14:35:54, 5.84s/it]
{'loss': 0.4832, 'learning_rate': 1.76346417631431e-05, 'epoch': 0.25}
+
25%|██▍ | 2950/11952 [1:06:21<14:35:54, 5.84s/it]
25%|██▍ | 2951/11952 [1:06:27<14:37:17, 5.85s/it]
{'loss': 0.4912, 'learning_rate': 1.763289129033032e-05, 'epoch': 0.25}
+
25%|██▍ | 2951/11952 [1:06:27<14:37:17, 5.85s/it]
25%|██▍ | 2952/11952 [1:06:33<14:27:47, 5.79s/it]
{'loss': 0.5079, 'learning_rate': 1.7631140256989753e-05, 'epoch': 0.25}
+
25%|██▍ | 2952/11952 [1:06:33<14:27:47, 5.79s/it]
25%|██▍ | 2953/11952 [1:06:39<14:23:05, 5.75s/it]
{'loss': 0.4972, 'learning_rate': 1.762938866324998e-05, 'epoch': 0.25}
+
25%|██▍ | 2953/11952 [1:06:39<14:23:05, 5.75s/it]
25%|██▍ | 2954/11952 [1:06:45<14:40:48, 5.87s/it]
{'loss': 0.4955, 'learning_rate': 1.7627636509239646e-05, 'epoch': 0.25}
+
25%|██▍ | 2954/11952 [1:06:45<14:40:48, 5.87s/it]
25%|██▍ | 2955/11952 [1:06:50<14:32:12, 5.82s/it]
{'loss': 0.4958, 'learning_rate': 1.7625883795087405e-05, 'epoch': 0.25}
+
25%|██▍ | 2955/11952 [1:06:50<14:32:12, 5.82s/it]
25%|██▍ | 2956/11952 [1:06:56<14:32:49, 5.82s/it]
{'loss': 0.4923, 'learning_rate': 1.762413052092198e-05, 'epoch': 0.25}
+
25%|██▍ | 2956/11952 [1:06:56<14:32:49, 5.82s/it]
25%|██▍ | 2957/11952 [1:07:02<14:35:05, 5.84s/it]
{'loss': 0.4913, 'learning_rate': 1.7622376686872122e-05, 'epoch': 0.25}
+
25%|██▍ | 2957/11952 [1:07:02<14:35:05, 5.84s/it]
25%|██▍ | 2958/11952 [1:07:08<14:26:58, 5.78s/it]
{'loss': 0.51, 'learning_rate': 1.762062229306662e-05, 'epoch': 0.25}
+
25%|██▍ | 2958/11952 [1:07:08<14:26:58, 5.78s/it]
25%|██▍ | 2959/11952 [1:07:14<14:24:29, 5.77s/it]
{'loss': 0.4916, 'learning_rate': 1.7618867339634314e-05, 'epoch': 0.25}
+
25%|██▍ | 2959/11952 [1:07:14<14:24:29, 5.77s/it]
25%|██▍ | 2960/11952 [1:07:19<14:26:58, 5.78s/it]
{'loss': 0.5067, 'learning_rate': 1.7617111826704083e-05, 'epoch': 0.25}
+
25%|██▍ | 2960/11952 [1:07:19<14:26:58, 5.78s/it]
25%|██▍ | 2961/11952 [1:07:26<14:44:10, 5.90s/it]
{'loss': 0.517, 'learning_rate': 1.761535575440484e-05, 'epoch': 0.25}
+
25%|██▍ | 2961/11952 [1:07:26<14:44:10, 5.90s/it]
25%|██▍ | 2962/11952 [1:07:31<14:41:20, 5.88s/it]
{'loss': 0.4977, 'learning_rate': 1.7613599122865545e-05, 'epoch': 0.25}
+
25%|██▍ | 2962/11952 [1:07:31<14:41:20, 5.88s/it]
25%|██▍ | 2963/11952 [1:07:37<14:34:33, 5.84s/it]
{'loss': 0.5007, 'learning_rate': 1.76118419322152e-05, 'epoch': 0.25}
+
25%|██▍ | 2963/11952 [1:07:37<14:34:33, 5.84s/it]
25%|██▍ | 2964/11952 [1:07:43<14:43:54, 5.90s/it]
{'loss': 0.4947, 'learning_rate': 1.761008418258284e-05, 'epoch': 0.25}
+
25%|██▍ | 2964/11952 [1:07:43<14:43:54, 5.90s/it]
25%|██▍ | 2965/11952 [1:07:49<14:46:10, 5.92s/it]
{'loss': 0.5109, 'learning_rate': 1.7608325874097548e-05, 'epoch': 0.25}
+
25%|██▍ | 2965/11952 [1:07:49<14:46:10, 5.92s/it]
25%|██▍ | 2966/11952 [1:07:55<14:33:07, 5.83s/it]
{'loss': 0.4925, 'learning_rate': 1.7606567006888453e-05, 'epoch': 0.25}
+
25%|██▍ | 2966/11952 [1:07:55<14:33:07, 5.83s/it]
25%|██▍ | 2967/11952 [1:08:01<14:33:43, 5.83s/it]
{'loss': 0.4935, 'learning_rate': 1.7604807581084714e-05, 'epoch': 0.25}
+
25%|██▍ | 2967/11952 [1:08:01<14:33:43, 5.83s/it]
25%|██▍ | 2968/11952 [1:08:06<14:33:52, 5.84s/it]
{'loss': 0.4883, 'learning_rate': 1.7603047596815538e-05, 'epoch': 0.25}
+
25%|██▍ | 2968/11952 [1:08:06<14:33:52, 5.84s/it]
25%|██▍ | 2969/11952 [1:08:12<14:41:28, 5.89s/it]
{'loss': 0.5063, 'learning_rate': 1.760128705421017e-05, 'epoch': 0.25}
+
25%|██▍ | 2969/11952 [1:08:12<14:41:28, 5.89s/it]
25%|██▍ | 2970/11952 [1:08:18<14:37:49, 5.86s/it]
{'loss': 0.4865, 'learning_rate': 1.7599525953397898e-05, 'epoch': 0.25}
+
25%|██▍ | 2970/11952 [1:08:18<14:37:49, 5.86s/it]
25%|██▍ | 2971/11952 [1:08:24<14:33:26, 5.84s/it]
{'loss': 0.5095, 'learning_rate': 1.7597764294508048e-05, 'epoch': 0.25}
+
25%|██▍ | 2971/11952 [1:08:24<14:33:26, 5.84s/it]
25%|██▍ | 2972/11952 [1:08:30<14:25:58, 5.79s/it]
{'loss': 0.4756, 'learning_rate': 1.7596002077669988e-05, 'epoch': 0.25}
+
25%|██▍ | 2972/11952 [1:08:30<14:25:58, 5.79s/it]
25%|██▍ | 2973/11952 [1:08:35<14:25:08, 5.78s/it]
{'loss': 0.4943, 'learning_rate': 1.759423930301313e-05, 'epoch': 0.25}
+
25%|██▍ | 2973/11952 [1:08:35<14:25:08, 5.78s/it]
25%|██▍ | 2974/11952 [1:08:42<14:42:32, 5.90s/it]
{'loss': 0.5059, 'learning_rate': 1.7592475970666926e-05, 'epoch': 0.25}
+
25%|██▍ | 2974/11952 [1:08:42<14:42:32, 5.90s/it]
25%|██▍ | 2975/11952 [1:08:48<14:42:58, 5.90s/it]
{'loss': 0.493, 'learning_rate': 1.7590712080760865e-05, 'epoch': 0.25}
+
25%|██▍ | 2975/11952 [1:08:48<14:42:58, 5.90s/it]
25%|██▍ | 2976/11952 [1:08:53<14:42:27, 5.90s/it]
{'loss': 0.4919, 'learning_rate': 1.7588947633424478e-05, 'epoch': 0.25}
+
25%|██▍ | 2976/11952 [1:08:53<14:42:27, 5.90s/it]
25%|██▍ | 2977/11952 [1:08:59<14:31:22, 5.83s/it]
{'loss': 0.492, 'learning_rate': 1.7587182628787343e-05, 'epoch': 0.25}
+
25%|██▍ | 2977/11952 [1:08:59<14:31:22, 5.83s/it]
25%|██▍ | 2978/11952 [1:09:05<14:17:23, 5.73s/it]
{'loss': 0.5072, 'learning_rate': 1.758541706697908e-05, 'epoch': 0.25}
+
25%|██▍ | 2978/11952 [1:09:05<14:17:23, 5.73s/it]
25%|██▍ | 2979/11952 [1:09:10<14:18:08, 5.74s/it]
{'loss': 0.4911, 'learning_rate': 1.758365094812933e-05, 'epoch': 0.25}
+
25%|██▍ | 2979/11952 [1:09:10<14:18:08, 5.74s/it]
25%|██▍ | 2980/11952 [1:09:16<14:23:03, 5.77s/it]
{'loss': 0.4993, 'learning_rate': 1.75818842723678e-05, 'epoch': 0.25}
+
25%|██▍ | 2980/11952 [1:09:16<14:23:03, 5.77s/it]
25%|██▍ | 2981/11952 [1:09:22<14:18:00, 5.74s/it]
{'loss': 0.5072, 'learning_rate': 1.7580117039824224e-05, 'epoch': 0.25}
+
25%|██▍ | 2981/11952 [1:09:22<14:18:00, 5.74s/it]
25%|██▍ | 2982/11952 [1:09:28<14:13:45, 5.71s/it]
{'loss': 0.4968, 'learning_rate': 1.757834925062838e-05, 'epoch': 0.25}
+
25%|██▍ | 2982/11952 [1:09:28<14:13:45, 5.71s/it]
25%|██▍ | 2983/11952 [1:09:33<14:12:38, 5.70s/it]
{'loss': 0.4873, 'learning_rate': 1.7576580904910088e-05, 'epoch': 0.25}
+
25%|██▍ | 2983/11952 [1:09:33<14:12:38, 5.70s/it]
25%|██▍ | 2984/11952 [1:09:39<14:20:38, 5.76s/it]
{'loss': 0.5004, 'learning_rate': 1.757481200279921e-05, 'epoch': 0.25}
+
25%|██▍ | 2984/11952 [1:09:39<14:20:38, 5.76s/it]
25%|██▍ | 2985/11952 [1:09:45<14:19:22, 5.75s/it]
{'loss': 0.5078, 'learning_rate': 1.7573042544425644e-05, 'epoch': 0.25}
+
25%|██▍ | 2985/11952 [1:09:45<14:19:22, 5.75s/it]
25%|██▍ | 2986/11952 [1:09:51<14:25:45, 5.79s/it]
{'loss': 0.486, 'learning_rate': 1.757127252991933e-05, 'epoch': 0.25}
+
25%|██▍ | 2986/11952 [1:09:51<14:25:45, 5.79s/it]
25%|██▍ | 2987/11952 [1:09:56<14:21:22, 5.76s/it]
{'loss': 0.5065, 'learning_rate': 1.7569501959410253e-05, 'epoch': 0.25}
+
25%|██▍ | 2987/11952 [1:09:56<14:21:22, 5.76s/it]
25%|██▌ | 2988/11952 [1:10:02<14:29:04, 5.82s/it]
{'loss': 0.5147, 'learning_rate': 1.7567730833028436e-05, 'epoch': 0.25}
+
25%|██▌ | 2988/11952 [1:10:02<14:29:04, 5.82s/it]
25%|██▌ | 2989/11952 [1:10:08<14:31:02, 5.83s/it]
{'loss': 0.4804, 'learning_rate': 1.7565959150903943e-05, 'epoch': 0.25}
+
25%|██▌ | 2989/11952 [1:10:08<14:31:02, 5.83s/it]
25%|██▌ | 2990/11952 [1:10:14<14:41:11, 5.90s/it]
{'loss': 0.4937, 'learning_rate': 1.756418691316688e-05, 'epoch': 0.25}
+
25%|██▌ | 2990/11952 [1:10:14<14:41:11, 5.90s/it]
25%|██▌ | 2991/11952 [1:10:20<14:48:39, 5.95s/it]
{'loss': 0.4972, 'learning_rate': 1.7562414119947392e-05, 'epoch': 0.25}
+
25%|██▌ | 2991/11952 [1:10:20<14:48:39, 5.95s/it]
25%|██▌ | 2992/11952 [1:10:26<14:34:00, 5.85s/it]
{'loss': 0.4794, 'learning_rate': 1.7560640771375668e-05, 'epoch': 0.25}
+
25%|██▌ | 2992/11952 [1:10:26<14:34:00, 5.85s/it]
25%|██▌ | 2993/11952 [1:10:32<14:33:05, 5.85s/it]
{'loss': 0.5034, 'learning_rate': 1.755886686758193e-05, 'epoch': 0.25}
+
25%|██▌ | 2993/11952 [1:10:32<14:33:05, 5.85s/it]
25%|██▌ | 2994/11952 [1:10:38<14:31:24, 5.84s/it]
{'loss': 0.5085, 'learning_rate': 1.7557092408696446e-05, 'epoch': 0.25}
+
25%|██▌ | 2994/11952 [1:10:38<14:31:24, 5.84s/it]
25%|██▌ | 2995/11952 [1:10:43<14:29:16, 5.82s/it]
{'loss': 0.4924, 'learning_rate': 1.7555317394849532e-05, 'epoch': 0.25}
+
25%|██▌ | 2995/11952 [1:10:43<14:29:16, 5.82s/it]
25%|██▌ | 2996/11952 [1:10:49<14:38:18, 5.88s/it]
{'loss': 0.5068, 'learning_rate': 1.7553541826171535e-05, 'epoch': 0.25}
+
25%|██▌ | 2996/11952 [1:10:49<14:38:18, 5.88s/it]
25%|██▌ | 2997/11952 [1:10:55<14:36:17, 5.87s/it]
{'loss': 0.4977, 'learning_rate': 1.755176570279284e-05, 'epoch': 0.25}
+
25%|██▌ | 2997/11952 [1:10:55<14:36:17, 5.87s/it]
25%|██▌ | 2998/11952 [1:11:01<14:42:11, 5.91s/it]
{'loss': 0.4948, 'learning_rate': 1.7549989024843883e-05, 'epoch': 0.25}
+
25%|██▌ | 2998/11952 [1:11:01<14:42:11, 5.91s/it]
25%|██▌ | 2999/11952 [1:11:07<14:41:04, 5.90s/it]
{'loss': 0.5113, 'learning_rate': 1.7548211792455134e-05, 'epoch': 0.25}
+
25%|██▌ | 2999/11952 [1:11:07<14:41:04, 5.90s/it]1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+54 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+6 AutoResumeHook: Checking whether to suspend...
+
25%|██▌ | 3000/11952 [1:11:13<14:40:53, 5.90s/it]3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4921, 'learning_rate': 1.754643400575711e-05, 'epoch': 0.25}
+
25%|██▌ | 3000/11952 [1:11:13<14:40:53, 5.90s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
25%|██▌ | 3001/11952 [1:11:43<32:46:12, 13.18s/it]
{'loss': 0.4879, 'learning_rate': 1.7544655664880357e-05, 'epoch': 0.25}
+
25%|██▌ | 3001/11952 [1:11:43<32:46:12, 13.18s/it]
25%|██▌ | 3002/11952 [1:11:49<27:21:50, 11.01s/it]
{'loss': 0.5032, 'learning_rate': 1.7542876769955475e-05, 'epoch': 0.25}
+
25%|██▌ | 3002/11952 [1:11:49<27:21:50, 11.01s/it]
25%|██▌ | 3003/11952 [1:11:55<23:30:52, 9.46s/it]
{'loss': 0.4926, 'learning_rate': 1.7541097321113093e-05, 'epoch': 0.25}
+
25%|██▌ | 3003/11952 [1:11:55<23:30:52, 9.46s/it]
25%|██▌ | 3004/11952 [1:12:01<20:39:37, 8.31s/it]
{'loss': 0.4976, 'learning_rate': 1.7539317318483893e-05, 'epoch': 0.25}
+
25%|██▌ | 3004/11952 [1:12:01<20:39:37, 8.31s/it]
25%|██▌ | 3005/11952 [1:12:06<18:45:37, 7.55s/it]
{'loss': 0.4868, 'learning_rate': 1.7537536762198584e-05, 'epoch': 0.25}
+
25%|██▌ | 3005/11952 [1:12:06<18:45:37, 7.55s/it]
25%|██▌ | 3006/11952 [1:12:12<17:18:20, 6.96s/it]
{'loss': 0.5015, 'learning_rate': 1.753575565238793e-05, 'epoch': 0.25}
+
25%|██▌ | 3006/11952 [1:12:12<17:18:20, 6.96s/it]
25%|██▌ | 3007/11952 [1:12:18<16:23:57, 6.60s/it]
{'loss': 0.4932, 'learning_rate': 1.753397398918272e-05, 'epoch': 0.25}
+
25%|██▌ | 3007/11952 [1:12:18<16:23:57, 6.60s/it]
25%|██▌ | 3008/11952 [1:12:24<15:54:41, 6.40s/it]
{'loss': 0.5025, 'learning_rate': 1.75321917727138e-05, 'epoch': 0.25}
+
25%|██▌ | 3008/11952 [1:12:24<15:54:41, 6.40s/it]
25%|██▌ | 3009/11952 [1:12:30<15:30:39, 6.24s/it]
{'loss': 0.5077, 'learning_rate': 1.7530409003112042e-05, 'epoch': 0.25}
+
25%|██▌ | 3009/11952 [1:12:30<15:30:39, 6.24s/it]
25%|██▌ | 3010/11952 [1:12:35<15:11:58, 6.12s/it]
{'loss': 0.5092, 'learning_rate': 1.7528625680508372e-05, 'epoch': 0.25}
+
25%|██▌ | 3010/11952 [1:12:35<15:11:58, 6.12s/it]
25%|██▌ | 3011/11952 [1:12:41<15:01:48, 6.05s/it]
{'loss': 0.483, 'learning_rate': 1.7526841805033742e-05, 'epoch': 0.25}
+
25%|██▌ | 3011/11952 [1:12:41<15:01:48, 6.05s/it]
25%|██▌ | 3012/11952 [1:12:47<14:53:50, 6.00s/it]
{'loss': 0.4801, 'learning_rate': 1.752505737681916e-05, 'epoch': 0.25}
+
25%|██▌ | 3012/11952 [1:12:47<14:53:50, 6.00s/it]
25%|██▌ | 3013/11952 [1:12:53<14:44:58, 5.94s/it]
{'loss': 0.5236, 'learning_rate': 1.7523272395995657e-05, 'epoch': 0.25}
+
25%|██▌ | 3013/11952 [1:12:53<14:44:58, 5.94s/it]
25%|██▌ | 3014/11952 [1:12:59<14:42:12, 5.92s/it]
{'loss': 0.4854, 'learning_rate': 1.752148686269433e-05, 'epoch': 0.25}
+
25%|██▌ | 3014/11952 [1:12:59<14:42:12, 5.92s/it]
25%|██▌ | 3015/11952 [1:13:05<14:40:27, 5.91s/it]
{'loss': 0.4899, 'learning_rate': 1.7519700777046285e-05, 'epoch': 0.25}
+
25%|██▌ | 3015/11952 [1:13:05<14:40:27, 5.91s/it]
25%|██▌ | 3016/11952 [1:13:11<14:33:29, 5.86s/it]
{'loss': 0.4946, 'learning_rate': 1.7517914139182694e-05, 'epoch': 0.25}
+
25%|██▌ | 3016/11952 [1:13:11<14:33:29, 5.86s/it]
25%|██▌ | 3017/11952 [1:13:16<14:19:38, 5.77s/it]
{'loss': 0.4829, 'learning_rate': 1.751612694923476e-05, 'epoch': 0.25}
+
25%|██▌ | 3017/11952 [1:13:16<14:19:38, 5.77s/it]
25%|██▌ | 3018/11952 [1:13:22<14:17:44, 5.76s/it]
{'loss': 0.4841, 'learning_rate': 1.751433920733372e-05, 'epoch': 0.25}
+
25%|██▌ | 3018/11952 [1:13:22<14:17:44, 5.76s/it]
25%|██▌ | 3019/11952 [1:13:28<14:15:08, 5.74s/it]
{'loss': 0.5057, 'learning_rate': 1.7512550913610867e-05, 'epoch': 0.25}
+
25%|██▌ | 3019/11952 [1:13:28<14:15:08, 5.74s/it]
25%|██▌ | 3020/11952 [1:13:33<14:21:28, 5.79s/it]
{'loss': 0.4959, 'learning_rate': 1.751076206819752e-05, 'epoch': 0.25}
+
25%|██▌ | 3020/11952 [1:13:33<14:21:28, 5.79s/it]
25%|██▌ | 3021/11952 [1:13:39<14:14:27, 5.74s/it]
{'loss': 0.5034, 'learning_rate': 1.750897267122505e-05, 'epoch': 0.25}
+
25%|██▌ | 3021/11952 [1:13:39<14:14:27, 5.74s/it]
25%|██▌ | 3022/11952 [1:13:45<14:13:15, 5.73s/it]
{'loss': 0.4933, 'learning_rate': 1.7507182722824854e-05, 'epoch': 0.25}
+
25%|██▌ | 3022/11952 [1:13:45<14:13:15, 5.73s/it]
25%|██▌ | 3023/11952 [1:13:51<14:17:42, 5.76s/it]
{'loss': 0.5029, 'learning_rate': 1.7505392223128385e-05, 'epoch': 0.25}
+
25%|██▌ | 3023/11952 [1:13:51<14:17:42, 5.76s/it]
25%|██▌ | 3024/11952 [1:13:56<14:11:51, 5.72s/it]
{'loss': 0.5082, 'learning_rate': 1.750360117226713e-05, 'epoch': 0.25}
+
25%|██▌ | 3024/11952 [1:13:56<14:11:51, 5.72s/it]
25%|██▌ | 3025/11952 [1:14:02<14:03:10, 5.67s/it]
{'loss': 0.4933, 'learning_rate': 1.7501809570372614e-05, 'epoch': 0.25}
+
25%|██▌ | 3025/11952 [1:14:02<14:03:10, 5.67s/it]
25%|██▌ | 3026/11952 [1:14:07<14:02:25, 5.66s/it]
{'loss': 0.4984, 'learning_rate': 1.7500017417576406e-05, 'epoch': 0.25}
+
25%|██▌ | 3026/11952 [1:14:07<14:02:25, 5.66s/it]
25%|██▌ | 3027/11952 [1:14:13<14:07:11, 5.70s/it]
{'loss': 0.5161, 'learning_rate': 1.7498224714010113e-05, 'epoch': 0.25}
+
25%|██▌ | 3027/11952 [1:14:13<14:07:11, 5.70s/it]
25%|██▌ | 3028/11952 [1:14:19<14:11:43, 5.73s/it]
{'loss': 0.5026, 'learning_rate': 1.7496431459805387e-05, 'epoch': 0.25}
+
25%|██▌ | 3028/11952 [1:14:19<14:11:43, 5.73s/it]
25%|██▌ | 3029/11952 [1:14:25<14:14:44, 5.75s/it]
{'loss': 0.5023, 'learning_rate': 1.749463765509391e-05, 'epoch': 0.25}
+
25%|██▌ | 3029/11952 [1:14:25<14:14:44, 5.75s/it]
25%|██▌ | 3030/11952 [1:14:31<14:30:08, 5.85s/it]
{'loss': 0.5051, 'learning_rate': 1.749284330000742e-05, 'epoch': 0.25}
+
25%|██▌ | 3030/11952 [1:14:31<14:30:08, 5.85s/it]
25%|██▌ | 3031/11952 [1:14:36<14:18:01, 5.77s/it]
{'loss': 0.503, 'learning_rate': 1.7491048394677682e-05, 'epoch': 0.25}
+
25%|██▌ | 3031/11952 [1:14:36<14:18:01, 5.77s/it]
25%|██▌ | 3032/11952 [1:14:43<14:31:12, 5.86s/it]
{'loss': 0.5008, 'learning_rate': 1.7489252939236506e-05, 'epoch': 0.25}
+
25%|██▌ | 3032/11952 [1:14:43<14:31:12, 5.86s/it]
25%|██▌ | 3033/11952 [1:14:49<14:36:05, 5.89s/it]
{'loss': 0.507, 'learning_rate': 1.7487456933815746e-05, 'epoch': 0.25}
+
25%|██▌ | 3033/11952 [1:14:49<14:36:05, 5.89s/it]
25%|██▌ | 3034/11952 [1:14:54<14:30:38, 5.86s/it]
{'loss': 0.5189, 'learning_rate': 1.7485660378547293e-05, 'epoch': 0.25}
+
25%|██▌ | 3034/11952 [1:14:54<14:30:38, 5.86s/it]
25%|██▌ | 3035/11952 [1:15:00<14:40:46, 5.93s/it]
{'loss': 0.4798, 'learning_rate': 1.7483863273563072e-05, 'epoch': 0.25}
+
25%|██▌ | 3035/11952 [1:15:00<14:40:46, 5.93s/it]
25%|██▌ | 3036/11952 [1:15:06<14:46:25, 5.97s/it]
{'loss': 0.4859, 'learning_rate': 1.7482065618995063e-05, 'epoch': 0.25}
+
25%|██▌ | 3036/11952 [1:15:06<14:46:25, 5.97s/it]
25%|██▌ | 3037/11952 [1:15:12<14:41:56, 5.94s/it]
{'loss': 0.5047, 'learning_rate': 1.7480267414975274e-05, 'epoch': 0.25}
+
25%|██▌ | 3037/11952 [1:15:12<14:41:56, 5.94s/it]
25%|██▌ | 3038/11952 [1:15:18<14:53:25, 6.01s/it]
{'loss': 0.4966, 'learning_rate': 1.7478468661635763e-05, 'epoch': 0.25}
+
25%|██▌ | 3038/11952 [1:15:18<14:53:25, 6.01s/it]
25%|██▌ | 3039/11952 [1:15:24<14:34:12, 5.88s/it]
{'loss': 0.4787, 'learning_rate': 1.7476669359108614e-05, 'epoch': 0.25}
+
25%|██▌ | 3039/11952 [1:15:24<14:34:12, 5.88s/it]
25%|██▌ | 3040/11952 [1:15:30<14:16:50, 5.77s/it]
{'loss': 0.4912, 'learning_rate': 1.7474869507525967e-05, 'epoch': 0.25}
+
25%|██▌ | 3040/11952 [1:15:30<14:16:50, 5.77s/it]
25%|██▌ | 3041/11952 [1:15:35<14:20:06, 5.79s/it]
{'loss': 0.4911, 'learning_rate': 1.7473069107019993e-05, 'epoch': 0.25}
+
25%|██▌ | 3041/11952 [1:15:35<14:20:06, 5.79s/it]
25%|██▌ | 3042/11952 [1:15:41<14:26:27, 5.83s/it]
{'loss': 0.4955, 'learning_rate': 1.7471268157722907e-05, 'epoch': 0.25}
+
25%|██▌ | 3042/11952 [1:15:41<14:26:27, 5.83s/it]
25%|██▌ | 3043/11952 [1:15:48<14:45:20, 5.96s/it]
{'loss': 0.4862, 'learning_rate': 1.7469466659766963e-05, 'epoch': 0.25}
+
25%|██▌ | 3043/11952 [1:15:48<14:45:20, 5.96s/it]
25%|██▌ | 3044/11952 [1:15:53<14:38:12, 5.92s/it]
{'loss': 0.5016, 'learning_rate': 1.7467664613284455e-05, 'epoch': 0.25}
+
25%|██▌ | 3044/11952 [1:15:53<14:38:12, 5.92s/it]
25%|██▌ | 3045/11952 [1:15:59<14:32:22, 5.88s/it]
{'loss': 0.5008, 'learning_rate': 1.7465862018407718e-05, 'epoch': 0.25}
+
25%|██▌ | 3045/11952 [1:15:59<14:32:22, 5.88s/it]
25%|██▌ | 3046/11952 [1:16:05<14:35:51, 5.90s/it]
{'loss': 0.5055, 'learning_rate': 1.746405887526913e-05, 'epoch': 0.25}
+
25%|██▌ | 3046/11952 [1:16:05<14:35:51, 5.90s/it]
25%|██▌ | 3047/11952 [1:16:11<14:26:36, 5.84s/it]
{'loss': 0.4982, 'learning_rate': 1.74622551840011e-05, 'epoch': 0.25}
+
25%|██▌ | 3047/11952 [1:16:11<14:26:36, 5.84s/it]
26%|██▌ | 3048/11952 [1:16:17<14:24:52, 5.83s/it]
{'loss': 0.5026, 'learning_rate': 1.7460450944736087e-05, 'epoch': 0.26}
+
26%|██▌ | 3048/11952 [1:16:17<14:24:52, 5.83s/it]
26%|██▌ | 3049/11952 [1:16:22<14:14:05, 5.76s/it]
{'loss': 0.4959, 'learning_rate': 1.7458646157606585e-05, 'epoch': 0.26}
+
26%|██▌ | 3049/11952 [1:16:22<14:14:05, 5.76s/it]2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+75 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
26%|██▌ | 3050/11952 [1:16:28<14:04:42, 5.69s/it]
{'loss': 0.4894, 'learning_rate': 1.745684082274514e-05, 'epoch': 0.26}
+
26%|██▌ | 3050/11952 [1:16:28<14:04:42, 5.69s/it]
26%|██▌ | 3051/11952 [1:16:34<14:19:22, 5.79s/it]
{'loss': 0.4976, 'learning_rate': 1.7455034940284313e-05, 'epoch': 0.26}
+
26%|██▌ | 3051/11952 [1:16:34<14:19:22, 5.79s/it]
26%|██▌ | 3052/11952 [1:16:40<14:16:08, 5.77s/it]
{'loss': 0.4959, 'learning_rate': 1.745322851035673e-05, 'epoch': 0.26}
+
26%|██▌ | 3052/11952 [1:16:40<14:16:08, 5.77s/it]
26%|██▌ | 3053/11952 [1:16:45<14:15:13, 5.77s/it]
{'loss': 0.4848, 'learning_rate': 1.7451421533095047e-05, 'epoch': 0.26}
+
26%|██▌ | 3053/11952 [1:16:45<14:15:13, 5.77s/it]
26%|██▌ | 3054/11952 [1:16:51<14:09:15, 5.73s/it]
{'loss': 0.5046, 'learning_rate': 1.744961400863196e-05, 'epoch': 0.26}
+
26%|██▌ | 3054/11952 [1:16:51<14:09:15, 5.73s/it]
26%|██▌ | 3055/11952 [1:16:57<14:03:00, 5.69s/it]
{'loss': 0.4826, 'learning_rate': 1.7447805937100203e-05, 'epoch': 0.26}
+
26%|██▌ | 3055/11952 [1:16:57<14:03:00, 5.69s/it]
26%|██▌ | 3056/11952 [1:17:02<14:02:22, 5.68s/it]
{'loss': 0.4998, 'learning_rate': 1.7445997318632555e-05, 'epoch': 0.26}
+
26%|██▌ | 3056/11952 [1:17:02<14:02:22, 5.68s/it]
26%|██▌ | 3057/11952 [1:17:08<14:15:32, 5.77s/it]
{'loss': 0.4941, 'learning_rate': 1.7444188153361836e-05, 'epoch': 0.26}
+
26%|██▌ | 3057/11952 [1:17:08<14:15:32, 5.77s/it]
26%|██▌ | 3058/11952 [1:17:14<14:16:16, 5.78s/it]
{'loss': 0.4904, 'learning_rate': 1.74423784414209e-05, 'epoch': 0.26}
+
26%|██▌ | 3058/11952 [1:17:14<14:16:16, 5.78s/it]
26%|██▌ | 3059/11952 [1:17:20<14:17:12, 5.78s/it]
{'loss': 0.4982, 'learning_rate': 1.744056818294265e-05, 'epoch': 0.26}
+
26%|██▌ | 3059/11952 [1:17:20<14:17:12, 5.78s/it]
26%|██▌ | 3060/11952 [1:17:26<14:22:45, 5.82s/it]
{'loss': 0.4896, 'learning_rate': 1.743875737806002e-05, 'epoch': 0.26}
+
26%|██▌ | 3060/11952 [1:17:26<14:22:45, 5.82s/it]
26%|██▌ | 3061/11952 [1:17:31<14:11:45, 5.75s/it]
{'loss': 0.5043, 'learning_rate': 1.7436946026905986e-05, 'epoch': 0.26}
+
26%|██▌ | 3061/11952 [1:17:31<14:11:45, 5.75s/it]
26%|██▌ | 3062/11952 [1:17:37<14:21:25, 5.81s/it]
{'loss': 0.4901, 'learning_rate': 1.743513412961357e-05, 'epoch': 0.26}
+
26%|██▌ | 3062/11952 [1:17:37<14:21:25, 5.81s/it]
26%|██▌ | 3063/11952 [1:17:43<14:29:43, 5.87s/it]
{'loss': 0.4888, 'learning_rate': 1.7433321686315824e-05, 'epoch': 0.26}
+
26%|██▌ | 3063/11952 [1:17:43<14:29:43, 5.87s/it]
26%|██▌ | 3064/11952 [1:17:49<14:36:58, 5.92s/it]
{'loss': 0.498, 'learning_rate': 1.7431508697145855e-05, 'epoch': 0.26}
+
26%|██▌ | 3064/11952 [1:17:49<14:36:58, 5.92s/it]
26%|██▌ | 3065/11952 [1:17:55<14:28:57, 5.87s/it]
{'loss': 0.5043, 'learning_rate': 1.7429695162236798e-05, 'epoch': 0.26}
+
26%|██▌ | 3065/11952 [1:17:55<14:28:57, 5.87s/it]
26%|██▌ | 3066/11952 [1:18:01<14:25:23, 5.84s/it]
{'loss': 0.4807, 'learning_rate': 1.7427881081721828e-05, 'epoch': 0.26}
+
26%|██▌ | 3066/11952 [1:18:01<14:25:23, 5.84s/it]
26%|██▌ | 3067/11952 [1:18:07<14:40:49, 5.95s/it]
{'loss': 0.483, 'learning_rate': 1.7426066455734167e-05, 'epoch': 0.26}
+
26%|██▌ | 3067/11952 [1:18:07<14:40:49, 5.95s/it]
26%|██▌ | 3068/11952 [1:18:13<14:36:38, 5.92s/it]
{'loss': 0.5025, 'learning_rate': 1.7424251284407075e-05, 'epoch': 0.26}
+
26%|██▌ | 3068/11952 [1:18:13<14:36:38, 5.92s/it]
26%|██▌ | 3069/11952 [1:18:19<14:45:14, 5.98s/it]
{'loss': 0.5057, 'learning_rate': 1.7422435567873846e-05, 'epoch': 0.26}
+
26%|██▌ | 3069/11952 [1:18:19<14:45:14, 5.98s/it]
26%|██▌ | 3070/11952 [1:18:25<14:37:43, 5.93s/it]
{'loss': 0.4982, 'learning_rate': 1.742061930626782e-05, 'epoch': 0.26}
+
26%|██▌ | 3070/11952 [1:18:25<14:37:43, 5.93s/it]
26%|██▌ | 3071/11952 [1:18:31<14:35:41, 5.92s/it]
{'loss': 0.5053, 'learning_rate': 1.7418802499722377e-05, 'epoch': 0.26}
+
26%|██▌ | 3071/11952 [1:18:31<14:35:41, 5.92s/it]
26%|██▌ | 3072/11952 [1:18:36<14:19:22, 5.81s/it]
{'loss': 0.5214, 'learning_rate': 1.7416985148370938e-05, 'epoch': 0.26}
+
26%|██▌ | 3072/11952 [1:18:36<14:19:22, 5.81s/it]
26%|██▌ | 3073/11952 [1:18:42<14:16:46, 5.79s/it]
{'loss': 0.4795, 'learning_rate': 1.741516725234696e-05, 'epoch': 0.26}
+
26%|██▌ | 3073/11952 [1:18:42<14:16:46, 5.79s/it]
26%|██▌ | 3074/11952 [1:18:47<14:03:30, 5.70s/it]
{'loss': 0.4918, 'learning_rate': 1.7413348811783938e-05, 'epoch': 0.26}
+
26%|██▌ | 3074/11952 [1:18:47<14:03:30, 5.70s/it]
26%|██▌ | 3075/11952 [1:18:53<14:03:56, 5.70s/it]
{'loss': 0.4958, 'learning_rate': 1.7411529826815416e-05, 'epoch': 0.26}
+
26%|██▌ | 3075/11952 [1:18:53<14:03:56, 5.70s/it]
26%|██▌ | 3076/11952 [1:18:59<14:14:19, 5.78s/it]
{'loss': 0.502, 'learning_rate': 1.740971029757497e-05, 'epoch': 0.26}
+
26%|██▌ | 3076/11952 [1:18:59<14:14:19, 5.78s/it]
26%|██▌ | 3077/11952 [1:19:05<14:04:33, 5.71s/it]
{'loss': 0.4911, 'learning_rate': 1.7407890224196217e-05, 'epoch': 0.26}
+
26%|██▌ | 3077/11952 [1:19:05<14:04:33, 5.71s/it]
26%|██▌ | 3078/11952 [1:19:10<14:02:20, 5.70s/it]
{'loss': 0.503, 'learning_rate': 1.7406069606812822e-05, 'epoch': 0.26}
+
26%|██▌ | 3078/11952 [1:19:10<14:02:20, 5.70s/it]
26%|██▌ | 3079/11952 [1:19:16<14:05:27, 5.72s/it]
{'loss': 0.4926, 'learning_rate': 1.7404248445558476e-05, 'epoch': 0.26}
+
26%|██▌ | 3079/11952 [1:19:16<14:05:27, 5.72s/it]
26%|██▌ | 3080/11952 [1:19:22<14:10:36, 5.75s/it]
{'loss': 0.4967, 'learning_rate': 1.7402426740566922e-05, 'epoch': 0.26}
+
26%|██▌ | 3080/11952 [1:19:22<14:10:36, 5.75s/it]
26%|██▌ | 3081/11952 [1:19:28<14:23:33, 5.84s/it]
{'loss': 0.4957, 'learning_rate': 1.7400604491971937e-05, 'epoch': 0.26}
+
26%|██▌ | 3081/11952 [1:19:28<14:23:33, 5.84s/it]
26%|██▌ | 3082/11952 [1:19:34<14:11:17, 5.76s/it]
{'loss': 0.4982, 'learning_rate': 1.7398781699907337e-05, 'epoch': 0.26}
+
26%|██▌ | 3082/11952 [1:19:34<14:11:17, 5.76s/it]
26%|██▌ | 3083/11952 [1:19:39<13:58:47, 5.67s/it]
{'loss': 0.4722, 'learning_rate': 1.7396958364506983e-05, 'epoch': 0.26}
+
26%|██▌ | 3083/11952 [1:19:39<13:58:47, 5.67s/it]
26%|██▌ | 3084/11952 [1:19:44<13:49:48, 5.61s/it]
{'loss': 0.4908, 'learning_rate': 1.7395134485904775e-05, 'epoch': 0.26}
+
26%|██▌ | 3084/11952 [1:19:44<13:49:48, 5.61s/it]
26%|██▌ | 3085/11952 [1:19:50<14:02:04, 5.70s/it]
{'loss': 0.5098, 'learning_rate': 1.739331006423465e-05, 'epoch': 0.26}
+
26%|██▌ | 3085/11952 [1:19:50<14:02:04, 5.70s/it]
26%|██▌ | 3086/11952 [1:19:56<14:13:29, 5.78s/it]
{'loss': 0.4836, 'learning_rate': 1.7391485099630584e-05, 'epoch': 0.26}
+
26%|██▌ | 3086/11952 [1:19:56<14:13:29, 5.78s/it]
26%|██▌ | 3087/11952 [1:20:02<14:29:12, 5.88s/it]
{'loss': 0.5039, 'learning_rate': 1.7389659592226597e-05, 'epoch': 0.26}
+
26%|██▌ | 3087/11952 [1:20:02<14:29:12, 5.88s/it]
26%|██▌ | 3088/11952 [1:20:09<14:59:21, 6.09s/it]
{'loss': 0.4989, 'learning_rate': 1.7387833542156743e-05, 'epoch': 0.26}
+
26%|██▌ | 3088/11952 [1:20:09<14:59:21, 6.09s/it]
26%|██▌ | 3089/11952 [1:20:16<15:20:02, 6.23s/it]
{'loss': 0.4883, 'learning_rate': 1.7386006949555124e-05, 'epoch': 0.26}
+
26%|██▌ | 3089/11952 [1:20:16<15:20:02, 6.23s/it]
26%|██▌ | 3090/11952 [1:20:21<15:01:29, 6.10s/it]
{'loss': 0.4955, 'learning_rate': 1.7384179814555872e-05, 'epoch': 0.26}
+
26%|██▌ | 3090/11952 [1:20:21<15:01:29, 6.10s/it]
26%|██▌ | 3091/11952 [1:20:27<14:52:35, 6.04s/it]
{'loss': 0.5069, 'learning_rate': 1.7382352137293172e-05, 'epoch': 0.26}
+
26%|██▌ | 3091/11952 [1:20:27<14:52:35, 6.04s/it]
26%|██▌ | 3092/11952 [1:20:33<14:40:34, 5.96s/it]
{'loss': 0.4878, 'learning_rate': 1.7380523917901233e-05, 'epoch': 0.26}
+
26%|██▌ | 3092/11952 [1:20:33<14:40:34, 5.96s/it]
26%|██▌ | 3093/11952 [1:20:39<14:36:50, 5.94s/it]
{'loss': 0.4928, 'learning_rate': 1.7378695156514318e-05, 'epoch': 0.26}
+
26%|██▌ | 3093/11952 [1:20:39<14:36:50, 5.94s/it]
26%|██▌ | 3094/11952 [1:20:45<14:33:47, 5.92s/it]
{'loss': 0.5107, 'learning_rate': 1.7376865853266717e-05, 'epoch': 0.26}
+
26%|██▌ | 3094/11952 [1:20:45<14:33:47, 5.92s/it]
26%|██▌ | 3095/11952 [1:20:50<14:18:44, 5.82s/it]
{'loss': 0.4845, 'learning_rate': 1.7375036008292775e-05, 'epoch': 0.26}
+
26%|██▌ | 3095/11952 [1:20:50<14:18:44, 5.82s/it]
26%|██▌ | 3096/11952 [1:20:56<14:05:06, 5.73s/it]
{'loss': 0.5126, 'learning_rate': 1.7373205621726864e-05, 'epoch': 0.26}
+
26%|██▌ | 3096/11952 [1:20:56<14:05:06, 5.73s/it]
26%|██▌ | 3097/11952 [1:21:02<14:08:50, 5.75s/it]
{'loss': 0.4847, 'learning_rate': 1.7371374693703395e-05, 'epoch': 0.26}
+
26%|██▌ | 3097/11952 [1:21:02<14:08:50, 5.75s/it]
26%|██▌ | 3098/11952 [1:21:08<14:19:01, 5.82s/it]
{'loss': 0.5076, 'learning_rate': 1.736954322435683e-05, 'epoch': 0.26}
+
26%|██▌ | 3098/11952 [1:21:08<14:19:01, 5.82s/it]
26%|██▌ | 3099/11952 [1:21:13<14:12:17, 5.78s/it]
{'loss': 0.4967, 'learning_rate': 1.7367711213821663e-05, 'epoch': 0.26}
+
26%|██▌ | 3099/11952 [1:21:13<14:12:17, 5.78s/it]2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...4
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
26%|██▌ | 3100/11952 [1:21:19<14:15:43, 5.80s/it]
{'loss': 0.508, 'learning_rate': 1.736587866223243e-05, 'epoch': 0.26}
+
26%|██▌ | 3100/11952 [1:21:19<14:15:43, 5.80s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
26%|██▌ | 3101/11952 [1:21:54<35:26:44, 14.42s/it]
{'loss': 0.4877, 'learning_rate': 1.7364045569723706e-05, 'epoch': 0.26}
+
26%|██▌ | 3101/11952 [1:21:54<35:26:44, 14.42s/it]
26%|██▌ | 3102/11952 [1:22:00<29:27:19, 11.98s/it]
{'loss': 0.4913, 'learning_rate': 1.7362211936430103e-05, 'epoch': 0.26}
+
26%|██▌ | 3102/11952 [1:22:00<29:27:19, 11.98s/it]
26%|██▌ | 3103/11952 [1:22:06<24:47:48, 10.09s/it]
{'loss': 0.5046, 'learning_rate': 1.7360377762486277e-05, 'epoch': 0.26}
+
26%|██▌ | 3103/11952 [1:22:06<24:47:48, 10.09s/it]
26%|██▌ | 3104/11952 [1:22:11<21:31:42, 8.76s/it]
{'loss': 0.5047, 'learning_rate': 1.7358543048026925e-05, 'epoch': 0.26}
+
26%|██▌ | 3104/11952 [1:22:11<21:31:42, 8.76s/it]
26%|██▌ | 3105/11952 [1:22:17<19:12:39, 7.82s/it]
{'loss': 0.4684, 'learning_rate': 1.7356707793186777e-05, 'epoch': 0.26}
+
26%|██▌ | 3105/11952 [1:22:17<19:12:39, 7.82s/it]
26%|██▌ | 3106/11952 [1:22:23<17:44:29, 7.22s/it]
{'loss': 0.5183, 'learning_rate': 1.7354871998100605e-05, 'epoch': 0.26}
+
26%|██▌ | 3106/11952 [1:22:23<17:44:29, 7.22s/it]
26%|██▌ | 3107/11952 [1:22:28<16:31:29, 6.73s/it]
{'loss': 0.4857, 'learning_rate': 1.7353035662903225e-05, 'epoch': 0.26}
+
26%|██▌ | 3107/11952 [1:22:28<16:31:29, 6.73s/it]
26%|██▌ | 3108/11952 [1:22:34<15:39:41, 6.38s/it]
{'loss': 0.4787, 'learning_rate': 1.735119878772949e-05, 'epoch': 0.26}
+
26%|██▌ | 3108/11952 [1:22:34<15:39:41, 6.38s/it]
26%|██▌ | 3109/11952 [1:22:40<15:12:22, 6.19s/it]
{'loss': 0.4873, 'learning_rate': 1.7349361372714294e-05, 'epoch': 0.26}
+
26%|██▌ | 3109/11952 [1:22:40<15:12:22, 6.19s/it]
26%|██▌ | 3110/11952 [1:22:45<14:49:15, 6.03s/it]
{'loss': 0.4822, 'learning_rate': 1.7347523417992564e-05, 'epoch': 0.26}
+
26%|██▌ | 3110/11952 [1:22:45<14:49:15, 6.03s/it]
26%|██▌ | 3111/11952 [1:22:51<14:41:41, 5.98s/it]
{'loss': 0.4815, 'learning_rate': 1.7345684923699277e-05, 'epoch': 0.26}
+
26%|██▌ | 3111/11952 [1:22:51<14:41:41, 5.98s/it]
26%|██▌ | 3112/11952 [1:22:57<14:32:09, 5.92s/it]
{'loss': 0.5008, 'learning_rate': 1.734384588996944e-05, 'epoch': 0.26}
+
26%|██▌ | 3112/11952 [1:22:57<14:32:09, 5.92s/it]
26%|██▌ | 3113/11952 [1:23:03<14:18:50, 5.83s/it]
{'loss': 0.5086, 'learning_rate': 1.734200631693811e-05, 'epoch': 0.26}
+
26%|██▌ | 3113/11952 [1:23:03<14:18:50, 5.83s/it]
26%|██▌ | 3114/11952 [1:23:09<14:34:58, 5.94s/it]
{'loss': 0.4907, 'learning_rate': 1.7340166204740373e-05, 'epoch': 0.26}
+
26%|██▌ | 3114/11952 [1:23:09<14:34:58, 5.94s/it]
26%|██▌ | 3115/11952 [1:23:15<14:22:57, 5.86s/it]
{'loss': 0.4919, 'learning_rate': 1.7338325553511357e-05, 'epoch': 0.26}
+
26%|██▌ | 3115/11952 [1:23:15<14:22:57, 5.86s/it]
26%|██▌ | 3116/11952 [1:23:20<14:16:34, 5.82s/it]
{'loss': 0.5166, 'learning_rate': 1.7336484363386237e-05, 'epoch': 0.26}
+
26%|██▌ | 3116/11952 [1:23:20<14:16:34, 5.82s/it]
26%|██▌ | 3117/11952 [1:23:26<14:28:24, 5.90s/it]
{'loss': 0.4958, 'learning_rate': 1.7334642634500217e-05, 'epoch': 0.26}
+
26%|██▌ | 3117/11952 [1:23:26<14:28:24, 5.90s/it]
26%|██▌ | 3118/11952 [1:23:32<14:19:27, 5.84s/it]
{'loss': 0.4995, 'learning_rate': 1.7332800366988552e-05, 'epoch': 0.26}
+
26%|██▌ | 3118/11952 [1:23:32<14:19:27, 5.84s/it]
26%|██▌ | 3119/11952 [1:23:38<14:20:40, 5.85s/it]
{'loss': 0.5063, 'learning_rate': 1.733095756098653e-05, 'epoch': 0.26}
+
26%|██▌ | 3119/11952 [1:23:38<14:20:40, 5.85s/it]
26%|██▌ | 3120/11952 [1:23:44<14:19:46, 5.84s/it]
{'loss': 0.4965, 'learning_rate': 1.732911421662947e-05, 'epoch': 0.26}
+
26%|██▌ | 3120/11952 [1:23:44<14:19:46, 5.84s/it]
26%|██▌ | 3121/11952 [1:23:49<14:13:10, 5.80s/it]
{'loss': 0.5028, 'learning_rate': 1.732727033405275e-05, 'epoch': 0.26}
+
26%|██▌ | 3121/11952 [1:23:49<14:13:10, 5.80s/it]
26%|██▌ | 3122/11952 [1:23:55<14:09:07, 5.77s/it]
{'loss': 0.484, 'learning_rate': 1.7325425913391772e-05, 'epoch': 0.26}
+
26%|██▌ | 3122/11952 [1:23:55<14:09:07, 5.77s/it]
26%|██▌ | 3123/11952 [1:24:01<14:07:22, 5.76s/it]
{'loss': 0.516, 'learning_rate': 1.7323580954781986e-05, 'epoch': 0.26}
+
26%|██▌ | 3123/11952 [1:24:01<14:07:22, 5.76s/it]
26%|██▌ | 3124/11952 [1:24:07<14:39:21, 5.98s/it]
{'loss': 0.4818, 'learning_rate': 1.7321735458358872e-05, 'epoch': 0.26}
+
26%|██▌ | 3124/11952 [1:24:07<14:39:21, 5.98s/it]
26%|██▌ | 3125/11952 [1:24:13<14:33:08, 5.93s/it]
{'loss': 0.4944, 'learning_rate': 1.731988942425796e-05, 'epoch': 0.26}
+
26%|██▌ | 3125/11952 [1:24:13<14:33:08, 5.93s/it]
26%|██▌ | 3126/11952 [1:24:19<14:23:36, 5.87s/it]
{'loss': 0.5021, 'learning_rate': 1.7318042852614817e-05, 'epoch': 0.26}
+
26%|██▌ | 3126/11952 [1:24:19<14:23:36, 5.87s/it]
26%|██▌ | 3127/11952 [1:24:25<14:28:41, 5.91s/it]
{'loss': 0.5114, 'learning_rate': 1.7316195743565045e-05, 'epoch': 0.26}
+
26%|██▌ | 3127/11952 [1:24:25<14:28:41, 5.91s/it]
26%|██▌ | 3128/11952 [1:24:31<14:16:48, 5.83s/it]
{'loss': 0.5076, 'learning_rate': 1.7314348097244288e-05, 'epoch': 0.26}
+
26%|██▌ | 3128/11952 [1:24:31<14:16:48, 5.83s/it]
26%|██▌ | 3129/11952 [1:24:36<14:18:40, 5.84s/it]
{'loss': 0.503, 'learning_rate': 1.7312499913788225e-05, 'epoch': 0.26}
+
26%|██▌ | 3129/11952 [1:24:36<14:18:40, 5.84s/it]
26%|██▌ | 3130/11952 [1:24:42<14:12:15, 5.80s/it]
{'loss': 0.4836, 'learning_rate': 1.7310651193332586e-05, 'epoch': 0.26}
+
26%|██▌ | 3130/11952 [1:24:42<14:12:15, 5.80s/it]
26%|██▌ | 3131/11952 [1:24:48<14:21:25, 5.86s/it]
{'loss': 0.4987, 'learning_rate': 1.730880193601313e-05, 'epoch': 0.26}
+
26%|██▌ | 3131/11952 [1:24:48<14:21:25, 5.86s/it]
26%|██▌ | 3132/11952 [1:24:54<14:22:20, 5.87s/it]
{'loss': 0.4865, 'learning_rate': 1.7306952141965664e-05, 'epoch': 0.26}
+
26%|██▌ | 3132/11952 [1:24:54<14:22:20, 5.87s/it]
26%|██▌ | 3133/11952 [1:25:00<14:24:34, 5.88s/it]
{'loss': 0.4911, 'learning_rate': 1.7305101811326017e-05, 'epoch': 0.26}
+
26%|██▌ | 3133/11952 [1:25:00<14:24:34, 5.88s/it]
26%|██▌ | 3134/11952 [1:25:06<14:19:56, 5.85s/it]
{'loss': 0.5219, 'learning_rate': 1.7303250944230084e-05, 'epoch': 0.26}
+
26%|██▌ | 3134/11952 [1:25:06<14:19:56, 5.85s/it]
26%|██▌ | 3135/11952 [1:25:11<14:12:07, 5.80s/it]
{'loss': 0.4941, 'learning_rate': 1.7301399540813773e-05, 'epoch': 0.26}
+
26%|██▌ | 3135/11952 [1:25:11<14:12:07, 5.80s/it]
26%|██▌ | 3136/11952 [1:25:17<14:18:23, 5.84s/it]
{'loss': 0.4856, 'learning_rate': 1.729954760121305e-05, 'epoch': 0.26}
+
26%|██▌ | 3136/11952 [1:25:17<14:18:23, 5.84s/it]
26%|██▌ | 3137/11952 [1:25:23<14:07:59, 5.77s/it]
{'loss': 0.496, 'learning_rate': 1.7297695125563915e-05, 'epoch': 0.26}
+
26%|██▌ | 3137/11952 [1:25:23<14:07:59, 5.77s/it]
26%|██▋ | 3138/11952 [1:25:29<14:04:58, 5.75s/it]
{'loss': 0.4944, 'learning_rate': 1.72958421140024e-05, 'epoch': 0.26}
+
26%|██▋ | 3138/11952 [1:25:29<14:04:58, 5.75s/it]
26%|██▋ | 3139/11952 [1:25:35<14:20:03, 5.86s/it]
{'loss': 0.4983, 'learning_rate': 1.7293988566664586e-05, 'epoch': 0.26}
+
26%|██▋ | 3139/11952 [1:25:35<14:20:03, 5.86s/it]
26%|██▋ | 3140/11952 [1:25:41<14:21:52, 5.87s/it]
{'loss': 0.4886, 'learning_rate': 1.7292134483686594e-05, 'epoch': 0.26}
+
26%|██▋ | 3140/11952 [1:25:41<14:21:52, 5.87s/it]
26%|██▋ | 3141/11952 [1:25:47<14:31:28, 5.93s/it]
{'loss': 0.498, 'learning_rate': 1.7290279865204567e-05, 'epoch': 0.26}
+
26%|██▋ | 3141/11952 [1:25:47<14:31:28, 5.93s/it]
26%|██▋ | 3142/11952 [1:25:53<14:30:30, 5.93s/it]
{'loss': 0.4731, 'learning_rate': 1.728842471135472e-05, 'epoch': 0.26}
+
26%|██▋ | 3142/11952 [1:25:53<14:30:30, 5.93s/it]
26%|██▋ | 3143/11952 [1:25:59<14:33:46, 5.95s/it]
{'loss': 0.5268, 'learning_rate': 1.728656902227327e-05, 'epoch': 0.26}
+
26%|██▋ | 3143/11952 [1:25:59<14:33:46, 5.95s/it]
26%|██▋ | 3144/11952 [1:26:05<14:40:05, 6.00s/it]
{'loss': 0.5159, 'learning_rate': 1.72847127980965e-05, 'epoch': 0.26}
+
26%|██▋ | 3144/11952 [1:26:05<14:40:05, 6.00s/it]
26%|██▋ | 3145/11952 [1:26:11<14:31:50, 5.94s/it]
{'loss': 0.5017, 'learning_rate': 1.7282856038960724e-05, 'epoch': 0.26}
+
26%|██▋ | 3145/11952 [1:26:11<14:31:50, 5.94s/it]
26%|██▋ | 3146/11952 [1:26:16<14:27:53, 5.91s/it]
{'loss': 0.4799, 'learning_rate': 1.7280998745002286e-05, 'epoch': 0.26}
+
26%|██▋ | 3146/11952 [1:26:16<14:27:53, 5.91s/it]
26%|██▋ | 3147/11952 [1:26:22<14:22:29, 5.88s/it]
{'loss': 0.4828, 'learning_rate': 1.7279140916357588e-05, 'epoch': 0.26}
+
26%|██▋ | 3147/11952 [1:26:22<14:22:29, 5.88s/it]
26%|██▋ | 3148/11952 [1:26:28<14:23:41, 5.89s/it]
{'loss': 0.5081, 'learning_rate': 1.727728255316306e-05, 'epoch': 0.26}
+
26%|██▋ | 3148/11952 [1:26:28<14:23:41, 5.89s/it]
26%|██▋ | 3149/11952 [1:26:34<14:32:08, 5.94s/it]
{'loss': 0.4772, 'learning_rate': 1.7275423655555163e-05, 'epoch': 0.26}
+
26%|██▋ | 3149/11952 [1:26:34<14:32:08, 5.94s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+74 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
26%|██▋ | 3150/11952 [1:26:40<14:37:05, 5.98s/it]
{'loss': 0.5074, 'learning_rate': 1.7273564223670422e-05, 'epoch': 0.26}
+
26%|██▋ | 3150/11952 [1:26:40<14:37:05, 5.98s/it]
26%|██▋ | 3151/11952 [1:26:46<14:24:56, 5.90s/it]
{'loss': 0.4899, 'learning_rate': 1.727170425764537e-05, 'epoch': 0.26}
+
26%|██▋ | 3151/11952 [1:26:46<14:24:56, 5.90s/it]
26%|██▋ | 3152/11952 [1:26:52<14:35:08, 5.97s/it]
{'loss': 0.4881, 'learning_rate': 1.7269843757616605e-05, 'epoch': 0.26}
+
26%|██▋ | 3152/11952 [1:26:52<14:35:08, 5.97s/it]
26%|██▋ | 3153/11952 [1:26:58<14:30:54, 5.94s/it]
{'loss': 0.4807, 'learning_rate': 1.7267982723720755e-05, 'epoch': 0.26}
+
26%|██▋ | 3153/11952 [1:26:58<14:30:54, 5.94s/it]
26%|██▋ | 3154/11952 [1:27:04<14:24:02, 5.89s/it]
{'loss': 0.5115, 'learning_rate': 1.726612115609448e-05, 'epoch': 0.26}
+
26%|██▋ | 3154/11952 [1:27:04<14:24:02, 5.89s/it]
26%|██▋ | 3155/11952 [1:27:09<14:14:46, 5.83s/it]
{'loss': 0.5049, 'learning_rate': 1.7264259054874492e-05, 'epoch': 0.26}
+
26%|██▋ | 3155/11952 [1:27:09<14:14:46, 5.83s/it]
26%|██▋ | 3156/11952 [1:27:15<14:19:25, 5.86s/it]
{'loss': 0.496, 'learning_rate': 1.726239642019753e-05, 'epoch': 0.26}
+
26%|██▋ | 3156/11952 [1:27:15<14:19:25, 5.86s/it]
26%|██▋ | 3157/11952 [1:27:21<14:06:20, 5.77s/it]
{'loss': 0.4848, 'learning_rate': 1.7260533252200383e-05, 'epoch': 0.26}
+
26%|██▋ | 3157/11952 [1:27:21<14:06:20, 5.77s/it]
26%|██▋ | 3158/11952 [1:27:27<14:03:08, 5.75s/it]
{'loss': 0.5023, 'learning_rate': 1.7258669551019872e-05, 'epoch': 0.26}
+
26%|██▋ | 3158/11952 [1:27:27<14:03:08, 5.75s/it]
26%|██▋ | 3159/11952 [1:27:32<14:06:15, 5.77s/it]
{'loss': 0.5088, 'learning_rate': 1.725680531679286e-05, 'epoch': 0.26}
+
26%|██▋ | 3159/11952 [1:27:32<14:06:15, 5.77s/it]
26%|██▋ | 3160/11952 [1:27:38<14:01:12, 5.74s/it]
{'loss': 0.5108, 'learning_rate': 1.725494054965625e-05, 'epoch': 0.26}
+
26%|██▋ | 3160/11952 [1:27:38<14:01:12, 5.74s/it]
26%|██▋ | 3161/11952 [1:27:44<14:12:04, 5.82s/it]
{'loss': 0.4842, 'learning_rate': 1.7253075249746984e-05, 'epoch': 0.26}
+
26%|██▋ | 3161/11952 [1:27:44<14:12:04, 5.82s/it]
26%|██▋ | 3162/11952 [1:27:50<14:17:05, 5.85s/it]
{'loss': 0.4926, 'learning_rate': 1.7251209417202036e-05, 'epoch': 0.26}
+
26%|██▋ | 3162/11952 [1:27:50<14:17:05, 5.85s/it]
26%|██▋ | 3163/11952 [1:27:56<14:19:34, 5.87s/it]
{'loss': 0.5006, 'learning_rate': 1.724934305215843e-05, 'epoch': 0.26}
+
26%|██▋ | 3163/11952 [1:27:56<14:19:34, 5.87s/it]
26%|██▋ | 3164/11952 [1:28:02<14:20:47, 5.88s/it]
{'loss': 0.4902, 'learning_rate': 1.7247476154753222e-05, 'epoch': 0.26}
+
26%|██▋ | 3164/11952 [1:28:02<14:20:47, 5.88s/it]
26%|██▋ | 3165/11952 [1:28:08<14:12:24, 5.82s/it]
{'loss': 0.5061, 'learning_rate': 1.724560872512351e-05, 'epoch': 0.26}
+
26%|██▋ | 3165/11952 [1:28:08<14:12:24, 5.82s/it]
26%|██▋ | 3166/11952 [1:28:13<14:18:24, 5.86s/it]
{'loss': 0.4807, 'learning_rate': 1.724374076340643e-05, 'epoch': 0.26}
+
26%|██▋ | 3166/11952 [1:28:13<14:18:24, 5.86s/it]
26%|██▋ | 3167/11952 [1:28:19<14:18:46, 5.87s/it]
{'loss': 0.4988, 'learning_rate': 1.724187226973916e-05, 'epoch': 0.26}
+
26%|██▋ | 3167/11952 [1:28:19<14:18:46, 5.87s/it]
27%|██▋ | 3168/11952 [1:28:25<14:15:25, 5.84s/it]
{'loss': 0.4889, 'learning_rate': 1.7240003244258904e-05, 'epoch': 0.27}
+
27%|██▋ | 3168/11952 [1:28:25<14:15:25, 5.84s/it]
27%|██▋ | 3169/11952 [1:28:31<14:19:45, 5.87s/it]
{'loss': 0.488, 'learning_rate': 1.723813368710293e-05, 'epoch': 0.27}
+
27%|██▋ | 3169/11952 [1:28:31<14:19:45, 5.87s/it]
27%|██▋ | 3170/11952 [1:28:37<14:06:50, 5.79s/it]
{'loss': 0.5014, 'learning_rate': 1.723626359840852e-05, 'epoch': 0.27}
+
27%|██▋ | 3170/11952 [1:28:37<14:06:50, 5.79s/it]
27%|██▋ | 3171/11952 [1:28:42<14:08:39, 5.80s/it]
{'loss': 0.4979, 'learning_rate': 1.7234392978313012e-05, 'epoch': 0.27}
+
27%|██▋ | 3171/11952 [1:28:42<14:08:39, 5.80s/it]
27%|██▋ | 3172/11952 [1:28:48<14:05:57, 5.78s/it]
{'loss': 0.4916, 'learning_rate': 1.7232521826953773e-05, 'epoch': 0.27}
+
27%|██▋ | 3172/11952 [1:28:48<14:05:57, 5.78s/it]
27%|██▋ | 3173/11952 [1:28:54<14:00:11, 5.74s/it]
{'loss': 0.5112, 'learning_rate': 1.7230650144468212e-05, 'epoch': 0.27}
+
27%|██▋ | 3173/11952 [1:28:54<14:00:11, 5.74s/it]
27%|██▋ | 3174/11952 [1:29:00<14:14:11, 5.84s/it]
{'loss': 0.477, 'learning_rate': 1.7228777930993784e-05, 'epoch': 0.27}
+
27%|██▋ | 3174/11952 [1:29:00<14:14:11, 5.84s/it]
27%|██▋ | 3175/11952 [1:29:06<14:04:33, 5.77s/it]
{'loss': 0.5136, 'learning_rate': 1.7226905186667965e-05, 'epoch': 0.27}
+
27%|██▋ | 3175/11952 [1:29:06<14:04:33, 5.77s/it]
27%|██▋ | 3176/11952 [1:29:11<14:07:39, 5.80s/it]
{'loss': 0.5031, 'learning_rate': 1.722503191162829e-05, 'epoch': 0.27}
+
27%|██▋ | 3176/11952 [1:29:11<14:07:39, 5.80s/it]
27%|██▋ | 3177/11952 [1:29:17<14:07:11, 5.79s/it]
{'loss': 0.4908, 'learning_rate': 1.7223158106012326e-05, 'epoch': 0.27}
+
27%|██▋ | 3177/11952 [1:29:17<14:07:11, 5.79s/it]
27%|██▋ | 3178/11952 [1:29:23<14:01:29, 5.75s/it]
{'loss': 0.4848, 'learning_rate': 1.722128376995767e-05, 'epoch': 0.27}
+
27%|██▋ | 3178/11952 [1:29:23<14:01:29, 5.75s/it]
27%|██▋ | 3179/11952 [1:29:29<14:03:09, 5.77s/it]
{'loss': 0.4897, 'learning_rate': 1.721940890360197e-05, 'epoch': 0.27}
+
27%|██▋ | 3179/11952 [1:29:29<14:03:09, 5.77s/it]
27%|██▋ | 3180/11952 [1:29:35<14:13:34, 5.84s/it]
{'loss': 0.489, 'learning_rate': 1.7217533507082907e-05, 'epoch': 0.27}
+
27%|██▋ | 3180/11952 [1:29:35<14:13:34, 5.84s/it]
27%|██▋ | 3181/11952 [1:29:41<14:19:15, 5.88s/it]
{'loss': 0.5087, 'learning_rate': 1.721565758053821e-05, 'epoch': 0.27}
+
27%|██▋ | 3181/11952 [1:29:41<14:19:15, 5.88s/it]
27%|██▋ | 3182/11952 [1:29:46<14:03:55, 5.77s/it]
{'loss': 0.5086, 'learning_rate': 1.7213781124105623e-05, 'epoch': 0.27}
+
27%|██▋ | 3182/11952 [1:29:46<14:03:55, 5.77s/it]
27%|██▋ | 3183/11952 [1:29:52<14:20:16, 5.89s/it]
{'loss': 0.4942, 'learning_rate': 1.7211904137922962e-05, 'epoch': 0.27}
+
27%|██▋ | 3183/11952 [1:29:52<14:20:16, 5.89s/it]
27%|██▋ | 3184/11952 [1:29:58<14:18:08, 5.87s/it]
{'loss': 0.4779, 'learning_rate': 1.721002662212805e-05, 'epoch': 0.27}
+
27%|██▋ | 3184/11952 [1:29:58<14:18:08, 5.87s/it]
27%|██▋ | 3185/11952 [1:30:04<14:18:00, 5.87s/it]
{'loss': 0.4938, 'learning_rate': 1.720814857685878e-05, 'epoch': 0.27}
+
27%|██▋ | 3185/11952 [1:30:04<14:18:00, 5.87s/it]
27%|██▋ | 3186/11952 [1:30:10<14:08:22, 5.81s/it]
{'loss': 0.4867, 'learning_rate': 1.7206270002253056e-05, 'epoch': 0.27}
+
27%|██▋ | 3186/11952 [1:30:10<14:08:22, 5.81s/it]
27%|██▋ | 3187/11952 [1:30:15<14:02:45, 5.77s/it]
{'loss': 0.4784, 'learning_rate': 1.7204390898448837e-05, 'epoch': 0.27}
+
27%|██▋ | 3187/11952 [1:30:15<14:02:45, 5.77s/it]
27%|██▋ | 3188/11952 [1:30:21<14:02:08, 5.77s/it]
{'loss': 0.4861, 'learning_rate': 1.720251126558411e-05, 'epoch': 0.27}
+
27%|██▋ | 3188/11952 [1:30:21<14:02:08, 5.77s/it]
27%|██▋ | 3189/11952 [1:30:27<14:01:11, 5.76s/it]
{'loss': 0.5038, 'learning_rate': 1.720063110379692e-05, 'epoch': 0.27}
+
27%|██▋ | 3189/11952 [1:30:27<14:01:11, 5.76s/it]
27%|██▋ | 3190/11952 [1:30:33<14:04:05, 5.78s/it]
{'loss': 0.5021, 'learning_rate': 1.7198750413225327e-05, 'epoch': 0.27}
+
27%|██▋ | 3190/11952 [1:30:33<14:04:05, 5.78s/it]
27%|██▋ | 3191/11952 [1:30:39<14:13:27, 5.84s/it]
{'loss': 0.4814, 'learning_rate': 1.7196869194007448e-05, 'epoch': 0.27}
+
27%|██▋ | 3191/11952 [1:30:39<14:13:27, 5.84s/it]
27%|██▋ | 3192/11952 [1:30:45<14:14:25, 5.85s/it]
{'loss': 0.4862, 'learning_rate': 1.719498744628143e-05, 'epoch': 0.27}
+
27%|██▋ | 3192/11952 [1:30:45<14:14:25, 5.85s/it]
27%|██▋ | 3193/11952 [1:30:50<14:11:52, 5.84s/it]
{'loss': 0.5017, 'learning_rate': 1.719310517018546e-05, 'epoch': 0.27}
+
27%|██▋ | 3193/11952 [1:30:50<14:11:52, 5.84s/it]
27%|██▋ | 3194/11952 [1:30:56<14:10:05, 5.82s/it]
{'loss': 0.4901, 'learning_rate': 1.7191222365857764e-05, 'epoch': 0.27}
+
27%|██▋ | 3194/11952 [1:30:56<14:10:05, 5.82s/it]
27%|██▋ | 3195/11952 [1:31:02<13:59:11, 5.75s/it]
{'loss': 0.4953, 'learning_rate': 1.7189339033436607e-05, 'epoch': 0.27}
+
27%|██▋ | 3195/11952 [1:31:02<13:59:11, 5.75s/it]
27%|██▋ | 3196/11952 [1:31:07<13:57:00, 5.74s/it]
{'loss': 0.5086, 'learning_rate': 1.7187455173060294e-05, 'epoch': 0.27}
+
27%|██▋ | 3196/11952 [1:31:07<13:57:00, 5.74s/it]
27%|██▋ | 3197/11952 [1:31:13<14:02:00, 5.77s/it]
{'loss': 0.4942, 'learning_rate': 1.7185570784867168e-05, 'epoch': 0.27}
+
27%|██▋ | 3197/11952 [1:31:13<14:02:00, 5.77s/it]
27%|██▋ | 3198/11952 [1:31:19<14:16:32, 5.87s/it]
{'loss': 0.5027, 'learning_rate': 1.7183685868995616e-05, 'epoch': 0.27}
+
27%|██▋ | 3198/11952 [1:31:19<14:16:32, 5.87s/it]
27%|██▋ | 3199/11952 [1:31:25<14:06:15, 5.80s/it]
{'loss': 0.4924, 'learning_rate': 1.718180042558405e-05, 'epoch': 0.27}
+
27%|██▋ | 3199/11952 [1:31:25<14:06:15, 5.80s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
27%|██▋ | 3200/11952 [1:31:31<14:11:58, 5.84s/it]
{'loss': 0.517, 'learning_rate': 1.717991445477093e-05, 'epoch': 0.27}
+
27%|██▋ | 3200/11952 [1:31:31<14:11:58, 5.84s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
27%|██▋ | 3201/11952 [1:32:03<33:04:58, 13.61s/it]
{'loss': 0.4834, 'learning_rate': 1.7178027956694753e-05, 'epoch': 0.27}
+
27%|██▋ | 3201/11952 [1:32:03<33:04:58, 13.61s/it]
27%|██▋ | 3202/11952 [1:32:08<27:23:12, 11.27s/it]
{'loss': 0.4947, 'learning_rate': 1.7176140931494064e-05, 'epoch': 0.27}
+
27%|██▋ | 3202/11952 [1:32:08<27:23:12, 11.27s/it]
27%|██▋ | 3203/11952 [1:32:14<23:21:54, 9.61s/it]
{'loss': 0.5267, 'learning_rate': 1.717425337930743e-05, 'epoch': 0.27}
+
27%|██▋ | 3203/11952 [1:32:14<23:21:54, 9.61s/it]
27%|██▋ | 3204/11952 [1:32:21<20:57:25, 8.62s/it]
{'loss': 0.5019, 'learning_rate': 1.7172365300273467e-05, 'epoch': 0.27}
+
27%|██▋ | 3204/11952 [1:32:21<20:57:25, 8.62s/it]
27%|██▋ | 3205/11952 [1:32:26<18:46:02, 7.72s/it]
{'loss': 0.4692, 'learning_rate': 1.7170476694530834e-05, 'epoch': 0.27}
+
27%|██▋ | 3205/11952 [1:32:26<18:46:02, 7.72s/it]
27%|██▋ | 3206/11952 [1:32:32<17:30:56, 7.21s/it]
{'loss': 0.4858, 'learning_rate': 1.716858756221821e-05, 'epoch': 0.27}
+
27%|██▋ | 3206/11952 [1:32:32<17:30:56, 7.21s/it]
27%|██▋ | 3207/11952 [1:32:38<16:25:30, 6.76s/it]
{'loss': 0.5162, 'learning_rate': 1.7166697903474335e-05, 'epoch': 0.27}
+
27%|██▋ | 3207/11952 [1:32:38<16:25:30, 6.76s/it]
27%|██▋ | 3208/11952 [1:32:44<15:48:10, 6.51s/it]
{'loss': 0.493, 'learning_rate': 1.716480771843798e-05, 'epoch': 0.27}
+
27%|██▋ | 3208/11952 [1:32:44<15:48:10, 6.51s/it]
27%|██▋ | 3209/11952 [1:32:50<15:12:09, 6.26s/it]
{'loss': 0.4835, 'learning_rate': 1.7162917007247937e-05, 'epoch': 0.27}
+
27%|██▋ | 3209/11952 [1:32:50<15:12:09, 6.26s/it]
27%|██▋ | 3210/11952 [1:32:56<15:02:06, 6.19s/it]
{'loss': 0.5061, 'learning_rate': 1.7161025770043065e-05, 'epoch': 0.27}
+
27%|██▋ | 3210/11952 [1:32:56<15:02:06, 6.19s/it]
27%|██▋ | 3211/11952 [1:33:02<15:02:23, 6.19s/it]
{'loss': 0.4877, 'learning_rate': 1.7159134006962248e-05, 'epoch': 0.27}
+
27%|██▋ | 3211/11952 [1:33:02<15:02:23, 6.19s/it]
27%|██▋ | 3212/11952 [1:33:07<14:43:21, 6.06s/it]
{'loss': 0.4893, 'learning_rate': 1.7157241718144404e-05, 'epoch': 0.27}
+
27%|██▋ | 3212/11952 [1:33:07<14:43:21, 6.06s/it]
27%|██▋ | 3213/11952 [1:33:13<14:27:39, 5.96s/it]
{'loss': 0.4832, 'learning_rate': 1.7155348903728497e-05, 'epoch': 0.27}
+
27%|██▋ | 3213/11952 [1:33:13<14:27:39, 5.96s/it]
27%|██▋ | 3214/11952 [1:33:19<14:24:52, 5.94s/it]
{'loss': 0.4912, 'learning_rate': 1.715345556385353e-05, 'epoch': 0.27}
+
27%|██▋ | 3214/11952 [1:33:19<14:24:52, 5.94s/it]
27%|██▋ | 3215/11952 [1:33:25<14:17:56, 5.89s/it]
{'loss': 0.4865, 'learning_rate': 1.715156169865854e-05, 'epoch': 0.27}
+
27%|██▋ | 3215/11952 [1:33:25<14:17:56, 5.89s/it]
27%|██▋ | 3216/11952 [1:33:31<14:20:11, 5.91s/it]
{'loss': 0.4766, 'learning_rate': 1.7149667308282604e-05, 'epoch': 0.27}
+
27%|██▋ | 3216/11952 [1:33:31<14:20:11, 5.91s/it]
27%|██▋ | 3217/11952 [1:33:37<14:30:46, 5.98s/it]
{'loss': 0.5137, 'learning_rate': 1.714777239286484e-05, 'epoch': 0.27}
+
27%|██▋ | 3217/11952 [1:33:37<14:30:46, 5.98s/it]
27%|██▋ | 3218/11952 [1:33:43<14:27:16, 5.96s/it]
{'loss': 0.4717, 'learning_rate': 1.7145876952544395e-05, 'epoch': 0.27}
+
27%|██▋ | 3218/11952 [1:33:43<14:27:16, 5.96s/it]
27%|██▋ | 3219/11952 [1:33:49<14:19:38, 5.91s/it]
{'loss': 0.5099, 'learning_rate': 1.7143980987460475e-05, 'epoch': 0.27}
+
27%|██▋ | 3219/11952 [1:33:49<14:19:38, 5.91s/it]
27%|██▋ | 3220/11952 [1:33:55<14:23:08, 5.93s/it]
{'loss': 0.5271, 'learning_rate': 1.7142084497752304e-05, 'epoch': 0.27}
+
27%|██▋ | 3220/11952 [1:33:55<14:23:08, 5.93s/it]
27%|██▋ | 3221/11952 [1:34:01<14:22:57, 5.93s/it]
{'loss': 0.4995, 'learning_rate': 1.714018748355915e-05, 'epoch': 0.27}
+
27%|██▋ | 3221/11952 [1:34:01<14:22:57, 5.93s/it]
27%|██▋ | 3222/11952 [1:34:07<14:22:42, 5.93s/it]
{'loss': 0.522, 'learning_rate': 1.713828994502033e-05, 'epoch': 0.27}
+
27%|██▋ | 3222/11952 [1:34:07<14:22:42, 5.93s/it]
27%|██▋ | 3223/11952 [1:34:12<14:16:49, 5.89s/it]
{'loss': 0.4746, 'learning_rate': 1.7136391882275186e-05, 'epoch': 0.27}
+
27%|██▋ | 3223/11952 [1:34:12<14:16:49, 5.89s/it]
27%|██▋ | 3224/11952 [1:34:18<14:11:18, 5.85s/it]
{'loss': 0.4952, 'learning_rate': 1.7134493295463104e-05, 'epoch': 0.27}
+
27%|██▋ | 3224/11952 [1:34:18<14:11:18, 5.85s/it]
27%|██▋ | 3225/11952 [1:34:24<14:11:07, 5.85s/it]
{'loss': 0.4802, 'learning_rate': 1.713259418472351e-05, 'epoch': 0.27}
+
27%|██▋ | 3225/11952 [1:34:24<14:11:07, 5.85s/it]
27%|██▋ | 3226/11952 [1:34:30<14:07:09, 5.83s/it]
{'loss': 0.4934, 'learning_rate': 1.713069455019586e-05, 'epoch': 0.27}
+
27%|██▋ | 3226/11952 [1:34:30<14:07:09, 5.83s/it]
27%|██▋ | 3227/11952 [1:34:36<14:16:53, 5.89s/it]
{'loss': 0.5037, 'learning_rate': 1.712879439201967e-05, 'epoch': 0.27}
+
27%|██▋ | 3227/11952 [1:34:36<14:16:53, 5.89s/it]
27%|██▋ | 3228/11952 [1:34:41<14:00:36, 5.78s/it]
{'loss': 0.497, 'learning_rate': 1.7126893710334465e-05, 'epoch': 0.27}
+
27%|██▋ | 3228/11952 [1:34:41<14:00:36, 5.78s/it]
27%|██▋ | 3229/11952 [1:34:47<14:09:54, 5.85s/it]
{'loss': 0.4945, 'learning_rate': 1.7124992505279833e-05, 'epoch': 0.27}
+
27%|██▋ | 3229/11952 [1:34:47<14:09:54, 5.85s/it]
27%|██▋ | 3230/11952 [1:34:53<14:25:18, 5.95s/it]
{'loss': 0.4899, 'learning_rate': 1.712309077699538e-05, 'epoch': 0.27}
+
27%|██▋ | 3230/11952 [1:34:53<14:25:18, 5.95s/it]
27%|██▋ | 3231/11952 [1:34:59<14:11:43, 5.86s/it]
{'loss': 0.5034, 'learning_rate': 1.712118852562077e-05, 'epoch': 0.27}
+
27%|██▋ | 3231/11952 [1:34:59<14:11:43, 5.86s/it]
27%|██▋ | 3232/11952 [1:35:05<14:05:55, 5.82s/it]
{'loss': 0.4879, 'learning_rate': 1.71192857512957e-05, 'epoch': 0.27}
+
27%|██▋ | 3232/11952 [1:35:05<14:05:55, 5.82s/it]
27%|██▋ | 3233/11952 [1:35:10<13:53:23, 5.74s/it]
{'loss': 0.4883, 'learning_rate': 1.7117382454159887e-05, 'epoch': 0.27}
+
27%|██▋ | 3233/11952 [1:35:10<13:53:23, 5.74s/it]
27%|██▋ | 3234/11952 [1:35:16<13:46:24, 5.69s/it]
{'loss': 0.4988, 'learning_rate': 1.7115478634353117e-05, 'epoch': 0.27}
+
27%|██▋ | 3234/11952 [1:35:16<13:46:24, 5.69s/it]
27%|██▋ | 3235/11952 [1:35:22<13:51:58, 5.73s/it]
{'loss': 0.4861, 'learning_rate': 1.7113574292015185e-05, 'epoch': 0.27}
+
27%|██▋ | 3235/11952 [1:35:22<13:51:58, 5.73s/it]
27%|██▋ | 3236/11952 [1:35:28<13:58:59, 5.78s/it]
{'loss': 0.5031, 'learning_rate': 1.711166942728595e-05, 'epoch': 0.27}
+
27%|██▋ | 3236/11952 [1:35:28<13:58:59, 5.78s/it]
27%|██▋ | 3237/11952 [1:35:33<13:56:36, 5.76s/it]
{'loss': 0.4695, 'learning_rate': 1.710976404030529e-05, 'epoch': 0.27}
+
27%|██▋ | 3237/11952 [1:35:33<13:56:36, 5.76s/it]
27%|██▋ | 3238/11952 [1:35:39<13:50:24, 5.72s/it]
{'loss': 0.4973, 'learning_rate': 1.710785813121313e-05, 'epoch': 0.27}
+
27%|██▋ | 3238/11952 [1:35:39<13:50:24, 5.72s/it]
27%|██▋ | 3239/11952 [1:35:45<14:00:59, 5.79s/it]
{'loss': 0.5143, 'learning_rate': 1.7105951700149433e-05, 'epoch': 0.27}
+
27%|██▋ | 3239/11952 [1:35:45<14:00:59, 5.79s/it]
27%|██▋ | 3240/11952 [1:35:50<13:46:52, 5.69s/it]
{'loss': 0.4813, 'learning_rate': 1.7104044747254202e-05, 'epoch': 0.27}
+
27%|██▋ | 3240/11952 [1:35:50<13:46:52, 5.69s/it]
27%|██▋ | 3241/11952 [1:35:57<14:09:05, 5.85s/it]
{'loss': 0.513, 'learning_rate': 1.7102137272667466e-05, 'epoch': 0.27}
+
27%|██▋ | 3241/11952 [1:35:57<14:09:05, 5.85s/it]
27%|██▋ | 3242/11952 [1:36:03<14:09:53, 5.85s/it]
{'loss': 0.4643, 'learning_rate': 1.7100229276529314e-05, 'epoch': 0.27}
+
27%|██▋ | 3242/11952 [1:36:03<14:09:53, 5.85s/it]
27%|██▋ | 3243/11952 [1:36:09<14:18:33, 5.91s/it]
{'loss': 0.492, 'learning_rate': 1.7098320758979854e-05, 'epoch': 0.27}
+
27%|██▋ | 3243/11952 [1:36:09<14:18:33, 5.91s/it]
27%|██▋ | 3244/11952 [1:36:15<14:25:48, 5.97s/it]
{'loss': 0.4903, 'learning_rate': 1.7096411720159244e-05, 'epoch': 0.27}
+
27%|██▋ | 3244/11952 [1:36:15<14:25:48, 5.97s/it]
27%|██▋ | 3245/11952 [1:36:21<14:37:35, 6.05s/it]
{'loss': 0.5142, 'learning_rate': 1.7094502160207672e-05, 'epoch': 0.27}
+
27%|██▋ | 3245/11952 [1:36:21<14:37:35, 6.05s/it]
27%|██▋ | 3246/11952 [1:36:27<14:34:04, 6.02s/it]
{'loss': 0.4952, 'learning_rate': 1.7092592079265368e-05, 'epoch': 0.27}
+
27%|██▋ | 3246/11952 [1:36:27<14:34:04, 6.02s/it]
27%|██▋ | 3247/11952 [1:36:33<14:38:29, 6.06s/it]
{'loss': 0.491, 'learning_rate': 1.7090681477472605e-05, 'epoch': 0.27}
+
27%|██▋ | 3247/11952 [1:36:33<14:38:29, 6.06s/it]
27%|██▋ | 3248/11952 [1:36:39<14:34:30, 6.03s/it]
{'loss': 0.5151, 'learning_rate': 1.7088770354969685e-05, 'epoch': 0.27}
+
27%|██▋ | 3248/11952 [1:36:39<14:34:30, 6.03s/it]
27%|██▋ | 3249/11952 [1:36:45<14:20:46, 5.93s/it]
{'loss': 0.503, 'learning_rate': 1.708685871189695e-05, 'epoch': 0.27}
+
27%|██▋ | 3249/11952 [1:36:45<14:20:46, 5.93s/it]24 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
27%|██▋ | 3250/11952 [1:36:51<14:21:00, 5.94s/it]
{'loss': 0.5048, 'learning_rate': 1.7084946548394797e-05, 'epoch': 0.27}
+
27%|██▋ | 3250/11952 [1:36:51<14:21:00, 5.94s/it]
27%|██▋ | 3251/11952 [1:36:57<14:21:19, 5.94s/it]
{'loss': 0.4966, 'learning_rate': 1.7083033864603632e-05, 'epoch': 0.27}
+
27%|██▋ | 3251/11952 [1:36:57<14:21:19, 5.94s/it]
27%|██▋ | 3252/11952 [1:37:02<14:21:30, 5.94s/it]
{'loss': 0.5089, 'learning_rate': 1.7081120660663923e-05, 'epoch': 0.27}
+
27%|██▋ | 3252/11952 [1:37:02<14:21:30, 5.94s/it]
27%|██▋ | 3253/11952 [1:37:08<14:13:00, 5.88s/it]
{'loss': 0.4987, 'learning_rate': 1.7079206936716163e-05, 'epoch': 0.27}
+
27%|██▋ | 3253/11952 [1:37:08<14:13:00, 5.88s/it]
27%|██▋ | 3254/11952 [1:37:14<14:02:33, 5.81s/it]
{'loss': 0.4891, 'learning_rate': 1.707729269290089e-05, 'epoch': 0.27}
+
27%|██▋ | 3254/11952 [1:37:14<14:02:33, 5.81s/it]
27%|██▋ | 3255/11952 [1:37:20<13:58:01, 5.78s/it]
{'loss': 0.4912, 'learning_rate': 1.707537792935868e-05, 'epoch': 0.27}
+
27%|██▋ | 3255/11952 [1:37:20<13:58:01, 5.78s/it]
27%|██▋ | 3256/11952 [1:37:26<14:12:47, 5.88s/it]
{'loss': 0.4958, 'learning_rate': 1.7073462646230144e-05, 'epoch': 0.27}
+
27%|██▋ | 3256/11952 [1:37:26<14:12:47, 5.88s/it]
27%|██▋ | 3257/11952 [1:37:31<14:05:35, 5.84s/it]
{'loss': 0.4796, 'learning_rate': 1.7071546843655932e-05, 'epoch': 0.27}
+
27%|██▋ | 3257/11952 [1:37:31<14:05:35, 5.84s/it]
27%|██▋ | 3258/11952 [1:37:37<14:01:33, 5.81s/it]
{'loss': 0.494, 'learning_rate': 1.706963052177673e-05, 'epoch': 0.27}
+
27%|██▋ | 3258/11952 [1:37:37<14:01:33, 5.81s/it]
27%|██▋ | 3259/11952 [1:37:43<13:57:33, 5.78s/it]
{'loss': 0.5072, 'learning_rate': 1.706771368073327e-05, 'epoch': 0.27}
+
27%|██▋ | 3259/11952 [1:37:43<13:57:33, 5.78s/it]
27%|██▋ | 3260/11952 [1:37:49<13:51:18, 5.74s/it]
{'loss': 0.5034, 'learning_rate': 1.7065796320666312e-05, 'epoch': 0.27}
+
27%|██▋ | 3260/11952 [1:37:49<13:51:18, 5.74s/it]
27%|██▋ | 3261/11952 [1:37:55<14:04:51, 5.83s/it]
{'loss': 0.5014, 'learning_rate': 1.7063878441716665e-05, 'epoch': 0.27}
+
27%|██▋ | 3261/11952 [1:37:55<14:04:51, 5.83s/it]
27%|██▋ | 3262/11952 [1:38:01<14:14:46, 5.90s/it]
{'loss': 0.509, 'learning_rate': 1.7061960044025162e-05, 'epoch': 0.27}
+
27%|██▋ | 3262/11952 [1:38:01<14:14:46, 5.90s/it]
27%|██▋ | 3263/11952 [1:38:06<14:07:47, 5.85s/it]
{'loss': 0.504, 'learning_rate': 1.706004112773269e-05, 'epoch': 0.27}
+
27%|██▋ | 3263/11952 [1:38:06<14:07:47, 5.85s/it]
27%|██▋ | 3264/11952 [1:38:12<14:05:28, 5.84s/it]
{'loss': 0.494, 'learning_rate': 1.7058121692980157e-05, 'epoch': 0.27}
+
27%|██▋ | 3264/11952 [1:38:12<14:05:28, 5.84s/it]
27%|██▋ | 3265/11952 [1:38:18<14:08:25, 5.86s/it]
{'loss': 0.494, 'learning_rate': 1.7056201739908528e-05, 'epoch': 0.27}
+
27%|██▋ | 3265/11952 [1:38:18<14:08:25, 5.86s/it]
27%|██▋ | 3266/11952 [1:38:24<14:13:49, 5.90s/it]
{'loss': 0.4973, 'learning_rate': 1.705428126865879e-05, 'epoch': 0.27}
+
27%|██▋ | 3266/11952 [1:38:24<14:13:49, 5.90s/it]
27%|██▋ | 3267/11952 [1:38:30<14:11:00, 5.88s/it]
{'loss': 0.4877, 'learning_rate': 1.7052360279371978e-05, 'epoch': 0.27}
+
27%|██▋ | 3267/11952 [1:38:30<14:11:00, 5.88s/it]
27%|██▋ | 3268/11952 [1:38:36<13:57:59, 5.79s/it]
{'loss': 0.4844, 'learning_rate': 1.705043877218916e-05, 'epoch': 0.27}
+
27%|██▋ | 3268/11952 [1:38:36<13:57:59, 5.79s/it]
27%|██▋ | 3269/11952 [1:38:41<13:52:03, 5.75s/it]
{'loss': 0.5011, 'learning_rate': 1.7048516747251444e-05, 'epoch': 0.27}
+
27%|██▋ | 3269/11952 [1:38:41<13:52:03, 5.75s/it]
27%|██▋ | 3270/11952 [1:38:47<13:59:01, 5.80s/it]
{'loss': 0.4979, 'learning_rate': 1.704659420469997e-05, 'epoch': 0.27}
+
27%|██▋ | 3270/11952 [1:38:47<13:59:01, 5.80s/it]
27%|██▋ | 3271/11952 [1:38:53<14:06:15, 5.85s/it]
{'loss': 0.4596, 'learning_rate': 1.7044671144675935e-05, 'epoch': 0.27}
+
27%|██▋ | 3271/11952 [1:38:53<14:06:15, 5.85s/it]
27%|██▋ | 3272/11952 [1:38:59<13:57:58, 5.79s/it]
{'loss': 0.5083, 'learning_rate': 1.7042747567320548e-05, 'epoch': 0.27}
+
27%|██▋ | 3272/11952 [1:38:59<13:57:58, 5.79s/it]
27%|██▋ | 3273/11952 [1:39:05<14:23:11, 5.97s/it]
{'loss': 0.4956, 'learning_rate': 1.704082347277507e-05, 'epoch': 0.27}
+
27%|██▋ | 3273/11952 [1:39:05<14:23:11, 5.97s/it]
27%|██▋ | 3274/11952 [1:39:11<14:19:47, 5.94s/it]
{'loss': 0.481, 'learning_rate': 1.7038898861180805e-05, 'epoch': 0.27}
+
27%|██▋ | 3274/11952 [1:39:11<14:19:47, 5.94s/it]
27%|██▋ | 3275/11952 [1:39:17<14:20:43, 5.95s/it]
{'loss': 0.507, 'learning_rate': 1.7036973732679084e-05, 'epoch': 0.27}
+
27%|██▋ | 3275/11952 [1:39:17<14:20:43, 5.95s/it]
27%|██▋ | 3276/11952 [1:39:23<14:10:18, 5.88s/it]
{'loss': 0.4831, 'learning_rate': 1.7035048087411283e-05, 'epoch': 0.27}
+
27%|██▋ | 3276/11952 [1:39:23<14:10:18, 5.88s/it]
27%|██▋ | 3277/11952 [1:39:28<13:56:06, 5.78s/it]
{'loss': 0.4758, 'learning_rate': 1.703312192551881e-05, 'epoch': 0.27}
+
27%|██▋ | 3277/11952 [1:39:28<13:56:06, 5.78s/it]
27%|██▋ | 3278/11952 [1:39:34<14:01:07, 5.82s/it]
{'loss': 0.503, 'learning_rate': 1.703119524714311e-05, 'epoch': 0.27}
+
27%|██▋ | 3278/11952 [1:39:34<14:01:07, 5.82s/it]
27%|██▋ | 3279/11952 [1:39:40<14:01:06, 5.82s/it]
{'loss': 0.508, 'learning_rate': 1.702926805242568e-05, 'epoch': 0.27}
+
27%|██▋ | 3279/11952 [1:39:40<14:01:06, 5.82s/it]
27%|██▋ | 3280/11952 [1:39:46<14:01:14, 5.82s/it]
{'loss': 0.5148, 'learning_rate': 1.7027340341508043e-05, 'epoch': 0.27}
+
27%|██▋ | 3280/11952 [1:39:46<14:01:14, 5.82s/it]
27%|██▋ | 3281/11952 [1:39:51<13:53:27, 5.77s/it]
{'loss': 0.469, 'learning_rate': 1.702541211453176e-05, 'epoch': 0.27}
+
27%|██▋ | 3281/11952 [1:39:51<13:53:27, 5.77s/it]
27%|██▋ | 3282/11952 [1:39:57<13:49:31, 5.74s/it]
{'loss': 0.4877, 'learning_rate': 1.702348337163843e-05, 'epoch': 0.27}
+
27%|██▋ | 3282/11952 [1:39:57<13:49:31, 5.74s/it]
27%|██▋ | 3283/11952 [1:40:03<14:12:42, 5.90s/it]
{'loss': 0.5001, 'learning_rate': 1.7021554112969696e-05, 'epoch': 0.27}
+
27%|██▋ | 3283/11952 [1:40:03<14:12:42, 5.90s/it]
27%|██▋ | 3284/11952 [1:40:09<13:59:39, 5.81s/it]
{'loss': 0.4817, 'learning_rate': 1.701962433866723e-05, 'epoch': 0.27}
+
27%|██▋ | 3284/11952 [1:40:09<13:59:39, 5.81s/it]
27%|██▋ | 3285/11952 [1:40:15<14:24:02, 5.98s/it]
{'loss': 0.5152, 'learning_rate': 1.7017694048872756e-05, 'epoch': 0.27}
+
27%|██▋ | 3285/11952 [1:40:15<14:24:02, 5.98s/it]
27%|██▋ | 3286/11952 [1:40:21<14:03:59, 5.84s/it]
{'loss': 0.5012, 'learning_rate': 1.7015763243728014e-05, 'epoch': 0.27}
+
27%|██▋ | 3286/11952 [1:40:21<14:03:59, 5.84s/it]
28%|██▊ | 3287/11952 [1:40:27<13:56:00, 5.79s/it]
{'loss': 0.4863, 'learning_rate': 1.70138319233748e-05, 'epoch': 0.28}
+
28%|██▊ | 3287/11952 [1:40:27<13:56:00, 5.79s/it]
28%|██▊ | 3288/11952 [1:40:32<13:51:36, 5.76s/it]
{'loss': 0.4832, 'learning_rate': 1.7011900087954945e-05, 'epoch': 0.28}
+
28%|██▊ | 3288/11952 [1:40:32<13:51:36, 5.76s/it]
28%|██▊ | 3289/11952 [1:40:38<13:47:00, 5.73s/it]
{'loss': 0.5042, 'learning_rate': 1.7009967737610312e-05, 'epoch': 0.28}
+
28%|██▊ | 3289/11952 [1:40:38<13:47:00, 5.73s/it]
28%|██▊ | 3290/11952 [1:40:44<14:00:08, 5.82s/it]
{'loss': 0.5057, 'learning_rate': 1.70080348724828e-05, 'epoch': 0.28}
+
28%|██▊ | 3290/11952 [1:40:44<14:00:08, 5.82s/it]
28%|██▊ | 3291/11952 [1:40:50<14:18:42, 5.95s/it]
{'loss': 0.5154, 'learning_rate': 1.7006101492714362e-05, 'epoch': 0.28}
+
28%|██▊ | 3291/11952 [1:40:50<14:18:42, 5.95s/it]
28%|██▊ | 3292/11952 [1:40:56<14:17:38, 5.94s/it]
{'loss': 0.4931, 'learning_rate': 1.7004167598446967e-05, 'epoch': 0.28}
+
28%|██▊ | 3292/11952 [1:40:56<14:17:38, 5.94s/it]
28%|██▊ | 3293/11952 [1:41:02<14:25:09, 5.99s/it]
{'loss': 0.5065, 'learning_rate': 1.700223318982264e-05, 'epoch': 0.28}
+
28%|██▊ | 3293/11952 [1:41:02<14:25:09, 5.99s/it]
28%|██▊ | 3294/11952 [1:41:08<14:12:34, 5.91s/it]
{'loss': 0.4968, 'learning_rate': 1.7000298266983428e-05, 'epoch': 0.28}
+
28%|██▊ | 3294/11952 [1:41:08<14:12:34, 5.91s/it]
28%|██▊ | 3295/11952 [1:41:13<13:58:31, 5.81s/it]
{'loss': 0.4878, 'learning_rate': 1.699836283007143e-05, 'epoch': 0.28}
+
28%|██▊ | 3295/11952 [1:41:13<13:58:31, 5.81s/it]
28%|██▊ | 3296/11952 [1:41:19<13:54:40, 5.79s/it]
{'loss': 0.4811, 'learning_rate': 1.6996426879228775e-05, 'epoch': 0.28}
+
28%|██▊ | 3296/11952 [1:41:19<13:54:40, 5.79s/it]
28%|██▊ | 3297/11952 [1:41:25<13:57:56, 5.81s/it]
{'loss': 0.5043, 'learning_rate': 1.6994490414597627e-05, 'epoch': 0.28}
+
28%|██▊ | 3297/11952 [1:41:25<13:57:56, 5.81s/it]
28%|██▊ | 3298/11952 [1:41:31<13:50:47, 5.76s/it]
{'loss': 0.4804, 'learning_rate': 1.6992553436320195e-05, 'epoch': 0.28}
+
28%|██▊ | 3298/11952 [1:41:31<13:50:47, 5.76s/it]
28%|██▊ | 3299/11952 [1:41:37<13:52:56, 5.78s/it]
{'loss': 0.481, 'learning_rate': 1.6990615944538725e-05, 'epoch': 0.28}
+
28%|██▊ | 3299/11952 [1:41:37<13:52:56, 5.78s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+17 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
28%|██▊ | 3300/11952 [1:41:43<14:04:09, 5.85s/it]
{'loss': 0.4824, 'learning_rate': 1.6988677939395496e-05, 'epoch': 0.28}
+
28%|██▊ | 3300/11952 [1:41:43<14:04:09, 5.85s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
28%|██▊ | 3301/11952 [1:42:17<34:41:46, 14.44s/it]
{'loss': 0.4943, 'learning_rate': 1.698673942103283e-05, 'epoch': 0.28}
+
28%|██▊ | 3301/11952 [1:42:17<34:41:46, 14.44s/it]
28%|██▊ | 3302/11952 [1:42:23<28:28:39, 11.85s/it]
{'loss': 0.4982, 'learning_rate': 1.6984800389593076e-05, 'epoch': 0.28}
+
28%|██▊ | 3302/11952 [1:42:23<28:28:39, 11.85s/it]
28%|██▊ | 3303/11952 [1:42:29<24:22:18, 10.14s/it]
{'loss': 0.4838, 'learning_rate': 1.6982860845218637e-05, 'epoch': 0.28}
+
28%|██▊ | 3303/11952 [1:42:29<24:22:18, 10.14s/it]
28%|██▊ | 3304/11952 [1:42:35<21:22:36, 8.90s/it]
{'loss': 0.5223, 'learning_rate': 1.698092078805194e-05, 'epoch': 0.28}
+
28%|██▊ | 3304/11952 [1:42:35<21:22:36, 8.90s/it]
28%|██▊ | 3305/11952 [1:42:41<18:55:44, 7.88s/it]
{'loss': 0.4791, 'learning_rate': 1.6978980218235454e-05, 'epoch': 0.28}
+
28%|██▊ | 3305/11952 [1:42:41<18:55:44, 7.88s/it]
28%|██▊ | 3306/11952 [1:42:46<17:31:48, 7.30s/it]
{'loss': 0.4881, 'learning_rate': 1.697703913591169e-05, 'epoch': 0.28}
+
28%|██▊ | 3306/11952 [1:42:46<17:31:48, 7.30s/it]
28%|██▊ | 3307/11952 [1:42:52<16:13:13, 6.75s/it]
{'loss': 0.4824, 'learning_rate': 1.6975097541223195e-05, 'epoch': 0.28}
+
28%|██▊ | 3307/11952 [1:42:52<16:13:13, 6.75s/it]
28%|██▊ | 3308/11952 [1:42:58<15:30:20, 6.46s/it]
{'loss': 0.4667, 'learning_rate': 1.6973155434312544e-05, 'epoch': 0.28}
+
28%|██▊ | 3308/11952 [1:42:58<15:30:20, 6.46s/it]
28%|██▊ | 3309/11952 [1:43:04<15:17:57, 6.37s/it]
{'loss': 0.509, 'learning_rate': 1.6971212815322365e-05, 'epoch': 0.28}
+
28%|██▊ | 3309/11952 [1:43:04<15:17:57, 6.37s/it]
28%|██▊ | 3310/11952 [1:43:10<14:51:02, 6.19s/it]
{'loss': 0.5058, 'learning_rate': 1.696926968439531e-05, 'epoch': 0.28}
+
28%|██▊ | 3310/11952 [1:43:10<14:51:02, 6.19s/it]
28%|██▊ | 3311/11952 [1:43:15<14:28:37, 6.03s/it]
{'loss': 0.5017, 'learning_rate': 1.6967326041674076e-05, 'epoch': 0.28}
+
28%|██▊ | 3311/11952 [1:43:15<14:28:37, 6.03s/it]
28%|██▊ | 3312/11952 [1:43:21<14:15:10, 5.94s/it]
{'loss': 0.4986, 'learning_rate': 1.69653818873014e-05, 'epoch': 0.28}
+
28%|██▊ | 3312/11952 [1:43:21<14:15:10, 5.94s/it]
28%|██▊ | 3313/11952 [1:43:27<14:23:54, 6.00s/it]
{'loss': 0.5003, 'learning_rate': 1.6963437221420046e-05, 'epoch': 0.28}
+
28%|██▊ | 3313/11952 [1:43:27<14:23:54, 6.00s/it]
28%|██▊ | 3314/11952 [1:43:33<14:28:57, 6.04s/it]
{'loss': 0.4991, 'learning_rate': 1.6961492044172824e-05, 'epoch': 0.28}
+
28%|██▊ | 3314/11952 [1:43:33<14:28:57, 6.04s/it]
28%|██▊ | 3315/11952 [1:43:39<14:27:41, 6.03s/it]
{'loss': 0.495, 'learning_rate': 1.6959546355702584e-05, 'epoch': 0.28}
+
28%|██▊ | 3315/11952 [1:43:39<14:27:41, 6.03s/it]
28%|██▊ | 3316/11952 [1:43:46<14:41:08, 6.12s/it]
{'loss': 0.4848, 'learning_rate': 1.6957600156152206e-05, 'epoch': 0.28}
+
28%|██▊ | 3316/11952 [1:43:46<14:41:08, 6.12s/it]
28%|██▊ | 3317/11952 [1:43:51<14:23:09, 6.00s/it]
{'loss': 0.4958, 'learning_rate': 1.6955653445664612e-05, 'epoch': 0.28}
+
28%|██▊ | 3317/11952 [1:43:51<14:23:09, 6.00s/it]
28%|██▊ | 3318/11952 [1:43:57<14:13:25, 5.93s/it]
{'loss': 0.4899, 'learning_rate': 1.695370622438276e-05, 'epoch': 0.28}
+
28%|██▊ | 3318/11952 [1:43:57<14:13:25, 5.93s/it]
28%|██▊ | 3319/11952 [1:44:03<14:21:31, 5.99s/it]
{'loss': 0.4963, 'learning_rate': 1.6951758492449646e-05, 'epoch': 0.28}
+
28%|██▊ | 3319/11952 [1:44:03<14:21:31, 5.99s/it]
28%|██▊ | 3320/11952 [1:44:09<14:10:54, 5.91s/it]
{'loss': 0.4902, 'learning_rate': 1.6949810250008302e-05, 'epoch': 0.28}
+
28%|██▊ | 3320/11952 [1:44:09<14:10:54, 5.91s/it]
28%|██▊ | 3321/11952 [1:44:15<14:01:20, 5.85s/it]
{'loss': 0.4889, 'learning_rate': 1.69478614972018e-05, 'epoch': 0.28}
+
28%|██▊ | 3321/11952 [1:44:15<14:01:20, 5.85s/it]
28%|██▊ | 3322/11952 [1:44:20<13:53:31, 5.80s/it]
{'loss': 0.4899, 'learning_rate': 1.694591223417325e-05, 'epoch': 0.28}
+
28%|██▊ | 3322/11952 [1:44:20<13:53:31, 5.80s/it]
28%|██▊ | 3323/11952 [1:44:26<14:00:29, 5.84s/it]
{'loss': 0.4928, 'learning_rate': 1.694396246106579e-05, 'epoch': 0.28}
+
28%|██▊ | 3323/11952 [1:44:26<14:00:29, 5.84s/it]
28%|██▊ | 3324/11952 [1:44:32<13:51:22, 5.78s/it]
{'loss': 0.5079, 'learning_rate': 1.6942012178022613e-05, 'epoch': 0.28}
+
28%|██▊ | 3324/11952 [1:44:32<13:51:22, 5.78s/it]
28%|██▊ | 3325/11952 [1:44:37<13:38:02, 5.69s/it]
{'loss': 0.48, 'learning_rate': 1.6940061385186936e-05, 'epoch': 0.28}
+
28%|██▊ | 3325/11952 [1:44:37<13:38:02, 5.69s/it]
28%|██▊ | 3326/11952 [1:44:43<13:48:29, 5.76s/it]
{'loss': 0.4855, 'learning_rate': 1.6938110082702014e-05, 'epoch': 0.28}
+
28%|██▊ | 3326/11952 [1:44:43<13:48:29, 5.76s/it]
28%|██▊ | 3327/11952 [1:44:50<14:08:34, 5.90s/it]
{'loss': 0.4925, 'learning_rate': 1.6936158270711148e-05, 'epoch': 0.28}
+
28%|██▊ | 3327/11952 [1:44:50<14:08:34, 5.90s/it]
28%|██▊ | 3328/11952 [1:44:55<13:58:47, 5.84s/it]
{'loss': 0.4942, 'learning_rate': 1.6934205949357666e-05, 'epoch': 0.28}
+
28%|██▊ | 3328/11952 [1:44:55<13:58:47, 5.84s/it]
28%|██▊ | 3329/11952 [1:45:01<13:54:07, 5.80s/it]
{'loss': 0.507, 'learning_rate': 1.693225311878494e-05, 'epoch': 0.28}
+
28%|██▊ | 3329/11952 [1:45:01<13:54:07, 5.80s/it]
28%|██▊ | 3330/11952 [1:45:07<13:55:16, 5.81s/it]
{'loss': 0.4764, 'learning_rate': 1.6930299779136382e-05, 'epoch': 0.28}
+
28%|██▊ | 3330/11952 [1:45:07<13:55:16, 5.81s/it]
28%|██▊ | 3331/11952 [1:45:12<13:46:38, 5.75s/it]
{'loss': 0.49, 'learning_rate': 1.6928345930555432e-05, 'epoch': 0.28}
+
28%|██▊ | 3331/11952 [1:45:12<13:46:38, 5.75s/it]
28%|██▊ | 3332/11952 [1:45:18<13:45:43, 5.75s/it]
{'loss': 0.4877, 'learning_rate': 1.6926391573185576e-05, 'epoch': 0.28}
+
28%|██▊ | 3332/11952 [1:45:18<13:45:43, 5.75s/it]
28%|██▊ | 3333/11952 [1:45:24<13:50:44, 5.78s/it]
{'loss': 0.491, 'learning_rate': 1.692443670717033e-05, 'epoch': 0.28}
+
28%|██▊ | 3333/11952 [1:45:24<13:50:44, 5.78s/it]
28%|██▊ | 3334/11952 [1:45:30<14:10:07, 5.92s/it]
{'loss': 0.4942, 'learning_rate': 1.6922481332653248e-05, 'epoch': 0.28}
+
28%|██▊ | 3334/11952 [1:45:30<14:10:07, 5.92s/it]
28%|██▊ | 3335/11952 [1:45:36<14:04:12, 5.88s/it]
{'loss': 0.4978, 'learning_rate': 1.6920525449777937e-05, 'epoch': 0.28}
+
28%|██▊ | 3335/11952 [1:45:36<14:04:12, 5.88s/it]
28%|██▊ | 3336/11952 [1:45:42<13:52:14, 5.80s/it]
{'loss': 0.4789, 'learning_rate': 1.691856905868802e-05, 'epoch': 0.28}
+
28%|██▊ | 3336/11952 [1:45:42<13:52:14, 5.80s/it]
28%|██▊ | 3337/11952 [1:45:47<13:43:56, 5.74s/it]
{'loss': 0.4907, 'learning_rate': 1.6916612159527166e-05, 'epoch': 0.28}
+
28%|██▊ | 3337/11952 [1:45:47<13:43:56, 5.74s/it]
28%|██▊ | 3338/11952 [1:45:53<13:57:35, 5.83s/it]
{'loss': 0.5074, 'learning_rate': 1.6914654752439083e-05, 'epoch': 0.28}
+
28%|██▊ | 3338/11952 [1:45:53<13:57:35, 5.83s/it]
28%|██▊ | 3339/11952 [1:45:59<13:48:56, 5.77s/it]
{'loss': 0.4883, 'learning_rate': 1.691269683756752e-05, 'epoch': 0.28}
+
28%|██▊ | 3339/11952 [1:45:59<13:48:56, 5.77s/it]
28%|██▊ | 3340/11952 [1:46:05<13:48:52, 5.77s/it]
{'loss': 0.4935, 'learning_rate': 1.6910738415056245e-05, 'epoch': 0.28}
+
28%|██▊ | 3340/11952 [1:46:05<13:48:52, 5.77s/it]
28%|██▊ | 3341/11952 [1:46:11<14:05:28, 5.89s/it]
{'loss': 0.5326, 'learning_rate': 1.6908779485049093e-05, 'epoch': 0.28}
+
28%|██▊ | 3341/11952 [1:46:11<14:05:28, 5.89s/it]
28%|██▊ | 3342/11952 [1:46:17<14:15:39, 5.96s/it]
{'loss': 0.5007, 'learning_rate': 1.6906820047689907e-05, 'epoch': 0.28}
+
28%|██▊ | 3342/11952 [1:46:17<14:15:39, 5.96s/it]
28%|██▊ | 3343/11952 [1:46:23<13:57:07, 5.83s/it]
{'loss': 0.473, 'learning_rate': 1.6904860103122587e-05, 'epoch': 0.28}
+
28%|██▊ | 3343/11952 [1:46:23<13:57:07, 5.83s/it]
28%|██▊ | 3344/11952 [1:46:28<13:58:38, 5.85s/it]
{'loss': 0.4961, 'learning_rate': 1.6902899651491056e-05, 'epoch': 0.28}
+
28%|██▊ | 3344/11952 [1:46:28<13:58:38, 5.85s/it]
28%|██▊ | 3345/11952 [1:46:34<13:53:07, 5.81s/it]
{'loss': 0.4919, 'learning_rate': 1.690093869293929e-05, 'epoch': 0.28}
+
28%|██▊ | 3345/11952 [1:46:34<13:53:07, 5.81s/it]
28%|██▊ | 3346/11952 [1:46:40<13:52:31, 5.80s/it]
{'loss': 0.5026, 'learning_rate': 1.6898977227611288e-05, 'epoch': 0.28}
+
28%|██▊ | 3346/11952 [1:46:40<13:52:31, 5.80s/it]
28%|██▊ | 3347/11952 [1:46:46<14:00:02, 5.86s/it]
{'loss': 0.5022, 'learning_rate': 1.6897015255651093e-05, 'epoch': 0.28}
+
28%|██▊ | 3347/11952 [1:46:46<14:00:02, 5.86s/it]
28%|██▊ | 3348/11952 [1:46:52<13:58:10, 5.85s/it]
{'loss': 0.4966, 'learning_rate': 1.6895052777202784e-05, 'epoch': 0.28}
+
28%|██▊ | 3348/11952 [1:46:52<13:58:10, 5.85s/it]
28%|██▊ | 3349/11952 [1:46:57<13:43:26, 5.74s/it]
{'loss': 0.511, 'learning_rate': 1.689308979241048e-05, 'epoch': 0.28}
+
28%|██▊ | 3349/11952 [1:46:57<13:43:26, 5.74s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+35 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
28%|██▊ | 3350/11952 [1:47:03<13:54:29, 5.82s/it]
{'loss': 0.4936, 'learning_rate': 1.6891126301418334e-05, 'epoch': 0.28}
+
28%|██▊ | 3350/11952 [1:47:03<13:54:29, 5.82s/it]
28%|██▊ | 3351/11952 [1:47:09<13:49:28, 5.79s/it]
{'loss': 0.4949, 'learning_rate': 1.688916230437053e-05, 'epoch': 0.28}
+
28%|██▊ | 3351/11952 [1:47:09<13:49:28, 5.79s/it]
28%|██▊ | 3352/11952 [1:47:15<13:39:22, 5.72s/it]
{'loss': 0.504, 'learning_rate': 1.68871978014113e-05, 'epoch': 0.28}
+
28%|██▊ | 3352/11952 [1:47:15<13:39:22, 5.72s/it]
28%|██▊ | 3353/11952 [1:47:21<13:54:49, 5.83s/it]
{'loss': 0.4937, 'learning_rate': 1.6885232792684914e-05, 'epoch': 0.28}
+
28%|██▊ | 3353/11952 [1:47:21<13:54:49, 5.83s/it]
28%|██▊ | 3354/11952 [1:47:26<13:55:14, 5.83s/it]
{'loss': 0.5026, 'learning_rate': 1.6883267278335668e-05, 'epoch': 0.28}
+
28%|██▊ | 3354/11952 [1:47:26<13:55:14, 5.83s/it]
28%|██▊ | 3355/11952 [1:47:32<13:46:45, 5.77s/it]
{'loss': 0.4734, 'learning_rate': 1.68813012585079e-05, 'epoch': 0.28}
+
28%|██▊ | 3355/11952 [1:47:32<13:46:45, 5.77s/it]
28%|██▊ | 3356/11952 [1:47:38<13:59:43, 5.86s/it]
{'loss': 0.4808, 'learning_rate': 1.687933473334599e-05, 'epoch': 0.28}
+
28%|██▊ | 3356/11952 [1:47:38<13:59:43, 5.86s/it]
28%|██▊ | 3357/11952 [1:47:44<14:07:22, 5.92s/it]
{'loss': 0.4932, 'learning_rate': 1.6877367702994353e-05, 'epoch': 0.28}
+
28%|██▊ | 3357/11952 [1:47:44<14:07:22, 5.92s/it]
28%|██▊ | 3358/11952 [1:47:50<13:58:25, 5.85s/it]
{'loss': 0.5041, 'learning_rate': 1.6875400167597433e-05, 'epoch': 0.28}
+
28%|██▊ | 3358/11952 [1:47:50<13:58:25, 5.85s/it]
28%|██▊ | 3359/11952 [1:47:56<14:00:15, 5.87s/it]
{'loss': 0.4932, 'learning_rate': 1.6873432127299725e-05, 'epoch': 0.28}
+
28%|██▊ | 3359/11952 [1:47:56<14:00:15, 5.87s/it]
28%|██▊ | 3360/11952 [1:48:02<13:58:01, 5.85s/it]
{'loss': 0.4834, 'learning_rate': 1.6871463582245753e-05, 'epoch': 0.28}
+
28%|██▊ | 3360/11952 [1:48:02<13:58:01, 5.85s/it]
28%|██▊ | 3361/11952 [1:48:07<13:51:44, 5.81s/it]
{'loss': 0.499, 'learning_rate': 1.6869494532580072e-05, 'epoch': 0.28}
+
28%|██▊ | 3361/11952 [1:48:07<13:51:44, 5.81s/it]
28%|██▊ | 3362/11952 [1:48:13<13:52:31, 5.82s/it]
{'loss': 0.4741, 'learning_rate': 1.6867524978447286e-05, 'epoch': 0.28}
+
28%|██▊ | 3362/11952 [1:48:13<13:52:31, 5.82s/it]
28%|██▊ | 3363/11952 [1:48:19<13:45:19, 5.77s/it]
{'loss': 0.5121, 'learning_rate': 1.6865554919992026e-05, 'epoch': 0.28}
+
28%|██▊ | 3363/11952 [1:48:19<13:45:19, 5.77s/it]
28%|██▊ | 3364/11952 [1:48:25<14:00:42, 5.87s/it]
{'loss': 0.5057, 'learning_rate': 1.6863584357358974e-05, 'epoch': 0.28}
+
28%|██▊ | 3364/11952 [1:48:25<14:00:42, 5.87s/it]
28%|██▊ | 3365/11952 [1:48:31<13:52:45, 5.82s/it]
{'loss': 0.4854, 'learning_rate': 1.686161329069283e-05, 'epoch': 0.28}
+
28%|██▊ | 3365/11952 [1:48:31<13:52:45, 5.82s/it]
28%|██▊ | 3366/11952 [1:48:36<13:47:56, 5.79s/it]
{'loss': 0.4994, 'learning_rate': 1.685964172013835e-05, 'epoch': 0.28}
+
28%|██▊ | 3366/11952 [1:48:36<13:47:56, 5.79s/it]
28%|██▊ | 3367/11952 [1:48:42<13:40:36, 5.74s/it]
{'loss': 0.4862, 'learning_rate': 1.685766964584031e-05, 'epoch': 0.28}
+
28%|██▊ | 3367/11952 [1:48:42<13:40:36, 5.74s/it]
28%|██▊ | 3368/11952 [1:48:48<13:51:37, 5.81s/it]
{'loss': 0.4974, 'learning_rate': 1.685569706794354e-05, 'epoch': 0.28}
+
28%|██▊ | 3368/11952 [1:48:48<13:51:37, 5.81s/it]
28%|██▊ | 3369/11952 [1:48:54<13:46:38, 5.78s/it]
{'loss': 0.5175, 'learning_rate': 1.6853723986592885e-05, 'epoch': 0.28}
+
28%|██▊ | 3369/11952 [1:48:54<13:46:38, 5.78s/it]
28%|██▊ | 3370/11952 [1:48:59<13:47:05, 5.78s/it]
{'loss': 0.5038, 'learning_rate': 1.685175040193325e-05, 'epoch': 0.28}
+
28%|██▊ | 3370/11952 [1:48:59<13:47:05, 5.78s/it]
28%|██▊ | 3371/11952 [1:49:05<13:56:46, 5.85s/it]
{'loss': 0.5083, 'learning_rate': 1.6849776314109568e-05, 'epoch': 0.28}
+
28%|██▊ | 3371/11952 [1:49:05<13:56:46, 5.85s/it]
28%|██▊ | 3372/11952 [1:49:12<14:14:22, 5.97s/it]
{'loss': 0.5001, 'learning_rate': 1.6847801723266798e-05, 'epoch': 0.28}
+
28%|██▊ | 3372/11952 [1:49:12<14:14:22, 5.97s/it]
28%|██▊ | 3373/11952 [1:49:18<14:08:29, 5.93s/it]
{'loss': 0.5107, 'learning_rate': 1.6845826629549952e-05, 'epoch': 0.28}
+
28%|██▊ | 3373/11952 [1:49:18<14:08:29, 5.93s/it]
28%|██▊ | 3374/11952 [1:49:24<14:19:32, 6.01s/it]
{'loss': 0.5127, 'learning_rate': 1.6843851033104076e-05, 'epoch': 0.28}
+
28%|██▊ | 3374/11952 [1:49:24<14:19:32, 6.01s/it]
28%|██▊ | 3375/11952 [1:49:30<14:14:37, 5.98s/it]
{'loss': 0.491, 'learning_rate': 1.6841874934074244e-05, 'epoch': 0.28}
+
28%|██▊ | 3375/11952 [1:49:30<14:14:37, 5.98s/it]
28%|██▊ | 3376/11952 [1:49:35<14:00:20, 5.88s/it]
{'loss': 0.495, 'learning_rate': 1.6839898332605575e-05, 'epoch': 0.28}
+
28%|██▊ | 3376/11952 [1:49:35<14:00:20, 5.88s/it]
28%|██▊ | 3377/11952 [1:49:41<13:51:49, 5.82s/it]
{'loss': 0.4971, 'learning_rate': 1.683792122884322e-05, 'epoch': 0.28}
+
28%|██▊ | 3377/11952 [1:49:41<13:51:49, 5.82s/it]
28%|██▊ | 3378/11952 [1:49:47<13:46:42, 5.79s/it]
{'loss': 0.5114, 'learning_rate': 1.6835943622932377e-05, 'epoch': 0.28}
+
28%|██▊ | 3378/11952 [1:49:47<13:46:42, 5.79s/it]
28%|██▊ | 3379/11952 [1:49:53<13:49:26, 5.81s/it]
{'loss': 0.4907, 'learning_rate': 1.6833965515018257e-05, 'epoch': 0.28}
+
28%|██▊ | 3379/11952 [1:49:53<13:49:26, 5.81s/it]
28%|██▊ | 3380/11952 [1:49:58<13:47:08, 5.79s/it]
{'loss': 0.519, 'learning_rate': 1.683198690524614e-05, 'epoch': 0.28}
+
28%|██▊ | 3380/11952 [1:49:58<13:47:08, 5.79s/it]
28%|██▊ | 3381/11952 [1:50:04<13:54:33, 5.84s/it]
{'loss': 0.4936, 'learning_rate': 1.6830007793761323e-05, 'epoch': 0.28}
+
28%|██▊ | 3381/11952 [1:50:04<13:54:33, 5.84s/it]
28%|██▊ | 3382/11952 [1:50:10<13:54:37, 5.84s/it]
{'loss': 0.4878, 'learning_rate': 1.682802818070914e-05, 'epoch': 0.28}
+
28%|██▊ | 3382/11952 [1:50:10<13:54:37, 5.84s/it]
28%|██▊ | 3383/11952 [1:50:16<13:46:03, 5.78s/it]
{'loss': 0.4965, 'learning_rate': 1.6826048066234967e-05, 'epoch': 0.28}
+
28%|██▊ | 3383/11952 [1:50:16<13:46:03, 5.78s/it]
28%|██▊ | 3384/11952 [1:50:21<13:43:51, 5.77s/it]
{'loss': 0.5071, 'learning_rate': 1.6824067450484214e-05, 'epoch': 0.28}
+
28%|██▊ | 3384/11952 [1:50:21<13:43:51, 5.77s/it]
28%|██▊ | 3385/11952 [1:50:27<13:36:00, 5.72s/it]
{'loss': 0.4647, 'learning_rate': 1.682208633360233e-05, 'epoch': 0.28}
+
28%|██▊ | 3385/11952 [1:50:27<13:36:00, 5.72s/it]
28%|██▊ | 3386/11952 [1:50:33<13:34:59, 5.71s/it]
{'loss': 0.484, 'learning_rate': 1.6820104715734803e-05, 'epoch': 0.28}
+
28%|██▊ | 3386/11952 [1:50:33<13:34:59, 5.71s/it]
28%|██▊ | 3387/11952 [1:50:39<13:45:42, 5.78s/it]
{'loss': 0.4863, 'learning_rate': 1.6818122597027152e-05, 'epoch': 0.28}
+
28%|██▊ | 3387/11952 [1:50:39<13:45:42, 5.78s/it]
28%|██▊ | 3388/11952 [1:50:45<14:03:09, 5.91s/it]
{'loss': 0.4965, 'learning_rate': 1.681613997762494e-05, 'epoch': 0.28}
+
28%|██▊ | 3388/11952 [1:50:45<14:03:09, 5.91s/it]
28%|██▊ | 3389/11952 [1:50:51<13:59:34, 5.88s/it]
{'loss': 0.4948, 'learning_rate': 1.6814156857673753e-05, 'epoch': 0.28}
+
28%|██▊ | 3389/11952 [1:50:51<13:59:34, 5.88s/it]
28%|██▊ | 3390/11952 [1:50:57<14:01:25, 5.90s/it]
{'loss': 0.4834, 'learning_rate': 1.6812173237319232e-05, 'epoch': 0.28}
+
28%|██▊ | 3390/11952 [1:50:57<14:01:25, 5.90s/it]
28%|██▊ | 3391/11952 [1:51:03<14:01:47, 5.90s/it]
{'loss': 0.5055, 'learning_rate': 1.6810189116707042e-05, 'epoch': 0.28}
+
28%|██▊ | 3391/11952 [1:51:03<14:01:47, 5.90s/it]
28%|██▊ | 3392/11952 [1:51:08<13:58:25, 5.88s/it]
{'loss': 0.5029, 'learning_rate': 1.6808204495982887e-05, 'epoch': 0.28}
+
28%|██▊ | 3392/11952 [1:51:08<13:58:25, 5.88s/it]
28%|██▊ | 3393/11952 [1:51:14<13:47:09, 5.80s/it]
{'loss': 0.495, 'learning_rate': 1.6806219375292513e-05, 'epoch': 0.28}
+
28%|██▊ | 3393/11952 [1:51:14<13:47:09, 5.80s/it]
28%|██▊ | 3394/11952 [1:51:20<13:41:47, 5.76s/it]
{'loss': 0.4815, 'learning_rate': 1.68042337547817e-05, 'epoch': 0.28}
+
28%|██▊ | 3394/11952 [1:51:20<13:41:47, 5.76s/it]
28%|██▊ | 3395/11952 [1:51:26<13:53:52, 5.85s/it]
{'loss': 0.4937, 'learning_rate': 1.6802247634596256e-05, 'epoch': 0.28}
+
28%|██▊ | 3395/11952 [1:51:26<13:53:52, 5.85s/it]
28%|██▊ | 3396/11952 [1:51:31<13:41:48, 5.76s/it]
{'loss': 0.5125, 'learning_rate': 1.680026101488204e-05, 'epoch': 0.28}
+
28%|██▊ | 3396/11952 [1:51:31<13:41:48, 5.76s/it]
28%|██▊ | 3397/11952 [1:51:37<13:45:51, 5.79s/it]
{'loss': 0.4883, 'learning_rate': 1.679827389578494e-05, 'epoch': 0.28}
+
28%|██▊ | 3397/11952 [1:51:37<13:45:51, 5.79s/it]
28%|██▊ | 3398/11952 [1:51:43<13:53:59, 5.85s/it]
{'loss': 0.503, 'learning_rate': 1.6796286277450882e-05, 'epoch': 0.28}
+
28%|██▊ | 3398/11952 [1:51:43<13:53:59, 5.85s/it]
28%|██▊ | 3399/11952 [1:51:49<13:47:38, 5.81s/it]
{'loss': 0.4779, 'learning_rate': 1.6794298160025822e-05, 'epoch': 0.28}
+
28%|██▊ | 3399/11952 [1:51:49<13:47:38, 5.81s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
28%|██▊ | 3400/11952 [1:51:55<13:56:40, 5.87s/it]
{'loss': 0.4657, 'learning_rate': 1.6792309543655774e-05, 'epoch': 0.28}
+
28%|██▊ | 3400/11952 [1:51:55<13:56:40, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
28%|██▊ | 3401/11952 [1:52:29<34:00:08, 14.32s/it]
{'loss': 0.5017, 'learning_rate': 1.6790320428486757e-05, 'epoch': 0.28}
+
28%|██▊ | 3401/11952 [1:52:29<34:00:08, 14.32s/it]
28%|██▊ | 3402/11952 [1:52:35<27:51:35, 11.73s/it]
{'loss': 0.4918, 'learning_rate': 1.6788330814664856e-05, 'epoch': 0.28}
+
28%|██▊ | 3402/11952 [1:52:35<27:51:35, 11.73s/it]
28%|██▊ | 3403/11952 [1:52:40<23:33:55, 9.92s/it]
{'loss': 0.4799, 'learning_rate': 1.678634070233617e-05, 'epoch': 0.28}
+
28%|██▊ | 3403/11952 [1:52:40<23:33:55, 9.92s/it]
28%|██▊ | 3404/11952 [1:52:46<20:43:01, 8.73s/it]
{'loss': 0.4953, 'learning_rate': 1.6784350091646852e-05, 'epoch': 0.28}
+
28%|██▊ | 3404/11952 [1:52:46<20:43:01, 8.73s/it]
28%|██▊ | 3405/11952 [1:52:52<18:34:32, 7.82s/it]
{'loss': 0.5107, 'learning_rate': 1.6782358982743084e-05, 'epoch': 0.28}
+
28%|██▊ | 3405/11952 [1:52:52<18:34:32, 7.82s/it]
28%|██▊ | 3406/11952 [1:52:58<17:00:33, 7.17s/it]
{'loss': 0.4833, 'learning_rate': 1.6780367375771075e-05, 'epoch': 0.28}
+
28%|██▊ | 3406/11952 [1:52:58<17:00:33, 7.17s/it]
29%|██▊ | 3407/11952 [1:53:04<16:16:15, 6.85s/it]
{'loss': 0.493, 'learning_rate': 1.6778375270877095e-05, 'epoch': 0.29}
+
29%|██▊ | 3407/11952 [1:53:04<16:16:15, 6.85s/it]
29%|██▊ | 3408/11952 [1:53:09<15:26:09, 6.50s/it]
{'loss': 0.4983, 'learning_rate': 1.6776382668207424e-05, 'epoch': 0.29}
+
29%|██▊ | 3408/11952 [1:53:09<15:26:09, 6.50s/it]
29%|██▊ | 3409/11952 [1:53:15<14:44:07, 6.21s/it]
{'loss': 0.482, 'learning_rate': 1.6774389567908394e-05, 'epoch': 0.29}
+
29%|██▊ | 3409/11952 [1:53:15<14:44:07, 6.21s/it]
29%|██▊ | 3410/11952 [1:53:21<14:36:54, 6.16s/it]
{'loss': 0.502, 'learning_rate': 1.677239597012638e-05, 'epoch': 0.29}
+
29%|██▊ | 3410/11952 [1:53:21<14:36:54, 6.16s/it]
29%|██▊ | 3411/11952 [1:53:27<14:23:54, 6.07s/it]
{'loss': 0.5169, 'learning_rate': 1.6770401875007766e-05, 'epoch': 0.29}
+
29%|██▊ | 3411/11952 [1:53:27<14:23:54, 6.07s/it]
29%|██▊ | 3412/11952 [1:53:33<14:11:57, 5.99s/it]
{'loss': 0.4878, 'learning_rate': 1.6768407282699e-05, 'epoch': 0.29}
+
29%|██▊ | 3412/11952 [1:53:33<14:11:57, 5.99s/it]
29%|██▊ | 3413/11952 [1:53:39<14:10:33, 5.98s/it]
{'loss': 0.5064, 'learning_rate': 1.6766412193346555e-05, 'epoch': 0.29}
+
29%|██▊ | 3413/11952 [1:53:39<14:10:33, 5.98s/it]
29%|██▊ | 3414/11952 [1:53:44<13:56:01, 5.88s/it]
{'loss': 0.5101, 'learning_rate': 1.6764416607096942e-05, 'epoch': 0.29}
+
29%|██▊ | 3414/11952 [1:53:44<13:56:01, 5.88s/it]
29%|██▊ | 3415/11952 [1:53:50<13:50:37, 5.84s/it]
{'loss': 0.5111, 'learning_rate': 1.6762420524096712e-05, 'epoch': 0.29}
+
29%|██▊ | 3415/11952 [1:53:50<13:50:37, 5.84s/it]
29%|██▊ | 3416/11952 [1:53:56<14:05:44, 5.94s/it]
{'loss': 0.4933, 'learning_rate': 1.6760423944492442e-05, 'epoch': 0.29}
+
29%|██▊ | 3416/11952 [1:53:56<14:05:44, 5.94s/it]
29%|██▊ | 3417/11952 [1:54:02<13:59:36, 5.90s/it]
{'loss': 0.4991, 'learning_rate': 1.6758426868430758e-05, 'epoch': 0.29}
+
29%|██▊ | 3417/11952 [1:54:02<13:59:36, 5.90s/it]
29%|██▊ | 3418/11952 [1:54:08<14:01:51, 5.92s/it]
{'loss': 0.5079, 'learning_rate': 1.6756429296058314e-05, 'epoch': 0.29}
+
29%|██▊ | 3418/11952 [1:54:08<14:01:51, 5.92s/it]
29%|██▊ | 3419/11952 [1:54:14<14:10:48, 5.98s/it]
{'loss': 0.4799, 'learning_rate': 1.6754431227521806e-05, 'epoch': 0.29}
+
29%|██▊ | 3419/11952 [1:54:14<14:10:48, 5.98s/it]
29%|██▊ | 3420/11952 [1:54:20<14:00:41, 5.91s/it]
{'loss': 0.4992, 'learning_rate': 1.6752432662967958e-05, 'epoch': 0.29}
+
29%|██▊ | 3420/11952 [1:54:20<14:00:41, 5.91s/it]
29%|██▊ | 3421/11952 [1:54:25<13:46:42, 5.81s/it]
{'loss': 0.5113, 'learning_rate': 1.6750433602543546e-05, 'epoch': 0.29}
+
29%|██▊ | 3421/11952 [1:54:25<13:46:42, 5.81s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (4374 > 4096). Running this sequence through the model will result in indexing errors
+
29%|██▊ | 3422/11952 [1:54:32<14:04:32, 5.94s/it]
{'loss': 0.4779, 'learning_rate': 1.674843404639537e-05, 'epoch': 0.29}
+
29%|██▊ | 3422/11952 [1:54:32<14:04:32, 5.94s/it]
29%|██▊ | 3423/11952 [1:54:37<14:03:05, 5.93s/it]
{'loss': 0.509, 'learning_rate': 1.6746433994670258e-05, 'epoch': 0.29}
+
29%|██▊ | 3423/11952 [1:54:37<14:03:05, 5.93s/it]
29%|██▊ | 3424/11952 [1:54:43<13:45:36, 5.81s/it]
{'loss': 0.4972, 'learning_rate': 1.6744433447515098e-05, 'epoch': 0.29}
+
29%|██▊ | 3424/11952 [1:54:43<13:45:36, 5.81s/it]
29%|██▊ | 3425/11952 [1:54:49<13:43:38, 5.80s/it]
{'loss': 0.4903, 'learning_rate': 1.67424324050768e-05, 'epoch': 0.29}
+
29%|██▊ | 3425/11952 [1:54:49<13:43:38, 5.80s/it]
29%|██▊ | 3426/11952 [1:54:55<13:43:12, 5.79s/it]
{'loss': 0.4894, 'learning_rate': 1.6740430867502307e-05, 'epoch': 0.29}
+
29%|██▊ | 3426/11952 [1:54:55<13:43:12, 5.79s/it]
29%|██▊ | 3427/11952 [1:55:00<13:42:33, 5.79s/it]
{'loss': 0.4954, 'learning_rate': 1.6738428834938606e-05, 'epoch': 0.29}
+
29%|██▊ | 3427/11952 [1:55:00<13:42:33, 5.79s/it]
29%|██▊ | 3428/11952 [1:55:07<14:08:07, 5.97s/it]
{'loss': 0.4985, 'learning_rate': 1.6736426307532722e-05, 'epoch': 0.29}
+
29%|██▊ | 3428/11952 [1:55:07<14:08:07, 5.97s/it]
29%|██▊ | 3429/11952 [1:55:13<13:59:51, 5.91s/it]
{'loss': 0.4952, 'learning_rate': 1.6734423285431705e-05, 'epoch': 0.29}
+
29%|██▊ | 3429/11952 [1:55:13<13:59:51, 5.91s/it]
29%|██▊ | 3430/11952 [1:55:19<14:12:32, 6.00s/it]
{'loss': 0.5189, 'learning_rate': 1.6732419768782656e-05, 'epoch': 0.29}
+
29%|██▊ | 3430/11952 [1:55:19<14:12:32, 6.00s/it]
29%|██▊ | 3431/11952 [1:55:25<14:12:05, 6.00s/it]
{'loss': 0.4859, 'learning_rate': 1.6730415757732702e-05, 'epoch': 0.29}
+
29%|██▊ | 3431/11952 [1:55:25<14:12:05, 6.00s/it]
29%|██▊ | 3432/11952 [1:55:31<14:02:46, 5.94s/it]
{'loss': 0.5037, 'learning_rate': 1.6728411252429006e-05, 'epoch': 0.29}
+
29%|██▊ | 3432/11952 [1:55:31<14:02:46, 5.94s/it]
29%|██▊ | 3433/11952 [1:55:36<14:01:42, 5.93s/it]
{'loss': 0.4977, 'learning_rate': 1.672640625301877e-05, 'epoch': 0.29}
+
29%|██▊ | 3433/11952 [1:55:36<14:01:42, 5.93s/it]
29%|██▊ | 3434/11952 [1:55:42<13:57:13, 5.90s/it]
{'loss': 0.4831, 'learning_rate': 1.6724400759649243e-05, 'epoch': 0.29}
+
29%|██▊ | 3434/11952 [1:55:42<13:57:13, 5.90s/it]
29%|██▊ | 3435/11952 [1:55:48<13:49:43, 5.85s/it]
{'loss': 0.4928, 'learning_rate': 1.672239477246769e-05, 'epoch': 0.29}
+
29%|██▊ | 3435/11952 [1:55:48<13:49:43, 5.85s/it]
29%|██▊ | 3436/11952 [1:55:54<13:58:25, 5.91s/it]
{'loss': 0.4899, 'learning_rate': 1.6720388291621423e-05, 'epoch': 0.29}
+
29%|██▊ | 3436/11952 [1:55:54<13:58:25, 5.91s/it]
29%|██▉ | 3437/11952 [1:56:00<13:41:34, 5.79s/it]
{'loss': 0.4841, 'learning_rate': 1.6718381317257793e-05, 'epoch': 0.29}
+
29%|██▉ | 3437/11952 [1:56:00<13:41:34, 5.79s/it]
29%|██▉ | 3438/11952 [1:56:06<13:56:10, 5.89s/it]
{'loss': 0.5012, 'learning_rate': 1.6716373849524187e-05, 'epoch': 0.29}
+
29%|██▉ | 3438/11952 [1:56:06<13:56:10, 5.89s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
29%|██▉ | 3439/11952 [1:56:12<14:06:54, 5.97s/it]
{'loss': 0.5064, 'learning_rate': 1.671436588856802e-05, 'epoch': 0.29}
+
29%|██▉ | 3439/11952 [1:56:12<14:06:54, 5.97s/it]
29%|██▉ | 3440/11952 [1:56:17<13:50:57, 5.86s/it]
{'loss': 0.4881, 'learning_rate': 1.6712357434536747e-05, 'epoch': 0.29}
+
29%|██▉ | 3440/11952 [1:56:17<13:50:57, 5.86s/it]
29%|██▉ | 3441/11952 [1:56:23<13:50:10, 5.85s/it]
{'loss': 0.4914, 'learning_rate': 1.6710348487577863e-05, 'epoch': 0.29}
+
29%|██▉ | 3441/11952 [1:56:23<13:50:10, 5.85s/it]
29%|██▉ | 3442/11952 [1:56:29<13:56:41, 5.90s/it]
{'loss': 0.4985, 'learning_rate': 1.6708339047838897e-05, 'epoch': 0.29}
+
29%|██▉ | 3442/11952 [1:56:29<13:56:41, 5.90s/it]
29%|██▉ | 3443/11952 [1:56:35<13:53:51, 5.88s/it]
{'loss': 0.4928, 'learning_rate': 1.6706329115467412e-05, 'epoch': 0.29}
+
29%|██▉ | 3443/11952 [1:56:35<13:53:51, 5.88s/it]
29%|██▉ | 3444/11952 [1:56:41<13:42:21, 5.80s/it]
{'loss': 0.4741, 'learning_rate': 1.670431869061101e-05, 'epoch': 0.29}
+
29%|██▉ | 3444/11952 [1:56:41<13:42:21, 5.80s/it]
29%|██▉ | 3445/11952 [1:56:47<13:43:53, 5.81s/it]
{'loss': 0.4799, 'learning_rate': 1.6702307773417334e-05, 'epoch': 0.29}
+
29%|██▉ | 3445/11952 [1:56:47<13:43:53, 5.81s/it]
29%|██▉ | 3446/11952 [1:56:52<13:42:35, 5.80s/it]
{'loss': 0.5049, 'learning_rate': 1.6700296364034048e-05, 'epoch': 0.29}
+
29%|██▉ | 3446/11952 [1:56:52<13:42:35, 5.80s/it]
29%|██▉ | 3447/11952 [1:56:58<13:43:08, 5.81s/it]
{'loss': 0.5034, 'learning_rate': 1.6698284462608866e-05, 'epoch': 0.29}
+
29%|██▉ | 3447/11952 [1:56:58<13:43:08, 5.81s/it]
29%|██▉ | 3448/11952 [1:57:04<13:46:08, 5.83s/it]
{'loss': 0.4924, 'learning_rate': 1.6696272069289533e-05, 'epoch': 0.29}
+
29%|██▉ | 3448/11952 [1:57:04<13:46:08, 5.83s/it]
29%|██▉ | 3449/11952 [1:57:10<13:50:25, 5.86s/it]
{'loss': 0.5037, 'learning_rate': 1.6694259184223833e-05, 'epoch': 0.29}
+
29%|██▉ | 3449/11952 [1:57:10<13:50:25, 5.86s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...7
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
29%|██▉ | 3450/11952 [1:57:16<13:51:08, 5.87s/it]
{'loss': 0.4939, 'learning_rate': 1.6692245807559578e-05, 'epoch': 0.29}
+
29%|██▉ | 3450/11952 [1:57:16<13:51:08, 5.87s/it]
29%|██▉ | 3451/11952 [1:57:22<14:00:52, 5.93s/it]
{'loss': 0.4952, 'learning_rate': 1.669023193944463e-05, 'epoch': 0.29}
+
29%|██▉ | 3451/11952 [1:57:22<14:00:52, 5.93s/it]
29%|██▉ | 3452/11952 [1:57:28<13:49:15, 5.85s/it]
{'loss': 0.4887, 'learning_rate': 1.668821758002688e-05, 'epoch': 0.29}
+
29%|██▉ | 3452/11952 [1:57:28<13:49:15, 5.85s/it]
29%|██▉ | 3453/11952 [1:57:33<13:51:11, 5.87s/it]
{'loss': 0.5063, 'learning_rate': 1.668620272945424e-05, 'epoch': 0.29}
+
29%|██▉ | 3453/11952 [1:57:33<13:51:11, 5.87s/it]
29%|██▉ | 3454/11952 [1:57:39<13:49:22, 5.86s/it]
{'loss': 0.4739, 'learning_rate': 1.6684187387874686e-05, 'epoch': 0.29}
+
29%|██▉ | 3454/11952 [1:57:39<13:49:22, 5.86s/it]
29%|██▉ | 3455/11952 [1:57:45<13:58:32, 5.92s/it]
{'loss': 0.5013, 'learning_rate': 1.668217155543621e-05, 'epoch': 0.29}
+
29%|██▉ | 3455/11952 [1:57:45<13:58:32, 5.92s/it]
29%|██▉ | 3456/11952 [1:57:51<13:51:03, 5.87s/it]
{'loss': 0.4862, 'learning_rate': 1.668015523228685e-05, 'epoch': 0.29}
+
29%|██▉ | 3456/11952 [1:57:51<13:51:03, 5.87s/it]
29%|██▉ | 3457/11952 [1:57:57<13:57:04, 5.91s/it]
{'loss': 0.4973, 'learning_rate': 1.6678138418574673e-05, 'epoch': 0.29}
+
29%|██▉ | 3457/11952 [1:57:57<13:57:04, 5.91s/it]
29%|██▉ | 3458/11952 [1:58:03<13:54:44, 5.90s/it]
{'loss': 0.4797, 'learning_rate': 1.6676121114447784e-05, 'epoch': 0.29}
+
29%|██▉ | 3458/11952 [1:58:03<13:54:44, 5.90s/it]
29%|██▉ | 3459/11952 [1:58:09<13:51:46, 5.88s/it]
{'loss': 0.5063, 'learning_rate': 1.6674103320054335e-05, 'epoch': 0.29}
+
29%|██▉ | 3459/11952 [1:58:09<13:51:46, 5.88s/it]
29%|██▉ | 3460/11952 [1:58:15<13:45:53, 5.84s/it]
{'loss': 0.4745, 'learning_rate': 1.6672085035542497e-05, 'epoch': 0.29}
+
29%|██▉ | 3460/11952 [1:58:15<13:45:53, 5.84s/it]
29%|██▉ | 3461/11952 [1:58:21<14:02:40, 5.95s/it]
{'loss': 0.4841, 'learning_rate': 1.667006626106048e-05, 'epoch': 0.29}
+
29%|██▉ | 3461/11952 [1:58:21<14:02:40, 5.95s/it]
29%|██▉ | 3462/11952 [1:58:27<14:03:57, 5.96s/it]
{'loss': 0.4975, 'learning_rate': 1.6668046996756544e-05, 'epoch': 0.29}
+
29%|██▉ | 3462/11952 [1:58:27<14:03:57, 5.96s/it]
29%|██▉ | 3463/11952 [1:58:33<13:54:17, 5.90s/it]
{'loss': 0.5235, 'learning_rate': 1.6666027242778972e-05, 'epoch': 0.29}
+
29%|██▉ | 3463/11952 [1:58:33<13:54:17, 5.90s/it]
29%|██▉ | 3464/11952 [1:58:38<13:42:27, 5.81s/it]
{'loss': 0.4883, 'learning_rate': 1.666400699927608e-05, 'epoch': 0.29}
+
29%|██▉ | 3464/11952 [1:58:38<13:42:27, 5.81s/it]
29%|██▉ | 3465/11952 [1:58:44<13:56:02, 5.91s/it]
{'loss': 0.5063, 'learning_rate': 1.6661986266396235e-05, 'epoch': 0.29}
+
29%|██▉ | 3465/11952 [1:58:44<13:56:02, 5.91s/it]
29%|██▉ | 3466/11952 [1:58:51<14:09:56, 6.01s/it]
{'loss': 0.4858, 'learning_rate': 1.6659965044287826e-05, 'epoch': 0.29}
+
29%|██▉ | 3466/11952 [1:58:51<14:09:56, 6.01s/it]
29%|██▉ | 3467/11952 [1:58:56<14:05:15, 5.98s/it]
{'loss': 0.4754, 'learning_rate': 1.6657943333099287e-05, 'epoch': 0.29}
+
29%|██▉ | 3467/11952 [1:58:56<14:05:15, 5.98s/it]
29%|██▉ | 3468/11952 [1:59:02<14:03:46, 5.97s/it]
{'loss': 0.4743, 'learning_rate': 1.6655921132979082e-05, 'epoch': 0.29}
+
29%|██▉ | 3468/11952 [1:59:02<14:03:46, 5.97s/it]
29%|██▉ | 3469/11952 [1:59:08<13:47:17, 5.85s/it]
{'loss': 0.4887, 'learning_rate': 1.6653898444075713e-05, 'epoch': 0.29}
+
29%|██▉ | 3469/11952 [1:59:08<13:47:17, 5.85s/it]
29%|██▉ | 3470/11952 [1:59:14<13:46:13, 5.84s/it]
{'loss': 0.4948, 'learning_rate': 1.6651875266537718e-05, 'epoch': 0.29}
+
29%|██▉ | 3470/11952 [1:59:14<13:46:13, 5.84s/it]
29%|██▉ | 3471/11952 [1:59:20<13:53:47, 5.90s/it]
{'loss': 0.4873, 'learning_rate': 1.664985160051367e-05, 'epoch': 0.29}
+
29%|██▉ | 3471/11952 [1:59:20<13:53:47, 5.90s/it]
29%|██▉ | 3472/11952 [1:59:26<13:52:55, 5.89s/it]
{'loss': 0.486, 'learning_rate': 1.6647827446152183e-05, 'epoch': 0.29}
+
29%|██▉ | 3472/11952 [1:59:26<13:52:55, 5.89s/it]
29%|██▉ | 3473/11952 [1:59:32<13:58:05, 5.93s/it]
{'loss': 0.4984, 'learning_rate': 1.6645802803601893e-05, 'epoch': 0.29}
+
29%|██▉ | 3473/11952 [1:59:32<13:58:05, 5.93s/it]
29%|██▉ | 3474/11952 [1:59:38<14:00:39, 5.95s/it]
{'loss': 0.5056, 'learning_rate': 1.664377767301149e-05, 'epoch': 0.29}
+
29%|██▉ | 3474/11952 [1:59:38<14:00:39, 5.95s/it]
29%|██▉ | 3475/11952 [1:59:43<13:51:12, 5.88s/it]
{'loss': 0.4926, 'learning_rate': 1.664175205452969e-05, 'epoch': 0.29}
+
29%|██▉ | 3475/11952 [1:59:43<13:51:12, 5.88s/it]
29%|██▉ | 3476/11952 [1:59:49<13:55:31, 5.91s/it]
{'loss': 0.5159, 'learning_rate': 1.663972594830524e-05, 'epoch': 0.29}
+
29%|██▉ | 3476/11952 [1:59:49<13:55:31, 5.91s/it]
29%|██▉ | 3477/11952 [1:59:55<13:59:51, 5.95s/it]
{'loss': 0.5252, 'learning_rate': 1.6637699354486936e-05, 'epoch': 0.29}
+
29%|██▉ | 3477/11952 [1:59:55<13:59:51, 5.95s/it]
29%|██▉ | 3478/11952 [2:00:01<13:54:10, 5.91s/it]
{'loss': 0.4872, 'learning_rate': 1.6635672273223597e-05, 'epoch': 0.29}
+
29%|██▉ | 3478/11952 [2:00:01<13:54:10, 5.91s/it]
29%|██▉ | 3479/11952 [2:00:07<13:49:25, 5.87s/it]
{'loss': 0.4877, 'learning_rate': 1.663364470466409e-05, 'epoch': 0.29}
+
29%|██▉ | 3479/11952 [2:00:07<13:49:25, 5.87s/it]
29%|██▉ | 3480/11952 [2:00:13<13:47:40, 5.86s/it]
{'loss': 0.4879, 'learning_rate': 1.6631616648957303e-05, 'epoch': 0.29}
+
29%|██▉ | 3480/11952 [2:00:13<13:47:40, 5.86s/it]
29%|██▉ | 3481/11952 [2:00:19<13:42:29, 5.83s/it]
{'loss': 0.4756, 'learning_rate': 1.6629588106252173e-05, 'epoch': 0.29}
+
29%|██▉ | 3481/11952 [2:00:19<13:42:29, 5.83s/it]
29%|██▉ | 3482/11952 [2:00:25<13:53:30, 5.90s/it]
{'loss': 0.5409, 'learning_rate': 1.6627559076697672e-05, 'epoch': 0.29}
+
29%|██▉ | 3482/11952 [2:00:25<13:53:30, 5.90s/it]
29%|██▉ | 3483/11952 [2:00:30<13:44:18, 5.84s/it]
{'loss': 0.5017, 'learning_rate': 1.6625529560442793e-05, 'epoch': 0.29}
+
29%|██▉ | 3483/11952 [2:00:30<13:44:18, 5.84s/it]
29%|██▉ | 3484/11952 [2:00:36<13:35:35, 5.78s/it]
{'loss': 0.4925, 'learning_rate': 1.6623499557636584e-05, 'epoch': 0.29}
+
29%|██▉ | 3484/11952 [2:00:36<13:35:35, 5.78s/it]
29%|██▉ | 3485/11952 [2:00:42<13:35:12, 5.78s/it]
{'loss': 0.4936, 'learning_rate': 1.6621469068428114e-05, 'epoch': 0.29}
+
29%|██▉ | 3485/11952 [2:00:42<13:35:12, 5.78s/it]
29%|██▉ | 3486/11952 [2:00:48<13:41:00, 5.82s/it]
{'loss': 0.5126, 'learning_rate': 1.66194380929665e-05, 'epoch': 0.29}
+
29%|██▉ | 3486/11952 [2:00:48<13:41:00, 5.82s/it]
29%|██▉ | 3487/11952 [2:00:53<13:32:43, 5.76s/it]
{'loss': 0.4967, 'learning_rate': 1.6617406631400884e-05, 'epoch': 0.29}
+
29%|██▉ | 3487/11952 [2:00:53<13:32:43, 5.76s/it]
29%|██▉ | 3488/11952 [2:00:59<13:45:25, 5.85s/it]
{'loss': 0.4864, 'learning_rate': 1.6615374683880445e-05, 'epoch': 0.29}
+
29%|██▉ | 3488/11952 [2:00:59<13:45:25, 5.85s/it]
29%|██▉ | 3489/11952 [2:01:05<13:39:12, 5.81s/it]
{'loss': 0.4922, 'learning_rate': 1.6613342250554406e-05, 'epoch': 0.29}
+
29%|██▉ | 3489/11952 [2:01:05<13:39:12, 5.81s/it]
29%|██▉ | 3490/11952 [2:01:11<13:44:31, 5.85s/it]
{'loss': 0.4962, 'learning_rate': 1.6611309331572022e-05, 'epoch': 0.29}
+
29%|██▉ | 3490/11952 [2:01:11<13:44:31, 5.85s/it]
29%|██▉ | 3491/11952 [2:01:17<13:43:47, 5.84s/it]
{'loss': 0.4899, 'learning_rate': 1.6609275927082577e-05, 'epoch': 0.29}
+
29%|██▉ | 3491/11952 [2:01:17<13:43:47, 5.84s/it]
29%|██▉ | 3492/11952 [2:01:23<13:35:24, 5.78s/it]
{'loss': 0.4947, 'learning_rate': 1.66072420372354e-05, 'epoch': 0.29}
+
29%|██▉ | 3492/11952 [2:01:23<13:35:24, 5.78s/it]
29%|██▉ | 3493/11952 [2:01:28<13:39:42, 5.81s/it]
{'loss': 0.5001, 'learning_rate': 1.660520766217985e-05, 'epoch': 0.29}
+
29%|██▉ | 3493/11952 [2:01:28<13:39:42, 5.81s/it]
29%|██▉ | 3494/11952 [2:01:35<13:52:27, 5.91s/it]
{'loss': 0.5018, 'learning_rate': 1.6603172802065317e-05, 'epoch': 0.29}
+
29%|██▉ | 3494/11952 [2:01:35<13:52:27, 5.91s/it]
29%|██▉ | 3495/11952 [2:01:40<13:48:56, 5.88s/it]
{'loss': 0.5025, 'learning_rate': 1.6601137457041242e-05, 'epoch': 0.29}
+
29%|██▉ | 3495/11952 [2:01:40<13:48:56, 5.88s/it]
29%|██▉ | 3496/11952 [2:01:46<13:49:40, 5.89s/it]
{'loss': 0.4887, 'learning_rate': 1.6599101627257087e-05, 'epoch': 0.29}
+
29%|██▉ | 3496/11952 [2:01:46<13:49:40, 5.89s/it]
29%|██▉ | 3497/11952 [2:01:52<13:41:28, 5.83s/it]
{'loss': 0.4875, 'learning_rate': 1.6597065312862358e-05, 'epoch': 0.29}
+
29%|██▉ | 3497/11952 [2:01:52<13:41:28, 5.83s/it]
29%|██▉ | 3498/11952 [2:01:58<13:33:00, 5.77s/it]
{'loss': 0.5023, 'learning_rate': 1.659502851400659e-05, 'epoch': 0.29}
+
29%|██▉ | 3498/11952 [2:01:58<13:33:00, 5.77s/it]
29%|██▉ | 3499/11952 [2:02:04<13:46:42, 5.87s/it]
{'loss': 0.4966, 'learning_rate': 1.6592991230839355e-05, 'epoch': 0.29}
+
29%|██▉ | 3499/11952 [2:02:04<13:46:42, 5.87s/it]10 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...4
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
29%|██▉ | 3500/11952 [2:02:10<14:03:09, 5.99s/it]7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5032, 'learning_rate': 1.659095346351027e-05, 'epoch': 0.29}
+
29%|██▉ | 3500/11952 [2:02:10<14:03:09, 5.99s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
29%|██▉ | 3501/11952 [2:02:42<32:33:47, 13.87s/it]
{'loss': 0.4823, 'learning_rate': 1.6588915212168977e-05, 'epoch': 0.29}
+
29%|██▉ | 3501/11952 [2:02:42<32:33:47, 13.87s/it]
29%|██▉ | 3502/11952 [2:02:48<26:54:01, 11.46s/it]
{'loss': 0.5014, 'learning_rate': 1.658687647696516e-05, 'epoch': 0.29}
+
29%|██▉ | 3502/11952 [2:02:48<26:54:01, 11.46s/it]
29%|██▉ | 3503/11952 [2:02:54<22:49:10, 9.72s/it]
{'loss': 0.4557, 'learning_rate': 1.658483725804853e-05, 'epoch': 0.29}
+
29%|██▉ | 3503/11952 [2:02:54<22:49:10, 9.72s/it]
29%|██▉ | 3504/11952 [2:02:59<19:58:10, 8.51s/it]
{'loss': 0.5108, 'learning_rate': 1.6582797555568834e-05, 'epoch': 0.29}
+
29%|██▉ | 3504/11952 [2:02:59<19:58:10, 8.51s/it]
29%|██▉ | 3505/11952 [2:03:05<18:13:53, 7.77s/it]
{'loss': 0.5026, 'learning_rate': 1.658075736967587e-05, 'epoch': 0.29}
+
29%|██▉ | 3505/11952 [2:03:05<18:13:53, 7.77s/it]
29%|██▉ | 3506/11952 [2:03:11<16:50:15, 7.18s/it]
{'loss': 0.5017, 'learning_rate': 1.6578716700519454e-05, 'epoch': 0.29}
+
29%|██▉ | 3506/11952 [2:03:11<16:50:15, 7.18s/it]
29%|██▉ | 3507/11952 [2:03:17<16:02:47, 6.84s/it]
{'loss': 0.4901, 'learning_rate': 1.657667554824945e-05, 'epoch': 0.29}
+
29%|██▉ | 3507/11952 [2:03:17<16:02:47, 6.84s/it]
29%|██▉ | 3508/11952 [2:03:23<15:13:10, 6.49s/it]
{'loss': 0.4907, 'learning_rate': 1.6574633913015742e-05, 'epoch': 0.29}
+
29%|██▉ | 3508/11952 [2:03:23<15:13:10, 6.49s/it]
29%|██▉ | 3509/11952 [2:03:29<14:42:56, 6.27s/it]
{'loss': 0.4864, 'learning_rate': 1.657259179496827e-05, 'epoch': 0.29}
+
29%|██▉ | 3509/11952 [2:03:29<14:42:56, 6.27s/it]
29%|██▉ | 3510/11952 [2:03:35<14:25:42, 6.15s/it]
{'loss': 0.495, 'learning_rate': 1.6570549194256995e-05, 'epoch': 0.29}
+
29%|██▉ | 3510/11952 [2:03:35<14:25:42, 6.15s/it]
29%|██▉ | 3511/11952 [2:03:40<14:12:04, 6.06s/it]
{'loss': 0.5021, 'learning_rate': 1.6568506111031913e-05, 'epoch': 0.29}
+
29%|██▉ | 3511/11952 [2:03:40<14:12:04, 6.06s/it]
29%|██▉ | 3512/11952 [2:03:46<14:02:35, 5.99s/it]
{'loss': 0.5074, 'learning_rate': 1.6566462545443066e-05, 'epoch': 0.29}
+
29%|██▉ | 3512/11952 [2:03:46<14:02:35, 5.99s/it]
29%|██▉ | 3513/11952 [2:03:52<14:04:17, 6.00s/it]
{'loss': 0.4989, 'learning_rate': 1.656441849764052e-05, 'epoch': 0.29}
+
29%|██▉ | 3513/11952 [2:03:52<14:04:17, 6.00s/it]
29%|██▉ | 3514/11952 [2:03:58<14:05:44, 6.01s/it]
{'loss': 0.509, 'learning_rate': 1.6562373967774382e-05, 'epoch': 0.29}
+
29%|██▉ | 3514/11952 [2:03:58<14:05:44, 6.01s/it]
29%|██▉ | 3515/11952 [2:04:04<13:58:38, 5.96s/it]
{'loss': 0.5201, 'learning_rate': 1.6560328955994796e-05, 'epoch': 0.29}
+
29%|██▉ | 3515/11952 [2:04:04<13:58:38, 5.96s/it]
29%|██▉ | 3516/11952 [2:04:10<14:05:50, 6.02s/it]
{'loss': 0.5027, 'learning_rate': 1.655828346245194e-05, 'epoch': 0.29}
+
29%|██▉ | 3516/11952 [2:04:10<14:05:50, 6.02s/it]
29%|██▉ | 3517/11952 [2:04:16<14:00:08, 5.98s/it]
{'loss': 0.4831, 'learning_rate': 1.655623748729602e-05, 'epoch': 0.29}
+
29%|██▉ | 3517/11952 [2:04:16<14:00:08, 5.98s/it]
29%|██▉ | 3518/11952 [2:04:22<14:03:38, 6.00s/it]
{'loss': 0.5112, 'learning_rate': 1.655419103067729e-05, 'epoch': 0.29}
+
29%|██▉ | 3518/11952 [2:04:22<14:03:38, 6.00s/it]
29%|██▉ | 3519/11952 [2:04:28<14:06:16, 6.02s/it]
{'loss': 0.4874, 'learning_rate': 1.6552144092746032e-05, 'epoch': 0.29}
+
29%|██▉ | 3519/11952 [2:04:28<14:06:16, 6.02s/it]
29%|██▉ | 3520/11952 [2:04:35<14:13:14, 6.07s/it]
{'loss': 0.4991, 'learning_rate': 1.6550096673652565e-05, 'epoch': 0.29}
+
29%|██▉ | 3520/11952 [2:04:35<14:13:14, 6.07s/it]
29%|██▉ | 3521/11952 [2:04:40<13:58:45, 5.97s/it]
{'loss': 0.4899, 'learning_rate': 1.654804877354724e-05, 'epoch': 0.29}
+
29%|██▉ | 3521/11952 [2:04:40<13:58:45, 5.97s/it]
29%|██▉ | 3522/11952 [2:04:46<14:04:09, 6.01s/it]
{'loss': 0.5151, 'learning_rate': 1.654600039258045e-05, 'epoch': 0.29}
+
29%|██▉ | 3522/11952 [2:04:46<14:04:09, 6.01s/it]
29%|██▉ | 3523/11952 [2:04:52<13:48:01, 5.89s/it]
{'loss': 0.5163, 'learning_rate': 1.6543951530902618e-05, 'epoch': 0.29}
+
29%|██▉ | 3523/11952 [2:04:52<13:48:01, 5.89s/it]
29%|██▉ | 3524/11952 [2:04:58<13:36:43, 5.81s/it]
{'loss': 0.4763, 'learning_rate': 1.6541902188664206e-05, 'epoch': 0.29}
+
29%|██▉ | 3524/11952 [2:04:58<13:36:43, 5.81s/it]
29%|██▉ | 3525/11952 [2:05:03<13:31:40, 5.78s/it]
{'loss': 0.5012, 'learning_rate': 1.6539852366015702e-05, 'epoch': 0.29}
+
29%|██▉ | 3525/11952 [2:05:03<13:31:40, 5.78s/it]
30%|██▉ | 3526/11952 [2:05:09<13:23:47, 5.72s/it]
{'loss': 0.4732, 'learning_rate': 1.6537802063107646e-05, 'epoch': 0.3}
+
30%|██▉ | 3526/11952 [2:05:09<13:23:47, 5.72s/it]
30%|██▉ | 3527/11952 [2:05:15<13:35:42, 5.81s/it]
{'loss': 0.51, 'learning_rate': 1.6535751280090598e-05, 'epoch': 0.3}
+
30%|██▉ | 3527/11952 [2:05:15<13:35:42, 5.81s/it]
30%|██▉ | 3528/11952 [2:05:21<13:33:53, 5.80s/it]
{'loss': 0.5077, 'learning_rate': 1.6533700017115162e-05, 'epoch': 0.3}
+
30%|██▉ | 3528/11952 [2:05:21<13:33:53, 5.80s/it]
30%|██▉ | 3529/11952 [2:05:26<13:31:53, 5.78s/it]
{'loss': 0.5029, 'learning_rate': 1.653164827433197e-05, 'epoch': 0.3}
+
30%|██▉ | 3529/11952 [2:05:26<13:31:53, 5.78s/it]
30%|██▉ | 3530/11952 [2:05:32<13:40:27, 5.85s/it]
{'loss': 0.4791, 'learning_rate': 1.6529596051891696e-05, 'epoch': 0.3}
+
30%|██▉ | 3530/11952 [2:05:32<13:40:27, 5.85s/it]
30%|██▉ | 3531/11952 [2:05:38<13:39:32, 5.84s/it]
{'loss': 0.5035, 'learning_rate': 1.6527543349945047e-05, 'epoch': 0.3}
+
30%|██▉ | 3531/11952 [2:05:38<13:39:32, 5.84s/it]
30%|██▉ | 3532/11952 [2:05:44<13:38:02, 5.83s/it]
{'loss': 0.4892, 'learning_rate': 1.6525490168642765e-05, 'epoch': 0.3}
+
30%|██▉ | 3532/11952 [2:05:44<13:38:02, 5.83s/it]
30%|██▉ | 3533/11952 [2:05:50<13:42:19, 5.86s/it]
{'loss': 0.4915, 'learning_rate': 1.6523436508135624e-05, 'epoch': 0.3}
+
30%|██▉ | 3533/11952 [2:05:50<13:42:19, 5.86s/it]
30%|██▉ | 3534/11952 [2:05:56<13:34:28, 5.81s/it]
{'loss': 0.4816, 'learning_rate': 1.6521382368574442e-05, 'epoch': 0.3}
+
30%|██▉ | 3534/11952 [2:05:56<13:34:28, 5.81s/it]
30%|██▉ | 3535/11952 [2:06:02<13:38:07, 5.83s/it]
{'loss': 0.481, 'learning_rate': 1.651932775011006e-05, 'epoch': 0.3}
+
30%|██▉ | 3535/11952 [2:06:02<13:38:07, 5.83s/it]
30%|██▉ | 3536/11952 [2:06:08<13:45:11, 5.88s/it]
{'loss': 0.4885, 'learning_rate': 1.6517272652893367e-05, 'epoch': 0.3}
+
30%|██▉ | 3536/11952 [2:06:08<13:45:11, 5.88s/it]
30%|██▉ | 3537/11952 [2:06:14<13:46:56, 5.90s/it]
{'loss': 0.506, 'learning_rate': 1.6515217077075276e-05, 'epoch': 0.3}
+
30%|██▉ | 3537/11952 [2:06:14<13:46:56, 5.90s/it]
30%|██▉ | 3538/11952 [2:06:19<13:49:14, 5.91s/it]
{'loss': 0.4849, 'learning_rate': 1.651316102280674e-05, 'epoch': 0.3}
+
30%|██▉ | 3538/11952 [2:06:19<13:49:14, 5.91s/it]
30%|██▉ | 3539/11952 [2:06:25<13:40:06, 5.85s/it]
{'loss': 0.5038, 'learning_rate': 1.6511104490238753e-05, 'epoch': 0.3}
+
30%|██▉ | 3539/11952 [2:06:25<13:40:06, 5.85s/it]
30%|██▉ | 3540/11952 [2:06:31<13:49:31, 5.92s/it]
{'loss': 0.5172, 'learning_rate': 1.6509047479522332e-05, 'epoch': 0.3}
+
30%|██▉ | 3540/11952 [2:06:31<13:49:31, 5.92s/it]
30%|██▉ | 3541/11952 [2:06:37<13:44:20, 5.88s/it]
{'loss': 0.4906, 'learning_rate': 1.650698999080854e-05, 'epoch': 0.3}
+
30%|██▉ | 3541/11952 [2:06:37<13:44:20, 5.88s/it]
30%|██▉ | 3542/11952 [2:06:43<13:51:45, 5.93s/it]
{'loss': 0.4895, 'learning_rate': 1.6504932024248462e-05, 'epoch': 0.3}
+
30%|██▉ | 3542/11952 [2:06:43<13:51:45, 5.93s/it]
30%|██▉ | 3543/11952 [2:06:49<13:54:12, 5.95s/it]
{'loss': 0.4769, 'learning_rate': 1.6502873579993238e-05, 'epoch': 0.3}
+
30%|██▉ | 3543/11952 [2:06:49<13:54:12, 5.95s/it]
30%|██▉ | 3544/11952 [2:06:55<13:48:31, 5.91s/it]
{'loss': 0.5035, 'learning_rate': 1.6500814658194024e-05, 'epoch': 0.3}
+
30%|██▉ | 3544/11952 [2:06:55<13:48:31, 5.91s/it]
30%|██▉ | 3545/11952 [2:07:01<13:50:56, 5.93s/it]
{'loss': 0.5003, 'learning_rate': 1.649875525900202e-05, 'epoch': 0.3}
+
30%|██▉ | 3545/11952 [2:07:01<13:50:56, 5.93s/it]
30%|██▉ | 3546/11952 [2:07:07<13:41:07, 5.86s/it]
{'loss': 0.4854, 'learning_rate': 1.649669538256846e-05, 'epoch': 0.3}
+
30%|██▉ | 3546/11952 [2:07:07<13:41:07, 5.86s/it]
30%|██▉ | 3547/11952 [2:07:12<13:38:55, 5.85s/it]
{'loss': 0.4941, 'learning_rate': 1.6494635029044613e-05, 'epoch': 0.3}
+
30%|██▉ | 3547/11952 [2:07:12<13:38:55, 5.85s/it]
30%|██▉ | 3548/11952 [2:07:18<13:35:59, 5.83s/it]
{'loss': 0.4851, 'learning_rate': 1.649257419858178e-05, 'epoch': 0.3}
+
30%|██▉ | 3548/11952 [2:07:18<13:35:59, 5.83s/it]
30%|██▉ | 3549/11952 [2:07:24<13:45:41, 5.90s/it]
{'loss': 0.4964, 'learning_rate': 1.6490512891331304e-05, 'epoch': 0.3}
+
30%|██▉ | 3549/11952 [2:07:24<13:45:41, 5.90s/it]3 AutoResumeHook: Checking whether to suspend...
+7 15AutoResumeHook: Checking whether to suspend...20 4
+ AutoResumeHook: Checking whether to suspend...6 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
+AutoResumeHook: Checking whether to suspend...
+
+ AutoResumeHook: Checking whether to suspend...
+
30%|██▉ | 3550/11952 [2:07:30<13:41:50, 5.87s/it]
{'loss': 0.5009, 'learning_rate': 1.6488451107444556e-05, 'epoch': 0.3}
+
30%|██▉ | 3550/11952 [2:07:30<13:41:50, 5.87s/it]
30%|██▉ | 3551/11952 [2:07:36<13:42:14, 5.87s/it]
{'loss': 0.496, 'learning_rate': 1.648638884707295e-05, 'epoch': 0.3}
+
30%|██▉ | 3551/11952 [2:07:36<13:42:14, 5.87s/it]
30%|██▉ | 3552/11952 [2:07:42<13:36:04, 5.83s/it]
{'loss': 0.5007, 'learning_rate': 1.6484326110367924e-05, 'epoch': 0.3}
+
30%|██▉ | 3552/11952 [2:07:42<13:36:04, 5.83s/it]
30%|██▉ | 3553/11952 [2:07:47<13:34:24, 5.82s/it]
{'loss': 0.5075, 'learning_rate': 1.648226289748096e-05, 'epoch': 0.3}
+
30%|██▉ | 3553/11952 [2:07:47<13:34:24, 5.82s/it]
30%|██▉ | 3554/11952 [2:07:53<13:39:48, 5.86s/it]
{'loss': 0.4816, 'learning_rate': 1.648019920856357e-05, 'epoch': 0.3}
+
30%|██▉ | 3554/11952 [2:07:53<13:39:48, 5.86s/it]
30%|██▉ | 3555/11952 [2:07:59<13:37:12, 5.84s/it]
{'loss': 0.5059, 'learning_rate': 1.6478135043767303e-05, 'epoch': 0.3}
+
30%|██▉ | 3555/11952 [2:07:59<13:37:12, 5.84s/it]
30%|██▉ | 3556/11952 [2:08:05<13:33:51, 5.82s/it]
{'loss': 0.4913, 'learning_rate': 1.647607040324374e-05, 'epoch': 0.3}
+
30%|██▉ | 3556/11952 [2:08:05<13:33:51, 5.82s/it]
30%|██▉ | 3557/11952 [2:08:11<13:36:16, 5.83s/it]
{'loss': 0.4945, 'learning_rate': 1.6474005287144507e-05, 'epoch': 0.3}
+
30%|██▉ | 3557/11952 [2:08:11<13:36:16, 5.83s/it]
30%|██▉ | 3558/11952 [2:08:17<13:32:39, 5.81s/it]
{'loss': 0.4799, 'learning_rate': 1.647193969562125e-05, 'epoch': 0.3}
+
30%|██▉ | 3558/11952 [2:08:17<13:32:39, 5.81s/it]
30%|██▉ | 3559/11952 [2:08:22<13:31:39, 5.80s/it]
{'loss': 0.5039, 'learning_rate': 1.6469873628825665e-05, 'epoch': 0.3}
+
30%|██▉ | 3559/11952 [2:08:22<13:31:39, 5.80s/it]
30%|██▉ | 3560/11952 [2:08:28<13:26:11, 5.76s/it]
{'loss': 0.4956, 'learning_rate': 1.6467807086909468e-05, 'epoch': 0.3}
+
30%|██▉ | 3560/11952 [2:08:28<13:26:11, 5.76s/it]
30%|██▉ | 3561/11952 [2:08:34<13:46:27, 5.91s/it]
{'loss': 0.5098, 'learning_rate': 1.646574007002442e-05, 'epoch': 0.3}
+
30%|██▉ | 3561/11952 [2:08:34<13:46:27, 5.91s/it]
30%|██▉ | 3562/11952 [2:08:40<13:43:20, 5.89s/it]
{'loss': 0.4929, 'learning_rate': 1.6463672578322315e-05, 'epoch': 0.3}
+
30%|██▉ | 3562/11952 [2:08:40<13:43:20, 5.89s/it]
30%|██▉ | 3563/11952 [2:08:46<13:58:35, 6.00s/it]
{'loss': 0.4958, 'learning_rate': 1.646160461195498e-05, 'epoch': 0.3}
+
30%|██▉ | 3563/11952 [2:08:46<13:58:35, 6.00s/it]
30%|██▉ | 3564/11952 [2:08:52<13:56:05, 5.98s/it]
{'loss': 0.4969, 'learning_rate': 1.6459536171074278e-05, 'epoch': 0.3}
+
30%|██▉ | 3564/11952 [2:08:52<13:56:05, 5.98s/it]
30%|██▉ | 3565/11952 [2:08:58<13:36:00, 5.84s/it]
{'loss': 0.5093, 'learning_rate': 1.6457467255832108e-05, 'epoch': 0.3}
+
30%|██▉ | 3565/11952 [2:08:58<13:36:00, 5.84s/it]
30%|██▉ | 3566/11952 [2:09:04<13:35:41, 5.84s/it]
{'loss': 0.4717, 'learning_rate': 1.64553978663804e-05, 'epoch': 0.3}
+
30%|██▉ | 3566/11952 [2:09:04<13:35:41, 5.84s/it]
30%|██▉ | 3567/11952 [2:09:10<13:41:16, 5.88s/it]
{'loss': 0.498, 'learning_rate': 1.645332800287112e-05, 'epoch': 0.3}
+
30%|██▉ | 3567/11952 [2:09:10<13:41:16, 5.88s/it]
30%|██▉ | 3568/11952 [2:09:16<13:43:42, 5.89s/it]
{'loss': 0.5006, 'learning_rate': 1.645125766545628e-05, 'epoch': 0.3}
+
30%|██▉ | 3568/11952 [2:09:16<13:43:42, 5.89s/it]
30%|██▉ | 3569/11952 [2:09:21<13:34:21, 5.83s/it]
{'loss': 0.5093, 'learning_rate': 1.6449186854287903e-05, 'epoch': 0.3}
+
30%|██▉ | 3569/11952 [2:09:21<13:34:21, 5.83s/it]
30%|██▉ | 3570/11952 [2:09:27<13:36:26, 5.84s/it]
{'loss': 0.5111, 'learning_rate': 1.644711556951807e-05, 'epoch': 0.3}
+
30%|██▉ | 3570/11952 [2:09:27<13:36:26, 5.84s/it]
30%|██▉ | 3571/11952 [2:09:33<13:30:49, 5.80s/it]
{'loss': 0.5057, 'learning_rate': 1.6445043811298887e-05, 'epoch': 0.3}
+
30%|██▉ | 3571/11952 [2:09:33<13:30:49, 5.80s/it]
30%|██▉ | 3572/11952 [2:09:39<13:33:20, 5.82s/it]
{'loss': 0.4916, 'learning_rate': 1.644297157978249e-05, 'epoch': 0.3}
+
30%|██▉ | 3572/11952 [2:09:39<13:33:20, 5.82s/it]
30%|██▉ | 3573/11952 [2:09:45<13:37:22, 5.85s/it]
{'loss': 0.4835, 'learning_rate': 1.644089887512106e-05, 'epoch': 0.3}
+
30%|██▉ | 3573/11952 [2:09:45<13:37:22, 5.85s/it]
30%|██▉ | 3574/11952 [2:09:50<13:24:33, 5.76s/it]
{'loss': 0.4892, 'learning_rate': 1.6438825697466808e-05, 'epoch': 0.3}
+
30%|██▉ | 3574/11952 [2:09:50<13:24:33, 5.76s/it]
30%|██▉ | 3575/11952 [2:09:56<13:19:03, 5.72s/it]
{'loss': 0.4817, 'learning_rate': 1.6436752046971975e-05, 'epoch': 0.3}
+
30%|██▉ | 3575/11952 [2:09:56<13:19:03, 5.72s/it]
30%|██▉ | 3576/11952 [2:10:02<13:25:42, 5.77s/it]
{'loss': 0.483, 'learning_rate': 1.6434677923788848e-05, 'epoch': 0.3}
+
30%|██▉ | 3576/11952 [2:10:02<13:25:42, 5.77s/it]
30%|██▉ | 3577/11952 [2:10:07<13:23:34, 5.76s/it]
{'loss': 0.5143, 'learning_rate': 1.6432603328069732e-05, 'epoch': 0.3}
+
30%|██▉ | 3577/11952 [2:10:07<13:23:34, 5.76s/it]
30%|██▉ | 3578/11952 [2:10:14<13:39:13, 5.87s/it]
{'loss': 0.507, 'learning_rate': 1.643052825996699e-05, 'epoch': 0.3}
+
30%|██▉ | 3578/11952 [2:10:14<13:39:13, 5.87s/it]
30%|██▉ | 3579/11952 [2:10:20<13:43:38, 5.90s/it]
{'loss': 0.4962, 'learning_rate': 1.6428452719632994e-05, 'epoch': 0.3}
+
30%|██▉ | 3579/11952 [2:10:20<13:43:38, 5.90s/it]
30%|██▉ | 3580/11952 [2:10:25<13:43:03, 5.90s/it]
{'loss': 0.5072, 'learning_rate': 1.642637670722017e-05, 'epoch': 0.3}
+
30%|██▉ | 3580/11952 [2:10:25<13:43:03, 5.90s/it]
30%|██▉ | 3581/11952 [2:10:31<13:28:30, 5.80s/it]
{'loss': 0.4931, 'learning_rate': 1.642430022288097e-05, 'epoch': 0.3}
+
30%|██▉ | 3581/11952 [2:10:31<13:28:30, 5.80s/it]
30%|██▉ | 3582/11952 [2:10:37<13:21:41, 5.75s/it]
{'loss': 0.4838, 'learning_rate': 1.6422223266767883e-05, 'epoch': 0.3}
+
30%|██▉ | 3582/11952 [2:10:37<13:21:41, 5.75s/it]
30%|██▉ | 3583/11952 [2:10:43<13:30:40, 5.81s/it]
{'loss': 0.5034, 'learning_rate': 1.642014583903343e-05, 'epoch': 0.3}
+
30%|██▉ | 3583/11952 [2:10:43<13:30:40, 5.81s/it]
30%|██▉ | 3584/11952 [2:10:48<13:30:08, 5.81s/it]
{'loss': 0.5004, 'learning_rate': 1.641806793983017e-05, 'epoch': 0.3}
+
30%|██▉ | 3584/11952 [2:10:48<13:30:08, 5.81s/it]
30%|██▉ | 3585/11952 [2:10:54<13:20:57, 5.74s/it]
{'loss': 0.4913, 'learning_rate': 1.6415989569310698e-05, 'epoch': 0.3}
+
30%|██▉ | 3585/11952 [2:10:54<13:20:57, 5.74s/it]
30%|███ | 3586/11952 [2:11:00<13:32:13, 5.83s/it]
{'loss': 0.4919, 'learning_rate': 1.6413910727627637e-05, 'epoch': 0.3}
+
30%|███ | 3586/11952 [2:11:00<13:32:13, 5.83s/it]
30%|███ | 3587/11952 [2:11:06<13:28:29, 5.80s/it]
{'loss': 0.5063, 'learning_rate': 1.6411831414933647e-05, 'epoch': 0.3}
+
30%|███ | 3587/11952 [2:11:06<13:28:29, 5.80s/it]
30%|███ | 3588/11952 [2:11:12<13:29:56, 5.81s/it]
{'loss': 0.481, 'learning_rate': 1.6409751631381428e-05, 'epoch': 0.3}
+
30%|███ | 3588/11952 [2:11:12<13:29:56, 5.81s/it]
30%|███ | 3589/11952 [2:11:17<13:30:46, 5.82s/it]
{'loss': 0.5164, 'learning_rate': 1.640767137712371e-05, 'epoch': 0.3}
+
30%|███ | 3589/11952 [2:11:17<13:30:46, 5.82s/it]
30%|███ | 3590/11952 [2:11:23<13:27:24, 5.79s/it]
{'loss': 0.4764, 'learning_rate': 1.6405590652313256e-05, 'epoch': 0.3}
+
30%|███ | 3590/11952 [2:11:23<13:27:24, 5.79s/it]
30%|███ | 3591/11952 [2:11:29<13:17:01, 5.72s/it]
{'loss': 0.4895, 'learning_rate': 1.640350945710287e-05, 'epoch': 0.3}
+
30%|███ | 3591/11952 [2:11:29<13:17:01, 5.72s/it]
30%|███ | 3592/11952 [2:11:34<13:21:28, 5.75s/it]
{'loss': 0.5138, 'learning_rate': 1.640142779164538e-05, 'epoch': 0.3}
+
30%|███ | 3592/11952 [2:11:34<13:21:28, 5.75s/it]
30%|███ | 3593/11952 [2:11:40<13:14:28, 5.70s/it]
{'loss': 0.476, 'learning_rate': 1.6399345656093663e-05, 'epoch': 0.3}
+
30%|███ | 3593/11952 [2:11:40<13:14:28, 5.70s/it]
30%|███ | 3594/11952 [2:11:46<13:40:50, 5.89s/it]
{'loss': 0.4773, 'learning_rate': 1.6397263050600615e-05, 'epoch': 0.3}
+
30%|███ | 3594/11952 [2:11:46<13:40:50, 5.89s/it]
30%|███ | 3595/11952 [2:11:53<13:51:09, 5.97s/it]
{'loss': 0.5097, 'learning_rate': 1.6395179975319178e-05, 'epoch': 0.3}
+
30%|███ | 3595/11952 [2:11:53<13:51:09, 5.97s/it]
30%|███ | 3596/11952 [2:11:58<13:47:35, 5.94s/it]
{'loss': 0.5019, 'learning_rate': 1.6393096430402323e-05, 'epoch': 0.3}
+
30%|███ | 3596/11952 [2:11:58<13:47:35, 5.94s/it]
30%|███ | 3597/11952 [2:12:04<13:48:42, 5.95s/it]
{'loss': 0.4923, 'learning_rate': 1.6391012416003053e-05, 'epoch': 0.3}
+
30%|███ | 3597/11952 [2:12:04<13:48:42, 5.95s/it]
30%|███ | 3598/11952 [2:12:10<13:31:07, 5.83s/it]
{'loss': 0.4851, 'learning_rate': 1.638892793227442e-05, 'epoch': 0.3}
+
30%|███ | 3598/11952 [2:12:10<13:31:07, 5.83s/it]
30%|███ | 3599/11952 [2:12:16<13:34:55, 5.85s/it]
{'loss': 0.4981, 'learning_rate': 1.6386842979369487e-05, 'epoch': 0.3}
+
30%|███ | 3599/11952 [2:12:16<13:34:55, 5.85s/it]3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+57 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+2 AutoResumeHook: Checking whether to suspend...
+60 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
30%|███ | 3600/11952 [2:12:22<13:29:37, 5.82s/it]
{'loss': 0.5019, 'learning_rate': 1.6384757557441373e-05, 'epoch': 0.3}
+
30%|███ | 3600/11952 [2:12:22<13:29:37, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
30%|███ | 3601/11952 [2:12:54<32:13:40, 13.89s/it]
{'loss': 0.492, 'learning_rate': 1.6382671666643223e-05, 'epoch': 0.3}
+
30%|███ | 3601/11952 [2:12:54<32:13:40, 13.89s/it]
30%|███ | 3602/11952 [2:13:00<26:27:29, 11.41s/it]
{'loss': 0.4817, 'learning_rate': 1.638058530712821e-05, 'epoch': 0.3}
+
30%|███ | 3602/11952 [2:13:00<26:27:29, 11.41s/it]
30%|███ | 3603/11952 [2:13:06<22:28:44, 9.69s/it]
{'loss': 0.5039, 'learning_rate': 1.6378498479049553e-05, 'epoch': 0.3}
+
30%|███ | 3603/11952 [2:13:06<22:28:44, 9.69s/it]
30%|███ | 3604/11952 [2:13:11<19:45:53, 8.52s/it]
{'loss': 0.5044, 'learning_rate': 1.6376411182560498e-05, 'epoch': 0.3}
+
30%|███ | 3604/11952 [2:13:11<19:45:53, 8.52s/it]
30%|███ | 3605/11952 [2:13:17<18:00:25, 7.77s/it]
{'loss': 0.5089, 'learning_rate': 1.6374323417814325e-05, 'epoch': 0.3}
+
30%|███ | 3605/11952 [2:13:17<18:00:25, 7.77s/it]
30%|███ | 3606/11952 [2:13:23<16:32:58, 7.14s/it]
{'loss': 0.4915, 'learning_rate': 1.6372235184964357e-05, 'epoch': 0.3}
+
30%|███ | 3606/11952 [2:13:23<16:32:58, 7.14s/it]
30%|███ | 3607/11952 [2:13:29<15:28:15, 6.67s/it]
{'loss': 0.4752, 'learning_rate': 1.6370146484163935e-05, 'epoch': 0.3}
+
30%|███ | 3607/11952 [2:13:29<15:28:15, 6.67s/it]
30%|███ | 3608/11952 [2:13:35<14:56:42, 6.45s/it]
{'loss': 0.5043, 'learning_rate': 1.6368057315566454e-05, 'epoch': 0.3}
+
30%|███ | 3608/11952 [2:13:35<14:56:42, 6.45s/it]
30%|███ | 3609/11952 [2:13:40<14:31:54, 6.27s/it]
{'loss': 0.5013, 'learning_rate': 1.636596767932533e-05, 'epoch': 0.3}
+
30%|███ | 3609/11952 [2:13:40<14:31:54, 6.27s/it]
30%|███ | 3610/11952 [2:13:46<14:10:28, 6.12s/it]
{'loss': 0.482, 'learning_rate': 1.636387757559402e-05, 'epoch': 0.3}
+
30%|███ | 3610/11952 [2:13:46<14:10:28, 6.12s/it]
30%|███ | 3611/11952 [2:13:52<14:01:05, 6.05s/it]
{'loss': 0.524, 'learning_rate': 1.6361787004526006e-05, 'epoch': 0.3}
+
30%|███ | 3611/11952 [2:13:52<14:01:05, 6.05s/it]
30%|███ | 3612/11952 [2:13:58<13:56:55, 6.02s/it]
{'loss': 0.5078, 'learning_rate': 1.635969596627482e-05, 'epoch': 0.3}
+
30%|███ | 3612/11952 [2:13:58<13:56:55, 6.02s/it]
30%|███ | 3613/11952 [2:14:04<13:44:40, 5.93s/it]
{'loss': 0.4964, 'learning_rate': 1.635760446099401e-05, 'epoch': 0.3}
+
30%|███ | 3613/11952 [2:14:04<13:44:40, 5.93s/it]
30%|███ | 3614/11952 [2:14:10<13:43:51, 5.93s/it]
{'loss': 0.4827, 'learning_rate': 1.6355512488837173e-05, 'epoch': 0.3}
+
30%|███ | 3614/11952 [2:14:10<13:43:51, 5.93s/it]
30%|███ | 3615/11952 [2:14:15<13:37:27, 5.88s/it]
{'loss': 0.4924, 'learning_rate': 1.6353420049957932e-05, 'epoch': 0.3}
+
30%|███ | 3615/11952 [2:14:15<13:37:27, 5.88s/it]
30%|███ | 3616/11952 [2:14:22<13:47:36, 5.96s/it]
{'loss': 0.5235, 'learning_rate': 1.6351327144509954e-05, 'epoch': 0.3}
+
30%|███ | 3616/11952 [2:14:22<13:47:36, 5.96s/it]
30%|███ | 3617/11952 [2:14:27<13:42:11, 5.92s/it]
{'loss': 0.4919, 'learning_rate': 1.6349233772646923e-05, 'epoch': 0.3}
+
30%|███ | 3617/11952 [2:14:27<13:42:11, 5.92s/it]
30%|███ | 3618/11952 [2:14:33<13:45:37, 5.94s/it]
{'loss': 0.5046, 'learning_rate': 1.6347139934522572e-05, 'epoch': 0.3}
+
30%|███ | 3618/11952 [2:14:33<13:45:37, 5.94s/it]
30%|███ | 3619/11952 [2:14:39<13:49:26, 5.97s/it]
{'loss': 0.5007, 'learning_rate': 1.6345045630290664e-05, 'epoch': 0.3}
+
30%|███ | 3619/11952 [2:14:39<13:49:26, 5.97s/it]
30%|███ | 3620/11952 [2:14:45<13:44:04, 5.93s/it]
{'loss': 0.4592, 'learning_rate': 1.6342950860105e-05, 'epoch': 0.3}
+
30%|███ | 3620/11952 [2:14:45<13:44:04, 5.93s/it]
30%|███ | 3621/11952 [2:14:51<13:34:20, 5.86s/it]
{'loss': 0.4886, 'learning_rate': 1.63408556241194e-05, 'epoch': 0.3}
+
30%|███ | 3621/11952 [2:14:51<13:34:20, 5.86s/it]
30%|███ | 3622/11952 [2:14:57<13:30:17, 5.84s/it]
{'loss': 0.4956, 'learning_rate': 1.633875992248774e-05, 'epoch': 0.3}
+
30%|███ | 3622/11952 [2:14:57<13:30:17, 5.84s/it]
30%|███ | 3623/11952 [2:15:03<13:40:28, 5.91s/it]
{'loss': 0.4919, 'learning_rate': 1.633666375536392e-05, 'epoch': 0.3}
+
30%|███ | 3623/11952 [2:15:03<13:40:28, 5.91s/it]
30%|███ | 3624/11952 [2:15:09<13:37:09, 5.89s/it]
{'loss': 0.5073, 'learning_rate': 1.6334567122901862e-05, 'epoch': 0.3}
+
30%|███ | 3624/11952 [2:15:09<13:37:09, 5.89s/it]
30%|███ | 3625/11952 [2:15:15<13:37:47, 5.89s/it]
{'loss': 0.5198, 'learning_rate': 1.633247002525555e-05, 'epoch': 0.3}
+
30%|███ | 3625/11952 [2:15:15<13:37:47, 5.89s/it]
30%|███ | 3626/11952 [2:15:20<13:31:53, 5.85s/it]
{'loss': 0.481, 'learning_rate': 1.6330372462578972e-05, 'epoch': 0.3}
+
30%|███ | 3626/11952 [2:15:20<13:31:53, 5.85s/it]
30%|███ | 3627/11952 [2:15:26<13:40:29, 5.91s/it]
{'loss': 0.4838, 'learning_rate': 1.6328274435026174e-05, 'epoch': 0.3}
+
30%|███ | 3627/11952 [2:15:26<13:40:29, 5.91s/it]
30%|███ | 3628/11952 [2:15:32<13:30:47, 5.84s/it]
{'loss': 0.4937, 'learning_rate': 1.6326175942751222e-05, 'epoch': 0.3}
+
30%|███ | 3628/11952 [2:15:32<13:30:47, 5.84s/it]
30%|███ | 3629/11952 [2:15:38<13:27:08, 5.82s/it]
{'loss': 0.4734, 'learning_rate': 1.632407698590822e-05, 'epoch': 0.3}
+
30%|███ | 3629/11952 [2:15:38<13:27:08, 5.82s/it]
30%|███ | 3630/11952 [2:15:44<13:22:56, 5.79s/it]
{'loss': 0.4866, 'learning_rate': 1.6321977564651313e-05, 'epoch': 0.3}
+
30%|███ | 3630/11952 [2:15:44<13:22:56, 5.79s/it]
30%|███ | 3631/11952 [2:15:50<13:32:01, 5.86s/it]
{'loss': 0.5065, 'learning_rate': 1.6319877679134662e-05, 'epoch': 0.3}
+
30%|███ | 3631/11952 [2:15:50<13:32:01, 5.86s/it]
30%|███ | 3632/11952 [2:15:56<13:36:09, 5.89s/it]
{'loss': 0.4771, 'learning_rate': 1.6317777329512485e-05, 'epoch': 0.3}
+
30%|███ | 3632/11952 [2:15:56<13:36:09, 5.89s/it]
30%|███ | 3633/11952 [2:16:01<13:33:44, 5.87s/it]
{'loss': 0.4991, 'learning_rate': 1.6315676515939015e-05, 'epoch': 0.3}
+
30%|███ | 3633/11952 [2:16:01<13:33:44, 5.87s/it]
30%|███ | 3634/11952 [2:16:07<13:39:55, 5.91s/it]
{'loss': 0.494, 'learning_rate': 1.6313575238568535e-05, 'epoch': 0.3}
+
30%|███ | 3634/11952 [2:16:07<13:39:55, 5.91s/it]
30%|███ | 3635/11952 [2:16:13<13:29:21, 5.84s/it]
{'loss': 0.4731, 'learning_rate': 1.6311473497555343e-05, 'epoch': 0.3}
+
30%|███ | 3635/11952 [2:16:13<13:29:21, 5.84s/it]
30%|███ | 3636/11952 [2:16:19<13:42:58, 5.94s/it]
{'loss': 0.5089, 'learning_rate': 1.6309371293053793e-05, 'epoch': 0.3}
+
30%|███ | 3636/11952 [2:16:19<13:42:58, 5.94s/it]
30%|███ | 3637/11952 [2:16:25<13:30:50, 5.85s/it]
{'loss': 0.4857, 'learning_rate': 1.630726862521826e-05, 'epoch': 0.3}
+
30%|███ | 3637/11952 [2:16:25<13:30:50, 5.85s/it]
30%|███ | 3638/11952 [2:16:31<13:24:11, 5.80s/it]
{'loss': 0.4843, 'learning_rate': 1.6305165494203147e-05, 'epoch': 0.3}
+
30%|███ | 3638/11952 [2:16:31<13:24:11, 5.80s/it]
30%|███ | 3639/11952 [2:16:37<13:37:54, 5.90s/it]
{'loss': 0.5002, 'learning_rate': 1.6303061900162912e-05, 'epoch': 0.3}
+
30%|███ | 3639/11952 [2:16:37<13:37:54, 5.90s/it]
30%|███ | 3640/11952 [2:16:42<13:27:13, 5.83s/it]
{'loss': 0.4996, 'learning_rate': 1.6300957843252027e-05, 'epoch': 0.3}
+
30%|███ | 3640/11952 [2:16:42<13:27:13, 5.83s/it]
30%|███ | 3641/11952 [2:16:48<13:32:20, 5.86s/it]
{'loss': 0.4843, 'learning_rate': 1.6298853323625003e-05, 'epoch': 0.3}
+
30%|███ | 3641/11952 [2:16:48<13:32:20, 5.86s/it]
30%|███ | 3642/11952 [2:16:54<13:24:47, 5.81s/it]
{'loss': 0.491, 'learning_rate': 1.6296748341436386e-05, 'epoch': 0.3}
+
30%|███ | 3642/11952 [2:16:54<13:24:47, 5.81s/it]
30%|███ | 3643/11952 [2:17:00<13:15:30, 5.74s/it]
{'loss': 0.4923, 'learning_rate': 1.6294642896840768e-05, 'epoch': 0.3}
+
30%|███ | 3643/11952 [2:17:00<13:15:30, 5.74s/it]
30%|███ | 3644/11952 [2:17:06<13:28:58, 5.84s/it]
{'loss': 0.4955, 'learning_rate': 1.6292536989992754e-05, 'epoch': 0.3}
+
30%|███ | 3644/11952 [2:17:06<13:28:58, 5.84s/it]
30%|███ | 3645/11952 [2:17:12<13:49:37, 5.99s/it]
{'loss': 0.4928, 'learning_rate': 1.6290430621046994e-05, 'epoch': 0.3}
+
30%|███ | 3645/11952 [2:17:12<13:49:37, 5.99s/it]
31%|███ | 3646/11952 [2:17:18<13:34:36, 5.88s/it]
{'loss': 0.4971, 'learning_rate': 1.6288323790158175e-05, 'epoch': 0.31}
+
31%|███ | 3646/11952 [2:17:18<13:34:36, 5.88s/it]
31%|███ | 3647/11952 [2:17:23<13:32:58, 5.87s/it]
{'loss': 0.488, 'learning_rate': 1.6286216497481014e-05, 'epoch': 0.31}
+
31%|███ | 3647/11952 [2:17:23<13:32:58, 5.87s/it]
31%|███ | 3648/11952 [2:17:30<13:47:27, 5.98s/it]
{'loss': 0.493, 'learning_rate': 1.6284108743170256e-05, 'epoch': 0.31}
+
31%|███ | 3648/11952 [2:17:30<13:47:27, 5.98s/it]
31%|███ | 3649/11952 [2:17:36<13:40:03, 5.93s/it]
{'loss': 0.4973, 'learning_rate': 1.628200052738069e-05, 'epoch': 0.31}
+
31%|███ | 3649/11952 [2:17:36<13:40:03, 5.93s/it]3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
31%|███ | 3650/11952 [2:17:41<13:32:06, 5.87s/it]
{'loss': 0.4951, 'learning_rate': 1.6279891850267134e-05, 'epoch': 0.31}
+
31%|███ | 3650/11952 [2:17:41<13:32:06, 5.87s/it]
31%|███ | 3651/11952 [2:17:47<13:35:28, 5.89s/it]
{'loss': 0.4991, 'learning_rate': 1.6277782711984446e-05, 'epoch': 0.31}
+
31%|███ | 3651/11952 [2:17:47<13:35:28, 5.89s/it]
31%|███ | 3652/11952 [2:17:53<13:23:46, 5.81s/it]
{'loss': 0.4884, 'learning_rate': 1.62756731126875e-05, 'epoch': 0.31}
+
31%|███ | 3652/11952 [2:17:53<13:23:46, 5.81s/it]
31%|███ | 3653/11952 [2:17:58<13:15:07, 5.75s/it]
{'loss': 0.4774, 'learning_rate': 1.6273563052531227e-05, 'epoch': 0.31}
+
31%|███ | 3653/11952 [2:17:58<13:15:07, 5.75s/it]
31%|███ | 3654/11952 [2:18:04<13:13:39, 5.74s/it]
{'loss': 0.4959, 'learning_rate': 1.6271452531670577e-05, 'epoch': 0.31}
+
31%|███ | 3654/11952 [2:18:04<13:13:39, 5.74s/it]
31%|███ | 3655/11952 [2:18:10<13:34:04, 5.89s/it]
{'loss': 0.4922, 'learning_rate': 1.6269341550260537e-05, 'epoch': 0.31}
+
31%|███ | 3655/11952 [2:18:10<13:34:04, 5.89s/it]
31%|███ | 3656/11952 [2:18:16<13:40:43, 5.94s/it]
{'loss': 0.5079, 'learning_rate': 1.6267230108456126e-05, 'epoch': 0.31}
+
31%|███ | 3656/11952 [2:18:16<13:40:43, 5.94s/it]
31%|███ | 3657/11952 [2:18:22<13:40:58, 5.94s/it]
{'loss': 0.482, 'learning_rate': 1.6265118206412412e-05, 'epoch': 0.31}
+
31%|███ | 3657/11952 [2:18:22<13:40:58, 5.94s/it]
31%|███ | 3658/11952 [2:18:28<13:31:23, 5.87s/it]
{'loss': 0.4812, 'learning_rate': 1.6263005844284468e-05, 'epoch': 0.31}
+
31%|███ | 3658/11952 [2:18:28<13:31:23, 5.87s/it]
31%|███ | 3659/11952 [2:18:34<13:23:12, 5.81s/it]
{'loss': 0.521, 'learning_rate': 1.6260893022227425e-05, 'epoch': 0.31}
+
31%|███ | 3659/11952 [2:18:34<13:23:12, 5.81s/it]
31%|███ | 3660/11952 [2:18:40<13:31:21, 5.87s/it]
{'loss': 0.4847, 'learning_rate': 1.6258779740396443e-05, 'epoch': 0.31}
+
31%|███ | 3660/11952 [2:18:40<13:31:21, 5.87s/it]
31%|███ | 3661/11952 [2:18:45<13:24:26, 5.82s/it]
{'loss': 0.499, 'learning_rate': 1.6256665998946708e-05, 'epoch': 0.31}
+
31%|███ | 3661/11952 [2:18:45<13:24:26, 5.82s/it]
31%|███ | 3662/11952 [2:18:51<13:32:28, 5.88s/it]
{'loss': 0.4978, 'learning_rate': 1.6254551798033444e-05, 'epoch': 0.31}
+
31%|███ | 3662/11952 [2:18:51<13:32:28, 5.88s/it]
31%|███ | 3663/11952 [2:18:57<13:30:41, 5.87s/it]
{'loss': 0.4887, 'learning_rate': 1.6252437137811913e-05, 'epoch': 0.31}
+
31%|███ | 3663/11952 [2:18:57<13:30:41, 5.87s/it]
31%|███ | 3664/11952 [2:19:03<13:33:46, 5.89s/it]
{'loss': 0.4927, 'learning_rate': 1.62503220184374e-05, 'epoch': 0.31}
+
31%|███ | 3664/11952 [2:19:03<13:33:46, 5.89s/it]
31%|███ | 3665/11952 [2:19:09<13:28:57, 5.86s/it]
{'loss': 0.4999, 'learning_rate': 1.624820644006524e-05, 'epoch': 0.31}
+
31%|███ | 3665/11952 [2:19:09<13:28:57, 5.86s/it]
31%|███ | 3666/11952 [2:19:15<13:31:43, 5.88s/it]
{'loss': 0.5203, 'learning_rate': 1.6246090402850783e-05, 'epoch': 0.31}
+
31%|███ | 3666/11952 [2:19:15<13:31:43, 5.88s/it]
31%|███ | 3667/11952 [2:19:21<13:38:27, 5.93s/it]
{'loss': 0.4929, 'learning_rate': 1.6243973906949434e-05, 'epoch': 0.31}
+
31%|███ | 3667/11952 [2:19:21<13:38:27, 5.93s/it]
31%|███ | 3668/11952 [2:19:27<13:28:38, 5.86s/it]
{'loss': 0.4796, 'learning_rate': 1.6241856952516604e-05, 'epoch': 0.31}
+
31%|███ | 3668/11952 [2:19:27<13:28:38, 5.86s/it]
31%|███ | 3669/11952 [2:19:33<13:28:04, 5.85s/it]
{'loss': 0.4937, 'learning_rate': 1.623973953970776e-05, 'epoch': 0.31}
+
31%|███ | 3669/11952 [2:19:33<13:28:04, 5.85s/it]
31%|███ | 3670/11952 [2:19:39<13:44:25, 5.97s/it]
{'loss': 0.4927, 'learning_rate': 1.6237621668678406e-05, 'epoch': 0.31}
+
31%|███ | 3670/11952 [2:19:39<13:44:25, 5.97s/it]
31%|███ | 3671/11952 [2:19:45<13:39:58, 5.94s/it]
{'loss': 0.4964, 'learning_rate': 1.6235503339584052e-05, 'epoch': 0.31}
+
31%|███ | 3671/11952 [2:19:45<13:39:58, 5.94s/it]
31%|███ | 3672/11952 [2:19:50<13:24:57, 5.83s/it]
{'loss': 0.4833, 'learning_rate': 1.6233384552580272e-05, 'epoch': 0.31}
+
31%|███ | 3672/11952 [2:19:50<13:24:57, 5.83s/it]
31%|███ | 3673/11952 [2:19:56<13:19:38, 5.80s/it]
{'loss': 0.4704, 'learning_rate': 1.6231265307822658e-05, 'epoch': 0.31}
+
31%|███ | 3673/11952 [2:19:56<13:19:38, 5.80s/it]
31%|███ | 3674/11952 [2:20:02<13:10:34, 5.73s/it]
{'loss': 0.5002, 'learning_rate': 1.622914560546684e-05, 'epoch': 0.31}
+
31%|███ | 3674/11952 [2:20:02<13:10:34, 5.73s/it]
31%|███ | 3675/11952 [2:20:08<13:29:24, 5.87s/it]
{'loss': 0.4905, 'learning_rate': 1.6227025445668473e-05, 'epoch': 0.31}
+
31%|███ | 3675/11952 [2:20:08<13:29:24, 5.87s/it]
31%|███ | 3676/11952 [2:20:14<13:25:21, 5.84s/it]
{'loss': 0.4894, 'learning_rate': 1.622490482858326e-05, 'epoch': 0.31}
+
31%|███ | 3676/11952 [2:20:14<13:25:21, 5.84s/it]
31%|███ | 3677/11952 [2:20:19<13:26:05, 5.84s/it]
{'loss': 0.4877, 'learning_rate': 1.6222783754366926e-05, 'epoch': 0.31}
+
31%|███ | 3677/11952 [2:20:19<13:26:05, 5.84s/it]
31%|███ | 3678/11952 [2:20:25<13:24:46, 5.84s/it]
{'loss': 0.4793, 'learning_rate': 1.6220662223175233e-05, 'epoch': 0.31}
+
31%|███ | 3678/11952 [2:20:25<13:24:46, 5.84s/it]
31%|███ | 3679/11952 [2:20:31<13:40:05, 5.95s/it]
{'loss': 0.4839, 'learning_rate': 1.6218540235163983e-05, 'epoch': 0.31}
+
31%|███ | 3679/11952 [2:20:31<13:40:05, 5.95s/it]
31%|███ | 3680/11952 [2:20:37<13:37:08, 5.93s/it]
{'loss': 0.4906, 'learning_rate': 1.6216417790489005e-05, 'epoch': 0.31}
+
31%|███ | 3680/11952 [2:20:37<13:37:08, 5.93s/it]
31%|███ | 3681/11952 [2:20:43<13:32:39, 5.90s/it]
{'loss': 0.4857, 'learning_rate': 1.6214294889306158e-05, 'epoch': 0.31}
+
31%|███ | 3681/11952 [2:20:43<13:32:39, 5.90s/it]
31%|███ | 3682/11952 [2:20:49<13:37:05, 5.93s/it]
{'loss': 0.4932, 'learning_rate': 1.621217153177134e-05, 'epoch': 0.31}
+
31%|███ | 3682/11952 [2:20:49<13:37:05, 5.93s/it]
31%|███ | 3683/11952 [2:20:55<13:36:27, 5.92s/it]
{'loss': 0.4943, 'learning_rate': 1.621004771804049e-05, 'epoch': 0.31}
+
31%|███ | 3683/11952 [2:20:55<13:36:27, 5.92s/it]
31%|███ | 3684/11952 [2:21:01<13:28:58, 5.87s/it]
{'loss': 0.517, 'learning_rate': 1.620792344826956e-05, 'epoch': 0.31}
+
31%|███ | 3684/11952 [2:21:01<13:28:58, 5.87s/it]
31%|███ | 3685/11952 [2:21:06<13:19:38, 5.80s/it]
{'loss': 0.4828, 'learning_rate': 1.6205798722614552e-05, 'epoch': 0.31}
+
31%|███ | 3685/11952 [2:21:06<13:19:38, 5.80s/it]
31%|███ | 3686/11952 [2:21:12<13:19:44, 5.81s/it]
{'loss': 0.473, 'learning_rate': 1.6203673541231497e-05, 'epoch': 0.31}
+
31%|███ | 3686/11952 [2:21:12<13:19:44, 5.81s/it]
31%|███ | 3687/11952 [2:21:18<13:15:38, 5.78s/it]
{'loss': 0.4931, 'learning_rate': 1.6201547904276463e-05, 'epoch': 0.31}
+
31%|███ | 3687/11952 [2:21:18<13:15:38, 5.78s/it]
31%|███ | 3688/11952 [2:21:24<13:17:54, 5.79s/it]
{'loss': 0.508, 'learning_rate': 1.6199421811905542e-05, 'epoch': 0.31}
+
31%|███ | 3688/11952 [2:21:24<13:17:54, 5.79s/it]
31%|███ | 3689/11952 [2:21:30<13:37:33, 5.94s/it]
{'loss': 0.4883, 'learning_rate': 1.619729526427487e-05, 'epoch': 0.31}
+
31%|███ | 3689/11952 [2:21:30<13:37:33, 5.94s/it]
31%|███ | 3690/11952 [2:21:36<13:28:54, 5.87s/it]
{'loss': 0.4819, 'learning_rate': 1.6195168261540612e-05, 'epoch': 0.31}
+
31%|███ | 3690/11952 [2:21:36<13:28:54, 5.87s/it]
31%|███ | 3691/11952 [2:21:41<13:23:28, 5.84s/it]
{'loss': 0.5097, 'learning_rate': 1.6193040803858965e-05, 'epoch': 0.31}
+
31%|███ | 3691/11952 [2:21:41<13:23:28, 5.84s/it]
31%|███ | 3692/11952 [2:21:47<13:14:30, 5.77s/it]
{'loss': 0.5071, 'learning_rate': 1.6190912891386154e-05, 'epoch': 0.31}
+
31%|███ | 3692/11952 [2:21:47<13:14:30, 5.77s/it]
31%|███ | 3693/11952 [2:21:53<13:06:05, 5.71s/it]
{'loss': 0.4829, 'learning_rate': 1.6188784524278455e-05, 'epoch': 0.31}
+
31%|███ | 3693/11952 [2:21:53<13:06:05, 5.71s/it]
31%|███ | 3694/11952 [2:21:59<13:23:34, 5.84s/it]
{'loss': 0.4916, 'learning_rate': 1.6186655702692162e-05, 'epoch': 0.31}
+
31%|███ | 3694/11952 [2:21:59<13:23:34, 5.84s/it]
31%|███ | 3695/11952 [2:22:05<13:24:19, 5.84s/it]
{'loss': 0.5002, 'learning_rate': 1.6184526426783607e-05, 'epoch': 0.31}
+
31%|███ | 3695/11952 [2:22:05<13:24:19, 5.84s/it]
31%|███ | 3696/11952 [2:22:10<13:22:55, 5.84s/it]
{'loss': 0.4863, 'learning_rate': 1.618239669670915e-05, 'epoch': 0.31}
+
31%|███ | 3696/11952 [2:22:10<13:22:55, 5.84s/it]
31%|███ | 3697/11952 [2:22:16<13:28:01, 5.87s/it]
{'loss': 0.5061, 'learning_rate': 1.61802665126252e-05, 'epoch': 0.31}
+
31%|███ | 3697/11952 [2:22:16<13:28:01, 5.87s/it]
31%|███ | 3698/11952 [2:22:22<13:28:12, 5.88s/it]
{'loss': 0.4785, 'learning_rate': 1.6178135874688183e-05, 'epoch': 0.31}
+
31%|███ | 3698/11952 [2:22:22<13:28:12, 5.88s/it]
31%|███ | 3699/11952 [2:22:28<13:30:02, 5.89s/it]
{'loss': 0.5046, 'learning_rate': 1.6176004783054556e-05, 'epoch': 0.31}
+
31%|███ | 3699/11952 [2:22:28<13:30:02, 5.89s/it]3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...7
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
31%|███ | 3700/11952 [2:22:34<13:19:49, 5.82s/it]
{'loss': 0.5005, 'learning_rate': 1.6173873237880832e-05, 'epoch': 0.31}
+
31%|███ | 3700/11952 [2:22:34<13:19:49, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
31%|███ | 3701/11952 [2:23:07<32:04:06, 13.99s/it]
{'loss': 0.4856, 'learning_rate': 1.6171741239323537e-05, 'epoch': 0.31}
+
31%|███ | 3701/11952 [2:23:07<32:04:06, 13.99s/it]
31%|███ | 3702/11952 [2:23:13<26:33:20, 11.59s/it]
{'loss': 0.5233, 'learning_rate': 1.6169608787539234e-05, 'epoch': 0.31}
+
31%|███ | 3702/11952 [2:23:13<26:33:20, 11.59s/it]
31%|███ | 3703/11952 [2:23:19<22:40:12, 9.89s/it]
{'loss': 0.4767, 'learning_rate': 1.6167475882684522e-05, 'epoch': 0.31}
+
31%|███ | 3703/11952 [2:23:19<22:40:12, 9.89s/it]
31%|███ | 3704/11952 [2:23:25<19:53:32, 8.68s/it]
{'loss': 0.5088, 'learning_rate': 1.6165342524916035e-05, 'epoch': 0.31}
+
31%|███ | 3704/11952 [2:23:25<19:53:32, 8.68s/it]
31%|███ | 3705/11952 [2:23:31<18:02:41, 7.88s/it]
{'loss': 0.5114, 'learning_rate': 1.6163208714390437e-05, 'epoch': 0.31}
+
31%|███ | 3705/11952 [2:23:31<18:02:41, 7.88s/it]
31%|███ | 3706/11952 [2:23:37<16:38:19, 7.26s/it]
{'loss': 0.503, 'learning_rate': 1.6161074451264425e-05, 'epoch': 0.31}
+
31%|███ | 3706/11952 [2:23:37<16:38:19, 7.26s/it]
31%|███ | 3707/11952 [2:23:43<15:44:00, 6.87s/it]
{'loss': 0.4942, 'learning_rate': 1.615893973569473e-05, 'epoch': 0.31}
+
31%|███ | 3707/11952 [2:23:43<15:44:00, 6.87s/it]
31%|███ | 3708/11952 [2:23:48<14:57:44, 6.53s/it]
{'loss': 0.4998, 'learning_rate': 1.615680456783812e-05, 'epoch': 0.31}
+
31%|███ | 3708/11952 [2:23:48<14:57:44, 6.53s/it]
31%|███ | 3709/11952 [2:23:54<14:21:18, 6.27s/it]
{'loss': 0.5169, 'learning_rate': 1.615466894785139e-05, 'epoch': 0.31}
+
31%|███ | 3709/11952 [2:23:54<14:21:18, 6.27s/it]
31%|███ | 3710/11952 [2:24:00<13:53:26, 6.07s/it]
{'loss': 0.4753, 'learning_rate': 1.6152532875891372e-05, 'epoch': 0.31}
+
31%|███ | 3710/11952 [2:24:00<13:53:26, 6.07s/it]
31%|███ | 3711/11952 [2:24:05<13:38:39, 5.96s/it]
{'loss': 0.481, 'learning_rate': 1.6150396352114926e-05, 'epoch': 0.31}
+
31%|███ | 3711/11952 [2:24:05<13:38:39, 5.96s/it]
31%|███ | 3712/11952 [2:24:11<13:25:37, 5.87s/it]
{'loss': 0.4966, 'learning_rate': 1.6148259376678957e-05, 'epoch': 0.31}
+
31%|███ | 3712/11952 [2:24:11<13:25:37, 5.87s/it]
31%|███ | 3713/11952 [2:24:17<13:27:08, 5.88s/it]
{'loss': 0.5167, 'learning_rate': 1.6146121949740393e-05, 'epoch': 0.31}
+
31%|███ | 3713/11952 [2:24:17<13:27:08, 5.88s/it]
31%|███ | 3714/11952 [2:24:23<13:37:45, 5.96s/it]
{'loss': 0.4961, 'learning_rate': 1.6143984071456197e-05, 'epoch': 0.31}
+
31%|███ | 3714/11952 [2:24:23<13:37:45, 5.96s/it]
31%|███ | 3715/11952 [2:24:29<13:43:37, 6.00s/it]
{'loss': 0.5012, 'learning_rate': 1.614184574198336e-05, 'epoch': 0.31}
+
31%|███ | 3715/11952 [2:24:29<13:43:37, 6.00s/it]
31%|███ | 3716/11952 [2:24:35<13:44:29, 6.01s/it]
{'loss': 0.4894, 'learning_rate': 1.613970696147892e-05, 'epoch': 0.31}
+
31%|███ | 3716/11952 [2:24:35<13:44:29, 6.01s/it]
31%|███ | 3717/11952 [2:24:41<13:41:49, 5.99s/it]
{'loss': 0.4937, 'learning_rate': 1.613756773009994e-05, 'epoch': 0.31}
+
31%|███ | 3717/11952 [2:24:41<13:41:49, 5.99s/it]
31%|███ | 3718/11952 [2:24:47<13:28:47, 5.89s/it]
{'loss': 0.4853, 'learning_rate': 1.6135428048003513e-05, 'epoch': 0.31}
+
31%|███ | 3718/11952 [2:24:47<13:28:47, 5.89s/it]
31%|███ | 3719/11952 [2:24:52<13:18:18, 5.82s/it]
{'loss': 0.5156, 'learning_rate': 1.6133287915346772e-05, 'epoch': 0.31}
+
31%|███ | 3719/11952 [2:24:52<13:18:18, 5.82s/it]
31%|███ | 3720/11952 [2:24:58<13:19:55, 5.83s/it]
{'loss': 0.4906, 'learning_rate': 1.6131147332286872e-05, 'epoch': 0.31}
+
31%|███ | 3720/11952 [2:24:58<13:19:55, 5.83s/it]
31%|███ | 3721/11952 [2:25:04<13:12:46, 5.78s/it]
{'loss': 0.4942, 'learning_rate': 1.6129006298981015e-05, 'epoch': 0.31}
+
31%|███ | 3721/11952 [2:25:04<13:12:46, 5.78s/it]
31%|███ | 3722/11952 [2:25:09<13:07:10, 5.74s/it]
{'loss': 0.5072, 'learning_rate': 1.6126864815586427e-05, 'epoch': 0.31}
+
31%|███ | 3722/11952 [2:25:09<13:07:10, 5.74s/it]
31%|███ | 3723/11952 [2:25:16<13:24:43, 5.87s/it]
{'loss': 0.5006, 'learning_rate': 1.6124722882260372e-05, 'epoch': 0.31}
+
31%|███ | 3723/11952 [2:25:16<13:24:43, 5.87s/it]
31%|███ | 3724/11952 [2:25:22<13:27:36, 5.89s/it]
{'loss': 0.4895, 'learning_rate': 1.6122580499160144e-05, 'epoch': 0.31}
+
31%|███ | 3724/11952 [2:25:22<13:27:36, 5.89s/it]
31%|███ | 3725/11952 [2:25:27<13:25:19, 5.87s/it]
{'loss': 0.5041, 'learning_rate': 1.6120437666443067e-05, 'epoch': 0.31}
+
31%|███ | 3725/11952 [2:25:27<13:25:19, 5.87s/it]WARNING: tokenization mismatch: 1 vs. 1419. [[{'from': 'human', 'value': 'ASSISTANT: You are an innovative tax advisory firm with the following knowledge and traits.\n\nKNOWLEDGE: Tax advisor, junior tax advisor, senior tax advisor, financial strategist, tax regulations.\n\nTRAITS: Empathy, innovation, solution orientation, professionalism, communication, client focus.\n\nTASK: Use your knowledge to develop an internal strategy document. We are a tax advisory firm looking to identify 10 creative ways to improve client satisfaction and loyalty. Focus on ideas that are tailored to the needs of tax advisors and enhance the overall client experience.\n\nOUTPUT: A table in German containing 10 creative strategies to improve client satisfaction and loyalty for a tax advisory firm, including a brief description for each.'}, {'from': 'gpt', 'value': 'Tabelle: 10 kreative Strategien zur Steigerung der Kundenzufriedenheit und -loyalität in einer Steuerberatungskanzlei\n\n| Nr. | Strategie | Beschreibung |\n| --- | --- | --- |\n| 1 | Personalisierter Service | Jeder Kunde erhält einen dedizierten Steuerberater, der auf seine individuellen Bedürfnisse und Anliegen eingeht. |\n| 2 | Proaktive Steuerplanung | Regelmäßige Updates und Empfehlungen zur Steueroptimierung, basierend auf aktuellen Gesetzesänderungen und Kundenzielen. |\n| 3 | Umfassende Schulungsangebote | Kostenlose Workshops und Webinare, um das Steuerwissen der Kunden zu erweitern und den Umgang mit Steuerthemen zu erleichtern. |\n| 4 | Digitale Plattform | Eine benutzerfreundliche Online-Plattform, die den Kunden den Zugriff auf ihre Steuerdokumente und den Kontakt zum Berater erleichtert. |\n| 5 | Einführung von Steuer-Coaching | Persönliche Coaching-Sitzungen, um den Kunden dabei zu unterstützen, ihre steuerlichen Ziele und Möglichkeiten besser zu verstehen. |\n| 6 | Schnelle Reaktionszeiten | Verbindliches Versprechen, innerhalb von 24 Stunden auf Kundenanfragen zu reagieren, um eine effiziente Kommunikation zu gewährleisten. |\n| 7 | Transparente Preisgestaltung | Klare und faire Preisstrukturen, die den Kunden im Voraus bekannt sind, um böse Überraschungen zu vermeiden. |\n| 8 | Individuelle Jahresgespräche | Regelmäßige persönliche Jahresgespräche, um auf die Bedürfnisse und Ziele der Kunden einzugehen und die Zusammenarbeit zu stärken. |\n| 9 | Kunden-Feedback-System | Einrichtung eines einfachen Feedback-Systems, um Kundenmeinungen und Verbesserungsvorschläge aktiv einzuholen und umzusetzen. |\n| 10 | Steuer-Newsletter und Informationsangebot | Monatlicher Newsletter mit aktuellen Steuerinformationen und Tipps, der den Kunden einen Mehrwert bietet und sie auf dem Laufenden hält. |'}, {'from': 'human', 'value': 'Bitte etwas kreativer und auf bezugnehmend auf die zwischenmenschliche Ebene.'}, {'from': 'gpt', 'value': 'Tabelle: 10 kreative Strategien zur Steigerung der Kundenzufriedenheit und -loyalität in einer Steuerberatungskanzlei mit Fokus auf zwischenmenschlicher Ebene\n\n| Nr. | Strategie | Beschreibung |\n| --- | --- | --- |\n| 1 | Kunden-Events | Organisation von regelmäßigen, informellen Veranstaltungen, um den persönlichen Kontakt zwischen Klienten und Beratern zu fördern. |\n| 2 | Persönliche Geburtstagsgrüße | Individuelle Geburtstagskarten oder -nachrichten für jeden Kunden, um Wertschätzung zu zeigen und Beziehungen zu stärken. |\n| 3 | Kundenbefragung & Anpassung | Aktives Einholen von Kundenmeinungen zur individuellen Betreuung und Anpassung unserer Leistungen entsprechend der Kundenbedürfnisse. |\n| 4 | Teamvorstellung & Empathie | Vorstellung unserer Berater auf der Firmenwebsite und in sozialen Medien, um eine persönliche und empathische Beziehung zum Kunden aufzubauen. |\n| 5 | Kunden-Mentoring-Programm | Schaffung eines Programms, bei dem langjährige Kunden als Mentoren für Neukunden fungieren, um Vertrauen und Loyalität zu fördern. |\n| 6 | "Tag der offenen Tür" | Einladung der Kunden zu einem "Tag der offenen Tür" in unserer Kanzlei, um ihnen einen persönlichen Einblick in unsere Arbeitsweise zu geben. |\n| 7 | Individuelle Erfolgsgeschichten | Erstellung von individuellen Erfolgsgeschichten für jeden Kunden, um ihre steuerlichen Erfolge hervorzuheben und ihre Loyalität zu stärken. |\n| 8 | Gemeinsame soziale Projekte | Zusammenarbeit mit Kunden an sozialen Projekten und Spendenaktionen, um gemeinsame Werte zu teilen und die Zusammenarbeit zu fördern. |\n| 9 | Flexibilität in der Kommunikation | Anbieten verschiedener Kommunikationswege (Telefon, E-Mail, Videoanruf, etc.), um auf die individuellen Bedürfnisse der Kunden einzugehen. |\n| 10 | Jährliches Kunden-Dankeschön | Überraschung der Kunden mit einer kleinen Aufmerksamkeit oder einem Dankeschön-Event, um die Wertschätzung für ihre Treue auszudrücken. |'}]] (ignored)
+
31%|███ | 3726/11952 [2:25:33<13:18:55, 5.83s/it]
{'loss': 0.4864, 'learning_rate': 1.6118294384266506e-05, 'epoch': 0.31}
+
31%|███ | 3726/11952 [2:25:33<13:18:55, 5.83s/it]
31%|███ | 3727/11952 [2:25:39<13:18:27, 5.82s/it]
{'loss': 0.4983, 'learning_rate': 1.6116150652787852e-05, 'epoch': 0.31}
+
31%|███ | 3727/11952 [2:25:39<13:18:27, 5.82s/it]
31%|███ | 3728/11952 [2:25:45<13:18:38, 5.83s/it]
{'loss': 0.5044, 'learning_rate': 1.6114006472164535e-05, 'epoch': 0.31}
+
31%|███ | 3728/11952 [2:25:45<13:18:38, 5.83s/it]
31%|███ | 3729/11952 [2:25:51<13:22:26, 5.86s/it]
{'loss': 0.4779, 'learning_rate': 1.6111861842554014e-05, 'epoch': 0.31}
+
31%|███ | 3729/11952 [2:25:51<13:22:26, 5.86s/it]
31%|███ | 3730/11952 [2:25:57<13:21:10, 5.85s/it]
{'loss': 0.4895, 'learning_rate': 1.6109716764113778e-05, 'epoch': 0.31}
+
31%|███ | 3730/11952 [2:25:57<13:21:10, 5.85s/it]
31%|███ | 3731/11952 [2:26:02<13:17:08, 5.82s/it]
{'loss': 0.4795, 'learning_rate': 1.6107571237001356e-05, 'epoch': 0.31}
+
31%|███ | 3731/11952 [2:26:02<13:17:08, 5.82s/it]
31%|███ | 3732/11952 [2:26:08<13:16:36, 5.81s/it]
{'loss': 0.4991, 'learning_rate': 1.6105425261374305e-05, 'epoch': 0.31}
+
31%|███ | 3732/11952 [2:26:08<13:16:36, 5.81s/it]
31%|███ | 3733/11952 [2:26:14<13:07:52, 5.75s/it]
{'loss': 0.4792, 'learning_rate': 1.6103278837390218e-05, 'epoch': 0.31}
+
31%|███ | 3733/11952 [2:26:14<13:07:52, 5.75s/it]
31%|███ | 3734/11952 [2:26:20<13:18:08, 5.83s/it]
{'loss': 0.4891, 'learning_rate': 1.6101131965206714e-05, 'epoch': 0.31}
+
31%|███ | 3734/11952 [2:26:20<13:18:08, 5.83s/it]
31%|███▏ | 3735/11952 [2:26:26<13:31:31, 5.93s/it]
{'loss': 0.5137, 'learning_rate': 1.6098984644981463e-05, 'epoch': 0.31}
+
31%|███▏ | 3735/11952 [2:26:26<13:31:31, 5.93s/it]
31%|███▏ | 3736/11952 [2:26:32<13:40:33, 5.99s/it]
{'loss': 0.5098, 'learning_rate': 1.6096836876872143e-05, 'epoch': 0.31}
+
31%|███▏ | 3736/11952 [2:26:32<13:40:33, 5.99s/it]
31%|███▏ | 3737/11952 [2:26:38<13:30:23, 5.92s/it]
{'loss': 0.5053, 'learning_rate': 1.6094688661036483e-05, 'epoch': 0.31}
+
31%|███▏ | 3737/11952 [2:26:38<13:30:23, 5.92s/it]
31%|███▏ | 3738/11952 [2:26:43<13:19:02, 5.84s/it]
{'loss': 0.4915, 'learning_rate': 1.6092539997632236e-05, 'epoch': 0.31}
+
31%|███▏ | 3738/11952 [2:26:43<13:19:02, 5.84s/it]
31%|███▏ | 3739/11952 [2:26:49<13:17:26, 5.83s/it]
{'loss': 0.4916, 'learning_rate': 1.609039088681719e-05, 'epoch': 0.31}
+
31%|███▏ | 3739/11952 [2:26:49<13:17:26, 5.83s/it]
31%|███▏ | 3740/11952 [2:26:55<13:12:23, 5.79s/it]
{'loss': 0.484, 'learning_rate': 1.6088241328749172e-05, 'epoch': 0.31}
+
31%|███▏ | 3740/11952 [2:26:55<13:12:23, 5.79s/it]
31%|███▏ | 3741/11952 [2:27:00<13:02:53, 5.72s/it]
{'loss': 0.5012, 'learning_rate': 1.6086091323586034e-05, 'epoch': 0.31}
+
31%|███▏ | 3741/11952 [2:27:00<13:02:53, 5.72s/it]
31%|███▏ | 3742/11952 [2:27:06<12:58:37, 5.69s/it]
{'loss': 0.4669, 'learning_rate': 1.6083940871485663e-05, 'epoch': 0.31}
+
31%|███▏ | 3742/11952 [2:27:06<12:58:37, 5.69s/it]
31%|███▏ | 3743/11952 [2:27:13<13:28:52, 5.91s/it]
{'loss': 0.4923, 'learning_rate': 1.608178997260598e-05, 'epoch': 0.31}
+
31%|███▏ | 3743/11952 [2:27:13<13:28:52, 5.91s/it]
31%|███▏ | 3744/11952 [2:27:18<13:30:19, 5.92s/it]
{'loss': 0.4927, 'learning_rate': 1.6079638627104937e-05, 'epoch': 0.31}
+
31%|███▏ | 3744/11952 [2:27:18<13:30:19, 5.92s/it]
31%|███▏ | 3745/11952 [2:27:24<13:31:40, 5.93s/it]
{'loss': 0.4755, 'learning_rate': 1.6077486835140518e-05, 'epoch': 0.31}
+
31%|███▏ | 3745/11952 [2:27:24<13:31:40, 5.93s/it]
31%|███▏ | 3746/11952 [2:27:30<13:18:39, 5.84s/it]
{'loss': 0.4855, 'learning_rate': 1.6075334596870746e-05, 'epoch': 0.31}
+
31%|███▏ | 3746/11952 [2:27:30<13:18:39, 5.84s/it]
31%|███▏ | 3747/11952 [2:27:35<13:02:28, 5.72s/it]
{'loss': 0.4979, 'learning_rate': 1.607318191245367e-05, 'epoch': 0.31}
+
31%|███▏ | 3747/11952 [2:27:35<13:02:28, 5.72s/it]
31%|███▏ | 3748/11952 [2:27:41<13:05:53, 5.75s/it]
{'loss': 0.4754, 'learning_rate': 1.607102878204738e-05, 'epoch': 0.31}
+
31%|███▏ | 3748/11952 [2:27:41<13:05:53, 5.75s/it]
31%|███▏ | 3749/11952 [2:27:47<13:21:33, 5.86s/it]
{'loss': 0.5086, 'learning_rate': 1.6068875205809978e-05, 'epoch': 0.31}
+
31%|███▏ | 3749/11952 [2:27:47<13:21:33, 5.86s/it]3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 5AutoResumeHook: Checking whether to suspend...2
+ 6 AutoResumeHook: Checking whether to suspend...0 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
+ AutoResumeHook: Checking whether to suspend...
+
31%|███▏ | 3750/11952 [2:27:53<13:26:21, 5.90s/it]
{'loss': 0.5113, 'learning_rate': 1.606672118389963e-05, 'epoch': 0.31}
+
31%|███▏ | 3750/11952 [2:27:53<13:26:21, 5.90s/it]
31%|███▏ | 3751/11952 [2:27:59<13:30:15, 5.93s/it]
{'loss': 0.5014, 'learning_rate': 1.6064566716474506e-05, 'epoch': 0.31}
+
31%|███▏ | 3751/11952 [2:27:59<13:30:15, 5.93s/it]
31%|███▏ | 3752/11952 [2:28:05<13:31:20, 5.94s/it]
{'loss': 0.4899, 'learning_rate': 1.606241180369283e-05, 'epoch': 0.31}
+
31%|███▏ | 3752/11952 [2:28:05<13:31:20, 5.94s/it]
31%|███▏ | 3753/11952 [2:28:11<13:29:01, 5.92s/it]
{'loss': 0.5102, 'learning_rate': 1.606025644571285e-05, 'epoch': 0.31}
+
31%|███▏ | 3753/11952 [2:28:11<13:29:01, 5.92s/it]
31%|███▏ | 3754/11952 [2:28:17<13:31:02, 5.94s/it]
{'loss': 0.4875, 'learning_rate': 1.6058100642692837e-05, 'epoch': 0.31}
+
31%|███▏ | 3754/11952 [2:28:17<13:31:02, 5.94s/it]
31%|███▏ | 3755/11952 [2:28:23<13:39:57, 6.00s/it]
{'loss': 0.5025, 'learning_rate': 1.6055944394791113e-05, 'epoch': 0.31}
+
31%|███▏ | 3755/11952 [2:28:23<13:39:57, 6.00s/it]
31%|███▏ | 3756/11952 [2:28:29<13:34:19, 5.96s/it]
{'loss': 0.4748, 'learning_rate': 1.605378770216602e-05, 'epoch': 0.31}
+
31%|███▏ | 3756/11952 [2:28:29<13:34:19, 5.96s/it]
31%|███▏ | 3757/11952 [2:28:35<13:17:01, 5.84s/it]
{'loss': 0.4893, 'learning_rate': 1.605163056497594e-05, 'epoch': 0.31}
+
31%|███▏ | 3757/11952 [2:28:35<13:17:01, 5.84s/it]
31%|███▏ | 3758/11952 [2:28:41<13:29:15, 5.93s/it]
{'loss': 0.4999, 'learning_rate': 1.6049472983379285e-05, 'epoch': 0.31}
+
31%|███▏ | 3758/11952 [2:28:41<13:29:15, 5.93s/it]
31%|███▏ | 3759/11952 [2:28:47<13:26:29, 5.91s/it]
{'loss': 0.5149, 'learning_rate': 1.6047314957534487e-05, 'epoch': 0.31}
+
31%|███▏ | 3759/11952 [2:28:47<13:26:29, 5.91s/it]
31%|███▏ | 3760/11952 [2:28:52<13:17:05, 5.84s/it]
{'loss': 0.4722, 'learning_rate': 1.604515648760004e-05, 'epoch': 0.31}
+
31%|███▏ | 3760/11952 [2:28:52<13:17:05, 5.84s/it]
31%|███▏ | 3761/11952 [2:28:58<13:19:21, 5.86s/it]
{'loss': 0.5037, 'learning_rate': 1.6042997573734437e-05, 'epoch': 0.31}
+
31%|███▏ | 3761/11952 [2:28:58<13:19:21, 5.86s/it]
31%|███▏ | 3762/11952 [2:29:04<13:15:58, 5.83s/it]
{'loss': 0.4684, 'learning_rate': 1.6040838216096233e-05, 'epoch': 0.31}
+
31%|███▏ | 3762/11952 [2:29:04<13:15:58, 5.83s/it]
31%|███▏ | 3763/11952 [2:29:10<13:10:31, 5.79s/it]
{'loss': 0.5232, 'learning_rate': 1.6038678414843994e-05, 'epoch': 0.31}
+
31%|███▏ | 3763/11952 [2:29:10<13:10:31, 5.79s/it]
31%|███▏ | 3764/11952 [2:29:16<13:15:55, 5.83s/it]
{'loss': 0.4807, 'learning_rate': 1.6036518170136326e-05, 'epoch': 0.31}
+
31%|███▏ | 3764/11952 [2:29:16<13:15:55, 5.83s/it]
32%|███▏ | 3765/11952 [2:29:22<13:14:33, 5.82s/it]
{'loss': 0.4972, 'learning_rate': 1.603435748213187e-05, 'epoch': 0.31}
+
32%|███▏ | 3765/11952 [2:29:22<13:14:33, 5.82s/it]
32%|███▏ | 3766/11952 [2:29:27<13:07:41, 5.77s/it]
{'loss': 0.4843, 'learning_rate': 1.6032196350989306e-05, 'epoch': 0.32}
+
32%|███▏ | 3766/11952 [2:29:27<13:07:41, 5.77s/it]
32%|███▏ | 3767/11952 [2:29:33<13:19:58, 5.86s/it]
{'loss': 0.4668, 'learning_rate': 1.603003477686733e-05, 'epoch': 0.32}
+
32%|███▏ | 3767/11952 [2:29:33<13:19:58, 5.86s/it]
32%|███▏ | 3768/11952 [2:29:39<13:07:34, 5.77s/it]
{'loss': 0.4949, 'learning_rate': 1.6027872759924678e-05, 'epoch': 0.32}
+
32%|███▏ | 3768/11952 [2:29:39<13:07:34, 5.77s/it]
32%|███▏ | 3769/11952 [2:29:44<13:02:16, 5.74s/it]
{'loss': 0.4948, 'learning_rate': 1.6025710300320124e-05, 'epoch': 0.32}
+
32%|███▏ | 3769/11952 [2:29:45<13:02:16, 5.74s/it]
32%|███▏ | 3770/11952 [2:29:50<13:00:40, 5.72s/it]
{'loss': 0.4746, 'learning_rate': 1.6023547398212467e-05, 'epoch': 0.32}
+
32%|███▏ | 3770/11952 [2:29:50<13:00:40, 5.72s/it]
32%|███▏ | 3771/11952 [2:29:56<12:55:02, 5.68s/it]
{'loss': 0.476, 'learning_rate': 1.6021384053760546e-05, 'epoch': 0.32}
+
32%|███▏ | 3771/11952 [2:29:56<12:55:02, 5.68s/it]
32%|███▏ | 3772/11952 [2:30:02<13:00:42, 5.73s/it]
{'loss': 0.4951, 'learning_rate': 1.6019220267123223e-05, 'epoch': 0.32}
+
32%|███▏ | 3772/11952 [2:30:02<13:00:42, 5.73s/it]
32%|███▏ | 3773/11952 [2:30:07<13:00:17, 5.72s/it]
{'loss': 0.4662, 'learning_rate': 1.60170560384594e-05, 'epoch': 0.32}
+
32%|███▏ | 3773/11952 [2:30:07<13:00:17, 5.72s/it]
32%|███▏ | 3774/11952 [2:30:13<13:06:31, 5.77s/it]
{'loss': 0.4972, 'learning_rate': 1.601489136792801e-05, 'epoch': 0.32}
+
32%|███▏ | 3774/11952 [2:30:13<13:06:31, 5.77s/it]
32%|███▏ | 3775/11952 [2:30:19<13:03:35, 5.75s/it]
{'loss': 0.4956, 'learning_rate': 1.6012726255688013e-05, 'epoch': 0.32}
+
32%|███▏ | 3775/11952 [2:30:19<13:03:35, 5.75s/it]
32%|███▏ | 3776/11952 [2:30:25<13:11:30, 5.81s/it]
{'loss': 0.4779, 'learning_rate': 1.6010560701898405e-05, 'epoch': 0.32}
+
32%|███▏ | 3776/11952 [2:30:25<13:11:30, 5.81s/it]
32%|███▏ | 3777/11952 [2:30:31<13:22:41, 5.89s/it]
{'loss': 0.5058, 'learning_rate': 1.6008394706718224e-05, 'epoch': 0.32}
+
32%|███▏ | 3777/11952 [2:30:31<13:22:41, 5.89s/it]
32%|███▏ | 3778/11952 [2:30:37<13:26:14, 5.92s/it]
{'loss': 0.5015, 'learning_rate': 1.6006228270306526e-05, 'epoch': 0.32}
+
32%|███▏ | 3778/11952 [2:30:37<13:26:14, 5.92s/it]
32%|███▏ | 3779/11952 [2:30:43<13:12:51, 5.82s/it]
{'loss': 0.4791, 'learning_rate': 1.6004061392822407e-05, 'epoch': 0.32}
+
32%|███▏ | 3779/11952 [2:30:43<13:12:51, 5.82s/it]
32%|███▏ | 3780/11952 [2:30:48<13:14:45, 5.84s/it]
{'loss': 0.4736, 'learning_rate': 1.6001894074424987e-05, 'epoch': 0.32}
+
32%|███▏ | 3780/11952 [2:30:48<13:14:45, 5.84s/it]
32%|███▏ | 3781/11952 [2:30:54<13:14:39, 5.84s/it]
{'loss': 0.4803, 'learning_rate': 1.5999726315273435e-05, 'epoch': 0.32}
+
32%|███▏ | 3781/11952 [2:30:54<13:14:39, 5.84s/it]
32%|███▏ | 3782/11952 [2:31:00<13:22:00, 5.89s/it]
{'loss': 0.5038, 'learning_rate': 1.599755811552693e-05, 'epoch': 0.32}
+
32%|███▏ | 3782/11952 [2:31:00<13:22:00, 5.89s/it]
32%|███▏ | 3783/11952 [2:31:06<13:20:17, 5.88s/it]
{'loss': 0.4888, 'learning_rate': 1.5995389475344715e-05, 'epoch': 0.32}
+
32%|███▏ | 3783/11952 [2:31:06<13:20:17, 5.88s/it]
32%|███▏ | 3784/11952 [2:31:12<13:13:57, 5.83s/it]
{'loss': 0.4943, 'learning_rate': 1.5993220394886024e-05, 'epoch': 0.32}
+
32%|███▏ | 3784/11952 [2:31:12<13:13:57, 5.83s/it]
32%|███▏ | 3785/11952 [2:31:18<13:15:22, 5.84s/it]
{'loss': 0.5088, 'learning_rate': 1.5991050874310156e-05, 'epoch': 0.32}
+
32%|███▏ | 3785/11952 [2:31:18<13:15:22, 5.84s/it]
32%|███▏ | 3786/11952 [2:31:23<13:05:14, 5.77s/it]
{'loss': 0.4833, 'learning_rate': 1.5988880913776434e-05, 'epoch': 0.32}
+
32%|███▏ | 3786/11952 [2:31:23<13:05:14, 5.77s/it]
32%|███▏ | 3787/11952 [2:31:29<13:06:58, 5.78s/it]
{'loss': 0.499, 'learning_rate': 1.5986710513444205e-05, 'epoch': 0.32}
+
32%|███▏ | 3787/11952 [2:31:29<13:06:58, 5.78s/it]
32%|███▏ | 3788/11952 [2:31:35<13:16:39, 5.85s/it]
{'loss': 0.4909, 'learning_rate': 1.5984539673472856e-05, 'epoch': 0.32}
+
32%|███▏ | 3788/11952 [2:31:35<13:16:39, 5.85s/it]
32%|███▏ | 3789/11952 [2:31:41<13:16:50, 5.86s/it]
{'loss': 0.4929, 'learning_rate': 1.5982368394021804e-05, 'epoch': 0.32}
+
32%|███▏ | 3789/11952 [2:31:41<13:16:50, 5.86s/it]
32%|███▏ | 3790/11952 [2:31:47<13:22:07, 5.90s/it]
{'loss': 0.4894, 'learning_rate': 1.5980196675250504e-05, 'epoch': 0.32}
+
32%|███▏ | 3790/11952 [2:31:47<13:22:07, 5.90s/it]
32%|███▏ | 3791/11952 [2:31:53<13:25:45, 5.92s/it]
{'loss': 0.4776, 'learning_rate': 1.5978024517318428e-05, 'epoch': 0.32}
+
32%|███▏ | 3791/11952 [2:31:53<13:25:45, 5.92s/it]
32%|███▏ | 3792/11952 [2:31:59<13:23:20, 5.91s/it]
{'loss': 0.4832, 'learning_rate': 1.5975851920385103e-05, 'epoch': 0.32}
+
32%|███▏ | 3792/11952 [2:31:59<13:23:20, 5.91s/it]
32%|███▏ | 3793/11952 [2:32:05<13:19:29, 5.88s/it]
{'loss': 0.4832, 'learning_rate': 1.5973678884610062e-05, 'epoch': 0.32}
+
32%|███▏ | 3793/11952 [2:32:05<13:19:29, 5.88s/it]
32%|███▏ | 3794/11952 [2:32:11<13:21:02, 5.89s/it]
{'loss': 0.4827, 'learning_rate': 1.597150541015289e-05, 'epoch': 0.32}
+
32%|███▏ | 3794/11952 [2:32:11<13:21:02, 5.89s/it]
32%|███▏ | 3795/11952 [2:32:16<13:13:39, 5.84s/it]
{'loss': 0.4805, 'learning_rate': 1.5969331497173203e-05, 'epoch': 0.32}
+
32%|███▏ | 3795/11952 [2:32:16<13:13:39, 5.84s/it]
32%|███▏ | 3796/11952 [2:32:22<13:05:13, 5.78s/it]
{'loss': 0.4961, 'learning_rate': 1.5967157145830638e-05, 'epoch': 0.32}
+
32%|███▏ | 3796/11952 [2:32:22<13:05:13, 5.78s/it]
32%|███▏ | 3797/11952 [2:32:28<13:07:21, 5.79s/it]
{'loss': 0.5165, 'learning_rate': 1.596498235628487e-05, 'epoch': 0.32}
+
32%|███▏ | 3797/11952 [2:32:28<13:07:21, 5.79s/it]
32%|███▏ | 3798/11952 [2:32:34<13:06:26, 5.79s/it]
{'loss': 0.4927, 'learning_rate': 1.5962807128695606e-05, 'epoch': 0.32}
+
32%|███▏ | 3798/11952 [2:32:34<13:06:26, 5.79s/it]
32%|███▏ | 3799/11952 [2:32:39<13:13:34, 5.84s/it]
{'loss': 0.5033, 'learning_rate': 1.5960631463222592e-05, 'epoch': 0.32}
+
32%|███▏ | 3799/11952 [2:32:39<13:13:34, 5.84s/it]3 AutoResumeHook: Checking whether to suspend...
+41 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
32%|███▏ | 3800/11952 [2:32:45<13:08:20, 5.80s/it]
{'loss': 0.4744, 'learning_rate': 1.595845536002559e-05, 'epoch': 0.32}
+
32%|███▏ | 3800/11952 [2:32:45<13:08:20, 5.80s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
32%|███▏ | 3801/11952 [2:33:18<31:21:20, 13.85s/it]
{'loss': 0.4675, 'learning_rate': 1.5956278819264417e-05, 'epoch': 0.32}
+
32%|███▏ | 3801/11952 [2:33:18<31:21:20, 13.85s/it]
32%|███▏ | 3802/11952 [2:33:23<25:45:23, 11.38s/it]
{'loss': 0.4773, 'learning_rate': 1.5954101841098895e-05, 'epoch': 0.32}
+
32%|███▏ | 3802/11952 [2:33:23<25:45:23, 11.38s/it]
32%|███▏ | 3803/11952 [2:33:29<21:51:58, 9.66s/it]
{'loss': 0.4848, 'learning_rate': 1.59519244256889e-05, 'epoch': 0.32}
+
32%|███▏ | 3803/11952 [2:33:29<21:51:58, 9.66s/it]
32%|███▏ | 3804/11952 [2:33:35<19:29:17, 8.61s/it]
{'loss': 0.4883, 'learning_rate': 1.5949746573194334e-05, 'epoch': 0.32}
+
32%|███▏ | 3804/11952 [2:33:35<19:29:17, 8.61s/it]
32%|███▏ | 3805/11952 [2:33:41<17:43:51, 7.84s/it]
{'loss': 0.4869, 'learning_rate': 1.5947568283775125e-05, 'epoch': 0.32}
+
32%|███▏ | 3805/11952 [2:33:41<17:43:51, 7.84s/it]
32%|███▏ | 3806/11952 [2:33:47<16:10:41, 7.15s/it]
{'loss': 0.4972, 'learning_rate': 1.5945389557591237e-05, 'epoch': 0.32}
+
32%|███▏ | 3806/11952 [2:33:47<16:10:41, 7.15s/it]
32%|███▏ | 3807/11952 [2:33:52<15:08:50, 6.69s/it]
{'loss': 0.4711, 'learning_rate': 1.594321039480267e-05, 'epoch': 0.32}
+
32%|███▏ | 3807/11952 [2:33:52<15:08:50, 6.69s/it]
32%|███▏ | 3808/11952 [2:33:58<14:28:29, 6.40s/it]
{'loss': 0.4634, 'learning_rate': 1.5941030795569452e-05, 'epoch': 0.32}
+
32%|███▏ | 3808/11952 [2:33:58<14:28:29, 6.40s/it]
32%|███▏ | 3809/11952 [2:34:04<14:12:16, 6.28s/it]
{'loss': 0.4964, 'learning_rate': 1.5938850760051643e-05, 'epoch': 0.32}
+
32%|███▏ | 3809/11952 [2:34:04<14:12:16, 6.28s/it]
32%|███▏ | 3810/11952 [2:34:10<13:51:57, 6.13s/it]
{'loss': 0.4977, 'learning_rate': 1.5936670288409335e-05, 'epoch': 0.32}
+
32%|███▏ | 3810/11952 [2:34:10<13:51:57, 6.13s/it]
32%|███▏ | 3811/11952 [2:34:16<13:47:21, 6.10s/it]
{'loss': 0.5042, 'learning_rate': 1.5934489380802653e-05, 'epoch': 0.32}
+
32%|███▏ | 3811/11952 [2:34:16<13:47:21, 6.10s/it]
32%|███▏ | 3812/11952 [2:34:22<13:31:05, 5.98s/it]
{'loss': 0.493, 'learning_rate': 1.5932308037391756e-05, 'epoch': 0.32}
+
32%|███▏ | 3812/11952 [2:34:22<13:31:05, 5.98s/it]
32%|███▏ | 3813/11952 [2:34:27<13:22:59, 5.92s/it]
{'loss': 0.4989, 'learning_rate': 1.593012625833683e-05, 'epoch': 0.32}
+
32%|███▏ | 3813/11952 [2:34:27<13:22:59, 5.92s/it]
32%|███▏ | 3814/11952 [2:34:33<13:23:19, 5.92s/it]
{'loss': 0.4855, 'learning_rate': 1.59279440437981e-05, 'epoch': 0.32}
+
32%|███▏ | 3814/11952 [2:34:33<13:23:19, 5.92s/it]
32%|███▏ | 3815/11952 [2:34:39<13:18:59, 5.89s/it]
{'loss': 0.483, 'learning_rate': 1.592576139393581e-05, 'epoch': 0.32}
+
32%|███▏ | 3815/11952 [2:34:39<13:18:59, 5.89s/it]
32%|███▏ | 3816/11952 [2:34:45<13:07:51, 5.81s/it]
{'loss': 0.4849, 'learning_rate': 1.5923578308910254e-05, 'epoch': 0.32}
+
32%|███▏ | 3816/11952 [2:34:45<13:07:51, 5.81s/it]
32%|███▏ | 3817/11952 [2:34:50<13:00:05, 5.75s/it]
{'loss': 0.483, 'learning_rate': 1.592139478888174e-05, 'epoch': 0.32}
+
32%|███▏ | 3817/11952 [2:34:50<13:00:05, 5.75s/it]
32%|███▏ | 3818/11952 [2:34:56<13:01:11, 5.76s/it]
{'loss': 0.511, 'learning_rate': 1.5919210834010628e-05, 'epoch': 0.32}
+
32%|███▏ | 3818/11952 [2:34:56<13:01:11, 5.76s/it]
32%|███▏ | 3819/11952 [2:35:02<13:03:12, 5.78s/it]
{'loss': 0.4953, 'learning_rate': 1.5917026444457288e-05, 'epoch': 0.32}
+
32%|███▏ | 3819/11952 [2:35:02<13:03:12, 5.78s/it]
32%|███▏ | 3820/11952 [2:35:08<12:56:37, 5.73s/it]
{'loss': 0.4849, 'learning_rate': 1.591484162038214e-05, 'epoch': 0.32}
+
32%|███▏ | 3820/11952 [2:35:08<12:56:37, 5.73s/it]
32%|███▏ | 3821/11952 [2:35:13<12:53:43, 5.71s/it]
{'loss': 0.4783, 'learning_rate': 1.5912656361945626e-05, 'epoch': 0.32}
+
32%|███▏ | 3821/11952 [2:35:13<12:53:43, 5.71s/it]
32%|███▏ | 3822/11952 [2:35:19<12:52:00, 5.70s/it]
{'loss': 0.4872, 'learning_rate': 1.5910470669308217e-05, 'epoch': 0.32}
+
32%|███▏ | 3822/11952 [2:35:19<12:52:00, 5.70s/it]
32%|███▏ | 3823/11952 [2:35:25<13:02:16, 5.77s/it]
{'loss': 0.5001, 'learning_rate': 1.5908284542630425e-05, 'epoch': 0.32}
+
32%|███▏ | 3823/11952 [2:35:25<13:02:16, 5.77s/it]
32%|███▏ | 3824/11952 [2:35:30<12:52:52, 5.71s/it]
{'loss': 0.4711, 'learning_rate': 1.5906097982072793e-05, 'epoch': 0.32}
+
32%|███▏ | 3824/11952 [2:35:30<12:52:52, 5.71s/it]
32%|███▏ | 3825/11952 [2:35:36<12:52:10, 5.70s/it]
{'loss': 0.468, 'learning_rate': 1.590391098779589e-05, 'epoch': 0.32}
+
32%|███▏ | 3825/11952 [2:35:36<12:52:10, 5.70s/it]
32%|███▏ | 3826/11952 [2:35:42<13:07:22, 5.81s/it]
{'loss': 0.5036, 'learning_rate': 1.5901723559960322e-05, 'epoch': 0.32}
+
32%|███▏ | 3826/11952 [2:35:42<13:07:22, 5.81s/it]
32%|███▏ | 3827/11952 [2:35:48<13:03:29, 5.79s/it]
{'loss': 0.483, 'learning_rate': 1.5899535698726723e-05, 'epoch': 0.32}
+
32%|███▏ | 3827/11952 [2:35:48<13:03:29, 5.79s/it]
32%|███▏ | 3828/11952 [2:35:54<13:15:16, 5.87s/it]
{'loss': 0.4843, 'learning_rate': 1.5897347404255757e-05, 'epoch': 0.32}
+
32%|███▏ | 3828/11952 [2:35:54<13:15:16, 5.87s/it]
32%|███▏ | 3829/11952 [2:36:00<13:12:48, 5.86s/it]
{'loss': 0.4897, 'learning_rate': 1.589515867670813e-05, 'epoch': 0.32}
+
32%|███▏ | 3829/11952 [2:36:00<13:12:48, 5.86s/it]
32%|███▏ | 3830/11952 [2:36:05<12:58:59, 5.75s/it]
{'loss': 0.4886, 'learning_rate': 1.589296951624457e-05, 'epoch': 0.32}
+
32%|███▏ | 3830/11952 [2:36:05<12:58:59, 5.75s/it]
32%|███▏ | 3831/11952 [2:36:11<12:52:42, 5.71s/it]
{'loss': 0.4777, 'learning_rate': 1.5890779923025832e-05, 'epoch': 0.32}
+
32%|███▏ | 3831/11952 [2:36:11<12:52:42, 5.71s/it]
32%|███▏ | 3832/11952 [2:36:17<12:57:26, 5.74s/it]
{'loss': 0.495, 'learning_rate': 1.5888589897212726e-05, 'epoch': 0.32}
+
32%|███▏ | 3832/11952 [2:36:17<12:57:26, 5.74s/it]
32%|███▏ | 3833/11952 [2:36:23<12:56:25, 5.74s/it]
{'loss': 0.4896, 'learning_rate': 1.5886399438966068e-05, 'epoch': 0.32}
+
32%|███▏ | 3833/11952 [2:36:23<12:56:25, 5.74s/it]
32%|███▏ | 3834/11952 [2:36:28<12:56:26, 5.74s/it]
{'loss': 0.4846, 'learning_rate': 1.5884208548446716e-05, 'epoch': 0.32}
+
32%|███▏ | 3834/11952 [2:36:28<12:56:26, 5.74s/it]
32%|███▏ | 3835/11952 [2:36:34<12:58:28, 5.75s/it]
{'loss': 0.4673, 'learning_rate': 1.5882017225815566e-05, 'epoch': 0.32}
+
32%|███▏ | 3835/11952 [2:36:34<12:58:28, 5.75s/it]
32%|███▏ | 3836/11952 [2:36:40<13:08:22, 5.83s/it]
{'loss': 0.4854, 'learning_rate': 1.5879825471233538e-05, 'epoch': 0.32}
+
32%|███▏ | 3836/11952 [2:36:40<13:08:22, 5.83s/it]
32%|███▏ | 3837/11952 [2:36:46<13:01:34, 5.78s/it]
{'loss': 0.4916, 'learning_rate': 1.5877633284861577e-05, 'epoch': 0.32}
+
32%|███▏ | 3837/11952 [2:36:46<13:01:34, 5.78s/it]
32%|███▏ | 3838/11952 [2:36:52<13:13:13, 5.87s/it]
{'loss': 0.4774, 'learning_rate': 1.587544066686068e-05, 'epoch': 0.32}
+
32%|███▏ | 3838/11952 [2:36:52<13:13:13, 5.87s/it]
32%|███▏ | 3839/11952 [2:36:58<13:17:38, 5.90s/it]
{'loss': 0.4825, 'learning_rate': 1.5873247617391854e-05, 'epoch': 0.32}
+
32%|███▏ | 3839/11952 [2:36:58<13:17:38, 5.90s/it]
32%|███▏ | 3840/11952 [2:37:04<13:24:07, 5.95s/it]
{'loss': 0.4933, 'learning_rate': 1.5871054136616154e-05, 'epoch': 0.32}
+
32%|███▏ | 3840/11952 [2:37:04<13:24:07, 5.95s/it]
32%|███▏ | 3841/11952 [2:37:10<13:23:15, 5.94s/it]
{'loss': 0.5059, 'learning_rate': 1.5868860224694656e-05, 'epoch': 0.32}
+
32%|███▏ | 3841/11952 [2:37:10<13:23:15, 5.94s/it]
32%|███▏ | 3842/11952 [2:37:16<13:22:34, 5.94s/it]
{'loss': 0.4819, 'learning_rate': 1.586666588178848e-05, 'epoch': 0.32}
+
32%|███▏ | 3842/11952 [2:37:16<13:22:34, 5.94s/it]
32%|███▏ | 3843/11952 [2:37:21<13:13:35, 5.87s/it]
{'loss': 0.4753, 'learning_rate': 1.5864471108058755e-05, 'epoch': 0.32}
+
32%|███▏ | 3843/11952 [2:37:21<13:13:35, 5.87s/it]
32%|███▏ | 3844/11952 [2:37:27<13:16:12, 5.89s/it]
{'loss': 0.5028, 'learning_rate': 1.586227590366667e-05, 'epoch': 0.32}
+
32%|███▏ | 3844/11952 [2:37:27<13:16:12, 5.89s/it]
32%|███▏ | 3845/11952 [2:37:33<13:13:23, 5.87s/it]
{'loss': 0.5122, 'learning_rate': 1.586008026877342e-05, 'epoch': 0.32}
+
32%|███▏ | 3845/11952 [2:37:33<13:13:23, 5.87s/it]
32%|███▏ | 3846/11952 [2:37:40<13:37:44, 6.05s/it]
{'loss': 0.5066, 'learning_rate': 1.585788420354025e-05, 'epoch': 0.32}
+
32%|███▏ | 3846/11952 [2:37:40<13:37:44, 6.05s/it]
32%|███▏ | 3847/11952 [2:37:46<13:35:22, 6.04s/it]
{'loss': 0.4991, 'learning_rate': 1.5855687708128433e-05, 'epoch': 0.32}
+
32%|███▏ | 3847/11952 [2:37:46<13:35:22, 6.04s/it]
32%|███▏ | 3848/11952 [2:37:51<13:21:12, 5.93s/it]
{'loss': 0.4953, 'learning_rate': 1.5853490782699266e-05, 'epoch': 0.32}
+
32%|███▏ | 3848/11952 [2:37:51<13:21:12, 5.93s/it]
32%|███▏ | 3849/11952 [2:37:57<13:13:22, 5.87s/it]
{'loss': 0.4834, 'learning_rate': 1.5851293427414075e-05, 'epoch': 0.32}
+
32%|███▏ | 3849/11952 [2:37:57<13:13:22, 5.87s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
32%|███▏ | 3850/11952 [2:38:03<13:22:08, 5.94s/it]
{'loss': 0.49, 'learning_rate': 1.584909564243424e-05, 'epoch': 0.32}
+
32%|███▏ | 3850/11952 [2:38:03<13:22:08, 5.94s/it]
32%|███▏ | 3851/11952 [2:38:09<13:09:44, 5.85s/it]
{'loss': 0.4989, 'learning_rate': 1.5846897427921147e-05, 'epoch': 0.32}
+
32%|███▏ | 3851/11952 [2:38:09<13:09:44, 5.85s/it]
32%|███▏ | 3852/11952 [2:38:14<13:03:23, 5.80s/it]
{'loss': 0.481, 'learning_rate': 1.584469878403623e-05, 'epoch': 0.32}
+
32%|███▏ | 3852/11952 [2:38:14<13:03:23, 5.80s/it]
32%|███▏ | 3853/11952 [2:38:20<13:05:36, 5.82s/it]
{'loss': 0.5093, 'learning_rate': 1.5842499710940936e-05, 'epoch': 0.32}
+
32%|███▏ | 3853/11952 [2:38:20<13:05:36, 5.82s/it]
32%|███▏ | 3854/11952 [2:38:26<13:02:55, 5.80s/it]
{'loss': 0.4943, 'learning_rate': 1.5840300208796767e-05, 'epoch': 0.32}
+
32%|███▏ | 3854/11952 [2:38:26<13:02:55, 5.80s/it]
32%|███▏ | 3855/11952 [2:38:32<13:01:11, 5.79s/it]
{'loss': 0.4794, 'learning_rate': 1.5838100277765244e-05, 'epoch': 0.32}
+
32%|███▏ | 3855/11952 [2:38:32<13:01:11, 5.79s/it]
32%|███▏ | 3856/11952 [2:38:38<13:02:28, 5.80s/it]
{'loss': 0.4951, 'learning_rate': 1.5835899918007917e-05, 'epoch': 0.32}
+
32%|███▏ | 3856/11952 [2:38:38<13:02:28, 5.80s/it]
32%|███▏ | 3857/11952 [2:38:44<13:30:59, 6.01s/it]
{'loss': 0.4958, 'learning_rate': 1.5833699129686376e-05, 'epoch': 0.32}
+
32%|███▏ | 3857/11952 [2:38:44<13:30:59, 6.01s/it]
32%|███▏ | 3858/11952 [2:38:50<13:20:35, 5.93s/it]
{'loss': 0.5049, 'learning_rate': 1.5831497912962235e-05, 'epoch': 0.32}
+
32%|███▏ | 3858/11952 [2:38:50<13:20:35, 5.93s/it]
32%|███▏ | 3859/11952 [2:38:56<13:18:37, 5.92s/it]
{'loss': 0.4801, 'learning_rate': 1.5829296267997142e-05, 'epoch': 0.32}
+
32%|███▏ | 3859/11952 [2:38:56<13:18:37, 5.92s/it]
32%|███▏ | 3860/11952 [2:39:02<13:14:21, 5.89s/it]
{'loss': 0.4781, 'learning_rate': 1.582709419495277e-05, 'epoch': 0.32}
+
32%|███▏ | 3860/11952 [2:39:02<13:14:21, 5.89s/it]
32%|███▏ | 3861/11952 [2:39:08<13:20:41, 5.94s/it]
{'loss': 0.5053, 'learning_rate': 1.5824891693990845e-05, 'epoch': 0.32}
+
32%|███▏ | 3861/11952 [2:39:08<13:20:41, 5.94s/it]
32%|███▏ | 3862/11952 [2:39:13<13:14:10, 5.89s/it]
{'loss': 0.5095, 'learning_rate': 1.58226887652731e-05, 'epoch': 0.32}
+
32%|███▏ | 3862/11952 [2:39:13<13:14:10, 5.89s/it]
32%|███▏ | 3863/11952 [2:39:19<13:09:18, 5.85s/it]
{'loss': 0.5, 'learning_rate': 1.582048540896131e-05, 'epoch': 0.32}
+
32%|███▏ | 3863/11952 [2:39:19<13:09:18, 5.85s/it]
32%|███▏ | 3864/11952 [2:39:25<13:10:50, 5.87s/it]
{'loss': 0.4818, 'learning_rate': 1.581828162521728e-05, 'epoch': 0.32}
+
32%|███▏ | 3864/11952 [2:39:25<13:10:50, 5.87s/it]
32%|███▏ | 3865/11952 [2:39:31<13:09:23, 5.86s/it]
{'loss': 0.4957, 'learning_rate': 1.5816077414202848e-05, 'epoch': 0.32}
+
32%|███▏ | 3865/11952 [2:39:31<13:09:23, 5.86s/it]
32%|███▏ | 3866/11952 [2:39:37<12:59:58, 5.79s/it]
{'loss': 0.477, 'learning_rate': 1.5813872776079882e-05, 'epoch': 0.32}
+
32%|███▏ | 3866/11952 [2:39:37<12:59:58, 5.79s/it]
32%|███▏ | 3867/11952 [2:39:42<12:59:54, 5.79s/it]
{'loss': 0.4875, 'learning_rate': 1.581166771101028e-05, 'epoch': 0.32}
+
32%|███▏ | 3867/11952 [2:39:42<12:59:54, 5.79s/it]
32%|███▏ | 3868/11952 [2:39:48<13:02:36, 5.81s/it]
{'loss': 0.4905, 'learning_rate': 1.5809462219155976e-05, 'epoch': 0.32}
+
32%|███▏ | 3868/11952 [2:39:48<13:02:36, 5.81s/it]
32%|███▏ | 3869/11952 [2:39:54<13:06:15, 5.84s/it]
{'loss': 0.4993, 'learning_rate': 1.580725630067893e-05, 'epoch': 0.32}
+
32%|███▏ | 3869/11952 [2:39:54<13:06:15, 5.84s/it]
32%|███▏ | 3870/11952 [2:40:00<13:12:05, 5.88s/it]
{'loss': 0.486, 'learning_rate': 1.5805049955741135e-05, 'epoch': 0.32}
+
32%|███▏ | 3870/11952 [2:40:00<13:12:05, 5.88s/it]
32%|███▏ | 3871/11952 [2:40:06<13:09:40, 5.86s/it]
{'loss': 0.4895, 'learning_rate': 1.5802843184504614e-05, 'epoch': 0.32}
+
32%|███▏ | 3871/11952 [2:40:06<13:09:40, 5.86s/it]
32%|███▏ | 3872/11952 [2:40:12<13:18:08, 5.93s/it]
{'loss': 0.5033, 'learning_rate': 1.5800635987131426e-05, 'epoch': 0.32}
+
32%|███▏ | 3872/11952 [2:40:12<13:18:08, 5.93s/it]
32%|███▏ | 3873/11952 [2:40:18<13:15:53, 5.91s/it]
{'loss': 0.4842, 'learning_rate': 1.579842836378366e-05, 'epoch': 0.32}
+
32%|███▏ | 3873/11952 [2:40:18<13:15:53, 5.91s/it]
32%|███▏ | 3874/11952 [2:40:24<13:12:43, 5.89s/it]
{'loss': 0.479, 'learning_rate': 1.579622031462343e-05, 'epoch': 0.32}
+
32%|███▏ | 3874/11952 [2:40:24<13:12:43, 5.89s/it]
32%|███▏ | 3875/11952 [2:40:30<13:11:22, 5.88s/it]
{'loss': 0.5077, 'learning_rate': 1.5794011839812888e-05, 'epoch': 0.32}
+
32%|███▏ | 3875/11952 [2:40:30<13:11:22, 5.88s/it]
32%|███▏ | 3876/11952 [2:40:35<12:58:22, 5.78s/it]
{'loss': 0.4942, 'learning_rate': 1.579180293951422e-05, 'epoch': 0.32}
+
32%|███▏ | 3876/11952 [2:40:35<12:58:22, 5.78s/it]
32%|███▏ | 3877/11952 [2:40:41<12:54:42, 5.76s/it]
{'loss': 0.4722, 'learning_rate': 1.5789593613889632e-05, 'epoch': 0.32}
+
32%|███▏ | 3877/11952 [2:40:41<12:54:42, 5.76s/it]
32%|███▏ | 3878/11952 [2:40:46<12:48:59, 5.71s/it]
{'loss': 0.48, 'learning_rate': 1.5787383863101366e-05, 'epoch': 0.32}
+
32%|███▏ | 3878/11952 [2:40:46<12:48:59, 5.71s/it]
32%|███▏ | 3879/11952 [2:40:52<12:58:29, 5.79s/it]
{'loss': 0.4909, 'learning_rate': 1.5785173687311704e-05, 'epoch': 0.32}
+
32%|███▏ | 3879/11952 [2:40:52<12:58:29, 5.79s/it]
32%|███▏ | 3880/11952 [2:40:58<13:07:55, 5.86s/it]
{'loss': 0.4962, 'learning_rate': 1.5782963086682946e-05, 'epoch': 0.32}
+
32%|███▏ | 3880/11952 [2:40:58<13:07:55, 5.86s/it]
32%|███▏ | 3881/11952 [2:41:05<13:29:54, 6.02s/it]
{'loss': 0.502, 'learning_rate': 1.5780752061377436e-05, 'epoch': 0.32}
+
32%|███▏ | 3881/11952 [2:41:05<13:29:54, 6.02s/it]
32%|███▏ | 3882/11952 [2:41:11<13:27:36, 6.00s/it]
{'loss': 0.4961, 'learning_rate': 1.5778540611557538e-05, 'epoch': 0.32}
+
32%|███▏ | 3882/11952 [2:41:11<13:27:36, 6.00s/it]
32%|███▏ | 3883/11952 [2:41:17<13:28:37, 6.01s/it]
{'loss': 0.506, 'learning_rate': 1.577632873738565e-05, 'epoch': 0.32}
+
32%|███▏ | 3883/11952 [2:41:17<13:28:37, 6.01s/it]
32%|███▏ | 3884/11952 [2:41:23<13:18:23, 5.94s/it]
{'loss': 0.4868, 'learning_rate': 1.5774116439024206e-05, 'epoch': 0.32}
+
32%|███▏ | 3884/11952 [2:41:23<13:18:23, 5.94s/it]
33%|███▎ | 3885/11952 [2:41:28<13:13:40, 5.90s/it]
{'loss': 0.4888, 'learning_rate': 1.5771903716635666e-05, 'epoch': 0.33}
+
33%|███▎ | 3885/11952 [2:41:28<13:13:40, 5.90s/it]
33%|███▎ | 3886/11952 [2:41:34<13:16:38, 5.93s/it]
{'loss': 0.5003, 'learning_rate': 1.576969057038253e-05, 'epoch': 0.33}
+
33%|███▎ | 3886/11952 [2:41:34<13:16:38, 5.93s/it]
33%|███▎ | 3887/11952 [2:41:40<13:16:18, 5.92s/it]
{'loss': 0.4854, 'learning_rate': 1.5767477000427306e-05, 'epoch': 0.33}
+
33%|███▎ | 3887/11952 [2:41:40<13:16:18, 5.92s/it]
33%|███▎ | 3888/11952 [2:41:46<13:10:07, 5.88s/it]
{'loss': 0.4996, 'learning_rate': 1.576526300693257e-05, 'epoch': 0.33}
+
33%|███▎ | 3888/11952 [2:41:46<13:10:07, 5.88s/it]
33%|███▎ | 3889/11952 [2:41:52<13:18:21, 5.94s/it]
{'loss': 0.4976, 'learning_rate': 1.5763048590060894e-05, 'epoch': 0.33}
+
33%|███▎ | 3889/11952 [2:41:52<13:18:21, 5.94s/it]
33%|███▎ | 3890/11952 [2:41:58<13:06:00, 5.85s/it]
{'loss': 0.4881, 'learning_rate': 1.5760833749974898e-05, 'epoch': 0.33}
+
33%|███▎ | 3890/11952 [2:41:58<13:06:00, 5.85s/it]
33%|███▎ | 3891/11952 [2:42:04<13:11:13, 5.89s/it]
{'loss': 0.494, 'learning_rate': 1.5758618486837232e-05, 'epoch': 0.33}
+
33%|███▎ | 3891/11952 [2:42:04<13:11:13, 5.89s/it]
33%|███▎ | 3892/11952 [2:42:10<13:05:09, 5.84s/it]
{'loss': 0.4804, 'learning_rate': 1.5756402800810582e-05, 'epoch': 0.33}
+
33%|███▎ | 3892/11952 [2:42:10<13:05:09, 5.84s/it]
33%|███▎ | 3893/11952 [2:42:15<13:02:04, 5.82s/it]
{'loss': 0.4861, 'learning_rate': 1.575418669205765e-05, 'epoch': 0.33}
+
33%|███▎ | 3893/11952 [2:42:15<13:02:04, 5.82s/it]
33%|███▎ | 3894/11952 [2:42:21<13:10:07, 5.88s/it]
{'loss': 0.4914, 'learning_rate': 1.575197016074118e-05, 'epoch': 0.33}
+
33%|███▎ | 3894/11952 [2:42:21<13:10:07, 5.88s/it]
33%|███▎ | 3895/11952 [2:42:27<13:01:07, 5.82s/it]
{'loss': 0.4872, 'learning_rate': 1.5749753207023944e-05, 'epoch': 0.33}
+
33%|███▎ | 3895/11952 [2:42:27<13:01:07, 5.82s/it]
33%|███▎ | 3896/11952 [2:42:33<12:50:57, 5.74s/it]
{'loss': 0.489, 'learning_rate': 1.574753583106875e-05, 'epoch': 0.33}
+
33%|███▎ | 3896/11952 [2:42:33<12:50:57, 5.74s/it]
33%|███▎ | 3897/11952 [2:42:39<13:05:19, 5.85s/it]
{'loss': 0.4924, 'learning_rate': 1.574531803303843e-05, 'epoch': 0.33}
+
33%|███▎ | 3897/11952 [2:42:39<13:05:19, 5.85s/it]
33%|███▎ | 3898/11952 [2:42:44<12:58:22, 5.80s/it]
{'loss': 0.4816, 'learning_rate': 1.574309981309585e-05, 'epoch': 0.33}
+
33%|███▎ | 3898/11952 [2:42:44<12:58:22, 5.80s/it]
33%|███▎ | 3899/11952 [2:42:50<12:54:21, 5.77s/it]
{'loss': 0.4639, 'learning_rate': 1.574088117140391e-05, 'epoch': 0.33}
+
33%|███▎ | 3899/11952 [2:42:50<12:54:21, 5.77s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
33%|███▎ | 3900/11952 [2:42:56<12:49:27, 5.73s/it]
{'loss': 0.4816, 'learning_rate': 1.573866210812553e-05, 'epoch': 0.33}
+
33%|███▎ | 3900/11952 [2:42:56<12:49:27, 5.73s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-3900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
33%|███▎ | 3901/11952 [2:43:28<30:29:39, 13.64s/it]
{'loss': 0.4962, 'learning_rate': 1.5736442623423675e-05, 'epoch': 0.33}
+
33%|███▎ | 3901/11952 [2:43:28<30:29:39, 13.64s/it]
33%|███▎ | 3902/11952 [2:43:34<25:12:18, 11.27s/it]
{'loss': 0.4772, 'learning_rate': 1.5734222717461338e-05, 'epoch': 0.33}
+
33%|███▎ | 3902/11952 [2:43:34<25:12:18, 11.27s/it]
33%|███▎ | 3903/11952 [2:43:40<21:44:41, 9.73s/it]
{'loss': 0.5055, 'learning_rate': 1.5732002390401527e-05, 'epoch': 0.33}
+
33%|███▎ | 3903/11952 [2:43:40<21:44:41, 9.73s/it]
33%|███▎ | 3904/11952 [2:43:45<19:03:58, 8.53s/it]
{'loss': 0.5134, 'learning_rate': 1.5729781642407305e-05, 'epoch': 0.33}
+
33%|███▎ | 3904/11952 [2:43:45<19:03:58, 8.53s/it]
33%|███▎ | 3905/11952 [2:43:52<17:40:24, 7.91s/it]
{'loss': 0.4845, 'learning_rate': 1.5727560473641755e-05, 'epoch': 0.33}
+
33%|███▎ | 3905/11952 [2:43:52<17:40:24, 7.91s/it]
33%|███▎ | 3906/11952 [2:43:58<16:12:06, 7.25s/it]
{'loss': 0.4959, 'learning_rate': 1.572533888426798e-05, 'epoch': 0.33}
+
33%|███▎ | 3906/11952 [2:43:58<16:12:06, 7.25s/it]
33%|███▎ | 3907/11952 [2:44:03<15:17:29, 6.84s/it]
{'loss': 0.5198, 'learning_rate': 1.5723116874449136e-05, 'epoch': 0.33}
+
33%|███▎ | 3907/11952 [2:44:03<15:17:29, 6.84s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (5014 > 4096). Running this sequence through the model will result in indexing errors
+
33%|███▎ | 3908/11952 [2:44:09<14:38:13, 6.55s/it]
{'loss': 0.4905, 'learning_rate': 1.5720894444348393e-05, 'epoch': 0.33}
+
33%|███▎ | 3908/11952 [2:44:09<14:38:13, 6.55s/it]
33%|███▎ | 3909/11952 [2:44:15<14:04:33, 6.30s/it]
{'loss': 0.4815, 'learning_rate': 1.5718671594128957e-05, 'epoch': 0.33}
+
33%|███▎ | 3909/11952 [2:44:15<14:04:33, 6.30s/it]
33%|███▎ | 3910/11952 [2:44:21<13:51:25, 6.20s/it]
{'loss': 0.5216, 'learning_rate': 1.571644832395406e-05, 'epoch': 0.33}
+
33%|███▎ | 3910/11952 [2:44:21<13:51:25, 6.20s/it]
33%|███▎ | 3911/11952 [2:44:27<13:38:25, 6.11s/it]
{'loss': 0.4948, 'learning_rate': 1.5714224633986978e-05, 'epoch': 0.33}
+
33%|███▎ | 3911/11952 [2:44:27<13:38:25, 6.11s/it]
33%|███▎ | 3912/11952 [2:44:33<13:23:15, 5.99s/it]
{'loss': 0.4868, 'learning_rate': 1.5712000524391004e-05, 'epoch': 0.33}
+
33%|███▎ | 3912/11952 [2:44:33<13:23:15, 5.99s/it]
33%|███▎ | 3913/11952 [2:44:39<13:19:15, 5.97s/it]
{'loss': 0.488, 'learning_rate': 1.5709775995329475e-05, 'epoch': 0.33}
+
33%|███▎ | 3913/11952 [2:44:39<13:19:15, 5.97s/it]
33%|███▎ | 3914/11952 [2:44:44<13:17:49, 5.96s/it]
{'loss': 0.4918, 'learning_rate': 1.570755104696574e-05, 'epoch': 0.33}
+
33%|███▎ | 3914/11952 [2:44:44<13:17:49, 5.96s/it]
33%|███▎ | 3915/11952 [2:44:50<13:17:02, 5.95s/it]
{'loss': 0.4765, 'learning_rate': 1.5705325679463198e-05, 'epoch': 0.33}
+
33%|███▎ | 3915/11952 [2:44:50<13:17:02, 5.95s/it]
33%|███▎ | 3916/11952 [2:44:57<13:22:44, 5.99s/it]
{'loss': 0.501, 'learning_rate': 1.5703099892985267e-05, 'epoch': 0.33}
+
33%|███▎ | 3916/11952 [2:44:57<13:22:44, 5.99s/it]
33%|███▎ | 3917/11952 [2:45:02<13:05:42, 5.87s/it]
{'loss': 0.4919, 'learning_rate': 1.5700873687695405e-05, 'epoch': 0.33}
+
33%|███▎ | 3917/11952 [2:45:02<13:05:42, 5.87s/it]
33%|███▎ | 3918/11952 [2:45:08<13:13:22, 5.93s/it]
{'loss': 0.4837, 'learning_rate': 1.5698647063757086e-05, 'epoch': 0.33}
+
33%|███▎ | 3918/11952 [2:45:08<13:13:22, 5.93s/it]
33%|███▎ | 3919/11952 [2:45:14<13:05:48, 5.87s/it]
{'loss': 0.4798, 'learning_rate': 1.5696420021333828e-05, 'epoch': 0.33}
+
33%|███▎ | 3919/11952 [2:45:14<13:05:48, 5.87s/it]
33%|███▎ | 3920/11952 [2:45:19<12:53:30, 5.78s/it]
{'loss': 0.4893, 'learning_rate': 1.5694192560589184e-05, 'epoch': 0.33}
+
33%|███▎ | 3920/11952 [2:45:19<12:53:30, 5.78s/it]
33%|███▎ | 3921/11952 [2:45:25<12:48:43, 5.74s/it]
{'loss': 0.4969, 'learning_rate': 1.5691964681686715e-05, 'epoch': 0.33}
+
33%|███▎ | 3921/11952 [2:45:25<12:48:43, 5.74s/it]
33%|███▎ | 3922/11952 [2:45:31<12:49:19, 5.75s/it]
{'loss': 0.4692, 'learning_rate': 1.5689736384790038e-05, 'epoch': 0.33}
+
33%|███▎ | 3922/11952 [2:45:31<12:49:19, 5.75s/it]
33%|███▎ | 3923/11952 [2:45:37<12:58:15, 5.82s/it]
{'loss': 0.4862, 'learning_rate': 1.5687507670062788e-05, 'epoch': 0.33}
+
33%|███▎ | 3923/11952 [2:45:37<12:58:15, 5.82s/it]
33%|███▎ | 3924/11952 [2:45:42<12:51:51, 5.77s/it]
{'loss': 0.4888, 'learning_rate': 1.5685278537668627e-05, 'epoch': 0.33}
+
33%|███▎ | 3924/11952 [2:45:42<12:51:51, 5.77s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
33%|███▎ | 3925/11952 [2:45:49<13:07:49, 5.89s/it]
{'loss': 0.518, 'learning_rate': 1.568304898777126e-05, 'epoch': 0.33}
+
33%|███▎ | 3925/11952 [2:45:49<13:07:49, 5.89s/it]
33%|███▎ | 3926/11952 [2:45:54<12:59:55, 5.83s/it]
{'loss': 0.4963, 'learning_rate': 1.568081902053441e-05, 'epoch': 0.33}
+
33%|███▎ | 3926/11952 [2:45:54<12:59:55, 5.83s/it]
33%|███▎ | 3927/11952 [2:46:00<12:47:14, 5.74s/it]
{'loss': 0.4802, 'learning_rate': 1.567858863612184e-05, 'epoch': 0.33}
+
33%|███▎ | 3927/11952 [2:46:00<12:47:14, 5.74s/it]
33%|███▎ | 3928/11952 [2:46:06<12:59:10, 5.83s/it]
{'loss': 0.5066, 'learning_rate': 1.5676357834697342e-05, 'epoch': 0.33}
+
33%|███▎ | 3928/11952 [2:46:06<12:59:10, 5.83s/it]
33%|███▎ | 3929/11952 [2:46:12<12:59:31, 5.83s/it]
{'loss': 0.495, 'learning_rate': 1.5674126616424735e-05, 'epoch': 0.33}
+
33%|███▎ | 3929/11952 [2:46:12<12:59:31, 5.83s/it]
33%|███▎ | 3930/11952 [2:46:17<12:52:59, 5.78s/it]
{'loss': 0.4616, 'learning_rate': 1.5671894981467866e-05, 'epoch': 0.33}
+
33%|███▎ | 3930/11952 [2:46:17<12:52:59, 5.78s/it]
33%|███▎ | 3931/11952 [2:46:23<12:46:12, 5.73s/it]
{'loss': 0.4896, 'learning_rate': 1.5669662929990622e-05, 'epoch': 0.33}
+
33%|███▎ | 3931/11952 [2:46:23<12:46:12, 5.73s/it]
33%|███▎ | 3932/11952 [2:46:29<12:41:11, 5.69s/it]
{'loss': 0.4981, 'learning_rate': 1.5667430462156918e-05, 'epoch': 0.33}
+
33%|███▎ | 3932/11952 [2:46:29<12:41:11, 5.69s/it]
33%|███▎ | 3933/11952 [2:46:35<12:57:28, 5.82s/it]
{'loss': 0.4783, 'learning_rate': 1.566519757813069e-05, 'epoch': 0.33}
+
33%|███▎ | 3933/11952 [2:46:35<12:57:28, 5.82s/it]
33%|███▎ | 3934/11952 [2:46:41<12:57:45, 5.82s/it]
{'loss': 0.5017, 'learning_rate': 1.5662964278075913e-05, 'epoch': 0.33}
+
33%|███▎ | 3934/11952 [2:46:41<12:57:45, 5.82s/it]
33%|███▎ | 3935/11952 [2:46:46<12:58:22, 5.83s/it]
{'loss': 0.4876, 'learning_rate': 1.5660730562156596e-05, 'epoch': 0.33}
+
33%|███▎ | 3935/11952 [2:46:46<12:58:22, 5.83s/it]
33%|███▎ | 3936/11952 [2:46:53<13:11:05, 5.92s/it]
{'loss': 0.4888, 'learning_rate': 1.5658496430536772e-05, 'epoch': 0.33}
+
33%|███▎ | 3936/11952 [2:46:53<13:11:05, 5.92s/it]
33%|███▎ | 3937/11952 [2:46:59<13:19:46, 5.99s/it]
{'loss': 0.484, 'learning_rate': 1.5656261883380504e-05, 'epoch': 0.33}
+
33%|███▎ | 3937/11952 [2:46:59<13:19:46, 5.99s/it]
33%|███▎ | 3938/11952 [2:47:04<13:09:33, 5.91s/it]
{'loss': 0.5082, 'learning_rate': 1.565402692085189e-05, 'epoch': 0.33}
+
33%|███▎ | 3938/11952 [2:47:04<13:09:33, 5.91s/it]
33%|███▎ | 3939/11952 [2:47:10<13:04:40, 5.88s/it]
{'loss': 0.4958, 'learning_rate': 1.5651791543115056e-05, 'epoch': 0.33}
+
33%|███▎ | 3939/11952 [2:47:10<13:04:40, 5.88s/it]
33%|███▎ | 3940/11952 [2:47:16<12:55:45, 5.81s/it]
{'loss': 0.4958, 'learning_rate': 1.564955575033416e-05, 'epoch': 0.33}
+
33%|███▎ | 3940/11952 [2:47:16<12:55:45, 5.81s/it]
33%|███▎ | 3941/11952 [2:47:22<12:54:53, 5.80s/it]
{'loss': 0.5015, 'learning_rate': 1.5647319542673386e-05, 'epoch': 0.33}
+
33%|███▎ | 3941/11952 [2:47:22<12:54:53, 5.80s/it]
33%|███▎ | 3942/11952 [2:47:27<12:55:15, 5.81s/it]
{'loss': 0.4872, 'learning_rate': 1.564508292029695e-05, 'epoch': 0.33}
+
33%|███▎ | 3942/11952 [2:47:27<12:55:15, 5.81s/it]
33%|███▎ | 3943/11952 [2:47:33<12:55:39, 5.81s/it]
{'loss': 0.471, 'learning_rate': 1.5642845883369114e-05, 'epoch': 0.33}
+
33%|███▎ | 3943/11952 [2:47:33<12:55:39, 5.81s/it]
33%|███▎ | 3944/11952 [2:47:39<12:47:46, 5.75s/it]
{'loss': 0.484, 'learning_rate': 1.564060843205414e-05, 'epoch': 0.33}
+
33%|███▎ | 3944/11952 [2:47:39<12:47:46, 5.75s/it]
33%|███▎ | 3945/11952 [2:47:45<12:55:46, 5.81s/it]
{'loss': 0.4949, 'learning_rate': 1.5638370566516344e-05, 'epoch': 0.33}
+
33%|███▎ | 3945/11952 [2:47:45<12:55:46, 5.81s/it]
33%|███▎ | 3946/11952 [2:47:50<12:47:14, 5.75s/it]
{'loss': 0.4749, 'learning_rate': 1.5636132286920066e-05, 'epoch': 0.33}
+
33%|███▎ | 3946/11952 [2:47:50<12:47:14, 5.75s/it]
33%|███▎ | 3947/11952 [2:47:56<12:50:19, 5.77s/it]
{'loss': 0.4953, 'learning_rate': 1.5633893593429677e-05, 'epoch': 0.33}
+
33%|███▎ | 3947/11952 [2:47:56<12:50:19, 5.77s/it]
33%|███▎ | 3948/11952 [2:48:02<13:06:32, 5.90s/it]
{'loss': 0.513, 'learning_rate': 1.5631654486209572e-05, 'epoch': 0.33}
+
33%|███▎ | 3948/11952 [2:48:02<13:06:32, 5.90s/it]
33%|███▎ | 3949/11952 [2:48:08<13:01:51, 5.86s/it]
{'loss': 0.4946, 'learning_rate': 1.5629414965424187e-05, 'epoch': 0.33}
+
33%|███▎ | 3949/11952 [2:48:08<13:01:51, 5.86s/it]6 AutoResumeHook: Checking whether to suspend...
+21 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
33%|███▎ | 3950/11952 [2:48:14<12:56:11, 5.82s/it]
{'loss': 0.4743, 'learning_rate': 1.5627175031237986e-05, 'epoch': 0.33}
+
33%|███▎ | 3950/11952 [2:48:14<12:56:11, 5.82s/it]
33%|███▎ | 3951/11952 [2:48:20<12:52:18, 5.79s/it]
{'loss': 0.4942, 'learning_rate': 1.562493468381545e-05, 'epoch': 0.33}
+
33%|███▎ | 3951/11952 [2:48:20<12:52:18, 5.79s/it]
33%|███▎ | 3952/11952 [2:48:26<12:58:21, 5.84s/it]
{'loss': 0.5027, 'learning_rate': 1.5622693923321105e-05, 'epoch': 0.33}
+
33%|███▎ | 3952/11952 [2:48:26<12:58:21, 5.84s/it]
33%|███▎ | 3953/11952 [2:48:31<12:53:33, 5.80s/it]
{'loss': 0.5063, 'learning_rate': 1.562045274991951e-05, 'epoch': 0.33}
+
33%|███▎ | 3953/11952 [2:48:31<12:53:33, 5.80s/it]
33%|███▎ | 3954/11952 [2:48:37<12:58:50, 5.84s/it]
{'loss': 0.5087, 'learning_rate': 1.5618211163775242e-05, 'epoch': 0.33}
+
33%|███▎ | 3954/11952 [2:48:37<12:58:50, 5.84s/it]
33%|███▎ | 3955/11952 [2:48:43<12:49:08, 5.77s/it]
{'loss': 0.4906, 'learning_rate': 1.561596916505291e-05, 'epoch': 0.33}
+
33%|███▎ | 3955/11952 [2:48:43<12:49:08, 5.77s/it]
33%|███▎ | 3956/11952 [2:48:49<12:48:09, 5.76s/it]
{'loss': 0.4729, 'learning_rate': 1.5613726753917166e-05, 'epoch': 0.33}
+
33%|███▎ | 3956/11952 [2:48:49<12:48:09, 5.76s/it]
33%|███▎ | 3957/11952 [2:48:54<12:42:07, 5.72s/it]
{'loss': 0.4925, 'learning_rate': 1.5611483930532677e-05, 'epoch': 0.33}
+
33%|███▎ | 3957/11952 [2:48:54<12:42:07, 5.72s/it]
33%|███▎ | 3958/11952 [2:49:00<12:49:27, 5.78s/it]
{'loss': 0.4867, 'learning_rate': 1.5609240695064146e-05, 'epoch': 0.33}
+
33%|███▎ | 3958/11952 [2:49:00<12:49:27, 5.78s/it]
33%|███▎ | 3959/11952 [2:49:06<12:48:00, 5.77s/it]
{'loss': 0.4978, 'learning_rate': 1.560699704767631e-05, 'epoch': 0.33}
+
33%|███▎ | 3959/11952 [2:49:06<12:48:00, 5.77s/it]
33%|███▎ | 3960/11952 [2:49:12<12:48:07, 5.77s/it]
{'loss': 0.4827, 'learning_rate': 1.5604752988533933e-05, 'epoch': 0.33}
+
33%|███▎ | 3960/11952 [2:49:12<12:48:07, 5.77s/it]
33%|███▎ | 3961/11952 [2:49:18<12:54:29, 5.82s/it]
{'loss': 0.4758, 'learning_rate': 1.560250851780181e-05, 'epoch': 0.33}
+
33%|███▎ | 3961/11952 [2:49:18<12:54:29, 5.82s/it]
33%|███▎ | 3962/11952 [2:49:24<12:57:50, 5.84s/it]
{'loss': 0.5156, 'learning_rate': 1.560026363564476e-05, 'epoch': 0.33}
+
33%|███▎ | 3962/11952 [2:49:24<12:57:50, 5.84s/it]
33%|███▎ | 3963/11952 [2:49:29<12:58:57, 5.85s/it]
{'loss': 0.4874, 'learning_rate': 1.5598018342227645e-05, 'epoch': 0.33}
+
33%|███▎ | 3963/11952 [2:49:29<12:58:57, 5.85s/it]
33%|███▎ | 3964/11952 [2:49:35<13:03:24, 5.88s/it]
{'loss': 0.4942, 'learning_rate': 1.5595772637715345e-05, 'epoch': 0.33}
+
33%|███▎ | 3964/11952 [2:49:35<13:03:24, 5.88s/it]
33%|███▎ | 3965/11952 [2:49:41<13:03:46, 5.89s/it]
{'loss': 0.4825, 'learning_rate': 1.5593526522272774e-05, 'epoch': 0.33}
+
33%|███▎ | 3965/11952 [2:49:41<13:03:46, 5.89s/it]
33%|███▎ | 3966/11952 [2:49:47<12:57:26, 5.84s/it]
{'loss': 0.4938, 'learning_rate': 1.5591279996064884e-05, 'epoch': 0.33}
+
33%|███▎ | 3966/11952 [2:49:47<12:57:26, 5.84s/it]
33%|███▎ | 3967/11952 [2:49:53<12:56:29, 5.83s/it]
{'loss': 0.5092, 'learning_rate': 1.558903305925665e-05, 'epoch': 0.33}
+
33%|███▎ | 3967/11952 [2:49:53<12:56:29, 5.83s/it]
33%|███▎ | 3968/11952 [2:49:58<12:47:01, 5.76s/it]
{'loss': 0.4806, 'learning_rate': 1.5586785712013073e-05, 'epoch': 0.33}
+
33%|███▎ | 3968/11952 [2:49:58<12:47:01, 5.76s/it]
33%|███▎ | 3969/11952 [2:50:04<12:50:48, 5.79s/it]
{'loss': 0.5001, 'learning_rate': 1.5584537954499186e-05, 'epoch': 0.33}
+
33%|███▎ | 3969/11952 [2:50:04<12:50:48, 5.79s/it]
33%|███▎ | 3970/11952 [2:50:10<12:54:49, 5.82s/it]
{'loss': 0.4897, 'learning_rate': 1.5582289786880064e-05, 'epoch': 0.33}
+
33%|███▎ | 3970/11952 [2:50:10<12:54:49, 5.82s/it]
33%|███▎ | 3971/11952 [2:50:16<12:54:09, 5.82s/it]
{'loss': 0.4813, 'learning_rate': 1.5580041209320797e-05, 'epoch': 0.33}
+
33%|███▎ | 3971/11952 [2:50:16<12:54:09, 5.82s/it]
33%|███▎ | 3972/11952 [2:50:22<12:58:33, 5.85s/it]
{'loss': 0.4873, 'learning_rate': 1.5577792221986512e-05, 'epoch': 0.33}
+
33%|███▎ | 3972/11952 [2:50:22<12:58:33, 5.85s/it]
33%|███▎ | 3973/11952 [2:50:28<13:14:07, 5.97s/it]
{'loss': 0.4936, 'learning_rate': 1.5575542825042368e-05, 'epoch': 0.33}
+
33%|███▎ | 3973/11952 [2:50:28<13:14:07, 5.97s/it]
33%|███▎ | 3974/11952 [2:50:34<12:58:54, 5.86s/it]
{'loss': 0.4823, 'learning_rate': 1.557329301865355e-05, 'epoch': 0.33}
+
33%|███▎ | 3974/11952 [2:50:34<12:58:54, 5.86s/it]
33%|███▎ | 3975/11952 [2:50:40<13:06:20, 5.91s/it]
{'loss': 0.4738, 'learning_rate': 1.557104280298527e-05, 'epoch': 0.33}
+
33%|███▎ | 3975/11952 [2:50:40<13:06:20, 5.91s/it]
33%|███▎ | 3976/11952 [2:50:46<12:59:17, 5.86s/it]
{'loss': 0.4857, 'learning_rate': 1.556879217820278e-05, 'epoch': 0.33}
+
33%|███▎ | 3976/11952 [2:50:46<12:59:17, 5.86s/it]
33%|███▎ | 3977/11952 [2:50:51<12:56:18, 5.84s/it]
{'loss': 0.4782, 'learning_rate': 1.5566541144471355e-05, 'epoch': 0.33}
+
33%|███▎ | 3977/11952 [2:50:51<12:56:18, 5.84s/it]
33%|███▎ | 3978/11952 [2:50:57<12:53:36, 5.82s/it]
{'loss': 0.5053, 'learning_rate': 1.55642897019563e-05, 'epoch': 0.33}
+
33%|███▎ | 3978/11952 [2:50:57<12:53:36, 5.82s/it]
33%|███▎ | 3979/11952 [2:51:03<12:38:29, 5.71s/it]
{'loss': 0.4842, 'learning_rate': 1.5562037850822954e-05, 'epoch': 0.33}
+
33%|███▎ | 3979/11952 [2:51:03<12:38:29, 5.71s/it]
33%|███▎ | 3980/11952 [2:51:09<12:53:30, 5.82s/it]
{'loss': 0.4971, 'learning_rate': 1.5559785591236683e-05, 'epoch': 0.33}
+
33%|███▎ | 3980/11952 [2:51:09<12:53:30, 5.82s/it]
33%|███▎ | 3981/11952 [2:51:14<12:50:58, 5.80s/it]
{'loss': 0.4861, 'learning_rate': 1.5557532923362883e-05, 'epoch': 0.33}
+
33%|███▎ | 3981/11952 [2:51:14<12:50:58, 5.80s/it]
33%|███▎ | 3982/11952 [2:51:21<13:13:51, 5.98s/it]
{'loss': 0.4977, 'learning_rate': 1.555527984736698e-05, 'epoch': 0.33}
+
33%|███▎ | 3982/11952 [2:51:21<13:13:51, 5.98s/it]
33%|███▎ | 3983/11952 [2:51:27<13:10:46, 5.95s/it]
{'loss': 0.5032, 'learning_rate': 1.555302636341443e-05, 'epoch': 0.33}
+
33%|███▎ | 3983/11952 [2:51:27<13:10:46, 5.95s/it]
33%|███▎ | 3984/11952 [2:51:33<13:21:35, 6.04s/it]
{'loss': 0.4829, 'learning_rate': 1.5550772471670724e-05, 'epoch': 0.33}
+
33%|███▎ | 3984/11952 [2:51:33<13:21:35, 6.04s/it]
33%|███▎ | 3985/11952 [2:51:39<13:10:48, 5.96s/it]
{'loss': 0.5062, 'learning_rate': 1.5548518172301373e-05, 'epoch': 0.33}
+
33%|███▎ | 3985/11952 [2:51:39<13:10:48, 5.96s/it]
33%|███▎ | 3986/11952 [2:51:45<13:07:01, 5.93s/it]
{'loss': 0.4957, 'learning_rate': 1.5546263465471926e-05, 'epoch': 0.33}
+
33%|███▎ | 3986/11952 [2:51:45<13:07:01, 5.93s/it]
33%|███▎ | 3987/11952 [2:51:51<13:15:04, 5.99s/it]
{'loss': 0.4942, 'learning_rate': 1.554400835134796e-05, 'epoch': 0.33}
+
33%|███▎ | 3987/11952 [2:51:51<13:15:04, 5.99s/it]
33%|███▎ | 3988/11952 [2:51:56<13:06:47, 5.93s/it]
{'loss': 0.4794, 'learning_rate': 1.554175283009508e-05, 'epoch': 0.33}
+
33%|███▎ | 3988/11952 [2:51:56<13:06:47, 5.93s/it]
33%|███▎ | 3989/11952 [2:52:02<13:02:53, 5.90s/it]
{'loss': 0.4872, 'learning_rate': 1.5539496901878915e-05, 'epoch': 0.33}
+
33%|███▎ | 3989/11952 [2:52:02<13:02:53, 5.90s/it]
33%|███▎ | 3990/11952 [2:52:08<12:58:07, 5.86s/it]
{'loss': 0.4901, 'learning_rate': 1.5537240566865145e-05, 'epoch': 0.33}
+
33%|███▎ | 3990/11952 [2:52:08<12:58:07, 5.86s/it]
33%|███▎ | 3991/11952 [2:52:14<12:52:28, 5.82s/it]
{'loss': 0.4855, 'learning_rate': 1.553498382521946e-05, 'epoch': 0.33}
+
33%|███▎ | 3991/11952 [2:52:14<12:52:28, 5.82s/it]
33%|███▎ | 3992/11952 [2:52:20<12:50:48, 5.81s/it]
{'loss': 0.4874, 'learning_rate': 1.5532726677107583e-05, 'epoch': 0.33}
+
33%|███▎ | 3992/11952 [2:52:20<12:50:48, 5.81s/it]
33%|███▎ | 3993/11952 [2:52:25<12:42:50, 5.75s/it]
{'loss': 0.4815, 'learning_rate': 1.553046912269527e-05, 'epoch': 0.33}
+
33%|███▎ | 3993/11952 [2:52:25<12:42:50, 5.75s/it]
33%|███▎ | 3994/11952 [2:52:31<12:43:10, 5.75s/it]
{'loss': 0.5012, 'learning_rate': 1.5528211162148305e-05, 'epoch': 0.33}
+
33%|███▎ | 3994/11952 [2:52:31<12:43:10, 5.75s/it]
33%|███▎ | 3995/11952 [2:52:37<12:36:03, 5.70s/it]
{'loss': 0.4831, 'learning_rate': 1.552595279563251e-05, 'epoch': 0.33}
+
33%|███▎ | 3995/11952 [2:52:37<12:36:03, 5.70s/it]
33%|███▎ | 3996/11952 [2:52:42<12:43:33, 5.76s/it]
{'loss': 0.487, 'learning_rate': 1.5523694023313723e-05, 'epoch': 0.33}
+
33%|███▎ | 3996/11952 [2:52:42<12:43:33, 5.76s/it]
33%|███▎ | 3997/11952 [2:52:48<12:44:58, 5.77s/it]
{'loss': 0.4729, 'learning_rate': 1.5521434845357824e-05, 'epoch': 0.33}
+
33%|███▎ | 3997/11952 [2:52:48<12:44:58, 5.77s/it]
33%|███▎ | 3998/11952 [2:52:54<12:39:30, 5.73s/it]
{'loss': 0.4859, 'learning_rate': 1.5519175261930716e-05, 'epoch': 0.33}
+
33%|███▎ | 3998/11952 [2:52:54<12:39:30, 5.73s/it]
33%|███▎ | 3999/11952 [2:53:00<12:51:13, 5.82s/it]
{'loss': 0.4979, 'learning_rate': 1.551691527319833e-05, 'epoch': 0.33}
+
33%|███▎ | 3999/11952 [2:53:00<12:51:13, 5.82s/it]1 AutoResumeHook: Checking whether to suspend...
+23 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+76 5 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
33%|███▎ | 4000/11952 [2:53:06<12:52:00, 5.83s/it]
{'loss': 0.4947, 'learning_rate': 1.551465487932663e-05, 'epoch': 0.33}
+
33%|███▎ | 4000/11952 [2:53:06<12:52:00, 5.83s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
33%|███▎ | 4001/11952 [2:53:38<30:30:35, 13.81s/it]
{'loss': 0.48, 'learning_rate': 1.551239408048162e-05, 'epoch': 0.33}
+
33%|███▎ | 4001/11952 [2:53:38<30:30:35, 13.81s/it]
33%|███▎ | 4002/11952 [2:53:44<25:04:51, 11.36s/it]
{'loss': 0.4818, 'learning_rate': 1.5510132876829313e-05, 'epoch': 0.33}
+
33%|███▎ | 4002/11952 [2:53:44<25:04:51, 11.36s/it]
33%|███▎ | 4003/11952 [2:53:49<21:14:46, 9.62s/it]
{'loss': 0.4845, 'learning_rate': 1.5507871268535765e-05, 'epoch': 0.33}
+
33%|███▎ | 4003/11952 [2:53:49<21:14:46, 9.62s/it]
34%|███▎ | 4004/11952 [2:53:55<18:43:11, 8.48s/it]
{'loss': 0.5188, 'learning_rate': 1.550560925576706e-05, 'epoch': 0.33}
+
34%|███▎ | 4004/11952 [2:53:55<18:43:11, 8.48s/it]
34%|███▎ | 4005/11952 [2:54:01<16:51:15, 7.64s/it]
{'loss': 0.479, 'learning_rate': 1.5503346838689314e-05, 'epoch': 0.34}
+
34%|███▎ | 4005/11952 [2:54:01<16:51:15, 7.64s/it]
34%|███▎ | 4006/11952 [2:54:07<15:37:18, 7.08s/it]
{'loss': 0.5038, 'learning_rate': 1.5501084017468665e-05, 'epoch': 0.34}
+
34%|███▎ | 4006/11952 [2:54:07<15:37:18, 7.08s/it]
34%|███▎ | 4007/11952 [2:54:13<14:53:33, 6.75s/it]
{'loss': 0.5002, 'learning_rate': 1.5498820792271284e-05, 'epoch': 0.34}
+
34%|███▎ | 4007/11952 [2:54:13<14:53:33, 6.75s/it]
34%|███▎ | 4008/11952 [2:54:19<14:26:18, 6.54s/it]
{'loss': 0.5109, 'learning_rate': 1.549655716326338e-05, 'epoch': 0.34}
+
34%|███▎ | 4008/11952 [2:54:19<14:26:18, 6.54s/it]
34%|███▎ | 4009/11952 [2:54:24<13:53:52, 6.30s/it]
{'loss': 0.4899, 'learning_rate': 1.5494293130611175e-05, 'epoch': 0.34}
+
34%|███▎ | 4009/11952 [2:54:24<13:53:52, 6.30s/it]
34%|███▎ | 4010/11952 [2:54:30<13:36:28, 6.17s/it]
{'loss': 0.4973, 'learning_rate': 1.5492028694480938e-05, 'epoch': 0.34}
+
34%|███▎ | 4010/11952 [2:54:30<13:36:28, 6.17s/it]
34%|███▎ | 4011/11952 [2:54:36<13:24:09, 6.08s/it]
{'loss': 0.4873, 'learning_rate': 1.5489763855038954e-05, 'epoch': 0.34}
+
34%|███▎ | 4011/11952 [2:54:36<13:24:09, 6.08s/it]
34%|███▎ | 4012/11952 [2:54:42<13:06:22, 5.94s/it]
{'loss': 0.4707, 'learning_rate': 1.548749861245155e-05, 'epoch': 0.34}
+
34%|███▎ | 4012/11952 [2:54:42<13:06:22, 5.94s/it]
34%|███▎ | 4013/11952 [2:54:48<13:09:17, 5.97s/it]
{'loss': 0.48, 'learning_rate': 1.548523296688507e-05, 'epoch': 0.34}
+
34%|███▎ | 4013/11952 [2:54:48<13:09:17, 5.97s/it]
34%|███▎ | 4014/11952 [2:54:53<12:58:53, 5.89s/it]
{'loss': 0.4909, 'learning_rate': 1.5482966918505897e-05, 'epoch': 0.34}
+
34%|███▎ | 4014/11952 [2:54:53<12:58:53, 5.89s/it]
34%|███▎ | 4015/11952 [2:55:00<13:08:00, 5.96s/it]
{'loss': 0.496, 'learning_rate': 1.5480700467480437e-05, 'epoch': 0.34}
+
34%|███▎ | 4015/11952 [2:55:00<13:08:00, 5.96s/it]
34%|███▎ | 4016/11952 [2:55:05<13:04:36, 5.93s/it]
{'loss': 0.4784, 'learning_rate': 1.547843361397513e-05, 'epoch': 0.34}
+
34%|███▎ | 4016/11952 [2:55:05<13:04:36, 5.93s/it]
34%|███▎ | 4017/11952 [2:55:11<13:03:49, 5.93s/it]
{'loss': 0.49, 'learning_rate': 1.5476166358156446e-05, 'epoch': 0.34}
+
34%|███▎ | 4017/11952 [2:55:11<13:03:49, 5.93s/it]
34%|███▎ | 4018/11952 [2:55:17<13:07:50, 5.96s/it]
{'loss': 0.5039, 'learning_rate': 1.5473898700190884e-05, 'epoch': 0.34}
+
34%|███▎ | 4018/11952 [2:55:17<13:07:50, 5.96s/it]
34%|███▎ | 4019/11952 [2:55:23<12:58:19, 5.89s/it]
{'loss': 0.4724, 'learning_rate': 1.5471630640244966e-05, 'epoch': 0.34}
+
34%|███▎ | 4019/11952 [2:55:23<12:58:19, 5.89s/it]
34%|███▎ | 4020/11952 [2:55:29<12:54:37, 5.86s/it]
{'loss': 0.481, 'learning_rate': 1.5469362178485252e-05, 'epoch': 0.34}
+
34%|███▎ | 4020/11952 [2:55:29<12:54:37, 5.86s/it]
34%|███▎ | 4021/11952 [2:55:35<12:54:20, 5.86s/it]
{'loss': 0.5026, 'learning_rate': 1.546709331507833e-05, 'epoch': 0.34}
+
34%|███▎ | 4021/11952 [2:55:35<12:54:20, 5.86s/it]
34%|███▎ | 4022/11952 [2:55:41<12:53:26, 5.85s/it]
{'loss': 0.4854, 'learning_rate': 1.5464824050190816e-05, 'epoch': 0.34}
+
34%|███▎ | 4022/11952 [2:55:41<12:53:26, 5.85s/it]
34%|███▎ | 4023/11952 [2:55:46<12:52:21, 5.84s/it]
{'loss': 0.5195, 'learning_rate': 1.5462554383989347e-05, 'epoch': 0.34}
+
34%|███▎ | 4023/11952 [2:55:46<12:52:21, 5.84s/it]
34%|███▎ | 4024/11952 [2:55:52<12:48:37, 5.82s/it]
{'loss': 0.4913, 'learning_rate': 1.546028431664061e-05, 'epoch': 0.34}
+
34%|███▎ | 4024/11952 [2:55:52<12:48:37, 5.82s/it]
34%|███▎ | 4025/11952 [2:55:58<12:48:18, 5.82s/it]
{'loss': 0.4944, 'learning_rate': 1.5458013848311305e-05, 'epoch': 0.34}
+
34%|███▎ | 4025/11952 [2:55:58<12:48:18, 5.82s/it]
34%|███▎ | 4026/11952 [2:56:04<12:41:01, 5.76s/it]
{'loss': 0.4911, 'learning_rate': 1.545574297916816e-05, 'epoch': 0.34}
+
34%|███▎ | 4026/11952 [2:56:04<12:41:01, 5.76s/it]
34%|███▎ | 4027/11952 [2:56:10<12:46:06, 5.80s/it]
{'loss': 0.4948, 'learning_rate': 1.5453471709377945e-05, 'epoch': 0.34}
+
34%|███▎ | 4027/11952 [2:56:10<12:46:06, 5.80s/it]
34%|███▎ | 4028/11952 [2:56:15<12:44:11, 5.79s/it]
{'loss': 0.4996, 'learning_rate': 1.545120003910745e-05, 'epoch': 0.34}
+
34%|███▎ | 4028/11952 [2:56:15<12:44:11, 5.79s/it]
34%|███▎ | 4029/11952 [2:56:21<12:41:26, 5.77s/it]
{'loss': 0.4778, 'learning_rate': 1.54489279685235e-05, 'epoch': 0.34}
+
34%|███▎ | 4029/11952 [2:56:21<12:41:26, 5.77s/it]
34%|███▎ | 4030/11952 [2:56:27<12:38:19, 5.74s/it]
{'loss': 0.4836, 'learning_rate': 1.544665549779294e-05, 'epoch': 0.34}
+
34%|███▎ | 4030/11952 [2:56:27<12:38:19, 5.74s/it]
34%|███▎ | 4031/11952 [2:56:33<12:51:40, 5.85s/it]
{'loss': 0.4674, 'learning_rate': 1.5444382627082657e-05, 'epoch': 0.34}
+
34%|███▎ | 4031/11952 [2:56:33<12:51:40, 5.85s/it]
34%|███▎ | 4032/11952 [2:56:39<12:48:01, 5.82s/it]
{'loss': 0.4828, 'learning_rate': 1.5442109356559556e-05, 'epoch': 0.34}
+
34%|███▎ | 4032/11952 [2:56:39<12:48:01, 5.82s/it]
34%|███▎ | 4033/11952 [2:56:44<12:39:05, 5.75s/it]
{'loss': 0.4952, 'learning_rate': 1.543983568639058e-05, 'epoch': 0.34}
+
34%|███▎ | 4033/11952 [2:56:44<12:39:05, 5.75s/it]
34%|███▍ | 4034/11952 [2:56:50<12:49:12, 5.83s/it]
{'loss': 0.4733, 'learning_rate': 1.5437561616742703e-05, 'epoch': 0.34}
+
34%|███▍ | 4034/11952 [2:56:50<12:49:12, 5.83s/it]
34%|███▍ | 4035/11952 [2:56:56<12:44:43, 5.80s/it]
{'loss': 0.4976, 'learning_rate': 1.543528714778291e-05, 'epoch': 0.34}
+
34%|███▍ | 4035/11952 [2:56:56<12:44:43, 5.80s/it]
34%|███▍ | 4036/11952 [2:57:02<12:44:06, 5.79s/it]
{'loss': 0.4952, 'learning_rate': 1.543301227967824e-05, 'epoch': 0.34}
+
34%|███▍ | 4036/11952 [2:57:02<12:44:06, 5.79s/it]
34%|███▍ | 4037/11952 [2:57:07<12:36:19, 5.73s/it]
{'loss': 0.496, 'learning_rate': 1.543073701259574e-05, 'epoch': 0.34}
+
34%|███▍ | 4037/11952 [2:57:07<12:36:19, 5.73s/it]
34%|███▍ | 4038/11952 [2:57:13<12:36:54, 5.74s/it]
{'loss': 0.4901, 'learning_rate': 1.542846134670251e-05, 'epoch': 0.34}
+
34%|███▍ | 4038/11952 [2:57:13<12:36:54, 5.74s/it]
34%|███▍ | 4039/11952 [2:57:19<12:53:02, 5.86s/it]
{'loss': 0.5044, 'learning_rate': 1.5426185282165652e-05, 'epoch': 0.34}
+
34%|███▍ | 4039/11952 [2:57:19<12:53:02, 5.86s/it]
34%|███▍ | 4040/11952 [2:57:25<12:47:54, 5.82s/it]
{'loss': 0.4779, 'learning_rate': 1.5423908819152317e-05, 'epoch': 0.34}
+
34%|███▍ | 4040/11952 [2:57:25<12:47:54, 5.82s/it]
34%|███▍ | 4041/11952 [2:57:31<12:56:43, 5.89s/it]
{'loss': 0.5076, 'learning_rate': 1.542163195782968e-05, 'epoch': 0.34}
+
34%|███▍ | 4041/11952 [2:57:31<12:56:43, 5.89s/it]
34%|███▍ | 4042/11952 [2:57:37<12:50:52, 5.85s/it]
{'loss': 0.4836, 'learning_rate': 1.5419354698364944e-05, 'epoch': 0.34}
+
34%|███▍ | 4042/11952 [2:57:37<12:50:52, 5.85s/it]
34%|███▍ | 4043/11952 [2:57:43<12:52:45, 5.86s/it]
{'loss': 0.4994, 'learning_rate': 1.5417077040925334e-05, 'epoch': 0.34}
+
34%|███▍ | 4043/11952 [2:57:43<12:52:45, 5.86s/it]
34%|███▍ | 4044/11952 [2:57:49<12:59:19, 5.91s/it]
{'loss': 0.5221, 'learning_rate': 1.541479898567812e-05, 'epoch': 0.34}
+
34%|███▍ | 4044/11952 [2:57:49<12:59:19, 5.91s/it]
34%|███▍ | 4045/11952 [2:57:54<12:56:15, 5.89s/it]
{'loss': 0.4938, 'learning_rate': 1.541252053279059e-05, 'epoch': 0.34}
+
34%|███▍ | 4045/11952 [2:57:54<12:56:15, 5.89s/it]
34%|███▍ | 4046/11952 [2:58:00<13:00:06, 5.92s/it]
{'loss': 0.4794, 'learning_rate': 1.541024168243007e-05, 'epoch': 0.34}
+
34%|███▍ | 4046/11952 [2:58:00<13:00:06, 5.92s/it]
34%|███▍ | 4047/11952 [2:58:06<12:49:16, 5.84s/it]
{'loss': 0.4798, 'learning_rate': 1.5407962434763897e-05, 'epoch': 0.34}
+
34%|███▍ | 4047/11952 [2:58:06<12:49:16, 5.84s/it]
34%|███▍ | 4048/11952 [2:58:12<12:42:07, 5.79s/it]
{'loss': 0.4878, 'learning_rate': 1.5405682789959455e-05, 'epoch': 0.34}
+
34%|███▍ | 4048/11952 [2:58:12<12:42:07, 5.79s/it]
34%|███▍ | 4049/11952 [2:58:17<12:39:16, 5.76s/it]
{'loss': 0.5025, 'learning_rate': 1.5403402748184156e-05, 'epoch': 0.34}
+
34%|███▍ | 4049/11952 [2:58:17<12:39:16, 5.76s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
34%|███▍ | 4050/11952 [2:58:24<13:00:00, 5.92s/it]7 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4778, 'learning_rate': 1.5401122309605437e-05, 'epoch': 0.34}
+
34%|███▍ | 4050/11952 [2:58:24<13:00:00, 5.92s/it]
34%|███▍ | 4051/11952 [2:58:29<12:43:33, 5.80s/it]
{'loss': 0.4801, 'learning_rate': 1.5398841474390754e-05, 'epoch': 0.34}
+
34%|███▍ | 4051/11952 [2:58:29<12:43:33, 5.80s/it]
34%|███▍ | 4052/11952 [2:58:35<12:36:23, 5.74s/it]
{'loss': 0.4845, 'learning_rate': 1.5396560242707613e-05, 'epoch': 0.34}
+
34%|███▍ | 4052/11952 [2:58:35<12:36:23, 5.74s/it]
34%|███▍ | 4053/11952 [2:58:41<12:37:37, 5.75s/it]
{'loss': 0.4736, 'learning_rate': 1.5394278614723535e-05, 'epoch': 0.34}
+
34%|███▍ | 4053/11952 [2:58:41<12:37:37, 5.75s/it]
34%|███▍ | 4054/11952 [2:58:47<12:44:59, 5.81s/it]
{'loss': 0.5036, 'learning_rate': 1.5391996590606066e-05, 'epoch': 0.34}
+
34%|███▍ | 4054/11952 [2:58:47<12:44:59, 5.81s/it]
34%|███▍ | 4055/11952 [2:58:52<12:45:41, 5.82s/it]
{'loss': 0.5004, 'learning_rate': 1.53897141705228e-05, 'epoch': 0.34}
+
34%|███▍ | 4055/11952 [2:58:52<12:45:41, 5.82s/it]
34%|███▍ | 4056/11952 [2:58:58<12:49:31, 5.85s/it]
{'loss': 0.4898, 'learning_rate': 1.538743135464134e-05, 'epoch': 0.34}
+
34%|███▍ | 4056/11952 [2:58:58<12:49:31, 5.85s/it]
34%|███▍ | 4057/11952 [2:59:04<12:42:08, 5.79s/it]
{'loss': 0.4723, 'learning_rate': 1.5385148143129328e-05, 'epoch': 0.34}
+
34%|███▍ | 4057/11952 [2:59:04<12:42:08, 5.79s/it]
34%|███▍ | 4058/11952 [2:59:10<12:44:44, 5.81s/it]
{'loss': 0.5157, 'learning_rate': 1.5382864536154437e-05, 'epoch': 0.34}
+
34%|███▍ | 4058/11952 [2:59:10<12:44:44, 5.81s/it]
34%|███▍ | 4059/11952 [2:59:16<12:41:24, 5.79s/it]
{'loss': 0.4803, 'learning_rate': 1.5380580533884364e-05, 'epoch': 0.34}
+
34%|███▍ | 4059/11952 [2:59:16<12:41:24, 5.79s/it]
34%|███▍ | 4060/11952 [2:59:22<12:46:02, 5.82s/it]
{'loss': 0.5016, 'learning_rate': 1.5378296136486837e-05, 'epoch': 0.34}
+
34%|███▍ | 4060/11952 [2:59:22<12:46:02, 5.82s/it]
34%|███▍ | 4061/11952 [2:59:27<12:34:29, 5.74s/it]
{'loss': 0.5045, 'learning_rate': 1.5376011344129608e-05, 'epoch': 0.34}
+
34%|███▍ | 4061/11952 [2:59:27<12:34:29, 5.74s/it]
34%|███▍ | 4062/11952 [2:59:33<12:33:40, 5.73s/it]
{'loss': 0.4805, 'learning_rate': 1.537372615698047e-05, 'epoch': 0.34}
+
34%|███▍ | 4062/11952 [2:59:33<12:33:40, 5.73s/it]
34%|███▍ | 4063/11952 [2:59:39<12:35:36, 5.75s/it]
{'loss': 0.5004, 'learning_rate': 1.5371440575207233e-05, 'epoch': 0.34}
+
34%|███▍ | 4063/11952 [2:59:39<12:35:36, 5.75s/it]
34%|███▍ | 4064/11952 [2:59:44<12:26:51, 5.68s/it]
{'loss': 0.4941, 'learning_rate': 1.536915459897774e-05, 'epoch': 0.34}
+
34%|███▍ | 4064/11952 [2:59:44<12:26:51, 5.68s/it]
34%|███▍ | 4065/11952 [2:59:50<12:30:51, 5.71s/it]
{'loss': 0.4623, 'learning_rate': 1.5366868228459866e-05, 'epoch': 0.34}
+
34%|███▍ | 4065/11952 [2:59:50<12:30:51, 5.71s/it]
34%|███▍ | 4066/11952 [2:59:55<12:26:56, 5.68s/it]
{'loss': 0.4911, 'learning_rate': 1.536458146382151e-05, 'epoch': 0.34}
+
34%|███▍ | 4066/11952 [2:59:55<12:26:56, 5.68s/it]
34%|███▍ | 4067/11952 [3:00:01<12:29:48, 5.71s/it]
{'loss': 0.4749, 'learning_rate': 1.536229430523061e-05, 'epoch': 0.34}
+
34%|███▍ | 4067/11952 [3:00:01<12:29:48, 5.71s/it]
34%|███▍ | 4068/11952 [3:00:07<12:30:58, 5.72s/it]
{'loss': 0.4797, 'learning_rate': 1.5360006752855113e-05, 'epoch': 0.34}
+
34%|███▍ | 4068/11952 [3:00:07<12:30:58, 5.72s/it]
34%|███▍ | 4069/11952 [3:00:13<12:32:11, 5.73s/it]
{'loss': 0.4853, 'learning_rate': 1.535771880686302e-05, 'epoch': 0.34}
+
34%|███▍ | 4069/11952 [3:00:13<12:32:11, 5.73s/it]
34%|███▍ | 4070/11952 [3:00:19<12:44:55, 5.82s/it]
{'loss': 0.4968, 'learning_rate': 1.5355430467422343e-05, 'epoch': 0.34}
+
34%|███▍ | 4070/11952 [3:00:19<12:44:55, 5.82s/it]
34%|███▍ | 4071/11952 [3:00:24<12:39:16, 5.78s/it]
{'loss': 0.4907, 'learning_rate': 1.535314173470112e-05, 'epoch': 0.34}
+
34%|███▍ | 4071/11952 [3:00:24<12:39:16, 5.78s/it]
34%|███▍ | 4072/11952 [3:00:30<12:36:42, 5.76s/it]
{'loss': 0.4847, 'learning_rate': 1.5350852608867436e-05, 'epoch': 0.34}
+
34%|███▍ | 4072/11952 [3:00:30<12:36:42, 5.76s/it]
34%|███▍ | 4073/11952 [3:00:36<12:36:47, 5.76s/it]
{'loss': 0.5151, 'learning_rate': 1.5348563090089394e-05, 'epoch': 0.34}
+
34%|███▍ | 4073/11952 [3:00:36<12:36:47, 5.76s/it]
34%|███▍ | 4074/11952 [3:00:42<12:43:00, 5.81s/it]
{'loss': 0.4775, 'learning_rate': 1.5346273178535126e-05, 'epoch': 0.34}
+
34%|███▍ | 4074/11952 [3:00:42<12:43:00, 5.81s/it]
34%|███▍ | 4075/11952 [3:00:48<12:44:45, 5.83s/it]
{'loss': 0.4907, 'learning_rate': 1.534398287437279e-05, 'epoch': 0.34}
+
34%|███▍ | 4075/11952 [3:00:48<12:44:45, 5.83s/it]
34%|███▍ | 4076/11952 [3:00:53<12:37:55, 5.77s/it]
{'loss': 0.466, 'learning_rate': 1.5341692177770583e-05, 'epoch': 0.34}
+
34%|███▍ | 4076/11952 [3:00:53<12:37:55, 5.77s/it]
34%|███▍ | 4077/11952 [3:00:59<12:23:38, 5.67s/it]
{'loss': 0.5019, 'learning_rate': 1.5339401088896715e-05, 'epoch': 0.34}
+
34%|███▍ | 4077/11952 [3:00:59<12:23:38, 5.67s/it]
34%|███▍ | 4078/11952 [3:01:05<12:30:36, 5.72s/it]
{'loss': 0.4801, 'learning_rate': 1.533710960791944e-05, 'epoch': 0.34}
+
34%|███▍ | 4078/11952 [3:01:05<12:30:36, 5.72s/it]
34%|███▍ | 4079/11952 [3:01:11<12:47:07, 5.85s/it]
{'loss': 0.4967, 'learning_rate': 1.5334817735007037e-05, 'epoch': 0.34}
+
34%|███▍ | 4079/11952 [3:01:11<12:47:07, 5.85s/it]
34%|███▍ | 4080/11952 [3:01:17<12:52:33, 5.89s/it]
{'loss': 0.4966, 'learning_rate': 1.533252547032781e-05, 'epoch': 0.34}
+
34%|███▍ | 4080/11952 [3:01:17<12:52:33, 5.89s/it]
34%|███▍ | 4081/11952 [3:01:23<12:55:20, 5.91s/it]
{'loss': 0.5023, 'learning_rate': 1.533023281405009e-05, 'epoch': 0.34}
+
34%|███▍ | 4081/11952 [3:01:23<12:55:20, 5.91s/it]
34%|███▍ | 4082/11952 [3:01:29<12:54:13, 5.90s/it]
{'loss': 0.5038, 'learning_rate': 1.5327939766342237e-05, 'epoch': 0.34}
+
34%|███▍ | 4082/11952 [3:01:29<12:54:13, 5.90s/it]
34%|███▍ | 4083/11952 [3:01:35<13:06:25, 6.00s/it]
{'loss': 0.4999, 'learning_rate': 1.5325646327372658e-05, 'epoch': 0.34}
+
34%|███▍ | 4083/11952 [3:01:35<13:06:25, 6.00s/it]
34%|███▍ | 4084/11952 [3:01:41<13:00:52, 5.95s/it]
{'loss': 0.4819, 'learning_rate': 1.532335249730976e-05, 'epoch': 0.34}
+
34%|███▍ | 4084/11952 [3:01:41<13:00:52, 5.95s/it]
34%|███▍ | 4085/11952 [3:01:47<12:58:27, 5.94s/it]
{'loss': 0.4924, 'learning_rate': 1.5321058276321988e-05, 'epoch': 0.34}
+
34%|███▍ | 4085/11952 [3:01:47<12:58:27, 5.94s/it]
34%|███▍ | 4086/11952 [3:01:52<12:52:24, 5.89s/it]
{'loss': 0.4895, 'learning_rate': 1.5318763664577838e-05, 'epoch': 0.34}
+
34%|███▍ | 4086/11952 [3:01:52<12:52:24, 5.89s/it]
34%|███▍ | 4087/11952 [3:01:58<12:45:28, 5.84s/it]
{'loss': 0.4882, 'learning_rate': 1.5316468662245805e-05, 'epoch': 0.34}
+
34%|███▍ | 4087/11952 [3:01:58<12:45:28, 5.84s/it]
34%|███▍ | 4088/11952 [3:02:04<12:47:11, 5.85s/it]
{'loss': 0.4849, 'learning_rate': 1.531417326949442e-05, 'epoch': 0.34}
+
34%|███▍ | 4088/11952 [3:02:04<12:47:11, 5.85s/it]
34%|███▍ | 4089/11952 [3:02:10<12:51:22, 5.89s/it]
{'loss': 0.4824, 'learning_rate': 1.5311877486492264e-05, 'epoch': 0.34}
+
34%|███▍ | 4089/11952 [3:02:10<12:51:22, 5.89s/it]
34%|███▍ | 4090/11952 [3:02:16<12:55:41, 5.92s/it]
{'loss': 0.483, 'learning_rate': 1.5309581313407914e-05, 'epoch': 0.34}
+
34%|███▍ | 4090/11952 [3:02:16<12:55:41, 5.92s/it]
34%|███▍ | 4091/11952 [3:02:22<12:51:07, 5.89s/it]
{'loss': 0.4939, 'learning_rate': 1.5307284750409993e-05, 'epoch': 0.34}
+
34%|███▍ | 4091/11952 [3:02:22<12:51:07, 5.89s/it]
34%|███▍ | 4092/11952 [3:02:28<12:49:43, 5.88s/it]
{'loss': 0.5149, 'learning_rate': 1.530498779766716e-05, 'epoch': 0.34}
+
34%|███▍ | 4092/11952 [3:02:28<12:49:43, 5.88s/it]
34%|███▍ | 4093/11952 [3:02:33<12:46:18, 5.85s/it]
{'loss': 0.4828, 'learning_rate': 1.5302690455348085e-05, 'epoch': 0.34}
+
34%|███▍ | 4093/11952 [3:02:33<12:46:18, 5.85s/it]
34%|███▍ | 4094/11952 [3:02:39<12:45:03, 5.84s/it]
{'loss': 0.4805, 'learning_rate': 1.530039272362148e-05, 'epoch': 0.34}
+
34%|███▍ | 4094/11952 [3:02:39<12:45:03, 5.84s/it]
34%|███▍ | 4095/11952 [3:02:45<12:41:34, 5.82s/it]
{'loss': 0.4946, 'learning_rate': 1.5298094602656077e-05, 'epoch': 0.34}
+
34%|███▍ | 4095/11952 [3:02:45<12:41:34, 5.82s/it]
34%|███▍ | 4096/11952 [3:02:50<12:26:18, 5.70s/it]
{'loss': 0.4826, 'learning_rate': 1.5295796092620646e-05, 'epoch': 0.34}
+
34%|███▍ | 4096/11952 [3:02:50<12:26:18, 5.70s/it]
34%|███▍ | 4097/11952 [3:02:56<12:38:37, 5.79s/it]
{'loss': 0.5091, 'learning_rate': 1.5293497193683974e-05, 'epoch': 0.34}
+
34%|███▍ | 4097/11952 [3:02:56<12:38:37, 5.79s/it]
34%|███▍ | 4098/11952 [3:03:02<12:31:32, 5.74s/it]
{'loss': 0.4893, 'learning_rate': 1.5291197906014886e-05, 'epoch': 0.34}
+
34%|███▍ | 4098/11952 [3:03:02<12:31:32, 5.74s/it]
34%|███▍ | 4099/11952 [3:03:08<12:28:49, 5.72s/it]
{'loss': 0.4873, 'learning_rate': 1.5288898229782234e-05, 'epoch': 0.34}
+
34%|███▍ | 4099/11952 [3:03:08<12:28:49, 5.72s/it]5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ 4 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
34%|███▍ | 4100/11952 [3:03:14<12:45:41, 5.85s/it]
{'loss': 0.4815, 'learning_rate': 1.5286598165154892e-05, 'epoch': 0.34}
+
34%|███▍ | 4100/11952 [3:03:14<12:45:41, 5.85s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
34%|███▍ | 4101/11952 [3:03:46<30:07:28, 13.81s/it]
{'loss': 0.4878, 'learning_rate': 1.5284297712301773e-05, 'epoch': 0.34}
+
34%|███▍ | 4101/11952 [3:03:46<30:07:28, 13.81s/it]
34%|███▍ | 4102/11952 [3:03:52<24:52:19, 11.41s/it]
{'loss': 0.4834, 'learning_rate': 1.5281996871391805e-05, 'epoch': 0.34}
+
34%|███▍ | 4102/11952 [3:03:52<24:52:19, 11.41s/it]
34%|███▍ | 4103/11952 [3:04:01<23:02:09, 10.57s/it]
{'loss': 0.4621, 'learning_rate': 1.5279695642593958e-05, 'epoch': 0.34}
+
34%|███▍ | 4103/11952 [3:04:01<23:02:09, 10.57s/it]
34%|███▍ | 4104/11952 [3:04:06<19:56:20, 9.15s/it]
{'loss': 0.4742, 'learning_rate': 1.527739402607722e-05, 'epoch': 0.34}
+
34%|███▍ | 4104/11952 [3:04:06<19:56:20, 9.15s/it]
34%|███▍ | 4105/11952 [3:04:12<17:36:48, 8.08s/it]
{'loss': 0.4787, 'learning_rate': 1.527509202201062e-05, 'epoch': 0.34}
+
34%|███▍ | 4105/11952 [3:04:12<17:36:48, 8.08s/it]
34%|███▍ | 4106/11952 [3:04:18<16:05:03, 7.38s/it]
{'loss': 0.495, 'learning_rate': 1.5272789630563202e-05, 'epoch': 0.34}
+
34%|███▍ | 4106/11952 [3:04:18<16:05:03, 7.38s/it]
34%|███▍ | 4107/11952 [3:04:24<15:00:58, 6.89s/it]
{'loss': 0.495, 'learning_rate': 1.527048685190404e-05, 'epoch': 0.34}
+
34%|███▍ | 4107/11952 [3:04:24<15:00:58, 6.89s/it]
34%|███▍ | 4108/11952 [3:04:29<14:11:26, 6.51s/it]
{'loss': 0.51, 'learning_rate': 1.5268183686202245e-05, 'epoch': 0.34}
+
34%|███▍ | 4108/11952 [3:04:29<14:11:26, 6.51s/it]
34%|███▍ | 4109/11952 [3:04:35<13:44:51, 6.31s/it]
{'loss': 0.4721, 'learning_rate': 1.5265880133626956e-05, 'epoch': 0.34}
+
34%|███▍ | 4109/11952 [3:04:35<13:44:51, 6.31s/it]
34%|███▍ | 4110/11952 [3:04:41<13:33:32, 6.22s/it]
{'loss': 0.498, 'learning_rate': 1.5263576194347334e-05, 'epoch': 0.34}
+
34%|███▍ | 4110/11952 [3:04:41<13:33:32, 6.22s/it]
34%|███▍ | 4111/11952 [3:04:47<13:18:06, 6.11s/it]
{'loss': 0.5005, 'learning_rate': 1.5261271868532568e-05, 'epoch': 0.34}
+
34%|███▍ | 4111/11952 [3:04:47<13:18:06, 6.11s/it]
34%|███▍ | 4112/11952 [3:04:53<13:00:20, 5.97s/it]
{'loss': 0.4735, 'learning_rate': 1.5258967156351878e-05, 'epoch': 0.34}
+
34%|███▍ | 4112/11952 [3:04:53<13:00:20, 5.97s/it]
34%|███▍ | 4113/11952 [3:04:58<12:53:52, 5.92s/it]
{'loss': 0.4863, 'learning_rate': 1.525666205797451e-05, 'epoch': 0.34}
+
34%|███▍ | 4113/11952 [3:04:58<12:53:52, 5.92s/it]
34%|███▍ | 4114/11952 [3:05:05<13:07:18, 6.03s/it]
{'loss': 0.4886, 'learning_rate': 1.5254356573569748e-05, 'epoch': 0.34}
+
34%|███▍ | 4114/11952 [3:05:05<13:07:18, 6.03s/it]
34%|███▍ | 4115/11952 [3:05:10<12:55:22, 5.94s/it]
{'loss': 0.4866, 'learning_rate': 1.5252050703306895e-05, 'epoch': 0.34}
+
34%|███▍ | 4115/11952 [3:05:10<12:55:22, 5.94s/it]
34%|███▍ | 4116/11952 [3:05:16<12:46:24, 5.87s/it]
{'loss': 0.5044, 'learning_rate': 1.5249744447355282e-05, 'epoch': 0.34}
+
34%|███▍ | 4116/11952 [3:05:16<12:46:24, 5.87s/it]
34%|███▍ | 4117/11952 [3:05:22<12:43:41, 5.85s/it]
{'loss': 0.4863, 'learning_rate': 1.5247437805884273e-05, 'epoch': 0.34}
+
34%|███▍ | 4117/11952 [3:05:22<12:43:41, 5.85s/it]
34%|███▍ | 4118/11952 [3:05:28<12:54:26, 5.93s/it]
{'loss': 0.5085, 'learning_rate': 1.5245130779063255e-05, 'epoch': 0.34}
+
34%|███▍ | 4118/11952 [3:05:28<12:54:26, 5.93s/it]
34%|███▍ | 4119/11952 [3:05:34<12:40:03, 5.82s/it]
{'loss': 0.4725, 'learning_rate': 1.524282336706165e-05, 'epoch': 0.34}
+
34%|███▍ | 4119/11952 [3:05:34<12:40:03, 5.82s/it]
34%|███▍ | 4120/11952 [3:05:39<12:35:30, 5.79s/it]
{'loss': 0.4866, 'learning_rate': 1.5240515570048903e-05, 'epoch': 0.34}
+
34%|███▍ | 4120/11952 [3:05:39<12:35:30, 5.79s/it]
34%|███▍ | 4121/11952 [3:05:45<12:46:59, 5.88s/it]
{'loss': 0.485, 'learning_rate': 1.5238207388194493e-05, 'epoch': 0.34}
+
34%|███▍ | 4121/11952 [3:05:45<12:46:59, 5.88s/it]
34%|███▍ | 4122/11952 [3:05:51<12:46:14, 5.87s/it]
{'loss': 0.5004, 'learning_rate': 1.5235898821667916e-05, 'epoch': 0.34}
+
34%|███▍ | 4122/11952 [3:05:51<12:46:14, 5.87s/it]
34%|███▍ | 4123/11952 [3:05:57<12:34:01, 5.78s/it]
{'loss': 0.4852, 'learning_rate': 1.5233589870638708e-05, 'epoch': 0.34}
+
34%|███▍ | 4123/11952 [3:05:57<12:34:01, 5.78s/it]
35%|███▍ | 4124/11952 [3:06:03<12:33:07, 5.77s/it]
{'loss': 0.4778, 'learning_rate': 1.5231280535276426e-05, 'epoch': 0.35}
+
35%|███▍ | 4124/11952 [3:06:03<12:33:07, 5.77s/it]
35%|███▍ | 4125/11952 [3:06:08<12:24:24, 5.71s/it]
{'loss': 0.4932, 'learning_rate': 1.5228970815750666e-05, 'epoch': 0.35}
+
35%|███▍ | 4125/11952 [3:06:08<12:24:24, 5.71s/it]
35%|███▍ | 4126/11952 [3:06:14<12:25:41, 5.72s/it]
{'loss': 0.4973, 'learning_rate': 1.5226660712231032e-05, 'epoch': 0.35}
+
35%|███▍ | 4126/11952 [3:06:14<12:25:41, 5.72s/it]
35%|███▍ | 4127/11952 [3:06:19<12:23:33, 5.70s/it]
{'loss': 0.4899, 'learning_rate': 1.5224350224887179e-05, 'epoch': 0.35}
+
35%|███▍ | 4127/11952 [3:06:19<12:23:33, 5.70s/it]
35%|███▍ | 4128/11952 [3:06:25<12:18:42, 5.66s/it]
{'loss': 0.4763, 'learning_rate': 1.5222039353888774e-05, 'epoch': 0.35}
+
35%|███▍ | 4128/11952 [3:06:25<12:18:42, 5.66s/it]
35%|███▍ | 4129/11952 [3:06:31<12:20:27, 5.68s/it]
{'loss': 0.4994, 'learning_rate': 1.5219728099405516e-05, 'epoch': 0.35}
+
35%|███▍ | 4129/11952 [3:06:31<12:20:27, 5.68s/it]
35%|███▍ | 4130/11952 [3:06:37<12:26:36, 5.73s/it]
{'loss': 0.4798, 'learning_rate': 1.521741646160714e-05, 'epoch': 0.35}
+
35%|███▍ | 4130/11952 [3:06:37<12:26:36, 5.73s/it]
35%|███▍ | 4131/11952 [3:06:42<12:32:16, 5.77s/it]
{'loss': 0.4698, 'learning_rate': 1.5215104440663399e-05, 'epoch': 0.35}
+
35%|███▍ | 4131/11952 [3:06:42<12:32:16, 5.77s/it]
35%|███▍ | 4132/11952 [3:06:51<14:08:55, 6.51s/it]
{'loss': 0.472, 'learning_rate': 1.521279203674408e-05, 'epoch': 0.35}
+
35%|███▍ | 4132/11952 [3:06:51<14:08:55, 6.51s/it]
35%|███▍ | 4133/11952 [3:06:56<13:39:34, 6.29s/it]
{'loss': 0.4933, 'learning_rate': 1.5210479250018995e-05, 'epoch': 0.35}
+
35%|███▍ | 4133/11952 [3:06:56<13:39:34, 6.29s/it]
35%|███▍ | 4134/11952 [3:07:02<13:14:14, 6.10s/it]
{'loss': 0.4828, 'learning_rate': 1.5208166080657982e-05, 'epoch': 0.35}
+
35%|███▍ | 4134/11952 [3:07:02<13:14:14, 6.10s/it]
35%|███▍ | 4135/11952 [3:07:08<13:03:20, 6.01s/it]
{'loss': 0.497, 'learning_rate': 1.520585252883092e-05, 'epoch': 0.35}
+
35%|███▍ | 4135/11952 [3:07:08<13:03:20, 6.01s/it]WARNING: tokenization mismatch: 1 vs. 1440. [[{'from': 'human', 'value': 'ASSISTANT: Du bist ein Personalmarketing-Experte mit den folgenden Kenntnissen und Eigenschaften.\n\nKENNTNISSE: Personalmarketing, Social Media Marketing, Facebook-Marketing, Kampagnenentwicklung, Zielgruppenanalyse, Content-Strategie, Werbeanzeigen, Performance-Messung, Personalgewinnung, Steuerfachangestellte.\n\nEIGENSCHAFTEN: Kreativ, strategisch, analytisch, kommunikativ, zielorientiert, detailverliebt, teamorientiert.\n\nAUFGABE: Entwickle eine erfolgreiche Personalmarketing-Strategie für die Gewinnung von Steuerfachangestellten über Facebook. Erstelle eine Tabelle mit allen Maßnahmen und weise jeder Maßnahme den zuständigen Spezialisten in einer Marketingagentur zu. Achte dabei auf Zielgruppenanalyse, Content-Strategie, Werbeanzeigen und Performance-Messung.\n\nOUTPUT: Eine Tabelle mit allen Maßnahmen für eine erfolgreiche Personalmarketing-Kampagne zur Gewinnung von Steuerfachangestellten auf Facebook, die die Verantwortlichkeiten der Spezialisten in einer Marketingagentur aufzeigt, einschließlich Zielgruppenanalyse, Content-Strategie, Werbeanzeigen und Performance-Messung.'}, {'from': 'gpt', 'value': '| Maßnahme | Beschreibung | Zuständiger Spezialist |\n| --- | --- | --- |\n| Zielgruppenanalyse | Analyse der demografischen Daten, Interessen und Verhaltensweisen der potenziellen Bewerber. | Marktanalyst |\n| Erstellung von Personas | Entwicklung von fiktiven, repräsentativen Bewerberprofilen zur besseren Zielgruppenansprache. | Personalmarketing-Experte |\n| Content-Strategie | Planung von relevantem, ansprechendem und zielgruppenspezifischem Content. | Content-Stratege |\n| Redaktionsplan | Erstellung eines Zeitplans für die Veröffentlichung von Inhalten auf Facebook. | Social Media Manager |\n| Erstellung von Werbeanzeigen | Design und Texten von ansprechenden, zielgruppenspezifischen Facebook-Werbeanzeigen. | Art Director & Copywriter |\n| Auswahl von Targeting-Optionen | Festlegung der Zielgruppenparameter für die Facebook-Werbekampagnen. | Facebook-Marketing-Experte |\n| Budgetierung und Zeitplanung | Festlegung des Budgets und der Laufzeit für die Facebook-Werbekampagnen. | Media Planner |\n| Erstellung von Landing Pages | Gestaltung und Implementierung von spezifischen Landing Pages für die Bewerbung. | Web-Designer |\n| Performance-Messung | Überwachung und Analyse der Kampagnenleistung, einschließlich KPIs wie Klicks und Bewerbungen. | Data Analyst |\n| A/B-Testing | Durchführung von A/B-Tests, um die Effektivität von Anzeigen und Landing Pages zu optimieren. | Conversion-Optimierungsexperte |\n| Community-Management | Interaktion mit der Zielgruppe auf Facebook, Beantwortung von Fragen und Moderation von Diskussionen. | Community Manager |\n| Reporting und Optimierung | Regelmäßige Berichterstattung über die Kampagnenergebnisse und Anpassung der Strategie. | Performance Marketing-Manager |'}, {'from': 'human', 'value': 'Weiter.'}, {'from': 'gpt', 'value': 'Hier sind einige zusätzliche Maßnahmen, die Sie in Ihre Personalmarketing-Strategie für die Gewinnung von Steuerfachangestellten über Facebook einbeziehen können:\n\n| Maßnahme | Beschreibung | Zuständiger Spezialist |\n| --- | --- | --- |\n| Video-Content | Erstellung von Video-Content, wie Interviews mit aktuellen Mitarbeitern oder Berufsalltagsvideos. | Videoproduzent |\n| Influencer-Marketing | Zusammenarbeit mit Influencern aus der Branche, um Ihre Arbeitgebermarke zu stärken. | Influencer-Marketing-Experte |\n| Anpassung von Stellenanzeigen | Anpassung der Stellenanzeigen auf Facebook, um die Zielgruppe besser anzusprechen. | Personalmarketing-Experte |\n| Mitarbeiter-Testimonials | Teilen von Erfahrungsberichten und Zitaten der Mitarbeiter auf Facebook, um Authentizität zu schaffen. | Content-Stratege |\n| Virtuelle Karriere-Events | Durchführung von virtuellen Karriere-Events oder Informationsveranstaltungen auf Facebook. | Event-Manager |\n| Interaktive Umfragen und Quiz | Nutzung von interaktiven Umfragen und Quiz auf Facebook, um das Engagement zu erhöhen. | Social Media Manager |\n| Remarketing-Kampagnen | Einsatz von Remarketing-Anzeigen, um die Personen erneut anzusprechen, die bereits interessiert waren. | Facebook-Marketing-Experte |\n| Monitoring von Wettbewerbern | Beobachtung der Personalmarketing-Aktivitäten der Wettbewerber auf Facebook und Ableitung von Optimierungspotenzialen. | Marktanalyst |\n| Integration von Chatbots | Implementierung von Chatbots auf der Facebook-Seite und der Landing Page zur Automatisierung des Bewerbungsprozesses. | Chatbot-Entwickler |\n| Employer Branding-Kampagne | Entwicklung einer Employer Branding-Kampagne, die die Unternehmenskultur und -werte hervorhebt. | Employer Branding-Experte |\n\nMit diesen erweiterten Maßnahmen können Sie eine noch umfassendere Personalmarketing-Strategie entwickeln, die die Chancen erhöht, qualifizierte Steuerfachangestellte über Facebook zu gewinnen.'}]] (ignored)
+
35%|███▍ | 4136/11952 [3:07:14<12:48:52, 5.90s/it]
{'loss': 0.4824, 'learning_rate': 1.5203538594707699e-05, 'epoch': 0.35}
+
35%|███▍ | 4136/11952 [3:07:14<12:48:52, 5.90s/it]
35%|███▍ | 4137/11952 [3:07:19<12:42:11, 5.85s/it]
{'loss': 0.4743, 'learning_rate': 1.520122427845825e-05, 'epoch': 0.35}
+
35%|███▍ | 4137/11952 [3:07:19<12:42:11, 5.85s/it]
35%|███▍ | 4138/11952 [3:07:28<14:47:03, 6.81s/it]
{'loss': 0.5035, 'learning_rate': 1.5198909580252517e-05, 'epoch': 0.35}
+
35%|███▍ | 4138/11952 [3:07:28<14:47:03, 6.81s/it]
35%|███▍ | 4139/11952 [3:07:34<14:11:51, 6.54s/it]
{'loss': 0.5019, 'learning_rate': 1.519659450026049e-05, 'epoch': 0.35}
+
35%|███▍ | 4139/11952 [3:07:34<14:11:51, 6.54s/it]
35%|███▍ | 4140/11952 [3:07:40<13:39:37, 6.30s/it]
{'loss': 0.5058, 'learning_rate': 1.519427903865218e-05, 'epoch': 0.35}
+
35%|███▍ | 4140/11952 [3:07:40<13:39:37, 6.30s/it]
35%|███▍ | 4141/11952 [3:07:46<13:42:09, 6.32s/it]
{'loss': 0.4959, 'learning_rate': 1.519196319559762e-05, 'epoch': 0.35}
+
35%|███▍ | 4141/11952 [3:07:46<13:42:09, 6.32s/it]
35%|███▍ | 4142/11952 [3:07:55<14:53:53, 6.87s/it]
{'loss': 0.4922, 'learning_rate': 1.518964697126688e-05, 'epoch': 0.35}
+
35%|███▍ | 4142/11952 [3:07:55<14:53:53, 6.87s/it]
35%|███▍ | 4143/11952 [3:08:00<14:05:01, 6.49s/it]
{'loss': 0.5021, 'learning_rate': 1.518733036583005e-05, 'epoch': 0.35}
+
35%|███▍ | 4143/11952 [3:08:00<14:05:01, 6.49s/it]
35%|███▍ | 4144/11952 [3:08:06<13:52:56, 6.40s/it]
{'loss': 0.4927, 'learning_rate': 1.5185013379457254e-05, 'epoch': 0.35}
+
35%|███▍ | 4144/11952 [3:08:06<13:52:56, 6.40s/it]
35%|███▍ | 4145/11952 [3:08:15<15:38:18, 7.21s/it]
{'loss': 0.5034, 'learning_rate': 1.5182696012318641e-05, 'epoch': 0.35}
+
35%|███▍ | 4145/11952 [3:08:15<15:38:18, 7.21s/it]
35%|███▍ | 4146/11952 [3:08:21<14:36:41, 6.74s/it]
{'loss': 0.498, 'learning_rate': 1.518037826458439e-05, 'epoch': 0.35}
+
35%|███▍ | 4146/11952 [3:08:21<14:36:41, 6.74s/it]
35%|███▍ | 4147/11952 [3:08:30<16:17:35, 7.52s/it]
{'loss': 0.5033, 'learning_rate': 1.5178060136424706e-05, 'epoch': 0.35}
+
35%|███▍ | 4147/11952 [3:08:30<16:17:35, 7.52s/it]
35%|███▍ | 4148/11952 [3:08:36<15:09:46, 6.99s/it]
{'loss': 0.4818, 'learning_rate': 1.5175741628009824e-05, 'epoch': 0.35}
+
35%|███▍ | 4148/11952 [3:08:36<15:09:46, 6.99s/it]
35%|███▍ | 4149/11952 [3:08:42<14:20:38, 6.62s/it]
{'loss': 0.5017, 'learning_rate': 1.5173422739510003e-05, 'epoch': 0.35}
+
35%|███▍ | 4149/11952 [3:08:42<14:20:38, 6.62s/it]3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+74 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+ AutoResumeHook: Checking whether to suspend...
+
35%|███▍ | 4150/11952 [3:08:48<13:50:58, 6.39s/it]
{'loss': 0.4716, 'learning_rate': 1.5171103471095533e-05, 'epoch': 0.35}
+
35%|███▍ | 4150/11952 [3:08:48<13:50:58, 6.39s/it]
35%|███▍ | 4151/11952 [3:08:53<13:23:42, 6.18s/it]
{'loss': 0.4648, 'learning_rate': 1.5168783822936735e-05, 'epoch': 0.35}
+
35%|███▍ | 4151/11952 [3:08:53<13:23:42, 6.18s/it]
35%|███▍ | 4152/11952 [3:08:59<13:00:19, 6.00s/it]
{'loss': 0.4952, 'learning_rate': 1.516646379520395e-05, 'epoch': 0.35}
+
35%|███▍ | 4152/11952 [3:08:59<13:00:19, 6.00s/it]
35%|███▍ | 4153/11952 [3:09:05<12:51:29, 5.94s/it]
{'loss': 0.4907, 'learning_rate': 1.5164143388067554e-05, 'epoch': 0.35}
+
35%|███▍ | 4153/11952 [3:09:05<12:51:29, 5.94s/it]
35%|███▍ | 4154/11952 [3:09:11<12:53:47, 5.95s/it]
{'loss': 0.4882, 'learning_rate': 1.5161822601697945e-05, 'epoch': 0.35}
+
35%|███▍ | 4154/11952 [3:09:11<12:53:47, 5.95s/it]
35%|███▍ | 4155/11952 [3:09:17<12:47:57, 5.91s/it]
{'loss': 0.4774, 'learning_rate': 1.5159501436265553e-05, 'epoch': 0.35}
+
35%|███▍ | 4155/11952 [3:09:17<12:47:57, 5.91s/it]
35%|███▍ | 4156/11952 [3:09:22<12:45:09, 5.89s/it]
{'loss': 0.4901, 'learning_rate': 1.5157179891940837e-05, 'epoch': 0.35}
+
35%|███▍ | 4156/11952 [3:09:22<12:45:09, 5.89s/it]
35%|███▍ | 4157/11952 [3:09:28<12:33:27, 5.80s/it]
{'loss': 0.4773, 'learning_rate': 1.5154857968894278e-05, 'epoch': 0.35}
+
35%|███▍ | 4157/11952 [3:09:28<12:33:27, 5.80s/it]
35%|███▍ | 4158/11952 [3:09:34<12:37:20, 5.83s/it]
{'loss': 0.4894, 'learning_rate': 1.5152535667296395e-05, 'epoch': 0.35}
+
35%|███▍ | 4158/11952 [3:09:34<12:37:20, 5.83s/it]
35%|███▍ | 4159/11952 [3:09:40<12:34:07, 5.81s/it]
{'loss': 0.4976, 'learning_rate': 1.5150212987317721e-05, 'epoch': 0.35}
+
35%|███▍ | 4159/11952 [3:09:40<12:34:07, 5.81s/it]
35%|███▍ | 4160/11952 [3:09:45<12:29:30, 5.77s/it]
{'loss': 0.4964, 'learning_rate': 1.5147889929128825e-05, 'epoch': 0.35}
+
35%|███▍ | 4160/11952 [3:09:45<12:29:30, 5.77s/it]WARNING: tokenization mismatch: 1 vs. 64. [[{'from': 'human', 'value': '\nWhat vitamin is this vegetable associated with?\nAnswer the question using a single word or phrase.'}, {'from': 'gpt', 'value': ''}]] (ignored)
+
35%|███▍ | 4161/11952 [3:09:51<12:35:05, 5.82s/it]
{'loss': 0.4747, 'learning_rate': 1.5145566492900305e-05, 'epoch': 0.35}
+
35%|███▍ | 4161/11952 [3:09:51<12:35:05, 5.82s/it]
35%|███▍ | 4162/11952 [3:09:57<12:33:35, 5.80s/it]
{'loss': 0.4627, 'learning_rate': 1.5143242678802787e-05, 'epoch': 0.35}
+
35%|███▍ | 4162/11952 [3:09:57<12:33:35, 5.80s/it]
35%|███▍ | 4163/11952 [3:10:03<12:31:59, 5.79s/it]
{'loss': 0.483, 'learning_rate': 1.5140918487006918e-05, 'epoch': 0.35}
+
35%|███▍ | 4163/11952 [3:10:03<12:31:59, 5.79s/it]
35%|███▍ | 4164/11952 [3:10:08<12:24:36, 5.74s/it]
{'loss': 0.4939, 'learning_rate': 1.5138593917683374e-05, 'epoch': 0.35}
+
35%|███▍ | 4164/11952 [3:10:08<12:24:36, 5.74s/it]
35%|███▍ | 4165/11952 [3:10:15<12:39:17, 5.85s/it]
{'loss': 0.4938, 'learning_rate': 1.513626897100287e-05, 'epoch': 0.35}
+
35%|███▍ | 4165/11952 [3:10:15<12:39:17, 5.85s/it]
35%|███▍ | 4166/11952 [3:10:21<12:42:36, 5.88s/it]
{'loss': 0.4925, 'learning_rate': 1.5133943647136131e-05, 'epoch': 0.35}
+
35%|███▍ | 4166/11952 [3:10:21<12:42:36, 5.88s/it]
35%|███▍ | 4167/11952 [3:10:26<12:29:44, 5.78s/it]
{'loss': 0.4871, 'learning_rate': 1.5131617946253928e-05, 'epoch': 0.35}
+
35%|███▍ | 4167/11952 [3:10:26<12:29:44, 5.78s/it]
35%|███▍ | 4168/11952 [3:10:32<12:36:35, 5.83s/it]
{'loss': 0.4939, 'learning_rate': 1.5129291868527052e-05, 'epoch': 0.35}
+
35%|███▍ | 4168/11952 [3:10:32<12:36:35, 5.83s/it]
35%|███▍ | 4169/11952 [3:10:38<12:31:10, 5.79s/it]
{'loss': 0.4752, 'learning_rate': 1.5126965414126309e-05, 'epoch': 0.35}
+
35%|███▍ | 4169/11952 [3:10:38<12:31:10, 5.79s/it]
35%|███▍ | 4170/11952 [3:10:44<12:39:07, 5.85s/it]
{'loss': 0.4781, 'learning_rate': 1.512463858322255e-05, 'epoch': 0.35}
+
35%|███▍ | 4170/11952 [3:10:44<12:39:07, 5.85s/it]
35%|███▍ | 4171/11952 [3:10:50<12:53:23, 5.96s/it]
{'loss': 0.4782, 'learning_rate': 1.5122311375986649e-05, 'epoch': 0.35}
+
35%|███▍ | 4171/11952 [3:10:50<12:53:23, 5.96s/it]
35%|███▍ | 4172/11952 [3:10:56<12:51:32, 5.95s/it]
{'loss': 0.4739, 'learning_rate': 1.511998379258951e-05, 'epoch': 0.35}
+
35%|███▍ | 4172/11952 [3:10:56<12:51:32, 5.95s/it]
35%|███▍ | 4173/11952 [3:11:02<12:43:07, 5.89s/it]
{'loss': 0.5065, 'learning_rate': 1.5117655833202052e-05, 'epoch': 0.35}
+
35%|███▍ | 4173/11952 [3:11:02<12:43:07, 5.89s/it]
35%|███▍ | 4174/11952 [3:11:08<12:48:45, 5.93s/it]
{'loss': 0.5288, 'learning_rate': 1.5115327497995238e-05, 'epoch': 0.35}
+
35%|███▍ | 4174/11952 [3:11:08<12:48:45, 5.93s/it]
35%|███▍ | 4175/11952 [3:11:14<12:58:44, 6.01s/it]
{'loss': 0.4939, 'learning_rate': 1.511299878714005e-05, 'epoch': 0.35}
+
35%|███▍ | 4175/11952 [3:11:14<12:58:44, 6.01s/it]
35%|███▍ | 4176/11952 [3:11:20<12:48:00, 5.93s/it]
{'loss': 0.5027, 'learning_rate': 1.5110669700807496e-05, 'epoch': 0.35}
+
35%|███▍ | 4176/11952 [3:11:20<12:48:00, 5.93s/it]
35%|███▍ | 4177/11952 [3:11:26<12:49:57, 5.94s/it]
{'loss': 0.5097, 'learning_rate': 1.5108340239168614e-05, 'epoch': 0.35}
+
35%|███▍ | 4177/11952 [3:11:26<12:49:57, 5.94s/it]
35%|███▍ | 4178/11952 [3:11:32<12:56:17, 5.99s/it]
{'loss': 0.4741, 'learning_rate': 1.5106010402394477e-05, 'epoch': 0.35}
+
35%|███▍ | 4178/11952 [3:11:32<12:56:17, 5.99s/it]
35%|███▍ | 4179/11952 [3:11:37<12:42:00, 5.88s/it]
{'loss': 0.4856, 'learning_rate': 1.5103680190656169e-05, 'epoch': 0.35}
+
35%|███▍ | 4179/11952 [3:11:37<12:42:00, 5.88s/it]
35%|███▍ | 4180/11952 [3:11:43<12:34:47, 5.83s/it]
{'loss': 0.5238, 'learning_rate': 1.5101349604124816e-05, 'epoch': 0.35}
+
35%|███▍ | 4180/11952 [3:11:43<12:34:47, 5.83s/it]
35%|███▍ | 4181/11952 [3:11:49<12:23:01, 5.74s/it]
{'loss': 0.4797, 'learning_rate': 1.5099018642971568e-05, 'epoch': 0.35}
+
35%|███▍ | 4181/11952 [3:11:49<12:23:01, 5.74s/it]
35%|███▍ | 4182/11952 [3:11:54<12:31:41, 5.80s/it]
{'loss': 0.5027, 'learning_rate': 1.5096687307367601e-05, 'epoch': 0.35}
+
35%|███▍ | 4182/11952 [3:11:54<12:31:41, 5.80s/it]
35%|███▍ | 4183/11952 [3:12:00<12:31:17, 5.80s/it]
{'loss': 0.481, 'learning_rate': 1.5094355597484111e-05, 'epoch': 0.35}
+
35%|███▍ | 4183/11952 [3:12:00<12:31:17, 5.80s/it]
35%|███▌ | 4184/11952 [3:12:06<12:30:10, 5.79s/it]
{'loss': 0.5015, 'learning_rate': 1.509202351349234e-05, 'epoch': 0.35}
+
35%|███▌ | 4184/11952 [3:12:06<12:30:10, 5.79s/it]
35%|███▌ | 4185/11952 [3:12:12<12:25:30, 5.76s/it]
{'loss': 0.4847, 'learning_rate': 1.508969105556354e-05, 'epoch': 0.35}
+
35%|███▌ | 4185/11952 [3:12:12<12:25:30, 5.76s/it]
35%|███▌ | 4186/11952 [3:12:18<12:32:13, 5.81s/it]
{'loss': 0.4803, 'learning_rate': 1.5087358223869e-05, 'epoch': 0.35}
+
35%|███▌ | 4186/11952 [3:12:18<12:32:13, 5.81s/it]
35%|███▌ | 4187/11952 [3:12:24<12:33:54, 5.83s/it]
{'loss': 0.4904, 'learning_rate': 1.5085025018580029e-05, 'epoch': 0.35}
+
35%|███▌ | 4187/11952 [3:12:24<12:33:54, 5.83s/it]
35%|███▌ | 4188/11952 [3:12:29<12:37:28, 5.85s/it]
{'loss': 0.4654, 'learning_rate': 1.5082691439867973e-05, 'epoch': 0.35}
+
35%|███▌ | 4188/11952 [3:12:29<12:37:28, 5.85s/it]
35%|███▌ | 4189/11952 [3:12:35<12:42:16, 5.89s/it]
{'loss': 0.4828, 'learning_rate': 1.5080357487904198e-05, 'epoch': 0.35}
+
35%|███▌ | 4189/11952 [3:12:35<12:42:16, 5.89s/it]
35%|███▌ | 4190/11952 [3:12:42<13:01:16, 6.04s/it]
{'loss': 0.5049, 'learning_rate': 1.5078023162860099e-05, 'epoch': 0.35}
+
35%|███▌ | 4190/11952 [3:12:42<13:01:16, 6.04s/it]
35%|███▌ | 4191/11952 [3:12:48<12:49:31, 5.95s/it]
{'loss': 0.4923, 'learning_rate': 1.5075688464907099e-05, 'epoch': 0.35}
+
35%|███▌ | 4191/11952 [3:12:48<12:49:31, 5.95s/it]
35%|███▌ | 4192/11952 [3:12:53<12:47:32, 5.93s/it]
{'loss': 0.4693, 'learning_rate': 1.5073353394216652e-05, 'epoch': 0.35}
+
35%|███▌ | 4192/11952 [3:12:53<12:47:32, 5.93s/it]
35%|███▌ | 4193/11952 [3:12:59<12:44:15, 5.91s/it]
{'loss': 0.4917, 'learning_rate': 1.5071017950960234e-05, 'epoch': 0.35}
+
35%|███▌ | 4193/11952 [3:12:59<12:44:15, 5.91s/it]
35%|███▌ | 4194/11952 [3:13:05<12:47:48, 5.94s/it]
{'loss': 0.495, 'learning_rate': 1.5068682135309347e-05, 'epoch': 0.35}
+
35%|███▌ | 4194/11952 [3:13:05<12:47:48, 5.94s/it]
35%|███▌ | 4195/11952 [3:13:11<12:42:06, 5.89s/it]
{'loss': 0.4869, 'learning_rate': 1.5066345947435525e-05, 'epoch': 0.35}
+
35%|███▌ | 4195/11952 [3:13:11<12:42:06, 5.89s/it]
35%|███▌ | 4196/11952 [3:13:17<12:39:02, 5.87s/it]
{'loss': 0.4836, 'learning_rate': 1.5064009387510333e-05, 'epoch': 0.35}
+
35%|███▌ | 4196/11952 [3:13:17<12:39:02, 5.87s/it]
35%|███▌ | 4197/11952 [3:13:23<12:52:17, 5.98s/it]
{'loss': 0.4999, 'learning_rate': 1.5061672455705352e-05, 'epoch': 0.35}
+
35%|███▌ | 4197/11952 [3:13:23<12:52:17, 5.98s/it]
35%|███▌ | 4198/11952 [3:13:29<12:53:53, 5.99s/it]
{'loss': 0.5058, 'learning_rate': 1.50593351521922e-05, 'epoch': 0.35}
+
35%|███▌ | 4198/11952 [3:13:29<12:53:53, 5.99s/it]
35%|███▌ | 4199/11952 [3:13:35<12:55:17, 6.00s/it]
{'loss': 0.4897, 'learning_rate': 1.505699747714252e-05, 'epoch': 0.35}
+
35%|███▌ | 4199/11952 [3:13:35<12:55:17, 6.00s/it]2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...4
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
35%|███▌ | 4200/11952 [3:13:41<13:04:45, 6.07s/it]
{'loss': 0.4752, 'learning_rate': 1.5054659430727974e-05, 'epoch': 0.35}
+
35%|███▌ | 4200/11952 [3:13:41<13:04:45, 6.07s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
35%|███▌ | 4201/11952 [3:14:13<29:50:44, 13.86s/it]
{'loss': 0.4942, 'learning_rate': 1.5052321013120263e-05, 'epoch': 0.35}
+
35%|███▌ | 4201/11952 [3:14:13<29:50:44, 13.86s/it]
35%|███▌ | 4202/11952 [3:14:19<24:27:29, 11.36s/it]
{'loss': 0.4665, 'learning_rate': 1.5049982224491115e-05, 'epoch': 0.35}
+
35%|███▌ | 4202/11952 [3:14:19<24:27:29, 11.36s/it]
35%|███▌ | 4203/11952 [3:14:25<21:01:39, 9.77s/it]
{'loss': 0.497, 'learning_rate': 1.5047643065012276e-05, 'epoch': 0.35}
+
35%|███▌ | 4203/11952 [3:14:25<21:01:39, 9.77s/it]
35%|███▌ | 4204/11952 [3:14:31<18:28:07, 8.58s/it]
{'loss': 0.5008, 'learning_rate': 1.5045303534855524e-05, 'epoch': 0.35}
+
35%|███▌ | 4204/11952 [3:14:31<18:28:07, 8.58s/it]
35%|███▌ | 4205/11952 [3:14:37<16:48:47, 7.81s/it]
{'loss': 0.4908, 'learning_rate': 1.5042963634192667e-05, 'epoch': 0.35}
+
35%|███▌ | 4205/11952 [3:14:37<16:48:47, 7.81s/it]
35%|███▌ | 4206/11952 [3:14:43<15:33:32, 7.23s/it]
{'loss': 0.498, 'learning_rate': 1.5040623363195535e-05, 'epoch': 0.35}
+
35%|███▌ | 4206/11952 [3:14:43<15:33:32, 7.23s/it]
35%|███▌ | 4207/11952 [3:14:49<14:38:29, 6.81s/it]
{'loss': 0.4864, 'learning_rate': 1.5038282722035986e-05, 'epoch': 0.35}
+
35%|███▌ | 4207/11952 [3:14:49<14:38:29, 6.81s/it]
35%|███▌ | 4208/11952 [3:14:54<13:52:49, 6.45s/it]
{'loss': 0.5004, 'learning_rate': 1.5035941710885915e-05, 'epoch': 0.35}
+
35%|███▌ | 4208/11952 [3:14:54<13:52:49, 6.45s/it]
35%|███▌ | 4209/11952 [3:15:00<13:30:57, 6.28s/it]
{'loss': 0.5207, 'learning_rate': 1.5033600329917227e-05, 'epoch': 0.35}
+
35%|███▌ | 4209/11952 [3:15:00<13:30:57, 6.28s/it]
35%|███▌ | 4210/11952 [3:15:06<13:11:59, 6.14s/it]
{'loss': 0.4731, 'learning_rate': 1.5031258579301868e-05, 'epoch': 0.35}
+
35%|███▌ | 4210/11952 [3:15:06<13:11:59, 6.14s/it]
35%|███▌ | 4211/11952 [3:15:11<12:51:41, 5.98s/it]
{'loss': 0.4995, 'learning_rate': 1.5028916459211804e-05, 'epoch': 0.35}
+
35%|███▌ | 4211/11952 [3:15:11<12:51:41, 5.98s/it]
35%|███▌ | 4212/11952 [3:15:17<12:48:09, 5.95s/it]
{'loss': 0.4928, 'learning_rate': 1.5026573969819035e-05, 'epoch': 0.35}
+
35%|███▌ | 4212/11952 [3:15:17<12:48:09, 5.95s/it]
35%|███▌ | 4213/11952 [3:15:23<12:53:37, 6.00s/it]
{'loss': 0.4968, 'learning_rate': 1.502423111129558e-05, 'epoch': 0.35}
+
35%|███▌ | 4213/11952 [3:15:23<12:53:37, 6.00s/it]
35%|███▌ | 4214/11952 [3:15:29<12:42:15, 5.91s/it]
{'loss': 0.4896, 'learning_rate': 1.5021887883813488e-05, 'epoch': 0.35}
+
35%|███▌ | 4214/11952 [3:15:29<12:42:15, 5.91s/it]
35%|███▌ | 4215/11952 [3:15:35<12:43:33, 5.92s/it]
{'loss': 0.4845, 'learning_rate': 1.501954428754484e-05, 'epoch': 0.35}
+
35%|███▌ | 4215/11952 [3:15:35<12:43:33, 5.92s/it]
35%|███▌ | 4216/11952 [3:15:41<12:53:05, 6.00s/it]
{'loss': 0.4936, 'learning_rate': 1.5017200322661735e-05, 'epoch': 0.35}
+
35%|███▌ | 4216/11952 [3:15:41<12:53:05, 6.00s/it]
35%|███▌ | 4217/11952 [3:15:47<12:41:45, 5.91s/it]
{'loss': 0.4902, 'learning_rate': 1.5014855989336308e-05, 'epoch': 0.35}
+
35%|███▌ | 4217/11952 [3:15:47<12:41:45, 5.91s/it]
35%|███▌ | 4218/11952 [3:15:53<12:27:05, 5.80s/it]
{'loss': 0.4821, 'learning_rate': 1.5012511287740715e-05, 'epoch': 0.35}
+
35%|███▌ | 4218/11952 [3:15:53<12:27:05, 5.80s/it]
35%|███▌ | 4219/11952 [3:15:58<12:32:10, 5.84s/it]
{'loss': 0.4979, 'learning_rate': 1.5010166218047139e-05, 'epoch': 0.35}
+
35%|███▌ | 4219/11952 [3:15:58<12:32:10, 5.84s/it]
35%|███▌ | 4220/11952 [3:16:04<12:24:37, 5.78s/it]
{'loss': 0.4948, 'learning_rate': 1.50078207804278e-05, 'epoch': 0.35}
+
35%|███▌ | 4220/11952 [3:16:04<12:24:37, 5.78s/it]
35%|███▌ | 4221/11952 [3:16:10<12:20:41, 5.75s/it]
{'loss': 0.4824, 'learning_rate': 1.5005474975054928e-05, 'epoch': 0.35}
+
35%|███▌ | 4221/11952 [3:16:10<12:20:41, 5.75s/it]
35%|███▌ | 4222/11952 [3:16:16<12:21:35, 5.76s/it]
{'loss': 0.4921, 'learning_rate': 1.5003128802100792e-05, 'epoch': 0.35}
+
35%|███▌ | 4222/11952 [3:16:16<12:21:35, 5.76s/it]
35%|███▌ | 4223/11952 [3:16:21<12:25:12, 5.79s/it]
{'loss': 0.4964, 'learning_rate': 1.500078226173769e-05, 'epoch': 0.35}
+
35%|███▌ | 4223/11952 [3:16:21<12:25:12, 5.79s/it]
35%|███▌ | 4224/11952 [3:16:27<12:17:44, 5.73s/it]
{'loss': 0.4867, 'learning_rate': 1.4998435354137937e-05, 'epoch': 0.35}
+
35%|███▌ | 4224/11952 [3:16:27<12:17:44, 5.73s/it]
35%|███▌ | 4225/11952 [3:16:33<12:23:38, 5.77s/it]
{'loss': 0.4999, 'learning_rate': 1.4996088079473884e-05, 'epoch': 0.35}
+
35%|███▌ | 4225/11952 [3:16:33<12:23:38, 5.77s/it]
35%|███▌ | 4226/11952 [3:16:39<12:21:32, 5.76s/it]
{'loss': 0.5114, 'learning_rate': 1.4993740437917898e-05, 'epoch': 0.35}
+
35%|███▌ | 4226/11952 [3:16:39<12:21:32, 5.76s/it]
35%|███▌ | 4227/11952 [3:16:44<12:19:56, 5.75s/it]
{'loss': 0.4886, 'learning_rate': 1.4991392429642389e-05, 'epoch': 0.35}
+
35%|███▌ | 4227/11952 [3:16:44<12:19:56, 5.75s/it]
35%|███▌ | 4228/11952 [3:16:51<12:39:58, 5.90s/it]
{'loss': 0.4818, 'learning_rate': 1.498904405481978e-05, 'epoch': 0.35}
+
35%|███▌ | 4228/11952 [3:16:51<12:39:58, 5.90s/it]
35%|███▌ | 4229/11952 [3:16:57<12:44:41, 5.94s/it]
{'loss': 0.5041, 'learning_rate': 1.4986695313622525e-05, 'epoch': 0.35}
+
35%|███▌ | 4229/11952 [3:16:57<12:44:41, 5.94s/it]
35%|███▌ | 4230/11952 [3:17:02<12:38:09, 5.89s/it]
{'loss': 0.4954, 'learning_rate': 1.4984346206223108e-05, 'epoch': 0.35}
+
35%|███▌ | 4230/11952 [3:17:02<12:38:09, 5.89s/it]
35%|███▌ | 4231/11952 [3:17:09<12:58:24, 6.05s/it]
{'loss': 0.494, 'learning_rate': 1.4981996732794038e-05, 'epoch': 0.35}
+
35%|███▌ | 4231/11952 [3:17:09<12:58:24, 6.05s/it]
35%|███▌ | 4232/11952 [3:17:15<13:05:52, 6.11s/it]
{'loss': 0.4941, 'learning_rate': 1.4979646893507847e-05, 'epoch': 0.35}
+
35%|███▌ | 4232/11952 [3:17:15<13:05:52, 6.11s/it]
35%|███▌ | 4233/11952 [3:17:21<12:56:15, 6.03s/it]
{'loss': 0.4994, 'learning_rate': 1.4977296688537101e-05, 'epoch': 0.35}
+
35%|███▌ | 4233/11952 [3:17:21<12:56:15, 6.03s/it]
35%|███▌ | 4234/11952 [3:17:27<12:45:02, 5.95s/it]
{'loss': 0.4972, 'learning_rate': 1.4974946118054392e-05, 'epoch': 0.35}
+
35%|███▌ | 4234/11952 [3:17:27<12:45:02, 5.95s/it]
35%|███▌ | 4235/11952 [3:17:33<12:42:39, 5.93s/it]
{'loss': 0.4681, 'learning_rate': 1.4972595182232328e-05, 'epoch': 0.35}
+
35%|███▌ | 4235/11952 [3:17:33<12:42:39, 5.93s/it]
35%|███▌ | 4236/11952 [3:17:38<12:35:51, 5.88s/it]
{'loss': 0.4936, 'learning_rate': 1.4970243881243558e-05, 'epoch': 0.35}
+
35%|███▌ | 4236/11952 [3:17:38<12:35:51, 5.88s/it]
35%|███▌ | 4237/11952 [3:17:44<12:29:14, 5.83s/it]
{'loss': 0.4879, 'learning_rate': 1.4967892215260751e-05, 'epoch': 0.35}
+
35%|███▌ | 4237/11952 [3:17:44<12:29:14, 5.83s/it]
35%|███▌ | 4238/11952 [3:17:50<12:40:13, 5.91s/it]
{'loss': 0.4786, 'learning_rate': 1.49655401844566e-05, 'epoch': 0.35}
+
35%|███▌ | 4238/11952 [3:17:50<12:40:13, 5.91s/it]
35%|███▌ | 4239/11952 [3:17:56<12:30:36, 5.84s/it]
{'loss': 0.4921, 'learning_rate': 1.4963187789003835e-05, 'epoch': 0.35}
+
35%|███▌ | 4239/11952 [3:17:56<12:30:36, 5.84s/it]
35%|███▌ | 4240/11952 [3:18:02<12:37:10, 5.89s/it]
{'loss': 0.4926, 'learning_rate': 1.49608350290752e-05, 'epoch': 0.35}
+
35%|███▌ | 4240/11952 [3:18:02<12:37:10, 5.89s/it]
35%|███▌ | 4241/11952 [3:18:08<12:33:56, 5.87s/it]
{'loss': 0.4689, 'learning_rate': 1.4958481904843473e-05, 'epoch': 0.35}
+
35%|███▌ | 4241/11952 [3:18:08<12:33:56, 5.87s/it]
35%|███▌ | 4242/11952 [3:18:13<12:31:30, 5.85s/it]
{'loss': 0.478, 'learning_rate': 1.4956128416481459e-05, 'epoch': 0.35}
+
35%|███▌ | 4242/11952 [3:18:13<12:31:30, 5.85s/it]
36%|███▌ | 4243/11952 [3:18:19<12:24:37, 5.80s/it]
{'loss': 0.4967, 'learning_rate': 1.4953774564161991e-05, 'epoch': 0.35}
+
36%|███▌ | 4243/11952 [3:18:19<12:24:37, 5.80s/it]
36%|███▌ | 4244/11952 [3:18:25<12:31:01, 5.85s/it]
{'loss': 0.4759, 'learning_rate': 1.495142034805792e-05, 'epoch': 0.36}
+
36%|███▌ | 4244/11952 [3:18:25<12:31:01, 5.85s/it]
36%|███▌ | 4245/11952 [3:18:31<12:18:40, 5.75s/it]
{'loss': 0.4725, 'learning_rate': 1.4949065768342136e-05, 'epoch': 0.36}
+
36%|███▌ | 4245/11952 [3:18:31<12:18:40, 5.75s/it]
36%|███▌ | 4246/11952 [3:18:36<12:17:38, 5.74s/it]
{'loss': 0.4913, 'learning_rate': 1.4946710825187545e-05, 'epoch': 0.36}
+
36%|███▌ | 4246/11952 [3:18:36<12:17:38, 5.74s/it]
36%|███▌ | 4247/11952 [3:18:42<12:25:28, 5.81s/it]
{'loss': 0.4778, 'learning_rate': 1.4944355518767086e-05, 'epoch': 0.36}
+
36%|███▌ | 4247/11952 [3:18:42<12:25:28, 5.81s/it]
36%|███▌ | 4248/11952 [3:18:48<12:28:05, 5.83s/it]
{'loss': 0.4754, 'learning_rate': 1.4941999849253723e-05, 'epoch': 0.36}
+
36%|███▌ | 4248/11952 [3:18:48<12:28:05, 5.83s/it]
36%|███▌ | 4249/11952 [3:18:54<12:23:51, 5.79s/it]
{'loss': 0.4989, 'learning_rate': 1.4939643816820449e-05, 'epoch': 0.36}
+
36%|███▌ | 4249/11952 [3:18:54<12:23:51, 5.79s/it]3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
36%|███▌ | 4250/11952 [3:19:00<12:38:24, 5.91s/it]
{'loss': 0.4903, 'learning_rate': 1.4937287421640277e-05, 'epoch': 0.36}
+
36%|███▌ | 4250/11952 [3:19:00<12:38:24, 5.91s/it]
36%|███▌ | 4251/11952 [3:19:06<12:30:37, 5.85s/it]
{'loss': 0.4936, 'learning_rate': 1.493493066388625e-05, 'epoch': 0.36}
+
36%|███▌ | 4251/11952 [3:19:06<12:30:37, 5.85s/it]
36%|███▌ | 4252/11952 [3:19:12<12:38:53, 5.91s/it]
{'loss': 0.4945, 'learning_rate': 1.4932573543731441e-05, 'epoch': 0.36}
+
36%|███▌ | 4252/11952 [3:19:12<12:38:53, 5.91s/it]
36%|███▌ | 4253/11952 [3:19:18<12:35:51, 5.89s/it]
{'loss': 0.5001, 'learning_rate': 1.493021606134895e-05, 'epoch': 0.36}
+
36%|███▌ | 4253/11952 [3:19:18<12:35:51, 5.89s/it]
36%|███▌ | 4254/11952 [3:19:24<12:41:13, 5.93s/it]
{'loss': 0.4595, 'learning_rate': 1.4927858216911897e-05, 'epoch': 0.36}
+
36%|███▌ | 4254/11952 [3:19:24<12:41:13, 5.93s/it]
36%|███▌ | 4255/11952 [3:19:30<12:39:31, 5.92s/it]
{'loss': 0.4922, 'learning_rate': 1.492550001059343e-05, 'epoch': 0.36}
+
36%|███▌ | 4255/11952 [3:19:30<12:39:31, 5.92s/it]
36%|███▌ | 4256/11952 [3:19:36<12:47:05, 5.98s/it]
{'loss': 0.4985, 'learning_rate': 1.4923141442566732e-05, 'epoch': 0.36}
+
36%|███▌ | 4256/11952 [3:19:36<12:47:05, 5.98s/it]
36%|███▌ | 4257/11952 [3:19:42<12:41:38, 5.94s/it]
{'loss': 0.5076, 'learning_rate': 1.4920782513005003e-05, 'epoch': 0.36}
+
36%|███▌ | 4257/11952 [3:19:42<12:41:38, 5.94s/it]
36%|███▌ | 4258/11952 [3:19:48<12:49:47, 6.00s/it]
{'loss': 0.5075, 'learning_rate': 1.4918423222081473e-05, 'epoch': 0.36}
+
36%|███▌ | 4258/11952 [3:19:48<12:49:47, 6.00s/it]
36%|███▌ | 4259/11952 [3:19:53<12:38:19, 5.91s/it]
{'loss': 0.5165, 'learning_rate': 1.4916063569969398e-05, 'epoch': 0.36}
+
36%|███▌ | 4259/11952 [3:19:53<12:38:19, 5.91s/it]
36%|███▌ | 4260/11952 [3:19:59<12:26:00, 5.82s/it]
{'loss': 0.4758, 'learning_rate': 1.4913703556842066e-05, 'epoch': 0.36}
+
36%|███▌ | 4260/11952 [3:19:59<12:26:00, 5.82s/it]
36%|███▌ | 4261/11952 [3:20:05<12:31:18, 5.86s/it]
{'loss': 0.4828, 'learning_rate': 1.491134318287278e-05, 'epoch': 0.36}
+
36%|███▌ | 4261/11952 [3:20:05<12:31:18, 5.86s/it]
36%|███▌ | 4262/11952 [3:20:11<12:27:03, 5.83s/it]
{'loss': 0.4891, 'learning_rate': 1.4908982448234875e-05, 'epoch': 0.36}
+
36%|███▌ | 4262/11952 [3:20:11<12:27:03, 5.83s/it]
36%|███▌ | 4263/11952 [3:20:16<12:25:46, 5.82s/it]
{'loss': 0.4657, 'learning_rate': 1.490662135310172e-05, 'epoch': 0.36}
+
36%|███▌ | 4263/11952 [3:20:16<12:25:46, 5.82s/it]
36%|███▌ | 4264/11952 [3:20:23<12:33:18, 5.88s/it]
{'loss': 0.5058, 'learning_rate': 1.49042598976467e-05, 'epoch': 0.36}
+
36%|███▌ | 4264/11952 [3:20:23<12:33:18, 5.88s/it]
36%|███▌ | 4265/11952 [3:20:28<12:30:12, 5.86s/it]
{'loss': 0.4888, 'learning_rate': 1.4901898082043232e-05, 'epoch': 0.36}
+
36%|███▌ | 4265/11952 [3:20:28<12:30:12, 5.86s/it]
36%|███▌ | 4266/11952 [3:20:34<12:34:11, 5.89s/it]
{'loss': 0.4943, 'learning_rate': 1.4899535906464757e-05, 'epoch': 0.36}
+
36%|███▌ | 4266/11952 [3:20:34<12:34:11, 5.89s/it]
36%|███▌ | 4267/11952 [3:20:40<12:28:06, 5.84s/it]
{'loss': 0.4916, 'learning_rate': 1.4897173371084743e-05, 'epoch': 0.36}
+
36%|███▌ | 4267/11952 [3:20:40<12:28:06, 5.84s/it]
36%|███▌ | 4268/11952 [3:20:46<12:28:07, 5.84s/it]
{'loss': 0.4967, 'learning_rate': 1.4894810476076688e-05, 'epoch': 0.36}
+
36%|███▌ | 4268/11952 [3:20:46<12:28:07, 5.84s/it]
36%|███▌ | 4269/11952 [3:20:52<12:24:15, 5.81s/it]
{'loss': 0.5103, 'learning_rate': 1.489244722161411e-05, 'epoch': 0.36}
+
36%|███▌ | 4269/11952 [3:20:52<12:24:15, 5.81s/it]
36%|███▌ | 4270/11952 [3:20:57<12:17:35, 5.76s/it]
{'loss': 0.4885, 'learning_rate': 1.4890083607870559e-05, 'epoch': 0.36}
+
36%|███▌ | 4270/11952 [3:20:57<12:17:35, 5.76s/it]
36%|███▌ | 4271/11952 [3:21:03<12:31:58, 5.87s/it]
{'loss': 0.5045, 'learning_rate': 1.4887719635019605e-05, 'epoch': 0.36}
+
36%|███▌ | 4271/11952 [3:21:03<12:31:58, 5.87s/it]
36%|███▌ | 4272/11952 [3:21:09<12:28:28, 5.85s/it]
{'loss': 0.4692, 'learning_rate': 1.488535530323485e-05, 'epoch': 0.36}
+
36%|███▌ | 4272/11952 [3:21:09<12:28:28, 5.85s/it]
36%|███▌ | 4273/11952 [3:21:15<12:33:17, 5.89s/it]
{'loss': 0.5159, 'learning_rate': 1.4882990612689918e-05, 'epoch': 0.36}
+
36%|███▌ | 4273/11952 [3:21:15<12:33:17, 5.89s/it]
36%|███▌ | 4274/11952 [3:21:21<12:38:18, 5.93s/it]
{'loss': 0.4899, 'learning_rate': 1.488062556355847e-05, 'epoch': 0.36}
+
36%|███▌ | 4274/11952 [3:21:21<12:38:18, 5.93s/it]
36%|███▌ | 4275/11952 [3:21:27<12:37:45, 5.92s/it]
{'loss': 0.4831, 'learning_rate': 1.4878260156014182e-05, 'epoch': 0.36}
+
36%|███▌ | 4275/11952 [3:21:27<12:37:45, 5.92s/it]
36%|███▌ | 4276/11952 [3:21:33<12:30:27, 5.87s/it]
{'loss': 0.4664, 'learning_rate': 1.4875894390230757e-05, 'epoch': 0.36}
+
36%|███▌ | 4276/11952 [3:21:33<12:30:27, 5.87s/it]
36%|███▌ | 4277/11952 [3:21:38<12:17:18, 5.76s/it]
{'loss': 0.4861, 'learning_rate': 1.4873528266381927e-05, 'epoch': 0.36}
+
36%|███▌ | 4277/11952 [3:21:38<12:17:18, 5.76s/it]
36%|███▌ | 4278/11952 [3:21:44<12:10:10, 5.71s/it]
{'loss': 0.4937, 'learning_rate': 1.487116178464145e-05, 'epoch': 0.36}
+
36%|███▌ | 4278/11952 [3:21:44<12:10:10, 5.71s/it]
36%|███▌ | 4279/11952 [3:21:50<12:17:01, 5.76s/it]
{'loss': 0.4788, 'learning_rate': 1.4868794945183113e-05, 'epoch': 0.36}
+
36%|███▌ | 4279/11952 [3:21:50<12:17:01, 5.76s/it]
36%|███▌ | 4280/11952 [3:21:56<12:26:05, 5.83s/it]
{'loss': 0.4746, 'learning_rate': 1.4866427748180729e-05, 'epoch': 0.36}
+
36%|███▌ | 4280/11952 [3:21:56<12:26:05, 5.83s/it]
36%|███▌ | 4281/11952 [3:22:02<12:34:32, 5.90s/it]
{'loss': 0.5078, 'learning_rate': 1.4864060193808133e-05, 'epoch': 0.36}
+
36%|███▌ | 4281/11952 [3:22:02<12:34:32, 5.90s/it]
36%|███▌ | 4282/11952 [3:22:08<12:32:54, 5.89s/it]
{'loss': 0.4726, 'learning_rate': 1.4861692282239181e-05, 'epoch': 0.36}
+
36%|███▌ | 4282/11952 [3:22:08<12:32:54, 5.89s/it]
36%|███▌ | 4283/11952 [3:22:14<12:42:15, 5.96s/it]
{'loss': 0.4855, 'learning_rate': 1.4859324013647773e-05, 'epoch': 0.36}
+
36%|███▌ | 4283/11952 [3:22:14<12:42:15, 5.96s/it]
36%|███▌ | 4284/11952 [3:22:20<12:36:34, 5.92s/it]
{'loss': 0.4965, 'learning_rate': 1.4856955388207821e-05, 'epoch': 0.36}
+
36%|███▌ | 4284/11952 [3:22:20<12:36:34, 5.92s/it]
36%|███▌ | 4285/11952 [3:22:26<12:35:45, 5.91s/it]
{'loss': 0.4585, 'learning_rate': 1.485458640609327e-05, 'epoch': 0.36}
+
36%|███▌ | 4285/11952 [3:22:26<12:35:45, 5.91s/it]
36%|███▌ | 4286/11952 [3:22:31<12:31:08, 5.88s/it]
{'loss': 0.4939, 'learning_rate': 1.4852217067478082e-05, 'epoch': 0.36}
+
36%|███▌ | 4286/11952 [3:22:31<12:31:08, 5.88s/it]
36%|███▌ | 4287/11952 [3:22:38<12:42:55, 5.97s/it]
{'loss': 0.4907, 'learning_rate': 1.4849847372536252e-05, 'epoch': 0.36}
+
36%|███▌ | 4287/11952 [3:22:38<12:42:55, 5.97s/it]
36%|███▌ | 4288/11952 [3:22:43<12:35:00, 5.91s/it]
{'loss': 0.4992, 'learning_rate': 1.4847477321441806e-05, 'epoch': 0.36}
+
36%|███▌ | 4288/11952 [3:22:43<12:35:00, 5.91s/it]
36%|███▌ | 4289/11952 [3:22:49<12:24:14, 5.83s/it]
{'loss': 0.4741, 'learning_rate': 1.4845106914368786e-05, 'epoch': 0.36}
+
36%|███▌ | 4289/11952 [3:22:49<12:24:14, 5.83s/it]
36%|███▌ | 4290/11952 [3:22:55<12:21:46, 5.81s/it]
{'loss': 0.5102, 'learning_rate': 1.4842736151491268e-05, 'epoch': 0.36}
+
36%|███▌ | 4290/11952 [3:22:55<12:21:46, 5.81s/it]
36%|███▌ | 4291/11952 [3:23:01<12:23:09, 5.82s/it]
{'loss': 0.4947, 'learning_rate': 1.484036503298335e-05, 'epoch': 0.36}
+
36%|███▌ | 4291/11952 [3:23:01<12:23:09, 5.82s/it]
36%|███▌ | 4292/11952 [3:23:06<12:26:54, 5.85s/it]
{'loss': 0.5033, 'learning_rate': 1.4837993559019157e-05, 'epoch': 0.36}
+
36%|███▌ | 4292/11952 [3:23:06<12:26:54, 5.85s/it]
36%|███▌ | 4293/11952 [3:23:13<12:38:51, 5.94s/it]
{'loss': 0.4976, 'learning_rate': 1.4835621729772838e-05, 'epoch': 0.36}
+
36%|███▌ | 4293/11952 [3:23:13<12:38:51, 5.94s/it]
36%|███▌ | 4294/11952 [3:23:18<12:32:46, 5.90s/it]
{'loss': 0.4881, 'learning_rate': 1.4833249545418572e-05, 'epoch': 0.36}
+
36%|███▌ | 4294/11952 [3:23:18<12:32:46, 5.90s/it]
36%|███▌ | 4295/11952 [3:23:24<12:16:55, 5.77s/it]
{'loss': 0.4842, 'learning_rate': 1.4830877006130561e-05, 'epoch': 0.36}
+
36%|███▌ | 4295/11952 [3:23:24<12:16:55, 5.77s/it]
36%|███▌ | 4296/11952 [3:23:30<12:32:28, 5.90s/it]
{'loss': 0.5006, 'learning_rate': 1.4828504112083038e-05, 'epoch': 0.36}
+
36%|███▌ | 4296/11952 [3:23:30<12:32:28, 5.90s/it]
36%|███▌ | 4297/11952 [3:23:36<12:26:00, 5.85s/it]
{'loss': 0.4883, 'learning_rate': 1.4826130863450257e-05, 'epoch': 0.36}
+
36%|███▌ | 4297/11952 [3:23:36<12:26:00, 5.85s/it]
36%|███▌ | 4298/11952 [3:23:42<12:20:31, 5.80s/it]
{'loss': 0.4763, 'learning_rate': 1.4823757260406498e-05, 'epoch': 0.36}
+
36%|███▌ | 4298/11952 [3:23:42<12:20:31, 5.80s/it]
36%|███▌ | 4299/11952 [3:23:47<12:13:41, 5.75s/it]
{'loss': 0.4734, 'learning_rate': 1.4821383303126067e-05, 'epoch': 0.36}
+
36%|███▌ | 4299/11952 [3:23:47<12:13:41, 5.75s/it]3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
36%|███▌ | 4300/11952 [3:23:53<12:14:50, 5.76s/it]
{'loss': 0.5042, 'learning_rate': 1.48190089917833e-05, 'epoch': 0.36}
+
36%|███▌ | 4300/11952 [3:23:53<12:14:50, 5.76s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
36%|███▌ | 4301/11952 [3:24:25<28:52:37, 13.59s/it]
{'loss': 0.4874, 'learning_rate': 1.4816634326552561e-05, 'epoch': 0.36}
+
36%|███▌ | 4301/11952 [3:24:25<28:52:37, 13.59s/it]
36%|███▌ | 4302/11952 [3:24:31<24:04:28, 11.33s/it]
{'loss': 0.4944, 'learning_rate': 1.481425930760823e-05, 'epoch': 0.36}
+
36%|███▌ | 4302/11952 [3:24:31<24:04:28, 11.33s/it]
36%|███▌ | 4303/11952 [3:24:37<20:37:51, 9.71s/it]
{'loss': 0.512, 'learning_rate': 1.4811883935124716e-05, 'epoch': 0.36}
+
36%|███▌ | 4303/11952 [3:24:37<20:37:51, 9.71s/it]
36%|███▌ | 4304/11952 [3:24:43<18:20:10, 8.63s/it]
{'loss': 0.5002, 'learning_rate': 1.480950820927646e-05, 'epoch': 0.36}
+
36%|███▌ | 4304/11952 [3:24:43<18:20:10, 8.63s/it]
36%|███▌ | 4305/11952 [3:24:49<16:30:42, 7.77s/it]
{'loss': 0.4948, 'learning_rate': 1.480713213023793e-05, 'epoch': 0.36}
+
36%|███▌ | 4305/11952 [3:24:49<16:30:42, 7.77s/it]
36%|███▌ | 4306/11952 [3:24:55<15:20:26, 7.22s/it]
{'loss': 0.4853, 'learning_rate': 1.4804755698183606e-05, 'epoch': 0.36}
+
36%|███▌ | 4306/11952 [3:24:55<15:20:26, 7.22s/it]
36%|███▌ | 4307/11952 [3:25:00<14:21:45, 6.76s/it]
{'loss': 0.4656, 'learning_rate': 1.4802378913288009e-05, 'epoch': 0.36}
+
36%|███▌ | 4307/11952 [3:25:00<14:21:45, 6.76s/it]
36%|███▌ | 4308/11952 [3:25:06<13:37:14, 6.41s/it]
{'loss': 0.4808, 'learning_rate': 1.4800001775725684e-05, 'epoch': 0.36}
+
36%|███▌ | 4308/11952 [3:25:06<13:37:14, 6.41s/it]
36%|███▌ | 4309/11952 [3:25:12<13:10:04, 6.20s/it]
{'loss': 0.4804, 'learning_rate': 1.4797624285671187e-05, 'epoch': 0.36}
+
36%|███▌ | 4309/11952 [3:25:12<13:10:04, 6.20s/it]
36%|███▌ | 4310/11952 [3:25:17<12:51:27, 6.06s/it]
{'loss': 0.4866, 'learning_rate': 1.4795246443299119e-05, 'epoch': 0.36}
+
36%|███▌ | 4310/11952 [3:25:17<12:51:27, 6.06s/it]
36%|███▌ | 4311/11952 [3:25:23<12:37:29, 5.95s/it]
{'loss': 0.5026, 'learning_rate': 1.4792868248784098e-05, 'epoch': 0.36}
+
36%|███▌ | 4311/11952 [3:25:23<12:37:29, 5.95s/it]
36%|███▌ | 4312/11952 [3:25:29<12:31:38, 5.90s/it]
{'loss': 0.4892, 'learning_rate': 1.4790489702300768e-05, 'epoch': 0.36}
+
36%|███▌ | 4312/11952 [3:25:29<12:31:38, 5.90s/it]
36%|███▌ | 4313/11952 [3:25:35<12:33:23, 5.92s/it]
{'loss': 0.4854, 'learning_rate': 1.4788110804023798e-05, 'epoch': 0.36}
+
36%|███▌ | 4313/11952 [3:25:35<12:33:23, 5.92s/it]
36%|███▌ | 4314/11952 [3:25:41<12:33:48, 5.92s/it]
{'loss': 0.4904, 'learning_rate': 1.4785731554127885e-05, 'epoch': 0.36}
+
36%|███▌ | 4314/11952 [3:25:41<12:33:48, 5.92s/it]
36%|███▌ | 4315/11952 [3:25:46<12:22:13, 5.83s/it]
{'loss': 0.4885, 'learning_rate': 1.4783351952787754e-05, 'epoch': 0.36}
+
36%|███▌ | 4315/11952 [3:25:46<12:22:13, 5.83s/it]
36%|███▌ | 4316/11952 [3:25:52<12:29:32, 5.89s/it]
{'loss': 0.4908, 'learning_rate': 1.4780972000178151e-05, 'epoch': 0.36}
+
36%|███▌ | 4316/11952 [3:25:52<12:29:32, 5.89s/it]
36%|███▌ | 4317/11952 [3:25:58<12:30:12, 5.90s/it]
{'loss': 0.4939, 'learning_rate': 1.477859169647385e-05, 'epoch': 0.36}
+
36%|███▌ | 4317/11952 [3:25:58<12:30:12, 5.90s/it]
36%|███▌ | 4318/11952 [3:26:04<12:27:40, 5.88s/it]
{'loss': 0.4988, 'learning_rate': 1.4776211041849651e-05, 'epoch': 0.36}
+
36%|███▌ | 4318/11952 [3:26:04<12:27:40, 5.88s/it]
36%|███▌ | 4319/11952 [3:26:10<12:25:21, 5.86s/it]
{'loss': 0.4819, 'learning_rate': 1.4773830036480377e-05, 'epoch': 0.36}
+
36%|███▌ | 4319/11952 [3:26:10<12:25:21, 5.86s/it]
36%|███▌ | 4320/11952 [3:26:16<12:44:03, 6.01s/it]
{'loss': 0.4991, 'learning_rate': 1.4771448680540881e-05, 'epoch': 0.36}
+
36%|███▌ | 4320/11952 [3:26:16<12:44:03, 6.01s/it]
36%|███▌ | 4321/11952 [3:26:22<12:34:10, 5.93s/it]
{'loss': 0.4881, 'learning_rate': 1.4769066974206041e-05, 'epoch': 0.36}
+
36%|███▌ | 4321/11952 [3:26:22<12:34:10, 5.93s/it]
36%|███▌ | 4322/11952 [3:26:28<12:29:22, 5.89s/it]
{'loss': 0.511, 'learning_rate': 1.476668491765076e-05, 'epoch': 0.36}
+
36%|███▌ | 4322/11952 [3:26:28<12:29:22, 5.89s/it]
36%|███▌ | 4323/11952 [3:26:34<12:22:06, 5.84s/it]
{'loss': 0.4744, 'learning_rate': 1.4764302511049962e-05, 'epoch': 0.36}
+
36%|███▌ | 4323/11952 [3:26:34<12:22:06, 5.84s/it]
36%|███▌ | 4324/11952 [3:26:39<12:19:51, 5.82s/it]
{'loss': 0.4949, 'learning_rate': 1.4761919754578603e-05, 'epoch': 0.36}
+
36%|███▌ | 4324/11952 [3:26:39<12:19:51, 5.82s/it]
36%|███▌ | 4325/11952 [3:26:45<12:13:17, 5.77s/it]
{'loss': 0.4802, 'learning_rate': 1.4759536648411668e-05, 'epoch': 0.36}
+
36%|███▌ | 4325/11952 [3:26:45<12:13:17, 5.77s/it]
36%|███▌ | 4326/11952 [3:26:51<12:07:30, 5.72s/it]
{'loss': 0.4845, 'learning_rate': 1.4757153192724154e-05, 'epoch': 0.36}
+
36%|███▌ | 4326/11952 [3:26:51<12:07:30, 5.72s/it]
36%|███▌ | 4327/11952 [3:26:56<12:01:51, 5.68s/it]
{'loss': 0.4661, 'learning_rate': 1.4754769387691096e-05, 'epoch': 0.36}
+
36%|███▌ | 4327/11952 [3:26:56<12:01:51, 5.68s/it]
36%|███▌ | 4328/11952 [3:27:02<12:03:27, 5.69s/it]
{'loss': 0.4855, 'learning_rate': 1.4752385233487554e-05, 'epoch': 0.36}
+
36%|███▌ | 4328/11952 [3:27:02<12:03:27, 5.69s/it]
36%|███▌ | 4329/11952 [3:27:08<12:02:24, 5.69s/it]
{'loss': 0.465, 'learning_rate': 1.4750000730288605e-05, 'epoch': 0.36}
+
36%|███▌ | 4329/11952 [3:27:08<12:02:24, 5.69s/it]
36%|███▌ | 4330/11952 [3:27:13<12:04:30, 5.70s/it]
{'loss': 0.4894, 'learning_rate': 1.4747615878269358e-05, 'epoch': 0.36}
+
36%|███▌ | 4330/11952 [3:27:13<12:04:30, 5.70s/it]
36%|███▌ | 4331/11952 [3:27:19<12:18:40, 5.82s/it]
{'loss': 0.5, 'learning_rate': 1.474523067760495e-05, 'epoch': 0.36}
+
36%|███▌ | 4331/11952 [3:27:19<12:18:40, 5.82s/it]
36%|███▌ | 4332/11952 [3:27:26<12:32:21, 5.92s/it]
{'loss': 0.5042, 'learning_rate': 1.4742845128470538e-05, 'epoch': 0.36}
+
36%|███▌ | 4332/11952 [3:27:26<12:32:21, 5.92s/it]
36%|███▋ | 4333/11952 [3:27:32<12:38:17, 5.97s/it]
{'loss': 0.4949, 'learning_rate': 1.4740459231041306e-05, 'epoch': 0.36}
+
36%|███▋ | 4333/11952 [3:27:32<12:38:17, 5.97s/it]
36%|███▋ | 4334/11952 [3:27:38<12:34:13, 5.94s/it]
{'loss': 0.505, 'learning_rate': 1.4738072985492462e-05, 'epoch': 0.36}
+
36%|███▋ | 4334/11952 [3:27:38<12:34:13, 5.94s/it]
36%|███▋ | 4335/11952 [3:27:43<12:31:17, 5.92s/it]
{'loss': 0.4786, 'learning_rate': 1.4735686391999249e-05, 'epoch': 0.36}
+
36%|███▋ | 4335/11952 [3:27:43<12:31:17, 5.92s/it]
36%|███▋ | 4336/11952 [3:27:49<12:18:11, 5.82s/it]
{'loss': 0.482, 'learning_rate': 1.4733299450736925e-05, 'epoch': 0.36}
+
36%|███▋ | 4336/11952 [3:27:49<12:18:11, 5.82s/it]
36%|███▋ | 4337/11952 [3:27:55<12:24:35, 5.87s/it]
{'loss': 0.4861, 'learning_rate': 1.4730912161880772e-05, 'epoch': 0.36}
+
36%|███▋ | 4337/11952 [3:27:55<12:24:35, 5.87s/it]
36%|███▋ | 4338/11952 [3:28:01<12:32:33, 5.93s/it]
{'loss': 0.4779, 'learning_rate': 1.4728524525606111e-05, 'epoch': 0.36}
+
36%|███▋ | 4338/11952 [3:28:01<12:32:33, 5.93s/it]
36%|███▋ | 4339/11952 [3:28:07<12:33:09, 5.94s/it]
{'loss': 0.4865, 'learning_rate': 1.4726136542088277e-05, 'epoch': 0.36}
+
36%|███▋ | 4339/11952 [3:28:07<12:33:09, 5.94s/it]
36%|███▋ | 4340/11952 [3:28:13<12:29:49, 5.91s/it]
{'loss': 0.4938, 'learning_rate': 1.4723748211502628e-05, 'epoch': 0.36}
+
36%|███▋ | 4340/11952 [3:28:13<12:29:49, 5.91s/it]
36%|███▋ | 4341/11952 [3:28:19<12:32:05, 5.93s/it]
{'loss': 0.4721, 'learning_rate': 1.4721359534024562e-05, 'epoch': 0.36}
+
36%|███▋ | 4341/11952 [3:28:19<12:32:05, 5.93s/it]
36%|███▋ | 4342/11952 [3:28:25<12:44:58, 6.03s/it]
{'loss': 0.4929, 'learning_rate': 1.4718970509829489e-05, 'epoch': 0.36}
+
36%|███▋ | 4342/11952 [3:28:25<12:44:58, 6.03s/it]
36%|███▋ | 4343/11952 [3:28:31<12:34:20, 5.95s/it]
{'loss': 0.5027, 'learning_rate': 1.4716581139092851e-05, 'epoch': 0.36}
+
36%|███▋ | 4343/11952 [3:28:31<12:34:20, 5.95s/it]
36%|███▋ | 4344/11952 [3:28:37<12:40:18, 6.00s/it]
{'loss': 0.4993, 'learning_rate': 1.471419142199011e-05, 'epoch': 0.36}
+
36%|███▋ | 4344/11952 [3:28:37<12:40:18, 6.00s/it]
36%|███▋ | 4345/11952 [3:28:43<12:34:42, 5.95s/it]
{'loss': 0.4877, 'learning_rate': 1.4711801358696755e-05, 'epoch': 0.36}
+
36%|███▋ | 4345/11952 [3:28:43<12:34:42, 5.95s/it]
36%|███▋ | 4346/11952 [3:28:49<12:26:22, 5.89s/it]
{'loss': 0.491, 'learning_rate': 1.4709410949388311e-05, 'epoch': 0.36}
+
36%|███▋ | 4346/11952 [3:28:49<12:26:22, 5.89s/it]
36%|███▋ | 4347/11952 [3:28:54<12:21:58, 5.85s/it]
{'loss': 0.5074, 'learning_rate': 1.4707020194240313e-05, 'epoch': 0.36}
+
36%|███▋ | 4347/11952 [3:28:54<12:21:58, 5.85s/it]
36%|███▋ | 4348/11952 [3:29:00<12:24:33, 5.87s/it]
{'loss': 0.5038, 'learning_rate': 1.4704629093428331e-05, 'epoch': 0.36}
+
36%|███▋ | 4348/11952 [3:29:00<12:24:33, 5.87s/it]
36%|███▋ | 4349/11952 [3:29:06<12:34:34, 5.95s/it]
{'loss': 0.4815, 'learning_rate': 1.4702237647127957e-05, 'epoch': 0.36}
+
36%|███▋ | 4349/11952 [3:29:06<12:34:34, 5.95s/it]3 AutoResumeHook: Checking whether to suspend...2
+ AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...5
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
36%|███▋ | 4350/11952 [3:29:13<12:46:30, 6.05s/it]
{'loss': 0.5135, 'learning_rate': 1.4699845855514807e-05, 'epoch': 0.36}
+
36%|███▋ | 4350/11952 [3:29:13<12:46:30, 6.05s/it]
36%|███▋ | 4351/11952 [3:29:19<12:39:54, 6.00s/it]
{'loss': 0.4867, 'learning_rate': 1.4697453718764525e-05, 'epoch': 0.36}
+
36%|███▋ | 4351/11952 [3:29:19<12:39:54, 6.00s/it]
36%|███▋ | 4352/11952 [3:29:25<12:47:34, 6.06s/it]
{'loss': 0.5028, 'learning_rate': 1.4695061237052781e-05, 'epoch': 0.36}
+
36%|███▋ | 4352/11952 [3:29:25<12:47:34, 6.06s/it]
36%|███▋ | 4353/11952 [3:29:31<12:38:23, 5.99s/it]
{'loss': 0.5103, 'learning_rate': 1.4692668410555269e-05, 'epoch': 0.36}
+
36%|███▋ | 4353/11952 [3:29:31<12:38:23, 5.99s/it]
36%|███▋ | 4354/11952 [3:29:36<12:35:43, 5.97s/it]
{'loss': 0.486, 'learning_rate': 1.4690275239447704e-05, 'epoch': 0.36}
+
36%|███▋ | 4354/11952 [3:29:36<12:35:43, 5.97s/it]
36%|███▋ | 4355/11952 [3:29:42<12:19:40, 5.84s/it]
{'loss': 0.4773, 'learning_rate': 1.4687881723905834e-05, 'epoch': 0.36}
+
36%|███▋ | 4355/11952 [3:29:42<12:19:40, 5.84s/it]
36%|███▋ | 4356/11952 [3:29:48<12:15:31, 5.81s/it]
{'loss': 0.486, 'learning_rate': 1.4685487864105431e-05, 'epoch': 0.36}
+
36%|███▋ | 4356/11952 [3:29:48<12:15:31, 5.81s/it]
36%|███▋ | 4357/11952 [3:29:53<12:11:46, 5.78s/it]
{'loss': 0.502, 'learning_rate': 1.4683093660222288e-05, 'epoch': 0.36}
+
36%|███▋ | 4357/11952 [3:29:53<12:11:46, 5.78s/it]
36%|███▋ | 4358/11952 [3:30:00<12:30:57, 5.93s/it]
{'loss': 0.5118, 'learning_rate': 1.4680699112432223e-05, 'epoch': 0.36}
+
36%|███▋ | 4358/11952 [3:30:00<12:30:57, 5.93s/it]
36%|███▋ | 4359/11952 [3:30:06<12:34:17, 5.96s/it]
{'loss': 0.475, 'learning_rate': 1.4678304220911086e-05, 'epoch': 0.36}
+
36%|███▋ | 4359/11952 [3:30:06<12:34:17, 5.96s/it]
36%|███▋ | 4360/11952 [3:30:12<12:30:44, 5.93s/it]
{'loss': 0.4904, 'learning_rate': 1.4675908985834744e-05, 'epoch': 0.36}
+
36%|███▋ | 4360/11952 [3:30:12<12:30:44, 5.93s/it]
36%|███▋ | 4361/11952 [3:30:17<12:21:59, 5.86s/it]
{'loss': 0.494, 'learning_rate': 1.4673513407379095e-05, 'epoch': 0.36}
+
36%|███▋ | 4361/11952 [3:30:17<12:21:59, 5.86s/it]
36%|███▋ | 4362/11952 [3:30:23<12:32:55, 5.95s/it]
{'loss': 0.4699, 'learning_rate': 1.4671117485720058e-05, 'epoch': 0.36}
+
36%|███▋ | 4362/11952 [3:30:23<12:32:55, 5.95s/it]
37%|███▋ | 4363/11952 [3:30:29<12:28:18, 5.92s/it]
{'loss': 0.4813, 'learning_rate': 1.4668721221033586e-05, 'epoch': 0.37}
+
37%|███▋ | 4363/11952 [3:30:29<12:28:18, 5.92s/it]
37%|███▋ | 4364/11952 [3:30:35<12:20:24, 5.85s/it]
{'loss': 0.5052, 'learning_rate': 1.4666324613495641e-05, 'epoch': 0.37}
+
37%|███▋ | 4364/11952 [3:30:35<12:20:24, 5.85s/it]
37%|███▋ | 4365/11952 [3:30:41<12:21:30, 5.86s/it]
{'loss': 0.5067, 'learning_rate': 1.4663927663282228e-05, 'epoch': 0.37}
+
37%|███▋ | 4365/11952 [3:30:41<12:21:30, 5.86s/it]
37%|███▋ | 4366/11952 [3:30:47<12:18:23, 5.84s/it]
{'loss': 0.4903, 'learning_rate': 1.4661530370569366e-05, 'epoch': 0.37}
+
37%|███▋ | 4366/11952 [3:30:47<12:18:23, 5.84s/it]
37%|███▋ | 4367/11952 [3:30:52<12:10:49, 5.78s/it]
{'loss': 0.4757, 'learning_rate': 1.4659132735533104e-05, 'epoch': 0.37}
+
37%|███▋ | 4367/11952 [3:30:52<12:10:49, 5.78s/it]
37%|███▋ | 4368/11952 [3:30:58<12:06:07, 5.74s/it]
{'loss': 0.4849, 'learning_rate': 1.4656734758349509e-05, 'epoch': 0.37}
+
37%|███▋ | 4368/11952 [3:30:58<12:06:07, 5.74s/it]
37%|███▋ | 4369/11952 [3:31:04<12:01:05, 5.71s/it]
{'loss': 0.5033, 'learning_rate': 1.4654336439194686e-05, 'epoch': 0.37}
+
37%|███▋ | 4369/11952 [3:31:04<12:01:05, 5.71s/it]
37%|███▋ | 4370/11952 [3:31:10<12:16:18, 5.83s/it]
{'loss': 0.4794, 'learning_rate': 1.4651937778244748e-05, 'epoch': 0.37}
+
37%|███▋ | 4370/11952 [3:31:10<12:16:18, 5.83s/it]
37%|███▋ | 4371/11952 [3:31:16<12:18:13, 5.84s/it]
{'loss': 0.4982, 'learning_rate': 1.464953877567585e-05, 'epoch': 0.37}
+
37%|███▋ | 4371/11952 [3:31:16<12:18:13, 5.84s/it]
37%|███▋ | 4372/11952 [3:31:21<12:07:54, 5.76s/it]
{'loss': 0.4785, 'learning_rate': 1.4647139431664167e-05, 'epoch': 0.37}
+
37%|███▋ | 4372/11952 [3:31:21<12:07:54, 5.76s/it]
37%|███▋ | 4373/11952 [3:31:27<12:12:04, 5.80s/it]
{'loss': 0.4746, 'learning_rate': 1.4644739746385894e-05, 'epoch': 0.37}
+
37%|███▋ | 4373/11952 [3:31:27<12:12:04, 5.80s/it]
37%|███▋ | 4374/11952 [3:31:33<12:09:39, 5.78s/it]
{'loss': 0.4791, 'learning_rate': 1.4642339720017249e-05, 'epoch': 0.37}
+
37%|███▋ | 4374/11952 [3:31:33<12:09:39, 5.78s/it]
37%|███▋ | 4375/11952 [3:31:38<12:06:38, 5.75s/it]
{'loss': 0.482, 'learning_rate': 1.4639939352734484e-05, 'epoch': 0.37}
+
37%|███▋ | 4375/11952 [3:31:38<12:06:38, 5.75s/it]
37%|███▋ | 4376/11952 [3:31:44<12:06:03, 5.75s/it]
{'loss': 0.4858, 'learning_rate': 1.4637538644713873e-05, 'epoch': 0.37}
+
37%|███▋ | 4376/11952 [3:31:44<12:06:03, 5.75s/it]
37%|███▋ | 4377/11952 [3:31:50<12:16:38, 5.83s/it]
{'loss': 0.4855, 'learning_rate': 1.4635137596131715e-05, 'epoch': 0.37}
+
37%|███▋ | 4377/11952 [3:31:50<12:16:38, 5.83s/it]
37%|███▋ | 4378/11952 [3:31:56<12:18:58, 5.85s/it]
{'loss': 0.4978, 'learning_rate': 1.4632736207164326e-05, 'epoch': 0.37}
+
37%|███▋ | 4378/11952 [3:31:56<12:18:58, 5.85s/it]
37%|███▋ | 4379/11952 [3:32:02<12:10:56, 5.79s/it]
{'loss': 0.4673, 'learning_rate': 1.4630334477988064e-05, 'epoch': 0.37}
+
37%|███▋ | 4379/11952 [3:32:02<12:10:56, 5.79s/it]
37%|███▋ | 4380/11952 [3:32:08<12:25:16, 5.91s/it]
{'loss': 0.4958, 'learning_rate': 1.4627932408779295e-05, 'epoch': 0.37}
+
37%|███▋ | 4380/11952 [3:32:08<12:25:16, 5.91s/it]
37%|███▋ | 4381/11952 [3:32:14<12:13:25, 5.81s/it]
{'loss': 0.5042, 'learning_rate': 1.4625529999714416e-05, 'epoch': 0.37}
+
37%|███▋ | 4381/11952 [3:32:14<12:13:25, 5.81s/it]
37%|███▋ | 4382/11952 [3:32:19<12:16:29, 5.84s/it]
{'loss': 0.4891, 'learning_rate': 1.4623127250969858e-05, 'epoch': 0.37}
+
37%|███▋ | 4382/11952 [3:32:19<12:16:29, 5.84s/it]
37%|███▋ | 4383/11952 [3:32:25<12:16:29, 5.84s/it]
{'loss': 0.5032, 'learning_rate': 1.4620724162722062e-05, 'epoch': 0.37}
+
37%|███▋ | 4383/11952 [3:32:25<12:16:29, 5.84s/it]
37%|███▋ | 4384/11952 [3:32:31<12:15:24, 5.83s/it]
{'loss': 0.4884, 'learning_rate': 1.4618320735147501e-05, 'epoch': 0.37}
+
37%|███▋ | 4384/11952 [3:32:31<12:15:24, 5.83s/it]
37%|███▋ | 4385/11952 [3:32:37<12:05:28, 5.75s/it]
{'loss': 0.4967, 'learning_rate': 1.4615916968422674e-05, 'epoch': 0.37}
+
37%|███▋ | 4385/11952 [3:32:37<12:05:28, 5.75s/it]
37%|███▋ | 4386/11952 [3:32:42<12:01:50, 5.72s/it]
{'loss': 0.4824, 'learning_rate': 1.4613512862724103e-05, 'epoch': 0.37}
+
37%|███▋ | 4386/11952 [3:32:42<12:01:50, 5.72s/it]
37%|███▋ | 4387/11952 [3:32:48<12:05:19, 5.75s/it]
{'loss': 0.4766, 'learning_rate': 1.4611108418228342e-05, 'epoch': 0.37}
+
37%|███▋ | 4387/11952 [3:32:48<12:05:19, 5.75s/it]
37%|███▋ | 4388/11952 [3:32:54<11:59:00, 5.70s/it]
{'loss': 0.4905, 'learning_rate': 1.460870363511195e-05, 'epoch': 0.37}
+
37%|███▋ | 4388/11952 [3:32:54<11:59:00, 5.70s/it]
37%|███▋ | 4389/11952 [3:32:59<11:58:17, 5.70s/it]
{'loss': 0.4821, 'learning_rate': 1.460629851355154e-05, 'epoch': 0.37}
+
37%|███▋ | 4389/11952 [3:32:59<11:58:17, 5.70s/it]
37%|███▋ | 4390/11952 [3:33:05<11:58:22, 5.70s/it]
{'loss': 0.4958, 'learning_rate': 1.460389305372372e-05, 'epoch': 0.37}
+
37%|███▋ | 4390/11952 [3:33:05<11:58:22, 5.70s/it]
37%|███▋ | 4391/11952 [3:33:11<11:59:47, 5.71s/it]
{'loss': 0.4676, 'learning_rate': 1.4601487255805146e-05, 'epoch': 0.37}
+
37%|███▋ | 4391/11952 [3:33:11<11:59:47, 5.71s/it]
37%|███▋ | 4392/11952 [3:33:17<12:03:07, 5.74s/it]
{'loss': 0.501, 'learning_rate': 1.4599081119972486e-05, 'epoch': 0.37}
+
37%|███▋ | 4392/11952 [3:33:17<12:03:07, 5.74s/it]
37%|███▋ | 4393/11952 [3:33:22<12:01:42, 5.73s/it]
{'loss': 0.4787, 'learning_rate': 1.459667464640244e-05, 'epoch': 0.37}
+
37%|███▋ | 4393/11952 [3:33:22<12:01:42, 5.73s/it]
37%|███▋ | 4394/11952 [3:33:28<12:06:53, 5.77s/it]
{'loss': 0.5029, 'learning_rate': 1.4594267835271725e-05, 'epoch': 0.37}
+
37%|███▋ | 4394/11952 [3:33:28<12:06:53, 5.77s/it]
37%|███▋ | 4395/11952 [3:33:34<12:10:45, 5.80s/it]
{'loss': 0.5047, 'learning_rate': 1.4591860686757089e-05, 'epoch': 0.37}
+
37%|███▋ | 4395/11952 [3:33:34<12:10:45, 5.80s/it]
37%|███▋ | 4396/11952 [3:33:40<12:11:47, 5.81s/it]
{'loss': 0.5009, 'learning_rate': 1.4589453201035302e-05, 'epoch': 0.37}
+
37%|███▋ | 4396/11952 [3:33:40<12:11:47, 5.81s/it]
37%|███▋ | 4397/11952 [3:33:46<12:21:44, 5.89s/it]
{'loss': 0.4818, 'learning_rate': 1.4587045378283162e-05, 'epoch': 0.37}
+
37%|███▋ | 4397/11952 [3:33:46<12:21:44, 5.89s/it]
37%|███▋ | 4398/11952 [3:33:52<12:12:56, 5.82s/it]
{'loss': 0.4601, 'learning_rate': 1.4584637218677488e-05, 'epoch': 0.37}
+
37%|███▋ | 4398/11952 [3:33:52<12:12:56, 5.82s/it]
37%|███▋ | 4399/11952 [3:33:57<12:06:44, 5.77s/it]
{'loss': 0.504, 'learning_rate': 1.4582228722395128e-05, 'epoch': 0.37}
+
37%|███▋ | 4399/11952 [3:33:57<12:06:44, 5.77s/it]3 AutoResumeHook: Checking whether to suspend...
+72 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+5
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
37%|███▋ | 4400/11952 [3:34:03<12:03:05, 5.74s/it]4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4719, 'learning_rate': 1.4579819889612949e-05, 'epoch': 0.37}
+
37%|███▋ | 4400/11952 [3:34:03<12:03:05, 5.74s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
37%|███▋ | 4401/11952 [3:34:38<30:20:53, 14.47s/it]
{'loss': 0.5031, 'learning_rate': 1.4577410720507842e-05, 'epoch': 0.37}
+
37%|███▋ | 4401/11952 [3:34:38<30:20:53, 14.47s/it]
37%|███▋ | 4402/11952 [3:34:43<24:41:03, 11.77s/it]
{'loss': 0.4812, 'learning_rate': 1.4575001215256735e-05, 'epoch': 0.37}
+
37%|███▋ | 4402/11952 [3:34:43<24:41:03, 11.77s/it]
37%|███▋ | 4403/11952 [3:34:49<20:59:20, 10.01s/it]
{'loss': 0.4906, 'learning_rate': 1.4572591374036567e-05, 'epoch': 0.37}
+
37%|███▋ | 4403/11952 [3:34:49<20:59:20, 10.01s/it]
37%|███▋ | 4404/11952 [3:34:56<18:38:23, 8.89s/it]
{'loss': 0.4945, 'learning_rate': 1.4570181197024307e-05, 'epoch': 0.37}
+
37%|███▋ | 4404/11952 [3:34:56<18:38:23, 8.89s/it]
37%|███▋ | 4405/11952 [3:35:01<16:34:50, 7.91s/it]
{'loss': 0.4849, 'learning_rate': 1.4567770684396947e-05, 'epoch': 0.37}
+
37%|███▋ | 4405/11952 [3:35:01<16:34:50, 7.91s/it]
37%|███▋ | 4406/11952 [3:35:07<15:11:15, 7.25s/it]
{'loss': 0.4788, 'learning_rate': 1.456535983633151e-05, 'epoch': 0.37}
+
37%|███▋ | 4406/11952 [3:35:07<15:11:15, 7.25s/it]
37%|███▋ | 4407/11952 [3:35:12<14:10:31, 6.76s/it]
{'loss': 0.4917, 'learning_rate': 1.4562948653005032e-05, 'epoch': 0.37}
+
37%|███▋ | 4407/11952 [3:35:12<14:10:31, 6.76s/it]
37%|███▋ | 4408/11952 [3:35:18<13:30:01, 6.44s/it]
{'loss': 0.4728, 'learning_rate': 1.4560537134594586e-05, 'epoch': 0.37}
+
37%|███▋ | 4408/11952 [3:35:18<13:30:01, 6.44s/it]
37%|███▋ | 4409/11952 [3:35:24<13:24:49, 6.40s/it]
{'loss': 0.4997, 'learning_rate': 1.455812528127726e-05, 'epoch': 0.37}
+
37%|███▋ | 4409/11952 [3:35:24<13:24:49, 6.40s/it]
37%|███▋ | 4410/11952 [3:35:30<13:00:49, 6.21s/it]
{'loss': 0.493, 'learning_rate': 1.4555713093230173e-05, 'epoch': 0.37}
+
37%|███▋ | 4410/11952 [3:35:30<13:00:49, 6.21s/it]
37%|███▋ | 4411/11952 [3:35:36<12:39:51, 6.05s/it]
{'loss': 0.4758, 'learning_rate': 1.4553300570630464e-05, 'epoch': 0.37}
+
37%|███▋ | 4411/11952 [3:35:36<12:39:51, 6.05s/it]
37%|███▋ | 4412/11952 [3:35:42<12:38:04, 6.03s/it]
{'loss': 0.4887, 'learning_rate': 1.4550887713655297e-05, 'epoch': 0.37}
+
37%|███▋ | 4412/11952 [3:35:42<12:38:04, 6.03s/it]
37%|███▋ | 4413/11952 [3:35:48<12:29:50, 5.97s/it]
{'loss': 0.4892, 'learning_rate': 1.454847452248187e-05, 'epoch': 0.37}
+
37%|███▋ | 4413/11952 [3:35:48<12:29:50, 5.97s/it]
37%|███▋ | 4414/11952 [3:35:53<12:21:33, 5.90s/it]
{'loss': 0.4678, 'learning_rate': 1.4546060997287392e-05, 'epoch': 0.37}
+
37%|███▋ | 4414/11952 [3:35:53<12:21:33, 5.90s/it]
37%|███▋ | 4415/11952 [3:35:59<12:25:48, 5.94s/it]
{'loss': 0.5012, 'learning_rate': 1.45436471382491e-05, 'epoch': 0.37}
+
37%|███▋ | 4415/11952 [3:35:59<12:25:48, 5.94s/it]
37%|███▋ | 4416/11952 [3:36:05<12:19:14, 5.89s/it]
{'loss': 0.5001, 'learning_rate': 1.4541232945544263e-05, 'epoch': 0.37}
+
37%|███▋ | 4416/11952 [3:36:05<12:19:14, 5.89s/it]
37%|███▋ | 4417/11952 [3:36:11<12:07:50, 5.80s/it]
{'loss': 0.4674, 'learning_rate': 1.4538818419350164e-05, 'epoch': 0.37}
+
37%|███▋ | 4417/11952 [3:36:11<12:07:50, 5.80s/it]
37%|███▋ | 4418/11952 [3:36:17<12:04:26, 5.77s/it]
{'loss': 0.5016, 'learning_rate': 1.4536403559844123e-05, 'epoch': 0.37}
+
37%|███▋ | 4418/11952 [3:36:17<12:04:26, 5.77s/it]
37%|███▋ | 4419/11952 [3:36:22<12:08:03, 5.80s/it]
{'loss': 0.4768, 'learning_rate': 1.453398836720347e-05, 'epoch': 0.37}
+
37%|███▋ | 4419/11952 [3:36:22<12:08:03, 5.80s/it]
37%|███▋ | 4420/11952 [3:36:29<12:22:40, 5.92s/it]
{'loss': 0.4941, 'learning_rate': 1.453157284160557e-05, 'epoch': 0.37}
+
37%|███▋ | 4420/11952 [3:36:29<12:22:40, 5.92s/it]
37%|███▋ | 4421/11952 [3:36:34<12:13:55, 5.85s/it]
{'loss': 0.4916, 'learning_rate': 1.452915698322781e-05, 'epoch': 0.37}
+
37%|███▋ | 4421/11952 [3:36:34<12:13:55, 5.85s/it]
37%|███▋ | 4422/11952 [3:36:40<12:18:24, 5.88s/it]
{'loss': 0.4901, 'learning_rate': 1.4526740792247597e-05, 'epoch': 0.37}
+
37%|███▋ | 4422/11952 [3:36:40<12:18:24, 5.88s/it]
37%|███▋ | 4423/11952 [3:36:46<12:26:34, 5.95s/it]
{'loss': 0.4863, 'learning_rate': 1.4524324268842369e-05, 'epoch': 0.37}
+
37%|███▋ | 4423/11952 [3:36:46<12:26:34, 5.95s/it]
37%|███▋ | 4424/11952 [3:36:52<12:22:12, 5.92s/it]
{'loss': 0.4917, 'learning_rate': 1.4521907413189587e-05, 'epoch': 0.37}
+
37%|███▋ | 4424/11952 [3:36:52<12:22:12, 5.92s/it]
37%|███▋ | 4425/11952 [3:36:58<12:20:02, 5.90s/it]
{'loss': 0.4962, 'learning_rate': 1.4519490225466733e-05, 'epoch': 0.37}
+
37%|███▋ | 4425/11952 [3:36:58<12:20:02, 5.90s/it]
37%|███▋ | 4426/11952 [3:37:04<12:12:41, 5.84s/it]
{'loss': 0.485, 'learning_rate': 1.4517072705851312e-05, 'epoch': 0.37}
+
37%|███▋ | 4426/11952 [3:37:04<12:12:41, 5.84s/it]
37%|███▋ | 4427/11952 [3:37:09<12:04:03, 5.77s/it]
{'loss': 0.4956, 'learning_rate': 1.451465485452086e-05, 'epoch': 0.37}
+
37%|███▋ | 4427/11952 [3:37:09<12:04:03, 5.77s/it]
37%|███▋ | 4428/11952 [3:37:15<11:57:37, 5.72s/it]
{'loss': 0.4826, 'learning_rate': 1.4512236671652932e-05, 'epoch': 0.37}
+
37%|███▋ | 4428/11952 [3:37:15<11:57:37, 5.72s/it]
37%|███▋ | 4429/11952 [3:37:21<12:10:22, 5.83s/it]
{'loss': 0.4832, 'learning_rate': 1.4509818157425112e-05, 'epoch': 0.37}
+
37%|███▋ | 4429/11952 [3:37:21<12:10:22, 5.83s/it]
37%|███▋ | 4430/11952 [3:37:27<12:02:47, 5.77s/it]
{'loss': 0.4936, 'learning_rate': 1.4507399312015005e-05, 'epoch': 0.37}
+
37%|███▋ | 4430/11952 [3:37:27<12:02:47, 5.77s/it]
37%|███▋ | 4431/11952 [3:37:33<12:14:15, 5.86s/it]
{'loss': 0.4902, 'learning_rate': 1.4504980135600242e-05, 'epoch': 0.37}
+
37%|███▋ | 4431/11952 [3:37:33<12:14:15, 5.86s/it]
37%|███▋ | 4432/11952 [3:37:39<12:10:49, 5.83s/it]
{'loss': 0.4943, 'learning_rate': 1.4502560628358473e-05, 'epoch': 0.37}
+
37%|███▋ | 4432/11952 [3:37:39<12:10:49, 5.83s/it]
37%|███▋ | 4433/11952 [3:37:44<12:06:22, 5.80s/it]
{'loss': 0.4822, 'learning_rate': 1.4500140790467377e-05, 'epoch': 0.37}
+
37%|███▋ | 4433/11952 [3:37:44<12:06:22, 5.80s/it]
37%|███▋ | 4434/11952 [3:37:50<11:56:34, 5.72s/it]
{'loss': 0.4996, 'learning_rate': 1.449772062210466e-05, 'epoch': 0.37}
+
37%|███▋ | 4434/11952 [3:37:50<11:56:34, 5.72s/it]
37%|███▋ | 4435/11952 [3:37:56<12:06:06, 5.80s/it]
{'loss': 0.5047, 'learning_rate': 1.449530012344805e-05, 'epoch': 0.37}
+
37%|███▋ | 4435/11952 [3:37:56<12:06:06, 5.80s/it]
37%|███▋ | 4436/11952 [3:38:02<12:06:50, 5.80s/it]
{'loss': 0.4677, 'learning_rate': 1.4492879294675297e-05, 'epoch': 0.37}
+
37%|███▋ | 4436/11952 [3:38:02<12:06:50, 5.80s/it]
37%|███▋ | 4437/11952 [3:38:07<12:04:15, 5.78s/it]
{'loss': 0.4872, 'learning_rate': 1.4490458135964173e-05, 'epoch': 0.37}
+
37%|███▋ | 4437/11952 [3:38:07<12:04:15, 5.78s/it]
37%|███▋ | 4438/11952 [3:38:13<12:05:33, 5.79s/it]
{'loss': 0.4731, 'learning_rate': 1.4488036647492482e-05, 'epoch': 0.37}
+
37%|███▋ | 4438/11952 [3:38:13<12:05:33, 5.79s/it]
37%|███▋ | 4439/11952 [3:38:19<12:03:05, 5.77s/it]
{'loss': 0.4759, 'learning_rate': 1.4485614829438046e-05, 'epoch': 0.37}
+
37%|███▋ | 4439/11952 [3:38:19<12:03:05, 5.77s/it]
37%|███▋ | 4440/11952 [3:38:25<12:02:46, 5.77s/it]
{'loss': 0.4946, 'learning_rate': 1.4483192681978715e-05, 'epoch': 0.37}
+
37%|███▋ | 4440/11952 [3:38:25<12:02:46, 5.77s/it]
37%|███▋ | 4441/11952 [3:38:30<12:06:20, 5.80s/it]
{'loss': 0.4783, 'learning_rate': 1.4480770205292363e-05, 'epoch': 0.37}
+
37%|███▋ | 4441/11952 [3:38:30<12:06:20, 5.80s/it]
37%|███▋ | 4442/11952 [3:38:37<12:21:15, 5.92s/it]
{'loss': 0.4796, 'learning_rate': 1.4478347399556878e-05, 'epoch': 0.37}
+
37%|███▋ | 4442/11952 [3:38:37<12:21:15, 5.92s/it]
37%|███▋ | 4443/11952 [3:38:42<12:11:06, 5.84s/it]
{'loss': 0.495, 'learning_rate': 1.447592426495019e-05, 'epoch': 0.37}
+
37%|███▋ | 4443/11952 [3:38:42<12:11:06, 5.84s/it]
37%|███▋ | 4444/11952 [3:38:48<12:07:08, 5.81s/it]
{'loss': 0.4885, 'learning_rate': 1.4473500801650243e-05, 'epoch': 0.37}
+
37%|███▋ | 4444/11952 [3:38:48<12:07:08, 5.81s/it]
37%|███▋ | 4445/11952 [3:38:54<12:05:20, 5.80s/it]
{'loss': 0.4771, 'learning_rate': 1.4471077009835001e-05, 'epoch': 0.37}
+
37%|███▋ | 4445/11952 [3:38:54<12:05:20, 5.80s/it]
37%|███▋ | 4446/11952 [3:38:59<11:59:06, 5.75s/it]
{'loss': 0.4934, 'learning_rate': 1.446865288968246e-05, 'epoch': 0.37}
+
37%|███▋ | 4446/11952 [3:38:59<11:59:06, 5.75s/it]
37%|███▋ | 4447/11952 [3:39:05<12:01:01, 5.76s/it]
{'loss': 0.5003, 'learning_rate': 1.4466228441370638e-05, 'epoch': 0.37}
+
37%|███▋ | 4447/11952 [3:39:05<12:01:01, 5.76s/it]
37%|███▋ | 4448/11952 [3:39:11<12:08:57, 5.83s/it]
{'loss': 0.4921, 'learning_rate': 1.4463803665077573e-05, 'epoch': 0.37}
+
37%|███▋ | 4448/11952 [3:39:11<12:08:57, 5.83s/it]
37%|███▋ | 4449/11952 [3:39:17<12:01:29, 5.77s/it]
{'loss': 0.4844, 'learning_rate': 1.4461378560981335e-05, 'epoch': 0.37}
+
37%|███▋ | 4449/11952 [3:39:17<12:01:29, 5.77s/it]36 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+1 AutoResumeHook: Checking whether to suspend...
+75 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
37%|███▋ | 4450/11952 [3:39:23<11:56:00, 5.73s/it]
{'loss': 0.484, 'learning_rate': 1.4458953129260014e-05, 'epoch': 0.37}
+
37%|███▋ | 4450/11952 [3:39:23<11:56:00, 5.73s/it]
37%|███▋ | 4451/11952 [3:39:28<11:53:31, 5.71s/it]
{'loss': 0.477, 'learning_rate': 1.4456527370091722e-05, 'epoch': 0.37}
+
37%|███▋ | 4451/11952 [3:39:28<11:53:31, 5.71s/it]
37%|███▋ | 4452/11952 [3:39:34<12:01:55, 5.78s/it]
{'loss': 0.4759, 'learning_rate': 1.4454101283654594e-05, 'epoch': 0.37}
+
37%|███▋ | 4452/11952 [3:39:34<12:01:55, 5.78s/it]
37%|███▋ | 4453/11952 [3:39:40<11:57:52, 5.74s/it]
{'loss': 0.4673, 'learning_rate': 1.445167487012679e-05, 'epoch': 0.37}
+
37%|███▋ | 4453/11952 [3:39:40<11:57:52, 5.74s/it]
37%|███▋ | 4454/11952 [3:39:46<12:08:58, 5.83s/it]
{'loss': 0.4975, 'learning_rate': 1.4449248129686504e-05, 'epoch': 0.37}
+
37%|███▋ | 4454/11952 [3:39:46<12:08:58, 5.83s/it]
37%|███▋ | 4455/11952 [3:39:52<12:30:15, 6.00s/it]
{'loss': 0.5007, 'learning_rate': 1.4446821062511942e-05, 'epoch': 0.37}
+
37%|███▋ | 4455/11952 [3:39:52<12:30:15, 6.00s/it]
37%|███▋ | 4456/11952 [3:39:58<12:26:06, 5.97s/it]
{'loss': 0.5061, 'learning_rate': 1.4444393668781334e-05, 'epoch': 0.37}
+
37%|███▋ | 4456/11952 [3:39:58<12:26:06, 5.97s/it]
37%|███▋ | 4457/11952 [3:40:04<12:20:01, 5.92s/it]
{'loss': 0.4783, 'learning_rate': 1.4441965948672943e-05, 'epoch': 0.37}
+
37%|███▋ | 4457/11952 [3:40:04<12:20:01, 5.92s/it]
37%|███▋ | 4458/11952 [3:40:10<12:17:19, 5.90s/it]
{'loss': 0.5025, 'learning_rate': 1.4439537902365047e-05, 'epoch': 0.37}
+
37%|███▋ | 4458/11952 [3:40:10<12:17:19, 5.90s/it]
37%|███▋ | 4459/11952 [3:40:16<12:11:06, 5.85s/it]
{'loss': 0.4762, 'learning_rate': 1.4437109530035951e-05, 'epoch': 0.37}
+
37%|███▋ | 4459/11952 [3:40:16<12:11:06, 5.85s/it]
37%|███▋ | 4460/11952 [3:40:21<11:59:27, 5.76s/it]
{'loss': 0.503, 'learning_rate': 1.443468083186399e-05, 'epoch': 0.37}
+
37%|███▋ | 4460/11952 [3:40:21<11:59:27, 5.76s/it]
37%|███▋ | 4461/11952 [3:40:27<12:16:26, 5.90s/it]
{'loss': 0.4933, 'learning_rate': 1.443225180802751e-05, 'epoch': 0.37}
+
37%|███▋ | 4461/11952 [3:40:27<12:16:26, 5.90s/it]
37%|███▋ | 4462/11952 [3:40:33<12:07:54, 5.83s/it]
{'loss': 0.4887, 'learning_rate': 1.4429822458704896e-05, 'epoch': 0.37}
+
37%|███▋ | 4462/11952 [3:40:33<12:07:54, 5.83s/it]
37%|███▋ | 4463/11952 [3:40:39<12:04:37, 5.81s/it]
{'loss': 0.4973, 'learning_rate': 1.4427392784074545e-05, 'epoch': 0.37}
+
37%|███▋ | 4463/11952 [3:40:39<12:04:37, 5.81s/it]
37%|███▋ | 4464/11952 [3:40:45<12:21:57, 5.95s/it]
{'loss': 0.5274, 'learning_rate': 1.442496278431488e-05, 'epoch': 0.37}
+
37%|███▋ | 4464/11952 [3:40:45<12:21:57, 5.95s/it]
37%|███▋ | 4465/11952 [3:40:51<12:17:31, 5.91s/it]
{'loss': 0.4956, 'learning_rate': 1.4422532459604357e-05, 'epoch': 0.37}
+
37%|███▋ | 4465/11952 [3:40:51<12:17:31, 5.91s/it]
37%|███▋ | 4466/11952 [3:40:57<12:29:42, 6.01s/it]
{'loss': 0.4856, 'learning_rate': 1.442010181012144e-05, 'epoch': 0.37}
+
37%|███▋ | 4466/11952 [3:40:57<12:29:42, 6.01s/it]
37%|███▋ | 4467/11952 [3:41:03<12:34:02, 6.04s/it]
{'loss': 0.5036, 'learning_rate': 1.4417670836044635e-05, 'epoch': 0.37}
+
37%|███▋ | 4467/11952 [3:41:03<12:34:02, 6.04s/it]
37%|███▋ | 4468/11952 [3:41:09<12:26:32, 5.99s/it]
{'loss': 0.5218, 'learning_rate': 1.4415239537552457e-05, 'epoch': 0.37}
+
37%|███▋ | 4468/11952 [3:41:09<12:26:32, 5.99s/it]
37%|███▋ | 4469/11952 [3:41:15<12:17:59, 5.92s/it]
{'loss': 0.4733, 'learning_rate': 1.4412807914823452e-05, 'epoch': 0.37}
+
37%|███▋ | 4469/11952 [3:41:15<12:17:59, 5.92s/it]
37%|███▋ | 4470/11952 [3:41:21<12:12:29, 5.87s/it]
{'loss': 0.4742, 'learning_rate': 1.4410375968036185e-05, 'epoch': 0.37}
+
37%|███▋ | 4470/11952 [3:41:21<12:12:29, 5.87s/it]
37%|███▋ | 4471/11952 [3:41:26<12:02:54, 5.80s/it]
{'loss': 0.4971, 'learning_rate': 1.4407943697369255e-05, 'epoch': 0.37}
+
37%|███▋ | 4471/11952 [3:41:26<12:02:54, 5.80s/it]
37%|███▋ | 4472/11952 [3:41:32<12:11:19, 5.87s/it]
{'loss': 0.4941, 'learning_rate': 1.4405511103001274e-05, 'epoch': 0.37}
+
37%|███▋ | 4472/11952 [3:41:32<12:11:19, 5.87s/it]
37%|███▋ | 4473/11952 [3:41:38<12:04:54, 5.82s/it]
{'loss': 0.4734, 'learning_rate': 1.440307818511088e-05, 'epoch': 0.37}
+
37%|███▋ | 4473/11952 [3:41:38<12:04:54, 5.82s/it]
37%|███▋ | 4474/11952 [3:41:44<12:07:04, 5.83s/it]
{'loss': 0.494, 'learning_rate': 1.4400644943876736e-05, 'epoch': 0.37}
+
37%|███▋ | 4474/11952 [3:41:44<12:07:04, 5.83s/it]
37%|███▋ | 4475/11952 [3:41:49<12:02:04, 5.79s/it]
{'loss': 0.5102, 'learning_rate': 1.4398211379477534e-05, 'epoch': 0.37}
+
37%|███▋ | 4475/11952 [3:41:49<12:02:04, 5.79s/it]
37%|███▋ | 4476/11952 [3:41:56<12:17:00, 5.92s/it]
{'loss': 0.4926, 'learning_rate': 1.439577749209198e-05, 'epoch': 0.37}
+
37%|███▋ | 4476/11952 [3:41:56<12:17:00, 5.92s/it]
37%|███▋ | 4477/11952 [3:42:02<12:16:27, 5.91s/it]
{'loss': 0.4995, 'learning_rate': 1.439334328189881e-05, 'epoch': 0.37}
+
37%|███▋ | 4477/11952 [3:42:02<12:16:27, 5.91s/it]
37%|███▋ | 4478/11952 [3:42:07<12:03:42, 5.81s/it]
{'loss': 0.5003, 'learning_rate': 1.4390908749076787e-05, 'epoch': 0.37}
+
37%|███▋ | 4478/11952 [3:42:07<12:03:42, 5.81s/it]
37%|███▋ | 4479/11952 [3:42:13<12:08:56, 5.85s/it]
{'loss': 0.5023, 'learning_rate': 1.4388473893804683e-05, 'epoch': 0.37}
+
37%|███▋ | 4479/11952 [3:42:13<12:08:56, 5.85s/it]
37%|███▋ | 4480/11952 [3:42:19<12:14:36, 5.90s/it]
{'loss': 0.4786, 'learning_rate': 1.438603871626131e-05, 'epoch': 0.37}
+
37%|███▋ | 4480/11952 [3:42:19<12:14:36, 5.90s/it]
37%|███▋ | 4481/11952 [3:42:25<12:13:38, 5.89s/it]
{'loss': 0.4957, 'learning_rate': 1.4383603216625499e-05, 'epoch': 0.37}
+
37%|███▋ | 4481/11952 [3:42:25<12:13:38, 5.89s/it]
38%|███▊ | 4482/11952 [3:42:31<12:17:04, 5.92s/it]
{'loss': 0.5121, 'learning_rate': 1.4381167395076101e-05, 'epoch': 0.37}
+
38%|███▊ | 4482/11952 [3:42:31<12:17:04, 5.92s/it]
38%|███▊ | 4483/11952 [3:42:37<12:13:09, 5.89s/it]
{'loss': 0.4638, 'learning_rate': 1.4378731251791989e-05, 'epoch': 0.38}
+
38%|███▊ | 4483/11952 [3:42:37<12:13:09, 5.89s/it]
38%|███▊ | 4484/11952 [3:42:43<12:08:17, 5.85s/it]
{'loss': 0.4954, 'learning_rate': 1.4376294786952067e-05, 'epoch': 0.38}
+
38%|███▊ | 4484/11952 [3:42:43<12:08:17, 5.85s/it]
38%|███▊ | 4485/11952 [3:42:48<12:00:45, 5.79s/it]
{'loss': 0.4954, 'learning_rate': 1.4373858000735262e-05, 'epoch': 0.38}
+
38%|███▊ | 4485/11952 [3:42:48<12:00:45, 5.79s/it]
38%|███▊ | 4486/11952 [3:42:54<11:49:48, 5.70s/it]
{'loss': 0.4881, 'learning_rate': 1.4371420893320515e-05, 'epoch': 0.38}
+
38%|███▊ | 4486/11952 [3:42:54<11:49:48, 5.70s/it]
38%|███▊ | 4487/11952 [3:43:00<11:53:48, 5.74s/it]
{'loss': 0.5036, 'learning_rate': 1.4368983464886799e-05, 'epoch': 0.38}
+
38%|███▊ | 4487/11952 [3:43:00<11:53:48, 5.74s/it]
38%|███▊ | 4488/11952 [3:43:05<11:54:06, 5.74s/it]
{'loss': 0.4723, 'learning_rate': 1.4366545715613112e-05, 'epoch': 0.38}
+
38%|███▊ | 4488/11952 [3:43:05<11:54:06, 5.74s/it]
38%|███▊ | 4489/11952 [3:43:11<11:47:37, 5.69s/it]
{'loss': 0.4846, 'learning_rate': 1.4364107645678465e-05, 'epoch': 0.38}
+
38%|███▊ | 4489/11952 [3:43:11<11:47:37, 5.69s/it]
38%|███▊ | 4490/11952 [3:43:17<11:53:14, 5.73s/it]
{'loss': 0.4819, 'learning_rate': 1.4361669255261905e-05, 'epoch': 0.38}
+
38%|███▊ | 4490/11952 [3:43:17<11:53:14, 5.73s/it]
38%|███▊ | 4491/11952 [3:43:22<11:50:59, 5.72s/it]
{'loss': 0.4875, 'learning_rate': 1.43592305445425e-05, 'epoch': 0.38}
+
38%|███▊ | 4491/11952 [3:43:22<11:50:59, 5.72s/it]
38%|███▊ | 4492/11952 [3:43:28<11:47:02, 5.69s/it]
{'loss': 0.4895, 'learning_rate': 1.4356791513699334e-05, 'epoch': 0.38}
+
38%|███▊ | 4492/11952 [3:43:28<11:47:02, 5.69s/it]
38%|███▊ | 4493/11952 [3:43:34<11:41:51, 5.65s/it]
{'loss': 0.4762, 'learning_rate': 1.4354352162911522e-05, 'epoch': 0.38}
+
38%|███▊ | 4493/11952 [3:43:34<11:41:51, 5.65s/it]
38%|███▊ | 4494/11952 [3:43:39<11:44:05, 5.66s/it]
{'loss': 0.4905, 'learning_rate': 1.4351912492358196e-05, 'epoch': 0.38}
+
38%|███▊ | 4494/11952 [3:43:39<11:44:05, 5.66s/it]
38%|███▊ | 4495/11952 [3:43:45<12:02:54, 5.82s/it]
{'loss': 0.4592, 'learning_rate': 1.4349472502218515e-05, 'epoch': 0.38}
+
38%|███▊ | 4495/11952 [3:43:45<12:02:54, 5.82s/it]
38%|███▊ | 4496/11952 [3:43:52<12:13:04, 5.90s/it]
{'loss': 0.4966, 'learning_rate': 1.4347032192671668e-05, 'epoch': 0.38}
+
38%|███▊ | 4496/11952 [3:43:52<12:13:04, 5.90s/it]
38%|███▊ | 4497/11952 [3:43:57<12:00:09, 5.80s/it]
{'loss': 0.4847, 'learning_rate': 1.4344591563896857e-05, 'epoch': 0.38}
+
38%|███▊ | 4497/11952 [3:43:57<12:00:09, 5.80s/it]
38%|███▊ | 4498/11952 [3:44:03<11:58:12, 5.78s/it]
{'loss': 0.4795, 'learning_rate': 1.4342150616073312e-05, 'epoch': 0.38}
+
38%|███▊ | 4498/11952 [3:44:03<11:58:12, 5.78s/it]
38%|███▊ | 4499/11952 [3:44:09<12:04:41, 5.83s/it]
{'loss': 0.5128, 'learning_rate': 1.4339709349380285e-05, 'epoch': 0.38}
+
38%|███▊ | 4499/11952 [3:44:09<12:04:41, 5.83s/it]3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
38%|███▊ | 4500/11952 [3:44:14<11:56:13, 5.77s/it]
{'loss': 0.4757, 'learning_rate': 1.4337267763997054e-05, 'epoch': 0.38}
+
38%|███▊ | 4500/11952 [3:44:14<11:56:13, 5.77s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
38%|███▊ | 4501/11952 [3:44:48<29:14:33, 14.13s/it]
{'loss': 0.4912, 'learning_rate': 1.4334825860102917e-05, 'epoch': 0.38}
+
38%|███▊ | 4501/11952 [3:44:48<29:14:33, 14.13s/it]
38%|███▊ | 4502/11952 [3:44:54<24:05:02, 11.64s/it]
{'loss': 0.4773, 'learning_rate': 1.4332383637877203e-05, 'epoch': 0.38}
+
38%|███▊ | 4502/11952 [3:44:54<24:05:02, 11.64s/it]
38%|███▊ | 4503/11952 [3:44:59<20:20:47, 9.83s/it]
{'loss': 0.4955, 'learning_rate': 1.432994109749925e-05, 'epoch': 0.38}
+
38%|███▊ | 4503/11952 [3:44:59<20:20:47, 9.83s/it]
38%|███▊ | 4504/11952 [3:45:05<17:43:09, 8.56s/it]
{'loss': 0.4786, 'learning_rate': 1.4327498239148434e-05, 'epoch': 0.38}
+
38%|███▊ | 4504/11952 [3:45:05<17:43:09, 8.56s/it]
38%|███▊ | 4505/11952 [3:45:11<15:59:40, 7.73s/it]
{'loss': 0.4953, 'learning_rate': 1.4325055063004145e-05, 'epoch': 0.38}
+
38%|███▊ | 4505/11952 [3:45:11<15:59:40, 7.73s/it]
38%|███▊ | 4506/11952 [3:45:17<14:43:44, 7.12s/it]
{'loss': 0.4892, 'learning_rate': 1.4322611569245806e-05, 'epoch': 0.38}
+
38%|███▊ | 4506/11952 [3:45:17<14:43:44, 7.12s/it]
38%|███▊ | 4507/11952 [3:45:23<14:03:12, 6.80s/it]
{'loss': 0.4917, 'learning_rate': 1.4320167758052848e-05, 'epoch': 0.38}
+
38%|███▊ | 4507/11952 [3:45:23<14:03:12, 6.80s/it]
38%|███▊ | 4508/11952 [3:45:29<13:30:59, 6.54s/it]
{'loss': 0.4832, 'learning_rate': 1.4317723629604743e-05, 'epoch': 0.38}
+
38%|███▊ | 4508/11952 [3:45:29<13:30:59, 6.54s/it]
38%|███▊ | 4509/11952 [3:45:35<13:14:16, 6.40s/it]
{'loss': 0.4878, 'learning_rate': 1.431527918408097e-05, 'epoch': 0.38}
+
38%|███▊ | 4509/11952 [3:45:35<13:14:16, 6.40s/it]
38%|███▊ | 4510/11952 [3:45:40<12:51:10, 6.22s/it]
{'loss': 0.4948, 'learning_rate': 1.4312834421661044e-05, 'epoch': 0.38}
+
38%|███▊ | 4510/11952 [3:45:40<12:51:10, 6.22s/it]
38%|███▊ | 4511/11952 [3:45:46<12:32:17, 6.07s/it]
{'loss': 0.4869, 'learning_rate': 1.4310389342524494e-05, 'epoch': 0.38}
+
38%|███▊ | 4511/11952 [3:45:46<12:32:17, 6.07s/it]
38%|███▊ | 4512/11952 [3:45:52<12:19:17, 5.96s/it]
{'loss': 0.491, 'learning_rate': 1.4307943946850883e-05, 'epoch': 0.38}
+
38%|███▊ | 4512/11952 [3:45:52<12:19:17, 5.96s/it]
38%|███▊ | 4513/11952 [3:45:58<12:14:19, 5.92s/it]
{'loss': 0.4886, 'learning_rate': 1.4305498234819783e-05, 'epoch': 0.38}
+
38%|███▊ | 4513/11952 [3:45:58<12:14:19, 5.92s/it]
38%|███▊ | 4514/11952 [3:46:03<12:06:44, 5.86s/it]
{'loss': 0.4815, 'learning_rate': 1.4303052206610801e-05, 'epoch': 0.38}
+
38%|███▊ | 4514/11952 [3:46:03<12:06:44, 5.86s/it]
38%|███▊ | 4515/11952 [3:46:09<12:05:28, 5.85s/it]
{'loss': 0.4738, 'learning_rate': 1.4300605862403563e-05, 'epoch': 0.38}
+
38%|███▊ | 4515/11952 [3:46:09<12:05:28, 5.85s/it]
38%|███▊ | 4516/11952 [3:46:15<12:16:59, 5.95s/it]
{'loss': 0.5164, 'learning_rate': 1.4298159202377719e-05, 'epoch': 0.38}
+
38%|███▊ | 4516/11952 [3:46:15<12:16:59, 5.95s/it]
38%|███▊ | 4517/11952 [3:46:21<12:13:21, 5.92s/it]
{'loss': 0.4937, 'learning_rate': 1.4295712226712941e-05, 'epoch': 0.38}
+
38%|███▊ | 4517/11952 [3:46:21<12:13:21, 5.92s/it]
38%|███▊ | 4518/11952 [3:46:27<12:05:25, 5.85s/it]
{'loss': 0.4743, 'learning_rate': 1.4293264935588921e-05, 'epoch': 0.38}
+
38%|███▊ | 4518/11952 [3:46:27<12:05:25, 5.85s/it]
38%|███▊ | 4519/11952 [3:46:33<12:05:35, 5.86s/it]
{'loss': 0.4843, 'learning_rate': 1.4290817329185388e-05, 'epoch': 0.38}
+
38%|███▊ | 4519/11952 [3:46:33<12:05:35, 5.86s/it]
38%|███▊ | 4520/11952 [3:46:39<12:11:00, 5.90s/it]
{'loss': 0.4989, 'learning_rate': 1.428836940768207e-05, 'epoch': 0.38}
+
38%|███▊ | 4520/11952 [3:46:39<12:11:00, 5.90s/it]
38%|███▊ | 4521/11952 [3:46:45<12:15:01, 5.93s/it]
{'loss': 0.4858, 'learning_rate': 1.4285921171258741e-05, 'epoch': 0.38}
+
38%|███▊ | 4521/11952 [3:46:45<12:15:01, 5.93s/it]
38%|███▊ | 4522/11952 [3:46:50<12:04:36, 5.85s/it]
{'loss': 0.477, 'learning_rate': 1.4283472620095192e-05, 'epoch': 0.38}
+
38%|███▊ | 4522/11952 [3:46:50<12:04:36, 5.85s/it]
38%|███▊ | 4523/11952 [3:46:56<11:55:25, 5.78s/it]
{'loss': 0.4741, 'learning_rate': 1.4281023754371226e-05, 'epoch': 0.38}
+
38%|███▊ | 4523/11952 [3:46:56<11:55:25, 5.78s/it]
38%|███▊ | 4524/11952 [3:47:02<11:56:52, 5.79s/it]
{'loss': 0.4952, 'learning_rate': 1.4278574574266681e-05, 'epoch': 0.38}
+
38%|███▊ | 4524/11952 [3:47:02<11:56:52, 5.79s/it]
38%|███▊ | 4525/11952 [3:47:08<11:53:51, 5.77s/it]
{'loss': 0.4953, 'learning_rate': 1.4276125079961417e-05, 'epoch': 0.38}
+
38%|███▊ | 4525/11952 [3:47:08<11:53:51, 5.77s/it]
38%|███▊ | 4526/11952 [3:47:13<11:49:46, 5.73s/it]
{'loss': 0.5021, 'learning_rate': 1.4273675271635313e-05, 'epoch': 0.38}
+
38%|███▊ | 4526/11952 [3:47:13<11:49:46, 5.73s/it]
38%|███▊ | 4527/11952 [3:47:19<11:54:52, 5.78s/it]
{'loss': 0.4825, 'learning_rate': 1.4271225149468272e-05, 'epoch': 0.38}
+
38%|███▊ | 4527/11952 [3:47:19<11:54:52, 5.78s/it]
38%|███▊ | 4528/11952 [3:47:25<11:53:42, 5.77s/it]
{'loss': 0.4693, 'learning_rate': 1.426877471364022e-05, 'epoch': 0.38}
+
38%|███▊ | 4528/11952 [3:47:25<11:53:42, 5.77s/it]
38%|███▊ | 4529/11952 [3:47:31<12:12:13, 5.92s/it]
{'loss': 0.4788, 'learning_rate': 1.4266323964331112e-05, 'epoch': 0.38}
+
38%|███▊ | 4529/11952 [3:47:31<12:12:13, 5.92s/it]
38%|███▊ | 4530/11952 [3:47:37<12:11:43, 5.92s/it]
{'loss': 0.469, 'learning_rate': 1.4263872901720914e-05, 'epoch': 0.38}
+
38%|███▊ | 4530/11952 [3:47:37<12:11:43, 5.92s/it]
38%|███▊ | 4531/11952 [3:47:43<12:06:05, 5.87s/it]
{'loss': 0.4949, 'learning_rate': 1.4261421525989625e-05, 'epoch': 0.38}
+
38%|███▊ | 4531/11952 [3:47:43<12:06:05, 5.87s/it]
38%|███▊ | 4532/11952 [3:47:48<11:57:01, 5.80s/it]
{'loss': 0.4905, 'learning_rate': 1.4258969837317265e-05, 'epoch': 0.38}
+
38%|███▊ | 4532/11952 [3:47:48<11:57:01, 5.80s/it]
38%|███▊ | 4533/11952 [3:47:54<12:01:10, 5.83s/it]
{'loss': 0.488, 'learning_rate': 1.4256517835883874e-05, 'epoch': 0.38}
+
38%|███▊ | 4533/11952 [3:47:54<12:01:10, 5.83s/it]
38%|███▊ | 4534/11952 [3:48:00<12:01:20, 5.83s/it]
{'loss': 0.5049, 'learning_rate': 1.4254065521869519e-05, 'epoch': 0.38}
+
38%|███▊ | 4534/11952 [3:48:00<12:01:20, 5.83s/it]
38%|███▊ | 4535/11952 [3:48:06<12:14:02, 5.94s/it]
{'loss': 0.5057, 'learning_rate': 1.4251612895454282e-05, 'epoch': 0.38}
+
38%|███▊ | 4535/11952 [3:48:06<12:14:02, 5.94s/it]
38%|███▊ | 4536/11952 [3:48:12<12:13:09, 5.93s/it]
{'loss': 0.4912, 'learning_rate': 1.4249159956818279e-05, 'epoch': 0.38}
+
38%|███▊ | 4536/11952 [3:48:12<12:13:09, 5.93s/it]
38%|███▊ | 4537/11952 [3:48:18<12:07:22, 5.89s/it]
{'loss': 0.5032, 'learning_rate': 1.4246706706141646e-05, 'epoch': 0.38}
+
38%|███▊ | 4537/11952 [3:48:18<12:07:22, 5.89s/it]
38%|███▊ | 4538/11952 [3:48:24<12:09:51, 5.91s/it]
{'loss': 0.4765, 'learning_rate': 1.4244253143604531e-05, 'epoch': 0.38}
+
38%|███▊ | 4538/11952 [3:48:24<12:09:51, 5.91s/it]
38%|███▊ | 4539/11952 [3:48:30<12:16:59, 5.97s/it]
{'loss': 0.4854, 'learning_rate': 1.4241799269387122e-05, 'epoch': 0.38}
+
38%|███▊ | 4539/11952 [3:48:30<12:16:59, 5.97s/it]
38%|███▊ | 4540/11952 [3:48:36<12:04:25, 5.86s/it]
{'loss': 0.4815, 'learning_rate': 1.4239345083669615e-05, 'epoch': 0.38}
+
38%|███▊ | 4540/11952 [3:48:36<12:04:25, 5.86s/it]
38%|███▊ | 4541/11952 [3:48:42<12:08:12, 5.90s/it]
{'loss': 0.5124, 'learning_rate': 1.423689058663224e-05, 'epoch': 0.38}
+
38%|███▊ | 4541/11952 [3:48:42<12:08:12, 5.90s/it]
38%|███▊ | 4542/11952 [3:48:48<12:07:09, 5.89s/it]
{'loss': 0.4851, 'learning_rate': 1.4234435778455242e-05, 'epoch': 0.38}
+
38%|███▊ | 4542/11952 [3:48:48<12:07:09, 5.89s/it]
38%|███▊ | 4543/11952 [3:48:53<12:01:18, 5.84s/it]
{'loss': 0.5049, 'learning_rate': 1.4231980659318891e-05, 'epoch': 0.38}
+
38%|███▊ | 4543/11952 [3:48:53<12:01:18, 5.84s/it]
38%|███▊ | 4544/11952 [3:48:59<11:53:25, 5.78s/it]
{'loss': 0.4756, 'learning_rate': 1.4229525229403486e-05, 'epoch': 0.38}
+
38%|███▊ | 4544/11952 [3:48:59<11:53:25, 5.78s/it]
38%|███▊ | 4545/11952 [3:49:05<11:57:36, 5.81s/it]
{'loss': 0.4865, 'learning_rate': 1.4227069488889338e-05, 'epoch': 0.38}
+
38%|███▊ | 4545/11952 [3:49:05<11:57:36, 5.81s/it]
38%|███▊ | 4546/11952 [3:49:11<11:56:14, 5.80s/it]
{'loss': 0.4887, 'learning_rate': 1.422461343795679e-05, 'epoch': 0.38}
+
38%|███▊ | 4546/11952 [3:49:11<11:56:14, 5.80s/it]
38%|███▊ | 4547/11952 [3:49:17<12:03:09, 5.86s/it]
{'loss': 0.4804, 'learning_rate': 1.4222157076786201e-05, 'epoch': 0.38}
+
38%|███▊ | 4547/11952 [3:49:17<12:03:09, 5.86s/it]
38%|███▊ | 4548/11952 [3:49:22<11:53:23, 5.78s/it]
{'loss': 0.4999, 'learning_rate': 1.4219700405557958e-05, 'epoch': 0.38}
+
38%|███▊ | 4548/11952 [3:49:22<11:53:23, 5.78s/it]
38%|███▊ | 4549/11952 [3:49:28<11:57:06, 5.81s/it]
{'loss': 0.4974, 'learning_rate': 1.4217243424452466e-05, 'epoch': 0.38}
+
38%|███▊ | 4549/11952 [3:49:28<11:57:06, 5.81s/it]1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
38%|███▊ | 4550/11952 [3:49:34<11:53:42, 5.79s/it]
{'loss': 0.5029, 'learning_rate': 1.4214786133650162e-05, 'epoch': 0.38}
+
38%|███▊ | 4550/11952 [3:49:34<11:53:42, 5.79s/it]
38%|███▊ | 4551/11952 [3:49:40<11:52:41, 5.78s/it]
{'loss': 0.4983, 'learning_rate': 1.4212328533331493e-05, 'epoch': 0.38}
+
38%|███▊ | 4551/11952 [3:49:40<11:52:41, 5.78s/it]
38%|███▊ | 4552/11952 [3:49:46<11:56:49, 5.81s/it]
{'loss': 0.5079, 'learning_rate': 1.4209870623676934e-05, 'epoch': 0.38}
+
38%|███▊ | 4552/11952 [3:49:46<11:56:49, 5.81s/it]
38%|███▊ | 4553/11952 [3:49:51<11:59:10, 5.83s/it]
{'loss': 0.5062, 'learning_rate': 1.4207412404866992e-05, 'epoch': 0.38}
+
38%|███▊ | 4553/11952 [3:49:51<11:59:10, 5.83s/it]
38%|███▊ | 4554/11952 [3:49:57<12:03:20, 5.87s/it]
{'loss': 0.496, 'learning_rate': 1.420495387708218e-05, 'epoch': 0.38}
+
38%|███▊ | 4554/11952 [3:49:57<12:03:20, 5.87s/it]
38%|███▊ | 4555/11952 [3:50:03<11:53:53, 5.79s/it]
{'loss': 0.5021, 'learning_rate': 1.4202495040503043e-05, 'epoch': 0.38}
+
38%|███▊ | 4555/11952 [3:50:03<11:53:53, 5.79s/it]
38%|███▊ | 4556/11952 [3:50:09<11:48:40, 5.75s/it]
{'loss': 0.492, 'learning_rate': 1.4200035895310151e-05, 'epoch': 0.38}
+
38%|███▊ | 4556/11952 [3:50:09<11:48:40, 5.75s/it]
38%|███▊ | 4557/11952 [3:50:14<11:45:44, 5.73s/it]
{'loss': 0.4871, 'learning_rate': 1.4197576441684096e-05, 'epoch': 0.38}
+
38%|███▊ | 4557/11952 [3:50:14<11:45:44, 5.73s/it]
38%|███▊ | 4558/11952 [3:50:20<11:50:18, 5.76s/it]
{'loss': 0.4845, 'learning_rate': 1.4195116679805483e-05, 'epoch': 0.38}
+
38%|███▊ | 4558/11952 [3:50:20<11:50:18, 5.76s/it]
38%|███▊ | 4559/11952 [3:50:26<11:54:14, 5.80s/it]
{'loss': 0.4746, 'learning_rate': 1.4192656609854949e-05, 'epoch': 0.38}
+
38%|███▊ | 4559/11952 [3:50:26<11:54:14, 5.80s/it]
38%|███▊ | 4560/11952 [3:50:32<11:49:36, 5.76s/it]
{'loss': 0.486, 'learning_rate': 1.4190196232013154e-05, 'epoch': 0.38}
+
38%|███▊ | 4560/11952 [3:50:32<11:49:36, 5.76s/it]
38%|███▊ | 4561/11952 [3:50:38<11:59:20, 5.84s/it]
{'loss': 0.4918, 'learning_rate': 1.4187735546460775e-05, 'epoch': 0.38}
+
38%|███▊ | 4561/11952 [3:50:38<11:59:20, 5.84s/it]
38%|███▊ | 4562/11952 [3:50:44<12:03:24, 5.87s/it]
{'loss': 0.5124, 'learning_rate': 1.4185274553378513e-05, 'epoch': 0.38}
+
38%|███▊ | 4562/11952 [3:50:44<12:03:24, 5.87s/it]
38%|███▊ | 4563/11952 [3:50:49<11:57:28, 5.83s/it]
{'loss': 0.4785, 'learning_rate': 1.41828132529471e-05, 'epoch': 0.38}
+
38%|███▊ | 4563/11952 [3:50:49<11:57:28, 5.83s/it]
38%|███▊ | 4564/11952 [3:50:55<11:55:27, 5.81s/it]
{'loss': 0.4927, 'learning_rate': 1.4180351645347279e-05, 'epoch': 0.38}
+
38%|███▊ | 4564/11952 [3:50:55<11:55:27, 5.81s/it]
38%|███▊ | 4565/11952 [3:51:01<12:10:15, 5.93s/it]
{'loss': 0.5018, 'learning_rate': 1.417788973075982e-05, 'epoch': 0.38}
+
38%|███▊ | 4565/11952 [3:51:01<12:10:15, 5.93s/it]
38%|███▊ | 4566/11952 [3:51:07<12:00:19, 5.85s/it]
{'loss': 0.4941, 'learning_rate': 1.4175427509365516e-05, 'epoch': 0.38}
+
38%|███▊ | 4566/11952 [3:51:07<12:00:19, 5.85s/it]
38%|███▊ | 4567/11952 [3:51:13<12:11:17, 5.94s/it]
{'loss': 0.4783, 'learning_rate': 1.417296498134518e-05, 'epoch': 0.38}
+
38%|███▊ | 4567/11952 [3:51:13<12:11:17, 5.94s/it]
38%|███▊ | 4568/11952 [3:51:19<12:15:33, 5.98s/it]
{'loss': 0.5057, 'learning_rate': 1.4170502146879656e-05, 'epoch': 0.38}
+
38%|███▊ | 4568/11952 [3:51:19<12:15:33, 5.98s/it]
38%|███▊ | 4569/11952 [3:51:25<12:15:52, 5.98s/it]
{'loss': 0.5271, 'learning_rate': 1.4168039006149799e-05, 'epoch': 0.38}
+
38%|███▊ | 4569/11952 [3:51:25<12:15:52, 5.98s/it]
38%|███▊ | 4570/11952 [3:51:31<12:01:30, 5.86s/it]
{'loss': 0.4779, 'learning_rate': 1.4165575559336496e-05, 'epoch': 0.38}
+
38%|███▊ | 4570/11952 [3:51:31<12:01:30, 5.86s/it]
38%|███▊ | 4571/11952 [3:51:37<12:01:47, 5.87s/it]
{'loss': 0.4642, 'learning_rate': 1.4163111806620646e-05, 'epoch': 0.38}
+
38%|███▊ | 4571/11952 [3:51:37<12:01:47, 5.87s/it]
38%|███▊ | 4572/11952 [3:51:43<12:06:16, 5.90s/it]
{'loss': 0.5108, 'learning_rate': 1.416064774818318e-05, 'epoch': 0.38}
+
38%|███▊ | 4572/11952 [3:51:43<12:06:16, 5.90s/it]
38%|███▊ | 4573/11952 [3:51:49<12:04:08, 5.89s/it]
{'loss': 0.4914, 'learning_rate': 1.4158183384205052e-05, 'epoch': 0.38}
+
38%|███▊ | 4573/11952 [3:51:49<12:04:08, 5.89s/it]
38%|███▊ | 4574/11952 [3:51:54<12:02:42, 5.88s/it]
{'loss': 0.4902, 'learning_rate': 1.4155718714867232e-05, 'epoch': 0.38}
+
38%|███▊ | 4574/11952 [3:51:54<12:02:42, 5.88s/it]
38%|███▊ | 4575/11952 [3:52:00<12:04:10, 5.89s/it]
{'loss': 0.4846, 'learning_rate': 1.4153253740350717e-05, 'epoch': 0.38}
+
38%|███▊ | 4575/11952 [3:52:00<12:04:10, 5.89s/it]
38%|███▊ | 4576/11952 [3:52:06<12:02:11, 5.87s/it]
{'loss': 0.4685, 'learning_rate': 1.4150788460836516e-05, 'epoch': 0.38}
+
38%|███▊ | 4576/11952 [3:52:06<12:02:11, 5.87s/it]
38%|███▊ | 4577/11952 [3:52:12<12:00:16, 5.86s/it]
{'loss': 0.4808, 'learning_rate': 1.4148322876505675e-05, 'epoch': 0.38}
+
38%|███▊ | 4577/11952 [3:52:12<12:00:16, 5.86s/it]
38%|███▊ | 4578/11952 [3:52:18<11:56:32, 5.83s/it]
{'loss': 0.4915, 'learning_rate': 1.4145856987539261e-05, 'epoch': 0.38}
+
38%|███▊ | 4578/11952 [3:52:18<11:56:32, 5.83s/it]
38%|███▊ | 4579/11952 [3:52:24<11:59:39, 5.86s/it]
{'loss': 0.4938, 'learning_rate': 1.414339079411835e-05, 'epoch': 0.38}
+
38%|███▊ | 4579/11952 [3:52:24<11:59:39, 5.86s/it]
38%|███▊ | 4580/11952 [3:52:30<12:07:23, 5.92s/it]
{'loss': 0.4984, 'learning_rate': 1.4140924296424055e-05, 'epoch': 0.38}
+
38%|███▊ | 4580/11952 [3:52:30<12:07:23, 5.92s/it]
38%|███▊ | 4581/11952 [3:52:36<12:03:15, 5.89s/it]
{'loss': 0.4884, 'learning_rate': 1.4138457494637501e-05, 'epoch': 0.38}
+
38%|███▊ | 4581/11952 [3:52:36<12:03:15, 5.89s/it]
38%|███▊ | 4582/11952 [3:52:41<11:59:49, 5.86s/it]
{'loss': 0.4833, 'learning_rate': 1.4135990388939839e-05, 'epoch': 0.38}
+
38%|███▊ | 4582/11952 [3:52:41<11:59:49, 5.86s/it]
38%|███▊ | 4583/11952 [3:52:47<11:52:23, 5.80s/it]
{'loss': 0.4856, 'learning_rate': 1.4133522979512252e-05, 'epoch': 0.38}
+
38%|███▊ | 4583/11952 [3:52:47<11:52:23, 5.80s/it]
38%|███▊ | 4584/11952 [3:52:53<12:07:36, 5.93s/it]
{'loss': 0.4952, 'learning_rate': 1.4131055266535926e-05, 'epoch': 0.38}
+
38%|███▊ | 4584/11952 [3:52:53<12:07:36, 5.93s/it]
38%|███▊ | 4585/11952 [3:52:59<12:14:59, 5.99s/it]
{'loss': 0.5056, 'learning_rate': 1.4128587250192087e-05, 'epoch': 0.38}
+
38%|███▊ | 4585/11952 [3:52:59<12:14:59, 5.99s/it]
38%|███▊ | 4586/11952 [3:53:05<12:07:48, 5.93s/it]
{'loss': 0.4818, 'learning_rate': 1.412611893066197e-05, 'epoch': 0.38}
+
38%|███▊ | 4586/11952 [3:53:05<12:07:48, 5.93s/it]
38%|███▊ | 4587/11952 [3:53:11<12:00:58, 5.87s/it]
{'loss': 0.4854, 'learning_rate': 1.4123650308126839e-05, 'epoch': 0.38}
+
38%|███▊ | 4587/11952 [3:53:11<12:00:58, 5.87s/it]
38%|███▊ | 4588/11952 [3:53:17<12:05:23, 5.91s/it]
{'loss': 0.4762, 'learning_rate': 1.4121181382767986e-05, 'epoch': 0.38}
+
38%|███▊ | 4588/11952 [3:53:17<12:05:23, 5.91s/it]
38%|███▊ | 4589/11952 [3:53:22<11:49:43, 5.78s/it]
{'loss': 0.4713, 'learning_rate': 1.4118712154766708e-05, 'epoch': 0.38}
+
38%|███▊ | 4589/11952 [3:53:22<11:49:43, 5.78s/it]
38%|███▊ | 4590/11952 [3:53:28<11:47:19, 5.76s/it]
{'loss': 0.4836, 'learning_rate': 1.4116242624304343e-05, 'epoch': 0.38}
+
38%|███▊ | 4590/11952 [3:53:28<11:47:19, 5.76s/it]
38%|███▊ | 4591/11952 [3:53:34<11:52:50, 5.81s/it]
{'loss': 0.4767, 'learning_rate': 1.411377279156224e-05, 'epoch': 0.38}
+
38%|███▊ | 4591/11952 [3:53:34<11:52:50, 5.81s/it]
38%|███▊ | 4592/11952 [3:53:40<11:45:01, 5.75s/it]
{'loss': 0.4845, 'learning_rate': 1.4111302656721775e-05, 'epoch': 0.38}
+
38%|███▊ | 4592/11952 [3:53:40<11:45:01, 5.75s/it]
38%|███▊ | 4593/11952 [3:53:45<11:46:43, 5.76s/it]
{'loss': 0.4769, 'learning_rate': 1.410883221996434e-05, 'epoch': 0.38}
+
38%|███▊ | 4593/11952 [3:53:45<11:46:43, 5.76s/it]
38%|███▊ | 4594/11952 [3:53:51<11:50:24, 5.79s/it]
{'loss': 0.4906, 'learning_rate': 1.410636148147136e-05, 'epoch': 0.38}
+
38%|███▊ | 4594/11952 [3:53:51<11:50:24, 5.79s/it]
38%|███▊ | 4595/11952 [3:53:57<11:45:25, 5.75s/it]
{'loss': 0.4971, 'learning_rate': 1.4103890441424271e-05, 'epoch': 0.38}
+
38%|███▊ | 4595/11952 [3:53:57<11:45:25, 5.75s/it]
38%|███▊ | 4596/11952 [3:54:03<11:41:52, 5.72s/it]
{'loss': 0.481, 'learning_rate': 1.4101419100004537e-05, 'epoch': 0.38}
+
38%|███▊ | 4596/11952 [3:54:03<11:41:52, 5.72s/it]
38%|███▊ | 4597/11952 [3:54:09<11:49:35, 5.79s/it]
{'loss': 0.4774, 'learning_rate': 1.4098947457393641e-05, 'epoch': 0.38}
+
38%|███▊ | 4597/11952 [3:54:09<11:49:35, 5.79s/it]
38%|███▊ | 4598/11952 [3:54:14<11:47:59, 5.78s/it]
{'loss': 0.4893, 'learning_rate': 1.4096475513773097e-05, 'epoch': 0.38}
+
38%|███▊ | 4598/11952 [3:54:14<11:47:59, 5.78s/it]
38%|███▊ | 4599/11952 [3:54:20<12:04:40, 5.91s/it]
{'loss': 0.4874, 'learning_rate': 1.4094003269324428e-05, 'epoch': 0.38}
+
38%|███▊ | 4599/11952 [3:54:20<12:04:40, 5.91s/it]51 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
38%|███▊ | 4600/11952 [3:54:26<12:03:58, 5.91s/it]
{'loss': 0.5024, 'learning_rate': 1.4091530724229188e-05, 'epoch': 0.38}
+
38%|███▊ | 4600/11952 [3:54:26<12:03:58, 5.91s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
38%|███▊ | 4601/11952 [3:55:00<29:03:47, 14.23s/it]
{'loss': 0.5141, 'learning_rate': 1.408905787866895e-05, 'epoch': 0.38}
+
38%|███▊ | 4601/11952 [3:55:00<29:03:47, 14.23s/it]
39%|███▊ | 4602/11952 [3:55:06<23:44:47, 11.63s/it]
{'loss': 0.4768, 'learning_rate': 1.4086584732825306e-05, 'epoch': 0.39}
+
39%|███▊ | 4602/11952 [3:55:06<23:44:47, 11.63s/it]
39%|███▊ | 4603/11952 [3:55:11<20:03:08, 9.82s/it]
{'loss': 0.5032, 'learning_rate': 1.4084111286879878e-05, 'epoch': 0.39}
+
39%|███▊ | 4603/11952 [3:55:11<20:03:08, 9.82s/it]
39%|███▊ | 4604/11952 [3:55:17<17:37:49, 8.64s/it]
{'loss': 0.4939, 'learning_rate': 1.4081637541014306e-05, 'epoch': 0.39}
+
39%|███▊ | 4604/11952 [3:55:17<17:37:49, 8.64s/it]
39%|███▊ | 4605/11952 [3:55:23<16:01:59, 7.86s/it]
{'loss': 0.4796, 'learning_rate': 1.4079163495410248e-05, 'epoch': 0.39}
+
39%|███▊ | 4605/11952 [3:55:23<16:01:59, 7.86s/it]
39%|███▊ | 4606/11952 [3:55:29<14:41:26, 7.20s/it]
{'loss': 0.4617, 'learning_rate': 1.407668915024939e-05, 'epoch': 0.39}
+
39%|███▊ | 4606/11952 [3:55:29<14:41:26, 7.20s/it]
39%|███▊ | 4607/11952 [3:55:34<13:39:25, 6.69s/it]
{'loss': 0.4805, 'learning_rate': 1.4074214505713437e-05, 'epoch': 0.39}
+
39%|███▊ | 4607/11952 [3:55:34<13:39:25, 6.69s/it]
39%|███▊ | 4608/11952 [3:55:40<13:12:07, 6.47s/it]
{'loss': 0.4849, 'learning_rate': 1.4071739561984115e-05, 'epoch': 0.39}
+
39%|███▊ | 4608/11952 [3:55:40<13:12:07, 6.47s/it]
39%|███▊ | 4609/11952 [3:55:46<12:49:27, 6.29s/it]
{'loss': 0.4756, 'learning_rate': 1.4069264319243178e-05, 'epoch': 0.39}
+
39%|███▊ | 4609/11952 [3:55:46<12:49:27, 6.29s/it]
39%|███▊ | 4610/11952 [3:55:52<12:33:46, 6.16s/it]
{'loss': 0.517, 'learning_rate': 1.4066788777672393e-05, 'epoch': 0.39}
+
39%|███▊ | 4610/11952 [3:55:52<12:33:46, 6.16s/it]
39%|███▊ | 4611/11952 [3:55:58<12:15:08, 6.01s/it]
{'loss': 0.476, 'learning_rate': 1.4064312937453556e-05, 'epoch': 0.39}
+
39%|███▊ | 4611/11952 [3:55:58<12:15:08, 6.01s/it]
39%|███▊ | 4612/11952 [3:56:04<12:33:42, 6.16s/it]
{'loss': 0.5265, 'learning_rate': 1.406183679876848e-05, 'epoch': 0.39}
+
39%|███▊ | 4612/11952 [3:56:04<12:33:42, 6.16s/it]
39%|███▊ | 4613/11952 [3:56:10<12:27:04, 6.11s/it]
{'loss': 0.4927, 'learning_rate': 1.4059360361799004e-05, 'epoch': 0.39}
+
39%|███▊ | 4613/11952 [3:56:10<12:27:04, 6.11s/it]
39%|███▊ | 4614/11952 [3:56:16<12:14:35, 6.01s/it]
{'loss': 0.4918, 'learning_rate': 1.4056883626726989e-05, 'epoch': 0.39}
+
39%|███▊ | 4614/11952 [3:56:16<12:14:35, 6.01s/it]
39%|███▊ | 4615/11952 [3:56:22<12:12:19, 5.99s/it]
{'loss': 0.4821, 'learning_rate': 1.4054406593734316e-05, 'epoch': 0.39}
+
39%|███▊ | 4615/11952 [3:56:22<12:12:19, 5.99s/it]
39%|███▊ | 4616/11952 [3:56:28<12:10:32, 5.97s/it]
{'loss': 0.4773, 'learning_rate': 1.4051929263002884e-05, 'epoch': 0.39}
+
39%|███▊ | 4616/11952 [3:56:28<12:10:32, 5.97s/it]
39%|███▊ | 4617/11952 [3:56:33<11:59:44, 5.89s/it]
{'loss': 0.491, 'learning_rate': 1.404945163471462e-05, 'epoch': 0.39}
+
39%|███▊ | 4617/11952 [3:56:33<11:59:44, 5.89s/it]
39%|███▊ | 4618/11952 [3:56:40<12:11:46, 5.99s/it]
{'loss': 0.4877, 'learning_rate': 1.4046973709051467e-05, 'epoch': 0.39}
+
39%|███▊ | 4618/11952 [3:56:40<12:11:46, 5.99s/it]
39%|███▊ | 4619/11952 [3:56:46<12:15:38, 6.02s/it]
{'loss': 0.4922, 'learning_rate': 1.4044495486195404e-05, 'epoch': 0.39}
+
39%|███▊ | 4619/11952 [3:56:46<12:15:38, 6.02s/it]
39%|███▊ | 4620/11952 [3:56:51<12:03:26, 5.92s/it]
{'loss': 0.4758, 'learning_rate': 1.4042016966328411e-05, 'epoch': 0.39}
+
39%|███▊ | 4620/11952 [3:56:51<12:03:26, 5.92s/it]
39%|███▊ | 4621/11952 [3:56:57<12:05:46, 5.94s/it]
{'loss': 0.526, 'learning_rate': 1.4039538149632508e-05, 'epoch': 0.39}
+
39%|███▊ | 4621/11952 [3:56:57<12:05:46, 5.94s/it]
39%|███▊ | 4622/11952 [3:57:03<11:56:22, 5.86s/it]
{'loss': 0.4764, 'learning_rate': 1.4037059036289722e-05, 'epoch': 0.39}
+
39%|███▊ | 4622/11952 [3:57:03<11:56:22, 5.86s/it]
39%|███▊ | 4623/11952 [3:57:09<11:47:56, 5.80s/it]
{'loss': 0.4764, 'learning_rate': 1.4034579626482112e-05, 'epoch': 0.39}
+
39%|███▊ | 4623/11952 [3:57:09<11:47:56, 5.80s/it]
39%|███▊ | 4624/11952 [3:57:15<12:01:10, 5.90s/it]
{'loss': 0.4878, 'learning_rate': 1.4032099920391753e-05, 'epoch': 0.39}
+
39%|███▊ | 4624/11952 [3:57:15<12:01:10, 5.90s/it]
39%|███▊ | 4625/11952 [3:57:21<11:52:32, 5.83s/it]
{'loss': 0.4794, 'learning_rate': 1.402961991820075e-05, 'epoch': 0.39}
+
39%|███▊ | 4625/11952 [3:57:21<11:52:32, 5.83s/it]
39%|███▊ | 4626/11952 [3:57:26<11:49:50, 5.81s/it]
{'loss': 0.4732, 'learning_rate': 1.4027139620091221e-05, 'epoch': 0.39}
+
39%|███▊ | 4626/11952 [3:57:26<11:49:50, 5.81s/it]
39%|███▊ | 4627/11952 [3:57:32<11:52:08, 5.83s/it]
{'loss': 0.4775, 'learning_rate': 1.4024659026245307e-05, 'epoch': 0.39}
+
39%|███▊ | 4627/11952 [3:57:32<11:52:08, 5.83s/it]
39%|███▊ | 4628/11952 [3:57:38<11:55:55, 5.87s/it]
{'loss': 0.5077, 'learning_rate': 1.4022178136845173e-05, 'epoch': 0.39}
+
39%|███▊ | 4628/11952 [3:57:38<11:55:55, 5.87s/it]
39%|███▊ | 4629/11952 [3:57:44<11:59:39, 5.90s/it]
{'loss': 0.4914, 'learning_rate': 1.4019696952073008e-05, 'epoch': 0.39}
+
39%|███▊ | 4629/11952 [3:57:44<11:59:39, 5.90s/it]
39%|███▊ | 4630/11952 [3:57:50<11:47:42, 5.80s/it]
{'loss': 0.4836, 'learning_rate': 1.4017215472111016e-05, 'epoch': 0.39}
+
39%|███▊ | 4630/11952 [3:57:50<11:47:42, 5.80s/it]
39%|███▊ | 4631/11952 [3:57:55<11:42:34, 5.76s/it]
{'loss': 0.4965, 'learning_rate': 1.401473369714143e-05, 'epoch': 0.39}
+
39%|███▊ | 4631/11952 [3:57:55<11:42:34, 5.76s/it]
39%|███▉ | 4632/11952 [3:58:02<11:55:56, 5.87s/it]
{'loss': 0.4938, 'learning_rate': 1.40122516273465e-05, 'epoch': 0.39}
+
39%|███▉ | 4632/11952 [3:58:02<11:55:56, 5.87s/it]
39%|███▉ | 4633/11952 [3:58:07<11:49:38, 5.82s/it]
{'loss': 0.4691, 'learning_rate': 1.4009769262908498e-05, 'epoch': 0.39}
+
39%|███▉ | 4633/11952 [3:58:07<11:49:38, 5.82s/it]Jun 10 16:33:11.115388 2754440 slurmstepd 0x155550ab8700: error: *** STEP 8828654.0 ON batch-block1-0014 CANCELLED AT 2025-06-10T16:33:11 DUE TO TIME LIMIT ***
+srun: Job step aborted: Waiting up to 122 seconds for job step to finish.
+
39%|███▉ | 4634/11952 [3:58:13<11:53:56, 5.85s/it]
{'loss': 0.4841, 'learning_rate': 1.4007286604009717e-05, 'epoch': 0.39}
+
39%|███▉ | 4634/11952 [3:58:13<11:53:56, 5.85s/it]srun: error: batch-block1-0014: task 0: Terminated
+srun: Terminating StepId=8828654.0
+srun: job 8833833 queued and waiting for resources
+srun: job 8833833 has been allocated resources
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+MASTER_ADDR=batch-block1-2091
+JobID: 8833833 | Full list: batch-block1-2091
+NETWORK=Efficient-Large-Model/VILA1.5-3b
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
+*****************************************
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+[2025-06-10 16:39:53,981] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:53,981] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:53,981] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:53,981] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:53,981] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:53,981] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:53,981] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:53,982] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 16:39:55,326] [INFO] [comm.py:625:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 16:39:55,326] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 16:39:55,326] [INFO] [comm.py:594:init_distributed] cdb=None
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+[2025-06-10 16:40:03,685] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 2.70B parameters
+
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.82s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.83s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.83s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.85s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.86s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.87s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.88s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.58s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.06s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.58s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.07s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.58s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.07s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.59s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.07s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.60s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.09s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.61s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.10s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 2.61s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:06<00:00, 3.10s/it]
+
Loading checkpoint shards: 50%|█████ | 1/2 [00:07<00:07, 7.96s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:08<00:00, 3.82s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:08<00:00, 4.44s/it]
+[2025-06-10 16:40:12,844] [WARNING] [partition_parameters.py:836:_post_init_method] param `probe` in SiglipMultiheadAttentionPoolingHead not on GPU so was not broadcasted from rank 0
+[2025-06-10 16:40:12,845] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.13B parameters
+[2025-06-10 16:40:14,786] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.15B parameters
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj'][Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[dist-0-of-8] LlavaLlamaModel(
+ (llm): LlamaForCausalLM(
+ (model): LlamaModel(
+ (embed_tokens): Embedding(32000, 2560, padding_idx=0)
+ (layers): ModuleList(
+ (0-31): 32 x LlamaDecoderLayer(
+ (self_attn): LlamaFlashAttention2(
+ (q_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (k_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (v_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (o_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (rotary_emb): LlamaRotaryEmbedding()
+ )
+ (mlp): LlamaMLP(
+ (gate_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (up_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (down_proj): Linear(in_features=6912, out_features=2560, bias=False)
+ (act_fn): SiLU()
+ )
+ (input_layernorm): LlamaRMSNorm()
+ (post_attention_layernorm): LlamaRMSNorm()
+ )
+ )
+ (norm): LlamaRMSNorm()
+ )
+ (lm_head): Linear(in_features=2560, out_features=32000, bias=False)
+ )
+ (vision_tower): SiglipVisionTower(
+ (vision_tower): SiglipVisionModel(
+ (vision_model): SiglipVisionTransformer(
+ (embeddings): SiglipVisionEmbeddings(
+ (patch_embedding): Conv2d(3, 1152, kernel_size=(14, 14), stride=(14, 14), padding=valid)
+ (position_embedding): Embedding(729, 1152)
+ )
+ (encoder): SiglipEncoder(
+ (layers): ModuleList(
+ (0-26): 27 x SiglipEncoderLayer(
+ (self_attn): SiglipAttention(
+ (k_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (v_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (q_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (out_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layer_norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ (layer_norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ )
+ )
+ )
+ (post_layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (head): SiglipMultiheadAttentionPoolingHead(
+ (attention): MultiheadAttention(
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ )
+ )
+ )
+ )
+ (mm_projector): MultimodalProjector(
+ (layers): Sequential(
+ (0): DownSampleBlock()
+ (1): LayerNorm((4608,), eps=1e-05, elementwise_affine=True)
+ (2): Linear(in_features=4608, out_features=2560, bias=True)
+ (3): GELU(approximate='none')
+ (4): Linear(in_features=2560, out_features=2560, bias=True)
+ )
+ )
+)
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[dist-0-of-8] Tunable parameters:
+language model True
+[dist-0-of-8] vision tower True
+[dist-0-of-8] mm projector True
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8137388229370117
+length of dataloader: 23905 3059964
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8366923332214355
+[GPU memory] before trainer 0.8308329582214355
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8238749504089355
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8318400382995605
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8313822746276855
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8324503898620605
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8313822746276855
+Parameter Offload: Total persistent parameters: 593856 in 349 params
+wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.18.7
+wandb: Run data is saved locally in /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/wandb/run-20250610_164124-ytg7r6zj
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run vila_3b_path_mask
+wandb: ⭐️ View project at https://wandb.ai/memmelma/VILA
+wandb: 🚀 View run at https://wandb.ai/memmelma/VILA/runs/ytg7r6zj
+
0%| | 0/11952 [00:00, ?it/s]Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+
38%|███▊ | 4601/11952 [00:23<00:37, 193.83it/s]
{'loss': 0.5141, 'learning_rate': 1.408905787866895e-05, 'epoch': 0.38}
+
38%|███▊ | 4601/11952 [00:23<00:37, 193.83it/s]
{'loss': 0.4768, 'learning_rate': 1.4086584732825306e-05, 'epoch': 0.39}
+
39%|███▊ | 4602/11952 [00:29<00:37, 193.83it/s]
{'loss': 0.5029, 'learning_rate': 1.4084111286879878e-05, 'epoch': 0.39}
+
39%|███▊ | 4603/11952 [00:34<00:37, 193.83it/s]
39%|███▊ | 4603/11952 [00:38<00:37, 193.83it/s]
39%|███▊ | 4604/11952 [00:40<01:16, 96.07it/s]
{'loss': 0.4939, 'learning_rate': 1.4081637541014306e-05, 'epoch': 0.39}
+
39%|███▊ | 4604/11952 [00:40<01:16, 96.07it/s]
39%|███▊ | 4605/11952 [00:46<01:36, 76.20it/s]
{'loss': 0.4798, 'learning_rate': 1.4079163495410248e-05, 'epoch': 0.39}
+
39%|███▊ | 4605/11952 [00:46<01:36, 76.20it/s]
39%|███▊ | 4606/11952 [00:52<02:02, 59.86it/s]
{'loss': 0.4618, 'learning_rate': 1.407668915024939e-05, 'epoch': 0.39}
+
39%|███▊ | 4606/11952 [00:52<02:02, 59.86it/s]
39%|███▊ | 4607/11952 [00:57<02:39, 46.17it/s]
{'loss': 0.4803, 'learning_rate': 1.4074214505713437e-05, 'epoch': 0.39}
+
39%|███▊ | 4607/11952 [00:58<02:39, 46.17it/s]
39%|███▊ | 4608/11952 [01:03<03:35, 34.10it/s]
{'loss': 0.4847, 'learning_rate': 1.4071739561984115e-05, 'epoch': 0.39}
+
39%|███▊ | 4608/11952 [01:03<03:35, 34.10it/s]
39%|███▊ | 4609/11952 [01:09<04:54, 24.96it/s]
{'loss': 0.4754, 'learning_rate': 1.4069264319243178e-05, 'epoch': 0.39}
+
39%|███▊ | 4609/11952 [01:09<04:54, 24.96it/s]
39%|███▊ | 4610/11952 [01:15<06:45, 18.09it/s]
{'loss': 0.5171, 'learning_rate': 1.4066788777672393e-05, 'epoch': 0.39}
+
39%|███▊ | 4610/11952 [01:15<06:45, 18.09it/s]
39%|███▊ | 4611/11952 [01:21<09:18, 13.15it/s]
{'loss': 0.4757, 'learning_rate': 1.4064312937453556e-05, 'epoch': 0.39}
+
39%|███▊ | 4611/11952 [01:21<09:18, 13.15it/s]
39%|███▊ | 4612/11952 [01:27<13:29, 9.07it/s]
{'loss': 0.5263, 'learning_rate': 1.406183679876848e-05, 'epoch': 0.39}
+
39%|███▊ | 4612/11952 [01:27<13:29, 9.07it/s]
39%|███▊ | 4613/11952 [01:33<18:53, 6.48it/s]
{'loss': 0.4928, 'learning_rate': 1.4059360361799004e-05, 'epoch': 0.39}
+
39%|███▊ | 4613/11952 [01:33<18:53, 6.48it/s]
39%|███▊ | 4614/11952 [01:39<26:11, 4.67it/s]
{'loss': 0.4916, 'learning_rate': 1.4056883626726989e-05, 'epoch': 0.39}
+
39%|███▊ | 4614/11952 [01:39<26:11, 4.67it/s]
39%|███▊ | 4615/11952 [01:45<36:40, 3.33it/s]
{'loss': 0.482, 'learning_rate': 1.4054406593734316e-05, 'epoch': 0.39}
+
39%|███▊ | 4615/11952 [01:45<36:40, 3.33it/s]
39%|███▊ | 4616/11952 [01:51<51:05, 2.39it/s]
{'loss': 0.4772, 'learning_rate': 1.4051929263002884e-05, 'epoch': 0.39}
+
39%|███▊ | 4616/11952 [01:51<51:05, 2.39it/s]
39%|███▊ | 4617/11952 [01:57<1:09:41, 1.75it/s]
{'loss': 0.4909, 'learning_rate': 1.404945163471462e-05, 'epoch': 0.39}
+
39%|███▊ | 4617/11952 [01:57<1:09:41, 1.75it/s]
39%|███▊ | 4618/11952 [02:03<1:37:04, 1.26it/s]
{'loss': 0.4879, 'learning_rate': 1.4046973709051467e-05, 'epoch': 0.39}
+
39%|███▊ | 4618/11952 [02:03<1:37:04, 1.26it/s]
39%|███▊ | 4619/11952 [02:09<2:11:46, 1.08s/it]
{'loss': 0.492, 'learning_rate': 1.4044495486195404e-05, 'epoch': 0.39}
+
39%|███▊ | 4619/11952 [02:09<2:11:46, 1.08s/it]
39%|███▊ | 4620/11952 [02:15<2:51:52, 1.41s/it]
{'loss': 0.4755, 'learning_rate': 1.4042016966328411e-05, 'epoch': 0.39}
+
39%|███▊ | 4620/11952 [02:15<2:51:52, 1.41s/it]
39%|███▊ | 4621/11952 [02:21<3:43:34, 1.83s/it]
{'loss': 0.526, 'learning_rate': 1.4039538149632508e-05, 'epoch': 0.39}
+
39%|███▊ | 4621/11952 [02:21<3:43:34, 1.83s/it]
39%|███▊ | 4622/11952 [02:26<4:38:32, 2.28s/it]
{'loss': 0.4765, 'learning_rate': 1.4037059036289722e-05, 'epoch': 0.39}
+
39%|███▊ | 4622/11952 [02:26<4:38:32, 2.28s/it]
39%|███▊ | 4623/11952 [02:32<5:36:56, 2.76s/it]
{'loss': 0.4763, 'learning_rate': 1.4034579626482112e-05, 'epoch': 0.39}
+
39%|███▊ | 4623/11952 [02:32<5:36:56, 2.76s/it]
39%|███▊ | 4624/11952 [02:38<6:47:49, 3.34s/it]
{'loss': 0.4879, 'learning_rate': 1.4032099920391753e-05, 'epoch': 0.39}
+
39%|███▊ | 4624/11952 [02:38<6:47:49, 3.34s/it]
39%|███▊ | 4625/11952 [02:44<7:43:26, 3.80s/it]
{'loss': 0.4795, 'learning_rate': 1.402961991820075e-05, 'epoch': 0.39}
+
39%|███▊ | 4625/11952 [02:44<7:43:26, 3.80s/it]
39%|███▊ | 4626/11952 [02:50<8:35:26, 4.22s/it]
{'loss': 0.4731, 'learning_rate': 1.4027139620091221e-05, 'epoch': 0.39}
+
39%|███▊ | 4626/11952 [02:50<8:35:26, 4.22s/it]
39%|███▊ | 4627/11952 [02:56<9:23:09, 4.61s/it]
{'loss': 0.4775, 'learning_rate': 1.4024659026245307e-05, 'epoch': 0.39}
+
39%|███▊ | 4627/11952 [02:56<9:23:09, 4.61s/it]
39%|███▊ | 4628/11952 [03:01<10:03:46, 4.95s/it]
{'loss': 0.5075, 'learning_rate': 1.4022178136845173e-05, 'epoch': 0.39}
+
39%|███▊ | 4628/11952 [03:01<10:03:46, 4.95s/it]
39%|███▊ | 4629/11952 [03:07<10:37:12, 5.22s/it]
{'loss': 0.4915, 'learning_rate': 1.4019696952073008e-05, 'epoch': 0.39}
+
39%|███▊ | 4629/11952 [03:07<10:37:12, 5.22s/it]
39%|███▊ | 4630/11952 [03:13<10:52:15, 5.34s/it]
{'loss': 0.4835, 'learning_rate': 1.4017215472111016e-05, 'epoch': 0.39}
+
39%|███▊ | 4630/11952 [03:13<10:52:15, 5.34s/it]
39%|███▊ | 4631/11952 [03:19<11:02:57, 5.43s/it]
{'loss': 0.4964, 'learning_rate': 1.401473369714143e-05, 'epoch': 0.39}
+
39%|███▊ | 4631/11952 [03:19<11:02:57, 5.43s/it]
39%|███▉ | 4632/11952 [03:25<11:26:57, 5.63s/it]
{'loss': 0.4938, 'learning_rate': 1.40122516273465e-05, 'epoch': 0.39}
+
39%|███▉ | 4632/11952 [03:25<11:26:57, 5.63s/it]
39%|███▉ | 4633/11952 [03:31<11:29:33, 5.65s/it]
{'loss': 0.4688, 'learning_rate': 1.4009769262908498e-05, 'epoch': 0.39}
+
39%|███▉ | 4633/11952 [03:31<11:29:33, 5.65s/it]
39%|███▉ | 4634/11952 [03:37<11:40:40, 5.74s/it]
{'loss': 0.4844, 'learning_rate': 1.4007286604009717e-05, 'epoch': 0.39}
+
39%|███▉ | 4634/11952 [03:37<11:40:40, 5.74s/it]
39%|███▉ | 4635/11952 [03:43<11:51:58, 5.84s/it]
{'loss': 0.5028, 'learning_rate': 1.400480365083248e-05, 'epoch': 0.39}
+
39%|███▉ | 4635/11952 [03:43<11:51:58, 5.84s/it]
39%|███▉ | 4636/11952 [03:49<11:55:08, 5.87s/it]
{'loss': 0.4694, 'learning_rate': 1.400232040355912e-05, 'epoch': 0.39}
+
39%|███▉ | 4636/11952 [03:49<11:55:08, 5.87s/it]
39%|███▉ | 4637/11952 [03:54<11:56:57, 5.88s/it]
{'loss': 0.5068, 'learning_rate': 1.3999836862371992e-05, 'epoch': 0.39}
+
39%|███▉ | 4637/11952 [03:54<11:56:57, 5.88s/it]
39%|███▉ | 4638/11952 [04:01<12:03:28, 5.93s/it]
{'loss': 0.526, 'learning_rate': 1.3997353027453484e-05, 'epoch': 0.39}
+
39%|███▉ | 4638/11952 [04:01<12:03:28, 5.93s/it]
39%|███▉ | 4639/11952 [04:06<11:54:36, 5.86s/it]
{'loss': 0.5087, 'learning_rate': 1.3994868898985996e-05, 'epoch': 0.39}
+
39%|███▉ | 4639/11952 [04:06<11:54:36, 5.86s/it]
39%|███▉ | 4640/11952 [04:12<11:57:19, 5.89s/it]
{'loss': 0.4647, 'learning_rate': 1.399238447715195e-05, 'epoch': 0.39}
+
39%|███▉ | 4640/11952 [04:12<11:57:19, 5.89s/it]
39%|███▉ | 4641/11952 [04:18<11:57:10, 5.89s/it]
{'loss': 0.5089, 'learning_rate': 1.3989899762133797e-05, 'epoch': 0.39}
+
39%|███▉ | 4641/11952 [04:18<11:57:10, 5.89s/it]
39%|███▉ | 4642/11952 [04:24<11:46:50, 5.80s/it]
{'loss': 0.477, 'learning_rate': 1.3987414754114e-05, 'epoch': 0.39}
+
39%|███▉ | 4642/11952 [04:24<11:46:50, 5.80s/it]
39%|███▉ | 4643/11952 [04:29<11:41:09, 5.76s/it]
{'loss': 0.4633, 'learning_rate': 1.3984929453275045e-05, 'epoch': 0.39}
+
39%|███▉ | 4643/11952 [04:29<11:41:09, 5.76s/it]
39%|███▉ | 4644/11952 [04:35<11:49:18, 5.82s/it]
{'loss': 0.4792, 'learning_rate': 1.3982443859799446e-05, 'epoch': 0.39}
+
39%|███▉ | 4644/11952 [04:35<11:49:18, 5.82s/it]
39%|███▉ | 4645/11952 [04:41<11:53:32, 5.86s/it]
{'loss': 0.508, 'learning_rate': 1.3979957973869738e-05, 'epoch': 0.39}
+
39%|███▉ | 4645/11952 [04:41<11:53:32, 5.86s/it]
39%|███▉ | 4646/11952 [04:47<11:55:58, 5.88s/it]
{'loss': 0.4722, 'learning_rate': 1.397747179566847e-05, 'epoch': 0.39}
+
39%|███▉ | 4646/11952 [04:47<11:55:58, 5.88s/it]
39%|███▉ | 4647/11952 [04:53<11:46:12, 5.80s/it]
{'loss': 0.4924, 'learning_rate': 1.3974985325378215e-05, 'epoch': 0.39}
+
39%|███▉ | 4647/11952 [04:53<11:46:12, 5.80s/it]
39%|███▉ | 4648/11952 [04:58<11:39:49, 5.75s/it]
{'loss': 0.4871, 'learning_rate': 1.397249856318157e-05, 'epoch': 0.39}
+
39%|███▉ | 4648/11952 [04:58<11:39:49, 5.75s/it]
39%|███▉ | 4649/11952 [05:04<11:46:06, 5.80s/it]
{'loss': 0.4978, 'learning_rate': 1.3970011509261155e-05, 'epoch': 0.39}
+
39%|███▉ | 4649/11952 [05:04<11:46:06, 5.80s/it]6 AutoResumeHook: Checking whether to suspend...
+73 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...2
+ AutoResumeHook: Checking whether to suspend...
+
39%|███▉ | 4650/11952 [05:11<12:02:58, 5.94s/it]1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4922, 'learning_rate': 1.3967524163799606e-05, 'epoch': 0.39}
+
39%|███▉ | 4650/11952 [05:11<12:02:58, 5.94s/it]
39%|███▉ | 4651/11952 [05:16<12:01:05, 5.93s/it]
{'loss': 0.4957, 'learning_rate': 1.3965036526979586e-05, 'epoch': 0.39}
+
39%|███▉ | 4651/11952 [05:16<12:01:05, 5.93s/it]
39%|███▉ | 4652/11952 [05:22<11:51:14, 5.85s/it]
{'loss': 0.4908, 'learning_rate': 1.3962548598983774e-05, 'epoch': 0.39}
+
39%|███▉ | 4652/11952 [05:22<11:51:14, 5.85s/it]
39%|███▉ | 4653/11952 [05:28<11:47:40, 5.82s/it]
{'loss': 0.489, 'learning_rate': 1.3960060379994875e-05, 'epoch': 0.39}
+
39%|███▉ | 4653/11952 [05:28<11:47:40, 5.82s/it]
39%|███▉ | 4654/11952 [05:34<11:58:35, 5.91s/it]
{'loss': 0.4736, 'learning_rate': 1.395757187019561e-05, 'epoch': 0.39}
+
39%|███▉ | 4654/11952 [05:34<11:58:35, 5.91s/it]
39%|███▉ | 4655/11952 [05:40<12:06:20, 5.97s/it]
{'loss': 0.4822, 'learning_rate': 1.3955083069768733e-05, 'epoch': 0.39}
+
39%|███▉ | 4655/11952 [05:40<12:06:20, 5.97s/it]
39%|███▉ | 4656/11952 [05:46<11:51:42, 5.85s/it]
{'loss': 0.4798, 'learning_rate': 1.3952593978897002e-05, 'epoch': 0.39}
+
39%|███▉ | 4656/11952 [05:46<11:51:42, 5.85s/it]
39%|███▉ | 4657/11952 [05:51<11:41:14, 5.77s/it]
{'loss': 0.4925, 'learning_rate': 1.3950104597763212e-05, 'epoch': 0.39}
+
39%|███▉ | 4657/11952 [05:51<11:41:14, 5.77s/it]
39%|███▉ | 4658/11952 [05:57<11:48:17, 5.83s/it]
{'loss': 0.4817, 'learning_rate': 1.3947614926550168e-05, 'epoch': 0.39}
+
39%|███▉ | 4658/11952 [05:57<11:48:17, 5.83s/it]
39%|███▉ | 4659/11952 [06:03<11:42:54, 5.78s/it]
{'loss': 0.4935, 'learning_rate': 1.3945124965440701e-05, 'epoch': 0.39}
+
39%|███▉ | 4659/11952 [06:03<11:42:54, 5.78s/it]
39%|███▉ | 4660/11952 [06:09<11:44:49, 5.80s/it]
{'loss': 0.5021, 'learning_rate': 1.3942634714617671e-05, 'epoch': 0.39}
+
39%|███▉ | 4660/11952 [06:09<11:44:49, 5.80s/it]
39%|███▉ | 4661/11952 [06:15<12:02:08, 5.94s/it]
{'loss': 0.492, 'learning_rate': 1.3940144174263943e-05, 'epoch': 0.39}
+
39%|███▉ | 4661/11952 [06:15<12:02:08, 5.94s/it]
39%|███▉ | 4662/11952 [06:21<12:17:19, 6.07s/it]
{'loss': 0.4698, 'learning_rate': 1.3937653344562417e-05, 'epoch': 0.39}
+
39%|███▉ | 4662/11952 [06:21<12:17:19, 6.07s/it]
39%|███▉ | 4663/11952 [06:27<12:11:13, 6.02s/it]
{'loss': 0.4974, 'learning_rate': 1.3935162225696006e-05, 'epoch': 0.39}
+
39%|███▉ | 4663/11952 [06:27<12:11:13, 6.02s/it]
39%|███▉ | 4664/11952 [06:33<11:58:43, 5.92s/it]
{'loss': 0.4825, 'learning_rate': 1.3932670817847647e-05, 'epoch': 0.39}
+
39%|███▉ | 4664/11952 [06:33<11:58:43, 5.92s/it]
39%|███▉ | 4665/11952 [06:39<12:00:27, 5.93s/it]
{'loss': 0.4825, 'learning_rate': 1.3930179121200303e-05, 'epoch': 0.39}
+
39%|███▉ | 4665/11952 [06:39<12:00:27, 5.93s/it]
39%|███▉ | 4666/11952 [06:44<11:45:39, 5.81s/it]
{'loss': 0.4866, 'learning_rate': 1.392768713593695e-05, 'epoch': 0.39}
+
39%|███▉ | 4666/11952 [06:44<11:45:39, 5.81s/it]
39%|███▉ | 4667/11952 [06:50<11:49:41, 5.85s/it]
{'loss': 0.498, 'learning_rate': 1.3925194862240589e-05, 'epoch': 0.39}
+
39%|███▉ | 4667/11952 [06:50<11:49:41, 5.85s/it]
39%|███▉ | 4668/11952 [06:56<11:48:37, 5.84s/it]
{'loss': 0.4945, 'learning_rate': 1.3922702300294246e-05, 'epoch': 0.39}
+
39%|███▉ | 4668/11952 [06:56<11:48:37, 5.84s/it]
39%|███▉ | 4669/11952 [07:02<11:46:43, 5.82s/it]
{'loss': 0.4962, 'learning_rate': 1.3920209450280959e-05, 'epoch': 0.39}
+
39%|███▉ | 4669/11952 [07:02<11:46:43, 5.82s/it]
39%|███▉ | 4670/11952 [07:08<11:37:35, 5.75s/it]
{'loss': 0.4794, 'learning_rate': 1.3917716312383797e-05, 'epoch': 0.39}
+
39%|███▉ | 4670/11952 [07:08<11:37:35, 5.75s/it]
39%|███▉ | 4671/11952 [07:13<11:43:22, 5.80s/it]
{'loss': 0.4718, 'learning_rate': 1.3915222886785844e-05, 'epoch': 0.39}
+
39%|███▉ | 4671/11952 [07:13<11:43:22, 5.80s/it]
39%|███▉ | 4672/11952 [07:19<11:43:00, 5.79s/it]
{'loss': 0.485, 'learning_rate': 1.3912729173670207e-05, 'epoch': 0.39}
+
39%|███▉ | 4672/11952 [07:19<11:43:00, 5.79s/it]
39%|███▉ | 4673/11952 [07:25<11:40:08, 5.77s/it]
{'loss': 0.4924, 'learning_rate': 1.3910235173220015e-05, 'epoch': 0.39}
+
39%|███▉ | 4673/11952 [07:25<11:40:08, 5.77s/it]
39%|███▉ | 4674/11952 [07:31<11:51:56, 5.87s/it]
{'loss': 0.4844, 'learning_rate': 1.3907740885618415e-05, 'epoch': 0.39}
+
39%|███▉ | 4674/11952 [07:31<11:51:56, 5.87s/it]
39%|███▉ | 4675/11952 [07:37<11:44:46, 5.81s/it]
{'loss': 0.4807, 'learning_rate': 1.3905246311048575e-05, 'epoch': 0.39}
+
39%|███▉ | 4675/11952 [07:37<11:44:46, 5.81s/it]
39%|███▉ | 4676/11952 [07:43<11:56:21, 5.91s/it]
{'loss': 0.4933, 'learning_rate': 1.3902751449693693e-05, 'epoch': 0.39}
+
39%|███▉ | 4676/11952 [07:43<11:56:21, 5.91s/it]
39%|███▉ | 4677/11952 [07:49<11:54:31, 5.89s/it]
{'loss': 0.4699, 'learning_rate': 1.3900256301736976e-05, 'epoch': 0.39}
+
39%|███▉ | 4677/11952 [07:49<11:54:31, 5.89s/it]
39%|███▉ | 4678/11952 [07:55<11:56:49, 5.91s/it]
{'loss': 0.4775, 'learning_rate': 1.3897760867361657e-05, 'epoch': 0.39}
+
39%|███▉ | 4678/11952 [07:55<11:56:49, 5.91s/it]
39%|███▉ | 4679/11952 [08:01<11:52:01, 5.87s/it]
{'loss': 0.4956, 'learning_rate': 1.3895265146750994e-05, 'epoch': 0.39}
+
39%|███▉ | 4679/11952 [08:01<11:52:01, 5.87s/it]
39%|███▉ | 4680/11952 [08:07<11:58:50, 5.93s/it]
{'loss': 0.4707, 'learning_rate': 1.3892769140088259e-05, 'epoch': 0.39}
+
39%|███▉ | 4680/11952 [08:07<11:58:50, 5.93s/it]
39%|███▉ | 4681/11952 [08:12<11:57:54, 5.92s/it]
{'loss': 0.4774, 'learning_rate': 1.3890272847556747e-05, 'epoch': 0.39}
+
39%|███▉ | 4681/11952 [08:12<11:57:54, 5.92s/it]
39%|███▉ | 4682/11952 [08:18<11:52:54, 5.88s/it]
{'loss': 0.4832, 'learning_rate': 1.3887776269339783e-05, 'epoch': 0.39}
+
39%|███▉ | 4682/11952 [08:18<11:52:54, 5.88s/it]
39%|███▉ | 4683/11952 [08:24<11:56:58, 5.92s/it]
{'loss': 0.4933, 'learning_rate': 1.38852794056207e-05, 'epoch': 0.39}
+
39%|███▉ | 4683/11952 [08:24<11:56:58, 5.92s/it]
39%|███▉ | 4684/11952 [08:30<11:47:53, 5.84s/it]
{'loss': 0.4934, 'learning_rate': 1.3882782256582852e-05, 'epoch': 0.39}
+
39%|███▉ | 4684/11952 [08:30<11:47:53, 5.84s/it]
39%|███▉ | 4685/11952 [08:36<11:38:38, 5.77s/it]
{'loss': 0.4822, 'learning_rate': 1.388028482240963e-05, 'epoch': 0.39}
+
39%|███▉ | 4685/11952 [08:36<11:38:38, 5.77s/it]
39%|███▉ | 4686/11952 [08:41<11:40:22, 5.78s/it]
{'loss': 0.4891, 'learning_rate': 1.3877787103284428e-05, 'epoch': 0.39}
+
39%|███▉ | 4686/11952 [08:41<11:40:22, 5.78s/it]
39%|███▉ | 4687/11952 [08:47<11:49:38, 5.86s/it]
{'loss': 0.4905, 'learning_rate': 1.3875289099390672e-05, 'epoch': 0.39}
+
39%|███▉ | 4687/11952 [08:47<11:49:38, 5.86s/it]
39%|███▉ | 4688/11952 [08:53<11:52:19, 5.88s/it]
{'loss': 0.5032, 'learning_rate': 1.38727908109118e-05, 'epoch': 0.39}
+
39%|███▉ | 4688/11952 [08:53<11:52:19, 5.88s/it]
39%|███▉ | 4689/11952 [08:59<11:53:13, 5.89s/it]
{'loss': 0.4791, 'learning_rate': 1.3870292238031283e-05, 'epoch': 0.39}
+
39%|███▉ | 4689/11952 [08:59<11:53:13, 5.89s/it]
39%|███▉ | 4690/11952 [09:05<11:55:20, 5.91s/it]
{'loss': 0.4809, 'learning_rate': 1.3867793380932597e-05, 'epoch': 0.39}
+
39%|███▉ | 4690/11952 [09:05<11:55:20, 5.91s/it]
39%|███▉ | 4691/11952 [09:11<11:46:22, 5.84s/it]
{'loss': 0.4697, 'learning_rate': 1.3865294239799254e-05, 'epoch': 0.39}
+
39%|███▉ | 4691/11952 [09:11<11:46:22, 5.84s/it]
39%|███▉ | 4692/11952 [09:17<11:49:09, 5.86s/it]
{'loss': 0.5101, 'learning_rate': 1.386279481481478e-05, 'epoch': 0.39}
+
39%|███▉ | 4692/11952 [09:17<11:49:09, 5.86s/it]
39%|███▉ | 4693/11952 [09:22<11:41:33, 5.80s/it]
{'loss': 0.477, 'learning_rate': 1.3860295106162722e-05, 'epoch': 0.39}
+
39%|███▉ | 4693/11952 [09:22<11:41:33, 5.80s/it]
39%|███▉ | 4694/11952 [09:28<11:49:07, 5.86s/it]
{'loss': 0.4973, 'learning_rate': 1.3857795114026648e-05, 'epoch': 0.39}
+
39%|███▉ | 4694/11952 [09:28<11:49:07, 5.86s/it]
39%|███▉ | 4695/11952 [09:34<11:46:17, 5.84s/it]
{'loss': 0.4843, 'learning_rate': 1.3855294838590143e-05, 'epoch': 0.39}
+
39%|███▉ | 4695/11952 [09:34<11:46:17, 5.84s/it]
39%|███▉ | 4696/11952 [09:40<11:43:04, 5.81s/it]
{'loss': 0.4937, 'learning_rate': 1.3852794280036823e-05, 'epoch': 0.39}
+
39%|███▉ | 4696/11952 [09:40<11:43:04, 5.81s/it]
39%|███▉ | 4697/11952 [09:46<11:33:49, 5.74s/it]
{'loss': 0.481, 'learning_rate': 1.3850293438550317e-05, 'epoch': 0.39}
+
39%|███▉ | 4697/11952 [09:46<11:33:49, 5.74s/it]
39%|███▉ | 4698/11952 [09:51<11:29:57, 5.71s/it]
{'loss': 0.4813, 'learning_rate': 1.3847792314314272e-05, 'epoch': 0.39}
+
39%|███▉ | 4698/11952 [09:51<11:29:57, 5.71s/it]
39%|███▉ | 4699/11952 [09:57<11:33:41, 5.74s/it]
{'loss': 0.4771, 'learning_rate': 1.3845290907512367e-05, 'epoch': 0.39}
+
39%|███▉ | 4699/11952 [09:57<11:33:41, 5.74s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+3 6AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...1
+ AutoResumeHook: Checking whether to suspend...
+
39%|███▉ | 4700/11952 [10:03<11:39:27, 5.79s/it]
{'loss': 0.5068, 'learning_rate': 1.3842789218328289e-05, 'epoch': 0.39}
+
39%|███▉ | 4700/11952 [10:03<11:39:27, 5.79s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
39%|███▉ | 4701/11952 [10:40<30:21:56, 15.08s/it]
{'loss': 0.4914, 'learning_rate': 1.3840287246945759e-05, 'epoch': 0.39}
+
39%|███▉ | 4701/11952 [10:40<30:21:56, 15.08s/it]
39%|███▉ | 4702/11952 [10:46<24:48:26, 12.32s/it]
{'loss': 0.4749, 'learning_rate': 1.38377849935485e-05, 'epoch': 0.39}
+
39%|███▉ | 4702/11952 [10:46<24:48:26, 12.32s/it]
39%|███▉ | 4703/11952 [10:51<20:51:01, 10.35s/it]
{'loss': 0.4946, 'learning_rate': 1.3835282458320278e-05, 'epoch': 0.39}
+
39%|███▉ | 4703/11952 [10:51<20:51:01, 10.35s/it]
39%|███▉ | 4704/11952 [10:57<18:06:36, 9.00s/it]
{'loss': 0.4967, 'learning_rate': 1.3832779641444864e-05, 'epoch': 0.39}
+
39%|███▉ | 4704/11952 [10:57<18:06:36, 9.00s/it]
39%|███▉ | 4705/11952 [11:03<16:15:48, 8.08s/it]
{'loss': 0.4846, 'learning_rate': 1.3830276543106053e-05, 'epoch': 0.39}
+
39%|███▉ | 4705/11952 [11:03<16:15:48, 8.08s/it]
39%|███▉ | 4706/11952 [11:09<14:45:20, 7.33s/it]
{'loss': 0.4776, 'learning_rate': 1.3827773163487663e-05, 'epoch': 0.39}
+
39%|███▉ | 4706/11952 [11:09<14:45:20, 7.33s/it]
39%|███▉ | 4707/11952 [11:14<13:47:54, 6.86s/it]
{'loss': 0.505, 'learning_rate': 1.3825269502773538e-05, 'epoch': 0.39}
+
39%|███▉ | 4707/11952 [11:14<13:47:54, 6.86s/it]
39%|███▉ | 4708/11952 [11:20<13:10:08, 6.54s/it]
{'loss': 0.465, 'learning_rate': 1.3822765561147529e-05, 'epoch': 0.39}
+
39%|███▉ | 4708/11952 [11:20<13:10:08, 6.54s/it]
39%|███▉ | 4709/11952 [11:26<12:54:45, 6.42s/it]
{'loss': 0.4896, 'learning_rate': 1.3820261338793515e-05, 'epoch': 0.39}
+
39%|███▉ | 4709/11952 [11:26<12:54:45, 6.42s/it]
39%|███▉ | 4710/11952 [11:33<12:54:47, 6.42s/it]
{'loss': 0.5086, 'learning_rate': 1.3817756835895399e-05, 'epoch': 0.39}
+
39%|███▉ | 4710/11952 [11:33<12:54:47, 6.42s/it]
39%|███▉ | 4711/11952 [11:39<12:31:24, 6.23s/it]
{'loss': 0.5081, 'learning_rate': 1.38152520526371e-05, 'epoch': 0.39}
+
39%|███▉ | 4711/11952 [11:39<12:31:24, 6.23s/it]
39%|███▉ | 4712/11952 [11:44<12:10:48, 6.06s/it]
{'loss': 0.4698, 'learning_rate': 1.3812746989202559e-05, 'epoch': 0.39}
+
39%|███▉ | 4712/11952 [11:44<12:10:48, 6.06s/it]
39%|███▉ | 4713/11952 [11:50<12:11:37, 6.06s/it]
{'loss': 0.497, 'learning_rate': 1.3810241645775738e-05, 'epoch': 0.39}
+
39%|███▉ | 4713/11952 [11:50<12:11:37, 6.06s/it]
39%|███▉ | 4714/11952 [11:56<12:02:50, 5.99s/it]
{'loss': 0.4849, 'learning_rate': 1.380773602254062e-05, 'epoch': 0.39}
+
39%|███▉ | 4714/11952 [11:56<12:02:50, 5.99s/it]
39%|███▉ | 4715/11952 [12:02<11:56:09, 5.94s/it]
{'loss': 0.4766, 'learning_rate': 1.3805230119681203e-05, 'epoch': 0.39}
+
39%|███▉ | 4715/11952 [12:02<11:56:09, 5.94s/it]
39%|███▉ | 4716/11952 [12:08<11:52:55, 5.91s/it]
{'loss': 0.4944, 'learning_rate': 1.3802723937381512e-05, 'epoch': 0.39}
+
39%|███▉ | 4716/11952 [12:08<11:52:55, 5.91s/it]
39%|███▉ | 4717/11952 [12:14<12:12:48, 6.08s/it]
{'loss': 0.489, 'learning_rate': 1.3800217475825597e-05, 'epoch': 0.39}
+
39%|███▉ | 4717/11952 [12:14<12:12:48, 6.08s/it]
39%|███▉ | 4718/11952 [12:20<12:06:13, 6.02s/it]
{'loss': 0.4637, 'learning_rate': 1.3797710735197516e-05, 'epoch': 0.39}
+
39%|███▉ | 4718/11952 [12:20<12:06:13, 6.02s/it]
39%|███▉ | 4719/11952 [12:26<11:59:49, 5.97s/it]
{'loss': 0.482, 'learning_rate': 1.379520371568135e-05, 'epoch': 0.39}
+
39%|███▉ | 4719/11952 [12:26<11:59:49, 5.97s/it]
39%|███▉ | 4720/11952 [12:32<11:50:06, 5.89s/it]
{'loss': 0.5144, 'learning_rate': 1.3792696417461213e-05, 'epoch': 0.39}
+
39%|███▉ | 4720/11952 [12:32<11:50:06, 5.89s/it]
39%|███▉ | 4721/11952 [12:37<11:42:16, 5.83s/it]
{'loss': 0.4927, 'learning_rate': 1.3790188840721223e-05, 'epoch': 0.39}
+
39%|███▉ | 4721/11952 [12:37<11:42:16, 5.83s/it]
40%|███▉ | 4722/11952 [12:43<11:33:37, 5.76s/it]
{'loss': 0.4736, 'learning_rate': 1.378768098564553e-05, 'epoch': 0.4}
+
40%|███▉ | 4722/11952 [12:43<11:33:37, 5.76s/it]
40%|███▉ | 4723/11952 [12:49<11:35:07, 5.77s/it]
{'loss': 0.4891, 'learning_rate': 1.3785172852418303e-05, 'epoch': 0.4}
+
40%|███▉ | 4723/11952 [12:49<11:35:07, 5.77s/it]
40%|███▉ | 4724/11952 [12:55<11:48:37, 5.88s/it]
{'loss': 0.495, 'learning_rate': 1.3782664441223724e-05, 'epoch': 0.4}
+
40%|███▉ | 4724/11952 [12:55<11:48:37, 5.88s/it]
40%|███▉ | 4725/11952 [13:01<11:42:18, 5.83s/it]
{'loss': 0.4943, 'learning_rate': 1.3780155752246e-05, 'epoch': 0.4}
+
40%|███▉ | 4725/11952 [13:01<11:42:18, 5.83s/it]
40%|███▉ | 4726/11952 [13:07<11:45:39, 5.86s/it]
{'loss': 0.4907, 'learning_rate': 1.3777646785669357e-05, 'epoch': 0.4}
+
40%|███▉ | 4726/11952 [13:07<11:45:39, 5.86s/it]
40%|███▉ | 4727/11952 [13:12<11:41:19, 5.82s/it]
{'loss': 0.4822, 'learning_rate': 1.3775137541678052e-05, 'epoch': 0.4}
+
40%|███▉ | 4727/11952 [13:12<11:41:19, 5.82s/it]
40%|███▉ | 4728/11952 [13:18<11:42:40, 5.84s/it]
{'loss': 0.4896, 'learning_rate': 1.3772628020456346e-05, 'epoch': 0.4}
+
40%|███▉ | 4728/11952 [13:18<11:42:40, 5.84s/it]
40%|███▉ | 4729/11952 [13:24<11:35:28, 5.78s/it]
{'loss': 0.4812, 'learning_rate': 1.3770118222188529e-05, 'epoch': 0.4}
+
40%|███▉ | 4729/11952 [13:24<11:35:28, 5.78s/it]
40%|███▉ | 4730/11952 [13:29<11:28:29, 5.72s/it]
{'loss': 0.4859, 'learning_rate': 1.3767608147058913e-05, 'epoch': 0.4}
+
40%|███▉ | 4730/11952 [13:29<11:28:29, 5.72s/it]
40%|███▉ | 4731/11952 [13:35<11:29:54, 5.73s/it]
{'loss': 0.4721, 'learning_rate': 1.3765097795251822e-05, 'epoch': 0.4}
+
40%|███▉ | 4731/11952 [13:35<11:29:54, 5.73s/it]
40%|███▉ | 4732/11952 [13:41<11:24:59, 5.69s/it]
{'loss': 0.4959, 'learning_rate': 1.376258716695161e-05, 'epoch': 0.4}
+
40%|███▉ | 4732/11952 [13:41<11:24:59, 5.69s/it]
40%|███▉ | 4733/11952 [13:46<11:25:30, 5.70s/it]
{'loss': 0.4818, 'learning_rate': 1.376007626234265e-05, 'epoch': 0.4}
+
40%|███▉ | 4733/11952 [13:46<11:25:30, 5.70s/it]
40%|███▉ | 4734/11952 [13:52<11:29:25, 5.73s/it]
{'loss': 0.4732, 'learning_rate': 1.3757565081609327e-05, 'epoch': 0.4}
+
40%|███▉ | 4734/11952 [13:52<11:29:25, 5.73s/it]
40%|███▉ | 4735/11952 [13:58<11:22:54, 5.68s/it]
{'loss': 0.4902, 'learning_rate': 1.3755053624936055e-05, 'epoch': 0.4}
+
40%|███▉ | 4735/11952 [13:58<11:22:54, 5.68s/it]
40%|███▉ | 4736/11952 [14:04<11:31:43, 5.75s/it]
{'loss': 0.4942, 'learning_rate': 1.375254189250726e-05, 'epoch': 0.4}
+
40%|███▉ | 4736/11952 [14:04<11:31:43, 5.75s/it]
40%|███▉ | 4737/11952 [14:10<11:42:27, 5.84s/it]
{'loss': 0.4723, 'learning_rate': 1.3750029884507394e-05, 'epoch': 0.4}
+
40%|███▉ | 4737/11952 [14:10<11:42:27, 5.84s/it]
40%|███▉ | 4738/11952 [14:15<11:35:53, 5.79s/it]
{'loss': 0.5007, 'learning_rate': 1.3747517601120934e-05, 'epoch': 0.4}
+
40%|███▉ | 4738/11952 [14:15<11:35:53, 5.79s/it]
40%|███▉ | 4739/11952 [14:21<11:30:20, 5.74s/it]
{'loss': 0.5025, 'learning_rate': 1.3745005042532369e-05, 'epoch': 0.4}
+
40%|███▉ | 4739/11952 [14:21<11:30:20, 5.74s/it]
40%|███▉ | 4740/11952 [14:27<11:24:43, 5.70s/it]
{'loss': 0.4768, 'learning_rate': 1.374249220892621e-05, 'epoch': 0.4}
+
40%|███▉ | 4740/11952 [14:27<11:24:43, 5.70s/it]
40%|███▉ | 4741/11952 [14:33<11:33:04, 5.77s/it]
{'loss': 0.494, 'learning_rate': 1.3739979100486986e-05, 'epoch': 0.4}
+
40%|███▉ | 4741/11952 [14:33<11:33:04, 5.77s/it]
40%|███▉ | 4742/11952 [14:38<11:33:38, 5.77s/it]
{'loss': 0.5006, 'learning_rate': 1.3737465717399259e-05, 'epoch': 0.4}
+
40%|███▉ | 4742/11952 [14:38<11:33:38, 5.77s/it]
40%|███▉ | 4743/11952 [14:45<11:48:53, 5.90s/it]
{'loss': 0.4787, 'learning_rate': 1.3734952059847589e-05, 'epoch': 0.4}
+
40%|███▉ | 4743/11952 [14:45<11:48:53, 5.90s/it]
40%|███▉ | 4744/11952 [14:50<11:39:22, 5.82s/it]
{'loss': 0.486, 'learning_rate': 1.3732438128016578e-05, 'epoch': 0.4}
+
40%|███▉ | 4744/11952 [14:50<11:39:22, 5.82s/it]
40%|███▉ | 4745/11952 [14:56<11:35:12, 5.79s/it]
{'loss': 0.5041, 'learning_rate': 1.3729923922090836e-05, 'epoch': 0.4}
+
40%|███▉ | 4745/11952 [14:56<11:35:12, 5.79s/it]
40%|███▉ | 4746/11952 [15:02<11:40:22, 5.83s/it]
{'loss': 0.4867, 'learning_rate': 1.3727409442254994e-05, 'epoch': 0.4}
+
40%|███▉ | 4746/11952 [15:02<11:40:22, 5.83s/it]
40%|███▉ | 4747/11952 [15:08<11:38:19, 5.82s/it]
{'loss': 0.5076, 'learning_rate': 1.3724894688693704e-05, 'epoch': 0.4}
+
40%|███▉ | 4747/11952 [15:08<11:38:19, 5.82s/it]
40%|███▉ | 4748/11952 [15:13<11:29:45, 5.74s/it]
{'loss': 0.5011, 'learning_rate': 1.3722379661591643e-05, 'epoch': 0.4}
+
40%|███▉ | 4748/11952 [15:13<11:29:45, 5.74s/it]
40%|███▉ | 4749/11952 [15:19<11:34:14, 5.78s/it]
{'loss': 0.4931, 'learning_rate': 1.3719864361133502e-05, 'epoch': 0.4}
+
40%|███▉ | 4749/11952 [15:19<11:34:14, 5.78s/it]4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
40%|███▉ | 4750/11952 [15:25<11:42:03, 5.85s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4803, 'learning_rate': 1.3717348787503993e-05, 'epoch': 0.4}
+
40%|███▉ | 4750/11952 [15:25<11:42:03, 5.85s/it]
40%|███▉ | 4751/11952 [15:31<11:44:44, 5.87s/it]
{'loss': 0.4869, 'learning_rate': 1.3714832940887854e-05, 'epoch': 0.4}
+
40%|███▉ | 4751/11952 [15:31<11:44:44, 5.87s/it]
40%|███▉ | 4752/11952 [15:37<11:53:05, 5.94s/it]
{'loss': 0.4963, 'learning_rate': 1.3712316821469831e-05, 'epoch': 0.4}
+
40%|███▉ | 4752/11952 [15:37<11:53:05, 5.94s/it]
40%|███▉ | 4753/11952 [15:43<11:53:49, 5.95s/it]
{'loss': 0.4769, 'learning_rate': 1.3709800429434702e-05, 'epoch': 0.4}
+
40%|███▉ | 4753/11952 [15:43<11:53:49, 5.95s/it]
40%|███▉ | 4754/11952 [15:49<11:41:42, 5.85s/it]
{'loss': 0.477, 'learning_rate': 1.370728376496726e-05, 'epoch': 0.4}
+
40%|███▉ | 4754/11952 [15:49<11:41:42, 5.85s/it]
40%|███▉ | 4755/11952 [15:54<11:36:08, 5.80s/it]
{'loss': 0.5086, 'learning_rate': 1.3704766828252321e-05, 'epoch': 0.4}
+
40%|███▉ | 4755/11952 [15:54<11:36:08, 5.80s/it]
40%|███▉ | 4756/11952 [16:01<11:46:59, 5.89s/it]
{'loss': 0.4896, 'learning_rate': 1.3702249619474712e-05, 'epoch': 0.4}
+
40%|███▉ | 4756/11952 [16:01<11:46:59, 5.89s/it]
40%|███▉ | 4757/11952 [16:06<11:33:02, 5.78s/it]
{'loss': 0.4693, 'learning_rate': 1.369973213881929e-05, 'epoch': 0.4}
+
40%|███▉ | 4757/11952 [16:06<11:33:02, 5.78s/it]
40%|███▉ | 4758/11952 [16:12<11:28:56, 5.75s/it]
{'loss': 0.4847, 'learning_rate': 1.3697214386470932e-05, 'epoch': 0.4}
+
40%|███▉ | 4758/11952 [16:12<11:28:56, 5.75s/it]
40%|███▉ | 4759/11952 [16:18<11:41:55, 5.86s/it]
{'loss': 0.4807, 'learning_rate': 1.3694696362614524e-05, 'epoch': 0.4}
+
40%|███▉ | 4759/11952 [16:18<11:41:55, 5.86s/it]
40%|███▉ | 4760/11952 [16:24<11:48:53, 5.91s/it]
{'loss': 0.4717, 'learning_rate': 1.3692178067434982e-05, 'epoch': 0.4}
+
40%|███▉ | 4760/11952 [16:24<11:48:53, 5.91s/it]
40%|███▉ | 4761/11952 [16:30<11:44:13, 5.88s/it]
{'loss': 0.4815, 'learning_rate': 1.3689659501117243e-05, 'epoch': 0.4}
+
40%|███▉ | 4761/11952 [16:30<11:44:13, 5.88s/it]
40%|███▉ | 4762/11952 [16:35<11:42:34, 5.86s/it]
{'loss': 0.4829, 'learning_rate': 1.3687140663846252e-05, 'epoch': 0.4}
+
40%|███▉ | 4762/11952 [16:35<11:42:34, 5.86s/it]
40%|███▉ | 4763/11952 [16:41<11:37:14, 5.82s/it]
{'loss': 0.4869, 'learning_rate': 1.3684621555806988e-05, 'epoch': 0.4}
+
40%|███▉ | 4763/11952 [16:41<11:37:14, 5.82s/it]
40%|███▉ | 4764/11952 [16:47<11:39:43, 5.84s/it]
{'loss': 0.4915, 'learning_rate': 1.3682102177184444e-05, 'epoch': 0.4}
+
40%|███▉ | 4764/11952 [16:47<11:39:43, 5.84s/it]
40%|███▉ | 4765/11952 [16:53<11:47:21, 5.91s/it]
{'loss': 0.4821, 'learning_rate': 1.3679582528163633e-05, 'epoch': 0.4}
+
40%|███▉ | 4765/11952 [16:53<11:47:21, 5.91s/it]
40%|███▉ | 4766/11952 [16:59<11:49:39, 5.93s/it]
{'loss': 0.4984, 'learning_rate': 1.3677062608929583e-05, 'epoch': 0.4}
+
40%|███▉ | 4766/11952 [16:59<11:49:39, 5.93s/it]
40%|███▉ | 4767/11952 [17:05<11:38:38, 5.83s/it]
{'loss': 0.4911, 'learning_rate': 1.3674542419667347e-05, 'epoch': 0.4}
+
40%|███▉ | 4767/11952 [17:05<11:38:38, 5.83s/it]
40%|███▉ | 4768/11952 [17:10<11:36:33, 5.82s/it]
{'loss': 0.4761, 'learning_rate': 1.3672021960562001e-05, 'epoch': 0.4}
+
40%|███▉ | 4768/11952 [17:10<11:36:33, 5.82s/it]
40%|███▉ | 4769/11952 [17:17<11:51:49, 5.95s/it]
{'loss': 0.4801, 'learning_rate': 1.3669501231798638e-05, 'epoch': 0.4}
+
40%|███▉ | 4769/11952 [17:17<11:51:49, 5.95s/it]
40%|███▉ | 4770/11952 [17:23<11:55:28, 5.98s/it]
{'loss': 0.5164, 'learning_rate': 1.3666980233562364e-05, 'epoch': 0.4}
+
40%|███▉ | 4770/11952 [17:23<11:55:28, 5.98s/it]
40%|███▉ | 4771/11952 [17:29<12:02:32, 6.04s/it]
{'loss': 0.4852, 'learning_rate': 1.3664458966038314e-05, 'epoch': 0.4}
+
40%|███▉ | 4771/11952 [17:29<12:02:32, 6.04s/it]
40%|███▉ | 4772/11952 [17:35<12:09:50, 6.10s/it]
{'loss': 0.4944, 'learning_rate': 1.366193742941164e-05, 'epoch': 0.4}
+
40%|███▉ | 4772/11952 [17:35<12:09:50, 6.10s/it]
40%|███▉ | 4773/11952 [17:41<12:11:00, 6.11s/it]
{'loss': 0.4886, 'learning_rate': 1.365941562386751e-05, 'epoch': 0.4}
+
40%|███▉ | 4773/11952 [17:41<12:11:00, 6.11s/it]
40%|███▉ | 4774/11952 [17:47<11:59:46, 6.02s/it]
{'loss': 0.4837, 'learning_rate': 1.3656893549591121e-05, 'epoch': 0.4}
+
40%|███▉ | 4774/11952 [17:47<11:59:46, 6.02s/it]
40%|███▉ | 4775/11952 [17:53<12:01:56, 6.04s/it]
{'loss': 0.4903, 'learning_rate': 1.3654371206767678e-05, 'epoch': 0.4}
+
40%|███▉ | 4775/11952 [17:53<12:01:56, 6.04s/it]
40%|███▉ | 4776/11952 [17:59<11:44:39, 5.89s/it]
{'loss': 0.4611, 'learning_rate': 1.3651848595582416e-05, 'epoch': 0.4}
+
40%|███▉ | 4776/11952 [17:59<11:44:39, 5.89s/it]
40%|███▉ | 4777/11952 [18:05<11:39:59, 5.85s/it]
{'loss': 0.4914, 'learning_rate': 1.3649325716220579e-05, 'epoch': 0.4}
+
40%|███▉ | 4777/11952 [18:05<11:39:59, 5.85s/it]
40%|███▉ | 4778/11952 [18:11<11:44:42, 5.89s/it]
{'loss': 0.4672, 'learning_rate': 1.364680256886744e-05, 'epoch': 0.4}
+
40%|███▉ | 4778/11952 [18:11<11:44:42, 5.89s/it]
40%|███▉ | 4779/11952 [18:17<11:47:31, 5.92s/it]
{'loss': 0.4768, 'learning_rate': 1.364427915370829e-05, 'epoch': 0.4}
+
40%|███▉ | 4779/11952 [18:17<11:47:31, 5.92s/it]
40%|███▉ | 4780/11952 [18:22<11:48:26, 5.93s/it]
{'loss': 0.4871, 'learning_rate': 1.3641755470928435e-05, 'epoch': 0.4}
+
40%|███▉ | 4780/11952 [18:22<11:48:26, 5.93s/it]
40%|████ | 4781/11952 [18:28<11:42:58, 5.88s/it]
{'loss': 0.4953, 'learning_rate': 1.3639231520713207e-05, 'epoch': 0.4}
+
40%|████ | 4781/11952 [18:28<11:42:58, 5.88s/it]
40%|████ | 4782/11952 [18:34<11:54:44, 5.98s/it]
{'loss': 0.4642, 'learning_rate': 1.3636707303247953e-05, 'epoch': 0.4}
+
40%|████ | 4782/11952 [18:34<11:54:44, 5.98s/it]
40%|████ | 4783/11952 [18:40<11:55:34, 5.99s/it]
{'loss': 0.5042, 'learning_rate': 1.363418281871804e-05, 'epoch': 0.4}
+
40%|████ | 4783/11952 [18:40<11:55:34, 5.99s/it]
40%|████ | 4784/11952 [18:47<12:06:11, 6.08s/it]
{'loss': 0.485, 'learning_rate': 1.3631658067308857e-05, 'epoch': 0.4}
+
40%|████ | 4784/11952 [18:47<12:06:11, 6.08s/it]
40%|████ | 4785/11952 [18:53<11:58:11, 6.01s/it]
{'loss': 0.4988, 'learning_rate': 1.362913304920581e-05, 'epoch': 0.4}
+
40%|████ | 4785/11952 [18:53<11:58:11, 6.01s/it]
40%|████ | 4786/11952 [18:58<11:45:36, 5.91s/it]
{'loss': 0.4921, 'learning_rate': 1.3626607764594329e-05, 'epoch': 0.4}
+
40%|████ | 4786/11952 [18:58<11:45:36, 5.91s/it]
40%|████ | 4787/11952 [19:04<11:55:12, 5.99s/it]
{'loss': 0.5012, 'learning_rate': 1.3624082213659854e-05, 'epoch': 0.4}
+
40%|████ | 4787/11952 [19:04<11:55:12, 5.99s/it]
40%|████ | 4788/11952 [19:10<11:49:01, 5.94s/it]
{'loss': 0.4926, 'learning_rate': 1.3621556396587856e-05, 'epoch': 0.4}
+
40%|████ | 4788/11952 [19:10<11:49:01, 5.94s/it]
40%|████ | 4789/11952 [19:16<11:45:36, 5.91s/it]
{'loss': 0.4879, 'learning_rate': 1.3619030313563821e-05, 'epoch': 0.4}
+
40%|████ | 4789/11952 [19:16<11:45:36, 5.91s/it]
40%|████ | 4790/11952 [19:22<11:58:33, 6.02s/it]
{'loss': 0.4911, 'learning_rate': 1.3616503964773252e-05, 'epoch': 0.4}
+
40%|████ | 4790/11952 [19:22<11:58:33, 6.02s/it]
40%|████ | 4791/11952 [19:28<11:44:47, 5.91s/it]
{'loss': 0.4665, 'learning_rate': 1.3613977350401675e-05, 'epoch': 0.4}
+
40%|████ | 4791/11952 [19:28<11:44:47, 5.91s/it]
40%|████ | 4792/11952 [19:34<11:40:17, 5.87s/it]
{'loss': 0.4938, 'learning_rate': 1.3611450470634631e-05, 'epoch': 0.4}
+
40%|████ | 4792/11952 [19:34<11:40:17, 5.87s/it]
40%|████ | 4793/11952 [19:40<11:55:59, 6.00s/it]
{'loss': 0.4847, 'learning_rate': 1.3608923325657686e-05, 'epoch': 0.4}
+
40%|████ | 4793/11952 [19:40<11:55:59, 6.00s/it]
40%|████ | 4794/11952 [19:46<11:45:06, 5.91s/it]
{'loss': 0.5109, 'learning_rate': 1.3606395915656423e-05, 'epoch': 0.4}
+
40%|████ | 4794/11952 [19:46<11:45:06, 5.91s/it]
40%|████ | 4795/11952 [19:52<11:48:39, 5.94s/it]
{'loss': 0.4765, 'learning_rate': 1.3603868240816445e-05, 'epoch': 0.4}
+
40%|████ | 4795/11952 [19:52<11:48:39, 5.94s/it]
40%|████ | 4796/11952 [19:58<11:50:48, 5.96s/it]
{'loss': 0.4859, 'learning_rate': 1.3601340301323371e-05, 'epoch': 0.4}
+
40%|████ | 4796/11952 [19:58<11:50:48, 5.96s/it]
40%|████ | 4797/11952 [20:04<11:54:31, 5.99s/it]
{'loss': 0.505, 'learning_rate': 1.3598812097362846e-05, 'epoch': 0.4}
+
40%|████ | 4797/11952 [20:04<11:54:31, 5.99s/it]
40%|████ | 4798/11952 [20:10<11:57:52, 6.02s/it]
{'loss': 0.5041, 'learning_rate': 1.3596283629120527e-05, 'epoch': 0.4}
+
40%|████ | 4798/11952 [20:10<11:57:52, 6.02s/it]
40%|████ | 4799/11952 [20:16<11:48:35, 5.94s/it]
{'loss': 0.4924, 'learning_rate': 1.3593754896782099e-05, 'epoch': 0.4}
+
40%|████ | 4799/11952 [20:16<11:48:35, 5.94s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+067 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+5 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
40%|████ | 4800/11952 [20:22<11:53:39, 5.99s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.467, 'learning_rate': 1.359122590053326e-05, 'epoch': 0.4}
+
40%|████ | 4800/11952 [20:22<11:53:39, 5.99s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
40%|████ | 4801/11952 [20:54<27:33:32, 13.87s/it]
{'loss': 0.5029, 'learning_rate': 1.3588696640559725e-05, 'epoch': 0.4}
+
40%|████ | 4801/11952 [20:54<27:33:32, 13.87s/it]
40%|████ | 4802/11952 [21:00<22:50:01, 11.50s/it]
{'loss': 0.4932, 'learning_rate': 1.3586167117047238e-05, 'epoch': 0.4}
+
40%|████ | 4802/11952 [21:00<22:50:01, 11.50s/it]
40%|████ | 4803/11952 [21:06<19:16:48, 9.71s/it]
{'loss': 0.4759, 'learning_rate': 1.358363733018155e-05, 'epoch': 0.4}
+
40%|████ | 4803/11952 [21:06<19:16:48, 9.71s/it]
40%|████ | 4804/11952 [21:12<17:10:32, 8.65s/it]
{'loss': 0.5209, 'learning_rate': 1.3581107280148443e-05, 'epoch': 0.4}
+
40%|████ | 4804/11952 [21:12<17:10:32, 8.65s/it]
40%|████ | 4805/11952 [21:18<15:34:41, 7.85s/it]
{'loss': 0.4676, 'learning_rate': 1.3578576967133712e-05, 'epoch': 0.4}
+
40%|████ | 4805/11952 [21:18<15:34:41, 7.85s/it]
40%|████ | 4806/11952 [21:23<14:19:19, 7.22s/it]
{'loss': 0.4666, 'learning_rate': 1.3576046391323176e-05, 'epoch': 0.4}
+
40%|████ | 4806/11952 [21:23<14:19:19, 7.22s/it]
40%|████ | 4807/11952 [21:29<13:29:51, 6.80s/it]
{'loss': 0.4912, 'learning_rate': 1.3573515552902663e-05, 'epoch': 0.4}
+
40%|████ | 4807/11952 [21:29<13:29:51, 6.80s/it]
40%|████ | 4808/11952 [21:35<12:46:54, 6.44s/it]
{'loss': 0.4882, 'learning_rate': 1.3570984452058035e-05, 'epoch': 0.4}
+
40%|████ | 4808/11952 [21:35<12:46:54, 6.44s/it]
40%|████ | 4809/11952 [21:41<12:26:46, 6.27s/it]
{'loss': 0.475, 'learning_rate': 1.356845308897516e-05, 'epoch': 0.4}
+
40%|████ | 4809/11952 [21:41<12:26:46, 6.27s/it]
40%|████ | 4810/11952 [21:47<12:22:38, 6.24s/it]
{'loss': 0.4938, 'learning_rate': 1.3565921463839934e-05, 'epoch': 0.4}
+
40%|████ | 4810/11952 [21:47<12:22:38, 6.24s/it]
40%|████ | 4811/11952 [21:53<12:12:18, 6.15s/it]
{'loss': 0.4858, 'learning_rate': 1.3563389576838264e-05, 'epoch': 0.4}
+
40%|████ | 4811/11952 [21:53<12:12:18, 6.15s/it]
40%|████ | 4812/11952 [21:59<12:05:55, 6.10s/it]
{'loss': 0.4817, 'learning_rate': 1.3560857428156086e-05, 'epoch': 0.4}
+
40%|████ | 4812/11952 [21:59<12:05:55, 6.10s/it]
40%|████ | 4813/11952 [22:05<12:10:35, 6.14s/it]
{'loss': 0.5182, 'learning_rate': 1.355832501797935e-05, 'epoch': 0.4}
+
40%|████ | 4813/11952 [22:05<12:10:35, 6.14s/it]
40%|████ | 4814/11952 [22:11<11:50:24, 5.97s/it]
{'loss': 0.5071, 'learning_rate': 1.3555792346494023e-05, 'epoch': 0.4}
+
40%|████ | 4814/11952 [22:11<11:50:24, 5.97s/it]
40%|████ | 4815/11952 [22:17<11:49:38, 5.97s/it]
{'loss': 0.486, 'learning_rate': 1.35532594138861e-05, 'epoch': 0.4}
+
40%|████ | 4815/11952 [22:17<11:49:38, 5.97s/it]
40%|████ | 4816/11952 [22:22<11:43:34, 5.92s/it]
{'loss': 0.4677, 'learning_rate': 1.355072622034158e-05, 'epoch': 0.4}
+
40%|████ | 4816/11952 [22:22<11:43:34, 5.92s/it]
40%|████ | 4817/11952 [22:28<11:34:30, 5.84s/it]
{'loss': 0.4871, 'learning_rate': 1.3548192766046499e-05, 'epoch': 0.4}
+
40%|████ | 4817/11952 [22:28<11:34:30, 5.84s/it]
40%|████ | 4818/11952 [22:34<11:35:56, 5.85s/it]
{'loss': 0.505, 'learning_rate': 1.3545659051186897e-05, 'epoch': 0.4}
+
40%|████ | 4818/11952 [22:34<11:35:56, 5.85s/it]
40%|████ | 4819/11952 [22:40<11:46:39, 5.94s/it]
{'loss': 0.4679, 'learning_rate': 1.3543125075948842e-05, 'epoch': 0.4}
+
40%|████ | 4819/11952 [22:40<11:46:39, 5.94s/it]
40%|████ | 4820/11952 [22:47<12:01:35, 6.07s/it]
{'loss': 0.518, 'learning_rate': 1.354059084051842e-05, 'epoch': 0.4}
+
40%|████ | 4820/11952 [22:47<12:01:35, 6.07s/it]
40%|████ | 4821/11952 [22:53<11:59:14, 6.05s/it]
{'loss': 0.4902, 'learning_rate': 1.3538056345081729e-05, 'epoch': 0.4}
+
40%|████ | 4821/11952 [22:53<11:59:14, 6.05s/it]
40%|████ | 4822/11952 [22:58<11:44:46, 5.93s/it]
{'loss': 0.4813, 'learning_rate': 1.35355215898249e-05, 'epoch': 0.4}
+
40%|████ | 4822/11952 [22:58<11:44:46, 5.93s/it]
40%|████ | 4823/11952 [23:04<11:42:18, 5.91s/it]
{'loss': 0.4975, 'learning_rate': 1.3532986574934071e-05, 'epoch': 0.4}
+
40%|████ | 4823/11952 [23:04<11:42:18, 5.91s/it]
40%|████ | 4824/11952 [23:10<11:42:00, 5.91s/it]
{'loss': 0.4795, 'learning_rate': 1.35304513005954e-05, 'epoch': 0.4}
+
40%|████ | 4824/11952 [23:10<11:42:00, 5.91s/it]
40%|████ | 4825/11952 [23:16<11:29:19, 5.80s/it]
{'loss': 0.4782, 'learning_rate': 1.352791576699507e-05, 'epoch': 0.4}
+
40%|████ | 4825/11952 [23:16<11:29:19, 5.80s/it]
40%|████ | 4826/11952 [23:21<11:30:33, 5.81s/it]
{'loss': 0.491, 'learning_rate': 1.3525379974319282e-05, 'epoch': 0.4}
+
40%|████ | 4826/11952 [23:21<11:30:33, 5.81s/it]
40%|████ | 4827/11952 [23:27<11:32:34, 5.83s/it]
{'loss': 0.4788, 'learning_rate': 1.352284392275425e-05, 'epoch': 0.4}
+
40%|████ | 4827/11952 [23:27<11:32:34, 5.83s/it]
40%|████ | 4828/11952 [23:33<11:40:18, 5.90s/it]
{'loss': 0.4711, 'learning_rate': 1.3520307612486211e-05, 'epoch': 0.4}
+
40%|████ | 4828/11952 [23:33<11:40:18, 5.90s/it]
40%|████ | 4829/11952 [23:39<11:34:36, 5.85s/it]
{'loss': 0.4901, 'learning_rate': 1.3517771043701427e-05, 'epoch': 0.4}
+
40%|████ | 4829/11952 [23:39<11:34:36, 5.85s/it]
40%|████ | 4830/11952 [23:45<11:41:08, 5.91s/it]
{'loss': 0.4877, 'learning_rate': 1.3515234216586169e-05, 'epoch': 0.4}
+
40%|████ | 4830/11952 [23:45<11:41:08, 5.91s/it]
40%|████ | 4831/11952 [23:51<11:47:29, 5.96s/it]
{'loss': 0.4863, 'learning_rate': 1.3512697131326726e-05, 'epoch': 0.4}
+
40%|████ | 4831/11952 [23:51<11:47:29, 5.96s/it]
40%|████ | 4832/11952 [23:57<11:36:10, 5.87s/it]
{'loss': 0.4971, 'learning_rate': 1.351015978810942e-05, 'epoch': 0.4}
+
40%|████ | 4832/11952 [23:57<11:36:10, 5.87s/it]
40%|████ | 4833/11952 [24:03<11:31:58, 5.83s/it]
{'loss': 0.4835, 'learning_rate': 1.3507622187120582e-05, 'epoch': 0.4}
+
40%|████ | 4833/11952 [24:03<11:31:58, 5.83s/it]
40%|████ | 4834/11952 [24:08<11:28:37, 5.80s/it]
{'loss': 0.4859, 'learning_rate': 1.3505084328546554e-05, 'epoch': 0.4}
+
40%|████ | 4834/11952 [24:08<11:28:37, 5.80s/it]
40%|████ | 4835/11952 [24:14<11:31:19, 5.83s/it]
{'loss': 0.4858, 'learning_rate': 1.3502546212573715e-05, 'epoch': 0.4}
+
40%|████ | 4835/11952 [24:14<11:31:19, 5.83s/it]
40%|████ | 4836/11952 [24:20<11:25:21, 5.78s/it]
{'loss': 0.4833, 'learning_rate': 1.350000783938845e-05, 'epoch': 0.4}
+
40%|████ | 4836/11952 [24:20<11:25:21, 5.78s/it]
40%|████ | 4837/11952 [24:26<11:28:48, 5.81s/it]
{'loss': 0.4879, 'learning_rate': 1.3497469209177166e-05, 'epoch': 0.4}
+
40%|████ | 4837/11952 [24:26<11:28:48, 5.81s/it]
40%|████ | 4838/11952 [24:31<11:25:55, 5.79s/it]
{'loss': 0.4848, 'learning_rate': 1.349493032212629e-05, 'epoch': 0.4}
+
40%|████ | 4838/11952 [24:31<11:25:55, 5.79s/it]
40%|████ | 4839/11952 [24:37<11:19:03, 5.73s/it]
{'loss': 0.4863, 'learning_rate': 1.3492391178422271e-05, 'epoch': 0.4}
+
40%|████ | 4839/11952 [24:37<11:19:03, 5.73s/it]
40%|████ | 4840/11952 [24:43<11:15:18, 5.70s/it]
{'loss': 0.48, 'learning_rate': 1.3489851778251563e-05, 'epoch': 0.4}
+
40%|████ | 4840/11952 [24:43<11:15:18, 5.70s/it]
41%|████ | 4841/11952 [24:49<11:20:32, 5.74s/it]
{'loss': 0.4777, 'learning_rate': 1.3487312121800661e-05, 'epoch': 0.41}
+
41%|████ | 4841/11952 [24:49<11:20:32, 5.74s/it]
41%|████ | 4842/11952 [24:55<11:32:05, 5.84s/it]
{'loss': 0.4783, 'learning_rate': 1.3484772209256061e-05, 'epoch': 0.41}
+
41%|████ | 4842/11952 [24:55<11:32:05, 5.84s/it]
41%|████ | 4843/11952 [25:00<11:23:53, 5.77s/it]
{'loss': 0.5042, 'learning_rate': 1.3482232040804286e-05, 'epoch': 0.41}
+
41%|████ | 4843/11952 [25:00<11:23:53, 5.77s/it]
41%|████ | 4844/11952 [25:06<11:25:05, 5.78s/it]
{'loss': 0.4642, 'learning_rate': 1.3479691616631869e-05, 'epoch': 0.41}
+
41%|████ | 4844/11952 [25:06<11:25:05, 5.78s/it]
41%|████ | 4845/11952 [25:12<11:36:21, 5.88s/it]
{'loss': 0.4839, 'learning_rate': 1.3477150936925374e-05, 'epoch': 0.41}
+
41%|████ | 4845/11952 [25:12<11:36:21, 5.88s/it]
41%|████ | 4846/11952 [25:18<11:25:12, 5.79s/it]
{'loss': 0.4922, 'learning_rate': 1.3474610001871379e-05, 'epoch': 0.41}
+
41%|████ | 4846/11952 [25:18<11:25:12, 5.79s/it]
41%|████ | 4847/11952 [25:24<11:27:40, 5.81s/it]
{'loss': 0.4956, 'learning_rate': 1.3472068811656477e-05, 'epoch': 0.41}
+
41%|████ | 4847/11952 [25:24<11:27:40, 5.81s/it]
41%|████ | 4848/11952 [25:29<11:23:22, 5.77s/it]
{'loss': 0.479, 'learning_rate': 1.3469527366467281e-05, 'epoch': 0.41}
+
41%|████ | 4848/11952 [25:29<11:23:22, 5.77s/it]
41%|████ | 4849/11952 [25:35<11:30:09, 5.83s/it]
{'loss': 0.502, 'learning_rate': 1.3466985666490428e-05, 'epoch': 0.41}
+
41%|████ | 4849/11952 [25:35<11:30:09, 5.83s/it]7 AutoResumeHook: Checking whether to suspend...4
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
41%|████ | 4850/11952 [25:41<11:33:04, 5.86s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4734, 'learning_rate': 1.3464443711912566e-05, 'epoch': 0.41}
+
41%|████ | 4850/11952 [25:41<11:33:04, 5.86s/it]
41%|████ | 4851/11952 [25:47<11:32:09, 5.85s/it]
{'loss': 0.4976, 'learning_rate': 1.3461901502920371e-05, 'epoch': 0.41}
+
41%|████ | 4851/11952 [25:47<11:32:09, 5.85s/it]
41%|████ | 4852/11952 [25:53<11:29:30, 5.83s/it]
{'loss': 0.4828, 'learning_rate': 1.3459359039700525e-05, 'epoch': 0.41}
+
41%|████ | 4852/11952 [25:53<11:29:30, 5.83s/it]
41%|████ | 4853/11952 [25:59<11:39:59, 5.92s/it]
{'loss': 0.488, 'learning_rate': 1.3456816322439742e-05, 'epoch': 0.41}
+
41%|████ | 4853/11952 [25:59<11:39:59, 5.92s/it]
41%|████ | 4854/11952 [26:05<11:33:53, 5.87s/it]
{'loss': 0.4822, 'learning_rate': 1.3454273351324747e-05, 'epoch': 0.41}
+
41%|████ | 4854/11952 [26:05<11:33:53, 5.87s/it]
41%|████ | 4855/11952 [26:11<11:39:05, 5.91s/it]
{'loss': 0.4855, 'learning_rate': 1.345173012654228e-05, 'epoch': 0.41}
+
41%|████ | 4855/11952 [26:11<11:39:05, 5.91s/it]
41%|████ | 4856/11952 [26:16<11:29:54, 5.83s/it]
{'loss': 0.4978, 'learning_rate': 1.3449186648279114e-05, 'epoch': 0.41}
+
41%|████ | 4856/11952 [26:16<11:29:54, 5.83s/it]
41%|████ | 4857/11952 [26:22<11:35:52, 5.88s/it]
{'loss': 0.4827, 'learning_rate': 1.3446642916722027e-05, 'epoch': 0.41}
+
41%|████ | 4857/11952 [26:22<11:35:52, 5.88s/it]
41%|████ | 4858/11952 [26:28<11:46:03, 5.97s/it]
{'loss': 0.5126, 'learning_rate': 1.3444098932057818e-05, 'epoch': 0.41}
+
41%|████ | 4858/11952 [26:28<11:46:03, 5.97s/it]
41%|████ | 4859/11952 [26:34<11:39:55, 5.92s/it]
{'loss': 0.4707, 'learning_rate': 1.3441554694473307e-05, 'epoch': 0.41}
+
41%|████ | 4859/11952 [26:34<11:39:55, 5.92s/it]
41%|████ | 4860/11952 [26:40<11:28:02, 5.82s/it]
{'loss': 0.5114, 'learning_rate': 1.3439010204155334e-05, 'epoch': 0.41}
+
41%|████ | 4860/11952 [26:40<11:28:02, 5.82s/it]
41%|████ | 4861/11952 [26:46<11:28:39, 5.83s/it]
{'loss': 0.5015, 'learning_rate': 1.3436465461290757e-05, 'epoch': 0.41}
+
41%|████ | 4861/11952 [26:46<11:28:39, 5.83s/it]
41%|████ | 4862/11952 [26:52<11:43:35, 5.95s/it]
{'loss': 0.4831, 'learning_rate': 1.343392046606645e-05, 'epoch': 0.41}
+
41%|████ | 4862/11952 [26:52<11:43:35, 5.95s/it]
41%|████ | 4863/11952 [26:58<11:39:05, 5.92s/it]
{'loss': 0.4898, 'learning_rate': 1.3431375218669307e-05, 'epoch': 0.41}
+
41%|████ | 4863/11952 [26:58<11:39:05, 5.92s/it]
41%|████ | 4864/11952 [27:04<11:44:27, 5.96s/it]
{'loss': 0.4893, 'learning_rate': 1.342882971928624e-05, 'epoch': 0.41}
+
41%|████ | 4864/11952 [27:04<11:44:27, 5.96s/it]
41%|████ | 4865/11952 [27:10<11:43:29, 5.96s/it]
{'loss': 0.4799, 'learning_rate': 1.3426283968104178e-05, 'epoch': 0.41}
+
41%|████ | 4865/11952 [27:10<11:43:29, 5.96s/it]
41%|████ | 4866/11952 [27:15<11:35:33, 5.89s/it]
{'loss': 0.4845, 'learning_rate': 1.3423737965310073e-05, 'epoch': 0.41}
+
41%|████ | 4866/11952 [27:15<11:35:33, 5.89s/it]
41%|████ | 4867/11952 [27:21<11:39:17, 5.92s/it]
{'loss': 0.4986, 'learning_rate': 1.3421191711090895e-05, 'epoch': 0.41}
+
41%|████ | 4867/11952 [27:21<11:39:17, 5.92s/it]
41%|████ | 4868/11952 [27:27<11:34:15, 5.88s/it]
{'loss': 0.4814, 'learning_rate': 1.3418645205633625e-05, 'epoch': 0.41}
+
41%|████ | 4868/11952 [27:27<11:34:15, 5.88s/it]
41%|████ | 4869/11952 [27:33<11:33:48, 5.88s/it]
{'loss': 0.4772, 'learning_rate': 1.341609844912527e-05, 'epoch': 0.41}
+
41%|████ | 4869/11952 [27:33<11:33:48, 5.88s/it]
41%|████ | 4870/11952 [27:39<11:29:32, 5.84s/it]
{'loss': 0.4904, 'learning_rate': 1.3413551441752855e-05, 'epoch': 0.41}
+
41%|████ | 4870/11952 [27:39<11:29:32, 5.84s/it]
41%|████ | 4871/11952 [27:45<11:32:38, 5.87s/it]
{'loss': 0.4926, 'learning_rate': 1.341100418370342e-05, 'epoch': 0.41}
+
41%|████ | 4871/11952 [27:45<11:32:38, 5.87s/it]
41%|████ | 4872/11952 [27:51<11:38:09, 5.92s/it]
{'loss': 0.4714, 'learning_rate': 1.3408456675164023e-05, 'epoch': 0.41}
+
41%|████ | 4872/11952 [27:51<11:38:09, 5.92s/it]
41%|████ | 4873/11952 [27:57<11:48:10, 6.00s/it]
{'loss': 0.471, 'learning_rate': 1.3405908916321748e-05, 'epoch': 0.41}
+
41%|████ | 4873/11952 [27:57<11:48:10, 6.00s/it]
41%|████ | 4874/11952 [28:03<11:37:22, 5.91s/it]
{'loss': 0.5065, 'learning_rate': 1.3403360907363687e-05, 'epoch': 0.41}
+
41%|████ | 4874/11952 [28:03<11:37:22, 5.91s/it]
41%|████ | 4875/11952 [28:09<11:34:59, 5.89s/it]
{'loss': 0.4832, 'learning_rate': 1.3400812648476956e-05, 'epoch': 0.41}
+
41%|████ | 4875/11952 [28:09<11:34:59, 5.89s/it]
41%|████ | 4876/11952 [28:15<11:36:04, 5.90s/it]
{'loss': 0.4877, 'learning_rate': 1.3398264139848687e-05, 'epoch': 0.41}
+
41%|████ | 4876/11952 [28:15<11:36:04, 5.90s/it]
41%|████ | 4877/11952 [28:20<11:29:05, 5.84s/it]
{'loss': 0.4762, 'learning_rate': 1.3395715381666038e-05, 'epoch': 0.41}
+
41%|████ | 4877/11952 [28:20<11:29:05, 5.84s/it]
41%|████ | 4878/11952 [28:26<11:27:24, 5.83s/it]
{'loss': 0.4868, 'learning_rate': 1.3393166374116175e-05, 'epoch': 0.41}
+
41%|████ | 4878/11952 [28:26<11:27:24, 5.83s/it]
41%|████ | 4879/11952 [28:32<11:25:11, 5.81s/it]
{'loss': 0.4823, 'learning_rate': 1.3390617117386285e-05, 'epoch': 0.41}
+
41%|████ | 4879/11952 [28:32<11:25:11, 5.81s/it]
41%|████ | 4880/11952 [28:38<11:27:55, 5.84s/it]
{'loss': 0.4737, 'learning_rate': 1.3388067611663578e-05, 'epoch': 0.41}
+
41%|████ | 4880/11952 [28:38<11:27:55, 5.84s/it]
41%|████ | 4881/11952 [28:44<11:29:40, 5.85s/it]
{'loss': 0.4901, 'learning_rate': 1.3385517857135274e-05, 'epoch': 0.41}
+
41%|████ | 4881/11952 [28:44<11:29:40, 5.85s/it]
41%|████ | 4882/11952 [28:49<11:27:43, 5.84s/it]
{'loss': 0.4653, 'learning_rate': 1.3382967853988623e-05, 'epoch': 0.41}
+
41%|████ | 4882/11952 [28:49<11:27:43, 5.84s/it]
41%|████ | 4883/11952 [28:55<11:19:46, 5.77s/it]
{'loss': 0.4864, 'learning_rate': 1.3380417602410884e-05, 'epoch': 0.41}
+
41%|████ | 4883/11952 [28:55<11:19:46, 5.77s/it]
41%|████ | 4884/11952 [29:01<11:21:57, 5.79s/it]
{'loss': 0.4931, 'learning_rate': 1.3377867102589336e-05, 'epoch': 0.41}
+
41%|████ | 4884/11952 [29:01<11:21:57, 5.79s/it]
41%|████ | 4885/11952 [29:07<11:20:42, 5.78s/it]
{'loss': 0.4761, 'learning_rate': 1.3375316354711277e-05, 'epoch': 0.41}
+
41%|████ | 4885/11952 [29:07<11:20:42, 5.78s/it]
41%|████ | 4886/11952 [29:13<11:34:16, 5.90s/it]
{'loss': 0.489, 'learning_rate': 1.3372765358964024e-05, 'epoch': 0.41}
+
41%|████ | 4886/11952 [29:13<11:34:16, 5.90s/it]
41%|████ | 4887/11952 [29:19<11:29:05, 5.85s/it]
{'loss': 0.4897, 'learning_rate': 1.3370214115534912e-05, 'epoch': 0.41}
+
41%|████ | 4887/11952 [29:19<11:29:05, 5.85s/it]
41%|████ | 4888/11952 [29:24<11:22:51, 5.80s/it]
{'loss': 0.4856, 'learning_rate': 1.3367662624611293e-05, 'epoch': 0.41}
+
41%|████ | 4888/11952 [29:24<11:22:51, 5.80s/it]
41%|████ | 4889/11952 [29:30<11:34:12, 5.90s/it]
{'loss': 0.5125, 'learning_rate': 1.3365110886380537e-05, 'epoch': 0.41}
+
41%|████ | 4889/11952 [29:30<11:34:12, 5.90s/it]
41%|████ | 4890/11952 [29:36<11:33:13, 5.89s/it]
{'loss': 0.4959, 'learning_rate': 1.3362558901030035e-05, 'epoch': 0.41}
+
41%|████ | 4890/11952 [29:36<11:33:13, 5.89s/it]
41%|████ | 4891/11952 [29:42<11:26:10, 5.83s/it]
{'loss': 0.4597, 'learning_rate': 1.3360006668747195e-05, 'epoch': 0.41}
+
41%|████ | 4891/11952 [29:42<11:26:10, 5.83s/it]
41%|████ | 4892/11952 [29:48<11:25:22, 5.82s/it]
{'loss': 0.5056, 'learning_rate': 1.3357454189719437e-05, 'epoch': 0.41}
+
41%|████ | 4892/11952 [29:48<11:25:22, 5.82s/it]
41%|████ | 4893/11952 [29:54<11:25:43, 5.83s/it]
{'loss': 0.4856, 'learning_rate': 1.3354901464134208e-05, 'epoch': 0.41}
+
41%|████ | 4893/11952 [29:54<11:25:43, 5.83s/it]
41%|████ | 4894/11952 [29:59<11:22:48, 5.80s/it]
{'loss': 0.4788, 'learning_rate': 1.3352348492178972e-05, 'epoch': 0.41}
+
41%|████ | 4894/11952 [29:59<11:22:48, 5.80s/it]
41%|████ | 4895/11952 [30:05<11:22:58, 5.81s/it]
{'loss': 0.4858, 'learning_rate': 1.3349795274041208e-05, 'epoch': 0.41}
+
41%|████ | 4895/11952 [30:05<11:22:58, 5.81s/it]
41%|████ | 4896/11952 [30:11<11:19:15, 5.78s/it]
{'loss': 0.4982, 'learning_rate': 1.3347241809908408e-05, 'epoch': 0.41}
+
41%|████ | 4896/11952 [30:11<11:19:15, 5.78s/it]
41%|████ | 4897/11952 [30:17<11:19:00, 5.77s/it]
{'loss': 0.4558, 'learning_rate': 1.3344688099968092e-05, 'epoch': 0.41}
+
41%|████ | 4897/11952 [30:17<11:19:00, 5.77s/it]
41%|████ | 4898/11952 [30:23<11:26:41, 5.84s/it]
{'loss': 0.482, 'learning_rate': 1.3342134144407796e-05, 'epoch': 0.41}
+
41%|████ | 4898/11952 [30:23<11:26:41, 5.84s/it]
41%|████ | 4899/11952 [30:29<11:48:46, 6.03s/it]
{'loss': 0.5045, 'learning_rate': 1.3339579943415069e-05, 'epoch': 0.41}
+
41%|████ | 4899/11952 [30:29<11:48:46, 6.03s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+60 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ 3 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
41%|████ | 4900/11952 [30:35<11:46:13, 6.01s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4684, 'learning_rate': 1.333702549717748e-05, 'epoch': 0.41}
+
41%|████ | 4900/11952 [30:35<11:46:13, 6.01s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-4900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
41%|████ | 4901/11952 [31:05<25:55:06, 13.23s/it]
{'loss': 0.4804, 'learning_rate': 1.3334470805882615e-05, 'epoch': 0.41}
+
41%|████ | 4901/11952 [31:05<25:55:06, 13.23s/it]
41%|████ | 4902/11952 [31:11<21:38:09, 11.05s/it]
{'loss': 0.4914, 'learning_rate': 1.3331915869718088e-05, 'epoch': 0.41}
+
41%|████ | 4902/11952 [31:11<21:38:09, 11.05s/it]
41%|████ | 4903/11952 [31:17<18:44:01, 9.57s/it]
{'loss': 0.4885, 'learning_rate': 1.3329360688871518e-05, 'epoch': 0.41}
+
41%|████ | 4903/11952 [31:17<18:44:01, 9.57s/it]
41%|████ | 4904/11952 [31:23<16:45:26, 8.56s/it]
{'loss': 0.4959, 'learning_rate': 1.3326805263530545e-05, 'epoch': 0.41}
+
41%|████ | 4904/11952 [31:23<16:45:26, 8.56s/it]
41%|████ | 4905/11952 [31:29<15:03:16, 7.69s/it]
{'loss': 0.4996, 'learning_rate': 1.3324249593882832e-05, 'epoch': 0.41}
+
41%|████ | 4905/11952 [31:29<15:03:16, 7.69s/it]
41%|████ | 4906/11952 [31:35<13:50:48, 7.07s/it]
{'loss': 0.4728, 'learning_rate': 1.3321693680116054e-05, 'epoch': 0.41}
+
41%|████ | 4906/11952 [31:35<13:50:48, 7.07s/it]
41%|████ | 4907/11952 [31:41<13:15:42, 6.78s/it]
{'loss': 0.4861, 'learning_rate': 1.3319137522417908e-05, 'epoch': 0.41}
+
41%|████ | 4907/11952 [31:41<13:15:42, 6.78s/it]
41%|████ | 4908/11952 [31:46<12:31:57, 6.41s/it]
{'loss': 0.4854, 'learning_rate': 1.3316581120976109e-05, 'epoch': 0.41}
+
41%|████ | 4908/11952 [31:46<12:31:57, 6.41s/it]
41%|████ | 4909/11952 [31:52<12:10:23, 6.22s/it]
{'loss': 0.4933, 'learning_rate': 1.3314024475978388e-05, 'epoch': 0.41}
+
41%|████ | 4909/11952 [31:52<12:10:23, 6.22s/it]
41%|████ | 4910/11952 [31:58<11:50:50, 6.06s/it]
{'loss': 0.4676, 'learning_rate': 1.331146758761249e-05, 'epoch': 0.41}
+
41%|████ | 4910/11952 [31:58<11:50:50, 6.06s/it]
41%|████ | 4911/11952 [32:03<11:38:02, 5.95s/it]
{'loss': 0.4983, 'learning_rate': 1.3308910456066191e-05, 'epoch': 0.41}
+
41%|████ | 4911/11952 [32:03<11:38:02, 5.95s/it]
41%|████ | 4912/11952 [32:09<11:31:12, 5.89s/it]
{'loss': 0.5059, 'learning_rate': 1.3306353081527265e-05, 'epoch': 0.41}
+
41%|████ | 4912/11952 [32:09<11:31:12, 5.89s/it]
41%|████ | 4913/11952 [32:16<11:52:06, 6.07s/it]
{'loss': 0.4859, 'learning_rate': 1.3303795464183522e-05, 'epoch': 0.41}
+
41%|████ | 4913/11952 [32:16<11:52:06, 6.07s/it]
41%|████ | 4914/11952 [32:22<11:53:29, 6.08s/it]
{'loss': 0.5003, 'learning_rate': 1.3301237604222786e-05, 'epoch': 0.41}
+
41%|████ | 4914/11952 [32:22<11:53:29, 6.08s/it]
41%|████ | 4915/11952 [32:27<11:36:05, 5.94s/it]
{'loss': 0.4709, 'learning_rate': 1.329867950183289e-05, 'epoch': 0.41}
+
41%|████ | 4915/11952 [32:27<11:36:05, 5.94s/it]
41%|████ | 4916/11952 [32:33<11:35:36, 5.93s/it]
{'loss': 0.5096, 'learning_rate': 1.3296121157201689e-05, 'epoch': 0.41}
+
41%|████ | 4916/11952 [32:33<11:35:36, 5.93s/it]
41%|████ | 4917/11952 [32:39<11:37:06, 5.95s/it]
{'loss': 0.4888, 'learning_rate': 1.329356257051706e-05, 'epoch': 0.41}
+
41%|████ | 4917/11952 [32:39<11:37:06, 5.95s/it]
41%|████ | 4918/11952 [32:45<11:25:59, 5.85s/it]
{'loss': 0.4876, 'learning_rate': 1.3291003741966898e-05, 'epoch': 0.41}
+
41%|████ | 4918/11952 [32:45<11:25:59, 5.85s/it]
41%|████ | 4919/11952 [32:50<11:16:09, 5.77s/it]
{'loss': 0.4887, 'learning_rate': 1.3288444671739106e-05, 'epoch': 0.41}
+
41%|████ | 4919/11952 [32:50<11:16:09, 5.77s/it]
41%|████ | 4920/11952 [32:56<11:08:44, 5.71s/it]
{'loss': 0.4732, 'learning_rate': 1.3285885360021615e-05, 'epoch': 0.41}
+
41%|████ | 4920/11952 [32:56<11:08:44, 5.71s/it]
41%|████ | 4921/11952 [33:02<11:06:02, 5.68s/it]
{'loss': 0.4874, 'learning_rate': 1.3283325807002374e-05, 'epoch': 0.41}
+
41%|████ | 4921/11952 [33:02<11:06:02, 5.68s/it]
41%|████ | 4922/11952 [33:08<11:14:43, 5.76s/it]
{'loss': 0.4845, 'learning_rate': 1.3280766012869338e-05, 'epoch': 0.41}
+
41%|████ | 4922/11952 [33:08<11:14:43, 5.76s/it]
41%|████ | 4923/11952 [33:14<11:24:01, 5.84s/it]
{'loss': 0.4866, 'learning_rate': 1.3278205977810492e-05, 'epoch': 0.41}
+
41%|████ | 4923/11952 [33:14<11:24:01, 5.84s/it]
41%|████ | 4924/11952 [33:19<11:15:34, 5.77s/it]
{'loss': 0.4692, 'learning_rate': 1.3275645702013836e-05, 'epoch': 0.41}
+
41%|████ | 4924/11952 [33:19<11:15:34, 5.77s/it]
41%|████ | 4925/11952 [33:25<11:15:27, 5.77s/it]
{'loss': 0.4743, 'learning_rate': 1.3273085185667385e-05, 'epoch': 0.41}
+
41%|████ | 4925/11952 [33:25<11:15:27, 5.77s/it]
41%|████ | 4926/11952 [33:31<11:15:22, 5.77s/it]
{'loss': 0.4811, 'learning_rate': 1.327052442895917e-05, 'epoch': 0.41}
+
41%|████ | 4926/11952 [33:31<11:15:22, 5.77s/it]
41%|████ | 4927/11952 [33:37<11:23:31, 5.84s/it]
{'loss': 0.4902, 'learning_rate': 1.3267963432077242e-05, 'epoch': 0.41}
+
41%|████ | 4927/11952 [33:37<11:23:31, 5.84s/it]
41%|████ | 4928/11952 [33:43<11:36:53, 5.95s/it]
{'loss': 0.475, 'learning_rate': 1.3265402195209675e-05, 'epoch': 0.41}
+
41%|████ | 4928/11952 [33:43<11:36:53, 5.95s/it]
41%|████ | 4929/11952 [33:49<11:48:56, 6.06s/it]
{'loss': 0.4967, 'learning_rate': 1.3262840718544552e-05, 'epoch': 0.41}
+
41%|████ | 4929/11952 [33:49<11:48:56, 6.06s/it]
41%|████ | 4930/11952 [33:55<11:49:41, 6.06s/it]
{'loss': 0.4948, 'learning_rate': 1.3260279002269977e-05, 'epoch': 0.41}
+
41%|████ | 4930/11952 [33:55<11:49:41, 6.06s/it]
41%|████▏ | 4931/11952 [34:01<11:37:29, 5.96s/it]
{'loss': 0.467, 'learning_rate': 1.3257717046574074e-05, 'epoch': 0.41}
+
41%|████▏ | 4931/11952 [34:01<11:37:29, 5.96s/it]
41%|████▏ | 4932/11952 [34:07<11:37:37, 5.96s/it]
{'loss': 0.4723, 'learning_rate': 1.325515485164498e-05, 'epoch': 0.41}
+
41%|████▏ | 4932/11952 [34:07<11:37:37, 5.96s/it]
41%|████▏ | 4933/11952 [34:13<11:29:56, 5.90s/it]
{'loss': 0.4997, 'learning_rate': 1.3252592417670856e-05, 'epoch': 0.41}
+
41%|████▏ | 4933/11952 [34:13<11:29:56, 5.90s/it]
41%|████▏ | 4934/11952 [34:18<11:21:38, 5.83s/it]
{'loss': 0.4764, 'learning_rate': 1.3250029744839867e-05, 'epoch': 0.41}
+
41%|████▏ | 4934/11952 [34:18<11:21:38, 5.83s/it]
41%|████▏ | 4935/11952 [34:24<11:25:51, 5.86s/it]
{'loss': 0.492, 'learning_rate': 1.3247466833340216e-05, 'epoch': 0.41}
+
41%|████▏ | 4935/11952 [34:24<11:25:51, 5.86s/it]
41%|████▏ | 4936/11952 [34:30<11:23:17, 5.84s/it]
{'loss': 0.4627, 'learning_rate': 1.324490368336011e-05, 'epoch': 0.41}
+
41%|████▏ | 4936/11952 [34:30<11:23:17, 5.84s/it]
41%|████▏ | 4937/11952 [34:36<11:13:09, 5.76s/it]
{'loss': 0.484, 'learning_rate': 1.324234029508777e-05, 'epoch': 0.41}
+
41%|████▏ | 4937/11952 [34:36<11:13:09, 5.76s/it]
41%|████▏ | 4938/11952 [34:42<11:18:18, 5.80s/it]
{'loss': 0.4789, 'learning_rate': 1.3239776668711444e-05, 'epoch': 0.41}
+
41%|████▏ | 4938/11952 [34:42<11:18:18, 5.80s/it]
41%|████▏ | 4939/11952 [34:47<11:12:24, 5.75s/it]
{'loss': 0.4715, 'learning_rate': 1.3237212804419398e-05, 'epoch': 0.41}
+
41%|████▏ | 4939/11952 [34:47<11:12:24, 5.75s/it]
41%|████▏ | 4940/11952 [34:53<11:06:41, 5.70s/it]
{'loss': 0.4995, 'learning_rate': 1.3234648702399903e-05, 'epoch': 0.41}
+
41%|████▏ | 4940/11952 [34:53<11:06:41, 5.70s/it]
41%|████▏ | 4941/11952 [34:59<11:05:50, 5.70s/it]
{'loss': 0.4747, 'learning_rate': 1.3232084362841267e-05, 'epoch': 0.41}
+
41%|████▏ | 4941/11952 [34:59<11:05:50, 5.70s/it]
41%|████▏ | 4942/11952 [35:04<11:06:39, 5.71s/it]
{'loss': 0.4898, 'learning_rate': 1.3229519785931795e-05, 'epoch': 0.41}
+
41%|████▏ | 4942/11952 [35:04<11:06:39, 5.71s/it]
41%|████▏ | 4943/11952 [35:10<11:15:23, 5.78s/it]
{'loss': 0.5059, 'learning_rate': 1.3226954971859827e-05, 'epoch': 0.41}
+
41%|████▏ | 4943/11952 [35:10<11:15:23, 5.78s/it]
41%|████▏ | 4944/11952 [35:16<11:16:32, 5.79s/it]
{'loss': 0.4816, 'learning_rate': 1.3224389920813703e-05, 'epoch': 0.41}
+
41%|████▏ | 4944/11952 [35:16<11:16:32, 5.79s/it]
41%|████▏ | 4945/11952 [35:22<11:19:29, 5.82s/it]
{'loss': 0.474, 'learning_rate': 1.3221824632981797e-05, 'epoch': 0.41}
+
41%|████▏ | 4945/11952 [35:22<11:19:29, 5.82s/it]
41%|████▏ | 4946/11952 [35:28<11:12:54, 5.76s/it]
{'loss': 0.4707, 'learning_rate': 1.3219259108552488e-05, 'epoch': 0.41}
+
41%|████▏ | 4946/11952 [35:28<11:12:54, 5.76s/it]
41%|████▏ | 4947/11952 [35:33<11:17:25, 5.80s/it]
{'loss': 0.4751, 'learning_rate': 1.3216693347714183e-05, 'epoch': 0.41}
+
41%|████▏ | 4947/11952 [35:33<11:17:25, 5.80s/it]
41%|████▏ | 4948/11952 [35:39<11:13:48, 5.77s/it]
{'loss': 0.4763, 'learning_rate': 1.3214127350655294e-05, 'epoch': 0.41}
+
41%|████▏ | 4948/11952 [35:39<11:13:48, 5.77s/it]
41%|████▏ | 4949/11952 [35:45<11:23:40, 5.86s/it]
{'loss': 0.517, 'learning_rate': 1.3211561117564267e-05, 'epoch': 0.41}
+
41%|████▏ | 4949/11952 [35:45<11:23:40, 5.86s/it]7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+026 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
41%|████▏ | 4950/11952 [35:51<11:25:54, 5.88s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4788, 'learning_rate': 1.3208994648629546e-05, 'epoch': 0.41}
+
41%|████▏ | 4950/11952 [35:51<11:25:54, 5.88s/it]
41%|████▏ | 4951/11952 [35:57<11:20:50, 5.83s/it]
{'loss': 0.4886, 'learning_rate': 1.3206427944039604e-05, 'epoch': 0.41}
+
41%|████▏ | 4951/11952 [35:57<11:20:50, 5.83s/it]
41%|████▏ | 4952/11952 [36:03<11:34:34, 5.95s/it]
{'loss': 0.4797, 'learning_rate': 1.3203861003982933e-05, 'epoch': 0.41}
+
41%|████▏ | 4952/11952 [36:03<11:34:34, 5.95s/it]
41%|████▏ | 4953/11952 [36:09<11:23:19, 5.86s/it]
{'loss': 0.4796, 'learning_rate': 1.3201293828648032e-05, 'epoch': 0.41}
+
41%|████▏ | 4953/11952 [36:09<11:23:19, 5.86s/it]
41%|████▏ | 4954/11952 [36:14<11:15:20, 5.79s/it]
{'loss': 0.4591, 'learning_rate': 1.3198726418223428e-05, 'epoch': 0.41}
+
41%|████▏ | 4954/11952 [36:14<11:15:20, 5.79s/it]
41%|████▏ | 4955/11952 [36:20<11:16:07, 5.80s/it]
{'loss': 0.4763, 'learning_rate': 1.3196158772897663e-05, 'epoch': 0.41}
+
41%|████▏ | 4955/11952 [36:20<11:16:07, 5.80s/it]
41%|████▏ | 4956/11952 [36:26<11:26:42, 5.89s/it]
{'loss': 0.4906, 'learning_rate': 1.3193590892859291e-05, 'epoch': 0.41}
+
41%|████▏ | 4956/11952 [36:26<11:26:42, 5.89s/it]
41%|████▏ | 4957/11952 [36:32<11:25:47, 5.88s/it]
{'loss': 0.492, 'learning_rate': 1.3191022778296887e-05, 'epoch': 0.41}
+
41%|████▏ | 4957/11952 [36:32<11:25:47, 5.88s/it]
41%|████▏ | 4958/11952 [36:38<11:20:31, 5.84s/it]
{'loss': 0.4808, 'learning_rate': 1.318845442939904e-05, 'epoch': 0.41}
+
41%|████▏ | 4958/11952 [36:38<11:20:31, 5.84s/it]
41%|████▏ | 4959/11952 [36:44<11:29:48, 5.92s/it]
{'loss': 0.495, 'learning_rate': 1.3185885846354365e-05, 'epoch': 0.41}
+
41%|████▏ | 4959/11952 [36:44<11:29:48, 5.92s/it]
41%|████▏ | 4960/11952 [36:50<11:16:44, 5.81s/it]
{'loss': 0.4769, 'learning_rate': 1.3183317029351483e-05, 'epoch': 0.41}
+
41%|████▏ | 4960/11952 [36:50<11:16:44, 5.81s/it]
42%|████▏ | 4961/11952 [36:55<11:12:45, 5.77s/it]
{'loss': 0.4781, 'learning_rate': 1.3180747978579039e-05, 'epoch': 0.42}
+
42%|████▏ | 4961/11952 [36:55<11:12:45, 5.77s/it]
42%|████▏ | 4962/11952 [37:01<11:08:46, 5.74s/it]
{'loss': 0.4663, 'learning_rate': 1.3178178694225695e-05, 'epoch': 0.42}
+
42%|████▏ | 4962/11952 [37:01<11:08:46, 5.74s/it]
42%|████▏ | 4963/11952 [37:07<11:11:45, 5.77s/it]
{'loss': 0.4681, 'learning_rate': 1.3175609176480122e-05, 'epoch': 0.42}
+
42%|████▏ | 4963/11952 [37:07<11:11:45, 5.77s/it]
42%|████▏ | 4964/11952 [37:12<11:05:52, 5.72s/it]
{'loss': 0.4945, 'learning_rate': 1.317303942553102e-05, 'epoch': 0.42}
+
42%|████▏ | 4964/11952 [37:12<11:05:52, 5.72s/it]
42%|████▏ | 4965/11952 [37:18<11:12:13, 5.77s/it]
{'loss': 0.47, 'learning_rate': 1.3170469441567104e-05, 'epoch': 0.42}
+
42%|████▏ | 4965/11952 [37:18<11:12:13, 5.77s/it]
42%|████▏ | 4966/11952 [37:24<11:09:11, 5.75s/it]
{'loss': 0.4708, 'learning_rate': 1.3167899224777098e-05, 'epoch': 0.42}
+
42%|████▏ | 4966/11952 [37:24<11:09:11, 5.75s/it]
42%|████▏ | 4967/11952 [37:30<11:08:37, 5.74s/it]
{'loss': 0.5071, 'learning_rate': 1.316532877534975e-05, 'epoch': 0.42}
+
42%|████▏ | 4967/11952 [37:30<11:08:37, 5.74s/it]
42%|████▏ | 4968/11952 [37:35<11:03:06, 5.70s/it]
{'loss': 0.4788, 'learning_rate': 1.316275809347382e-05, 'epoch': 0.42}
+
42%|████▏ | 4968/11952 [37:35<11:03:06, 5.70s/it]
42%|████▏ | 4969/11952 [37:41<11:09:46, 5.75s/it]
{'loss': 0.4694, 'learning_rate': 1.316018717933809e-05, 'epoch': 0.42}
+
42%|████▏ | 4969/11952 [37:41<11:09:46, 5.75s/it]
42%|████▏ | 4970/11952 [37:47<11:19:01, 5.84s/it]
{'loss': 0.4749, 'learning_rate': 1.3157616033131361e-05, 'epoch': 0.42}
+
42%|████▏ | 4970/11952 [37:47<11:19:01, 5.84s/it]
42%|████▏ | 4971/11952 [37:53<11:31:05, 5.94s/it]
{'loss': 0.4792, 'learning_rate': 1.315504465504244e-05, 'epoch': 0.42}
+
42%|████▏ | 4971/11952 [37:53<11:31:05, 5.94s/it]
42%|████▏ | 4972/11952 [37:59<11:25:43, 5.89s/it]
{'loss': 0.4936, 'learning_rate': 1.3152473045260168e-05, 'epoch': 0.42}
+
42%|████▏ | 4972/11952 [37:59<11:25:43, 5.89s/it]
42%|████▏ | 4973/11952 [38:06<11:41:29, 6.03s/it]
{'loss': 0.5079, 'learning_rate': 1.3149901203973383e-05, 'epoch': 0.42}
+
42%|████▏ | 4973/11952 [38:06<11:41:29, 6.03s/it]
42%|████▏ | 4974/11952 [38:11<11:32:56, 5.96s/it]
{'loss': 0.4884, 'learning_rate': 1.3147329131370956e-05, 'epoch': 0.42}
+
42%|████▏ | 4974/11952 [38:11<11:32:56, 5.96s/it]
42%|████▏ | 4975/11952 [38:17<11:22:28, 5.87s/it]
{'loss': 0.4967, 'learning_rate': 1.3144756827641769e-05, 'epoch': 0.42}
+
42%|████▏ | 4975/11952 [38:17<11:22:28, 5.87s/it]
42%|████▏ | 4976/11952 [38:23<11:27:48, 5.92s/it]
{'loss': 0.48, 'learning_rate': 1.3142184292974723e-05, 'epoch': 0.42}
+
42%|████▏ | 4976/11952 [38:23<11:27:48, 5.92s/it]
42%|████▏ | 4977/11952 [38:29<11:22:41, 5.87s/it]
{'loss': 0.502, 'learning_rate': 1.3139611527558729e-05, 'epoch': 0.42}
+
42%|████▏ | 4977/11952 [38:29<11:22:41, 5.87s/it]
42%|████▏ | 4978/11952 [38:35<11:23:51, 5.88s/it]
{'loss': 0.4875, 'learning_rate': 1.3137038531582721e-05, 'epoch': 0.42}
+
42%|████▏ | 4978/11952 [38:35<11:23:51, 5.88s/it]
42%|████▏ | 4979/11952 [38:41<11:34:04, 5.97s/it]
{'loss': 0.4827, 'learning_rate': 1.3134465305235653e-05, 'epoch': 0.42}
+
42%|████▏ | 4979/11952 [38:41<11:34:04, 5.97s/it]
42%|████▏ | 4980/11952 [38:47<11:25:08, 5.90s/it]
{'loss': 0.479, 'learning_rate': 1.3131891848706492e-05, 'epoch': 0.42}
+
42%|████▏ | 4980/11952 [38:47<11:25:08, 5.90s/it]
42%|████▏ | 4981/11952 [38:52<11:16:26, 5.82s/it]
{'loss': 0.4702, 'learning_rate': 1.3129318162184216e-05, 'epoch': 0.42}
+
42%|████▏ | 4981/11952 [38:52<11:16:26, 5.82s/it]
42%|████▏ | 4982/11952 [38:58<11:25:07, 5.90s/it]
{'loss': 0.4727, 'learning_rate': 1.3126744245857835e-05, 'epoch': 0.42}
+
42%|████▏ | 4982/11952 [38:58<11:25:07, 5.90s/it]
42%|████▏ | 4983/11952 [39:04<11:21:39, 5.87s/it]
{'loss': 0.4882, 'learning_rate': 1.312417009991636e-05, 'epoch': 0.42}
+
42%|████▏ | 4983/11952 [39:04<11:21:39, 5.87s/it]
42%|████▏ | 4984/11952 [39:10<11:36:37, 6.00s/it]
{'loss': 0.4865, 'learning_rate': 1.3121595724548825e-05, 'epoch': 0.42}
+
42%|████▏ | 4984/11952 [39:10<11:36:37, 6.00s/it]
42%|████▏ | 4985/11952 [39:16<11:22:33, 5.88s/it]
{'loss': 0.4924, 'learning_rate': 1.3119021119944287e-05, 'epoch': 0.42}
+
42%|████▏ | 4985/11952 [39:16<11:22:33, 5.88s/it]
42%|████▏ | 4986/11952 [39:22<11:37:02, 6.00s/it]
{'loss': 0.499, 'learning_rate': 1.3116446286291811e-05, 'epoch': 0.42}
+
42%|████▏ | 4986/11952 [39:22<11:37:02, 6.00s/it]
42%|████▏ | 4987/11952 [39:28<11:37:01, 6.00s/it]
{'loss': 0.4787, 'learning_rate': 1.3113871223780481e-05, 'epoch': 0.42}
+
42%|████▏ | 4987/11952 [39:28<11:37:01, 6.00s/it]
42%|████▏ | 4988/11952 [39:34<11:27:33, 5.92s/it]
{'loss': 0.478, 'learning_rate': 1.3111295932599396e-05, 'epoch': 0.42}
+
42%|████▏ | 4988/11952 [39:34<11:27:33, 5.92s/it]
42%|████▏ | 4989/11952 [39:40<11:26:37, 5.92s/it]
{'loss': 0.4822, 'learning_rate': 1.3108720412937681e-05, 'epoch': 0.42}
+
42%|████▏ | 4989/11952 [39:40<11:26:37, 5.92s/it]
42%|████▏ | 4990/11952 [39:46<11:22:42, 5.88s/it]
{'loss': 0.4804, 'learning_rate': 1.3106144664984473e-05, 'epoch': 0.42}
+
42%|████▏ | 4990/11952 [39:46<11:22:42, 5.88s/it]
42%|████▏ | 4991/11952 [39:52<11:28:19, 5.93s/it]
{'loss': 0.4707, 'learning_rate': 1.3103568688928917e-05, 'epoch': 0.42}
+
42%|████▏ | 4991/11952 [39:52<11:28:19, 5.93s/it]
42%|████▏ | 4992/11952 [39:57<11:17:53, 5.84s/it]
{'loss': 0.4968, 'learning_rate': 1.3100992484960185e-05, 'epoch': 0.42}
+
42%|████▏ | 4992/11952 [39:57<11:17:53, 5.84s/it]
42%|████▏ | 4993/11952 [40:03<11:13:17, 5.81s/it]
{'loss': 0.4693, 'learning_rate': 1.3098416053267463e-05, 'epoch': 0.42}
+
42%|████▏ | 4993/11952 [40:03<11:13:17, 5.81s/it]
42%|████▏ | 4994/11952 [40:09<11:16:16, 5.83s/it]
{'loss': 0.4758, 'learning_rate': 1.3095839394039953e-05, 'epoch': 0.42}
+
42%|████▏ | 4994/11952 [40:09<11:16:16, 5.83s/it]
42%|████▏ | 4995/11952 [40:15<11:14:54, 5.82s/it]
{'loss': 0.5018, 'learning_rate': 1.3093262507466873e-05, 'epoch': 0.42}
+
42%|████▏ | 4995/11952 [40:15<11:14:54, 5.82s/it]
42%|████▏ | 4996/11952 [40:21<11:15:48, 5.83s/it]
{'loss': 0.4784, 'learning_rate': 1.3090685393737464e-05, 'epoch': 0.42}
+
42%|████▏ | 4996/11952 [40:21<11:15:48, 5.83s/it]
42%|████▏ | 4997/11952 [40:27<11:16:17, 5.83s/it]
{'loss': 0.4755, 'learning_rate': 1.3088108053040974e-05, 'epoch': 0.42}
+
42%|████▏ | 4997/11952 [40:27<11:16:17, 5.83s/it]
42%|████▏ | 4998/11952 [40:32<11:13:32, 5.81s/it]
{'loss': 0.4867, 'learning_rate': 1.308553048556667e-05, 'epoch': 0.42}
+
42%|████▏ | 4998/11952 [40:32<11:13:32, 5.81s/it]
42%|████▏ | 4999/11952 [40:38<11:11:34, 5.80s/it]
{'loss': 0.4803, 'learning_rate': 1.3082952691503843e-05, 'epoch': 0.42}
+
42%|████▏ | 4999/11952 [40:38<11:11:34, 5.80s/it]4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
42%|████▏ | 5000/11952 [40:44<11:17:59, 5.85s/it]3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4798, 'learning_rate': 1.3080374671041793e-05, 'epoch': 0.42}
+
42%|████▏ | 5000/11952 [40:44<11:17:59, 5.85s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
42%|████▏ | 5001/11952 [41:17<27:17:52, 14.14s/it]
{'loss': 0.4852, 'learning_rate': 1.3077796424369842e-05, 'epoch': 0.42}
+
42%|████▏ | 5001/11952 [41:17<27:17:52, 14.14s/it]
42%|████▏ | 5002/11952 [41:23<22:22:42, 11.59s/it]
{'loss': 0.4841, 'learning_rate': 1.307521795167732e-05, 'epoch': 0.42}
+
42%|████▏ | 5002/11952 [41:23<22:22:42, 11.59s/it]
42%|████▏ | 5003/11952 [41:29<19:09:33, 9.93s/it]
{'loss': 0.5082, 'learning_rate': 1.3072639253153583e-05, 'epoch': 0.42}
+
42%|████▏ | 5003/11952 [41:29<19:09:33, 9.93s/it]
42%|████▏ | 5004/11952 [41:35<16:51:32, 8.74s/it]
{'loss': 0.4823, 'learning_rate': 1.3070060328988e-05, 'epoch': 0.42}
+
42%|████▏ | 5004/11952 [41:35<16:51:32, 8.74s/it]
42%|████▏ | 5005/11952 [41:41<15:10:57, 7.87s/it]
{'loss': 0.4915, 'learning_rate': 1.3067481179369951e-05, 'epoch': 0.42}
+
42%|████▏ | 5005/11952 [41:41<15:10:57, 7.87s/it]
42%|████▏ | 5006/11952 [41:47<14:04:10, 7.29s/it]
{'loss': 0.5137, 'learning_rate': 1.306490180448885e-05, 'epoch': 0.42}
+
42%|████▏ | 5006/11952 [41:47<14:04:10, 7.29s/it]
42%|████▏ | 5007/11952 [41:53<13:16:34, 6.88s/it]
{'loss': 0.509, 'learning_rate': 1.3062322204534105e-05, 'epoch': 0.42}
+
42%|████▏ | 5007/11952 [41:53<13:16:34, 6.88s/it]
42%|████▏ | 5008/11952 [41:59<12:49:20, 6.65s/it]
{'loss': 0.4846, 'learning_rate': 1.3059742379695158e-05, 'epoch': 0.42}
+
42%|████▏ | 5008/11952 [41:59<12:49:20, 6.65s/it]
42%|████▏ | 5009/11952 [42:05<12:26:52, 6.45s/it]
{'loss': 0.4945, 'learning_rate': 1.3057162330161453e-05, 'epoch': 0.42}
+
42%|████▏ | 5009/11952 [42:05<12:26:52, 6.45s/it]
42%|████▏ | 5010/11952 [42:11<12:09:52, 6.31s/it]
{'loss': 0.4883, 'learning_rate': 1.305458205612246e-05, 'epoch': 0.42}
+
42%|████▏ | 5010/11952 [42:11<12:09:52, 6.31s/it]
42%|████▏ | 5011/11952 [42:17<12:04:00, 6.26s/it]
{'loss': 0.4953, 'learning_rate': 1.3052001557767671e-05, 'epoch': 0.42}
+
42%|████▏ | 5011/11952 [42:17<12:04:00, 6.26s/it]
42%|████▏ | 5012/11952 [42:23<11:39:54, 6.05s/it]
{'loss': 0.5003, 'learning_rate': 1.304942083528658e-05, 'epoch': 0.42}
+
42%|████▏ | 5012/11952 [42:23<11:39:54, 6.05s/it]
42%|████▏ | 5013/11952 [42:29<11:34:50, 6.01s/it]
{'loss': 0.4656, 'learning_rate': 1.3046839888868706e-05, 'epoch': 0.42}
+
42%|████▏ | 5013/11952 [42:29<11:34:50, 6.01s/it]
42%|████▏ | 5014/11952 [42:35<11:34:52, 6.01s/it]
{'loss': 0.492, 'learning_rate': 1.3044258718703581e-05, 'epoch': 0.42}
+
42%|████▏ | 5014/11952 [42:35<11:34:52, 6.01s/it]
42%|████▏ | 5015/11952 [42:40<11:26:57, 5.94s/it]
{'loss': 0.4865, 'learning_rate': 1.304167732498076e-05, 'epoch': 0.42}
+
42%|████▏ | 5015/11952 [42:40<11:26:57, 5.94s/it]
42%|████▏ | 5016/11952 [42:46<11:32:14, 5.99s/it]
{'loss': 0.486, 'learning_rate': 1.3039095707889808e-05, 'epoch': 0.42}
+
42%|████▏ | 5016/11952 [42:46<11:32:14, 5.99s/it]
42%|████▏ | 5017/11952 [42:52<11:28:09, 5.95s/it]
{'loss': 0.4977, 'learning_rate': 1.3036513867620309e-05, 'epoch': 0.42}
+
42%|████▏ | 5017/11952 [42:52<11:28:09, 5.95s/it]
42%|████▏ | 5018/11952 [42:58<11:26:19, 5.94s/it]
{'loss': 0.4894, 'learning_rate': 1.303393180436186e-05, 'epoch': 0.42}
+
42%|████▏ | 5018/11952 [42:58<11:26:19, 5.94s/it]
42%|████▏ | 5019/11952 [43:04<11:17:50, 5.87s/it]
{'loss': 0.4717, 'learning_rate': 1.3031349518304078e-05, 'epoch': 0.42}
+
42%|████▏ | 5019/11952 [43:04<11:17:50, 5.87s/it]
42%|████▏ | 5020/11952 [43:10<11:14:01, 5.83s/it]
{'loss': 0.5052, 'learning_rate': 1.3028767009636593e-05, 'epoch': 0.42}
+
42%|████▏ | 5020/11952 [43:10<11:14:01, 5.83s/it]
42%|████▏ | 5021/11952 [43:15<11:05:46, 5.76s/it]
{'loss': 0.4768, 'learning_rate': 1.3026184278549062e-05, 'epoch': 0.42}
+
42%|████▏ | 5021/11952 [43:15<11:05:46, 5.76s/it]
42%|████▏ | 5022/11952 [43:21<11:06:41, 5.77s/it]
{'loss': 0.4759, 'learning_rate': 1.302360132523114e-05, 'epoch': 0.42}
+
42%|████▏ | 5022/11952 [43:21<11:06:41, 5.77s/it]
42%|████▏ | 5023/11952 [43:27<11:02:11, 5.73s/it]
{'loss': 0.4861, 'learning_rate': 1.3021018149872516e-05, 'epoch': 0.42}
+
42%|████▏ | 5023/11952 [43:27<11:02:11, 5.73s/it]
42%|████▏ | 5024/11952 [43:33<11:07:13, 5.78s/it]
{'loss': 0.5004, 'learning_rate': 1.3018434752662882e-05, 'epoch': 0.42}
+
42%|████▏ | 5024/11952 [43:33<11:07:13, 5.78s/it]
42%|████▏ | 5025/11952 [43:38<11:05:28, 5.76s/it]
{'loss': 0.4867, 'learning_rate': 1.3015851133791955e-05, 'epoch': 0.42}
+
42%|████▏ | 5025/11952 [43:38<11:05:28, 5.76s/it]
42%|████▏ | 5026/11952 [43:44<11:03:52, 5.75s/it]
{'loss': 0.4708, 'learning_rate': 1.3013267293449463e-05, 'epoch': 0.42}
+
42%|████▏ | 5026/11952 [43:44<11:03:52, 5.75s/it]
42%|████▏ | 5027/11952 [43:50<11:00:34, 5.72s/it]
{'loss': 0.4981, 'learning_rate': 1.3010683231825158e-05, 'epoch': 0.42}
+
42%|████▏ | 5027/11952 [43:50<11:00:34, 5.72s/it]
42%|████▏ | 5028/11952 [43:56<11:11:12, 5.82s/it]
{'loss': 0.4881, 'learning_rate': 1.30080989491088e-05, 'epoch': 0.42}
+
42%|████▏ | 5028/11952 [43:56<11:11:12, 5.82s/it]
42%|████▏ | 5029/11952 [44:02<11:25:16, 5.94s/it]
{'loss': 0.4787, 'learning_rate': 1.300551444549016e-05, 'epoch': 0.42}
+
42%|████▏ | 5029/11952 [44:02<11:25:16, 5.94s/it]
42%|████▏ | 5030/11952 [44:08<11:23:09, 5.92s/it]
{'loss': 0.504, 'learning_rate': 1.3002929721159043e-05, 'epoch': 0.42}
+
42%|████▏ | 5030/11952 [44:08<11:23:09, 5.92s/it]
42%|████▏ | 5031/11952 [44:14<11:29:13, 5.98s/it]
{'loss': 0.511, 'learning_rate': 1.3000344776305258e-05, 'epoch': 0.42}
+
42%|████▏ | 5031/11952 [44:14<11:29:13, 5.98s/it]
42%|████▏ | 5032/11952 [44:20<11:18:49, 5.89s/it]
{'loss': 0.4751, 'learning_rate': 1.2997759611118634e-05, 'epoch': 0.42}
+
42%|████▏ | 5032/11952 [44:20<11:18:49, 5.89s/it]
42%|████▏ | 5033/11952 [44:25<11:14:49, 5.85s/it]
{'loss': 0.5148, 'learning_rate': 1.2995174225789008e-05, 'epoch': 0.42}
+
42%|████▏ | 5033/11952 [44:25<11:14:49, 5.85s/it]
42%|████▏ | 5034/11952 [44:31<11:13:08, 5.84s/it]
{'loss': 0.5013, 'learning_rate': 1.2992588620506251e-05, 'epoch': 0.42}
+
42%|████▏ | 5034/11952 [44:31<11:13:08, 5.84s/it]
42%|████▏ | 5035/11952 [44:37<11:18:12, 5.88s/it]
{'loss': 0.4959, 'learning_rate': 1.2990002795460228e-05, 'epoch': 0.42}
+
42%|████▏ | 5035/11952 [44:37<11:18:12, 5.88s/it]
42%|████▏ | 5036/11952 [44:43<11:26:01, 5.95s/it]
{'loss': 0.4788, 'learning_rate': 1.2987416750840836e-05, 'epoch': 0.42}
+
42%|████▏ | 5036/11952 [44:43<11:26:01, 5.95s/it]
42%|████▏ | 5037/11952 [44:49<11:28:30, 5.97s/it]
{'loss': 0.4932, 'learning_rate': 1.2984830486837985e-05, 'epoch': 0.42}
+
42%|████▏ | 5037/11952 [44:49<11:28:30, 5.97s/it]
42%|████▏ | 5038/11952 [44:55<11:19:31, 5.90s/it]
{'loss': 0.487, 'learning_rate': 1.2982244003641599e-05, 'epoch': 0.42}
+
42%|████▏ | 5038/11952 [44:55<11:19:31, 5.90s/it]
42%|████▏ | 5039/11952 [45:01<11:13:42, 5.85s/it]
{'loss': 0.4873, 'learning_rate': 1.2979657301441615e-05, 'epoch': 0.42}
+
42%|████▏ | 5039/11952 [45:01<11:13:42, 5.85s/it]
42%|████▏ | 5040/11952 [45:07<11:12:37, 5.84s/it]
{'loss': 0.4762, 'learning_rate': 1.2977070380427993e-05, 'epoch': 0.42}
+
42%|████▏ | 5040/11952 [45:07<11:12:37, 5.84s/it]
42%|████▏ | 5041/11952 [45:12<11:05:22, 5.78s/it]
{'loss': 0.4804, 'learning_rate': 1.2974483240790705e-05, 'epoch': 0.42}
+
42%|████▏ | 5041/11952 [45:12<11:05:22, 5.78s/it]
42%|████▏ | 5042/11952 [45:18<10:59:20, 5.73s/it]
{'loss': 0.4935, 'learning_rate': 1.2971895882719741e-05, 'epoch': 0.42}
+
42%|████▏ | 5042/11952 [45:18<10:59:20, 5.73s/it]
42%|████▏ | 5043/11952 [45:24<11:07:57, 5.80s/it]
{'loss': 0.4742, 'learning_rate': 1.2969308306405102e-05, 'epoch': 0.42}
+
42%|████▏ | 5043/11952 [45:24<11:07:57, 5.80s/it]
42%|████▏ | 5044/11952 [45:30<11:10:09, 5.82s/it]
{'loss': 0.5088, 'learning_rate': 1.2966720512036813e-05, 'epoch': 0.42}
+
42%|████▏ | 5044/11952 [45:30<11:10:09, 5.82s/it]
42%|████▏ | 5045/11952 [45:36<11:11:11, 5.83s/it]
{'loss': 0.4828, 'learning_rate': 1.2964132499804907e-05, 'epoch': 0.42}
+
42%|████▏ | 5045/11952 [45:36<11:11:11, 5.83s/it]
42%|████▏ | 5046/11952 [45:41<11:11:41, 5.84s/it]
{'loss': 0.4859, 'learning_rate': 1.296154426989944e-05, 'epoch': 0.42}
+
42%|████▏ | 5046/11952 [45:41<11:11:41, 5.84s/it]
42%|████▏ | 5047/11952 [45:47<11:09:24, 5.82s/it]
{'loss': 0.4948, 'learning_rate': 1.2958955822510482e-05, 'epoch': 0.42}
+
42%|████▏ | 5047/11952 [45:47<11:09:24, 5.82s/it]
42%|████▏ | 5048/11952 [45:53<11:10:52, 5.83s/it]
{'loss': 0.4609, 'learning_rate': 1.2956367157828113e-05, 'epoch': 0.42}
+
42%|████▏ | 5048/11952 [45:53<11:10:52, 5.83s/it]
42%|████▏ | 5049/11952 [45:59<11:16:26, 5.88s/it]
{'loss': 0.5, 'learning_rate': 1.295377827604244e-05, 'epoch': 0.42}
+
42%|████▏ | 5049/11952 [45:59<11:16:26, 5.88s/it]7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
42%|████▏ | 5050/11952 [46:05<11:17:52, 5.89s/it]
{'loss': 0.4859, 'learning_rate': 1.295118917734357e-05, 'epoch': 0.42}
+
42%|████▏ | 5050/11952 [46:05<11:17:52, 5.89s/it]
42%|████▏ | 5051/11952 [46:11<11:16:53, 5.89s/it]
{'loss': 0.4748, 'learning_rate': 1.2948599861921644e-05, 'epoch': 0.42}
+
42%|████▏ | 5051/11952 [46:11<11:16:53, 5.89s/it]
42%|████▏ | 5052/11952 [46:16<11:09:55, 5.83s/it]
{'loss': 0.4679, 'learning_rate': 1.2946010329966811e-05, 'epoch': 0.42}
+
42%|████▏ | 5052/11952 [46:17<11:09:55, 5.83s/it]
42%|████▏ | 5053/11952 [46:22<11:06:19, 5.79s/it]
{'loss': 0.4995, 'learning_rate': 1.2943420581669231e-05, 'epoch': 0.42}
+
42%|████▏ | 5053/11952 [46:22<11:06:19, 5.79s/it]
42%|████▏ | 5054/11952 [46:28<11:11:24, 5.84s/it]
{'loss': 0.5, 'learning_rate': 1.2940830617219087e-05, 'epoch': 0.42}
+
42%|████▏ | 5054/11952 [46:28<11:11:24, 5.84s/it]
42%|████▏ | 5055/11952 [46:34<11:11:03, 5.84s/it]
{'loss': 0.4732, 'learning_rate': 1.2938240436806575e-05, 'epoch': 0.42}
+
42%|████▏ | 5055/11952 [46:34<11:11:03, 5.84s/it]
42%|████▏ | 5056/11952 [46:40<11:10:12, 5.83s/it]
{'loss': 0.4839, 'learning_rate': 1.2935650040621901e-05, 'epoch': 0.42}
+
42%|████▏ | 5056/11952 [46:40<11:10:12, 5.83s/it]
42%|████▏ | 5057/11952 [46:46<11:11:01, 5.84s/it]
{'loss': 0.4713, 'learning_rate': 1.2933059428855303e-05, 'epoch': 0.42}
+
42%|████▏ | 5057/11952 [46:46<11:11:01, 5.84s/it]
42%|████▏ | 5058/11952 [46:51<11:05:43, 5.79s/it]
{'loss': 0.4795, 'learning_rate': 1.2930468601697022e-05, 'epoch': 0.42}
+
42%|████▏ | 5058/11952 [46:51<11:05:43, 5.79s/it]
42%|████▏ | 5059/11952 [46:57<10:57:16, 5.72s/it]
{'loss': 0.4778, 'learning_rate': 1.2927877559337311e-05, 'epoch': 0.42}
+
42%|████▏ | 5059/11952 [46:57<10:57:16, 5.72s/it]
42%|████▏ | 5060/11952 [47:03<10:59:53, 5.74s/it]
{'loss': 0.4813, 'learning_rate': 1.2925286301966451e-05, 'epoch': 0.42}
+
42%|████▏ | 5060/11952 [47:03<10:59:53, 5.74s/it]
42%|████▏ | 5061/11952 [47:09<11:02:23, 5.77s/it]
{'loss': 0.5003, 'learning_rate': 1.2922694829774733e-05, 'epoch': 0.42}
+
42%|████▏ | 5061/11952 [47:09<11:02:23, 5.77s/it]
42%|████▏ | 5062/11952 [47:14<11:04:44, 5.79s/it]
{'loss': 0.4835, 'learning_rate': 1.2920103142952465e-05, 'epoch': 0.42}
+
42%|████▏ | 5062/11952 [47:14<11:04:44, 5.79s/it]
42%|████▏ | 5063/11952 [47:21<11:18:32, 5.91s/it]
{'loss': 0.4714, 'learning_rate': 1.2917511241689963e-05, 'epoch': 0.42}
+
42%|████▏ | 5063/11952 [47:21<11:18:32, 5.91s/it]
42%|████▏ | 5064/11952 [47:26<11:12:55, 5.86s/it]
{'loss': 0.5055, 'learning_rate': 1.2914919126177576e-05, 'epoch': 0.42}
+
42%|████▏ | 5064/11952 [47:26<11:12:55, 5.86s/it]
42%|████▏ | 5065/11952 [47:32<11:08:49, 5.83s/it]
{'loss': 0.4942, 'learning_rate': 1.291232679660565e-05, 'epoch': 0.42}
+
42%|████▏ | 5065/11952 [47:32<11:08:49, 5.83s/it]
42%|████▏ | 5066/11952 [47:38<11:17:41, 5.90s/it]
{'loss': 0.4614, 'learning_rate': 1.2909734253164557e-05, 'epoch': 0.42}
+
42%|████▏ | 5066/11952 [47:38<11:17:41, 5.90s/it]
42%|████▏ | 5067/11952 [47:44<11:10:15, 5.84s/it]
{'loss': 0.4689, 'learning_rate': 1.2907141496044679e-05, 'epoch': 0.42}
+
42%|████▏ | 5067/11952 [47:44<11:10:15, 5.84s/it]
42%|████▏ | 5068/11952 [47:49<11:04:08, 5.79s/it]
{'loss': 0.4843, 'learning_rate': 1.2904548525436429e-05, 'epoch': 0.42}
+
42%|████▏ | 5068/11952 [47:49<11:04:08, 5.79s/it]
42%|████▏ | 5069/11952 [47:55<11:01:36, 5.77s/it]
{'loss': 0.472, 'learning_rate': 1.2901955341530213e-05, 'epoch': 0.42}
+
42%|████▏ | 5069/11952 [47:55<11:01:36, 5.77s/it]
42%|████▏ | 5070/11952 [48:01<11:00:21, 5.76s/it]
{'loss': 0.489, 'learning_rate': 1.2899361944516464e-05, 'epoch': 0.42}
+
42%|████▏ | 5070/11952 [48:01<11:00:21, 5.76s/it]
42%|████▏ | 5071/11952 [48:07<10:59:04, 5.75s/it]
{'loss': 0.5033, 'learning_rate': 1.2896768334585635e-05, 'epoch': 0.42}
+
42%|████▏ | 5071/11952 [48:07<10:59:04, 5.75s/it]
42%|████▏ | 5072/11952 [48:12<10:55:33, 5.72s/it]
{'loss': 0.4797, 'learning_rate': 1.2894174511928189e-05, 'epoch': 0.42}
+
42%|████▏ | 5072/11952 [48:12<10:55:33, 5.72s/it]
42%|████▏ | 5073/11952 [48:18<11:05:16, 5.80s/it]
{'loss': 0.4992, 'learning_rate': 1.2891580476734602e-05, 'epoch': 0.42}
+
42%|████▏ | 5073/11952 [48:18<11:05:16, 5.80s/it]
42%|████▏ | 5074/11952 [48:24<11:13:58, 5.88s/it]
{'loss': 0.4896, 'learning_rate': 1.2888986229195375e-05, 'epoch': 0.42}
+
42%|████▏ | 5074/11952 [48:24<11:13:58, 5.88s/it]
42%|████▏ | 5075/11952 [48:30<11:14:09, 5.88s/it]
{'loss': 0.4872, 'learning_rate': 1.2886391769501016e-05, 'epoch': 0.42}
+
42%|████▏ | 5075/11952 [48:30<11:14:09, 5.88s/it]
42%|████▏ | 5076/11952 [48:36<11:21:18, 5.95s/it]
{'loss': 0.4663, 'learning_rate': 1.2883797097842048e-05, 'epoch': 0.42}
+
42%|████▏ | 5076/11952 [48:36<11:21:18, 5.95s/it]
42%|████▏ | 5077/11952 [48:43<11:28:59, 6.01s/it]
{'loss': 0.4954, 'learning_rate': 1.2881202214409016e-05, 'epoch': 0.42}
+
42%|████▏ | 5077/11952 [48:43<11:28:59, 6.01s/it]
42%|████▏ | 5078/11952 [48:48<11:26:28, 5.99s/it]
{'loss': 0.5041, 'learning_rate': 1.2878607119392479e-05, 'epoch': 0.42}
+
42%|████▏ | 5078/11952 [48:48<11:26:28, 5.99s/it]
42%|████▏ | 5079/11952 [48:54<11:20:12, 5.94s/it]
{'loss': 0.4777, 'learning_rate': 1.2876011812983009e-05, 'epoch': 0.42}
+
42%|████▏ | 5079/11952 [48:54<11:20:12, 5.94s/it]
43%|████▎ | 5080/11952 [49:00<11:21:36, 5.95s/it]
{'loss': 0.5026, 'learning_rate': 1.287341629537119e-05, 'epoch': 0.43}
+
43%|████▎ | 5080/11952 [49:00<11:21:36, 5.95s/it]
43%|████▎ | 5081/11952 [49:06<11:21:18, 5.95s/it]
{'loss': 0.471, 'learning_rate': 1.2870820566747633e-05, 'epoch': 0.43}
+
43%|████▎ | 5081/11952 [49:06<11:21:18, 5.95s/it]
43%|████▎ | 5082/11952 [49:12<11:16:43, 5.91s/it]
{'loss': 0.4873, 'learning_rate': 1.2868224627302952e-05, 'epoch': 0.43}
+
43%|████▎ | 5082/11952 [49:12<11:16:43, 5.91s/it]
43%|████▎ | 5083/11952 [49:18<11:18:06, 5.92s/it]
{'loss': 0.488, 'learning_rate': 1.2865628477227787e-05, 'epoch': 0.43}
+
43%|████▎ | 5083/11952 [49:18<11:18:06, 5.92s/it]
43%|████▎ | 5084/11952 [49:24<11:22:09, 5.96s/it]
{'loss': 0.4907, 'learning_rate': 1.2863032116712781e-05, 'epoch': 0.43}
+
43%|████▎ | 5084/11952 [49:24<11:22:09, 5.96s/it]
43%|████▎ | 5085/11952 [49:30<11:17:42, 5.92s/it]
{'loss': 0.4816, 'learning_rate': 1.2860435545948609e-05, 'epoch': 0.43}
+
43%|████▎ | 5085/11952 [49:30<11:17:42, 5.92s/it]
43%|████▎ | 5086/11952 [49:36<11:26:04, 6.00s/it]
{'loss': 0.4917, 'learning_rate': 1.2857838765125945e-05, 'epoch': 0.43}
+
43%|████▎ | 5086/11952 [49:36<11:26:04, 6.00s/it]
43%|████▎ | 5087/11952 [49:42<11:19:01, 5.93s/it]
{'loss': 0.4916, 'learning_rate': 1.285524177443549e-05, 'epoch': 0.43}
+
43%|████▎ | 5087/11952 [49:42<11:19:01, 5.93s/it]
43%|████▎ | 5088/11952 [49:47<11:07:14, 5.83s/it]
{'loss': 0.4771, 'learning_rate': 1.2852644574067955e-05, 'epoch': 0.43}
+
43%|████▎ | 5088/11952 [49:47<11:07:14, 5.83s/it]
43%|████▎ | 5089/11952 [49:53<11:14:11, 5.89s/it]
{'loss': 0.4911, 'learning_rate': 1.285004716421407e-05, 'epoch': 0.43}
+
43%|████▎ | 5089/11952 [49:53<11:14:11, 5.89s/it]
43%|████▎ | 5090/11952 [49:59<11:08:05, 5.84s/it]
{'loss': 0.4913, 'learning_rate': 1.2847449545064572e-05, 'epoch': 0.43}
+
43%|████▎ | 5090/11952 [49:59<11:08:05, 5.84s/it]
43%|████▎ | 5091/11952 [50:05<11:05:12, 5.82s/it]
{'loss': 0.4803, 'learning_rate': 1.2844851716810225e-05, 'epoch': 0.43}
+
43%|████▎ | 5091/11952 [50:05<11:05:12, 5.82s/it]
43%|████▎ | 5092/11952 [50:11<11:26:24, 6.00s/it]
{'loss': 0.4891, 'learning_rate': 1.2842253679641799e-05, 'epoch': 0.43}
+
43%|████▎ | 5092/11952 [50:11<11:26:24, 6.00s/it]
43%|████▎ | 5093/11952 [50:17<11:18:33, 5.94s/it]
{'loss': 0.4777, 'learning_rate': 1.2839655433750084e-05, 'epoch': 0.43}
+
43%|████▎ | 5093/11952 [50:17<11:18:33, 5.94s/it]
43%|████▎ | 5094/11952 [50:23<11:10:58, 5.87s/it]
{'loss': 0.4791, 'learning_rate': 1.2837056979325886e-05, 'epoch': 0.43}
+
43%|████▎ | 5094/11952 [50:23<11:10:58, 5.87s/it]
43%|████▎ | 5095/11952 [50:29<11:13:55, 5.90s/it]
{'loss': 0.4653, 'learning_rate': 1.2834458316560023e-05, 'epoch': 0.43}
+
43%|████▎ | 5095/11952 [50:29<11:13:55, 5.90s/it]
43%|████▎ | 5096/11952 [50:35<11:10:24, 5.87s/it]
{'loss': 0.4935, 'learning_rate': 1.2831859445643333e-05, 'epoch': 0.43}
+
43%|████▎ | 5096/11952 [50:35<11:10:24, 5.87s/it]
43%|████▎ | 5097/11952 [50:40<11:07:19, 5.84s/it]
{'loss': 0.5006, 'learning_rate': 1.282926036676666e-05, 'epoch': 0.43}
+
43%|████▎ | 5097/11952 [50:40<11:07:19, 5.84s/it]
43%|████▎ | 5098/11952 [50:46<11:05:20, 5.82s/it]
{'loss': 0.463, 'learning_rate': 1.2826661080120877e-05, 'epoch': 0.43}
+
43%|████▎ | 5098/11952 [50:46<11:05:20, 5.82s/it]
43%|████▎ | 5099/11952 [50:52<11:05:12, 5.82s/it]
{'loss': 0.4902, 'learning_rate': 1.282406158589686e-05, 'epoch': 0.43}
+
43%|████▎ | 5099/11952 [50:52<11:05:12, 5.82s/it]4 AutoResumeHook: Checking whether to suspend...
+062 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+ 7 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+5 AutoResumeHook: Checking whether to suspend...
+
43%|████▎ | 5100/11952 [50:58<10:57:16, 5.76s/it]1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4759, 'learning_rate': 1.2821461884285506e-05, 'epoch': 0.43}
+
43%|████▎ | 5100/11952 [50:58<10:57:16, 5.76s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
43%|████▎ | 5101/11952 [51:29<25:46:53, 13.55s/it]
{'loss': 0.4796, 'learning_rate': 1.2818861975477728e-05, 'epoch': 0.43}
+
43%|████▎ | 5101/11952 [51:29<25:46:53, 13.55s/it]
43%|████▎ | 5102/11952 [51:35<21:19:15, 11.21s/it]
{'loss': 0.4833, 'learning_rate': 1.2816261859664448e-05, 'epoch': 0.43}
+
43%|████▎ | 5102/11952 [51:35<21:19:15, 11.21s/it]
43%|████▎ | 5103/11952 [51:41<18:11:17, 9.56s/it]
{'loss': 0.4863, 'learning_rate': 1.2813661537036613e-05, 'epoch': 0.43}
+
43%|████▎ | 5103/11952 [51:41<18:11:17, 9.56s/it]
43%|████▎ | 5104/11952 [51:47<16:04:33, 8.45s/it]
{'loss': 0.4719, 'learning_rate': 1.2811061007785175e-05, 'epoch': 0.43}
+
43%|████▎ | 5104/11952 [51:47<16:04:33, 8.45s/it]
43%|████▎ | 5105/11952 [51:53<14:37:04, 7.69s/it]
{'loss': 0.4843, 'learning_rate': 1.2808460272101113e-05, 'epoch': 0.43}
+
43%|████▎ | 5105/11952 [51:53<14:37:04, 7.69s/it]
43%|████▎ | 5106/11952 [51:58<13:32:45, 7.12s/it]
{'loss': 0.4763, 'learning_rate': 1.280585933017541e-05, 'epoch': 0.43}
+
43%|████▎ | 5106/11952 [51:58<13:32:45, 7.12s/it]
43%|████▎ | 5107/11952 [52:04<12:52:34, 6.77s/it]
{'loss': 0.4812, 'learning_rate': 1.2803258182199064e-05, 'epoch': 0.43}
+
43%|████▎ | 5107/11952 [52:04<12:52:34, 6.77s/it]
43%|████▎ | 5108/11952 [52:10<12:24:45, 6.53s/it]
{'loss': 0.4878, 'learning_rate': 1.2800656828363098e-05, 'epoch': 0.43}
+
43%|████▎ | 5108/11952 [52:10<12:24:45, 6.53s/it]
43%|████▎ | 5109/11952 [52:16<11:54:58, 6.27s/it]
{'loss': 0.4949, 'learning_rate': 1.2798055268858544e-05, 'epoch': 0.43}
+
43%|████▎ | 5109/11952 [52:16<11:54:58, 6.27s/it]
43%|████▎ | 5110/11952 [52:22<11:39:00, 6.13s/it]
{'loss': 0.5089, 'learning_rate': 1.2795453503876449e-05, 'epoch': 0.43}
+
43%|████▎ | 5110/11952 [52:22<11:39:00, 6.13s/it]
43%|████▎ | 5111/11952 [52:28<11:31:13, 6.06s/it]
{'loss': 0.482, 'learning_rate': 1.2792851533607875e-05, 'epoch': 0.43}
+
43%|████▎ | 5111/11952 [52:28<11:31:13, 6.06s/it]
43%|████▎ | 5112/11952 [52:33<11:22:57, 5.99s/it]
{'loss': 0.5057, 'learning_rate': 1.2790249358243902e-05, 'epoch': 0.43}
+
43%|████▎ | 5112/11952 [52:33<11:22:57, 5.99s/it]
43%|████▎ | 5113/11952 [52:39<11:12:28, 5.90s/it]
{'loss': 0.5177, 'learning_rate': 1.2787646977975623e-05, 'epoch': 0.43}
+
43%|████▎ | 5113/11952 [52:39<11:12:28, 5.90s/it]
43%|████▎ | 5114/11952 [52:45<11:01:58, 5.81s/it]
{'loss': 0.461, 'learning_rate': 1.2785044392994142e-05, 'epoch': 0.43}
+
43%|████▎ | 5114/11952 [52:45<11:01:58, 5.81s/it]
43%|████▎ | 5115/11952 [52:51<11:05:00, 5.84s/it]
{'loss': 0.479, 'learning_rate': 1.2782441603490585e-05, 'epoch': 0.43}
+
43%|████▎ | 5115/11952 [52:51<11:05:00, 5.84s/it]
43%|████▎ | 5116/11952 [52:56<10:59:52, 5.79s/it]
{'loss': 0.5029, 'learning_rate': 1.277983860965609e-05, 'epoch': 0.43}
+
43%|████▎ | 5116/11952 [52:56<10:59:52, 5.79s/it]
43%|████▎ | 5117/11952 [53:02<11:07:03, 5.86s/it]
{'loss': 0.475, 'learning_rate': 1.277723541168181e-05, 'epoch': 0.43}
+
43%|████▎ | 5117/11952 [53:02<11:07:03, 5.86s/it]
43%|████▎ | 5118/11952 [53:08<11:03:42, 5.83s/it]
{'loss': 0.4754, 'learning_rate': 1.2774632009758911e-05, 'epoch': 0.43}
+
43%|████▎ | 5118/11952 [53:08<11:03:42, 5.83s/it]
43%|████▎ | 5119/11952 [53:14<10:56:39, 5.77s/it]
{'loss': 0.483, 'learning_rate': 1.2772028404078581e-05, 'epoch': 0.43}
+
43%|████▎ | 5119/11952 [53:14<10:56:39, 5.77s/it]
43%|████▎ | 5120/11952 [53:19<10:52:25, 5.73s/it]
{'loss': 0.4806, 'learning_rate': 1.2769424594832014e-05, 'epoch': 0.43}
+
43%|████▎ | 5120/11952 [53:19<10:52:25, 5.73s/it]
43%|████▎ | 5121/11952 [53:25<10:46:41, 5.68s/it]
{'loss': 0.4651, 'learning_rate': 1.2766820582210421e-05, 'epoch': 0.43}
+
43%|████▎ | 5121/11952 [53:25<10:46:41, 5.68s/it]
43%|████▎ | 5122/11952 [53:31<11:01:22, 5.81s/it]
{'loss': 0.4875, 'learning_rate': 1.2764216366405036e-05, 'epoch': 0.43}
+
43%|████▎ | 5122/11952 [53:31<11:01:22, 5.81s/it]
43%|████▎ | 5123/11952 [53:37<11:09:50, 5.89s/it]
{'loss': 0.4948, 'learning_rate': 1.2761611947607095e-05, 'epoch': 0.43}
+
43%|████▎ | 5123/11952 [53:37<11:09:50, 5.89s/it]
43%|████▎ | 5124/11952 [53:43<11:06:35, 5.86s/it]
{'loss': 0.4835, 'learning_rate': 1.2759007326007862e-05, 'epoch': 0.43}
+
43%|████▎ | 5124/11952 [53:43<11:06:35, 5.86s/it]
43%|████▎ | 5125/11952 [53:49<11:15:32, 5.94s/it]
{'loss': 0.4828, 'learning_rate': 1.2756402501798606e-05, 'epoch': 0.43}
+
43%|████▎ | 5125/11952 [53:49<11:15:32, 5.94s/it]
43%|████▎ | 5126/11952 [53:55<11:08:35, 5.88s/it]
{'loss': 0.4781, 'learning_rate': 1.2753797475170613e-05, 'epoch': 0.43}
+
43%|████▎ | 5126/11952 [53:55<11:08:35, 5.88s/it]
43%|████▎ | 5127/11952 [54:00<11:01:52, 5.82s/it]
{'loss': 0.4875, 'learning_rate': 1.275119224631519e-05, 'epoch': 0.43}
+
43%|████▎ | 5127/11952 [54:00<11:01:52, 5.82s/it]
43%|████▎ | 5128/11952 [54:06<10:52:43, 5.74s/it]
{'loss': 0.4688, 'learning_rate': 1.2748586815423646e-05, 'epoch': 0.43}
+
43%|████▎ | 5128/11952 [54:06<10:52:43, 5.74s/it]
43%|████▎ | 5129/11952 [54:12<11:01:09, 5.81s/it]
{'loss': 0.479, 'learning_rate': 1.2745981182687323e-05, 'epoch': 0.43}
+
43%|████▎ | 5129/11952 [54:12<11:01:09, 5.81s/it]
43%|████▎ | 5130/11952 [54:18<11:03:57, 5.84s/it]
{'loss': 0.4941, 'learning_rate': 1.2743375348297567e-05, 'epoch': 0.43}
+
43%|████▎ | 5130/11952 [54:18<11:03:57, 5.84s/it]
43%|████▎ | 5131/11952 [54:24<11:11:26, 5.91s/it]
{'loss': 0.5048, 'learning_rate': 1.274076931244573e-05, 'epoch': 0.43}
+
43%|████▎ | 5131/11952 [54:24<11:11:26, 5.91s/it]
43%|████▎ | 5132/11952 [54:30<11:18:27, 5.97s/it]
{'loss': 0.4627, 'learning_rate': 1.2738163075323198e-05, 'epoch': 0.43}
+
43%|████▎ | 5132/11952 [54:30<11:18:27, 5.97s/it]
43%|████▎ | 5133/11952 [54:36<11:13:35, 5.93s/it]
{'loss': 0.4784, 'learning_rate': 1.2735556637121356e-05, 'epoch': 0.43}
+
43%|████▎ | 5133/11952 [54:36<11:13:35, 5.93s/it]
43%|████▎ | 5134/11952 [54:42<11:07:35, 5.87s/it]
{'loss': 0.4883, 'learning_rate': 1.2732949998031612e-05, 'epoch': 0.43}
+
43%|████▎ | 5134/11952 [54:42<11:07:35, 5.87s/it]
43%|████▎ | 5135/11952 [54:47<11:05:43, 5.86s/it]
{'loss': 0.4992, 'learning_rate': 1.2730343158245389e-05, 'epoch': 0.43}
+
43%|████▎ | 5135/11952 [54:47<11:05:43, 5.86s/it]
43%|████▎ | 5136/11952 [54:53<10:59:54, 5.81s/it]
{'loss': 0.4715, 'learning_rate': 1.2727736117954122e-05, 'epoch': 0.43}
+
43%|████▎ | 5136/11952 [54:53<10:59:54, 5.81s/it]
43%|████▎ | 5137/11952 [54:59<11:01:23, 5.82s/it]
{'loss': 0.4769, 'learning_rate': 1.272512887734926e-05, 'epoch': 0.43}
+
43%|████▎ | 5137/11952 [54:59<11:01:23, 5.82s/it]
43%|████▎ | 5138/11952 [55:05<10:53:23, 5.75s/it]
{'loss': 0.5004, 'learning_rate': 1.2722521436622263e-05, 'epoch': 0.43}
+
43%|████▎ | 5138/11952 [55:05<10:53:23, 5.75s/it]
43%|████▎ | 5139/11952 [55:10<10:57:02, 5.79s/it]
{'loss': 0.4909, 'learning_rate': 1.2719913795964618e-05, 'epoch': 0.43}
+
43%|████▎ | 5139/11952 [55:10<10:57:02, 5.79s/it]
43%|████▎ | 5140/11952 [55:16<10:58:07, 5.80s/it]
{'loss': 0.4747, 'learning_rate': 1.271730595556782e-05, 'epoch': 0.43}
+
43%|████▎ | 5140/11952 [55:16<10:58:07, 5.80s/it]
43%|████▎ | 5141/11952 [55:22<10:50:51, 5.73s/it]
{'loss': 0.4969, 'learning_rate': 1.2714697915623374e-05, 'epoch': 0.43}
+
43%|████▎ | 5141/11952 [55:22<10:50:51, 5.73s/it]
43%|████▎ | 5142/11952 [55:28<10:51:24, 5.74s/it]
{'loss': 0.479, 'learning_rate': 1.2712089676322803e-05, 'epoch': 0.43}
+
43%|████▎ | 5142/11952 [55:28<10:51:24, 5.74s/it]
43%|████▎ | 5143/11952 [55:33<10:47:44, 5.71s/it]
{'loss': 0.4771, 'learning_rate': 1.2709481237857643e-05, 'epoch': 0.43}
+
43%|████▎ | 5143/11952 [55:33<10:47:44, 5.71s/it]
43%|████▎ | 5144/11952 [55:39<10:57:20, 5.79s/it]
{'loss': 0.5098, 'learning_rate': 1.2706872600419456e-05, 'epoch': 0.43}
+
43%|████▎ | 5144/11952 [55:39<10:57:20, 5.79s/it]
43%|████▎ | 5145/11952 [55:45<10:58:01, 5.80s/it]
{'loss': 0.4819, 'learning_rate': 1.2704263764199803e-05, 'epoch': 0.43}
+
43%|████▎ | 5145/11952 [55:45<10:58:01, 5.80s/it]
43%|████▎ | 5146/11952 [55:51<10:52:46, 5.75s/it]
{'loss': 0.4838, 'learning_rate': 1.2701654729390264e-05, 'epoch': 0.43}
+
43%|████▎ | 5146/11952 [55:51<10:52:46, 5.75s/it]
43%|████▎ | 5147/11952 [55:57<11:02:14, 5.84s/it]
{'loss': 0.4829, 'learning_rate': 1.2699045496182442e-05, 'epoch': 0.43}
+
43%|████▎ | 5147/11952 [55:57<11:02:14, 5.84s/it]
43%|████▎ | 5148/11952 [56:03<11:05:29, 5.87s/it]
{'loss': 0.4952, 'learning_rate': 1.2696436064767943e-05, 'epoch': 0.43}
+
43%|████▎ | 5148/11952 [56:03<11:05:29, 5.87s/it]
43%|████▎ | 5149/11952 [56:09<11:15:07, 5.95s/it]
{'loss': 0.4854, 'learning_rate': 1.2693826435338394e-05, 'epoch': 0.43}
+
43%|████▎ | 5149/11952 [56:09<11:15:07, 5.95s/it]4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 0AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
43%|████▎ | 5150/11952 [56:14<11:03:35, 5.85s/it]1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.483, 'learning_rate': 1.269121660808544e-05, 'epoch': 0.43}
+
43%|████▎ | 5150/11952 [56:14<11:03:35, 5.85s/it]
43%|████▎ | 5151/11952 [56:20<10:55:29, 5.78s/it]
{'loss': 0.4843, 'learning_rate': 1.2688606583200728e-05, 'epoch': 0.43}
+
43%|████▎ | 5151/11952 [56:20<10:55:29, 5.78s/it]
43%|████▎ | 5152/11952 [56:26<10:53:45, 5.77s/it]
{'loss': 0.4863, 'learning_rate': 1.2685996360875933e-05, 'epoch': 0.43}
+
43%|████▎ | 5152/11952 [56:26<10:53:45, 5.77s/it]
43%|████▎ | 5153/11952 [56:32<10:55:11, 5.78s/it]
{'loss': 0.4922, 'learning_rate': 1.2683385941302737e-05, 'epoch': 0.43}
+
43%|████▎ | 5153/11952 [56:32<10:55:11, 5.78s/it]
43%|████▎ | 5154/11952 [56:38<11:16:46, 5.97s/it]
{'loss': 0.4687, 'learning_rate': 1.2680775324672839e-05, 'epoch': 0.43}
+
43%|████▎ | 5154/11952 [56:38<11:16:46, 5.97s/it]
43%|████▎ | 5155/11952 [56:44<11:10:47, 5.92s/it]
{'loss': 0.494, 'learning_rate': 1.2678164511177948e-05, 'epoch': 0.43}
+
43%|████▎ | 5155/11952 [56:44<11:10:47, 5.92s/it]
43%|████▎ | 5156/11952 [56:50<11:06:13, 5.88s/it]
{'loss': 0.4872, 'learning_rate': 1.26755535010098e-05, 'epoch': 0.43}
+
43%|████▎ | 5156/11952 [56:50<11:06:13, 5.88s/it]
43%|████▎ | 5157/11952 [56:56<11:08:20, 5.90s/it]
{'loss': 0.4892, 'learning_rate': 1.267294229436013e-05, 'epoch': 0.43}
+
43%|████▎ | 5157/11952 [56:56<11:08:20, 5.90s/it]
43%|████▎ | 5158/11952 [57:02<11:16:07, 5.97s/it]
{'loss': 0.4867, 'learning_rate': 1.2670330891420694e-05, 'epoch': 0.43}
+
43%|████▎ | 5158/11952 [57:02<11:16:07, 5.97s/it]
43%|████▎ | 5159/11952 [57:07<11:03:31, 5.86s/it]
{'loss': 0.4676, 'learning_rate': 1.266771929238326e-05, 'epoch': 0.43}
+
43%|████▎ | 5159/11952 [57:07<11:03:31, 5.86s/it]
43%|████▎ | 5160/11952 [57:13<10:58:32, 5.82s/it]
{'loss': 0.4976, 'learning_rate': 1.2665107497439623e-05, 'epoch': 0.43}
+
43%|████▎ | 5160/11952 [57:13<10:58:32, 5.82s/it]
43%|████▎ | 5161/11952 [57:19<10:57:15, 5.81s/it]
{'loss': 0.4855, 'learning_rate': 1.2662495506781575e-05, 'epoch': 0.43}
+
43%|████▎ | 5161/11952 [57:19<10:57:15, 5.81s/it]
43%|████▎ | 5162/11952 [57:25<10:53:52, 5.78s/it]
{'loss': 0.4878, 'learning_rate': 1.265988332060093e-05, 'epoch': 0.43}
+
43%|████▎ | 5162/11952 [57:25<10:53:52, 5.78s/it]
43%|████▎ | 5163/11952 [57:31<11:03:27, 5.86s/it]
{'loss': 0.4841, 'learning_rate': 1.265727093908952e-05, 'epoch': 0.43}
+
43%|████▎ | 5163/11952 [57:31<11:03:27, 5.86s/it]
43%|████▎ | 5164/11952 [57:37<11:09:20, 5.92s/it]
{'loss': 0.4876, 'learning_rate': 1.265465836243918e-05, 'epoch': 0.43}
+
43%|████▎ | 5164/11952 [57:37<11:09:20, 5.92s/it]
43%|████▎ | 5165/11952 [57:42<11:00:40, 5.84s/it]
{'loss': 0.4905, 'learning_rate': 1.2652045590841774e-05, 'epoch': 0.43}
+
43%|████▎ | 5165/11952 [57:42<11:00:40, 5.84s/it]
43%|████▎ | 5166/11952 [57:48<11:06:11, 5.89s/it]
{'loss': 0.4761, 'learning_rate': 1.2649432624489171e-05, 'epoch': 0.43}
+
43%|████▎ | 5166/11952 [57:48<11:06:11, 5.89s/it]
43%|████▎ | 5167/11952 [57:54<11:03:10, 5.86s/it]
{'loss': 0.4716, 'learning_rate': 1.2646819463573257e-05, 'epoch': 0.43}
+
43%|████▎ | 5167/11952 [57:54<11:03:10, 5.86s/it]
43%|████▎ | 5168/11952 [58:00<11:10:40, 5.93s/it]
{'loss': 0.4791, 'learning_rate': 1.264420610828593e-05, 'epoch': 0.43}
+
43%|████▎ | 5168/11952 [58:00<11:10:40, 5.93s/it]
43%|████▎ | 5169/11952 [58:06<11:07:08, 5.90s/it]
{'loss': 0.4844, 'learning_rate': 1.2641592558819102e-05, 'epoch': 0.43}
+
43%|████▎ | 5169/11952 [58:06<11:07:08, 5.90s/it]
43%|████▎ | 5170/11952 [58:12<11:15:03, 5.97s/it]
{'loss': 0.4864, 'learning_rate': 1.2638978815364705e-05, 'epoch': 0.43}
+
43%|████▎ | 5170/11952 [58:12<11:15:03, 5.97s/it]
43%|████▎ | 5171/11952 [58:18<11:09:18, 5.92s/it]
{'loss': 0.4723, 'learning_rate': 1.2636364878114682e-05, 'epoch': 0.43}
+
43%|████▎ | 5171/11952 [58:18<11:09:18, 5.92s/it]
43%|████▎ | 5172/11952 [58:24<11:02:26, 5.86s/it]
{'loss': 0.4821, 'learning_rate': 1.2633750747260985e-05, 'epoch': 0.43}
+
43%|████▎ | 5172/11952 [58:24<11:02:26, 5.86s/it]
43%|████▎ | 5173/11952 [58:30<11:07:37, 5.91s/it]
{'loss': 0.4819, 'learning_rate': 1.263113642299559e-05, 'epoch': 0.43}
+
43%|████▎ | 5173/11952 [58:30<11:07:37, 5.91s/it]
43%|████▎ | 5174/11952 [58:35<11:01:48, 5.86s/it]
{'loss': 0.4784, 'learning_rate': 1.2628521905510476e-05, 'epoch': 0.43}
+
43%|████▎ | 5174/11952 [58:35<11:01:48, 5.86s/it]
43%|████▎ | 5175/11952 [58:41<10:58:41, 5.83s/it]
{'loss': 0.4812, 'learning_rate': 1.2625907194997652e-05, 'epoch': 0.43}
+
43%|████▎ | 5175/11952 [58:41<10:58:41, 5.83s/it]
43%|████▎ | 5176/11952 [58:47<11:02:34, 5.87s/it]
{'loss': 0.4735, 'learning_rate': 1.2623292291649119e-05, 'epoch': 0.43}
+
43%|████▎ | 5176/11952 [58:47<11:02:34, 5.87s/it]
43%|████▎ | 5177/11952 [58:53<11:04:08, 5.88s/it]
{'loss': 0.4846, 'learning_rate': 1.2620677195656916e-05, 'epoch': 0.43}
+
43%|████▎ | 5177/11952 [58:53<11:04:08, 5.88s/it]
43%|████▎ | 5178/11952 [58:59<10:57:11, 5.82s/it]
{'loss': 0.5012, 'learning_rate': 1.261806190721308e-05, 'epoch': 0.43}
+
43%|████▎ | 5178/11952 [58:59<10:57:11, 5.82s/it]
43%|████▎ | 5179/11952 [59:05<11:05:46, 5.90s/it]
{'loss': 0.5073, 'learning_rate': 1.2615446426509663e-05, 'epoch': 0.43}
+
43%|████▎ | 5179/11952 [59:05<11:05:46, 5.90s/it]
43%|████▎ | 5180/11952 [59:11<11:16:17, 5.99s/it]
{'loss': 0.4963, 'learning_rate': 1.261283075373874e-05, 'epoch': 0.43}
+
43%|████▎ | 5180/11952 [59:11<11:16:17, 5.99s/it]
43%|████▎ | 5181/11952 [59:17<11:06:47, 5.91s/it]
{'loss': 0.4903, 'learning_rate': 1.2610214889092399e-05, 'epoch': 0.43}
+
43%|████▎ | 5181/11952 [59:17<11:06:47, 5.91s/it]
43%|████▎ | 5182/11952 [59:23<11:04:56, 5.89s/it]
{'loss': 0.485, 'learning_rate': 1.2607598832762728e-05, 'epoch': 0.43}
+
43%|████▎ | 5182/11952 [59:23<11:04:56, 5.89s/it]
43%|████▎ | 5183/11952 [59:28<10:55:24, 5.81s/it]
{'loss': 0.4773, 'learning_rate': 1.2604982584941846e-05, 'epoch': 0.43}
+
43%|████▎ | 5183/11952 [59:28<10:55:24, 5.81s/it]
43%|████▎ | 5184/11952 [59:34<10:53:40, 5.80s/it]
{'loss': 0.4819, 'learning_rate': 1.2602366145821879e-05, 'epoch': 0.43}
+
43%|████▎ | 5184/11952 [59:34<10:53:40, 5.80s/it]
43%|████▎ | 5185/11952 [59:40<10:52:23, 5.78s/it]
{'loss': 0.4781, 'learning_rate': 1.2599749515594964e-05, 'epoch': 0.43}
+
43%|████▎ | 5185/11952 [59:40<10:52:23, 5.78s/it]
43%|████▎ | 5186/11952 [59:45<10:43:42, 5.71s/it]
{'loss': 0.4648, 'learning_rate': 1.2597132694453258e-05, 'epoch': 0.43}
+
43%|████▎ | 5186/11952 [59:45<10:43:42, 5.71s/it]
43%|████▎ | 5187/11952 [59:51<10:57:30, 5.83s/it]
{'loss': 0.4819, 'learning_rate': 1.259451568258893e-05, 'epoch': 0.43}
+
43%|████▎ | 5187/11952 [59:51<10:57:30, 5.83s/it]
43%|████▎ | 5188/11952 [59:57<11:05:03, 5.90s/it]
{'loss': 0.5044, 'learning_rate': 1.2591898480194165e-05, 'epoch': 0.43}
+
43%|████▎ | 5188/11952 [59:57<11:05:03, 5.90s/it]
43%|████▎ | 5189/11952 [1:00:03<10:54:03, 5.80s/it]
{'loss': 0.4943, 'learning_rate': 1.2589281087461152e-05, 'epoch': 0.43}
+
43%|████▎ | 5189/11952 [1:00:03<10:54:03, 5.80s/it]
43%|████▎ | 5190/11952 [1:00:09<11:02:26, 5.88s/it]
{'loss': 0.4827, 'learning_rate': 1.2586663504582104e-05, 'epoch': 0.43}
+
43%|████▎ | 5190/11952 [1:00:09<11:02:26, 5.88s/it]
43%|████▎ | 5191/11952 [1:00:15<11:03:30, 5.89s/it]
{'loss': 0.4828, 'learning_rate': 1.258404573174925e-05, 'epoch': 0.43}
+
43%|████▎ | 5191/11952 [1:00:15<11:03:30, 5.89s/it]
43%|████▎ | 5192/11952 [1:00:21<11:03:50, 5.89s/it]
{'loss': 0.4685, 'learning_rate': 1.2581427769154826e-05, 'epoch': 0.43}
+
43%|████▎ | 5192/11952 [1:00:21<11:03:50, 5.89s/it]
43%|████▎ | 5193/11952 [1:00:27<10:54:32, 5.81s/it]
{'loss': 0.4819, 'learning_rate': 1.2578809616991081e-05, 'epoch': 0.43}
+
43%|████▎ | 5193/11952 [1:00:27<10:54:32, 5.81s/it]
43%|████▎ | 5194/11952 [1:00:33<11:13:39, 5.98s/it]
{'loss': 0.4996, 'learning_rate': 1.2576191275450287e-05, 'epoch': 0.43}
+
43%|████▎ | 5194/11952 [1:00:33<11:13:39, 5.98s/it]
43%|████▎ | 5195/11952 [1:00:39<11:17:16, 6.01s/it]
{'loss': 0.4831, 'learning_rate': 1.2573572744724718e-05, 'epoch': 0.43}
+
43%|████▎ | 5195/11952 [1:00:39<11:17:16, 6.01s/it]
43%|████▎ | 5196/11952 [1:00:45<11:08:53, 5.94s/it]
{'loss': 0.499, 'learning_rate': 1.2570954025006672e-05, 'epoch': 0.43}
+
43%|████▎ | 5196/11952 [1:00:45<11:08:53, 5.94s/it]
43%|████▎ | 5197/11952 [1:00:51<11:06:35, 5.92s/it]
{'loss': 0.4894, 'learning_rate': 1.2568335116488457e-05, 'epoch': 0.43}
+
43%|████▎ | 5197/11952 [1:00:51<11:06:35, 5.92s/it]
43%|████▎ | 5198/11952 [1:00:56<11:03:30, 5.89s/it]
{'loss': 0.4802, 'learning_rate': 1.2565716019362393e-05, 'epoch': 0.43}
+
43%|████▎ | 5198/11952 [1:00:56<11:03:30, 5.89s/it]
43%|████▎ | 5199/11952 [1:01:03<11:09:48, 5.95s/it]
{'loss': 0.479, 'learning_rate': 1.2563096733820816e-05, 'epoch': 0.43}
+
43%|████▎ | 5199/11952 [1:01:03<11:09:48, 5.95s/it]7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
44%|████▎ | 5200/11952 [1:01:08<11:04:48, 5.91s/it]1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4739, 'learning_rate': 1.2560477260056072e-05, 'epoch': 0.44}
+
44%|████▎ | 5200/11952 [1:01:08<11:04:48, 5.91s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
44%|████▎ | 5201/11952 [1:01:39<24:57:34, 13.31s/it]
{'loss': 0.4864, 'learning_rate': 1.2557857598260532e-05, 'epoch': 0.44}
+
44%|████▎ | 5201/11952 [1:01:39<24:57:34, 13.31s/it]
44%|████▎ | 5202/11952 [1:01:45<20:51:16, 11.12s/it]
{'loss': 0.4791, 'learning_rate': 1.255523774862657e-05, 'epoch': 0.44}
+
44%|████▎ | 5202/11952 [1:01:45<20:51:16, 11.12s/it]
44%|████▎ | 5203/11952 [1:01:51<18:01:00, 9.61s/it]
{'loss': 0.4939, 'learning_rate': 1.2552617711346572e-05, 'epoch': 0.44}
+
44%|████▎ | 5203/11952 [1:01:51<18:01:00, 9.61s/it]
44%|████▎ | 5204/11952 [1:01:57<16:01:47, 8.55s/it]
{'loss': 0.4796, 'learning_rate': 1.254999748661295e-05, 'epoch': 0.44}
+
44%|████▎ | 5204/11952 [1:01:57<16:01:47, 8.55s/it]
44%|████▎ | 5205/11952 [1:02:03<14:34:20, 7.78s/it]
{'loss': 0.4678, 'learning_rate': 1.2547377074618114e-05, 'epoch': 0.44}
+
44%|████▎ | 5205/11952 [1:02:03<14:34:20, 7.78s/it]
44%|████▎ | 5206/11952 [1:02:09<13:33:50, 7.24s/it]
{'loss': 0.4995, 'learning_rate': 1.2544756475554505e-05, 'epoch': 0.44}
+
44%|████▎ | 5206/11952 [1:02:09<13:33:50, 7.24s/it]
44%|████▎ | 5207/11952 [1:02:15<12:46:53, 6.82s/it]
{'loss': 0.483, 'learning_rate': 1.2542135689614565e-05, 'epoch': 0.44}
+
44%|████▎ | 5207/11952 [1:02:15<12:46:53, 6.82s/it]
44%|████▎ | 5208/11952 [1:02:21<12:14:24, 6.53s/it]
{'loss': 0.4679, 'learning_rate': 1.2539514716990753e-05, 'epoch': 0.44}
+
44%|████▎ | 5208/11952 [1:02:21<12:14:24, 6.53s/it]
44%|████▎ | 5209/11952 [1:02:27<11:53:14, 6.35s/it]
{'loss': 0.4865, 'learning_rate': 1.2536893557875543e-05, 'epoch': 0.44}
+
44%|████▎ | 5209/11952 [1:02:27<11:53:14, 6.35s/it]
44%|████▎ | 5210/11952 [1:02:33<11:40:18, 6.23s/it]
{'loss': 0.4795, 'learning_rate': 1.253427221246142e-05, 'epoch': 0.44}
+
44%|████▎ | 5210/11952 [1:02:33<11:40:18, 6.23s/it]
44%|████▎ | 5211/11952 [1:02:38<11:23:23, 6.08s/it]
{'loss': 0.4777, 'learning_rate': 1.2531650680940888e-05, 'epoch': 0.44}
+
44%|████▎ | 5211/11952 [1:02:38<11:23:23, 6.08s/it]
44%|████▎ | 5212/11952 [1:02:44<11:08:34, 5.95s/it]
{'loss': 0.4953, 'learning_rate': 1.252902896350646e-05, 'epoch': 0.44}
+
44%|████▎ | 5212/11952 [1:02:44<11:08:34, 5.95s/it]
44%|████▎ | 5213/11952 [1:02:50<11:06:34, 5.93s/it]
{'loss': 0.5058, 'learning_rate': 1.252640706035066e-05, 'epoch': 0.44}
+
44%|████▎ | 5213/11952 [1:02:50<11:06:34, 5.93s/it]
44%|████▎ | 5214/11952 [1:02:56<11:04:36, 5.92s/it]
{'loss': 0.4991, 'learning_rate': 1.2523784971666039e-05, 'epoch': 0.44}
+
44%|████▎ | 5214/11952 [1:02:56<11:04:36, 5.92s/it]
44%|████▎ | 5215/11952 [1:03:02<11:10:01, 5.97s/it]
{'loss': 0.4984, 'learning_rate': 1.2521162697645144e-05, 'epoch': 0.44}
+
44%|████▎ | 5215/11952 [1:03:02<11:10:01, 5.97s/it]
44%|████▎ | 5216/11952 [1:03:08<10:58:13, 5.86s/it]
{'loss': 0.4979, 'learning_rate': 1.251854023848055e-05, 'epoch': 0.44}
+
44%|████▎ | 5216/11952 [1:03:08<10:58:13, 5.86s/it]
44%|████▎ | 5217/11952 [1:03:13<10:52:03, 5.81s/it]
{'loss': 0.4866, 'learning_rate': 1.251591759436483e-05, 'epoch': 0.44}
+
44%|████▎ | 5217/11952 [1:03:13<10:52:03, 5.81s/it]
44%|████▎ | 5218/11952 [1:03:19<10:48:45, 5.78s/it]
{'loss': 0.4815, 'learning_rate': 1.2513294765490593e-05, 'epoch': 0.44}
+
44%|████▎ | 5218/11952 [1:03:19<10:48:45, 5.78s/it]
44%|████▎ | 5219/11952 [1:03:25<10:46:29, 5.76s/it]
{'loss': 0.4922, 'learning_rate': 1.2510671752050441e-05, 'epoch': 0.44}
+
44%|████▎ | 5219/11952 [1:03:25<10:46:29, 5.76s/it]
44%|████▎ | 5220/11952 [1:03:30<10:47:05, 5.77s/it]
{'loss': 0.4619, 'learning_rate': 1.2508048554236996e-05, 'epoch': 0.44}
+
44%|████▎ | 5220/11952 [1:03:30<10:47:05, 5.77s/it]
44%|████▎ | 5221/11952 [1:03:36<10:45:22, 5.75s/it]
{'loss': 0.4701, 'learning_rate': 1.2505425172242895e-05, 'epoch': 0.44}
+
44%|████▎ | 5221/11952 [1:03:36<10:45:22, 5.75s/it]
44%|████▎ | 5222/11952 [1:03:42<10:55:53, 5.85s/it]
{'loss': 0.4784, 'learning_rate': 1.2502801606260792e-05, 'epoch': 0.44}
+
44%|████▎ | 5222/11952 [1:03:42<10:55:53, 5.85s/it]
44%|████▎ | 5223/11952 [1:03:48<10:50:57, 5.80s/it]
{'loss': 0.4772, 'learning_rate': 1.2500177856483351e-05, 'epoch': 0.44}
+
44%|████▎ | 5223/11952 [1:03:48<10:50:57, 5.80s/it]
44%|████▎ | 5224/11952 [1:03:54<11:01:03, 5.90s/it]
{'loss': 0.4912, 'learning_rate': 1.2497553923103247e-05, 'epoch': 0.44}
+
44%|████▎ | 5224/11952 [1:03:54<11:01:03, 5.90s/it]
44%|████▎ | 5225/11952 [1:04:00<11:01:30, 5.90s/it]
{'loss': 0.4981, 'learning_rate': 1.249492980631317e-05, 'epoch': 0.44}
+
44%|████▎ | 5225/11952 [1:04:00<11:01:30, 5.90s/it]
44%|████▎ | 5226/11952 [1:04:06<10:55:45, 5.85s/it]
{'loss': 0.4649, 'learning_rate': 1.2492305506305824e-05, 'epoch': 0.44}
+
44%|████▎ | 5226/11952 [1:04:06<10:55:45, 5.85s/it]
44%|████▎ | 5227/11952 [1:04:12<10:56:29, 5.86s/it]
{'loss': 0.4915, 'learning_rate': 1.2489681023273927e-05, 'epoch': 0.44}
+
44%|████▎ | 5227/11952 [1:04:12<10:56:29, 5.86s/it]
44%|████▎ | 5228/11952 [1:04:17<10:59:10, 5.88s/it]
{'loss': 0.4691, 'learning_rate': 1.2487056357410215e-05, 'epoch': 0.44}
+
44%|████▎ | 5228/11952 [1:04:17<10:59:10, 5.88s/it]
44%|████▍ | 5229/11952 [1:04:23<10:53:38, 5.83s/it]
{'loss': 0.4756, 'learning_rate': 1.2484431508907429e-05, 'epoch': 0.44}
+
44%|████▍ | 5229/11952 [1:04:23<10:53:38, 5.83s/it]
44%|████▍ | 5230/11952 [1:04:29<10:56:50, 5.86s/it]
{'loss': 0.4938, 'learning_rate': 1.2481806477958323e-05, 'epoch': 0.44}
+
44%|████▍ | 5230/11952 [1:04:29<10:56:50, 5.86s/it]
44%|████▍ | 5231/11952 [1:04:35<11:01:21, 5.90s/it]
{'loss': 0.4832, 'learning_rate': 1.247918126475567e-05, 'epoch': 0.44}
+
44%|████▍ | 5231/11952 [1:04:35<11:01:21, 5.90s/it]
44%|████▍ | 5232/11952 [1:04:41<10:55:06, 5.85s/it]
{'loss': 0.4856, 'learning_rate': 1.2476555869492262e-05, 'epoch': 0.44}
+
44%|████▍ | 5232/11952 [1:04:41<10:55:06, 5.85s/it]
44%|████▍ | 5233/11952 [1:04:47<10:53:57, 5.84s/it]
{'loss': 0.4804, 'learning_rate': 1.2473930292360889e-05, 'epoch': 0.44}
+
44%|████▍ | 5233/11952 [1:04:47<10:53:57, 5.84s/it]
44%|████▍ | 5234/11952 [1:04:53<11:00:39, 5.90s/it]
{'loss': 0.5037, 'learning_rate': 1.2471304533554364e-05, 'epoch': 0.44}
+
44%|████▍ | 5234/11952 [1:04:53<11:00:39, 5.90s/it]
44%|████▍ | 5235/11952 [1:04:59<10:58:04, 5.88s/it]
{'loss': 0.4744, 'learning_rate': 1.2468678593265518e-05, 'epoch': 0.44}
+
44%|████▍ | 5235/11952 [1:04:59<10:58:04, 5.88s/it]
44%|████▍ | 5236/11952 [1:05:04<10:56:53, 5.87s/it]
{'loss': 0.4723, 'learning_rate': 1.2466052471687178e-05, 'epoch': 0.44}
+
44%|████▍ | 5236/11952 [1:05:04<10:56:53, 5.87s/it]
44%|████▍ | 5237/11952 [1:05:10<11:03:01, 5.92s/it]
{'loss': 0.4755, 'learning_rate': 1.2463426169012204e-05, 'epoch': 0.44}
+
44%|████▍ | 5237/11952 [1:05:10<11:03:01, 5.92s/it]
44%|████▍ | 5238/11952 [1:05:17<11:08:40, 5.98s/it]
{'loss': 0.4816, 'learning_rate': 1.2460799685433457e-05, 'epoch': 0.44}
+
44%|████▍ | 5238/11952 [1:05:17<11:08:40, 5.98s/it]
44%|████▍ | 5239/11952 [1:05:23<11:16:56, 6.05s/it]
{'loss': 0.4794, 'learning_rate': 1.245817302114382e-05, 'epoch': 0.44}
+
44%|████▍ | 5239/11952 [1:05:23<11:16:56, 6.05s/it]
44%|████▍ | 5240/11952 [1:05:28<11:05:06, 5.95s/it]
{'loss': 0.4817, 'learning_rate': 1.2455546176336177e-05, 'epoch': 0.44}
+
44%|████▍ | 5240/11952 [1:05:28<11:05:06, 5.95s/it]
44%|████▍ | 5241/11952 [1:05:34<11:07:13, 5.97s/it]
{'loss': 0.5024, 'learning_rate': 1.2452919151203439e-05, 'epoch': 0.44}
+
44%|████▍ | 5241/11952 [1:05:34<11:07:13, 5.97s/it]
44%|████▍ | 5242/11952 [1:05:40<11:04:24, 5.94s/it]
{'loss': 0.4645, 'learning_rate': 1.245029194593852e-05, 'epoch': 0.44}
+
44%|████▍ | 5242/11952 [1:05:40<11:04:24, 5.94s/it]
44%|████▍ | 5243/11952 [1:05:46<11:07:26, 5.97s/it]
{'loss': 0.4934, 'learning_rate': 1.2447664560734352e-05, 'epoch': 0.44}
+
44%|████▍ | 5243/11952 [1:05:46<11:07:26, 5.97s/it]
44%|████▍ | 5244/11952 [1:05:52<11:01:35, 5.92s/it]
{'loss': 0.4699, 'learning_rate': 1.2445036995783876e-05, 'epoch': 0.44}
+
44%|████▍ | 5244/11952 [1:05:52<11:01:35, 5.92s/it]
44%|████▍ | 5245/11952 [1:05:58<10:58:32, 5.89s/it]
{'loss': 0.4868, 'learning_rate': 1.2442409251280058e-05, 'epoch': 0.44}
+
44%|████▍ | 5245/11952 [1:05:58<10:58:32, 5.89s/it]
44%|████▍ | 5246/11952 [1:06:04<10:57:45, 5.89s/it]
{'loss': 0.4947, 'learning_rate': 1.2439781327415858e-05, 'epoch': 0.44}
+
44%|████▍ | 5246/11952 [1:06:04<10:57:45, 5.89s/it]
44%|████▍ | 5247/11952 [1:06:10<10:57:50, 5.89s/it]
{'loss': 0.4851, 'learning_rate': 1.2437153224384269e-05, 'epoch': 0.44}
+
44%|████▍ | 5247/11952 [1:06:10<10:57:50, 5.89s/it]
44%|████▍ | 5248/11952 [1:06:16<10:59:53, 5.91s/it]
{'loss': 0.5058, 'learning_rate': 1.2434524942378283e-05, 'epoch': 0.44}
+
44%|████▍ | 5248/11952 [1:06:16<10:59:53, 5.91s/it]
44%|████▍ | 5249/11952 [1:06:21<10:54:14, 5.86s/it]
{'loss': 0.4728, 'learning_rate': 1.2431896481590912e-05, 'epoch': 0.44}
+
44%|████▍ | 5249/11952 [1:06:21<10:54:14, 5.86s/it]7 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...2
+AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+51 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
44%|████▍ | 5250/11952 [1:06:27<10:53:42, 5.85s/it]
{'loss': 0.4873, 'learning_rate': 1.2429267842215181e-05, 'epoch': 0.44}
+
44%|████▍ | 5250/11952 [1:06:27<10:53:42, 5.85s/it]
44%|████▍ | 5251/11952 [1:06:33<10:45:07, 5.78s/it]
{'loss': 0.4701, 'learning_rate': 1.2426639024444118e-05, 'epoch': 0.44}
+
44%|████▍ | 5251/11952 [1:06:33<10:45:07, 5.78s/it]
44%|████▍ | 5252/11952 [1:06:39<10:56:35, 5.88s/it]
{'loss': 0.4963, 'learning_rate': 1.2424010028470779e-05, 'epoch': 0.44}
+
44%|████▍ | 5252/11952 [1:06:39<10:56:35, 5.88s/it]
44%|████▍ | 5253/11952 [1:06:45<11:04:13, 5.95s/it]
{'loss': 0.501, 'learning_rate': 1.242138085448823e-05, 'epoch': 0.44}
+
44%|████▍ | 5253/11952 [1:06:45<11:04:13, 5.95s/it]
44%|████▍ | 5254/11952 [1:06:51<10:52:13, 5.84s/it]
{'loss': 0.4718, 'learning_rate': 1.2418751502689537e-05, 'epoch': 0.44}
+
44%|████▍ | 5254/11952 [1:06:51<10:52:13, 5.84s/it]
44%|████▍ | 5255/11952 [1:06:57<10:58:09, 5.90s/it]
{'loss': 0.5091, 'learning_rate': 1.24161219732678e-05, 'epoch': 0.44}
+
44%|████▍ | 5255/11952 [1:06:57<10:58:09, 5.90s/it]
44%|████▍ | 5256/11952 [1:07:03<11:02:43, 5.94s/it]
{'loss': 0.493, 'learning_rate': 1.241349226641611e-05, 'epoch': 0.44}
+
44%|████▍ | 5256/11952 [1:07:03<11:02:43, 5.94s/it]
44%|████▍ | 5257/11952 [1:07:09<10:56:53, 5.89s/it]
{'loss': 0.4905, 'learning_rate': 1.2410862382327587e-05, 'epoch': 0.44}
+
44%|████▍ | 5257/11952 [1:07:09<10:56:53, 5.89s/it]
44%|████▍ | 5258/11952 [1:07:15<11:00:42, 5.92s/it]
{'loss': 0.4691, 'learning_rate': 1.240823232119536e-05, 'epoch': 0.44}
+
44%|████▍ | 5258/11952 [1:07:15<11:00:42, 5.92s/it]
44%|████▍ | 5259/11952 [1:07:20<10:56:41, 5.89s/it]
{'loss': 0.4941, 'learning_rate': 1.2405602083212567e-05, 'epoch': 0.44}
+
44%|████▍ | 5259/11952 [1:07:20<10:56:41, 5.89s/it]
44%|████▍ | 5260/11952 [1:07:26<11:03:39, 5.95s/it]
{'loss': 0.4871, 'learning_rate': 1.2402971668572364e-05, 'epoch': 0.44}
+
44%|████▍ | 5260/11952 [1:07:26<11:03:39, 5.95s/it]
44%|████▍ | 5261/11952 [1:07:32<11:04:18, 5.96s/it]
{'loss': 0.4755, 'learning_rate': 1.2400341077467912e-05, 'epoch': 0.44}
+
44%|████▍ | 5261/11952 [1:07:32<11:04:18, 5.96s/it]
44%|████▍ | 5262/11952 [1:07:39<11:21:29, 6.11s/it]
{'loss': 0.4886, 'learning_rate': 1.2397710310092396e-05, 'epoch': 0.44}
+
44%|████▍ | 5262/11952 [1:07:39<11:21:29, 6.11s/it]
44%|████▍ | 5263/11952 [1:07:45<11:28:25, 6.18s/it]
{'loss': 0.5008, 'learning_rate': 1.2395079366639011e-05, 'epoch': 0.44}
+
44%|████▍ | 5263/11952 [1:07:45<11:28:25, 6.18s/it]
44%|████▍ | 5264/11952 [1:07:51<11:16:33, 6.07s/it]
{'loss': 0.4723, 'learning_rate': 1.2392448247300959e-05, 'epoch': 0.44}
+
44%|████▍ | 5264/11952 [1:07:51<11:16:33, 6.07s/it]
44%|████▍ | 5265/11952 [1:07:57<11:07:30, 5.99s/it]
{'loss': 0.4819, 'learning_rate': 1.2389816952271456e-05, 'epoch': 0.44}
+
44%|████▍ | 5265/11952 [1:07:57<11:07:30, 5.99s/it]
44%|████▍ | 5266/11952 [1:08:03<10:59:08, 5.92s/it]
{'loss': 0.4801, 'learning_rate': 1.238718548174374e-05, 'epoch': 0.44}
+
44%|████▍ | 5266/11952 [1:08:03<10:59:08, 5.92s/it]
44%|████▍ | 5267/11952 [1:08:09<11:02:13, 5.94s/it]
{'loss': 0.5106, 'learning_rate': 1.2384553835911049e-05, 'epoch': 0.44}
+
44%|████▍ | 5267/11952 [1:08:09<11:02:13, 5.94s/it]
44%|████▍ | 5268/11952 [1:08:15<11:14:44, 6.06s/it]
{'loss': 0.5061, 'learning_rate': 1.2381922014966641e-05, 'epoch': 0.44}
+
44%|████▍ | 5268/11952 [1:08:15<11:14:44, 6.06s/it]
44%|████▍ | 5269/11952 [1:08:21<11:12:10, 6.03s/it]
{'loss': 0.4961, 'learning_rate': 1.237929001910379e-05, 'epoch': 0.44}
+
44%|████▍ | 5269/11952 [1:08:21<11:12:10, 6.03s/it]
44%|████▍ | 5270/11952 [1:08:27<11:10:25, 6.02s/it]
{'loss': 0.4996, 'learning_rate': 1.2376657848515774e-05, 'epoch': 0.44}
+
44%|████▍ | 5270/11952 [1:08:27<11:10:25, 6.02s/it]
44%|████▍ | 5271/11952 [1:08:33<11:16:55, 6.08s/it]
{'loss': 0.4873, 'learning_rate': 1.237402550339589e-05, 'epoch': 0.44}
+
44%|████▍ | 5271/11952 [1:08:33<11:16:55, 6.08s/it]
44%|████▍ | 5272/11952 [1:08:39<11:11:51, 6.03s/it]
{'loss': 0.4964, 'learning_rate': 1.2371392983937449e-05, 'epoch': 0.44}
+
44%|████▍ | 5272/11952 [1:08:39<11:11:51, 6.03s/it]
44%|████▍ | 5273/11952 [1:08:45<11:05:00, 5.97s/it]
{'loss': 0.493, 'learning_rate': 1.2368760290333771e-05, 'epoch': 0.44}
+
44%|████▍ | 5273/11952 [1:08:45<11:05:00, 5.97s/it]
44%|████▍ | 5274/11952 [1:08:51<10:54:49, 5.88s/it]
{'loss': 0.4932, 'learning_rate': 1.2366127422778192e-05, 'epoch': 0.44}
+
44%|████▍ | 5274/11952 [1:08:51<10:54:49, 5.88s/it]
44%|████▍ | 5275/11952 [1:08:56<10:52:45, 5.87s/it]
{'loss': 0.4952, 'learning_rate': 1.2363494381464052e-05, 'epoch': 0.44}
+
44%|████▍ | 5275/11952 [1:08:56<10:52:45, 5.87s/it]
44%|████▍ | 5276/11952 [1:09:02<10:48:53, 5.83s/it]
{'loss': 0.4878, 'learning_rate': 1.2360861166584717e-05, 'epoch': 0.44}
+
44%|████▍ | 5276/11952 [1:09:02<10:48:53, 5.83s/it]
44%|████▍ | 5277/11952 [1:09:08<10:58:17, 5.92s/it]
{'loss': 0.4842, 'learning_rate': 1.2358227778333556e-05, 'epoch': 0.44}
+
44%|████▍ | 5277/11952 [1:09:08<10:58:17, 5.92s/it]
44%|████▍ | 5278/11952 [1:09:14<10:55:52, 5.90s/it]
{'loss': 0.4739, 'learning_rate': 1.2355594216903956e-05, 'epoch': 0.44}
+
44%|████▍ | 5278/11952 [1:09:14<10:55:52, 5.90s/it]
44%|████▍ | 5279/11952 [1:09:20<10:42:29, 5.78s/it]
{'loss': 0.4898, 'learning_rate': 1.2352960482489317e-05, 'epoch': 0.44}
+
44%|████▍ | 5279/11952 [1:09:20<10:42:29, 5.78s/it]
44%|████▍ | 5280/11952 [1:09:25<10:41:56, 5.77s/it]
{'loss': 0.45, 'learning_rate': 1.2350326575283047e-05, 'epoch': 0.44}
+
44%|████▍ | 5280/11952 [1:09:25<10:41:56, 5.77s/it]
44%|████▍ | 5281/11952 [1:09:31<10:49:33, 5.84s/it]
{'loss': 0.4845, 'learning_rate': 1.2347692495478565e-05, 'epoch': 0.44}
+
44%|████▍ | 5281/11952 [1:09:31<10:49:33, 5.84s/it]
44%|████▍ | 5282/11952 [1:09:37<10:39:57, 5.76s/it]
{'loss': 0.4905, 'learning_rate': 1.2345058243269314e-05, 'epoch': 0.44}
+
44%|████▍ | 5282/11952 [1:09:37<10:39:57, 5.76s/it]
44%|████▍ | 5283/11952 [1:09:43<10:36:23, 5.73s/it]
{'loss': 0.4936, 'learning_rate': 1.234242381884874e-05, 'epoch': 0.44}
+
44%|████▍ | 5283/11952 [1:09:43<10:36:23, 5.73s/it]
44%|████▍ | 5284/11952 [1:09:48<10:35:55, 5.72s/it]
{'loss': 0.4803, 'learning_rate': 1.2339789222410301e-05, 'epoch': 0.44}
+
44%|████▍ | 5284/11952 [1:09:48<10:35:55, 5.72s/it]
44%|████▍ | 5285/11952 [1:09:54<10:45:16, 5.81s/it]
{'loss': 0.4985, 'learning_rate': 1.2337154454147476e-05, 'epoch': 0.44}
+
44%|████▍ | 5285/11952 [1:09:54<10:45:16, 5.81s/it]
44%|████▍ | 5286/11952 [1:10:00<10:45:53, 5.81s/it]
{'loss': 0.4824, 'learning_rate': 1.2334519514253747e-05, 'epoch': 0.44}
+
44%|████▍ | 5286/11952 [1:10:00<10:45:53, 5.81s/it]
44%|████▍ | 5287/11952 [1:10:06<10:52:51, 5.88s/it]
{'loss': 0.4794, 'learning_rate': 1.2331884402922613e-05, 'epoch': 0.44}
+
44%|████▍ | 5287/11952 [1:10:06<10:52:51, 5.88s/it]
44%|████▍ | 5288/11952 [1:10:12<10:50:59, 5.86s/it]
{'loss': 0.4644, 'learning_rate': 1.2329249120347591e-05, 'epoch': 0.44}
+
44%|████▍ | 5288/11952 [1:10:12<10:50:59, 5.86s/it]
44%|████▍ | 5289/11952 [1:10:18<10:50:32, 5.86s/it]
{'loss': 0.4718, 'learning_rate': 1.23266136667222e-05, 'epoch': 0.44}
+
44%|████▍ | 5289/11952 [1:10:18<10:50:32, 5.86s/it]
44%|████▍ | 5290/11952 [1:10:24<10:52:03, 5.87s/it]
{'loss': 0.4865, 'learning_rate': 1.2323978042239982e-05, 'epoch': 0.44}
+
44%|████▍ | 5290/11952 [1:10:24<10:52:03, 5.87s/it]
44%|████▍ | 5291/11952 [1:10:30<10:51:02, 5.86s/it]
{'loss': 0.4865, 'learning_rate': 1.232134224709448e-05, 'epoch': 0.44}
+
44%|████▍ | 5291/11952 [1:10:30<10:51:02, 5.86s/it]
44%|████▍ | 5292/11952 [1:10:35<10:46:08, 5.82s/it]
{'loss': 0.4886, 'learning_rate': 1.2318706281479256e-05, 'epoch': 0.44}
+
44%|████▍ | 5292/11952 [1:10:35<10:46:08, 5.82s/it]
44%|████▍ | 5293/11952 [1:10:41<10:47:16, 5.83s/it]
{'loss': 0.4689, 'learning_rate': 1.2316070145587888e-05, 'epoch': 0.44}
+
44%|████▍ | 5293/11952 [1:10:41<10:47:16, 5.83s/it]
44%|████▍ | 5294/11952 [1:10:47<10:43:16, 5.80s/it]
{'loss': 0.4984, 'learning_rate': 1.2313433839613964e-05, 'epoch': 0.44}
+
44%|████▍ | 5294/11952 [1:10:47<10:43:16, 5.80s/it]
44%|████▍ | 5295/11952 [1:10:53<10:39:35, 5.76s/it]
{'loss': 0.497, 'learning_rate': 1.2310797363751078e-05, 'epoch': 0.44}
+
44%|████▍ | 5295/11952 [1:10:53<10:39:35, 5.76s/it]
44%|████▍ | 5296/11952 [1:10:58<10:37:23, 5.75s/it]
{'loss': 0.4869, 'learning_rate': 1.230816071819285e-05, 'epoch': 0.44}
+
44%|████▍ | 5296/11952 [1:10:58<10:37:23, 5.75s/it]
44%|████▍ | 5297/11952 [1:11:04<10:45:18, 5.82s/it]
{'loss': 0.5057, 'learning_rate': 1.2305523903132897e-05, 'epoch': 0.44}
+
44%|████▍ | 5297/11952 [1:11:04<10:45:18, 5.82s/it]
44%|████▍ | 5298/11952 [1:11:10<10:54:42, 5.90s/it]
{'loss': 0.4959, 'learning_rate': 1.2302886918764856e-05, 'epoch': 0.44}
+
44%|████▍ | 5298/11952 [1:11:10<10:54:42, 5.90s/it]
44%|████▍ | 5299/11952 [1:11:16<11:01:13, 5.96s/it]
{'loss': 0.4867, 'learning_rate': 1.230024976528238e-05, 'epoch': 0.44}
+
44%|████▍ | 5299/11952 [1:11:16<11:01:13, 5.96s/it]7 6AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+ 5 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
44%|████▍ | 5300/11952 [1:11:22<10:52:54, 5.89s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4817, 'learning_rate': 1.2297612442879129e-05, 'epoch': 0.44}
+
44%|████▍ | 5300/11952 [1:11:22<10:52:54, 5.89s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
44%|████▍ | 5301/11952 [1:11:52<24:16:17, 13.14s/it]
{'loss': 0.4834, 'learning_rate': 1.2294974951748775e-05, 'epoch': 0.44}
+
44%|████▍ | 5301/11952 [1:11:52<24:16:17, 13.14s/it]
44%|████▍ | 5302/11952 [1:11:58<20:15:00, 10.96s/it]
{'loss': 0.4934, 'learning_rate': 1.2292337292085006e-05, 'epoch': 0.44}
+
44%|████▍ | 5302/11952 [1:11:58<20:15:00, 10.96s/it]
44%|████▍ | 5303/11952 [1:12:04<17:37:25, 9.54s/it]
{'loss': 0.4969, 'learning_rate': 1.2289699464081521e-05, 'epoch': 0.44}
+
44%|████▍ | 5303/11952 [1:12:04<17:37:25, 9.54s/it]
44%|████▍ | 5304/11952 [1:12:10<15:29:16, 8.39s/it]
{'loss': 0.4713, 'learning_rate': 1.2287061467932033e-05, 'epoch': 0.44}
+
44%|████▍ | 5304/11952 [1:12:10<15:29:16, 8.39s/it]
44%|████▍ | 5305/11952 [1:12:16<13:59:21, 7.58s/it]
{'loss': 0.4615, 'learning_rate': 1.228442330383026e-05, 'epoch': 0.44}
+
44%|████▍ | 5305/11952 [1:12:16<13:59:21, 7.58s/it]
44%|████▍ | 5306/11952 [1:12:22<13:13:20, 7.16s/it]
{'loss': 0.4634, 'learning_rate': 1.2281784971969944e-05, 'epoch': 0.44}
+
44%|████▍ | 5306/11952 [1:12:22<13:13:20, 7.16s/it]
44%|████▍ | 5307/11952 [1:12:28<12:26:13, 6.74s/it]
{'loss': 0.4882, 'learning_rate': 1.227914647254483e-05, 'epoch': 0.44}
+
44%|████▍ | 5307/11952 [1:12:28<12:26:13, 6.74s/it]
44%|████▍ | 5308/11952 [1:12:33<11:52:01, 6.43s/it]
{'loss': 0.4769, 'learning_rate': 1.2276507805748676e-05, 'epoch': 0.44}
+
44%|████▍ | 5308/11952 [1:12:33<11:52:01, 6.43s/it]
44%|████▍ | 5309/11952 [1:12:39<11:31:12, 6.24s/it]
{'loss': 0.4874, 'learning_rate': 1.227386897177526e-05, 'epoch': 0.44}
+
44%|████▍ | 5309/11952 [1:12:39<11:31:12, 6.24s/it]
44%|████▍ | 5310/11952 [1:12:45<11:12:41, 6.08s/it]
{'loss': 0.504, 'learning_rate': 1.2271229970818366e-05, 'epoch': 0.44}
+
44%|████▍ | 5310/11952 [1:12:45<11:12:41, 6.08s/it]
44%|████▍ | 5311/11952 [1:12:51<11:16:19, 6.11s/it]
{'loss': 0.4827, 'learning_rate': 1.2268590803071787e-05, 'epoch': 0.44}
+
44%|████▍ | 5311/11952 [1:12:51<11:16:19, 6.11s/it]
44%|████▍ | 5312/11952 [1:12:57<11:06:04, 6.02s/it]
{'loss': 0.4654, 'learning_rate': 1.2265951468729336e-05, 'epoch': 0.44}
+
44%|████▍ | 5312/11952 [1:12:57<11:06:04, 6.02s/it]
44%|████▍ | 5313/11952 [1:13:03<10:59:02, 5.96s/it]
{'loss': 0.5182, 'learning_rate': 1.2263311967984834e-05, 'epoch': 0.44}
+
44%|████▍ | 5313/11952 [1:13:03<10:59:02, 5.96s/it]
44%|████▍ | 5314/11952 [1:13:09<11:01:24, 5.98s/it]
{'loss': 0.4757, 'learning_rate': 1.2260672301032116e-05, 'epoch': 0.44}
+
44%|████▍ | 5314/11952 [1:13:09<11:01:24, 5.98s/it]
44%|████▍ | 5315/11952 [1:13:15<10:57:06, 5.94s/it]
{'loss': 0.4899, 'learning_rate': 1.2258032468065024e-05, 'epoch': 0.44}
+
44%|████▍ | 5315/11952 [1:13:15<10:57:06, 5.94s/it]
44%|████▍ | 5316/11952 [1:13:20<10:56:50, 5.94s/it]
{'loss': 0.4886, 'learning_rate': 1.2255392469277421e-05, 'epoch': 0.44}
+
44%|████▍ | 5316/11952 [1:13:20<10:56:50, 5.94s/it]
44%|████▍ | 5317/11952 [1:13:26<10:50:14, 5.88s/it]
{'loss': 0.4833, 'learning_rate': 1.2252752304863178e-05, 'epoch': 0.44}
+
44%|████▍ | 5317/11952 [1:13:26<10:50:14, 5.88s/it]
44%|████▍ | 5318/11952 [1:13:32<10:49:20, 5.87s/it]
{'loss': 0.4766, 'learning_rate': 1.2250111975016173e-05, 'epoch': 0.44}
+
44%|████▍ | 5318/11952 [1:13:32<10:49:20, 5.87s/it]
45%|████▍ | 5319/11952 [1:13:38<10:37:36, 5.77s/it]
{'loss': 0.4942, 'learning_rate': 1.2247471479930303e-05, 'epoch': 0.45}
+
45%|████▍ | 5319/11952 [1:13:38<10:37:36, 5.77s/it]
45%|████▍ | 5320/11952 [1:13:43<10:38:06, 5.77s/it]
{'loss': 0.4695, 'learning_rate': 1.2244830819799478e-05, 'epoch': 0.45}
+
45%|████▍ | 5320/11952 [1:13:43<10:38:06, 5.77s/it]
45%|████▍ | 5321/11952 [1:13:49<10:43:39, 5.82s/it]
{'loss': 0.4811, 'learning_rate': 1.2242189994817614e-05, 'epoch': 0.45}
+
45%|████▍ | 5321/11952 [1:13:49<10:43:39, 5.82s/it]
45%|████▍ | 5322/11952 [1:13:55<10:41:49, 5.81s/it]
{'loss': 0.4927, 'learning_rate': 1.2239549005178642e-05, 'epoch': 0.45}
+
45%|████▍ | 5322/11952 [1:13:55<10:41:49, 5.81s/it]
45%|████▍ | 5323/11952 [1:14:01<10:44:53, 5.84s/it]
{'loss': 0.4838, 'learning_rate': 1.2236907851076505e-05, 'epoch': 0.45}
+
45%|████▍ | 5323/11952 [1:14:01<10:44:53, 5.84s/it]
45%|████▍ | 5324/11952 [1:14:07<10:40:19, 5.80s/it]
{'loss': 0.4872, 'learning_rate': 1.2234266532705161e-05, 'epoch': 0.45}
+
45%|████▍ | 5324/11952 [1:14:07<10:40:19, 5.80s/it]
45%|████▍ | 5325/11952 [1:14:13<10:43:44, 5.83s/it]
{'loss': 0.492, 'learning_rate': 1.2231625050258576e-05, 'epoch': 0.45}
+
45%|████▍ | 5325/11952 [1:14:13<10:43:44, 5.83s/it]
45%|████▍ | 5326/11952 [1:14:18<10:37:26, 5.77s/it]
{'loss': 0.4847, 'learning_rate': 1.2228983403930727e-05, 'epoch': 0.45}
+
45%|████▍ | 5326/11952 [1:14:18<10:37:26, 5.77s/it]
45%|████▍ | 5327/11952 [1:14:24<10:44:27, 5.84s/it]
{'loss': 0.4641, 'learning_rate': 1.2226341593915612e-05, 'epoch': 0.45}
+
45%|████▍ | 5327/11952 [1:14:24<10:44:27, 5.84s/it]
45%|████▍ | 5328/11952 [1:14:30<10:45:55, 5.85s/it]
{'loss': 0.5174, 'learning_rate': 1.2223699620407227e-05, 'epoch': 0.45}
+
45%|████▍ | 5328/11952 [1:14:30<10:45:55, 5.85s/it]
45%|████▍ | 5329/11952 [1:14:36<10:44:11, 5.84s/it]
{'loss': 0.4728, 'learning_rate': 1.222105748359959e-05, 'epoch': 0.45}
+
45%|████▍ | 5329/11952 [1:14:36<10:44:11, 5.84s/it]
45%|████▍ | 5330/11952 [1:14:42<10:54:37, 5.93s/it]
{'loss': 0.4889, 'learning_rate': 1.2218415183686732e-05, 'epoch': 0.45}
+
45%|████▍ | 5330/11952 [1:14:42<10:54:37, 5.93s/it]
45%|████▍ | 5331/11952 [1:14:48<10:47:07, 5.86s/it]
{'loss': 0.5182, 'learning_rate': 1.2215772720862691e-05, 'epoch': 0.45}
+
45%|████▍ | 5331/11952 [1:14:48<10:47:07, 5.86s/it]
45%|████▍ | 5332/11952 [1:14:54<10:47:37, 5.87s/it]
{'loss': 0.4757, 'learning_rate': 1.2213130095321517e-05, 'epoch': 0.45}
+
45%|████▍ | 5332/11952 [1:14:54<10:47:37, 5.87s/it]
45%|████▍ | 5333/11952 [1:15:00<10:54:59, 5.94s/it]
{'loss': 0.4729, 'learning_rate': 1.221048730725727e-05, 'epoch': 0.45}
+
45%|████▍ | 5333/11952 [1:15:00<10:54:59, 5.94s/it]
45%|████▍ | 5334/11952 [1:15:06<10:57:12, 5.96s/it]
{'loss': 0.4839, 'learning_rate': 1.2207844356864031e-05, 'epoch': 0.45}
+
45%|████▍ | 5334/11952 [1:15:06<10:57:12, 5.96s/it]
45%|████▍ | 5335/11952 [1:15:11<10:39:48, 5.80s/it]
{'loss': 0.4946, 'learning_rate': 1.2205201244335889e-05, 'epoch': 0.45}
+
45%|████▍ | 5335/11952 [1:15:11<10:39:48, 5.80s/it]
45%|████▍ | 5336/11952 [1:15:17<10:43:24, 5.84s/it]
{'loss': 0.4686, 'learning_rate': 1.2202557969866934e-05, 'epoch': 0.45}
+
45%|████▍ | 5336/11952 [1:15:17<10:43:24, 5.84s/it]
45%|████▍ | 5337/11952 [1:15:23<10:39:44, 5.80s/it]
{'loss': 0.4722, 'learning_rate': 1.2199914533651289e-05, 'epoch': 0.45}
+
45%|████▍ | 5337/11952 [1:15:23<10:39:44, 5.80s/it]
45%|████▍ | 5338/11952 [1:15:29<10:42:43, 5.83s/it]
{'loss': 0.4708, 'learning_rate': 1.2197270935883068e-05, 'epoch': 0.45}
+
45%|████▍ | 5338/11952 [1:15:29<10:42:43, 5.83s/it]
45%|████▍ | 5339/11952 [1:15:35<10:53:22, 5.93s/it]
{'loss': 0.5, 'learning_rate': 1.2194627176756408e-05, 'epoch': 0.45}
+
45%|████▍ | 5339/11952 [1:15:35<10:53:22, 5.93s/it]
45%|████▍ | 5340/11952 [1:15:41<10:49:59, 5.90s/it]
{'loss': 0.463, 'learning_rate': 1.2191983256465455e-05, 'epoch': 0.45}
+
45%|████▍ | 5340/11952 [1:15:41<10:49:59, 5.90s/it]
45%|████▍ | 5341/11952 [1:15:47<10:53:26, 5.93s/it]
{'loss': 0.4606, 'learning_rate': 1.2189339175204373e-05, 'epoch': 0.45}
+
45%|████▍ | 5341/11952 [1:15:47<10:53:26, 5.93s/it]
45%|████▍ | 5342/11952 [1:15:53<10:53:22, 5.93s/it]
{'loss': 0.5079, 'learning_rate': 1.2186694933167326e-05, 'epoch': 0.45}
+
45%|████▍ | 5342/11952 [1:15:53<10:53:22, 5.93s/it]
45%|████▍ | 5343/11952 [1:15:58<10:47:15, 5.88s/it]
{'loss': 0.4716, 'learning_rate': 1.2184050530548496e-05, 'epoch': 0.45}
+
45%|████▍ | 5343/11952 [1:15:58<10:47:15, 5.88s/it]
45%|████▍ | 5344/11952 [1:16:04<10:45:38, 5.86s/it]
{'loss': 0.4788, 'learning_rate': 1.2181405967542082e-05, 'epoch': 0.45}
+
45%|████▍ | 5344/11952 [1:16:04<10:45:38, 5.86s/it]
45%|████▍ | 5345/11952 [1:16:10<10:40:24, 5.82s/it]
{'loss': 0.488, 'learning_rate': 1.2178761244342286e-05, 'epoch': 0.45}
+
45%|████▍ | 5345/11952 [1:16:10<10:40:24, 5.82s/it]
45%|████▍ | 5346/11952 [1:16:16<10:38:12, 5.80s/it]
{'loss': 0.4836, 'learning_rate': 1.2176116361143326e-05, 'epoch': 0.45}
+
45%|████▍ | 5346/11952 [1:16:16<10:38:12, 5.80s/it]
45%|████▍ | 5347/11952 [1:16:21<10:37:11, 5.79s/it]
{'loss': 0.4844, 'learning_rate': 1.2173471318139431e-05, 'epoch': 0.45}
+
45%|████▍ | 5347/11952 [1:16:21<10:37:11, 5.79s/it]
45%|████▍ | 5348/11952 [1:16:27<10:38:38, 5.80s/it]
{'loss': 0.4895, 'learning_rate': 1.2170826115524845e-05, 'epoch': 0.45}
+
45%|████▍ | 5348/11952 [1:16:27<10:38:38, 5.80s/it]
45%|████▍ | 5349/11952 [1:16:33<10:38:13, 5.80s/it]
{'loss': 0.4887, 'learning_rate': 1.2168180753493817e-05, 'epoch': 0.45}
+
45%|████▍ | 5349/11952 [1:16:33<10:38:13, 5.80s/it]6 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
45%|████▍ | 5350/11952 [1:16:39<10:29:17, 5.72s/it]53 2AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4839, 'learning_rate': 1.2165535232240611e-05, 'epoch': 0.45}
+
45%|████▍ | 5350/11952 [1:16:39<10:29:17, 5.72s/it]
45%|████▍ | 5351/11952 [1:16:45<10:38:09, 5.80s/it]
{'loss': 0.4759, 'learning_rate': 1.2162889551959506e-05, 'epoch': 0.45}
+
45%|████▍ | 5351/11952 [1:16:45<10:38:09, 5.80s/it]
45%|████▍ | 5352/11952 [1:16:50<10:39:59, 5.82s/it]
{'loss': 0.4753, 'learning_rate': 1.216024371284479e-05, 'epoch': 0.45}
+
45%|████▍ | 5352/11952 [1:16:50<10:39:59, 5.82s/it]
45%|████▍ | 5353/11952 [1:16:56<10:39:35, 5.82s/it]
{'loss': 0.4875, 'learning_rate': 1.215759771509076e-05, 'epoch': 0.45}
+
45%|████▍ | 5353/11952 [1:16:56<10:39:35, 5.82s/it]
45%|████▍ | 5354/11952 [1:17:02<10:40:24, 5.82s/it]
{'loss': 0.4858, 'learning_rate': 1.2154951558891728e-05, 'epoch': 0.45}
+
45%|████▍ | 5354/11952 [1:17:02<10:40:24, 5.82s/it]
45%|████▍ | 5355/11952 [1:17:08<10:47:00, 5.88s/it]
{'loss': 0.4829, 'learning_rate': 1.2152305244442014e-05, 'epoch': 0.45}
+
45%|████▍ | 5355/11952 [1:17:08<10:47:00, 5.88s/it]
45%|████▍ | 5356/11952 [1:17:14<10:46:13, 5.88s/it]
{'loss': 0.4784, 'learning_rate': 1.2149658771935955e-05, 'epoch': 0.45}
+
45%|████▍ | 5356/11952 [1:17:14<10:46:13, 5.88s/it]
45%|████▍ | 5357/11952 [1:17:20<10:44:37, 5.86s/it]
{'loss': 0.4715, 'learning_rate': 1.21470121415679e-05, 'epoch': 0.45}
+
45%|████▍ | 5357/11952 [1:17:20<10:44:37, 5.86s/it]
45%|████▍ | 5358/11952 [1:17:25<10:35:14, 5.78s/it]
{'loss': 0.4761, 'learning_rate': 1.2144365353532204e-05, 'epoch': 0.45}
+
45%|████▍ | 5358/11952 [1:17:25<10:35:14, 5.78s/it]
45%|████▍ | 5359/11952 [1:17:32<10:45:41, 5.88s/it]
{'loss': 0.4941, 'learning_rate': 1.2141718408023233e-05, 'epoch': 0.45}
+
45%|████▍ | 5359/11952 [1:17:32<10:45:41, 5.88s/it]
45%|████▍ | 5360/11952 [1:17:37<10:43:11, 5.85s/it]
{'loss': 0.4754, 'learning_rate': 1.2139071305235368e-05, 'epoch': 0.45}
+
45%|████▍ | 5360/11952 [1:17:37<10:43:11, 5.85s/it]
45%|████▍ | 5361/11952 [1:17:43<10:37:33, 5.80s/it]
{'loss': 0.4846, 'learning_rate': 1.2136424045363007e-05, 'epoch': 0.45}
+
45%|████▍ | 5361/11952 [1:17:43<10:37:33, 5.80s/it]
45%|████▍ | 5362/11952 [1:17:49<10:31:02, 5.75s/it]
{'loss': 0.4779, 'learning_rate': 1.2133776628600552e-05, 'epoch': 0.45}
+
45%|████▍ | 5362/11952 [1:17:49<10:31:02, 5.75s/it]
45%|████▍ | 5363/11952 [1:17:55<10:35:06, 5.78s/it]
{'loss': 0.481, 'learning_rate': 1.2131129055142411e-05, 'epoch': 0.45}
+
45%|████▍ | 5363/11952 [1:17:55<10:35:06, 5.78s/it]
45%|████▍ | 5364/11952 [1:18:01<10:46:02, 5.88s/it]
{'loss': 0.4914, 'learning_rate': 1.2128481325183022e-05, 'epoch': 0.45}
+
45%|████▍ | 5364/11952 [1:18:01<10:46:02, 5.88s/it]
45%|████▍ | 5365/11952 [1:18:07<10:47:10, 5.90s/it]
{'loss': 0.4922, 'learning_rate': 1.2125833438916812e-05, 'epoch': 0.45}
+
45%|████▍ | 5365/11952 [1:18:07<10:47:10, 5.90s/it]
45%|████▍ | 5366/11952 [1:18:12<10:37:00, 5.80s/it]
{'loss': 0.4835, 'learning_rate': 1.2123185396538242e-05, 'epoch': 0.45}
+
45%|████▍ | 5366/11952 [1:18:12<10:37:00, 5.80s/it]
45%|████▍ | 5367/11952 [1:18:18<10:39:25, 5.83s/it]
{'loss': 0.4769, 'learning_rate': 1.2120537198241763e-05, 'epoch': 0.45}
+
45%|████▍ | 5367/11952 [1:18:18<10:39:25, 5.83s/it]
45%|████▍ | 5368/11952 [1:18:24<10:42:31, 5.86s/it]
{'loss': 0.4646, 'learning_rate': 1.2117888844221852e-05, 'epoch': 0.45}
+
45%|████▍ | 5368/11952 [1:18:24<10:42:31, 5.86s/it]
45%|████▍ | 5369/11952 [1:18:30<10:36:46, 5.80s/it]
{'loss': 0.4822, 'learning_rate': 1.2115240334672997e-05, 'epoch': 0.45}
+
45%|████▍ | 5369/11952 [1:18:30<10:36:46, 5.80s/it]
45%|████▍ | 5370/11952 [1:18:36<10:43:33, 5.87s/it]
{'loss': 0.4844, 'learning_rate': 1.2112591669789685e-05, 'epoch': 0.45}
+
45%|████▍ | 5370/11952 [1:18:36<10:43:33, 5.87s/it]
45%|████▍ | 5371/11952 [1:18:42<10:46:35, 5.90s/it]
{'loss': 0.4739, 'learning_rate': 1.2109942849766432e-05, 'epoch': 0.45}
+
45%|████▍ | 5371/11952 [1:18:42<10:46:35, 5.90s/it]
45%|████▍ | 5372/11952 [1:18:48<10:47:18, 5.90s/it]
{'loss': 0.4888, 'learning_rate': 1.210729387479775e-05, 'epoch': 0.45}
+
45%|████▍ | 5372/11952 [1:18:48<10:47:18, 5.90s/it]
45%|████▍ | 5373/11952 [1:18:54<10:49:27, 5.92s/it]
{'loss': 0.496, 'learning_rate': 1.210464474507817e-05, 'epoch': 0.45}
+
45%|████▍ | 5373/11952 [1:18:54<10:49:27, 5.92s/it]
45%|████▍ | 5374/11952 [1:18:59<10:50:37, 5.93s/it]
{'loss': 0.4643, 'learning_rate': 1.2101995460802235e-05, 'epoch': 0.45}
+
45%|████▍ | 5374/11952 [1:18:59<10:50:37, 5.93s/it]
45%|████▍ | 5375/11952 [1:19:05<10:41:07, 5.85s/it]
{'loss': 0.4959, 'learning_rate': 1.2099346022164496e-05, 'epoch': 0.45}
+
45%|████▍ | 5375/11952 [1:19:05<10:41:07, 5.85s/it]
45%|████▍ | 5376/11952 [1:19:11<10:42:23, 5.86s/it]
{'loss': 0.4997, 'learning_rate': 1.2096696429359518e-05, 'epoch': 0.45}
+
45%|████▍ | 5376/11952 [1:19:11<10:42:23, 5.86s/it]
45%|████▍ | 5377/11952 [1:19:17<10:52:24, 5.95s/it]
{'loss': 0.5001, 'learning_rate': 1.2094046682581872e-05, 'epoch': 0.45}
+
45%|████▍ | 5377/11952 [1:19:17<10:52:24, 5.95s/it]
45%|████▍ | 5378/11952 [1:19:23<10:56:41, 5.99s/it]
{'loss': 0.4878, 'learning_rate': 1.209139678202615e-05, 'epoch': 0.45}
+
45%|████▍ | 5378/11952 [1:19:23<10:56:41, 5.99s/it]
45%|████▌ | 5379/11952 [1:19:29<10:45:55, 5.90s/it]
{'loss': 0.4932, 'learning_rate': 1.2088746727886949e-05, 'epoch': 0.45}
+
45%|████▌ | 5379/11952 [1:19:29<10:45:55, 5.90s/it]
45%|████▌ | 5380/11952 [1:19:35<10:47:49, 5.91s/it]
{'loss': 0.4941, 'learning_rate': 1.2086096520358872e-05, 'epoch': 0.45}
+
45%|████▌ | 5380/11952 [1:19:35<10:47:49, 5.91s/it]
45%|████▌ | 5381/11952 [1:19:41<10:46:21, 5.90s/it]
{'loss': 0.4906, 'learning_rate': 1.2083446159636543e-05, 'epoch': 0.45}
+
45%|████▌ | 5381/11952 [1:19:41<10:46:21, 5.90s/it]
45%|████▌ | 5382/11952 [1:19:46<10:40:22, 5.85s/it]
{'loss': 0.4808, 'learning_rate': 1.2080795645914595e-05, 'epoch': 0.45}
+
45%|████▌ | 5382/11952 [1:19:46<10:40:22, 5.85s/it]
45%|████▌ | 5383/11952 [1:19:52<10:39:02, 5.84s/it]
{'loss': 0.5055, 'learning_rate': 1.2078144979387674e-05, 'epoch': 0.45}
+
45%|████▌ | 5383/11952 [1:19:52<10:39:02, 5.84s/it]
45%|████▌ | 5384/11952 [1:19:58<10:47:02, 5.91s/it]
{'loss': 0.4768, 'learning_rate': 1.2075494160250423e-05, 'epoch': 0.45}
+
45%|████▌ | 5384/11952 [1:19:58<10:47:02, 5.91s/it]
45%|████▌ | 5385/11952 [1:20:04<10:47:21, 5.91s/it]
{'loss': 0.4818, 'learning_rate': 1.2072843188697516e-05, 'epoch': 0.45}
+
45%|████▌ | 5385/11952 [1:20:04<10:47:21, 5.91s/it]
45%|████▌ | 5386/11952 [1:20:10<10:54:45, 5.98s/it]
{'loss': 0.4919, 'learning_rate': 1.2070192064923627e-05, 'epoch': 0.45}
+
45%|████▌ | 5386/11952 [1:20:10<10:54:45, 5.98s/it]
45%|████▌ | 5387/11952 [1:20:16<10:44:25, 5.89s/it]
{'loss': 0.4866, 'learning_rate': 1.2067540789123441e-05, 'epoch': 0.45}
+
45%|████▌ | 5387/11952 [1:20:16<10:44:25, 5.89s/it]
45%|████▌ | 5388/11952 [1:20:22<10:36:49, 5.82s/it]
{'loss': 0.4826, 'learning_rate': 1.2064889361491663e-05, 'epoch': 0.45}
+
45%|████▌ | 5388/11952 [1:20:22<10:36:49, 5.82s/it]
45%|████▌ | 5389/11952 [1:20:28<10:45:23, 5.90s/it]
{'loss': 0.4683, 'learning_rate': 1.2062237782222996e-05, 'epoch': 0.45}
+
45%|████▌ | 5389/11952 [1:20:28<10:45:23, 5.90s/it]
45%|████▌ | 5390/11952 [1:20:33<10:36:14, 5.82s/it]
{'loss': 0.4713, 'learning_rate': 1.2059586051512164e-05, 'epoch': 0.45}
+
45%|████▌ | 5390/11952 [1:20:33<10:36:14, 5.82s/it]
45%|████▌ | 5391/11952 [1:20:40<10:45:53, 5.91s/it]
{'loss': 0.4872, 'learning_rate': 1.20569341695539e-05, 'epoch': 0.45}
+
45%|████▌ | 5391/11952 [1:20:40<10:45:53, 5.91s/it]
45%|████▌ | 5392/11952 [1:20:46<10:47:48, 5.93s/it]
{'loss': 0.5091, 'learning_rate': 1.2054282136542946e-05, 'epoch': 0.45}
+
45%|████▌ | 5392/11952 [1:20:46<10:47:48, 5.93s/it]
45%|████▌ | 5393/11952 [1:20:51<10:44:20, 5.89s/it]
{'loss': 0.4817, 'learning_rate': 1.2051629952674055e-05, 'epoch': 0.45}
+
45%|████▌ | 5393/11952 [1:20:51<10:44:20, 5.89s/it]
45%|████▌ | 5394/11952 [1:20:57<10:43:57, 5.89s/it]
{'loss': 0.5097, 'learning_rate': 1.2048977618141995e-05, 'epoch': 0.45}
+
45%|████▌ | 5394/11952 [1:20:57<10:43:57, 5.89s/it]
45%|████▌ | 5395/11952 [1:21:03<10:37:57, 5.84s/it]
{'loss': 0.4779, 'learning_rate': 1.2046325133141542e-05, 'epoch': 0.45}
+
45%|████▌ | 5395/11952 [1:21:03<10:37:57, 5.84s/it]
45%|████▌ | 5396/11952 [1:21:09<10:42:27, 5.88s/it]
{'loss': 0.4591, 'learning_rate': 1.2043672497867479e-05, 'epoch': 0.45}
+
45%|████▌ | 5396/11952 [1:21:09<10:42:27, 5.88s/it]
45%|████▌ | 5397/11952 [1:21:15<10:38:21, 5.84s/it]
{'loss': 0.4957, 'learning_rate': 1.2041019712514607e-05, 'epoch': 0.45}
+
45%|████▌ | 5397/11952 [1:21:15<10:38:21, 5.84s/it]
45%|████▌ | 5398/11952 [1:21:21<10:36:48, 5.83s/it]
{'loss': 0.475, 'learning_rate': 1.2038366777277743e-05, 'epoch': 0.45}
+
45%|████▌ | 5398/11952 [1:21:21<10:36:48, 5.83s/it]
45%|████▌ | 5399/11952 [1:21:27<10:53:07, 5.98s/it]
{'loss': 0.483, 'learning_rate': 1.2035713692351698e-05, 'epoch': 0.45}
+
45%|████▌ | 5399/11952 [1:21:27<10:53:07, 5.98s/it]67 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+5 2AutoResumeHook: Checking whether to suspend...
45%|████▌ | 5400/11952 [1:21:33<10:47:48, 5.93s/it]
+ AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4841, 'learning_rate': 1.2033060457931308e-05, 'epoch': 0.45}
+
45%|████▌ | 5400/11952 [1:21:33<10:47:48, 5.93s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
45%|████▌ | 5401/11952 [1:22:04<24:26:11, 13.43s/it]
{'loss': 0.4775, 'learning_rate': 1.203040707421141e-05, 'epoch': 0.45}
+
45%|████▌ | 5401/11952 [1:22:04<24:26:11, 13.43s/it]
45%|████▌ | 5402/11952 [1:22:09<20:11:41, 11.10s/it]
{'loss': 0.466, 'learning_rate': 1.2027753541386865e-05, 'epoch': 0.45}
+
45%|████▌ | 5402/11952 [1:22:09<20:11:41, 11.10s/it]
45%|████▌ | 5403/11952 [1:22:15<17:10:53, 9.44s/it]
{'loss': 0.4859, 'learning_rate': 1.2025099859652532e-05, 'epoch': 0.45}
+
45%|████▌ | 5403/11952 [1:22:15<17:10:53, 9.44s/it]
45%|████▌ | 5404/11952 [1:22:21<15:09:43, 8.34s/it]
{'loss': 0.4848, 'learning_rate': 1.202244602920329e-05, 'epoch': 0.45}
+
45%|████▌ | 5404/11952 [1:22:21<15:09:43, 8.34s/it]
45%|████▌ | 5405/11952 [1:22:26<13:48:47, 7.60s/it]
{'loss': 0.4779, 'learning_rate': 1.2019792050234022e-05, 'epoch': 0.45}
+
45%|████▌ | 5405/11952 [1:22:26<13:48:47, 7.60s/it]
45%|████▌ | 5406/11952 [1:22:33<13:05:19, 7.20s/it]
{'loss': 0.4719, 'learning_rate': 1.2017137922939629e-05, 'epoch': 0.45}
+
45%|████▌ | 5406/11952 [1:22:33<13:05:19, 7.20s/it]
45%|████▌ | 5407/11952 [1:22:39<12:32:10, 6.90s/it]
{'loss': 0.4811, 'learning_rate': 1.2014483647515014e-05, 'epoch': 0.45}
+
45%|████▌ | 5407/11952 [1:22:39<12:32:10, 6.90s/it]
45%|████▌ | 5408/11952 [1:22:45<11:55:31, 6.56s/it]
{'loss': 0.4836, 'learning_rate': 1.2011829224155101e-05, 'epoch': 0.45}
+
45%|████▌ | 5408/11952 [1:22:45<11:55:31, 6.56s/it]
45%|████▌ | 5409/11952 [1:22:51<11:58:10, 6.59s/it]
{'loss': 0.4754, 'learning_rate': 1.2009174653054815e-05, 'epoch': 0.45}
+
45%|████▌ | 5409/11952 [1:22:51<11:58:10, 6.59s/it]
45%|████▌ | 5410/11952 [1:22:58<11:47:34, 6.49s/it]
{'loss': 0.4843, 'learning_rate': 1.2006519934409105e-05, 'epoch': 0.45}
+
45%|████▌ | 5410/11952 [1:22:58<11:47:34, 6.49s/it]
45%|████▌ | 5411/11952 [1:23:03<11:22:15, 6.26s/it]
{'loss': 0.4793, 'learning_rate': 1.200386506841291e-05, 'epoch': 0.45}
+
45%|████▌ | 5411/11952 [1:23:03<11:22:15, 6.26s/it]
45%|████▌ | 5412/11952 [1:23:09<11:11:52, 6.16s/it]
{'loss': 0.4602, 'learning_rate': 1.20012100552612e-05, 'epoch': 0.45}
+
45%|████▌ | 5412/11952 [1:23:09<11:11:52, 6.16s/it]
45%|████▌ | 5413/11952 [1:23:15<11:01:01, 6.07s/it]
{'loss': 0.4766, 'learning_rate': 1.1998554895148953e-05, 'epoch': 0.45}
+
45%|████▌ | 5413/11952 [1:23:15<11:01:01, 6.07s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (5002 > 4096). Running this sequence through the model will result in indexing errors
+
45%|████▌ | 5414/11952 [1:23:21<10:50:16, 5.97s/it]
{'loss': 0.4675, 'learning_rate': 1.199589958827114e-05, 'epoch': 0.45}
+
45%|████▌ | 5414/11952 [1:23:21<10:50:16, 5.97s/it]
45%|████▌ | 5415/11952 [1:23:27<10:44:40, 5.92s/it]
{'loss': 0.4753, 'learning_rate': 1.1993244134822767e-05, 'epoch': 0.45}
+
45%|████▌ | 5415/11952 [1:23:27<10:44:40, 5.92s/it]
45%|████▌ | 5416/11952 [1:23:32<10:40:13, 5.88s/it]
{'loss': 0.4726, 'learning_rate': 1.1990588534998834e-05, 'epoch': 0.45}
+
45%|████▌ | 5416/11952 [1:23:32<10:40:13, 5.88s/it]
45%|████▌ | 5417/11952 [1:23:38<10:37:09, 5.85s/it]
{'loss': 0.4837, 'learning_rate': 1.1987932788994362e-05, 'epoch': 0.45}
+
45%|████▌ | 5417/11952 [1:23:38<10:37:09, 5.85s/it]
45%|████▌ | 5418/11952 [1:23:44<10:33:16, 5.82s/it]
{'loss': 0.475, 'learning_rate': 1.1985276897004367e-05, 'epoch': 0.45}
+
45%|████▌ | 5418/11952 [1:23:44<10:33:16, 5.82s/it]
45%|████▌ | 5419/11952 [1:23:50<10:43:30, 5.91s/it]
{'loss': 0.4957, 'learning_rate': 1.1982620859223902e-05, 'epoch': 0.45}
+
45%|████▌ | 5419/11952 [1:23:50<10:43:30, 5.91s/it]
45%|████▌ | 5420/11952 [1:23:56<10:40:00, 5.88s/it]
{'loss': 0.5041, 'learning_rate': 1.1979964675848004e-05, 'epoch': 0.45}
+
45%|████▌ | 5420/11952 [1:23:56<10:40:00, 5.88s/it]
45%|████▌ | 5421/11952 [1:24:01<10:29:05, 5.78s/it]
{'loss': 0.4591, 'learning_rate': 1.1977308347071735e-05, 'epoch': 0.45}
+
45%|████▌ | 5421/11952 [1:24:01<10:29:05, 5.78s/it]
45%|████▌ | 5422/11952 [1:24:07<10:30:26, 5.79s/it]
{'loss': 0.4675, 'learning_rate': 1.1974651873090163e-05, 'epoch': 0.45}
+
45%|████▌ | 5422/11952 [1:24:07<10:30:26, 5.79s/it]
45%|████▌ | 5423/11952 [1:24:14<10:49:20, 5.97s/it]
{'loss': 0.4879, 'learning_rate': 1.1971995254098374e-05, 'epoch': 0.45}
+
45%|████▌ | 5423/11952 [1:24:14<10:49:20, 5.97s/it]
45%|████▌ | 5424/11952 [1:24:19<10:42:06, 5.90s/it]
{'loss': 0.464, 'learning_rate': 1.1969338490291455e-05, 'epoch': 0.45}
+
45%|████▌ | 5424/11952 [1:24:19<10:42:06, 5.90s/it]
45%|████▌ | 5425/11952 [1:24:25<10:32:32, 5.81s/it]
{'loss': 0.4879, 'learning_rate': 1.1966681581864507e-05, 'epoch': 0.45}
+
45%|████▌ | 5425/11952 [1:24:25<10:32:32, 5.81s/it]
45%|████▌ | 5426/11952 [1:24:31<10:39:59, 5.88s/it]
{'loss': 0.5053, 'learning_rate': 1.1964024529012648e-05, 'epoch': 0.45}
+
45%|████▌ | 5426/11952 [1:24:31<10:39:59, 5.88s/it]
45%|████▌ | 5427/11952 [1:24:37<10:30:46, 5.80s/it]
{'loss': 0.5042, 'learning_rate': 1.196136733193099e-05, 'epoch': 0.45}
+
45%|████▌ | 5427/11952 [1:24:37<10:30:46, 5.80s/it]
45%|████▌ | 5428/11952 [1:24:42<10:26:42, 5.76s/it]
{'loss': 0.4944, 'learning_rate': 1.1958709990814677e-05, 'epoch': 0.45}
+
45%|████▌ | 5428/11952 [1:24:42<10:26:42, 5.76s/it]
45%|████▌ | 5429/11952 [1:24:48<10:27:47, 5.77s/it]
{'loss': 0.4783, 'learning_rate': 1.1956052505858851e-05, 'epoch': 0.45}
+
45%|████▌ | 5429/11952 [1:24:48<10:27:47, 5.77s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
45%|████▌ | 5430/11952 [1:24:55<10:47:35, 5.96s/it]
{'loss': 0.5042, 'learning_rate': 1.1953394877258662e-05, 'epoch': 0.45}
+
45%|████▌ | 5430/11952 [1:24:55<10:47:35, 5.96s/it]
45%|████▌ | 5431/11952 [1:25:00<10:39:46, 5.89s/it]
{'loss': 0.4801, 'learning_rate': 1.1950737105209278e-05, 'epoch': 0.45}
+
45%|████▌ | 5431/11952 [1:25:00<10:39:46, 5.89s/it]
45%|████▌ | 5432/11952 [1:25:06<10:34:59, 5.84s/it]
{'loss': 0.502, 'learning_rate': 1.1948079189905872e-05, 'epoch': 0.45}
+
45%|████▌ | 5432/11952 [1:25:06<10:34:59, 5.84s/it]
45%|████▌ | 5433/11952 [1:25:12<10:30:21, 5.80s/it]
{'loss': 0.4985, 'learning_rate': 1.1945421131543639e-05, 'epoch': 0.45}
+
45%|████▌ | 5433/11952 [1:25:12<10:30:21, 5.80s/it]
45%|████▌ | 5434/11952 [1:25:17<10:25:15, 5.76s/it]
{'loss': 0.4746, 'learning_rate': 1.1942762930317768e-05, 'epoch': 0.45}
+
45%|████▌ | 5434/11952 [1:25:17<10:25:15, 5.76s/it]
45%|████▌ | 5435/11952 [1:25:23<10:24:49, 5.75s/it]
{'loss': 0.4948, 'learning_rate': 1.1940104586423465e-05, 'epoch': 0.45}
+
45%|████▌ | 5435/11952 [1:25:23<10:24:49, 5.75s/it]
45%|████▌ | 5436/11952 [1:25:29<10:24:34, 5.75s/it]
{'loss': 0.4836, 'learning_rate': 1.1937446100055954e-05, 'epoch': 0.45}
+
45%|████▌ | 5436/11952 [1:25:29<10:24:34, 5.75s/it]
45%|████▌ | 5437/11952 [1:25:35<10:31:04, 5.81s/it]
{'loss': 0.4663, 'learning_rate': 1.1934787471410457e-05, 'epoch': 0.45}
+
45%|████▌ | 5437/11952 [1:25:35<10:31:04, 5.81s/it]
45%|████▌ | 5438/11952 [1:25:41<10:49:05, 5.98s/it]
{'loss': 0.5137, 'learning_rate': 1.1932128700682216e-05, 'epoch': 0.45}
+
45%|████▌ | 5438/11952 [1:25:41<10:49:05, 5.98s/it]
46%|████▌ | 5439/11952 [1:25:47<10:47:42, 5.97s/it]
{'loss': 0.4803, 'learning_rate': 1.1929469788066481e-05, 'epoch': 0.46}
+
46%|████▌ | 5439/11952 [1:25:47<10:47:42, 5.97s/it]
46%|████▌ | 5440/11952 [1:25:53<10:50:09, 5.99s/it]
{'loss': 0.4849, 'learning_rate': 1.1926810733758511e-05, 'epoch': 0.46}
+
46%|████▌ | 5440/11952 [1:25:53<10:50:09, 5.99s/it]
46%|████▌ | 5441/11952 [1:25:59<10:42:39, 5.92s/it]
{'loss': 0.4916, 'learning_rate': 1.1924151537953574e-05, 'epoch': 0.46}
+
46%|████▌ | 5441/11952 [1:25:59<10:42:39, 5.92s/it]
46%|████▌ | 5442/11952 [1:26:05<10:33:53, 5.84s/it]
{'loss': 0.4784, 'learning_rate': 1.1921492200846949e-05, 'epoch': 0.46}
+
46%|████▌ | 5442/11952 [1:26:05<10:33:53, 5.84s/it]
46%|████▌ | 5443/11952 [1:26:11<10:37:55, 5.88s/it]
{'loss': 0.4805, 'learning_rate': 1.191883272263393e-05, 'epoch': 0.46}
+
46%|████▌ | 5443/11952 [1:26:11<10:37:55, 5.88s/it]
46%|████▌ | 5444/11952 [1:26:16<10:33:50, 5.84s/it]
{'loss': 0.4756, 'learning_rate': 1.1916173103509819e-05, 'epoch': 0.46}
+
46%|████▌ | 5444/11952 [1:26:16<10:33:50, 5.84s/it]
46%|████▌ | 5445/11952 [1:26:22<10:40:13, 5.90s/it]
{'loss': 0.5125, 'learning_rate': 1.191351334366992e-05, 'epoch': 0.46}
+
46%|████▌ | 5445/11952 [1:26:22<10:40:13, 5.90s/it]
46%|████▌ | 5446/11952 [1:26:28<10:32:21, 5.83s/it]
{'loss': 0.4804, 'learning_rate': 1.1910853443309566e-05, 'epoch': 0.46}
+
46%|████▌ | 5446/11952 [1:26:28<10:32:21, 5.83s/it]
46%|████▌ | 5447/11952 [1:26:34<10:32:17, 5.83s/it]
{'loss': 0.4834, 'learning_rate': 1.190819340262408e-05, 'epoch': 0.46}
+
46%|████▌ | 5447/11952 [1:26:34<10:32:17, 5.83s/it]
46%|████▌ | 5448/11952 [1:26:40<10:30:53, 5.82s/it]
{'loss': 0.4813, 'learning_rate': 1.1905533221808805e-05, 'epoch': 0.46}
+
46%|████▌ | 5448/11952 [1:26:40<10:30:53, 5.82s/it]
46%|████▌ | 5449/11952 [1:26:45<10:31:45, 5.83s/it]
{'loss': 0.501, 'learning_rate': 1.1902872901059102e-05, 'epoch': 0.46}
+
46%|████▌ | 5449/11952 [1:26:45<10:31:45, 5.83s/it]0 76 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
46%|████▌ | 5450/11952 [1:26:51<10:32:59, 5.84s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+23 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4523, 'learning_rate': 1.1900212440570324e-05, 'epoch': 0.46}
+
46%|████▌ | 5450/11952 [1:26:51<10:32:59, 5.84s/it]
46%|████▌ | 5451/11952 [1:26:57<10:26:43, 5.78s/it]
{'loss': 0.4583, 'learning_rate': 1.1897551840537848e-05, 'epoch': 0.46}
+
46%|████▌ | 5451/11952 [1:26:57<10:26:43, 5.78s/it]
46%|████▌ | 5452/11952 [1:27:03<10:25:31, 5.77s/it]
{'loss': 0.4717, 'learning_rate': 1.1894891101157058e-05, 'epoch': 0.46}
+
46%|████▌ | 5452/11952 [1:27:03<10:25:31, 5.77s/it]
46%|████▌ | 5453/11952 [1:27:09<10:29:17, 5.81s/it]
{'loss': 0.4813, 'learning_rate': 1.1892230222623345e-05, 'epoch': 0.46}
+
46%|████▌ | 5453/11952 [1:27:09<10:29:17, 5.81s/it]
46%|████▌ | 5454/11952 [1:27:14<10:27:29, 5.79s/it]
{'loss': 0.495, 'learning_rate': 1.1889569205132119e-05, 'epoch': 0.46}
+
46%|████▌ | 5454/11952 [1:27:14<10:27:29, 5.79s/it]
46%|████▌ | 5455/11952 [1:27:21<10:41:19, 5.92s/it]
{'loss': 0.4842, 'learning_rate': 1.1886908048878785e-05, 'epoch': 0.46}
+
46%|████▌ | 5455/11952 [1:27:21<10:41:19, 5.92s/it]
46%|████▌ | 5456/11952 [1:27:27<10:41:28, 5.92s/it]
{'loss': 0.4882, 'learning_rate': 1.1884246754058775e-05, 'epoch': 0.46}
+
46%|████▌ | 5456/11952 [1:27:27<10:41:28, 5.92s/it]
46%|████▌ | 5457/11952 [1:27:32<10:28:56, 5.81s/it]
{'loss': 0.4802, 'learning_rate': 1.1881585320867521e-05, 'epoch': 0.46}
+
46%|████▌ | 5457/11952 [1:27:32<10:28:56, 5.81s/it]
46%|████▌ | 5458/11952 [1:27:38<10:27:09, 5.79s/it]
{'loss': 0.4653, 'learning_rate': 1.1878923749500466e-05, 'epoch': 0.46}
+
46%|████▌ | 5458/11952 [1:27:38<10:27:09, 5.79s/it]
46%|████▌ | 5459/11952 [1:27:44<10:26:20, 5.79s/it]
{'loss': 0.4861, 'learning_rate': 1.1876262040153064e-05, 'epoch': 0.46}
+
46%|████▌ | 5459/11952 [1:27:44<10:26:20, 5.79s/it]
46%|████▌ | 5460/11952 [1:27:49<10:29:33, 5.82s/it]
{'loss': 0.4977, 'learning_rate': 1.1873600193020786e-05, 'epoch': 0.46}
+
46%|████▌ | 5460/11952 [1:27:49<10:29:33, 5.82s/it]
46%|████▌ | 5461/11952 [1:27:55<10:21:24, 5.74s/it]
{'loss': 0.4697, 'learning_rate': 1.18709382082991e-05, 'epoch': 0.46}
+
46%|████▌ | 5461/11952 [1:27:55<10:21:24, 5.74s/it]
46%|████▌ | 5462/11952 [1:28:01<10:34:38, 5.87s/it]
{'loss': 0.4973, 'learning_rate': 1.1868276086183494e-05, 'epoch': 0.46}
+
46%|████▌ | 5462/11952 [1:28:01<10:34:38, 5.87s/it]
46%|████▌ | 5463/11952 [1:28:07<10:42:41, 5.94s/it]
{'loss': 0.5125, 'learning_rate': 1.1865613826869463e-05, 'epoch': 0.46}
+
46%|████▌ | 5463/11952 [1:28:07<10:42:41, 5.94s/it]
46%|████▌ | 5464/11952 [1:28:13<10:40:29, 5.92s/it]
{'loss': 0.4998, 'learning_rate': 1.1862951430552514e-05, 'epoch': 0.46}
+
46%|████▌ | 5464/11952 [1:28:13<10:40:29, 5.92s/it]
46%|████▌ | 5465/11952 [1:28:19<10:38:40, 5.91s/it]
{'loss': 0.4609, 'learning_rate': 1.1860288897428158e-05, 'epoch': 0.46}
+
46%|████▌ | 5465/11952 [1:28:19<10:38:40, 5.91s/it]
46%|████▌ | 5466/11952 [1:28:25<10:47:44, 5.99s/it]
{'loss': 0.47, 'learning_rate': 1.1857626227691924e-05, 'epoch': 0.46}
+
46%|████▌ | 5466/11952 [1:28:25<10:47:44, 5.99s/it]
46%|████▌ | 5467/11952 [1:28:31<10:44:48, 5.97s/it]
{'loss': 0.4728, 'learning_rate': 1.1854963421539348e-05, 'epoch': 0.46}
+
46%|████▌ | 5467/11952 [1:28:31<10:44:48, 5.97s/it]
46%|████▌ | 5468/11952 [1:28:37<10:44:34, 5.96s/it]
{'loss': 0.4885, 'learning_rate': 1.185230047916597e-05, 'epoch': 0.46}
+
46%|████▌ | 5468/11952 [1:28:37<10:44:34, 5.96s/it]
46%|████▌ | 5469/11952 [1:28:43<10:37:30, 5.90s/it]
{'loss': 0.49, 'learning_rate': 1.1849637400767351e-05, 'epoch': 0.46}
+
46%|████▌ | 5469/11952 [1:28:43<10:37:30, 5.90s/it]
46%|████▌ | 5470/11952 [1:28:49<10:34:00, 5.87s/it]
{'loss': 0.5007, 'learning_rate': 1.1846974186539055e-05, 'epoch': 0.46}
+
46%|████▌ | 5470/11952 [1:28:49<10:34:00, 5.87s/it]
46%|████▌ | 5471/11952 [1:28:54<10:29:06, 5.82s/it]
{'loss': 0.4694, 'learning_rate': 1.1844310836676658e-05, 'epoch': 0.46}
+
46%|████▌ | 5471/11952 [1:28:54<10:29:06, 5.82s/it]
46%|████▌ | 5472/11952 [1:29:00<10:34:19, 5.87s/it]
{'loss': 0.4736, 'learning_rate': 1.184164735137574e-05, 'epoch': 0.46}
+
46%|████▌ | 5472/11952 [1:29:00<10:34:19, 5.87s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (5158 > 4096). Running this sequence through the model will result in indexing errors
+
46%|████▌ | 5473/11952 [1:29:06<10:35:58, 5.89s/it]
{'loss': 0.5052, 'learning_rate': 1.1838983730831904e-05, 'epoch': 0.46}
+
46%|████▌ | 5473/11952 [1:29:06<10:35:58, 5.89s/it]
46%|████▌ | 5474/11952 [1:29:12<10:32:01, 5.85s/it]
{'loss': 0.4826, 'learning_rate': 1.1836319975240751e-05, 'epoch': 0.46}
+
46%|████▌ | 5474/11952 [1:29:12<10:32:01, 5.85s/it]
46%|████▌ | 5475/11952 [1:29:18<10:34:49, 5.88s/it]
{'loss': 0.4675, 'learning_rate': 1.1833656084797898e-05, 'epoch': 0.46}
+
46%|████▌ | 5475/11952 [1:29:18<10:34:49, 5.88s/it]
46%|████▌ | 5476/11952 [1:29:24<10:42:17, 5.95s/it]
{'loss': 0.4842, 'learning_rate': 1.1830992059698967e-05, 'epoch': 0.46}
+
46%|████▌ | 5476/11952 [1:29:24<10:42:17, 5.95s/it]
46%|████▌ | 5477/11952 [1:29:30<10:33:25, 5.87s/it]
{'loss': 0.4937, 'learning_rate': 1.1828327900139596e-05, 'epoch': 0.46}
+
46%|████▌ | 5477/11952 [1:29:30<10:33:25, 5.87s/it]
46%|████▌ | 5478/11952 [1:29:36<10:28:44, 5.83s/it]
{'loss': 0.4691, 'learning_rate': 1.1825663606315425e-05, 'epoch': 0.46}
+
46%|████▌ | 5478/11952 [1:29:36<10:28:44, 5.83s/it]
46%|████▌ | 5479/11952 [1:29:41<10:30:11, 5.84s/it]
{'loss': 0.4715, 'learning_rate': 1.1822999178422114e-05, 'epoch': 0.46}
+
46%|████▌ | 5479/11952 [1:29:41<10:30:11, 5.84s/it]
46%|████▌ | 5480/11952 [1:29:48<10:41:32, 5.95s/it]
{'loss': 0.4987, 'learning_rate': 1.182033461665533e-05, 'epoch': 0.46}
+
46%|████▌ | 5480/11952 [1:29:48<10:41:32, 5.95s/it]
46%|████▌ | 5481/11952 [1:29:54<10:49:01, 6.02s/it]
{'loss': 0.4855, 'learning_rate': 1.181766992121074e-05, 'epoch': 0.46}
+
46%|████▌ | 5481/11952 [1:29:54<10:49:01, 6.02s/it]
46%|████▌ | 5482/11952 [1:30:00<10:40:12, 5.94s/it]
{'loss': 0.4915, 'learning_rate': 1.1815005092284033e-05, 'epoch': 0.46}
+
46%|████▌ | 5482/11952 [1:30:00<10:40:12, 5.94s/it]
46%|████▌ | 5483/11952 [1:30:05<10:35:39, 5.90s/it]
{'loss': 0.469, 'learning_rate': 1.18123401300709e-05, 'epoch': 0.46}
+
46%|████▌ | 5483/11952 [1:30:05<10:35:39, 5.90s/it]
46%|████▌ | 5484/11952 [1:30:11<10:34:55, 5.89s/it]
{'loss': 0.4964, 'learning_rate': 1.1809675034767043e-05, 'epoch': 0.46}
+
46%|████▌ | 5484/11952 [1:30:11<10:34:55, 5.89s/it]
46%|████▌ | 5485/11952 [1:30:17<10:41:31, 5.95s/it]
{'loss': 0.4829, 'learning_rate': 1.1807009806568181e-05, 'epoch': 0.46}
+
46%|████▌ | 5485/11952 [1:30:17<10:41:31, 5.95s/it]
46%|████▌ | 5486/11952 [1:30:23<10:34:31, 5.89s/it]
{'loss': 0.4707, 'learning_rate': 1.1804344445670034e-05, 'epoch': 0.46}
+
46%|████▌ | 5486/11952 [1:30:23<10:34:31, 5.89s/it]
46%|████▌ | 5487/11952 [1:30:29<10:33:12, 5.88s/it]
{'loss': 0.4788, 'learning_rate': 1.1801678952268338e-05, 'epoch': 0.46}
+
46%|████▌ | 5487/11952 [1:30:29<10:33:12, 5.88s/it]
46%|████▌ | 5488/11952 [1:30:35<10:35:34, 5.90s/it]
{'loss': 0.4759, 'learning_rate': 1.179901332655883e-05, 'epoch': 0.46}
+
46%|████▌ | 5488/11952 [1:30:35<10:35:34, 5.90s/it]
46%|████▌ | 5489/11952 [1:30:41<10:39:18, 5.94s/it]
{'loss': 0.4847, 'learning_rate': 1.1796347568737268e-05, 'epoch': 0.46}
+
46%|████▌ | 5489/11952 [1:30:41<10:39:18, 5.94s/it]
46%|████▌ | 5490/11952 [1:30:47<10:31:06, 5.86s/it]
{'loss': 0.4786, 'learning_rate': 1.1793681678999412e-05, 'epoch': 0.46}
+
46%|████▌ | 5490/11952 [1:30:47<10:31:06, 5.86s/it]
46%|████▌ | 5491/11952 [1:30:52<10:32:04, 5.87s/it]
{'loss': 0.4953, 'learning_rate': 1.1791015657541037e-05, 'epoch': 0.46}
+
46%|████▌ | 5491/11952 [1:30:52<10:32:04, 5.87s/it]
46%|████▌ | 5492/11952 [1:30:58<10:31:44, 5.87s/it]
{'loss': 0.4832, 'learning_rate': 1.1788349504557917e-05, 'epoch': 0.46}
+
46%|████▌ | 5492/11952 [1:30:58<10:31:44, 5.87s/it]
46%|████▌ | 5493/11952 [1:31:04<10:34:26, 5.89s/it]
{'loss': 0.4776, 'learning_rate': 1.1785683220245849e-05, 'epoch': 0.46}
+
46%|████▌ | 5493/11952 [1:31:04<10:34:26, 5.89s/it]
46%|████▌ | 5494/11952 [1:31:10<10:35:35, 5.91s/it]
{'loss': 0.4789, 'learning_rate': 1.1783016804800631e-05, 'epoch': 0.46}
+
46%|████▌ | 5494/11952 [1:31:10<10:35:35, 5.91s/it]
46%|████▌ | 5495/11952 [1:31:16<10:31:09, 5.86s/it]
{'loss': 0.4819, 'learning_rate': 1.1780350258418078e-05, 'epoch': 0.46}
+
46%|████▌ | 5495/11952 [1:31:16<10:31:09, 5.86s/it]
46%|████▌ | 5496/11952 [1:31:22<10:28:37, 5.84s/it]
{'loss': 0.4795, 'learning_rate': 1.1777683581294003e-05, 'epoch': 0.46}
+
46%|████▌ | 5496/11952 [1:31:22<10:28:37, 5.84s/it]
46%|████▌ | 5497/11952 [1:31:28<10:37:01, 5.92s/it]
{'loss': 0.4736, 'learning_rate': 1.1775016773624246e-05, 'epoch': 0.46}
+
46%|████▌ | 5497/11952 [1:31:28<10:37:01, 5.92s/it]
46%|████▌ | 5498/11952 [1:31:34<10:35:51, 5.91s/it]
{'loss': 0.5113, 'learning_rate': 1.1772349835604638e-05, 'epoch': 0.46}
+
46%|████▌ | 5498/11952 [1:31:34<10:35:51, 5.91s/it]
46%|████▌ | 5499/11952 [1:31:40<10:30:44, 5.86s/it]
{'loss': 0.4702, 'learning_rate': 1.1769682767431026e-05, 'epoch': 0.46}
+
46%|████▌ | 5499/11952 [1:31:40<10:30:44, 5.86s/it]07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+16 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
46%|████▌ | 5500/11952 [1:31:46<10:49:01, 6.04s/it]2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4802, 'learning_rate': 1.1767015569299274e-05, 'epoch': 0.46}
+
46%|████▌ | 5500/11952 [1:31:46<10:49:01, 6.04s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
46%|████▌ | 5501/11952 [1:32:15<22:57:20, 12.81s/it]
{'loss': 0.4804, 'learning_rate': 1.1764348241405249e-05, 'epoch': 0.46}
+
46%|████▌ | 5501/11952 [1:32:15<22:57:20, 12.81s/it]
46%|████▌ | 5502/11952 [1:32:20<19:06:24, 10.66s/it]
{'loss': 0.4852, 'learning_rate': 1.1761680783944829e-05, 'epoch': 0.46}
+
46%|████▌ | 5502/11952 [1:32:20<19:06:24, 10.66s/it]
46%|████▌ | 5503/11952 [1:32:26<16:38:06, 9.29s/it]
{'loss': 0.4836, 'learning_rate': 1.1759013197113895e-05, 'epoch': 0.46}
+
46%|████▌ | 5503/11952 [1:32:26<16:38:06, 9.29s/it]
46%|████▌ | 5504/11952 [1:32:32<14:42:18, 8.21s/it]
{'loss': 0.4939, 'learning_rate': 1.175634548110835e-05, 'epoch': 0.46}
+
46%|████▌ | 5504/11952 [1:32:32<14:42:18, 8.21s/it]
46%|████▌ | 5505/11952 [1:32:38<13:27:07, 7.51s/it]
{'loss': 0.5088, 'learning_rate': 1.1753677636124101e-05, 'epoch': 0.46}
+
46%|████▌ | 5505/11952 [1:32:38<13:27:07, 7.51s/it]
46%|████▌ | 5506/11952 [1:32:44<12:41:18, 7.09s/it]
{'loss': 0.471, 'learning_rate': 1.1751009662357059e-05, 'epoch': 0.46}
+
46%|████▌ | 5506/11952 [1:32:44<12:41:18, 7.09s/it]
46%|████▌ | 5507/11952 [1:32:50<12:15:35, 6.85s/it]
{'loss': 0.489, 'learning_rate': 1.1748341560003149e-05, 'epoch': 0.46}
+
46%|████▌ | 5507/11952 [1:32:50<12:15:35, 6.85s/it]
46%|████▌ | 5508/11952 [1:32:56<11:38:52, 6.51s/it]
{'loss': 0.4822, 'learning_rate': 1.174567332925831e-05, 'epoch': 0.46}
+
46%|████▌ | 5508/11952 [1:32:56<11:38:52, 6.51s/it]
46%|████▌ | 5509/11952 [1:33:02<11:10:33, 6.24s/it]
{'loss': 0.4794, 'learning_rate': 1.174300497031848e-05, 'epoch': 0.46}
+
46%|████▌ | 5509/11952 [1:33:02<11:10:33, 6.24s/it]
46%|████▌ | 5510/11952 [1:33:07<10:52:28, 6.08s/it]
{'loss': 0.4821, 'learning_rate': 1.1740336483379613e-05, 'epoch': 0.46}
+
46%|████▌ | 5510/11952 [1:33:07<10:52:28, 6.08s/it]
46%|████▌ | 5511/11952 [1:33:13<10:39:48, 5.96s/it]
{'loss': 0.4755, 'learning_rate': 1.1737667868637674e-05, 'epoch': 0.46}
+
46%|████▌ | 5511/11952 [1:33:13<10:39:48, 5.96s/it]
46%|████▌ | 5512/11952 [1:33:19<10:32:18, 5.89s/it]
{'loss': 0.4849, 'learning_rate': 1.1734999126288637e-05, 'epoch': 0.46}
+
46%|████▌ | 5512/11952 [1:33:19<10:32:18, 5.89s/it]
46%|████▌ | 5513/11952 [1:33:25<10:39:48, 5.96s/it]
{'loss': 0.4922, 'learning_rate': 1.1732330256528477e-05, 'epoch': 0.46}
+
46%|████▌ | 5513/11952 [1:33:25<10:39:48, 5.96s/it]
46%|████▌ | 5514/11952 [1:33:30<10:28:55, 5.86s/it]
{'loss': 0.4849, 'learning_rate': 1.1729661259553193e-05, 'epoch': 0.46}
+
46%|████▌ | 5514/11952 [1:33:30<10:28:55, 5.86s/it]
46%|████▌ | 5515/11952 [1:33:36<10:32:03, 5.89s/it]
{'loss': 0.4955, 'learning_rate': 1.1726992135558776e-05, 'epoch': 0.46}
+
46%|████▌ | 5515/11952 [1:33:36<10:32:03, 5.89s/it]
46%|████▌ | 5516/11952 [1:33:42<10:28:41, 5.86s/it]
{'loss': 0.4834, 'learning_rate': 1.1724322884741242e-05, 'epoch': 0.46}
+
46%|████▌ | 5516/11952 [1:33:42<10:28:41, 5.86s/it]
46%|████▌ | 5517/11952 [1:33:48<10:22:34, 5.80s/it]
{'loss': 0.5012, 'learning_rate': 1.1721653507296604e-05, 'epoch': 0.46}
+
46%|████▌ | 5517/11952 [1:33:48<10:22:34, 5.80s/it]
46%|████▌ | 5518/11952 [1:33:54<10:21:52, 5.80s/it]
{'loss': 0.4802, 'learning_rate': 1.1718984003420899e-05, 'epoch': 0.46}
+
46%|████▌ | 5518/11952 [1:33:54<10:21:52, 5.80s/it]
46%|████▌ | 5519/11952 [1:33:59<10:17:23, 5.76s/it]
{'loss': 0.4789, 'learning_rate': 1.1716314373310154e-05, 'epoch': 0.46}
+
46%|████▌ | 5519/11952 [1:33:59<10:17:23, 5.76s/it]
46%|████▌ | 5520/11952 [1:34:06<10:30:08, 5.88s/it]
{'loss': 0.4883, 'learning_rate': 1.171364461716042e-05, 'epoch': 0.46}
+
46%|████▌ | 5520/11952 [1:34:06<10:30:08, 5.88s/it]
46%|████▌ | 5521/11952 [1:34:11<10:31:17, 5.89s/it]
{'loss': 0.4702, 'learning_rate': 1.1710974735167755e-05, 'epoch': 0.46}
+
46%|████▌ | 5521/11952 [1:34:11<10:31:17, 5.89s/it]
46%|████▌ | 5522/11952 [1:34:17<10:21:01, 5.79s/it]
{'loss': 0.4768, 'learning_rate': 1.1708304727528223e-05, 'epoch': 0.46}
+
46%|████▌ | 5522/11952 [1:34:17<10:21:01, 5.79s/it]
46%|████▌ | 5523/11952 [1:34:23<10:20:01, 5.79s/it]
{'loss': 0.4884, 'learning_rate': 1.1705634594437893e-05, 'epoch': 0.46}
+
46%|████▌ | 5523/11952 [1:34:23<10:20:01, 5.79s/it]
46%|████▌ | 5524/11952 [1:34:28<10:17:06, 5.76s/it]
{'loss': 0.4935, 'learning_rate': 1.1702964336092857e-05, 'epoch': 0.46}
+
46%|████▌ | 5524/11952 [1:34:28<10:17:06, 5.76s/it]
46%|████▌ | 5525/11952 [1:34:35<10:29:50, 5.88s/it]
{'loss': 0.4804, 'learning_rate': 1.17002939526892e-05, 'epoch': 0.46}
+
46%|████▌ | 5525/11952 [1:34:35<10:29:50, 5.88s/it]
46%|████▌ | 5526/11952 [1:34:40<10:27:52, 5.86s/it]
{'loss': 0.4896, 'learning_rate': 1.169762344442303e-05, 'epoch': 0.46}
+
46%|████▌ | 5526/11952 [1:34:40<10:27:52, 5.86s/it]
46%|████▌ | 5527/11952 [1:34:46<10:26:49, 5.85s/it]
{'loss': 0.4846, 'learning_rate': 1.1694952811490451e-05, 'epoch': 0.46}
+
46%|████▌ | 5527/11952 [1:34:46<10:26:49, 5.85s/it]
46%|████▋ | 5528/11952 [1:34:52<10:24:57, 5.84s/it]
{'loss': 0.4812, 'learning_rate': 1.1692282054087594e-05, 'epoch': 0.46}
+
46%|████▋ | 5528/11952 [1:34:52<10:24:57, 5.84s/it]
46%|████▋ | 5529/11952 [1:34:58<10:26:51, 5.86s/it]
{'loss': 0.5226, 'learning_rate': 1.1689611172410577e-05, 'epoch': 0.46}
+
46%|████▋ | 5529/11952 [1:34:58<10:26:51, 5.86s/it]
46%|████▋ | 5530/11952 [1:35:04<10:18:04, 5.77s/it]
{'loss': 0.4731, 'learning_rate': 1.1686940166655543e-05, 'epoch': 0.46}
+
46%|████▋ | 5530/11952 [1:35:04<10:18:04, 5.77s/it]
46%|████▋ | 5531/11952 [1:35:09<10:23:05, 5.82s/it]
{'loss': 0.475, 'learning_rate': 1.1684269037018641e-05, 'epoch': 0.46}
+
46%|████▋ | 5531/11952 [1:35:09<10:23:05, 5.82s/it]
46%|████▋ | 5532/11952 [1:35:16<10:34:28, 5.93s/it]
{'loss': 0.5193, 'learning_rate': 1.1681597783696027e-05, 'epoch': 0.46}
+
46%|████▋ | 5532/11952 [1:35:16<10:34:28, 5.93s/it]
46%|████▋ | 5533/11952 [1:35:22<10:33:52, 5.92s/it]
{'loss': 0.4724, 'learning_rate': 1.1678926406883866e-05, 'epoch': 0.46}
+
46%|████▋ | 5533/11952 [1:35:22<10:33:52, 5.92s/it]
46%|████▋ | 5534/11952 [1:35:28<10:34:25, 5.93s/it]
{'loss': 0.4698, 'learning_rate': 1.1676254906778331e-05, 'epoch': 0.46}
+
46%|████▋ | 5534/11952 [1:35:28<10:34:25, 5.93s/it]
46%|████▋ | 5535/11952 [1:35:33<10:31:46, 5.91s/it]
{'loss': 0.4757, 'learning_rate': 1.1673583283575607e-05, 'epoch': 0.46}
+
46%|████▋ | 5535/11952 [1:35:33<10:31:46, 5.91s/it]
46%|████▋ | 5536/11952 [1:35:39<10:34:03, 5.93s/it]
{'loss': 0.48, 'learning_rate': 1.1670911537471889e-05, 'epoch': 0.46}
+
46%|████▋ | 5536/11952 [1:35:39<10:34:03, 5.93s/it]
46%|████▋ | 5537/11952 [1:35:45<10:32:04, 5.91s/it]
{'loss': 0.4737, 'learning_rate': 1.1668239668663377e-05, 'epoch': 0.46}
+
46%|████▋ | 5537/11952 [1:35:45<10:32:04, 5.91s/it]
46%|████▋ | 5538/11952 [1:35:51<10:23:48, 5.84s/it]
{'loss': 0.4547, 'learning_rate': 1.1665567677346285e-05, 'epoch': 0.46}
+
46%|████▋ | 5538/11952 [1:35:51<10:23:48, 5.84s/it]
46%|████▋ | 5539/11952 [1:35:57<10:29:17, 5.89s/it]
{'loss': 0.4934, 'learning_rate': 1.166289556371683e-05, 'epoch': 0.46}
+
46%|████▋ | 5539/11952 [1:35:57<10:29:17, 5.89s/it]
46%|████▋ | 5540/11952 [1:36:03<10:34:55, 5.94s/it]
{'loss': 0.4754, 'learning_rate': 1.1660223327971239e-05, 'epoch': 0.46}
+
46%|████▋ | 5540/11952 [1:36:03<10:34:55, 5.94s/it]
46%|████▋ | 5541/11952 [1:36:09<10:27:09, 5.87s/it]
{'loss': 0.473, 'learning_rate': 1.1657550970305752e-05, 'epoch': 0.46}
+
46%|████▋ | 5541/11952 [1:36:09<10:27:09, 5.87s/it]
46%|████▋ | 5542/11952 [1:36:14<10:22:58, 5.83s/it]
{'loss': 0.4748, 'learning_rate': 1.1654878490916617e-05, 'epoch': 0.46}
+
46%|████▋ | 5542/11952 [1:36:14<10:22:58, 5.83s/it]
46%|████▋ | 5543/11952 [1:36:20<10:24:02, 5.84s/it]
{'loss': 0.486, 'learning_rate': 1.165220589000009e-05, 'epoch': 0.46}
+
46%|████▋ | 5543/11952 [1:36:20<10:24:02, 5.84s/it]
46%|████▋ | 5544/11952 [1:36:26<10:17:21, 5.78s/it]
{'loss': 0.4595, 'learning_rate': 1.1649533167752434e-05, 'epoch': 0.46}
+
46%|████▋ | 5544/11952 [1:36:26<10:17:21, 5.78s/it]
46%|████▋ | 5545/11952 [1:36:32<10:21:39, 5.82s/it]
{'loss': 0.4842, 'learning_rate': 1.164686032436992e-05, 'epoch': 0.46}
+
46%|████▋ | 5545/11952 [1:36:32<10:21:39, 5.82s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (4399 > 4096). Running this sequence through the model will result in indexing errors
+
46%|████▋ | 5546/11952 [1:36:38<10:22:46, 5.83s/it]
{'loss': 0.4897, 'learning_rate': 1.1644187360048838e-05, 'epoch': 0.46}
+
46%|████▋ | 5546/11952 [1:36:38<10:22:46, 5.83s/it]
46%|████▋ | 5547/11952 [1:36:43<10:20:35, 5.81s/it]
{'loss': 0.4752, 'learning_rate': 1.164151427498547e-05, 'epoch': 0.46}
+
46%|████▋ | 5547/11952 [1:36:43<10:20:35, 5.81s/it]
46%|████▋ | 5548/11952 [1:36:49<10:13:50, 5.75s/it]
{'loss': 0.4937, 'learning_rate': 1.1638841069376125e-05, 'epoch': 0.46}
+
46%|████▋ | 5548/11952 [1:36:49<10:13:50, 5.75s/it]
46%|████▋ | 5549/11952 [1:36:55<10:15:49, 5.77s/it]
{'loss': 0.4841, 'learning_rate': 1.1636167743417111e-05, 'epoch': 0.46}
+
46%|████▋ | 5549/11952 [1:36:55<10:15:49, 5.77s/it]6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
46%|████▋ | 5550/11952 [1:37:01<10:14:29, 5.76s/it]5 AutoResumeHook: Checking whether to suspend...
+24 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4826, 'learning_rate': 1.1633494297304738e-05, 'epoch': 0.46}
+
46%|████▋ | 5550/11952 [1:37:01<10:14:29, 5.76s/it]
46%|████▋ | 5551/11952 [1:37:07<10:21:36, 5.83s/it]
{'loss': 0.4777, 'learning_rate': 1.163082073123534e-05, 'epoch': 0.46}
+
46%|████▋ | 5551/11952 [1:37:07<10:21:36, 5.83s/it]
46%|████▋ | 5552/11952 [1:37:13<10:33:42, 5.94s/it]
{'loss': 0.4806, 'learning_rate': 1.1628147045405248e-05, 'epoch': 0.46}
+
46%|████▋ | 5552/11952 [1:37:13<10:33:42, 5.94s/it]
46%|████▋ | 5553/11952 [1:37:19<10:37:26, 5.98s/it]
{'loss': 0.4643, 'learning_rate': 1.1625473240010814e-05, 'epoch': 0.46}
+
46%|████▋ | 5553/11952 [1:37:19<10:37:26, 5.98s/it]
46%|████▋ | 5554/11952 [1:37:25<10:34:45, 5.95s/it]
{'loss': 0.5037, 'learning_rate': 1.1622799315248382e-05, 'epoch': 0.46}
+
46%|████▋ | 5554/11952 [1:37:25<10:34:45, 5.95s/it]
46%|████▋ | 5555/11952 [1:37:30<10:26:56, 5.88s/it]
{'loss': 0.4654, 'learning_rate': 1.1620125271314322e-05, 'epoch': 0.46}
+
46%|████▋ | 5555/11952 [1:37:30<10:26:56, 5.88s/it]
46%|████▋ | 5556/11952 [1:37:36<10:16:16, 5.78s/it]
{'loss': 0.4785, 'learning_rate': 1.1617451108404996e-05, 'epoch': 0.46}
+
46%|████▋ | 5556/11952 [1:37:36<10:16:16, 5.78s/it]
46%|████▋ | 5557/11952 [1:37:42<10:27:55, 5.89s/it]
{'loss': 0.4712, 'learning_rate': 1.1614776826716791e-05, 'epoch': 0.46}
+
46%|████▋ | 5557/11952 [1:37:42<10:27:55, 5.89s/it]
47%|████▋ | 5558/11952 [1:37:48<10:23:26, 5.85s/it]
{'loss': 0.4797, 'learning_rate': 1.161210242644609e-05, 'epoch': 0.47}
+
47%|████▋ | 5558/11952 [1:37:48<10:23:26, 5.85s/it]
47%|████▋ | 5559/11952 [1:37:54<10:27:15, 5.89s/it]
{'loss': 0.4672, 'learning_rate': 1.1609427907789294e-05, 'epoch': 0.47}
+
47%|████▋ | 5559/11952 [1:37:54<10:27:15, 5.89s/it]
47%|████▋ | 5560/11952 [1:38:00<10:30:52, 5.92s/it]
{'loss': 0.5135, 'learning_rate': 1.160675327094281e-05, 'epoch': 0.47}
+
47%|████▋ | 5560/11952 [1:38:00<10:30:52, 5.92s/it]
47%|████▋ | 5561/11952 [1:38:06<10:33:17, 5.95s/it]
{'loss': 0.5052, 'learning_rate': 1.160407851610304e-05, 'epoch': 0.47}
+
47%|████▋ | 5561/11952 [1:38:06<10:33:17, 5.95s/it]
47%|████▋ | 5562/11952 [1:38:12<10:25:32, 5.87s/it]
{'loss': 0.4833, 'learning_rate': 1.1601403643466422e-05, 'epoch': 0.47}
+
47%|████▋ | 5562/11952 [1:38:12<10:25:32, 5.87s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
47%|████▋ | 5563/11952 [1:38:18<10:33:41, 5.95s/it]
{'loss': 0.5247, 'learning_rate': 1.159872865322938e-05, 'epoch': 0.47}
+
47%|████▋ | 5563/11952 [1:38:18<10:33:41, 5.95s/it]
47%|████▋ | 5564/11952 [1:38:24<10:34:27, 5.96s/it]
{'loss': 0.5032, 'learning_rate': 1.1596053545588355e-05, 'epoch': 0.47}
+
47%|████▋ | 5564/11952 [1:38:24<10:34:27, 5.96s/it]
47%|████▋ | 5565/11952 [1:38:30<10:35:50, 5.97s/it]
{'loss': 0.4918, 'learning_rate': 1.1593378320739796e-05, 'epoch': 0.47}
+
47%|████▋ | 5565/11952 [1:38:30<10:35:50, 5.97s/it]
47%|████▋ | 5566/11952 [1:38:36<10:46:34, 6.07s/it]
{'loss': 0.4745, 'learning_rate': 1.1590702978880159e-05, 'epoch': 0.47}
+
47%|████▋ | 5566/11952 [1:38:36<10:46:34, 6.07s/it]
47%|████▋ | 5567/11952 [1:38:42<10:37:39, 5.99s/it]
{'loss': 0.4933, 'learning_rate': 1.1588027520205915e-05, 'epoch': 0.47}
+
47%|████▋ | 5567/11952 [1:38:42<10:37:39, 5.99s/it]
47%|████▋ | 5568/11952 [1:38:48<10:28:39, 5.91s/it]
{'loss': 0.4832, 'learning_rate': 1.1585351944913532e-05, 'epoch': 0.47}
+
47%|████▋ | 5568/11952 [1:38:48<10:28:39, 5.91s/it]
47%|████▋ | 5569/11952 [1:38:53<10:21:41, 5.84s/it]
{'loss': 0.4923, 'learning_rate': 1.1582676253199498e-05, 'epoch': 0.47}
+
47%|████▋ | 5569/11952 [1:38:53<10:21:41, 5.84s/it]
47%|████▋ | 5570/11952 [1:38:59<10:26:32, 5.89s/it]
{'loss': 0.4878, 'learning_rate': 1.1580000445260305e-05, 'epoch': 0.47}
+
47%|████▋ | 5570/11952 [1:38:59<10:26:32, 5.89s/it]
47%|████▋ | 5571/11952 [1:39:05<10:25:13, 5.88s/it]
{'loss': 0.4873, 'learning_rate': 1.1577324521292445e-05, 'epoch': 0.47}
+
47%|████▋ | 5571/11952 [1:39:05<10:25:13, 5.88s/it]
47%|████▋ | 5572/11952 [1:39:11<10:28:58, 5.92s/it]
{'loss': 0.4808, 'learning_rate': 1.1574648481492434e-05, 'epoch': 0.47}
+
47%|████▋ | 5572/11952 [1:39:11<10:28:58, 5.92s/it]
47%|████▋ | 5573/11952 [1:39:17<10:36:13, 5.98s/it]
{'loss': 0.4868, 'learning_rate': 1.1571972326056794e-05, 'epoch': 0.47}
+
47%|████▋ | 5573/11952 [1:39:17<10:36:13, 5.98s/it]
47%|████▋ | 5574/11952 [1:39:23<10:30:29, 5.93s/it]
{'loss': 0.49, 'learning_rate': 1.156929605518204e-05, 'epoch': 0.47}
+
47%|████▋ | 5574/11952 [1:39:23<10:30:29, 5.93s/it]
47%|████▋ | 5575/11952 [1:39:29<10:29:38, 5.92s/it]
{'loss': 0.468, 'learning_rate': 1.1566619669064709e-05, 'epoch': 0.47}
+
47%|████▋ | 5575/11952 [1:39:29<10:29:38, 5.92s/it]
47%|████▋ | 5576/11952 [1:39:35<10:20:32, 5.84s/it]
{'loss': 0.4702, 'learning_rate': 1.1563943167901348e-05, 'epoch': 0.47}
+
47%|████▋ | 5576/11952 [1:39:35<10:20:32, 5.84s/it]
47%|████▋ | 5577/11952 [1:39:41<10:23:04, 5.86s/it]
{'loss': 0.4777, 'learning_rate': 1.1561266551888505e-05, 'epoch': 0.47}
+
47%|████▋ | 5577/11952 [1:39:41<10:23:04, 5.86s/it]
47%|████▋ | 5578/11952 [1:39:47<10:27:10, 5.90s/it]
{'loss': 0.4819, 'learning_rate': 1.1558589821222742e-05, 'epoch': 0.47}
+
47%|████▋ | 5578/11952 [1:39:47<10:27:10, 5.90s/it]
47%|████▋ | 5579/11952 [1:39:53<10:43:41, 6.06s/it]
{'loss': 0.4927, 'learning_rate': 1.1555912976100623e-05, 'epoch': 0.47}
+
47%|████▋ | 5579/11952 [1:39:53<10:43:41, 6.06s/it]
47%|████▋ | 5580/11952 [1:39:59<10:49:41, 6.12s/it]
{'loss': 0.4894, 'learning_rate': 1.155323601671873e-05, 'epoch': 0.47}
+
47%|████▋ | 5580/11952 [1:39:59<10:49:41, 6.12s/it]
47%|████▋ | 5581/11952 [1:40:05<10:40:15, 6.03s/it]
{'loss': 0.4895, 'learning_rate': 1.155055894327364e-05, 'epoch': 0.47}
+
47%|████▋ | 5581/11952 [1:40:05<10:40:15, 6.03s/it]
47%|████▋ | 5582/11952 [1:40:11<10:29:32, 5.93s/it]
{'loss': 0.4753, 'learning_rate': 1.1547881755961952e-05, 'epoch': 0.47}
+
47%|████▋ | 5582/11952 [1:40:11<10:29:32, 5.93s/it]
47%|████▋ | 5583/11952 [1:40:17<10:31:16, 5.95s/it]
{'loss': 0.483, 'learning_rate': 1.1545204454980268e-05, 'epoch': 0.47}
+
47%|████▋ | 5583/11952 [1:40:17<10:31:16, 5.95s/it]
47%|████▋ | 5584/11952 [1:40:23<10:33:54, 5.97s/it]
{'loss': 0.4889, 'learning_rate': 1.1542527040525192e-05, 'epoch': 0.47}
+
47%|████▋ | 5584/11952 [1:40:23<10:33:54, 5.97s/it]
47%|████▋ | 5585/11952 [1:40:28<10:25:02, 5.89s/it]
{'loss': 0.4702, 'learning_rate': 1.1539849512793348e-05, 'epoch': 0.47}
+
47%|████▋ | 5585/11952 [1:40:28<10:25:02, 5.89s/it]
47%|████▋ | 5586/11952 [1:40:34<10:24:05, 5.88s/it]
{'loss': 0.4892, 'learning_rate': 1.1537171871981363e-05, 'epoch': 0.47}
+
47%|████▋ | 5586/11952 [1:40:34<10:24:05, 5.88s/it]
47%|████▋ | 5587/11952 [1:40:40<10:21:11, 5.86s/it]
{'loss': 0.4854, 'learning_rate': 1.1534494118285865e-05, 'epoch': 0.47}
+
47%|████▋ | 5587/11952 [1:40:40<10:21:11, 5.86s/it]
47%|████▋ | 5588/11952 [1:40:46<10:21:11, 5.86s/it]
{'loss': 0.4915, 'learning_rate': 1.1531816251903503e-05, 'epoch': 0.47}
+
47%|████▋ | 5588/11952 [1:40:46<10:21:11, 5.86s/it]
47%|████▋ | 5589/11952 [1:40:52<10:24:53, 5.89s/it]
{'loss': 0.4627, 'learning_rate': 1.1529138273030927e-05, 'epoch': 0.47}
+
47%|████▋ | 5589/11952 [1:40:52<10:24:53, 5.89s/it]
47%|████▋ | 5590/11952 [1:40:58<10:25:45, 5.90s/it]
{'loss': 0.4904, 'learning_rate': 1.1526460181864799e-05, 'epoch': 0.47}
+
47%|████▋ | 5590/11952 [1:40:58<10:25:45, 5.90s/it]
47%|████▋ | 5591/11952 [1:41:04<10:27:11, 5.92s/it]
{'loss': 0.5022, 'learning_rate': 1.152378197860178e-05, 'epoch': 0.47}
+
47%|████▋ | 5591/11952 [1:41:04<10:27:11, 5.92s/it]
47%|████▋ | 5592/11952 [1:41:10<10:52:14, 6.15s/it]
{'loss': 0.4974, 'learning_rate': 1.1521103663438551e-05, 'epoch': 0.47}
+
47%|████▋ | 5592/11952 [1:41:11<10:52:14, 6.15s/it]
47%|████▋ | 5593/11952 [1:41:16<10:44:00, 6.08s/it]
{'loss': 0.48, 'learning_rate': 1.1518425236571797e-05, 'epoch': 0.47}
+
47%|████▋ | 5593/11952 [1:41:16<10:44:00, 6.08s/it]
47%|████▋ | 5594/11952 [1:41:22<10:27:02, 5.92s/it]
{'loss': 0.4676, 'learning_rate': 1.1515746698198211e-05, 'epoch': 0.47}
+
47%|████▋ | 5594/11952 [1:41:22<10:27:02, 5.92s/it]
47%|████▋ | 5595/11952 [1:41:27<10:15:22, 5.81s/it]
{'loss': 0.4756, 'learning_rate': 1.1513068048514489e-05, 'epoch': 0.47}
+
47%|████▋ | 5595/11952 [1:41:27<10:15:22, 5.81s/it]
47%|████▋ | 5596/11952 [1:41:34<10:28:35, 5.93s/it]
{'loss': 0.4957, 'learning_rate': 1.1510389287717345e-05, 'epoch': 0.47}
+
47%|████▋ | 5596/11952 [1:41:34<10:28:35, 5.93s/it]
47%|████▋ | 5597/11952 [1:41:40<10:25:15, 5.90s/it]
{'loss': 0.4611, 'learning_rate': 1.150771041600349e-05, 'epoch': 0.47}
+
47%|████▋ | 5597/11952 [1:41:40<10:25:15, 5.90s/it]
47%|████▋ | 5598/11952 [1:41:45<10:17:54, 5.83s/it]
{'loss': 0.4657, 'learning_rate': 1.1505031433569658e-05, 'epoch': 0.47}
+
47%|████▋ | 5598/11952 [1:41:45<10:17:54, 5.83s/it]
47%|████▋ | 5599/11952 [1:41:51<10:16:00, 5.82s/it]
{'loss': 0.4936, 'learning_rate': 1.1502352340612576e-05, 'epoch': 0.47}
+
47%|████▋ | 5599/11952 [1:41:51<10:16:00, 5.82s/it]7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
47%|████▋ | 5600/11952 [1:41:57<10:24:13, 5.90s/it]3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4698, 'learning_rate': 1.1499673137328986e-05, 'epoch': 0.47}
+
47%|████▋ | 5600/11952 [1:41:57<10:24:13, 5.90s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
47%|████▋ | 5601/11952 [1:42:24<21:26:20, 12.15s/it]
{'loss': 0.4816, 'learning_rate': 1.1496993823915639e-05, 'epoch': 0.47}
+
47%|████▋ | 5601/11952 [1:42:24<21:26:20, 12.15s/it]
47%|████▋ | 5602/11952 [1:42:29<17:59:25, 10.20s/it]
{'loss': 0.4927, 'learning_rate': 1.1494314400569288e-05, 'epoch': 0.47}
+
47%|████▋ | 5602/11952 [1:42:29<17:59:25, 10.20s/it]
47%|████▋ | 5603/11952 [1:42:35<15:37:14, 8.86s/it]
{'loss': 0.4541, 'learning_rate': 1.1491634867486707e-05, 'epoch': 0.47}
+
47%|████▋ | 5603/11952 [1:42:35<15:37:14, 8.86s/it]
47%|████▋ | 5604/11952 [1:42:41<14:10:30, 8.04s/it]
{'loss': 0.48, 'learning_rate': 1.1488955224864667e-05, 'epoch': 0.47}
+
47%|████▋ | 5604/11952 [1:42:41<14:10:30, 8.04s/it]
47%|████▋ | 5605/11952 [1:42:47<13:00:11, 7.38s/it]
{'loss': 0.4936, 'learning_rate': 1.1486275472899943e-05, 'epoch': 0.47}
+
47%|████▋ | 5605/11952 [1:42:47<13:00:11, 7.38s/it]
47%|████▋ | 5606/11952 [1:42:53<12:14:09, 6.94s/it]
{'loss': 0.4853, 'learning_rate': 1.1483595611789336e-05, 'epoch': 0.47}
+
47%|████▋ | 5606/11952 [1:42:53<12:14:09, 6.94s/it]
47%|████▋ | 5607/11952 [1:42:59<11:51:42, 6.73s/it]
{'loss': 0.4817, 'learning_rate': 1.1480915641729633e-05, 'epoch': 0.47}
+
47%|████▋ | 5607/11952 [1:42:59<11:51:42, 6.73s/it]
47%|████▋ | 5608/11952 [1:43:05<11:22:06, 6.45s/it]
{'loss': 0.4931, 'learning_rate': 1.147823556291765e-05, 'epoch': 0.47}
+
47%|████▋ | 5608/11952 [1:43:05<11:22:06, 6.45s/it]
47%|████▋ | 5609/11952 [1:43:11<10:57:13, 6.22s/it]
{'loss': 0.4849, 'learning_rate': 1.1475555375550191e-05, 'epoch': 0.47}
+
47%|████▋ | 5609/11952 [1:43:11<10:57:13, 6.22s/it]
47%|████▋ | 5610/11952 [1:43:17<10:42:57, 6.08s/it]
{'loss': 0.4649, 'learning_rate': 1.1472875079824087e-05, 'epoch': 0.47}
+
47%|████▋ | 5610/11952 [1:43:17<10:42:57, 6.08s/it]
47%|████▋ | 5611/11952 [1:43:22<10:30:37, 5.97s/it]
{'loss': 0.4762, 'learning_rate': 1.1470194675936159e-05, 'epoch': 0.47}
+
47%|████▋ | 5611/11952 [1:43:22<10:30:37, 5.97s/it]
47%|████▋ | 5612/11952 [1:43:28<10:17:07, 5.84s/it]
{'loss': 0.4908, 'learning_rate': 1.1467514164083252e-05, 'epoch': 0.47}
+
47%|████▋ | 5612/11952 [1:43:28<10:17:07, 5.84s/it]
47%|████▋ | 5613/11952 [1:43:34<10:19:31, 5.86s/it]
{'loss': 0.4826, 'learning_rate': 1.1464833544462203e-05, 'epoch': 0.47}
+
47%|████▋ | 5613/11952 [1:43:34<10:19:31, 5.86s/it]
47%|████▋ | 5614/11952 [1:43:40<10:17:26, 5.85s/it]
{'loss': 0.4964, 'learning_rate': 1.1462152817269879e-05, 'epoch': 0.47}
+
47%|████▋ | 5614/11952 [1:43:40<10:17:26, 5.85s/it]
47%|████▋ | 5615/11952 [1:43:45<10:10:28, 5.78s/it]
{'loss': 0.4881, 'learning_rate': 1.145947198270313e-05, 'epoch': 0.47}
+
47%|████▋ | 5615/11952 [1:43:45<10:10:28, 5.78s/it]
47%|████▋ | 5616/11952 [1:43:51<10:12:36, 5.80s/it]
{'loss': 0.4719, 'learning_rate': 1.1456791040958828e-05, 'epoch': 0.47}
+
47%|████▋ | 5616/11952 [1:43:51<10:12:36, 5.80s/it]
47%|████▋ | 5617/11952 [1:43:57<10:14:29, 5.82s/it]
{'loss': 0.4977, 'learning_rate': 1.1454109992233851e-05, 'epoch': 0.47}
+
47%|████▋ | 5617/11952 [1:43:57<10:14:29, 5.82s/it]
47%|████▋ | 5618/11952 [1:44:03<10:18:59, 5.86s/it]
{'loss': 0.4921, 'learning_rate': 1.1451428836725087e-05, 'epoch': 0.47}
+
47%|████▋ | 5618/11952 [1:44:03<10:18:59, 5.86s/it]
47%|████▋ | 5619/11952 [1:44:09<10:19:46, 5.87s/it]
{'loss': 0.476, 'learning_rate': 1.1448747574629424e-05, 'epoch': 0.47}
+
47%|████▋ | 5619/11952 [1:44:09<10:19:46, 5.87s/it]
47%|████▋ | 5620/11952 [1:44:14<10:15:23, 5.83s/it]
{'loss': 0.4831, 'learning_rate': 1.1446066206143766e-05, 'epoch': 0.47}
+
47%|████▋ | 5620/11952 [1:44:14<10:15:23, 5.83s/it]
47%|████▋ | 5621/11952 [1:44:21<10:26:27, 5.94s/it]
{'loss': 0.4824, 'learning_rate': 1.1443384731465021e-05, 'epoch': 0.47}
+
47%|████▋ | 5621/11952 [1:44:21<10:26:27, 5.94s/it]
47%|████▋ | 5622/11952 [1:44:26<10:15:45, 5.84s/it]
{'loss': 0.4794, 'learning_rate': 1.1440703150790102e-05, 'epoch': 0.47}
+
47%|████▋ | 5622/11952 [1:44:26<10:15:45, 5.84s/it]
47%|████▋ | 5623/11952 [1:44:32<10:15:29, 5.83s/it]
{'loss': 0.4919, 'learning_rate': 1.1438021464315939e-05, 'epoch': 0.47}
+
47%|████▋ | 5623/11952 [1:44:32<10:15:29, 5.83s/it]
47%|████▋ | 5624/11952 [1:44:38<10:12:16, 5.81s/it]
{'loss': 0.4893, 'learning_rate': 1.143533967223946e-05, 'epoch': 0.47}
+
47%|████▋ | 5624/11952 [1:44:38<10:12:16, 5.81s/it]
47%|████▋ | 5625/11952 [1:44:43<10:07:03, 5.76s/it]
{'loss': 0.4674, 'learning_rate': 1.1432657774757607e-05, 'epoch': 0.47}
+
47%|████▋ | 5625/11952 [1:44:43<10:07:03, 5.76s/it]
47%|████▋ | 5626/11952 [1:44:49<10:15:06, 5.83s/it]
{'loss': 0.4806, 'learning_rate': 1.1429975772067322e-05, 'epoch': 0.47}
+
47%|████▋ | 5626/11952 [1:44:49<10:15:06, 5.83s/it]
47%|████▋ | 5627/11952 [1:44:55<10:20:53, 5.89s/it]
{'loss': 0.5062, 'learning_rate': 1.1427293664365568e-05, 'epoch': 0.47}
+
47%|████▋ | 5627/11952 [1:44:56<10:20:53, 5.89s/it]
47%|████▋ | 5628/11952 [1:45:02<10:27:36, 5.95s/it]
{'loss': 0.4882, 'learning_rate': 1.1424611451849301e-05, 'epoch': 0.47}
+
47%|████▋ | 5628/11952 [1:45:02<10:27:36, 5.95s/it]
47%|████▋ | 5629/11952 [1:45:07<10:17:18, 5.86s/it]
{'loss': 0.4883, 'learning_rate': 1.1421929134715492e-05, 'epoch': 0.47}
+
47%|████▋ | 5629/11952 [1:45:07<10:17:18, 5.86s/it]
47%|████▋ | 5630/11952 [1:45:13<10:09:22, 5.78s/it]
{'loss': 0.4493, 'learning_rate': 1.1419246713161128e-05, 'epoch': 0.47}
+
47%|████▋ | 5630/11952 [1:45:13<10:09:22, 5.78s/it]
47%|████▋ | 5631/11952 [1:45:19<10:18:45, 5.87s/it]
{'loss': 0.4925, 'learning_rate': 1.1416564187383185e-05, 'epoch': 0.47}
+
47%|████▋ | 5631/11952 [1:45:19<10:18:45, 5.87s/it]
47%|████▋ | 5632/11952 [1:45:25<10:18:00, 5.87s/it]
{'loss': 0.4814, 'learning_rate': 1.1413881557578662e-05, 'epoch': 0.47}
+
47%|████▋ | 5632/11952 [1:45:25<10:18:00, 5.87s/it]
47%|████▋ | 5633/11952 [1:45:30<10:06:38, 5.76s/it]
{'loss': 0.4868, 'learning_rate': 1.1411198823944553e-05, 'epoch': 0.47}
+
47%|████▋ | 5633/11952 [1:45:30<10:06:38, 5.76s/it]
47%|████▋ | 5634/11952 [1:45:36<10:04:28, 5.74s/it]
{'loss': 0.4744, 'learning_rate': 1.1408515986677877e-05, 'epoch': 0.47}
+
47%|████▋ | 5634/11952 [1:45:36<10:04:28, 5.74s/it]
47%|████▋ | 5635/11952 [1:45:42<10:02:10, 5.72s/it]
{'loss': 0.4786, 'learning_rate': 1.1405833045975644e-05, 'epoch': 0.47}
+
47%|████▋ | 5635/11952 [1:45:42<10:02:10, 5.72s/it]
47%|████▋ | 5636/11952 [1:45:47<10:05:27, 5.75s/it]
{'loss': 0.4724, 'learning_rate': 1.140315000203488e-05, 'epoch': 0.47}
+
47%|████▋ | 5636/11952 [1:45:47<10:05:27, 5.75s/it]
47%|████▋ | 5637/11952 [1:45:53<10:09:41, 5.79s/it]
{'loss': 0.4885, 'learning_rate': 1.1400466855052617e-05, 'epoch': 0.47}
+
47%|████▋ | 5637/11952 [1:45:53<10:09:41, 5.79s/it]
47%|████▋ | 5638/11952 [1:45:59<10:12:26, 5.82s/it]
{'loss': 0.4876, 'learning_rate': 1.139778360522589e-05, 'epoch': 0.47}
+
47%|████▋ | 5638/11952 [1:45:59<10:12:26, 5.82s/it]
47%|████▋ | 5639/11952 [1:46:05<10:06:49, 5.77s/it]
{'loss': 0.4921, 'learning_rate': 1.139510025275175e-05, 'epoch': 0.47}
+
47%|████▋ | 5639/11952 [1:46:05<10:06:49, 5.77s/it]
47%|████▋ | 5640/11952 [1:46:11<10:07:57, 5.78s/it]
{'loss': 0.5004, 'learning_rate': 1.139241679782725e-05, 'epoch': 0.47}
+
47%|████▋ | 5640/11952 [1:46:11<10:07:57, 5.78s/it]
47%|████▋ | 5641/11952 [1:46:17<10:10:02, 5.80s/it]
{'loss': 0.4859, 'learning_rate': 1.1389733240649454e-05, 'epoch': 0.47}
+
47%|████▋ | 5641/11952 [1:46:17<10:10:02, 5.80s/it]
47%|████▋ | 5642/11952 [1:46:22<10:08:32, 5.79s/it]
{'loss': 0.4938, 'learning_rate': 1.1387049581415428e-05, 'epoch': 0.47}
+
47%|████▋ | 5642/11952 [1:46:22<10:08:32, 5.79s/it]
47%|████▋ | 5643/11952 [1:46:28<10:04:46, 5.75s/it]
{'loss': 0.4681, 'learning_rate': 1.138436582032225e-05, 'epoch': 0.47}
+
47%|████▋ | 5643/11952 [1:46:28<10:04:46, 5.75s/it]
47%|████▋ | 5644/11952 [1:46:34<10:08:14, 5.79s/it]
{'loss': 0.4845, 'learning_rate': 1.1381681957567e-05, 'epoch': 0.47}
+
47%|████▋ | 5644/11952 [1:46:34<10:08:14, 5.79s/it]
47%|████▋ | 5645/11952 [1:46:40<10:11:04, 5.81s/it]
{'loss': 0.4733, 'learning_rate': 1.1378997993346782e-05, 'epoch': 0.47}
+
47%|████▋ | 5645/11952 [1:46:40<10:11:04, 5.81s/it]
47%|████▋ | 5646/11952 [1:46:46<10:10:34, 5.81s/it]
{'loss': 0.4937, 'learning_rate': 1.137631392785868e-05, 'epoch': 0.47}
+
47%|████▋ | 5646/11952 [1:46:46<10:10:34, 5.81s/it]
47%|████▋ | 5647/11952 [1:46:51<10:04:00, 5.75s/it]
{'loss': 0.4775, 'learning_rate': 1.1373629761299811e-05, 'epoch': 0.47}
+
47%|████▋ | 5647/11952 [1:46:51<10:04:00, 5.75s/it]
47%|████▋ | 5648/11952 [1:46:57<10:01:14, 5.72s/it]
{'loss': 0.471, 'learning_rate': 1.1370945493867284e-05, 'epoch': 0.47}
+
47%|████▋ | 5648/11952 [1:46:57<10:01:14, 5.72s/it]
47%|████▋ | 5649/11952 [1:47:02<9:59:42, 5.71s/it]
{'loss': 0.4901, 'learning_rate': 1.1368261125758224e-05, 'epoch': 0.47}
+
47%|████▋ | 5649/11952 [1:47:02<9:59:42, 5.71s/it]2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
47%|████▋ | 5650/11952 [1:47:08<9:52:48, 5.64s/it]3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4707, 'learning_rate': 1.1365576657169754e-05, 'epoch': 0.47}
+
47%|████▋ | 5650/11952 [1:47:08<9:52:48, 5.64s/it]
47%|████▋ | 5651/11952 [1:47:14<9:52:58, 5.65s/it]
{'loss': 0.4803, 'learning_rate': 1.136289208829902e-05, 'epoch': 0.47}
+
47%|████▋ | 5651/11952 [1:47:14<9:52:58, 5.65s/it]
47%|████▋ | 5652/11952 [1:47:20<10:05:44, 5.77s/it]
{'loss': 0.4749, 'learning_rate': 1.1360207419343157e-05, 'epoch': 0.47}
+
47%|████▋ | 5652/11952 [1:47:20<10:05:44, 5.77s/it]
47%|████▋ | 5653/11952 [1:47:25<10:06:27, 5.78s/it]
{'loss': 0.4835, 'learning_rate': 1.1357522650499317e-05, 'epoch': 0.47}
+
47%|████▋ | 5653/11952 [1:47:25<10:06:27, 5.78s/it]
47%|████▋ | 5654/11952 [1:47:31<10:14:04, 5.85s/it]
{'loss': 0.4921, 'learning_rate': 1.135483778196466e-05, 'epoch': 0.47}
+
47%|████▋ | 5654/11952 [1:47:31<10:14:04, 5.85s/it]
47%|████▋ | 5655/11952 [1:47:37<10:19:01, 5.90s/it]
{'loss': 0.4825, 'learning_rate': 1.1352152813936354e-05, 'epoch': 0.47}
+
47%|████▋ | 5655/11952 [1:47:37<10:19:01, 5.90s/it]
47%|████▋ | 5656/11952 [1:47:43<10:14:29, 5.86s/it]
{'loss': 0.4778, 'learning_rate': 1.1349467746611569e-05, 'epoch': 0.47}
+
47%|████▋ | 5656/11952 [1:47:43<10:14:29, 5.86s/it]
47%|████▋ | 5657/11952 [1:47:49<10:17:54, 5.89s/it]
{'loss': 0.4877, 'learning_rate': 1.1346782580187486e-05, 'epoch': 0.47}
+
47%|████▋ | 5657/11952 [1:47:49<10:17:54, 5.89s/it]
47%|████▋ | 5658/11952 [1:47:55<10:22:52, 5.94s/it]
{'loss': 0.5045, 'learning_rate': 1.1344097314861292e-05, 'epoch': 0.47}
+
47%|████▋ | 5658/11952 [1:47:55<10:22:52, 5.94s/it]
47%|████▋ | 5659/11952 [1:48:01<10:25:23, 5.96s/it]
{'loss': 0.4885, 'learning_rate': 1.1341411950830179e-05, 'epoch': 0.47}
+
47%|████▋ | 5659/11952 [1:48:01<10:25:23, 5.96s/it]
47%|████▋ | 5660/11952 [1:48:07<10:22:07, 5.93s/it]
{'loss': 0.4939, 'learning_rate': 1.1338726488291351e-05, 'epoch': 0.47}
+
47%|████▋ | 5660/11952 [1:48:07<10:22:07, 5.93s/it]
47%|████▋ | 5661/11952 [1:48:13<10:17:39, 5.89s/it]
{'loss': 0.4826, 'learning_rate': 1.1336040927442023e-05, 'epoch': 0.47}
+
47%|████▋ | 5661/11952 [1:48:13<10:17:39, 5.89s/it]
47%|████▋ | 5662/11952 [1:48:19<10:15:05, 5.87s/it]
{'loss': 0.4694, 'learning_rate': 1.1333355268479403e-05, 'epoch': 0.47}
+
47%|████▋ | 5662/11952 [1:48:19<10:15:05, 5.87s/it]
47%|████▋ | 5663/11952 [1:48:25<10:25:47, 5.97s/it]
{'loss': 0.467, 'learning_rate': 1.1330669511600716e-05, 'epoch': 0.47}
+
47%|████▋ | 5663/11952 [1:48:25<10:25:47, 5.97s/it]
47%|████▋ | 5664/11952 [1:48:31<10:29:18, 6.00s/it]
{'loss': 0.5067, 'learning_rate': 1.1327983657003197e-05, 'epoch': 0.47}
+
47%|████▋ | 5664/11952 [1:48:31<10:29:18, 6.00s/it]
47%|████▋ | 5665/11952 [1:48:37<10:30:42, 6.02s/it]
{'loss': 0.4779, 'learning_rate': 1.1325297704884081e-05, 'epoch': 0.47}
+
47%|████▋ | 5665/11952 [1:48:37<10:30:42, 6.02s/it]
47%|████▋ | 5666/11952 [1:48:43<10:29:27, 6.01s/it]
{'loss': 0.4802, 'learning_rate': 1.132261165544062e-05, 'epoch': 0.47}
+
47%|████▋ | 5666/11952 [1:48:43<10:29:27, 6.01s/it]
47%|████▋ | 5667/11952 [1:48:49<10:15:36, 5.88s/it]
{'loss': 0.4811, 'learning_rate': 1.131992550887005e-05, 'epoch': 0.47}
+
47%|████▋ | 5667/11952 [1:48:49<10:15:36, 5.88s/it]
47%|████▋ | 5668/11952 [1:48:55<10:14:53, 5.87s/it]
{'loss': 0.5074, 'learning_rate': 1.1317239265369648e-05, 'epoch': 0.47}
+
47%|████▋ | 5668/11952 [1:48:55<10:14:53, 5.87s/it]
47%|████▋ | 5669/11952 [1:49:01<10:27:31, 5.99s/it]
{'loss': 0.4494, 'learning_rate': 1.131455292513667e-05, 'epoch': 0.47}
+
47%|████▋ | 5669/11952 [1:49:01<10:27:31, 5.99s/it]
47%|████▋ | 5670/11952 [1:49:07<10:20:55, 5.93s/it]
{'loss': 0.4755, 'learning_rate': 1.1311866488368392e-05, 'epoch': 0.47}
+
47%|████▋ | 5670/11952 [1:49:07<10:20:55, 5.93s/it]
47%|████▋ | 5671/11952 [1:49:13<10:21:50, 5.94s/it]
{'loss': 0.5055, 'learning_rate': 1.1309179955262097e-05, 'epoch': 0.47}
+
47%|████▋ | 5671/11952 [1:49:13<10:21:50, 5.94s/it]
47%|████▋ | 5672/11952 [1:49:18<10:10:52, 5.84s/it]
{'loss': 0.4714, 'learning_rate': 1.1306493326015074e-05, 'epoch': 0.47}
+
47%|████▋ | 5672/11952 [1:49:18<10:10:52, 5.84s/it]
47%|████▋ | 5673/11952 [1:49:24<10:21:31, 5.94s/it]
{'loss': 0.4855, 'learning_rate': 1.1303806600824613e-05, 'epoch': 0.47}
+
47%|████▋ | 5673/11952 [1:49:24<10:21:31, 5.94s/it]
47%|████▋ | 5674/11952 [1:49:30<10:15:03, 5.88s/it]
{'loss': 0.4815, 'learning_rate': 1.1301119779888015e-05, 'epoch': 0.47}
+
47%|████▋ | 5674/11952 [1:49:30<10:15:03, 5.88s/it]
47%|████▋ | 5675/11952 [1:49:36<10:15:51, 5.89s/it]
{'loss': 0.4807, 'learning_rate': 1.1298432863402595e-05, 'epoch': 0.47}
+
47%|████▋ | 5675/11952 [1:49:36<10:15:51, 5.89s/it]
47%|████▋ | 5676/11952 [1:49:42<10:18:00, 5.91s/it]
{'loss': 0.4727, 'learning_rate': 1.1295745851565667e-05, 'epoch': 0.47}
+
47%|████▋ | 5676/11952 [1:49:42<10:18:00, 5.91s/it]
47%|████▋ | 5677/11952 [1:49:48<10:20:28, 5.93s/it]
{'loss': 0.4793, 'learning_rate': 1.1293058744574552e-05, 'epoch': 0.47}
+
47%|████▋ | 5677/11952 [1:49:48<10:20:28, 5.93s/it]
48%|████▊ | 5678/11952 [1:49:54<10:15:44, 5.89s/it]
{'loss': 0.4741, 'learning_rate': 1.129037154262658e-05, 'epoch': 0.48}
+
48%|████▊ | 5678/11952 [1:49:54<10:15:44, 5.89s/it]
48%|████▊ | 5679/11952 [1:50:00<10:17:10, 5.90s/it]
{'loss': 0.4584, 'learning_rate': 1.128768424591909e-05, 'epoch': 0.48}
+
48%|████▊ | 5679/11952 [1:50:00<10:17:10, 5.90s/it]
48%|████▊ | 5680/11952 [1:50:06<10:19:01, 5.92s/it]
{'loss': 0.4911, 'learning_rate': 1.1284996854649424e-05, 'epoch': 0.48}
+
48%|████▊ | 5680/11952 [1:50:06<10:19:01, 5.92s/it]
48%|████▊ | 5681/11952 [1:50:11<10:09:24, 5.83s/it]
{'loss': 0.4811, 'learning_rate': 1.1282309369014937e-05, 'epoch': 0.48}
+
48%|████▊ | 5681/11952 [1:50:11<10:09:24, 5.83s/it]
48%|████▊ | 5682/11952 [1:50:17<10:09:17, 5.83s/it]
{'loss': 0.4769, 'learning_rate': 1.127962178921298e-05, 'epoch': 0.48}
+
48%|████▊ | 5682/11952 [1:50:17<10:09:17, 5.83s/it]
48%|████▊ | 5683/11952 [1:50:23<10:14:58, 5.89s/it]
{'loss': 0.4743, 'learning_rate': 1.1276934115440924e-05, 'epoch': 0.48}
+
48%|████▊ | 5683/11952 [1:50:23<10:14:58, 5.89s/it]
48%|████▊ | 5684/11952 [1:50:29<10:14:08, 5.88s/it]
{'loss': 0.48, 'learning_rate': 1.1274246347896136e-05, 'epoch': 0.48}
+
48%|████▊ | 5684/11952 [1:50:29<10:14:08, 5.88s/it]
48%|████▊ | 5685/11952 [1:50:35<10:11:07, 5.85s/it]
{'loss': 0.4874, 'learning_rate': 1.1271558486775995e-05, 'epoch': 0.48}
+
48%|████▊ | 5685/11952 [1:50:35<10:11:07, 5.85s/it]
48%|████▊ | 5686/11952 [1:50:40<10:05:45, 5.80s/it]
{'loss': 0.463, 'learning_rate': 1.1268870532277889e-05, 'epoch': 0.48}
+
48%|████▊ | 5686/11952 [1:50:40<10:05:45, 5.80s/it]
48%|████▊ | 5687/11952 [1:50:46<9:58:55, 5.74s/it]
{'loss': 0.4752, 'learning_rate': 1.1266182484599209e-05, 'epoch': 0.48}
+
48%|████▊ | 5687/11952 [1:50:46<9:58:55, 5.74s/it]
48%|████▊ | 5688/11952 [1:50:52<9:54:44, 5.70s/it]
{'loss': 0.4682, 'learning_rate': 1.1263494343937354e-05, 'epoch': 0.48}
+
48%|████▊ | 5688/11952 [1:50:52<9:54:44, 5.70s/it]
48%|████▊ | 5689/11952 [1:50:57<9:58:39, 5.74s/it]
{'loss': 0.4947, 'learning_rate': 1.1260806110489726e-05, 'epoch': 0.48}
+
48%|████▊ | 5689/11952 [1:50:57<9:58:39, 5.74s/it]
48%|████▊ | 5690/11952 [1:51:04<10:12:42, 5.87s/it]
{'loss': 0.4735, 'learning_rate': 1.1258117784453746e-05, 'epoch': 0.48}
+
48%|████▊ | 5690/11952 [1:51:04<10:12:42, 5.87s/it]
48%|████▊ | 5691/11952 [1:51:10<10:15:39, 5.90s/it]
{'loss': 0.4578, 'learning_rate': 1.1255429366026826e-05, 'epoch': 0.48}
+
48%|████▊ | 5691/11952 [1:51:10<10:15:39, 5.90s/it]
48%|████▊ | 5692/11952 [1:51:15<10:08:34, 5.83s/it]
{'loss': 0.4827, 'learning_rate': 1.1252740855406397e-05, 'epoch': 0.48}
+
48%|████▊ | 5692/11952 [1:51:15<10:08:34, 5.83s/it]
48%|████▊ | 5693/11952 [1:51:21<10:02:49, 5.78s/it]
{'loss': 0.4848, 'learning_rate': 1.1250052252789891e-05, 'epoch': 0.48}
+
48%|████▊ | 5693/11952 [1:51:21<10:02:49, 5.78s/it]
48%|████▊ | 5694/11952 [1:51:27<10:24:34, 5.99s/it]
{'loss': 0.4687, 'learning_rate': 1.1247363558374745e-05, 'epoch': 0.48}
+
48%|████▊ | 5694/11952 [1:51:27<10:24:34, 5.99s/it]
48%|████▊ | 5695/11952 [1:51:33<10:13:02, 5.88s/it]
{'loss': 0.473, 'learning_rate': 1.1244674772358406e-05, 'epoch': 0.48}
+
48%|████▊ | 5695/11952 [1:51:33<10:13:02, 5.88s/it]
48%|████▊ | 5696/11952 [1:51:39<10:16:21, 5.91s/it]
{'loss': 0.4834, 'learning_rate': 1.124198589493833e-05, 'epoch': 0.48}
+
48%|████▊ | 5696/11952 [1:51:39<10:16:21, 5.91s/it]
48%|████▊ | 5697/11952 [1:51:45<10:09:00, 5.84s/it]
{'loss': 0.4675, 'learning_rate': 1.1239296926311975e-05, 'epoch': 0.48}
+
48%|████▊ | 5697/11952 [1:51:45<10:09:00, 5.84s/it]
48%|████▊ | 5698/11952 [1:51:51<10:11:46, 5.87s/it]
{'loss': 0.4829, 'learning_rate': 1.123660786667681e-05, 'epoch': 0.48}
+
48%|████▊ | 5698/11952 [1:51:51<10:11:46, 5.87s/it]
48%|████▊ | 5699/11952 [1:51:56<10:07:36, 5.83s/it]
{'loss': 0.4824, 'learning_rate': 1.1233918716230308e-05, 'epoch': 0.48}
+
48%|████▊ | 5699/11952 [1:51:56<10:07:36, 5.83s/it]2 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
48%|████▊ | 5700/11952 [1:52:02<10:11:58, 5.87s/it]6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+34 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4713, 'learning_rate': 1.1231229475169945e-05, 'epoch': 0.48}
+
48%|████▊ | 5700/11952 [1:52:02<10:11:58, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
48%|████▊ | 5701/11952 [1:52:32<22:28:23, 12.94s/it]
{'loss': 0.4831, 'learning_rate': 1.1228540143693209e-05, 'epoch': 0.48}
+
48%|████▊ | 5701/11952 [1:52:32<22:28:23, 12.94s/it]
48%|████▊ | 5702/11952 [1:52:38<18:48:37, 10.83s/it]
{'loss': 0.4796, 'learning_rate': 1.12258507219976e-05, 'epoch': 0.48}
+
48%|████▊ | 5702/11952 [1:52:38<18:48:37, 10.83s/it]
48%|████▊ | 5703/11952 [1:52:43<16:07:36, 9.29s/it]
{'loss': 0.4962, 'learning_rate': 1.122316121028061e-05, 'epoch': 0.48}
+
48%|████▊ | 5703/11952 [1:52:43<16:07:36, 9.29s/it]
48%|████▊ | 5704/11952 [1:52:49<14:22:37, 8.28s/it]
{'loss': 0.4918, 'learning_rate': 1.1220471608739748e-05, 'epoch': 0.48}
+
48%|████▊ | 5704/11952 [1:52:49<14:22:37, 8.28s/it]
48%|████▊ | 5705/11952 [1:52:55<13:05:06, 7.54s/it]
{'loss': 0.4789, 'learning_rate': 1.1217781917572524e-05, 'epoch': 0.48}
+
48%|████▊ | 5705/11952 [1:52:55<13:05:06, 7.54s/it]
48%|████▊ | 5706/11952 [1:53:01<12:12:45, 7.04s/it]
{'loss': 0.5123, 'learning_rate': 1.1215092136976466e-05, 'epoch': 0.48}
+
48%|████▊ | 5706/11952 [1:53:01<12:12:45, 7.04s/it]
48%|████▊ | 5707/11952 [1:53:07<11:32:29, 6.65s/it]
{'loss': 0.478, 'learning_rate': 1.1212402267149094e-05, 'epoch': 0.48}
+
48%|████▊ | 5707/11952 [1:53:07<11:32:29, 6.65s/it]
48%|████▊ | 5708/11952 [1:53:13<11:08:22, 6.42s/it]
{'loss': 0.4826, 'learning_rate': 1.1209712308287941e-05, 'epoch': 0.48}
+
48%|████▊ | 5708/11952 [1:53:13<11:08:22, 6.42s/it]
48%|████▊ | 5709/11952 [1:53:18<10:51:44, 6.26s/it]
{'loss': 0.4965, 'learning_rate': 1.120702226059055e-05, 'epoch': 0.48}
+
48%|████▊ | 5709/11952 [1:53:18<10:51:44, 6.26s/it]
48%|████▊ | 5710/11952 [1:53:25<10:45:13, 6.20s/it]
{'loss': 0.469, 'learning_rate': 1.1204332124254463e-05, 'epoch': 0.48}
+
48%|████▊ | 5710/11952 [1:53:25<10:45:13, 6.20s/it]
48%|████▊ | 5711/11952 [1:53:30<10:30:48, 6.06s/it]
{'loss': 0.4617, 'learning_rate': 1.1201641899477231e-05, 'epoch': 0.48}
+
48%|████▊ | 5711/11952 [1:53:30<10:30:48, 6.06s/it]
48%|████▊ | 5712/11952 [1:53:36<10:17:55, 5.94s/it]
{'loss': 0.4843, 'learning_rate': 1.119895158645642e-05, 'epoch': 0.48}
+
48%|████▊ | 5712/11952 [1:53:36<10:17:55, 5.94s/it]
48%|████▊ | 5713/11952 [1:53:42<10:15:28, 5.92s/it]
{'loss': 0.4833, 'learning_rate': 1.1196261185389593e-05, 'epoch': 0.48}
+
48%|████▊ | 5713/11952 [1:53:42<10:15:28, 5.92s/it]
48%|████▊ | 5714/11952 [1:53:48<10:11:27, 5.88s/it]
{'loss': 0.4829, 'learning_rate': 1.1193570696474317e-05, 'epoch': 0.48}
+
48%|████▊ | 5714/11952 [1:53:48<10:11:27, 5.88s/it]
48%|████▊ | 5715/11952 [1:53:54<10:16:31, 5.93s/it]
{'loss': 0.4845, 'learning_rate': 1.1190880119908175e-05, 'epoch': 0.48}
+
48%|████▊ | 5715/11952 [1:53:54<10:16:31, 5.93s/it]
48%|████▊ | 5716/11952 [1:54:00<10:20:57, 5.97s/it]
{'loss': 0.4692, 'learning_rate': 1.1188189455888747e-05, 'epoch': 0.48}
+
48%|████▊ | 5716/11952 [1:54:00<10:20:57, 5.97s/it]
48%|████▊ | 5717/11952 [1:54:06<10:28:48, 6.05s/it]
{'loss': 0.4786, 'learning_rate': 1.1185498704613632e-05, 'epoch': 0.48}
+
48%|████▊ | 5717/11952 [1:54:06<10:28:48, 6.05s/it]
48%|████▊ | 5718/11952 [1:54:12<10:17:52, 5.95s/it]
{'loss': 0.4714, 'learning_rate': 1.1182807866280419e-05, 'epoch': 0.48}
+
48%|████▊ | 5718/11952 [1:54:12<10:17:52, 5.95s/it]
48%|████▊ | 5719/11952 [1:54:17<10:08:45, 5.86s/it]
{'loss': 0.4922, 'learning_rate': 1.1180116941086719e-05, 'epoch': 0.48}
+
48%|████▊ | 5719/11952 [1:54:17<10:08:45, 5.86s/it]
48%|████▊ | 5720/11952 [1:54:23<10:10:47, 5.88s/it]
{'loss': 0.4893, 'learning_rate': 1.1177425929230137e-05, 'epoch': 0.48}
+
48%|████▊ | 5720/11952 [1:54:23<10:10:47, 5.88s/it]
48%|████▊ | 5721/11952 [1:54:29<10:05:40, 5.83s/it]
{'loss': 0.476, 'learning_rate': 1.117473483090829e-05, 'epoch': 0.48}
+
48%|████▊ | 5721/11952 [1:54:29<10:05:40, 5.83s/it]
48%|████▊ | 5722/11952 [1:54:35<10:20:14, 5.97s/it]
{'loss': 0.4827, 'learning_rate': 1.1172043646318809e-05, 'epoch': 0.48}
+
48%|████▊ | 5722/11952 [1:54:35<10:20:14, 5.97s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (4338 > 4096). Running this sequence through the model will result in indexing errors
+
48%|████▊ | 5723/11952 [1:54:41<10:13:59, 5.91s/it]
{'loss': 0.4936, 'learning_rate': 1.1169352375659314e-05, 'epoch': 0.48}
+
48%|████▊ | 5723/11952 [1:54:41<10:13:59, 5.91s/it]
48%|████▊ | 5724/11952 [1:54:47<10:03:36, 5.82s/it]
{'loss': 0.4858, 'learning_rate': 1.1166661019127447e-05, 'epoch': 0.48}
+
48%|████▊ | 5724/11952 [1:54:47<10:03:36, 5.82s/it]
48%|████▊ | 5725/11952 [1:54:52<9:59:45, 5.78s/it]
{'loss': 0.4639, 'learning_rate': 1.1163969576920846e-05, 'epoch': 0.48}
+
48%|████▊ | 5725/11952 [1:54:52<9:59:45, 5.78s/it]
48%|████▊ | 5726/11952 [1:54:58<10:04:38, 5.83s/it]
{'loss': 0.5047, 'learning_rate': 1.1161278049237157e-05, 'epoch': 0.48}
+
48%|████▊ | 5726/11952 [1:54:58<10:04:38, 5.83s/it]
48%|████▊ | 5727/11952 [1:55:04<9:53:09, 5.72s/it]
{'loss': 0.4743, 'learning_rate': 1.1158586436274042e-05, 'epoch': 0.48}
+
48%|████▊ | 5727/11952 [1:55:04<9:53:09, 5.72s/it]
48%|████▊ | 5728/11952 [1:55:10<10:00:08, 5.79s/it]
{'loss': 0.485, 'learning_rate': 1.1155894738229156e-05, 'epoch': 0.48}
+
48%|████▊ | 5728/11952 [1:55:10<10:00:08, 5.79s/it]
48%|████▊ | 5729/11952 [1:55:15<9:55:50, 5.74s/it]
{'loss': 0.4729, 'learning_rate': 1.115320295530017e-05, 'epoch': 0.48}
+
48%|████▊ | 5729/11952 [1:55:15<9:55:50, 5.74s/it]
48%|████▊ | 5730/11952 [1:55:21<9:52:20, 5.71s/it]
{'loss': 0.4761, 'learning_rate': 1.1150511087684757e-05, 'epoch': 0.48}
+
48%|████▊ | 5730/11952 [1:55:21<9:52:20, 5.71s/it]
48%|████▊ | 5731/11952 [1:55:27<9:54:48, 5.74s/it]
{'loss': 0.4886, 'learning_rate': 1.1147819135580588e-05, 'epoch': 0.48}
+
48%|████▊ | 5731/11952 [1:55:27<9:54:48, 5.74s/it]
48%|████▊ | 5732/11952 [1:55:33<10:04:33, 5.83s/it]
{'loss': 0.4789, 'learning_rate': 1.1145127099185363e-05, 'epoch': 0.48}
+
48%|████▊ | 5732/11952 [1:55:33<10:04:33, 5.83s/it]
48%|████▊ | 5733/11952 [1:55:39<10:08:34, 5.87s/it]
{'loss': 0.495, 'learning_rate': 1.1142434978696763e-05, 'epoch': 0.48}
+
48%|████▊ | 5733/11952 [1:55:39<10:08:34, 5.87s/it]
48%|████▊ | 5734/11952 [1:55:45<10:10:08, 5.89s/it]
{'loss': 0.4717, 'learning_rate': 1.1139742774312495e-05, 'epoch': 0.48}
+
48%|████▊ | 5734/11952 [1:55:45<10:10:08, 5.89s/it]
48%|████▊ | 5735/11952 [1:55:51<10:13:49, 5.92s/it]
{'loss': 0.495, 'learning_rate': 1.1137050486230251e-05, 'epoch': 0.48}
+
48%|████▊ | 5735/11952 [1:55:51<10:13:49, 5.92s/it]
48%|████▊ | 5736/11952 [1:55:56<10:06:20, 5.85s/it]
{'loss': 0.4825, 'learning_rate': 1.1134358114647752e-05, 'epoch': 0.48}
+
48%|████▊ | 5736/11952 [1:55:56<10:06:20, 5.85s/it]
48%|████▊ | 5737/11952 [1:56:02<10:04:46, 5.84s/it]
{'loss': 0.476, 'learning_rate': 1.1131665659762712e-05, 'epoch': 0.48}
+
48%|████▊ | 5737/11952 [1:56:02<10:04:46, 5.84s/it]
48%|████▊ | 5738/11952 [1:56:08<10:13:23, 5.92s/it]
{'loss': 0.4794, 'learning_rate': 1.112897312177285e-05, 'epoch': 0.48}
+
48%|████▊ | 5738/11952 [1:56:08<10:13:23, 5.92s/it]
48%|████▊ | 5739/11952 [1:56:14<10:15:40, 5.95s/it]
{'loss': 0.4632, 'learning_rate': 1.11262805008759e-05, 'epoch': 0.48}
+
48%|████▊ | 5739/11952 [1:56:14<10:15:40, 5.95s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
48%|████▊ | 5740/11952 [1:56:20<10:20:05, 5.99s/it]
{'loss': 0.5031, 'learning_rate': 1.1123587797269596e-05, 'epoch': 0.48}
+
48%|████▊ | 5740/11952 [1:56:20<10:20:05, 5.99s/it]
48%|████▊ | 5741/11952 [1:56:26<10:12:26, 5.92s/it]
{'loss': 0.4687, 'learning_rate': 1.1120895011151675e-05, 'epoch': 0.48}
+
48%|████▊ | 5741/11952 [1:56:26<10:12:26, 5.92s/it]
48%|████▊ | 5742/11952 [1:56:32<10:03:07, 5.83s/it]
{'loss': 0.5017, 'learning_rate': 1.1118202142719887e-05, 'epoch': 0.48}
+
48%|████▊ | 5742/11952 [1:56:32<10:03:07, 5.83s/it]
48%|████▊ | 5743/11952 [1:56:38<10:02:39, 5.82s/it]
{'loss': 0.4941, 'learning_rate': 1.1115509192171988e-05, 'epoch': 0.48}
+
48%|████▊ | 5743/11952 [1:56:38<10:02:39, 5.82s/it]
48%|████▊ | 5744/11952 [1:56:44<10:06:08, 5.86s/it]
{'loss': 0.4736, 'learning_rate': 1.111281615970573e-05, 'epoch': 0.48}
+
48%|████▊ | 5744/11952 [1:56:44<10:06:08, 5.86s/it]
48%|████▊ | 5745/11952 [1:56:49<9:58:04, 5.78s/it]
{'loss': 0.4698, 'learning_rate': 1.1110123045518882e-05, 'epoch': 0.48}
+
48%|████▊ | 5745/11952 [1:56:49<9:58:04, 5.78s/it]
48%|████▊ | 5746/11952 [1:56:55<10:03:36, 5.84s/it]
{'loss': 0.491, 'learning_rate': 1.1107429849809215e-05, 'epoch': 0.48}
+
48%|████▊ | 5746/11952 [1:56:55<10:03:36, 5.84s/it]
48%|████▊ | 5747/11952 [1:57:01<10:08:50, 5.89s/it]
{'loss': 0.4839, 'learning_rate': 1.1104736572774506e-05, 'epoch': 0.48}
+
48%|████▊ | 5747/11952 [1:57:01<10:08:50, 5.89s/it]
48%|████▊ | 5748/11952 [1:57:07<10:12:51, 5.93s/it]
{'loss': 0.4779, 'learning_rate': 1.1102043214612539e-05, 'epoch': 0.48}
+
48%|████▊ | 5748/11952 [1:57:07<10:12:51, 5.93s/it]
48%|████▊ | 5749/11952 [1:57:13<10:18:47, 5.99s/it]
{'loss': 0.4833, 'learning_rate': 1.1099349775521103e-05, 'epoch': 0.48}
+
48%|████▊ | 5749/11952 [1:57:13<10:18:47, 5.99s/it]2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+10 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...7
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
48%|████▊ | 5750/11952 [1:57:19<10:18:09, 5.98s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4852, 'learning_rate': 1.1096656255697991e-05, 'epoch': 0.48}
+
48%|████▊ | 5750/11952 [1:57:19<10:18:09, 5.98s/it]
48%|████▊ | 5751/11952 [1:57:25<10:05:23, 5.86s/it]
{'loss': 0.4684, 'learning_rate': 1.1093962655341002e-05, 'epoch': 0.48}
+
48%|████▊ | 5751/11952 [1:57:25<10:05:23, 5.86s/it]
48%|████▊ | 5752/11952 [1:57:31<10:08:04, 5.88s/it]
{'loss': 0.4879, 'learning_rate': 1.1091268974647947e-05, 'epoch': 0.48}
+
48%|████▊ | 5752/11952 [1:57:31<10:08:04, 5.88s/it]
48%|████▊ | 5753/11952 [1:57:37<10:23:13, 6.03s/it]
{'loss': 0.4902, 'learning_rate': 1.108857521381664e-05, 'epoch': 0.48}
+
48%|████▊ | 5753/11952 [1:57:37<10:23:13, 6.03s/it]
48%|████▊ | 5754/11952 [1:57:43<10:12:45, 5.93s/it]
{'loss': 0.4738, 'learning_rate': 1.1085881373044895e-05, 'epoch': 0.48}
+
48%|████▊ | 5754/11952 [1:57:43<10:12:45, 5.93s/it]
48%|████▊ | 5755/11952 [1:57:49<10:09:23, 5.90s/it]
{'loss': 0.4899, 'learning_rate': 1.1083187452530539e-05, 'epoch': 0.48}
+
48%|████▊ | 5755/11952 [1:57:49<10:09:23, 5.90s/it]
48%|████▊ | 5756/11952 [1:57:55<10:09:39, 5.90s/it]
{'loss': 0.4831, 'learning_rate': 1.1080493452471403e-05, 'epoch': 0.48}
+
48%|████▊ | 5756/11952 [1:57:55<10:09:39, 5.90s/it]
48%|████▊ | 5757/11952 [1:58:00<10:05:32, 5.86s/it]
{'loss': 0.4738, 'learning_rate': 1.1077799373065321e-05, 'epoch': 0.48}
+
48%|████▊ | 5757/11952 [1:58:00<10:05:32, 5.86s/it]
48%|████▊ | 5758/11952 [1:58:06<10:07:47, 5.89s/it]
{'loss': 0.4864, 'learning_rate': 1.1075105214510135e-05, 'epoch': 0.48}
+
48%|████▊ | 5758/11952 [1:58:06<10:07:47, 5.89s/it]
48%|████▊ | 5759/11952 [1:58:12<10:03:55, 5.85s/it]
{'loss': 0.4776, 'learning_rate': 1.1072410977003693e-05, 'epoch': 0.48}
+
48%|████▊ | 5759/11952 [1:58:12<10:03:55, 5.85s/it]
48%|████▊ | 5760/11952 [1:58:18<10:13:04, 5.94s/it]
{'loss': 0.4847, 'learning_rate': 1.1069716660743852e-05, 'epoch': 0.48}
+
48%|████▊ | 5760/11952 [1:58:18<10:13:04, 5.94s/it]
48%|████▊ | 5761/11952 [1:58:24<10:05:18, 5.87s/it]
{'loss': 0.482, 'learning_rate': 1.1067022265928472e-05, 'epoch': 0.48}
+
48%|████▊ | 5761/11952 [1:58:24<10:05:18, 5.87s/it]
48%|████▊ | 5762/11952 [1:58:30<10:18:15, 5.99s/it]
{'loss': 0.4857, 'learning_rate': 1.1064327792755405e-05, 'epoch': 0.48}
+
48%|████▊ | 5762/11952 [1:58:30<10:18:15, 5.99s/it]
48%|████▊ | 5763/11952 [1:58:36<10:13:20, 5.95s/it]
{'loss': 0.4833, 'learning_rate': 1.1061633241422538e-05, 'epoch': 0.48}
+
48%|████▊ | 5763/11952 [1:58:36<10:13:20, 5.95s/it]
48%|████▊ | 5764/11952 [1:58:42<10:05:53, 5.87s/it]
{'loss': 0.4706, 'learning_rate': 1.1058938612127744e-05, 'epoch': 0.48}
+
48%|████▊ | 5764/11952 [1:58:42<10:05:53, 5.87s/it]
48%|████▊ | 5765/11952 [1:58:47<10:02:42, 5.84s/it]
{'loss': 0.481, 'learning_rate': 1.1056243905068899e-05, 'epoch': 0.48}
+
48%|████▊ | 5765/11952 [1:58:47<10:02:42, 5.84s/it]
48%|████▊ | 5766/11952 [1:58:53<10:01:16, 5.83s/it]
{'loss': 0.4646, 'learning_rate': 1.1053549120443893e-05, 'epoch': 0.48}
+
48%|████▊ | 5766/11952 [1:58:53<10:01:16, 5.83s/it]
48%|████▊ | 5767/11952 [1:58:59<10:08:01, 5.90s/it]
{'loss': 0.4928, 'learning_rate': 1.1050854258450623e-05, 'epoch': 0.48}
+
48%|████▊ | 5767/11952 [1:58:59<10:08:01, 5.90s/it]
48%|████▊ | 5768/11952 [1:59:05<10:02:16, 5.84s/it]
{'loss': 0.4864, 'learning_rate': 1.104815931928699e-05, 'epoch': 0.48}
+
48%|████▊ | 5768/11952 [1:59:05<10:02:16, 5.84s/it]
48%|████▊ | 5769/11952 [1:59:11<10:06:04, 5.88s/it]
{'loss': 0.4873, 'learning_rate': 1.1045464303150892e-05, 'epoch': 0.48}
+
48%|████▊ | 5769/11952 [1:59:11<10:06:04, 5.88s/it]
48%|████▊ | 5770/11952 [1:59:17<10:04:17, 5.87s/it]
{'loss': 0.4881, 'learning_rate': 1.1042769210240248e-05, 'epoch': 0.48}
+
48%|████▊ | 5770/11952 [1:59:17<10:04:17, 5.87s/it]
48%|████▊ | 5771/11952 [1:59:23<10:04:16, 5.87s/it]
{'loss': 0.4759, 'learning_rate': 1.1040074040752971e-05, 'epoch': 0.48}
+
48%|████▊ | 5771/11952 [1:59:23<10:04:16, 5.87s/it]
48%|████▊ | 5772/11952 [1:59:29<10:03:35, 5.86s/it]
{'loss': 0.4723, 'learning_rate': 1.1037378794886977e-05, 'epoch': 0.48}
+
48%|████▊ | 5772/11952 [1:59:29<10:03:35, 5.86s/it]
48%|████▊ | 5773/11952 [1:59:34<9:57:11, 5.80s/it]
{'loss': 0.468, 'learning_rate': 1.1034683472840201e-05, 'epoch': 0.48}
+
48%|████▊ | 5773/11952 [1:59:34<9:57:11, 5.80s/it]
48%|████▊ | 5774/11952 [1:59:40<9:55:22, 5.78s/it]
{'loss': 0.4803, 'learning_rate': 1.1031988074810578e-05, 'epoch': 0.48}
+
48%|████▊ | 5774/11952 [1:59:40<9:55:22, 5.78s/it]
48%|████▊ | 5775/11952 [1:59:46<9:52:19, 5.75s/it]
{'loss': 0.5059, 'learning_rate': 1.1029292600996042e-05, 'epoch': 0.48}
+
48%|████▊ | 5775/11952 [1:59:46<9:52:19, 5.75s/it]
48%|████▊ | 5776/11952 [1:59:51<9:50:42, 5.74s/it]
{'loss': 0.4792, 'learning_rate': 1.1026597051594534e-05, 'epoch': 0.48}
+
48%|████▊ | 5776/11952 [1:59:51<9:50:42, 5.74s/it]
48%|████▊ | 5777/11952 [1:59:57<9:51:24, 5.75s/it]
{'loss': 0.4762, 'learning_rate': 1.102390142680401e-05, 'epoch': 0.48}
+
48%|████▊ | 5777/11952 [1:59:57<9:51:24, 5.75s/it]
48%|████▊ | 5778/11952 [2:00:03<9:55:44, 5.79s/it]
{'loss': 0.4988, 'learning_rate': 1.1021205726822429e-05, 'epoch': 0.48}
+
48%|████▊ | 5778/11952 [2:00:03<9:55:44, 5.79s/it]
48%|████▊ | 5779/11952 [2:00:09<10:05:05, 5.88s/it]
{'loss': 0.4742, 'learning_rate': 1.1018509951847743e-05, 'epoch': 0.48}
+
48%|████▊ | 5779/11952 [2:00:09<10:05:05, 5.88s/it]
48%|████▊ | 5780/11952 [2:00:15<9:59:01, 5.82s/it]
{'loss': 0.4762, 'learning_rate': 1.1015814102077921e-05, 'epoch': 0.48}
+
48%|████▊ | 5780/11952 [2:00:15<9:59:01, 5.82s/it]
48%|████▊ | 5781/11952 [2:00:21<10:02:46, 5.86s/it]
{'loss': 0.4947, 'learning_rate': 1.1013118177710942e-05, 'epoch': 0.48}
+
48%|████▊ | 5781/11952 [2:00:21<10:02:46, 5.86s/it]
48%|████▊ | 5782/11952 [2:00:26<9:57:17, 5.81s/it]
{'loss': 0.4727, 'learning_rate': 1.1010422178944772e-05, 'epoch': 0.48}
+
48%|████▊ | 5782/11952 [2:00:26<9:57:17, 5.81s/it]
48%|████▊ | 5783/11952 [2:00:32<10:03:42, 5.87s/it]
{'loss': 0.4662, 'learning_rate': 1.10077261059774e-05, 'epoch': 0.48}
+
48%|████▊ | 5783/11952 [2:00:32<10:03:42, 5.87s/it]
48%|████▊ | 5784/11952 [2:00:38<10:03:10, 5.87s/it]
{'loss': 0.4927, 'learning_rate': 1.1005029959006818e-05, 'epoch': 0.48}
+
48%|████▊ | 5784/11952 [2:00:38<10:03:10, 5.87s/it]
48%|████▊ | 5785/11952 [2:00:44<10:05:52, 5.89s/it]
{'loss': 0.4872, 'learning_rate': 1.1002333738231016e-05, 'epoch': 0.48}
+
48%|████▊ | 5785/11952 [2:00:44<10:05:52, 5.89s/it]
48%|████▊ | 5786/11952 [2:00:50<10:03:27, 5.87s/it]
{'loss': 0.4899, 'learning_rate': 1.099963744384799e-05, 'epoch': 0.48}
+
48%|████▊ | 5786/11952 [2:00:50<10:03:27, 5.87s/it]
48%|████▊ | 5787/11952 [2:00:56<10:01:01, 5.85s/it]
{'loss': 0.4824, 'learning_rate': 1.0996941076055751e-05, 'epoch': 0.48}
+
48%|████▊ | 5787/11952 [2:00:56<10:01:01, 5.85s/it]
48%|████▊ | 5788/11952 [2:01:02<10:03:31, 5.87s/it]
{'loss': 0.4645, 'learning_rate': 1.0994244635052304e-05, 'epoch': 0.48}
+
48%|████▊ | 5788/11952 [2:01:02<10:03:31, 5.87s/it]
48%|████▊ | 5789/11952 [2:01:08<10:01:23, 5.85s/it]
{'loss': 0.4843, 'learning_rate': 1.0991548121035664e-05, 'epoch': 0.48}
+
48%|████▊ | 5789/11952 [2:01:08<10:01:23, 5.85s/it]
48%|████▊ | 5790/11952 [2:01:14<10:05:45, 5.90s/it]
{'loss': 0.4767, 'learning_rate': 1.098885153420386e-05, 'epoch': 0.48}
+
48%|████▊ | 5790/11952 [2:01:14<10:05:45, 5.90s/it]
48%|████▊ | 5791/11952 [2:01:20<10:06:49, 5.91s/it]
{'loss': 0.4897, 'learning_rate': 1.098615487475491e-05, 'epoch': 0.48}
+
48%|████▊ | 5791/11952 [2:01:20<10:06:49, 5.91s/it]
48%|████▊ | 5792/11952 [2:01:26<10:11:00, 5.95s/it]
{'loss': 0.4754, 'learning_rate': 1.0983458142886848e-05, 'epoch': 0.48}
+
48%|████▊ | 5792/11952 [2:01:26<10:11:00, 5.95s/it]
48%|████▊ | 5793/11952 [2:01:31<10:06:34, 5.91s/it]
{'loss': 0.4671, 'learning_rate': 1.0980761338797707e-05, 'epoch': 0.48}
+
48%|████▊ | 5793/11952 [2:01:31<10:06:34, 5.91s/it]
48%|████▊ | 5794/11952 [2:01:37<10:12:26, 5.97s/it]
{'loss': 0.4932, 'learning_rate': 1.0978064462685536e-05, 'epoch': 0.48}
+
48%|████▊ | 5794/11952 [2:01:38<10:12:26, 5.97s/it]
48%|████▊ | 5795/11952 [2:01:43<10:04:07, 5.89s/it]
{'loss': 0.4822, 'learning_rate': 1.0975367514748378e-05, 'epoch': 0.48}
+
48%|████▊ | 5795/11952 [2:01:43<10:04:07, 5.89s/it]
48%|████▊ | 5796/11952 [2:01:49<10:04:32, 5.89s/it]
{'loss': 0.5096, 'learning_rate': 1.0972670495184286e-05, 'epoch': 0.48}
+
48%|████▊ | 5796/11952 [2:01:49<10:04:32, 5.89s/it]
49%|████▊ | 5797/11952 [2:01:55<9:59:26, 5.84s/it]
{'loss': 0.5035, 'learning_rate': 1.0969973404191322e-05, 'epoch': 0.49}
+
49%|████▊ | 5797/11952 [2:01:55<9:59:26, 5.84s/it]
49%|████▊ | 5798/11952 [2:02:01<10:05:46, 5.91s/it]
{'loss': 0.4778, 'learning_rate': 1.096727624196754e-05, 'epoch': 0.49}
+
49%|████▊ | 5798/11952 [2:02:01<10:05:46, 5.91s/it]
49%|████▊ | 5799/11952 [2:02:07<10:08:33, 5.93s/it]
{'loss': 0.4801, 'learning_rate': 1.0964579008711018e-05, 'epoch': 0.49}
+
49%|████▊ | 5799/11952 [2:02:07<10:08:33, 5.93s/it]2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
49%|████▊ | 5800/11952 [2:02:13<10:10:29, 5.95s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4845, 'learning_rate': 1.0961881704619823e-05, 'epoch': 0.49}
+
49%|████▊ | 5800/11952 [2:02:13<10:10:29, 5.95s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
49%|████▊ | 5801/11952 [2:02:43<22:48:07, 13.35s/it]
{'loss': 0.4793, 'learning_rate': 1.095918432989204e-05, 'epoch': 0.49}
+
49%|████▊ | 5801/11952 [2:02:43<22:48:07, 13.35s/it]
49%|████▊ | 5802/11952 [2:02:49<18:55:07, 11.07s/it]
{'loss': 0.4717, 'learning_rate': 1.0956486884725748e-05, 'epoch': 0.49}
+
49%|████▊ | 5802/11952 [2:02:49<18:55:07, 11.07s/it]
49%|████▊ | 5803/11952 [2:02:55<16:13:14, 9.50s/it]
{'loss': 0.4756, 'learning_rate': 1.0953789369319031e-05, 'epoch': 0.49}
+
49%|████▊ | 5803/11952 [2:02:55<16:13:14, 9.50s/it]
49%|████▊ | 5804/11952 [2:03:01<14:36:13, 8.55s/it]
{'loss': 0.485, 'learning_rate': 1.0951091783869998e-05, 'epoch': 0.49}
+
49%|████▊ | 5804/11952 [2:03:01<14:36:13, 8.55s/it]
49%|████▊ | 5805/11952 [2:03:07<13:09:47, 7.71s/it]
{'loss': 0.496, 'learning_rate': 1.0948394128576739e-05, 'epoch': 0.49}
+
49%|████▊ | 5805/11952 [2:03:07<13:09:47, 7.71s/it]
49%|████▊ | 5806/11952 [2:03:13<12:11:37, 7.14s/it]
{'loss': 0.4963, 'learning_rate': 1.094569640363736e-05, 'epoch': 0.49}
+
49%|████▊ | 5806/11952 [2:03:13<12:11:37, 7.14s/it]
49%|████▊ | 5807/11952 [2:03:19<11:38:49, 6.82s/it]
{'loss': 0.4884, 'learning_rate': 1.0942998609249968e-05, 'epoch': 0.49}
+
49%|████▊ | 5807/11952 [2:03:19<11:38:49, 6.82s/it]
49%|████▊ | 5808/11952 [2:03:25<11:14:07, 6.58s/it]
{'loss': 0.4687, 'learning_rate': 1.0940300745612679e-05, 'epoch': 0.49}
+
49%|████▊ | 5808/11952 [2:03:25<11:14:07, 6.58s/it]
49%|████▊ | 5809/11952 [2:03:31<10:57:21, 6.42s/it]
{'loss': 0.4779, 'learning_rate': 1.0937602812923617e-05, 'epoch': 0.49}
+
49%|████▊ | 5809/11952 [2:03:31<10:57:21, 6.42s/it]
49%|████▊ | 5810/11952 [2:03:37<10:47:41, 6.33s/it]
{'loss': 0.4892, 'learning_rate': 1.0934904811380904e-05, 'epoch': 0.49}
+
49%|████▊ | 5810/11952 [2:03:37<10:47:41, 6.33s/it]
49%|████▊ | 5811/11952 [2:03:43<10:34:07, 6.20s/it]
{'loss': 0.4831, 'learning_rate': 1.0932206741182672e-05, 'epoch': 0.49}
+
49%|████▊ | 5811/11952 [2:03:43<10:34:07, 6.20s/it]
49%|████▊ | 5812/11952 [2:03:49<10:27:26, 6.13s/it]
{'loss': 0.4711, 'learning_rate': 1.0929508602527052e-05, 'epoch': 0.49}
+
49%|████▊ | 5812/11952 [2:03:49<10:27:26, 6.13s/it]
49%|████▊ | 5813/11952 [2:03:55<10:14:52, 6.01s/it]
{'loss': 0.4934, 'learning_rate': 1.0926810395612187e-05, 'epoch': 0.49}
+
49%|████▊ | 5813/11952 [2:03:55<10:14:52, 6.01s/it]
49%|████▊ | 5814/11952 [2:04:01<10:12:05, 5.98s/it]
{'loss': 0.48, 'learning_rate': 1.0924112120636222e-05, 'epoch': 0.49}
+
49%|████▊ | 5814/11952 [2:04:01<10:12:05, 5.98s/it]
49%|████▊ | 5815/11952 [2:04:07<10:07:15, 5.94s/it]
{'loss': 0.4744, 'learning_rate': 1.0921413777797305e-05, 'epoch': 0.49}
+
49%|████▊ | 5815/11952 [2:04:07<10:07:15, 5.94s/it]
49%|████▊ | 5816/11952 [2:04:12<10:00:58, 5.88s/it]
{'loss': 0.4796, 'learning_rate': 1.0918715367293595e-05, 'epoch': 0.49}
+
49%|████▊ | 5816/11952 [2:04:12<10:00:58, 5.88s/it]
49%|████▊ | 5817/11952 [2:04:18<10:01:37, 5.88s/it]
{'loss': 0.4669, 'learning_rate': 1.0916016889323246e-05, 'epoch': 0.49}
+
49%|████▊ | 5817/11952 [2:04:18<10:01:37, 5.88s/it]
49%|████▊ | 5818/11952 [2:04:24<9:53:14, 5.80s/it]
{'loss': 0.4656, 'learning_rate': 1.0913318344084428e-05, 'epoch': 0.49}
+
49%|████▊ | 5818/11952 [2:04:24<9:53:14, 5.80s/it]
49%|████▊ | 5819/11952 [2:04:30<10:00:04, 5.87s/it]
{'loss': 0.4658, 'learning_rate': 1.0910619731775311e-05, 'epoch': 0.49}
+
49%|████▊ | 5819/11952 [2:04:30<10:00:04, 5.87s/it]
49%|████▊ | 5820/11952 [2:04:36<10:02:33, 5.90s/it]
{'loss': 0.4817, 'learning_rate': 1.0907921052594066e-05, 'epoch': 0.49}
+
49%|████▊ | 5820/11952 [2:04:36<10:02:33, 5.90s/it]
49%|████▊ | 5821/11952 [2:04:42<10:03:57, 5.91s/it]
{'loss': 0.4862, 'learning_rate': 1.0905222306738879e-05, 'epoch': 0.49}
+
49%|████▊ | 5821/11952 [2:04:42<10:03:57, 5.91s/it]
49%|████▊ | 5822/11952 [2:04:48<9:59:54, 5.87s/it]
{'loss': 0.4828, 'learning_rate': 1.0902523494407928e-05, 'epoch': 0.49}
+
49%|████▊ | 5822/11952 [2:04:48<9:59:54, 5.87s/it]
49%|████▊ | 5823/11952 [2:04:53<9:58:16, 5.86s/it]
{'loss': 0.4725, 'learning_rate': 1.0899824615799406e-05, 'epoch': 0.49}
+
49%|████▊ | 5823/11952 [2:04:53<9:58:16, 5.86s/it]
49%|████▊ | 5824/11952 [2:04:59<9:51:11, 5.79s/it]
{'loss': 0.4827, 'learning_rate': 1.0897125671111507e-05, 'epoch': 0.49}
+
49%|████▊ | 5824/11952 [2:04:59<9:51:11, 5.79s/it]
49%|████▊ | 5825/11952 [2:05:05<9:45:33, 5.73s/it]
{'loss': 0.4902, 'learning_rate': 1.089442666054243e-05, 'epoch': 0.49}
+
49%|████▊ | 5825/11952 [2:05:05<9:45:33, 5.73s/it]
49%|████▊ | 5826/11952 [2:05:10<9:49:15, 5.77s/it]
{'loss': 0.465, 'learning_rate': 1.0891727584290381e-05, 'epoch': 0.49}
+
49%|████▊ | 5826/11952 [2:05:10<9:49:15, 5.77s/it]
49%|████▉ | 5827/11952 [2:05:16<9:49:25, 5.77s/it]
{'loss': 0.4795, 'learning_rate': 1.0889028442553565e-05, 'epoch': 0.49}
+
49%|████▉ | 5827/11952 [2:05:16<9:49:25, 5.77s/it]
49%|████▉ | 5828/11952 [2:05:22<9:54:44, 5.83s/it]
{'loss': 0.4693, 'learning_rate': 1.08863292355302e-05, 'epoch': 0.49}
+
49%|████▉ | 5828/11952 [2:05:22<9:54:44, 5.83s/it]
49%|████▉ | 5829/11952 [2:05:28<9:59:15, 5.87s/it]
{'loss': 0.4781, 'learning_rate': 1.0883629963418501e-05, 'epoch': 0.49}
+
49%|████▉ | 5829/11952 [2:05:28<9:59:15, 5.87s/it]
49%|████▉ | 5830/11952 [2:05:34<9:55:11, 5.83s/it]
{'loss': 0.5004, 'learning_rate': 1.088093062641669e-05, 'epoch': 0.49}
+
49%|████▉ | 5830/11952 [2:05:34<9:55:11, 5.83s/it]
49%|████▉ | 5831/11952 [2:05:40<9:49:36, 5.78s/it]
{'loss': 0.4815, 'learning_rate': 1.0878231224723001e-05, 'epoch': 0.49}
+
49%|████▉ | 5831/11952 [2:05:40<9:49:36, 5.78s/it]
49%|████▉ | 5832/11952 [2:05:46<10:06:41, 5.95s/it]
{'loss': 0.4879, 'learning_rate': 1.0875531758535668e-05, 'epoch': 0.49}
+
49%|████▉ | 5832/11952 [2:05:46<10:06:41, 5.95s/it]
49%|████▉ | 5833/11952 [2:05:52<10:04:21, 5.93s/it]
{'loss': 0.4919, 'learning_rate': 1.0872832228052919e-05, 'epoch': 0.49}
+
49%|████▉ | 5833/11952 [2:05:52<10:04:21, 5.93s/it]
49%|████▉ | 5834/11952 [2:05:57<9:54:01, 5.83s/it]
{'loss': 0.5049, 'learning_rate': 1.0870132633472999e-05, 'epoch': 0.49}
+
49%|████▉ | 5834/11952 [2:05:57<9:54:01, 5.83s/it]
49%|████▉ | 5835/11952 [2:06:03<9:58:27, 5.87s/it]
{'loss': 0.4874, 'learning_rate': 1.0867432974994162e-05, 'epoch': 0.49}
+
49%|████▉ | 5835/11952 [2:06:03<9:58:27, 5.87s/it]
49%|████▉ | 5836/11952 [2:06:09<10:00:39, 5.89s/it]
{'loss': 0.4906, 'learning_rate': 1.0864733252814654e-05, 'epoch': 0.49}
+
49%|████▉ | 5836/11952 [2:06:09<10:00:39, 5.89s/it]
49%|████▉ | 5837/11952 [2:06:15<9:58:19, 5.87s/it]
{'loss': 0.4875, 'learning_rate': 1.0862033467132732e-05, 'epoch': 0.49}
+
49%|████▉ | 5837/11952 [2:06:15<9:58:19, 5.87s/it]
49%|████▉ | 5838/11952 [2:06:21<9:48:34, 5.78s/it]
{'loss': 0.4617, 'learning_rate': 1.0859333618146659e-05, 'epoch': 0.49}
+
49%|████▉ | 5838/11952 [2:06:21<9:48:34, 5.78s/it]
49%|████▉ | 5839/11952 [2:06:27<9:57:21, 5.86s/it]
{'loss': 0.4761, 'learning_rate': 1.0856633706054698e-05, 'epoch': 0.49}
+
49%|████▉ | 5839/11952 [2:06:27<9:57:21, 5.86s/it]
49%|████▉ | 5840/11952 [2:06:33<10:00:37, 5.90s/it]
{'loss': 0.4735, 'learning_rate': 1.0853933731055122e-05, 'epoch': 0.49}
+
49%|████▉ | 5840/11952 [2:06:33<10:00:37, 5.90s/it]
49%|████▉ | 5841/11952 [2:06:39<9:59:49, 5.89s/it]
{'loss': 0.4843, 'learning_rate': 1.0851233693346204e-05, 'epoch': 0.49}
+
49%|████▉ | 5841/11952 [2:06:39<9:59:49, 5.89s/it]
49%|████▉ | 5842/11952 [2:06:45<10:15:36, 6.05s/it]
{'loss': 0.4845, 'learning_rate': 1.0848533593126225e-05, 'epoch': 0.49}
+
49%|████▉ | 5842/11952 [2:06:45<10:15:36, 6.05s/it]
49%|████▉ | 5843/11952 [2:06:51<10:03:38, 5.93s/it]
{'loss': 0.4731, 'learning_rate': 1.0845833430593467e-05, 'epoch': 0.49}
+
49%|████▉ | 5843/11952 [2:06:51<10:03:38, 5.93s/it]
49%|████▉ | 5844/11952 [2:06:56<9:58:27, 5.88s/it]
{'loss': 0.4897, 'learning_rate': 1.0843133205946218e-05, 'epoch': 0.49}
+
49%|████▉ | 5844/11952 [2:06:56<9:58:27, 5.88s/it]
49%|████▉ | 5845/11952 [2:07:02<10:02:11, 5.92s/it]
{'loss': 0.501, 'learning_rate': 1.0840432919382774e-05, 'epoch': 0.49}
+
49%|████▉ | 5845/11952 [2:07:02<10:02:11, 5.92s/it]
49%|████▉ | 5846/11952 [2:07:08<9:54:43, 5.84s/it]
{'loss': 0.4934, 'learning_rate': 1.0837732571101437e-05, 'epoch': 0.49}
+
49%|████▉ | 5846/11952 [2:07:08<9:54:43, 5.84s/it]
49%|████▉ | 5847/11952 [2:07:14<9:56:32, 5.86s/it]
{'loss': 0.4878, 'learning_rate': 1.0835032161300499e-05, 'epoch': 0.49}
+
49%|████▉ | 5847/11952 [2:07:14<9:56:32, 5.86s/it]
49%|████▉ | 5848/11952 [2:07:20<10:00:52, 5.91s/it]
{'loss': 0.4885, 'learning_rate': 1.0832331690178274e-05, 'epoch': 0.49}
+
49%|████▉ | 5848/11952 [2:07:20<10:00:52, 5.91s/it]
49%|████▉ | 5849/11952 [2:07:26<10:12:04, 6.02s/it]
{'loss': 0.4741, 'learning_rate': 1.0829631157933071e-05, 'epoch': 0.49}
+
49%|████▉ | 5849/11952 [2:07:26<10:12:04, 6.02s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+04 3AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
49%|████▉ | 5850/11952 [2:07:32<10:11:09, 6.01s/it]
{'loss': 0.5027, 'learning_rate': 1.0826930564763207e-05, 'epoch': 0.49}
+
49%|████▉ | 5850/11952 [2:07:32<10:11:09, 6.01s/it]
49%|████▉ | 5851/11952 [2:07:38<10:02:51, 5.93s/it]
{'loss': 0.4769, 'learning_rate': 1.0824229910867002e-05, 'epoch': 0.49}
+
49%|████▉ | 5851/11952 [2:07:38<10:02:51, 5.93s/it]
49%|████▉ | 5852/11952 [2:07:44<10:03:43, 5.94s/it]
{'loss': 0.4863, 'learning_rate': 1.0821529196442782e-05, 'epoch': 0.49}
+
49%|████▉ | 5852/11952 [2:07:44<10:03:43, 5.94s/it]
49%|████▉ | 5853/11952 [2:07:50<10:01:15, 5.92s/it]
{'loss': 0.4707, 'learning_rate': 1.0818828421688873e-05, 'epoch': 0.49}
+
49%|████▉ | 5853/11952 [2:07:50<10:01:15, 5.92s/it]
49%|████▉ | 5854/11952 [2:07:56<10:03:32, 5.94s/it]
{'loss': 0.4718, 'learning_rate': 1.081612758680361e-05, 'epoch': 0.49}
+
49%|████▉ | 5854/11952 [2:07:56<10:03:32, 5.94s/it]
49%|████▉ | 5855/11952 [2:08:02<9:58:08, 5.89s/it]
{'loss': 0.469, 'learning_rate': 1.0813426691985331e-05, 'epoch': 0.49}
+
49%|████▉ | 5855/11952 [2:08:02<9:58:08, 5.89s/it]
49%|████▉ | 5856/11952 [2:08:08<10:05:42, 5.96s/it]
{'loss': 0.4993, 'learning_rate': 1.0810725737432381e-05, 'epoch': 0.49}
+
49%|████▉ | 5856/11952 [2:08:08<10:05:42, 5.96s/it]
49%|████▉ | 5857/11952 [2:08:13<9:57:00, 5.88s/it]
{'loss': 0.4695, 'learning_rate': 1.0808024723343104e-05, 'epoch': 0.49}
+
49%|████▉ | 5857/11952 [2:08:13<9:57:00, 5.88s/it]
49%|████▉ | 5858/11952 [2:08:19<9:57:38, 5.88s/it]
{'loss': 0.4555, 'learning_rate': 1.0805323649915854e-05, 'epoch': 0.49}
+
49%|████▉ | 5858/11952 [2:08:19<9:57:38, 5.88s/it]
49%|████▉ | 5859/11952 [2:08:25<9:55:32, 5.86s/it]
{'loss': 0.4673, 'learning_rate': 1.0802622517348982e-05, 'epoch': 0.49}
+
49%|████▉ | 5859/11952 [2:08:25<9:55:32, 5.86s/it]
49%|████▉ | 5860/11952 [2:08:31<9:53:27, 5.85s/it]
{'loss': 0.4788, 'learning_rate': 1.0799921325840851e-05, 'epoch': 0.49}
+
49%|████▉ | 5860/11952 [2:08:31<9:53:27, 5.85s/it]
49%|████▉ | 5861/11952 [2:08:37<9:49:53, 5.81s/it]
{'loss': 0.4518, 'learning_rate': 1.0797220075589825e-05, 'epoch': 0.49}
+
49%|████▉ | 5861/11952 [2:08:37<9:49:53, 5.81s/it]
49%|████▉ | 5862/11952 [2:08:42<9:47:26, 5.79s/it]
{'loss': 0.4822, 'learning_rate': 1.0794518766794272e-05, 'epoch': 0.49}
+
49%|████▉ | 5862/11952 [2:08:42<9:47:26, 5.79s/it]
49%|████▉ | 5863/11952 [2:08:48<9:50:21, 5.82s/it]
{'loss': 0.4787, 'learning_rate': 1.079181739965257e-05, 'epoch': 0.49}
+
49%|████▉ | 5863/11952 [2:08:48<9:50:21, 5.82s/it]
49%|████▉ | 5864/11952 [2:08:54<9:54:49, 5.86s/it]
{'loss': 0.4897, 'learning_rate': 1.0789115974363086e-05, 'epoch': 0.49}
+
49%|████▉ | 5864/11952 [2:08:54<9:54:49, 5.86s/it]
49%|████▉ | 5865/11952 [2:09:00<9:56:55, 5.88s/it]
{'loss': 0.4997, 'learning_rate': 1.0786414491124208e-05, 'epoch': 0.49}
+
49%|████▉ | 5865/11952 [2:09:00<9:56:55, 5.88s/it]
49%|████▉ | 5866/11952 [2:09:06<10:02:39, 5.94s/it]
{'loss': 0.4807, 'learning_rate': 1.0783712950134324e-05, 'epoch': 0.49}
+
49%|████▉ | 5866/11952 [2:09:06<10:02:39, 5.94s/it]
49%|████▉ | 5867/11952 [2:09:12<10:11:41, 6.03s/it]
{'loss': 0.4609, 'learning_rate': 1.0781011351591819e-05, 'epoch': 0.49}
+
49%|████▉ | 5867/11952 [2:09:12<10:11:41, 6.03s/it]
49%|████▉ | 5868/11952 [2:09:18<10:02:34, 5.94s/it]
{'loss': 0.4857, 'learning_rate': 1.0778309695695088e-05, 'epoch': 0.49}
+
49%|████▉ | 5868/11952 [2:09:18<10:02:34, 5.94s/it]
49%|████▉ | 5869/11952 [2:09:24<10:02:39, 5.94s/it]
{'loss': 0.4819, 'learning_rate': 1.077560798264253e-05, 'epoch': 0.49}
+
49%|████▉ | 5869/11952 [2:09:24<10:02:39, 5.94s/it]
49%|████▉ | 5870/11952 [2:09:30<9:58:30, 5.90s/it]
{'loss': 0.4784, 'learning_rate': 1.0772906212632547e-05, 'epoch': 0.49}
+
49%|████▉ | 5870/11952 [2:09:30<9:58:30, 5.90s/it]
49%|████▉ | 5871/11952 [2:09:36<9:55:47, 5.88s/it]
{'loss': 0.4976, 'learning_rate': 1.0770204385863547e-05, 'epoch': 0.49}
+
49%|████▉ | 5871/11952 [2:09:36<9:55:47, 5.88s/it]
49%|████▉ | 5872/11952 [2:09:42<9:53:40, 5.86s/it]
{'loss': 0.473, 'learning_rate': 1.0767502502533945e-05, 'epoch': 0.49}
+
49%|████▉ | 5872/11952 [2:09:42<9:53:40, 5.86s/it]
49%|████▉ | 5873/11952 [2:09:48<9:56:03, 5.88s/it]
{'loss': 0.4696, 'learning_rate': 1.0764800562842149e-05, 'epoch': 0.49}
+
49%|████▉ | 5873/11952 [2:09:48<9:56:03, 5.88s/it]
49%|████▉ | 5874/11952 [2:09:53<9:52:22, 5.85s/it]
{'loss': 0.4932, 'learning_rate': 1.0762098566986578e-05, 'epoch': 0.49}
+
49%|████▉ | 5874/11952 [2:09:53<9:52:22, 5.85s/it]
49%|████▉ | 5875/11952 [2:09:59<9:51:37, 5.84s/it]
{'loss': 0.4942, 'learning_rate': 1.0759396515165657e-05, 'epoch': 0.49}
+
49%|████▉ | 5875/11952 [2:09:59<9:51:37, 5.84s/it]
49%|████▉ | 5876/11952 [2:10:05<9:43:44, 5.76s/it]
{'loss': 0.4632, 'learning_rate': 1.075669440757782e-05, 'epoch': 0.49}
+
49%|████▉ | 5876/11952 [2:10:05<9:43:44, 5.76s/it]
49%|████▉ | 5877/11952 [2:10:11<9:44:45, 5.78s/it]
{'loss': 0.477, 'learning_rate': 1.075399224442149e-05, 'epoch': 0.49}
+
49%|████▉ | 5877/11952 [2:10:11<9:44:45, 5.78s/it]
49%|████▉ | 5878/11952 [2:10:17<9:55:56, 5.89s/it]
{'loss': 0.49, 'learning_rate': 1.0751290025895104e-05, 'epoch': 0.49}
+
49%|████▉ | 5878/11952 [2:10:17<9:55:56, 5.89s/it]
49%|████▉ | 5879/11952 [2:10:22<9:46:41, 5.80s/it]
{'loss': 0.4698, 'learning_rate': 1.0748587752197106e-05, 'epoch': 0.49}
+
49%|████▉ | 5879/11952 [2:10:22<9:46:41, 5.80s/it]
49%|████▉ | 5880/11952 [2:10:28<9:47:56, 5.81s/it]
{'loss': 0.4739, 'learning_rate': 1.0745885423525934e-05, 'epoch': 0.49}
+
49%|████▉ | 5880/11952 [2:10:28<9:47:56, 5.81s/it]
49%|████▉ | 5881/11952 [2:10:34<9:47:21, 5.80s/it]
{'loss': 0.4757, 'learning_rate': 1.0743183040080043e-05, 'epoch': 0.49}
+
49%|████▉ | 5881/11952 [2:10:34<9:47:21, 5.80s/it]
49%|████▉ | 5882/11952 [2:10:39<9:39:03, 5.72s/it]
{'loss': 0.4677, 'learning_rate': 1.0740480602057877e-05, 'epoch': 0.49}
+
49%|████▉ | 5882/11952 [2:10:39<9:39:03, 5.72s/it]
49%|████▉ | 5883/11952 [2:10:45<9:41:33, 5.75s/it]
{'loss': 0.4867, 'learning_rate': 1.0737778109657899e-05, 'epoch': 0.49}
+
49%|████▉ | 5883/11952 [2:10:45<9:41:33, 5.75s/it]
49%|████▉ | 5884/11952 [2:10:51<9:41:14, 5.75s/it]
{'loss': 0.4678, 'learning_rate': 1.0735075563078565e-05, 'epoch': 0.49}
+
49%|████▉ | 5884/11952 [2:10:51<9:41:14, 5.75s/it]
49%|████▉ | 5885/11952 [2:10:57<9:43:24, 5.77s/it]
{'loss': 0.4661, 'learning_rate': 1.0732372962518337e-05, 'epoch': 0.49}
+
49%|████▉ | 5885/11952 [2:10:57<9:43:24, 5.77s/it]
49%|████▉ | 5886/11952 [2:11:02<9:40:53, 5.75s/it]
{'loss': 0.4743, 'learning_rate': 1.0729670308175683e-05, 'epoch': 0.49}
+
49%|████▉ | 5886/11952 [2:11:02<9:40:53, 5.75s/it]
49%|████▉ | 5887/11952 [2:11:08<9:37:41, 5.71s/it]
{'loss': 0.4877, 'learning_rate': 1.072696760024908e-05, 'epoch': 0.49}
+
49%|████▉ | 5887/11952 [2:11:08<9:37:41, 5.71s/it]
49%|████▉ | 5888/11952 [2:11:14<9:52:39, 5.86s/it]
{'loss': 0.4869, 'learning_rate': 1.0724264838936998e-05, 'epoch': 0.49}
+
49%|████▉ | 5888/11952 [2:11:14<9:52:39, 5.86s/it]
49%|████▉ | 5889/11952 [2:11:20<9:52:30, 5.86s/it]
{'loss': 0.4722, 'learning_rate': 1.0721562024437919e-05, 'epoch': 0.49}
+
49%|████▉ | 5889/11952 [2:11:20<9:52:30, 5.86s/it]
49%|████▉ | 5890/11952 [2:11:26<9:55:32, 5.89s/it]
{'loss': 0.4959, 'learning_rate': 1.0718859156950329e-05, 'epoch': 0.49}
+
49%|████▉ | 5890/11952 [2:11:26<9:55:32, 5.89s/it]
49%|████▉ | 5891/11952 [2:11:32<9:50:40, 5.85s/it]
{'loss': 0.4653, 'learning_rate': 1.071615623667271e-05, 'epoch': 0.49}
+
49%|████▉ | 5891/11952 [2:11:32<9:50:40, 5.85s/it]
49%|████▉ | 5892/11952 [2:11:38<9:43:56, 5.78s/it]
{'loss': 0.4606, 'learning_rate': 1.0713453263803553e-05, 'epoch': 0.49}
+
49%|████▉ | 5892/11952 [2:11:38<9:43:56, 5.78s/it]
49%|████▉ | 5893/11952 [2:11:43<9:44:15, 5.79s/it]
{'loss': 0.49, 'learning_rate': 1.071075023854136e-05, 'epoch': 0.49}
+
49%|████▉ | 5893/11952 [2:11:43<9:44:15, 5.79s/it]
49%|████▉ | 5894/11952 [2:11:49<9:49:59, 5.84s/it]
{'loss': 0.4895, 'learning_rate': 1.0708047161084626e-05, 'epoch': 0.49}
+
49%|████▉ | 5894/11952 [2:11:49<9:49:59, 5.84s/it]
49%|████▉ | 5895/11952 [2:11:56<10:02:30, 5.97s/it]
{'loss': 0.4806, 'learning_rate': 1.070534403163185e-05, 'epoch': 0.49}
+
49%|████▉ | 5895/11952 [2:11:56<10:02:30, 5.97s/it]
49%|████▉ | 5896/11952 [2:12:01<9:58:24, 5.93s/it]
{'loss': 0.4713, 'learning_rate': 1.0702640850381542e-05, 'epoch': 0.49}
+
49%|████▉ | 5896/11952 [2:12:01<9:58:24, 5.93s/it]
49%|████▉ | 5897/11952 [2:12:07<9:57:24, 5.92s/it]
{'loss': 0.4832, 'learning_rate': 1.0699937617532216e-05, 'epoch': 0.49}
+
49%|████▉ | 5897/11952 [2:12:07<9:57:24, 5.92s/it]
49%|████▉ | 5898/11952 [2:12:13<9:57:35, 5.92s/it]
{'loss': 0.4784, 'learning_rate': 1.0697234333282382e-05, 'epoch': 0.49}
+
49%|████▉ | 5898/11952 [2:12:13<9:57:35, 5.92s/it]
49%|████▉ | 5899/11952 [2:12:19<9:48:18, 5.83s/it]
{'loss': 0.4696, 'learning_rate': 1.0694530997830556e-05, 'epoch': 0.49}
+
49%|████▉ | 5899/11952 [2:12:19<9:48:18, 5.83s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+013 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
49%|████▉ | 5900/11952 [2:12:25<9:47:07, 5.82s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.5059, 'learning_rate': 1.0691827611375268e-05, 'epoch': 0.49}
+
49%|████▉ | 5900/11952 [2:12:25<9:47:07, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-5900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
49%|████▉ | 5901/11952 [2:12:56<22:34:38, 13.43s/it]
{'loss': 0.4705, 'learning_rate': 1.068912417411503e-05, 'epoch': 0.49}
+
49%|████▉ | 5901/11952 [2:12:56<22:34:38, 13.43s/it]
49%|████▉ | 5902/11952 [2:13:01<18:38:43, 11.09s/it]
{'loss': 0.4696, 'learning_rate': 1.0686420686248382e-05, 'epoch': 0.49}
+
49%|████▉ | 5902/11952 [2:13:01<18:38:43, 11.09s/it]
49%|████▉ | 5903/11952 [2:13:07<16:04:37, 9.57s/it]
{'loss': 0.4935, 'learning_rate': 1.0683717147973856e-05, 'epoch': 0.49}
+
49%|████▉ | 5903/11952 [2:13:07<16:04:37, 9.57s/it]
49%|████▉ | 5904/11952 [2:13:13<14:07:22, 8.41s/it]
{'loss': 0.4837, 'learning_rate': 1.0681013559489985e-05, 'epoch': 0.49}
+
49%|████▉ | 5904/11952 [2:13:13<14:07:22, 8.41s/it]
49%|████▉ | 5905/11952 [2:13:19<12:47:30, 7.62s/it]
{'loss': 0.4748, 'learning_rate': 1.067830992099531e-05, 'epoch': 0.49}
+
49%|████▉ | 5905/11952 [2:13:19<12:47:30, 7.62s/it]
49%|████▉ | 5906/11952 [2:13:25<12:02:42, 7.17s/it]
{'loss': 0.4827, 'learning_rate': 1.0675606232688377e-05, 'epoch': 0.49}
+
49%|████▉ | 5906/11952 [2:13:25<12:02:42, 7.17s/it]
49%|████▉ | 5907/11952 [2:13:31<11:24:15, 6.79s/it]
{'loss': 0.5115, 'learning_rate': 1.0672902494767731e-05, 'epoch': 0.49}
+
49%|████▉ | 5907/11952 [2:13:31<11:24:15, 6.79s/it]
49%|████▉ | 5908/11952 [2:13:37<11:07:09, 6.62s/it]
{'loss': 0.4813, 'learning_rate': 1.0670198707431927e-05, 'epoch': 0.49}
+
49%|████▉ | 5908/11952 [2:13:37<11:07:09, 6.62s/it]
49%|████▉ | 5909/11952 [2:13:43<10:45:37, 6.41s/it]
{'loss': 0.4771, 'learning_rate': 1.0667494870879513e-05, 'epoch': 0.49}
+
49%|████▉ | 5909/11952 [2:13:43<10:45:37, 6.41s/it]
49%|████▉ | 5910/11952 [2:13:49<10:42:53, 6.38s/it]
{'loss': 0.5049, 'learning_rate': 1.0664790985309058e-05, 'epoch': 0.49}
+
49%|████▉ | 5910/11952 [2:13:49<10:42:53, 6.38s/it]
49%|████▉ | 5911/11952 [2:13:55<10:26:15, 6.22s/it]
{'loss': 0.4861, 'learning_rate': 1.0662087050919111e-05, 'epoch': 0.49}
+
49%|████▉ | 5911/11952 [2:13:55<10:26:15, 6.22s/it]
49%|████▉ | 5912/11952 [2:14:01<10:13:25, 6.09s/it]
{'loss': 0.4752, 'learning_rate': 1.065938306790825e-05, 'epoch': 0.49}
+
49%|████▉ | 5912/11952 [2:14:01<10:13:25, 6.09s/it]
49%|████▉ | 5913/11952 [2:14:07<9:58:23, 5.95s/it]
{'loss': 0.4789, 'learning_rate': 1.0656679036475038e-05, 'epoch': 0.49}
+
49%|████▉ | 5913/11952 [2:14:07<9:58:23, 5.95s/it]
49%|████▉ | 5914/11952 [2:14:13<10:10:42, 6.07s/it]
{'loss': 0.4715, 'learning_rate': 1.065397495681805e-05, 'epoch': 0.49}
+
49%|████▉ | 5914/11952 [2:14:13<10:10:42, 6.07s/it]
49%|████▉ | 5915/11952 [2:14:19<9:57:32, 5.94s/it]
{'loss': 0.4669, 'learning_rate': 1.065127082913586e-05, 'epoch': 0.49}
+
49%|████▉ | 5915/11952 [2:14:19<9:57:32, 5.94s/it]
49%|████▉ | 5916/11952 [2:14:24<9:49:11, 5.86s/it]
{'loss': 0.4878, 'learning_rate': 1.0648566653627048e-05, 'epoch': 0.49}
+
49%|████▉ | 5916/11952 [2:14:24<9:49:11, 5.86s/it]
50%|████▉ | 5917/11952 [2:14:30<9:46:23, 5.83s/it]
{'loss': 0.4657, 'learning_rate': 1.06458624304902e-05, 'epoch': 0.5}
+
50%|████▉ | 5917/11952 [2:14:30<9:46:23, 5.83s/it]
50%|████▉ | 5918/11952 [2:14:36<9:57:42, 5.94s/it]
{'loss': 0.4867, 'learning_rate': 1.0643158159923902e-05, 'epoch': 0.5}
+
50%|████▉ | 5918/11952 [2:14:36<9:57:42, 5.94s/it]
50%|████▉ | 5919/11952 [2:14:42<9:51:19, 5.88s/it]
{'loss': 0.4842, 'learning_rate': 1.0640453842126742e-05, 'epoch': 0.5}
+
50%|████▉ | 5919/11952 [2:14:42<9:51:19, 5.88s/it]
50%|████▉ | 5920/11952 [2:14:48<9:46:49, 5.84s/it]
{'loss': 0.4846, 'learning_rate': 1.0637749477297317e-05, 'epoch': 0.5}
+
50%|████▉ | 5920/11952 [2:14:48<9:46:49, 5.84s/it]
50%|████▉ | 5921/11952 [2:14:53<9:37:39, 5.75s/it]
{'loss': 0.4753, 'learning_rate': 1.063504506563422e-05, 'epoch': 0.5}
+
50%|████▉ | 5921/11952 [2:14:53<9:37:39, 5.75s/it]
50%|████▉ | 5922/11952 [2:14:59<9:34:24, 5.72s/it]
{'loss': 0.4803, 'learning_rate': 1.0632340607336056e-05, 'epoch': 0.5}
+
50%|████▉ | 5922/11952 [2:14:59<9:34:24, 5.72s/it]
50%|████▉ | 5923/11952 [2:15:05<9:33:57, 5.71s/it]
{'loss': 0.4649, 'learning_rate': 1.062963610260143e-05, 'epoch': 0.5}
+
50%|████▉ | 5923/11952 [2:15:05<9:33:57, 5.71s/it]
50%|████▉ | 5924/11952 [2:15:11<9:40:58, 5.78s/it]
{'loss': 0.5102, 'learning_rate': 1.0626931551628948e-05, 'epoch': 0.5}
+
50%|████▉ | 5924/11952 [2:15:11<9:40:58, 5.78s/it]
50%|████▉ | 5925/11952 [2:15:17<9:47:56, 5.85s/it]
{'loss': 0.4758, 'learning_rate': 1.0624226954617221e-05, 'epoch': 0.5}
+
50%|████▉ | 5925/11952 [2:15:17<9:47:56, 5.85s/it]
50%|████▉ | 5926/11952 [2:15:23<9:51:37, 5.89s/it]
{'loss': 0.4701, 'learning_rate': 1.0621522311764857e-05, 'epoch': 0.5}
+
50%|████▉ | 5926/11952 [2:15:23<9:51:37, 5.89s/it]
50%|████▉ | 5927/11952 [2:15:29<9:52:39, 5.90s/it]
{'loss': 0.4919, 'learning_rate': 1.0618817623270484e-05, 'epoch': 0.5}
+
50%|████▉ | 5927/11952 [2:15:29<9:52:39, 5.90s/it]
50%|████▉ | 5928/11952 [2:15:35<9:57:34, 5.95s/it]
{'loss': 0.5002, 'learning_rate': 1.061611288933272e-05, 'epoch': 0.5}
+
50%|████▉ | 5928/11952 [2:15:35<9:57:34, 5.95s/it]
50%|████▉ | 5929/11952 [2:15:41<10:00:23, 5.98s/it]
{'loss': 0.4994, 'learning_rate': 1.0613408110150185e-05, 'epoch': 0.5}
+
50%|████▉ | 5929/11952 [2:15:41<10:00:23, 5.98s/it]
50%|████▉ | 5930/11952 [2:15:46<9:55:21, 5.93s/it]
{'loss': 0.4734, 'learning_rate': 1.061070328592151e-05, 'epoch': 0.5}
+
50%|████▉ | 5930/11952 [2:15:46<9:55:21, 5.93s/it]
50%|████▉ | 5931/11952 [2:15:52<9:49:15, 5.87s/it]
{'loss': 0.4737, 'learning_rate': 1.0607998416845329e-05, 'epoch': 0.5}
+
50%|████▉ | 5931/11952 [2:15:52<9:49:15, 5.87s/it]
50%|████▉ | 5932/11952 [2:15:58<9:42:40, 5.81s/it]
{'loss': 0.4695, 'learning_rate': 1.0605293503120268e-05, 'epoch': 0.5}
+
50%|████▉ | 5932/11952 [2:15:58<9:42:40, 5.81s/it]
50%|████▉ | 5933/11952 [2:16:04<9:41:48, 5.80s/it]
{'loss': 0.4705, 'learning_rate': 1.0602588544944972e-05, 'epoch': 0.5}
+
50%|████▉ | 5933/11952 [2:16:04<9:41:48, 5.80s/it]
50%|████▉ | 5934/11952 [2:16:09<9:38:44, 5.77s/it]
{'loss': 0.4683, 'learning_rate': 1.059988354251808e-05, 'epoch': 0.5}
+
50%|████▉ | 5934/11952 [2:16:09<9:38:44, 5.77s/it]
50%|████▉ | 5935/11952 [2:16:15<9:45:48, 5.84s/it]
{'loss': 0.4895, 'learning_rate': 1.059717849603824e-05, 'epoch': 0.5}
+
50%|████▉ | 5935/11952 [2:16:15<9:45:48, 5.84s/it]
50%|████▉ | 5936/11952 [2:16:21<9:44:26, 5.83s/it]
{'loss': 0.4732, 'learning_rate': 1.0594473405704088e-05, 'epoch': 0.5}
+
50%|████▉ | 5936/11952 [2:16:21<9:44:26, 5.83s/it]
50%|████▉ | 5937/11952 [2:16:27<9:49:29, 5.88s/it]
{'loss': 0.4844, 'learning_rate': 1.0591768271714285e-05, 'epoch': 0.5}
+
50%|████▉ | 5937/11952 [2:16:27<9:49:29, 5.88s/it]
50%|████▉ | 5938/11952 [2:16:33<9:59:24, 5.98s/it]
{'loss': 0.4746, 'learning_rate': 1.058906309426748e-05, 'epoch': 0.5}
+
50%|████▉ | 5938/11952 [2:16:33<9:59:24, 5.98s/it]
50%|████▉ | 5939/11952 [2:16:39<9:55:33, 5.94s/it]
{'loss': 0.4765, 'learning_rate': 1.0586357873562332e-05, 'epoch': 0.5}
+
50%|████▉ | 5939/11952 [2:16:39<9:55:33, 5.94s/it]
50%|████▉ | 5940/11952 [2:16:45<10:00:56, 6.00s/it]
{'loss': 0.4753, 'learning_rate': 1.0583652609797501e-05, 'epoch': 0.5}
+
50%|████▉ | 5940/11952 [2:16:45<10:00:56, 6.00s/it]
50%|████▉ | 5941/11952 [2:16:51<9:50:18, 5.89s/it]
{'loss': 0.4755, 'learning_rate': 1.0580947303171651e-05, 'epoch': 0.5}
+
50%|████▉ | 5941/11952 [2:16:51<9:50:18, 5.89s/it]
50%|████▉ | 5942/11952 [2:16:57<9:45:52, 5.85s/it]
{'loss': 0.4855, 'learning_rate': 1.0578241953883445e-05, 'epoch': 0.5}
+
50%|████▉ | 5942/11952 [2:16:57<9:45:52, 5.85s/it]
50%|████▉ | 5943/11952 [2:17:03<9:48:21, 5.87s/it]
{'loss': 0.4863, 'learning_rate': 1.0575536562131556e-05, 'epoch': 0.5}
+
50%|████▉ | 5943/11952 [2:17:03<9:48:21, 5.87s/it]
50%|████▉ | 5944/11952 [2:17:09<9:47:27, 5.87s/it]
{'loss': 0.4672, 'learning_rate': 1.0572831128114658e-05, 'epoch': 0.5}
+
50%|████▉ | 5944/11952 [2:17:09<9:47:27, 5.87s/it]
50%|████▉ | 5945/11952 [2:17:14<9:41:23, 5.81s/it]
{'loss': 0.4928, 'learning_rate': 1.0570125652031425e-05, 'epoch': 0.5}
+
50%|████▉ | 5945/11952 [2:17:14<9:41:23, 5.81s/it]
50%|████▉ | 5946/11952 [2:17:20<9:40:57, 5.80s/it]
{'loss': 0.4896, 'learning_rate': 1.0567420134080531e-05, 'epoch': 0.5}
+
50%|████▉ | 5946/11952 [2:17:20<9:40:57, 5.80s/it]
50%|████▉ | 5947/11952 [2:17:26<9:36:55, 5.76s/it]
{'loss': 0.4839, 'learning_rate': 1.0564714574460664e-05, 'epoch': 0.5}
+
50%|████▉ | 5947/11952 [2:17:26<9:36:55, 5.76s/it]
50%|████▉ | 5948/11952 [2:17:31<9:35:31, 5.75s/it]
{'loss': 0.4808, 'learning_rate': 1.0562008973370508e-05, 'epoch': 0.5}
+
50%|████▉ | 5948/11952 [2:17:31<9:35:31, 5.75s/it]
50%|████▉ | 5949/11952 [2:17:37<9:35:24, 5.75s/it]
{'loss': 0.4783, 'learning_rate': 1.0559303331008752e-05, 'epoch': 0.5}
+
50%|████▉ | 5949/11952 [2:17:37<9:35:24, 5.75s/it]2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
50%|████▉ | 5950/11952 [2:17:43<9:52:09, 5.92s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4887, 'learning_rate': 1.0556597647574083e-05, 'epoch': 0.5}
+
50%|████▉ | 5950/11952 [2:17:43<9:52:09, 5.92s/it]
50%|████▉ | 5951/11952 [2:17:50<9:56:31, 5.96s/it]
{'loss': 0.4867, 'learning_rate': 1.05538919232652e-05, 'epoch': 0.5}
+
50%|████▉ | 5951/11952 [2:17:50<9:56:31, 5.96s/it]
50%|████▉ | 5952/11952 [2:17:55<9:53:08, 5.93s/it]
{'loss': 0.5122, 'learning_rate': 1.0551186158280795e-05, 'epoch': 0.5}
+
50%|████▉ | 5952/11952 [2:17:55<9:53:08, 5.93s/it]
50%|████▉ | 5953/11952 [2:18:01<9:46:44, 5.87s/it]
{'loss': 0.4623, 'learning_rate': 1.0548480352819573e-05, 'epoch': 0.5}
+
50%|████▉ | 5953/11952 [2:18:01<9:46:44, 5.87s/it]
50%|████▉ | 5954/11952 [2:18:07<9:45:19, 5.86s/it]
{'loss': 0.4677, 'learning_rate': 1.0545774507080237e-05, 'epoch': 0.5}
+
50%|████▉ | 5954/11952 [2:18:07<9:45:19, 5.86s/it]
50%|████▉ | 5955/11952 [2:18:13<9:51:50, 5.92s/it]
{'loss': 0.4772, 'learning_rate': 1.054306862126149e-05, 'epoch': 0.5}
+
50%|████▉ | 5955/11952 [2:18:13<9:51:50, 5.92s/it]
50%|████▉ | 5956/11952 [2:18:19<9:52:07, 5.93s/it]
{'loss': 0.4747, 'learning_rate': 1.0540362695562043e-05, 'epoch': 0.5}
+
50%|████▉ | 5956/11952 [2:18:19<9:52:07, 5.93s/it]
50%|████▉ | 5957/11952 [2:18:25<9:46:15, 5.87s/it]
{'loss': 0.4751, 'learning_rate': 1.0537656730180606e-05, 'epoch': 0.5}
+
50%|████▉ | 5957/11952 [2:18:25<9:46:15, 5.87s/it]
50%|████▉ | 5958/11952 [2:18:30<9:42:56, 5.84s/it]
{'loss': 0.4904, 'learning_rate': 1.0534950725315893e-05, 'epoch': 0.5}
+
50%|████▉ | 5958/11952 [2:18:30<9:42:56, 5.84s/it]
50%|████▉ | 5959/11952 [2:18:36<9:43:52, 5.85s/it]
{'loss': 0.4845, 'learning_rate': 1.0532244681166628e-05, 'epoch': 0.5}
+
50%|████▉ | 5959/11952 [2:18:36<9:43:52, 5.85s/it]
50%|████▉ | 5960/11952 [2:18:42<9:46:25, 5.87s/it]
{'loss': 0.4788, 'learning_rate': 1.0529538597931524e-05, 'epoch': 0.5}
+
50%|████▉ | 5960/11952 [2:18:42<9:46:25, 5.87s/it]
50%|████▉ | 5961/11952 [2:18:48<9:44:30, 5.85s/it]
{'loss': 0.4771, 'learning_rate': 1.052683247580931e-05, 'epoch': 0.5}
+
50%|████▉ | 5961/11952 [2:18:48<9:44:30, 5.85s/it]
50%|████▉ | 5962/11952 [2:18:54<9:41:54, 5.83s/it]
{'loss': 0.4895, 'learning_rate': 1.0524126314998711e-05, 'epoch': 0.5}
+
50%|████▉ | 5962/11952 [2:18:54<9:41:54, 5.83s/it]
50%|████▉ | 5963/11952 [2:19:00<9:39:20, 5.80s/it]
{'loss': 0.4743, 'learning_rate': 1.0521420115698448e-05, 'epoch': 0.5}
+
50%|████▉ | 5963/11952 [2:19:00<9:39:20, 5.80s/it]
50%|████▉ | 5964/11952 [2:19:06<9:44:23, 5.86s/it]
{'loss': 0.4543, 'learning_rate': 1.0518713878107268e-05, 'epoch': 0.5}
+
50%|████▉ | 5964/11952 [2:19:06<9:44:23, 5.86s/it]
50%|████▉ | 5965/11952 [2:19:12<9:56:26, 5.98s/it]
{'loss': 0.4893, 'learning_rate': 1.0516007602423896e-05, 'epoch': 0.5}
+
50%|████▉ | 5965/11952 [2:19:12<9:56:26, 5.98s/it]
50%|████▉ | 5966/11952 [2:19:18<9:54:57, 5.96s/it]
{'loss': 0.4831, 'learning_rate': 1.0513301288847076e-05, 'epoch': 0.5}
+
50%|████▉ | 5966/11952 [2:19:18<9:54:57, 5.96s/it]
50%|████▉ | 5967/11952 [2:19:23<9:44:33, 5.86s/it]
{'loss': 0.4739, 'learning_rate': 1.0510594937575537e-05, 'epoch': 0.5}
+
50%|████▉ | 5967/11952 [2:19:23<9:44:33, 5.86s/it]
50%|████▉ | 5968/11952 [2:19:29<9:51:41, 5.93s/it]
{'loss': 0.4901, 'learning_rate': 1.0507888548808034e-05, 'epoch': 0.5}
+
50%|████▉ | 5968/11952 [2:19:29<9:51:41, 5.93s/it]
50%|████▉ | 5969/11952 [2:19:35<9:53:55, 5.96s/it]
{'loss': 0.4903, 'learning_rate': 1.0505182122743309e-05, 'epoch': 0.5}
+
50%|████▉ | 5969/11952 [2:19:35<9:53:55, 5.96s/it]
50%|████▉ | 5970/11952 [2:19:42<9:57:43, 6.00s/it]
{'loss': 0.4827, 'learning_rate': 1.0502475659580107e-05, 'epoch': 0.5}
+
50%|████▉ | 5970/11952 [2:19:42<9:57:43, 6.00s/it]
50%|████▉ | 5971/11952 [2:19:48<10:05:22, 6.07s/it]
{'loss': 0.4875, 'learning_rate': 1.0499769159517186e-05, 'epoch': 0.5}
+
50%|████▉ | 5971/11952 [2:19:48<10:05:22, 6.07s/it]
50%|████▉ | 5972/11952 [2:19:53<9:51:07, 5.93s/it]
{'loss': 0.4978, 'learning_rate': 1.0497062622753296e-05, 'epoch': 0.5}
+
50%|████▉ | 5972/11952 [2:19:53<9:51:07, 5.93s/it]
50%|████▉ | 5973/11952 [2:19:59<9:42:32, 5.85s/it]
{'loss': 0.4832, 'learning_rate': 1.049435604948719e-05, 'epoch': 0.5}
+
50%|████▉ | 5973/11952 [2:19:59<9:42:32, 5.85s/it]
50%|████▉ | 5974/11952 [2:20:05<9:40:54, 5.83s/it]
{'loss': 0.4586, 'learning_rate': 1.0491649439917636e-05, 'epoch': 0.5}
+
50%|████▉ | 5974/11952 [2:20:05<9:40:54, 5.83s/it]
50%|████▉ | 5975/11952 [2:20:11<9:44:25, 5.87s/it]
{'loss': 0.4639, 'learning_rate': 1.0488942794243393e-05, 'epoch': 0.5}
+
50%|████▉ | 5975/11952 [2:20:11<9:44:25, 5.87s/it]
50%|█████ | 5976/11952 [2:20:17<9:53:28, 5.96s/it]
{'loss': 0.4936, 'learning_rate': 1.0486236112663224e-05, 'epoch': 0.5}
+
50%|█████ | 5976/11952 [2:20:17<9:53:28, 5.96s/it]
50%|█████ | 5977/11952 [2:20:23<9:41:59, 5.84s/it]
{'loss': 0.4603, 'learning_rate': 1.0483529395375896e-05, 'epoch': 0.5}
+
50%|█████ | 5977/11952 [2:20:23<9:41:59, 5.84s/it]
50%|█████ | 5978/11952 [2:20:28<9:42:04, 5.85s/it]
{'loss': 0.4836, 'learning_rate': 1.0480822642580178e-05, 'epoch': 0.5}
+
50%|█████ | 5978/11952 [2:20:28<9:42:04, 5.85s/it]
50%|█████ | 5979/11952 [2:20:34<9:43:15, 5.86s/it]
{'loss': 0.5113, 'learning_rate': 1.0478115854474848e-05, 'epoch': 0.5}
+
50%|█████ | 5979/11952 [2:20:34<9:43:15, 5.86s/it]
50%|█████ | 5980/11952 [2:20:40<9:38:56, 5.82s/it]
{'loss': 0.4747, 'learning_rate': 1.0475409031258678e-05, 'epoch': 0.5}
+
50%|█████ | 5980/11952 [2:20:40<9:38:56, 5.82s/it]
50%|█████ | 5981/11952 [2:20:46<9:38:41, 5.82s/it]
{'loss': 0.4841, 'learning_rate': 1.0472702173130447e-05, 'epoch': 0.5}
+
50%|█████ | 5981/11952 [2:20:46<9:38:41, 5.82s/it]
50%|█████ | 5982/11952 [2:20:51<9:31:51, 5.75s/it]
{'loss': 0.4726, 'learning_rate': 1.0469995280288936e-05, 'epoch': 0.5}
+
50%|█████ | 5982/11952 [2:20:51<9:31:51, 5.75s/it]
50%|█████ | 5983/11952 [2:20:57<9:30:55, 5.74s/it]
{'loss': 0.47, 'learning_rate': 1.0467288352932923e-05, 'epoch': 0.5}
+
50%|█████ | 5983/11952 [2:20:57<9:30:55, 5.74s/it]
50%|█████ | 5984/11952 [2:21:03<9:33:48, 5.77s/it]
{'loss': 0.4819, 'learning_rate': 1.0464581391261198e-05, 'epoch': 0.5}
+
50%|█████ | 5984/11952 [2:21:03<9:33:48, 5.77s/it]
50%|█████ | 5985/11952 [2:21:09<9:37:10, 5.80s/it]
{'loss': 0.4767, 'learning_rate': 1.0461874395472549e-05, 'epoch': 0.5}
+
50%|█████ | 5985/11952 [2:21:09<9:37:10, 5.80s/it]
50%|█████ | 5986/11952 [2:21:15<9:42:29, 5.86s/it]
{'loss': 0.4681, 'learning_rate': 1.0459167365765765e-05, 'epoch': 0.5}
+
50%|█████ | 5986/11952 [2:21:15<9:42:29, 5.86s/it]
50%|█████ | 5987/11952 [2:21:21<9:39:50, 5.83s/it]
{'loss': 0.4776, 'learning_rate': 1.0456460302339636e-05, 'epoch': 0.5}
+
50%|█████ | 5987/11952 [2:21:21<9:39:50, 5.83s/it]
50%|█████ | 5988/11952 [2:21:26<9:40:10, 5.84s/it]
{'loss': 0.4719, 'learning_rate': 1.0453753205392967e-05, 'epoch': 0.5}
+
50%|█████ | 5988/11952 [2:21:26<9:40:10, 5.84s/it]
50%|█████ | 5989/11952 [2:21:32<9:39:15, 5.83s/it]
{'loss': 0.4728, 'learning_rate': 1.0451046075124544e-05, 'epoch': 0.5}
+
50%|█████ | 5989/11952 [2:21:32<9:39:15, 5.83s/it]
50%|█████ | 5990/11952 [2:21:38<9:40:32, 5.84s/it]
{'loss': 0.4883, 'learning_rate': 1.0448338911733178e-05, 'epoch': 0.5}
+
50%|█████ | 5990/11952 [2:21:38<9:40:32, 5.84s/it]
50%|█████ | 5991/11952 [2:21:44<9:41:34, 5.85s/it]
{'loss': 0.5035, 'learning_rate': 1.0445631715417666e-05, 'epoch': 0.5}
+
50%|█████ | 5991/11952 [2:21:44<9:41:34, 5.85s/it]
50%|█████ | 5992/11952 [2:21:50<9:54:47, 5.99s/it]
{'loss': 0.4744, 'learning_rate': 1.0442924486376813e-05, 'epoch': 0.5}
+
50%|█████ | 5992/11952 [2:21:50<9:54:47, 5.99s/it]
50%|█████ | 5993/11952 [2:21:56<9:51:47, 5.96s/it]
{'loss': 0.498, 'learning_rate': 1.0440217224809427e-05, 'epoch': 0.5}
+
50%|█████ | 5993/11952 [2:21:56<9:51:47, 5.96s/it]
50%|█████ | 5994/11952 [2:22:02<9:43:30, 5.88s/it]
{'loss': 0.4707, 'learning_rate': 1.043750993091432e-05, 'epoch': 0.5}
+
50%|█████ | 5994/11952 [2:22:02<9:43:30, 5.88s/it]
50%|█████ | 5995/11952 [2:22:08<9:54:39, 5.99s/it]
{'loss': 0.4854, 'learning_rate': 1.0434802604890306e-05, 'epoch': 0.5}
+
50%|█████ | 5995/11952 [2:22:08<9:54:39, 5.99s/it]
50%|█████ | 5996/11952 [2:22:14<9:56:52, 6.01s/it]
{'loss': 0.4768, 'learning_rate': 1.0432095246936195e-05, 'epoch': 0.5}
+
50%|█████ | 5996/11952 [2:22:14<9:56:52, 6.01s/it]
50%|█████ | 5997/11952 [2:22:20<9:46:32, 5.91s/it]
{'loss': 0.4729, 'learning_rate': 1.0429387857250806e-05, 'epoch': 0.5}
+
50%|█████ | 5997/11952 [2:22:20<9:46:32, 5.91s/it]
50%|█████ | 5998/11952 [2:22:26<9:52:52, 5.97s/it]
{'loss': 0.483, 'learning_rate': 1.042668043603296e-05, 'epoch': 0.5}
+
50%|█████ | 5998/11952 [2:22:26<9:52:52, 5.97s/it]
50%|█████ | 5999/11952 [2:22:32<10:01:23, 6.06s/it]
{'loss': 0.4757, 'learning_rate': 1.0423972983481477e-05, 'epoch': 0.5}
+
50%|█████ | 5999/11952 [2:22:32<10:01:23, 6.06s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+71 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
50%|█████ | 6000/11952 [2:22:38<9:52:18, 5.97s/it] 5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4865, 'learning_rate': 1.0421265499795181e-05, 'epoch': 0.5}
+
50%|█████ | 6000/11952 [2:22:38<9:52:18, 5.97s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
50%|█████ | 6001/11952 [2:23:07<21:21:51, 12.92s/it]
{'loss': 0.4946, 'learning_rate': 1.0418557985172899e-05, 'epoch': 0.5}
+
50%|█████ | 6001/11952 [2:23:07<21:21:51, 12.92s/it]
50%|█████ | 6002/11952 [2:23:13<17:55:26, 10.84s/it]
{'loss': 0.4533, 'learning_rate': 1.0415850439813462e-05, 'epoch': 0.5}
+
50%|█████ | 6002/11952 [2:23:13<17:55:26, 10.84s/it]
50%|█████ | 6003/11952 [2:23:19<15:22:13, 9.30s/it]
{'loss': 0.4847, 'learning_rate': 1.0413142863915695e-05, 'epoch': 0.5}
+
50%|█████ | 6003/11952 [2:23:19<15:22:13, 9.30s/it]
50%|█████ | 6004/11952 [2:23:25<13:39:19, 8.26s/it]
{'loss': 0.4828, 'learning_rate': 1.0410435257678433e-05, 'epoch': 0.5}
+
50%|█████ | 6004/11952 [2:23:25<13:39:19, 8.26s/it]
50%|█████ | 6005/11952 [2:23:30<12:20:46, 7.47s/it]
{'loss': 0.4671, 'learning_rate': 1.0407727621300516e-05, 'epoch': 0.5}
+
50%|█████ | 6005/11952 [2:23:30<12:20:46, 7.47s/it]
50%|█████ | 6006/11952 [2:23:36<11:29:48, 6.96s/it]
{'loss': 0.4716, 'learning_rate': 1.0405019954980779e-05, 'epoch': 0.5}
+
50%|█████ | 6006/11952 [2:23:36<11:29:48, 6.96s/it]
50%|█████ | 6007/11952 [2:23:42<10:52:26, 6.58s/it]
{'loss': 0.4786, 'learning_rate': 1.0402312258918061e-05, 'epoch': 0.5}
+
50%|█████ | 6007/11952 [2:23:42<10:52:26, 6.58s/it]
50%|█████ | 6008/11952 [2:23:48<10:41:16, 6.47s/it]
{'loss': 0.4873, 'learning_rate': 1.03996045333112e-05, 'epoch': 0.5}
+
50%|█████ | 6008/11952 [2:23:48<10:41:16, 6.47s/it]
50%|█████ | 6009/11952 [2:23:54<10:29:34, 6.36s/it]
{'loss': 0.479, 'learning_rate': 1.0396896778359047e-05, 'epoch': 0.5}
+
50%|█████ | 6009/11952 [2:23:54<10:29:34, 6.36s/it]
50%|█████ | 6010/11952 [2:24:00<10:12:49, 6.19s/it]
{'loss': 0.463, 'learning_rate': 1.0394188994260445e-05, 'epoch': 0.5}
+
50%|█████ | 6010/11952 [2:24:00<10:12:49, 6.19s/it]
50%|█████ | 6011/11952 [2:24:06<10:04:28, 6.10s/it]
{'loss': 0.4551, 'learning_rate': 1.0391481181214244e-05, 'epoch': 0.5}
+
50%|█████ | 6011/11952 [2:24:06<10:04:28, 6.10s/it]
50%|█████ | 6012/11952 [2:24:11<9:50:02, 5.96s/it]
{'loss': 0.4634, 'learning_rate': 1.0388773339419294e-05, 'epoch': 0.5}
+
50%|█████ | 6012/11952 [2:24:11<9:50:02, 5.96s/it]
50%|█████ | 6013/11952 [2:24:18<9:56:59, 6.03s/it]
{'loss': 0.4834, 'learning_rate': 1.0386065469074447e-05, 'epoch': 0.5}
+
50%|█████ | 6013/11952 [2:24:18<9:56:59, 6.03s/it]
50%|█████ | 6014/11952 [2:24:24<9:59:47, 6.06s/it]
{'loss': 0.4901, 'learning_rate': 1.0383357570378553e-05, 'epoch': 0.5}
+
50%|█████ | 6014/11952 [2:24:24<9:59:47, 6.06s/it]
50%|█████ | 6015/11952 [2:24:30<9:50:03, 5.96s/it]
{'loss': 0.4779, 'learning_rate': 1.0380649643530476e-05, 'epoch': 0.5}
+
50%|█████ | 6015/11952 [2:24:30<9:50:03, 5.96s/it]
50%|█████ | 6016/11952 [2:24:35<9:50:21, 5.97s/it]
{'loss': 0.4925, 'learning_rate': 1.0377941688729074e-05, 'epoch': 0.5}
+
50%|█████ | 6016/11952 [2:24:35<9:50:21, 5.97s/it]
50%|█████ | 6017/11952 [2:24:42<10:03:02, 6.10s/it]
{'loss': 0.4912, 'learning_rate': 1.0375233706173207e-05, 'epoch': 0.5}
+
50%|█████ | 6017/11952 [2:24:42<10:03:02, 6.10s/it]
50%|█████ | 6018/11952 [2:24:48<10:05:12, 6.12s/it]
{'loss': 0.4781, 'learning_rate': 1.0372525696061735e-05, 'epoch': 0.5}
+
50%|█████ | 6018/11952 [2:24:48<10:05:12, 6.12s/it]
50%|█████ | 6019/11952 [2:24:54<9:50:04, 5.97s/it]
{'loss': 0.4854, 'learning_rate': 1.0369817658593524e-05, 'epoch': 0.5}
+
50%|█████ | 6019/11952 [2:24:54<9:50:04, 5.97s/it]
50%|█████ | 6020/11952 [2:25:00<9:48:16, 5.95s/it]
{'loss': 0.4858, 'learning_rate': 1.0367109593967445e-05, 'epoch': 0.5}
+
50%|█████ | 6020/11952 [2:25:00<9:48:16, 5.95s/it]
50%|█████ | 6021/11952 [2:25:06<9:47:25, 5.94s/it]
{'loss': 0.4811, 'learning_rate': 1.0364401502382364e-05, 'epoch': 0.5}
+
50%|█████ | 6021/11952 [2:25:06<9:47:25, 5.94s/it]
50%|█████ | 6022/11952 [2:25:11<9:43:59, 5.91s/it]
{'loss': 0.4865, 'learning_rate': 1.0361693384037154e-05, 'epoch': 0.5}
+
50%|█████ | 6022/11952 [2:25:11<9:43:59, 5.91s/it]
50%|█████ | 6023/11952 [2:25:17<9:41:23, 5.88s/it]
{'loss': 0.4867, 'learning_rate': 1.0358985239130685e-05, 'epoch': 0.5}
+
50%|█████ | 6023/11952 [2:25:17<9:41:23, 5.88s/it]
50%|█████ | 6024/11952 [2:25:23<9:44:38, 5.92s/it]
{'loss': 0.4796, 'learning_rate': 1.035627706786183e-05, 'epoch': 0.5}
+
50%|█████ | 6024/11952 [2:25:23<9:44:38, 5.92s/it]
50%|█████ | 6025/11952 [2:25:29<9:40:47, 5.88s/it]
{'loss': 0.486, 'learning_rate': 1.035356887042947e-05, 'epoch': 0.5}
+
50%|█████ | 6025/11952 [2:25:29<9:40:47, 5.88s/it]
50%|█████ | 6026/11952 [2:25:35<9:49:56, 5.97s/it]
{'loss': 0.4733, 'learning_rate': 1.0350860647032488e-05, 'epoch': 0.5}
+
50%|█████ | 6026/11952 [2:25:35<9:49:56, 5.97s/it]
50%|█████ | 6027/11952 [2:25:41<9:50:18, 5.98s/it]
{'loss': 0.4706, 'learning_rate': 1.0348152397869757e-05, 'epoch': 0.5}
+
50%|█████ | 6027/11952 [2:25:41<9:50:18, 5.98s/it]
50%|█████ | 6028/11952 [2:25:47<9:42:49, 5.90s/it]
{'loss': 0.4709, 'learning_rate': 1.0345444123140159e-05, 'epoch': 0.5}
+
50%|█████ | 6028/11952 [2:25:47<9:42:49, 5.90s/it]
50%|█████ | 6029/11952 [2:25:52<9:34:45, 5.82s/it]
{'loss': 0.4718, 'learning_rate': 1.0342735823042585e-05, 'epoch': 0.5}
+
50%|█████ | 6029/11952 [2:25:52<9:34:45, 5.82s/it]
50%|█████ | 6030/11952 [2:25:58<9:36:00, 5.84s/it]
{'loss': 0.476, 'learning_rate': 1.0340027497775915e-05, 'epoch': 0.5}
+
50%|█████ | 6030/11952 [2:25:58<9:36:00, 5.84s/it]
50%|█████ | 6031/11952 [2:26:04<9:42:38, 5.90s/it]
{'loss': 0.4838, 'learning_rate': 1.0337319147539042e-05, 'epoch': 0.5}
+
50%|█████ | 6031/11952 [2:26:04<9:42:38, 5.90s/it]
50%|█████ | 6032/11952 [2:26:11<9:49:41, 5.98s/it]
{'loss': 0.4914, 'learning_rate': 1.0334610772530851e-05, 'epoch': 0.5}
+
50%|█████ | 6032/11952 [2:26:11<9:49:41, 5.98s/it]
50%|█████ | 6033/11952 [2:26:16<9:40:31, 5.88s/it]
{'loss': 0.4516, 'learning_rate': 1.033190237295024e-05, 'epoch': 0.5}
+
50%|█████ | 6033/11952 [2:26:16<9:40:31, 5.88s/it]
50%|█████ | 6034/11952 [2:26:22<9:41:00, 5.89s/it]
{'loss': 0.4834, 'learning_rate': 1.0329193948996097e-05, 'epoch': 0.5}
+
50%|█████ | 6034/11952 [2:26:22<9:41:00, 5.89s/it]
50%|█████ | 6035/11952 [2:26:28<9:42:04, 5.90s/it]
{'loss': 0.4735, 'learning_rate': 1.0326485500867316e-05, 'epoch': 0.5}
+
50%|█████ | 6035/11952 [2:26:28<9:42:04, 5.90s/it]
51%|█████ | 6036/11952 [2:26:34<9:40:24, 5.89s/it]
{'loss': 0.4786, 'learning_rate': 1.0323777028762804e-05, 'epoch': 0.5}
+
51%|█████ | 6036/11952 [2:26:34<9:40:24, 5.89s/it]
51%|█████ | 6037/11952 [2:26:40<9:31:24, 5.80s/it]
{'loss': 0.4708, 'learning_rate': 1.0321068532881454e-05, 'epoch': 0.51}
+
51%|█████ | 6037/11952 [2:26:40<9:31:24, 5.80s/it]
51%|█████ | 6038/11952 [2:26:45<9:34:20, 5.83s/it]
{'loss': 0.5103, 'learning_rate': 1.0318360013422162e-05, 'epoch': 0.51}
+
51%|█████ | 6038/11952 [2:26:45<9:34:20, 5.83s/it]
51%|█████ | 6039/11952 [2:26:51<9:32:10, 5.81s/it]
{'loss': 0.5011, 'learning_rate': 1.0315651470583836e-05, 'epoch': 0.51}
+
51%|█████ | 6039/11952 [2:26:51<9:32:10, 5.81s/it]
51%|█████ | 6040/11952 [2:26:57<9:35:28, 5.84s/it]
{'loss': 0.4685, 'learning_rate': 1.0312942904565379e-05, 'epoch': 0.51}
+
51%|█████ | 6040/11952 [2:26:57<9:35:28, 5.84s/it]
51%|█████ | 6041/11952 [2:27:03<9:46:46, 5.96s/it]
{'loss': 0.4897, 'learning_rate': 1.0310234315565699e-05, 'epoch': 0.51}
+
51%|█████ | 6041/11952 [2:27:03<9:46:46, 5.96s/it]
51%|█████ | 6042/11952 [2:27:09<9:35:45, 5.85s/it]
{'loss': 0.489, 'learning_rate': 1.0307525703783698e-05, 'epoch': 0.51}
+
51%|█████ | 6042/11952 [2:27:09<9:35:45, 5.85s/it]
51%|█████ | 6043/11952 [2:27:15<9:50:05, 5.99s/it]
{'loss': 0.4754, 'learning_rate': 1.0304817069418292e-05, 'epoch': 0.51}
+
51%|█████ | 6043/11952 [2:27:15<9:50:05, 5.99s/it]
51%|█████ | 6044/11952 [2:27:21<9:45:13, 5.94s/it]
{'loss': 0.4889, 'learning_rate': 1.0302108412668387e-05, 'epoch': 0.51}
+
51%|█████ | 6044/11952 [2:27:21<9:45:13, 5.94s/it]
51%|█████ | 6045/11952 [2:27:27<9:46:43, 5.96s/it]
{'loss': 0.4967, 'learning_rate': 1.0299399733732893e-05, 'epoch': 0.51}
+
51%|█████ | 6045/11952 [2:27:27<9:46:43, 5.96s/it]
51%|█████ | 6046/11952 [2:27:33<9:42:53, 5.92s/it]
{'loss': 0.4701, 'learning_rate': 1.029669103281073e-05, 'epoch': 0.51}
+
51%|█████ | 6046/11952 [2:27:33<9:42:53, 5.92s/it]
51%|█████ | 6047/11952 [2:27:39<9:44:37, 5.94s/it]
{'loss': 0.4751, 'learning_rate': 1.0293982310100814e-05, 'epoch': 0.51}
+
51%|█████ | 6047/11952 [2:27:39<9:44:37, 5.94s/it]
51%|█████ | 6048/11952 [2:27:45<9:41:47, 5.91s/it]
{'loss': 0.4912, 'learning_rate': 1.0291273565802058e-05, 'epoch': 0.51}
+
51%|█████ | 6048/11952 [2:27:45<9:41:47, 5.91s/it]
51%|█████ | 6049/11952 [2:27:50<9:30:21, 5.80s/it]
{'loss': 0.4817, 'learning_rate': 1.0288564800113383e-05, 'epoch': 0.51}
+
51%|█████ | 6049/11952 [2:27:50<9:30:21, 5.80s/it]02 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
51%|█████ | 6050/11952 [2:27:56<9:22:35, 5.72s/it]7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4599, 'learning_rate': 1.0285856013233708e-05, 'epoch': 0.51}
+
51%|█████ | 6050/11952 [2:27:56<9:22:35, 5.72s/it]
51%|█████ | 6051/11952 [2:28:02<9:25:17, 5.75s/it]
{'loss': 0.4964, 'learning_rate': 1.0283147205361959e-05, 'epoch': 0.51}
+
51%|█████ | 6051/11952 [2:28:02<9:25:17, 5.75s/it]
51%|█████ | 6052/11952 [2:28:08<9:32:12, 5.82s/it]
{'loss': 0.4632, 'learning_rate': 1.0280438376697056e-05, 'epoch': 0.51}
+
51%|█████ | 6052/11952 [2:28:08<9:32:12, 5.82s/it]
51%|█████ | 6053/11952 [2:28:13<9:33:37, 5.83s/it]
{'loss': 0.463, 'learning_rate': 1.0277729527437924e-05, 'epoch': 0.51}
+
51%|█████ | 6053/11952 [2:28:13<9:33:37, 5.83s/it]
51%|█████ | 6054/11952 [2:28:19<9:32:21, 5.82s/it]
{'loss': 0.493, 'learning_rate': 1.0275020657783492e-05, 'epoch': 0.51}
+
51%|█████ | 6054/11952 [2:28:19<9:32:21, 5.82s/it]
51%|█████ | 6055/11952 [2:28:25<9:41:44, 5.92s/it]
{'loss': 0.4833, 'learning_rate': 1.0272311767932686e-05, 'epoch': 0.51}
+
51%|█████ | 6055/11952 [2:28:25<9:41:44, 5.92s/it]
51%|█████ | 6056/11952 [2:28:31<9:34:14, 5.84s/it]
{'loss': 0.4912, 'learning_rate': 1.0269602858084435e-05, 'epoch': 0.51}
+
51%|█████ | 6056/11952 [2:28:31<9:34:14, 5.84s/it]
51%|█████ | 6057/11952 [2:28:37<9:34:24, 5.85s/it]
{'loss': 0.481, 'learning_rate': 1.0266893928437673e-05, 'epoch': 0.51}
+
51%|█████ | 6057/11952 [2:28:37<9:34:24, 5.85s/it]
51%|█████ | 6058/11952 [2:28:43<9:42:30, 5.93s/it]
{'loss': 0.4745, 'learning_rate': 1.0264184979191331e-05, 'epoch': 0.51}
+
51%|█████ | 6058/11952 [2:28:43<9:42:30, 5.93s/it]
51%|█████ | 6059/11952 [2:28:49<9:38:47, 5.89s/it]
{'loss': 0.4958, 'learning_rate': 1.0261476010544345e-05, 'epoch': 0.51}
+
51%|█████ | 6059/11952 [2:28:49<9:38:47, 5.89s/it]
51%|█████ | 6060/11952 [2:28:55<9:38:41, 5.89s/it]
{'loss': 0.491, 'learning_rate': 1.0258767022695645e-05, 'epoch': 0.51}
+
51%|█████ | 6060/11952 [2:28:55<9:38:41, 5.89s/it]
51%|█████ | 6061/11952 [2:29:01<9:43:20, 5.94s/it]
{'loss': 0.4881, 'learning_rate': 1.0256058015844173e-05, 'epoch': 0.51}
+
51%|█████ | 6061/11952 [2:29:01<9:43:20, 5.94s/it]
51%|█████ | 6062/11952 [2:29:06<9:32:31, 5.83s/it]
{'loss': 0.4736, 'learning_rate': 1.0253348990188863e-05, 'epoch': 0.51}
+
51%|█████ | 6062/11952 [2:29:06<9:32:31, 5.83s/it]
51%|█████ | 6063/11952 [2:29:12<9:25:00, 5.76s/it]
{'loss': 0.4744, 'learning_rate': 1.025063994592866e-05, 'epoch': 0.51}
+
51%|█████ | 6063/11952 [2:29:12<9:25:00, 5.76s/it]
51%|█████ | 6064/11952 [2:29:18<9:27:13, 5.78s/it]
{'loss': 0.4759, 'learning_rate': 1.02479308832625e-05, 'epoch': 0.51}
+
51%|█████ | 6064/11952 [2:29:18<9:27:13, 5.78s/it]
51%|█████ | 6065/11952 [2:29:24<9:40:48, 5.92s/it]
{'loss': 0.4655, 'learning_rate': 1.0245221802389328e-05, 'epoch': 0.51}
+
51%|█████ | 6065/11952 [2:29:24<9:40:48, 5.92s/it]
51%|█████ | 6066/11952 [2:29:30<9:33:59, 5.85s/it]
{'loss': 0.4912, 'learning_rate': 1.0242512703508085e-05, 'epoch': 0.51}
+
51%|█████ | 6066/11952 [2:29:30<9:33:59, 5.85s/it]
51%|█████ | 6067/11952 [2:29:36<9:34:38, 5.86s/it]
{'loss': 0.4852, 'learning_rate': 1.023980358681772e-05, 'epoch': 0.51}
+
51%|█████ | 6067/11952 [2:29:36<9:34:38, 5.86s/it]
51%|█████ | 6068/11952 [2:29:42<9:37:58, 5.89s/it]
{'loss': 0.4838, 'learning_rate': 1.0237094452517178e-05, 'epoch': 0.51}
+
51%|█████ | 6068/11952 [2:29:42<9:37:58, 5.89s/it]
51%|█████ | 6069/11952 [2:29:48<9:39:52, 5.91s/it]
{'loss': 0.4851, 'learning_rate': 1.0234385300805403e-05, 'epoch': 0.51}
+
51%|█████ | 6069/11952 [2:29:48<9:39:52, 5.91s/it]
51%|█████ | 6070/11952 [2:29:53<9:33:04, 5.85s/it]
{'loss': 0.4732, 'learning_rate': 1.0231676131881348e-05, 'epoch': 0.51}
+
51%|█████ | 6070/11952 [2:29:53<9:33:04, 5.85s/it]
51%|█████ | 6071/11952 [2:30:00<9:50:33, 6.03s/it]
{'loss': 0.4902, 'learning_rate': 1.022896694594396e-05, 'epoch': 0.51}
+
51%|█████ | 6071/11952 [2:30:00<9:50:33, 6.03s/it]
51%|█████ | 6072/11952 [2:30:06<9:49:01, 6.01s/it]
{'loss': 0.4603, 'learning_rate': 1.022625774319219e-05, 'epoch': 0.51}
+
51%|█████ | 6072/11952 [2:30:06<9:49:01, 6.01s/it]
51%|█████ | 6073/11952 [2:30:11<9:40:23, 5.92s/it]
{'loss': 0.4785, 'learning_rate': 1.0223548523824996e-05, 'epoch': 0.51}
+
51%|█████ | 6073/11952 [2:30:11<9:40:23, 5.92s/it]
51%|█████ | 6074/11952 [2:30:17<9:30:47, 5.83s/it]
{'loss': 0.4651, 'learning_rate': 1.0220839288041328e-05, 'epoch': 0.51}
+
51%|█████ | 6074/11952 [2:30:17<9:30:47, 5.83s/it]
51%|█████ | 6075/11952 [2:30:23<9:28:03, 5.80s/it]
{'loss': 0.4707, 'learning_rate': 1.021813003604014e-05, 'epoch': 0.51}
+
51%|█████ | 6075/11952 [2:30:23<9:28:03, 5.80s/it]
51%|█████ | 6076/11952 [2:30:29<9:28:04, 5.80s/it]
{'loss': 0.5073, 'learning_rate': 1.0215420768020388e-05, 'epoch': 0.51}
+
51%|█████ | 6076/11952 [2:30:29<9:28:04, 5.80s/it]
51%|█████ | 6077/11952 [2:30:35<9:42:13, 5.95s/it]
{'loss': 0.4872, 'learning_rate': 1.0212711484181034e-05, 'epoch': 0.51}
+
51%|█████ | 6077/11952 [2:30:35<9:42:13, 5.95s/it]
51%|█████ | 6078/11952 [2:30:41<9:37:57, 5.90s/it]
{'loss': 0.4836, 'learning_rate': 1.0210002184721033e-05, 'epoch': 0.51}
+
51%|█████ | 6078/11952 [2:30:41<9:37:57, 5.90s/it]
51%|█████ | 6079/11952 [2:30:46<9:29:13, 5.82s/it]
{'loss': 0.46, 'learning_rate': 1.0207292869839343e-05, 'epoch': 0.51}
+
51%|█████ | 6079/11952 [2:30:46<9:29:13, 5.82s/it]
51%|█████ | 6080/11952 [2:30:52<9:24:00, 5.76s/it]
{'loss': 0.4641, 'learning_rate': 1.020458353973493e-05, 'epoch': 0.51}
+
51%|█████ | 6080/11952 [2:30:52<9:24:00, 5.76s/it]
51%|█████ | 6081/11952 [2:30:58<9:23:45, 5.76s/it]
{'loss': 0.4703, 'learning_rate': 1.0201874194606748e-05, 'epoch': 0.51}
+
51%|█████ | 6081/11952 [2:30:58<9:23:45, 5.76s/it]
51%|█████ | 6082/11952 [2:31:03<9:21:42, 5.74s/it]
{'loss': 0.4775, 'learning_rate': 1.019916483465377e-05, 'epoch': 0.51}
+
51%|█████ | 6082/11952 [2:31:03<9:21:42, 5.74s/it]
51%|█████ | 6083/11952 [2:31:09<9:20:14, 5.73s/it]
{'loss': 0.4857, 'learning_rate': 1.019645546007495e-05, 'epoch': 0.51}
+
51%|█████ | 6083/11952 [2:31:09<9:20:14, 5.73s/it]
51%|█████ | 6084/11952 [2:31:15<9:19:28, 5.72s/it]
{'loss': 0.4703, 'learning_rate': 1.0193746071069262e-05, 'epoch': 0.51}
+
51%|█████ | 6084/11952 [2:31:15<9:19:28, 5.72s/it]
51%|█████ | 6085/11952 [2:31:21<9:24:23, 5.77s/it]
{'loss': 0.4713, 'learning_rate': 1.0191036667835668e-05, 'epoch': 0.51}
+
51%|█████ | 6085/11952 [2:31:21<9:24:23, 5.77s/it]
51%|█████ | 6086/11952 [2:31:26<9:25:53, 5.79s/it]
{'loss': 0.4823, 'learning_rate': 1.0188327250573133e-05, 'epoch': 0.51}
+
51%|█████ | 6086/11952 [2:31:26<9:25:53, 5.79s/it]
51%|█████ | 6087/11952 [2:31:32<9:26:10, 5.79s/it]
{'loss': 0.4943, 'learning_rate': 1.0185617819480628e-05, 'epoch': 0.51}
+
51%|█████ | 6087/11952 [2:31:32<9:26:10, 5.79s/it]
51%|█████ | 6088/11952 [2:31:38<9:32:02, 5.85s/it]
{'loss': 0.4849, 'learning_rate': 1.0182908374757126e-05, 'epoch': 0.51}
+
51%|█████ | 6088/11952 [2:31:38<9:32:02, 5.85s/it]
51%|█████ | 6089/11952 [2:31:44<9:29:41, 5.83s/it]
{'loss': 0.4815, 'learning_rate': 1.0180198916601592e-05, 'epoch': 0.51}
+
51%|█████ | 6089/11952 [2:31:44<9:29:41, 5.83s/it]
51%|█████ | 6090/11952 [2:31:50<9:37:30, 5.91s/it]
{'loss': 0.486, 'learning_rate': 1.0177489445212998e-05, 'epoch': 0.51}
+
51%|█████ | 6090/11952 [2:31:50<9:37:30, 5.91s/it]
51%|█████ | 6091/11952 [2:31:56<9:39:51, 5.94s/it]
{'loss': 0.4575, 'learning_rate': 1.0174779960790318e-05, 'epoch': 0.51}
+
51%|█████ | 6091/11952 [2:31:56<9:39:51, 5.94s/it]
51%|█████ | 6092/11952 [2:32:02<9:34:36, 5.88s/it]
{'loss': 0.4709, 'learning_rate': 1.0172070463532524e-05, 'epoch': 0.51}
+
51%|█████ | 6092/11952 [2:32:02<9:34:36, 5.88s/it]
51%|█████ | 6093/11952 [2:32:08<9:39:33, 5.94s/it]
{'loss': 0.4649, 'learning_rate': 1.016936095363859e-05, 'epoch': 0.51}
+
51%|█████ | 6093/11952 [2:32:08<9:39:33, 5.94s/it]
51%|█████ | 6094/11952 [2:32:14<9:44:21, 5.99s/it]
{'loss': 0.4872, 'learning_rate': 1.0166651431307494e-05, 'epoch': 0.51}
+
51%|█████ | 6094/11952 [2:32:14<9:44:21, 5.99s/it]
51%|█████ | 6095/11952 [2:32:20<9:41:16, 5.95s/it]
{'loss': 0.4819, 'learning_rate': 1.0163941896738213e-05, 'epoch': 0.51}
+
51%|█████ | 6095/11952 [2:32:20<9:41:16, 5.95s/it]
51%|█████ | 6096/11952 [2:32:26<9:33:56, 5.88s/it]
{'loss': 0.4658, 'learning_rate': 1.0161232350129715e-05, 'epoch': 0.51}
+
51%|█████ | 6096/11952 [2:32:26<9:33:56, 5.88s/it]
51%|█████ | 6097/11952 [2:32:32<9:41:58, 5.96s/it]
{'loss': 0.4744, 'learning_rate': 1.0158522791680985e-05, 'epoch': 0.51}
+
51%|█████ | 6097/11952 [2:32:32<9:41:58, 5.96s/it]
51%|█████ | 6098/11952 [2:32:38<9:49:04, 6.04s/it]
{'loss': 0.4849, 'learning_rate': 1.0155813221591004e-05, 'epoch': 0.51}
+
51%|█████ | 6098/11952 [2:32:38<9:49:04, 6.04s/it]
51%|█████ | 6099/11952 [2:32:44<9:47:27, 6.02s/it]
{'loss': 0.4775, 'learning_rate': 1.0153103640058745e-05, 'epoch': 0.51}
+
51%|█████ | 6099/11952 [2:32:44<9:47:27, 6.02s/it]4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
51%|█████ | 6100/11952 [2:32:49<9:32:26, 5.87s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4644, 'learning_rate': 1.0150394047283192e-05, 'epoch': 0.51}
+
51%|█████ | 6100/11952 [2:32:49<9:32:26, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
51%|█████ | 6101/11952 [2:33:19<20:57:58, 12.90s/it]
{'loss': 0.4933, 'learning_rate': 1.0147684443463328e-05, 'epoch': 0.51}
+
51%|█████ | 6101/11952 [2:33:19<20:57:58, 12.90s/it]
51%|█████ | 6102/11952 [2:33:25<17:28:24, 10.75s/it]
{'loss': 0.4612, 'learning_rate': 1.0144974828798131e-05, 'epoch': 0.51}
+
51%|█████ | 6102/11952 [2:33:25<17:28:24, 10.75s/it]
51%|█████ | 6103/11952 [2:33:30<15:00:04, 9.23s/it]
{'loss': 0.4857, 'learning_rate': 1.0142265203486583e-05, 'epoch': 0.51}
+
51%|█████ | 6103/11952 [2:33:30<15:00:04, 9.23s/it]
51%|█████ | 6104/11952 [2:33:36<13:17:27, 8.18s/it]
{'loss': 0.4879, 'learning_rate': 1.0139555567727674e-05, 'epoch': 0.51}
+
51%|█████ | 6104/11952 [2:33:36<13:17:27, 8.18s/it]
51%|█████ | 6105/11952 [2:33:42<12:14:00, 7.53s/it]
{'loss': 0.4769, 'learning_rate': 1.0136845921720385e-05, 'epoch': 0.51}
+
51%|█████ | 6105/11952 [2:33:42<12:14:00, 7.53s/it]
51%|█████ | 6106/11952 [2:33:48<11:21:57, 7.00s/it]
{'loss': 0.4763, 'learning_rate': 1.0134136265663698e-05, 'epoch': 0.51}
+
51%|█████ | 6106/11952 [2:33:48<11:21:57, 7.00s/it]
51%|█████ | 6107/11952 [2:33:54<10:47:03, 6.64s/it]
{'loss': 0.4778, 'learning_rate': 1.01314265997566e-05, 'epoch': 0.51}
+
51%|█████ | 6107/11952 [2:33:54<10:47:03, 6.64s/it]
51%|█████ | 6108/11952 [2:33:59<10:23:36, 6.40s/it]
{'loss': 0.4715, 'learning_rate': 1.0128716924198083e-05, 'epoch': 0.51}
+
51%|█████ | 6108/11952 [2:33:59<10:23:36, 6.40s/it]
51%|█████ | 6109/11952 [2:34:05<10:05:57, 6.22s/it]
{'loss': 0.468, 'learning_rate': 1.012600723918713e-05, 'epoch': 0.51}
+
51%|█████ | 6109/11952 [2:34:05<10:05:57, 6.22s/it]
51%|█████ | 6110/11952 [2:34:11<9:55:29, 6.12s/it]
{'loss': 0.5026, 'learning_rate': 1.0123297544922728e-05, 'epoch': 0.51}
+
51%|█████ | 6110/11952 [2:34:11<9:55:29, 6.12s/it]
51%|█████ | 6111/11952 [2:34:17<9:47:37, 6.04s/it]
{'loss': 0.4965, 'learning_rate': 1.0120587841603868e-05, 'epoch': 0.51}
+
51%|█████ | 6111/11952 [2:34:17<9:47:37, 6.04s/it]
51%|█████ | 6112/11952 [2:34:23<9:45:35, 6.02s/it]
{'loss': 0.4759, 'learning_rate': 1.011787812942954e-05, 'epoch': 0.51}
+
51%|█████ | 6112/11952 [2:34:23<9:45:35, 6.02s/it]
51%|█████ | 6113/11952 [2:34:29<9:43:26, 6.00s/it]
{'loss': 0.4755, 'learning_rate': 1.0115168408598728e-05, 'epoch': 0.51}
+
51%|█████ | 6113/11952 [2:34:29<9:43:26, 6.00s/it]
51%|█████ | 6114/11952 [2:34:34<9:30:44, 5.87s/it]
{'loss': 0.4671, 'learning_rate': 1.011245867931043e-05, 'epoch': 0.51}
+
51%|█████ | 6114/11952 [2:34:34<9:30:44, 5.87s/it]
51%|█████ | 6115/11952 [2:34:40<9:23:52, 5.80s/it]
{'loss': 0.4646, 'learning_rate': 1.0109748941763635e-05, 'epoch': 0.51}
+
51%|█████ | 6115/11952 [2:34:40<9:23:52, 5.80s/it]
51%|█████ | 6116/11952 [2:34:46<9:27:25, 5.83s/it]
{'loss': 0.4868, 'learning_rate': 1.0107039196157335e-05, 'epoch': 0.51}
+
51%|█████ | 6116/11952 [2:34:46<9:27:25, 5.83s/it]
51%|█████ | 6117/11952 [2:34:52<9:21:27, 5.77s/it]
{'loss': 0.4626, 'learning_rate': 1.010432944269052e-05, 'epoch': 0.51}
+
51%|█████ | 6117/11952 [2:34:52<9:21:27, 5.77s/it]
51%|█████ | 6118/11952 [2:34:58<9:28:23, 5.85s/it]
{'loss': 0.4982, 'learning_rate': 1.0101619681562183e-05, 'epoch': 0.51}
+
51%|█████ | 6118/11952 [2:34:58<9:28:23, 5.85s/it]
51%|█████ | 6119/11952 [2:35:04<9:35:57, 5.92s/it]
{'loss': 0.4729, 'learning_rate': 1.0098909912971322e-05, 'epoch': 0.51}
+
51%|█████ | 6119/11952 [2:35:04<9:35:57, 5.92s/it]
51%|█████ | 6120/11952 [2:35:09<9:31:52, 5.88s/it]
{'loss': 0.4953, 'learning_rate': 1.0096200137116924e-05, 'epoch': 0.51}
+
51%|█████ | 6120/11952 [2:35:09<9:31:52, 5.88s/it]
51%|█████ | 6121/11952 [2:35:15<9:31:06, 5.88s/it]
{'loss': 0.4823, 'learning_rate': 1.0093490354197994e-05, 'epoch': 0.51}
+
51%|█████ | 6121/11952 [2:35:15<9:31:06, 5.88s/it]
51%|█████ | 6122/11952 [2:35:21<9:27:36, 5.84s/it]
{'loss': 0.4974, 'learning_rate': 1.0090780564413518e-05, 'epoch': 0.51}
+
51%|█████ | 6122/11952 [2:35:21<9:27:36, 5.84s/it]
51%|█████ | 6123/11952 [2:35:27<9:24:46, 5.81s/it]
{'loss': 0.4955, 'learning_rate': 1.0088070767962497e-05, 'epoch': 0.51}
+
51%|█████ | 6123/11952 [2:35:27<9:24:46, 5.81s/it]
51%|█████ | 6124/11952 [2:35:33<9:39:02, 5.96s/it]
{'loss': 0.4789, 'learning_rate': 1.0085360965043923e-05, 'epoch': 0.51}
+
51%|█████ | 6124/11952 [2:35:33<9:39:02, 5.96s/it]
51%|█████ | 6125/11952 [2:35:39<9:37:10, 5.94s/it]
{'loss': 0.4786, 'learning_rate': 1.0082651155856795e-05, 'epoch': 0.51}
+
51%|█████ | 6125/11952 [2:35:39<9:37:10, 5.94s/it]
51%|█████▏ | 6126/11952 [2:35:45<9:40:17, 5.98s/it]
{'loss': 0.4877, 'learning_rate': 1.007994134060011e-05, 'epoch': 0.51}
+
51%|█████▏ | 6126/11952 [2:35:45<9:40:17, 5.98s/it]
51%|█████▏ | 6127/11952 [2:35:51<9:32:24, 5.90s/it]
{'loss': 0.4656, 'learning_rate': 1.0077231519472866e-05, 'epoch': 0.51}
+
51%|█████▏ | 6127/11952 [2:35:51<9:32:24, 5.90s/it]
51%|█████▏ | 6128/11952 [2:35:57<9:38:41, 5.96s/it]
{'loss': 0.4981, 'learning_rate': 1.007452169267406e-05, 'epoch': 0.51}
+
51%|█████▏ | 6128/11952 [2:35:57<9:38:41, 5.96s/it]
51%|█████▏ | 6129/11952 [2:36:03<9:30:42, 5.88s/it]
{'loss': 0.5001, 'learning_rate': 1.0071811860402692e-05, 'epoch': 0.51}
+
51%|█████▏ | 6129/11952 [2:36:03<9:30:42, 5.88s/it]
51%|█████▏ | 6130/11952 [2:36:09<9:41:34, 5.99s/it]
{'loss': 0.4817, 'learning_rate': 1.0069102022857757e-05, 'epoch': 0.51}
+
51%|█████▏ | 6130/11952 [2:36:09<9:41:34, 5.99s/it]
51%|█████▏ | 6131/11952 [2:36:15<9:36:59, 5.95s/it]
{'loss': 0.4879, 'learning_rate': 1.0066392180238258e-05, 'epoch': 0.51}
+
51%|█████▏ | 6131/11952 [2:36:15<9:36:59, 5.95s/it]
51%|█████▏ | 6132/11952 [2:36:20<9:28:43, 5.86s/it]
{'loss': 0.4897, 'learning_rate': 1.0063682332743196e-05, 'epoch': 0.51}
+
51%|█████▏ | 6132/11952 [2:36:20<9:28:43, 5.86s/it]
51%|█████▏ | 6133/11952 [2:36:26<9:33:18, 5.91s/it]
{'loss': 0.4781, 'learning_rate': 1.0060972480571565e-05, 'epoch': 0.51}
+
51%|█████▏ | 6133/11952 [2:36:26<9:33:18, 5.91s/it]
51%|█████▏ | 6134/11952 [2:36:32<9:31:13, 5.89s/it]
{'loss': 0.4542, 'learning_rate': 1.0058262623922368e-05, 'epoch': 0.51}
+
51%|█████▏ | 6134/11952 [2:36:32<9:31:13, 5.89s/it]
51%|█████▏ | 6135/11952 [2:36:38<9:25:25, 5.83s/it]
{'loss': 0.4887, 'learning_rate': 1.005555276299461e-05, 'epoch': 0.51}
+
51%|█████▏ | 6135/11952 [2:36:38<9:25:25, 5.83s/it]
51%|█████▏ | 6136/11952 [2:36:44<9:33:25, 5.92s/it]
{'loss': 0.4949, 'learning_rate': 1.0052842897987288e-05, 'epoch': 0.51}
+
51%|█████▏ | 6136/11952 [2:36:44<9:33:25, 5.92s/it]
51%|█████▏ | 6137/11952 [2:36:50<9:28:26, 5.87s/it]
{'loss': 0.4703, 'learning_rate': 1.0050133029099401e-05, 'epoch': 0.51}
+
51%|█████▏ | 6137/11952 [2:36:50<9:28:26, 5.87s/it]
51%|█████▏ | 6138/11952 [2:36:56<9:25:49, 5.84s/it]
{'loss': 0.4776, 'learning_rate': 1.0047423156529952e-05, 'epoch': 0.51}
+
51%|█████▏ | 6138/11952 [2:36:56<9:25:49, 5.84s/it]
51%|█████▏ | 6139/11952 [2:37:01<9:26:25, 5.85s/it]
{'loss': 0.4973, 'learning_rate': 1.0044713280477946e-05, 'epoch': 0.51}
+
51%|█████▏ | 6139/11952 [2:37:01<9:26:25, 5.85s/it]
51%|█████▏ | 6140/11952 [2:37:07<9:26:40, 5.85s/it]
{'loss': 0.4845, 'learning_rate': 1.0042003401142383e-05, 'epoch': 0.51}
+
51%|█████▏ | 6140/11952 [2:37:07<9:26:40, 5.85s/it]
51%|█████▏ | 6141/11952 [2:37:13<9:31:52, 5.90s/it]
{'loss': 0.4794, 'learning_rate': 1.0039293518722262e-05, 'epoch': 0.51}
+
51%|█████▏ | 6141/11952 [2:37:13<9:31:52, 5.90s/it]
51%|█████▏ | 6142/11952 [2:37:19<9:21:48, 5.80s/it]
{'loss': 0.4974, 'learning_rate': 1.0036583633416593e-05, 'epoch': 0.51}
+
51%|█████▏ | 6142/11952 [2:37:19<9:21:48, 5.80s/it]
51%|█████▏ | 6143/11952 [2:37:25<9:26:55, 5.86s/it]
{'loss': 0.4832, 'learning_rate': 1.0033873745424369e-05, 'epoch': 0.51}
+
51%|█████▏ | 6143/11952 [2:37:25<9:26:55, 5.86s/it]
51%|█████▏ | 6144/11952 [2:37:31<9:22:01, 5.81s/it]
{'loss': 0.4864, 'learning_rate': 1.00311638549446e-05, 'epoch': 0.51}
+
51%|█████▏ | 6144/11952 [2:37:31<9:22:01, 5.81s/it]
51%|█████▏ | 6145/11952 [2:37:37<9:28:48, 5.88s/it]
{'loss': 0.4641, 'learning_rate': 1.0028453962176287e-05, 'epoch': 0.51}
+
51%|█████▏ | 6145/11952 [2:37:37<9:28:48, 5.88s/it]
51%|█████▏ | 6146/11952 [2:37:42<9:22:47, 5.82s/it]
{'loss': 0.4801, 'learning_rate': 1.0025744067318435e-05, 'epoch': 0.51}
+
51%|█████▏ | 6146/11952 [2:37:42<9:22:47, 5.82s/it]
51%|█████▏ | 6147/11952 [2:37:48<9:28:05, 5.87s/it]
{'loss': 0.4759, 'learning_rate': 1.0023034170570044e-05, 'epoch': 0.51}
+
51%|█████▏ | 6147/11952 [2:37:48<9:28:05, 5.87s/it]
51%|█████▏ | 6148/11952 [2:37:54<9:28:23, 5.88s/it]
{'loss': 0.4816, 'learning_rate': 1.0020324272130117e-05, 'epoch': 0.51}
+
51%|█████▏ | 6148/11952 [2:37:54<9:28:23, 5.88s/it]
51%|█████▏ | 6149/11952 [2:38:00<9:24:50, 5.84s/it]
{'loss': 0.4867, 'learning_rate': 1.0017614372197667e-05, 'epoch': 0.51}
+
51%|█████▏ | 6149/11952 [2:38:00<9:24:50, 5.84s/it]7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+16 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
51%|█████▏ | 6150/11952 [2:38:05<9:17:28, 5.77s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4779, 'learning_rate': 1.0014904470971686e-05, 'epoch': 0.51}
+
51%|█████▏ | 6150/11952 [2:38:05<9:17:28, 5.77s/it]
51%|█████▏ | 6151/11952 [2:38:12<9:24:32, 5.84s/it]
{'loss': 0.4897, 'learning_rate': 1.0012194568651184e-05, 'epoch': 0.51}
+
51%|█████▏ | 6151/11952 [2:38:12<9:24:32, 5.84s/it]
51%|█████▏ | 6152/11952 [2:38:17<9:26:24, 5.86s/it]
{'loss': 0.4805, 'learning_rate': 1.0009484665435163e-05, 'epoch': 0.51}
+
51%|█████▏ | 6152/11952 [2:38:17<9:26:24, 5.86s/it]
51%|█████▏ | 6153/11952 [2:38:23<9:21:25, 5.81s/it]
{'loss': 0.4745, 'learning_rate': 1.0006774761522626e-05, 'epoch': 0.51}
+
51%|█████▏ | 6153/11952 [2:38:23<9:21:25, 5.81s/it]
51%|█████▏ | 6154/11952 [2:38:29<9:21:52, 5.81s/it]
{'loss': 0.4776, 'learning_rate': 1.000406485711258e-05, 'epoch': 0.51}
+
51%|█████▏ | 6154/11952 [2:38:29<9:21:52, 5.81s/it]
51%|█████▏ | 6155/11952 [2:38:35<9:22:36, 5.82s/it]
{'loss': 0.4708, 'learning_rate': 1.0001354952404027e-05, 'epoch': 0.51}
+
51%|█████▏ | 6155/11952 [2:38:35<9:22:36, 5.82s/it]
52%|█████▏ | 6156/11952 [2:38:40<9:17:56, 5.78s/it]
{'loss': 0.4719, 'learning_rate': 9.998645047595975e-06, 'epoch': 0.52}
+
52%|█████▏ | 6156/11952 [2:38:40<9:17:56, 5.78s/it]
52%|█████▏ | 6157/11952 [2:38:46<9:20:41, 5.81s/it]
{'loss': 0.4778, 'learning_rate': 9.995935142887424e-06, 'epoch': 0.52}
+
52%|█████▏ | 6157/11952 [2:38:46<9:20:41, 5.81s/it]
52%|█████▏ | 6158/11952 [2:38:52<9:27:23, 5.88s/it]
{'loss': 0.479, 'learning_rate': 9.993225238477377e-06, 'epoch': 0.52}
+
52%|█████▏ | 6158/11952 [2:38:52<9:27:23, 5.88s/it]
52%|█████▏ | 6159/11952 [2:38:58<9:31:00, 5.91s/it]
{'loss': 0.4616, 'learning_rate': 9.99051533456484e-06, 'epoch': 0.52}
+
52%|█████▏ | 6159/11952 [2:38:58<9:31:00, 5.91s/it]
52%|█████▏ | 6160/11952 [2:39:04<9:30:38, 5.91s/it]
{'loss': 0.4924, 'learning_rate': 9.987805431348818e-06, 'epoch': 0.52}
+
52%|█████▏ | 6160/11952 [2:39:04<9:30:38, 5.91s/it]
52%|█████▏ | 6161/11952 [2:39:10<9:24:26, 5.85s/it]
{'loss': 0.4886, 'learning_rate': 9.985095529028317e-06, 'epoch': 0.52}
+
52%|█████▏ | 6161/11952 [2:39:10<9:24:26, 5.85s/it]
52%|█████▏ | 6162/11952 [2:39:16<9:22:30, 5.83s/it]
{'loss': 0.473, 'learning_rate': 9.982385627802338e-06, 'epoch': 0.52}
+
52%|█████▏ | 6162/11952 [2:39:16<9:22:30, 5.83s/it]
52%|█████▏ | 6163/11952 [2:39:21<9:15:22, 5.76s/it]
{'loss': 0.5046, 'learning_rate': 9.979675727869884e-06, 'epoch': 0.52}
+
52%|█████▏ | 6163/11952 [2:39:21<9:15:22, 5.76s/it]
52%|█████▏ | 6164/11952 [2:39:27<9:10:10, 5.70s/it]
{'loss': 0.4845, 'learning_rate': 9.976965829429958e-06, 'epoch': 0.52}
+
52%|█████▏ | 6164/11952 [2:39:27<9:10:10, 5.70s/it]
52%|█████▏ | 6165/11952 [2:39:33<9:18:23, 5.79s/it]
{'loss': 0.4805, 'learning_rate': 9.97425593268157e-06, 'epoch': 0.52}
+
52%|█████▏ | 6165/11952 [2:39:33<9:18:23, 5.79s/it]
52%|█████▏ | 6166/11952 [2:39:39<9:20:14, 5.81s/it]
{'loss': 0.4887, 'learning_rate': 9.971546037823713e-06, 'epoch': 0.52}
+
52%|█████▏ | 6166/11952 [2:39:39<9:20:14, 5.81s/it]
52%|█████▏ | 6167/11952 [2:39:44<9:16:27, 5.77s/it]
{'loss': 0.4882, 'learning_rate': 9.968836145055402e-06, 'epoch': 0.52}
+
52%|█████▏ | 6167/11952 [2:39:44<9:16:27, 5.77s/it]
52%|█████▏ | 6168/11952 [2:39:50<9:19:01, 5.80s/it]
{'loss': 0.4744, 'learning_rate': 9.966126254575634e-06, 'epoch': 0.52}
+
52%|█████▏ | 6168/11952 [2:39:50<9:19:01, 5.80s/it]
52%|█████▏ | 6169/11952 [2:39:56<9:14:06, 5.75s/it]
{'loss': 0.4752, 'learning_rate': 9.963416366583412e-06, 'epoch': 0.52}
+
52%|█████▏ | 6169/11952 [2:39:56<9:14:06, 5.75s/it]
52%|█████▏ | 6170/11952 [2:40:02<9:16:44, 5.78s/it]
{'loss': 0.4858, 'learning_rate': 9.960706481277742e-06, 'epoch': 0.52}
+
52%|█████▏ | 6170/11952 [2:40:02<9:16:44, 5.78s/it]
52%|█████▏ | 6171/11952 [2:40:08<9:21:14, 5.82s/it]
{'loss': 0.4589, 'learning_rate': 9.957996598857622e-06, 'epoch': 0.52}
+
52%|█████▏ | 6171/11952 [2:40:08<9:21:14, 5.82s/it]
52%|█████▏ | 6172/11952 [2:40:14<9:23:16, 5.85s/it]
{'loss': 0.4713, 'learning_rate': 9.955286719522059e-06, 'epoch': 0.52}
+
52%|█████▏ | 6172/11952 [2:40:14<9:23:16, 5.85s/it]
52%|█████▏ | 6173/11952 [2:40:20<9:29:14, 5.91s/it]
{'loss': 0.5407, 'learning_rate': 9.952576843470048e-06, 'epoch': 0.52}
+
52%|█████▏ | 6173/11952 [2:40:20<9:29:14, 5.91s/it]
52%|█████▏ | 6174/11952 [2:40:26<9:32:27, 5.94s/it]
{'loss': 0.4929, 'learning_rate': 9.949866970900602e-06, 'epoch': 0.52}
+
52%|█████▏ | 6174/11952 [2:40:26<9:32:27, 5.94s/it]
52%|█████▏ | 6175/11952 [2:40:32<9:38:52, 6.01s/it]
{'loss': 0.4734, 'learning_rate': 9.947157102012716e-06, 'epoch': 0.52}
+
52%|█████▏ | 6175/11952 [2:40:32<9:38:52, 6.01s/it]
52%|█████▏ | 6176/11952 [2:40:38<9:29:54, 5.92s/it]
{'loss': 0.4758, 'learning_rate': 9.944447237005392e-06, 'epoch': 0.52}
+
52%|█████▏ | 6176/11952 [2:40:38<9:29:54, 5.92s/it]
52%|█████▏ | 6177/11952 [2:40:43<9:26:47, 5.89s/it]
{'loss': 0.4628, 'learning_rate': 9.941737376077634e-06, 'epoch': 0.52}
+
52%|█████▏ | 6177/11952 [2:40:43<9:26:47, 5.89s/it]
52%|█████▏ | 6178/11952 [2:40:49<9:21:37, 5.84s/it]
{'loss': 0.4739, 'learning_rate': 9.93902751942844e-06, 'epoch': 0.52}
+
52%|█████▏ | 6178/11952 [2:40:49<9:21:37, 5.84s/it]
52%|█████▏ | 6179/11952 [2:40:55<9:20:03, 5.82s/it]
{'loss': 0.4739, 'learning_rate': 9.93631766725681e-06, 'epoch': 0.52}
+
52%|█████▏ | 6179/11952 [2:40:55<9:20:03, 5.82s/it]
52%|█████▏ | 6180/11952 [2:41:01<9:27:15, 5.90s/it]
{'loss': 0.488, 'learning_rate': 9.93360781976174e-06, 'epoch': 0.52}
+
52%|█████▏ | 6180/11952 [2:41:01<9:27:15, 5.90s/it]
52%|█████▏ | 6181/11952 [2:41:08<9:46:38, 6.10s/it]
{'loss': 0.484, 'learning_rate': 9.930897977142245e-06, 'epoch': 0.52}
+
52%|█████▏ | 6181/11952 [2:41:08<9:46:38, 6.10s/it]
52%|█████▏ | 6182/11952 [2:41:13<9:41:34, 6.05s/it]
{'loss': 0.4858, 'learning_rate': 9.928188139597313e-06, 'epoch': 0.52}
+
52%|█████▏ | 6182/11952 [2:41:13<9:41:34, 6.05s/it]
52%|█████▏ | 6183/11952 [2:41:19<9:34:17, 5.97s/it]
{'loss': 0.4791, 'learning_rate': 9.925478307325944e-06, 'epoch': 0.52}
+
52%|█████▏ | 6183/11952 [2:41:19<9:34:17, 5.97s/it]
52%|█████▏ | 6184/11952 [2:41:25<9:35:49, 5.99s/it]
{'loss': 0.4836, 'learning_rate': 9.922768480527138e-06, 'epoch': 0.52}
+
52%|█████▏ | 6184/11952 [2:41:25<9:35:49, 5.99s/it]
52%|█████▏ | 6185/11952 [2:41:31<9:26:49, 5.90s/it]
{'loss': 0.471, 'learning_rate': 9.920058659399895e-06, 'epoch': 0.52}
+
52%|█████▏ | 6185/11952 [2:41:31<9:26:49, 5.90s/it]
52%|█████▏ | 6186/11952 [2:41:37<9:21:08, 5.84s/it]
{'loss': 0.4773, 'learning_rate': 9.91734884414321e-06, 'epoch': 0.52}
+
52%|█████▏ | 6186/11952 [2:41:37<9:21:08, 5.84s/it]
52%|█████▏ | 6187/11952 [2:41:42<9:17:28, 5.80s/it]
{'loss': 0.4778, 'learning_rate': 9.914639034956079e-06, 'epoch': 0.52}
+
52%|█████▏ | 6187/11952 [2:41:42<9:17:28, 5.80s/it]
52%|█████▏ | 6188/11952 [2:41:48<9:14:48, 5.78s/it]
{'loss': 0.4983, 'learning_rate': 9.911929232037507e-06, 'epoch': 0.52}
+
52%|█████▏ | 6188/11952 [2:41:48<9:14:48, 5.78s/it]
52%|█████▏ | 6189/11952 [2:41:54<9:12:19, 5.75s/it]
{'loss': 0.4768, 'learning_rate': 9.909219435586485e-06, 'epoch': 0.52}
+
52%|█████▏ | 6189/11952 [2:41:54<9:12:19, 5.75s/it]
52%|█████▏ | 6190/11952 [2:42:00<9:11:36, 5.74s/it]
{'loss': 0.4848, 'learning_rate': 9.906509645802009e-06, 'epoch': 0.52}
+
52%|█████▏ | 6190/11952 [2:42:00<9:11:36, 5.74s/it]
52%|█████▏ | 6191/11952 [2:42:05<9:07:14, 5.70s/it]
{'loss': 0.4802, 'learning_rate': 9.903799862883077e-06, 'epoch': 0.52}
+
52%|█████▏ | 6191/11952 [2:42:05<9:07:14, 5.70s/it]
52%|█████▏ | 6192/11952 [2:42:11<9:15:43, 5.79s/it]
{'loss': 0.4775, 'learning_rate': 9.901090087028685e-06, 'epoch': 0.52}
+
52%|█████▏ | 6192/11952 [2:42:11<9:15:43, 5.79s/it]
52%|█████▏ | 6193/11952 [2:42:17<9:18:16, 5.82s/it]
{'loss': 0.4846, 'learning_rate': 9.898380318437822e-06, 'epoch': 0.52}
+
52%|█████▏ | 6193/11952 [2:42:17<9:18:16, 5.82s/it]
52%|█████▏ | 6194/11952 [2:42:23<9:20:21, 5.84s/it]
{'loss': 0.4832, 'learning_rate': 9.895670557309484e-06, 'epoch': 0.52}
+
52%|█████▏ | 6194/11952 [2:42:23<9:20:21, 5.84s/it]
52%|█████▏ | 6195/11952 [2:42:29<9:17:11, 5.81s/it]
{'loss': 0.4866, 'learning_rate': 9.892960803842668e-06, 'epoch': 0.52}
+
52%|█████▏ | 6195/11952 [2:42:29<9:17:11, 5.81s/it]
52%|█████▏ | 6196/11952 [2:42:34<9:10:27, 5.74s/it]
{'loss': 0.4776, 'learning_rate': 9.890251058236368e-06, 'epoch': 0.52}
+
52%|█████▏ | 6196/11952 [2:42:34<9:10:27, 5.74s/it]
52%|█████▏ | 6197/11952 [2:42:40<9:25:49, 5.90s/it]
{'loss': 0.4772, 'learning_rate': 9.887541320689573e-06, 'epoch': 0.52}
+
52%|█████▏ | 6197/11952 [2:42:40<9:25:49, 5.90s/it]
52%|█████▏ | 6198/11952 [2:42:46<9:24:02, 5.88s/it]
{'loss': 0.5, 'learning_rate': 9.884831591401276e-06, 'epoch': 0.52}
+
52%|█████▏ | 6198/11952 [2:42:46<9:24:02, 5.88s/it]
52%|█████▏ | 6199/11952 [2:42:52<9:24:29, 5.89s/it]
{'loss': 0.4832, 'learning_rate': 9.882121870570465e-06, 'epoch': 0.52}
+
52%|█████▏ | 6199/11952 [2:42:52<9:24:29, 5.89s/it]3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+ 5 AutoResumeHook: Checking whether to suspend...
+1AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+
52%|█████▏ | 6200/11952 [2:42:58<9:22:23, 5.87s/it]
{'loss': 0.4802, 'learning_rate': 9.879412158396134e-06, 'epoch': 0.52}
+
52%|█████▏ | 6200/11952 [2:42:58<9:22:23, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
52%|█████▏ | 6201/11952 [2:43:23<18:28:25, 11.56s/it]
{'loss': 0.4718, 'learning_rate': 9.876702455077272e-06, 'epoch': 0.52}
+
52%|█████▏ | 6201/11952 [2:43:23<18:28:25, 11.56s/it]
52%|█████▏ | 6202/11952 [2:43:29<15:55:16, 9.97s/it]
{'loss': 0.4742, 'learning_rate': 9.873992760812871e-06, 'epoch': 0.52}
+
52%|█████▏ | 6202/11952 [2:43:29<15:55:16, 9.97s/it]
52%|█████▏ | 6203/11952 [2:43:35<13:57:54, 8.74s/it]
{'loss': 0.4717, 'learning_rate': 9.87128307580192e-06, 'epoch': 0.52}
+
52%|█████▏ | 6203/11952 [2:43:35<13:57:54, 8.74s/it]
52%|█████▏ | 6204/11952 [2:43:41<12:31:55, 7.85s/it]
{'loss': 0.4813, 'learning_rate': 9.868573400243402e-06, 'epoch': 0.52}
+
52%|█████▏ | 6204/11952 [2:43:41<12:31:55, 7.85s/it]
52%|█████▏ | 6205/11952 [2:43:47<11:38:34, 7.29s/it]
{'loss': 0.4895, 'learning_rate': 9.865863734336305e-06, 'epoch': 0.52}
+
52%|█████▏ | 6205/11952 [2:43:47<11:38:34, 7.29s/it]
52%|█████▏ | 6206/11952 [2:43:53<10:58:47, 6.88s/it]
{'loss': 0.4889, 'learning_rate': 9.86315407827962e-06, 'epoch': 0.52}
+
52%|█████▏ | 6206/11952 [2:43:53<10:58:47, 6.88s/it]
52%|█████▏ | 6207/11952 [2:43:58<10:22:24, 6.50s/it]
{'loss': 0.4873, 'learning_rate': 9.860444432272328e-06, 'epoch': 0.52}
+
52%|█████▏ | 6207/11952 [2:43:58<10:22:24, 6.50s/it]
52%|█████▏ | 6208/11952 [2:44:04<10:02:11, 6.29s/it]
{'loss': 0.4915, 'learning_rate': 9.857734796513417e-06, 'epoch': 0.52}
+
52%|█████▏ | 6208/11952 [2:44:04<10:02:11, 6.29s/it]
52%|█████▏ | 6209/11952 [2:44:10<9:50:20, 6.17s/it]
{'loss': 0.4696, 'learning_rate': 9.855025171201874e-06, 'epoch': 0.52}
+
52%|█████▏ | 6209/11952 [2:44:10<9:50:20, 6.17s/it]
52%|█████▏ | 6210/11952 [2:44:16<9:39:57, 6.06s/it]
{'loss': 0.4605, 'learning_rate': 9.852315556536674e-06, 'epoch': 0.52}
+
52%|█████▏ | 6210/11952 [2:44:16<9:39:57, 6.06s/it]
52%|█████▏ | 6211/11952 [2:44:21<9:25:54, 5.91s/it]
{'loss': 0.4808, 'learning_rate': 9.84960595271681e-06, 'epoch': 0.52}
+
52%|█████▏ | 6211/11952 [2:44:21<9:25:54, 5.91s/it]
52%|█████▏ | 6212/11952 [2:44:27<9:22:37, 5.88s/it]
{'loss': 0.4867, 'learning_rate': 9.846896359941258e-06, 'epoch': 0.52}
+
52%|█████▏ | 6212/11952 [2:44:27<9:22:37, 5.88s/it]
52%|█████▏ | 6213/11952 [2:44:33<9:26:03, 5.92s/it]
{'loss': 0.4805, 'learning_rate': 9.844186778409002e-06, 'epoch': 0.52}
+
52%|█████▏ | 6213/11952 [2:44:33<9:26:03, 5.92s/it]
52%|█████▏ | 6214/11952 [2:44:39<9:13:11, 5.78s/it]
{'loss': 0.4754, 'learning_rate': 9.841477208319015e-06, 'epoch': 0.52}
+
52%|█████▏ | 6214/11952 [2:44:39<9:13:11, 5.78s/it]
52%|█████▏ | 6215/11952 [2:44:44<9:05:49, 5.71s/it]
{'loss': 0.4691, 'learning_rate': 9.838767649870287e-06, 'epoch': 0.52}
+
52%|█████▏ | 6215/11952 [2:44:44<9:05:49, 5.71s/it]
52%|█████▏ | 6216/11952 [2:44:50<9:13:46, 5.79s/it]
{'loss': 0.4701, 'learning_rate': 9.83605810326179e-06, 'epoch': 0.52}
+
52%|█████▏ | 6216/11952 [2:44:50<9:13:46, 5.79s/it]
52%|█████▏ | 6217/11952 [2:44:56<9:21:48, 5.88s/it]
{'loss': 0.4799, 'learning_rate': 9.833348568692507e-06, 'epoch': 0.52}
+
52%|█████▏ | 6217/11952 [2:44:56<9:21:48, 5.88s/it]
52%|█████▏ | 6218/11952 [2:45:02<9:21:30, 5.88s/it]
{'loss': 0.4803, 'learning_rate': 9.830639046361412e-06, 'epoch': 0.52}
+
52%|█████▏ | 6218/11952 [2:45:02<9:21:30, 5.88s/it]
52%|█████▏ | 6219/11952 [2:45:08<9:20:24, 5.87s/it]
{'loss': 0.4602, 'learning_rate': 9.82792953646748e-06, 'epoch': 0.52}
+
52%|█████▏ | 6219/11952 [2:45:08<9:20:24, 5.87s/it]
52%|█████▏ | 6220/11952 [2:45:14<9:19:08, 5.85s/it]
{'loss': 0.4757, 'learning_rate': 9.825220039209687e-06, 'epoch': 0.52}
+
52%|█████▏ | 6220/11952 [2:45:14<9:19:08, 5.85s/it]
52%|█████▏ | 6221/11952 [2:45:19<9:14:29, 5.81s/it]
{'loss': 0.4817, 'learning_rate': 9.822510554787004e-06, 'epoch': 0.52}
+
52%|█████▏ | 6221/11952 [2:45:19<9:14:29, 5.81s/it]
52%|█████▏ | 6222/11952 [2:45:26<9:20:59, 5.87s/it]
{'loss': 0.4772, 'learning_rate': 9.819801083398411e-06, 'epoch': 0.52}
+
52%|█████▏ | 6222/11952 [2:45:26<9:20:59, 5.87s/it]
52%|█████▏ | 6223/11952 [2:45:31<9:20:11, 5.87s/it]
{'loss': 0.4876, 'learning_rate': 9.817091625242879e-06, 'epoch': 0.52}
+
52%|█████▏ | 6223/11952 [2:45:31<9:20:11, 5.87s/it]
52%|█████▏ | 6224/11952 [2:45:37<9:19:17, 5.86s/it]
{'loss': 0.4803, 'learning_rate': 9.814382180519375e-06, 'epoch': 0.52}
+
52%|█████▏ | 6224/11952 [2:45:37<9:19:17, 5.86s/it]
52%|█████▏ | 6225/11952 [2:45:43<9:17:41, 5.84s/it]
{'loss': 0.4761, 'learning_rate': 9.81167274942687e-06, 'epoch': 0.52}
+
52%|█████▏ | 6225/11952 [2:45:43<9:17:41, 5.84s/it]
52%|█████▏ | 6226/11952 [2:45:48<9:07:20, 5.74s/it]
{'loss': 0.4727, 'learning_rate': 9.808963332164337e-06, 'epoch': 0.52}
+
52%|█████▏ | 6226/11952 [2:45:48<9:07:20, 5.74s/it]
52%|█████▏ | 6227/11952 [2:45:54<9:13:06, 5.80s/it]
{'loss': 0.468, 'learning_rate': 9.806253928930743e-06, 'epoch': 0.52}
+
52%|█████▏ | 6227/11952 [2:45:54<9:13:06, 5.80s/it]
52%|█████▏ | 6228/11952 [2:46:00<9:12:40, 5.79s/it]
{'loss': 0.4583, 'learning_rate': 9.80354453992505e-06, 'epoch': 0.52}
+
52%|█████▏ | 6228/11952 [2:46:00<9:12:40, 5.79s/it]
52%|█████▏ | 6229/11952 [2:46:06<9:20:06, 5.87s/it]
{'loss': 0.4972, 'learning_rate': 9.800835165346234e-06, 'epoch': 0.52}
+
52%|█████▏ | 6229/11952 [2:46:06<9:20:06, 5.87s/it]
52%|█████▏ | 6230/11952 [2:46:12<9:11:49, 5.79s/it]
{'loss': 0.4874, 'learning_rate': 9.798125805393255e-06, 'epoch': 0.52}
+
52%|█████▏ | 6230/11952 [2:46:12<9:11:49, 5.79s/it]
52%|█████▏ | 6231/11952 [2:46:18<9:15:49, 5.83s/it]
{'loss': 0.4627, 'learning_rate': 9.795416460265074e-06, 'epoch': 0.52}
+
52%|█████▏ | 6231/11952 [2:46:18<9:15:49, 5.83s/it]
52%|█████▏ | 6232/11952 [2:46:24<9:20:07, 5.88s/it]
{'loss': 0.5072, 'learning_rate': 9.79270713016066e-06, 'epoch': 0.52}
+
52%|█████▏ | 6232/11952 [2:46:24<9:20:07, 5.88s/it]
52%|█████▏ | 6233/11952 [2:46:30<9:19:45, 5.87s/it]
{'loss': 0.4845, 'learning_rate': 9.789997815278973e-06, 'epoch': 0.52}
+
52%|█████▏ | 6233/11952 [2:46:30<9:19:45, 5.87s/it]
52%|█████▏ | 6234/11952 [2:46:36<9:26:49, 5.95s/it]
{'loss': 0.4799, 'learning_rate': 9.787288515818968e-06, 'epoch': 0.52}
+
52%|█████▏ | 6234/11952 [2:46:36<9:26:49, 5.95s/it]
52%|█████▏ | 6235/11952 [2:46:41<9:18:33, 5.86s/it]
{'loss': 0.47, 'learning_rate': 9.784579231979612e-06, 'epoch': 0.52}
+
52%|█████▏ | 6235/11952 [2:46:41<9:18:33, 5.86s/it]
52%|█████▏ | 6236/11952 [2:46:47<9:12:32, 5.80s/it]
{'loss': 0.4865, 'learning_rate': 9.781869963959861e-06, 'epoch': 0.52}
+
52%|█████▏ | 6236/11952 [2:46:47<9:12:32, 5.80s/it]
52%|█████▏ | 6237/11952 [2:46:53<9:18:12, 5.86s/it]
{'loss': 0.4727, 'learning_rate': 9.779160711958673e-06, 'epoch': 0.52}
+
52%|█████▏ | 6237/11952 [2:46:53<9:18:12, 5.86s/it]
52%|█████▏ | 6238/11952 [2:46:59<9:13:42, 5.81s/it]
{'loss': 0.4904, 'learning_rate': 9.776451476175006e-06, 'epoch': 0.52}
+
52%|█████▏ | 6238/11952 [2:46:59<9:13:42, 5.81s/it]
52%|█████▏ | 6239/11952 [2:47:04<9:07:54, 5.75s/it]
{'loss': 0.4865, 'learning_rate': 9.773742256807812e-06, 'epoch': 0.52}
+
52%|█████▏ | 6239/11952 [2:47:04<9:07:54, 5.75s/it]
52%|█████▏ | 6240/11952 [2:47:10<9:11:00, 5.79s/it]
{'loss': 0.4669, 'learning_rate': 9.771033054056044e-06, 'epoch': 0.52}
+
52%|█████▏ | 6240/11952 [2:47:10<9:11:00, 5.79s/it]
52%|█████▏ | 6241/11952 [2:47:16<9:11:35, 5.80s/it]
{'loss': 0.4877, 'learning_rate': 9.768323868118656e-06, 'epoch': 0.52}
+
52%|█████▏ | 6241/11952 [2:47:16<9:11:35, 5.80s/it]
52%|█████▏ | 6242/11952 [2:47:22<9:06:00, 5.74s/it]
{'loss': 0.469, 'learning_rate': 9.765614699194598e-06, 'epoch': 0.52}
+
52%|█████▏ | 6242/11952 [2:47:22<9:06:00, 5.74s/it]
52%|█████▏ | 6243/11952 [2:47:28<9:17:23, 5.86s/it]
{'loss': 0.473, 'learning_rate': 9.762905547482825e-06, 'epoch': 0.52}
+
52%|█████▏ | 6243/11952 [2:47:28<9:17:23, 5.86s/it]
52%|█████▏ | 6244/11952 [2:47:34<9:12:23, 5.81s/it]
{'loss': 0.4738, 'learning_rate': 9.760196413182283e-06, 'epoch': 0.52}
+
52%|█████▏ | 6244/11952 [2:47:34<9:12:23, 5.81s/it]
52%|█████▏ | 6245/11952 [2:47:40<9:18:18, 5.87s/it]
{'loss': 0.4813, 'learning_rate': 9.757487296491918e-06, 'epoch': 0.52}
+
52%|█████▏ | 6245/11952 [2:47:40<9:18:18, 5.87s/it]
52%|█████▏ | 6246/11952 [2:47:45<9:14:34, 5.83s/it]
{'loss': 0.4992, 'learning_rate': 9.754778197610674e-06, 'epoch': 0.52}
+
52%|█████▏ | 6246/11952 [2:47:45<9:14:34, 5.83s/it]
52%|█████▏ | 6247/11952 [2:47:51<9:14:09, 5.83s/it]
{'loss': 0.4679, 'learning_rate': 9.752069116737504e-06, 'epoch': 0.52}
+
52%|█████▏ | 6247/11952 [2:47:51<9:14:09, 5.83s/it]
52%|█████▏ | 6248/11952 [2:47:57<9:11:22, 5.80s/it]
{'loss': 0.456, 'learning_rate': 9.74936005407134e-06, 'epoch': 0.52}
+
52%|█████▏ | 6248/11952 [2:47:57<9:11:22, 5.80s/it]
52%|█████▏ | 6249/11952 [2:48:03<9:18:31, 5.88s/it]
{'loss': 0.4749, 'learning_rate': 9.746651009811137e-06, 'epoch': 0.52}
+
52%|█████▏ | 6249/11952 [2:48:03<9:18:31, 5.88s/it]4 AutoResumeHook: Checking whether to suspend...
+072 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
52%|█████▏ | 6250/11952 [2:48:09<9:22:55, 5.92s/it]3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4758, 'learning_rate': 9.74394198415583e-06, 'epoch': 0.52}
+
52%|█████▏ | 6250/11952 [2:48:09<9:22:55, 5.92s/it]
52%|█████▏ | 6251/11952 [2:48:15<9:27:51, 5.98s/it]
{'loss': 0.4719, 'learning_rate': 9.741232977304356e-06, 'epoch': 0.52}
+
52%|█████▏ | 6251/11952 [2:48:15<9:27:51, 5.98s/it]
52%|█████▏ | 6252/11952 [2:48:21<9:17:14, 5.87s/it]
{'loss': 0.4639, 'learning_rate': 9.738523989455659e-06, 'epoch': 0.52}
+
52%|█████▏ | 6252/11952 [2:48:21<9:17:14, 5.87s/it]
52%|█████▏ | 6253/11952 [2:48:26<9:15:41, 5.85s/it]
{'loss': 0.4738, 'learning_rate': 9.735815020808672e-06, 'epoch': 0.52}
+
52%|█████▏ | 6253/11952 [2:48:26<9:15:41, 5.85s/it]
52%|█████▏ | 6254/11952 [2:48:32<9:21:00, 5.91s/it]
{'loss': 0.4639, 'learning_rate': 9.733106071562332e-06, 'epoch': 0.52}
+
52%|█████▏ | 6254/11952 [2:48:32<9:21:00, 5.91s/it]
52%|█████▏ | 6255/11952 [2:48:38<9:15:41, 5.85s/it]
{'loss': 0.4905, 'learning_rate': 9.730397141915567e-06, 'epoch': 0.52}
+
52%|█████▏ | 6255/11952 [2:48:38<9:15:41, 5.85s/it]
52%|█████▏ | 6256/11952 [2:48:44<9:13:56, 5.83s/it]
{'loss': 0.4697, 'learning_rate': 9.727688232067318e-06, 'epoch': 0.52}
+
52%|█████▏ | 6256/11952 [2:48:44<9:13:56, 5.83s/it]
52%|█████▏ | 6257/11952 [2:48:50<9:19:24, 5.89s/it]
{'loss': 0.4867, 'learning_rate': 9.72497934221651e-06, 'epoch': 0.52}
+
52%|█████▏ | 6257/11952 [2:48:50<9:19:24, 5.89s/it]
52%|█████▏ | 6258/11952 [2:48:56<9:17:43, 5.88s/it]
{'loss': 0.4721, 'learning_rate': 9.722270472562078e-06, 'epoch': 0.52}
+
52%|█████▏ | 6258/11952 [2:48:56<9:17:43, 5.88s/it]
52%|█████▏ | 6259/11952 [2:49:02<9:10:53, 5.81s/it]
{'loss': 0.4716, 'learning_rate': 9.71956162330295e-06, 'epoch': 0.52}
+
52%|█████▏ | 6259/11952 [2:49:02<9:10:53, 5.81s/it]
52%|█████▏ | 6260/11952 [2:49:07<9:09:06, 5.79s/it]
{'loss': 0.4712, 'learning_rate': 9.716852794638046e-06, 'epoch': 0.52}
+
52%|█████▏ | 6260/11952 [2:49:07<9:09:06, 5.79s/it]
52%|█████▏ | 6261/11952 [2:49:13<9:05:41, 5.75s/it]
{'loss': 0.4798, 'learning_rate': 9.714143986766294e-06, 'epoch': 0.52}
+
52%|█████▏ | 6261/11952 [2:49:13<9:05:41, 5.75s/it]
52%|█████▏ | 6262/11952 [2:49:19<9:12:07, 5.82s/it]
{'loss': 0.4679, 'learning_rate': 9.711435199886618e-06, 'epoch': 0.52}
+
52%|█████▏ | 6262/11952 [2:49:19<9:12:07, 5.82s/it]
52%|█████▏ | 6263/11952 [2:49:25<9:19:07, 5.90s/it]
{'loss': 0.4605, 'learning_rate': 9.708726434197944e-06, 'epoch': 0.52}
+
52%|█████▏ | 6263/11952 [2:49:25<9:19:07, 5.90s/it]
52%|█████▏ | 6264/11952 [2:49:31<9:17:48, 5.88s/it]
{'loss': 0.4812, 'learning_rate': 9.706017689899189e-06, 'epoch': 0.52}
+
52%|█████▏ | 6264/11952 [2:49:31<9:17:48, 5.88s/it]
52%|█████▏ | 6265/11952 [2:49:37<9:13:43, 5.84s/it]
{'loss': 0.4768, 'learning_rate': 9.703308967189273e-06, 'epoch': 0.52}
+
52%|█████▏ | 6265/11952 [2:49:37<9:13:43, 5.84s/it]
52%|█████▏ | 6266/11952 [2:49:42<9:14:01, 5.85s/it]
{'loss': 0.4735, 'learning_rate': 9.700600266267109e-06, 'epoch': 0.52}
+
52%|█████▏ | 6266/11952 [2:49:42<9:14:01, 5.85s/it]
52%|█████▏ | 6267/11952 [2:49:49<9:23:08, 5.94s/it]
{'loss': 0.4862, 'learning_rate': 9.697891587331618e-06, 'epoch': 0.52}
+
52%|█████▏ | 6267/11952 [2:49:49<9:23:08, 5.94s/it]
52%|█████▏ | 6268/11952 [2:49:55<9:24:40, 5.96s/it]
{'loss': 0.4751, 'learning_rate': 9.695182930581715e-06, 'epoch': 0.52}
+
52%|█████▏ | 6268/11952 [2:49:55<9:24:40, 5.96s/it]
52%|█████▏ | 6269/11952 [2:50:00<9:18:02, 5.89s/it]
{'loss': 0.4512, 'learning_rate': 9.692474296216303e-06, 'epoch': 0.52}
+
52%|█████▏ | 6269/11952 [2:50:00<9:18:02, 5.89s/it]
52%|█████▏ | 6270/11952 [2:50:06<9:15:18, 5.86s/it]
{'loss': 0.4947, 'learning_rate': 9.689765684434305e-06, 'epoch': 0.52}
+
52%|█████▏ | 6270/11952 [2:50:06<9:15:18, 5.86s/it]
52%|█████▏ | 6271/11952 [2:50:12<9:15:21, 5.87s/it]
{'loss': 0.4816, 'learning_rate': 9.687057095434624e-06, 'epoch': 0.52}
+
52%|█████▏ | 6271/11952 [2:50:12<9:15:21, 5.87s/it]
52%|█████▏ | 6272/11952 [2:50:18<9:14:28, 5.86s/it]
{'loss': 0.4744, 'learning_rate': 9.684348529416166e-06, 'epoch': 0.52}
+
52%|█████▏ | 6272/11952 [2:50:18<9:14:28, 5.86s/it]
52%|█████▏ | 6273/11952 [2:50:24<9:17:10, 5.89s/it]
{'loss': 0.4612, 'learning_rate': 9.681639986577841e-06, 'epoch': 0.52}
+
52%|█████▏ | 6273/11952 [2:50:24<9:17:10, 5.89s/it]
52%|█████▏ | 6274/11952 [2:50:30<9:15:05, 5.87s/it]
{'loss': 0.4734, 'learning_rate': 9.678931467118553e-06, 'epoch': 0.52}
+
52%|█████▏ | 6274/11952 [2:50:30<9:15:05, 5.87s/it]
53%|█████▎ | 6275/11952 [2:50:35<9:07:07, 5.78s/it]
{'loss': 0.4665, 'learning_rate': 9.676222971237197e-06, 'epoch': 0.52}
+
53%|█████▎ | 6275/11952 [2:50:35<9:07:07, 5.78s/it]
53%|█████▎ | 6276/11952 [2:50:41<9:12:23, 5.84s/it]
{'loss': 0.4761, 'learning_rate': 9.673514499132683e-06, 'epoch': 0.53}
+
53%|█████▎ | 6276/11952 [2:50:41<9:12:23, 5.84s/it]
53%|█████▎ | 6277/11952 [2:50:47<9:04:47, 5.76s/it]
{'loss': 0.4849, 'learning_rate': 9.670806051003906e-06, 'epoch': 0.53}
+
53%|█████▎ | 6277/11952 [2:50:47<9:04:47, 5.76s/it]
53%|█████▎ | 6278/11952 [2:50:53<9:13:48, 5.86s/it]
{'loss': 0.479, 'learning_rate': 9.668097627049765e-06, 'epoch': 0.53}
+
53%|█████▎ | 6278/11952 [2:50:53<9:13:48, 5.86s/it]
53%|█████▎ | 6279/11952 [2:50:58<9:06:56, 5.78s/it]
{'loss': 0.471, 'learning_rate': 9.665389227469152e-06, 'epoch': 0.53}
+
53%|█████▎ | 6279/11952 [2:50:58<9:06:56, 5.78s/it]
53%|█████▎ | 6280/11952 [2:51:04<9:12:41, 5.85s/it]
{'loss': 0.4824, 'learning_rate': 9.662680852460963e-06, 'epoch': 0.53}
+
53%|█████▎ | 6280/11952 [2:51:04<9:12:41, 5.85s/it]
53%|█████▎ | 6281/11952 [2:51:10<9:09:29, 5.81s/it]
{'loss': 0.4746, 'learning_rate': 9.659972502224089e-06, 'epoch': 0.53}
+
53%|█████▎ | 6281/11952 [2:51:10<9:09:29, 5.81s/it]
53%|█████▎ | 6282/11952 [2:51:16<9:05:30, 5.77s/it]
{'loss': 0.4834, 'learning_rate': 9.657264176957419e-06, 'epoch': 0.53}
+
53%|█████▎ | 6282/11952 [2:51:16<9:05:30, 5.77s/it]
53%|█████▎ | 6283/11952 [2:51:22<9:09:06, 5.81s/it]
{'loss': 0.4928, 'learning_rate': 9.654555876859841e-06, 'epoch': 0.53}
+
53%|█████▎ | 6283/11952 [2:51:22<9:09:06, 5.81s/it]
53%|█████▎ | 6284/11952 [2:51:28<9:27:25, 6.01s/it]
{'loss': 0.4866, 'learning_rate': 9.651847602130247e-06, 'epoch': 0.53}
+
53%|█████▎ | 6284/11952 [2:51:28<9:27:25, 6.01s/it]
53%|█████▎ | 6285/11952 [2:51:34<9:26:47, 6.00s/it]
{'loss': 0.4769, 'learning_rate': 9.649139352967515e-06, 'epoch': 0.53}
+
53%|█████▎ | 6285/11952 [2:51:34<9:26:47, 6.00s/it]
53%|█████▎ | 6286/11952 [2:51:40<9:35:02, 6.09s/it]
{'loss': 0.4794, 'learning_rate': 9.646431129570531e-06, 'epoch': 0.53}
+
53%|█████▎ | 6286/11952 [2:51:40<9:35:02, 6.09s/it]
53%|█████▎ | 6287/11952 [2:51:46<9:28:45, 6.02s/it]
{'loss': 0.4776, 'learning_rate': 9.643722932138172e-06, 'epoch': 0.53}
+
53%|█████▎ | 6287/11952 [2:51:46<9:28:45, 6.02s/it]
53%|█████▎ | 6288/11952 [2:51:52<9:27:09, 6.01s/it]
{'loss': 0.4743, 'learning_rate': 9.64101476086932e-06, 'epoch': 0.53}
+
53%|█████▎ | 6288/11952 [2:51:52<9:27:09, 6.01s/it]
53%|█████▎ | 6289/11952 [2:51:58<9:18:07, 5.91s/it]
{'loss': 0.4793, 'learning_rate': 9.638306615962847e-06, 'epoch': 0.53}
+
53%|█████▎ | 6289/11952 [2:51:58<9:18:07, 5.91s/it]
53%|█████▎ | 6290/11952 [2:52:04<9:20:54, 5.94s/it]
{'loss': 0.4823, 'learning_rate': 9.635598497617636e-06, 'epoch': 0.53}
+
53%|█████▎ | 6290/11952 [2:52:04<9:20:54, 5.94s/it]
53%|█████▎ | 6291/11952 [2:52:10<9:15:44, 5.89s/it]
{'loss': 0.467, 'learning_rate': 9.632890406032556e-06, 'epoch': 0.53}
+
53%|█████▎ | 6291/11952 [2:52:10<9:15:44, 5.89s/it]
53%|█████▎ | 6292/11952 [2:52:16<9:13:03, 5.86s/it]
{'loss': 0.4598, 'learning_rate': 9.630182341406477e-06, 'epoch': 0.53}
+
53%|█████▎ | 6292/11952 [2:52:16<9:13:03, 5.86s/it]
53%|█████▎ | 6293/11952 [2:52:21<9:04:00, 5.77s/it]
{'loss': 0.4697, 'learning_rate': 9.627474303938267e-06, 'epoch': 0.53}
+
53%|█████▎ | 6293/11952 [2:52:21<9:04:00, 5.77s/it]
53%|█████▎ | 6294/11952 [2:52:27<9:10:18, 5.84s/it]
{'loss': 0.4777, 'learning_rate': 9.624766293826798e-06, 'epoch': 0.53}
+
53%|█████▎ | 6294/11952 [2:52:27<9:10:18, 5.84s/it]
53%|█████▎ | 6295/11952 [2:52:33<9:08:02, 5.81s/it]
{'loss': 0.4762, 'learning_rate': 9.62205831127093e-06, 'epoch': 0.53}
+
53%|█████▎ | 6295/11952 [2:52:33<9:08:02, 5.81s/it]
53%|█████▎ | 6296/11952 [2:52:39<9:11:58, 5.86s/it]
{'loss': 0.4949, 'learning_rate': 9.619350356469524e-06, 'epoch': 0.53}
+
53%|█████▎ | 6296/11952 [2:52:39<9:11:58, 5.86s/it]
53%|█████▎ | 6297/11952 [2:52:45<9:19:54, 5.94s/it]
{'loss': 0.4867, 'learning_rate': 9.616642429621449e-06, 'epoch': 0.53}
+
53%|█████▎ | 6297/11952 [2:52:45<9:19:54, 5.94s/it]
53%|█████▎ | 6298/11952 [2:52:51<9:11:48, 5.86s/it]
{'loss': 0.4907, 'learning_rate': 9.613934530925556e-06, 'epoch': 0.53}
+
53%|█████▎ | 6298/11952 [2:52:51<9:11:48, 5.86s/it]
53%|█████▎ | 6299/11952 [2:52:56<9:09:22, 5.83s/it]
{'loss': 0.4929, 'learning_rate': 9.611226660580709e-06, 'epoch': 0.53}
+
53%|█████▎ | 6299/11952 [2:52:56<9:09:22, 5.83s/it]4 AutoResumeHook: Checking whether to suspend...
+072 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
53%|█████▎ | 6300/11952 [2:53:02<9:08:13, 5.82s/it]1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4616, 'learning_rate': 9.60851881878576e-06, 'epoch': 0.53}
+
53%|█████▎ | 6300/11952 [2:53:02<9:08:13, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
53%|█████▎ | 6301/11952 [2:53:31<20:03:55, 12.78s/it]
{'loss': 0.4869, 'learning_rate': 9.605811005739558e-06, 'epoch': 0.53}
+
53%|█████▎ | 6301/11952 [2:53:31<20:03:55, 12.78s/it]
53%|█████▎ | 6302/11952 [2:53:37<16:45:25, 10.68s/it]
{'loss': 0.4846, 'learning_rate': 9.603103221640956e-06, 'epoch': 0.53}
+
53%|█████▎ | 6302/11952 [2:53:37<16:45:25, 10.68s/it]
53%|█████▎ | 6303/11952 [2:53:43<14:28:11, 9.22s/it]
{'loss': 0.4695, 'learning_rate': 9.600395466688801e-06, 'epoch': 0.53}
+
53%|█████▎ | 6303/11952 [2:53:43<14:28:11, 9.22s/it]
53%|█████▎ | 6304/11952 [2:53:49<12:49:56, 8.18s/it]
{'loss': 0.4904, 'learning_rate': 9.597687741081942e-06, 'epoch': 0.53}
+
53%|█████▎ | 6304/11952 [2:53:49<12:49:56, 8.18s/it]
53%|█████▎ | 6305/11952 [2:53:55<11:47:40, 7.52s/it]
{'loss': 0.4837, 'learning_rate': 9.594980045019224e-06, 'epoch': 0.53}
+
53%|█████▎ | 6305/11952 [2:53:55<11:47:40, 7.52s/it]
53%|█████▎ | 6306/11952 [2:54:01<11:12:57, 7.15s/it]
{'loss': 0.4682, 'learning_rate': 9.592272378699486e-06, 'epoch': 0.53}
+
53%|█████▎ | 6306/11952 [2:54:01<11:12:57, 7.15s/it]
53%|█████▎ | 6307/11952 [2:54:07<10:35:32, 6.76s/it]
{'loss': 0.4882, 'learning_rate': 9.589564742321569e-06, 'epoch': 0.53}
+
53%|█████▎ | 6307/11952 [2:54:07<10:35:32, 6.76s/it]
53%|█████▎ | 6308/11952 [2:54:12<10:08:22, 6.47s/it]
{'loss': 0.483, 'learning_rate': 9.586857136084309e-06, 'epoch': 0.53}
+
53%|█████▎ | 6308/11952 [2:54:12<10:08:22, 6.47s/it]
53%|█████▎ | 6309/11952 [2:54:19<10:01:00, 6.39s/it]
{'loss': 0.4886, 'learning_rate': 9.58414956018654e-06, 'epoch': 0.53}
+
53%|█████▎ | 6309/11952 [2:54:19<10:01:00, 6.39s/it]
53%|█████▎ | 6310/11952 [2:54:24<9:43:39, 6.21s/it]
{'loss': 0.491, 'learning_rate': 9.581442014827101e-06, 'epoch': 0.53}
+
53%|█████▎ | 6310/11952 [2:54:24<9:43:39, 6.21s/it]
53%|█████▎ | 6311/11952 [2:54:30<9:25:38, 6.02s/it]
{'loss': 0.4758, 'learning_rate': 9.57873450020482e-06, 'epoch': 0.53}
+
53%|█████▎ | 6311/11952 [2:54:30<9:25:38, 6.02s/it]
53%|█████▎ | 6312/11952 [2:54:36<9:24:36, 6.01s/it]
{'loss': 0.4617, 'learning_rate': 9.576027016518527e-06, 'epoch': 0.53}
+
53%|█████▎ | 6312/11952 [2:54:36<9:24:36, 6.01s/it]
53%|█████▎ | 6313/11952 [2:54:42<9:20:04, 5.96s/it]
{'loss': 0.4783, 'learning_rate': 9.573319563967043e-06, 'epoch': 0.53}
+
53%|█████▎ | 6313/11952 [2:54:42<9:20:04, 5.96s/it]
53%|█████▎ | 6314/11952 [2:54:48<9:23:06, 5.99s/it]
{'loss': 0.4769, 'learning_rate': 9.570612142749196e-06, 'epoch': 0.53}
+
53%|█████▎ | 6314/11952 [2:54:48<9:23:06, 5.99s/it]
53%|█████▎ | 6315/11952 [2:54:54<9:13:13, 5.89s/it]
{'loss': 0.4733, 'learning_rate': 9.56790475306381e-06, 'epoch': 0.53}
+
53%|█████▎ | 6315/11952 [2:54:54<9:13:13, 5.89s/it]
53%|█████▎ | 6316/11952 [2:55:00<9:14:19, 5.90s/it]
{'loss': 0.4816, 'learning_rate': 9.565197395109694e-06, 'epoch': 0.53}
+
53%|█████▎ | 6316/11952 [2:55:00<9:14:19, 5.90s/it]
53%|█████▎ | 6317/11952 [2:55:05<9:12:52, 5.89s/it]
{'loss': 0.4784, 'learning_rate': 9.56249006908568e-06, 'epoch': 0.53}
+
53%|█████▎ | 6317/11952 [2:55:05<9:12:52, 5.89s/it]
53%|█████▎ | 6318/11952 [2:55:11<9:12:11, 5.88s/it]
{'loss': 0.4769, 'learning_rate': 9.559782775190574e-06, 'epoch': 0.53}
+
53%|█████▎ | 6318/11952 [2:55:11<9:12:11, 5.88s/it]
53%|█████▎ | 6319/11952 [2:55:17<9:04:12, 5.80s/it]
{'loss': 0.4679, 'learning_rate': 9.55707551362319e-06, 'epoch': 0.53}
+
53%|█████▎ | 6319/11952 [2:55:17<9:04:12, 5.80s/it]
53%|█████▎ | 6320/11952 [2:55:23<9:07:50, 5.84s/it]
{'loss': 0.4917, 'learning_rate': 9.554368284582339e-06, 'epoch': 0.53}
+
53%|█████▎ | 6320/11952 [2:55:23<9:07:50, 5.84s/it]
53%|█████▎ | 6321/11952 [2:55:29<9:08:01, 5.84s/it]
{'loss': 0.4883, 'learning_rate': 9.551661088266825e-06, 'epoch': 0.53}
+
53%|█████▎ | 6321/11952 [2:55:29<9:08:01, 5.84s/it]
53%|█████▎ | 6322/11952 [2:55:34<9:03:18, 5.79s/it]
{'loss': 0.4608, 'learning_rate': 9.548953924875459e-06, 'epoch': 0.53}
+
53%|█████▎ | 6322/11952 [2:55:34<9:03:18, 5.79s/it]
53%|█████▎ | 6323/11952 [2:55:40<9:00:28, 5.76s/it]
{'loss': 0.4799, 'learning_rate': 9.546246794607037e-06, 'epoch': 0.53}
+
53%|█████▎ | 6323/11952 [2:55:40<9:00:28, 5.76s/it]
53%|█████▎ | 6324/11952 [2:55:46<8:56:35, 5.72s/it]
{'loss': 0.4842, 'learning_rate': 9.543539697660363e-06, 'epoch': 0.53}
+
53%|█████▎ | 6324/11952 [2:55:46<8:56:35, 5.72s/it]
53%|█████▎ | 6325/11952 [2:55:52<9:05:04, 5.81s/it]
{'loss': 0.4864, 'learning_rate': 9.540832634234238e-06, 'epoch': 0.53}
+
53%|█████▎ | 6325/11952 [2:55:52<9:05:04, 5.81s/it]
53%|█████▎ | 6326/11952 [2:55:57<9:02:51, 5.79s/it]
{'loss': 0.4847, 'learning_rate': 9.538125604527455e-06, 'epoch': 0.53}
+
53%|█████▎ | 6326/11952 [2:55:57<9:02:51, 5.79s/it]
53%|█████▎ | 6327/11952 [2:56:03<9:07:27, 5.84s/it]
{'loss': 0.5013, 'learning_rate': 9.535418608738808e-06, 'epoch': 0.53}
+
53%|█████▎ | 6327/11952 [2:56:03<9:07:27, 5.84s/it]
53%|█████▎ | 6328/11952 [2:56:09<9:11:03, 5.88s/it]
{'loss': 0.4738, 'learning_rate': 9.53271164706708e-06, 'epoch': 0.53}
+
53%|█████▎ | 6328/11952 [2:56:09<9:11:03, 5.88s/it]
53%|█████▎ | 6329/11952 [2:56:15<9:04:14, 5.81s/it]
{'loss': 0.4796, 'learning_rate': 9.53000471971107e-06, 'epoch': 0.53}
+
53%|█████▎ | 6329/11952 [2:56:15<9:04:14, 5.81s/it]
53%|█████▎ | 6330/11952 [2:56:21<9:06:41, 5.83s/it]
{'loss': 0.4594, 'learning_rate': 9.527297826869553e-06, 'epoch': 0.53}
+
53%|█████▎ | 6330/11952 [2:56:21<9:06:41, 5.83s/it]
53%|█████▎ | 6331/11952 [2:56:27<9:14:55, 5.92s/it]
{'loss': 0.4737, 'learning_rate': 9.524590968741324e-06, 'epoch': 0.53}
+
53%|█████▎ | 6331/11952 [2:56:27<9:14:55, 5.92s/it]
53%|█████▎ | 6332/11952 [2:56:33<9:08:30, 5.86s/it]
{'loss': 0.4757, 'learning_rate': 9.521884145525153e-06, 'epoch': 0.53}
+
53%|█████▎ | 6332/11952 [2:56:33<9:08:30, 5.86s/it]
53%|█████▎ | 6333/11952 [2:56:39<9:09:19, 5.87s/it]
{'loss': 0.5014, 'learning_rate': 9.519177357419824e-06, 'epoch': 0.53}
+
53%|█████▎ | 6333/11952 [2:56:39<9:09:19, 5.87s/it]
53%|█████▎ | 6334/11952 [2:56:45<9:12:57, 5.91s/it]
{'loss': 0.4906, 'learning_rate': 9.516470604624109e-06, 'epoch': 0.53}
+
53%|█████▎ | 6334/11952 [2:56:45<9:12:57, 5.91s/it]
53%|█████▎ | 6335/11952 [2:56:50<9:06:34, 5.84s/it]
{'loss': 0.4728, 'learning_rate': 9.513763887336781e-06, 'epoch': 0.53}
+
53%|█████▎ | 6335/11952 [2:56:50<9:06:34, 5.84s/it]
53%|█████▎ | 6336/11952 [2:56:56<8:59:54, 5.77s/it]
{'loss': 0.4792, 'learning_rate': 9.511057205756614e-06, 'epoch': 0.53}
+
53%|█████▎ | 6336/11952 [2:56:56<8:59:54, 5.77s/it]
53%|█████▎ | 6337/11952 [2:57:01<8:51:20, 5.68s/it]
{'loss': 0.4579, 'learning_rate': 9.508350560082364e-06, 'epoch': 0.53}
+
53%|█████▎ | 6337/11952 [2:57:01<8:51:20, 5.68s/it]
53%|█████▎ | 6338/11952 [2:57:07<8:57:49, 5.75s/it]
{'loss': 0.4688, 'learning_rate': 9.505643950512811e-06, 'epoch': 0.53}
+
53%|█████▎ | 6338/11952 [2:57:07<8:57:49, 5.75s/it]
53%|█████▎ | 6339/11952 [2:57:13<9:09:45, 5.88s/it]
{'loss': 0.489, 'learning_rate': 9.502937377246707e-06, 'epoch': 0.53}
+
53%|█████▎ | 6339/11952 [2:57:13<9:09:45, 5.88s/it]
53%|█████▎ | 6340/11952 [2:57:19<9:14:12, 5.93s/it]
{'loss': 0.4965, 'learning_rate': 9.500230840482817e-06, 'epoch': 0.53}
+
53%|█████▎ | 6340/11952 [2:57:19<9:14:12, 5.93s/it]
53%|█████▎ | 6341/11952 [2:57:26<9:19:59, 5.99s/it]
{'loss': 0.4631, 'learning_rate': 9.497524340419896e-06, 'epoch': 0.53}
+
53%|█████▎ | 6341/11952 [2:57:26<9:19:59, 5.99s/it]
53%|█████▎ | 6342/11952 [2:57:32<9:22:07, 6.01s/it]
{'loss': 0.4601, 'learning_rate': 9.494817877256696e-06, 'epoch': 0.53}
+
53%|█████▎ | 6342/11952 [2:57:32<9:22:07, 6.01s/it]
53%|█████▎ | 6343/11952 [2:57:37<9:09:03, 5.87s/it]
{'loss': 0.4815, 'learning_rate': 9.49211145119197e-06, 'epoch': 0.53}
+
53%|█████▎ | 6343/11952 [2:57:37<9:09:03, 5.87s/it]
53%|█████▎ | 6344/11952 [2:57:43<9:15:05, 5.94s/it]
{'loss': 0.4815, 'learning_rate': 9.489405062424464e-06, 'epoch': 0.53}
+
53%|█████▎ | 6344/11952 [2:57:43<9:15:05, 5.94s/it]
53%|█████▎ | 6345/11952 [2:57:49<9:13:13, 5.92s/it]
{'loss': 0.489, 'learning_rate': 9.486698711152928e-06, 'epoch': 0.53}
+
53%|█████▎ | 6345/11952 [2:57:49<9:13:13, 5.92s/it]
53%|█████▎ | 6346/11952 [2:57:55<9:07:42, 5.86s/it]
{'loss': 0.4806, 'learning_rate': 9.483992397576106e-06, 'epoch': 0.53}
+
53%|█████▎ | 6346/11952 [2:57:55<9:07:42, 5.86s/it]
53%|█████▎ | 6347/11952 [2:58:01<9:02:34, 5.81s/it]
{'loss': 0.4701, 'learning_rate': 9.481286121892734e-06, 'epoch': 0.53}
+
53%|█████▎ | 6347/11952 [2:58:01<9:02:34, 5.81s/it]
53%|█████▎ | 6348/11952 [2:58:06<9:01:25, 5.80s/it]
{'loss': 0.4687, 'learning_rate': 9.478579884301554e-06, 'epoch': 0.53}
+
53%|█████▎ | 6348/11952 [2:58:06<9:01:25, 5.80s/it]
53%|█████▎ | 6349/11952 [2:58:12<9:06:01, 5.85s/it]
{'loss': 0.4647, 'learning_rate': 9.475873685001295e-06, 'epoch': 0.53}
+
53%|█████▎ | 6349/11952 [2:58:12<9:06:01, 5.85s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...0
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
53%|█████▎ | 6350/11952 [2:58:18<8:56:56, 5.75s/it]4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4665, 'learning_rate': 9.473167524190692e-06, 'epoch': 0.53}
+
53%|█████▎ | 6350/11952 [2:58:18<8:56:56, 5.75s/it]
53%|█████▎ | 6351/11952 [2:58:23<8:54:00, 5.72s/it]
{'loss': 0.4681, 'learning_rate': 9.470461402068478e-06, 'epoch': 0.53}
+
53%|█████▎ | 6351/11952 [2:58:23<8:54:00, 5.72s/it]
53%|█████▎ | 6352/11952 [2:58:29<8:48:53, 5.67s/it]
{'loss': 0.482, 'learning_rate': 9.467755318833376e-06, 'epoch': 0.53}
+
53%|█████▎ | 6352/11952 [2:58:29<8:48:53, 5.67s/it]
53%|█████▎ | 6353/11952 [2:58:35<8:51:02, 5.69s/it]
{'loss': 0.4852, 'learning_rate': 9.46504927468411e-06, 'epoch': 0.53}
+
53%|█████▎ | 6353/11952 [2:58:35<8:51:02, 5.69s/it]
53%|█████▎ | 6354/11952 [2:58:40<8:50:30, 5.69s/it]
{'loss': 0.4887, 'learning_rate': 9.462343269819398e-06, 'epoch': 0.53}
+
53%|█████▎ | 6354/11952 [2:58:40<8:50:30, 5.69s/it]
53%|█████▎ | 6355/11952 [2:58:46<8:48:07, 5.66s/it]
{'loss': 0.4993, 'learning_rate': 9.459637304437962e-06, 'epoch': 0.53}
+
53%|█████▎ | 6355/11952 [2:58:46<8:48:07, 5.66s/it]
53%|█████▎ | 6356/11952 [2:58:52<8:54:22, 5.73s/it]
{'loss': 0.4926, 'learning_rate': 9.456931378738515e-06, 'epoch': 0.53}
+
53%|█████▎ | 6356/11952 [2:58:52<8:54:22, 5.73s/it]
53%|█████▎ | 6357/11952 [2:58:58<9:02:59, 5.82s/it]
{'loss': 0.4916, 'learning_rate': 9.454225492919765e-06, 'epoch': 0.53}
+
53%|█████▎ | 6357/11952 [2:58:58<9:02:59, 5.82s/it]
53%|█████▎ | 6358/11952 [2:59:04<9:01:26, 5.81s/it]
{'loss': 0.4718, 'learning_rate': 9.451519647180427e-06, 'epoch': 0.53}
+
53%|█████▎ | 6358/11952 [2:59:04<9:01:26, 5.81s/it]
53%|█████▎ | 6359/11952 [2:59:09<8:54:55, 5.74s/it]
{'loss': 0.4794, 'learning_rate': 9.448813841719207e-06, 'epoch': 0.53}
+
53%|█████▎ | 6359/11952 [2:59:09<8:54:55, 5.74s/it]
53%|█████▎ | 6360/11952 [2:59:15<8:55:48, 5.75s/it]
{'loss': 0.461, 'learning_rate': 9.446108076734803e-06, 'epoch': 0.53}
+
53%|█████▎ | 6360/11952 [2:59:15<8:55:48, 5.75s/it]
53%|█████▎ | 6361/11952 [2:59:21<8:58:40, 5.78s/it]
{'loss': 0.486, 'learning_rate': 9.44340235242592e-06, 'epoch': 0.53}
+
53%|█████▎ | 6361/11952 [2:59:21<8:58:40, 5.78s/it]
53%|█████▎ | 6362/11952 [2:59:27<8:59:17, 5.79s/it]
{'loss': 0.467, 'learning_rate': 9.440696668991253e-06, 'epoch': 0.53}
+
53%|█████▎ | 6362/11952 [2:59:27<8:59:17, 5.79s/it]
53%|█████▎ | 6363/11952 [2:59:32<8:55:58, 5.75s/it]
{'loss': 0.4657, 'learning_rate': 9.437991026629497e-06, 'epoch': 0.53}
+
53%|█████▎ | 6363/11952 [2:59:32<8:55:58, 5.75s/it]
53%|█████▎ | 6364/11952 [2:59:38<8:52:40, 5.72s/it]
{'loss': 0.4854, 'learning_rate': 9.435285425539337e-06, 'epoch': 0.53}
+
53%|█████▎ | 6364/11952 [2:59:38<8:52:40, 5.72s/it]
53%|█████▎ | 6365/11952 [2:59:44<8:58:27, 5.78s/it]
{'loss': 0.4839, 'learning_rate': 9.43257986591947e-06, 'epoch': 0.53}
+
53%|█████▎ | 6365/11952 [2:59:44<8:58:27, 5.78s/it]
53%|█████▎ | 6366/11952 [2:59:50<8:55:36, 5.75s/it]
{'loss': 0.4686, 'learning_rate': 9.42987434796858e-06, 'epoch': 0.53}
+
53%|█████▎ | 6366/11952 [2:59:50<8:55:36, 5.75s/it]
53%|█████▎ | 6367/11952 [2:59:55<8:53:32, 5.73s/it]
{'loss': 0.4639, 'learning_rate': 9.427168871885345e-06, 'epoch': 0.53}
+
53%|█████▎ | 6367/11952 [2:59:55<8:53:32, 5.73s/it]
53%|█████▎ | 6368/11952 [3:00:02<9:07:04, 5.88s/it]
{'loss': 0.4912, 'learning_rate': 9.424463437868445e-06, 'epoch': 0.53}
+
53%|█████▎ | 6368/11952 [3:00:02<9:07:04, 5.88s/it]
53%|█████▎ | 6369/11952 [3:00:07<9:04:20, 5.85s/it]
{'loss': 0.4673, 'learning_rate': 9.421758046116557e-06, 'epoch': 0.53}
+
53%|█████▎ | 6369/11952 [3:00:07<9:04:20, 5.85s/it]
53%|█████▎ | 6370/11952 [3:00:13<9:04:32, 5.85s/it]
{'loss': 0.4861, 'learning_rate': 9.419052696828352e-06, 'epoch': 0.53}
+
53%|█████▎ | 6370/11952 [3:00:13<9:04:32, 5.85s/it]
53%|█████▎ | 6371/11952 [3:00:19<9:00:29, 5.81s/it]
{'loss': 0.4816, 'learning_rate': 9.416347390202499e-06, 'epoch': 0.53}
+
53%|█████▎ | 6371/11952 [3:00:19<9:00:29, 5.81s/it]
53%|█████▎ | 6372/11952 [3:00:25<8:58:50, 5.79s/it]
{'loss': 0.4647, 'learning_rate': 9.41364212643767e-06, 'epoch': 0.53}
+
53%|█████▎ | 6372/11952 [3:00:25<8:58:50, 5.79s/it]
53%|█████▎ | 6373/11952 [3:00:31<8:58:47, 5.79s/it]
{'loss': 0.4781, 'learning_rate': 9.410936905732522e-06, 'epoch': 0.53}
+
53%|█████▎ | 6373/11952 [3:00:31<8:58:47, 5.79s/it]
53%|█████▎ | 6374/11952 [3:00:36<9:01:25, 5.82s/it]
{'loss': 0.4912, 'learning_rate': 9.40823172828572e-06, 'epoch': 0.53}
+
53%|█████▎ | 6374/11952 [3:00:36<9:01:25, 5.82s/it]
53%|█████▎ | 6375/11952 [3:00:42<8:55:19, 5.76s/it]
{'loss': 0.4641, 'learning_rate': 9.405526594295915e-06, 'epoch': 0.53}
+
53%|█████▎ | 6375/11952 [3:00:42<8:55:19, 5.76s/it]
53%|█████▎ | 6376/11952 [3:00:48<8:57:01, 5.78s/it]
{'loss': 0.4802, 'learning_rate': 9.402821503961766e-06, 'epoch': 0.53}
+
53%|█████▎ | 6376/11952 [3:00:48<8:57:01, 5.78s/it]
53%|█████▎ | 6377/11952 [3:00:54<9:08:56, 5.91s/it]
{'loss': 0.4938, 'learning_rate': 9.400116457481924e-06, 'epoch': 0.53}
+
53%|█████▎ | 6377/11952 [3:00:54<9:08:56, 5.91s/it]
53%|█████▎ | 6378/11952 [3:01:00<9:08:59, 5.91s/it]
{'loss': 0.4878, 'learning_rate': 9.397411455055028e-06, 'epoch': 0.53}
+
53%|█████▎ | 6378/11952 [3:01:00<9:08:59, 5.91s/it]
53%|█████▎ | 6379/11952 [3:01:06<9:18:59, 6.02s/it]
{'loss': 0.4762, 'learning_rate': 9.394706496879733e-06, 'epoch': 0.53}
+
53%|█████▎ | 6379/11952 [3:01:06<9:18:59, 6.02s/it]
53%|█████▎ | 6380/11952 [3:01:12<9:21:01, 6.04s/it]
{'loss': 0.4799, 'learning_rate': 9.392001583154675e-06, 'epoch': 0.53}
+
53%|█████▎ | 6380/11952 [3:01:12<9:21:01, 6.04s/it]
53%|█████▎ | 6381/11952 [3:01:18<9:17:22, 6.00s/it]
{'loss': 0.4966, 'learning_rate': 9.389296714078493e-06, 'epoch': 0.53}
+
53%|█████▎ | 6381/11952 [3:01:18<9:17:22, 6.00s/it]
53%|█████▎ | 6382/11952 [3:01:24<9:18:03, 6.01s/it]
{'loss': 0.4841, 'learning_rate': 9.386591889849819e-06, 'epoch': 0.53}
+
53%|█████▎ | 6382/11952 [3:01:24<9:18:03, 6.01s/it]
53%|█████▎ | 6383/11952 [3:01:30<9:06:51, 5.89s/it]
{'loss': 0.5037, 'learning_rate': 9.383887110667285e-06, 'epoch': 0.53}
+
53%|█████▎ | 6383/11952 [3:01:30<9:06:51, 5.89s/it]
53%|█████▎ | 6384/11952 [3:01:35<8:59:10, 5.81s/it]
{'loss': 0.4769, 'learning_rate': 9.381182376729516e-06, 'epoch': 0.53}
+
53%|█████▎ | 6384/11952 [3:01:35<8:59:10, 5.81s/it]
53%|█████▎ | 6385/11952 [3:01:41<9:04:22, 5.87s/it]
{'loss': 0.4716, 'learning_rate': 9.378477688235144e-06, 'epoch': 0.53}
+
53%|█████▎ | 6385/11952 [3:01:41<9:04:22, 5.87s/it]
53%|█████▎ | 6386/11952 [3:01:47<8:55:30, 5.77s/it]
{'loss': 0.4908, 'learning_rate': 9.375773045382782e-06, 'epoch': 0.53}
+
53%|█████▎ | 6386/11952 [3:01:47<8:55:30, 5.77s/it]
53%|█████▎ | 6387/11952 [3:01:53<8:52:41, 5.74s/it]
{'loss': 0.4506, 'learning_rate': 9.373068448371054e-06, 'epoch': 0.53}
+
53%|█████▎ | 6387/11952 [3:01:53<8:52:41, 5.74s/it]
53%|█████▎ | 6388/11952 [3:01:59<9:01:30, 5.84s/it]
{'loss': 0.4837, 'learning_rate': 9.370363897398573e-06, 'epoch': 0.53}
+
53%|█████▎ | 6388/11952 [3:01:59<9:01:30, 5.84s/it]
53%|█████▎ | 6389/11952 [3:02:04<8:57:31, 5.80s/it]
{'loss': 0.4797, 'learning_rate': 9.367659392663947e-06, 'epoch': 0.53}
+
53%|█████▎ | 6389/11952 [3:02:04<8:57:31, 5.80s/it]
53%|█████▎ | 6390/11952 [3:02:10<8:59:36, 5.82s/it]
{'loss': 0.4906, 'learning_rate': 9.364954934365783e-06, 'epoch': 0.53}
+
53%|█████▎ | 6390/11952 [3:02:10<8:59:36, 5.82s/it]
53%|█████▎ | 6391/11952 [3:02:16<8:54:55, 5.77s/it]
{'loss': 0.4653, 'learning_rate': 9.362250522702685e-06, 'epoch': 0.53}
+
53%|█████▎ | 6391/11952 [3:02:16<8:54:55, 5.77s/it]
53%|█████▎ | 6392/11952 [3:02:22<8:52:28, 5.75s/it]
{'loss': 0.4811, 'learning_rate': 9.35954615787326e-06, 'epoch': 0.53}
+
53%|█████▎ | 6392/11952 [3:02:22<8:52:28, 5.75s/it]
53%|█████▎ | 6393/11952 [3:02:27<8:52:08, 5.74s/it]
{'loss': 0.4746, 'learning_rate': 9.356841840076102e-06, 'epoch': 0.53}
+
53%|█████▎ | 6393/11952 [3:02:27<8:52:08, 5.74s/it]
53%|█████▎ | 6394/11952 [3:02:33<8:52:21, 5.75s/it]
{'loss': 0.4864, 'learning_rate': 9.354137569509804e-06, 'epoch': 0.53}
+
53%|█████▎ | 6394/11952 [3:02:33<8:52:21, 5.75s/it]
54%|█████▎ | 6395/11952 [3:02:39<8:55:38, 5.78s/it]
{'loss': 0.4882, 'learning_rate': 9.351433346372955e-06, 'epoch': 0.54}
+
54%|█████▎ | 6395/11952 [3:02:39<8:55:38, 5.78s/it]
54%|█████▎ | 6396/11952 [3:02:45<8:52:18, 5.75s/it]
{'loss': 0.4855, 'learning_rate': 9.348729170864145e-06, 'epoch': 0.54}
+
54%|█████▎ | 6396/11952 [3:02:45<8:52:18, 5.75s/it]
54%|█████▎ | 6397/11952 [3:02:51<8:53:59, 5.77s/it]
{'loss': 0.4606, 'learning_rate': 9.346025043181955e-06, 'epoch': 0.54}
+
54%|█████▎ | 6397/11952 [3:02:51<8:53:59, 5.77s/it]
54%|█████▎ | 6398/11952 [3:02:57<9:06:28, 5.90s/it]
{'loss': 0.482, 'learning_rate': 9.343320963524964e-06, 'epoch': 0.54}
+
54%|█████▎ | 6398/11952 [3:02:57<9:06:28, 5.90s/it]
54%|█████▎ | 6399/11952 [3:03:03<9:05:35, 5.90s/it]
{'loss': 0.4876, 'learning_rate': 9.340616932091752e-06, 'epoch': 0.54}
+
54%|█████▎ | 6399/11952 [3:03:03<9:05:35, 5.90s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+53 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+01 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
54%|█████▎ | 6400/11952 [3:03:09<9:11:16, 5.96s/it]
{'loss': 0.4936, 'learning_rate': 9.33791294908089e-06, 'epoch': 0.54}
+
54%|█████▎ | 6400/11952 [3:03:09<9:11:16, 5.96s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
54%|█████▎ | 6401/11952 [3:03:40<20:42:50, 13.43s/it]
{'loss': 0.495, 'learning_rate': 9.335209014690946e-06, 'epoch': 0.54}
+
54%|█████▎ | 6401/11952 [3:03:40<20:42:50, 13.43s/it]
54%|█████▎ | 6402/11952 [3:03:45<17:12:49, 11.17s/it]
{'loss': 0.4882, 'learning_rate': 9.332505129120489e-06, 'epoch': 0.54}
+
54%|█████▎ | 6402/11952 [3:03:45<17:12:49, 11.17s/it]
54%|█████▎ | 6403/11952 [3:03:52<14:56:30, 9.69s/it]
{'loss': 0.4871, 'learning_rate': 9.32980129256808e-06, 'epoch': 0.54}
+
54%|█████▎ | 6403/11952 [3:03:52<14:56:30, 9.69s/it]
54%|█████▎ | 6404/11952 [3:03:58<13:18:20, 8.63s/it]
{'loss': 0.4526, 'learning_rate': 9.327097505232274e-06, 'epoch': 0.54}
+
54%|█████▎ | 6404/11952 [3:03:58<13:18:20, 8.63s/it]
54%|█████▎ | 6405/11952 [3:04:04<12:05:41, 7.85s/it]
{'loss': 0.4816, 'learning_rate': 9.324393767311625e-06, 'epoch': 0.54}
+
54%|█████▎ | 6405/11952 [3:04:04<12:05:41, 7.85s/it]
54%|█████▎ | 6406/11952 [3:04:10<11:24:53, 7.41s/it]
{'loss': 0.4765, 'learning_rate': 9.321690079004691e-06, 'epoch': 0.54}
+
54%|█████▎ | 6406/11952 [3:04:10<11:24:53, 7.41s/it]
54%|█████▎ | 6407/11952 [3:04:16<10:41:34, 6.94s/it]
{'loss': 0.4737, 'learning_rate': 9.318986440510018e-06, 'epoch': 0.54}
+
54%|█████▎ | 6407/11952 [3:04:16<10:41:34, 6.94s/it]
54%|█████▎ | 6408/11952 [3:04:22<10:21:35, 6.73s/it]
{'loss': 0.4784, 'learning_rate': 9.316282852026147e-06, 'epoch': 0.54}
+
54%|█████▎ | 6408/11952 [3:04:22<10:21:35, 6.73s/it]
54%|█████▎ | 6409/11952 [3:04:31<11:08:08, 7.23s/it]
{'loss': 0.4744, 'learning_rate': 9.313579313751621e-06, 'epoch': 0.54}
+
54%|█████▎ | 6409/11952 [3:04:31<11:08:08, 7.23s/it]
54%|█████▎ | 6410/11952 [3:04:37<10:28:27, 6.80s/it]
{'loss': 0.4675, 'learning_rate': 9.310875825884972e-06, 'epoch': 0.54}
+
54%|█████▎ | 6410/11952 [3:04:37<10:28:27, 6.80s/it]
54%|█████▎ | 6411/11952 [3:04:43<10:03:52, 6.54s/it]
{'loss': 0.465, 'learning_rate': 9.308172388624739e-06, 'epoch': 0.54}
+
54%|█████▎ | 6411/11952 [3:04:43<10:03:52, 6.54s/it]
54%|█████▎ | 6412/11952 [3:04:48<9:47:46, 6.37s/it]
{'loss': 0.477, 'learning_rate': 9.305469002169442e-06, 'epoch': 0.54}
+
54%|█████▎ | 6412/11952 [3:04:48<9:47:46, 6.37s/it]
54%|█████▎ | 6413/11952 [3:04:54<9:36:39, 6.25s/it]
{'loss': 0.4649, 'learning_rate': 9.30276566671762e-06, 'epoch': 0.54}
+
54%|█████▎ | 6413/11952 [3:04:54<9:36:39, 6.25s/it]
54%|█████▎ | 6414/11952 [3:05:00<9:24:00, 6.11s/it]
{'loss': 0.4649, 'learning_rate': 9.300062382467785e-06, 'epoch': 0.54}
+
54%|█████▎ | 6414/11952 [3:05:00<9:24:00, 6.11s/it]
54%|█████▎ | 6415/11952 [3:05:06<9:10:38, 5.97s/it]
{'loss': 0.468, 'learning_rate': 9.29735914961846e-06, 'epoch': 0.54}
+
54%|█████▎ | 6415/11952 [3:05:06<9:10:38, 5.97s/it]
54%|█████▎ | 6416/11952 [3:05:12<9:08:02, 5.94s/it]
{'loss': 0.4863, 'learning_rate': 9.294655968368153e-06, 'epoch': 0.54}
+
54%|█████▎ | 6416/11952 [3:05:12<9:08:02, 5.94s/it]
54%|█████▎ | 6417/11952 [3:05:18<9:08:03, 5.94s/it]
{'loss': 0.4815, 'learning_rate': 9.291952838915379e-06, 'epoch': 0.54}
+
54%|█████▎ | 6417/11952 [3:05:18<9:08:03, 5.94s/it]
54%|█████▎ | 6418/11952 [3:05:23<9:01:12, 5.87s/it]
{'loss': 0.4916, 'learning_rate': 9.289249761458643e-06, 'epoch': 0.54}
+
54%|█████▎ | 6418/11952 [3:05:23<9:01:12, 5.87s/it]
54%|█████▎ | 6419/11952 [3:05:29<8:57:59, 5.83s/it]
{'loss': 0.4722, 'learning_rate': 9.286546736196447e-06, 'epoch': 0.54}
+
54%|█████▎ | 6419/11952 [3:05:29<8:57:59, 5.83s/it]
54%|█████▎ | 6420/11952 [3:05:35<9:10:50, 5.97s/it]
{'loss': 0.5097, 'learning_rate': 9.283843763327293e-06, 'epoch': 0.54}
+
54%|█████▎ | 6420/11952 [3:05:35<9:10:50, 5.97s/it]
54%|█████▎ | 6421/11952 [3:05:41<9:10:49, 5.98s/it]
{'loss': 0.4785, 'learning_rate': 9.281140843049674e-06, 'epoch': 0.54}
+
54%|█████▎ | 6421/11952 [3:05:41<9:10:49, 5.98s/it]
54%|█████▎ | 6422/11952 [3:05:47<9:10:22, 5.97s/it]
{'loss': 0.4712, 'learning_rate': 9.278437975562083e-06, 'epoch': 0.54}
+
54%|█████▎ | 6422/11952 [3:05:47<9:10:22, 5.97s/it]
54%|█████▎ | 6423/11952 [3:05:53<9:02:27, 5.89s/it]
{'loss': 0.4693, 'learning_rate': 9.275735161063006e-06, 'epoch': 0.54}
+
54%|█████▎ | 6423/11952 [3:05:53<9:02:27, 5.89s/it]
54%|█████▎ | 6424/11952 [3:05:59<9:07:56, 5.95s/it]
{'loss': 0.4631, 'learning_rate': 9.273032399750925e-06, 'epoch': 0.54}
+
54%|█████▎ | 6424/11952 [3:05:59<9:07:56, 5.95s/it]
54%|█████▍ | 6425/11952 [3:06:05<9:03:45, 5.90s/it]
{'loss': 0.4736, 'learning_rate': 9.270329691824318e-06, 'epoch': 0.54}
+
54%|█████▍ | 6425/11952 [3:06:05<9:03:45, 5.90s/it]
54%|█████▍ | 6426/11952 [3:06:11<9:06:44, 5.94s/it]
{'loss': 0.4763, 'learning_rate': 9.267627037481667e-06, 'epoch': 0.54}
+
54%|█████▍ | 6426/11952 [3:06:11<9:06:44, 5.94s/it]
54%|█████▍ | 6427/11952 [3:06:17<9:09:02, 5.96s/it]
{'loss': 0.475, 'learning_rate': 9.264924436921438e-06, 'epoch': 0.54}
+
54%|█████▍ | 6427/11952 [3:06:17<9:09:02, 5.96s/it]
54%|█████▍ | 6428/11952 [3:06:23<9:09:53, 5.97s/it]
{'loss': 0.5036, 'learning_rate': 9.262221890342104e-06, 'epoch': 0.54}
+
54%|█████▍ | 6428/11952 [3:06:23<9:09:53, 5.97s/it]
54%|█████▍ | 6429/11952 [3:06:29<9:10:19, 5.98s/it]
{'loss': 0.4682, 'learning_rate': 9.259519397942125e-06, 'epoch': 0.54}
+
54%|█████▍ | 6429/11952 [3:06:29<9:10:19, 5.98s/it]
54%|█████▍ | 6430/11952 [3:06:35<9:03:11, 5.90s/it]
{'loss': 0.4808, 'learning_rate': 9.256816959919962e-06, 'epoch': 0.54}
+
54%|█████▍ | 6430/11952 [3:06:35<9:03:11, 5.90s/it]
54%|█████▍ | 6431/11952 [3:06:41<9:03:22, 5.91s/it]
{'loss': 0.4676, 'learning_rate': 9.254114576474068e-06, 'epoch': 0.54}
+
54%|█████▍ | 6431/11952 [3:06:41<9:03:22, 5.91s/it]
54%|█████▍ | 6432/11952 [3:06:47<9:03:04, 5.90s/it]
{'loss': 0.4549, 'learning_rate': 9.251412247802896e-06, 'epoch': 0.54}
+
54%|█████▍ | 6432/11952 [3:06:47<9:03:04, 5.90s/it]
54%|█████▍ | 6433/11952 [3:06:53<9:16:13, 6.05s/it]
{'loss': 0.4904, 'learning_rate': 9.248709974104897e-06, 'epoch': 0.54}
+
54%|█████▍ | 6433/11952 [3:06:53<9:16:13, 6.05s/it]
54%|█████▍ | 6434/11952 [3:06:59<9:16:21, 6.05s/it]
{'loss': 0.4909, 'learning_rate': 9.246007755578514e-06, 'epoch': 0.54}
+
54%|█████▍ | 6434/11952 [3:06:59<9:16:21, 6.05s/it]
54%|█████▍ | 6435/11952 [3:07:05<9:15:22, 6.04s/it]
{'loss': 0.479, 'learning_rate': 9.243305592422184e-06, 'epoch': 0.54}
+
54%|█████▍ | 6435/11952 [3:07:05<9:15:22, 6.04s/it]
54%|█████▍ | 6436/11952 [3:07:11<9:17:19, 6.06s/it]
{'loss': 0.4879, 'learning_rate': 9.240603484834347e-06, 'epoch': 0.54}
+
54%|█████▍ | 6436/11952 [3:07:11<9:17:19, 6.06s/it]
54%|█████▍ | 6437/11952 [3:07:17<9:18:24, 6.08s/it]
{'loss': 0.4899, 'learning_rate': 9.237901433013427e-06, 'epoch': 0.54}
+
54%|█████▍ | 6437/11952 [3:07:17<9:18:24, 6.08s/it]
54%|█████▍ | 6438/11952 [3:07:23<9:10:22, 5.99s/it]
{'loss': 0.4525, 'learning_rate': 9.235199437157858e-06, 'epoch': 0.54}
+
54%|█████▍ | 6438/11952 [3:07:23<9:10:22, 5.99s/it]
54%|█████▍ | 6439/11952 [3:07:29<9:08:45, 5.97s/it]
{'loss': 0.4823, 'learning_rate': 9.232497497466057e-06, 'epoch': 0.54}
+
54%|█████▍ | 6439/11952 [3:07:29<9:08:45, 5.97s/it]
54%|█████▍ | 6440/11952 [3:07:35<9:05:13, 5.94s/it]
{'loss': 0.4723, 'learning_rate': 9.229795614136452e-06, 'epoch': 0.54}
+
54%|█████▍ | 6440/11952 [3:07:35<9:05:13, 5.94s/it]
54%|█████▍ | 6441/11952 [3:07:41<9:03:30, 5.92s/it]
{'loss': 0.4649, 'learning_rate': 9.227093787367454e-06, 'epoch': 0.54}
+
54%|█████▍ | 6441/11952 [3:07:41<9:03:30, 5.92s/it]
54%|█████▍ | 6442/11952 [3:07:49<10:20:51, 6.76s/it]
{'loss': 0.4885, 'learning_rate': 9.224392017357471e-06, 'epoch': 0.54}
+
54%|█████▍ | 6442/11952 [3:07:49<10:20:51, 6.76s/it]
54%|█████▍ | 6443/11952 [3:07:55<9:54:24, 6.47s/it]
{'loss': 0.4626, 'learning_rate': 9.221690304304915e-06, 'epoch': 0.54}
+
54%|█████▍ | 6443/11952 [3:07:55<9:54:24, 6.47s/it]
54%|█████▍ | 6444/11952 [3:08:01<9:38:04, 6.30s/it]
{'loss': 0.4568, 'learning_rate': 9.218988648408187e-06, 'epoch': 0.54}
+
54%|█████▍ | 6444/11952 [3:08:01<9:38:04, 6.30s/it]
54%|█████▍ | 6445/11952 [3:08:07<9:29:02, 6.20s/it]
{'loss': 0.4942, 'learning_rate': 9.216287049865681e-06, 'epoch': 0.54}
+
54%|█████▍ | 6445/11952 [3:08:07<9:29:02, 6.20s/it]
54%|█████▍ | 6446/11952 [3:08:13<9:24:25, 6.15s/it]
{'loss': 0.5012, 'learning_rate': 9.213585508875792e-06, 'epoch': 0.54}
+
54%|█████▍ | 6446/11952 [3:08:13<9:24:25, 6.15s/it]
54%|█████▍ | 6447/11952 [3:08:19<9:12:19, 6.02s/it]
{'loss': 0.4838, 'learning_rate': 9.210884025636916e-06, 'epoch': 0.54}
+
54%|█████▍ | 6447/11952 [3:08:19<9:12:19, 6.02s/it]
54%|█████▍ | 6448/11952 [3:08:28<10:29:04, 6.86s/it]
{'loss': 0.4744, 'learning_rate': 9.208182600347432e-06, 'epoch': 0.54}
+
54%|█████▍ | 6448/11952 [3:08:28<10:29:04, 6.86s/it]
54%|█████▍ | 6449/11952 [3:08:34<10:05:32, 6.60s/it]
{'loss': 0.4823, 'learning_rate': 9.20548123320573e-06, 'epoch': 0.54}
+
54%|█████▍ | 6449/11952 [3:08:34<10:05:32, 6.60s/it]4 AutoResumeHook: Checking whether to suspend...
+23 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
54%|█████▍ | 6450/11952 [3:08:43<11:16:57, 7.38s/it]1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4897, 'learning_rate': 9.20277992441018e-06, 'epoch': 0.54}
+
54%|█████▍ | 6450/11952 [3:08:43<11:16:57, 7.38s/it]
54%|█████▍ | 6451/11952 [3:08:49<10:35:43, 6.93s/it]
{'loss': 0.4671, 'learning_rate': 9.200078674159154e-06, 'epoch': 0.54}
+
54%|█████▍ | 6451/11952 [3:08:49<10:35:43, 6.93s/it]
54%|█████▍ | 6452/11952 [3:08:54<10:03:23, 6.58s/it]
{'loss': 0.4986, 'learning_rate': 9.197377482651023e-06, 'epoch': 0.54}
+
54%|█████▍ | 6452/11952 [3:08:54<10:03:23, 6.58s/it]
54%|█████▍ | 6453/11952 [3:09:00<9:36:26, 6.29s/it]
{'loss': 0.4702, 'learning_rate': 9.194676350084148e-06, 'epoch': 0.54}
+
54%|█████▍ | 6453/11952 [3:09:00<9:36:26, 6.29s/it]
54%|█████▍ | 6454/11952 [3:09:09<10:43:48, 7.03s/it]
{'loss': 0.4758, 'learning_rate': 9.191975276656898e-06, 'epoch': 0.54}
+
54%|█████▍ | 6454/11952 [3:09:09<10:43:48, 7.03s/it]
54%|█████▍ | 6455/11952 [3:09:18<11:46:42, 7.71s/it]
{'loss': 0.4712, 'learning_rate': 9.189274262567622e-06, 'epoch': 0.54}
+
54%|█████▍ | 6455/11952 [3:09:18<11:46:42, 7.71s/it]
54%|█████▍ | 6456/11952 [3:09:24<10:59:22, 7.20s/it]
{'loss': 0.4757, 'learning_rate': 9.186573308014672e-06, 'epoch': 0.54}
+
54%|█████▍ | 6456/11952 [3:09:24<10:59:22, 7.20s/it]
54%|█████▍ | 6457/11952 [3:09:33<11:41:30, 7.66s/it]
{'loss': 0.4419, 'learning_rate': 9.183872413196392e-06, 'epoch': 0.54}
+
54%|█████▍ | 6457/11952 [3:09:33<11:41:30, 7.66s/it]
54%|█████▍ | 6458/11952 [3:09:39<10:48:15, 7.08s/it]
{'loss': 0.483, 'learning_rate': 9.181171578311132e-06, 'epoch': 0.54}
+
54%|█████▍ | 6458/11952 [3:09:39<10:48:15, 7.08s/it]
54%|█████▍ | 6459/11952 [3:09:44<10:08:07, 6.64s/it]
{'loss': 0.4725, 'learning_rate': 9.17847080355722e-06, 'epoch': 0.54}
+
54%|█████▍ | 6459/11952 [3:09:44<10:08:07, 6.64s/it]
54%|█████▍ | 6460/11952 [3:09:50<9:44:09, 6.38s/it]
{'loss': 0.4854, 'learning_rate': 9.175770089133e-06, 'epoch': 0.54}
+
54%|█████▍ | 6460/11952 [3:09:50<9:44:09, 6.38s/it]
54%|█████▍ | 6461/11952 [3:09:58<10:30:16, 6.89s/it]
{'loss': 0.5029, 'learning_rate': 9.173069435236796e-06, 'epoch': 0.54}
+
54%|█████▍ | 6461/11952 [3:09:58<10:30:16, 6.89s/it]
54%|█████▍ | 6462/11952 [3:10:04<10:04:36, 6.61s/it]
{'loss': 0.4741, 'learning_rate': 9.170368842066932e-06, 'epoch': 0.54}
+
54%|█████▍ | 6462/11952 [3:10:04<10:04:36, 6.61s/it]
54%|█████▍ | 6463/11952 [3:10:10<9:38:58, 6.33s/it]
{'loss': 0.4736, 'learning_rate': 9.167668309821729e-06, 'epoch': 0.54}
+
54%|█████▍ | 6463/11952 [3:10:10<9:38:58, 6.33s/it]
54%|█████▍ | 6464/11952 [3:10:16<9:37:40, 6.32s/it]
{'loss': 0.5017, 'learning_rate': 9.164967838699504e-06, 'epoch': 0.54}
+
54%|█████▍ | 6464/11952 [3:10:16<9:37:40, 6.32s/it]
54%|█████▍ | 6465/11952 [3:10:22<9:30:22, 6.24s/it]
{'loss': 0.4903, 'learning_rate': 9.162267428898568e-06, 'epoch': 0.54}
+
54%|█████▍ | 6465/11952 [3:10:22<9:30:22, 6.24s/it]
54%|█████▍ | 6466/11952 [3:10:28<9:12:54, 6.05s/it]
{'loss': 0.4764, 'learning_rate': 9.159567080617226e-06, 'epoch': 0.54}
+
54%|█████▍ | 6466/11952 [3:10:28<9:12:54, 6.05s/it]
54%|█████▍ | 6467/11952 [3:10:33<9:02:43, 5.94s/it]
{'loss': 0.4889, 'learning_rate': 9.156866794053783e-06, 'epoch': 0.54}
+
54%|█████▍ | 6467/11952 [3:10:33<9:02:43, 5.94s/it]
54%|█████▍ | 6468/11952 [3:10:39<9:00:07, 5.91s/it]
{'loss': 0.4664, 'learning_rate': 9.154166569406537e-06, 'epoch': 0.54}
+
54%|█████▍ | 6468/11952 [3:10:39<9:00:07, 5.91s/it]
54%|█████▍ | 6469/11952 [3:10:45<9:08:29, 6.00s/it]
{'loss': 0.494, 'learning_rate': 9.15146640687378e-06, 'epoch': 0.54}
+
54%|█████▍ | 6469/11952 [3:10:45<9:08:29, 6.00s/it]
54%|█████▍ | 6470/11952 [3:10:51<9:02:11, 5.93s/it]
{'loss': 0.4731, 'learning_rate': 9.148766306653801e-06, 'epoch': 0.54}
+
54%|█████▍ | 6470/11952 [3:10:51<9:02:11, 5.93s/it]
54%|█████▍ | 6471/11952 [3:10:57<9:02:50, 5.94s/it]
{'loss': 0.4908, 'learning_rate': 9.146066268944883e-06, 'epoch': 0.54}
+
54%|█████▍ | 6471/11952 [3:10:57<9:02:50, 5.94s/it]
54%|█████▍ | 6472/11952 [3:11:03<8:59:19, 5.90s/it]
{'loss': 0.4881, 'learning_rate': 9.143366293945305e-06, 'epoch': 0.54}
+
54%|█████▍ | 6472/11952 [3:11:03<8:59:19, 5.90s/it]
54%|█████▍ | 6473/11952 [3:11:09<8:59:51, 5.91s/it]
{'loss': 0.4623, 'learning_rate': 9.140666381853343e-06, 'epoch': 0.54}
+
54%|█████▍ | 6473/11952 [3:11:09<8:59:51, 5.91s/it]
54%|█████▍ | 6474/11952 [3:11:15<8:55:56, 5.87s/it]
{'loss': 0.4839, 'learning_rate': 9.137966532867268e-06, 'epoch': 0.54}
+
54%|█████▍ | 6474/11952 [3:11:15<8:55:56, 5.87s/it]
54%|█████▍ | 6475/11952 [3:11:20<8:45:54, 5.76s/it]
{'loss': 0.484, 'learning_rate': 9.135266747185348e-06, 'epoch': 0.54}
+
54%|█████▍ | 6475/11952 [3:11:20<8:45:54, 5.76s/it]
54%|█████▍ | 6476/11952 [3:11:26<8:57:50, 5.89s/it]
{'loss': 0.4819, 'learning_rate': 9.132567025005842e-06, 'epoch': 0.54}
+
54%|█████▍ | 6476/11952 [3:11:26<8:57:50, 5.89s/it]
54%|█████▍ | 6477/11952 [3:11:33<9:05:06, 5.97s/it]
{'loss': 0.4728, 'learning_rate': 9.129867366527004e-06, 'epoch': 0.54}
+
54%|█████▍ | 6477/11952 [3:11:33<9:05:06, 5.97s/it]
54%|█████▍ | 6478/11952 [3:11:38<8:58:09, 5.90s/it]
{'loss': 0.4608, 'learning_rate': 9.127167771947086e-06, 'epoch': 0.54}
+
54%|█████▍ | 6478/11952 [3:11:38<8:58:09, 5.90s/it]
54%|█████▍ | 6479/11952 [3:11:44<8:58:28, 5.90s/it]
{'loss': 0.4677, 'learning_rate': 9.12446824146434e-06, 'epoch': 0.54}
+
54%|█████▍ | 6479/11952 [3:11:44<8:58:28, 5.90s/it]
54%|█████▍ | 6480/11952 [3:11:50<8:49:31, 5.81s/it]
{'loss': 0.4838, 'learning_rate': 9.121768775276997e-06, 'epoch': 0.54}
+
54%|█████▍ | 6480/11952 [3:11:50<8:49:31, 5.81s/it]
54%|█████▍ | 6481/11952 [3:11:55<8:44:36, 5.75s/it]
{'loss': 0.4658, 'learning_rate': 9.11906937358331e-06, 'epoch': 0.54}
+
54%|█████▍ | 6481/11952 [3:11:55<8:44:36, 5.75s/it]
54%|█████▍ | 6482/11952 [3:12:01<8:48:03, 5.79s/it]
{'loss': 0.4829, 'learning_rate': 9.116370036581504e-06, 'epoch': 0.54}
+
54%|█████▍ | 6482/11952 [3:12:01<8:48:03, 5.79s/it]
54%|█████▍ | 6483/11952 [3:12:07<8:49:20, 5.81s/it]
{'loss': 0.4701, 'learning_rate': 9.113670764469803e-06, 'epoch': 0.54}
+
54%|█████▍ | 6483/11952 [3:12:07<8:49:20, 5.81s/it]
54%|█████▍ | 6484/11952 [3:12:13<8:45:47, 5.77s/it]
{'loss': 0.4751, 'learning_rate': 9.110971557446437e-06, 'epoch': 0.54}
+
54%|█████▍ | 6484/11952 [3:12:13<8:45:47, 5.77s/it]
54%|█████▍ | 6485/11952 [3:12:18<8:39:13, 5.70s/it]
{'loss': 0.4502, 'learning_rate': 9.108272415709624e-06, 'epoch': 0.54}
+
54%|█████▍ | 6485/11952 [3:12:18<8:39:13, 5.70s/it]
54%|█████▍ | 6486/11952 [3:12:24<8:47:50, 5.79s/it]
{'loss': 0.4784, 'learning_rate': 9.105573339457574e-06, 'epoch': 0.54}
+
54%|█████▍ | 6486/11952 [3:12:24<8:47:50, 5.79s/it]
54%|█████▍ | 6487/11952 [3:12:30<8:49:43, 5.82s/it]
{'loss': 0.4574, 'learning_rate': 9.102874328888493e-06, 'epoch': 0.54}
+
54%|█████▍ | 6487/11952 [3:12:30<8:49:43, 5.82s/it]
54%|█████▍ | 6488/11952 [3:12:36<8:47:58, 5.80s/it]
{'loss': 0.4764, 'learning_rate': 9.100175384200595e-06, 'epoch': 0.54}
+
54%|█████▍ | 6488/11952 [3:12:36<8:47:58, 5.80s/it]
54%|█████▍ | 6489/11952 [3:12:42<8:48:15, 5.80s/it]
{'loss': 0.4746, 'learning_rate': 9.097476505592074e-06, 'epoch': 0.54}
+
54%|█████▍ | 6489/11952 [3:12:42<8:48:15, 5.80s/it]
54%|█████▍ | 6490/11952 [3:12:48<8:51:22, 5.84s/it]
{'loss': 0.4867, 'learning_rate': 9.094777693261124e-06, 'epoch': 0.54}
+
54%|█████▍ | 6490/11952 [3:12:48<8:51:22, 5.84s/it]
54%|█████▍ | 6491/11952 [3:12:54<8:56:03, 5.89s/it]
{'loss': 0.4723, 'learning_rate': 9.092078947405937e-06, 'epoch': 0.54}
+
54%|█████▍ | 6491/11952 [3:12:54<8:56:03, 5.89s/it]
54%|█████▍ | 6492/11952 [3:13:00<8:55:06, 5.88s/it]
{'loss': 0.4829, 'learning_rate': 9.089380268224694e-06, 'epoch': 0.54}
+
54%|█████▍ | 6492/11952 [3:13:00<8:55:06, 5.88s/it]
54%|█████▍ | 6493/11952 [3:13:05<8:47:46, 5.80s/it]
{'loss': 0.4703, 'learning_rate': 9.086681655915574e-06, 'epoch': 0.54}
+
54%|█████▍ | 6493/11952 [3:13:05<8:47:46, 5.80s/it]
54%|█████▍ | 6494/11952 [3:13:11<8:49:17, 5.82s/it]
{'loss': 0.4804, 'learning_rate': 9.083983110676755e-06, 'epoch': 0.54}
+
54%|█████▍ | 6494/11952 [3:13:11<8:49:17, 5.82s/it]
54%|█████▍ | 6495/11952 [3:13:17<8:48:14, 5.81s/it]
{'loss': 0.4808, 'learning_rate': 9.081284632706408e-06, 'epoch': 0.54}
+
54%|█████▍ | 6495/11952 [3:13:17<8:48:14, 5.81s/it]
54%|█████▍ | 6496/11952 [3:13:22<8:42:23, 5.74s/it]
{'loss': 0.4923, 'learning_rate': 9.078586222202698e-06, 'epoch': 0.54}
+
54%|█████▍ | 6496/11952 [3:13:22<8:42:23, 5.74s/it]
54%|█████▍ | 6497/11952 [3:13:28<8:45:49, 5.78s/it]
{'loss': 0.4779, 'learning_rate': 9.075887879363783e-06, 'epoch': 0.54}
+
54%|█████▍ | 6497/11952 [3:13:28<8:45:49, 5.78s/it]
54%|█████▍ | 6498/11952 [3:13:34<8:54:40, 5.88s/it]
{'loss': 0.4824, 'learning_rate': 9.073189604387815e-06, 'epoch': 0.54}
+
54%|█████▍ | 6498/11952 [3:13:34<8:54:40, 5.88s/it]
54%|█████▍ | 6499/11952 [3:13:40<8:46:17, 5.79s/it]
{'loss': 0.4912, 'learning_rate': 9.07049139747295e-06, 'epoch': 0.54}
+
54%|█████▍ | 6499/11952 [3:13:40<8:46:17, 5.79s/it]4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+053 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+ 2 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
54%|█████▍ | 6500/11952 [3:13:46<9:01:35, 5.96s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.477, 'learning_rate': 9.06779325881733e-06, 'epoch': 0.54}
+
54%|█████▍ | 6500/11952 [3:13:46<9:01:35, 5.96s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
54%|█████▍ | 6501/11952 [3:14:16<19:37:08, 12.96s/it]
{'loss': 0.4758, 'learning_rate': 9.065095188619096e-06, 'epoch': 0.54}
+
54%|█████▍ | 6501/11952 [3:14:16<19:37:08, 12.96s/it]
54%|█████▍ | 6502/11952 [3:14:22<16:26:26, 10.86s/it]
{'loss': 0.467, 'learning_rate': 9.062397187076384e-06, 'epoch': 0.54}
+
54%|█████▍ | 6502/11952 [3:14:22<16:26:26, 10.86s/it]
54%|█████▍ | 6503/11952 [3:14:27<14:09:19, 9.35s/it]
{'loss': 0.4954, 'learning_rate': 9.059699254387323e-06, 'epoch': 0.54}
+
54%|█████▍ | 6503/11952 [3:14:27<14:09:19, 9.35s/it]
54%|█████▍ | 6504/11952 [3:14:33<12:37:15, 8.34s/it]
{'loss': 0.4689, 'learning_rate': 9.057001390750035e-06, 'epoch': 0.54}
+
54%|█████▍ | 6504/11952 [3:14:33<12:37:15, 8.34s/it]
54%|█████▍ | 6505/11952 [3:14:39<11:31:02, 7.61s/it]
{'loss': 0.4764, 'learning_rate': 9.054303596362646e-06, 'epoch': 0.54}
+
54%|█████▍ | 6505/11952 [3:14:39<11:31:02, 7.61s/it]
54%|█████▍ | 6506/11952 [3:14:45<10:39:22, 7.04s/it]
{'loss': 0.4866, 'learning_rate': 9.051605871423266e-06, 'epoch': 0.54}
+
54%|█████▍ | 6506/11952 [3:14:45<10:39:22, 7.04s/it]
54%|█████▍ | 6507/11952 [3:14:51<10:10:28, 6.73s/it]
{'loss': 0.4834, 'learning_rate': 9.048908216130002e-06, 'epoch': 0.54}
+
54%|█████▍ | 6507/11952 [3:14:51<10:10:28, 6.73s/it]
54%|█████▍ | 6508/11952 [3:14:57<9:43:57, 6.44s/it]
{'loss': 0.4618, 'learning_rate': 9.046210630680968e-06, 'epoch': 0.54}
+
54%|█████▍ | 6508/11952 [3:14:57<9:43:57, 6.44s/it]
54%|█████▍ | 6509/11952 [3:15:03<9:25:57, 6.24s/it]
{'loss': 0.4803, 'learning_rate': 9.043513115274257e-06, 'epoch': 0.54}
+
54%|█████▍ | 6509/11952 [3:15:03<9:25:57, 6.24s/it]
54%|█████▍ | 6510/11952 [3:15:09<9:20:04, 6.17s/it]
{'loss': 0.4672, 'learning_rate': 9.040815670107964e-06, 'epoch': 0.54}
+
54%|█████▍ | 6510/11952 [3:15:09<9:20:04, 6.17s/it]
54%|█████▍ | 6511/11952 [3:15:14<9:09:20, 6.06s/it]
{'loss': 0.4937, 'learning_rate': 9.038118295380179e-06, 'epoch': 0.54}
+
54%|█████▍ | 6511/11952 [3:15:14<9:09:20, 6.06s/it]
54%|█████▍ | 6512/11952 [3:15:20<9:07:37, 6.04s/it]
{'loss': 0.4753, 'learning_rate': 9.035420991288987e-06, 'epoch': 0.54}
+
54%|█████▍ | 6512/11952 [3:15:20<9:07:37, 6.04s/it]
54%|█████▍ | 6513/11952 [3:15:26<9:10:21, 6.07s/it]
{'loss': 0.4871, 'learning_rate': 9.032723758032462e-06, 'epoch': 0.54}
+
54%|█████▍ | 6513/11952 [3:15:26<9:10:21, 6.07s/it]
55%|█████▍ | 6514/11952 [3:15:33<9:10:32, 6.07s/it]
{'loss': 0.4761, 'learning_rate': 9.030026595808682e-06, 'epoch': 0.54}
+
55%|█████▍ | 6514/11952 [3:15:33<9:10:32, 6.07s/it]
55%|█████▍ | 6515/11952 [3:15:39<9:12:14, 6.09s/it]
{'loss': 0.509, 'learning_rate': 9.027329504815714e-06, 'epoch': 0.55}
+
55%|█████▍ | 6515/11952 [3:15:39<9:12:14, 6.09s/it]
55%|█████▍ | 6516/11952 [3:15:45<9:07:14, 6.04s/it]
{'loss': 0.4935, 'learning_rate': 9.024632485251624e-06, 'epoch': 0.55}
+
55%|█████▍ | 6516/11952 [3:15:45<9:07:14, 6.04s/it]
55%|█████▍ | 6517/11952 [3:15:50<8:58:12, 5.94s/it]
{'loss': 0.4866, 'learning_rate': 9.021935537314467e-06, 'epoch': 0.55}
+
55%|█████▍ | 6517/11952 [3:15:50<8:58:12, 5.94s/it]
55%|█████▍ | 6518/11952 [3:15:56<8:53:01, 5.89s/it]
{'loss': 0.4957, 'learning_rate': 9.019238661202296e-06, 'epoch': 0.55}
+
55%|█████▍ | 6518/11952 [3:15:56<8:53:01, 5.89s/it]
55%|█████▍ | 6519/11952 [3:16:02<8:52:42, 5.88s/it]
{'loss': 0.4776, 'learning_rate': 9.016541857113157e-06, 'epoch': 0.55}
+
55%|█████▍ | 6519/11952 [3:16:02<8:52:42, 5.88s/it]
55%|█████▍ | 6520/11952 [3:16:08<8:44:44, 5.80s/it]
{'loss': 0.4852, 'learning_rate': 9.013845125245095e-06, 'epoch': 0.55}
+
55%|█████▍ | 6520/11952 [3:16:08<8:44:44, 5.80s/it]
55%|█████▍ | 6521/11952 [3:16:13<8:45:04, 5.80s/it]
{'loss': 0.4643, 'learning_rate': 9.01114846579614e-06, 'epoch': 0.55}
+
55%|█████▍ | 6521/11952 [3:16:13<8:45:04, 5.80s/it]
55%|█████▍ | 6522/11952 [3:16:19<8:48:11, 5.84s/it]
{'loss': 0.4801, 'learning_rate': 9.008451878964336e-06, 'epoch': 0.55}
+
55%|█████▍ | 6522/11952 [3:16:19<8:48:11, 5.84s/it]
55%|█████▍ | 6523/11952 [3:16:25<8:51:39, 5.88s/it]
{'loss': 0.4683, 'learning_rate': 9.005755364947699e-06, 'epoch': 0.55}
+
55%|█████▍ | 6523/11952 [3:16:25<8:51:39, 5.88s/it]
55%|█████▍ | 6524/11952 [3:16:31<8:45:58, 5.81s/it]
{'loss': 0.4803, 'learning_rate': 9.00305892394425e-06, 'epoch': 0.55}
+
55%|█████▍ | 6524/11952 [3:16:31<8:45:58, 5.81s/it]
55%|█████▍ | 6525/11952 [3:16:37<8:48:24, 5.84s/it]
{'loss': 0.4789, 'learning_rate': 9.000362556152013e-06, 'epoch': 0.55}
+
55%|█████▍ | 6525/11952 [3:16:37<8:48:24, 5.84s/it]
55%|█████▍ | 6526/11952 [3:16:43<8:59:04, 5.96s/it]
{'loss': 0.4686, 'learning_rate': 8.997666261768989e-06, 'epoch': 0.55}
+
55%|█████▍ | 6526/11952 [3:16:43<8:59:04, 5.96s/it]
55%|█████▍ | 6527/11952 [3:16:49<9:02:10, 6.00s/it]
{'loss': 0.5007, 'learning_rate': 8.994970040993187e-06, 'epoch': 0.55}
+
55%|█████▍ | 6527/11952 [3:16:49<9:02:10, 6.00s/it]
55%|█████▍ | 6528/11952 [3:16:55<9:00:40, 5.98s/it]
{'loss': 0.4736, 'learning_rate': 8.9922738940226e-06, 'epoch': 0.55}
+
55%|█████▍ | 6528/11952 [3:16:55<9:00:40, 5.98s/it]
55%|█████▍ | 6529/11952 [3:17:01<9:00:52, 5.98s/it]
{'loss': 0.4812, 'learning_rate': 8.989577821055231e-06, 'epoch': 0.55}
+
55%|█████▍ | 6529/11952 [3:17:01<9:00:52, 5.98s/it]
55%|█████▍ | 6530/11952 [3:17:07<9:00:14, 5.98s/it]
{'loss': 0.49, 'learning_rate': 8.986881822289062e-06, 'epoch': 0.55}
+
55%|█████▍ | 6530/11952 [3:17:07<9:00:14, 5.98s/it]
55%|█████▍ | 6531/11952 [3:17:13<8:59:09, 5.97s/it]
{'loss': 0.4833, 'learning_rate': 8.98418589792208e-06, 'epoch': 0.55}
+
55%|█████▍ | 6531/11952 [3:17:13<8:59:09, 5.97s/it]
55%|█████▍ | 6532/11952 [3:17:19<9:05:15, 6.04s/it]
{'loss': 0.4741, 'learning_rate': 8.98149004815226e-06, 'epoch': 0.55}
+
55%|█████▍ | 6532/11952 [3:17:19<9:05:15, 6.04s/it]
55%|█████▍ | 6533/11952 [3:17:25<8:53:48, 5.91s/it]
{'loss': 0.4823, 'learning_rate': 8.978794273177576e-06, 'epoch': 0.55}
+
55%|█████▍ | 6533/11952 [3:17:25<8:53:48, 5.91s/it]
55%|█████▍ | 6534/11952 [3:17:31<8:52:08, 5.89s/it]
{'loss': 0.4539, 'learning_rate': 8.97609857319599e-06, 'epoch': 0.55}
+
55%|█████▍ | 6534/11952 [3:17:31<8:52:08, 5.89s/it]
55%|█████▍ | 6535/11952 [3:17:36<8:49:29, 5.86s/it]
{'loss': 0.4686, 'learning_rate': 8.973402948405466e-06, 'epoch': 0.55}
+
55%|█████▍ | 6535/11952 [3:17:36<8:49:29, 5.86s/it]
55%|█████▍ | 6536/11952 [3:17:42<8:44:11, 5.81s/it]
{'loss': 0.4727, 'learning_rate': 8.970707399003961e-06, 'epoch': 0.55}
+
55%|█████▍ | 6536/11952 [3:17:42<8:44:11, 5.81s/it]
55%|█████▍ | 6537/11952 [3:17:48<8:43:41, 5.80s/it]
{'loss': 0.4807, 'learning_rate': 8.968011925189426e-06, 'epoch': 0.55}
+
55%|█████▍ | 6537/11952 [3:17:48<8:43:41, 5.80s/it]
55%|█████▍ | 6538/11952 [3:17:54<8:40:53, 5.77s/it]
{'loss': 0.4661, 'learning_rate': 8.9653165271598e-06, 'epoch': 0.55}
+
55%|█████▍ | 6538/11952 [3:17:54<8:40:53, 5.77s/it]
55%|█████▍ | 6539/11952 [3:17:59<8:41:13, 5.78s/it]
{'loss': 0.4563, 'learning_rate': 8.962621205113025e-06, 'epoch': 0.55}
+
55%|█████▍ | 6539/11952 [3:17:59<8:41:13, 5.78s/it]
55%|█████▍ | 6540/11952 [3:18:05<8:48:37, 5.86s/it]
{'loss': 0.4915, 'learning_rate': 8.959925959247036e-06, 'epoch': 0.55}
+
55%|█████▍ | 6540/11952 [3:18:05<8:48:37, 5.86s/it]
55%|█████▍ | 6541/11952 [3:18:11<8:45:12, 5.82s/it]
{'loss': 0.4776, 'learning_rate': 8.957230789759752e-06, 'epoch': 0.55}
+
55%|█████▍ | 6541/11952 [3:18:11<8:45:12, 5.82s/it]
55%|█████▍ | 6542/11952 [3:18:17<8:46:06, 5.83s/it]
{'loss': 0.4824, 'learning_rate': 8.954535696849108e-06, 'epoch': 0.55}
+
55%|█████▍ | 6542/11952 [3:18:17<8:46:06, 5.83s/it]
55%|█████▍ | 6543/11952 [3:18:23<8:47:06, 5.85s/it]
{'loss': 0.4858, 'learning_rate': 8.951840680713013e-06, 'epoch': 0.55}
+
55%|█████▍ | 6543/11952 [3:18:23<8:47:06, 5.85s/it]
55%|█████▍ | 6544/11952 [3:18:28<8:38:48, 5.76s/it]
{'loss': 0.4641, 'learning_rate': 8.949145741549378e-06, 'epoch': 0.55}
+
55%|█████▍ | 6544/11952 [3:18:28<8:38:48, 5.76s/it]
55%|█████▍ | 6545/11952 [3:18:34<8:41:12, 5.78s/it]
{'loss': 0.4672, 'learning_rate': 8.946450879556108e-06, 'epoch': 0.55}
+
55%|█████▍ | 6545/11952 [3:18:34<8:41:12, 5.78s/it]
55%|█████▍ | 6546/11952 [3:18:40<8:47:04, 5.85s/it]
{'loss': 0.4964, 'learning_rate': 8.943756094931106e-06, 'epoch': 0.55}
+
55%|█████▍ | 6546/11952 [3:18:40<8:47:04, 5.85s/it]
55%|█████▍ | 6547/11952 [3:18:46<8:44:08, 5.82s/it]
{'loss': 0.4896, 'learning_rate': 8.941061387872263e-06, 'epoch': 0.55}
+
55%|█████▍ | 6547/11952 [3:18:46<8:44:08, 5.82s/it]
55%|█████▍ | 6548/11952 [3:18:52<8:46:43, 5.85s/it]
{'loss': 0.4759, 'learning_rate': 8.938366758577462e-06, 'epoch': 0.55}
+
55%|█████▍ | 6548/11952 [3:18:52<8:46:43, 5.85s/it]
55%|█████▍ | 6549/11952 [3:18:58<8:44:16, 5.82s/it]
{'loss': 0.4772, 'learning_rate': 8.935672207244596e-06, 'epoch': 0.55}
+
55%|█████▍ | 6549/11952 [3:18:58<8:44:16, 5.82s/it]02 AutoResumeHook: Checking whether to suspend...
+ 6 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+3 AutoResumeHook: Checking whether to suspend...
+
55%|█████▍ | 6550/11952 [3:19:04<8:45:13, 5.83s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4732, 'learning_rate': 8.932977734071533e-06, 'epoch': 0.55}
+
55%|█████▍ | 6550/11952 [3:19:04<8:45:13, 5.83s/it]
55%|█████▍ | 6551/11952 [3:19:10<8:48:38, 5.87s/it]
{'loss': 0.4791, 'learning_rate': 8.93028333925615e-06, 'epoch': 0.55}
+
55%|█████▍ | 6551/11952 [3:19:10<8:48:38, 5.87s/it]
55%|█████▍ | 6552/11952 [3:19:15<8:49:28, 5.88s/it]
{'loss': 0.4696, 'learning_rate': 8.927589022996308e-06, 'epoch': 0.55}
+
55%|█████▍ | 6552/11952 [3:19:15<8:49:28, 5.88s/it]
55%|█████▍ | 6553/11952 [3:19:21<8:48:31, 5.87s/it]
{'loss': 0.4734, 'learning_rate': 8.92489478548987e-06, 'epoch': 0.55}
+
55%|█████▍ | 6553/11952 [3:19:21<8:48:31, 5.87s/it]
55%|█████▍ | 6554/11952 [3:19:27<8:46:33, 5.85s/it]
{'loss': 0.4917, 'learning_rate': 8.922200626934682e-06, 'epoch': 0.55}
+
55%|█████▍ | 6554/11952 [3:19:27<8:46:33, 5.85s/it]
55%|█████▍ | 6555/11952 [3:19:33<8:50:09, 5.89s/it]
{'loss': 0.4855, 'learning_rate': 8.919506547528599e-06, 'epoch': 0.55}
+
55%|█████▍ | 6555/11952 [3:19:33<8:50:09, 5.89s/it]
55%|█████▍ | 6556/11952 [3:19:39<8:57:41, 5.98s/it]
{'loss': 0.4893, 'learning_rate': 8.916812547469461e-06, 'epoch': 0.55}
+
55%|█████▍ | 6556/11952 [3:19:39<8:57:41, 5.98s/it]
55%|█████▍ | 6557/11952 [3:19:45<8:56:02, 5.96s/it]
{'loss': 0.4473, 'learning_rate': 8.914118626955106e-06, 'epoch': 0.55}
+
55%|█████▍ | 6557/11952 [3:19:45<8:56:02, 5.96s/it]
55%|█████▍ | 6558/11952 [3:19:51<8:53:09, 5.93s/it]
{'loss': 0.4829, 'learning_rate': 8.911424786183362e-06, 'epoch': 0.55}
+
55%|█████▍ | 6558/11952 [3:19:51<8:53:09, 5.93s/it]
55%|█████▍ | 6559/11952 [3:19:57<9:00:30, 6.01s/it]
{'loss': 0.4882, 'learning_rate': 8.908731025352055e-06, 'epoch': 0.55}
+
55%|█████▍ | 6559/11952 [3:19:57<9:00:30, 6.01s/it]
55%|█████▍ | 6560/11952 [3:20:03<8:53:29, 5.94s/it]
{'loss': 0.4827, 'learning_rate': 8.906037344659e-06, 'epoch': 0.55}
+
55%|█████▍ | 6560/11952 [3:20:03<8:53:29, 5.94s/it]
55%|█████▍ | 6561/11952 [3:20:10<9:08:21, 6.10s/it]
{'loss': 0.469, 'learning_rate': 8.903343744302016e-06, 'epoch': 0.55}
+
55%|█████▍ | 6561/11952 [3:20:10<9:08:21, 6.10s/it]
55%|█████▍ | 6562/11952 [3:20:15<9:03:07, 6.05s/it]
{'loss': 0.4783, 'learning_rate': 8.900650224478899e-06, 'epoch': 0.55}
+
55%|█████▍ | 6562/11952 [3:20:15<9:03:07, 6.05s/it]
55%|█████▍ | 6563/11952 [3:20:21<8:53:54, 5.94s/it]
{'loss': 0.4845, 'learning_rate': 8.897956785387463e-06, 'epoch': 0.55}
+
55%|█████▍ | 6563/11952 [3:20:21<8:53:54, 5.94s/it]
55%|█████▍ | 6564/11952 [3:20:27<8:53:23, 5.94s/it]
{'loss': 0.4707, 'learning_rate': 8.895263427225497e-06, 'epoch': 0.55}
+
55%|█████▍ | 6564/11952 [3:20:27<8:53:23, 5.94s/it]
55%|█████▍ | 6565/11952 [3:20:33<8:52:05, 5.93s/it]
{'loss': 0.4974, 'learning_rate': 8.89257015019079e-06, 'epoch': 0.55}
+
55%|█████▍ | 6565/11952 [3:20:33<8:52:05, 5.93s/it]
55%|█████▍ | 6566/11952 [3:20:39<8:49:31, 5.90s/it]
{'loss': 0.4709, 'learning_rate': 8.889876954481122e-06, 'epoch': 0.55}
+
55%|█████▍ | 6566/11952 [3:20:39<8:49:31, 5.90s/it]
55%|█████▍ | 6567/11952 [3:20:44<8:38:22, 5.78s/it]
{'loss': 0.4527, 'learning_rate': 8.887183840294274e-06, 'epoch': 0.55}
+
55%|█████▍ | 6567/11952 [3:20:44<8:38:22, 5.78s/it]
55%|█████▍ | 6568/11952 [3:20:50<8:37:24, 5.77s/it]
{'loss': 0.4861, 'learning_rate': 8.88449080782802e-06, 'epoch': 0.55}
+
55%|█████▍ | 6568/11952 [3:20:50<8:37:24, 5.77s/it]
55%|█████▍ | 6569/11952 [3:20:56<8:35:58, 5.75s/it]
{'loss': 0.4684, 'learning_rate': 8.881797857280113e-06, 'epoch': 0.55}
+
55%|█████▍ | 6569/11952 [3:20:56<8:35:58, 5.75s/it]
55%|█████▍ | 6570/11952 [3:21:02<8:36:53, 5.76s/it]
{'loss': 0.4724, 'learning_rate': 8.879104988848326e-06, 'epoch': 0.55}
+
55%|█████▍ | 6570/11952 [3:21:02<8:36:53, 5.76s/it]
55%|█████▍ | 6571/11952 [3:21:07<8:35:29, 5.75s/it]
{'loss': 0.4827, 'learning_rate': 8.876412202730405e-06, 'epoch': 0.55}
+
55%|█████▍ | 6571/11952 [3:21:07<8:35:29, 5.75s/it]
55%|█████▍ | 6572/11952 [3:21:13<8:43:44, 5.84s/it]
{'loss': 0.4686, 'learning_rate': 8.873719499124101e-06, 'epoch': 0.55}
+
55%|█████▍ | 6572/11952 [3:21:13<8:43:44, 5.84s/it]
55%|█████▍ | 6573/11952 [3:21:19<8:49:21, 5.90s/it]
{'loss': 0.4915, 'learning_rate': 8.871026878227151e-06, 'epoch': 0.55}
+
55%|█████▍ | 6573/11952 [3:21:19<8:49:21, 5.90s/it]
55%|█████▌ | 6574/11952 [3:21:25<8:47:29, 5.89s/it]
{'loss': 0.4946, 'learning_rate': 8.868334340237293e-06, 'epoch': 0.55}
+
55%|█████▌ | 6574/11952 [3:21:25<8:47:29, 5.89s/it]
55%|█████▌ | 6575/11952 [3:21:31<8:46:00, 5.87s/it]
{'loss': 0.4845, 'learning_rate': 8.86564188535225e-06, 'epoch': 0.55}
+
55%|█████▌ | 6575/11952 [3:21:31<8:46:00, 5.87s/it]
55%|█████▌ | 6576/11952 [3:21:37<8:38:45, 5.79s/it]
{'loss': 0.4632, 'learning_rate': 8.86294951376975e-06, 'epoch': 0.55}
+
55%|█████▌ | 6576/11952 [3:21:37<8:38:45, 5.79s/it]
55%|█████▌ | 6577/11952 [3:21:42<8:36:18, 5.76s/it]
{'loss': 0.4733, 'learning_rate': 8.86025722568751e-06, 'epoch': 0.55}
+
55%|█████▌ | 6577/11952 [3:21:42<8:36:18, 5.76s/it]
55%|█████▌ | 6578/11952 [3:21:48<8:37:50, 5.78s/it]
{'loss': 0.4629, 'learning_rate': 8.857565021303238e-06, 'epoch': 0.55}
+
55%|█████▌ | 6578/11952 [3:21:48<8:37:50, 5.78s/it]
55%|█████▌ | 6579/11952 [3:21:54<8:40:18, 5.81s/it]
{'loss': 0.4984, 'learning_rate': 8.85487290081464e-06, 'epoch': 0.55}
+
55%|█████▌ | 6579/11952 [3:21:54<8:40:18, 5.81s/it]
55%|█████▌ | 6580/11952 [3:22:00<8:37:40, 5.78s/it]
{'loss': 0.4787, 'learning_rate': 8.852180864419413e-06, 'epoch': 0.55}
+
55%|█████▌ | 6580/11952 [3:22:00<8:37:40, 5.78s/it]
55%|█████▌ | 6581/11952 [3:22:06<8:38:01, 5.79s/it]
{'loss': 0.4913, 'learning_rate': 8.84948891231525e-06, 'epoch': 0.55}
+
55%|█████▌ | 6581/11952 [3:22:06<8:38:01, 5.79s/it]
55%|█████▌ | 6582/11952 [3:22:11<8:31:48, 5.72s/it]
{'loss': 0.4955, 'learning_rate': 8.846797044699831e-06, 'epoch': 0.55}
+
55%|█████▌ | 6582/11952 [3:22:11<8:31:48, 5.72s/it]
55%|█████▌ | 6583/11952 [3:22:17<8:42:43, 5.84s/it]
{'loss': 0.478, 'learning_rate': 8.844105261770844e-06, 'epoch': 0.55}
+
55%|█████▌ | 6583/11952 [3:22:17<8:42:43, 5.84s/it]
55%|█████▌ | 6584/11952 [3:22:23<8:37:57, 5.79s/it]
{'loss': 0.4816, 'learning_rate': 8.84141356372596e-06, 'epoch': 0.55}
+
55%|█████▌ | 6584/11952 [3:22:23<8:37:57, 5.79s/it]
55%|█████▌ | 6585/11952 [3:22:29<8:43:59, 5.86s/it]
{'loss': 0.4711, 'learning_rate': 8.838721950762845e-06, 'epoch': 0.55}
+
55%|█████▌ | 6585/11952 [3:22:29<8:43:59, 5.86s/it]
55%|█████▌ | 6586/11952 [3:22:35<8:38:00, 5.79s/it]
{'loss': 0.4757, 'learning_rate': 8.836030423079157e-06, 'epoch': 0.55}
+
55%|█████▌ | 6586/11952 [3:22:35<8:38:00, 5.79s/it]
55%|█████▌ | 6587/11952 [3:22:40<8:39:21, 5.81s/it]
{'loss': 0.4635, 'learning_rate': 8.833338980872558e-06, 'epoch': 0.55}
+
55%|█████▌ | 6587/11952 [3:22:40<8:39:21, 5.81s/it]
55%|█████▌ | 6588/11952 [3:22:46<8:40:55, 5.83s/it]
{'loss': 0.4623, 'learning_rate': 8.830647624340689e-06, 'epoch': 0.55}
+
55%|█████▌ | 6588/11952 [3:22:46<8:40:55, 5.83s/it]
55%|█████▌ | 6589/11952 [3:22:52<8:31:56, 5.73s/it]
{'loss': 0.4898, 'learning_rate': 8.827956353681191e-06, 'epoch': 0.55}
+
55%|█████▌ | 6589/11952 [3:22:52<8:31:56, 5.73s/it]
55%|█████▌ | 6590/11952 [3:22:58<8:42:55, 5.85s/it]
{'loss': 0.4753, 'learning_rate': 8.82526516909171e-06, 'epoch': 0.55}
+
55%|█████▌ | 6590/11952 [3:22:58<8:42:55, 5.85s/it]
55%|█████▌ | 6591/11952 [3:23:04<8:48:15, 5.91s/it]
{'loss': 0.4799, 'learning_rate': 8.822574070769867e-06, 'epoch': 0.55}
+
55%|█████▌ | 6591/11952 [3:23:04<8:48:15, 5.91s/it]
55%|█████▌ | 6592/11952 [3:23:10<8:43:14, 5.86s/it]
{'loss': 0.4814, 'learning_rate': 8.819883058913285e-06, 'epoch': 0.55}
+
55%|█████▌ | 6592/11952 [3:23:10<8:43:14, 5.86s/it]
55%|█████▌ | 6593/11952 [3:23:16<8:45:28, 5.88s/it]
{'loss': 0.5005, 'learning_rate': 8.817192133719583e-06, 'epoch': 0.55}
+
55%|█████▌ | 6593/11952 [3:23:16<8:45:28, 5.88s/it]
55%|█████▌ | 6594/11952 [3:23:22<8:44:11, 5.87s/it]
{'loss': 0.4939, 'learning_rate': 8.814501295386373e-06, 'epoch': 0.55}
+
55%|█████▌ | 6594/11952 [3:23:22<8:44:11, 5.87s/it]
55%|█████▌ | 6595/11952 [3:23:27<8:41:35, 5.84s/it]
{'loss': 0.4781, 'learning_rate': 8.811810544111258e-06, 'epoch': 0.55}
+
55%|█████▌ | 6595/11952 [3:23:27<8:41:35, 5.84s/it]
55%|█████▌ | 6596/11952 [3:23:33<8:33:29, 5.75s/it]
{'loss': 0.4704, 'learning_rate': 8.809119880091829e-06, 'epoch': 0.55}
+
55%|█████▌ | 6596/11952 [3:23:33<8:33:29, 5.75s/it]
55%|█████▌ | 6597/11952 [3:23:39<8:32:27, 5.74s/it]
{'loss': 0.4791, 'learning_rate': 8.806429303525685e-06, 'epoch': 0.55}
+
55%|█████▌ | 6597/11952 [3:23:39<8:32:27, 5.74s/it]
55%|█████▌ | 6598/11952 [3:23:44<8:34:21, 5.76s/it]
{'loss': 0.4631, 'learning_rate': 8.803738814610409e-06, 'epoch': 0.55}
+
55%|█████▌ | 6598/11952 [3:23:44<8:34:21, 5.76s/it]
55%|█████▌ | 6599/11952 [3:23:50<8:36:56, 5.79s/it]
{'loss': 0.4904, 'learning_rate': 8.801048413543581e-06, 'epoch': 0.55}
+
55%|█████▌ | 6599/11952 [3:23:50<8:36:56, 5.79s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
55%|█████▌ | 6600/11952 [3:23:56<8:41:37, 5.85s/it]5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4783, 'learning_rate': 8.79835810052277e-06, 'epoch': 0.55}
+
55%|█████▌ | 6600/11952 [3:23:56<8:41:37, 5.85s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
55%|█████▌ | 6601/11952 [3:24:26<19:33:01, 13.15s/it]
{'loss': 0.4744, 'learning_rate': 8.79566787574554e-06, 'epoch': 0.55}
+
55%|█████▌ | 6601/11952 [3:24:26<19:33:01, 13.15s/it]
55%|█████▌ | 6602/11952 [3:24:33<16:28:42, 11.09s/it]
{'loss': 0.4782, 'learning_rate': 8.792977739409455e-06, 'epoch': 0.55}
+
55%|█████▌ | 6602/11952 [3:24:33<16:28:42, 11.09s/it]
55%|█████▌ | 6603/11952 [3:24:38<14:07:33, 9.51s/it]
{'loss': 0.478, 'learning_rate': 8.790287691712059e-06, 'epoch': 0.55}
+
55%|█████▌ | 6603/11952 [3:24:38<14:07:33, 9.51s/it]
55%|█████▌ | 6604/11952 [3:24:44<12:25:44, 8.37s/it]
{'loss': 0.4799, 'learning_rate': 8.78759773285091e-06, 'epoch': 0.55}
+
55%|█████▌ | 6604/11952 [3:24:44<12:25:44, 8.37s/it]
55%|█████▌ | 6605/11952 [3:24:50<11:23:29, 7.67s/it]
{'loss': 0.4553, 'learning_rate': 8.784907863023537e-06, 'epoch': 0.55}
+
55%|█████▌ | 6605/11952 [3:24:50<11:23:29, 7.67s/it]
55%|█████▌ | 6606/11952 [3:24:56<10:27:36, 7.04s/it]
{'loss': 0.4705, 'learning_rate': 8.782218082427478e-06, 'epoch': 0.55}
+
55%|█████▌ | 6606/11952 [3:24:56<10:27:36, 7.04s/it]
55%|█████▌ | 6607/11952 [3:25:02<9:52:37, 6.65s/it]
{'loss': 0.4689, 'learning_rate': 8.779528391260257e-06, 'epoch': 0.55}
+
55%|█████▌ | 6607/11952 [3:25:02<9:52:37, 6.65s/it]
55%|█████▌ | 6608/11952 [3:25:07<9:30:31, 6.41s/it]
{'loss': 0.4538, 'learning_rate': 8.776838789719396e-06, 'epoch': 0.55}
+
55%|█████▌ | 6608/11952 [3:25:07<9:30:31, 6.41s/it]
55%|█████▌ | 6609/11952 [3:25:13<9:20:04, 6.29s/it]
{'loss': 0.4857, 'learning_rate': 8.774149278002402e-06, 'epoch': 0.55}
+
55%|█████▌ | 6609/11952 [3:25:13<9:20:04, 6.29s/it]
55%|█████▌ | 6610/11952 [3:25:19<9:00:44, 6.07s/it]
{'loss': 0.4831, 'learning_rate': 8.771459856306791e-06, 'epoch': 0.55}
+
55%|█████▌ | 6610/11952 [3:25:19<9:00:44, 6.07s/it]
55%|█████▌ | 6611/11952 [3:25:25<8:57:57, 6.04s/it]
{'loss': 0.4744, 'learning_rate': 8.768770524830058e-06, 'epoch': 0.55}
+
55%|█████▌ | 6611/11952 [3:25:25<8:57:57, 6.04s/it]
55%|█████▌ | 6612/11952 [3:25:31<8:49:20, 5.95s/it]
{'loss': 0.4704, 'learning_rate': 8.766081283769695e-06, 'epoch': 0.55}
+
55%|█████▌ | 6612/11952 [3:25:31<8:49:20, 5.95s/it]
55%|█████▌ | 6613/11952 [3:25:37<8:48:46, 5.94s/it]
{'loss': 0.476, 'learning_rate': 8.763392133323192e-06, 'epoch': 0.55}
+
55%|█████▌ | 6613/11952 [3:25:37<8:48:46, 5.94s/it]
55%|█████▌ | 6614/11952 [3:25:43<8:56:44, 6.03s/it]
{'loss': 0.4742, 'learning_rate': 8.760703073688027e-06, 'epoch': 0.55}
+
55%|█████▌ | 6614/11952 [3:25:43<8:56:44, 6.03s/it]
55%|█████▌ | 6615/11952 [3:25:49<8:48:14, 5.94s/it]
{'loss': 0.469, 'learning_rate': 8.758014105061674e-06, 'epoch': 0.55}
+
55%|█████▌ | 6615/11952 [3:25:49<8:48:14, 5.94s/it]
55%|█████▌ | 6616/11952 [3:25:55<8:53:20, 6.00s/it]
{'loss': 0.4838, 'learning_rate': 8.755325227641596e-06, 'epoch': 0.55}
+
55%|█████▌ | 6616/11952 [3:25:55<8:53:20, 6.00s/it]
55%|█████▌ | 6617/11952 [3:26:01<8:57:16, 6.04s/it]
{'loss': 0.4951, 'learning_rate': 8.752636441625259e-06, 'epoch': 0.55}
+
55%|█████▌ | 6617/11952 [3:26:01<8:57:16, 6.04s/it]
55%|█████▌ | 6618/11952 [3:26:07<8:49:16, 5.95s/it]
{'loss': 0.4718, 'learning_rate': 8.749947747210112e-06, 'epoch': 0.55}
+
55%|█████▌ | 6618/11952 [3:26:07<8:49:16, 5.95s/it]
55%|█████▌ | 6619/11952 [3:26:12<8:43:55, 5.89s/it]
{'loss': 0.4653, 'learning_rate': 8.747259144593604e-06, 'epoch': 0.55}
+
55%|█████▌ | 6619/11952 [3:26:12<8:43:55, 5.89s/it]
55%|█████▌ | 6620/11952 [3:26:18<8:45:17, 5.91s/it]
{'loss': 0.472, 'learning_rate': 8.744570633973177e-06, 'epoch': 0.55}
+
55%|█████▌ | 6620/11952 [3:26:18<8:45:17, 5.91s/it]
55%|█████▌ | 6621/11952 [3:26:24<8:42:17, 5.88s/it]
{'loss': 0.4854, 'learning_rate': 8.741882215546259e-06, 'epoch': 0.55}
+
55%|█████▌ | 6621/11952 [3:26:24<8:42:17, 5.88s/it]
55%|█████▌ | 6622/11952 [3:26:30<8:35:11, 5.80s/it]
{'loss': 0.4681, 'learning_rate': 8.739193889510276e-06, 'epoch': 0.55}
+
55%|█████▌ | 6622/11952 [3:26:30<8:35:11, 5.80s/it]
55%|█████▌ | 6623/11952 [3:26:36<8:40:32, 5.86s/it]
{'loss': 0.4679, 'learning_rate': 8.736505656062648e-06, 'epoch': 0.55}
+
55%|█████▌ | 6623/11952 [3:26:36<8:40:32, 5.86s/it]
55%|█████▌ | 6624/11952 [3:26:42<8:44:03, 5.90s/it]
{'loss': 0.4907, 'learning_rate': 8.733817515400793e-06, 'epoch': 0.55}
+
55%|█████▌ | 6624/11952 [3:26:42<8:44:03, 5.90s/it]
55%|█████▌ | 6625/11952 [3:26:48<8:49:00, 5.96s/it]
{'loss': 0.4657, 'learning_rate': 8.731129467722113e-06, 'epoch': 0.55}
+
55%|█████▌ | 6625/11952 [3:26:48<8:49:00, 5.96s/it]
55%|█████▌ | 6626/11952 [3:26:54<8:45:43, 5.92s/it]
{'loss': 0.4657, 'learning_rate': 8.728441513224008e-06, 'epoch': 0.55}
+
55%|█████▌ | 6626/11952 [3:26:54<8:45:43, 5.92s/it]
55%|█████▌ | 6627/11952 [3:27:00<8:43:48, 5.90s/it]
{'loss': 0.4826, 'learning_rate': 8.725753652103868e-06, 'epoch': 0.55}
+
55%|█████▌ | 6627/11952 [3:27:00<8:43:48, 5.90s/it]
55%|█████▌ | 6628/11952 [3:27:05<8:39:03, 5.85s/it]
{'loss': 0.4653, 'learning_rate': 8.72306588455908e-06, 'epoch': 0.55}
+
55%|█████▌ | 6628/11952 [3:27:05<8:39:03, 5.85s/it]
55%|█████▌ | 6629/11952 [3:27:11<8:44:57, 5.92s/it]
{'loss': 0.4729, 'learning_rate': 8.720378210787024e-06, 'epoch': 0.55}
+
55%|█████▌ | 6629/11952 [3:27:11<8:44:57, 5.92s/it]
55%|█████▌ | 6630/11952 [3:27:17<8:39:34, 5.86s/it]
{'loss': 0.4685, 'learning_rate': 8.717690630985065e-06, 'epoch': 0.55}
+
55%|█████▌ | 6630/11952 [3:27:17<8:39:34, 5.86s/it]
55%|█████▌ | 6631/11952 [3:27:23<8:49:08, 5.97s/it]
{'loss': 0.4579, 'learning_rate': 8.715003145350576e-06, 'epoch': 0.55}
+
55%|█████▌ | 6631/11952 [3:27:23<8:49:08, 5.97s/it]
55%|█████▌ | 6632/11952 [3:27:29<8:49:14, 5.97s/it]
{'loss': 0.4743, 'learning_rate': 8.712315754080913e-06, 'epoch': 0.55}
+
55%|█████▌ | 6632/11952 [3:27:29<8:49:14, 5.97s/it]
55%|█████▌ | 6633/11952 [3:27:35<8:46:28, 5.94s/it]
{'loss': 0.4584, 'learning_rate': 8.709628457373421e-06, 'epoch': 0.55}
+
55%|█████▌ | 6633/11952 [3:27:35<8:46:28, 5.94s/it]
56%|█████▌ | 6634/11952 [3:27:41<8:42:35, 5.90s/it]
{'loss': 0.4803, 'learning_rate': 8.706941255425452e-06, 'epoch': 0.56}
+
56%|█████▌ | 6634/11952 [3:27:41<8:42:35, 5.90s/it]
56%|█████▌ | 6635/11952 [3:27:47<8:36:27, 5.83s/it]
{'loss': 0.4585, 'learning_rate': 8.704254148434338e-06, 'epoch': 0.56}
+
56%|█████▌ | 6635/11952 [3:27:47<8:36:27, 5.83s/it]
56%|█████▌ | 6636/11952 [3:27:52<8:34:58, 5.81s/it]
{'loss': 0.4726, 'learning_rate': 8.70156713659741e-06, 'epoch': 0.56}
+
56%|█████▌ | 6636/11952 [3:27:52<8:34:58, 5.81s/it]
56%|█████▌ | 6637/11952 [3:27:58<8:30:33, 5.76s/it]
{'loss': 0.4588, 'learning_rate': 8.698880220111987e-06, 'epoch': 0.56}
+
56%|█████▌ | 6637/11952 [3:27:58<8:30:33, 5.76s/it]
56%|█████▌ | 6638/11952 [3:28:04<8:30:31, 5.76s/it]
{'loss': 0.4938, 'learning_rate': 8.69619339917539e-06, 'epoch': 0.56}
+
56%|█████▌ | 6638/11952 [3:28:04<8:30:31, 5.76s/it]
56%|█████▌ | 6639/11952 [3:28:09<8:30:02, 5.76s/it]
{'loss': 0.4575, 'learning_rate': 8.69350667398493e-06, 'epoch': 0.56}
+
56%|█████▌ | 6639/11952 [3:28:09<8:30:02, 5.76s/it]
56%|█████▌ | 6640/11952 [3:28:16<8:39:40, 5.87s/it]
{'loss': 0.4914, 'learning_rate': 8.690820044737905e-06, 'epoch': 0.56}
+
56%|█████▌ | 6640/11952 [3:28:16<8:39:40, 5.87s/it]
56%|█████▌ | 6641/11952 [3:28:21<8:34:19, 5.81s/it]
{'loss': 0.4948, 'learning_rate': 8.688133511631611e-06, 'epoch': 0.56}
+
56%|█████▌ | 6641/11952 [3:28:21<8:34:19, 5.81s/it]
56%|█████▌ | 6642/11952 [3:28:27<8:42:01, 5.90s/it]
{'loss': 0.4842, 'learning_rate': 8.685447074863333e-06, 'epoch': 0.56}
+
56%|█████▌ | 6642/11952 [3:28:27<8:42:01, 5.90s/it]
56%|█████▌ | 6643/11952 [3:28:33<8:37:54, 5.85s/it]
{'loss': 0.4749, 'learning_rate': 8.682760734630357e-06, 'epoch': 0.56}
+
56%|█████▌ | 6643/11952 [3:28:33<8:37:54, 5.85s/it]
56%|█████▌ | 6644/11952 [3:28:39<8:36:49, 5.84s/it]
{'loss': 0.4753, 'learning_rate': 8.68007449112995e-06, 'epoch': 0.56}
+
56%|█████▌ | 6644/11952 [3:28:39<8:36:49, 5.84s/it]
56%|█████▌ | 6645/11952 [3:28:45<8:33:03, 5.80s/it]
{'loss': 0.4793, 'learning_rate': 8.677388344559386e-06, 'epoch': 0.56}
+
56%|█████▌ | 6645/11952 [3:28:45<8:33:03, 5.80s/it]
56%|█████▌ | 6646/11952 [3:28:50<8:30:47, 5.78s/it]
{'loss': 0.4646, 'learning_rate': 8.67470229511592e-06, 'epoch': 0.56}
+
56%|█████▌ | 6646/11952 [3:28:50<8:30:47, 5.78s/it]
56%|█████▌ | 6647/11952 [3:28:56<8:35:00, 5.82s/it]
{'loss': 0.4625, 'learning_rate': 8.672016342996805e-06, 'epoch': 0.56}
+
56%|█████▌ | 6647/11952 [3:28:56<8:35:00, 5.82s/it]
56%|█████▌ | 6648/11952 [3:29:02<8:42:03, 5.91s/it]
{'loss': 0.4775, 'learning_rate': 8.669330488399286e-06, 'epoch': 0.56}
+
56%|█████▌ | 6648/11952 [3:29:02<8:42:03, 5.91s/it]
56%|█████▌ | 6649/11952 [3:29:08<8:38:16, 5.86s/it]
{'loss': 0.4756, 'learning_rate': 8.6666447315206e-06, 'epoch': 0.56}
+
56%|█████▌ | 6649/11952 [3:29:08<8:38:16, 5.86s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
56%|█████▌ | 6650/11952 [3:29:14<8:43:37, 5.93s/it]5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4676, 'learning_rate': 8.663959072557979e-06, 'epoch': 0.56}
+
56%|█████▌ | 6650/11952 [3:29:14<8:43:37, 5.93s/it]
56%|█████▌ | 6651/11952 [3:29:20<8:34:31, 5.82s/it]
{'loss': 0.4726, 'learning_rate': 8.66127351170865e-06, 'epoch': 0.56}
+
56%|█████▌ | 6651/11952 [3:29:20<8:34:31, 5.82s/it]
56%|█████▌ | 6652/11952 [3:29:26<8:44:03, 5.93s/it]
{'loss': 0.4714, 'learning_rate': 8.658588049169825e-06, 'epoch': 0.56}
+
56%|█████▌ | 6652/11952 [3:29:26<8:44:03, 5.93s/it]
56%|█████▌ | 6653/11952 [3:29:32<8:37:23, 5.86s/it]
{'loss': 0.4803, 'learning_rate': 8.655902685138712e-06, 'epoch': 0.56}
+
56%|█████▌ | 6653/11952 [3:29:32<8:37:23, 5.86s/it]
56%|█████▌ | 6654/11952 [3:29:38<8:40:03, 5.89s/it]
{'loss': 0.4892, 'learning_rate': 8.653217419812517e-06, 'epoch': 0.56}
+
56%|█████▌ | 6654/11952 [3:29:38<8:40:03, 5.89s/it]
56%|█████▌ | 6655/11952 [3:29:44<8:42:17, 5.92s/it]
{'loss': 0.4818, 'learning_rate': 8.650532253388435e-06, 'epoch': 0.56}
+
56%|█████▌ | 6655/11952 [3:29:44<8:42:17, 5.92s/it]
56%|█████▌ | 6656/11952 [3:29:49<8:33:24, 5.82s/it]
{'loss': 0.4835, 'learning_rate': 8.64784718606365e-06, 'epoch': 0.56}
+
56%|█████▌ | 6656/11952 [3:29:49<8:33:24, 5.82s/it]
56%|█████▌ | 6657/11952 [3:29:55<8:31:02, 5.79s/it]
{'loss': 0.4779, 'learning_rate': 8.64516221803534e-06, 'epoch': 0.56}
+
56%|█████▌ | 6657/11952 [3:29:55<8:31:02, 5.79s/it]
56%|█████▌ | 6658/11952 [3:30:01<8:29:56, 5.78s/it]
{'loss': 0.4493, 'learning_rate': 8.642477349500686e-06, 'epoch': 0.56}
+
56%|█████▌ | 6658/11952 [3:30:01<8:29:56, 5.78s/it]
56%|█████▌ | 6659/11952 [3:30:07<8:30:37, 5.79s/it]
{'loss': 0.486, 'learning_rate': 8.639792580656845e-06, 'epoch': 0.56}
+
56%|█████▌ | 6659/11952 [3:30:07<8:30:37, 5.79s/it]
56%|█████▌ | 6660/11952 [3:30:12<8:29:54, 5.78s/it]
{'loss': 0.4814, 'learning_rate': 8.637107911700984e-06, 'epoch': 0.56}
+
56%|█████▌ | 6660/11952 [3:30:12<8:29:54, 5.78s/it]
56%|█████▌ | 6661/11952 [3:30:18<8:33:07, 5.82s/it]
{'loss': 0.4684, 'learning_rate': 8.634423342830247e-06, 'epoch': 0.56}
+
56%|█████▌ | 6661/11952 [3:30:18<8:33:07, 5.82s/it]
56%|█████▌ | 6662/11952 [3:30:24<8:27:46, 5.76s/it]
{'loss': 0.4948, 'learning_rate': 8.631738874241781e-06, 'epoch': 0.56}
+
56%|█████▌ | 6662/11952 [3:30:24<8:27:46, 5.76s/it]
56%|█████▌ | 6663/11952 [3:30:30<8:33:18, 5.82s/it]
{'loss': 0.4751, 'learning_rate': 8.629054506132719e-06, 'epoch': 0.56}
+
56%|█████▌ | 6663/11952 [3:30:30<8:33:18, 5.82s/it]
56%|█████▌ | 6664/11952 [3:30:36<8:39:44, 5.90s/it]
{'loss': 0.4949, 'learning_rate': 8.62637023870019e-06, 'epoch': 0.56}
+
56%|█████▌ | 6664/11952 [3:30:36<8:39:44, 5.90s/it]
56%|█████▌ | 6665/11952 [3:30:42<8:33:28, 5.83s/it]
{'loss': 0.4846, 'learning_rate': 8.623686072141322e-06, 'epoch': 0.56}
+
56%|█████▌ | 6665/11952 [3:30:42<8:33:28, 5.83s/it]
56%|█████▌ | 6666/11952 [3:30:47<8:29:27, 5.78s/it]
{'loss': 0.5014, 'learning_rate': 8.621002006653223e-06, 'epoch': 0.56}
+
56%|█████▌ | 6666/11952 [3:30:47<8:29:27, 5.78s/it]
56%|█████▌ | 6667/11952 [3:30:53<8:41:02, 5.92s/it]
{'loss': 0.4761, 'learning_rate': 8.618318042433001e-06, 'epoch': 0.56}
+
56%|█████▌ | 6667/11952 [3:30:53<8:41:02, 5.92s/it]
56%|█████▌ | 6668/11952 [3:30:59<8:34:34, 5.84s/it]
{'loss': 0.455, 'learning_rate': 8.615634179677754e-06, 'epoch': 0.56}
+
56%|█████▌ | 6668/11952 [3:30:59<8:34:34, 5.84s/it]
56%|█████▌ | 6669/11952 [3:31:05<8:39:57, 5.91s/it]
{'loss': 0.4812, 'learning_rate': 8.612950418584575e-06, 'epoch': 0.56}
+
56%|█████▌ | 6669/11952 [3:31:05<8:39:57, 5.91s/it]
56%|█████▌ | 6670/11952 [3:31:11<8:32:48, 5.83s/it]
{'loss': 0.445, 'learning_rate': 8.610266759350551e-06, 'epoch': 0.56}
+
56%|█████▌ | 6670/11952 [3:31:11<8:32:48, 5.83s/it]
56%|█████▌ | 6671/11952 [3:31:17<8:34:30, 5.85s/it]
{'loss': 0.4593, 'learning_rate': 8.60758320217275e-06, 'epoch': 0.56}
+
56%|█████▌ | 6671/11952 [3:31:17<8:34:30, 5.85s/it]
56%|█████▌ | 6672/11952 [3:31:23<8:42:28, 5.94s/it]
{'loss': 0.48, 'learning_rate': 8.604899747248251e-06, 'epoch': 0.56}
+
56%|█████▌ | 6672/11952 [3:31:23<8:42:28, 5.94s/it]
56%|█████▌ | 6673/11952 [3:31:29<8:39:15, 5.90s/it]
{'loss': 0.485, 'learning_rate': 8.602216394774114e-06, 'epoch': 0.56}
+
56%|█████▌ | 6673/11952 [3:31:29<8:39:15, 5.90s/it]
56%|█████▌ | 6674/11952 [3:31:35<8:44:08, 5.96s/it]
{'loss': 0.4597, 'learning_rate': 8.599533144947386e-06, 'epoch': 0.56}
+
56%|█████▌ | 6674/11952 [3:31:35<8:44:08, 5.96s/it]
56%|█████▌ | 6675/11952 [3:31:41<8:46:08, 5.98s/it]
{'loss': 0.4916, 'learning_rate': 8.596849997965122e-06, 'epoch': 0.56}
+
56%|█████▌ | 6675/11952 [3:31:41<8:46:08, 5.98s/it]
56%|█████▌ | 6676/11952 [3:31:46<8:36:31, 5.87s/it]
{'loss': 0.4836, 'learning_rate': 8.594166954024359e-06, 'epoch': 0.56}
+
56%|█████▌ | 6676/11952 [3:31:46<8:36:31, 5.87s/it]
56%|█████▌ | 6677/11952 [3:31:52<8:33:59, 5.85s/it]
{'loss': 0.4712, 'learning_rate': 8.591484013322128e-06, 'epoch': 0.56}
+
56%|█████▌ | 6677/11952 [3:31:52<8:33:59, 5.85s/it]
56%|█████▌ | 6678/11952 [3:31:58<8:42:56, 5.95s/it]
{'loss': 0.4779, 'learning_rate': 8.588801176055447e-06, 'epoch': 0.56}
+
56%|█████▌ | 6678/11952 [3:31:58<8:42:56, 5.95s/it]
56%|█████▌ | 6679/11952 [3:32:04<8:45:49, 5.98s/it]
{'loss': 0.4899, 'learning_rate': 8.586118442421341e-06, 'epoch': 0.56}
+
56%|█████▌ | 6679/11952 [3:32:04<8:45:49, 5.98s/it]
56%|█████▌ | 6680/11952 [3:32:10<8:42:40, 5.95s/it]
{'loss': 0.4701, 'learning_rate': 8.583435812616817e-06, 'epoch': 0.56}
+
56%|█████▌ | 6680/11952 [3:32:10<8:42:40, 5.95s/it]
56%|█████▌ | 6681/11952 [3:32:16<8:44:16, 5.97s/it]
{'loss': 0.4788, 'learning_rate': 8.580753286838875e-06, 'epoch': 0.56}
+
56%|█████▌ | 6681/11952 [3:32:16<8:44:16, 5.97s/it]
56%|█████▌ | 6682/11952 [3:32:23<8:50:43, 6.04s/it]
{'loss': 0.4701, 'learning_rate': 8.57807086528451e-06, 'epoch': 0.56}
+
56%|█████▌ | 6682/11952 [3:32:23<8:50:43, 6.04s/it]
56%|█████▌ | 6683/11952 [3:32:28<8:44:03, 5.97s/it]
{'loss': 0.4718, 'learning_rate': 8.575388548150702e-06, 'epoch': 0.56}
+
56%|█████▌ | 6683/11952 [3:32:28<8:44:03, 5.97s/it]
56%|█████▌ | 6684/11952 [3:32:34<8:38:25, 5.90s/it]
{'loss': 0.4727, 'learning_rate': 8.572706335634437e-06, 'epoch': 0.56}
+
56%|█████▌ | 6684/11952 [3:32:34<8:38:25, 5.90s/it]
56%|█████▌ | 6685/11952 [3:32:40<8:43:31, 5.96s/it]
{'loss': 0.4729, 'learning_rate': 8.570024227932678e-06, 'epoch': 0.56}
+
56%|█████▌ | 6685/11952 [3:32:40<8:43:31, 5.96s/it]
56%|█████▌ | 6686/11952 [3:32:46<8:43:46, 5.97s/it]
{'loss': 0.4713, 'learning_rate': 8.567342225242397e-06, 'epoch': 0.56}
+
56%|█████▌ | 6686/11952 [3:32:46<8:43:46, 5.97s/it]
56%|█████▌ | 6687/11952 [3:32:52<8:46:07, 6.00s/it]
{'loss': 0.4734, 'learning_rate': 8.564660327760543e-06, 'epoch': 0.56}
+
56%|█████▌ | 6687/11952 [3:32:52<8:46:07, 6.00s/it]
56%|█████▌ | 6688/11952 [3:32:58<8:40:20, 5.93s/it]
{'loss': 0.4841, 'learning_rate': 8.561978535684065e-06, 'epoch': 0.56}
+
56%|█████▌ | 6688/11952 [3:32:58<8:40:20, 5.93s/it]
56%|█████▌ | 6689/11952 [3:33:04<8:40:31, 5.93s/it]
{'loss': 0.4794, 'learning_rate': 8.5592968492099e-06, 'epoch': 0.56}
+
56%|█████▌ | 6689/11952 [3:33:04<8:40:31, 5.93s/it]
56%|█████▌ | 6690/11952 [3:33:10<8:39:27, 5.92s/it]
{'loss': 0.4915, 'learning_rate': 8.556615268534984e-06, 'epoch': 0.56}
+
56%|█████▌ | 6690/11952 [3:33:10<8:39:27, 5.92s/it]
56%|█████▌ | 6691/11952 [3:33:16<8:38:56, 5.92s/it]
{'loss': 0.4734, 'learning_rate': 8.553933793856234e-06, 'epoch': 0.56}
+
56%|█████▌ | 6691/11952 [3:33:16<8:38:56, 5.92s/it]
56%|█████▌ | 6692/11952 [3:33:22<8:46:16, 6.00s/it]
{'loss': 0.4661, 'learning_rate': 8.551252425370577e-06, 'epoch': 0.56}
+
56%|█████▌ | 6692/11952 [3:33:22<8:46:16, 6.00s/it]
56%|█████▌ | 6693/11952 [3:33:28<8:38:32, 5.92s/it]
{'loss': 0.4723, 'learning_rate': 8.548571163274915e-06, 'epoch': 0.56}
+
56%|█████▌ | 6693/11952 [3:33:28<8:38:32, 5.92s/it]
56%|█████▌ | 6694/11952 [3:33:33<8:31:15, 5.83s/it]
{'loss': 0.4812, 'learning_rate': 8.54589000776615e-06, 'epoch': 0.56}
+
56%|█████▌ | 6694/11952 [3:33:33<8:31:15, 5.83s/it]
56%|█████▌ | 6695/11952 [3:33:39<8:35:02, 5.88s/it]
{'loss': 0.4868, 'learning_rate': 8.543208959041174e-06, 'epoch': 0.56}
+
56%|█████▌ | 6695/11952 [3:33:39<8:35:02, 5.88s/it]
56%|█████▌ | 6696/11952 [3:33:45<8:34:34, 5.87s/it]
{'loss': 0.4789, 'learning_rate': 8.540528017296876e-06, 'epoch': 0.56}
+
56%|█████▌ | 6696/11952 [3:33:45<8:34:34, 5.87s/it]
56%|█████▌ | 6697/11952 [3:33:51<8:36:02, 5.89s/it]
{'loss': 0.4894, 'learning_rate': 8.537847182730126e-06, 'epoch': 0.56}
+
56%|█████▌ | 6697/11952 [3:33:51<8:36:02, 5.89s/it]
56%|█████▌ | 6698/11952 [3:33:57<8:31:05, 5.84s/it]
{'loss': 0.4734, 'learning_rate': 8.535166455537795e-06, 'epoch': 0.56}
+
56%|█████▌ | 6698/11952 [3:33:57<8:31:05, 5.84s/it]
56%|█████▌ | 6699/11952 [3:34:02<8:25:11, 5.77s/it]
{'loss': 0.4674, 'learning_rate': 8.532485835916754e-06, 'epoch': 0.56}
+
56%|█████▌ | 6699/11952 [3:34:02<8:25:11, 5.77s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
56%|█████▌ | 6700/11952 [3:34:08<8:20:03, 5.71s/it]5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4828, 'learning_rate': 8.529805324063843e-06, 'epoch': 0.56}
+
56%|█████▌ | 6700/11952 [3:34:08<8:20:03, 5.71s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
56%|█████▌ | 6701/11952 [3:34:38<19:00:39, 13.03s/it]
{'loss': 0.4801, 'learning_rate': 8.527124920175918e-06, 'epoch': 0.56}
+
56%|█████▌ | 6701/11952 [3:34:38<19:00:39, 13.03s/it]
56%|█████▌ | 6702/11952 [3:34:44<15:47:57, 10.83s/it]
{'loss': 0.4383, 'learning_rate': 8.524444624449812e-06, 'epoch': 0.56}
+
56%|█████▌ | 6702/11952 [3:34:44<15:47:57, 10.83s/it]
56%|█████▌ | 6703/11952 [3:34:50<13:33:10, 9.30s/it]
{'loss': 0.4693, 'learning_rate': 8.521764437082355e-06, 'epoch': 0.56}
+
56%|█████▌ | 6703/11952 [3:34:50<13:33:10, 9.30s/it]
56%|█████▌ | 6704/11952 [3:34:56<12:07:33, 8.32s/it]
{'loss': 0.4689, 'learning_rate': 8.519084358270368e-06, 'epoch': 0.56}
+
56%|█████▌ | 6704/11952 [3:34:56<12:07:33, 8.32s/it]
56%|█████▌ | 6705/11952 [3:35:01<10:59:36, 7.54s/it]
{'loss': 0.4543, 'learning_rate': 8.516404388210668e-06, 'epoch': 0.56}
+
56%|█████▌ | 6705/11952 [3:35:01<10:59:36, 7.54s/it]
56%|█████▌ | 6706/11952 [3:35:07<10:14:15, 7.03s/it]
{'loss': 0.4868, 'learning_rate': 8.513724527100055e-06, 'epoch': 0.56}
+
56%|█████▌ | 6706/11952 [3:35:07<10:14:15, 7.03s/it]
56%|█████▌ | 6707/11952 [3:35:13<9:39:17, 6.63s/it]
{'loss': 0.4848, 'learning_rate': 8.511044775135336e-06, 'epoch': 0.56}
+
56%|█████▌ | 6707/11952 [3:35:13<9:39:17, 6.63s/it]
56%|█████▌ | 6708/11952 [3:35:19<9:15:45, 6.36s/it]
{'loss': 0.4832, 'learning_rate': 8.508365132513296e-06, 'epoch': 0.56}
+
56%|█████▌ | 6708/11952 [3:35:19<9:15:45, 6.36s/it]
56%|█████▌ | 6709/11952 [3:35:24<9:01:26, 6.20s/it]
{'loss': 0.4872, 'learning_rate': 8.505685599430715e-06, 'epoch': 0.56}
+
56%|█████▌ | 6709/11952 [3:35:24<9:01:26, 6.20s/it]
56%|█████▌ | 6710/11952 [3:35:30<8:58:36, 6.16s/it]
{'loss': 0.4848, 'learning_rate': 8.503006176084366e-06, 'epoch': 0.56}
+
56%|█████▌ | 6710/11952 [3:35:30<8:58:36, 6.16s/it]
56%|█████▌ | 6711/11952 [3:35:36<8:54:57, 6.12s/it]
{'loss': 0.4751, 'learning_rate': 8.50032686267102e-06, 'epoch': 0.56}
+
56%|█████▌ | 6711/11952 [3:35:36<8:54:57, 6.12s/it]
56%|█████▌ | 6712/11952 [3:35:42<8:50:41, 6.08s/it]
{'loss': 0.4748, 'learning_rate': 8.497647659387426e-06, 'epoch': 0.56}
+
56%|█████▌ | 6712/11952 [3:35:42<8:50:41, 6.08s/it]
56%|█████▌ | 6713/11952 [3:35:48<8:45:01, 6.01s/it]
{'loss': 0.4774, 'learning_rate': 8.494968566430346e-06, 'epoch': 0.56}
+
56%|█████▌ | 6713/11952 [3:35:48<8:45:01, 6.01s/it]
56%|█████▌ | 6714/11952 [3:35:54<8:36:24, 5.92s/it]
{'loss': 0.4901, 'learning_rate': 8.492289583996511e-06, 'epoch': 0.56}
+
56%|█████▌ | 6714/11952 [3:35:54<8:36:24, 5.92s/it]
56%|█████▌ | 6715/11952 [3:36:00<8:31:21, 5.86s/it]
{'loss': 0.477, 'learning_rate': 8.489610712282658e-06, 'epoch': 0.56}
+
56%|█████▌ | 6715/11952 [3:36:00<8:31:21, 5.86s/it]
56%|█████▌ | 6716/11952 [3:36:06<8:34:16, 5.89s/it]
{'loss': 0.4673, 'learning_rate': 8.486931951485515e-06, 'epoch': 0.56}
+
56%|█████▌ | 6716/11952 [3:36:06<8:34:16, 5.89s/it]
56%|█████▌ | 6717/11952 [3:36:11<8:31:18, 5.86s/it]
{'loss': 0.4684, 'learning_rate': 8.484253301801794e-06, 'epoch': 0.56}
+
56%|█████▌ | 6717/11952 [3:36:11<8:31:18, 5.86s/it]
56%|█████▌ | 6718/11952 [3:36:17<8:35:20, 5.91s/it]
{'loss': 0.4901, 'learning_rate': 8.481574763428208e-06, 'epoch': 0.56}
+
56%|█████▌ | 6718/11952 [3:36:17<8:35:20, 5.91s/it]
56%|█████▌ | 6719/11952 [3:36:23<8:29:27, 5.84s/it]
{'loss': 0.4841, 'learning_rate': 8.47889633656145e-06, 'epoch': 0.56}
+
56%|█████▌ | 6719/11952 [3:36:23<8:29:27, 5.84s/it]
56%|█████▌ | 6720/11952 [3:36:29<8:26:58, 5.81s/it]
{'loss': 0.4742, 'learning_rate': 8.476218021398224e-06, 'epoch': 0.56}
+
56%|█████▌ | 6720/11952 [3:36:29<8:26:58, 5.81s/it]
56%|█████▌ | 6721/11952 [3:36:35<8:28:06, 5.83s/it]
{'loss': 0.473, 'learning_rate': 8.473539818135205e-06, 'epoch': 0.56}
+
56%|█████▌ | 6721/11952 [3:36:35<8:28:06, 5.83s/it]
56%|█████▌ | 6722/11952 [3:36:41<8:31:47, 5.87s/it]
{'loss': 0.4822, 'learning_rate': 8.470861726969075e-06, 'epoch': 0.56}
+
56%|█████▌ | 6722/11952 [3:36:41<8:31:47, 5.87s/it]
56%|█████▋ | 6723/11952 [3:36:46<8:23:02, 5.77s/it]
{'loss': 0.4779, 'learning_rate': 8.4681837480965e-06, 'epoch': 0.56}
+
56%|█████▋ | 6723/11952 [3:36:46<8:23:02, 5.77s/it]
56%|█████▋ | 6724/11952 [3:36:52<8:30:11, 5.86s/it]
{'loss': 0.4748, 'learning_rate': 8.46550588171414e-06, 'epoch': 0.56}
+
56%|█████▋ | 6724/11952 [3:36:52<8:30:11, 5.86s/it]
56%|█████▋ | 6725/11952 [3:36:58<8:33:18, 5.89s/it]
{'loss': 0.4784, 'learning_rate': 8.462828128018642e-06, 'epoch': 0.56}
+
56%|█████▋ | 6725/11952 [3:36:58<8:33:18, 5.89s/it]
56%|█████▋ | 6726/11952 [3:37:04<8:27:48, 5.83s/it]
{'loss': 0.4835, 'learning_rate': 8.460150487206652e-06, 'epoch': 0.56}
+
56%|█████▋ | 6726/11952 [3:37:04<8:27:48, 5.83s/it]
56%|█████▋ | 6727/11952 [3:37:10<8:32:32, 5.89s/it]
{'loss': 0.4796, 'learning_rate': 8.45747295947481e-06, 'epoch': 0.56}
+
56%|█████▋ | 6727/11952 [3:37:10<8:32:32, 5.89s/it]
56%|█████▋ | 6728/11952 [3:37:16<8:27:23, 5.83s/it]
{'loss': 0.4778, 'learning_rate': 8.454795545019737e-06, 'epoch': 0.56}
+
56%|█████▋ | 6728/11952 [3:37:16<8:27:23, 5.83s/it]
56%|█████▋ | 6729/11952 [3:37:22<8:32:23, 5.89s/it]
{'loss': 0.4831, 'learning_rate': 8.452118244038052e-06, 'epoch': 0.56}
+
56%|█████▋ | 6729/11952 [3:37:22<8:32:23, 5.89s/it]
56%|█████▋ | 6730/11952 [3:37:27<8:25:23, 5.81s/it]
{'loss': 0.4749, 'learning_rate': 8.449441056726364e-06, 'epoch': 0.56}
+
56%|█████▋ | 6730/11952 [3:37:27<8:25:23, 5.81s/it]
56%|█████▋ | 6731/11952 [3:37:33<8:26:30, 5.82s/it]
{'loss': 0.4853, 'learning_rate': 8.446763983281276e-06, 'epoch': 0.56}
+
56%|█████▋ | 6731/11952 [3:37:33<8:26:30, 5.82s/it]
56%|█████▋ | 6732/11952 [3:37:39<8:23:26, 5.79s/it]
{'loss': 0.491, 'learning_rate': 8.444087023899377e-06, 'epoch': 0.56}
+
56%|█████▋ | 6732/11952 [3:37:39<8:23:26, 5.79s/it]
56%|█████▋ | 6733/11952 [3:37:45<8:32:30, 5.89s/it]
{'loss': 0.4564, 'learning_rate': 8.44141017877726e-06, 'epoch': 0.56}
+
56%|█████▋ | 6733/11952 [3:37:45<8:32:30, 5.89s/it]
56%|█████▋ | 6734/11952 [3:37:51<8:26:22, 5.82s/it]
{'loss': 0.4818, 'learning_rate': 8.438733448111496e-06, 'epoch': 0.56}
+
56%|█████▋ | 6734/11952 [3:37:51<8:26:22, 5.82s/it]
56%|█████▋ | 6735/11952 [3:37:57<8:25:43, 5.82s/it]
{'loss': 0.4734, 'learning_rate': 8.436056832098655e-06, 'epoch': 0.56}
+
56%|█████▋ | 6735/11952 [3:37:57<8:25:43, 5.82s/it]
56%|█████▋ | 6736/11952 [3:38:02<8:20:00, 5.75s/it]
{'loss': 0.4585, 'learning_rate': 8.433380330935293e-06, 'epoch': 0.56}
+
56%|█████▋ | 6736/11952 [3:38:02<8:20:00, 5.75s/it]
56%|█████▋ | 6737/11952 [3:38:08<8:19:42, 5.75s/it]
{'loss': 0.4646, 'learning_rate': 8.430703944817967e-06, 'epoch': 0.56}
+
56%|█████▋ | 6737/11952 [3:38:08<8:19:42, 5.75s/it]
56%|█████▋ | 6738/11952 [3:38:14<8:21:02, 5.77s/it]
{'loss': 0.4824, 'learning_rate': 8.428027673943213e-06, 'epoch': 0.56}
+
56%|█████▋ | 6738/11952 [3:38:14<8:21:02, 5.77s/it]
56%|█████▋ | 6739/11952 [3:38:20<8:22:45, 5.79s/it]
{'loss': 0.4706, 'learning_rate': 8.425351518507565e-06, 'epoch': 0.56}
+
56%|█████▋ | 6739/11952 [3:38:20<8:22:45, 5.79s/it]
56%|█████▋ | 6740/11952 [3:38:25<8:21:21, 5.77s/it]
{'loss': 0.4733, 'learning_rate': 8.422675478707556e-06, 'epoch': 0.56}
+
56%|█████▋ | 6740/11952 [3:38:25<8:21:21, 5.77s/it]
56%|█████▋ | 6741/11952 [3:38:31<8:25:21, 5.82s/it]
{'loss': 0.5001, 'learning_rate': 8.4199995547397e-06, 'epoch': 0.56}
+
56%|█████▋ | 6741/11952 [3:38:31<8:25:21, 5.82s/it]
56%|█████▋ | 6742/11952 [3:38:37<8:21:02, 5.77s/it]
{'loss': 0.4803, 'learning_rate': 8.417323746800504e-06, 'epoch': 0.56}
+
56%|█████▋ | 6742/11952 [3:38:37<8:21:02, 5.77s/it]
56%|█████▋ | 6743/11952 [3:38:43<8:34:36, 5.93s/it]
{'loss': 0.4705, 'learning_rate': 8.414648055086471e-06, 'epoch': 0.56}
+
56%|█████▋ | 6743/11952 [3:38:43<8:34:36, 5.93s/it]
56%|█████▋ | 6744/11952 [3:38:49<8:33:34, 5.92s/it]
{'loss': 0.4768, 'learning_rate': 8.41197247979409e-06, 'epoch': 0.56}
+
56%|█████▋ | 6744/11952 [3:38:49<8:33:34, 5.92s/it]
56%|█████▋ | 6745/11952 [3:38:55<8:32:59, 5.91s/it]
{'loss': 0.4859, 'learning_rate': 8.409297021119843e-06, 'epoch': 0.56}
+
56%|█████▋ | 6745/11952 [3:38:55<8:32:59, 5.91s/it]
56%|█████▋ | 6746/11952 [3:39:01<8:26:27, 5.84s/it]
{'loss': 0.4715, 'learning_rate': 8.406621679260206e-06, 'epoch': 0.56}
+
56%|█████▋ | 6746/11952 [3:39:01<8:26:27, 5.84s/it]
56%|█████▋ | 6747/11952 [3:39:06<8:20:42, 5.77s/it]
{'loss': 0.462, 'learning_rate': 8.403946454411645e-06, 'epoch': 0.56}
+
56%|█████▋ | 6747/11952 [3:39:06<8:20:42, 5.77s/it]
56%|█████▋ | 6748/11952 [3:39:12<8:21:29, 5.78s/it]
{'loss': 0.4751, 'learning_rate': 8.401271346770622e-06, 'epoch': 0.56}
+
56%|█████▋ | 6748/11952 [3:39:12<8:21:29, 5.78s/it]
56%|█████▋ | 6749/11952 [3:39:18<8:24:38, 5.82s/it]
{'loss': 0.4768, 'learning_rate': 8.398596356533581e-06, 'epoch': 0.56}
+
56%|█████▋ | 6749/11952 [3:39:18<8:24:38, 5.82s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...0
+ 7 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
56%|█████▋ | 6750/11952 [3:39:24<8:23:23, 5.81s/it]1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.471, 'learning_rate': 8.395921483896963e-06, 'epoch': 0.56}
+
56%|█████▋ | 6750/11952 [3:39:24<8:23:23, 5.81s/it]
56%|█████▋ | 6751/11952 [3:39:29<8:22:49, 5.80s/it]
{'loss': 0.5009, 'learning_rate': 8.393246729057196e-06, 'epoch': 0.56}
+
56%|█████▋ | 6751/11952 [3:39:29<8:22:49, 5.80s/it]
56%|█████▋ | 6752/11952 [3:39:35<8:28:05, 5.86s/it]
{'loss': 0.4724, 'learning_rate': 8.39057209221071e-06, 'epoch': 0.56}
+
56%|█████▋ | 6752/11952 [3:39:35<8:28:05, 5.86s/it]
57%|█████▋ | 6753/11952 [3:39:41<8:25:52, 5.84s/it]
{'loss': 0.471, 'learning_rate': 8.38789757355391e-06, 'epoch': 0.56}
+
57%|█████▋ | 6753/11952 [3:39:41<8:25:52, 5.84s/it]
57%|█████▋ | 6754/11952 [3:39:47<8:22:55, 5.81s/it]
{'loss': 0.4789, 'learning_rate': 8.38522317328321e-06, 'epoch': 0.57}
+
57%|█████▋ | 6754/11952 [3:39:47<8:22:55, 5.81s/it]
57%|█████▋ | 6755/11952 [3:39:53<8:31:37, 5.91s/it]
{'loss': 0.4581, 'learning_rate': 8.382548891595006e-06, 'epoch': 0.57}
+
57%|█████▋ | 6755/11952 [3:39:53<8:31:37, 5.91s/it]
57%|█████▋ | 6756/11952 [3:39:59<8:35:47, 5.96s/it]
{'loss': 0.4895, 'learning_rate': 8.379874728685681e-06, 'epoch': 0.57}
+
57%|█████▋ | 6756/11952 [3:39:59<8:35:47, 5.96s/it]
57%|█████▋ | 6757/11952 [3:40:05<8:31:17, 5.91s/it]
{'loss': 0.4833, 'learning_rate': 8.37720068475162e-06, 'epoch': 0.57}
+
57%|█████▋ | 6757/11952 [3:40:05<8:31:17, 5.91s/it]
57%|█████▋ | 6758/11952 [3:40:11<8:29:08, 5.88s/it]
{'loss': 0.4793, 'learning_rate': 8.37452675998919e-06, 'epoch': 0.57}
+
57%|█████▋ | 6758/11952 [3:40:11<8:29:08, 5.88s/it]
57%|█████▋ | 6759/11952 [3:40:17<8:32:47, 5.92s/it]
{'loss': 0.4747, 'learning_rate': 8.371852954594755e-06, 'epoch': 0.57}
+
57%|█████▋ | 6759/11952 [3:40:17<8:32:47, 5.92s/it]
57%|█████▋ | 6760/11952 [3:40:23<8:32:46, 5.93s/it]
{'loss': 0.4749, 'learning_rate': 8.369179268764662e-06, 'epoch': 0.57}
+
57%|█████▋ | 6760/11952 [3:40:23<8:32:46, 5.93s/it]
57%|█████▋ | 6761/11952 [3:40:29<8:30:32, 5.90s/it]
{'loss': 0.4625, 'learning_rate': 8.366505702695264e-06, 'epoch': 0.57}
+
57%|█████▋ | 6761/11952 [3:40:29<8:30:32, 5.90s/it]
57%|█████▋ | 6762/11952 [3:40:34<8:28:28, 5.88s/it]
{'loss': 0.4828, 'learning_rate': 8.363832256582892e-06, 'epoch': 0.57}
+
57%|█████▋ | 6762/11952 [3:40:34<8:28:28, 5.88s/it]
57%|█████▋ | 6763/11952 [3:40:40<8:18:22, 5.76s/it]
{'loss': 0.4782, 'learning_rate': 8.361158930623877e-06, 'epoch': 0.57}
+
57%|█████▋ | 6763/11952 [3:40:40<8:18:22, 5.76s/it]
57%|█████▋ | 6764/11952 [3:40:46<8:28:16, 5.88s/it]
{'loss': 0.4788, 'learning_rate': 8.358485725014531e-06, 'epoch': 0.57}
+
57%|█████▋ | 6764/11952 [3:40:46<8:28:16, 5.88s/it]
57%|█████▋ | 6765/11952 [3:40:52<8:21:10, 5.80s/it]
{'loss': 0.4712, 'learning_rate': 8.355812639951168e-06, 'epoch': 0.57}
+
57%|█████▋ | 6765/11952 [3:40:52<8:21:10, 5.80s/it]
57%|█████▋ | 6766/11952 [3:40:58<8:31:11, 5.91s/it]
{'loss': 0.4894, 'learning_rate': 8.35313967563008e-06, 'epoch': 0.57}
+
57%|█████▋ | 6766/11952 [3:40:58<8:31:11, 5.91s/it]
57%|█████▋ | 6767/11952 [3:41:04<8:32:32, 5.93s/it]
{'loss': 0.4702, 'learning_rate': 8.350466832247568e-06, 'epoch': 0.57}
+
57%|█████▋ | 6767/11952 [3:41:04<8:32:32, 5.93s/it]
57%|█████▋ | 6768/11952 [3:41:10<8:31:53, 5.92s/it]
{'loss': 0.4668, 'learning_rate': 8.347794109999912e-06, 'epoch': 0.57}
+
57%|█████▋ | 6768/11952 [3:41:10<8:31:53, 5.92s/it]
57%|█████▋ | 6769/11952 [3:41:16<8:29:51, 5.90s/it]
{'loss': 0.4578, 'learning_rate': 8.345121509083384e-06, 'epoch': 0.57}
+
57%|█████▋ | 6769/11952 [3:41:16<8:29:51, 5.90s/it]
57%|█████▋ | 6770/11952 [3:41:21<8:23:36, 5.83s/it]
{'loss': 0.4826, 'learning_rate': 8.34244902969425e-06, 'epoch': 0.57}
+
57%|█████▋ | 6770/11952 [3:41:21<8:23:36, 5.83s/it]
57%|█████▋ | 6771/11952 [3:41:27<8:32:53, 5.94s/it]
{'loss': 0.4897, 'learning_rate': 8.339776672028765e-06, 'epoch': 0.57}
+
57%|█████▋ | 6771/11952 [3:41:27<8:32:53, 5.94s/it]
57%|█████▋ | 6772/11952 [3:41:33<8:26:17, 5.86s/it]
{'loss': 0.4767, 'learning_rate': 8.337104436283176e-06, 'epoch': 0.57}
+
57%|█████▋ | 6772/11952 [3:41:33<8:26:17, 5.86s/it]
57%|█████▋ | 6773/11952 [3:41:39<8:22:08, 5.82s/it]
{'loss': 0.5019, 'learning_rate': 8.334432322653717e-06, 'epoch': 0.57}
+
57%|█████▋ | 6773/11952 [3:41:39<8:22:08, 5.82s/it]
57%|█████▋ | 6774/11952 [3:41:45<8:28:28, 5.89s/it]
{'loss': 0.4777, 'learning_rate': 8.331760331336622e-06, 'epoch': 0.57}
+
57%|█████▋ | 6774/11952 [3:41:45<8:28:28, 5.89s/it]
57%|█████▋ | 6775/11952 [3:41:51<8:23:43, 5.84s/it]
{'loss': 0.4643, 'learning_rate': 8.329088462528113e-06, 'epoch': 0.57}
+
57%|█████▋ | 6775/11952 [3:41:51<8:23:43, 5.84s/it]
57%|█████▋ | 6776/11952 [3:41:57<8:25:23, 5.86s/it]
{'loss': 0.4687, 'learning_rate': 8.326416716424396e-06, 'epoch': 0.57}
+
57%|█████▋ | 6776/11952 [3:41:57<8:25:23, 5.86s/it]
57%|█████▋ | 6777/11952 [3:42:02<8:25:51, 5.87s/it]
{'loss': 0.4902, 'learning_rate': 8.323745093221672e-06, 'epoch': 0.57}
+
57%|█████▋ | 6777/11952 [3:42:02<8:25:51, 5.87s/it]
57%|█████▋ | 6778/11952 [3:42:08<8:27:43, 5.89s/it]
{'loss': 0.4804, 'learning_rate': 8.32107359311614e-06, 'epoch': 0.57}
+
57%|█████▋ | 6778/11952 [3:42:08<8:27:43, 5.89s/it]
57%|█████▋ | 6779/11952 [3:42:14<8:30:43, 5.92s/it]
{'loss': 0.4833, 'learning_rate': 8.318402216303978e-06, 'epoch': 0.57}
+
57%|█████▋ | 6779/11952 [3:42:14<8:30:43, 5.92s/it]
57%|█████▋ | 6780/11952 [3:42:20<8:26:19, 5.87s/it]
{'loss': 0.4916, 'learning_rate': 8.31573096298136e-06, 'epoch': 0.57}
+
57%|█████▋ | 6780/11952 [3:42:20<8:26:19, 5.87s/it]
57%|█████▋ | 6781/11952 [3:42:26<8:22:38, 5.83s/it]
{'loss': 0.4769, 'learning_rate': 8.313059833344459e-06, 'epoch': 0.57}
+
57%|█████▋ | 6781/11952 [3:42:26<8:22:38, 5.83s/it]
57%|█████▋ | 6782/11952 [3:42:32<8:28:21, 5.90s/it]
{'loss': 0.4853, 'learning_rate': 8.310388827589424e-06, 'epoch': 0.57}
+
57%|█████▋ | 6782/11952 [3:42:32<8:28:21, 5.90s/it]
57%|█████▋ | 6783/11952 [3:42:38<8:31:18, 5.94s/it]
{'loss': 0.4967, 'learning_rate': 8.30771794591241e-06, 'epoch': 0.57}
+
57%|█████▋ | 6783/11952 [3:42:38<8:31:18, 5.94s/it]
57%|█████▋ | 6784/11952 [3:42:44<8:23:30, 5.85s/it]
{'loss': 0.4618, 'learning_rate': 8.30504718850955e-06, 'epoch': 0.57}
+
57%|█████▋ | 6784/11952 [3:42:44<8:23:30, 5.85s/it]
57%|█████▋ | 6785/11952 [3:42:50<8:29:59, 5.92s/it]
{'loss': 0.4827, 'learning_rate': 8.302376555576974e-06, 'epoch': 0.57}
+
57%|█████▋ | 6785/11952 [3:42:50<8:29:59, 5.92s/it]
57%|█████▋ | 6786/11952 [3:42:55<8:23:56, 5.85s/it]
{'loss': 0.458, 'learning_rate': 8.299706047310803e-06, 'epoch': 0.57}
+
57%|█████▋ | 6786/11952 [3:42:55<8:23:56, 5.85s/it]
57%|█████▋ | 6787/11952 [3:43:02<8:36:02, 5.99s/it]
{'loss': 0.4838, 'learning_rate': 8.297035663907146e-06, 'epoch': 0.57}
+
57%|█████▋ | 6787/11952 [3:43:02<8:36:02, 5.99s/it]
57%|█████▋ | 6788/11952 [3:43:08<8:32:32, 5.96s/it]
{'loss': 0.4725, 'learning_rate': 8.294365405562107e-06, 'epoch': 0.57}
+
57%|█████▋ | 6788/11952 [3:43:08<8:32:32, 5.96s/it]
57%|█████▋ | 6789/11952 [3:43:13<8:30:26, 5.93s/it]
{'loss': 0.4844, 'learning_rate': 8.29169527247178e-06, 'epoch': 0.57}
+
57%|█████▋ | 6789/11952 [3:43:13<8:30:26, 5.93s/it]
57%|█████▋ | 6790/11952 [3:43:20<8:34:15, 5.98s/it]
{'loss': 0.479, 'learning_rate': 8.289025264832247e-06, 'epoch': 0.57}
+
57%|█████▋ | 6790/11952 [3:43:20<8:34:15, 5.98s/it]
57%|█████▋ | 6791/11952 [3:43:25<8:25:24, 5.88s/it]
{'loss': 0.4811, 'learning_rate': 8.286355382839584e-06, 'epoch': 0.57}
+
57%|█████▋ | 6791/11952 [3:43:25<8:25:24, 5.88s/it]
57%|█████▋ | 6792/11952 [3:43:31<8:27:02, 5.90s/it]
{'loss': 0.4781, 'learning_rate': 8.283685626689851e-06, 'epoch': 0.57}
+
57%|█████▋ | 6792/11952 [3:43:31<8:27:02, 5.90s/it]
57%|█████▋ | 6793/11952 [3:43:37<8:30:24, 5.94s/it]
{'loss': 0.4775, 'learning_rate': 8.281015996579106e-06, 'epoch': 0.57}
+
57%|█████▋ | 6793/11952 [3:43:37<8:30:24, 5.94s/it]
57%|█████▋ | 6794/11952 [3:43:43<8:23:56, 5.86s/it]
{'loss': 0.4994, 'learning_rate': 8.278346492703394e-06, 'epoch': 0.57}
+
57%|█████▋ | 6794/11952 [3:43:43<8:23:56, 5.86s/it]
57%|█████▋ | 6795/11952 [3:43:49<8:23:48, 5.86s/it]
{'loss': 0.4812, 'learning_rate': 8.275677115258761e-06, 'epoch': 0.57}
+
57%|█████▋ | 6795/11952 [3:43:49<8:23:48, 5.86s/it]
57%|█████▋ | 6796/11952 [3:43:55<8:32:24, 5.96s/it]
{'loss': 0.4621, 'learning_rate': 8.273007864441227e-06, 'epoch': 0.57}
+
57%|█████▋ | 6796/11952 [3:43:55<8:32:24, 5.96s/it]
57%|█████▋ | 6797/11952 [3:44:01<8:28:25, 5.92s/it]
{'loss': 0.4713, 'learning_rate': 8.27033874044681e-06, 'epoch': 0.57}
+
57%|█████▋ | 6797/11952 [3:44:01<8:28:25, 5.92s/it]
57%|█████▋ | 6798/11952 [3:44:07<8:34:36, 5.99s/it]
{'loss': 0.4923, 'learning_rate': 8.267669743471525e-06, 'epoch': 0.57}
+
57%|█████▋ | 6798/11952 [3:44:07<8:34:36, 5.99s/it]
57%|█████▋ | 6799/11952 [3:44:13<8:30:30, 5.94s/it]
{'loss': 0.4829, 'learning_rate': 8.265000873711368e-06, 'epoch': 0.57}
+
57%|█████▋ | 6799/11952 [3:44:13<8:30:30, 5.94s/it]07 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
57%|█████▋ | 6800/11952 [3:44:19<8:29:29, 5.93s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4658, 'learning_rate': 8.262332131362326e-06, 'epoch': 0.57}
+
57%|█████▋ | 6800/11952 [3:44:19<8:29:29, 5.93s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
57%|█████▋ | 6801/11952 [3:44:50<19:16:27, 13.47s/it]
{'loss': 0.5034, 'learning_rate': 8.259663516620389e-06, 'epoch': 0.57}
+
57%|█████▋ | 6801/11952 [3:44:50<19:16:27, 13.47s/it]
57%|█████▋ | 6802/11952 [3:44:56<16:01:43, 11.20s/it]
{'loss': 0.4598, 'learning_rate': 8.256995029681526e-06, 'epoch': 0.57}
+
57%|█████▋ | 6802/11952 [3:44:56<16:01:43, 11.20s/it]
57%|█████▋ | 6803/11952 [3:45:01<13:39:04, 9.54s/it]
{'loss': 0.4704, 'learning_rate': 8.254326670741694e-06, 'epoch': 0.57}
+
57%|█████▋ | 6803/11952 [3:45:01<13:39:04, 9.54s/it]
57%|█████▋ | 6804/11952 [3:45:07<12:11:01, 8.52s/it]
{'loss': 0.4928, 'learning_rate': 8.251658439996854e-06, 'epoch': 0.57}
+
57%|█████▋ | 6804/11952 [3:45:07<12:11:01, 8.52s/it]
57%|█████▋ | 6805/11952 [3:45:13<10:58:45, 7.68s/it]
{'loss': 0.4666, 'learning_rate': 8.248990337642946e-06, 'epoch': 0.57}
+
57%|█████▋ | 6805/11952 [3:45:13<10:58:45, 7.68s/it]
57%|█████▋ | 6806/11952 [3:45:19<10:14:43, 7.17s/it]
{'loss': 0.4721, 'learning_rate': 8.246322363875904e-06, 'epoch': 0.57}
+
57%|█████▋ | 6806/11952 [3:45:19<10:14:43, 7.17s/it]
57%|█████▋ | 6807/11952 [3:45:25<9:40:13, 6.77s/it]
{'loss': 0.474, 'learning_rate': 8.24365451889165e-06, 'epoch': 0.57}
+
57%|█████▋ | 6807/11952 [3:45:25<9:40:13, 6.77s/it]
57%|█████▋ | 6808/11952 [3:45:31<9:13:58, 6.46s/it]
{'loss': 0.4743, 'learning_rate': 8.240986802886105e-06, 'epoch': 0.57}
+
57%|█████▋ | 6808/11952 [3:45:31<9:13:58, 6.46s/it]
57%|█████▋ | 6809/11952 [3:45:37<9:01:29, 6.32s/it]
{'loss': 0.4705, 'learning_rate': 8.238319216055175e-06, 'epoch': 0.57}
+
57%|█████▋ | 6809/11952 [3:45:37<9:01:29, 6.32s/it]
57%|█████▋ | 6810/11952 [3:45:43<8:53:44, 6.23s/it]
{'loss': 0.4877, 'learning_rate': 8.235651758594753e-06, 'epoch': 0.57}
+
57%|█████▋ | 6810/11952 [3:45:43<8:53:44, 6.23s/it]
57%|█████▋ | 6811/11952 [3:45:48<8:40:54, 6.08s/it]
{'loss': 0.4727, 'learning_rate': 8.23298443070073e-06, 'epoch': 0.57}
+
57%|█████▋ | 6811/11952 [3:45:48<8:40:54, 6.08s/it]
57%|█████▋ | 6812/11952 [3:45:54<8:35:41, 6.02s/it]
{'loss': 0.4659, 'learning_rate': 8.230317232568977e-06, 'epoch': 0.57}
+
57%|█████▋ | 6812/11952 [3:45:54<8:35:41, 6.02s/it]
57%|█████▋ | 6813/11952 [3:46:00<8:28:10, 5.93s/it]
{'loss': 0.4665, 'learning_rate': 8.227650164395369e-06, 'epoch': 0.57}
+
57%|█████▋ | 6813/11952 [3:46:00<8:28:10, 5.93s/it]
57%|█████▋ | 6814/11952 [3:46:06<8:32:34, 5.99s/it]
{'loss': 0.461, 'learning_rate': 8.224983226375756e-06, 'epoch': 0.57}
+
57%|█████▋ | 6814/11952 [3:46:06<8:32:34, 5.99s/it]
57%|█████▋ | 6815/11952 [3:46:12<8:25:12, 5.90s/it]
{'loss': 0.4809, 'learning_rate': 8.222316418705995e-06, 'epoch': 0.57}
+
57%|█████▋ | 6815/11952 [3:46:12<8:25:12, 5.90s/it]
57%|█████▋ | 6816/11952 [3:46:18<8:25:26, 5.90s/it]
{'loss': 0.4596, 'learning_rate': 8.219649741581925e-06, 'epoch': 0.57}
+
57%|█████▋ | 6816/11952 [3:46:18<8:25:26, 5.90s/it]
57%|█████▋ | 6817/11952 [3:46:23<8:21:19, 5.86s/it]
{'loss': 0.4577, 'learning_rate': 8.216983195199372e-06, 'epoch': 0.57}
+
57%|█████▋ | 6817/11952 [3:46:23<8:21:19, 5.86s/it]
57%|█████▋ | 6818/11952 [3:46:30<8:26:12, 5.92s/it]
{'loss': 0.4787, 'learning_rate': 8.214316779754154e-06, 'epoch': 0.57}
+
57%|█████▋ | 6818/11952 [3:46:30<8:26:12, 5.92s/it]
57%|█████▋ | 6819/11952 [3:46:36<8:32:16, 5.99s/it]
{'loss': 0.4803, 'learning_rate': 8.211650495442088e-06, 'epoch': 0.57}
+
57%|█████▋ | 6819/11952 [3:46:36<8:32:16, 5.99s/it]
57%|█████▋ | 6820/11952 [3:46:41<8:26:02, 5.92s/it]
{'loss': 0.4821, 'learning_rate': 8.20898434245897e-06, 'epoch': 0.57}
+
57%|█████▋ | 6820/11952 [3:46:41<8:26:02, 5.92s/it]
57%|█████▋ | 6821/11952 [3:46:47<8:24:47, 5.90s/it]
{'loss': 0.4678, 'learning_rate': 8.206318321000588e-06, 'epoch': 0.57}
+
57%|█████▋ | 6821/11952 [3:46:47<8:24:47, 5.90s/it]
57%|█████▋ | 6822/11952 [3:46:53<8:19:53, 5.85s/it]
{'loss': 0.501, 'learning_rate': 8.203652431262733e-06, 'epoch': 0.57}
+
57%|█████▋ | 6822/11952 [3:46:53<8:19:53, 5.85s/it]
57%|█████▋ | 6823/11952 [3:46:59<8:29:13, 5.96s/it]
{'loss': 0.4752, 'learning_rate': 8.200986673441173e-06, 'epoch': 0.57}
+
57%|█████▋ | 6823/11952 [3:46:59<8:29:13, 5.96s/it]
57%|█████▋ | 6824/11952 [3:47:05<8:26:00, 5.92s/it]
{'loss': 0.4762, 'learning_rate': 8.198321047731665e-06, 'epoch': 0.57}
+
57%|█████▋ | 6824/11952 [3:47:05<8:26:00, 5.92s/it]
57%|█████▋ | 6825/11952 [3:47:11<8:22:54, 5.89s/it]
{'loss': 0.4846, 'learning_rate': 8.195655554329969e-06, 'epoch': 0.57}
+
57%|█████▋ | 6825/11952 [3:47:11<8:22:54, 5.89s/it]
57%|█████▋ | 6826/11952 [3:47:17<8:23:05, 5.89s/it]
{'loss': 0.4847, 'learning_rate': 8.192990193431824e-06, 'epoch': 0.57}
+
57%|█████▋ | 6826/11952 [3:47:17<8:23:05, 5.89s/it]
57%|█████▋ | 6827/11952 [3:47:23<8:23:36, 5.90s/it]
{'loss': 0.4782, 'learning_rate': 8.19032496523296e-06, 'epoch': 0.57}
+
57%|█████▋ | 6827/11952 [3:47:23<8:23:36, 5.90s/it]
57%|█████▋ | 6828/11952 [3:47:28<8:21:26, 5.87s/it]
{'loss': 0.4777, 'learning_rate': 8.187659869929104e-06, 'epoch': 0.57}
+
57%|█████▋ | 6828/11952 [3:47:28<8:21:26, 5.87s/it]
57%|█████▋ | 6829/11952 [3:47:34<8:22:15, 5.88s/it]
{'loss': 0.4826, 'learning_rate': 8.184994907715969e-06, 'epoch': 0.57}
+
57%|█████▋ | 6829/11952 [3:47:34<8:22:15, 5.88s/it]
57%|█████▋ | 6830/11952 [3:47:40<8:26:51, 5.94s/it]
{'loss': 0.4972, 'learning_rate': 8.182330078789262e-06, 'epoch': 0.57}
+
57%|█████▋ | 6830/11952 [3:47:40<8:26:51, 5.94s/it]
57%|█████▋ | 6831/11952 [3:47:46<8:21:23, 5.87s/it]
{'loss': 0.4655, 'learning_rate': 8.179665383344674e-06, 'epoch': 0.57}
+
57%|█████▋ | 6831/11952 [3:47:46<8:21:23, 5.87s/it]
57%|█████▋ | 6832/11952 [3:47:52<8:27:57, 5.95s/it]
{'loss': 0.4884, 'learning_rate': 8.177000821577888e-06, 'epoch': 0.57}
+
57%|█████▋ | 6832/11952 [3:47:52<8:27:57, 5.95s/it]
57%|█████▋ | 6833/11952 [3:47:58<8:26:21, 5.94s/it]
{'loss': 0.4607, 'learning_rate': 8.174336393684577e-06, 'epoch': 0.57}
+
57%|█████▋ | 6833/11952 [3:47:58<8:26:21, 5.94s/it]
57%|█████▋ | 6834/11952 [3:48:04<8:28:41, 5.96s/it]
{'loss': 0.4567, 'learning_rate': 8.17167209986041e-06, 'epoch': 0.57}
+
57%|█████▋ | 6834/11952 [3:48:04<8:28:41, 5.96s/it]
57%|█████▋ | 6835/11952 [3:48:10<8:25:49, 5.93s/it]
{'loss': 0.4858, 'learning_rate': 8.169007940301034e-06, 'epoch': 0.57}
+
57%|█████▋ | 6835/11952 [3:48:10<8:25:49, 5.93s/it]
57%|█████▋ | 6836/11952 [3:48:16<8:21:37, 5.88s/it]
{'loss': 0.473, 'learning_rate': 8.166343915202106e-06, 'epoch': 0.57}
+
57%|█████▋ | 6836/11952 [3:48:16<8:21:37, 5.88s/it]
57%|█████▋ | 6837/11952 [3:48:22<8:21:59, 5.89s/it]
{'loss': 0.4651, 'learning_rate': 8.163680024759252e-06, 'epoch': 0.57}
+
57%|█████▋ | 6837/11952 [3:48:22<8:21:59, 5.89s/it]
57%|█████▋ | 6838/11952 [3:48:28<8:18:28, 5.85s/it]
{'loss': 0.4667, 'learning_rate': 8.161016269168101e-06, 'epoch': 0.57}
+
57%|█████▋ | 6838/11952 [3:48:28<8:18:28, 5.85s/it]
57%|█████▋ | 6839/11952 [3:48:33<8:18:14, 5.85s/it]
{'loss': 0.5024, 'learning_rate': 8.158352648624263e-06, 'epoch': 0.57}
+
57%|█████▋ | 6839/11952 [3:48:33<8:18:14, 5.85s/it]
57%|█████▋ | 6840/11952 [3:48:39<8:19:46, 5.87s/it]
{'loss': 0.478, 'learning_rate': 8.155689163323348e-06, 'epoch': 0.57}
+
57%|█████▋ | 6840/11952 [3:48:39<8:19:46, 5.87s/it]
57%|█████▋ | 6841/11952 [3:48:45<8:23:37, 5.91s/it]
{'loss': 0.4516, 'learning_rate': 8.153025813460947e-06, 'epoch': 0.57}
+
57%|█████▋ | 6841/11952 [3:48:45<8:23:37, 5.91s/it]
57%|█████▋ | 6842/11952 [3:48:51<8:24:55, 5.93s/it]
{'loss': 0.478, 'learning_rate': 8.15036259923265e-06, 'epoch': 0.57}
+
57%|█████▋ | 6842/11952 [3:48:51<8:24:55, 5.93s/it]
57%|█████▋ | 6843/11952 [3:48:57<8:25:46, 5.94s/it]
{'loss': 0.4709, 'learning_rate': 8.147699520834033e-06, 'epoch': 0.57}
+
57%|█████▋ | 6843/11952 [3:48:57<8:25:46, 5.94s/it]
57%|█████▋ | 6844/11952 [3:49:03<8:16:00, 5.83s/it]
{'loss': 0.4604, 'learning_rate': 8.145036578460656e-06, 'epoch': 0.57}
+
57%|█████▋ | 6844/11952 [3:49:03<8:16:00, 5.83s/it]
57%|█████▋ | 6845/11952 [3:49:09<8:20:40, 5.88s/it]
{'loss': 0.4652, 'learning_rate': 8.142373772308078e-06, 'epoch': 0.57}
+
57%|█████▋ | 6845/11952 [3:49:09<8:20:40, 5.88s/it]
57%|█████▋ | 6846/11952 [3:49:15<8:24:25, 5.93s/it]
{'loss': 0.4943, 'learning_rate': 8.139711102571846e-06, 'epoch': 0.57}
+
57%|█████▋ | 6846/11952 [3:49:15<8:24:25, 5.93s/it]
57%|█████▋ | 6847/11952 [3:49:21<8:23:54, 5.92s/it]
{'loss': 0.4631, 'learning_rate': 8.137048569447492e-06, 'epoch': 0.57}
+
57%|█████▋ | 6847/11952 [3:49:21<8:23:54, 5.92s/it]
57%|█████▋ | 6848/11952 [3:49:27<8:34:15, 6.05s/it]
{'loss': 0.4891, 'learning_rate': 8.134386173130539e-06, 'epoch': 0.57}
+
57%|█████▋ | 6848/11952 [3:49:27<8:34:15, 6.05s/it]
57%|█████▋ | 6849/11952 [3:49:33<8:26:39, 5.96s/it]
{'loss': 0.4725, 'learning_rate': 8.131723913816508e-06, 'epoch': 0.57}
+
57%|█████▋ | 6849/11952 [3:49:33<8:26:39, 5.96s/it]7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...6 AutoResumeHook: Checking whether to suspend...
+
+
57%|█████▋ | 6850/11952 [3:49:39<8:22:56, 5.91s/it]4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4699, 'learning_rate': 8.129061791700903e-06, 'epoch': 0.57}
+
57%|█████▋ | 6850/11952 [3:49:39<8:22:56, 5.91s/it]
57%|█████▋ | 6851/11952 [3:49:45<8:25:55, 5.95s/it]
{'loss': 0.4892, 'learning_rate': 8.126399806979217e-06, 'epoch': 0.57}
+
57%|█████▋ | 6851/11952 [3:49:45<8:25:55, 5.95s/it]
57%|█████▋ | 6852/11952 [3:49:50<8:18:30, 5.86s/it]
{'loss': 0.4647, 'learning_rate': 8.123737959846937e-06, 'epoch': 0.57}
+
57%|█████▋ | 6852/11952 [3:49:50<8:18:30, 5.86s/it]
57%|█████▋ | 6853/11952 [3:49:56<8:21:42, 5.90s/it]
{'loss': 0.4725, 'learning_rate': 8.121076250499539e-06, 'epoch': 0.57}
+
57%|█████▋ | 6853/11952 [3:49:56<8:21:42, 5.90s/it]
57%|█████▋ | 6854/11952 [3:50:02<8:15:18, 5.83s/it]
{'loss': 0.4585, 'learning_rate': 8.118414679132484e-06, 'epoch': 0.57}
+
57%|█████▋ | 6854/11952 [3:50:02<8:15:18, 5.83s/it]
57%|█████▋ | 6855/11952 [3:50:08<8:08:06, 5.75s/it]
{'loss': 0.481, 'learning_rate': 8.115753245941225e-06, 'epoch': 0.57}
+
57%|█████▋ | 6855/11952 [3:50:08<8:08:06, 5.75s/it]
57%|█████▋ | 6856/11952 [3:50:13<8:11:18, 5.78s/it]
{'loss': 0.4593, 'learning_rate': 8.113091951121215e-06, 'epoch': 0.57}
+
57%|█████▋ | 6856/11952 [3:50:13<8:11:18, 5.78s/it]
57%|█████▋ | 6857/11952 [3:50:19<8:14:41, 5.83s/it]
{'loss': 0.4727, 'learning_rate': 8.110430794867884e-06, 'epoch': 0.57}
+
57%|█████▋ | 6857/11952 [3:50:19<8:14:41, 5.83s/it]
57%|█████▋ | 6858/11952 [3:50:25<8:11:09, 5.79s/it]
{'loss': 0.4692, 'learning_rate': 8.107769777376657e-06, 'epoch': 0.57}
+
57%|█████▋ | 6858/11952 [3:50:25<8:11:09, 5.79s/it]
57%|█████▋ | 6859/11952 [3:50:31<8:14:13, 5.82s/it]
{'loss': 0.4705, 'learning_rate': 8.105108898842946e-06, 'epoch': 0.57}
+
57%|█████▋ | 6859/11952 [3:50:31<8:14:13, 5.82s/it]
57%|█████▋ | 6860/11952 [3:50:37<8:17:20, 5.86s/it]
{'loss': 0.4907, 'learning_rate': 8.102448159462155e-06, 'epoch': 0.57}
+
57%|█████▋ | 6860/11952 [3:50:37<8:17:20, 5.86s/it]
57%|█████▋ | 6861/11952 [3:50:43<8:14:21, 5.83s/it]
{'loss': 0.4831, 'learning_rate': 8.099787559429682e-06, 'epoch': 0.57}
+
57%|█████▋ | 6861/11952 [3:50:43<8:14:21, 5.83s/it]
57%|█████▋ | 6862/11952 [3:50:48<8:13:09, 5.81s/it]
{'loss': 0.4815, 'learning_rate': 8.0971270989409e-06, 'epoch': 0.57}
+
57%|█████▋ | 6862/11952 [3:50:48<8:13:09, 5.81s/it]
57%|█████▋ | 6863/11952 [3:50:54<8:15:22, 5.84s/it]
{'loss': 0.4879, 'learning_rate': 8.094466778191194e-06, 'epoch': 0.57}
+
57%|█████▋ | 6863/11952 [3:50:54<8:15:22, 5.84s/it]
57%|█████▋ | 6864/11952 [3:51:00<8:13:11, 5.82s/it]
{'loss': 0.4851, 'learning_rate': 8.091806597375925e-06, 'epoch': 0.57}
+
57%|█████▋ | 6864/11952 [3:51:00<8:13:11, 5.82s/it]
57%|█████▋ | 6865/11952 [3:51:06<8:11:17, 5.79s/it]
{'loss': 0.4682, 'learning_rate': 8.089146556690437e-06, 'epoch': 0.57}
+
57%|█████▋ | 6865/11952 [3:51:06<8:11:17, 5.79s/it]
57%|█████▋ | 6866/11952 [3:51:12<8:10:57, 5.79s/it]
{'loss': 0.4849, 'learning_rate': 8.086486656330082e-06, 'epoch': 0.57}
+
57%|█████▋ | 6866/11952 [3:51:12<8:10:57, 5.79s/it]
57%|█████▋ | 6867/11952 [3:51:17<8:11:28, 5.80s/it]
{'loss': 0.4875, 'learning_rate': 8.083826896490186e-06, 'epoch': 0.57}
+
57%|█████▋ | 6867/11952 [3:51:17<8:11:28, 5.80s/it]
57%|█████▋ | 6868/11952 [3:51:23<8:13:26, 5.82s/it]
{'loss': 0.4755, 'learning_rate': 8.081167277366076e-06, 'epoch': 0.57}
+
57%|█████▋ | 6868/11952 [3:51:23<8:13:26, 5.82s/it]
57%|█████▋ | 6869/11952 [3:51:29<8:08:49, 5.77s/it]
{'loss': 0.4663, 'learning_rate': 8.078507799153053e-06, 'epoch': 0.57}
+
57%|█████▋ | 6869/11952 [3:51:29<8:08:49, 5.77s/it]
57%|█████▋ | 6870/11952 [3:51:35<8:12:58, 5.82s/it]
{'loss': 0.4806, 'learning_rate': 8.07584846204643e-06, 'epoch': 0.57}
+
57%|█████▋ | 6870/11952 [3:51:35<8:12:58, 5.82s/it]
57%|█████▋ | 6871/11952 [3:51:41<8:15:24, 5.85s/it]
{'loss': 0.4771, 'learning_rate': 8.073189266241492e-06, 'epoch': 0.57}
+
57%|█████▋ | 6871/11952 [3:51:41<8:15:24, 5.85s/it]
57%|█████▋ | 6872/11952 [3:51:47<8:20:36, 5.91s/it]
{'loss': 0.4727, 'learning_rate': 8.070530211933522e-06, 'epoch': 0.57}
+
57%|█████▋ | 6872/11952 [3:51:47<8:20:36, 5.91s/it]
58%|█████▊ | 6873/11952 [3:51:53<8:16:28, 5.86s/it]
{'loss': 0.4623, 'learning_rate': 8.067871299317786e-06, 'epoch': 0.58}
+
58%|█████▊ | 6873/11952 [3:51:53<8:16:28, 5.86s/it]
58%|█████▊ | 6874/11952 [3:51:58<8:12:07, 5.81s/it]
{'loss': 0.5038, 'learning_rate': 8.065212528589545e-06, 'epoch': 0.58}
+
58%|█████▊ | 6874/11952 [3:51:58<8:12:07, 5.81s/it]
58%|█████▊ | 6875/11952 [3:52:04<8:19:44, 5.91s/it]
{'loss': 0.4703, 'learning_rate': 8.062553899944049e-06, 'epoch': 0.58}
+
58%|█████▊ | 6875/11952 [3:52:04<8:19:44, 5.91s/it]
58%|█████▊ | 6876/11952 [3:52:10<8:15:19, 5.85s/it]
{'loss': 0.4934, 'learning_rate': 8.059895413576535e-06, 'epoch': 0.58}
+
58%|█████▊ | 6876/11952 [3:52:10<8:15:19, 5.85s/it]
58%|█████▊ | 6877/11952 [3:52:16<8:15:46, 5.86s/it]
{'loss': 0.4898, 'learning_rate': 8.057237069682235e-06, 'epoch': 0.58}
+
58%|█████▊ | 6877/11952 [3:52:16<8:15:46, 5.86s/it]
58%|█████▊ | 6878/11952 [3:52:22<8:14:09, 5.84s/it]
{'loss': 0.4677, 'learning_rate': 8.054578868456364e-06, 'epoch': 0.58}
+
58%|█████▊ | 6878/11952 [3:52:22<8:14:09, 5.84s/it]
58%|█████▊ | 6879/11952 [3:52:28<8:18:43, 5.90s/it]
{'loss': 0.5034, 'learning_rate': 8.05192081009413e-06, 'epoch': 0.58}
+
58%|█████▊ | 6879/11952 [3:52:28<8:18:43, 5.90s/it]
58%|█████▊ | 6880/11952 [3:52:34<8:16:37, 5.87s/it]
{'loss': 0.4796, 'learning_rate': 8.049262894790725e-06, 'epoch': 0.58}
+
58%|█████▊ | 6880/11952 [3:52:34<8:16:37, 5.87s/it]
58%|█████▊ | 6881/11952 [3:52:39<8:14:19, 5.85s/it]
{'loss': 0.4751, 'learning_rate': 8.046605122741343e-06, 'epoch': 0.58}
+
58%|█████▊ | 6881/11952 [3:52:40<8:14:19, 5.85s/it]
58%|█████▊ | 6882/11952 [3:52:45<8:04:49, 5.74s/it]
{'loss': 0.4621, 'learning_rate': 8.04394749414115e-06, 'epoch': 0.58}
+
58%|█████▊ | 6882/11952 [3:52:45<8:04:49, 5.74s/it]
58%|█████▊ | 6883/11952 [3:52:51<8:03:19, 5.72s/it]
{'loss': 0.4772, 'learning_rate': 8.041290009185325e-06, 'epoch': 0.58}
+
58%|█████▊ | 6883/11952 [3:52:51<8:03:19, 5.72s/it]
58%|█████▊ | 6884/11952 [3:52:56<8:03:13, 5.72s/it]
{'loss': 0.471, 'learning_rate': 8.038632668069011e-06, 'epoch': 0.58}
+
58%|█████▊ | 6884/11952 [3:52:56<8:03:13, 5.72s/it]
58%|█████▊ | 6885/11952 [3:53:03<8:17:43, 5.89s/it]
{'loss': 0.4558, 'learning_rate': 8.035975470987357e-06, 'epoch': 0.58}
+
58%|█████▊ | 6885/11952 [3:53:03<8:17:43, 5.89s/it]
58%|█████▊ | 6886/11952 [3:53:09<8:16:14, 5.88s/it]
{'loss': 0.4728, 'learning_rate': 8.033318418135494e-06, 'epoch': 0.58}
+
58%|█████▊ | 6886/11952 [3:53:09<8:16:14, 5.88s/it]
58%|█████▊ | 6887/11952 [3:53:14<8:14:44, 5.86s/it]
{'loss': 0.4667, 'learning_rate': 8.03066150970855e-06, 'epoch': 0.58}
+
58%|█████▊ | 6887/11952 [3:53:14<8:14:44, 5.86s/it]
58%|█████▊ | 6888/11952 [3:53:20<8:13:42, 5.85s/it]
{'loss': 0.4804, 'learning_rate': 8.02800474590163e-06, 'epoch': 0.58}
+
58%|█████▊ | 6888/11952 [3:53:20<8:13:42, 5.85s/it]
58%|█████▊ | 6889/11952 [3:53:26<8:07:38, 5.78s/it]
{'loss': 0.4809, 'learning_rate': 8.025348126909837e-06, 'epoch': 0.58}
+
58%|█████▊ | 6889/11952 [3:53:26<8:07:38, 5.78s/it]
58%|█████▊ | 6890/11952 [3:53:32<8:21:15, 5.94s/it]
{'loss': 0.4799, 'learning_rate': 8.02269165292827e-06, 'epoch': 0.58}
+
58%|█████▊ | 6890/11952 [3:53:32<8:21:15, 5.94s/it]
58%|█████▊ | 6891/11952 [3:53:38<8:15:53, 5.88s/it]
{'loss': 0.456, 'learning_rate': 8.020035324152e-06, 'epoch': 0.58}
+
58%|█████▊ | 6891/11952 [3:53:38<8:15:53, 5.88s/it]
58%|█████▊ | 6892/11952 [3:53:43<8:08:04, 5.79s/it]
{'loss': 0.4874, 'learning_rate': 8.017379140776103e-06, 'epoch': 0.58}
+
58%|█████▊ | 6892/11952 [3:53:43<8:08:04, 5.79s/it]
58%|█████▊ | 6893/11952 [3:53:49<8:11:51, 5.83s/it]
{'loss': 0.4772, 'learning_rate': 8.014723102995635e-06, 'epoch': 0.58}
+
58%|█████▊ | 6893/11952 [3:53:49<8:11:51, 5.83s/it]
58%|█████▊ | 6894/11952 [3:53:55<8:08:59, 5.80s/it]
{'loss': 0.4651, 'learning_rate': 8.012067211005645e-06, 'epoch': 0.58}
+
58%|█████▊ | 6894/11952 [3:53:55<8:08:59, 5.80s/it]
58%|█████▊ | 6895/11952 [3:54:01<8:17:37, 5.90s/it]
{'loss': 0.4828, 'learning_rate': 8.00941146500117e-06, 'epoch': 0.58}
+
58%|█████▊ | 6895/11952 [3:54:01<8:17:37, 5.90s/it]
58%|█████▊ | 6896/11952 [3:54:07<8:15:42, 5.88s/it]
{'loss': 0.4682, 'learning_rate': 8.006755865177233e-06, 'epoch': 0.58}
+
58%|█████▊ | 6896/11952 [3:54:07<8:15:42, 5.88s/it]
58%|█████▊ | 6897/11952 [3:54:13<8:16:15, 5.89s/it]
{'loss': 0.4852, 'learning_rate': 8.00410041172886e-06, 'epoch': 0.58}
+
58%|█████▊ | 6897/11952 [3:54:13<8:16:15, 5.89s/it]
58%|█████▊ | 6898/11952 [3:54:19<8:17:18, 5.90s/it]
{'loss': 0.4691, 'learning_rate': 8.001445104851052e-06, 'epoch': 0.58}
+
58%|█████▊ | 6898/11952 [3:54:19<8:17:18, 5.90s/it]
58%|█████▊ | 6899/11952 [3:54:25<8:12:28, 5.85s/it]
{'loss': 0.4742, 'learning_rate': 7.998789944738801e-06, 'epoch': 0.58}
+
58%|█████▊ | 6899/11952 [3:54:25<8:12:28, 5.85s/it]2 AutoResumeHook: Checking whether to suspend...
+063 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...7
+ AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
58%|█████▊ | 6900/11952 [3:54:31<8:19:48, 5.94s/it]5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4673, 'learning_rate': 7.996134931587092e-06, 'epoch': 0.58}
+
58%|█████▊ | 6900/11952 [3:54:31<8:19:48, 5.94s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-6900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
58%|█████▊ | 6901/11952 [3:54:59<17:48:02, 12.69s/it]
{'loss': 0.502, 'learning_rate': 7.993480065590902e-06, 'epoch': 0.58}
+
58%|█████▊ | 6901/11952 [3:54:59<17:48:02, 12.69s/it]
58%|█████▊ | 6902/11952 [3:55:05<14:55:20, 10.64s/it]
{'loss': 0.4745, 'learning_rate': 7.990825346945188e-06, 'epoch': 0.58}
+
58%|█████▊ | 6902/11952 [3:55:05<14:55:20, 10.64s/it]
58%|█████▊ | 6903/11952 [3:55:11<12:54:56, 9.21s/it]
{'loss': 0.4806, 'learning_rate': 7.9881707758449e-06, 'epoch': 0.58}
+
58%|█████▊ | 6903/11952 [3:55:11<12:54:56, 9.21s/it]
58%|█████▊ | 6904/11952 [3:55:17<11:37:36, 8.29s/it]
{'loss': 0.4838, 'learning_rate': 7.985516352484987e-06, 'epoch': 0.58}
+
58%|█████▊ | 6904/11952 [3:55:17<11:37:36, 8.29s/it]
58%|█████▊ | 6905/11952 [3:55:23<10:32:20, 7.52s/it]
{'loss': 0.4686, 'learning_rate': 7.982862077060376e-06, 'epoch': 0.58}
+
58%|█████▊ | 6905/11952 [3:55:23<10:32:20, 7.52s/it]
58%|█████▊ | 6906/11952 [3:55:29<9:47:57, 6.99s/it]
{'loss': 0.466, 'learning_rate': 7.98020794976598e-06, 'epoch': 0.58}
+
58%|█████▊ | 6906/11952 [3:55:29<9:47:57, 6.99s/it]
58%|█████▊ | 6907/11952 [3:55:34<9:14:55, 6.60s/it]
{'loss': 0.4756, 'learning_rate': 7.977553970796713e-06, 'epoch': 0.58}
+
58%|█████▊ | 6907/11952 [3:55:34<9:14:55, 6.60s/it]
58%|█████▊ | 6908/11952 [3:55:40<8:54:16, 6.36s/it]
{'loss': 0.4717, 'learning_rate': 7.974900140347473e-06, 'epoch': 0.58}
+
58%|█████▊ | 6908/11952 [3:55:40<8:54:16, 6.36s/it]
58%|█████▊ | 6909/11952 [3:55:46<8:36:59, 6.15s/it]
{'loss': 0.4496, 'learning_rate': 7.97224645861314e-06, 'epoch': 0.58}
+
58%|█████▊ | 6909/11952 [3:55:46<8:36:59, 6.15s/it]
58%|█████▊ | 6910/11952 [3:55:52<8:28:42, 6.05s/it]
{'loss': 0.4874, 'learning_rate': 7.969592925788592e-06, 'epoch': 0.58}
+
58%|█████▊ | 6910/11952 [3:55:52<8:28:42, 6.05s/it]
58%|█████▊ | 6911/11952 [3:55:57<8:21:31, 5.97s/it]
{'loss': 0.482, 'learning_rate': 7.966939542068694e-06, 'epoch': 0.58}
+
58%|█████▊ | 6911/11952 [3:55:57<8:21:31, 5.97s/it]
58%|█████▊ | 6912/11952 [3:56:03<8:23:51, 6.00s/it]
{'loss': 0.4715, 'learning_rate': 7.964286307648305e-06, 'epoch': 0.58}
+
58%|█████▊ | 6912/11952 [3:56:03<8:23:51, 6.00s/it]
58%|█████▊ | 6913/11952 [3:56:09<8:20:41, 5.96s/it]
{'loss': 0.4723, 'learning_rate': 7.96163322272226e-06, 'epoch': 0.58}
+
58%|█████▊ | 6913/11952 [3:56:09<8:20:41, 5.96s/it]
58%|█████▊ | 6914/11952 [3:56:15<8:12:20, 5.86s/it]
{'loss': 0.4682, 'learning_rate': 7.958980287485394e-06, 'epoch': 0.58}
+
58%|█████▊ | 6914/11952 [3:56:15<8:12:20, 5.86s/it]
58%|█████▊ | 6915/11952 [3:56:21<8:11:51, 5.86s/it]
{'loss': 0.4634, 'learning_rate': 7.956327502132523e-06, 'epoch': 0.58}
+
58%|█████▊ | 6915/11952 [3:56:21<8:11:51, 5.86s/it]
58%|█████▊ | 6916/11952 [3:56:27<8:10:07, 5.84s/it]
{'loss': 0.4693, 'learning_rate': 7.953674866858462e-06, 'epoch': 0.58}
+
58%|█████▊ | 6916/11952 [3:56:27<8:10:07, 5.84s/it]
58%|█████▊ | 6917/11952 [3:56:33<8:19:50, 5.96s/it]
{'loss': 0.4736, 'learning_rate': 7.951022381858005e-06, 'epoch': 0.58}
+
58%|█████▊ | 6917/11952 [3:56:33<8:19:50, 5.96s/it]
58%|█████▊ | 6918/11952 [3:56:38<8:14:30, 5.89s/it]
{'loss': 0.4643, 'learning_rate': 7.948370047325946e-06, 'epoch': 0.58}
+
58%|█████▊ | 6918/11952 [3:56:38<8:14:30, 5.89s/it]
58%|█████▊ | 6919/11952 [3:56:44<8:13:37, 5.88s/it]
{'loss': 0.4887, 'learning_rate': 7.945717863457057e-06, 'epoch': 0.58}
+
58%|█████▊ | 6919/11952 [3:56:44<8:13:37, 5.88s/it]
58%|█████▊ | 6920/11952 [3:56:50<8:14:20, 5.89s/it]
{'loss': 0.4975, 'learning_rate': 7.943065830446104e-06, 'epoch': 0.58}
+
58%|█████▊ | 6920/11952 [3:56:50<8:14:20, 5.89s/it]
58%|█████▊ | 6921/11952 [3:56:56<8:11:48, 5.87s/it]
{'loss': 0.5002, 'learning_rate': 7.940413948487838e-06, 'epoch': 0.58}
+
58%|█████▊ | 6921/11952 [3:56:56<8:11:48, 5.87s/it]
58%|█████▊ | 6922/11952 [3:57:02<8:17:07, 5.93s/it]
{'loss': 0.4834, 'learning_rate': 7.937762217777007e-06, 'epoch': 0.58}
+
58%|█████▊ | 6922/11952 [3:57:02<8:17:07, 5.93s/it]
58%|█████▊ | 6923/11952 [3:57:08<8:09:46, 5.84s/it]
{'loss': 0.4903, 'learning_rate': 7.935110638508339e-06, 'epoch': 0.58}
+
58%|█████▊ | 6923/11952 [3:57:08<8:09:46, 5.84s/it]
58%|█████▊ | 6924/11952 [3:57:14<8:08:31, 5.83s/it]
{'loss': 0.4688, 'learning_rate': 7.93245921087656e-06, 'epoch': 0.58}
+
58%|█████▊ | 6924/11952 [3:57:14<8:08:31, 5.83s/it]
58%|█████▊ | 6925/11952 [3:57:20<8:16:24, 5.92s/it]
{'loss': 0.4765, 'learning_rate': 7.929807935076376e-06, 'epoch': 0.58}
+
58%|█████▊ | 6925/11952 [3:57:20<8:16:24, 5.92s/it]
58%|█████▊ | 6926/11952 [3:57:26<8:19:25, 5.96s/it]
{'loss': 0.4793, 'learning_rate': 7.927156811302486e-06, 'epoch': 0.58}
+
58%|█████▊ | 6926/11952 [3:57:26<8:19:25, 5.96s/it]
58%|█████▊ | 6927/11952 [3:57:32<8:24:11, 6.02s/it]
{'loss': 0.4832, 'learning_rate': 7.92450583974958e-06, 'epoch': 0.58}
+
58%|█████▊ | 6927/11952 [3:57:32<8:24:11, 6.02s/it]
58%|█████▊ | 6928/11952 [3:57:38<8:15:35, 5.92s/it]
{'loss': 0.4811, 'learning_rate': 7.921855020612333e-06, 'epoch': 0.58}
+
58%|█████▊ | 6928/11952 [3:57:38<8:15:35, 5.92s/it]
58%|█████▊ | 6929/11952 [3:57:43<8:14:31, 5.91s/it]
{'loss': 0.4649, 'learning_rate': 7.919204354085408e-06, 'epoch': 0.58}
+
58%|█████▊ | 6929/11952 [3:57:43<8:14:31, 5.91s/it]
58%|█████▊ | 6930/11952 [3:57:49<8:13:18, 5.89s/it]
{'loss': 0.4554, 'learning_rate': 7.916553840363458e-06, 'epoch': 0.58}
+
58%|█████▊ | 6930/11952 [3:57:49<8:13:18, 5.89s/it]
58%|█████▊ | 6931/11952 [3:57:55<8:17:41, 5.95s/it]
{'loss': 0.4636, 'learning_rate': 7.913903479641131e-06, 'epoch': 0.58}
+
58%|█████▊ | 6931/11952 [3:57:55<8:17:41, 5.95s/it]Jun 10 20:39:24.547678 2777762 slurmstepd 0x155550ab8700: error: *** STEP 8833833.0 ON batch-block1-2091 CANCELLED AT 2025-06-10T20:39:24 DUE TO TIME LIMIT ***
+srun: Job step aborted: Waiting up to 122 seconds for job step to finish.
+srun: error: batch-block1-2091: task 0: Terminated
+srun: Terminating StepId=8833833.0
+srun: job 8837928 queued and waiting for resources
+srun: job 8837928 has been allocated resources
+srun: Job 8837928 step creation temporarily disabled, retrying (Requested nodes are busy)
+srun: Step created for StepId=8837928.0
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+MASTER_ADDR=batch-block1-0069
+JobID: 8837928 | Full list: batch-block1-0069
+NETWORK=Efficient-Large-Model/VILA1.5-3b
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
+*****************************************
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:46,817] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 20:46:48,000] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-10 20:46:48,000] [INFO] [comm.py:625:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+[2025-06-10 20:46:48,000] [INFO] [comm.py:594:init_distributed] cdb=None
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+[2025-06-10 20:46:55,826] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 2.70B parameters
+
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.23s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.24s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.24s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.25s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.25s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.27s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.28s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.32s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.75s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.32s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.76s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.32s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.76s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.33s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.77s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.33s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.77s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.34s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.78s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.38s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.81s/it]
+
Loading checkpoint shards: 50%|█████ | 1/2 [00:07<00:07, 7.19s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:07<00:00, 3.38s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:07<00:00, 3.95s/it]
+[2025-06-10 20:47:04,005] [WARNING] [partition_parameters.py:836:_post_init_method] param `probe` in SiglipMultiheadAttentionPoolingHead not on GPU so was not broadcasted from rank 0
+[2025-06-10 20:47:04,006] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.13B parameters
+[2025-06-10 20:47:05,562] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.15B parameters
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[dist-0-of-8] LlavaLlamaModel(
+ (llm): LlamaForCausalLM(
+ (model): LlamaModel(
+ (embed_tokens): Embedding(32000, 2560, padding_idx=0)
+ (layers): ModuleList(
+ (0-31): 32 x LlamaDecoderLayer(
+ (self_attn): LlamaFlashAttention2(
+ (q_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (k_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (v_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (o_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (rotary_emb): LlamaRotaryEmbedding()
+ )
+ (mlp): LlamaMLP(
+ (gate_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (up_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (down_proj): Linear(in_features=6912, out_features=2560, bias=False)
+ (act_fn): SiLU()
+ )
+ (input_layernorm): LlamaRMSNorm()
+ (post_attention_layernorm): LlamaRMSNorm()
+ )
+ )
+ (norm): LlamaRMSNorm()
+ )
+ (lm_head): Linear(in_features=2560, out_features=32000, bias=False)
+ )
+ (vision_tower): SiglipVisionTower(
+ (vision_tower): SiglipVisionModel(
+ (vision_model): SiglipVisionTransformer(
+ (embeddings): SiglipVisionEmbeddings(
+ (patch_embedding): Conv2d(3, 1152, kernel_size=(14, 14), stride=(14, 14), padding=valid)
+ (position_embedding): Embedding(729, 1152)
+ )
+ (encoder): SiglipEncoder(
+ (layers): ModuleList(
+ (0-26): 27 x SiglipEncoderLayer(
+ (self_attn): SiglipAttention(
+ (k_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (v_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (q_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (out_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layer_norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ (layer_norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ )
+ )
+ )
+ (post_layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (head): SiglipMultiheadAttentionPoolingHead(
+ (attention): MultiheadAttention(
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ )
+ )
+ )
+ )
+ (mm_projector): MultimodalProjector(
+ (layers): Sequential(
+ (0): DownSampleBlock()
+ (1): LayerNorm((4608,), eps=1e-05, elementwise_affine=True)
+ (2): Linear(in_features=4608, out_features=2560, bias=True)
+ (3): GELU(approximate='none')
+ (4): Linear(in_features=2560, out_features=2560, bias=True)
+ )
+ )
+)
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[dist-0-of-8] Tunable parameters:
+language model True
+[dist-0-of-8] vision tower True
+[dist-0-of-8] mm projector True
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8292460441589355
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8139371871948242
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8324503898620605
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8348307609558105
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8280863761901855
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8371806144714355
+length of dataloader: 23905 3059964
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8285441398620605
+[GPU memory] before trainer 0.8330912590026855
+Parameter Offload: Total persistent parameters: 593856 in 349 params
+wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.18.7
+wandb: Run data is saved locally in /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/wandb/run-20250610_204828-e6q2fclk
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run vila_3b_path_mask
+wandb: ⭐️ View project at https://wandb.ai/memmelma/VILA
+wandb: 🚀 View run at https://wandb.ai/memmelma/VILA/runs/e6q2fclk
+
0%| | 0/11952 [00:00, ?it/s]Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+
58%|█████▊ | 6901/11952 [00:23<00:17, 292.11it/s]
{'loss': 0.502, 'learning_rate': 7.993480065590902e-06, 'epoch': 0.58}
+
58%|█████▊ | 6901/11952 [00:23<00:17, 292.11it/s]
{'loss': 0.4744, 'learning_rate': 7.990825346945188e-06, 'epoch': 0.58}
+
58%|█████▊ | 6902/11952 [00:29<00:17, 292.11it/s]
{'loss': 0.4806, 'learning_rate': 7.9881707758449e-06, 'epoch': 0.58}
+
58%|█████▊ | 6903/11952 [00:35<00:17, 292.11it/s]
58%|█████▊ | 6903/11952 [00:38<00:17, 292.11it/s]
58%|█████▊ | 6904/11952 [00:41<00:35, 141.36it/s]
{'loss': 0.4837, 'learning_rate': 7.985516352484987e-06, 'epoch': 0.58}
+
58%|█████▊ | 6904/11952 [00:41<00:35, 141.36it/s]
58%|█████▊ | 6905/11952 [00:46<00:44, 114.43it/s]
{'loss': 0.4685, 'learning_rate': 7.982862077060376e-06, 'epoch': 0.58}
+
58%|█████▊ | 6905/11952 [00:46<00:44, 114.43it/s]
58%|█████▊ | 6906/11952 [00:52<00:56, 89.75it/s]
{'loss': 0.466, 'learning_rate': 7.98020794976598e-06, 'epoch': 0.58}
+
58%|█████▊ | 6906/11952 [00:52<00:56, 89.75it/s]
58%|█████▊ | 6907/11952 [00:58<01:13, 68.91it/s]
{'loss': 0.4756, 'learning_rate': 7.977553970796713e-06, 'epoch': 0.58}
+
58%|█████▊ | 6907/11952 [00:58<01:13, 68.91it/s]
58%|█████▊ | 6908/11952 [01:03<01:38, 51.42it/s]
{'loss': 0.472, 'learning_rate': 7.974900140347473e-06, 'epoch': 0.58}
+
58%|█████▊ | 6908/11952 [01:03<01:38, 51.42it/s]
58%|█████▊ | 6909/11952 [01:09<02:12, 38.02it/s]
{'loss': 0.4496, 'learning_rate': 7.97224645861314e-06, 'epoch': 0.58}
+
58%|█████▊ | 6909/11952 [01:09<02:12, 38.02it/s]
58%|█████▊ | 6910/11952 [01:15<03:03, 27.47it/s]
{'loss': 0.4872, 'learning_rate': 7.969592925788592e-06, 'epoch': 0.58}
+
58%|█████▊ | 6910/11952 [01:15<03:03, 27.47it/s]
58%|█████▊ | 6911/11952 [01:21<04:14, 19.77it/s]
{'loss': 0.4819, 'learning_rate': 7.966939542068694e-06, 'epoch': 0.58}
+
58%|█████▊ | 6911/11952 [01:21<04:14, 19.77it/s]
58%|█████▊ | 6912/11952 [01:27<06:01, 13.94it/s]
{'loss': 0.4716, 'learning_rate': 7.964286307648305e-06, 'epoch': 0.58}
+
58%|█████▊ | 6912/11952 [01:27<06:01, 13.94it/s]
58%|█████▊ | 6913/11952 [01:32<08:27, 9.92it/s]
{'loss': 0.4722, 'learning_rate': 7.96163322272226e-06, 'epoch': 0.58}
+
58%|█████▊ | 6913/11952 [01:32<08:27, 9.92it/s]
58%|█████▊ | 6914/11952 [01:38<11:46, 7.13it/s]
{'loss': 0.4683, 'learning_rate': 7.958980287485394e-06, 'epoch': 0.58}
+
58%|█████▊ | 6914/11952 [01:38<11:46, 7.13it/s]
58%|█████▊ | 6915/11952 [01:44<16:34, 5.06it/s]
{'loss': 0.4634, 'learning_rate': 7.956327502132523e-06, 'epoch': 0.58}
+
58%|█████▊ | 6915/11952 [01:44<16:34, 5.06it/s]
58%|█████▊ | 6916/11952 [01:50<23:12, 3.62it/s]
{'loss': 0.4692, 'learning_rate': 7.953674866858462e-06, 'epoch': 0.58}
+
58%|█████▊ | 6916/11952 [01:50<23:12, 3.62it/s]
58%|█████▊ | 6917/11952 [01:56<33:04, 2.54it/s]
{'loss': 0.4735, 'learning_rate': 7.951022381858005e-06, 'epoch': 0.58}
+
58%|█████▊ | 6917/11952 [01:56<33:04, 2.54it/s]
58%|█████▊ | 6918/11952 [02:02<45:25, 1.85it/s]
{'loss': 0.4642, 'learning_rate': 7.948370047325946e-06, 'epoch': 0.58}
+
58%|█████▊ | 6918/11952 [02:02<45:25, 1.85it/s]
58%|█████▊ | 6919/11952 [02:07<1:02:18, 1.35it/s]
{'loss': 0.4884, 'learning_rate': 7.945717863457057e-06, 'epoch': 0.58}
+
58%|█████▊ | 6919/11952 [02:07<1:02:18, 1.35it/s]
58%|█████▊ | 6920/11952 [02:13<1:24:30, 1.01s/it]
{'loss': 0.4975, 'learning_rate': 7.943065830446104e-06, 'epoch': 0.58}
+
58%|█████▊ | 6920/11952 [02:13<1:24:30, 1.01s/it]
58%|█████▊ | 6921/11952 [02:19<1:51:51, 1.33s/it]
{'loss': 0.5001, 'learning_rate': 7.940413948487838e-06, 'epoch': 0.58}
+
58%|█████▊ | 6921/11952 [02:19<1:51:51, 1.33s/it]
58%|█████▊ | 6922/11952 [02:25<2:27:01, 1.75s/it]
{'loss': 0.4835, 'learning_rate': 7.937762217777007e-06, 'epoch': 0.58}
+
58%|█████▊ | 6922/11952 [02:25<2:27:01, 1.75s/it]
58%|█████▊ | 6923/11952 [02:31<3:03:46, 2.19s/it]
{'loss': 0.4903, 'learning_rate': 7.935110638508339e-06, 'epoch': 0.58}
+
58%|█████▊ | 6923/11952 [02:31<3:03:46, 2.19s/it]
58%|█████▊ | 6924/11952 [02:36<3:45:14, 2.69s/it]
{'loss': 0.4688, 'learning_rate': 7.93245921087656e-06, 'epoch': 0.58}
+
58%|█████▊ | 6924/11952 [02:36<3:45:14, 2.69s/it]
58%|█████▊ | 6925/11952 [02:43<4:32:47, 3.26s/it]
{'loss': 0.4764, 'learning_rate': 7.929807935076376e-06, 'epoch': 0.58}
+
58%|█████▊ | 6925/11952 [02:43<4:32:47, 3.26s/it]
58%|█████▊ | 6926/11952 [02:49<5:17:13, 3.79s/it]
{'loss': 0.4792, 'learning_rate': 7.927156811302486e-06, 'epoch': 0.58}
+
58%|█████▊ | 6926/11952 [02:49<5:17:13, 3.79s/it]
58%|█████▊ | 6927/11952 [02:55<5:58:51, 4.28s/it]
{'loss': 0.4833, 'learning_rate': 7.92450583974958e-06, 'epoch': 0.58}
+
58%|█████▊ | 6927/11952 [02:55<5:58:51, 4.28s/it]
58%|█████▊ | 6928/11952 [03:00<6:25:57, 4.61s/it]
{'loss': 0.4812, 'learning_rate': 7.921855020612333e-06, 'epoch': 0.58}
+
58%|█████▊ | 6928/11952 [03:00<6:25:57, 4.61s/it]
58%|█████▊ | 6929/11952 [03:06<6:52:05, 4.92s/it]
{'loss': 0.4649, 'learning_rate': 7.919204354085408e-06, 'epoch': 0.58}
+
58%|█████▊ | 6929/11952 [03:06<6:52:05, 4.92s/it]
58%|█████▊ | 6930/11952 [03:12<7:11:55, 5.16s/it]
{'loss': 0.4554, 'learning_rate': 7.916553840363458e-06, 'epoch': 0.58}
+
58%|█████▊ | 6930/11952 [03:12<7:11:55, 5.16s/it]
58%|█████▊ | 6931/11952 [03:18<7:33:10, 5.42s/it]
{'loss': 0.4636, 'learning_rate': 7.913903479641131e-06, 'epoch': 0.58}
+
58%|█████▊ | 6931/11952 [03:18<7:33:10, 5.42s/it]
58%|█████▊ | 6932/11952 [03:24<7:51:09, 5.63s/it]
{'loss': 0.5109, 'learning_rate': 7.911253272113056e-06, 'epoch': 0.58}
+
58%|█████▊ | 6932/11952 [03:24<7:51:09, 5.63s/it]
58%|█████▊ | 6933/11952 [03:30<7:56:00, 5.69s/it]
{'loss': 0.4811, 'learning_rate': 7.908603217973853e-06, 'epoch': 0.58}
+
58%|█████▊ | 6933/11952 [03:30<7:56:00, 5.69s/it]
58%|█████▊ | 6934/11952 [03:36<7:59:23, 5.73s/it]
{'loss': 0.4753, 'learning_rate': 7.905953317418131e-06, 'epoch': 0.58}
+
58%|█████▊ | 6934/11952 [03:36<7:59:23, 5.73s/it]
58%|█████▊ | 6935/11952 [03:42<7:59:04, 5.73s/it]
{'loss': 0.4691, 'learning_rate': 7.903303570640488e-06, 'epoch': 0.58}
+
58%|█████▊ | 6935/11952 [03:42<7:59:04, 5.73s/it]
58%|█████▊ | 6936/11952 [03:47<7:58:47, 5.73s/it]
{'loss': 0.4661, 'learning_rate': 7.900653977835507e-06, 'epoch': 0.58}
+
58%|█████▊ | 6936/11952 [03:47<7:58:47, 5.73s/it]
58%|█████▊ | 6937/11952 [03:54<8:15:18, 5.93s/it]
{'loss': 0.4696, 'learning_rate': 7.898004539197766e-06, 'epoch': 0.58}
+
58%|█████▊ | 6937/11952 [03:54<8:15:18, 5.93s/it]
58%|█████▊ | 6938/11952 [04:00<8:12:12, 5.89s/it]
{'loss': 0.4606, 'learning_rate': 7.89535525492183e-06, 'epoch': 0.58}
+
58%|█████▊ | 6938/11952 [04:00<8:12:12, 5.89s/it]
58%|█████▊ | 6939/11952 [04:05<8:08:46, 5.85s/it]
{'loss': 0.4798, 'learning_rate': 7.892706125202254e-06, 'epoch': 0.58}
+
58%|█████▊ | 6939/11952 [04:05<8:08:46, 5.85s/it]
58%|█████▊ | 6940/11952 [04:11<8:06:53, 5.83s/it]
{'loss': 0.4586, 'learning_rate': 7.890057150233572e-06, 'epoch': 0.58}
+
58%|█████▊ | 6940/11952 [04:11<8:06:53, 5.83s/it]
58%|█████▊ | 6941/11952 [04:17<8:11:04, 5.88s/it]
{'loss': 0.4835, 'learning_rate': 7.887408330210316e-06, 'epoch': 0.58}
+
58%|█████▊ | 6941/11952 [04:17<8:11:04, 5.88s/it]
58%|█████▊ | 6942/11952 [04:23<8:10:47, 5.88s/it]
{'loss': 0.4821, 'learning_rate': 7.884759665327008e-06, 'epoch': 0.58}
+
58%|█████▊ | 6942/11952 [04:23<8:10:47, 5.88s/it]
58%|█████▊ | 6943/11952 [04:29<8:06:58, 5.83s/it]
{'loss': 0.4927, 'learning_rate': 7.882111155778152e-06, 'epoch': 0.58}
+
58%|█████▊ | 6943/11952 [04:29<8:06:58, 5.83s/it]
58%|█████▊ | 6944/11952 [04:35<8:10:27, 5.88s/it]
{'loss': 0.4873, 'learning_rate': 7.879462801758239e-06, 'epoch': 0.58}
+
58%|█████▊ | 6944/11952 [04:35<8:10:27, 5.88s/it]
58%|█████▊ | 6945/11952 [04:41<8:09:29, 5.87s/it]
{'loss': 0.4801, 'learning_rate': 7.876814603461763e-06, 'epoch': 0.58}
+
58%|█████▊ | 6945/11952 [04:41<8:09:29, 5.87s/it]
58%|█████▊ | 6946/11952 [04:46<8:05:08, 5.81s/it]
{'loss': 0.476, 'learning_rate': 7.87416656108319e-06, 'epoch': 0.58}
+
58%|█████▊ | 6946/11952 [04:46<8:05:08, 5.81s/it]
58%|█████▊ | 6947/11952 [04:52<8:01:36, 5.77s/it]
{'loss': 0.464, 'learning_rate': 7.871518674816982e-06, 'epoch': 0.58}
+
58%|█████▊ | 6947/11952 [04:52<8:01:36, 5.77s/it]
58%|█████▊ | 6948/11952 [04:58<8:00:27, 5.76s/it]
{'loss': 0.4831, 'learning_rate': 7.86887094485759e-06, 'epoch': 0.58}
+
58%|█████▊ | 6948/11952 [04:58<8:00:27, 5.76s/it]
58%|█████▊ | 6949/11952 [05:03<7:58:50, 5.74s/it]
{'loss': 0.4791, 'learning_rate': 7.866223371399453e-06, 'epoch': 0.58}
+
58%|█████▊ | 6949/11952 [05:03<7:58:50, 5.74s/it]1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+76 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
58%|█████▊ | 6950/11952 [05:09<8:06:39, 5.84s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4936, 'learning_rate': 7.863575954636993e-06, 'epoch': 0.58}
+
58%|█████▊ | 6950/11952 [05:09<8:06:39, 5.84s/it]
58%|█████▊ | 6951/11952 [05:15<8:05:54, 5.83s/it]
{'loss': 0.4846, 'learning_rate': 7.860928694764632e-06, 'epoch': 0.58}
+
58%|█████▊ | 6951/11952 [05:15<8:05:54, 5.83s/it]
58%|█████▊ | 6952/11952 [05:21<7:59:15, 5.75s/it]
{'loss': 0.4687, 'learning_rate': 7.858281591976768e-06, 'epoch': 0.58}
+
58%|█████▊ | 6952/11952 [05:21<7:59:15, 5.75s/it]
58%|█████▊ | 6953/11952 [05:26<7:55:27, 5.71s/it]
{'loss': 0.4587, 'learning_rate': 7.8556346464678e-06, 'epoch': 0.58}
+
58%|█████▊ | 6953/11952 [05:26<7:55:27, 5.71s/it]
58%|█████▊ | 6954/11952 [05:32<7:59:35, 5.76s/it]
{'loss': 0.4825, 'learning_rate': 7.852987858432104e-06, 'epoch': 0.58}
+
58%|█████▊ | 6954/11952 [05:32<7:59:35, 5.76s/it]
58%|█████▊ | 6955/11952 [05:38<7:54:29, 5.70s/it]
{'loss': 0.4723, 'learning_rate': 7.850341228064048e-06, 'epoch': 0.58}
+
58%|█████▊ | 6955/11952 [05:38<7:54:29, 5.70s/it]
58%|█████▊ | 6956/11952 [05:44<7:56:00, 5.72s/it]
{'loss': 0.4522, 'learning_rate': 7.84769475555799e-06, 'epoch': 0.58}
+
58%|█████▊ | 6956/11952 [05:44<7:56:00, 5.72s/it]
58%|█████▊ | 6957/11952 [05:49<7:53:44, 5.69s/it]
{'loss': 0.484, 'learning_rate': 7.845048441108276e-06, 'epoch': 0.58}
+
58%|█████▊ | 6957/11952 [05:49<7:53:44, 5.69s/it]
58%|█████▊ | 6958/11952 [05:55<7:55:04, 5.71s/it]
{'loss': 0.4794, 'learning_rate': 7.842402284909242e-06, 'epoch': 0.58}
+
58%|█████▊ | 6958/11952 [05:55<7:55:04, 5.71s/it]
58%|█████▊ | 6959/11952 [06:01<8:08:13, 5.87s/it]
{'loss': 0.4794, 'learning_rate': 7.839756287155213e-06, 'epoch': 0.58}
+
58%|█████▊ | 6959/11952 [06:01<8:08:13, 5.87s/it]
58%|█████▊ | 6960/11952 [06:07<8:09:57, 5.89s/it]
{'loss': 0.4825, 'learning_rate': 7.837110448040495e-06, 'epoch': 0.58}
+
58%|█████▊ | 6960/11952 [06:07<8:09:57, 5.89s/it]
58%|█████▊ | 6961/11952 [06:13<8:06:37, 5.85s/it]
{'loss': 0.4612, 'learning_rate': 7.834464767759392e-06, 'epoch': 0.58}
+
58%|█████▊ | 6961/11952 [06:13<8:06:37, 5.85s/it]
58%|█████▊ | 6962/11952 [06:19<8:05:09, 5.83s/it]
{'loss': 0.4708, 'learning_rate': 7.831819246506187e-06, 'epoch': 0.58}
+
58%|█████▊ | 6962/11952 [06:19<8:05:09, 5.83s/it]
58%|█████▊ | 6963/11952 [06:24<8:02:37, 5.80s/it]
{'loss': 0.4607, 'learning_rate': 7.829173884475158e-06, 'epoch': 0.58}
+
58%|█████▊ | 6963/11952 [06:24<8:02:37, 5.80s/it]
58%|█████▊ | 6964/11952 [06:30<8:00:06, 5.78s/it]
{'loss': 0.4605, 'learning_rate': 7.826528681860567e-06, 'epoch': 0.58}
+
58%|█████▊ | 6964/11952 [06:30<8:00:06, 5.78s/it]
58%|█████▊ | 6965/11952 [06:36<8:06:11, 5.85s/it]
{'loss': 0.4779, 'learning_rate': 7.823883638856675e-06, 'epoch': 0.58}
+
58%|█████▊ | 6965/11952 [06:36<8:06:11, 5.85s/it]
58%|█████▊ | 6966/11952 [06:42<8:01:42, 5.80s/it]
{'loss': 0.4447, 'learning_rate': 7.821238755657716e-06, 'epoch': 0.58}
+
58%|█████▊ | 6966/11952 [06:42<8:01:42, 5.80s/it]
58%|█████▊ | 6967/11952 [06:48<8:04:23, 5.83s/it]
{'loss': 0.4876, 'learning_rate': 7.818594032457922e-06, 'epoch': 0.58}
+
58%|█████▊ | 6967/11952 [06:48<8:04:23, 5.83s/it]
58%|█████▊ | 6968/11952 [06:54<8:02:53, 5.81s/it]
{'loss': 0.4654, 'learning_rate': 7.815949469451506e-06, 'epoch': 0.58}
+
58%|█████▊ | 6968/11952 [06:54<8:02:53, 5.81s/it]
58%|█████▊ | 6969/11952 [06:59<8:06:11, 5.85s/it]
{'loss': 0.4654, 'learning_rate': 7.813305066832679e-06, 'epoch': 0.58}
+
58%|█████▊ | 6969/11952 [06:59<8:06:11, 5.85s/it]
58%|█████▊ | 6970/11952 [07:05<8:09:13, 5.89s/it]
{'loss': 0.4729, 'learning_rate': 7.810660824795632e-06, 'epoch': 0.58}
+
58%|█████▊ | 6970/11952 [07:05<8:09:13, 5.89s/it]
58%|█████▊ | 6971/11952 [07:11<8:06:46, 5.86s/it]
{'loss': 0.4886, 'learning_rate': 7.808016743534546e-06, 'epoch': 0.58}
+
58%|█████▊ | 6971/11952 [07:11<8:06:46, 5.86s/it]
58%|█████▊ | 6972/11952 [07:17<8:04:14, 5.83s/it]
{'loss': 0.4669, 'learning_rate': 7.805372823243595e-06, 'epoch': 0.58}
+
58%|█████▊ | 6972/11952 [07:17<8:04:14, 5.83s/it]
58%|█████▊ | 6973/11952 [07:23<8:11:31, 5.92s/it]
{'loss': 0.4781, 'learning_rate': 7.802729064116933e-06, 'epoch': 0.58}
+
58%|█████▊ | 6973/11952 [07:23<8:11:31, 5.92s/it]
58%|█████▊ | 6974/11952 [07:29<8:12:00, 5.93s/it]
{'loss': 0.485, 'learning_rate': 7.800085466348715e-06, 'epoch': 0.58}
+
58%|█████▊ | 6974/11952 [07:29<8:12:00, 5.93s/it]
58%|█████▊ | 6975/11952 [07:35<8:07:55, 5.88s/it]
{'loss': 0.4754, 'learning_rate': 7.797442030133067e-06, 'epoch': 0.58}
+
58%|█████▊ | 6975/11952 [07:35<8:07:55, 5.88s/it]
58%|█████▊ | 6976/11952 [07:41<8:05:01, 5.85s/it]
{'loss': 0.4706, 'learning_rate': 7.794798755664116e-06, 'epoch': 0.58}
+
58%|█████▊ | 6976/11952 [07:41<8:05:01, 5.85s/it]
58%|█████▊ | 6977/11952 [07:46<7:59:24, 5.78s/it]
{'loss': 0.476, 'learning_rate': 7.79215564313597e-06, 'epoch': 0.58}
+
58%|█████▊ | 6977/11952 [07:46<7:59:24, 5.78s/it]
58%|█████▊ | 6978/11952 [07:52<8:01:36, 5.81s/it]
{'loss': 0.4709, 'learning_rate': 7.789512692742731e-06, 'epoch': 0.58}
+
58%|█████▊ | 6978/11952 [07:52<8:01:36, 5.81s/it]
58%|█████▊ | 6979/11952 [07:58<7:59:09, 5.78s/it]
{'loss': 0.481, 'learning_rate': 7.786869904678486e-06, 'epoch': 0.58}
+
58%|█████▊ | 6979/11952 [07:58<7:59:09, 5.78s/it]
58%|█████▊ | 6980/11952 [08:04<8:03:14, 5.83s/it]
{'loss': 0.4754, 'learning_rate': 7.784227279137314e-06, 'epoch': 0.58}
+
58%|█████▊ | 6980/11952 [08:04<8:03:14, 5.83s/it]
58%|█████▊ | 6981/11952 [08:09<7:58:44, 5.78s/it]
{'loss': 0.4683, 'learning_rate': 7.781584816313271e-06, 'epoch': 0.58}
+
58%|█████▊ | 6981/11952 [08:09<7:58:44, 5.78s/it]
58%|█████▊ | 6982/11952 [08:16<8:05:55, 5.87s/it]
{'loss': 0.4823, 'learning_rate': 7.778942516400413e-06, 'epoch': 0.58}
+
58%|█████▊ | 6982/11952 [08:16<8:05:55, 5.87s/it]
58%|█████▊ | 6983/11952 [08:22<8:14:57, 5.98s/it]
{'loss': 0.4723, 'learning_rate': 7.776300379592778e-06, 'epoch': 0.58}
+
58%|█████▊ | 6983/11952 [08:22<8:14:57, 5.98s/it]
58%|█████▊ | 6984/11952 [08:28<8:17:41, 6.01s/it]
{'loss': 0.4722, 'learning_rate': 7.773658406084395e-06, 'epoch': 0.58}
+
58%|█████▊ | 6984/11952 [08:28<8:17:41, 6.01s/it]
58%|█████▊ | 6985/11952 [08:34<8:13:13, 5.96s/it]
{'loss': 0.478, 'learning_rate': 7.771016596069273e-06, 'epoch': 0.58}
+
58%|█████▊ | 6985/11952 [08:34<8:13:13, 5.96s/it]
58%|█████▊ | 6986/11952 [08:40<8:14:53, 5.98s/it]
{'loss': 0.474, 'learning_rate': 7.768374949741427e-06, 'epoch': 0.58}
+
58%|█████▊ | 6986/11952 [08:40<8:14:53, 5.98s/it]
58%|█████▊ | 6987/11952 [08:46<8:16:18, 6.00s/it]
{'loss': 0.4582, 'learning_rate': 7.765733467294842e-06, 'epoch': 0.58}
+
58%|█████▊ | 6987/11952 [08:46<8:16:18, 6.00s/it]
58%|█████▊ | 6988/11952 [08:52<8:11:36, 5.94s/it]
{'loss': 0.4778, 'learning_rate': 7.763092148923496e-06, 'epoch': 0.58}
+
58%|█████▊ | 6988/11952 [08:52<8:11:36, 5.94s/it]
58%|█████▊ | 6989/11952 [08:57<8:11:17, 5.94s/it]
{'loss': 0.4914, 'learning_rate': 7.760450994821363e-06, 'epoch': 0.58}
+
58%|█████▊ | 6989/11952 [08:57<8:11:17, 5.94s/it]
58%|█████▊ | 6990/11952 [09:03<8:06:32, 5.88s/it]
{'loss': 0.4729, 'learning_rate': 7.757810005182391e-06, 'epoch': 0.58}
+
58%|█████▊ | 6990/11952 [09:03<8:06:32, 5.88s/it]
58%|█████▊ | 6991/11952 [09:09<8:04:37, 5.86s/it]
{'loss': 0.4858, 'learning_rate': 7.755169180200524e-06, 'epoch': 0.58}
+
58%|█████▊ | 6991/11952 [09:09<8:04:37, 5.86s/it]
59%|█████▊ | 6992/11952 [09:15<8:03:00, 5.84s/it]
{'loss': 0.4731, 'learning_rate': 7.752528520069697e-06, 'epoch': 0.58}
+
59%|█████▊ | 6992/11952 [09:15<8:03:00, 5.84s/it]
59%|█████▊ | 6993/11952 [09:21<7:59:50, 5.81s/it]
{'loss': 0.4915, 'learning_rate': 7.74988802498383e-06, 'epoch': 0.59}
+
59%|█████▊ | 6993/11952 [09:21<7:59:50, 5.81s/it]
59%|█████▊ | 6994/11952 [09:26<8:01:19, 5.82s/it]
{'loss': 0.4868, 'learning_rate': 7.747247695136825e-06, 'epoch': 0.59}
+
59%|█████▊ | 6994/11952 [09:26<8:01:19, 5.82s/it]
59%|█████▊ | 6995/11952 [09:32<8:01:07, 5.82s/it]
{'loss': 0.484, 'learning_rate': 7.74460753072258e-06, 'epoch': 0.59}
+
59%|█████▊ | 6995/11952 [09:32<8:01:07, 5.82s/it]
59%|█████▊ | 6996/11952 [09:38<8:02:54, 5.85s/it]
{'loss': 0.4831, 'learning_rate': 7.74196753193498e-06, 'epoch': 0.59}
+
59%|█████▊ | 6996/11952 [09:38<8:02:54, 5.85s/it]
59%|█████▊ | 6997/11952 [09:44<7:58:19, 5.79s/it]
{'loss': 0.4833, 'learning_rate': 7.739327698967891e-06, 'epoch': 0.59}
+
59%|█████▊ | 6997/11952 [09:44<7:58:19, 5.79s/it]
59%|█████▊ | 6998/11952 [09:49<7:54:33, 5.75s/it]
{'loss': 0.4727, 'learning_rate': 7.736688032015168e-06, 'epoch': 0.59}
+
59%|█████▊ | 6998/11952 [09:49<7:54:33, 5.75s/it]
59%|█████▊ | 6999/11952 [09:55<7:50:34, 5.70s/it]
{'loss': 0.4703, 'learning_rate': 7.734048531270664e-06, 'epoch': 0.59}
+
59%|█████▊ | 6999/11952 [09:55<7:50:34, 5.70s/it]07 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+ 15 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+3AutoResumeHook: Checking whether to suspend...
+
+AutoResumeHook: Checking whether to suspend...4
+2 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
59%|█████▊ | 7000/11952 [10:01<7:59:15, 5.81s/it]
{'loss': 0.438, 'learning_rate': 7.731409196928214e-06, 'epoch': 0.59}
+
59%|█████▊ | 7000/11952 [10:01<7:59:15, 5.81s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
59%|█████▊ | 7001/11952 [10:34<18:57:56, 13.79s/it]
{'loss': 0.4715, 'learning_rate': 7.728770029181638e-06, 'epoch': 0.59}
+
59%|█████▊ | 7001/11952 [10:34<18:57:56, 13.79s/it]
59%|█████▊ | 7002/11952 [10:39<15:37:42, 11.37s/it]
{'loss': 0.4702, 'learning_rate': 7.726131028224742e-06, 'epoch': 0.59}
+
59%|█████▊ | 7002/11952 [10:39<15:37:42, 11.37s/it]
59%|█████▊ | 7003/11952 [10:45<13:17:03, 9.66s/it]
{'loss': 0.4689, 'learning_rate': 7.723492194251326e-06, 'epoch': 0.59}
+
59%|█████▊ | 7003/11952 [10:45<13:17:03, 9.66s/it]
59%|█████▊ | 7004/11952 [10:51<11:38:44, 8.47s/it]
{'loss': 0.4701, 'learning_rate': 7.720853527455174e-06, 'epoch': 0.59}
+
59%|█████▊ | 7004/11952 [10:51<11:38:44, 8.47s/it]
59%|█████▊ | 7005/11952 [10:56<10:32:47, 7.67s/it]
{'loss': 0.475, 'learning_rate': 7.718215028030056e-06, 'epoch': 0.59}
+
59%|█████▊ | 7005/11952 [10:56<10:32:47, 7.67s/it]
59%|█████▊ | 7006/11952 [11:02<9:45:08, 7.10s/it]
{'loss': 0.4504, 'learning_rate': 7.71557669616974e-06, 'epoch': 0.59}
+
59%|█████▊ | 7006/11952 [11:02<9:45:08, 7.10s/it]
59%|█████▊ | 7007/11952 [11:08<9:07:36, 6.64s/it]
{'loss': 0.4582, 'learning_rate': 7.71293853206797e-06, 'epoch': 0.59}
+
59%|█████▊ | 7007/11952 [11:08<9:07:36, 6.64s/it]
59%|█████▊ | 7008/11952 [11:14<8:45:28, 6.38s/it]
{'loss': 0.4723, 'learning_rate': 7.710300535918482e-06, 'epoch': 0.59}
+
59%|█████▊ | 7008/11952 [11:14<8:45:28, 6.38s/it]
59%|█████▊ | 7009/11952 [11:19<8:35:11, 6.25s/it]
{'loss': 0.4739, 'learning_rate': 7.707662707914997e-06, 'epoch': 0.59}
+
59%|█████▊ | 7009/11952 [11:19<8:35:11, 6.25s/it]
59%|█████▊ | 7010/11952 [11:25<8:22:14, 6.10s/it]
{'loss': 0.4664, 'learning_rate': 7.705025048251228e-06, 'epoch': 0.59}
+
59%|█████▊ | 7010/11952 [11:25<8:22:14, 6.10s/it]
59%|█████▊ | 7011/11952 [11:31<8:17:55, 6.05s/it]
{'loss': 0.4789, 'learning_rate': 7.702387557120876e-06, 'epoch': 0.59}
+
59%|█████▊ | 7011/11952 [11:31<8:17:55, 6.05s/it]
59%|█████▊ | 7012/11952 [11:37<8:10:52, 5.96s/it]
{'loss': 0.4828, 'learning_rate': 7.699750234717622e-06, 'epoch': 0.59}
+
59%|█████▊ | 7012/11952 [11:37<8:10:52, 5.96s/it]
59%|█████▊ | 7013/11952 [11:43<8:12:13, 5.98s/it]
{'loss': 0.4587, 'learning_rate': 7.697113081235147e-06, 'epoch': 0.59}
+
59%|█████▊ | 7013/11952 [11:43<8:12:13, 5.98s/it]
59%|█████▊ | 7014/11952 [11:49<8:06:45, 5.91s/it]
{'loss': 0.4863, 'learning_rate': 7.694476096867105e-06, 'epoch': 0.59}
+
59%|█████▊ | 7014/11952 [11:49<8:06:45, 5.91s/it]
59%|█████▊ | 7015/11952 [11:54<8:02:11, 5.86s/it]
{'loss': 0.4657, 'learning_rate': 7.691839281807153e-06, 'epoch': 0.59}
+
59%|█████▊ | 7015/11952 [11:54<8:02:11, 5.86s/it]
59%|█████▊ | 7016/11952 [12:00<8:05:00, 5.90s/it]
{'loss': 0.4932, 'learning_rate': 7.689202636248923e-06, 'epoch': 0.59}
+
59%|█████▊ | 7016/11952 [12:00<8:05:00, 5.90s/it]
59%|█████▊ | 7017/11952 [12:06<7:58:31, 5.82s/it]
{'loss': 0.4581, 'learning_rate': 7.68656616038604e-06, 'epoch': 0.59}
+
59%|█████▊ | 7017/11952 [12:06<7:58:31, 5.82s/it]
59%|█████▊ | 7018/11952 [12:12<7:54:26, 5.77s/it]
{'loss': 0.4734, 'learning_rate': 7.683929854412114e-06, 'epoch': 0.59}
+
59%|█████▊ | 7018/11952 [12:12<7:54:26, 5.77s/it]
59%|█████▊ | 7019/11952 [12:17<7:50:38, 5.72s/it]
{'loss': 0.4629, 'learning_rate': 7.681293718520746e-06, 'epoch': 0.59}
+
59%|█████▊ | 7019/11952 [12:17<7:50:38, 5.72s/it]
59%|█████▊ | 7020/11952 [12:23<7:54:19, 5.77s/it]
{'loss': 0.4578, 'learning_rate': 7.678657752905522e-06, 'epoch': 0.59}
+
59%|█████▊ | 7020/11952 [12:23<7:54:19, 5.77s/it]
59%|█████▊ | 7021/11952 [12:29<7:48:25, 5.70s/it]
{'loss': 0.4507, 'learning_rate': 7.676021957760023e-06, 'epoch': 0.59}
+
59%|█████▊ | 7021/11952 [12:29<7:48:25, 5.70s/it]
59%|█████▉ | 7022/11952 [12:35<7:50:14, 5.72s/it]
{'loss': 0.4571, 'learning_rate': 7.673386333277802e-06, 'epoch': 0.59}
+
59%|█████▉ | 7022/11952 [12:35<7:50:14, 5.72s/it]
59%|█████▉ | 7023/11952 [12:40<7:55:28, 5.79s/it]
{'loss': 0.4914, 'learning_rate': 7.670750879652414e-06, 'epoch': 0.59}
+
59%|█████▉ | 7023/11952 [12:40<7:55:28, 5.79s/it]
59%|█████▉ | 7024/11952 [12:46<8:00:58, 5.86s/it]
{'loss': 0.4869, 'learning_rate': 7.668115597077388e-06, 'epoch': 0.59}
+
59%|█████▉ | 7024/11952 [12:46<8:00:58, 5.86s/it]
59%|█████▉ | 7025/11952 [12:53<8:06:53, 5.93s/it]
{'loss': 0.4831, 'learning_rate': 7.665480485746255e-06, 'epoch': 0.59}
+
59%|█████▉ | 7025/11952 [12:53<8:06:53, 5.93s/it]
59%|█████▉ | 7026/11952 [12:58<8:01:47, 5.87s/it]
{'loss': 0.4795, 'learning_rate': 7.662845545852526e-06, 'epoch': 0.59}
+
59%|█████▉ | 7026/11952 [12:58<8:01:47, 5.87s/it]
59%|█████▉ | 7027/11952 [13:04<8:02:38, 5.88s/it]
{'loss': 0.4938, 'learning_rate': 7.6602107775897e-06, 'epoch': 0.59}
+
59%|█████▉ | 7027/11952 [13:04<8:02:38, 5.88s/it]
59%|█████▉ | 7028/11952 [13:10<8:07:00, 5.93s/it]
{'loss': 0.4709, 'learning_rate': 7.657576181151266e-06, 'epoch': 0.59}
+
59%|█████▉ | 7028/11952 [13:10<8:07:00, 5.93s/it]
59%|█████▉ | 7029/11952 [13:16<8:05:43, 5.92s/it]
{'loss': 0.4714, 'learning_rate': 7.654941756730687e-06, 'epoch': 0.59}
+
59%|█████▉ | 7029/11952 [13:16<8:05:43, 5.92s/it]
59%|█████▉ | 7030/11952 [13:22<8:04:50, 5.91s/it]
{'loss': 0.4525, 'learning_rate': 7.652307504521437e-06, 'epoch': 0.59}
+
59%|█████▉ | 7030/11952 [13:22<8:04:50, 5.91s/it]
59%|█████▉ | 7031/11952 [13:28<7:56:33, 5.81s/it]
{'loss': 0.4659, 'learning_rate': 7.649673424716958e-06, 'epoch': 0.59}
+
59%|█████▉ | 7031/11952 [13:28<7:56:33, 5.81s/it]
59%|█████▉ | 7032/11952 [13:34<7:58:42, 5.84s/it]
{'loss': 0.4626, 'learning_rate': 7.647039517510685e-06, 'epoch': 0.59}
+
59%|█████▉ | 7032/11952 [13:34<7:58:42, 5.84s/it]
59%|█████▉ | 7033/11952 [13:39<7:58:53, 5.84s/it]
{'loss': 0.4977, 'learning_rate': 7.644405783096044e-06, 'epoch': 0.59}
+
59%|█████▉ | 7033/11952 [13:39<7:58:53, 5.84s/it]
59%|█████▉ | 7034/11952 [13:45<8:01:27, 5.87s/it]
{'loss': 0.4793, 'learning_rate': 7.641772221666446e-06, 'epoch': 0.59}
+
59%|█████▉ | 7034/11952 [13:45<8:01:27, 5.87s/it]
59%|█████▉ | 7035/11952 [13:52<8:09:13, 5.97s/it]
{'loss': 0.4711, 'learning_rate': 7.639138833415285e-06, 'epoch': 0.59}
+
59%|█████▉ | 7035/11952 [13:52<8:09:13, 5.97s/it]
59%|█████▉ | 7036/11952 [13:57<8:03:08, 5.90s/it]
{'loss': 0.4851, 'learning_rate': 7.636505618535953e-06, 'epoch': 0.59}
+
59%|█████▉ | 7036/11952 [13:57<8:03:08, 5.90s/it]
59%|█████▉ | 7037/11952 [14:03<7:55:35, 5.81s/it]
{'loss': 0.4648, 'learning_rate': 7.633872577221815e-06, 'epoch': 0.59}
+
59%|█████▉ | 7037/11952 [14:03<7:55:35, 5.81s/it]
59%|█████▉ | 7038/11952 [14:09<7:59:21, 5.85s/it]
{'loss': 0.4492, 'learning_rate': 7.631239709666234e-06, 'epoch': 0.59}
+
59%|█████▉ | 7038/11952 [14:09<7:59:21, 5.85s/it]
59%|█████▉ | 7039/11952 [14:15<8:01:34, 5.88s/it]
{'loss': 0.4862, 'learning_rate': 7.628607016062553e-06, 'epoch': 0.59}
+
59%|█████▉ | 7039/11952 [14:15<8:01:34, 5.88s/it]
59%|█████▉ | 7040/11952 [14:21<7:58:36, 5.85s/it]
{'loss': 0.4618, 'learning_rate': 7.625974496604109e-06, 'epoch': 0.59}
+
59%|█████▉ | 7040/11952 [14:21<7:58:36, 5.85s/it]
59%|█████▉ | 7041/11952 [14:26<7:53:07, 5.78s/it]
{'loss': 0.457, 'learning_rate': 7.623342151484229e-06, 'epoch': 0.59}
+
59%|█████▉ | 7041/11952 [14:26<7:53:07, 5.78s/it]
59%|█████▉ | 7042/11952 [14:32<7:54:52, 5.80s/it]
{'loss': 0.4916, 'learning_rate': 7.620709980896215e-06, 'epoch': 0.59}
+
59%|█████▉ | 7042/11952 [14:32<7:54:52, 5.80s/it]
59%|█████▉ | 7043/11952 [14:38<7:54:16, 5.80s/it]
{'loss': 0.5061, 'learning_rate': 7.618077985033363e-06, 'epoch': 0.59}
+
59%|█████▉ | 7043/11952 [14:38<7:54:16, 5.80s/it]
59%|█████▉ | 7044/11952 [14:44<8:00:26, 5.87s/it]
{'loss': 0.4657, 'learning_rate': 7.6154461640889555e-06, 'epoch': 0.59}
+
59%|█████▉ | 7044/11952 [14:44<8:00:26, 5.87s/it]
59%|█████▉ | 7045/11952 [14:50<8:02:07, 5.90s/it]
{'loss': 0.4678, 'learning_rate': 7.612814518256265e-06, 'epoch': 0.59}
+
59%|█████▉ | 7045/11952 [14:50<8:02:07, 5.90s/it]
59%|█████▉ | 7046/11952 [14:56<8:10:53, 6.00s/it]
{'loss': 0.4981, 'learning_rate': 7.610183047728543e-06, 'epoch': 0.59}
+
59%|█████▉ | 7046/11952 [14:56<8:10:53, 6.00s/it]
59%|█████▉ | 7047/11952 [15:02<8:01:24, 5.89s/it]
{'loss': 0.4745, 'learning_rate': 7.607551752699043e-06, 'epoch': 0.59}
+
59%|█████▉ | 7047/11952 [15:02<8:01:24, 5.89s/it]
59%|█████▉ | 7048/11952 [15:07<8:00:18, 5.88s/it]
{'loss': 0.4684, 'learning_rate': 7.604920633360991e-06, 'epoch': 0.59}
+
59%|█████▉ | 7048/11952 [15:07<8:00:18, 5.88s/it]
59%|█████▉ | 7049/11952 [15:13<7:55:34, 5.82s/it]
{'loss': 0.4702, 'learning_rate': 7.6022896899076045e-06, 'epoch': 0.59}
+
59%|█████▉ | 7049/11952 [15:13<7:55:34, 5.82s/it]06 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...53 AutoResumeHook: Checking whether to suspend...
+
+AutoResumeHook: Checking whether to suspend...
+47 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
59%|█████▉ | 7050/11952 [15:19<8:05:14, 5.94s/it]2 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4809, 'learning_rate': 7.59965892253209e-06, 'epoch': 0.59}
+
59%|█████▉ | 7050/11952 [15:19<8:05:14, 5.94s/it]
59%|█████▉ | 7051/11952 [15:25<8:06:49, 5.96s/it]
{'loss': 0.4865, 'learning_rate': 7.597028331427643e-06, 'epoch': 0.59}
+
59%|█████▉ | 7051/11952 [15:25<8:06:49, 5.96s/it]
59%|█████▉ | 7052/11952 [15:31<8:06:36, 5.96s/it]
{'loss': 0.4956, 'learning_rate': 7.594397916787439e-06, 'epoch': 0.59}
+
59%|█████▉ | 7052/11952 [15:31<8:06:36, 5.96s/it]
59%|█████▉ | 7053/11952 [15:37<8:06:45, 5.96s/it]
{'loss': 0.4843, 'learning_rate': 7.591767678804642e-06, 'epoch': 0.59}
+
59%|█████▉ | 7053/11952 [15:37<8:06:45, 5.96s/it]
59%|█████▉ | 7054/11952 [15:43<7:57:44, 5.85s/it]
{'loss': 0.4779, 'learning_rate': 7.589137617672415e-06, 'epoch': 0.59}
+
59%|█████▉ | 7054/11952 [15:43<7:57:44, 5.85s/it]
59%|█████▉ | 7055/11952 [15:49<7:51:52, 5.78s/it]
{'loss': 0.4786, 'learning_rate': 7.586507733583892e-06, 'epoch': 0.59}
+
59%|█████▉ | 7055/11952 [15:49<7:51:52, 5.78s/it]
59%|█████▉ | 7056/11952 [15:55<7:58:48, 5.87s/it]
{'loss': 0.4609, 'learning_rate': 7.583878026732204e-06, 'epoch': 0.59}
+
59%|█████▉ | 7056/11952 [15:55<7:58:48, 5.87s/it]
59%|█████▉ | 7057/11952 [16:00<7:55:47, 5.83s/it]
{'loss': 0.4686, 'learning_rate': 7.581248497310465e-06, 'epoch': 0.59}
+
59%|█████▉ | 7057/11952 [16:00<7:55:47, 5.83s/it]
59%|█████▉ | 7058/11952 [16:06<7:55:15, 5.83s/it]
{'loss': 0.479, 'learning_rate': 7.5786191455117765e-06, 'epoch': 0.59}
+
59%|█████▉ | 7058/11952 [16:06<7:55:15, 5.83s/it]
59%|█████▉ | 7059/11952 [16:12<8:01:54, 5.91s/it]
{'loss': 0.4769, 'learning_rate': 7.575989971529223e-06, 'epoch': 0.59}
+
59%|█████▉ | 7059/11952 [16:12<8:01:54, 5.91s/it]
59%|█████▉ | 7060/11952 [16:18<8:02:26, 5.92s/it]
{'loss': 0.4699, 'learning_rate': 7.573360975555885e-06, 'epoch': 0.59}
+
59%|█████▉ | 7060/11952 [16:18<8:02:26, 5.92s/it]
59%|█████▉ | 7061/11952 [16:24<8:00:21, 5.89s/it]
{'loss': 0.5061, 'learning_rate': 7.570732157784823e-06, 'epoch': 0.59}
+
59%|█████▉ | 7061/11952 [16:24<8:00:21, 5.89s/it]
59%|█████▉ | 7062/11952 [16:30<7:53:09, 5.81s/it]
{'loss': 0.4889, 'learning_rate': 7.56810351840909e-06, 'epoch': 0.59}
+
59%|█████▉ | 7062/11952 [16:30<7:53:09, 5.81s/it]
59%|█████▉ | 7063/11952 [16:35<7:53:34, 5.81s/it]
{'loss': 0.4664, 'learning_rate': 7.56547505762172e-06, 'epoch': 0.59}
+
59%|█████▉ | 7063/11952 [16:35<7:53:34, 5.81s/it]
59%|█████▉ | 7064/11952 [16:41<7:54:51, 5.83s/it]
{'loss': 0.4808, 'learning_rate': 7.562846775615734e-06, 'epoch': 0.59}
+
59%|█████▉ | 7064/11952 [16:41<7:54:51, 5.83s/it]
59%|█████▉ | 7065/11952 [16:47<7:53:28, 5.81s/it]
{'loss': 0.487, 'learning_rate': 7.560218672584143e-06, 'epoch': 0.59}
+
59%|█████▉ | 7065/11952 [16:47<7:53:28, 5.81s/it]
59%|█████▉ | 7066/11952 [16:53<7:57:23, 5.86s/it]
{'loss': 0.4975, 'learning_rate': 7.557590748719943e-06, 'epoch': 0.59}
+
59%|█████▉ | 7066/11952 [16:53<7:57:23, 5.86s/it]
59%|█████▉ | 7067/11952 [16:59<7:49:21, 5.76s/it]
{'loss': 0.4613, 'learning_rate': 7.5549630042161236e-06, 'epoch': 0.59}
+
59%|█████▉ | 7067/11952 [16:59<7:49:21, 5.76s/it]
59%|█████▉ | 7068/11952 [17:04<7:43:00, 5.69s/it]
{'loss': 0.4905, 'learning_rate': 7.552335439265652e-06, 'epoch': 0.59}
+
59%|█████▉ | 7068/11952 [17:04<7:43:00, 5.69s/it]
59%|█████▉ | 7069/11952 [17:10<7:50:46, 5.78s/it]
{'loss': 0.4649, 'learning_rate': 7.549708054061484e-06, 'epoch': 0.59}
+
59%|█████▉ | 7069/11952 [17:10<7:50:46, 5.78s/it]
59%|█████▉ | 7070/11952 [17:16<7:57:10, 5.86s/it]
{'loss': 0.5153, 'learning_rate': 7.547080848796564e-06, 'epoch': 0.59}
+
59%|█████▉ | 7070/11952 [17:16<7:57:10, 5.86s/it]
59%|█████▉ | 7071/11952 [17:22<7:51:36, 5.80s/it]
{'loss': 0.4835, 'learning_rate': 7.544453823663825e-06, 'epoch': 0.59}
+
59%|█████▉ | 7071/11952 [17:22<7:51:36, 5.80s/it]
59%|█████▉ | 7072/11952 [17:28<7:51:18, 5.79s/it]
{'loss': 0.4816, 'learning_rate': 7.541826978856185e-06, 'epoch': 0.59}
+
59%|█████▉ | 7072/11952 [17:28<7:51:18, 5.79s/it]
59%|█████▉ | 7073/11952 [17:33<7:44:46, 5.72s/it]
{'loss': 0.465, 'learning_rate': 7.539200314566543e-06, 'epoch': 0.59}
+
59%|█████▉ | 7073/11952 [17:33<7:44:46, 5.72s/it]
59%|█████▉ | 7074/11952 [17:39<7:45:09, 5.72s/it]
{'loss': 0.4549, 'learning_rate': 7.536573830987798e-06, 'epoch': 0.59}
+
59%|█████▉ | 7074/11952 [17:39<7:45:09, 5.72s/it]
59%|█████▉ | 7075/11952 [17:45<7:44:23, 5.71s/it]
{'loss': 0.4682, 'learning_rate': 7.533947528312825e-06, 'epoch': 0.59}
+
59%|█████▉ | 7075/11952 [17:45<7:44:23, 5.71s/it]
59%|█████▉ | 7076/11952 [17:50<7:45:53, 5.73s/it]
{'loss': 0.456, 'learning_rate': 7.531321406734486e-06, 'epoch': 0.59}
+
59%|█████▉ | 7076/11952 [17:50<7:45:53, 5.73s/it]
59%|█████▉ | 7077/11952 [17:56<7:44:41, 5.72s/it]
{'loss': 0.4794, 'learning_rate': 7.528695466445638e-06, 'epoch': 0.59}
+
59%|█████▉ | 7077/11952 [17:56<7:44:41, 5.72s/it]
59%|█████▉ | 7078/11952 [18:02<7:43:36, 5.71s/it]
{'loss': 0.461, 'learning_rate': 7.526069707639115e-06, 'epoch': 0.59}
+
59%|█████▉ | 7078/11952 [18:02<7:43:36, 5.71s/it]WARNING: tokenization mismatch: 1 vs. 789. [[{'from': 'human', 'value': 'ASSISTANT: You are a forward-thinking HR consultancy with the following knowledge and traits.\n\nKNOWLEDGE: HR management, employee satisfaction, talent retention, team building, workplace culture.\n\nTRAITS: Innovation, empathy, solution orientation, creativity, understanding, teamwork.\n\nTASK: Use your knowledge to create an internal strategy document. We are an HR consultancy looking to develop 10 creative ways to improve employee satisfaction. Focus on ideas that are innovative and engaging, and cater to the needs of HR managers and company leaders.\n\nOUTPUT: A table in German containing 10 creative strategies to improve employee satisfaction, including a brief description for each.'}, {'from': 'gpt', 'value': '| Nr. | Strategie | Beschreibung |\n| --- | --- | --- |\n| 1. | "Wertschätzungswand" | Eine Wand im Büro, auf der Mitarbeiter anonym ihre Kollegen für ihre Leistungen und Beiträge loben und anerkennen können. |\n| 2. | Flexible Arbeitsmodelle | Einführung von flexiblen Arbeitszeiten und Homeoffice-Optionen, um Work-Life-Balance zu verbessern und individuelle Bedürfnisse zu berücksichtigen. |\n| 3. | Mitarbeiter-Workshops für persönliche Entwicklung | Organisieren von internen Workshops und Schulungen, um persönliche und berufliche Fähigkeiten der Mitarbeiter zu fördern. |\n| 4. | Team-Building-Aktivitäten außerhalb des Arbeitsplatzes | Regelmäßige Veranstaltungen wie Escape Rooms, Sportevents oder Kochkurse, um den Zusammenhalt und die Kommunikation im Team zu stärken. |\n| 5. | Gesundheits- und Wellness-Programme | Einführung von Fitness- und Entspannungskursen wie Yoga, Meditation oder Massagen, um das Wohlbefinden der Mitarbeiter zu fördern. |\n| 6. | Feedback-Kultur und transparente Kommunikation | Etablierung einer offenen Feedback-Kultur und transparenter Kommunikation, um die Mitarbeiter in Entscheidungsprozesse einzubinden. |\n| 7. | Mitarbeiter-Mentoring-Programm | Einführung eines Mentoring-Programms, bei dem erfahrene Mitarbeiter ihr Wissen und ihre Erfahrungen mit jüngeren Kollegen teilen. |\n| 8. | "Innovationstage" | Einrichtung von speziellen Tagen, an denen Mitarbeiter an eigenen Projekten arbeiten oder innovative Ideen für das Unternehmen entwickeln können. |\n| 9. | Individuelle Karriereentwicklungspläne | Erstellung von personalisierten Karriereplänen in Zusammenarbeit mit den Mitarbeitern, um ihre berufliche Entwicklung zu unterstützen. |\n| 10. | Gemeinschaftliche soziale Verantwortung (CSR) Initiativen | Organisation von Freiwilligenprojekten und CSR-Aktivitäten, um den Mitarbeitern die Möglichkeit zu geben, sozialen Einfluss zu nehmen. |'}]] (ignored)
+
59%|█████▉ | 7079/11952 [18:08<7:54:48, 5.85s/it]
{'loss': 0.4683, 'learning_rate': 7.523444130507743e-06, 'epoch': 0.59}
+
59%|█████▉ | 7079/11952 [18:08<7:54:48, 5.85s/it]
59%|█████▉ | 7080/11952 [18:14<7:49:43, 5.78s/it]
{'loss': 0.471, 'learning_rate': 7.52081873524433e-06, 'epoch': 0.59}
+
59%|█████▉ | 7080/11952 [18:14<7:49:43, 5.78s/it]
59%|█████▉ | 7081/11952 [18:19<7:48:01, 5.76s/it]
{'loss': 0.4773, 'learning_rate': 7.518193522041679e-06, 'epoch': 0.59}
+
59%|█████▉ | 7081/11952 [18:19<7:48:01, 5.76s/it]
59%|█████▉ | 7082/11952 [18:25<7:47:08, 5.76s/it]
{'loss': 0.472, 'learning_rate': 7.5155684910925754e-06, 'epoch': 0.59}
+
59%|█████▉ | 7082/11952 [18:25<7:47:08, 5.76s/it]
59%|█████▉ | 7083/11952 [18:31<7:57:07, 5.88s/it]
{'loss': 0.4755, 'learning_rate': 7.5129436425897876e-06, 'epoch': 0.59}
+
59%|█████▉ | 7083/11952 [18:31<7:57:07, 5.88s/it]
59%|█████▉ | 7084/11952 [18:37<7:59:40, 5.91s/it]
{'loss': 0.4634, 'learning_rate': 7.510318976726074e-06, 'epoch': 0.59}
+
59%|█████▉ | 7084/11952 [18:37<7:59:40, 5.91s/it]
59%|█████▉ | 7085/11952 [18:43<8:00:28, 5.92s/it]
{'loss': 0.476, 'learning_rate': 7.507694493694179e-06, 'epoch': 0.59}
+
59%|█████▉ | 7085/11952 [18:43<8:00:28, 5.92s/it]
59%|█████▉ | 7086/11952 [18:49<7:54:06, 5.85s/it]
{'loss': 0.4749, 'learning_rate': 7.505070193686835e-06, 'epoch': 0.59}
+
59%|█████▉ | 7086/11952 [18:49<7:54:06, 5.85s/it]
59%|█████▉ | 7087/11952 [18:54<7:48:58, 5.78s/it]
{'loss': 0.4622, 'learning_rate': 7.502446076896754e-06, 'epoch': 0.59}
+
59%|█████▉ | 7087/11952 [18:54<7:48:58, 5.78s/it]
59%|█████▉ | 7088/11952 [19:00<7:46:06, 5.75s/it]
{'loss': 0.4815, 'learning_rate': 7.4998221435166504e-06, 'epoch': 0.59}
+
59%|█████▉ | 7088/11952 [19:00<7:46:06, 5.75s/it]
59%|█████▉ | 7089/11952 [19:06<7:48:33, 5.78s/it]
{'loss': 0.4569, 'learning_rate': 7.497198393739209e-06, 'epoch': 0.59}
+
59%|█████▉ | 7089/11952 [19:06<7:48:33, 5.78s/it]
59%|█████▉ | 7090/11952 [19:12<7:49:41, 5.80s/it]
{'loss': 0.4719, 'learning_rate': 7.494574827757107e-06, 'epoch': 0.59}
+
59%|█████▉ | 7090/11952 [19:12<7:49:41, 5.80s/it]
59%|█████▉ | 7091/11952 [19:17<7:47:15, 5.77s/it]
{'loss': 0.4518, 'learning_rate': 7.4919514457630085e-06, 'epoch': 0.59}
+
59%|█████▉ | 7091/11952 [19:17<7:47:15, 5.77s/it]
59%|█████▉ | 7092/11952 [19:23<7:42:15, 5.71s/it]
{'loss': 0.4851, 'learning_rate': 7.489328247949565e-06, 'epoch': 0.59}
+
59%|█████▉ | 7092/11952 [19:23<7:42:15, 5.71s/it]
59%|█████▉ | 7093/11952 [19:30<8:01:28, 5.95s/it]
{'loss': 0.4957, 'learning_rate': 7.486705234509412e-06, 'epoch': 0.59}
+
59%|█████▉ | 7093/11952 [19:30<8:01:28, 5.95s/it]
59%|█████▉ | 7094/11952 [19:36<8:02:53, 5.96s/it]
{'loss': 0.4889, 'learning_rate': 7.484082405635169e-06, 'epoch': 0.59}
+
59%|█████▉ | 7094/11952 [19:36<8:02:53, 5.96s/it]
59%|█████▉ | 7095/11952 [19:41<7:58:30, 5.91s/it]
{'loss': 0.4776, 'learning_rate': 7.481459761519454e-06, 'epoch': 0.59}
+
59%|█████▉ | 7095/11952 [19:41<7:58:30, 5.91s/it]
59%|█████▉ | 7096/11952 [19:47<7:50:27, 5.81s/it]
{'loss': 0.4728, 'learning_rate': 7.478837302354859e-06, 'epoch': 0.59}
+
59%|█████▉ | 7096/11952 [19:47<7:50:27, 5.81s/it]
59%|█████▉ | 7097/11952 [19:53<7:55:00, 5.87s/it]
{'loss': 0.4643, 'learning_rate': 7.476215028333964e-06, 'epoch': 0.59}
+
59%|█████▉ | 7097/11952 [19:53<7:55:00, 5.87s/it]
59%|█████▉ | 7098/11952 [19:59<7:48:30, 5.79s/it]
{'loss': 0.468, 'learning_rate': 7.473592939649341e-06, 'epoch': 0.59}
+
59%|█████▉ | 7098/11952 [19:59<7:48:30, 5.79s/it]
59%|█████▉ | 7099/11952 [20:04<7:50:11, 5.81s/it]
{'loss': 0.4845, 'learning_rate': 7.470971036493546e-06, 'epoch': 0.59}
+
59%|█████▉ | 7099/11952 [20:04<7:50:11, 5.81s/it]06 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...7
+ AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
59%|█████▉ | 7100/11952 [20:10<7:46:26, 5.77s/it]52 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4818, 'learning_rate': 7.468349319059114e-06, 'epoch': 0.59}
+
59%|█████▉ | 7100/11952 [20:10<7:46:26, 5.77s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
59%|█████▉ | 7101/11952 [20:42<18:17:32, 13.58s/it]
{'loss': 0.4749, 'learning_rate': 7.465727787538584e-06, 'epoch': 0.59}
+
59%|█████▉ | 7101/11952 [20:42<18:17:32, 13.58s/it]
59%|█████▉ | 7102/11952 [20:48<15:18:03, 11.36s/it]
{'loss': 0.477, 'learning_rate': 7.463106442124459e-06, 'epoch': 0.59}
+
59%|█████▉ | 7102/11952 [20:48<15:18:03, 11.36s/it]
59%|█████▉ | 7103/11952 [20:54<12:58:13, 9.63s/it]
{'loss': 0.4793, 'learning_rate': 7.46048528300925e-06, 'epoch': 0.59}
+
59%|█████▉ | 7103/11952 [20:54<12:58:13, 9.63s/it]
59%|█████▉ | 7104/11952 [21:00<11:35:13, 8.60s/it]
{'loss': 0.4767, 'learning_rate': 7.457864310385439e-06, 'epoch': 0.59}
+
59%|█████▉ | 7104/11952 [21:00<11:35:13, 8.60s/it]
59%|█████▉ | 7105/11952 [21:06<10:30:45, 7.81s/it]
{'loss': 0.474, 'learning_rate': 7.455243524445499e-06, 'epoch': 0.59}
+
59%|█████▉ | 7105/11952 [21:06<10:30:45, 7.81s/it]
59%|█████▉ | 7106/11952 [21:12<9:45:05, 7.24s/it]
{'loss': 0.4725, 'learning_rate': 7.452622925381887e-06, 'epoch': 0.59}
+
59%|█████▉ | 7106/11952 [21:12<9:45:05, 7.24s/it]
59%|█████▉ | 7107/11952 [21:18<9:12:27, 6.84s/it]
{'loss': 0.4833, 'learning_rate': 7.450002513387053e-06, 'epoch': 0.59}
+
59%|█████▉ | 7107/11952 [21:18<9:12:27, 6.84s/it]
59%|█████▉ | 7108/11952 [21:23<8:43:02, 6.48s/it]
{'loss': 0.4849, 'learning_rate': 7.4473822886534285e-06, 'epoch': 0.59}
+
59%|█████▉ | 7108/11952 [21:23<8:43:02, 6.48s/it]
59%|█████▉ | 7109/11952 [21:29<8:28:04, 6.29s/it]
{'loss': 0.498, 'learning_rate': 7.444762251373433e-06, 'epoch': 0.59}
+
59%|█████▉ | 7109/11952 [21:29<8:28:04, 6.29s/it]
59%|█████▉ | 7110/11952 [21:35<8:13:25, 6.11s/it]
{'loss': 0.4671, 'learning_rate': 7.442142401739469e-06, 'epoch': 0.59}
+
59%|█████▉ | 7110/11952 [21:35<8:13:25, 6.11s/it]
59%|█████▉ | 7111/11952 [21:41<8:07:02, 6.04s/it]
{'loss': 0.4719, 'learning_rate': 7.439522739943929e-06, 'epoch': 0.59}
+
59%|█████▉ | 7111/11952 [21:41<8:07:02, 6.04s/it]
60%|█████▉ | 7112/11952 [21:46<7:55:48, 5.90s/it]
{'loss': 0.4683, 'learning_rate': 7.436903266179187e-06, 'epoch': 0.6}
+
60%|█████▉ | 7112/11952 [21:46<7:55:48, 5.90s/it]
60%|█████▉ | 7113/11952 [21:52<7:53:18, 5.87s/it]
{'loss': 0.4745, 'learning_rate': 7.434283980637611e-06, 'epoch': 0.6}
+
60%|█████▉ | 7113/11952 [21:52<7:53:18, 5.87s/it]
60%|█████▉ | 7114/11952 [21:58<7:49:34, 5.82s/it]
{'loss': 0.4699, 'learning_rate': 7.4316648835115445e-06, 'epoch': 0.6}
+
60%|█████▉ | 7114/11952 [21:58<7:49:34, 5.82s/it]
60%|█████▉ | 7115/11952 [22:04<7:52:36, 5.86s/it]
{'loss': 0.4847, 'learning_rate': 7.4290459749933296e-06, 'epoch': 0.6}
+
60%|█████▉ | 7115/11952 [22:04<7:52:36, 5.86s/it]
60%|█████▉ | 7116/11952 [22:09<7:46:54, 5.79s/it]
{'loss': 0.5188, 'learning_rate': 7.426427255275284e-06, 'epoch': 0.6}
+
60%|█████▉ | 7116/11952 [22:09<7:46:54, 5.79s/it]
60%|█████▉ | 7117/11952 [22:15<7:44:18, 5.76s/it]
{'loss': 0.483, 'learning_rate': 7.423808724549715e-06, 'epoch': 0.6}
+
60%|█████▉ | 7117/11952 [22:15<7:44:18, 5.76s/it]
60%|█████▉ | 7118/11952 [22:21<7:47:30, 5.80s/it]
{'loss': 0.4699, 'learning_rate': 7.421190383008921e-06, 'epoch': 0.6}
+
60%|█████▉ | 7118/11952 [22:21<7:47:30, 5.80s/it]
60%|█████▉ | 7119/11952 [22:27<7:52:48, 5.87s/it]
{'loss': 0.4695, 'learning_rate': 7.418572230845178e-06, 'epoch': 0.6}
+
60%|█████▉ | 7119/11952 [22:27<7:52:48, 5.87s/it]
60%|█████▉ | 7120/11952 [22:33<7:49:04, 5.82s/it]
{'loss': 0.4848, 'learning_rate': 7.4159542682507535e-06, 'epoch': 0.6}
+
60%|█████▉ | 7120/11952 [22:33<7:49:04, 5.82s/it]
60%|█████▉ | 7121/11952 [22:38<7:42:40, 5.75s/it]
{'loss': 0.4621, 'learning_rate': 7.413336495417896e-06, 'epoch': 0.6}
+
60%|█████▉ | 7121/11952 [22:38<7:42:40, 5.75s/it]
60%|█████▉ | 7122/11952 [22:44<7:41:59, 5.74s/it]
{'loss': 0.464, 'learning_rate': 7.410718912538853e-06, 'epoch': 0.6}
+
60%|█████▉ | 7122/11952 [22:44<7:41:59, 5.74s/it]
60%|█████▉ | 7123/11952 [22:50<7:40:39, 5.72s/it]
{'loss': 0.4818, 'learning_rate': 7.40810151980584e-06, 'epoch': 0.6}
+
60%|█████▉ | 7123/11952 [22:50<7:40:39, 5.72s/it]
60%|█████▉ | 7124/11952 [22:55<7:39:19, 5.71s/it]
{'loss': 0.4593, 'learning_rate': 7.405484317411071e-06, 'epoch': 0.6}
+
60%|█████▉ | 7124/11952 [22:55<7:39:19, 5.71s/it]
60%|█████▉ | 7125/11952 [23:01<7:37:49, 5.69s/it]
{'loss': 0.4669, 'learning_rate': 7.4028673055467456e-06, 'epoch': 0.6}
+
60%|█████▉ | 7125/11952 [23:01<7:37:49, 5.69s/it]
60%|█████▉ | 7126/11952 [23:07<7:44:39, 5.78s/it]
{'loss': 0.4662, 'learning_rate': 7.400250484405041e-06, 'epoch': 0.6}
+
60%|█████▉ | 7126/11952 [23:07<7:44:39, 5.78s/it]
60%|█████▉ | 7127/11952 [23:13<7:44:48, 5.78s/it]
{'loss': 0.4847, 'learning_rate': 7.397633854178125e-06, 'epoch': 0.6}
+
60%|█████▉ | 7127/11952 [23:13<7:44:48, 5.78s/it]
60%|█████▉ | 7128/11952 [23:19<7:59:05, 5.96s/it]
{'loss': 0.4946, 'learning_rate': 7.395017415058154e-06, 'epoch': 0.6}
+
60%|█████▉ | 7128/11952 [23:19<7:59:05, 5.96s/it]
60%|█████▉ | 7129/11952 [23:25<7:56:00, 5.92s/it]
{'loss': 0.4734, 'learning_rate': 7.3924011672372745e-06, 'epoch': 0.6}
+
60%|█████▉ | 7129/11952 [23:25<7:56:00, 5.92s/it]
60%|█████▉ | 7130/11952 [23:31<7:52:30, 5.88s/it]
{'loss': 0.4795, 'learning_rate': 7.3897851109076055e-06, 'epoch': 0.6}
+
60%|█████▉ | 7130/11952 [23:31<7:52:30, 5.88s/it]
60%|█████▉ | 7131/11952 [23:36<7:45:55, 5.80s/it]
{'loss': 0.4637, 'learning_rate': 7.387169246261262e-06, 'epoch': 0.6}
+
60%|█████▉ | 7131/11952 [23:36<7:45:55, 5.80s/it]
60%|█████▉ | 7132/11952 [23:42<7:48:56, 5.84s/it]
{'loss': 0.4562, 'learning_rate': 7.3845535734903385e-06, 'epoch': 0.6}
+
60%|█████▉ | 7132/11952 [23:42<7:48:56, 5.84s/it]
60%|█████▉ | 7133/11952 [23:48<7:55:10, 5.92s/it]
{'loss': 0.4704, 'learning_rate': 7.381938092786926e-06, 'epoch': 0.6}
+
60%|█████▉ | 7133/11952 [23:48<7:55:10, 5.92s/it]
60%|█████▉ | 7134/11952 [23:55<8:02:54, 6.01s/it]
{'loss': 0.5288, 'learning_rate': 7.37932280434309e-06, 'epoch': 0.6}
+
60%|█████▉ | 7134/11952 [23:55<8:02:54, 6.01s/it]
60%|█████▉ | 7135/11952 [24:01<8:06:04, 6.05s/it]
{'loss': 0.4919, 'learning_rate': 7.376707708350881e-06, 'epoch': 0.6}
+
60%|█████▉ | 7135/11952 [24:01<8:06:04, 6.05s/it]
60%|█████▉ | 7136/11952 [24:07<8:04:09, 6.03s/it]
{'loss': 0.476, 'learning_rate': 7.374092805002353e-06, 'epoch': 0.6}
+
60%|█████▉ | 7136/11952 [24:07<8:04:09, 6.03s/it]
60%|█████▉ | 7137/11952 [24:12<7:56:27, 5.94s/it]
{'loss': 0.4844, 'learning_rate': 7.371478094489526e-06, 'epoch': 0.6}
+
60%|█████▉ | 7137/11952 [24:12<7:56:27, 5.94s/it]
60%|█████▉ | 7138/11952 [24:18<7:56:29, 5.94s/it]
{'loss': 0.4514, 'learning_rate': 7.368863577004415e-06, 'epoch': 0.6}
+
60%|█████▉ | 7138/11952 [24:18<7:56:29, 5.94s/it]
60%|█████▉ | 7139/11952 [24:24<7:50:28, 5.86s/it]
{'loss': 0.4578, 'learning_rate': 7.3662492527390195e-06, 'epoch': 0.6}
+
60%|█████▉ | 7139/11952 [24:24<7:50:28, 5.86s/it]
60%|█████▉ | 7140/11952 [24:30<7:47:31, 5.83s/it]
{'loss': 0.4904, 'learning_rate': 7.363635121885324e-06, 'epoch': 0.6}
+
60%|█████▉ | 7140/11952 [24:30<7:47:31, 5.83s/it]
60%|█████▉ | 7141/11952 [24:36<7:45:50, 5.81s/it]
{'loss': 0.4677, 'learning_rate': 7.361021184635296e-06, 'epoch': 0.6}
+
60%|█████▉ | 7141/11952 [24:36<7:45:50, 5.81s/it]
60%|█████▉ | 7142/11952 [24:41<7:47:16, 5.83s/it]
{'loss': 0.4727, 'learning_rate': 7.358407441180901e-06, 'epoch': 0.6}
+
60%|█████▉ | 7142/11952 [24:41<7:47:16, 5.83s/it]
60%|█████▉ | 7143/11952 [24:47<7:44:02, 5.79s/it]
{'loss': 0.4931, 'learning_rate': 7.355793891714073e-06, 'epoch': 0.6}
+
60%|█████▉ | 7143/11952 [24:47<7:44:02, 5.79s/it]
60%|█████▉ | 7144/11952 [24:53<7:41:50, 5.76s/it]
{'loss': 0.4635, 'learning_rate': 7.353180536426746e-06, 'epoch': 0.6}
+
60%|█████▉ | 7144/11952 [24:53<7:41:50, 5.76s/it]
60%|█████▉ | 7145/11952 [24:59<7:48:14, 5.84s/it]
{'loss': 0.4627, 'learning_rate': 7.350567375510831e-06, 'epoch': 0.6}
+
60%|█████▉ | 7145/11952 [24:59<7:48:14, 5.84s/it]
60%|█████▉ | 7146/11952 [25:05<7:50:18, 5.87s/it]
{'loss': 0.4851, 'learning_rate': 7.347954409158229e-06, 'epoch': 0.6}
+
60%|█████▉ | 7146/11952 [25:05<7:50:18, 5.87s/it]
60%|█████▉ | 7147/11952 [25:11<7:45:38, 5.81s/it]
{'loss': 0.4668, 'learning_rate': 7.345341637560822e-06, 'epoch': 0.6}
+
60%|█████▉ | 7147/11952 [25:11<7:45:38, 5.81s/it]
60%|█████▉ | 7148/11952 [25:16<7:39:04, 5.73s/it]
{'loss': 0.4759, 'learning_rate': 7.3427290609104825e-06, 'epoch': 0.6}
+
60%|█████▉ | 7148/11952 [25:16<7:39:04, 5.73s/it]
60%|█████▉ | 7149/11952 [25:22<7:46:57, 5.83s/it]
{'loss': 0.4839, 'learning_rate': 7.34011667939907e-06, 'epoch': 0.6}
+
60%|█████▉ | 7149/11952 [25:22<7:46:57, 5.83s/it]6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
60%|█████▉ | 7150/11952 [25:28<7:45:15, 5.81s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4695, 'learning_rate': 7.337504493218427e-06, 'epoch': 0.6}
+
60%|█████▉ | 7150/11952 [25:28<7:45:15, 5.81s/it]
60%|█████▉ | 7151/11952 [25:34<7:42:47, 5.78s/it]
{'loss': 0.4707, 'learning_rate': 7.33489250256038e-06, 'epoch': 0.6}
+
60%|█████▉ | 7151/11952 [25:34<7:42:47, 5.78s/it]
60%|█████▉ | 7152/11952 [25:40<7:54:55, 5.94s/it]
{'loss': 0.4862, 'learning_rate': 7.332280707616742e-06, 'epoch': 0.6}
+
60%|█████▉ | 7152/11952 [25:40<7:54:55, 5.94s/it]
60%|█████▉ | 7153/11952 [25:46<7:52:51, 5.91s/it]
{'loss': 0.4982, 'learning_rate': 7.329669108579312e-06, 'epoch': 0.6}
+
60%|█████▉ | 7153/11952 [25:46<7:52:51, 5.91s/it]
60%|█████▉ | 7154/11952 [25:52<7:55:06, 5.94s/it]
{'loss': 0.4853, 'learning_rate': 7.3270577056398765e-06, 'epoch': 0.6}
+
60%|█████▉ | 7154/11952 [25:52<7:55:06, 5.94s/it]
60%|█████▉ | 7155/11952 [25:58<7:51:05, 5.89s/it]
{'loss': 0.46, 'learning_rate': 7.324446498990202e-06, 'epoch': 0.6}
+
60%|█████▉ | 7155/11952 [25:58<7:51:05, 5.89s/it]
60%|█████▉ | 7156/11952 [26:04<8:03:18, 6.05s/it]
{'loss': 0.489, 'learning_rate': 7.321835488822052e-06, 'epoch': 0.6}
+
60%|█████▉ | 7156/11952 [26:04<8:03:18, 6.05s/it]
60%|█████▉ | 7157/11952 [26:10<8:00:33, 6.01s/it]
{'loss': 0.4728, 'learning_rate': 7.319224675327165e-06, 'epoch': 0.6}
+
60%|█████▉ | 7157/11952 [26:10<8:00:33, 6.01s/it]
60%|█████▉ | 7158/11952 [26:15<7:49:43, 5.88s/it]
{'loss': 0.4661, 'learning_rate': 7.316614058697264e-06, 'epoch': 0.6}
+
60%|█████▉ | 7158/11952 [26:15<7:49:43, 5.88s/it]
60%|█████▉ | 7159/11952 [26:22<7:54:23, 5.94s/it]
{'loss': 0.4589, 'learning_rate': 7.31400363912407e-06, 'epoch': 0.6}
+
60%|█████▉ | 7159/11952 [26:22<7:54:23, 5.94s/it]
60%|█████▉ | 7160/11952 [26:28<7:59:40, 6.01s/it]
{'loss': 0.477, 'learning_rate': 7.311393416799275e-06, 'epoch': 0.6}
+
60%|█████▉ | 7160/11952 [26:28<7:59:40, 6.01s/it]
60%|█████▉ | 7161/11952 [26:33<7:52:37, 5.92s/it]
{'loss': 0.4748, 'learning_rate': 7.308783391914566e-06, 'epoch': 0.6}
+
60%|█████▉ | 7161/11952 [26:33<7:52:37, 5.92s/it]
60%|█████▉ | 7162/11952 [26:39<7:48:33, 5.87s/it]
{'loss': 0.4859, 'learning_rate': 7.306173564661606e-06, 'epoch': 0.6}
+
60%|█████▉ | 7162/11952 [26:39<7:48:33, 5.87s/it]
60%|█████▉ | 7163/11952 [26:45<7:43:55, 5.81s/it]
{'loss': 0.4681, 'learning_rate': 7.303563935232059e-06, 'epoch': 0.6}
+
60%|█████▉ | 7163/11952 [26:45<7:43:55, 5.81s/it]
60%|█████▉ | 7164/11952 [26:51<7:47:51, 5.86s/it]
{'loss': 0.4732, 'learning_rate': 7.30095450381756e-06, 'epoch': 0.6}
+
60%|█████▉ | 7164/11952 [26:51<7:47:51, 5.86s/it]
60%|█████▉ | 7165/11952 [26:57<7:48:33, 5.87s/it]
{'loss': 0.4953, 'learning_rate': 7.298345270609738e-06, 'epoch': 0.6}
+
60%|█████▉ | 7165/11952 [26:57<7:48:33, 5.87s/it]
60%|█████▉ | 7166/11952 [27:02<7:44:06, 5.82s/it]
{'loss': 0.4648, 'learning_rate': 7.295736235800202e-06, 'epoch': 0.6}
+
60%|█████▉ | 7166/11952 [27:02<7:44:06, 5.82s/it]
60%|█████▉ | 7167/11952 [27:08<7:37:58, 5.74s/it]
{'loss': 0.4667, 'learning_rate': 7.293127399580548e-06, 'epoch': 0.6}
+
60%|█████▉ | 7167/11952 [27:08<7:37:58, 5.74s/it]
60%|█████▉ | 7168/11952 [27:14<7:40:48, 5.78s/it]
{'loss': 0.4753, 'learning_rate': 7.290518762142359e-06, 'epoch': 0.6}
+
60%|█████▉ | 7168/11952 [27:14<7:40:48, 5.78s/it]
60%|█████▉ | 7169/11952 [27:20<7:46:47, 5.86s/it]
{'loss': 0.4855, 'learning_rate': 7.287910323677199e-06, 'epoch': 0.6}
+
60%|█████▉ | 7169/11952 [27:20<7:46:47, 5.86s/it]
60%|█████▉ | 7170/11952 [27:25<7:40:35, 5.78s/it]
{'loss': 0.4779, 'learning_rate': 7.285302084376629e-06, 'epoch': 0.6}
+
60%|█████▉ | 7170/11952 [27:25<7:40:35, 5.78s/it]
60%|█████▉ | 7171/11952 [27:31<7:35:49, 5.72s/it]
{'loss': 0.4729, 'learning_rate': 7.282694044432182e-06, 'epoch': 0.6}
+
60%|█████▉ | 7171/11952 [27:31<7:35:49, 5.72s/it]
60%|██████ | 7172/11952 [27:37<7:32:59, 5.69s/it]
{'loss': 0.4795, 'learning_rate': 7.2800862040353834e-06, 'epoch': 0.6}
+
60%|██████ | 7172/11952 [27:37<7:32:59, 5.69s/it]
60%|██████ | 7173/11952 [27:42<7:34:59, 5.71s/it]
{'loss': 0.4546, 'learning_rate': 7.277478563377738e-06, 'epoch': 0.6}
+
60%|██████ | 7173/11952 [27:42<7:34:59, 5.71s/it]
60%|██████ | 7174/11952 [27:48<7:41:24, 5.79s/it]
{'loss': 0.4783, 'learning_rate': 7.274871122650746e-06, 'epoch': 0.6}
+
60%|██████ | 7174/11952 [27:48<7:41:24, 5.79s/it]
60%|██████ | 7175/11952 [27:54<7:41:10, 5.79s/it]
{'loss': 0.484, 'learning_rate': 7.272263882045884e-06, 'epoch': 0.6}
+
60%|██████ | 7175/11952 [27:54<7:41:10, 5.79s/it]
60%|██████ | 7176/11952 [28:00<7:39:19, 5.77s/it]
{'loss': 0.4802, 'learning_rate': 7.269656841754612e-06, 'epoch': 0.6}
+
60%|██████ | 7176/11952 [28:00<7:39:19, 5.77s/it]
60%|██████ | 7177/11952 [28:06<7:37:40, 5.75s/it]
{'loss': 0.4704, 'learning_rate': 7.2670500019683895e-06, 'epoch': 0.6}
+
60%|██████ | 7177/11952 [28:06<7:37:40, 5.75s/it]
60%|██████ | 7178/11952 [28:11<7:33:35, 5.70s/it]
{'loss': 0.4744, 'learning_rate': 7.264443362878648e-06, 'epoch': 0.6}
+
60%|██████ | 7178/11952 [28:11<7:33:35, 5.70s/it]
60%|██████ | 7179/11952 [28:17<7:32:22, 5.69s/it]
{'loss': 0.4763, 'learning_rate': 7.261836924676806e-06, 'epoch': 0.6}
+
60%|██████ | 7179/11952 [28:17<7:32:22, 5.69s/it]
60%|██████ | 7180/11952 [28:23<7:43:27, 5.83s/it]
{'loss': 0.4847, 'learning_rate': 7.259230687554273e-06, 'epoch': 0.6}
+
60%|██████ | 7180/11952 [28:23<7:43:27, 5.83s/it]
60%|██████ | 7181/11952 [28:29<7:44:39, 5.84s/it]
{'loss': 0.4645, 'learning_rate': 7.25662465170244e-06, 'epoch': 0.6}
+
60%|██████ | 7181/11952 [28:29<7:44:39, 5.84s/it]
60%|██████ | 7182/11952 [28:35<7:39:45, 5.78s/it]
{'loss': 0.4808, 'learning_rate': 7.254018817312676e-06, 'epoch': 0.6}
+
60%|██████ | 7182/11952 [28:35<7:39:45, 5.78s/it]
60%|██████ | 7183/11952 [28:41<7:47:48, 5.89s/it]
{'loss': 0.4698, 'learning_rate': 7.2514131845763535e-06, 'epoch': 0.6}
+
60%|██████ | 7183/11952 [28:41<7:47:48, 5.89s/it]
60%|██████ | 7184/11952 [28:46<7:40:38, 5.80s/it]
{'loss': 0.4562, 'learning_rate': 7.248807753684812e-06, 'epoch': 0.6}
+
60%|██████ | 7184/11952 [28:46<7:40:38, 5.80s/it]
60%|██████ | 7185/11952 [28:52<7:44:40, 5.85s/it]
{'loss': 0.4745, 'learning_rate': 7.246202524829389e-06, 'epoch': 0.6}
+
60%|██████ | 7185/11952 [28:52<7:44:40, 5.85s/it]
60%|██████ | 7186/11952 [28:58<7:41:24, 5.81s/it]
{'loss': 0.474, 'learning_rate': 7.243597498201398e-06, 'epoch': 0.6}
+
60%|██████ | 7186/11952 [28:58<7:41:24, 5.81s/it]
60%|██████ | 7187/11952 [29:04<7:43:28, 5.84s/it]
{'loss': 0.4557, 'learning_rate': 7.240992673992142e-06, 'epoch': 0.6}
+
60%|██████ | 7187/11952 [29:04<7:43:28, 5.84s/it]
60%|██████ | 7188/11952 [29:10<7:43:03, 5.83s/it]
{'loss': 0.4624, 'learning_rate': 7.238388052392906e-06, 'epoch': 0.6}
+
60%|██████ | 7188/11952 [29:10<7:43:03, 5.83s/it]
60%|██████ | 7189/11952 [29:16<7:43:02, 5.83s/it]
{'loss': 0.4785, 'learning_rate': 7.235783633594966e-06, 'epoch': 0.6}
+
60%|██████ | 7189/11952 [29:16<7:43:02, 5.83s/it]
60%|██████ | 7190/11952 [29:21<7:41:16, 5.81s/it]
{'loss': 0.4791, 'learning_rate': 7.2331794177895785e-06, 'epoch': 0.6}
+
60%|██████ | 7190/11952 [29:21<7:41:16, 5.81s/it]
60%|██████ | 7191/11952 [29:27<7:44:25, 5.85s/it]
{'loss': 0.4867, 'learning_rate': 7.230575405167989e-06, 'epoch': 0.6}
+
60%|██████ | 7191/11952 [29:27<7:44:25, 5.85s/it]
60%|██████ | 7192/11952 [29:33<7:45:46, 5.87s/it]
{'loss': 0.473, 'learning_rate': 7.2279715959214216e-06, 'epoch': 0.6}
+
60%|██████ | 7192/11952 [29:33<7:45:46, 5.87s/it]
60%|██████ | 7193/11952 [29:39<7:48:36, 5.91s/it]
{'loss': 0.4794, 'learning_rate': 7.2253679902410914e-06, 'epoch': 0.6}
+
60%|██████ | 7193/11952 [29:39<7:48:36, 5.91s/it]
60%|██████ | 7194/11952 [29:45<7:51:26, 5.95s/it]
{'loss': 0.4752, 'learning_rate': 7.2227645883181926e-06, 'epoch': 0.6}
+
60%|██████ | 7194/11952 [29:45<7:51:26, 5.95s/it]
60%|██████ | 7195/11952 [29:51<7:44:39, 5.86s/it]
{'loss': 0.4562, 'learning_rate': 7.220161390343914e-06, 'epoch': 0.6}
+
60%|██████ | 7195/11952 [29:51<7:44:39, 5.86s/it]
60%|██████ | 7196/11952 [29:56<7:37:50, 5.78s/it]
{'loss': 0.4697, 'learning_rate': 7.217558396509416e-06, 'epoch': 0.6}
+
60%|██████ | 7196/11952 [29:56<7:37:50, 5.78s/it]
60%|██████ | 7197/11952 [30:03<7:52:51, 5.97s/it]
{'loss': 0.479, 'learning_rate': 7.214955607005861e-06, 'epoch': 0.6}
+
60%|██████ | 7197/11952 [30:03<7:52:51, 5.97s/it]
60%|██████ | 7198/11952 [30:09<7:46:57, 5.89s/it]
{'loss': 0.4691, 'learning_rate': 7.212353022024381e-06, 'epoch': 0.6}
+
60%|██████ | 7198/11952 [30:09<7:46:57, 5.89s/it]
60%|██████ | 7199/11952 [30:15<7:58:32, 6.04s/it]
{'loss': 0.5009, 'learning_rate': 7.209750641756099e-06, 'epoch': 0.6}
+
60%|██████ | 7199/11952 [30:15<7:58:32, 6.04s/it]7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...2 AutoResumeHook: Checking whether to suspend...
+
+
60%|██████ | 7200/11952 [30:21<7:54:13, 5.99s/it]
{'loss': 0.4813, 'learning_rate': 7.2071484663921265e-06, 'epoch': 0.6}
+
60%|██████ | 7200/11952 [30:21<7:54:13, 5.99s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
60%|██████ | 7201/11952 [30:52<17:49:21, 13.50s/it]
{'loss': 0.4723, 'learning_rate': 7.2045464961235545e-06, 'epoch': 0.6}
+
60%|██████ | 7201/11952 [30:52<17:49:21, 13.50s/it]
60%|██████ | 7202/11952 [30:58<14:51:38, 11.26s/it]
{'loss': 0.4889, 'learning_rate': 7.2019447311414615e-06, 'epoch': 0.6}
+
60%|██████ | 7202/11952 [30:58<14:51:38, 11.26s/it]
60%|██████ | 7203/11952 [31:04<12:44:51, 9.66s/it]
{'loss': 0.4896, 'learning_rate': 7.199343171636903e-06, 'epoch': 0.6}
+
60%|██████ | 7203/11952 [31:04<12:44:51, 9.66s/it]
60%|██████ | 7204/11952 [31:10<11:10:48, 8.48s/it]
{'loss': 0.4664, 'learning_rate': 7.1967418178009396e-06, 'epoch': 0.6}
+
60%|██████ | 7204/11952 [31:10<11:10:48, 8.48s/it]
60%|██████ | 7205/11952 [31:15<10:07:10, 7.67s/it]
{'loss': 0.465, 'learning_rate': 7.1941406698245945e-06, 'epoch': 0.6}
+
60%|██████ | 7205/11952 [31:15<10:07:10, 7.67s/it]
60%|██████ | 7206/11952 [31:21<9:27:25, 7.17s/it]
{'loss': 0.4895, 'learning_rate': 7.1915397278988895e-06, 'epoch': 0.6}
+
60%|██████ | 7206/11952 [31:21<9:27:25, 7.17s/it]
60%|██████ | 7207/11952 [31:27<8:58:42, 6.81s/it]
{'loss': 0.4543, 'learning_rate': 7.188938992214827e-06, 'epoch': 0.6}
+
60%|██████ | 7207/11952 [31:27<8:58:42, 6.81s/it]
60%|██████ | 7208/11952 [31:33<8:31:35, 6.47s/it]
{'loss': 0.4568, 'learning_rate': 7.186338462963392e-06, 'epoch': 0.6}
+
60%|██████ | 7208/11952 [31:33<8:31:35, 6.47s/it]
60%|██████ | 7209/11952 [31:39<8:18:03, 6.30s/it]
{'loss': 0.4777, 'learning_rate': 7.183738140335556e-06, 'epoch': 0.6}
+
60%|██████ | 7209/11952 [31:39<8:18:03, 6.30s/it]
60%|██████ | 7210/11952 [31:45<8:05:51, 6.15s/it]
{'loss': 0.4731, 'learning_rate': 7.181138024522274e-06, 'epoch': 0.6}
+
60%|██████ | 7210/11952 [31:45<8:05:51, 6.15s/it]
60%|██████ | 7211/11952 [31:50<7:50:40, 5.96s/it]
{'loss': 0.4658, 'learning_rate': 7.1785381157144954e-06, 'epoch': 0.6}
+
60%|██████ | 7211/11952 [31:50<7:50:40, 5.96s/it]
60%|██████ | 7212/11952 [31:56<7:44:28, 5.88s/it]
{'loss': 0.4924, 'learning_rate': 7.175938414103143e-06, 'epoch': 0.6}
+
60%|██████ | 7212/11952 [31:56<7:44:28, 5.88s/it]
60%|██████ | 7213/11952 [32:02<7:48:22, 5.93s/it]
{'loss': 0.4749, 'learning_rate': 7.173338919879127e-06, 'epoch': 0.6}
+
60%|██████ | 7213/11952 [32:02<7:48:22, 5.93s/it]
60%|██████ | 7214/11952 [32:07<7:39:20, 5.82s/it]
{'loss': 0.46, 'learning_rate': 7.170739633233341e-06, 'epoch': 0.6}
+
60%|██████ | 7214/11952 [32:07<7:39:20, 5.82s/it]
60%|██████ | 7215/11952 [32:13<7:39:28, 5.82s/it]
{'loss': 0.486, 'learning_rate': 7.168140554356671e-06, 'epoch': 0.6}
+
60%|██████ | 7215/11952 [32:13<7:39:28, 5.82s/it]
60%|██████ | 7216/11952 [32:19<7:42:07, 5.85s/it]
{'loss': 0.4737, 'learning_rate': 7.165541683439976e-06, 'epoch': 0.6}
+
60%|██████ | 7216/11952 [32:19<7:42:07, 5.85s/it]
60%|██████ | 7217/11952 [32:25<7:36:30, 5.78s/it]
{'loss': 0.4437, 'learning_rate': 7.162943020674116e-06, 'epoch': 0.6}
+
60%|██████ | 7217/11952 [32:25<7:36:30, 5.78s/it]
60%|██████ | 7218/11952 [32:31<7:39:49, 5.83s/it]
{'loss': 0.4727, 'learning_rate': 7.160344566249918e-06, 'epoch': 0.6}
+
60%|██████ | 7218/11952 [32:31<7:39:49, 5.83s/it]
60%|██████ | 7219/11952 [32:36<7:37:05, 5.79s/it]
{'loss': 0.4749, 'learning_rate': 7.1577463203582056e-06, 'epoch': 0.6}
+
60%|██████ | 7219/11952 [32:36<7:37:05, 5.79s/it]
60%|██████ | 7220/11952 [32:43<7:42:51, 5.87s/it]
{'loss': 0.4594, 'learning_rate': 7.155148283189779e-06, 'epoch': 0.6}
+
60%|██████ | 7220/11952 [32:43<7:42:51, 5.87s/it]
60%|██████ | 7221/11952 [32:48<7:39:35, 5.83s/it]
{'loss': 0.4536, 'learning_rate': 7.152550454935432e-06, 'epoch': 0.6}
+
60%|██████ | 7221/11952 [32:48<7:39:35, 5.83s/it]
60%|██████ | 7222/11952 [32:54<7:35:49, 5.78s/it]
{'loss': 0.4791, 'learning_rate': 7.149952835785936e-06, 'epoch': 0.6}
+
60%|██████ | 7222/11952 [32:54<7:35:49, 5.78s/it]
60%|██████ | 7223/11952 [33:00<7:37:38, 5.81s/it]
{'loss': 0.4786, 'learning_rate': 7.147355425932045e-06, 'epoch': 0.6}
+
60%|██████ | 7223/11952 [33:00<7:37:38, 5.81s/it]
60%|██████ | 7224/11952 [33:06<7:36:38, 5.79s/it]
{'loss': 0.4874, 'learning_rate': 7.144758225564511e-06, 'epoch': 0.6}
+
60%|██████ | 7224/11952 [33:06<7:36:38, 5.79s/it]
60%|██████ | 7225/11952 [33:12<7:43:44, 5.89s/it]
{'loss': 0.4724, 'learning_rate': 7.1421612348740564e-06, 'epoch': 0.6}
+
60%|██████ | 7225/11952 [33:12<7:43:44, 5.89s/it]
60%|██████ | 7226/11952 [33:17<7:39:10, 5.83s/it]
{'loss': 0.4492, 'learning_rate': 7.139564454051393e-06, 'epoch': 0.6}
+
60%|██████ | 7226/11952 [33:17<7:39:10, 5.83s/it]
60%|██████ | 7227/11952 [33:23<7:45:14, 5.91s/it]
{'loss': 0.4765, 'learning_rate': 7.1369678832872205e-06, 'epoch': 0.6}
+
60%|██████ | 7227/11952 [33:23<7:45:14, 5.91s/it]
60%|██████ | 7228/11952 [33:29<7:40:48, 5.85s/it]
{'loss': 0.4604, 'learning_rate': 7.134371522772218e-06, 'epoch': 0.6}
+
60%|██████ | 7228/11952 [33:29<7:40:48, 5.85s/it]
60%|██████ | 7229/11952 [33:35<7:41:27, 5.86s/it]
{'loss': 0.4776, 'learning_rate': 7.131775372697051e-06, 'epoch': 0.6}
+
60%|██████ | 7229/11952 [33:35<7:41:27, 5.86s/it]
60%|██████ | 7230/11952 [33:41<7:48:30, 5.95s/it]
{'loss': 0.4757, 'learning_rate': 7.129179433252369e-06, 'epoch': 0.6}
+
60%|██████ | 7230/11952 [33:41<7:48:30, 5.95s/it]
61%|██████ | 7231/11952 [33:47<7:39:27, 5.84s/it]
{'loss': 0.4783, 'learning_rate': 7.126583704628811e-06, 'epoch': 0.6}
+
61%|██████ | 7231/11952 [33:47<7:39:27, 5.84s/it]
61%|██████ | 7232/11952 [33:52<7:35:08, 5.79s/it]
{'loss': 0.4575, 'learning_rate': 7.123988187016994e-06, 'epoch': 0.61}
+
61%|██████ | 7232/11952 [33:52<7:35:08, 5.79s/it]
61%|██████ | 7233/11952 [33:58<7:29:43, 5.72s/it]
{'loss': 0.4542, 'learning_rate': 7.121392880607524e-06, 'epoch': 0.61}
+
61%|██████ | 7233/11952 [33:58<7:29:43, 5.72s/it]
61%|██████ | 7234/11952 [34:04<7:33:09, 5.76s/it]
{'loss': 0.4811, 'learning_rate': 7.118797785590987e-06, 'epoch': 0.61}
+
61%|██████ | 7234/11952 [34:04<7:33:09, 5.76s/it]
61%|██████ | 7235/11952 [34:09<7:25:06, 5.66s/it]
{'loss': 0.4668, 'learning_rate': 7.116202902157955e-06, 'epoch': 0.61}
+
61%|██████ | 7235/11952 [34:09<7:25:06, 5.66s/it]
61%|██████ | 7236/11952 [34:15<7:24:53, 5.66s/it]
{'loss': 0.4617, 'learning_rate': 7.113608230498989e-06, 'epoch': 0.61}
+
61%|██████ | 7236/11952 [34:15<7:24:53, 5.66s/it]
61%|██████ | 7237/11952 [34:21<7:28:19, 5.71s/it]
{'loss': 0.4798, 'learning_rate': 7.1110137708046245e-06, 'epoch': 0.61}
+
61%|██████ | 7237/11952 [34:21<7:28:19, 5.71s/it]
61%|██████ | 7238/11952 [34:27<7:29:46, 5.72s/it]
{'loss': 0.4776, 'learning_rate': 7.108419523265398e-06, 'epoch': 0.61}
+
61%|██████ | 7238/11952 [34:27<7:29:46, 5.72s/it]
61%|██████ | 7239/11952 [34:32<7:31:08, 5.74s/it]
{'loss': 0.4692, 'learning_rate': 7.105825488071814e-06, 'epoch': 0.61}
+
61%|██████ | 7239/11952 [34:32<7:31:08, 5.74s/it]
61%|██████ | 7240/11952 [34:38<7:35:20, 5.80s/it]
{'loss': 0.5049, 'learning_rate': 7.1032316654143685e-06, 'epoch': 0.61}
+
61%|██████ | 7240/11952 [34:38<7:35:20, 5.80s/it]
61%|██████ | 7241/11952 [34:44<7:31:18, 5.75s/it]
{'loss': 0.497, 'learning_rate': 7.100638055483539e-06, 'epoch': 0.61}
+
61%|██████ | 7241/11952 [34:44<7:31:18, 5.75s/it]
61%|██████ | 7242/11952 [34:50<7:34:10, 5.79s/it]
{'loss': 0.4646, 'learning_rate': 7.098044658469794e-06, 'epoch': 0.61}
+
61%|██████ | 7242/11952 [34:50<7:34:10, 5.79s/it]
61%|██████ | 7243/11952 [34:56<7:33:20, 5.78s/it]
{'loss': 0.4768, 'learning_rate': 7.095451474563577e-06, 'epoch': 0.61}
+
61%|██████ | 7243/11952 [34:56<7:33:20, 5.78s/it]
61%|██████ | 7244/11952 [35:02<7:37:53, 5.84s/it]
{'loss': 0.4877, 'learning_rate': 7.0928585039553196e-06, 'epoch': 0.61}
+
61%|██████ | 7244/11952 [35:02<7:37:53, 5.84s/it]
61%|██████ | 7245/11952 [35:08<7:42:17, 5.89s/it]
{'loss': 0.4736, 'learning_rate': 7.090265746835448e-06, 'epoch': 0.61}
+
61%|██████ | 7245/11952 [35:08<7:42:17, 5.89s/it]
61%|██████ | 7246/11952 [35:13<7:37:58, 5.84s/it]
{'loss': 0.4889, 'learning_rate': 7.087673203394353e-06, 'epoch': 0.61}
+
61%|██████ | 7246/11952 [35:13<7:37:58, 5.84s/it]
61%|██████ | 7247/11952 [35:19<7:39:26, 5.86s/it]
{'loss': 0.4775, 'learning_rate': 7.085080873822427e-06, 'epoch': 0.61}
+
61%|██████ | 7247/11952 [35:19<7:39:26, 5.86s/it]
61%|██████ | 7248/11952 [35:25<7:43:03, 5.91s/it]
{'loss': 0.4754, 'learning_rate': 7.082488758310039e-06, 'epoch': 0.61}
+
61%|██████ | 7248/11952 [35:25<7:43:03, 5.91s/it]
61%|██████ | 7249/11952 [35:31<7:43:08, 5.91s/it]
{'loss': 0.4945, 'learning_rate': 7.079896857047541e-06, 'epoch': 0.61}
+
61%|██████ | 7249/11952 [35:31<7:43:08, 5.91s/it]07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...4
+ AutoResumeHook: Checking whether to suspend...
+51 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
61%|██████ | 7250/11952 [35:37<7:40:08, 5.87s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4771, 'learning_rate': 7.07730517022527e-06, 'epoch': 0.61}
+
61%|██████ | 7250/11952 [35:37<7:40:08, 5.87s/it]
61%|██████ | 7251/11952 [35:43<7:38:58, 5.86s/it]
{'loss': 0.4622, 'learning_rate': 7.074713698033551e-06, 'epoch': 0.61}
+
61%|██████ | 7251/11952 [35:43<7:38:58, 5.86s/it]
61%|██████ | 7252/11952 [35:48<7:37:31, 5.84s/it]
{'loss': 0.4601, 'learning_rate': 7.0721224406626895e-06, 'epoch': 0.61}
+
61%|██████ | 7252/11952 [35:48<7:37:31, 5.84s/it]
61%|██████ | 7253/11952 [35:54<7:37:43, 5.84s/it]
{'loss': 0.4758, 'learning_rate': 7.069531398302982e-06, 'epoch': 0.61}
+
61%|██████ | 7253/11952 [35:54<7:37:43, 5.84s/it]
61%|██████ | 7254/11952 [36:00<7:40:48, 5.89s/it]
{'loss': 0.4787, 'learning_rate': 7.0669405711447e-06, 'epoch': 0.61}
+
61%|██████ | 7254/11952 [36:00<7:40:48, 5.89s/it]
61%|██████ | 7255/11952 [36:06<7:45:20, 5.94s/it]
{'loss': 0.4817, 'learning_rate': 7.064349959378102e-06, 'epoch': 0.61}
+
61%|██████ | 7255/11952 [36:06<7:45:20, 5.94s/it]
61%|██████ | 7256/11952 [36:12<7:42:49, 5.91s/it]
{'loss': 0.4727, 'learning_rate': 7.061759563193431e-06, 'epoch': 0.61}
+
61%|██████ | 7256/11952 [36:12<7:42:49, 5.91s/it]
61%|██████ | 7257/11952 [36:18<7:45:28, 5.95s/it]
{'loss': 0.4839, 'learning_rate': 7.059169382780914e-06, 'epoch': 0.61}
+
61%|██████ | 7257/11952 [36:18<7:45:28, 5.95s/it]
61%|██████ | 7258/11952 [36:24<7:43:39, 5.93s/it]
{'loss': 0.4819, 'learning_rate': 7.05657941833077e-06, 'epoch': 0.61}
+
61%|██████ | 7258/11952 [36:24<7:43:39, 5.93s/it]
61%|██████ | 7259/11952 [36:30<7:37:57, 5.85s/it]
{'loss': 0.4709, 'learning_rate': 7.053989670033191e-06, 'epoch': 0.61}
+
61%|██████ | 7259/11952 [36:30<7:37:57, 5.85s/it]
61%|██████ | 7260/11952 [36:36<7:44:13, 5.94s/it]
{'loss': 0.5036, 'learning_rate': 7.051400138078357e-06, 'epoch': 0.61}
+
61%|██████ | 7260/11952 [36:36<7:44:13, 5.94s/it]
61%|██████ | 7261/11952 [36:42<7:49:47, 6.01s/it]
{'loss': 0.4635, 'learning_rate': 7.048810822656431e-06, 'epoch': 0.61}
+
61%|██████ | 7261/11952 [36:42<7:49:47, 6.01s/it]
61%|██████ | 7262/11952 [36:48<7:44:28, 5.94s/it]
{'loss': 0.4943, 'learning_rate': 7.046221723957566e-06, 'epoch': 0.61}
+
61%|██████ | 7262/11952 [36:48<7:44:28, 5.94s/it]
61%|██████ | 7263/11952 [36:54<7:41:34, 5.91s/it]
{'loss': 0.466, 'learning_rate': 7.043632842171891e-06, 'epoch': 0.61}
+
61%|██████ | 7263/11952 [36:54<7:41:34, 5.91s/it]
61%|██████ | 7264/11952 [37:00<7:40:34, 5.89s/it]
{'loss': 0.487, 'learning_rate': 7.04104417748952e-06, 'epoch': 0.61}
+
61%|██████ | 7264/11952 [37:00<7:40:34, 5.89s/it]
61%|██████ | 7265/11952 [37:06<7:40:49, 5.90s/it]
{'loss': 0.5054, 'learning_rate': 7.038455730100562e-06, 'epoch': 0.61}
+
61%|██████ | 7265/11952 [37:06<7:40:49, 5.90s/it]
61%|██████ | 7266/11952 [37:11<7:37:59, 5.86s/it]
{'loss': 0.4723, 'learning_rate': 7.035867500195095e-06, 'epoch': 0.61}
+
61%|██████ | 7266/11952 [37:11<7:37:59, 5.86s/it]
61%|██████ | 7267/11952 [37:17<7:43:21, 5.93s/it]
{'loss': 0.4646, 'learning_rate': 7.033279487963189e-06, 'epoch': 0.61}
+
61%|██████ | 7267/11952 [37:17<7:43:21, 5.93s/it]
61%|██████ | 7268/11952 [37:23<7:40:38, 5.90s/it]
{'loss': 0.49, 'learning_rate': 7.030691693594901e-06, 'epoch': 0.61}
+
61%|██████ | 7268/11952 [37:23<7:40:38, 5.90s/it]
61%|██████ | 7269/11952 [37:29<7:38:42, 5.88s/it]
{'loss': 0.4855, 'learning_rate': 7.028104117280265e-06, 'epoch': 0.61}
+
61%|██████ | 7269/11952 [37:29<7:38:42, 5.88s/it]
61%|██████ | 7270/11952 [37:35<7:33:27, 5.81s/it]
{'loss': 0.4694, 'learning_rate': 7.0255167592092995e-06, 'epoch': 0.61}
+
61%|██████ | 7270/11952 [37:35<7:33:27, 5.81s/it]
61%|██████ | 7271/11952 [37:41<7:33:10, 5.81s/it]
{'loss': 0.4606, 'learning_rate': 7.022929619572009e-06, 'epoch': 0.61}
+
61%|██████ | 7271/11952 [37:41<7:33:10, 5.81s/it]
61%|██████ | 7272/11952 [37:46<7:25:39, 5.71s/it]
{'loss': 0.4617, 'learning_rate': 7.020342698558387e-06, 'epoch': 0.61}
+
61%|██████ | 7272/11952 [37:46<7:25:39, 5.71s/it]
61%|██████ | 7273/11952 [37:52<7:27:03, 5.73s/it]
{'loss': 0.4771, 'learning_rate': 7.017755996358404e-06, 'epoch': 0.61}
+
61%|██████ | 7273/11952 [37:52<7:27:03, 5.73s/it]
61%|██████ | 7274/11952 [37:58<7:37:18, 5.87s/it]
{'loss': 0.4914, 'learning_rate': 7.015169513162018e-06, 'epoch': 0.61}
+
61%|██████ | 7274/11952 [37:58<7:37:18, 5.87s/it]
61%|██████ | 7275/11952 [38:04<7:46:27, 5.98s/it]
{'loss': 0.4829, 'learning_rate': 7.012583249159167e-06, 'epoch': 0.61}
+
61%|██████ | 7275/11952 [38:04<7:46:27, 5.98s/it]
61%|██████ | 7276/11952 [38:10<7:46:51, 5.99s/it]
{'loss': 0.488, 'learning_rate': 7.009997204539775e-06, 'epoch': 0.61}
+
61%|██████ | 7276/11952 [38:10<7:46:51, 5.99s/it]
61%|██████ | 7277/11952 [38:16<7:44:41, 5.96s/it]
{'loss': 0.4732, 'learning_rate': 7.007411379493755e-06, 'epoch': 0.61}
+
61%|██████ | 7277/11952 [38:16<7:44:41, 5.96s/it]
61%|██████ | 7278/11952 [38:22<7:47:09, 6.00s/it]
{'loss': 0.4704, 'learning_rate': 7.004825774210992e-06, 'epoch': 0.61}
+
61%|██████ | 7278/11952 [38:22<7:47:09, 6.00s/it]
61%|██████ | 7279/11952 [38:28<7:50:38, 6.04s/it]
{'loss': 0.4658, 'learning_rate': 7.002240388881369e-06, 'epoch': 0.61}
+
61%|██████ | 7279/11952 [38:28<7:50:38, 6.04s/it]
61%|██████ | 7280/11952 [38:34<7:52:13, 6.06s/it]
{'loss': 0.4793, 'learning_rate': 6.999655223694743e-06, 'epoch': 0.61}
+
61%|██████ | 7280/11952 [38:34<7:52:13, 6.06s/it]
61%|██████ | 7281/11952 [38:40<7:45:08, 5.97s/it]
{'loss': 0.4676, 'learning_rate': 6.997070278840961e-06, 'epoch': 0.61}
+
61%|██████ | 7281/11952 [38:40<7:45:08, 5.97s/it]
61%|██████ | 7282/11952 [38:46<7:37:22, 5.88s/it]
{'loss': 0.4818, 'learning_rate': 6.994485554509842e-06, 'epoch': 0.61}
+
61%|██████ | 7282/11952 [38:46<7:37:22, 5.88s/it]
61%|██████ | 7283/11952 [38:51<7:31:10, 5.80s/it]
{'loss': 0.4762, 'learning_rate': 6.9919010508912075e-06, 'epoch': 0.61}
+
61%|██████ | 7283/11952 [38:51<7:31:10, 5.80s/it]
61%|██████ | 7284/11952 [38:57<7:25:58, 5.73s/it]
{'loss': 0.4686, 'learning_rate': 6.989316768174848e-06, 'epoch': 0.61}
+
61%|██████ | 7284/11952 [38:57<7:25:58, 5.73s/it]
61%|██████ | 7285/11952 [39:03<7:19:33, 5.65s/it]
{'loss': 0.4748, 'learning_rate': 6.986732706550536e-06, 'epoch': 0.61}
+
61%|██████ | 7285/11952 [39:03<7:19:33, 5.65s/it]
61%|██████ | 7286/11952 [39:08<7:21:51, 5.68s/it]
{'loss': 0.4721, 'learning_rate': 6.984148866208047e-06, 'epoch': 0.61}
+
61%|██████ | 7286/11952 [39:08<7:21:51, 5.68s/it]
61%|██████ | 7287/11952 [39:14<7:24:21, 5.72s/it]
{'loss': 0.48, 'learning_rate': 6.98156524733712e-06, 'epoch': 0.61}
+
61%|██████ | 7287/11952 [39:14<7:24:21, 5.72s/it]
61%|██████ | 7288/11952 [39:20<7:20:13, 5.66s/it]
{'loss': 0.4841, 'learning_rate': 6.978981850127487e-06, 'epoch': 0.61}
+
61%|██████ | 7288/11952 [39:20<7:20:13, 5.66s/it]
61%|██████ | 7289/11952 [39:26<7:32:28, 5.82s/it]
{'loss': 0.4418, 'learning_rate': 6.976398674768863e-06, 'epoch': 0.61}
+
61%|██████ | 7289/11952 [39:26<7:32:28, 5.82s/it]
61%|██████ | 7290/11952 [39:32<7:36:12, 5.87s/it]
{'loss': 0.4861, 'learning_rate': 6.973815721450942e-06, 'epoch': 0.61}
+
61%|██████ | 7290/11952 [39:32<7:36:12, 5.87s/it]
61%|██████ | 7291/11952 [39:37<7:30:49, 5.80s/it]
{'loss': 0.4719, 'learning_rate': 6.971232990363406e-06, 'epoch': 0.61}
+
61%|██████ | 7291/11952 [39:37<7:30:49, 5.80s/it]
61%|██████ | 7292/11952 [39:43<7:31:46, 5.82s/it]
{'loss': 0.4704, 'learning_rate': 6.968650481695926e-06, 'epoch': 0.61}
+
61%|██████ | 7292/11952 [39:43<7:31:46, 5.82s/it]
61%|██████ | 7293/11952 [39:49<7:33:53, 5.85s/it]
{'loss': 0.4914, 'learning_rate': 6.966068195638143e-06, 'epoch': 0.61}
+
61%|██████ | 7293/11952 [39:49<7:33:53, 5.85s/it]
61%|██████ | 7294/11952 [39:55<7:34:54, 5.86s/it]
{'loss': 0.4566, 'learning_rate': 6.963486132379694e-06, 'epoch': 0.61}
+
61%|██████ | 7294/11952 [39:55<7:34:54, 5.86s/it]
61%|██████ | 7295/11952 [40:01<7:33:45, 5.85s/it]
{'loss': 0.4767, 'learning_rate': 6.960904292110194e-06, 'epoch': 0.61}
+
61%|██████ | 7295/11952 [40:01<7:33:45, 5.85s/it]
61%|██████ | 7296/11952 [40:07<7:38:50, 5.91s/it]
{'loss': 0.4918, 'learning_rate': 6.958322675019243e-06, 'epoch': 0.61}
+
61%|██████ | 7296/11952 [40:07<7:38:50, 5.91s/it]
61%|██████ | 7297/11952 [40:13<7:41:14, 5.95s/it]
{'loss': 0.4656, 'learning_rate': 6.955741281296421e-06, 'epoch': 0.61}
+
61%|██████ | 7297/11952 [40:13<7:41:14, 5.95s/it]
61%|██████ | 7298/11952 [40:19<7:42:05, 5.96s/it]
{'loss': 0.4493, 'learning_rate': 6.953160111131295e-06, 'epoch': 0.61}
+
61%|██████ | 7298/11952 [40:19<7:42:05, 5.96s/it]
61%|██████ | 7299/11952 [40:25<7:34:33, 5.86s/it]
{'loss': 0.4678, 'learning_rate': 6.950579164713422e-06, 'epoch': 0.61}
+
61%|██████ | 7299/11952 [40:25<7:34:33, 5.86s/it]0 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+41 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
61%|██████ | 7300/11952 [40:30<7:33:41, 5.85s/it]7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4811, 'learning_rate': 6.947998442232332e-06, 'epoch': 0.61}
+
61%|██████ | 7300/11952 [40:30<7:33:41, 5.85s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
61%|██████ | 7301/11952 [41:03<17:44:46, 13.74s/it]
{'loss': 0.4744, 'learning_rate': 6.945417943877541e-06, 'epoch': 0.61}
+
61%|██████ | 7301/11952 [41:03<17:44:46, 13.74s/it]
61%|██████ | 7302/11952 [41:09<14:42:53, 11.39s/it]
{'loss': 0.4583, 'learning_rate': 6.942837669838552e-06, 'epoch': 0.61}
+
61%|██████ | 7302/11952 [41:09<14:42:53, 11.39s/it]
61%|██████ | 7303/11952 [41:14<12:36:44, 9.77s/it]
{'loss': 0.498, 'learning_rate': 6.9402576203048474e-06, 'epoch': 0.61}
+
61%|██████ | 7303/11952 [41:14<12:36:44, 9.77s/it]
61%|██████ | 7304/11952 [41:20<11:08:37, 8.63s/it]
{'loss': 0.4433, 'learning_rate': 6.937677795465898e-06, 'epoch': 0.61}
+
61%|██████ | 7304/11952 [41:20<11:08:37, 8.63s/it]
61%|██████ | 7305/11952 [41:26<10:01:52, 7.77s/it]
{'loss': 0.4787, 'learning_rate': 6.935098195511151e-06, 'epoch': 0.61}
+
61%|██████ | 7305/11952 [41:26<10:01:52, 7.77s/it]
61%|██████ | 7306/11952 [41:32<9:12:07, 7.13s/it]
{'loss': 0.4839, 'learning_rate': 6.932518820630048e-06, 'epoch': 0.61}
+
61%|██████ | 7306/11952 [41:32<9:12:07, 7.13s/it]
61%|██████ | 7307/11952 [41:38<8:38:34, 6.70s/it]
{'loss': 0.4922, 'learning_rate': 6.929939671012005e-06, 'epoch': 0.61}
+
61%|██████ | 7307/11952 [41:38<8:38:34, 6.70s/it]
61%|██████ | 7308/11952 [41:43<8:14:04, 6.38s/it]
{'loss': 0.451, 'learning_rate': 6.9273607468464185e-06, 'epoch': 0.61}
+
61%|██████ | 7308/11952 [41:43<8:14:04, 6.38s/it]
61%|██████ | 7309/11952 [41:49<7:56:35, 6.16s/it]
{'loss': 0.4665, 'learning_rate': 6.924782048322683e-06, 'epoch': 0.61}
+
61%|██████ | 7309/11952 [41:49<7:56:35, 6.16s/it]
61%|██████ | 7310/11952 [41:55<7:53:22, 6.12s/it]
{'loss': 0.4927, 'learning_rate': 6.922203575630164e-06, 'epoch': 0.61}
+
61%|██████ | 7310/11952 [41:55<7:53:22, 6.12s/it]
61%|██████ | 7311/11952 [42:00<7:39:50, 5.94s/it]
{'loss': 0.4512, 'learning_rate': 6.9196253289582104e-06, 'epoch': 0.61}
+
61%|██████ | 7311/11952 [42:00<7:39:50, 5.94s/it]
61%|██████ | 7312/11952 [42:06<7:31:36, 5.84s/it]
{'loss': 0.4649, 'learning_rate': 6.917047308496159e-06, 'epoch': 0.61}
+
61%|██████ | 7312/11952 [42:06<7:31:36, 5.84s/it]
61%|██████ | 7313/11952 [42:12<7:33:41, 5.87s/it]
{'loss': 0.4551, 'learning_rate': 6.914469514433331e-06, 'epoch': 0.61}
+
61%|██████ | 7313/11952 [42:12<7:33:41, 5.87s/it]
61%|██████ | 7314/11952 [42:18<7:38:18, 5.93s/it]
{'loss': 0.4659, 'learning_rate': 6.9118919469590285e-06, 'epoch': 0.61}
+
61%|██████ | 7314/11952 [42:18<7:38:18, 5.93s/it]
61%|██████ | 7315/11952 [42:24<7:36:56, 5.91s/it]
{'loss': 0.4642, 'learning_rate': 6.9093146062625395e-06, 'epoch': 0.61}
+
61%|██████ | 7315/11952 [42:24<7:36:56, 5.91s/it]
61%|██████ | 7316/11952 [42:30<7:30:19, 5.83s/it]
{'loss': 0.4668, 'learning_rate': 6.906737492533129e-06, 'epoch': 0.61}
+
61%|██████ | 7316/11952 [42:30<7:30:19, 5.83s/it]
61%|██████ | 7317/11952 [42:36<7:35:10, 5.89s/it]
{'loss': 0.4703, 'learning_rate': 6.904160605960051e-06, 'epoch': 0.61}
+
61%|██████ | 7317/11952 [42:36<7:35:10, 5.89s/it]
61%|██████ | 7318/11952 [42:41<7:30:30, 5.83s/it]
{'loss': 0.4792, 'learning_rate': 6.901583946732542e-06, 'epoch': 0.61}
+
61%|██████ | 7318/11952 [42:41<7:30:30, 5.83s/it]
61%|██████ | 7319/11952 [42:47<7:29:43, 5.82s/it]
{'loss': 0.4782, 'learning_rate': 6.899007515039817e-06, 'epoch': 0.61}
+
61%|██████ | 7319/11952 [42:47<7:29:43, 5.82s/it]
61%|██████ | 7320/11952 [42:53<7:36:45, 5.92s/it]
{'loss': 0.4555, 'learning_rate': 6.896431311071086e-06, 'epoch': 0.61}
+
61%|██████ | 7320/11952 [42:53<7:36:45, 5.92s/it]
61%|██████▏ | 7321/11952 [42:59<7:30:58, 5.84s/it]
{'loss': 0.4866, 'learning_rate': 6.893855335015532e-06, 'epoch': 0.61}
+
61%|██████▏ | 7321/11952 [42:59<7:30:58, 5.84s/it]
61%|██████▏ | 7322/11952 [43:05<7:26:55, 5.79s/it]
{'loss': 0.4725, 'learning_rate': 6.891279587062321e-06, 'epoch': 0.61}
+
61%|██████▏ | 7322/11952 [43:05<7:26:55, 5.79s/it]
61%|██████▏ | 7323/11952 [43:11<7:35:23, 5.90s/it]
{'loss': 0.4588, 'learning_rate': 6.888704067400605e-06, 'epoch': 0.61}
+
61%|██████▏ | 7323/11952 [43:11<7:35:23, 5.90s/it]
61%|██████▏ | 7324/11952 [43:16<7:29:57, 5.83s/it]
{'loss': 0.4671, 'learning_rate': 6.886128776219525e-06, 'epoch': 0.61}
+
61%|██████▏ | 7324/11952 [43:16<7:29:57, 5.83s/it]
61%|██████▏ | 7325/11952 [43:22<7:28:12, 5.81s/it]
{'loss': 0.4611, 'learning_rate': 6.8835537137081955e-06, 'epoch': 0.61}
+
61%|██████▏ | 7325/11952 [43:22<7:28:12, 5.81s/it]
61%|██████▏ | 7326/11952 [43:28<7:26:40, 5.79s/it]
{'loss': 0.4666, 'learning_rate': 6.880978880055716e-06, 'epoch': 0.61}
+
61%|██████▏ | 7326/11952 [43:28<7:26:40, 5.79s/it]
61%|██████▏ | 7327/11952 [43:34<7:22:39, 5.74s/it]
{'loss': 0.473, 'learning_rate': 6.878404275451176e-06, 'epoch': 0.61}
+
61%|██████▏ | 7327/11952 [43:34<7:22:39, 5.74s/it]
61%|██████▏ | 7328/11952 [43:39<7:20:16, 5.71s/it]
{'loss': 0.4906, 'learning_rate': 6.875829900083642e-06, 'epoch': 0.61}
+
61%|██████▏ | 7328/11952 [43:39<7:20:16, 5.71s/it]
61%|██████▏ | 7329/11952 [43:45<7:25:23, 5.78s/it]
{'loss': 0.4585, 'learning_rate': 6.873255754142167e-06, 'epoch': 0.61}
+
61%|██████▏ | 7329/11952 [43:45<7:25:23, 5.78s/it]
61%|██████▏ | 7330/11952 [43:51<7:27:52, 5.81s/it]
{'loss': 0.4581, 'learning_rate': 6.870681837815784e-06, 'epoch': 0.61}
+
61%|██████▏ | 7330/11952 [43:51<7:27:52, 5.81s/it]
61%|██████▏ | 7331/11952 [43:56<7:21:01, 5.73s/it]
{'loss': 0.4791, 'learning_rate': 6.868108151293513e-06, 'epoch': 0.61}
+
61%|██████▏ | 7331/11952 [43:56<7:21:01, 5.73s/it]
61%|██████▏ | 7332/11952 [44:02<7:23:57, 5.77s/it]
{'loss': 0.4673, 'learning_rate': 6.865534694764348e-06, 'epoch': 0.61}
+
61%|██████▏ | 7332/11952 [44:02<7:23:57, 5.77s/it]
61%|██████▏ | 7333/11952 [44:08<7:25:27, 5.79s/it]
{'loss': 0.4584, 'learning_rate': 6.86296146841728e-06, 'epoch': 0.61}
+
61%|██████▏ | 7333/11952 [44:08<7:25:27, 5.79s/it]
61%|██████▏ | 7334/11952 [44:14<7:22:11, 5.75s/it]
{'loss': 0.4574, 'learning_rate': 6.860388472441274e-06, 'epoch': 0.61}
+
61%|██████▏ | 7334/11952 [44:14<7:22:11, 5.75s/it]
61%|██████▏ | 7335/11952 [44:20<7:24:38, 5.78s/it]
{'loss': 0.4765, 'learning_rate': 6.8578157070252815e-06, 'epoch': 0.61}
+
61%|██████▏ | 7335/11952 [44:20<7:24:38, 5.78s/it]
61%|██████▏ | 7336/11952 [44:25<7:22:42, 5.75s/it]
{'loss': 0.4709, 'learning_rate': 6.8552431723582335e-06, 'epoch': 0.61}
+
61%|██████▏ | 7336/11952 [44:25<7:22:42, 5.75s/it]
61%|██████▏ | 7337/11952 [44:31<7:23:08, 5.76s/it]
{'loss': 0.4589, 'learning_rate': 6.852670868629048e-06, 'epoch': 0.61}
+
61%|██████▏ | 7337/11952 [44:31<7:23:08, 5.76s/it]
61%|██████▏ | 7338/11952 [44:37<7:20:12, 5.72s/it]
{'loss': 0.4735, 'learning_rate': 6.85009879602662e-06, 'epoch': 0.61}
+
61%|██████▏ | 7338/11952 [44:37<7:20:12, 5.72s/it]
61%|██████▏ | 7339/11952 [44:42<7:18:16, 5.70s/it]
{'loss': 0.4506, 'learning_rate': 6.8475269547398335e-06, 'epoch': 0.61}
+
61%|██████▏ | 7339/11952 [44:42<7:18:16, 5.70s/it]
61%|██████▏ | 7340/11952 [44:48<7:18:18, 5.70s/it]
{'loss': 0.488, 'learning_rate': 6.844955344957559e-06, 'epoch': 0.61}
+
61%|██████▏ | 7340/11952 [44:48<7:18:18, 5.70s/it]
61%|██████▏ | 7341/11952 [44:54<7:17:10, 5.69s/it]
{'loss': 0.4864, 'learning_rate': 6.842383966868642e-06, 'epoch': 0.61}
+
61%|██████▏ | 7341/11952 [44:54<7:17:10, 5.69s/it]
61%|██████▏ | 7342/11952 [44:59<7:14:56, 5.66s/it]
{'loss': 0.4675, 'learning_rate': 6.839812820661912e-06, 'epoch': 0.61}
+
61%|██████▏ | 7342/11952 [44:59<7:14:56, 5.66s/it]
61%|██████▏ | 7343/11952 [45:05<7:22:41, 5.76s/it]
{'loss': 0.4823, 'learning_rate': 6.837241906526182e-06, 'epoch': 0.61}
+
61%|██████▏ | 7343/11952 [45:05<7:22:41, 5.76s/it]
61%|██████▏ | 7344/11952 [45:11<7:24:33, 5.79s/it]
{'loss': 0.4612, 'learning_rate': 6.834671224650254e-06, 'epoch': 0.61}
+
61%|██████▏ | 7344/11952 [45:11<7:24:33, 5.79s/it]
61%|██████▏ | 7345/11952 [45:17<7:26:32, 5.82s/it]
{'loss': 0.478, 'learning_rate': 6.832100775222906e-06, 'epoch': 0.61}
+
61%|██████▏ | 7345/11952 [45:17<7:26:32, 5.82s/it]
61%|██████▏ | 7346/11952 [45:23<7:21:46, 5.75s/it]
{'loss': 0.4456, 'learning_rate': 6.829530558432898e-06, 'epoch': 0.61}
+
61%|██████▏ | 7346/11952 [45:23<7:21:46, 5.75s/it]
61%|██████▏ | 7347/11952 [45:29<7:23:49, 5.78s/it]
{'loss': 0.4765, 'learning_rate': 6.8269605744689805e-06, 'epoch': 0.61}
+
61%|██████▏ | 7347/11952 [45:29<7:23:49, 5.78s/it]
61%|██████▏ | 7348/11952 [45:35<7:31:21, 5.88s/it]
{'loss': 0.481, 'learning_rate': 6.824390823519882e-06, 'epoch': 0.61}
+
61%|██████▏ | 7348/11952 [45:35<7:31:21, 5.88s/it]
61%|██████▏ | 7349/11952 [45:41<7:33:25, 5.91s/it]
{'loss': 0.4775, 'learning_rate': 6.82182130577431e-06, 'epoch': 0.61}
+
61%|██████▏ | 7349/11952 [45:41<7:33:25, 5.91s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...2 AutoResumeHook: Checking whether to suspend...
+
+5 AutoResumeHook: Checking whether to suspend...
+
61%|██████▏ | 7350/11952 [45:47<7:32:08, 5.89s/it]
{'loss': 0.4842, 'learning_rate': 6.819252021420966e-06, 'epoch': 0.61}
+
61%|██████▏ | 7350/11952 [45:47<7:32:08, 5.89s/it]
62%|██████▏ | 7351/11952 [45:52<7:27:15, 5.83s/it]
{'loss': 0.4671, 'learning_rate': 6.816682970648522e-06, 'epoch': 0.62}
+
62%|██████▏ | 7351/11952 [45:52<7:27:15, 5.83s/it]
62%|██████▏ | 7352/11952 [45:59<7:39:38, 6.00s/it]
{'loss': 0.4894, 'learning_rate': 6.814114153645641e-06, 'epoch': 0.62}
+
62%|██████▏ | 7352/11952 [45:59<7:39:38, 6.00s/it]
62%|██████▏ | 7353/11952 [46:04<7:32:42, 5.91s/it]
{'loss': 0.4694, 'learning_rate': 6.811545570600961e-06, 'epoch': 0.62}
+
62%|██████▏ | 7353/11952 [46:04<7:32:42, 5.91s/it]
62%|██████▏ | 7354/11952 [46:10<7:25:51, 5.82s/it]
{'loss': 0.4797, 'learning_rate': 6.808977221703115e-06, 'epoch': 0.62}
+
62%|██████▏ | 7354/11952 [46:10<7:25:51, 5.82s/it]
62%|██████▏ | 7355/11952 [46:16<7:25:46, 5.82s/it]
{'loss': 0.4816, 'learning_rate': 6.8064091071407115e-06, 'epoch': 0.62}
+
62%|██████▏ | 7355/11952 [46:16<7:25:46, 5.82s/it]
62%|██████▏ | 7356/11952 [46:22<7:26:19, 5.83s/it]
{'loss': 0.4575, 'learning_rate': 6.803841227102339e-06, 'epoch': 0.62}
+
62%|██████▏ | 7356/11952 [46:22<7:26:19, 5.83s/it]
62%|██████▏ | 7357/11952 [46:27<7:27:56, 5.85s/it]
{'loss': 0.4852, 'learning_rate': 6.801273581776575e-06, 'epoch': 0.62}
+
62%|██████▏ | 7357/11952 [46:27<7:27:56, 5.85s/it]
62%|██████▏ | 7358/11952 [46:34<7:33:02, 5.92s/it]
{'loss': 0.4799, 'learning_rate': 6.798706171351971e-06, 'epoch': 0.62}
+
62%|██████▏ | 7358/11952 [46:34<7:33:02, 5.92s/it]
62%|██████▏ | 7359/11952 [46:40<7:35:45, 5.95s/it]
{'loss': 0.4692, 'learning_rate': 6.796138996017073e-06, 'epoch': 0.62}
+
62%|██████▏ | 7359/11952 [46:40<7:35:45, 5.95s/it]
62%|██████▏ | 7360/11952 [46:46<7:35:26, 5.95s/it]
{'loss': 0.4631, 'learning_rate': 6.793572055960398e-06, 'epoch': 0.62}
+
62%|██████▏ | 7360/11952 [46:46<7:35:26, 5.95s/it]
62%|██████▏ | 7361/11952 [46:52<7:35:34, 5.95s/it]
{'loss': 0.47, 'learning_rate': 6.791005351370458e-06, 'epoch': 0.62}
+
62%|██████▏ | 7361/11952 [46:52<7:35:34, 5.95s/it]
62%|██████▏ | 7362/11952 [46:57<7:31:15, 5.90s/it]
{'loss': 0.4797, 'learning_rate': 6.788438882435737e-06, 'epoch': 0.62}
+
62%|██████▏ | 7362/11952 [46:57<7:31:15, 5.90s/it]
62%|██████▏ | 7363/11952 [47:03<7:32:17, 5.91s/it]
{'loss': 0.4582, 'learning_rate': 6.7858726493447084e-06, 'epoch': 0.62}
+
62%|██████▏ | 7363/11952 [47:03<7:32:17, 5.91s/it]
62%|██████▏ | 7364/11952 [47:09<7:33:57, 5.94s/it]
{'loss': 0.4842, 'learning_rate': 6.78330665228582e-06, 'epoch': 0.62}
+
62%|██████▏ | 7364/11952 [47:09<7:33:57, 5.94s/it]
62%|██████▏ | 7365/11952 [47:15<7:25:29, 5.83s/it]
{'loss': 0.4711, 'learning_rate': 6.780740891447515e-06, 'epoch': 0.62}
+
62%|██████▏ | 7365/11952 [47:15<7:25:29, 5.83s/it]
62%|██████▏ | 7366/11952 [47:21<7:28:14, 5.86s/it]
{'loss': 0.4705, 'learning_rate': 6.778175367018205e-06, 'epoch': 0.62}
+
62%|██████▏ | 7366/11952 [47:21<7:28:14, 5.86s/it]
62%|██████▏ | 7367/11952 [47:26<7:23:58, 5.81s/it]
{'loss': 0.4719, 'learning_rate': 6.775610079186299e-06, 'epoch': 0.62}
+
62%|██████▏ | 7367/11952 [47:26<7:23:58, 5.81s/it]
62%|██████▏ | 7368/11952 [47:32<7:28:51, 5.88s/it]
{'loss': 0.474, 'learning_rate': 6.773045028140177e-06, 'epoch': 0.62}
+
62%|██████▏ | 7368/11952 [47:32<7:28:51, 5.88s/it]
62%|██████▏ | 7369/11952 [47:38<7:30:22, 5.90s/it]
{'loss': 0.4711, 'learning_rate': 6.770480214068207e-06, 'epoch': 0.62}
+
62%|██████▏ | 7369/11952 [47:38<7:30:22, 5.90s/it]
62%|██████▏ | 7370/11952 [47:45<7:35:34, 5.97s/it]
{'loss': 0.4732, 'learning_rate': 6.767915637158735e-06, 'epoch': 0.62}
+
62%|██████▏ | 7370/11952 [47:45<7:35:34, 5.97s/it]
62%|██████▏ | 7371/11952 [47:51<7:38:55, 6.01s/it]
{'loss': 0.5037, 'learning_rate': 6.765351297600098e-06, 'epoch': 0.62}
+
62%|██████▏ | 7371/11952 [47:51<7:38:55, 6.01s/it]
62%|██████▏ | 7372/11952 [47:56<7:30:06, 5.90s/it]
{'loss': 0.4625, 'learning_rate': 6.762787195580609e-06, 'epoch': 0.62}
+
62%|██████▏ | 7372/11952 [47:56<7:30:06, 5.90s/it]
62%|██████▏ | 7373/11952 [48:02<7:24:27, 5.82s/it]
{'loss': 0.4838, 'learning_rate': 6.760223331288558e-06, 'epoch': 0.62}
+
62%|██████▏ | 7373/11952 [48:02<7:24:27, 5.82s/it]
62%|██████▏ | 7374/11952 [48:08<7:27:53, 5.87s/it]
{'loss': 0.4613, 'learning_rate': 6.757659704912234e-06, 'epoch': 0.62}
+
62%|██████▏ | 7374/11952 [48:08<7:27:53, 5.87s/it]
62%|██████▏ | 7375/11952 [48:14<7:24:21, 5.83s/it]
{'loss': 0.4719, 'learning_rate': 6.755096316639894e-06, 'epoch': 0.62}
+
62%|██████▏ | 7375/11952 [48:14<7:24:21, 5.83s/it]
62%|██████▏ | 7376/11952 [48:19<7:20:35, 5.78s/it]
{'loss': 0.4777, 'learning_rate': 6.752533166659786e-06, 'epoch': 0.62}
+
62%|██████▏ | 7376/11952 [48:19<7:20:35, 5.78s/it]
62%|██████▏ | 7377/11952 [48:25<7:23:37, 5.82s/it]
{'loss': 0.4718, 'learning_rate': 6.749970255160134e-06, 'epoch': 0.62}
+
62%|██████▏ | 7377/11952 [48:25<7:23:37, 5.82s/it]
62%|██████▏ | 7378/11952 [48:31<7:24:55, 5.84s/it]
{'loss': 0.4682, 'learning_rate': 6.747407582329151e-06, 'epoch': 0.62}
+
62%|██████▏ | 7378/11952 [48:31<7:24:55, 5.84s/it]
62%|██████▏ | 7379/11952 [48:37<7:17:03, 5.73s/it]
{'loss': 0.4711, 'learning_rate': 6.744845148355023e-06, 'epoch': 0.62}
+
62%|██████▏ | 7379/11952 [48:37<7:17:03, 5.73s/it]
62%|██████▏ | 7380/11952 [48:43<7:26:43, 5.86s/it]
{'loss': 0.4649, 'learning_rate': 6.742282953425928e-06, 'epoch': 0.62}
+
62%|██████▏ | 7380/11952 [48:43<7:26:43, 5.86s/it]
62%|██████▏ | 7381/11952 [48:48<7:20:35, 5.78s/it]
{'loss': 0.4666, 'learning_rate': 6.739720997730024e-06, 'epoch': 0.62}
+
62%|██████▏ | 7381/11952 [48:48<7:20:35, 5.78s/it]
62%|██████▏ | 7382/11952 [48:54<7:28:22, 5.89s/it]
{'loss': 0.4793, 'learning_rate': 6.73715928145545e-06, 'epoch': 0.62}
+
62%|██████▏ | 7382/11952 [48:54<7:28:22, 5.89s/it]
62%|██████▏ | 7383/11952 [49:00<7:27:07, 5.87s/it]
{'loss': 0.4825, 'learning_rate': 6.734597804790328e-06, 'epoch': 0.62}
+
62%|██████▏ | 7383/11952 [49:00<7:27:07, 5.87s/it]
62%|██████▏ | 7384/11952 [49:06<7:22:58, 5.82s/it]
{'loss': 0.4683, 'learning_rate': 6.732036567922761e-06, 'epoch': 0.62}
+
62%|██████▏ | 7384/11952 [49:06<7:22:58, 5.82s/it]
62%|██████▏ | 7385/11952 [49:12<7:19:47, 5.78s/it]
{'loss': 0.4744, 'learning_rate': 6.729475571040835e-06, 'epoch': 0.62}
+
62%|██████▏ | 7385/11952 [49:12<7:19:47, 5.78s/it]
62%|██████▏ | 7386/11952 [49:18<7:21:59, 5.81s/it]
{'loss': 0.4606, 'learning_rate': 6.726914814332621e-06, 'epoch': 0.62}
+
62%|██████▏ | 7386/11952 [49:18<7:21:59, 5.81s/it]
62%|██████▏ | 7387/11952 [49:23<7:20:41, 5.79s/it]
{'loss': 0.4713, 'learning_rate': 6.724354297986164e-06, 'epoch': 0.62}
+
62%|██████▏ | 7387/11952 [49:23<7:20:41, 5.79s/it]
62%|██████▏ | 7388/11952 [49:29<7:23:44, 5.83s/it]
{'loss': 0.5145, 'learning_rate': 6.7217940221895095e-06, 'epoch': 0.62}
+
62%|██████▏ | 7388/11952 [49:29<7:23:44, 5.83s/it]
62%|██████▏ | 7389/11952 [49:35<7:20:08, 5.79s/it]
{'loss': 0.4723, 'learning_rate': 6.7192339871306655e-06, 'epoch': 0.62}
+
62%|██████▏ | 7389/11952 [49:35<7:20:08, 5.79s/it]
62%|██████▏ | 7390/11952 [49:41<7:17:54, 5.76s/it]
{'loss': 0.4768, 'learning_rate': 6.7166741929976295e-06, 'epoch': 0.62}
+
62%|██████▏ | 7390/11952 [49:41<7:17:54, 5.76s/it]
62%|██████▏ | 7391/11952 [49:46<7:17:17, 5.75s/it]
{'loss': 0.4662, 'learning_rate': 6.7141146399783875e-06, 'epoch': 0.62}
+
62%|██████▏ | 7391/11952 [49:46<7:17:17, 5.75s/it]
62%|██████▏ | 7392/11952 [49:52<7:18:45, 5.77s/it]
{'loss': 0.4682, 'learning_rate': 6.711555328260899e-06, 'epoch': 0.62}
+
62%|██████▏ | 7392/11952 [49:52<7:18:45, 5.77s/it]
62%|██████▏ | 7393/11952 [49:58<7:23:41, 5.84s/it]
{'loss': 0.4747, 'learning_rate': 6.708996258033109e-06, 'epoch': 0.62}
+
62%|██████▏ | 7393/11952 [49:58<7:23:41, 5.84s/it]
62%|██████▏ | 7394/11952 [50:04<7:18:25, 5.77s/it]
{'loss': 0.4901, 'learning_rate': 6.706437429482942e-06, 'epoch': 0.62}
+
62%|██████▏ | 7394/11952 [50:04<7:18:25, 5.77s/it]
62%|██████▏ | 7395/11952 [50:09<7:15:25, 5.73s/it]
{'loss': 0.4792, 'learning_rate': 6.703878842798315e-06, 'epoch': 0.62}
+
62%|██████▏ | 7395/11952 [50:09<7:15:25, 5.73s/it]
62%|██████▏ | 7396/11952 [50:15<7:18:46, 5.78s/it]
{'loss': 0.4451, 'learning_rate': 6.701320498167115e-06, 'epoch': 0.62}
+
62%|██████▏ | 7396/11952 [50:15<7:18:46, 5.78s/it]
62%|██████▏ | 7397/11952 [50:21<7:23:36, 5.84s/it]
{'loss': 0.4769, 'learning_rate': 6.6987623957772165e-06, 'epoch': 0.62}
+
62%|██████▏ | 7397/11952 [50:21<7:23:36, 5.84s/it]
62%|██████▏ | 7398/11952 [50:27<7:20:07, 5.80s/it]
{'loss': 0.4691, 'learning_rate': 6.696204535816479e-06, 'epoch': 0.62}
+
62%|██████▏ | 7398/11952 [50:27<7:20:07, 5.80s/it]
62%|██████▏ | 7399/11952 [50:33<7:18:59, 5.79s/it]
{'loss': 0.4577, 'learning_rate': 6.693646918472739e-06, 'epoch': 0.62}
+
62%|██████▏ | 7399/11952 [50:33<7:18:59, 5.79s/it]07 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
62%|██████▏ | 7400/11952 [50:38<7:17:23, 5.77s/it]2 AutoResumeHook: Checking whether to suspend...3
+5 4AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+
{'loss': 0.4784, 'learning_rate': 6.691089543933815e-06, 'epoch': 0.62}
+
62%|██████▏ | 7400/11952 [50:38<7:17:23, 5.77s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
62%|██████▏ | 7401/11952 [51:08<16:16:03, 12.87s/it]
{'loss': 0.4884, 'learning_rate': 6.68853241238751e-06, 'epoch': 0.62}
+
62%|██████▏ | 7401/11952 [51:08<16:16:03, 12.87s/it]
62%|██████▏ | 7402/11952 [51:13<13:29:17, 10.67s/it]
{'loss': 0.4705, 'learning_rate': 6.685975524021615e-06, 'epoch': 0.62}
+
62%|██████▏ | 7402/11952 [51:13<13:29:17, 10.67s/it]
62%|██████▏ | 7403/11952 [51:19<11:39:52, 9.23s/it]
{'loss': 0.4748, 'learning_rate': 6.683418879023893e-06, 'epoch': 0.62}
+
62%|██████▏ | 7403/11952 [51:19<11:39:52, 9.23s/it]
62%|██████▏ | 7404/11952 [51:25<10:26:08, 8.26s/it]
{'loss': 0.49, 'learning_rate': 6.6808624775820954e-06, 'epoch': 0.62}
+
62%|██████▏ | 7404/11952 [51:25<10:26:08, 8.26s/it]
62%|██████▏ | 7405/11952 [51:31<9:25:50, 7.47s/it]
{'loss': 0.456, 'learning_rate': 6.678306319883948e-06, 'epoch': 0.62}
+
62%|██████▏ | 7405/11952 [51:31<9:25:50, 7.47s/it]
62%|██████▏ | 7406/11952 [51:37<8:51:03, 7.01s/it]
{'loss': 0.447, 'learning_rate': 6.675750406117172e-06, 'epoch': 0.62}
+
62%|██████▏ | 7406/11952 [51:37<8:51:03, 7.01s/it]
62%|██████▏ | 7407/11952 [51:43<8:20:36, 6.61s/it]
{'loss': 0.4794, 'learning_rate': 6.673194736469455e-06, 'epoch': 0.62}
+
62%|██████▏ | 7407/11952 [51:43<8:20:36, 6.61s/it]
62%|██████▏ | 7408/11952 [51:49<8:09:41, 6.47s/it]
{'loss': 0.4712, 'learning_rate': 6.670639311128484e-06, 'epoch': 0.62}
+
62%|██████▏ | 7408/11952 [51:49<8:09:41, 6.47s/it]
62%|██████▏ | 7409/11952 [51:54<7:53:21, 6.25s/it]
{'loss': 0.4512, 'learning_rate': 6.668084130281913e-06, 'epoch': 0.62}
+
62%|██████▏ | 7409/11952 [51:54<7:53:21, 6.25s/it]
62%|██████▏ | 7410/11952 [52:00<7:41:52, 6.10s/it]
{'loss': 0.4734, 'learning_rate': 6.665529194117386e-06, 'epoch': 0.62}
+
62%|██████▏ | 7410/11952 [52:00<7:41:52, 6.10s/it]
62%|██████▏ | 7411/11952 [52:06<7:33:48, 6.00s/it]
{'loss': 0.4735, 'learning_rate': 6.662974502822524e-06, 'epoch': 0.62}
+
62%|██████▏ | 7411/11952 [52:06<7:33:48, 6.00s/it]
62%|██████▏ | 7412/11952 [52:12<7:32:18, 5.98s/it]
{'loss': 0.4767, 'learning_rate': 6.660420056584935e-06, 'epoch': 0.62}
+
62%|██████▏ | 7412/11952 [52:12<7:32:18, 5.98s/it]
62%|██████▏ | 7413/11952 [52:18<7:29:42, 5.94s/it]
{'loss': 0.4643, 'learning_rate': 6.65786585559221e-06, 'epoch': 0.62}
+
62%|██████▏ | 7413/11952 [52:18<7:29:42, 5.94s/it]
62%|██████▏ | 7414/11952 [52:24<7:26:30, 5.90s/it]
{'loss': 0.4899, 'learning_rate': 6.655311900031909e-06, 'epoch': 0.62}
+
62%|██████▏ | 7414/11952 [52:24<7:26:30, 5.90s/it]
62%|██████▏ | 7415/11952 [52:29<7:22:12, 5.85s/it]
{'loss': 0.4542, 'learning_rate': 6.652758190091595e-06, 'epoch': 0.62}
+
62%|██████▏ | 7415/11952 [52:29<7:22:12, 5.85s/it]
62%|██████▏ | 7416/11952 [52:35<7:22:04, 5.85s/it]
{'loss': 0.4742, 'learning_rate': 6.650204725958795e-06, 'epoch': 0.62}
+
62%|██████▏ | 7416/11952 [52:35<7:22:04, 5.85s/it]
62%|██████▏ | 7417/11952 [52:41<7:24:47, 5.88s/it]
{'loss': 0.4802, 'learning_rate': 6.647651507821029e-06, 'epoch': 0.62}
+
62%|██████▏ | 7417/11952 [52:41<7:24:47, 5.88s/it]
62%|██████▏ | 7418/11952 [52:47<7:22:02, 5.85s/it]
{'loss': 0.4728, 'learning_rate': 6.645098535865793e-06, 'epoch': 0.62}
+
62%|██████▏ | 7418/11952 [52:47<7:22:02, 5.85s/it]
62%|██████▏ | 7419/11952 [52:53<7:20:07, 5.83s/it]
{'loss': 0.4773, 'learning_rate': 6.642545810280567e-06, 'epoch': 0.62}
+
62%|██████▏ | 7419/11952 [52:53<7:20:07, 5.83s/it]
62%|██████▏ | 7420/11952 [52:58<7:14:54, 5.76s/it]
{'loss': 0.4743, 'learning_rate': 6.63999333125281e-06, 'epoch': 0.62}
+
62%|██████▏ | 7420/11952 [52:58<7:14:54, 5.76s/it]
62%|██████▏ | 7421/11952 [53:04<7:09:26, 5.69s/it]
{'loss': 0.4709, 'learning_rate': 6.637441098969967e-06, 'epoch': 0.62}
+
62%|██████▏ | 7421/11952 [53:04<7:09:26, 5.69s/it]
62%|██████▏ | 7422/11952 [53:10<7:18:09, 5.80s/it]
{'loss': 0.4619, 'learning_rate': 6.634889113619463e-06, 'epoch': 0.62}
+
62%|██████▏ | 7422/11952 [53:10<7:18:09, 5.80s/it]
62%|██████▏ | 7423/11952 [53:16<7:26:08, 5.91s/it]
{'loss': 0.4638, 'learning_rate': 6.632337375388709e-06, 'epoch': 0.62}
+
62%|██████▏ | 7423/11952 [53:16<7:26:08, 5.91s/it]
62%|██████▏ | 7424/11952 [53:22<7:26:21, 5.91s/it]
{'loss': 0.4739, 'learning_rate': 6.629785884465091e-06, 'epoch': 0.62}
+
62%|██████▏ | 7424/11952 [53:22<7:26:21, 5.91s/it]
62%|██████▏ | 7425/11952 [53:28<7:20:00, 5.83s/it]
{'loss': 0.4845, 'learning_rate': 6.62723464103598e-06, 'epoch': 0.62}
+
62%|██████▏ | 7425/11952 [53:28<7:20:00, 5.83s/it]
62%|██████▏ | 7426/11952 [53:33<7:22:12, 5.86s/it]
{'loss': 0.46, 'learning_rate': 6.624683645288726e-06, 'epoch': 0.62}
+
62%|██████▏ | 7426/11952 [53:33<7:22:12, 5.86s/it]
62%|██████▏ | 7427/11952 [53:40<7:25:46, 5.91s/it]
{'loss': 0.4822, 'learning_rate': 6.622132897410668e-06, 'epoch': 0.62}
+
62%|██████▏ | 7427/11952 [53:40<7:25:46, 5.91s/it]
62%|██████▏ | 7428/11952 [53:45<7:24:06, 5.89s/it]
{'loss': 0.4872, 'learning_rate': 6.619582397589117e-06, 'epoch': 0.62}
+
62%|██████▏ | 7428/11952 [53:45<7:24:06, 5.89s/it]
62%|██████▏ | 7429/11952 [53:51<7:18:31, 5.82s/it]
{'loss': 0.4577, 'learning_rate': 6.617032146011377e-06, 'epoch': 0.62}
+
62%|██████▏ | 7429/11952 [53:51<7:18:31, 5.82s/it]
62%|██████▏ | 7430/11952 [53:57<7:18:44, 5.82s/it]
{'loss': 0.4661, 'learning_rate': 6.614482142864728e-06, 'epoch': 0.62}
+
62%|██████▏ | 7430/11952 [53:57<7:18:44, 5.82s/it]
62%|██████▏ | 7431/11952 [54:03<7:20:17, 5.84s/it]
{'loss': 0.4734, 'learning_rate': 6.611932388336425e-06, 'epoch': 0.62}
+
62%|██████▏ | 7431/11952 [54:03<7:20:17, 5.84s/it]
62%|██████▏ | 7432/11952 [54:09<7:30:13, 5.98s/it]
{'loss': 0.5089, 'learning_rate': 6.609382882613717e-06, 'epoch': 0.62}
+
62%|██████▏ | 7432/11952 [54:09<7:30:13, 5.98s/it]
62%|██████▏ | 7433/11952 [54:15<7:27:19, 5.94s/it]
{'loss': 0.4623, 'learning_rate': 6.606833625883829e-06, 'epoch': 0.62}
+
62%|██████▏ | 7433/11952 [54:15<7:27:19, 5.94s/it]
62%|██████▏ | 7434/11952 [54:21<7:23:49, 5.89s/it]
{'loss': 0.4694, 'learning_rate': 6.604284618333967e-06, 'epoch': 0.62}
+
62%|██████▏ | 7434/11952 [54:21<7:23:49, 5.89s/it]
62%|██████▏ | 7435/11952 [54:26<7:20:17, 5.85s/it]
{'loss': 0.4794, 'learning_rate': 6.601735860151313e-06, 'epoch': 0.62}
+
62%|██████▏ | 7435/11952 [54:26<7:20:17, 5.85s/it]
62%|██████▏ | 7436/11952 [54:32<7:19:15, 5.84s/it]
{'loss': 0.4663, 'learning_rate': 6.599187351523046e-06, 'epoch': 0.62}
+
62%|██████▏ | 7436/11952 [54:32<7:19:15, 5.84s/it]
62%|██████▏ | 7437/11952 [54:38<7:16:35, 5.80s/it]
{'loss': 0.4743, 'learning_rate': 6.596639092636315e-06, 'epoch': 0.62}
+
62%|██████▏ | 7437/11952 [54:38<7:16:35, 5.80s/it]
62%|██████▏ | 7438/11952 [54:44<7:18:35, 5.83s/it]
{'loss': 0.4755, 'learning_rate': 6.594091083678256e-06, 'epoch': 0.62}
+
62%|██████▏ | 7438/11952 [54:44<7:18:35, 5.83s/it]
62%|██████▏ | 7439/11952 [54:50<7:19:23, 5.84s/it]
{'loss': 0.4826, 'learning_rate': 6.5915433248359795e-06, 'epoch': 0.62}
+
62%|██████▏ | 7439/11952 [54:50<7:19:23, 5.84s/it]
62%|██████▏ | 7440/11952 [54:56<7:27:59, 5.96s/it]
{'loss': 0.4959, 'learning_rate': 6.588995816296585e-06, 'epoch': 0.62}
+
62%|██████▏ | 7440/11952 [54:56<7:27:59, 5.96s/it]
62%|██████▏ | 7441/11952 [55:02<7:27:26, 5.95s/it]
{'loss': 0.4803, 'learning_rate': 6.586448558247147e-06, 'epoch': 0.62}
+
62%|██████▏ | 7441/11952 [55:02<7:27:26, 5.95s/it]
62%|██████▏ | 7442/11952 [55:08<7:25:01, 5.92s/it]
{'loss': 0.4815, 'learning_rate': 6.58390155087473e-06, 'epoch': 0.62}
+
62%|██████▏ | 7442/11952 [55:08<7:25:01, 5.92s/it]
62%|██████▏ | 7443/11952 [55:14<7:24:13, 5.91s/it]
{'loss': 0.4684, 'learning_rate': 6.581354794366377e-06, 'epoch': 0.62}
+
62%|██████▏ | 7443/11952 [55:14<7:24:13, 5.91s/it]
62%|██████▏ | 7444/11952 [55:19<7:19:38, 5.85s/it]
{'loss': 0.4681, 'learning_rate': 6.578808288909109e-06, 'epoch': 0.62}
+
62%|██████▏ | 7444/11952 [55:19<7:19:38, 5.85s/it]
62%|██████▏ | 7445/11952 [55:25<7:15:33, 5.80s/it]
{'loss': 0.4779, 'learning_rate': 6.576262034689929e-06, 'epoch': 0.62}
+
62%|██████▏ | 7445/11952 [55:25<7:15:33, 5.80s/it]
62%|██████▏ | 7446/11952 [55:31<7:13:08, 5.77s/it]
{'loss': 0.4647, 'learning_rate': 6.573716031895825e-06, 'epoch': 0.62}
+
62%|██████▏ | 7446/11952 [55:31<7:13:08, 5.77s/it]
62%|██████▏ | 7447/11952 [55:36<7:14:20, 5.78s/it]
{'loss': 0.4679, 'learning_rate': 6.571170280713765e-06, 'epoch': 0.62}
+
62%|██████▏ | 7447/11952 [55:36<7:14:20, 5.78s/it]
62%|██████▏ | 7448/11952 [55:42<7:13:05, 5.77s/it]
{'loss': 0.472, 'learning_rate': 6.568624781330694e-06, 'epoch': 0.62}
+
62%|██████▏ | 7448/11952 [55:42<7:13:05, 5.77s/it]
62%|██████▏ | 7449/11952 [55:48<7:16:11, 5.81s/it]
{'loss': 0.4853, 'learning_rate': 6.566079533933551e-06, 'epoch': 0.62}
+
62%|██████▏ | 7449/11952 [55:48<7:16:11, 5.81s/it]7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 6AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
62%|██████▏ | 7450/11952 [55:54<7:20:01, 5.86s/it]
{'loss': 0.4819, 'learning_rate': 6.563534538709244e-06, 'epoch': 0.62}
+
62%|██████▏ | 7450/11952 [55:54<7:20:01, 5.86s/it]
62%|██████▏ | 7451/11952 [56:00<7:20:01, 5.87s/it]
{'loss': 0.4661, 'learning_rate': 6.560989795844668e-06, 'epoch': 0.62}
+
62%|██████▏ | 7451/11952 [56:00<7:20:01, 5.87s/it]
62%|██████▏ | 7452/11952 [56:06<7:22:13, 5.90s/it]
{'loss': 0.4871, 'learning_rate': 6.558445305526695e-06, 'epoch': 0.62}
+
62%|██████▏ | 7452/11952 [56:06<7:22:13, 5.90s/it]
62%|██████▏ | 7453/11952 [56:12<7:29:49, 6.00s/it]
{'loss': 0.4697, 'learning_rate': 6.555901067942188e-06, 'epoch': 0.62}
+
62%|██████▏ | 7453/11952 [56:12<7:29:49, 6.00s/it]
62%|██████▏ | 7454/11952 [56:18<7:23:43, 5.92s/it]
{'loss': 0.4684, 'learning_rate': 6.553357083277979e-06, 'epoch': 0.62}
+
62%|██████▏ | 7454/11952 [56:18<7:23:43, 5.92s/it]
62%|██████▏ | 7455/11952 [56:24<7:21:16, 5.89s/it]
{'loss': 0.448, 'learning_rate': 6.550813351720888e-06, 'epoch': 0.62}
+
62%|██████▏ | 7455/11952 [56:24<7:21:16, 5.89s/it]
62%|██████▏ | 7456/11952 [56:29<7:15:00, 5.81s/it]
{'loss': 0.4641, 'learning_rate': 6.54826987345772e-06, 'epoch': 0.62}
+
62%|██████▏ | 7456/11952 [56:29<7:15:00, 5.81s/it]
62%|██████▏ | 7457/11952 [56:35<7:14:09, 5.80s/it]
{'loss': 0.4725, 'learning_rate': 6.545726648675255e-06, 'epoch': 0.62}
+
62%|██████▏ | 7457/11952 [56:35<7:14:09, 5.80s/it]
62%|██████▏ | 7458/11952 [56:41<7:20:25, 5.88s/it]
{'loss': 0.4737, 'learning_rate': 6.54318367756026e-06, 'epoch': 0.62}
+
62%|██████▏ | 7458/11952 [56:41<7:20:25, 5.88s/it]
62%|██████▏ | 7459/11952 [56:47<7:14:19, 5.80s/it]
{'loss': 0.4911, 'learning_rate': 6.540640960299477e-06, 'epoch': 0.62}
+
62%|██████▏ | 7459/11952 [56:47<7:14:19, 5.80s/it]
62%|██████▏ | 7460/11952 [56:52<7:11:28, 5.76s/it]
{'loss': 0.4779, 'learning_rate': 6.538098497079634e-06, 'epoch': 0.62}
+
62%|██████▏ | 7460/11952 [56:52<7:11:28, 5.76s/it]
62%|██████▏ | 7461/11952 [56:58<7:14:16, 5.80s/it]
{'loss': 0.4593, 'learning_rate': 6.5355562880874345e-06, 'epoch': 0.62}
+
62%|██████▏ | 7461/11952 [56:58<7:14:16, 5.80s/it]
62%|██████▏ | 7462/11952 [57:04<7:12:24, 5.78s/it]
{'loss': 0.4589, 'learning_rate': 6.533014333509573e-06, 'epoch': 0.62}
+
62%|██████▏ | 7462/11952 [57:04<7:12:24, 5.78s/it]
62%|██████▏ | 7463/11952 [57:10<7:06:21, 5.70s/it]
{'loss': 0.485, 'learning_rate': 6.530472633532718e-06, 'epoch': 0.62}
+
62%|██████▏ | 7463/11952 [57:10<7:06:21, 5.70s/it]
62%|██████▏ | 7464/11952 [57:16<7:16:38, 5.84s/it]
{'loss': 0.5078, 'learning_rate': 6.527931188343525e-06, 'epoch': 0.62}
+
62%|██████▏ | 7464/11952 [57:16<7:16:38, 5.84s/it]
62%|██████▏ | 7465/11952 [57:22<7:18:20, 5.86s/it]
{'loss': 0.4716, 'learning_rate': 6.525389998128624e-06, 'epoch': 0.62}
+
62%|██████▏ | 7465/11952 [57:22<7:18:20, 5.86s/it]
62%|██████▏ | 7466/11952 [57:27<7:12:06, 5.78s/it]
{'loss': 0.4613, 'learning_rate': 6.522849063074628e-06, 'epoch': 0.62}
+
62%|██████▏ | 7466/11952 [57:27<7:12:06, 5.78s/it]
62%|██████▏ | 7467/11952 [57:33<7:08:49, 5.74s/it]
{'loss': 0.4736, 'learning_rate': 6.520308383368134e-06, 'epoch': 0.62}
+
62%|██████▏ | 7467/11952 [57:33<7:08:49, 5.74s/it]
62%|██████▏ | 7468/11952 [57:39<7:09:56, 5.75s/it]
{'loss': 0.4775, 'learning_rate': 6.51776795919572e-06, 'epoch': 0.62}
+
62%|██████▏ | 7468/11952 [57:39<7:09:56, 5.75s/it]
62%|██████▏ | 7469/11952 [57:44<7:09:39, 5.75s/it]
{'loss': 0.4675, 'learning_rate': 6.515227790743939e-06, 'epoch': 0.62}
+
62%|██████▏ | 7469/11952 [57:44<7:09:39, 5.75s/it]
62%|██████▎ | 7470/11952 [57:50<7:10:11, 5.76s/it]
{'loss': 0.5053, 'learning_rate': 6.51268787819934e-06, 'epoch': 0.62}
+
62%|██████▎ | 7470/11952 [57:50<7:10:11, 5.76s/it]
63%|██████▎ | 7471/11952 [57:56<7:11:56, 5.78s/it]
{'loss': 0.4562, 'learning_rate': 6.510148221748438e-06, 'epoch': 0.63}
+
63%|██████▎ | 7471/11952 [57:56<7:11:56, 5.78s/it]
63%|██████▎ | 7472/11952 [58:02<7:14:53, 5.82s/it]
{'loss': 0.4942, 'learning_rate': 6.507608821577733e-06, 'epoch': 0.63}
+
63%|██████▎ | 7472/11952 [58:02<7:14:53, 5.82s/it]
63%|██████▎ | 7473/11952 [58:08<7:13:30, 5.81s/it]
{'loss': 0.4833, 'learning_rate': 6.505069677873712e-06, 'epoch': 0.63}
+
63%|██████▎ | 7473/11952 [58:08<7:13:30, 5.81s/it]
63%|██████▎ | 7474/11952 [58:14<7:14:48, 5.83s/it]
{'loss': 0.4595, 'learning_rate': 6.502530790822838e-06, 'epoch': 0.63}
+
63%|██████▎ | 7474/11952 [58:14<7:14:48, 5.83s/it]
63%|██████▎ | 7475/11952 [58:19<7:11:20, 5.78s/it]
{'loss': 0.4807, 'learning_rate': 6.499992160611556e-06, 'epoch': 0.63}
+
63%|██████▎ | 7475/11952 [58:19<7:11:20, 5.78s/it]
63%|██████▎ | 7476/11952 [58:25<7:16:33, 5.85s/it]
{'loss': 0.4696, 'learning_rate': 6.4974537874262865e-06, 'epoch': 0.63}
+
63%|██████▎ | 7476/11952 [58:25<7:16:33, 5.85s/it]
63%|██████▎ | 7477/11952 [58:31<7:14:35, 5.83s/it]
{'loss': 0.4573, 'learning_rate': 6.494915671453448e-06, 'epoch': 0.63}
+
63%|██████▎ | 7477/11952 [58:31<7:14:35, 5.83s/it]
63%|██████▎ | 7478/11952 [58:37<7:15:08, 5.84s/it]
{'loss': 0.4639, 'learning_rate': 6.492377812879422e-06, 'epoch': 0.63}
+
63%|██████▎ | 7478/11952 [58:37<7:15:08, 5.84s/it]
63%|██████▎ | 7479/11952 [58:43<7:09:36, 5.76s/it]
{'loss': 0.4548, 'learning_rate': 6.489840211890581e-06, 'epoch': 0.63}
+
63%|██████▎ | 7479/11952 [58:43<7:09:36, 5.76s/it]
63%|██████▎ | 7480/11952 [58:48<7:07:42, 5.74s/it]
{'loss': 0.4844, 'learning_rate': 6.4873028686732755e-06, 'epoch': 0.63}
+
63%|██████▎ | 7480/11952 [58:48<7:07:42, 5.74s/it]
63%|██████▎ | 7481/11952 [58:54<7:07:15, 5.73s/it]
{'loss': 0.4707, 'learning_rate': 6.484765783413838e-06, 'epoch': 0.63}
+
63%|██████▎ | 7481/11952 [58:54<7:07:15, 5.73s/it]
63%|██████▎ | 7482/11952 [59:00<7:07:13, 5.73s/it]
{'loss': 0.4791, 'learning_rate': 6.482228956298575e-06, 'epoch': 0.63}
+
63%|██████▎ | 7482/11952 [59:00<7:07:13, 5.73s/it]
63%|██████▎ | 7483/11952 [59:06<7:10:02, 5.77s/it]
{'loss': 0.4717, 'learning_rate': 6.479692387513788e-06, 'epoch': 0.63}
+
63%|██████▎ | 7483/11952 [59:06<7:10:02, 5.77s/it]
63%|██████▎ | 7484/11952 [59:11<7:07:45, 5.74s/it]
{'loss': 0.4769, 'learning_rate': 6.477156077245752e-06, 'epoch': 0.63}
+
63%|██████▎ | 7484/11952 [59:11<7:07:45, 5.74s/it]
63%|██████▎ | 7485/11952 [59:17<7:05:32, 5.72s/it]
{'loss': 0.487, 'learning_rate': 6.474620025680722e-06, 'epoch': 0.63}
+
63%|██████▎ | 7485/11952 [59:17<7:05:32, 5.72s/it]
63%|██████▎ | 7486/11952 [59:23<7:08:20, 5.75s/it]
{'loss': 0.4828, 'learning_rate': 6.472084233004934e-06, 'epoch': 0.63}
+
63%|██████▎ | 7486/11952 [59:23<7:08:20, 5.75s/it]
63%|██████▎ | 7487/11952 [59:29<7:09:18, 5.77s/it]
{'loss': 0.4782, 'learning_rate': 6.469548699404603e-06, 'epoch': 0.63}
+
63%|██████▎ | 7487/11952 [59:29<7:09:18, 5.77s/it]
63%|██████▎ | 7488/11952 [59:35<7:15:26, 5.85s/it]
{'loss': 0.4786, 'learning_rate': 6.467013425065935e-06, 'epoch': 0.63}
+
63%|██████▎ | 7488/11952 [59:35<7:15:26, 5.85s/it]
63%|██████▎ | 7489/11952 [59:41<7:17:00, 5.87s/it]
{'loss': 0.4812, 'learning_rate': 6.464478410175101e-06, 'epoch': 0.63}
+
63%|██████▎ | 7489/11952 [59:41<7:17:00, 5.87s/it]
63%|██████▎ | 7490/11952 [59:47<7:21:03, 5.93s/it]
{'loss': 0.4729, 'learning_rate': 6.461943654918271e-06, 'epoch': 0.63}
+
63%|██████▎ | 7490/11952 [59:47<7:21:03, 5.93s/it]
63%|██████▎ | 7491/11952 [59:52<7:19:20, 5.91s/it]
{'loss': 0.4727, 'learning_rate': 6.459409159481584e-06, 'epoch': 0.63}
+
63%|██████▎ | 7491/11952 [59:52<7:19:20, 5.91s/it]
63%|██████▎ | 7492/11952 [59:59<7:25:43, 6.00s/it]
{'loss': 0.4939, 'learning_rate': 6.456874924051162e-06, 'epoch': 0.63}
+
63%|██████▎ | 7492/11952 [59:59<7:25:43, 6.00s/it]
63%|██████▎ | 7493/11952 [1:00:04<7:19:38, 5.92s/it]
{'loss': 0.4628, 'learning_rate': 6.454340948813105e-06, 'epoch': 0.63}
+
63%|██████▎ | 7493/11952 [1:00:04<7:19:38, 5.92s/it]
63%|██████▎ | 7494/11952 [1:00:10<7:17:01, 5.88s/it]
{'loss': 0.4971, 'learning_rate': 6.451807233953504e-06, 'epoch': 0.63}
+
63%|██████▎ | 7494/11952 [1:00:10<7:17:01, 5.88s/it]
63%|██████▎ | 7495/11952 [1:00:16<7:13:34, 5.84s/it]
{'loss': 0.4719, 'learning_rate': 6.4492737796584225e-06, 'epoch': 0.63}
+
63%|██████▎ | 7495/11952 [1:00:16<7:13:34, 5.84s/it]
63%|██████▎ | 7496/11952 [1:00:21<7:04:15, 5.71s/it]
{'loss': 0.4494, 'learning_rate': 6.446740586113902e-06, 'epoch': 0.63}
+
63%|██████▎ | 7496/11952 [1:00:21<7:04:15, 5.71s/it]
63%|██████▎ | 7497/11952 [1:00:27<7:07:15, 5.75s/it]
{'loss': 0.4809, 'learning_rate': 6.4442076535059774e-06, 'epoch': 0.63}
+
63%|██████▎ | 7497/11952 [1:00:27<7:07:15, 5.75s/it]
63%|██████▎ | 7498/11952 [1:00:33<7:13:41, 5.84s/it]
{'loss': 0.4808, 'learning_rate': 6.441674982020654e-06, 'epoch': 0.63}
+
63%|██████▎ | 7498/11952 [1:00:33<7:13:41, 5.84s/it]
63%|██████▎ | 7499/11952 [1:00:39<7:13:57, 5.85s/it]
{'loss': 0.4673, 'learning_rate': 6.439142571843915e-06, 'epoch': 0.63}
+
63%|██████▎ | 7499/11952 [1:00:39<7:13:57, 5.85s/it]1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
63%|██████▎ | 7500/11952 [1:00:45<7:13:34, 5.84s/it]
{'loss': 0.4685, 'learning_rate': 6.43661042316174e-06, 'epoch': 0.63}
+
63%|██████▎ | 7500/11952 [1:00:45<7:13:34, 5.84s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
63%|██████▎ | 7501/11952 [1:01:16<16:30:24, 13.35s/it]
{'loss': 0.4587, 'learning_rate': 6.434078536160072e-06, 'epoch': 0.63}
+
63%|██████▎ | 7501/11952 [1:01:16<16:30:24, 13.35s/it]
63%|██████▎ | 7502/11952 [1:01:21<13:39:04, 11.04s/it]
{'loss': 0.4609, 'learning_rate': 6.431546911024844e-06, 'epoch': 0.63}
+
63%|██████▎ | 7502/11952 [1:01:21<13:39:04, 11.04s/it]
63%|██████▎ | 7503/11952 [1:01:27<11:39:46, 9.44s/it]
{'loss': 0.4694, 'learning_rate': 6.429015547941968e-06, 'epoch': 0.63}
+
63%|██████▎ | 7503/11952 [1:01:27<11:39:46, 9.44s/it]
63%|██████▎ | 7504/11952 [1:01:33<10:17:28, 8.33s/it]
{'loss': 0.4861, 'learning_rate': 6.426484447097336e-06, 'epoch': 0.63}
+
63%|██████▎ | 7504/11952 [1:01:33<10:17:28, 8.33s/it]
63%|██████▎ | 7505/11952 [1:01:39<9:19:32, 7.55s/it]
{'loss': 0.4696, 'learning_rate': 6.423953608676827e-06, 'epoch': 0.63}
+
63%|██████▎ | 7505/11952 [1:01:39<9:19:32, 7.55s/it]
63%|██████▎ | 7506/11952 [1:01:44<8:42:21, 7.05s/it]
{'loss': 0.483, 'learning_rate': 6.42142303286629e-06, 'epoch': 0.63}
+
63%|██████▎ | 7506/11952 [1:01:44<8:42:21, 7.05s/it]
63%|██████▎ | 7507/11952 [1:01:50<8:09:46, 6.61s/it]
{'loss': 0.4773, 'learning_rate': 6.418892719851561e-06, 'epoch': 0.63}
+
63%|██████▎ | 7507/11952 [1:01:50<8:09:46, 6.61s/it]
63%|██████▎ | 7508/11952 [1:01:56<7:54:11, 6.40s/it]
{'loss': 0.4661, 'learning_rate': 6.416362669818454e-06, 'epoch': 0.63}
+
63%|██████▎ | 7508/11952 [1:01:56<7:54:11, 6.40s/it]
63%|██████▎ | 7509/11952 [1:02:02<7:42:46, 6.25s/it]
{'loss': 0.4772, 'learning_rate': 6.413832882952769e-06, 'epoch': 0.63}
+
63%|██████▎ | 7509/11952 [1:02:02<7:42:46, 6.25s/it]
63%|██████▎ | 7510/11952 [1:02:08<7:41:52, 6.24s/it]
{'loss': 0.4728, 'learning_rate': 6.411303359440277e-06, 'epoch': 0.63}
+
63%|██████▎ | 7510/11952 [1:02:08<7:41:52, 6.24s/it]
63%|██████▎ | 7511/11952 [1:02:14<7:28:08, 6.05s/it]
{'loss': 0.4697, 'learning_rate': 6.408774099466744e-06, 'epoch': 0.63}
+
63%|██████▎ | 7511/11952 [1:02:14<7:28:08, 6.05s/it]
63%|██████▎ | 7512/11952 [1:02:19<7:22:01, 5.97s/it]
{'loss': 0.4669, 'learning_rate': 6.406245103217903e-06, 'epoch': 0.63}
+
63%|██████▎ | 7512/11952 [1:02:19<7:22:01, 5.97s/it]
63%|██████▎ | 7513/11952 [1:02:25<7:20:36, 5.96s/it]
{'loss': 0.4848, 'learning_rate': 6.403716370879476e-06, 'epoch': 0.63}
+
63%|██████▎ | 7513/11952 [1:02:25<7:20:36, 5.96s/it]
63%|██████▎ | 7514/11952 [1:02:31<7:17:00, 5.91s/it]
{'loss': 0.4847, 'learning_rate': 6.401187902637157e-06, 'epoch': 0.63}
+
63%|██████▎ | 7514/11952 [1:02:31<7:17:00, 5.91s/it]
63%|██████▎ | 7515/11952 [1:02:37<7:17:15, 5.91s/it]
{'loss': 0.4871, 'learning_rate': 6.398659698676632e-06, 'epoch': 0.63}
+
63%|██████▎ | 7515/11952 [1:02:37<7:17:15, 5.91s/it]
63%|██████▎ | 7516/11952 [1:02:43<7:17:02, 5.91s/it]
{'loss': 0.4799, 'learning_rate': 6.396131759183557e-06, 'epoch': 0.63}
+
63%|██████▎ | 7516/11952 [1:02:43<7:17:02, 5.91s/it]
63%|██████▎ | 7517/11952 [1:02:49<7:11:34, 5.84s/it]
{'loss': 0.4634, 'learning_rate': 6.393604084343579e-06, 'epoch': 0.63}
+
63%|██████▎ | 7517/11952 [1:02:49<7:11:34, 5.84s/it]
63%|██████▎ | 7518/11952 [1:02:54<7:07:57, 5.79s/it]
{'loss': 0.4661, 'learning_rate': 6.391076674342316e-06, 'epoch': 0.63}
+
63%|██████▎ | 7518/11952 [1:02:54<7:07:57, 5.79s/it]
63%|██████▎ | 7519/11952 [1:03:00<7:08:35, 5.80s/it]
{'loss': 0.4611, 'learning_rate': 6.388549529365371e-06, 'epoch': 0.63}
+
63%|██████▎ | 7519/11952 [1:03:00<7:08:35, 5.80s/it]
63%|██████▎ | 7520/11952 [1:03:06<7:10:54, 5.83s/it]
{'loss': 0.4653, 'learning_rate': 6.3860226495983295e-06, 'epoch': 0.63}
+
63%|██████▎ | 7520/11952 [1:03:06<7:10:54, 5.83s/it]
63%|██████▎ | 7521/11952 [1:03:12<7:13:18, 5.87s/it]
{'loss': 0.4802, 'learning_rate': 6.383496035226752e-06, 'epoch': 0.63}
+
63%|██████▎ | 7521/11952 [1:03:12<7:13:18, 5.87s/it]
63%|██████▎ | 7522/11952 [1:03:18<7:06:44, 5.78s/it]
{'loss': 0.4697, 'learning_rate': 6.380969686436183e-06, 'epoch': 0.63}
+
63%|██████▎ | 7522/11952 [1:03:18<7:06:44, 5.78s/it]
63%|██████▎ | 7523/11952 [1:03:23<7:03:44, 5.74s/it]
{'loss': 0.47, 'learning_rate': 6.378443603412145e-06, 'epoch': 0.63}
+
63%|██████▎ | 7523/11952 [1:03:23<7:03:44, 5.74s/it]
63%|██████▎ | 7524/11952 [1:03:29<7:08:38, 5.81s/it]
{'loss': 0.4656, 'learning_rate': 6.375917786340149e-06, 'epoch': 0.63}
+
63%|██████▎ | 7524/11952 [1:03:29<7:08:38, 5.81s/it]
63%|██████▎ | 7525/11952 [1:03:35<7:03:21, 5.74s/it]
{'loss': 0.4674, 'learning_rate': 6.373392235405674e-06, 'epoch': 0.63}
+
63%|██████▎ | 7525/11952 [1:03:35<7:03:21, 5.74s/it]
63%|██████▎ | 7526/11952 [1:03:40<6:59:38, 5.69s/it]
{'loss': 0.454, 'learning_rate': 6.3708669507941925e-06, 'epoch': 0.63}
+
63%|██████▎ | 7526/11952 [1:03:40<6:59:38, 5.69s/it]
63%|██████▎ | 7527/11952 [1:03:46<7:02:06, 5.72s/it]
{'loss': 0.4648, 'learning_rate': 6.368341932691146e-06, 'epoch': 0.63}
+
63%|██████▎ | 7527/11952 [1:03:46<7:02:06, 5.72s/it]
63%|██████▎ | 7528/11952 [1:03:52<7:11:14, 5.85s/it]
{'loss': 0.4764, 'learning_rate': 6.365817181281965e-06, 'epoch': 0.63}
+
63%|██████▎ | 7528/11952 [1:03:52<7:11:14, 5.85s/it]
63%|██████▎ | 7529/11952 [1:03:58<7:08:40, 5.82s/it]
{'loss': 0.4925, 'learning_rate': 6.36329269675205e-06, 'epoch': 0.63}
+
63%|██████▎ | 7529/11952 [1:03:58<7:08:40, 5.82s/it]
63%|██████▎ | 7530/11952 [1:04:04<7:16:16, 5.92s/it]
{'loss': 0.4803, 'learning_rate': 6.360768479286793e-06, 'epoch': 0.63}
+
63%|██████▎ | 7530/11952 [1:04:04<7:16:16, 5.92s/it]
63%|██████▎ | 7531/11952 [1:04:10<7:08:12, 5.81s/it]
{'loss': 0.4688, 'learning_rate': 6.358244529071565e-06, 'epoch': 0.63}
+
63%|██████▎ | 7531/11952 [1:04:10<7:08:12, 5.81s/it]
63%|██████▎ | 7532/11952 [1:04:15<7:01:52, 5.73s/it]
{'loss': 0.4638, 'learning_rate': 6.355720846291713e-06, 'epoch': 0.63}
+
63%|██████▎ | 7532/11952 [1:04:15<7:01:52, 5.73s/it]
63%|██████▎ | 7533/11952 [1:04:21<7:07:21, 5.80s/it]
{'loss': 0.4732, 'learning_rate': 6.3531974311325625e-06, 'epoch': 0.63}
+
63%|██████▎ | 7533/11952 [1:04:21<7:07:21, 5.80s/it]
63%|██████▎ | 7534/11952 [1:04:28<7:15:45, 5.92s/it]
{'loss': 0.4725, 'learning_rate': 6.350674283779424e-06, 'epoch': 0.63}
+
63%|██████▎ | 7534/11952 [1:04:28<7:15:45, 5.92s/it]
63%|██████▎ | 7535/11952 [1:04:33<7:14:18, 5.90s/it]
{'loss': 0.46, 'learning_rate': 6.348151404417589e-06, 'epoch': 0.63}
+
63%|██████▎ | 7535/11952 [1:04:33<7:14:18, 5.90s/it]
63%|██████▎ | 7536/11952 [1:04:39<7:11:54, 5.87s/it]
{'loss': 0.4699, 'learning_rate': 6.3456287932323255e-06, 'epoch': 0.63}
+
63%|██████▎ | 7536/11952 [1:04:39<7:11:54, 5.87s/it]
63%|██████▎ | 7537/11952 [1:04:45<7:04:58, 5.78s/it]
{'loss': 0.464, 'learning_rate': 6.34310645040888e-06, 'epoch': 0.63}
+
63%|██████▎ | 7537/11952 [1:04:45<7:04:58, 5.78s/it]
63%|██████▎ | 7538/11952 [1:04:51<7:07:55, 5.82s/it]
{'loss': 0.4604, 'learning_rate': 6.34058437613249e-06, 'epoch': 0.63}
+
63%|██████▎ | 7538/11952 [1:04:51<7:07:55, 5.82s/it]
63%|██████▎ | 7539/11952 [1:04:56<7:03:13, 5.75s/it]
{'loss': 0.4868, 'learning_rate': 6.338062570588363e-06, 'epoch': 0.63}
+
63%|██████▎ | 7539/11952 [1:04:56<7:03:13, 5.75s/it]
63%|██████▎ | 7540/11952 [1:05:02<7:02:18, 5.74s/it]
{'loss': 0.4638, 'learning_rate': 6.335541033961687e-06, 'epoch': 0.63}
+
63%|██████▎ | 7540/11952 [1:05:02<7:02:18, 5.74s/it]
63%|██████▎ | 7541/11952 [1:05:08<7:01:28, 5.73s/it]
{'loss': 0.4742, 'learning_rate': 6.33301976643764e-06, 'epoch': 0.63}
+
63%|██████▎ | 7541/11952 [1:05:08<7:01:28, 5.73s/it]
63%|██████▎ | 7542/11952 [1:05:14<7:10:48, 5.86s/it]
{'loss': 0.4737, 'learning_rate': 6.330498768201367e-06, 'epoch': 0.63}
+
63%|██████▎ | 7542/11952 [1:05:14<7:10:48, 5.86s/it]
63%|██████▎ | 7543/11952 [1:05:20<7:09:23, 5.84s/it]
{'loss': 0.476, 'learning_rate': 6.327978039438003e-06, 'epoch': 0.63}
+
63%|██████▎ | 7543/11952 [1:05:20<7:09:23, 5.84s/it]
63%|██████▎ | 7544/11952 [1:05:25<7:06:15, 5.80s/it]
{'loss': 0.4563, 'learning_rate': 6.325457580332655e-06, 'epoch': 0.63}
+
63%|██████▎ | 7544/11952 [1:05:25<7:06:15, 5.80s/it]
63%|██████▎ | 7545/11952 [1:05:31<7:06:12, 5.80s/it]
{'loss': 0.4869, 'learning_rate': 6.3229373910704205e-06, 'epoch': 0.63}
+
63%|██████▎ | 7545/11952 [1:05:31<7:06:12, 5.80s/it]
63%|██████▎ | 7546/11952 [1:05:37<7:09:04, 5.84s/it]
{'loss': 0.4795, 'learning_rate': 6.3204174718363705e-06, 'epoch': 0.63}
+
63%|██████▎ | 7546/11952 [1:05:37<7:09:04, 5.84s/it]
63%|██████▎ | 7547/11952 [1:05:43<7:06:04, 5.80s/it]
{'loss': 0.4641, 'learning_rate': 6.317897822815559e-06, 'epoch': 0.63}
+
63%|██████▎ | 7547/11952 [1:05:43<7:06:04, 5.80s/it]
63%|██████▎ | 7548/11952 [1:05:49<7:06:30, 5.81s/it]
{'loss': 0.4707, 'learning_rate': 6.315378444193014e-06, 'epoch': 0.63}
+
63%|██████▎ | 7548/11952 [1:05:49<7:06:30, 5.81s/it]
63%|██████▎ | 7549/11952 [1:05:54<6:59:41, 5.72s/it]
{'loss': 0.4488, 'learning_rate': 6.31285933615375e-06, 'epoch': 0.63}
+
63%|██████▎ | 7549/11952 [1:05:54<6:59:41, 5.72s/it]1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...4 AutoResumeHook: Checking whether to suspend...
+
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
63%|██████▎ | 7550/11952 [1:06:00<6:59:22, 5.72s/it]
+
{'loss': 0.4658, 'learning_rate': 6.310340498882763e-06, 'epoch': 0.63}
+
63%|██████▎ | 7550/11952 [1:06:00<6:59:22, 5.72s/it]
63%|██████▎ | 7551/11952 [1:06:05<6:54:48, 5.66s/it]
{'loss': 0.4589, 'learning_rate': 6.30782193256502e-06, 'epoch': 0.63}
+
63%|██████▎ | 7551/11952 [1:06:05<6:54:48, 5.66s/it]
63%|██████▎ | 7552/11952 [1:06:11<7:03:26, 5.77s/it]
{'loss': 0.4657, 'learning_rate': 6.305303637385478e-06, 'epoch': 0.63}
+
63%|██████▎ | 7552/11952 [1:06:11<7:03:26, 5.77s/it]
63%|██████▎ | 7553/11952 [1:06:17<7:01:30, 5.75s/it]
{'loss': 0.4786, 'learning_rate': 6.302785613529072e-06, 'epoch': 0.63}
+
63%|██████▎ | 7553/11952 [1:06:17<7:01:30, 5.75s/it]
63%|██████▎ | 7554/11952 [1:06:23<6:56:18, 5.68s/it]
{'loss': 0.4664, 'learning_rate': 6.300267861180713e-06, 'epoch': 0.63}
+
63%|██████▎ | 7554/11952 [1:06:23<6:56:18, 5.68s/it]
63%|██████▎ | 7555/11952 [1:06:28<6:56:41, 5.69s/it]
{'loss': 0.4712, 'learning_rate': 6.297750380525289e-06, 'epoch': 0.63}
+
63%|██████▎ | 7555/11952 [1:06:28<6:56:41, 5.69s/it]
63%|██████▎ | 7556/11952 [1:06:34<6:56:33, 5.69s/it]
{'loss': 0.4753, 'learning_rate': 6.295233171747683e-06, 'epoch': 0.63}
+
63%|██████▎ | 7556/11952 [1:06:34<6:56:33, 5.69s/it]
63%|██████▎ | 7557/11952 [1:06:40<6:59:36, 5.73s/it]
{'loss': 0.4655, 'learning_rate': 6.292716235032738e-06, 'epoch': 0.63}
+
63%|██████▎ | 7557/11952 [1:06:40<6:59:36, 5.73s/it]
63%|██████▎ | 7558/11952 [1:06:45<6:55:24, 5.67s/it]
{'loss': 0.4664, 'learning_rate': 6.290199570565298e-06, 'epoch': 0.63}
+
63%|██████▎ | 7558/11952 [1:06:45<6:55:24, 5.67s/it]
63%|██████▎ | 7559/11952 [1:06:51<7:01:30, 5.76s/it]
{'loss': 0.4774, 'learning_rate': 6.287683178530172e-06, 'epoch': 0.63}
+
63%|██████▎ | 7559/11952 [1:06:51<7:01:30, 5.76s/it]
63%|██████▎ | 7560/11952 [1:06:57<7:01:20, 5.76s/it]
{'loss': 0.482, 'learning_rate': 6.285167059112149e-06, 'epoch': 0.63}
+
63%|██████▎ | 7560/11952 [1:06:57<7:01:20, 5.76s/it]
63%|██████▎ | 7561/11952 [1:07:03<7:00:18, 5.74s/it]
{'loss': 0.4864, 'learning_rate': 6.282651212496009e-06, 'epoch': 0.63}
+
63%|██████▎ | 7561/11952 [1:07:03<7:00:18, 5.74s/it]
63%|██████▎ | 7562/11952 [1:07:09<7:04:28, 5.80s/it]
{'loss': 0.4768, 'learning_rate': 6.280135638866502e-06, 'epoch': 0.63}
+
63%|██████▎ | 7562/11952 [1:07:09<7:04:28, 5.80s/it]
63%|██████▎ | 7563/11952 [1:07:14<7:01:29, 5.76s/it]
{'loss': 0.4789, 'learning_rate': 6.277620338408362e-06, 'epoch': 0.63}
+
63%|██████▎ | 7563/11952 [1:07:14<7:01:29, 5.76s/it]
63%|██████▎ | 7564/11952 [1:07:20<7:00:29, 5.75s/it]
{'loss': 0.4865, 'learning_rate': 6.275105311306298e-06, 'epoch': 0.63}
+
63%|██████▎ | 7564/11952 [1:07:20<7:00:29, 5.75s/it]
63%|██████▎ | 7565/11952 [1:07:26<7:01:38, 5.77s/it]
{'loss': 0.4426, 'learning_rate': 6.272590557745011e-06, 'epoch': 0.63}
+
63%|██████▎ | 7565/11952 [1:07:26<7:01:38, 5.77s/it]
63%|██████▎ | 7566/11952 [1:07:32<7:00:31, 5.75s/it]
{'loss': 0.4658, 'learning_rate': 6.270076077909166e-06, 'epoch': 0.63}
+
63%|██████▎ | 7566/11952 [1:07:32<7:00:31, 5.75s/it]
63%|██████▎ | 7567/11952 [1:07:38<7:03:12, 5.79s/it]
{'loss': 0.4645, 'learning_rate': 6.267561871983424e-06, 'epoch': 0.63}
+
63%|██████▎ | 7567/11952 [1:07:38<7:03:12, 5.79s/it]
63%|██████▎ | 7568/11952 [1:07:43<7:05:03, 5.82s/it]
{'loss': 0.4599, 'learning_rate': 6.265047940152413e-06, 'epoch': 0.63}
+
63%|██████▎ | 7568/11952 [1:07:43<7:05:03, 5.82s/it]
63%|██████▎ | 7569/11952 [1:07:49<7:05:45, 5.83s/it]
{'loss': 0.4751, 'learning_rate': 6.262534282600747e-06, 'epoch': 0.63}
+
63%|██████▎ | 7569/11952 [1:07:49<7:05:45, 5.83s/it]
63%|██████▎ | 7570/11952 [1:07:55<7:11:25, 5.91s/it]
{'loss': 0.4681, 'learning_rate': 6.2600208995130156e-06, 'epoch': 0.63}
+
63%|██████▎ | 7570/11952 [1:07:55<7:11:25, 5.91s/it]
63%|██████▎ | 7571/11952 [1:08:01<7:07:24, 5.85s/it]
{'loss': 0.4576, 'learning_rate': 6.257507791073792e-06, 'epoch': 0.63}
+
63%|██████▎ | 7571/11952 [1:08:01<7:07:24, 5.85s/it]
63%|██████▎ | 7572/11952 [1:08:07<7:01:33, 5.77s/it]
{'loss': 0.4755, 'learning_rate': 6.254994957467633e-06, 'epoch': 0.63}
+
63%|██████▎ | 7572/11952 [1:08:07<7:01:33, 5.77s/it]
63%|██████▎ | 7573/11952 [1:08:13<7:08:17, 5.87s/it]
{'loss': 0.4781, 'learning_rate': 6.252482398879068e-06, 'epoch': 0.63}
+
63%|██████▎ | 7573/11952 [1:08:13<7:08:17, 5.87s/it]
63%|██████▎ | 7574/11952 [1:08:19<7:10:10, 5.90s/it]
{'loss': 0.4545, 'learning_rate': 6.249970115492609e-06, 'epoch': 0.63}
+
63%|██████▎ | 7574/11952 [1:08:19<7:10:10, 5.90s/it]
63%|██████▎ | 7575/11952 [1:08:25<7:16:06, 5.98s/it]
{'loss': 0.4745, 'learning_rate': 6.247458107492745e-06, 'epoch': 0.63}
+
63%|██████▎ | 7575/11952 [1:08:25<7:16:06, 5.98s/it]
63%|██████▎ | 7576/11952 [1:08:31<7:14:00, 5.95s/it]
{'loss': 0.4892, 'learning_rate': 6.244946375063951e-06, 'epoch': 0.63}
+
63%|██████▎ | 7576/11952 [1:08:31<7:14:00, 5.95s/it]
63%|██████▎ | 7577/11952 [1:08:37<7:10:21, 5.90s/it]
{'loss': 0.4818, 'learning_rate': 6.242434918390678e-06, 'epoch': 0.63}
+
63%|██████▎ | 7577/11952 [1:08:37<7:10:21, 5.90s/it]
63%|██████▎ | 7578/11952 [1:08:42<7:07:49, 5.87s/it]
{'loss': 0.4687, 'learning_rate': 6.239923737657351e-06, 'epoch': 0.63}
+
63%|██████▎ | 7578/11952 [1:08:42<7:07:49, 5.87s/it]
63%|██████▎ | 7579/11952 [1:08:48<7:05:55, 5.84s/it]
{'loss': 0.4732, 'learning_rate': 6.237412833048389e-06, 'epoch': 0.63}
+
63%|██████▎ | 7579/11952 [1:08:48<7:05:55, 5.84s/it]
63%|██████▎ | 7580/11952 [1:08:54<7:10:02, 5.90s/it]
{'loss': 0.4699, 'learning_rate': 6.2349022047481784e-06, 'epoch': 0.63}
+
63%|██████▎ | 7580/11952 [1:08:54<7:10:02, 5.90s/it]
63%|██████▎ | 7581/11952 [1:09:00<7:15:21, 5.98s/it]
{'loss': 0.4839, 'learning_rate': 6.2323918529410895e-06, 'epoch': 0.63}
+
63%|██████▎ | 7581/11952 [1:09:00<7:15:21, 5.98s/it]
63%|██████▎ | 7582/11952 [1:09:06<7:09:49, 5.90s/it]
{'loss': 0.4702, 'learning_rate': 6.2298817778114725e-06, 'epoch': 0.63}
+
63%|██████▎ | 7582/11952 [1:09:06<7:09:49, 5.90s/it]
63%|██████▎ | 7583/11952 [1:09:12<7:13:06, 5.95s/it]
{'loss': 0.4687, 'learning_rate': 6.227371979543658e-06, 'epoch': 0.63}
+
63%|██████▎ | 7583/11952 [1:09:12<7:13:06, 5.95s/it]
63%|██████▎ | 7584/11952 [1:09:18<7:21:46, 6.07s/it]
{'loss': 0.5033, 'learning_rate': 6.224862458321954e-06, 'epoch': 0.63}
+
63%|██████▎ | 7584/11952 [1:09:18<7:21:46, 6.07s/it]
63%|██████▎ | 7585/11952 [1:09:24<7:13:30, 5.96s/it]
{'loss': 0.4622, 'learning_rate': 6.222353214330643e-06, 'epoch': 0.63}
+
63%|██████▎ | 7585/11952 [1:09:24<7:13:30, 5.96s/it]
63%|██████▎ | 7586/11952 [1:09:30<7:05:52, 5.85s/it]
{'loss': 0.4653, 'learning_rate': 6.2198442477540036e-06, 'epoch': 0.63}
+
63%|██████▎ | 7586/11952 [1:09:30<7:05:52, 5.85s/it]
63%|██████▎ | 7587/11952 [1:09:36<7:12:11, 5.94s/it]
{'loss': 0.4618, 'learning_rate': 6.2173355587762805e-06, 'epoch': 0.63}
+
63%|██████▎ | 7587/11952 [1:09:36<7:12:11, 5.94s/it]
63%|██████▎ | 7588/11952 [1:09:42<7:06:09, 5.86s/it]
{'loss': 0.4721, 'learning_rate': 6.214827147581701e-06, 'epoch': 0.63}
+
63%|██████▎ | 7588/11952 [1:09:42<7:06:09, 5.86s/it]
63%|██████▎ | 7589/11952 [1:09:47<7:06:41, 5.87s/it]
{'loss': 0.4822, 'learning_rate': 6.212319014354472e-06, 'epoch': 0.63}
+
63%|██████▎ | 7589/11952 [1:09:47<7:06:41, 5.87s/it]
64%|██████▎ | 7590/11952 [1:09:53<6:59:14, 5.77s/it]
{'loss': 0.4573, 'learning_rate': 6.209811159278778e-06, 'epoch': 0.64}
+
64%|██████▎ | 7590/11952 [1:09:53<6:59:14, 5.77s/it]
64%|██████▎ | 7591/11952 [1:09:59<7:01:13, 5.80s/it]
{'loss': 0.4765, 'learning_rate': 6.207303582538789e-06, 'epoch': 0.64}
+
64%|██████▎ | 7591/11952 [1:09:59<7:01:13, 5.80s/it]
64%|██████▎ | 7592/11952 [1:10:05<7:05:22, 5.85s/it]
{'loss': 0.4657, 'learning_rate': 6.2047962843186495e-06, 'epoch': 0.64}
+
64%|██████▎ | 7592/11952 [1:10:05<7:05:22, 5.85s/it]
64%|██████▎ | 7593/11952 [1:10:11<7:06:11, 5.87s/it]
{'loss': 0.4607, 'learning_rate': 6.202289264802488e-06, 'epoch': 0.64}
+
64%|██████▎ | 7593/11952 [1:10:11<7:06:11, 5.87s/it]
64%|██████▎ | 7594/11952 [1:10:16<6:59:09, 5.77s/it]
{'loss': 0.4389, 'learning_rate': 6.199782524174406e-06, 'epoch': 0.64}
+
64%|██████▎ | 7594/11952 [1:10:16<6:59:09, 5.77s/it]
64%|██████▎ | 7595/11952 [1:10:22<6:54:20, 5.71s/it]
{'loss': 0.4819, 'learning_rate': 6.197276062618489e-06, 'epoch': 0.64}
+
64%|██████▎ | 7595/11952 [1:10:22<6:54:20, 5.71s/it]
64%|██████▎ | 7596/11952 [1:10:28<7:00:21, 5.79s/it]
{'loss': 0.4754, 'learning_rate': 6.194769880318801e-06, 'epoch': 0.64}
+
64%|██████▎ | 7596/11952 [1:10:28<7:00:21, 5.79s/it]
64%|██████▎ | 7597/11952 [1:10:34<7:10:31, 5.93s/it]
{'loss': 0.4634, 'learning_rate': 6.192263977459385e-06, 'epoch': 0.64}
+
64%|██████▎ | 7597/11952 [1:10:34<7:10:31, 5.93s/it]
64%|██████▎ | 7598/11952 [1:10:40<7:03:35, 5.84s/it]
{'loss': 0.4707, 'learning_rate': 6.189758354224262e-06, 'epoch': 0.64}
+
64%|██████▎ | 7598/11952 [1:10:40<7:03:35, 5.84s/it]
64%|██████▎ | 7599/11952 [1:10:46<7:07:39, 5.89s/it]
{'loss': 0.4694, 'learning_rate': 6.187253010797443e-06, 'epoch': 0.64}
+
64%|██████▎ | 7599/11952 [1:10:46<7:07:39, 5.89s/it]76 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+2 3AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
64%|██████▎ | 7600/11952 [1:10:52<7:12:30, 5.96s/it]
{'loss': 0.4673, 'learning_rate': 6.1847479473629035e-06, 'epoch': 0.64}
+
64%|██████▎ | 7600/11952 [1:10:52<7:12:30, 5.96s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
64%|██████▎ | 7601/11952 [1:11:21<15:44:50, 13.03s/it]
{'loss': 0.4739, 'learning_rate': 6.1822431641046045e-06, 'epoch': 0.64}
+
64%|██████▎ | 7601/11952 [1:11:21<15:44:50, 13.03s/it]
64%|██████▎ | 7602/11952 [1:11:27<13:05:12, 10.83s/it]
{'loss': 0.4772, 'learning_rate': 6.1797386612064895e-06, 'epoch': 0.64}
+
64%|██████▎ | 7602/11952 [1:11:27<13:05:12, 10.83s/it]
64%|██████▎ | 7603/11952 [1:11:33<11:14:12, 9.30s/it]
{'loss': 0.4582, 'learning_rate': 6.177234438852477e-06, 'epoch': 0.64}
+
64%|██████▎ | 7603/11952 [1:11:33<11:14:12, 9.30s/it]
64%|██████▎ | 7604/11952 [1:11:39<9:56:10, 8.23s/it]
{'loss': 0.4811, 'learning_rate': 6.174730497226467e-06, 'epoch': 0.64}
+
64%|██████▎ | 7604/11952 [1:11:39<9:56:10, 8.23s/it]
64%|██████▎ | 7605/11952 [1:11:44<8:58:25, 7.43s/it]
{'loss': 0.4807, 'learning_rate': 6.172226836512336e-06, 'epoch': 0.64}
+
64%|██████▎ | 7605/11952 [1:11:44<8:58:25, 7.43s/it]
64%|██████▎ | 7606/11952 [1:11:50<8:29:07, 7.03s/it]
{'loss': 0.4766, 'learning_rate': 6.16972345689395e-06, 'epoch': 0.64}
+
64%|██████▎ | 7606/11952 [1:11:50<8:29:07, 7.03s/it]
64%|██████▎ | 7607/11952 [1:11:56<7:55:43, 6.57s/it]
{'loss': 0.4655, 'learning_rate': 6.167220358555138e-06, 'epoch': 0.64}
+
64%|██████▎ | 7607/11952 [1:11:56<7:55:43, 6.57s/it]
64%|██████▎ | 7608/11952 [1:12:01<7:33:18, 6.26s/it]
{'loss': 0.4603, 'learning_rate': 6.164717541679724e-06, 'epoch': 0.64}
+
64%|██████▎ | 7608/11952 [1:12:01<7:33:18, 6.26s/it]
64%|██████▎ | 7609/11952 [1:12:07<7:19:46, 6.08s/it]
{'loss': 0.4671, 'learning_rate': 6.162215006451502e-06, 'epoch': 0.64}
+
64%|██████▎ | 7609/11952 [1:12:07<7:19:46, 6.08s/it]
64%|██████▎ | 7610/11952 [1:12:13<7:13:01, 5.98s/it]
{'loss': 0.4648, 'learning_rate': 6.159712753054248e-06, 'epoch': 0.64}
+
64%|██████▎ | 7610/11952 [1:12:13<7:13:01, 5.98s/it]
64%|██████▎ | 7611/11952 [1:12:18<7:05:56, 5.89s/it]
{'loss': 0.4749, 'learning_rate': 6.157210781671713e-06, 'epoch': 0.64}
+
64%|██████▎ | 7611/11952 [1:12:18<7:05:56, 5.89s/it]
64%|██████▎ | 7612/11952 [1:12:25<7:12:49, 5.98s/it]
{'loss': 0.4573, 'learning_rate': 6.154709092487633e-06, 'epoch': 0.64}
+
64%|██████▎ | 7612/11952 [1:12:25<7:12:49, 5.98s/it]
64%|██████▎ | 7613/11952 [1:12:30<7:10:11, 5.95s/it]
{'loss': 0.4714, 'learning_rate': 6.152207685685727e-06, 'epoch': 0.64}
+
64%|██████▎ | 7613/11952 [1:12:30<7:10:11, 5.95s/it]
64%|██████▎ | 7614/11952 [1:12:36<7:07:12, 5.91s/it]
{'loss': 0.4892, 'learning_rate': 6.1497065614496866e-06, 'epoch': 0.64}
+
64%|██████▎ | 7614/11952 [1:12:36<7:07:12, 5.91s/it]
64%|██████▎ | 7615/11952 [1:12:42<7:08:27, 5.93s/it]
{'loss': 0.4641, 'learning_rate': 6.147205719963181e-06, 'epoch': 0.64}
+
64%|██████▎ | 7615/11952 [1:12:42<7:08:27, 5.93s/it]
64%|██████▎ | 7616/11952 [1:12:48<7:11:54, 5.98s/it]
{'loss': 0.4658, 'learning_rate': 6.144705161409858e-06, 'epoch': 0.64}
+
64%|██████▎ | 7616/11952 [1:12:48<7:11:54, 5.98s/it]
64%|██████▎ | 7617/11952 [1:12:54<7:10:29, 5.96s/it]
{'loss': 0.4738, 'learning_rate': 6.142204885973358e-06, 'epoch': 0.64}
+
64%|██████▎ | 7617/11952 [1:12:54<7:10:29, 5.96s/it]
64%|██████▎ | 7618/11952 [1:13:00<7:11:17, 5.97s/it]
{'loss': 0.4532, 'learning_rate': 6.1397048938372825e-06, 'epoch': 0.64}
+
64%|██████▎ | 7618/11952 [1:13:00<7:11:17, 5.97s/it]
64%|██████▎ | 7619/11952 [1:13:06<7:08:54, 5.94s/it]
{'loss': 0.481, 'learning_rate': 6.13720518518522e-06, 'epoch': 0.64}
+
64%|██████▎ | 7619/11952 [1:13:06<7:08:54, 5.94s/it]
64%|██████▍ | 7620/11952 [1:13:12<7:01:51, 5.84s/it]
{'loss': 0.4683, 'learning_rate': 6.134705760200747e-06, 'epoch': 0.64}
+
64%|██████▍ | 7620/11952 [1:13:12<7:01:51, 5.84s/it]
64%|██████▍ | 7621/11952 [1:13:17<6:54:30, 5.74s/it]
{'loss': 0.4594, 'learning_rate': 6.132206619067407e-06, 'epoch': 0.64}
+
64%|██████▍ | 7621/11952 [1:13:17<6:54:30, 5.74s/it]
64%|██████▍ | 7622/11952 [1:13:23<6:50:58, 5.69s/it]
{'loss': 0.4808, 'learning_rate': 6.1297077619687216e-06, 'epoch': 0.64}
+
64%|██████▍ | 7622/11952 [1:13:23<6:50:58, 5.69s/it]
64%|██████▍ | 7623/11952 [1:13:29<6:54:45, 5.75s/it]
{'loss': 0.4638, 'learning_rate': 6.127209189088204e-06, 'epoch': 0.64}
+
64%|██████▍ | 7623/11952 [1:13:29<6:54:45, 5.75s/it]
64%|██████▍ | 7624/11952 [1:13:35<7:00:03, 5.82s/it]
{'loss': 0.4768, 'learning_rate': 6.1247109006093345e-06, 'epoch': 0.64}
+
64%|██████▍ | 7624/11952 [1:13:35<7:00:03, 5.82s/it]
64%|██████▍ | 7625/11952 [1:13:41<7:04:17, 5.88s/it]
{'loss': 0.4717, 'learning_rate': 6.122212896715577e-06, 'epoch': 0.64}
+
64%|██████▍ | 7625/11952 [1:13:41<7:04:17, 5.88s/it]
64%|██████▍ | 7626/11952 [1:13:47<7:07:07, 5.92s/it]
{'loss': 0.4688, 'learning_rate': 6.119715177590373e-06, 'epoch': 0.64}
+
64%|██████▍ | 7626/11952 [1:13:47<7:07:07, 5.92s/it]
64%|██████▍ | 7627/11952 [1:13:52<6:59:19, 5.82s/it]
{'loss': 0.4736, 'learning_rate': 6.1172177434171495e-06, 'epoch': 0.64}
+
64%|██████▍ | 7627/11952 [1:13:52<6:59:19, 5.82s/it]
64%|██████▍ | 7628/11952 [1:13:58<7:02:02, 5.86s/it]
{'loss': 0.5022, 'learning_rate': 6.114720594379304e-06, 'epoch': 0.64}
+
64%|██████▍ | 7628/11952 [1:13:58<7:02:02, 5.86s/it]
64%|██████▍ | 7629/11952 [1:14:05<7:13:08, 6.01s/it]
{'loss': 0.4698, 'learning_rate': 6.112223730660221e-06, 'epoch': 0.64}
+
64%|██████▍ | 7629/11952 [1:14:05<7:13:08, 6.01s/it]
64%|██████▍ | 7630/11952 [1:14:11<7:13:34, 6.02s/it]
{'loss': 0.4825, 'learning_rate': 6.109727152443254e-06, 'epoch': 0.64}
+
64%|██████▍ | 7630/11952 [1:14:11<7:13:34, 6.02s/it]
64%|██████▍ | 7631/11952 [1:14:16<7:08:43, 5.95s/it]
{'loss': 0.4657, 'learning_rate': 6.1072308599117445e-06, 'epoch': 0.64}
+
64%|██████▍ | 7631/11952 [1:14:16<7:08:43, 5.95s/it]
64%|██████▍ | 7632/11952 [1:14:22<6:59:21, 5.82s/it]
{'loss': 0.4716, 'learning_rate': 6.104734853249009e-06, 'epoch': 0.64}
+
64%|██████▍ | 7632/11952 [1:14:22<6:59:21, 5.82s/it]
64%|██████▍ | 7633/11952 [1:14:27<6:51:57, 5.72s/it]
{'loss': 0.4828, 'learning_rate': 6.102239132638343e-06, 'epoch': 0.64}
+
64%|██████▍ | 7633/11952 [1:14:27<6:51:57, 5.72s/it]
64%|██████▍ | 7634/11952 [1:14:33<6:47:36, 5.66s/it]
{'loss': 0.4588, 'learning_rate': 6.099743698263028e-06, 'epoch': 0.64}
+
64%|██████▍ | 7634/11952 [1:14:33<6:47:36, 5.66s/it]
64%|██████▍ | 7635/11952 [1:14:39<6:50:40, 5.71s/it]
{'loss': 0.4679, 'learning_rate': 6.097248550306311e-06, 'epoch': 0.64}
+
64%|██████▍ | 7635/11952 [1:14:39<6:50:40, 5.71s/it]
64%|██████▍ | 7636/11952 [1:14:44<6:49:21, 5.69s/it]
{'loss': 0.4711, 'learning_rate': 6.094753688951428e-06, 'epoch': 0.64}
+
64%|██████▍ | 7636/11952 [1:14:44<6:49:21, 5.69s/it]
64%|██████▍ | 7637/11952 [1:14:50<6:57:37, 5.81s/it]
{'loss': 0.4754, 'learning_rate': 6.092259114381589e-06, 'epoch': 0.64}
+
64%|██████▍ | 7637/11952 [1:14:50<6:57:37, 5.81s/it]
64%|██████▍ | 7638/11952 [1:14:56<6:55:27, 5.78s/it]
{'loss': 0.4503, 'learning_rate': 6.089764826779989e-06, 'epoch': 0.64}
+
64%|██████▍ | 7638/11952 [1:14:56<6:55:27, 5.78s/it]
64%|██████▍ | 7639/11952 [1:15:02<6:58:11, 5.82s/it]
{'loss': 0.4527, 'learning_rate': 6.087270826329793e-06, 'epoch': 0.64}
+
64%|██████▍ | 7639/11952 [1:15:02<6:58:11, 5.82s/it]
64%|██████▍ | 7640/11952 [1:15:08<6:56:03, 5.79s/it]
{'loss': 0.4627, 'learning_rate': 6.084777113214156e-06, 'epoch': 0.64}
+
64%|██████▍ | 7640/11952 [1:15:08<6:56:03, 5.79s/it]
64%|██████▍ | 7641/11952 [1:15:14<6:55:48, 5.79s/it]
{'loss': 0.4812, 'learning_rate': 6.082283687616204e-06, 'epoch': 0.64}
+
64%|██████▍ | 7641/11952 [1:15:14<6:55:48, 5.79s/it]
64%|██████▍ | 7642/11952 [1:15:20<7:03:20, 5.89s/it]
{'loss': 0.4899, 'learning_rate': 6.079790549719044e-06, 'epoch': 0.64}
+
64%|██████▍ | 7642/11952 [1:15:20<7:03:20, 5.89s/it]
64%|██████▍ | 7643/11952 [1:15:26<7:08:17, 5.96s/it]
{'loss': 0.4577, 'learning_rate': 6.077297699705758e-06, 'epoch': 0.64}
+
64%|██████▍ | 7643/11952 [1:15:26<7:08:17, 5.96s/it]
64%|██████▍ | 7644/11952 [1:15:31<7:00:02, 5.85s/it]
{'loss': 0.4823, 'learning_rate': 6.074805137759414e-06, 'epoch': 0.64}
+
64%|██████▍ | 7644/11952 [1:15:31<7:00:02, 5.85s/it]
64%|██████▍ | 7645/11952 [1:15:37<6:56:44, 5.81s/it]
{'loss': 0.4605, 'learning_rate': 6.072312864063054e-06, 'epoch': 0.64}
+
64%|██████▍ | 7645/11952 [1:15:37<6:56:44, 5.81s/it]
64%|██████▍ | 7646/11952 [1:15:43<6:59:09, 5.84s/it]
{'loss': 0.4674, 'learning_rate': 6.0698208787996995e-06, 'epoch': 0.64}
+
64%|██████▍ | 7646/11952 [1:15:43<6:59:09, 5.84s/it]
64%|██████▍ | 7647/11952 [1:15:49<6:53:30, 5.76s/it]
{'loss': 0.4326, 'learning_rate': 6.067329182152355e-06, 'epoch': 0.64}
+
64%|██████▍ | 7647/11952 [1:15:49<6:53:30, 5.76s/it]
64%|██████▍ | 7648/11952 [1:15:54<6:52:02, 5.74s/it]
{'loss': 0.4767, 'learning_rate': 6.064837774303997e-06, 'epoch': 0.64}
+
64%|██████▍ | 7648/11952 [1:15:54<6:52:02, 5.74s/it]
64%|██████▍ | 7649/11952 [1:16:00<6:59:46, 5.85s/it]
{'loss': 0.4843, 'learning_rate': 6.0623466554375864e-06, 'epoch': 0.64}
+
64%|██████▍ | 7649/11952 [1:16:00<6:59:46, 5.85s/it]6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+25 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
64%|██████▍ | 7650/11952 [1:16:06<6:54:14, 5.78s/it]
{'loss': 0.4827, 'learning_rate': 6.059855825736061e-06, 'epoch': 0.64}
+
64%|██████▍ | 7650/11952 [1:16:06<6:54:14, 5.78s/it]
64%|██████▍ | 7651/11952 [1:16:12<6:48:21, 5.70s/it]
{'loss': 0.4549, 'learning_rate': 6.057365285382333e-06, 'epoch': 0.64}
+
64%|██████▍ | 7651/11952 [1:16:12<6:48:21, 5.70s/it]
64%|██████▍ | 7652/11952 [1:16:17<6:47:03, 5.68s/it]
{'loss': 0.4818, 'learning_rate': 6.0548750345593e-06, 'epoch': 0.64}
+
64%|██████▍ | 7652/11952 [1:16:17<6:47:03, 5.68s/it]
64%|██████▍ | 7653/11952 [1:16:23<6:45:04, 5.65s/it]
{'loss': 0.4602, 'learning_rate': 6.052385073449833e-06, 'epoch': 0.64}
+
64%|██████▍ | 7653/11952 [1:16:23<6:45:04, 5.65s/it]
64%|██████▍ | 7654/11952 [1:16:29<6:51:51, 5.75s/it]
{'loss': 0.4846, 'learning_rate': 6.049895402236789e-06, 'epoch': 0.64}
+
64%|██████▍ | 7654/11952 [1:16:29<6:51:51, 5.75s/it]
64%|██████▍ | 7655/11952 [1:16:34<6:50:41, 5.73s/it]
{'loss': 0.4772, 'learning_rate': 6.047406021103e-06, 'epoch': 0.64}
+
64%|██████▍ | 7655/11952 [1:16:34<6:50:41, 5.73s/it]
64%|██████▍ | 7656/11952 [1:16:40<6:53:58, 5.78s/it]
{'loss': 0.4602, 'learning_rate': 6.04491693023127e-06, 'epoch': 0.64}
+
64%|██████▍ | 7656/11952 [1:16:40<6:53:58, 5.78s/it]
64%|██████▍ | 7657/11952 [1:16:46<6:56:30, 5.82s/it]
{'loss': 0.4973, 'learning_rate': 6.042428129804392e-06, 'epoch': 0.64}
+
64%|██████▍ | 7657/11952 [1:16:46<6:56:30, 5.82s/it]
64%|██████▍ | 7658/11952 [1:16:52<7:02:28, 5.90s/it]
{'loss': 0.4907, 'learning_rate': 6.0399396200051285e-06, 'epoch': 0.64}
+
64%|██████▍ | 7658/11952 [1:16:52<7:02:28, 5.90s/it]
64%|██████▍ | 7659/11952 [1:16:58<7:00:30, 5.88s/it]
{'loss': 0.4616, 'learning_rate': 6.0374514010162296e-06, 'epoch': 0.64}
+
64%|██████▍ | 7659/11952 [1:16:58<7:00:30, 5.88s/it]
64%|██████▍ | 7660/11952 [1:17:04<6:57:08, 5.83s/it]
{'loss': 0.4955, 'learning_rate': 6.034963473020417e-06, 'epoch': 0.64}
+
64%|██████▍ | 7660/11952 [1:17:04<6:57:08, 5.83s/it]
64%|██████▍ | 7661/11952 [1:17:10<6:58:34, 5.85s/it]
{'loss': 0.4642, 'learning_rate': 6.0324758362003956e-06, 'epoch': 0.64}
+
64%|██████▍ | 7661/11952 [1:17:10<6:58:34, 5.85s/it]
64%|██████▍ | 7662/11952 [1:17:16<6:55:46, 5.82s/it]
{'loss': 0.4725, 'learning_rate': 6.029988490738849e-06, 'epoch': 0.64}
+
64%|██████▍ | 7662/11952 [1:17:16<6:55:46, 5.82s/it]
64%|██████▍ | 7663/11952 [1:17:21<6:52:24, 5.77s/it]
{'loss': 0.4769, 'learning_rate': 6.027501436818433e-06, 'epoch': 0.64}
+
64%|██████▍ | 7663/11952 [1:17:21<6:52:24, 5.77s/it]
64%|██████▍ | 7664/11952 [1:17:27<6:55:21, 5.81s/it]
{'loss': 0.4685, 'learning_rate': 6.0250146746217895e-06, 'epoch': 0.64}
+
64%|██████▍ | 7664/11952 [1:17:27<6:55:21, 5.81s/it]
64%|██████▍ | 7665/11952 [1:17:33<6:56:00, 5.82s/it]
{'loss': 0.4556, 'learning_rate': 6.022528204331534e-06, 'epoch': 0.64}
+
64%|██████▍ | 7665/11952 [1:17:33<6:56:00, 5.82s/it]
64%|██████▍ | 7666/11952 [1:17:39<6:53:08, 5.78s/it]
{'loss': 0.4587, 'learning_rate': 6.020042026130262e-06, 'epoch': 0.64}
+
64%|██████▍ | 7666/11952 [1:17:39<6:53:08, 5.78s/it]
64%|██████▍ | 7667/11952 [1:17:45<6:59:42, 5.88s/it]
{'loss': 0.4977, 'learning_rate': 6.017556140200553e-06, 'epoch': 0.64}
+
64%|██████▍ | 7667/11952 [1:17:45<6:59:42, 5.88s/it]
64%|██████▍ | 7668/11952 [1:17:50<6:53:11, 5.79s/it]
{'loss': 0.4682, 'learning_rate': 6.015070546724957e-06, 'epoch': 0.64}
+
64%|██████▍ | 7668/11952 [1:17:50<6:53:11, 5.79s/it]
64%|██████▍ | 7669/11952 [1:17:56<6:54:55, 5.81s/it]
{'loss': 0.4524, 'learning_rate': 6.012585245886004e-06, 'epoch': 0.64}
+
64%|██████▍ | 7669/11952 [1:17:56<6:54:55, 5.81s/it]
64%|██████▍ | 7670/11952 [1:18:03<7:06:00, 5.97s/it]
{'loss': 0.4828, 'learning_rate': 6.0101002378662066e-06, 'epoch': 0.64}
+
64%|██████▍ | 7670/11952 [1:18:03<7:06:00, 5.97s/it]
64%|██████▍ | 7671/11952 [1:18:08<6:59:39, 5.88s/it]
{'loss': 0.4578, 'learning_rate': 6.007615522848053e-06, 'epoch': 0.64}
+
64%|██████▍ | 7671/11952 [1:18:08<6:59:39, 5.88s/it]
64%|██████▍ | 7672/11952 [1:18:14<6:57:34, 5.85s/it]
{'loss': 0.4576, 'learning_rate': 6.00513110101401e-06, 'epoch': 0.64}
+
64%|██████▍ | 7672/11952 [1:18:14<6:57:34, 5.85s/it]
64%|██████▍ | 7673/11952 [1:18:20<7:00:32, 5.90s/it]
{'loss': 0.4703, 'learning_rate': 6.002646972546517e-06, 'epoch': 0.64}
+
64%|██████▍ | 7673/11952 [1:18:20<7:00:32, 5.90s/it]
64%|██████▍ | 7674/11952 [1:18:26<7:01:16, 5.91s/it]
{'loss': 0.4826, 'learning_rate': 6.000163137628009e-06, 'epoch': 0.64}
+
64%|██████▍ | 7674/11952 [1:18:26<7:01:16, 5.91s/it]
64%|██████▍ | 7675/11952 [1:18:32<7:00:17, 5.90s/it]
{'loss': 0.4883, 'learning_rate': 5.997679596440884e-06, 'epoch': 0.64}
+
64%|██████▍ | 7675/11952 [1:18:32<7:00:17, 5.90s/it]
64%|██████▍ | 7676/11952 [1:18:37<6:53:04, 5.80s/it]
{'loss': 0.4739, 'learning_rate': 5.995196349167523e-06, 'epoch': 0.64}
+
64%|██████▍ | 7676/11952 [1:18:37<6:53:04, 5.80s/it]
64%|██████▍ | 7677/11952 [1:18:43<6:58:08, 5.87s/it]
{'loss': 0.485, 'learning_rate': 5.992713395990285e-06, 'epoch': 0.64}
+
64%|██████▍ | 7677/11952 [1:18:43<6:58:08, 5.87s/it]
64%|██████▍ | 7678/11952 [1:18:49<6:58:43, 5.88s/it]
{'loss': 0.4745, 'learning_rate': 5.990230737091505e-06, 'epoch': 0.64}
+
64%|██████▍ | 7678/11952 [1:18:49<6:58:43, 5.88s/it]
64%|██████▍ | 7679/11952 [1:18:55<6:56:27, 5.85s/it]
{'loss': 0.4834, 'learning_rate': 5.987748372653504e-06, 'epoch': 0.64}
+
64%|██████▍ | 7679/11952 [1:18:55<6:56:27, 5.85s/it]
64%|██████▍ | 7680/11952 [1:19:01<7:00:32, 5.91s/it]
{'loss': 0.466, 'learning_rate': 5.9852663028585704e-06, 'epoch': 0.64}
+
64%|██████▍ | 7680/11952 [1:19:01<7:00:32, 5.91s/it]
64%|██████▍ | 7681/11952 [1:19:07<6:54:19, 5.82s/it]
{'loss': 0.4647, 'learning_rate': 5.982784527888985e-06, 'epoch': 0.64}
+
64%|██████▍ | 7681/11952 [1:19:07<6:54:19, 5.82s/it]
64%|██████▍ | 7682/11952 [1:19:12<6:49:40, 5.76s/it]
{'loss': 0.476, 'learning_rate': 5.980303047926996e-06, 'epoch': 0.64}
+
64%|██████▍ | 7682/11952 [1:19:12<6:49:40, 5.76s/it]
64%|██████▍ | 7683/11952 [1:19:18<6:57:59, 5.87s/it]
{'loss': 0.4727, 'learning_rate': 5.977821863154832e-06, 'epoch': 0.64}
+
64%|██████▍ | 7683/11952 [1:19:18<6:57:59, 5.87s/it]
64%|██████▍ | 7684/11952 [1:19:24<6:56:21, 5.85s/it]
{'loss': 0.463, 'learning_rate': 5.975340973754697e-06, 'epoch': 0.64}
+
64%|██████▍ | 7684/11952 [1:19:24<6:56:21, 5.85s/it]
64%|██████▍ | 7685/11952 [1:19:30<6:54:50, 5.83s/it]
{'loss': 0.474, 'learning_rate': 5.972860379908784e-06, 'epoch': 0.64}
+
64%|██████▍ | 7685/11952 [1:19:30<6:54:50, 5.83s/it]
64%|██████▍ | 7686/11952 [1:19:36<6:57:14, 5.87s/it]
{'loss': 0.4732, 'learning_rate': 5.970380081799254e-06, 'epoch': 0.64}
+
64%|██████▍ | 7686/11952 [1:19:36<6:57:14, 5.87s/it]
64%|██████▍ | 7687/11952 [1:19:42<6:59:08, 5.90s/it]
{'loss': 0.4832, 'learning_rate': 5.967900079608247e-06, 'epoch': 0.64}
+
64%|██████▍ | 7687/11952 [1:19:42<6:59:08, 5.90s/it]
64%|██████▍ | 7688/11952 [1:19:48<6:58:30, 5.89s/it]
{'loss': 0.4749, 'learning_rate': 5.965420373517892e-06, 'epoch': 0.64}
+
64%|██████▍ | 7688/11952 [1:19:48<6:58:30, 5.89s/it]
64%|██████▍ | 7689/11952 [1:19:54<7:06:55, 6.01s/it]
{'loss': 0.4943, 'learning_rate': 5.96294096371028e-06, 'epoch': 0.64}
+
64%|██████▍ | 7689/11952 [1:19:54<7:06:55, 6.01s/it]
64%|██████▍ | 7690/11952 [1:20:00<7:01:03, 5.93s/it]
{'loss': 0.4747, 'learning_rate': 5.960461850367496e-06, 'epoch': 0.64}
+
64%|██████▍ | 7690/11952 [1:20:00<7:01:03, 5.93s/it]
64%|██████▍ | 7691/11952 [1:20:05<6:52:06, 5.80s/it]
{'loss': 0.4638, 'learning_rate': 5.9579830336715905e-06, 'epoch': 0.64}
+
64%|██████▍ | 7691/11952 [1:20:05<6:52:06, 5.80s/it]
64%|██████▍ | 7692/11952 [1:20:12<7:00:04, 5.92s/it]
{'loss': 0.4821, 'learning_rate': 5.9555045138046e-06, 'epoch': 0.64}
+
64%|██████▍ | 7692/11952 [1:20:12<7:00:04, 5.92s/it]
64%|██████▍ | 7693/11952 [1:20:18<7:04:37, 5.98s/it]
{'loss': 0.4843, 'learning_rate': 5.953026290948534e-06, 'epoch': 0.64}
+
64%|██████▍ | 7693/11952 [1:20:18<7:04:37, 5.98s/it]
64%|██████▍ | 7694/11952 [1:20:24<7:05:37, 6.00s/it]
{'loss': 0.4715, 'learning_rate': 5.950548365285383e-06, 'epoch': 0.64}
+
64%|██████▍ | 7694/11952 [1:20:24<7:05:37, 6.00s/it]
64%|██████▍ | 7695/11952 [1:20:30<7:00:42, 5.93s/it]
{'loss': 0.4683, 'learning_rate': 5.948070736997118e-06, 'epoch': 0.64}
+
64%|██████▍ | 7695/11952 [1:20:30<7:00:42, 5.93s/it]
64%|██████▍ | 7696/11952 [1:20:35<6:54:23, 5.84s/it]
{'loss': 0.4626, 'learning_rate': 5.9455934062656874e-06, 'epoch': 0.64}
+
64%|██████▍ | 7696/11952 [1:20:35<6:54:23, 5.84s/it]
64%|██████▍ | 7697/11952 [1:20:41<6:58:09, 5.90s/it]
{'loss': 0.4571, 'learning_rate': 5.943116373273012e-06, 'epoch': 0.64}
+
64%|██████▍ | 7697/11952 [1:20:41<6:58:09, 5.90s/it]
64%|██████▍ | 7698/11952 [1:20:47<6:49:00, 5.77s/it]
{'loss': 0.48, 'learning_rate': 5.940639638200998e-06, 'epoch': 0.64}
+
64%|██████▍ | 7698/11952 [1:20:47<6:49:00, 5.77s/it]
64%|██████▍ | 7699/11952 [1:20:52<6:46:13, 5.73s/it]
{'loss': 0.4771, 'learning_rate': 5.938163201231523e-06, 'epoch': 0.64}
+
64%|██████▍ | 7699/11952 [1:20:52<6:46:13, 5.73s/it]7 AutoResumeHook: Checking whether to suspend...
+61 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...2
+ AutoResumeHook: Checking whether to suspend...
+
64%|██████▍ | 7700/11952 [1:20:58<6:45:03, 5.72s/it]5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4547, 'learning_rate': 5.935687062546449e-06, 'epoch': 0.64}
+
64%|██████▍ | 7700/11952 [1:20:58<6:45:03, 5.72s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
64%|██████▍ | 7701/11952 [1:21:26<14:38:24, 12.40s/it]
{'loss': 0.4689, 'learning_rate': 5.933211222327608e-06, 'epoch': 0.64}
+
64%|██████▍ | 7701/11952 [1:21:26<14:38:24, 12.40s/it]
64%|██████▍ | 7702/11952 [1:21:32<12:15:52, 10.39s/it]
{'loss': 0.4698, 'learning_rate': 5.930735680756825e-06, 'epoch': 0.64}
+
64%|██████▍ | 7702/11952 [1:21:32<12:15:52, 10.39s/it]
64%|██████▍ | 7703/11952 [1:21:37<10:36:56, 8.99s/it]
{'loss': 0.4458, 'learning_rate': 5.928260438015887e-06, 'epoch': 0.64}
+
64%|██████▍ | 7703/11952 [1:21:37<10:36:56, 8.99s/it]
64%|██████▍ | 7704/11952 [1:21:43<9:26:41, 8.00s/it]
{'loss': 0.4599, 'learning_rate': 5.925785494286566e-06, 'epoch': 0.64}
+
64%|██████▍ | 7704/11952 [1:21:43<9:26:41, 8.00s/it]
64%|██████▍ | 7705/11952 [1:21:49<8:35:50, 7.29s/it]
{'loss': 0.4897, 'learning_rate': 5.923310849750614e-06, 'epoch': 0.64}
+
64%|██████▍ | 7705/11952 [1:21:49<8:35:50, 7.29s/it]
64%|██████▍ | 7706/11952 [1:21:54<8:00:38, 6.79s/it]
{'loss': 0.4731, 'learning_rate': 5.920836504589756e-06, 'epoch': 0.64}
+
64%|██████▍ | 7706/11952 [1:21:54<8:00:38, 6.79s/it]
64%|██████▍ | 7707/11952 [1:22:00<7:38:27, 6.48s/it]
{'loss': 0.4675, 'learning_rate': 5.9183624589856956e-06, 'epoch': 0.64}
+
64%|██████▍ | 7707/11952 [1:22:00<7:38:27, 6.48s/it]
64%|██████▍ | 7708/11952 [1:22:06<7:30:08, 6.36s/it]
{'loss': 0.4822, 'learning_rate': 5.915888713120124e-06, 'epoch': 0.64}
+
64%|██████▍ | 7708/11952 [1:22:06<7:30:08, 6.36s/it]
64%|██████▍ | 7709/11952 [1:22:12<7:15:45, 6.16s/it]
{'loss': 0.4777, 'learning_rate': 5.913415267174696e-06, 'epoch': 0.64}
+
64%|██████▍ | 7709/11952 [1:22:12<7:15:45, 6.16s/it]
65%|██████▍ | 7710/11952 [1:22:18<7:09:40, 6.08s/it]
{'loss': 0.4775, 'learning_rate': 5.910942121331054e-06, 'epoch': 0.65}
+
65%|██████▍ | 7710/11952 [1:22:18<7:09:40, 6.08s/it]
65%|██████▍ | 7711/11952 [1:22:24<7:04:40, 6.01s/it]
{'loss': 0.4773, 'learning_rate': 5.908469275770815e-06, 'epoch': 0.65}
+
65%|██████▍ | 7711/11952 [1:22:24<7:04:40, 6.01s/it]
65%|██████▍ | 7712/11952 [1:22:29<6:55:48, 5.88s/it]
{'loss': 0.4766, 'learning_rate': 5.905996730675575e-06, 'epoch': 0.65}
+
65%|██████▍ | 7712/11952 [1:22:29<6:55:48, 5.88s/it]
65%|██████▍ | 7713/11952 [1:22:35<6:59:19, 5.94s/it]
{'loss': 0.4699, 'learning_rate': 5.903524486226907e-06, 'epoch': 0.65}
+
65%|██████▍ | 7713/11952 [1:22:35<6:59:19, 5.94s/it]
65%|██████▍ | 7714/11952 [1:22:41<6:58:59, 5.93s/it]
{'loss': 0.4748, 'learning_rate': 5.901052542606358e-06, 'epoch': 0.65}
+
65%|██████▍ | 7714/11952 [1:22:41<6:58:59, 5.93s/it]
65%|██████▍ | 7715/11952 [1:22:47<6:57:33, 5.91s/it]
{'loss': 0.4859, 'learning_rate': 5.898580899995463e-06, 'epoch': 0.65}
+
65%|██████▍ | 7715/11952 [1:22:47<6:57:33, 5.91s/it]
65%|██████▍ | 7716/11952 [1:22:53<6:52:54, 5.85s/it]
{'loss': 0.4632, 'learning_rate': 5.896109558575731e-06, 'epoch': 0.65}
+
65%|██████▍ | 7716/11952 [1:22:53<6:52:54, 5.85s/it]
65%|██████▍ | 7717/11952 [1:22:59<6:50:47, 5.82s/it]
{'loss': 0.4726, 'learning_rate': 5.893638518528643e-06, 'epoch': 0.65}
+
65%|██████▍ | 7717/11952 [1:22:59<6:50:47, 5.82s/it]
65%|██████▍ | 7718/11952 [1:23:04<6:47:13, 5.77s/it]
{'loss': 0.4775, 'learning_rate': 5.891167780035663e-06, 'epoch': 0.65}
+
65%|██████▍ | 7718/11952 [1:23:04<6:47:13, 5.77s/it]
65%|██████▍ | 7719/11952 [1:23:10<6:52:36, 5.85s/it]
{'loss': 0.4747, 'learning_rate': 5.888697343278229e-06, 'epoch': 0.65}
+
65%|██████▍ | 7719/11952 [1:23:10<6:52:36, 5.85s/it]
65%|██████▍ | 7720/11952 [1:23:16<6:52:02, 5.84s/it]
{'loss': 0.4684, 'learning_rate': 5.886227208437763e-06, 'epoch': 0.65}
+
65%|██████▍ | 7720/11952 [1:23:16<6:52:02, 5.84s/it]
65%|██████▍ | 7721/11952 [1:23:22<6:46:17, 5.76s/it]
{'loss': 0.4646, 'learning_rate': 5.8837573756956575e-06, 'epoch': 0.65}
+
65%|██████▍ | 7721/11952 [1:23:22<6:46:17, 5.76s/it]
65%|██████▍ | 7722/11952 [1:23:27<6:44:39, 5.74s/it]
{'loss': 0.4675, 'learning_rate': 5.881287845233292e-06, 'epoch': 0.65}
+
65%|██████▍ | 7722/11952 [1:23:27<6:44:39, 5.74s/it]
65%|██████▍ | 7723/11952 [1:23:33<6:50:54, 5.83s/it]
{'loss': 0.4882, 'learning_rate': 5.878818617232018e-06, 'epoch': 0.65}
+
65%|██████▍ | 7723/11952 [1:23:33<6:50:54, 5.83s/it]
65%|██████▍ | 7724/11952 [1:23:39<6:51:23, 5.84s/it]
{'loss': 0.4614, 'learning_rate': 5.876349691873162e-06, 'epoch': 0.65}
+
65%|██████▍ | 7724/11952 [1:23:39<6:51:23, 5.84s/it]
65%|██████▍ | 7725/11952 [1:23:45<6:48:19, 5.80s/it]
{'loss': 0.4633, 'learning_rate': 5.873881069338032e-06, 'epoch': 0.65}
+
65%|██████▍ | 7725/11952 [1:23:45<6:48:19, 5.80s/it]
65%|██████▍ | 7726/11952 [1:23:51<6:45:54, 5.76s/it]
{'loss': 0.4684, 'learning_rate': 5.871412749807917e-06, 'epoch': 0.65}
+
65%|██████▍ | 7726/11952 [1:23:51<6:45:54, 5.76s/it]
65%|██████▍ | 7727/11952 [1:23:56<6:43:43, 5.73s/it]
{'loss': 0.4677, 'learning_rate': 5.868944733464077e-06, 'epoch': 0.65}
+
65%|██████▍ | 7727/11952 [1:23:56<6:43:43, 5.73s/it]
65%|██████▍ | 7728/11952 [1:24:03<7:01:09, 5.98s/it]
{'loss': 0.4895, 'learning_rate': 5.866477020487748e-06, 'epoch': 0.65}
+
65%|██████▍ | 7728/11952 [1:24:03<7:01:09, 5.98s/it]
65%|██████▍ | 7729/11952 [1:24:09<6:56:49, 5.92s/it]
{'loss': 0.4697, 'learning_rate': 5.86400961106016e-06, 'epoch': 0.65}
+
65%|██████▍ | 7729/11952 [1:24:09<6:56:49, 5.92s/it]
65%|██████▍ | 7730/11952 [1:24:15<7:03:10, 6.01s/it]
{'loss': 0.4953, 'learning_rate': 5.8615425053625005e-06, 'epoch': 0.65}
+
65%|██████▍ | 7730/11952 [1:24:15<7:03:10, 6.01s/it]
65%|██████▍ | 7731/11952 [1:24:20<6:52:20, 5.86s/it]
{'loss': 0.464, 'learning_rate': 5.859075703575949e-06, 'epoch': 0.65}
+
65%|██████▍ | 7731/11952 [1:24:20<6:52:20, 5.86s/it]
65%|██████▍ | 7732/11952 [1:24:26<6:48:24, 5.81s/it]
{'loss': 0.4749, 'learning_rate': 5.856609205881654e-06, 'epoch': 0.65}
+
65%|██████▍ | 7732/11952 [1:24:26<6:48:24, 5.81s/it]
65%|██████▍ | 7733/11952 [1:24:32<6:54:45, 5.90s/it]
{'loss': 0.4698, 'learning_rate': 5.854143012460745e-06, 'epoch': 0.65}
+
65%|██████▍ | 7733/11952 [1:24:32<6:54:45, 5.90s/it]
65%|██████▍ | 7734/11952 [1:24:38<7:01:24, 5.99s/it]
{'loss': 0.4582, 'learning_rate': 5.851677123494326e-06, 'epoch': 0.65}
+
65%|██████▍ | 7734/11952 [1:24:38<7:01:24, 5.99s/it]
65%|██████▍ | 7735/11952 [1:24:45<7:13:33, 6.17s/it]
{'loss': 0.4782, 'learning_rate': 5.849211539163486e-06, 'epoch': 0.65}
+
65%|██████▍ | 7735/11952 [1:24:45<7:13:33, 6.17s/it]
65%|██████▍ | 7736/11952 [1:24:51<7:07:12, 6.08s/it]
{'loss': 0.4867, 'learning_rate': 5.846746259649288e-06, 'epoch': 0.65}
+
65%|██████▍ | 7736/11952 [1:24:51<7:07:12, 6.08s/it]
65%|██████▍ | 7737/11952 [1:24:57<7:04:22, 6.04s/it]
{'loss': 0.4811, 'learning_rate': 5.844281285132769e-06, 'epoch': 0.65}
+
65%|██████▍ | 7737/11952 [1:24:57<7:04:22, 6.04s/it]
65%|██████▍ | 7738/11952 [1:25:02<6:57:13, 5.94s/it]
{'loss': 0.4702, 'learning_rate': 5.841816615794948e-06, 'epoch': 0.65}
+
65%|██████▍ | 7738/11952 [1:25:02<6:57:13, 5.94s/it]
65%|██████▍ | 7739/11952 [1:25:08<6:57:15, 5.94s/it]
{'loss': 0.4787, 'learning_rate': 5.839352251816821e-06, 'epoch': 0.65}
+
65%|██████▍ | 7739/11952 [1:25:08<6:57:15, 5.94s/it]
65%|██████▍ | 7740/11952 [1:25:14<6:48:56, 5.83s/it]
{'loss': 0.4668, 'learning_rate': 5.836888193379359e-06, 'epoch': 0.65}
+
65%|██████▍ | 7740/11952 [1:25:14<6:48:56, 5.83s/it]
65%|██████▍ | 7741/11952 [1:25:20<6:47:03, 5.80s/it]
{'loss': 0.4868, 'learning_rate': 5.834424440663512e-06, 'epoch': 0.65}
+
65%|██████▍ | 7741/11952 [1:25:20<6:47:03, 5.80s/it]
65%|██████▍ | 7742/11952 [1:25:25<6:46:12, 5.79s/it]
{'loss': 0.4854, 'learning_rate': 5.831960993850203e-06, 'epoch': 0.65}
+
65%|██████▍ | 7742/11952 [1:25:25<6:46:12, 5.79s/it]
65%|██████▍ | 7743/11952 [1:25:31<6:41:03, 5.72s/it]
{'loss': 0.4697, 'learning_rate': 5.829497853120345e-06, 'epoch': 0.65}
+
65%|██████▍ | 7743/11952 [1:25:31<6:41:03, 5.72s/it]
65%|██████▍ | 7744/11952 [1:25:37<6:48:23, 5.82s/it]
{'loss': 0.4569, 'learning_rate': 5.827035018654821e-06, 'epoch': 0.65}
+
65%|██████▍ | 7744/11952 [1:25:37<6:48:23, 5.82s/it]
65%|██████▍ | 7745/11952 [1:25:43<6:47:43, 5.81s/it]
{'loss': 0.464, 'learning_rate': 5.824572490634488e-06, 'epoch': 0.65}
+
65%|██████▍ | 7745/11952 [1:25:43<6:47:43, 5.81s/it]
65%|██████▍ | 7746/11952 [1:25:49<6:51:56, 5.88s/it]
{'loss': 0.5041, 'learning_rate': 5.822110269240184e-06, 'epoch': 0.65}
+
65%|██████▍ | 7746/11952 [1:25:49<6:51:56, 5.88s/it]
65%|██████▍ | 7747/11952 [1:25:55<6:48:29, 5.83s/it]
{'loss': 0.4528, 'learning_rate': 5.819648354652725e-06, 'epoch': 0.65}
+
65%|██████▍ | 7747/11952 [1:25:55<6:48:29, 5.83s/it]
65%|██████▍ | 7748/11952 [1:26:01<6:52:04, 5.88s/it]
{'loss': 0.4847, 'learning_rate': 5.8171867470529e-06, 'epoch': 0.65}
+
65%|██████▍ | 7748/11952 [1:26:01<6:52:04, 5.88s/it]
65%|██████▍ | 7749/11952 [1:26:06<6:45:37, 5.79s/it]
{'loss': 0.4592, 'learning_rate': 5.8147254466214865e-06, 'epoch': 0.65}
+
65%|██████▍ | 7749/11952 [1:26:06<6:45:37, 5.79s/it]6 AutoResumeHook: Checking whether to suspend...
+35 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
65%|██████▍ | 7750/11952 [1:26:12<6:42:41, 5.75s/it]
{'loss': 0.4716, 'learning_rate': 5.812264453539228e-06, 'epoch': 0.65}
+
65%|██████▍ | 7750/11952 [1:26:12<6:42:41, 5.75s/it]
65%|██████▍ | 7751/11952 [1:26:18<6:44:28, 5.78s/it]
{'loss': 0.473, 'learning_rate': 5.809803767986851e-06, 'epoch': 0.65}
+
65%|██████▍ | 7751/11952 [1:26:18<6:44:28, 5.78s/it]
65%|██████▍ | 7752/11952 [1:26:24<6:50:30, 5.86s/it]
{'loss': 0.4787, 'learning_rate': 5.807343390145055e-06, 'epoch': 0.65}
+
65%|██████▍ | 7752/11952 [1:26:24<6:50:30, 5.86s/it]
65%|██████▍ | 7753/11952 [1:26:30<6:51:35, 5.88s/it]
{'loss': 0.4637, 'learning_rate': 5.80488332019452e-06, 'epoch': 0.65}
+
65%|██████▍ | 7753/11952 [1:26:30<6:51:35, 5.88s/it]
65%|██████▍ | 7754/11952 [1:26:36<6:52:47, 5.90s/it]
{'loss': 0.4845, 'learning_rate': 5.802423558315908e-06, 'epoch': 0.65}
+
65%|██████▍ | 7754/11952 [1:26:36<6:52:47, 5.90s/it]
65%|██████▍ | 7755/11952 [1:26:41<6:49:14, 5.85s/it]
{'loss': 0.4641, 'learning_rate': 5.799964104689847e-06, 'epoch': 0.65}
+
65%|██████▍ | 7755/11952 [1:26:41<6:49:14, 5.85s/it]
65%|██████▍ | 7756/11952 [1:26:47<6:44:12, 5.78s/it]
{'loss': 0.4473, 'learning_rate': 5.797504959496957e-06, 'epoch': 0.65}
+
65%|██████▍ | 7756/11952 [1:26:47<6:44:12, 5.78s/it]
65%|██████▍ | 7757/11952 [1:26:53<6:42:34, 5.76s/it]
{'loss': 0.4654, 'learning_rate': 5.795046122917823e-06, 'epoch': 0.65}
+
65%|██████▍ | 7757/11952 [1:26:53<6:42:34, 5.76s/it]
65%|██████▍ | 7758/11952 [1:26:58<6:40:07, 5.72s/it]
{'loss': 0.4761, 'learning_rate': 5.792587595133012e-06, 'epoch': 0.65}
+
65%|██████▍ | 7758/11952 [1:26:58<6:40:07, 5.72s/it]
65%|██████▍ | 7759/11952 [1:27:04<6:39:15, 5.71s/it]
{'loss': 0.4757, 'learning_rate': 5.790129376323068e-06, 'epoch': 0.65}
+
65%|██████▍ | 7759/11952 [1:27:04<6:39:15, 5.71s/it]
65%|██████▍ | 7760/11952 [1:27:10<6:47:53, 5.84s/it]
{'loss': 0.4667, 'learning_rate': 5.787671466668513e-06, 'epoch': 0.65}
+
65%|██████▍ | 7760/11952 [1:27:10<6:47:53, 5.84s/it]
65%|██████▍ | 7761/11952 [1:27:16<6:46:19, 5.82s/it]
{'loss': 0.5057, 'learning_rate': 5.785213866349844e-06, 'epoch': 0.65}
+
65%|██████▍ | 7761/11952 [1:27:16<6:46:19, 5.82s/it]
65%|██████▍ | 7762/11952 [1:27:22<6:45:31, 5.81s/it]
{'loss': 0.4902, 'learning_rate': 5.782756575547535e-06, 'epoch': 0.65}
+
65%|██████▍ | 7762/11952 [1:27:22<6:45:31, 5.81s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
65%|██████▍ | 7763/11952 [1:27:28<6:56:19, 5.96s/it]
{'loss': 0.4814, 'learning_rate': 5.780299594442047e-06, 'epoch': 0.65}
+
65%|██████▍ | 7763/11952 [1:27:28<6:56:19, 5.96s/it]
65%|██████▍ | 7764/11952 [1:27:34<6:49:23, 5.87s/it]
{'loss': 0.4806, 'learning_rate': 5.777842923213801e-06, 'epoch': 0.65}
+
65%|██████▍ | 7764/11952 [1:27:34<6:49:23, 5.87s/it]
65%|██████▍ | 7765/11952 [1:27:40<6:49:26, 5.87s/it]
{'loss': 0.4772, 'learning_rate': 5.775386562043212e-06, 'epoch': 0.65}
+
65%|██████▍ | 7765/11952 [1:27:40<6:49:26, 5.87s/it]
65%|██████▍ | 7766/11952 [1:27:45<6:43:57, 5.79s/it]
{'loss': 0.4515, 'learning_rate': 5.7729305111106645e-06, 'epoch': 0.65}
+
65%|██████▍ | 7766/11952 [1:27:45<6:43:57, 5.79s/it]
65%|██████▍ | 7767/11952 [1:27:51<6:51:58, 5.91s/it]
{'loss': 0.4629, 'learning_rate': 5.770474770596518e-06, 'epoch': 0.65}
+
65%|██████▍ | 7767/11952 [1:27:51<6:51:58, 5.91s/it]
65%|██████▍ | 7768/11952 [1:27:57<6:46:54, 5.84s/it]
{'loss': 0.4687, 'learning_rate': 5.768019340681113e-06, 'epoch': 0.65}
+
65%|██████▍ | 7768/11952 [1:27:57<6:46:54, 5.84s/it]
65%|██████▌ | 7769/11952 [1:28:03<6:45:11, 5.81s/it]
{'loss': 0.458, 'learning_rate': 5.765564221544759e-06, 'epoch': 0.65}
+
65%|██████▌ | 7769/11952 [1:28:03<6:45:11, 5.81s/it]
65%|██████▌ | 7770/11952 [1:28:09<6:50:27, 5.89s/it]
{'loss': 0.4801, 'learning_rate': 5.763109413367762e-06, 'epoch': 0.65}
+
65%|██████▌ | 7770/11952 [1:28:09<6:50:27, 5.89s/it]
65%|██████▌ | 7771/11952 [1:28:15<6:50:25, 5.89s/it]
{'loss': 0.5006, 'learning_rate': 5.760654916330388e-06, 'epoch': 0.65}
+
65%|██████▌ | 7771/11952 [1:28:15<6:50:25, 5.89s/it]
65%|██████▌ | 7772/11952 [1:28:21<6:49:37, 5.88s/it]
{'loss': 0.4343, 'learning_rate': 5.758200730612883e-06, 'epoch': 0.65}
+
65%|██████▌ | 7772/11952 [1:28:21<6:49:37, 5.88s/it]
65%|██████▌ | 7773/11952 [1:28:27<6:55:14, 5.96s/it]
{'loss': 0.4685, 'learning_rate': 5.75574685639547e-06, 'epoch': 0.65}
+
65%|██████▌ | 7773/11952 [1:28:27<6:55:14, 5.96s/it]
65%|██████▌ | 7774/11952 [1:28:33<7:02:50, 6.07s/it]
{'loss': 0.4836, 'learning_rate': 5.7532932938583575e-06, 'epoch': 0.65}
+
65%|██████▌ | 7774/11952 [1:28:33<7:02:50, 6.07s/it]
65%|██████▌ | 7775/11952 [1:28:39<7:00:10, 6.04s/it]
{'loss': 0.4585, 'learning_rate': 5.750840043181722e-06, 'epoch': 0.65}
+
65%|██████▌ | 7775/11952 [1:28:39<7:00:10, 6.04s/it]
65%|██████▌ | 7776/11952 [1:28:45<6:58:27, 6.01s/it]
{'loss': 0.4923, 'learning_rate': 5.7483871045457185e-06, 'epoch': 0.65}
+
65%|██████▌ | 7776/11952 [1:28:45<6:58:27, 6.01s/it]
65%|██████▌ | 7777/11952 [1:28:51<7:00:05, 6.04s/it]
{'loss': 0.4916, 'learning_rate': 5.745934478130484e-06, 'epoch': 0.65}
+
65%|██████▌ | 7777/11952 [1:28:51<7:00:05, 6.04s/it]
65%|██████▌ | 7778/11952 [1:28:57<6:58:07, 6.01s/it]
{'loss': 0.4803, 'learning_rate': 5.7434821641161285e-06, 'epoch': 0.65}
+
65%|██████▌ | 7778/11952 [1:28:57<6:58:07, 6.01s/it]
65%|██████▌ | 7779/11952 [1:29:03<6:50:51, 5.91s/it]
{'loss': 0.4627, 'learning_rate': 5.74103016268274e-06, 'epoch': 0.65}
+
65%|██████▌ | 7779/11952 [1:29:03<6:50:51, 5.91s/it]
65%|██████▌ | 7780/11952 [1:29:08<6:45:48, 5.84s/it]
{'loss': 0.4538, 'learning_rate': 5.738578474010379e-06, 'epoch': 0.65}
+
65%|██████▌ | 7780/11952 [1:29:08<6:45:48, 5.84s/it]
65%|██████▌ | 7781/11952 [1:29:14<6:51:07, 5.91s/it]
{'loss': 0.4798, 'learning_rate': 5.736127098279092e-06, 'epoch': 0.65}
+
65%|██████▌ | 7781/11952 [1:29:14<6:51:07, 5.91s/it]
65%|██████▌ | 7782/11952 [1:29:20<6:49:58, 5.90s/it]
{'loss': 0.4515, 'learning_rate': 5.733676035668891e-06, 'epoch': 0.65}
+
65%|██████▌ | 7782/11952 [1:29:20<6:49:58, 5.90s/it]
65%|██████▌ | 7783/11952 [1:29:26<6:50:48, 5.91s/it]
{'loss': 0.4924, 'learning_rate': 5.731225286359781e-06, 'epoch': 0.65}
+
65%|██████▌ | 7783/11952 [1:29:26<6:50:48, 5.91s/it]
65%|██████▌ | 7784/11952 [1:29:32<6:45:58, 5.84s/it]
{'loss': 0.468, 'learning_rate': 5.728774850531733e-06, 'epoch': 0.65}
+
65%|██████▌ | 7784/11952 [1:29:32<6:45:58, 5.84s/it]
65%|██████▌ | 7785/11952 [1:29:38<6:48:18, 5.88s/it]
{'loss': 0.4704, 'learning_rate': 5.726324728364688e-06, 'epoch': 0.65}
+
65%|██████▌ | 7785/11952 [1:29:38<6:48:18, 5.88s/it]
65%|██████▌ | 7786/11952 [1:29:44<6:43:38, 5.81s/it]
{'loss': 0.4524, 'learning_rate': 5.723874920038586e-06, 'epoch': 0.65}
+
65%|██████▌ | 7786/11952 [1:29:44<6:43:38, 5.81s/it]
65%|██████▌ | 7787/11952 [1:29:49<6:43:37, 5.81s/it]
{'loss': 0.4711, 'learning_rate': 5.721425425733322e-06, 'epoch': 0.65}
+
65%|██████▌ | 7787/11952 [1:29:49<6:43:37, 5.81s/it]
65%|██████▌ | 7788/11952 [1:29:55<6:38:58, 5.75s/it]
{'loss': 0.4704, 'learning_rate': 5.718976245628779e-06, 'epoch': 0.65}
+
65%|██████▌ | 7788/11952 [1:29:55<6:38:58, 5.75s/it]
65%|██████▌ | 7789/11952 [1:30:01<6:47:22, 5.87s/it]
{'loss': 0.475, 'learning_rate': 5.7165273799048105e-06, 'epoch': 0.65}
+
65%|██████▌ | 7789/11952 [1:30:01<6:47:22, 5.87s/it]
65%|██████▌ | 7790/11952 [1:30:07<6:40:57, 5.78s/it]
{'loss': 0.4684, 'learning_rate': 5.71407882874126e-06, 'epoch': 0.65}
+
65%|██████▌ | 7790/11952 [1:30:07<6:40:57, 5.78s/it]
65%|██████▌ | 7791/11952 [1:30:13<6:42:30, 5.80s/it]
{'loss': 0.4576, 'learning_rate': 5.711630592317933e-06, 'epoch': 0.65}
+
65%|██████▌ | 7791/11952 [1:30:13<6:42:30, 5.80s/it]
65%|██████▌ | 7792/11952 [1:30:18<6:41:58, 5.80s/it]
{'loss': 0.4713, 'learning_rate': 5.709182670814619e-06, 'epoch': 0.65}
+
65%|██████▌ | 7792/11952 [1:30:18<6:41:58, 5.80s/it]
65%|██████▌ | 7793/11952 [1:30:24<6:43:38, 5.82s/it]
{'loss': 0.4866, 'learning_rate': 5.706735064411082e-06, 'epoch': 0.65}
+
65%|██████▌ | 7793/11952 [1:30:24<6:43:38, 5.82s/it]
65%|██████▌ | 7794/11952 [1:30:30<6:44:17, 5.83s/it]
{'loss': 0.4498, 'learning_rate': 5.704287773287061e-06, 'epoch': 0.65}
+
65%|██████▌ | 7794/11952 [1:30:30<6:44:17, 5.83s/it]
65%|██████▌ | 7795/11952 [1:30:36<6:46:34, 5.87s/it]
{'loss': 0.4883, 'learning_rate': 5.701840797622284e-06, 'epoch': 0.65}
+
65%|██████▌ | 7795/11952 [1:30:36<6:46:34, 5.87s/it]
65%|██████▌ | 7796/11952 [1:30:42<6:50:30, 5.93s/it]
{'loss': 0.4998, 'learning_rate': 5.699394137596437e-06, 'epoch': 0.65}
+
65%|██████▌ | 7796/11952 [1:30:42<6:50:30, 5.93s/it]
65%|██████▌ | 7797/11952 [1:30:48<6:52:15, 5.95s/it]
{'loss': 0.4451, 'learning_rate': 5.6969477933892e-06, 'epoch': 0.65}
+
65%|██████▌ | 7797/11952 [1:30:48<6:52:15, 5.95s/it]
65%|██████▌ | 7798/11952 [1:30:54<6:53:17, 5.97s/it]
{'loss': 0.4563, 'learning_rate': 5.69450176518022e-06, 'epoch': 0.65}
+
65%|██████▌ | 7798/11952 [1:30:54<6:53:17, 5.97s/it]
65%|██████▌ | 7799/11952 [1:31:00<6:54:22, 5.99s/it]
{'loss': 0.4794, 'learning_rate': 5.692056053149122e-06, 'epoch': 0.65}
+
65%|██████▌ | 7799/11952 [1:31:00<6:54:22, 5.99s/it]1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+36 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
65%|██████▌ | 7800/11952 [1:31:06<6:49:16, 5.91s/it]
{'loss': 0.4454, 'learning_rate': 5.68961065747551e-06, 'epoch': 0.65}
+
65%|██████▌ | 7800/11952 [1:31:06<6:49:16, 5.91s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
65%|██████▌ | 7801/11952 [1:31:35<14:58:27, 12.99s/it]
{'loss': 0.4627, 'learning_rate': 5.687165578338962e-06, 'epoch': 0.65}
+
65%|██████▌ | 7801/11952 [1:31:35<14:58:27, 12.99s/it]
65%|██████▌ | 7802/11952 [1:31:41<12:25:57, 10.78s/it]
{'loss': 0.4788, 'learning_rate': 5.684720815919036e-06, 'epoch': 0.65}
+
65%|██████▌ | 7802/11952 [1:31:41<12:25:57, 10.78s/it]
65%|██████▌ | 7803/11952 [1:31:47<10:40:34, 9.26s/it]
{'loss': 0.4744, 'learning_rate': 5.682276370395261e-06, 'epoch': 0.65}
+
65%|██████▌ | 7803/11952 [1:31:47<10:40:34, 9.26s/it]
65%|██████▌ | 7804/11952 [1:31:53<9:31:58, 8.27s/it]
{'loss': 0.4643, 'learning_rate': 5.679832241947154e-06, 'epoch': 0.65}
+
65%|██████▌ | 7804/11952 [1:31:53<9:31:58, 8.27s/it]
65%|██████▌ | 7805/11952 [1:31:59<8:43:56, 7.58s/it]
{'loss': 0.4488, 'learning_rate': 5.677388430754196e-06, 'epoch': 0.65}
+
65%|██████▌ | 7805/11952 [1:31:59<8:43:56, 7.58s/it]
65%|██████▌ | 7806/11952 [1:32:04<8:03:38, 7.00s/it]
{'loss': 0.4716, 'learning_rate': 5.674944936995854e-06, 'epoch': 0.65}
+
65%|██████▌ | 7806/11952 [1:32:04<8:03:38, 7.00s/it]
65%|██████▌ | 7807/11952 [1:32:10<7:41:30, 6.68s/it]
{'loss': 0.4773, 'learning_rate': 5.672501760851568e-06, 'epoch': 0.65}
+
65%|██████▌ | 7807/11952 [1:32:10<7:41:30, 6.68s/it]
65%|██████▌ | 7808/11952 [1:32:16<7:21:24, 6.39s/it]
{'loss': 0.4811, 'learning_rate': 5.6700589025007535e-06, 'epoch': 0.65}
+
65%|██████▌ | 7808/11952 [1:32:16<7:21:24, 6.39s/it]
65%|██████▌ | 7809/11952 [1:32:22<7:04:51, 6.15s/it]
{'loss': 0.491, 'learning_rate': 5.667616362122803e-06, 'epoch': 0.65}
+
65%|██████▌ | 7809/11952 [1:32:22<7:04:51, 6.15s/it]
65%|██████▌ | 7810/11952 [1:32:27<6:58:27, 6.06s/it]
{'loss': 0.4657, 'learning_rate': 5.665174139897083e-06, 'epoch': 0.65}
+
65%|██████▌ | 7810/11952 [1:32:27<6:58:27, 6.06s/it]
65%|██████▌ | 7811/11952 [1:32:33<6:50:47, 5.95s/it]
{'loss': 0.4906, 'learning_rate': 5.662732236002949e-06, 'epoch': 0.65}
+
65%|██████▌ | 7811/11952 [1:32:33<6:50:47, 5.95s/it]
65%|██████▌ | 7812/11952 [1:32:39<6:43:08, 5.84s/it]
{'loss': 0.481, 'learning_rate': 5.660290650619719e-06, 'epoch': 0.65}
+
65%|██████▌ | 7812/11952 [1:32:39<6:43:08, 5.84s/it]
65%|██████▌ | 7813/11952 [1:32:44<6:39:59, 5.80s/it]
{'loss': 0.4664, 'learning_rate': 5.657849383926693e-06, 'epoch': 0.65}
+
65%|██████▌ | 7813/11952 [1:32:44<6:39:59, 5.80s/it]
65%|██████▌ | 7814/11952 [1:32:50<6:40:49, 5.81s/it]
{'loss': 0.4844, 'learning_rate': 5.655408436103149e-06, 'epoch': 0.65}
+
65%|██████▌ | 7814/11952 [1:32:50<6:40:49, 5.81s/it]
65%|██████▌ | 7815/11952 [1:32:56<6:35:27, 5.74s/it]
{'loss': 0.4665, 'learning_rate': 5.652967807328334e-06, 'epoch': 0.65}
+
65%|██████▌ | 7815/11952 [1:32:56<6:35:27, 5.74s/it]
65%|██████▌ | 7816/11952 [1:33:01<6:32:44, 5.70s/it]
{'loss': 0.4795, 'learning_rate': 5.6505274977814875e-06, 'epoch': 0.65}
+
65%|██████▌ | 7816/11952 [1:33:01<6:32:44, 5.70s/it]
65%|██████▌ | 7817/11952 [1:33:07<6:35:07, 5.73s/it]
{'loss': 0.4739, 'learning_rate': 5.648087507641806e-06, 'epoch': 0.65}
+
65%|██████▌ | 7817/11952 [1:33:07<6:35:07, 5.73s/it]
65%|██████▌ | 7818/11952 [1:33:13<6:32:35, 5.70s/it]
{'loss': 0.508, 'learning_rate': 5.6456478370884815e-06, 'epoch': 0.65}
+
65%|██████▌ | 7818/11952 [1:33:13<6:32:35, 5.70s/it]
65%|██████▌ | 7819/11952 [1:33:19<6:43:31, 5.86s/it]
{'loss': 0.4686, 'learning_rate': 5.643208486300669e-06, 'epoch': 0.65}
+
65%|██████▌ | 7819/11952 [1:33:19<6:43:31, 5.86s/it]
65%|██████▌ | 7820/11952 [1:33:25<6:37:28, 5.77s/it]
{'loss': 0.4812, 'learning_rate': 5.640769455457502e-06, 'epoch': 0.65}
+
65%|██████▌ | 7820/11952 [1:33:25<6:37:28, 5.77s/it]
65%|██████▌ | 7821/11952 [1:33:30<6:35:44, 5.75s/it]
{'loss': 0.4453, 'learning_rate': 5.6383307447380965e-06, 'epoch': 0.65}
+
65%|██████▌ | 7821/11952 [1:33:30<6:35:44, 5.75s/it]
65%|██████▌ | 7822/11952 [1:33:36<6:39:38, 5.81s/it]
{'loss': 0.4728, 'learning_rate': 5.635892354321539e-06, 'epoch': 0.65}
+
65%|██████▌ | 7822/11952 [1:33:36<6:39:38, 5.81s/it]
65%|██████▌ | 7823/11952 [1:33:42<6:42:15, 5.85s/it]
{'loss': 0.4947, 'learning_rate': 5.633454284386893e-06, 'epoch': 0.65}
+
65%|██████▌ | 7823/11952 [1:33:42<6:42:15, 5.85s/it]
65%|██████▌ | 7824/11952 [1:33:48<6:37:39, 5.78s/it]
{'loss': 0.4628, 'learning_rate': 5.631016535113204e-06, 'epoch': 0.65}
+
65%|██████▌ | 7824/11952 [1:33:48<6:37:39, 5.78s/it]
65%|██████▌ | 7825/11952 [1:33:53<6:34:20, 5.73s/it]
{'loss': 0.4684, 'learning_rate': 5.628579106679491e-06, 'epoch': 0.65}
+
65%|██████▌ | 7825/11952 [1:33:53<6:34:20, 5.73s/it]
65%|██████▌ | 7826/11952 [1:33:59<6:32:39, 5.71s/it]
{'loss': 0.4589, 'learning_rate': 5.62614199926474e-06, 'epoch': 0.65}
+
65%|██████▌ | 7826/11952 [1:33:59<6:32:39, 5.71s/it]
65%|██████▌ | 7827/11952 [1:34:05<6:30:57, 5.69s/it]
{'loss': 0.483, 'learning_rate': 5.623705213047933e-06, 'epoch': 0.65}
+
65%|██████▌ | 7827/11952 [1:34:05<6:30:57, 5.69s/it]
65%|██████▌ | 7828/11952 [1:34:10<6:29:30, 5.67s/it]
{'loss': 0.4802, 'learning_rate': 5.621268748208013e-06, 'epoch': 0.65}
+
65%|██████▌ | 7828/11952 [1:34:10<6:29:30, 5.67s/it]
66%|██████▌ | 7829/11952 [1:34:16<6:30:54, 5.69s/it]
{'loss': 0.4595, 'learning_rate': 5.618832604923904e-06, 'epoch': 0.66}
+
66%|██████▌ | 7829/11952 [1:34:16<6:30:54, 5.69s/it]
66%|██████▌ | 7830/11952 [1:34:22<6:35:22, 5.76s/it]
{'loss': 0.4818, 'learning_rate': 5.616396783374501e-06, 'epoch': 0.66}
+
66%|██████▌ | 7830/11952 [1:34:22<6:35:22, 5.76s/it]
66%|██████▌ | 7831/11952 [1:34:28<6:36:40, 5.78s/it]
{'loss': 0.4592, 'learning_rate': 5.613961283738692e-06, 'epoch': 0.66}
+
66%|██████▌ | 7831/11952 [1:34:28<6:36:40, 5.78s/it]
66%|██████▌ | 7832/11952 [1:34:34<6:44:31, 5.89s/it]
{'loss': 0.4717, 'learning_rate': 5.61152610619532e-06, 'epoch': 0.66}
+
66%|██████▌ | 7832/11952 [1:34:34<6:44:31, 5.89s/it]
66%|██████▌ | 7833/11952 [1:34:40<6:43:56, 5.88s/it]
{'loss': 0.4754, 'learning_rate': 5.60909125092322e-06, 'epoch': 0.66}
+
66%|██████▌ | 7833/11952 [1:34:40<6:43:56, 5.88s/it]
66%|██████▌ | 7834/11952 [1:34:46<6:41:48, 5.85s/it]
{'loss': 0.4837, 'learning_rate': 5.606656718101193e-06, 'epoch': 0.66}
+
66%|██████▌ | 7834/11952 [1:34:46<6:41:48, 5.85s/it]
66%|██████▌ | 7835/11952 [1:34:52<6:43:25, 5.88s/it]
{'loss': 0.4693, 'learning_rate': 5.604222507908021e-06, 'epoch': 0.66}
+
66%|██████▌ | 7835/11952 [1:34:52<6:43:25, 5.88s/it]
66%|██████▌ | 7836/11952 [1:34:57<6:40:57, 5.84s/it]
{'loss': 0.4601, 'learning_rate': 5.60178862052247e-06, 'epoch': 0.66}
+
66%|██████▌ | 7836/11952 [1:34:57<6:40:57, 5.84s/it]
66%|██████▌ | 7837/11952 [1:35:03<6:38:06, 5.80s/it]
{'loss': 0.5122, 'learning_rate': 5.599355056123263e-06, 'epoch': 0.66}
+
66%|██████▌ | 7837/11952 [1:35:03<6:38:06, 5.80s/it]
66%|██████▌ | 7838/11952 [1:35:09<6:38:23, 5.81s/it]
{'loss': 0.4721, 'learning_rate': 5.596921814889122e-06, 'epoch': 0.66}
+
66%|██████▌ | 7838/11952 [1:35:09<6:38:23, 5.81s/it]
66%|██████▌ | 7839/11952 [1:35:15<6:48:03, 5.95s/it]
{'loss': 0.481, 'learning_rate': 5.594488896998729e-06, 'epoch': 0.66}
+
66%|██████▌ | 7839/11952 [1:35:15<6:48:03, 5.95s/it]
66%|██████▌ | 7840/11952 [1:35:21<6:37:35, 5.80s/it]
{'loss': 0.4778, 'learning_rate': 5.592056302630748e-06, 'epoch': 0.66}
+
66%|██████▌ | 7840/11952 [1:35:21<6:37:35, 5.80s/it]
66%|██████▌ | 7841/11952 [1:35:26<6:36:20, 5.78s/it]
{'loss': 0.4752, 'learning_rate': 5.589624031963816e-06, 'epoch': 0.66}
+
66%|██████▌ | 7841/11952 [1:35:26<6:36:20, 5.78s/it]
66%|██████▌ | 7842/11952 [1:35:33<6:48:43, 5.97s/it]
{'loss': 0.4595, 'learning_rate': 5.5871920851765535e-06, 'epoch': 0.66}
+
66%|██████▌ | 7842/11952 [1:35:33<6:48:43, 5.97s/it]
66%|██████▌ | 7843/11952 [1:35:39<6:48:37, 5.97s/it]
{'loss': 0.4692, 'learning_rate': 5.584760462447548e-06, 'epoch': 0.66}
+
66%|██████▌ | 7843/11952 [1:35:39<6:48:37, 5.97s/it]
66%|██████▌ | 7844/11952 [1:35:45<6:48:20, 5.96s/it]
{'loss': 0.47, 'learning_rate': 5.582329163955367e-06, 'epoch': 0.66}
+
66%|██████▌ | 7844/11952 [1:35:45<6:48:20, 5.96s/it]
66%|██████▌ | 7845/11952 [1:35:50<6:44:42, 5.91s/it]
{'loss': 0.4761, 'learning_rate': 5.579898189878561e-06, 'epoch': 0.66}
+
66%|██████▌ | 7845/11952 [1:35:50<6:44:42, 5.91s/it]
66%|██████▌ | 7846/11952 [1:35:56<6:38:47, 5.83s/it]
{'loss': 0.473, 'learning_rate': 5.577467540395645e-06, 'epoch': 0.66}
+
66%|██████▌ | 7846/11952 [1:35:56<6:38:47, 5.83s/it]
66%|██████▌ | 7847/11952 [1:36:02<6:33:37, 5.75s/it]
{'loss': 0.4554, 'learning_rate': 5.575037215685119e-06, 'epoch': 0.66}
+
66%|██████▌ | 7847/11952 [1:36:02<6:33:37, 5.75s/it]
66%|██████▌ | 7848/11952 [1:36:07<6:32:12, 5.73s/it]
{'loss': 0.4822, 'learning_rate': 5.572607215925458e-06, 'epoch': 0.66}
+
66%|██████▌ | 7848/11952 [1:36:07<6:32:12, 5.73s/it]
66%|██████▌ | 7849/11952 [1:36:13<6:30:02, 5.70s/it]
{'loss': 0.4727, 'learning_rate': 5.570177541295107e-06, 'epoch': 0.66}
+
66%|██████▌ | 7849/11952 [1:36:13<6:30:02, 5.70s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+42 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
66%|██████▌ | 7850/11952 [1:36:19<6:39:35, 5.84s/it]
{'loss': 0.4875, 'learning_rate': 5.567748191972493e-06, 'epoch': 0.66}
+
66%|██████▌ | 7850/11952 [1:36:19<6:39:35, 5.84s/it]
66%|██████▌ | 7851/11952 [1:36:25<6:34:05, 5.77s/it]
{'loss': 0.4617, 'learning_rate': 5.565319168136012e-06, 'epoch': 0.66}
+
66%|██████▌ | 7851/11952 [1:36:25<6:34:05, 5.77s/it]
66%|██████▌ | 7852/11952 [1:36:31<6:36:47, 5.81s/it]
{'loss': 0.4695, 'learning_rate': 5.56289046996405e-06, 'epoch': 0.66}
+
66%|██████▌ | 7852/11952 [1:36:31<6:36:47, 5.81s/it]
66%|██████▌ | 7853/11952 [1:36:36<6:37:23, 5.82s/it]
{'loss': 0.4883, 'learning_rate': 5.5604620976349575e-06, 'epoch': 0.66}
+
66%|██████▌ | 7853/11952 [1:36:36<6:37:23, 5.82s/it]
66%|██████▌ | 7854/11952 [1:36:43<6:43:58, 5.91s/it]
{'loss': 0.4778, 'learning_rate': 5.558034051327061e-06, 'epoch': 0.66}
+
66%|██████▌ | 7854/11952 [1:36:43<6:43:58, 5.91s/it]
66%|██████▌ | 7855/11952 [1:36:48<6:42:24, 5.89s/it]
{'loss': 0.4758, 'learning_rate': 5.55560633121867e-06, 'epoch': 0.66}
+
66%|██████▌ | 7855/11952 [1:36:48<6:42:24, 5.89s/it]
66%|██████▌ | 7856/11952 [1:36:55<6:56:07, 6.10s/it]
{'loss': 0.4683, 'learning_rate': 5.553178937488061e-06, 'epoch': 0.66}
+
66%|██████▌ | 7856/11952 [1:36:55<6:56:07, 6.10s/it]
66%|██████▌ | 7857/11952 [1:37:01<6:58:30, 6.13s/it]
{'loss': 0.4598, 'learning_rate': 5.550751870313494e-06, 'epoch': 0.66}
+
66%|██████▌ | 7857/11952 [1:37:01<6:58:30, 6.13s/it]
66%|██████▌ | 7858/11952 [1:37:07<6:54:40, 6.08s/it]
{'loss': 0.5035, 'learning_rate': 5.548325129873209e-06, 'epoch': 0.66}
+
66%|██████▌ | 7858/11952 [1:37:07<6:54:40, 6.08s/it]
66%|██████▌ | 7859/11952 [1:37:13<6:51:25, 6.03s/it]
{'loss': 0.4741, 'learning_rate': 5.545898716345408e-06, 'epoch': 0.66}
+
66%|██████▌ | 7859/11952 [1:37:13<6:51:25, 6.03s/it]
66%|██████▌ | 7860/11952 [1:37:19<6:48:34, 5.99s/it]
{'loss': 0.4689, 'learning_rate': 5.543472629908282e-06, 'epoch': 0.66}
+
66%|██████▌ | 7860/11952 [1:37:19<6:48:34, 5.99s/it]
66%|██████▌ | 7861/11952 [1:37:25<6:47:30, 5.98s/it]
{'loss': 0.4767, 'learning_rate': 5.541046870739987e-06, 'epoch': 0.66}
+
66%|██████▌ | 7861/11952 [1:37:25<6:47:30, 5.98s/it]
66%|██████▌ | 7862/11952 [1:37:31<6:42:03, 5.90s/it]
{'loss': 0.4579, 'learning_rate': 5.538621439018666e-06, 'epoch': 0.66}
+
66%|██████▌ | 7862/11952 [1:37:31<6:42:03, 5.90s/it]
66%|██████▌ | 7863/11952 [1:37:36<6:37:17, 5.83s/it]
{'loss': 0.4773, 'learning_rate': 5.53619633492243e-06, 'epoch': 0.66}
+
66%|██████▌ | 7863/11952 [1:37:36<6:37:17, 5.83s/it]
66%|██████▌ | 7864/11952 [1:37:42<6:36:01, 5.81s/it]
{'loss': 0.4711, 'learning_rate': 5.533771558629365e-06, 'epoch': 0.66}
+
66%|██████▌ | 7864/11952 [1:37:42<6:36:01, 5.81s/it]
66%|██████▌ | 7865/11952 [1:37:48<6:37:59, 5.84s/it]
{'loss': 0.482, 'learning_rate': 5.531347110317544e-06, 'epoch': 0.66}
+
66%|██████▌ | 7865/11952 [1:37:48<6:37:59, 5.84s/it]
66%|██████▌ | 7866/11952 [1:37:54<6:32:20, 5.76s/it]
{'loss': 0.443, 'learning_rate': 5.528922990165004e-06, 'epoch': 0.66}
+
66%|██████▌ | 7866/11952 [1:37:54<6:32:20, 5.76s/it]
66%|██████▌ | 7867/11952 [1:37:59<6:31:48, 5.75s/it]
{'loss': 0.4557, 'learning_rate': 5.52649919834976e-06, 'epoch': 0.66}
+
66%|██████▌ | 7867/11952 [1:37:59<6:31:48, 5.75s/it]
66%|██████▌ | 7868/11952 [1:38:05<6:28:24, 5.71s/it]
{'loss': 0.4646, 'learning_rate': 5.524075735049812e-06, 'epoch': 0.66}
+
66%|██████▌ | 7868/11952 [1:38:05<6:28:24, 5.71s/it]
66%|██████▌ | 7869/11952 [1:38:11<6:26:21, 5.68s/it]
{'loss': 0.4632, 'learning_rate': 5.521652600443124e-06, 'epoch': 0.66}
+
66%|██████▌ | 7869/11952 [1:38:11<6:26:21, 5.68s/it]
66%|██████▌ | 7870/11952 [1:38:16<6:25:53, 5.67s/it]
{'loss': 0.4557, 'learning_rate': 5.519229794707643e-06, 'epoch': 0.66}
+
66%|██████▌ | 7870/11952 [1:38:16<6:25:53, 5.67s/it]
66%|██████▌ | 7871/11952 [1:38:22<6:23:45, 5.64s/it]
{'loss': 0.475, 'learning_rate': 5.516807318021286e-06, 'epoch': 0.66}
+
66%|██████▌ | 7871/11952 [1:38:22<6:23:45, 5.64s/it]
66%|██████▌ | 7872/11952 [1:38:28<6:30:07, 5.74s/it]
{'loss': 0.4735, 'learning_rate': 5.514385170561956e-06, 'epoch': 0.66}
+
66%|██████▌ | 7872/11952 [1:38:28<6:30:07, 5.74s/it]
66%|██████▌ | 7873/11952 [1:38:33<6:29:20, 5.73s/it]
{'loss': 0.4566, 'learning_rate': 5.511963352507521e-06, 'epoch': 0.66}
+
66%|██████▌ | 7873/11952 [1:38:33<6:29:20, 5.73s/it]
66%|██████▌ | 7874/11952 [1:38:40<6:37:10, 5.84s/it]
{'loss': 0.4755, 'learning_rate': 5.50954186403583e-06, 'epoch': 0.66}
+
66%|██████▌ | 7874/11952 [1:38:40<6:37:10, 5.84s/it]
66%|██████▌ | 7875/11952 [1:38:45<6:37:59, 5.86s/it]
{'loss': 0.4943, 'learning_rate': 5.507120705324709e-06, 'epoch': 0.66}
+
66%|██████▌ | 7875/11952 [1:38:45<6:37:59, 5.86s/it]
66%|██████▌ | 7876/11952 [1:38:51<6:34:26, 5.81s/it]
{'loss': 0.4656, 'learning_rate': 5.504699876551951e-06, 'epoch': 0.66}
+
66%|██████▌ | 7876/11952 [1:38:51<6:34:26, 5.81s/it]
66%|██████▌ | 7877/11952 [1:38:57<6:40:51, 5.90s/it]
{'loss': 0.4863, 'learning_rate': 5.502279377895341e-06, 'epoch': 0.66}
+
66%|██████▌ | 7877/11952 [1:38:57<6:40:51, 5.90s/it]
66%|██████▌ | 7878/11952 [1:39:03<6:42:33, 5.93s/it]
{'loss': 0.4729, 'learning_rate': 5.499859209532622e-06, 'epoch': 0.66}
+
66%|██████▌ | 7878/11952 [1:39:03<6:42:33, 5.93s/it]
66%|██████▌ | 7879/11952 [1:39:09<6:38:51, 5.88s/it]
{'loss': 0.4802, 'learning_rate': 5.497439371641528e-06, 'epoch': 0.66}
+
66%|██████▌ | 7879/11952 [1:39:09<6:38:51, 5.88s/it]
66%|██████▌ | 7880/11952 [1:39:15<6:32:59, 5.79s/it]
{'loss': 0.4667, 'learning_rate': 5.495019864399761e-06, 'epoch': 0.66}
+
66%|██████▌ | 7880/11952 [1:39:15<6:32:59, 5.79s/it]
66%|██████▌ | 7881/11952 [1:39:21<6:37:38, 5.86s/it]
{'loss': 0.4724, 'learning_rate': 5.492600687984997e-06, 'epoch': 0.66}
+
66%|██████▌ | 7881/11952 [1:39:21<6:37:38, 5.86s/it]
66%|██████▌ | 7882/11952 [1:39:27<6:41:40, 5.92s/it]
{'loss': 0.4769, 'learning_rate': 5.490181842574891e-06, 'epoch': 0.66}
+
66%|██████▌ | 7882/11952 [1:39:27<6:41:40, 5.92s/it]
66%|██████▌ | 7883/11952 [1:39:32<6:33:56, 5.81s/it]
{'loss': 0.4641, 'learning_rate': 5.487763328347071e-06, 'epoch': 0.66}
+
66%|██████▌ | 7883/11952 [1:39:32<6:33:56, 5.81s/it]
66%|██████▌ | 7884/11952 [1:39:38<6:35:57, 5.84s/it]
{'loss': 0.485, 'learning_rate': 5.485345145479147e-06, 'epoch': 0.66}
+
66%|██████▌ | 7884/11952 [1:39:38<6:35:57, 5.84s/it]
66%|██████▌ | 7885/11952 [1:39:44<6:33:46, 5.81s/it]
{'loss': 0.4727, 'learning_rate': 5.482927294148691e-06, 'epoch': 0.66}
+
66%|██████▌ | 7885/11952 [1:39:44<6:33:46, 5.81s/it]
66%|██████▌ | 7886/11952 [1:39:50<6:33:07, 5.80s/it]
{'loss': 0.4835, 'learning_rate': 5.480509774533271e-06, 'epoch': 0.66}
+
66%|██████▌ | 7886/11952 [1:39:50<6:33:07, 5.80s/it]
66%|██████▌ | 7887/11952 [1:39:56<6:38:25, 5.88s/it]
{'loss': 0.4731, 'learning_rate': 5.478092586810413e-06, 'epoch': 0.66}
+
66%|██████▌ | 7887/11952 [1:39:56<6:38:25, 5.88s/it]
66%|██████▌ | 7888/11952 [1:40:01<6:35:36, 5.84s/it]
{'loss': 0.4807, 'learning_rate': 5.47567573115763e-06, 'epoch': 0.66}
+
66%|██████▌ | 7888/11952 [1:40:01<6:35:36, 5.84s/it]
66%|██████▌ | 7889/11952 [1:40:07<6:38:51, 5.89s/it]
{'loss': 0.4883, 'learning_rate': 5.473259207752404e-06, 'epoch': 0.66}
+
66%|██████▌ | 7889/11952 [1:40:07<6:38:51, 5.89s/it]
66%|██████▌ | 7890/11952 [1:40:13<6:39:37, 5.90s/it]
{'loss': 0.4636, 'learning_rate': 5.470843016772194e-06, 'epoch': 0.66}
+
66%|██████▌ | 7890/11952 [1:40:13<6:39:37, 5.90s/it]
66%|██████▌ | 7891/11952 [1:40:19<6:42:02, 5.94s/it]
{'loss': 0.4616, 'learning_rate': 5.468427158394434e-06, 'epoch': 0.66}
+
66%|██████▌ | 7891/11952 [1:40:19<6:42:02, 5.94s/it]
66%|██████▌ | 7892/11952 [1:40:25<6:42:48, 5.95s/it]
{'loss': 0.4808, 'learning_rate': 5.466011632796531e-06, 'epoch': 0.66}
+
66%|██████▌ | 7892/11952 [1:40:25<6:42:48, 5.95s/it]
66%|██████▌ | 7893/11952 [1:40:31<6:37:35, 5.88s/it]
{'loss': 0.4907, 'learning_rate': 5.463596440155878e-06, 'epoch': 0.66}
+
66%|██████▌ | 7893/11952 [1:40:31<6:37:35, 5.88s/it]
66%|██████▌ | 7894/11952 [1:40:37<6:35:50, 5.85s/it]
{'loss': 0.4812, 'learning_rate': 5.461181580649837e-06, 'epoch': 0.66}
+
66%|██████▌ | 7894/11952 [1:40:37<6:35:50, 5.85s/it]
66%|██████▌ | 7895/11952 [1:40:43<6:36:29, 5.86s/it]
{'loss': 0.4711, 'learning_rate': 5.4587670544557404e-06, 'epoch': 0.66}
+
66%|██████▌ | 7895/11952 [1:40:43<6:36:29, 5.86s/it]
66%|██████▌ | 7896/11952 [1:40:49<6:39:05, 5.90s/it]
{'loss': 0.4735, 'learning_rate': 5.456352861750904e-06, 'epoch': 0.66}
+
66%|██████▌ | 7896/11952 [1:40:49<6:39:05, 5.90s/it]
66%|██████▌ | 7897/11952 [1:40:55<6:35:52, 5.86s/it]
{'loss': 0.4667, 'learning_rate': 5.453939002712611e-06, 'epoch': 0.66}
+
66%|██████▌ | 7897/11952 [1:40:55<6:35:52, 5.86s/it]
66%|██████▌ | 7898/11952 [1:41:00<6:32:52, 5.81s/it]
{'loss': 0.4629, 'learning_rate': 5.451525477518133e-06, 'epoch': 0.66}
+
66%|██████▌ | 7898/11952 [1:41:00<6:32:52, 5.81s/it]
66%|██████▌ | 7899/11952 [1:41:06<6:36:14, 5.87s/it]
{'loss': 0.4739, 'learning_rate': 5.4491122863447e-06, 'epoch': 0.66}
+
66%|██████▌ | 7899/11952 [1:41:06<6:36:14, 5.87s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
+
66%|██████▌ | 7900/11952 [1:41:12<6:37:03, 5.88s/it]
{'loss': 0.4901, 'learning_rate': 5.446699429369538e-06, 'epoch': 0.66}
+
66%|██████▌ | 7900/11952 [1:41:12<6:37:03, 5.88s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-7900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
66%|██████▌ | 7901/11952 [1:41:41<14:23:47, 12.79s/it]
{'loss': 0.4603, 'learning_rate': 5.444286906769831e-06, 'epoch': 0.66}
+
66%|██████▌ | 7901/11952 [1:41:41<14:23:47, 12.79s/it]
66%|██████▌ | 7902/11952 [1:41:47<12:07:23, 10.78s/it]
{'loss': 0.474, 'learning_rate': 5.441874718722744e-06, 'epoch': 0.66}
+
66%|██████▌ | 7902/11952 [1:41:47<12:07:23, 10.78s/it]
66%|██████▌ | 7903/11952 [1:41:53<10:25:43, 9.27s/it]
{'loss': 0.4659, 'learning_rate': 5.439462865405419e-06, 'epoch': 0.66}
+
66%|██████▌ | 7903/11952 [1:41:53<10:25:43, 9.27s/it]
66%|██████▌ | 7904/11952 [1:41:59<9:19:15, 8.29s/it]
{'loss': 0.4519, 'learning_rate': 5.437051346994973e-06, 'epoch': 0.66}
+
66%|██████▌ | 7904/11952 [1:41:59<9:19:15, 8.29s/it]
66%|██████▌ | 7905/11952 [1:42:05<8:30:12, 7.56s/it]
{'loss': 0.4696, 'learning_rate': 5.434640163668494e-06, 'epoch': 0.66}
+
66%|██████▌ | 7905/11952 [1:42:05<8:30:12, 7.56s/it]
66%|██████▌ | 7906/11952 [1:42:11<8:02:05, 7.15s/it]
{'loss': 0.5035, 'learning_rate': 5.432229315603054e-06, 'epoch': 0.66}
+
66%|██████▌ | 7906/11952 [1:42:11<8:02:05, 7.15s/it]
66%|██████▌ | 7907/11952 [1:42:17<7:36:48, 6.78s/it]
{'loss': 0.4653, 'learning_rate': 5.429818802975697e-06, 'epoch': 0.66}
+
66%|██████▌ | 7907/11952 [1:42:17<7:36:48, 6.78s/it]
66%|██████▌ | 7908/11952 [1:42:23<7:18:44, 6.51s/it]
{'loss': 0.473, 'learning_rate': 5.427408625963434e-06, 'epoch': 0.66}
+
66%|██████▌ | 7908/11952 [1:42:23<7:18:44, 6.51s/it]
66%|██████▌ | 7909/11952 [1:42:29<7:03:59, 6.29s/it]
{'loss': 0.5055, 'learning_rate': 5.424998784743266e-06, 'epoch': 0.66}
+
66%|██████▌ | 7909/11952 [1:42:29<7:03:59, 6.29s/it]
66%|██████▌ | 7910/11952 [1:42:34<6:56:52, 6.19s/it]
{'loss': 0.4932, 'learning_rate': 5.4225892794921585e-06, 'epoch': 0.66}
+
66%|██████▌ | 7910/11952 [1:42:34<6:56:52, 6.19s/it]
66%|██████▌ | 7911/11952 [1:42:40<6:44:55, 6.01s/it]
{'loss': 0.4689, 'learning_rate': 5.420180110387056e-06, 'epoch': 0.66}
+
66%|██████▌ | 7911/11952 [1:42:40<6:44:55, 6.01s/it]
66%|██████▌ | 7912/11952 [1:42:46<6:35:30, 5.87s/it]
{'loss': 0.4671, 'learning_rate': 5.417771277604873e-06, 'epoch': 0.66}
+
66%|██████▌ | 7912/11952 [1:42:46<6:35:30, 5.87s/it]
66%|██████▌ | 7913/11952 [1:42:51<6:33:20, 5.84s/it]
{'loss': 0.4679, 'learning_rate': 5.4153627813225114e-06, 'epoch': 0.66}
+
66%|██████▌ | 7913/11952 [1:42:51<6:33:20, 5.84s/it]
66%|██████▌ | 7914/11952 [1:42:57<6:31:02, 5.81s/it]
{'loss': 0.4852, 'learning_rate': 5.412954621716839e-06, 'epoch': 0.66}
+
66%|██████▌ | 7914/11952 [1:42:57<6:31:02, 5.81s/it]
66%|██████▌ | 7915/11952 [1:43:03<6:31:54, 5.82s/it]
{'loss': 0.4746, 'learning_rate': 5.410546798964701e-06, 'epoch': 0.66}
+
66%|██████▌ | 7915/11952 [1:43:03<6:31:54, 5.82s/it]
66%|██████▌ | 7916/11952 [1:43:09<6:26:50, 5.75s/it]
{'loss': 0.4582, 'learning_rate': 5.408139313242916e-06, 'epoch': 0.66}
+
66%|██████▌ | 7916/11952 [1:43:09<6:26:50, 5.75s/it]
66%|██████▌ | 7917/11952 [1:43:14<6:24:49, 5.72s/it]
{'loss': 0.4603, 'learning_rate': 5.405732164728276e-06, 'epoch': 0.66}
+
66%|██████▌ | 7917/11952 [1:43:14<6:24:49, 5.72s/it]
66%|██████▌ | 7918/11952 [1:43:20<6:32:35, 5.84s/it]
{'loss': 0.4852, 'learning_rate': 5.4033253535975635e-06, 'epoch': 0.66}
+
66%|██████▌ | 7918/11952 [1:43:20<6:32:35, 5.84s/it]
66%|██████▋ | 7919/11952 [1:43:26<6:28:30, 5.78s/it]
{'loss': 0.4561, 'learning_rate': 5.400918880027513e-06, 'epoch': 0.66}
+
66%|██████▋ | 7919/11952 [1:43:26<6:28:30, 5.78s/it]
66%|██████▋ | 7920/11952 [1:43:32<6:31:12, 5.82s/it]
{'loss': 0.4665, 'learning_rate': 5.398512744194854e-06, 'epoch': 0.66}
+
66%|██████▋ | 7920/11952 [1:43:32<6:31:12, 5.82s/it]
66%|██████▋ | 7921/11952 [1:43:38<6:30:46, 5.82s/it]
{'loss': 0.4571, 'learning_rate': 5.3961069462762804e-06, 'epoch': 0.66}
+
66%|██████▋ | 7921/11952 [1:43:38<6:30:46, 5.82s/it]
66%|██████▋ | 7922/11952 [1:43:43<6:27:17, 5.77s/it]
{'loss': 0.4624, 'learning_rate': 5.3937014864484635e-06, 'epoch': 0.66}
+
66%|██████▋ | 7922/11952 [1:43:43<6:27:17, 5.77s/it]
66%|██████▋ | 7923/11952 [1:43:49<6:25:20, 5.74s/it]
{'loss': 0.4613, 'learning_rate': 5.39129636488805e-06, 'epoch': 0.66}
+
66%|██████▋ | 7923/11952 [1:43:49<6:25:20, 5.74s/it]
66%|██████▋ | 7924/11952 [1:43:55<6:27:41, 5.78s/it]
{'loss': 0.4828, 'learning_rate': 5.388891581771664e-06, 'epoch': 0.66}
+
66%|██████▋ | 7924/11952 [1:43:55<6:27:41, 5.78s/it]
66%|██████▋ | 7925/11952 [1:44:01<6:28:06, 5.78s/it]
{'loss': 0.4632, 'learning_rate': 5.3864871372759e-06, 'epoch': 0.66}
+
66%|██████▋ | 7925/11952 [1:44:01<6:28:06, 5.78s/it]
66%|██████▋ | 7926/11952 [1:44:07<6:36:20, 5.91s/it]
{'loss': 0.4565, 'learning_rate': 5.384083031577327e-06, 'epoch': 0.66}
+
66%|██████▋ | 7926/11952 [1:44:07<6:36:20, 5.91s/it]
66%|██████▋ | 7927/11952 [1:44:13<6:36:40, 5.91s/it]
{'loss': 0.4787, 'learning_rate': 5.381679264852503e-06, 'epoch': 0.66}
+
66%|██████▋ | 7927/11952 [1:44:13<6:36:40, 5.91s/it]
66%|██████▋ | 7928/11952 [1:44:19<6:34:02, 5.88s/it]
{'loss': 0.4624, 'learning_rate': 5.379275837277944e-06, 'epoch': 0.66}
+
66%|██████▋ | 7928/11952 [1:44:19<6:34:02, 5.88s/it]
66%|██████▋ | 7929/11952 [1:44:24<6:33:32, 5.87s/it]
{'loss': 0.4692, 'learning_rate': 5.3768727490301445e-06, 'epoch': 0.66}
+
66%|██████▋ | 7929/11952 [1:44:24<6:33:32, 5.87s/it]
66%|██████▋ | 7930/11952 [1:44:30<6:31:01, 5.83s/it]
{'loss': 0.454, 'learning_rate': 5.374470000285584e-06, 'epoch': 0.66}
+
66%|██████▋ | 7930/11952 [1:44:30<6:31:01, 5.83s/it]
66%|██████▋ | 7931/11952 [1:44:36<6:29:43, 5.82s/it]
{'loss': 0.4773, 'learning_rate': 5.3720675912207085e-06, 'epoch': 0.66}
+
66%|██████▋ | 7931/11952 [1:44:36<6:29:43, 5.82s/it]
66%|██████▋ | 7932/11952 [1:44:42<6:28:17, 5.80s/it]
{'loss': 0.4697, 'learning_rate': 5.369665522011938e-06, 'epoch': 0.66}
+
66%|██████▋ | 7932/11952 [1:44:42<6:28:17, 5.80s/it]
66%|██████▋ | 7933/11952 [1:44:48<6:33:54, 5.88s/it]
{'loss': 0.4758, 'learning_rate': 5.367263792835673e-06, 'epoch': 0.66}
+
66%|██████▋ | 7933/11952 [1:44:48<6:33:54, 5.88s/it]
66%|██████▋ | 7934/11952 [1:44:54<6:31:29, 5.85s/it]
{'loss': 0.4822, 'learning_rate': 5.3648624038682886e-06, 'epoch': 0.66}
+
66%|██████▋ | 7934/11952 [1:44:54<6:31:29, 5.85s/it]
66%|██████▋ | 7935/11952 [1:45:00<6:33:35, 5.88s/it]
{'loss': 0.4614, 'learning_rate': 5.362461355286129e-06, 'epoch': 0.66}
+
66%|██████▋ | 7935/11952 [1:45:00<6:33:35, 5.88s/it]
66%|██████▋ | 7936/11952 [1:45:05<6:29:20, 5.82s/it]
{'loss': 0.4877, 'learning_rate': 5.360060647265519e-06, 'epoch': 0.66}
+
66%|██████▋ | 7936/11952 [1:45:05<6:29:20, 5.82s/it]
66%|██████▋ | 7937/11952 [1:45:12<6:40:09, 5.98s/it]
{'loss': 0.4527, 'learning_rate': 5.357660279982757e-06, 'epoch': 0.66}
+
66%|██████▋ | 7937/11952 [1:45:12<6:40:09, 5.98s/it]
66%|██████▋ | 7938/11952 [1:45:17<6:30:47, 5.84s/it]
{'loss': 0.4733, 'learning_rate': 5.35526025361411e-06, 'epoch': 0.66}
+
66%|██████▋ | 7938/11952 [1:45:17<6:30:47, 5.84s/it]
66%|██████▋ | 7939/11952 [1:45:23<6:29:45, 5.83s/it]
{'loss': 0.4525, 'learning_rate': 5.352860568335835e-06, 'epoch': 0.66}
+
66%|██████▋ | 7939/11952 [1:45:23<6:29:45, 5.83s/it]
66%|██████▋ | 7940/11952 [1:45:29<6:29:38, 5.83s/it]
{'loss': 0.4608, 'learning_rate': 5.3504612243241474e-06, 'epoch': 0.66}
+
66%|██████▋ | 7940/11952 [1:45:29<6:29:38, 5.83s/it]
66%|██████▋ | 7941/11952 [1:45:35<6:29:17, 5.82s/it]
{'loss': 0.4853, 'learning_rate': 5.3480622217552524e-06, 'epoch': 0.66}
+
66%|██████▋ | 7941/11952 [1:45:35<6:29:17, 5.82s/it]
66%|██████▋ | 7942/11952 [1:45:40<6:29:16, 5.82s/it]
{'loss': 0.4678, 'learning_rate': 5.3456635608053186e-06, 'epoch': 0.66}
+
66%|██████▋ | 7942/11952 [1:45:40<6:29:16, 5.82s/it]
66%|██████▋ | 7943/11952 [1:45:46<6:29:32, 5.83s/it]
{'loss': 0.4678, 'learning_rate': 5.343265241650495e-06, 'epoch': 0.66}
+
66%|██████▋ | 7943/11952 [1:45:46<6:29:32, 5.83s/it]
66%|██████▋ | 7944/11952 [1:45:52<6:28:11, 5.81s/it]
{'loss': 0.471, 'learning_rate': 5.340867264466902e-06, 'epoch': 0.66}
+
66%|██████▋ | 7944/11952 [1:45:52<6:28:11, 5.81s/it]
66%|██████▋ | 7945/11952 [1:45:58<6:23:52, 5.75s/it]
{'loss': 0.4485, 'learning_rate': 5.338469629430638e-06, 'epoch': 0.66}
+
66%|██████▋ | 7945/11952 [1:45:58<6:23:52, 5.75s/it]
66%|██████▋ | 7946/11952 [1:46:03<6:22:08, 5.72s/it]
{'loss': 0.4902, 'learning_rate': 5.336072336717773e-06, 'epoch': 0.66}
+
66%|██████▋ | 7946/11952 [1:46:03<6:22:08, 5.72s/it]
66%|██████▋ | 7947/11952 [1:46:09<6:25:28, 5.77s/it]
{'loss': 0.47, 'learning_rate': 5.333675386504361e-06, 'epoch': 0.66}
+
66%|██████▋ | 7947/11952 [1:46:09<6:25:28, 5.77s/it]
66%|██████▋ | 7948/11952 [1:46:15<6:21:21, 5.71s/it]
{'loss': 0.4581, 'learning_rate': 5.33127877896642e-06, 'epoch': 0.66}
+
66%|██████▋ | 7948/11952 [1:46:15<6:21:21, 5.71s/it]
67%|██████▋ | 7949/11952 [1:46:21<6:32:05, 5.88s/it]
{'loss': 0.4655, 'learning_rate': 5.328882514279942e-06, 'epoch': 0.67}
+
67%|██████▋ | 7949/11952 [1:46:21<6:32:05, 5.88s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
67%|██████▋ | 7950/11952 [1:46:27<6:37:42, 5.96s/it]4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4873, 'learning_rate': 5.3264865926209076e-06, 'epoch': 0.67}
+
67%|██████▋ | 7950/11952 [1:46:27<6:37:42, 5.96s/it]
67%|██████▋ | 7951/11952 [1:46:33<6:34:53, 5.92s/it]
{'loss': 0.4545, 'learning_rate': 5.324091014165259e-06, 'epoch': 0.67}
+
67%|██████▋ | 7951/11952 [1:46:33<6:34:53, 5.92s/it]
67%|██████▋ | 7952/11952 [1:46:39<6:28:33, 5.83s/it]
{'loss': 0.4819, 'learning_rate': 5.3216957790889176e-06, 'epoch': 0.67}
+
67%|██████▋ | 7952/11952 [1:46:39<6:28:33, 5.83s/it]
67%|██████▋ | 7953/11952 [1:46:44<6:30:36, 5.86s/it]
{'loss': 0.4598, 'learning_rate': 5.319300887567777e-06, 'epoch': 0.67}
+
67%|██████▋ | 7953/11952 [1:46:44<6:30:36, 5.86s/it]
67%|██████▋ | 7954/11952 [1:46:50<6:25:48, 5.79s/it]
{'loss': 0.4577, 'learning_rate': 5.316906339777714e-06, 'epoch': 0.67}
+
67%|██████▋ | 7954/11952 [1:46:50<6:25:48, 5.79s/it]
67%|██████▋ | 7955/11952 [1:46:56<6:22:53, 5.75s/it]
{'loss': 0.4706, 'learning_rate': 5.31451213589457e-06, 'epoch': 0.67}
+
67%|██████▋ | 7955/11952 [1:46:56<6:22:53, 5.75s/it]
67%|██████▋ | 7956/11952 [1:47:02<6:25:01, 5.78s/it]
{'loss': 0.4746, 'learning_rate': 5.312118276094167e-06, 'epoch': 0.67}
+
67%|██████▋ | 7956/11952 [1:47:02<6:25:01, 5.78s/it]
67%|██████▋ | 7957/11952 [1:47:08<6:29:32, 5.85s/it]
{'loss': 0.4613, 'learning_rate': 5.3097247605522996e-06, 'epoch': 0.67}
+
67%|██████▋ | 7957/11952 [1:47:08<6:29:32, 5.85s/it]
67%|██████▋ | 7958/11952 [1:47:13<6:27:54, 5.83s/it]
{'loss': 0.469, 'learning_rate': 5.307331589444737e-06, 'epoch': 0.67}
+
67%|██████▋ | 7958/11952 [1:47:13<6:27:54, 5.83s/it]
67%|██████▋ | 7959/11952 [1:47:19<6:26:39, 5.81s/it]
{'loss': 0.4634, 'learning_rate': 5.304938762947221e-06, 'epoch': 0.67}
+
67%|██████▋ | 7959/11952 [1:47:19<6:26:39, 5.81s/it]
67%|██████▋ | 7960/11952 [1:47:25<6:31:07, 5.88s/it]
{'loss': 0.4984, 'learning_rate': 5.3025462812354744e-06, 'epoch': 0.67}
+
67%|██████▋ | 7960/11952 [1:47:25<6:31:07, 5.88s/it]
67%|██████▋ | 7961/11952 [1:47:31<6:27:13, 5.82s/it]
{'loss': 0.4598, 'learning_rate': 5.300154144485194e-06, 'epoch': 0.67}
+
67%|██████▋ | 7961/11952 [1:47:31<6:27:13, 5.82s/it]
67%|██████▋ | 7962/11952 [1:47:36<6:22:23, 5.75s/it]
{'loss': 0.448, 'learning_rate': 5.297762352872044e-06, 'epoch': 0.67}
+
67%|██████▋ | 7962/11952 [1:47:36<6:22:23, 5.75s/it]
67%|██████▋ | 7963/11952 [1:47:42<6:26:11, 5.81s/it]
{'loss': 0.4654, 'learning_rate': 5.2953709065716704e-06, 'epoch': 0.67}
+
67%|██████▋ | 7963/11952 [1:47:42<6:26:11, 5.81s/it]
67%|██████▋ | 7964/11952 [1:47:48<6:28:08, 5.84s/it]
{'loss': 0.4789, 'learning_rate': 5.292979805759689e-06, 'epoch': 0.67}
+
67%|██████▋ | 7964/11952 [1:47:48<6:28:08, 5.84s/it]
67%|██████▋ | 7965/11952 [1:47:54<6:24:14, 5.78s/it]
{'loss': 0.4614, 'learning_rate': 5.290589050611692e-06, 'epoch': 0.67}
+
67%|██████▋ | 7965/11952 [1:47:54<6:24:14, 5.78s/it]
67%|██████▋ | 7966/11952 [1:48:00<6:29:09, 5.86s/it]
{'loss': 0.4794, 'learning_rate': 5.288198641303248e-06, 'epoch': 0.67}
+
67%|██████▋ | 7966/11952 [1:48:00<6:29:09, 5.86s/it]
67%|██████▋ | 7967/11952 [1:48:06<6:35:18, 5.95s/it]
{'loss': 0.454, 'learning_rate': 5.285808578009894e-06, 'epoch': 0.67}
+
67%|██████▋ | 7967/11952 [1:48:06<6:35:18, 5.95s/it]
67%|██████▋ | 7968/11952 [1:48:12<6:29:23, 5.86s/it]
{'loss': 0.4548, 'learning_rate': 5.283418860907155e-06, 'epoch': 0.67}
+
67%|██████▋ | 7968/11952 [1:48:12<6:29:23, 5.86s/it]
67%|██████▋ | 7969/11952 [1:48:18<6:35:51, 5.96s/it]
{'loss': 0.469, 'learning_rate': 5.281029490170515e-06, 'epoch': 0.67}
+
67%|██████▋ | 7969/11952 [1:48:18<6:35:51, 5.96s/it]
67%|██████▋ | 7970/11952 [1:48:24<6:36:19, 5.97s/it]
{'loss': 0.4638, 'learning_rate': 5.2786404659754375e-06, 'epoch': 0.67}
+
67%|██████▋ | 7970/11952 [1:48:24<6:36:19, 5.97s/it]
67%|██████▋ | 7971/11952 [1:48:30<6:32:35, 5.92s/it]
{'loss': 0.4919, 'learning_rate': 5.276251788497373e-06, 'epoch': 0.67}
+
67%|██████▋ | 7971/11952 [1:48:30<6:32:35, 5.92s/it]
67%|██████▋ | 7972/11952 [1:48:36<6:28:14, 5.85s/it]
{'loss': 0.4731, 'learning_rate': 5.273863457911728e-06, 'epoch': 0.67}
+
67%|██████▋ | 7972/11952 [1:48:36<6:28:14, 5.85s/it]
67%|██████▋ | 7973/11952 [1:48:41<6:30:25, 5.89s/it]
{'loss': 0.4618, 'learning_rate': 5.271475474393889e-06, 'epoch': 0.67}
+
67%|██████▋ | 7973/11952 [1:48:41<6:30:25, 5.89s/it]
67%|██████▋ | 7974/11952 [1:48:47<6:27:24, 5.84s/it]
{'loss': 0.4624, 'learning_rate': 5.269087838119229e-06, 'epoch': 0.67}
+
67%|██████▋ | 7974/11952 [1:48:47<6:27:24, 5.84s/it]
67%|██████▋ | 7975/11952 [1:48:53<6:28:34, 5.86s/it]
{'loss': 0.4752, 'learning_rate': 5.266700549263079e-06, 'epoch': 0.67}
+
67%|██████▋ | 7975/11952 [1:48:53<6:28:34, 5.86s/it]
67%|██████▋ | 7976/11952 [1:48:59<6:34:20, 5.95s/it]
{'loss': 0.4623, 'learning_rate': 5.264313608000755e-06, 'epoch': 0.67}
+
67%|██████▋ | 7976/11952 [1:48:59<6:34:20, 5.95s/it]
67%|██████▋ | 7977/11952 [1:49:05<6:34:32, 5.96s/it]
{'loss': 0.4629, 'learning_rate': 5.261927014507542e-06, 'epoch': 0.67}
+
67%|██████▋ | 7977/11952 [1:49:05<6:34:32, 5.96s/it]
67%|██████▋ | 7978/11952 [1:49:11<6:33:51, 5.95s/it]
{'loss': 0.457, 'learning_rate': 5.2595407689587006e-06, 'epoch': 0.67}
+
67%|██████▋ | 7978/11952 [1:49:11<6:33:51, 5.95s/it]
67%|██████▋ | 7979/11952 [1:49:17<6:27:07, 5.85s/it]
{'loss': 0.4797, 'learning_rate': 5.2571548715294664e-06, 'epoch': 0.67}
+
67%|██████▋ | 7979/11952 [1:49:17<6:27:07, 5.85s/it]
67%|██████▋ | 7980/11952 [1:49:22<6:22:00, 5.77s/it]
{'loss': 0.474, 'learning_rate': 5.254769322395053e-06, 'epoch': 0.67}
+
67%|██████▋ | 7980/11952 [1:49:22<6:22:00, 5.77s/it]
67%|██████▋ | 7981/11952 [1:49:29<6:28:56, 5.88s/it]
{'loss': 0.456, 'learning_rate': 5.2523841217306415e-06, 'epoch': 0.67}
+
67%|██████▋ | 7981/11952 [1:49:29<6:28:56, 5.88s/it]
67%|██████▋ | 7982/11952 [1:49:34<6:30:53, 5.91s/it]
{'loss': 0.454, 'learning_rate': 5.249999269711396e-06, 'epoch': 0.67}
+
67%|██████▋ | 7982/11952 [1:49:35<6:30:53, 5.91s/it]
67%|██████▋ | 7983/11952 [1:49:40<6:26:18, 5.84s/it]
{'loss': 0.4753, 'learning_rate': 5.247614766512449e-06, 'epoch': 0.67}
+
67%|██████▋ | 7983/11952 [1:49:40<6:26:18, 5.84s/it]
67%|██████▋ | 7984/11952 [1:49:46<6:24:03, 5.81s/it]
{'loss': 0.4781, 'learning_rate': 5.245230612308906e-06, 'epoch': 0.67}
+
67%|██████▋ | 7984/11952 [1:49:46<6:24:03, 5.81s/it]
67%|██████▋ | 7985/11952 [1:49:52<6:26:49, 5.85s/it]
{'loss': 0.4845, 'learning_rate': 5.24284680727585e-06, 'epoch': 0.67}
+
67%|██████▋ | 7985/11952 [1:49:52<6:26:49, 5.85s/it]
67%|██████▋ | 7986/11952 [1:49:58<6:31:14, 5.92s/it]
{'loss': 0.4856, 'learning_rate': 5.240463351588339e-06, 'epoch': 0.67}
+
67%|██████▋ | 7986/11952 [1:49:58<6:31:14, 5.92s/it]
67%|██████▋ | 7987/11952 [1:50:04<6:28:10, 5.87s/it]
{'loss': 0.4736, 'learning_rate': 5.238080245421397e-06, 'epoch': 0.67}
+
67%|██████▋ | 7987/11952 [1:50:04<6:28:10, 5.87s/it]
67%|██████▋ | 7988/11952 [1:50:09<6:25:22, 5.83s/it]
{'loss': 0.4765, 'learning_rate': 5.235697488950041e-06, 'epoch': 0.67}
+
67%|██████▋ | 7988/11952 [1:50:09<6:25:22, 5.83s/it]
67%|██████▋ | 7989/11952 [1:50:15<6:23:25, 5.81s/it]
{'loss': 0.4583, 'learning_rate': 5.233315082349245e-06, 'epoch': 0.67}
+
67%|██████▋ | 7989/11952 [1:50:15<6:23:25, 5.81s/it]
67%|██████▋ | 7990/11952 [1:50:21<6:22:03, 5.79s/it]
{'loss': 0.467, 'learning_rate': 5.2309330257939596e-06, 'epoch': 0.67}
+
67%|██████▋ | 7990/11952 [1:50:21<6:22:03, 5.79s/it]
67%|██████▋ | 7991/11952 [1:50:27<6:28:30, 5.89s/it]
{'loss': 0.4896, 'learning_rate': 5.22855131945912e-06, 'epoch': 0.67}
+
67%|██████▋ | 7991/11952 [1:50:27<6:28:30, 5.89s/it]
67%|██████▋ | 7992/11952 [1:50:33<6:22:53, 5.80s/it]
{'loss': 0.4487, 'learning_rate': 5.226169963519625e-06, 'epoch': 0.67}
+
67%|██████▋ | 7992/11952 [1:50:33<6:22:53, 5.80s/it]
67%|██████▋ | 7993/11952 [1:50:38<6:21:06, 5.78s/it]
{'loss': 0.4804, 'learning_rate': 5.223788958150353e-06, 'epoch': 0.67}
+
67%|██████▋ | 7993/11952 [1:50:38<6:21:06, 5.78s/it]
67%|██████▋ | 7994/11952 [1:50:44<6:22:11, 5.79s/it]
{'loss': 0.4854, 'learning_rate': 5.221408303526151e-06, 'epoch': 0.67}
+
67%|██████▋ | 7994/11952 [1:50:44<6:22:11, 5.79s/it]
67%|██████▋ | 7995/11952 [1:50:50<6:21:19, 5.78s/it]
{'loss': 0.4575, 'learning_rate': 5.219027999821851e-06, 'epoch': 0.67}
+
67%|██████▋ | 7995/11952 [1:50:50<6:21:19, 5.78s/it]
67%|██████▋ | 7996/11952 [1:50:56<6:20:29, 5.77s/it]
{'loss': 0.4674, 'learning_rate': 5.2166480472122475e-06, 'epoch': 0.67}
+
67%|██████▋ | 7996/11952 [1:50:56<6:20:29, 5.77s/it]
67%|██████▋ | 7997/11952 [1:51:02<6:27:31, 5.88s/it]
{'loss': 0.4684, 'learning_rate': 5.214268445872117e-06, 'epoch': 0.67}
+
67%|██████▋ | 7997/11952 [1:51:02<6:27:31, 5.88s/it]
67%|██████▋ | 7998/11952 [1:51:08<6:29:37, 5.91s/it]
{'loss': 0.4653, 'learning_rate': 5.211889195976207e-06, 'epoch': 0.67}
+
67%|██████▋ | 7998/11952 [1:51:08<6:29:37, 5.91s/it]
67%|██████▋ | 7999/11952 [1:51:13<6:23:23, 5.82s/it]
{'loss': 0.4578, 'learning_rate': 5.209510297699239e-06, 'epoch': 0.67}
+
67%|██████▋ | 7999/11952 [1:51:13<6:23:23, 5.82s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
67%|██████▋ | 8000/11952 [1:51:19<6:24:25, 5.84s/it]4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4672, 'learning_rate': 5.2071317512159055e-06, 'epoch': 0.67}
+
67%|██████▋ | 8000/11952 [1:51:19<6:24:25, 5.84s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
67%|██████▋ | 8001/11952 [1:51:50<14:33:38, 13.27s/it]
{'loss': 0.4591, 'learning_rate': 5.204753556700881e-06, 'epoch': 0.67}
+
67%|██████▋ | 8001/11952 [1:51:50<14:33:38, 13.27s/it]
67%|██████▋ | 8002/11952 [1:51:56<12:02:51, 10.98s/it]
{'loss': 0.4749, 'learning_rate': 5.202375714328814e-06, 'epoch': 0.67}
+
67%|██████▋ | 8002/11952 [1:51:56<12:02:51, 10.98s/it]
67%|██████▋ | 8003/11952 [1:52:02<10:25:04, 9.50s/it]
{'loss': 0.483, 'learning_rate': 5.199998224274321e-06, 'epoch': 0.67}
+
67%|██████▋ | 8003/11952 [1:52:02<10:25:04, 9.50s/it]
67%|██████▋ | 8004/11952 [1:52:08<9:16:41, 8.46s/it]
{'loss': 0.4896, 'learning_rate': 5.197621086711993e-06, 'epoch': 0.67}
+
67%|██████▋ | 8004/11952 [1:52:08<9:16:41, 8.46s/it]
67%|██████▋ | 8005/11952 [1:52:14<8:32:07, 7.78s/it]
{'loss': 0.4701, 'learning_rate': 5.195244301816398e-06, 'epoch': 0.67}
+
67%|██████▋ | 8005/11952 [1:52:14<8:32:07, 7.78s/it]
67%|██████▋ | 8006/11952 [1:52:20<7:50:11, 7.15s/it]
{'loss': 0.4645, 'learning_rate': 5.192867869762076e-06, 'epoch': 0.67}
+
67%|██████▋ | 8006/11952 [1:52:20<7:50:11, 7.15s/it]
67%|██████▋ | 8007/11952 [1:52:25<7:21:05, 6.71s/it]
{'loss': 0.4561, 'learning_rate': 5.1904917907235395e-06, 'epoch': 0.67}
+
67%|██████▋ | 8007/11952 [1:52:25<7:21:05, 6.71s/it]
67%|██████▋ | 8008/11952 [1:52:31<7:06:48, 6.49s/it]
{'loss': 0.4791, 'learning_rate': 5.188116064875286e-06, 'epoch': 0.67}
+
67%|██████▋ | 8008/11952 [1:52:31<7:06:48, 6.49s/it]
67%|██████▋ | 8009/11952 [1:52:37<6:51:55, 6.27s/it]
{'loss': 0.4797, 'learning_rate': 5.185740692391774e-06, 'epoch': 0.67}
+
67%|██████▋ | 8009/11952 [1:52:37<6:51:55, 6.27s/it]
67%|██████▋ | 8010/11952 [1:52:43<6:45:39, 6.17s/it]
{'loss': 0.4743, 'learning_rate': 5.183365673447442e-06, 'epoch': 0.67}
+
67%|██████▋ | 8010/11952 [1:52:43<6:45:39, 6.17s/it]
67%|██████▋ | 8011/11952 [1:52:49<6:41:36, 6.11s/it]
{'loss': 0.4652, 'learning_rate': 5.180991008216698e-06, 'epoch': 0.67}
+
67%|██████▋ | 8011/11952 [1:52:49<6:41:36, 6.11s/it]
67%|██████▋ | 8012/11952 [1:52:55<6:40:23, 6.10s/it]
{'loss': 0.4932, 'learning_rate': 5.178616696873935e-06, 'epoch': 0.67}
+
67%|██████▋ | 8012/11952 [1:52:55<6:40:23, 6.10s/it]
67%|██████▋ | 8013/11952 [1:53:01<6:40:31, 6.10s/it]
{'loss': 0.4888, 'learning_rate': 5.1762427395935065e-06, 'epoch': 0.67}
+
67%|██████▋ | 8013/11952 [1:53:01<6:40:31, 6.10s/it]
67%|██████▋ | 8014/11952 [1:53:07<6:40:11, 6.10s/it]
{'loss': 0.48, 'learning_rate': 5.173869136549744e-06, 'epoch': 0.67}
+
67%|██████▋ | 8014/11952 [1:53:07<6:40:11, 6.10s/it]
67%|██████▋ | 8015/11952 [1:53:13<6:32:45, 5.99s/it]
{'loss': 0.465, 'learning_rate': 5.171495887916962e-06, 'epoch': 0.67}
+
67%|██████▋ | 8015/11952 [1:53:13<6:32:45, 5.99s/it]
67%|██████▋ | 8016/11952 [1:53:19<6:31:22, 5.97s/it]
{'loss': 0.4495, 'learning_rate': 5.1691229938694396e-06, 'epoch': 0.67}
+
67%|██████▋ | 8016/11952 [1:53:19<6:31:22, 5.97s/it]
67%|██████▋ | 8017/11952 [1:53:25<6:27:08, 5.90s/it]
{'loss': 0.4761, 'learning_rate': 5.166750454581432e-06, 'epoch': 0.67}
+
67%|██████▋ | 8017/11952 [1:53:25<6:27:08, 5.90s/it]
67%|██████▋ | 8018/11952 [1:53:31<6:29:17, 5.94s/it]
{'loss': 0.4633, 'learning_rate': 5.164378270227167e-06, 'epoch': 0.67}
+
67%|██████▋ | 8018/11952 [1:53:31<6:29:17, 5.94s/it]
67%|██████▋ | 8019/11952 [1:53:36<6:23:23, 5.85s/it]
{'loss': 0.4559, 'learning_rate': 5.162006440980849e-06, 'epoch': 0.67}
+
67%|██████▋ | 8019/11952 [1:53:36<6:23:23, 5.85s/it]
67%|██████▋ | 8020/11952 [1:53:42<6:28:48, 5.93s/it]
{'loss': 0.4589, 'learning_rate': 5.159634967016653e-06, 'epoch': 0.67}
+
67%|██████▋ | 8020/11952 [1:53:42<6:28:48, 5.93s/it]
67%|██████▋ | 8021/11952 [1:53:48<6:30:15, 5.96s/it]
{'loss': 0.4933, 'learning_rate': 5.157263848508735e-06, 'epoch': 0.67}
+
67%|██████▋ | 8021/11952 [1:53:48<6:30:15, 5.96s/it]
67%|██████▋ | 8022/11952 [1:53:54<6:25:20, 5.88s/it]
{'loss': 0.4685, 'learning_rate': 5.154893085631213e-06, 'epoch': 0.67}
+
67%|██████▋ | 8022/11952 [1:53:54<6:25:20, 5.88s/it]
67%|██████▋ | 8023/11952 [1:54:00<6:30:42, 5.97s/it]
{'loss': 0.4722, 'learning_rate': 5.152522678558195e-06, 'epoch': 0.67}
+
67%|██████▋ | 8023/11952 [1:54:00<6:30:42, 5.97s/it]
67%|██████▋ | 8024/11952 [1:54:06<6:23:51, 5.86s/it]
{'loss': 0.473, 'learning_rate': 5.150152627463749e-06, 'epoch': 0.67}
+
67%|██████▋ | 8024/11952 [1:54:06<6:23:51, 5.86s/it]
67%|██████▋ | 8025/11952 [1:54:12<6:22:18, 5.84s/it]
{'loss': 0.4841, 'learning_rate': 5.1477829325219235e-06, 'epoch': 0.67}
+
67%|██████▋ | 8025/11952 [1:54:12<6:22:18, 5.84s/it]
67%|██████▋ | 8026/11952 [1:54:17<6:19:51, 5.81s/it]
{'loss': 0.4842, 'learning_rate': 5.1454135939067365e-06, 'epoch': 0.67}
+
67%|██████▋ | 8026/11952 [1:54:17<6:19:51, 5.81s/it]
67%|██████▋ | 8027/11952 [1:54:23<6:18:33, 5.79s/it]
{'loss': 0.4715, 'learning_rate': 5.143044611792183e-06, 'epoch': 0.67}
+
67%|██████▋ | 8027/11952 [1:54:23<6:18:33, 5.79s/it]
67%|██████▋ | 8028/11952 [1:54:29<6:20:08, 5.81s/it]
{'loss': 0.4933, 'learning_rate': 5.140675986352228e-06, 'epoch': 0.67}
+
67%|██████▋ | 8028/11952 [1:54:29<6:20:08, 5.81s/it]
67%|██████▋ | 8029/11952 [1:54:34<6:14:41, 5.73s/it]
{'loss': 0.4563, 'learning_rate': 5.13830771776082e-06, 'epoch': 0.67}
+
67%|██████▋ | 8029/11952 [1:54:34<6:14:41, 5.73s/it]
67%|██████▋ | 8030/11952 [1:54:40<6:11:24, 5.68s/it]
{'loss': 0.4535, 'learning_rate': 5.135939806191874e-06, 'epoch': 0.67}
+
67%|██████▋ | 8030/11952 [1:54:40<6:11:24, 5.68s/it]
67%|██████▋ | 8031/11952 [1:54:46<6:09:59, 5.66s/it]
{'loss': 0.4683, 'learning_rate': 5.133572251819272e-06, 'epoch': 0.67}
+
67%|██████▋ | 8031/11952 [1:54:46<6:09:59, 5.66s/it]
67%|██████▋ | 8032/11952 [1:54:52<6:18:14, 5.79s/it]
{'loss': 0.4829, 'learning_rate': 5.131205054816888e-06, 'epoch': 0.67}
+
67%|██████▋ | 8032/11952 [1:54:52<6:18:14, 5.79s/it]
67%|██████▋ | 8033/11952 [1:54:58<6:21:15, 5.84s/it]
{'loss': 0.4593, 'learning_rate': 5.128838215358553e-06, 'epoch': 0.67}
+
67%|██████▋ | 8033/11952 [1:54:58<6:21:15, 5.84s/it]
67%|██████▋ | 8034/11952 [1:55:03<6:19:39, 5.81s/it]
{'loss': 0.4618, 'learning_rate': 5.126471733618079e-06, 'epoch': 0.67}
+
67%|██████▋ | 8034/11952 [1:55:03<6:19:39, 5.81s/it]
67%|██████▋ | 8035/11952 [1:55:09<6:19:24, 5.81s/it]
{'loss': 0.4798, 'learning_rate': 5.124105609769246e-06, 'epoch': 0.67}
+
67%|██████▋ | 8035/11952 [1:55:09<6:19:24, 5.81s/it]
67%|██████▋ | 8036/11952 [1:55:15<6:22:19, 5.86s/it]
{'loss': 0.4731, 'learning_rate': 5.12173984398582e-06, 'epoch': 0.67}
+
67%|██████▋ | 8036/11952 [1:55:15<6:22:19, 5.86s/it]
67%|██████▋ | 8037/11952 [1:55:21<6:30:04, 5.98s/it]
{'loss': 0.4838, 'learning_rate': 5.119374436441531e-06, 'epoch': 0.67}
+
67%|██████▋ | 8037/11952 [1:55:21<6:30:04, 5.98s/it]
67%|██████▋ | 8038/11952 [1:55:27<6:28:36, 5.96s/it]
{'loss': 0.4896, 'learning_rate': 5.117009387310083e-06, 'epoch': 0.67}
+
67%|██████▋ | 8038/11952 [1:55:27<6:28:36, 5.96s/it]
67%|██████▋ | 8039/11952 [1:55:33<6:29:50, 5.98s/it]
{'loss': 0.4656, 'learning_rate': 5.114644696765157e-06, 'epoch': 0.67}
+
67%|██████▋ | 8039/11952 [1:55:33<6:29:50, 5.98s/it]
67%|██████▋ | 8040/11952 [1:55:39<6:24:28, 5.90s/it]
{'loss': 0.4628, 'learning_rate': 5.112280364980402e-06, 'epoch': 0.67}
+
67%|██████▋ | 8040/11952 [1:55:39<6:24:28, 5.90s/it]
67%|██████▋ | 8041/11952 [1:55:45<6:27:00, 5.94s/it]
{'loss': 0.469, 'learning_rate': 5.109916392129446e-06, 'epoch': 0.67}
+
67%|██████▋ | 8041/11952 [1:55:45<6:27:00, 5.94s/it]
67%|██████▋ | 8042/11952 [1:55:51<6:24:03, 5.89s/it]
{'loss': 0.4615, 'learning_rate': 5.1075527783858934e-06, 'epoch': 0.67}
+
67%|██████▋ | 8042/11952 [1:55:51<6:24:03, 5.89s/it]
67%|██████▋ | 8043/11952 [1:55:57<6:30:14, 5.99s/it]
{'loss': 0.4725, 'learning_rate': 5.105189523923312e-06, 'epoch': 0.67}
+
67%|██████▋ | 8043/11952 [1:55:57<6:30:14, 5.99s/it]
67%|██████▋ | 8044/11952 [1:56:03<6:26:50, 5.94s/it]
{'loss': 0.4601, 'learning_rate': 5.1028266289152565e-06, 'epoch': 0.67}
+
67%|██████▋ | 8044/11952 [1:56:03<6:26:50, 5.94s/it]
67%|██████▋ | 8045/11952 [1:56:09<6:28:19, 5.96s/it]
{'loss': 0.4656, 'learning_rate': 5.100464093535244e-06, 'epoch': 0.67}
+
67%|██████▋ | 8045/11952 [1:56:09<6:28:19, 5.96s/it]
67%|██████▋ | 8046/11952 [1:56:15<6:26:55, 5.94s/it]
{'loss': 0.4931, 'learning_rate': 5.098101917956771e-06, 'epoch': 0.67}
+
67%|██████▋ | 8046/11952 [1:56:15<6:26:55, 5.94s/it]
67%|██████▋ | 8047/11952 [1:56:21<6:20:29, 5.85s/it]
{'loss': 0.4619, 'learning_rate': 5.0957401023533036e-06, 'epoch': 0.67}
+
67%|██████▋ | 8047/11952 [1:56:21<6:20:29, 5.85s/it]
67%|██████▋ | 8048/11952 [1:56:26<6:22:56, 5.89s/it]
{'loss': 0.4562, 'learning_rate': 5.093378646898282e-06, 'epoch': 0.67}
+
67%|██████▋ | 8048/11952 [1:56:26<6:22:56, 5.89s/it]
67%|██████▋ | 8049/11952 [1:56:32<6:19:20, 5.83s/it]
{'loss': 0.4753, 'learning_rate': 5.091017551765127e-06, 'epoch': 0.67}
+
67%|██████▋ | 8049/11952 [1:56:32<6:19:20, 5.83s/it]61 AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
67%|██████▋ | 8050/11952 [1:56:38<6:18:51, 5.83s/it]34 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.475, 'learning_rate': 5.0886568171272265e-06, 'epoch': 0.67}
+
67%|██████▋ | 8050/11952 [1:56:38<6:18:51, 5.83s/it]
67%|██████▋ | 8051/11952 [1:56:44<6:20:34, 5.85s/it]
{'loss': 0.453, 'learning_rate': 5.08629644315794e-06, 'epoch': 0.67}
+
67%|██████▋ | 8051/11952 [1:56:44<6:20:34, 5.85s/it]
67%|██████▋ | 8052/11952 [1:56:50<6:20:08, 5.85s/it]
{'loss': 0.4629, 'learning_rate': 5.0839364300306016e-06, 'epoch': 0.67}
+
67%|██████▋ | 8052/11952 [1:56:50<6:20:08, 5.85s/it]
67%|██████▋ | 8053/11952 [1:56:55<6:17:04, 5.80s/it]
{'loss': 0.4749, 'learning_rate': 5.081576777918529e-06, 'epoch': 0.67}
+
67%|██████▋ | 8053/11952 [1:56:55<6:17:04, 5.80s/it]
67%|██████▋ | 8054/11952 [1:57:02<6:23:09, 5.90s/it]
{'loss': 0.4747, 'learning_rate': 5.079217486994999e-06, 'epoch': 0.67}
+
67%|██████▋ | 8054/11952 [1:57:02<6:23:09, 5.90s/it]
67%|██████▋ | 8055/11952 [1:57:07<6:17:11, 5.81s/it]
{'loss': 0.4711, 'learning_rate': 5.0768585574332675e-06, 'epoch': 0.67}
+
67%|██████▋ | 8055/11952 [1:57:07<6:17:11, 5.81s/it]
67%|██████▋ | 8056/11952 [1:57:13<6:15:45, 5.79s/it]
{'loss': 0.4655, 'learning_rate': 5.074499989406569e-06, 'epoch': 0.67}
+
67%|██████▋ | 8056/11952 [1:57:13<6:15:45, 5.79s/it]
67%|██████▋ | 8057/11952 [1:57:19<6:11:59, 5.73s/it]
{'loss': 0.4468, 'learning_rate': 5.072141783088107e-06, 'epoch': 0.67}
+
67%|██████▋ | 8057/11952 [1:57:19<6:11:59, 5.73s/it]
67%|██████▋ | 8058/11952 [1:57:24<6:08:26, 5.68s/it]
{'loss': 0.45, 'learning_rate': 5.069783938651054e-06, 'epoch': 0.67}
+
67%|██████▋ | 8058/11952 [1:57:24<6:08:26, 5.68s/it]
67%|██████▋ | 8059/11952 [1:57:30<6:16:18, 5.80s/it]
{'loss': 0.4939, 'learning_rate': 5.067426456268563e-06, 'epoch': 0.67}
+
67%|██████▋ | 8059/11952 [1:57:30<6:16:18, 5.80s/it]
67%|██████▋ | 8060/11952 [1:57:36<6:19:53, 5.86s/it]
{'loss': 0.4619, 'learning_rate': 5.065069336113756e-06, 'epoch': 0.67}
+
67%|██████▋ | 8060/11952 [1:57:36<6:19:53, 5.86s/it]
67%|██████▋ | 8061/11952 [1:57:42<6:21:38, 5.89s/it]
{'loss': 0.4636, 'learning_rate': 5.062712578359728e-06, 'epoch': 0.67}
+
67%|██████▋ | 8061/11952 [1:57:42<6:21:38, 5.89s/it]
67%|██████▋ | 8062/11952 [1:57:48<6:23:00, 5.91s/it]
{'loss': 0.4795, 'learning_rate': 5.060356183179556e-06, 'epoch': 0.67}
+
67%|██████▋ | 8062/11952 [1:57:48<6:23:00, 5.91s/it]
67%|██████▋ | 8063/11952 [1:57:54<6:19:06, 5.85s/it]
{'loss': 0.471, 'learning_rate': 5.058000150746276e-06, 'epoch': 0.67}
+
67%|██████▋ | 8063/11952 [1:57:54<6:19:06, 5.85s/it]
67%|██████▋ | 8064/11952 [1:57:59<6:13:51, 5.77s/it]
{'loss': 0.4677, 'learning_rate': 5.055644481232914e-06, 'epoch': 0.67}
+
67%|██████▋ | 8064/11952 [1:57:59<6:13:51, 5.77s/it]
67%|██████▋ | 8065/11952 [1:58:05<6:09:50, 5.71s/it]
{'loss': 0.4624, 'learning_rate': 5.0532891748124565e-06, 'epoch': 0.67}
+
67%|██████▋ | 8065/11952 [1:58:05<6:09:50, 5.71s/it]
67%|██████▋ | 8066/11952 [1:58:11<6:07:51, 5.68s/it]
{'loss': 0.4759, 'learning_rate': 5.050934231657867e-06, 'epoch': 0.67}
+
67%|██████▋ | 8066/11952 [1:58:11<6:07:51, 5.68s/it]
67%|██████▋ | 8067/11952 [1:58:17<6:16:17, 5.81s/it]
{'loss': 0.4778, 'learning_rate': 5.048579651942083e-06, 'epoch': 0.67}
+
67%|██████▋ | 8067/11952 [1:58:17<6:16:17, 5.81s/it]
68%|██████▊ | 8068/11952 [1:58:22<6:16:30, 5.82s/it]
{'loss': 0.4734, 'learning_rate': 5.046225435838015e-06, 'epoch': 0.68}
+
68%|██████▊ | 8068/11952 [1:58:22<6:16:30, 5.82s/it]
68%|██████▊ | 8069/11952 [1:58:28<6:16:51, 5.82s/it]
{'loss': 0.4746, 'learning_rate': 5.043871583518542e-06, 'epoch': 0.68}
+
68%|██████▊ | 8069/11952 [1:58:28<6:16:51, 5.82s/it]
68%|██████▊ | 8070/11952 [1:58:34<6:20:58, 5.89s/it]
{'loss': 0.4566, 'learning_rate': 5.04151809515653e-06, 'epoch': 0.68}
+
68%|██████▊ | 8070/11952 [1:58:34<6:20:58, 5.89s/it]
68%|██████▊ | 8071/11952 [1:58:40<6:14:44, 5.79s/it]
{'loss': 0.4637, 'learning_rate': 5.039164970924805e-06, 'epoch': 0.68}
+
68%|██████▊ | 8071/11952 [1:58:40<6:14:44, 5.79s/it]
68%|██████▊ | 8072/11952 [1:58:45<6:10:01, 5.72s/it]
{'loss': 0.453, 'learning_rate': 5.0368122109961716e-06, 'epoch': 0.68}
+
68%|██████▊ | 8072/11952 [1:58:45<6:10:01, 5.72s/it]
68%|██████▊ | 8073/11952 [1:58:51<6:07:54, 5.69s/it]
{'loss': 0.4528, 'learning_rate': 5.034459815543401e-06, 'epoch': 0.68}
+
68%|██████▊ | 8073/11952 [1:58:51<6:07:54, 5.69s/it]
68%|██████▊ | 8074/11952 [1:58:57<6:10:07, 5.73s/it]
{'loss': 0.4723, 'learning_rate': 5.032107784739253e-06, 'epoch': 0.68}
+
68%|██████▊ | 8074/11952 [1:58:57<6:10:07, 5.73s/it]
68%|██████▊ | 8075/11952 [1:59:03<6:14:19, 5.79s/it]
{'loss': 0.4791, 'learning_rate': 5.029756118756446e-06, 'epoch': 0.68}
+
68%|██████▊ | 8075/11952 [1:59:03<6:14:19, 5.79s/it]
68%|██████▊ | 8076/11952 [1:59:09<6:13:32, 5.78s/it]
{'loss': 0.4692, 'learning_rate': 5.027404817767672e-06, 'epoch': 0.68}
+
68%|██████▊ | 8076/11952 [1:59:09<6:13:32, 5.78s/it]
68%|██████▊ | 8077/11952 [1:59:14<6:08:25, 5.70s/it]
{'loss': 0.4452, 'learning_rate': 5.025053881945612e-06, 'epoch': 0.68}
+
68%|██████▊ | 8077/11952 [1:59:14<6:08:25, 5.70s/it]
68%|██████▊ | 8078/11952 [1:59:20<6:16:39, 5.83s/it]
{'loss': 0.4711, 'learning_rate': 5.0227033114629e-06, 'epoch': 0.68}
+
68%|██████▊ | 8078/11952 [1:59:20<6:16:39, 5.83s/it]
68%|██████▊ | 8079/11952 [1:59:26<6:15:35, 5.82s/it]
{'loss': 0.4609, 'learning_rate': 5.020353106492156e-06, 'epoch': 0.68}
+
68%|██████▊ | 8079/11952 [1:59:26<6:15:35, 5.82s/it]
68%|██████▊ | 8080/11952 [1:59:32<6:12:56, 5.78s/it]
{'loss': 0.4732, 'learning_rate': 5.018003267205969e-06, 'epoch': 0.68}
+
68%|██████▊ | 8080/11952 [1:59:32<6:12:56, 5.78s/it]
68%|██████▊ | 8081/11952 [1:59:37<6:11:24, 5.76s/it]
{'loss': 0.4574, 'learning_rate': 5.015653793776898e-06, 'epoch': 0.68}
+
68%|██████▊ | 8081/11952 [1:59:37<6:11:24, 5.76s/it]
68%|██████▊ | 8082/11952 [1:59:43<6:08:53, 5.72s/it]
{'loss': 0.4587, 'learning_rate': 5.013304686377478e-06, 'epoch': 0.68}
+
68%|██████▊ | 8082/11952 [1:59:43<6:08:53, 5.72s/it]
68%|██████▊ | 8083/11952 [1:59:49<6:09:45, 5.73s/it]
{'loss': 0.4708, 'learning_rate': 5.010955945180225e-06, 'epoch': 0.68}
+
68%|██████▊ | 8083/11952 [1:59:49<6:09:45, 5.73s/it]
68%|██████▊ | 8084/11952 [1:59:54<6:04:57, 5.66s/it]
{'loss': 0.4685, 'learning_rate': 5.008607570357612e-06, 'epoch': 0.68}
+
68%|██████▊ | 8084/11952 [1:59:54<6:04:57, 5.66s/it]
68%|██████▊ | 8085/11952 [2:00:00<6:05:19, 5.67s/it]
{'loss': 0.4661, 'learning_rate': 5.006259562082102e-06, 'epoch': 0.68}
+
68%|██████▊ | 8085/11952 [2:00:00<6:05:19, 5.67s/it]
68%|██████▊ | 8086/11952 [2:00:06<6:06:34, 5.69s/it]
{'loss': 0.4538, 'learning_rate': 5.003911920526119e-06, 'epoch': 0.68}
+
68%|██████▊ | 8086/11952 [2:00:06<6:06:34, 5.69s/it]
68%|██████▊ | 8087/11952 [2:00:12<6:08:18, 5.72s/it]
{'loss': 0.4543, 'learning_rate': 5.0015646458620645e-06, 'epoch': 0.68}
+
68%|██████▊ | 8087/11952 [2:00:12<6:08:18, 5.72s/it]
68%|██████▊ | 8088/11952 [2:00:17<6:10:06, 5.75s/it]
{'loss': 0.4777, 'learning_rate': 4.999217738262313e-06, 'epoch': 0.68}
+
68%|██████▊ | 8088/11952 [2:00:17<6:10:06, 5.75s/it]
68%|██████▊ | 8089/11952 [2:00:23<6:16:26, 5.85s/it]
{'loss': 0.4714, 'learning_rate': 4.996871197899207e-06, 'epoch': 0.68}
+
68%|██████▊ | 8089/11952 [2:00:23<6:16:26, 5.85s/it]
68%|██████▊ | 8090/11952 [2:00:29<6:14:18, 5.82s/it]
{'loss': 0.4666, 'learning_rate': 4.994525024945075e-06, 'epoch': 0.68}
+
68%|██████▊ | 8090/11952 [2:00:29<6:14:18, 5.82s/it]
68%|██████▊ | 8091/11952 [2:00:35<6:11:04, 5.77s/it]
{'loss': 0.4673, 'learning_rate': 4.992179219572204e-06, 'epoch': 0.68}
+
68%|██████▊ | 8091/11952 [2:00:35<6:11:04, 5.77s/it]
68%|██████▊ | 8092/11952 [2:00:41<6:19:17, 5.90s/it]
{'loss': 0.4602, 'learning_rate': 4.989833781952864e-06, 'epoch': 0.68}
+
68%|██████▊ | 8092/11952 [2:00:41<6:19:17, 5.90s/it]
68%|██████▊ | 8093/11952 [2:00:47<6:17:56, 5.88s/it]
{'loss': 0.4727, 'learning_rate': 4.987488712259288e-06, 'epoch': 0.68}
+
68%|██████▊ | 8093/11952 [2:00:47<6:17:56, 5.88s/it]
68%|██████▊ | 8094/11952 [2:00:52<6:11:28, 5.78s/it]
{'loss': 0.4598, 'learning_rate': 4.985144010663695e-06, 'epoch': 0.68}
+
68%|██████▊ | 8094/11952 [2:00:52<6:11:28, 5.78s/it]
68%|██████▊ | 8095/11952 [2:00:58<6:16:13, 5.85s/it]
{'loss': 0.4775, 'learning_rate': 4.982799677338268e-06, 'epoch': 0.68}
+
68%|██████▊ | 8095/11952 [2:00:58<6:16:13, 5.85s/it]
68%|██████▊ | 8096/11952 [2:01:04<6:16:35, 5.86s/it]
{'loss': 0.4617, 'learning_rate': 4.980455712455161e-06, 'epoch': 0.68}
+
68%|██████▊ | 8096/11952 [2:01:04<6:16:35, 5.86s/it]
68%|██████▊ | 8097/11952 [2:01:10<6:12:05, 5.79s/it]
{'loss': 0.4769, 'learning_rate': 4.978112116186512e-06, 'epoch': 0.68}
+
68%|██████▊ | 8097/11952 [2:01:10<6:12:05, 5.79s/it]
68%|██████▊ | 8098/11952 [2:01:16<6:19:50, 5.91s/it]
{'loss': 0.4757, 'learning_rate': 4.975768888704422e-06, 'epoch': 0.68}
+
68%|██████▊ | 8098/11952 [2:01:16<6:19:50, 5.91s/it]
68%|██████▊ | 8099/11952 [2:01:22<6:16:36, 5.86s/it]
{'loss': 0.4748, 'learning_rate': 4.973426030180968e-06, 'epoch': 0.68}
+
68%|██████▊ | 8099/11952 [2:01:22<6:16:36, 5.86s/it]6 AutoResumeHook: Checking whether to suspend...
+17 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
68%|██████▊ | 8100/11952 [2:01:28<6:19:24, 5.91s/it]
{'loss': 0.4697, 'learning_rate': 4.971083540788199e-06, 'epoch': 0.68}
+
68%|██████▊ | 8100/11952 [2:01:28<6:19:24, 5.91s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
68%|██████▊ | 8101/11952 [2:01:56<13:31:58, 12.65s/it]
{'loss': 0.4743, 'learning_rate': 4.968741420698137e-06, 'epoch': 0.68}
+
68%|██████▊ | 8101/11952 [2:01:56<13:31:58, 12.65s/it]
68%|██████▊ | 8102/11952 [2:02:02<11:26:55, 10.71s/it]
{'loss': 0.4653, 'learning_rate': 4.966399670082779e-06, 'epoch': 0.68}
+
68%|██████▊ | 8102/11952 [2:02:02<11:26:55, 10.71s/it]
68%|██████▊ | 8103/11952 [2:02:08<9:49:13, 9.18s/it]
{'loss': 0.4759, 'learning_rate': 4.964058289114089e-06, 'epoch': 0.68}
+
68%|██████▊ | 8103/11952 [2:02:08<9:49:13, 9.18s/it]
68%|██████▊ | 8104/11952 [2:02:14<8:55:08, 8.34s/it]
{'loss': 0.5013, 'learning_rate': 4.961717277964012e-06, 'epoch': 0.68}
+
68%|██████▊ | 8104/11952 [2:02:14<8:55:08, 8.34s/it]
68%|██████▊ | 8105/11952 [2:02:20<8:09:06, 7.63s/it]
{'loss': 0.4803, 'learning_rate': 4.959376636804467e-06, 'epoch': 0.68}
+
68%|██████▊ | 8105/11952 [2:02:20<8:09:06, 7.63s/it]
68%|██████▊ | 8106/11952 [2:02:26<7:30:56, 7.03s/it]
{'loss': 0.4712, 'learning_rate': 4.9570363658073366e-06, 'epoch': 0.68}
+
68%|██████▊ | 8106/11952 [2:02:26<7:30:56, 7.03s/it]
68%|██████▊ | 8107/11952 [2:02:32<7:02:25, 6.59s/it]
{'loss': 0.4678, 'learning_rate': 4.954696465144479e-06, 'epoch': 0.68}
+
68%|██████▊ | 8107/11952 [2:02:32<7:02:25, 6.59s/it]
68%|██████▊ | 8108/11952 [2:02:37<6:41:36, 6.27s/it]
{'loss': 0.4561, 'learning_rate': 4.952356934987728e-06, 'epoch': 0.68}
+
68%|██████▊ | 8108/11952 [2:02:37<6:41:36, 6.27s/it]
68%|██████▊ | 8109/11952 [2:02:43<6:36:56, 6.20s/it]
{'loss': 0.4624, 'learning_rate': 4.95001777550889e-06, 'epoch': 0.68}
+
68%|██████▊ | 8109/11952 [2:02:43<6:36:56, 6.20s/it]
68%|██████▊ | 8110/11952 [2:02:49<6:36:04, 6.19s/it]
{'loss': 0.4786, 'learning_rate': 4.947678986879737e-06, 'epoch': 0.68}
+
68%|██████▊ | 8110/11952 [2:02:49<6:36:04, 6.19s/it]
68%|██████▊ | 8111/11952 [2:02:55<6:26:15, 6.03s/it]
{'loss': 0.4465, 'learning_rate': 4.945340569272029e-06, 'epoch': 0.68}
+
68%|██████▊ | 8111/11952 [2:02:55<6:26:15, 6.03s/it]
68%|██████▊ | 8112/11952 [2:03:01<6:18:49, 5.92s/it]
{'loss': 0.477, 'learning_rate': 4.943002522857487e-06, 'epoch': 0.68}
+
68%|██████▊ | 8112/11952 [2:03:01<6:18:49, 5.92s/it]
68%|██████▊ | 8113/11952 [2:03:07<6:19:08, 5.93s/it]
{'loss': 0.4772, 'learning_rate': 4.940664847807804e-06, 'epoch': 0.68}
+
68%|██████▊ | 8113/11952 [2:03:07<6:19:08, 5.93s/it]
68%|██████▊ | 8114/11952 [2:03:13<6:18:41, 5.92s/it]
{'loss': 0.4757, 'learning_rate': 4.9383275442946495e-06, 'epoch': 0.68}
+
68%|██████▊ | 8114/11952 [2:03:13<6:18:41, 5.92s/it]
68%|██████▊ | 8115/11952 [2:03:19<6:19:57, 5.94s/it]
{'loss': 0.4488, 'learning_rate': 4.935990612489671e-06, 'epoch': 0.68}
+
68%|██████▊ | 8115/11952 [2:03:19<6:19:57, 5.94s/it]
68%|██████▊ | 8116/11952 [2:03:24<6:16:43, 5.89s/it]
{'loss': 0.4872, 'learning_rate': 4.933654052564477e-06, 'epoch': 0.68}
+
68%|██████▊ | 8116/11952 [2:03:24<6:16:43, 5.89s/it]
68%|██████▊ | 8117/11952 [2:03:30<6:09:46, 5.79s/it]
{'loss': 0.4675, 'learning_rate': 4.931317864690655e-06, 'epoch': 0.68}
+
68%|██████▊ | 8117/11952 [2:03:30<6:09:46, 5.79s/it]
68%|██████▊ | 8118/11952 [2:03:35<6:06:15, 5.73s/it]
{'loss': 0.4818, 'learning_rate': 4.92898204903977e-06, 'epoch': 0.68}
+
68%|██████▊ | 8118/11952 [2:03:35<6:06:15, 5.73s/it]
68%|██████▊ | 8119/11952 [2:03:41<6:05:05, 5.72s/it]
{'loss': 0.4752, 'learning_rate': 4.92664660578335e-06, 'epoch': 0.68}
+
68%|██████▊ | 8119/11952 [2:03:41<6:05:05, 5.72s/it]
68%|██████▊ | 8120/11952 [2:03:47<6:03:58, 5.70s/it]
{'loss': 0.4517, 'learning_rate': 4.924311535092904e-06, 'epoch': 0.68}
+
68%|██████▊ | 8120/11952 [2:03:47<6:03:58, 5.70s/it]
68%|██████▊ | 8121/11952 [2:03:53<6:04:29, 5.71s/it]
{'loss': 0.4548, 'learning_rate': 4.9219768371399055e-06, 'epoch': 0.68}
+
68%|██████▊ | 8121/11952 [2:03:53<6:04:29, 5.71s/it]
68%|██████▊ | 8122/11952 [2:03:58<6:02:31, 5.68s/it]
{'loss': 0.454, 'learning_rate': 4.919642512095808e-06, 'epoch': 0.68}
+
68%|██████▊ | 8122/11952 [2:03:58<6:02:31, 5.68s/it]
68%|██████▊ | 8123/11952 [2:04:04<5:58:32, 5.62s/it]
{'loss': 0.4802, 'learning_rate': 4.917308560132029e-06, 'epoch': 0.68}
+
68%|██████▊ | 8123/11952 [2:04:04<5:58:32, 5.62s/it]
68%|██████▊ | 8124/11952 [2:04:09<5:56:11, 5.58s/it]
{'loss': 0.4431, 'learning_rate': 4.914974981419974e-06, 'epoch': 0.68}
+
68%|██████▊ | 8124/11952 [2:04:09<5:56:11, 5.58s/it]
68%|██████▊ | 8125/11952 [2:04:15<5:54:48, 5.56s/it]
{'loss': 0.4663, 'learning_rate': 4.9126417761310005e-06, 'epoch': 0.68}
+
68%|██████▊ | 8125/11952 [2:04:15<5:54:48, 5.56s/it]
68%|██████▊ | 8126/11952 [2:04:20<5:54:19, 5.56s/it]
{'loss': 0.4542, 'learning_rate': 4.9103089444364605e-06, 'epoch': 0.68}
+
68%|██████▊ | 8126/11952 [2:04:20<5:54:19, 5.56s/it]
68%|██████▊ | 8127/11952 [2:04:26<6:02:45, 5.69s/it]
{'loss': 0.4589, 'learning_rate': 4.9079764865076615e-06, 'epoch': 0.68}
+
68%|██████▊ | 8127/11952 [2:04:26<6:02:45, 5.69s/it]
68%|██████▊ | 8128/11952 [2:04:32<6:03:19, 5.70s/it]
{'loss': 0.4767, 'learning_rate': 4.90564440251589e-06, 'epoch': 0.68}
+
68%|██████▊ | 8128/11952 [2:04:32<6:03:19, 5.70s/it]
68%|██████▊ | 8129/11952 [2:04:38<6:15:40, 5.90s/it]
{'loss': 0.463, 'learning_rate': 4.903312692632405e-06, 'epoch': 0.68}
+
68%|██████▊ | 8129/11952 [2:04:38<6:15:40, 5.90s/it]
68%|██████▊ | 8130/11952 [2:04:44<6:12:03, 5.84s/it]
{'loss': 0.4729, 'learning_rate': 4.9009813570284326e-06, 'epoch': 0.68}
+
68%|██████▊ | 8130/11952 [2:04:44<6:12:03, 5.84s/it]
68%|██████▊ | 8131/11952 [2:04:49<6:06:12, 5.75s/it]
{'loss': 0.4562, 'learning_rate': 4.898650395875185e-06, 'epoch': 0.68}
+
68%|██████▊ | 8131/11952 [2:04:49<6:06:12, 5.75s/it]
68%|██████▊ | 8132/11952 [2:04:55<6:07:31, 5.77s/it]
{'loss': 0.4701, 'learning_rate': 4.896319809343834e-06, 'epoch': 0.68}
+
68%|██████▊ | 8132/11952 [2:04:55<6:07:31, 5.77s/it]
68%|██████▊ | 8133/11952 [2:05:01<6:03:49, 5.72s/it]
{'loss': 0.4578, 'learning_rate': 4.893989597605528e-06, 'epoch': 0.68}
+
68%|██████▊ | 8133/11952 [2:05:01<6:03:49, 5.72s/it]
68%|██████▊ | 8134/11952 [2:05:07<6:04:47, 5.73s/it]
{'loss': 0.4918, 'learning_rate': 4.8916597608313855e-06, 'epoch': 0.68}
+
68%|██████▊ | 8134/11952 [2:05:07<6:04:47, 5.73s/it]
68%|██████▊ | 8135/11952 [2:05:12<6:01:58, 5.69s/it]
{'loss': 0.4608, 'learning_rate': 4.8893302991925075e-06, 'epoch': 0.68}
+
68%|██████▊ | 8135/11952 [2:05:12<6:01:58, 5.69s/it]
68%|██████▊ | 8136/11952 [2:05:18<5:58:17, 5.63s/it]
{'loss': 0.4662, 'learning_rate': 4.887001212859954e-06, 'epoch': 0.68}
+
68%|██████▊ | 8136/11952 [2:05:18<5:58:17, 5.63s/it]
68%|██████▊ | 8137/11952 [2:05:24<6:01:42, 5.69s/it]
{'loss': 0.4747, 'learning_rate': 4.884672502004762e-06, 'epoch': 0.68}
+
68%|██████▊ | 8137/11952 [2:05:24<6:01:42, 5.69s/it]
68%|██████▊ | 8138/11952 [2:05:30<6:10:54, 5.83s/it]
{'loss': 0.4636, 'learning_rate': 4.8823441667979475e-06, 'epoch': 0.68}
+
68%|██████▊ | 8138/11952 [2:05:30<6:10:54, 5.83s/it]
68%|██████▊ | 8139/11952 [2:05:36<6:14:02, 5.89s/it]
{'loss': 0.4709, 'learning_rate': 4.880016207410493e-06, 'epoch': 0.68}
+
68%|██████▊ | 8139/11952 [2:05:36<6:14:02, 5.89s/it]
68%|██████▊ | 8140/11952 [2:05:42<6:11:28, 5.85s/it]
{'loss': 0.4848, 'learning_rate': 4.877688624013353e-06, 'epoch': 0.68}
+
68%|██████▊ | 8140/11952 [2:05:42<6:11:28, 5.85s/it]
68%|██████▊ | 8141/11952 [2:05:47<6:11:07, 5.84s/it]
{'loss': 0.4728, 'learning_rate': 4.875361416777453e-06, 'epoch': 0.68}
+
68%|██████▊ | 8141/11952 [2:05:47<6:11:07, 5.84s/it]
68%|██████▊ | 8142/11952 [2:05:53<6:15:01, 5.91s/it]
{'loss': 0.494, 'learning_rate': 4.873034585873697e-06, 'epoch': 0.68}
+
68%|██████▊ | 8142/11952 [2:05:53<6:15:01, 5.91s/it]
68%|██████▊ | 8143/11952 [2:05:59<6:11:54, 5.86s/it]
{'loss': 0.4538, 'learning_rate': 4.870708131472957e-06, 'epoch': 0.68}
+
68%|██████▊ | 8143/11952 [2:05:59<6:11:54, 5.86s/it]
68%|██████▊ | 8144/11952 [2:06:05<6:18:16, 5.96s/it]
{'loss': 0.4667, 'learning_rate': 4.868382053746072e-06, 'epoch': 0.68}
+
68%|██████▊ | 8144/11952 [2:06:05<6:18:16, 5.96s/it]
68%|██████▊ | 8145/11952 [2:06:11<6:12:58, 5.88s/it]
{'loss': 0.4854, 'learning_rate': 4.866056352863866e-06, 'epoch': 0.68}
+
68%|██████▊ | 8145/11952 [2:06:11<6:12:58, 5.88s/it]
68%|██████▊ | 8146/11952 [2:06:17<6:12:40, 5.88s/it]
{'loss': 0.4811, 'learning_rate': 4.8637310289971314e-06, 'epoch': 0.68}
+
68%|██████▊ | 8146/11952 [2:06:17<6:12:40, 5.88s/it]
68%|██████▊ | 8147/11952 [2:06:23<6:16:37, 5.94s/it]
{'loss': 0.471, 'learning_rate': 4.861406082316626e-06, 'epoch': 0.68}
+
68%|██████▊ | 8147/11952 [2:06:23<6:16:37, 5.94s/it]
68%|██████▊ | 8148/11952 [2:06:29<6:12:16, 5.87s/it]
{'loss': 0.4748, 'learning_rate': 4.8590815129930865e-06, 'epoch': 0.68}
+
68%|██████▊ | 8148/11952 [2:06:29<6:12:16, 5.87s/it]
68%|██████▊ | 8149/11952 [2:06:35<6:12:14, 5.87s/it]
{'loss': 0.4685, 'learning_rate': 4.8567573211972175e-06, 'epoch': 0.68}
+
68%|██████▊ | 8149/11952 [2:06:35<6:12:14, 5.87s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
68%|██████▊ | 8150/11952 [2:06:41<6:20:39, 6.01s/it]2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4846, 'learning_rate': 4.854433507099698e-06, 'epoch': 0.68}
+
68%|██████▊ | 8150/11952 [2:06:41<6:20:39, 6.01s/it]
68%|██████▊ | 8151/11952 [2:06:47<6:24:11, 6.06s/it]
{'loss': 0.4754, 'learning_rate': 4.852110070871175e-06, 'epoch': 0.68}
+
68%|██████▊ | 8151/11952 [2:06:47<6:24:11, 6.06s/it]
68%|██████▊ | 8152/11952 [2:06:53<6:19:12, 5.99s/it]
{'loss': 0.464, 'learning_rate': 4.849787012682282e-06, 'epoch': 0.68}
+
68%|██████▊ | 8152/11952 [2:06:53<6:19:12, 5.99s/it]
68%|██████▊ | 8153/11952 [2:06:58<6:11:04, 5.86s/it]
{'loss': 0.4705, 'learning_rate': 4.8474643327036095e-06, 'epoch': 0.68}
+
68%|██████▊ | 8153/11952 [2:06:58<6:11:04, 5.86s/it]
68%|██████▊ | 8154/11952 [2:07:04<6:10:46, 5.86s/it]
{'loss': 0.4814, 'learning_rate': 4.845142031105724e-06, 'epoch': 0.68}
+
68%|██████▊ | 8154/11952 [2:07:04<6:10:46, 5.86s/it]
68%|██████▊ | 8155/11952 [2:07:10<6:07:32, 5.81s/it]
{'loss': 0.4669, 'learning_rate': 4.8428201080591645e-06, 'epoch': 0.68}
+
68%|██████▊ | 8155/11952 [2:07:10<6:07:32, 5.81s/it]
68%|██████▊ | 8156/11952 [2:07:16<6:10:06, 5.85s/it]
{'loss': 0.4703, 'learning_rate': 4.840498563734449e-06, 'epoch': 0.68}
+
68%|██████▊ | 8156/11952 [2:07:16<6:10:06, 5.85s/it]
68%|██████▊ | 8157/11952 [2:07:22<6:08:58, 5.83s/it]
{'loss': 0.4661, 'learning_rate': 4.838177398302056e-06, 'epoch': 0.68}
+
68%|██████▊ | 8157/11952 [2:07:22<6:08:58, 5.83s/it]
68%|██████▊ | 8158/11952 [2:07:28<6:14:40, 5.93s/it]
{'loss': 0.4684, 'learning_rate': 4.8358566119324494e-06, 'epoch': 0.68}
+
68%|██████▊ | 8158/11952 [2:07:28<6:14:40, 5.93s/it]
68%|██████▊ | 8159/11952 [2:07:34<6:10:36, 5.86s/it]
{'loss': 0.4745, 'learning_rate': 4.833536204796052e-06, 'epoch': 0.68}
+
68%|██████▊ | 8159/11952 [2:07:34<6:10:36, 5.86s/it]
68%|██████▊ | 8160/11952 [2:07:40<6:11:08, 5.87s/it]
{'loss': 0.4634, 'learning_rate': 4.831216177063268e-06, 'epoch': 0.68}
+
68%|██████▊ | 8160/11952 [2:07:40<6:11:08, 5.87s/it]
68%|██████▊ | 8161/11952 [2:07:45<6:10:41, 5.87s/it]
{'loss': 0.4606, 'learning_rate': 4.82889652890447e-06, 'epoch': 0.68}
+
68%|██████▊ | 8161/11952 [2:07:45<6:10:41, 5.87s/it]
68%|██████▊ | 8162/11952 [2:07:51<6:06:35, 5.80s/it]
{'loss': 0.4659, 'learning_rate': 4.8265772604900015e-06, 'epoch': 0.68}
+
68%|██████▊ | 8162/11952 [2:07:51<6:06:35, 5.80s/it]
68%|██████▊ | 8163/11952 [2:07:57<6:04:16, 5.77s/it]
{'loss': 0.4668, 'learning_rate': 4.824258371990181e-06, 'epoch': 0.68}
+
68%|██████▊ | 8163/11952 [2:07:57<6:04:16, 5.77s/it]
68%|██████▊ | 8164/11952 [2:08:02<6:01:10, 5.72s/it]
{'loss': 0.4562, 'learning_rate': 4.821939863575295e-06, 'epoch': 0.68}
+
68%|██████▊ | 8164/11952 [2:08:02<6:01:10, 5.72s/it]
68%|██████▊ | 8165/11952 [2:08:08<5:57:53, 5.67s/it]
{'loss': 0.4466, 'learning_rate': 4.819621735415613e-06, 'epoch': 0.68}
+
68%|██████▊ | 8165/11952 [2:08:08<5:57:53, 5.67s/it]
68%|██████▊ | 8166/11952 [2:08:14<6:02:12, 5.74s/it]
{'loss': 0.4877, 'learning_rate': 4.817303987681359e-06, 'epoch': 0.68}
+
68%|██████▊ | 8166/11952 [2:08:14<6:02:12, 5.74s/it]
68%|██████▊ | 8167/11952 [2:08:20<6:07:00, 5.82s/it]
{'loss': 0.4766, 'learning_rate': 4.814986620542747e-06, 'epoch': 0.68}
+
68%|██████▊ | 8167/11952 [2:08:20<6:07:00, 5.82s/it]
68%|██████▊ | 8168/11952 [2:08:25<6:04:21, 5.78s/it]
{'loss': 0.4601, 'learning_rate': 4.8126696341699515e-06, 'epoch': 0.68}
+
68%|██████▊ | 8168/11952 [2:08:25<6:04:21, 5.78s/it]
68%|██████▊ | 8169/11952 [2:08:31<6:06:43, 5.82s/it]
{'loss': 0.4765, 'learning_rate': 4.810353028733123e-06, 'epoch': 0.68}
+
68%|██████▊ | 8169/11952 [2:08:31<6:06:43, 5.82s/it]
68%|██████▊ | 8170/11952 [2:08:37<6:07:04, 5.82s/it]
{'loss': 0.4913, 'learning_rate': 4.808036804402383e-06, 'epoch': 0.68}
+
68%|██████▊ | 8170/11952 [2:08:37<6:07:04, 5.82s/it]
68%|██████▊ | 8171/11952 [2:08:43<6:03:10, 5.76s/it]
{'loss': 0.4553, 'learning_rate': 4.80572096134782e-06, 'epoch': 0.68}
+
68%|██████▊ | 8171/11952 [2:08:43<6:03:10, 5.76s/it]
68%|██████▊ | 8172/11952 [2:08:48<6:00:29, 5.72s/it]
{'loss': 0.4824, 'learning_rate': 4.803405499739511e-06, 'epoch': 0.68}
+
68%|██████▊ | 8172/11952 [2:08:48<6:00:29, 5.72s/it]
68%|██████▊ | 8173/11952 [2:08:54<5:57:22, 5.67s/it]
{'loss': 0.466, 'learning_rate': 4.801090419747486e-06, 'epoch': 0.68}
+
68%|██████▊ | 8173/11952 [2:08:54<5:57:22, 5.67s/it]
68%|██████▊ | 8174/11952 [2:09:00<6:00:57, 5.73s/it]
{'loss': 0.4502, 'learning_rate': 4.798775721541757e-06, 'epoch': 0.68}
+
68%|██████▊ | 8174/11952 [2:09:00<6:00:57, 5.73s/it]
68%|██████▊ | 8175/11952 [2:09:06<6:00:48, 5.73s/it]
{'loss': 0.453, 'learning_rate': 4.796461405292302e-06, 'epoch': 0.68}
+
68%|██████▊ | 8175/11952 [2:09:06<6:00:48, 5.73s/it]
68%|██████▊ | 8176/11952 [2:09:12<6:09:55, 5.88s/it]
{'loss': 0.4768, 'learning_rate': 4.794147471169082e-06, 'epoch': 0.68}
+
68%|██████▊ | 8176/11952 [2:09:12<6:09:55, 5.88s/it]
68%|██████▊ | 8177/11952 [2:09:18<6:14:15, 5.95s/it]
{'loss': 0.4754, 'learning_rate': 4.7918339193420195e-06, 'epoch': 0.68}
+
68%|██████▊ | 8177/11952 [2:09:18<6:14:15, 5.95s/it]
68%|██████▊ | 8178/11952 [2:09:24<6:18:54, 6.02s/it]
{'loss': 0.4688, 'learning_rate': 4.789520749981007e-06, 'epoch': 0.68}
+
68%|██████▊ | 8178/11952 [2:09:24<6:18:54, 6.02s/it]
68%|██████▊ | 8179/11952 [2:09:30<6:16:23, 5.99s/it]
{'loss': 0.4925, 'learning_rate': 4.787207963255922e-06, 'epoch': 0.68}
+
68%|██████▊ | 8179/11952 [2:09:30<6:16:23, 5.99s/it]
68%|██████▊ | 8180/11952 [2:09:36<6:08:32, 5.86s/it]
{'loss': 0.4751, 'learning_rate': 4.7848955593366035e-06, 'epoch': 0.68}
+
68%|██████▊ | 8180/11952 [2:09:36<6:08:32, 5.86s/it]
68%|██████▊ | 8181/11952 [2:09:41<6:05:28, 5.81s/it]
{'loss': 0.4647, 'learning_rate': 4.782583538392863e-06, 'epoch': 0.68}
+
68%|██████▊ | 8181/11952 [2:09:41<6:05:28, 5.81s/it]
68%|██████▊ | 8182/11952 [2:09:47<6:06:10, 5.83s/it]
{'loss': 0.4637, 'learning_rate': 4.7802719005944875e-06, 'epoch': 0.68}
+
68%|██████▊ | 8182/11952 [2:09:47<6:06:10, 5.83s/it]
68%|██████▊ | 8183/11952 [2:09:53<6:09:47, 5.89s/it]
{'loss': 0.4859, 'learning_rate': 4.777960646111233e-06, 'epoch': 0.68}
+
68%|██████▊ | 8183/11952 [2:09:53<6:09:47, 5.89s/it]
68%|██████▊ | 8184/11952 [2:09:59<6:07:34, 5.85s/it]
{'loss': 0.4761, 'learning_rate': 4.775649775112828e-06, 'epoch': 0.68}
+
68%|██████▊ | 8184/11952 [2:09:59<6:07:34, 5.85s/it]
68%|██████▊ | 8185/11952 [2:10:05<6:01:59, 5.77s/it]
{'loss': 0.4867, 'learning_rate': 4.77333928776897e-06, 'epoch': 0.68}
+
68%|██████▊ | 8185/11952 [2:10:05<6:01:59, 5.77s/it]
68%|██████▊ | 8186/11952 [2:10:11<6:06:21, 5.84s/it]
{'loss': 0.4683, 'learning_rate': 4.771029184249339e-06, 'epoch': 0.68}
+
68%|██████▊ | 8186/11952 [2:10:11<6:06:21, 5.84s/it]
68%|██████▊ | 8187/11952 [2:10:16<6:05:17, 5.82s/it]
{'loss': 0.4825, 'learning_rate': 4.768719464723572e-06, 'epoch': 0.68}
+
68%|██████▊ | 8187/11952 [2:10:16<6:05:17, 5.82s/it]
69%|██████▊ | 8188/11952 [2:10:22<6:03:37, 5.80s/it]
{'loss': 0.4661, 'learning_rate': 4.766410129361294e-06, 'epoch': 0.69}
+
69%|██████▊ | 8188/11952 [2:10:22<6:03:37, 5.80s/it]
69%|██████▊ | 8189/11952 [2:10:28<6:07:30, 5.86s/it]
{'loss': 0.4592, 'learning_rate': 4.7641011783320866e-06, 'epoch': 0.69}
+
69%|██████▊ | 8189/11952 [2:10:28<6:07:30, 5.86s/it]
69%|██████▊ | 8190/11952 [2:10:34<6:08:43, 5.88s/it]
{'loss': 0.4794, 'learning_rate': 4.7617926118055125e-06, 'epoch': 0.69}
+
69%|██████▊ | 8190/11952 [2:10:34<6:08:43, 5.88s/it]
69%|██████▊ | 8191/11952 [2:10:40<6:01:53, 5.77s/it]
{'loss': 0.4742, 'learning_rate': 4.7594844299511e-06, 'epoch': 0.69}
+
69%|██████▊ | 8191/11952 [2:10:40<6:01:53, 5.77s/it]
69%|██████▊ | 8192/11952 [2:10:45<6:02:13, 5.78s/it]
{'loss': 0.4719, 'learning_rate': 4.757176632938351e-06, 'epoch': 0.69}
+
69%|██████▊ | 8192/11952 [2:10:45<6:02:13, 5.78s/it]
69%|██████▊ | 8193/11952 [2:10:51<6:08:42, 5.89s/it]
{'loss': 0.4626, 'learning_rate': 4.754869220936748e-06, 'epoch': 0.69}
+
69%|██████▊ | 8193/11952 [2:10:51<6:08:42, 5.89s/it]
69%|██████▊ | 8194/11952 [2:10:57<6:02:00, 5.78s/it]
{'loss': 0.4645, 'learning_rate': 4.752562194115732e-06, 'epoch': 0.69}
+
69%|██████▊ | 8194/11952 [2:10:57<6:02:00, 5.78s/it]
69%|██████▊ | 8195/11952 [2:11:02<5:56:49, 5.70s/it]
{'loss': 0.4626, 'learning_rate': 4.750255552644722e-06, 'epoch': 0.69}
+
69%|██████▊ | 8195/11952 [2:11:02<5:56:49, 5.70s/it]
69%|██████▊ | 8196/11952 [2:11:09<6:03:53, 5.81s/it]
{'loss': 0.4671, 'learning_rate': 4.7479492966931076e-06, 'epoch': 0.69}
+
69%|██████▊ | 8196/11952 [2:11:09<6:03:53, 5.81s/it]
69%|██████▊ | 8197/11952 [2:11:14<6:02:46, 5.80s/it]
{'loss': 0.4699, 'learning_rate': 4.745643426430254e-06, 'epoch': 0.69}
+
69%|██████▊ | 8197/11952 [2:11:14<6:02:46, 5.80s/it]
69%|██████▊ | 8198/11952 [2:11:20<6:06:33, 5.86s/it]
{'loss': 0.4682, 'learning_rate': 4.743337942025489e-06, 'epoch': 0.69}
+
69%|██████▊ | 8198/11952 [2:11:20<6:06:33, 5.86s/it]
69%|██████▊ | 8199/11952 [2:11:26<6:05:02, 5.84s/it]
{'loss': 0.4568, 'learning_rate': 4.741032843648126e-06, 'epoch': 0.69}
+
69%|██████▊ | 8199/11952 [2:11:26<6:05:02, 5.84s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
69%|██████▊ | 8200/11952 [2:11:32<6:08:29, 5.89s/it]2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4775, 'learning_rate': 4.738728131467436e-06, 'epoch': 0.69}
+
69%|██████▊ | 8200/11952 [2:11:32<6:08:29, 5.89s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
69%|██████▊ | 8201/11952 [2:12:03<13:50:57, 13.29s/it]
{'loss': 0.4795, 'learning_rate': 4.73642380565267e-06, 'epoch': 0.69}
+
69%|██████▊ | 8201/11952 [2:12:03<13:50:57, 13.29s/it]
69%|██████▊ | 8202/11952 [2:12:08<11:28:40, 11.02s/it]
{'loss': 0.4591, 'learning_rate': 4.734119866373046e-06, 'epoch': 0.69}
+
69%|██████▊ | 8202/11952 [2:12:08<11:28:40, 11.02s/it]
69%|██████▊ | 8203/11952 [2:12:14<9:49:21, 9.43s/it]
{'loss': 0.4689, 'learning_rate': 4.731816313797757e-06, 'epoch': 0.69}
+
69%|██████▊ | 8203/11952 [2:12:14<9:49:21, 9.43s/it]
69%|██████▊ | 8204/11952 [2:12:20<8:38:15, 8.30s/it]
{'loss': 0.4534, 'learning_rate': 4.7295131480959655e-06, 'epoch': 0.69}
+
69%|██████▊ | 8204/11952 [2:12:20<8:38:15, 8.30s/it]
69%|██████▊ | 8205/11952 [2:12:26<7:52:33, 7.57s/it]
{'loss': 0.4792, 'learning_rate': 4.727210369436803e-06, 'epoch': 0.69}
+
69%|██████▊ | 8205/11952 [2:12:26<7:52:33, 7.57s/it]
69%|██████▊ | 8206/11952 [2:12:31<7:18:12, 7.02s/it]
{'loss': 0.4638, 'learning_rate': 4.724907977989384e-06, 'epoch': 0.69}
+
69%|██████▊ | 8206/11952 [2:12:31<7:18:12, 7.02s/it]
69%|██████▊ | 8207/11952 [2:12:37<6:56:32, 6.67s/it]
{'loss': 0.4603, 'learning_rate': 4.7226059739227796e-06, 'epoch': 0.69}
+
69%|██████▊ | 8207/11952 [2:12:37<6:56:32, 6.67s/it]
69%|██████▊ | 8208/11952 [2:12:43<6:36:28, 6.35s/it]
{'loss': 0.4847, 'learning_rate': 4.720304357406044e-06, 'epoch': 0.69}
+
69%|██████▊ | 8208/11952 [2:12:43<6:36:28, 6.35s/it]
69%|██████▊ | 8209/11952 [2:12:49<6:31:04, 6.27s/it]
{'loss': 0.464, 'learning_rate': 4.7180031286081975e-06, 'epoch': 0.69}
+
69%|██████▊ | 8209/11952 [2:12:49<6:31:04, 6.27s/it]
69%|██████▊ | 8210/11952 [2:12:55<6:24:52, 6.17s/it]
{'loss': 0.4724, 'learning_rate': 4.715702287698232e-06, 'epoch': 0.69}
+
69%|██████▊ | 8210/11952 [2:12:55<6:24:52, 6.17s/it]
69%|██████▊ | 8211/11952 [2:13:01<6:17:59, 6.06s/it]
{'loss': 0.4716, 'learning_rate': 4.71340183484511e-06, 'epoch': 0.69}
+
69%|██████▊ | 8211/11952 [2:13:01<6:17:59, 6.06s/it]
69%|██████▊ | 8212/11952 [2:13:06<6:12:30, 5.98s/it]
{'loss': 0.471, 'learning_rate': 4.711101770217766e-06, 'epoch': 0.69}
+
69%|██████▊ | 8212/11952 [2:13:06<6:12:30, 5.98s/it]
69%|██████▊ | 8213/11952 [2:13:12<6:06:18, 5.88s/it]
{'loss': 0.473, 'learning_rate': 4.708802093985113e-06, 'epoch': 0.69}
+
69%|██████▊ | 8213/11952 [2:13:12<6:06:18, 5.88s/it]
69%|██████▊ | 8214/11952 [2:13:18<6:05:51, 5.87s/it]
{'loss': 0.4778, 'learning_rate': 4.706502806316028e-06, 'epoch': 0.69}
+
69%|██████▊ | 8214/11952 [2:13:18<6:05:51, 5.87s/it]
69%|██████▊ | 8215/11952 [2:13:24<6:05:51, 5.87s/it]
{'loss': 0.4548, 'learning_rate': 4.704203907379358e-06, 'epoch': 0.69}
+
69%|██████▊ | 8215/11952 [2:13:24<6:05:51, 5.87s/it]
69%|██████▊ | 8216/11952 [2:13:30<6:09:56, 5.94s/it]
{'loss': 0.484, 'learning_rate': 4.7019053973439265e-06, 'epoch': 0.69}
+
69%|██████▊ | 8216/11952 [2:13:30<6:09:56, 5.94s/it]
69%|██████▉ | 8217/11952 [2:13:36<6:07:33, 5.90s/it]
{'loss': 0.473, 'learning_rate': 4.6996072763785225e-06, 'epoch': 0.69}
+
69%|██████▉ | 8217/11952 [2:13:36<6:07:33, 5.90s/it]
69%|██████▉ | 8218/11952 [2:13:42<6:05:51, 5.88s/it]
{'loss': 0.4642, 'learning_rate': 4.697309544651918e-06, 'epoch': 0.69}
+
69%|██████▉ | 8218/11952 [2:13:42<6:05:51, 5.88s/it]
69%|██████▉ | 8219/11952 [2:13:47<6:04:13, 5.85s/it]
{'loss': 0.4716, 'learning_rate': 4.6950122023328415e-06, 'epoch': 0.69}
+
69%|██████▉ | 8219/11952 [2:13:47<6:04:13, 5.85s/it]
69%|██████▉ | 8220/11952 [2:13:53<5:59:47, 5.78s/it]
{'loss': 0.4708, 'learning_rate': 4.692715249590007e-06, 'epoch': 0.69}
+
69%|██████▉ | 8220/11952 [2:13:53<5:59:47, 5.78s/it]
69%|██████▉ | 8221/11952 [2:13:59<6:04:09, 5.86s/it]
{'loss': 0.4752, 'learning_rate': 4.69041868659209e-06, 'epoch': 0.69}
+
69%|██████▉ | 8221/11952 [2:13:59<6:04:09, 5.86s/it]
69%|██████▉ | 8222/11952 [2:14:05<6:00:14, 5.79s/it]
{'loss': 0.4551, 'learning_rate': 4.68812251350774e-06, 'epoch': 0.69}
+
69%|██████▉ | 8222/11952 [2:14:05<6:00:14, 5.79s/it]
69%|██████▉ | 8223/11952 [2:14:11<6:02:20, 5.83s/it]
{'loss': 0.4794, 'learning_rate': 4.685826730505581e-06, 'epoch': 0.69}
+
69%|██████▉ | 8223/11952 [2:14:11<6:02:20, 5.83s/it]
69%|██████▉ | 8224/11952 [2:14:17<6:04:22, 5.86s/it]
{'loss': 0.4568, 'learning_rate': 4.683531337754201e-06, 'epoch': 0.69}
+
69%|██████▉ | 8224/11952 [2:14:17<6:04:22, 5.86s/it]
69%|██████▉ | 8225/11952 [2:14:22<5:58:48, 5.78s/it]
{'loss': 0.4637, 'learning_rate': 4.6812363354221675e-06, 'epoch': 0.69}
+
69%|██████▉ | 8225/11952 [2:14:22<5:58:48, 5.78s/it]
69%|██████▉ | 8226/11952 [2:14:28<6:00:35, 5.81s/it]
{'loss': 0.4712, 'learning_rate': 4.678941723678012e-06, 'epoch': 0.69}
+
69%|██████▉ | 8226/11952 [2:14:28<6:00:35, 5.81s/it]
69%|██████▉ | 8227/11952 [2:14:34<5:59:04, 5.78s/it]
{'loss': 0.4848, 'learning_rate': 4.676647502690248e-06, 'epoch': 0.69}
+
69%|██████▉ | 8227/11952 [2:14:34<5:59:04, 5.78s/it]
69%|██████▉ | 8228/11952 [2:14:40<6:01:18, 5.82s/it]
{'loss': 0.4672, 'learning_rate': 4.674353672627345e-06, 'epoch': 0.69}
+
69%|██████▉ | 8228/11952 [2:14:40<6:01:18, 5.82s/it]
69%|██████▉ | 8229/11952 [2:14:45<6:00:51, 5.82s/it]
{'loss': 0.4781, 'learning_rate': 4.672060233657762e-06, 'epoch': 0.69}
+
69%|██████▉ | 8229/11952 [2:14:45<6:00:51, 5.82s/it]
69%|██████▉ | 8230/11952 [2:14:51<5:59:19, 5.79s/it]
{'loss': 0.4555, 'learning_rate': 4.669767185949915e-06, 'epoch': 0.69}
+
69%|██████▉ | 8230/11952 [2:14:51<5:59:19, 5.79s/it]
69%|██████▉ | 8231/11952 [2:14:57<5:59:27, 5.80s/it]
{'loss': 0.4874, 'learning_rate': 4.667474529672196e-06, 'epoch': 0.69}
+
69%|██████▉ | 8231/11952 [2:14:57<5:59:27, 5.80s/it]
69%|██████▉ | 8232/11952 [2:15:03<6:01:52, 5.84s/it]
{'loss': 0.4607, 'learning_rate': 4.665182264992966e-06, 'epoch': 0.69}
+
69%|██████▉ | 8232/11952 [2:15:03<6:01:52, 5.84s/it]
69%|██████▉ | 8233/11952 [2:15:09<5:57:42, 5.77s/it]
{'loss': 0.4571, 'learning_rate': 4.66289039208056e-06, 'epoch': 0.69}
+
69%|██████▉ | 8233/11952 [2:15:09<5:57:42, 5.77s/it]
69%|██████▉ | 8234/11952 [2:15:15<6:01:54, 5.84s/it]
{'loss': 0.4561, 'learning_rate': 4.660598911103288e-06, 'epoch': 0.69}
+
69%|██████▉ | 8234/11952 [2:15:15<6:01:54, 5.84s/it]
69%|██████▉ | 8235/11952 [2:15:21<6:08:00, 5.94s/it]
{'loss': 0.4632, 'learning_rate': 4.658307822229423e-06, 'epoch': 0.69}
+
69%|██████▉ | 8235/11952 [2:15:21<6:08:00, 5.94s/it]
69%|██████▉ | 8236/11952 [2:15:26<6:02:35, 5.85s/it]
{'loss': 0.4754, 'learning_rate': 4.656017125627214e-06, 'epoch': 0.69}
+
69%|██████▉ | 8236/11952 [2:15:26<6:02:35, 5.85s/it]
69%|██████▉ | 8237/11952 [2:15:32<6:00:26, 5.82s/it]
{'loss': 0.483, 'learning_rate': 4.653726821464876e-06, 'epoch': 0.69}
+
69%|██████▉ | 8237/11952 [2:15:32<6:00:26, 5.82s/it]
69%|██████▉ | 8238/11952 [2:15:38<6:07:50, 5.94s/it]
{'loss': 0.4668, 'learning_rate': 4.651436909910607e-06, 'epoch': 0.69}
+
69%|██████▉ | 8238/11952 [2:15:38<6:07:50, 5.94s/it]
69%|██████▉ | 8239/11952 [2:15:44<6:08:09, 5.95s/it]
{'loss': 0.4958, 'learning_rate': 4.649147391132562e-06, 'epoch': 0.69}
+
69%|██████▉ | 8239/11952 [2:15:44<6:08:09, 5.95s/it]
69%|██████▉ | 8240/11952 [2:15:50<6:05:03, 5.90s/it]
{'loss': 0.4723, 'learning_rate': 4.646858265298881e-06, 'epoch': 0.69}
+
69%|██████▉ | 8240/11952 [2:15:50<6:05:03, 5.90s/it]
69%|██████▉ | 8241/11952 [2:15:56<6:04:17, 5.89s/it]
{'loss': 0.4746, 'learning_rate': 4.644569532577662e-06, 'epoch': 0.69}
+
69%|██████▉ | 8241/11952 [2:15:56<6:04:17, 5.89s/it]
69%|██████▉ | 8242/11952 [2:16:02<6:00:19, 5.83s/it]
{'loss': 0.4718, 'learning_rate': 4.6422811931369825e-06, 'epoch': 0.69}
+
69%|██████▉ | 8242/11952 [2:16:02<6:00:19, 5.83s/it]
69%|██████▉ | 8243/11952 [2:16:07<5:58:49, 5.80s/it]
{'loss': 0.4667, 'learning_rate': 4.639993247144889e-06, 'epoch': 0.69}
+
69%|██████▉ | 8243/11952 [2:16:07<5:58:49, 5.80s/it]
69%|██████▉ | 8244/11952 [2:16:13<5:55:04, 5.75s/it]
{'loss': 0.4615, 'learning_rate': 4.637705694769396e-06, 'epoch': 0.69}
+
69%|██████▉ | 8244/11952 [2:16:13<5:55:04, 5.75s/it]
69%|██████▉ | 8245/11952 [2:16:19<6:00:38, 5.84s/it]
{'loss': 0.4802, 'learning_rate': 4.635418536178492e-06, 'epoch': 0.69}
+
69%|██████▉ | 8245/11952 [2:16:19<6:00:38, 5.84s/it]
69%|██████▉ | 8246/11952 [2:16:25<5:58:25, 5.80s/it]
{'loss': 0.471, 'learning_rate': 4.633131771540136e-06, 'epoch': 0.69}
+
69%|██████▉ | 8246/11952 [2:16:25<5:58:25, 5.80s/it]
69%|██████▉ | 8247/11952 [2:16:30<5:56:59, 5.78s/it]
{'loss': 0.4659, 'learning_rate': 4.630845401022264e-06, 'epoch': 0.69}
+
69%|██████▉ | 8247/11952 [2:16:30<5:56:59, 5.78s/it]
69%|██████▉ | 8248/11952 [2:16:36<5:55:18, 5.76s/it]
{'loss': 0.48, 'learning_rate': 4.628559424792769e-06, 'epoch': 0.69}
+
69%|██████▉ | 8248/11952 [2:16:36<5:55:18, 5.76s/it]
69%|██████▉ | 8249/11952 [2:16:42<5:59:02, 5.82s/it]
{'loss': 0.4433, 'learning_rate': 4.626273843019532e-06, 'epoch': 0.69}
+
69%|██████▉ | 8249/11952 [2:16:42<5:59:02, 5.82s/it]1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+065 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
69%|██████▉ | 8250/11952 [2:16:48<6:01:36, 5.86s/it]7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4805, 'learning_rate': 4.623988655870394e-06, 'epoch': 0.69}
+
69%|██████▉ | 8250/11952 [2:16:48<6:01:36, 5.86s/it]
69%|██████▉ | 8251/11952 [2:16:54<6:00:53, 5.85s/it]
{'loss': 0.4693, 'learning_rate': 4.621703863513168e-06, 'epoch': 0.69}
+
69%|██████▉ | 8251/11952 [2:16:54<6:00:53, 5.85s/it]
69%|██████▉ | 8252/11952 [2:17:00<6:03:26, 5.89s/it]
{'loss': 0.4697, 'learning_rate': 4.61941946611564e-06, 'epoch': 0.69}
+
69%|██████▉ | 8252/11952 [2:17:00<6:03:26, 5.89s/it]
69%|██████▉ | 8253/11952 [2:17:05<5:57:06, 5.79s/it]
{'loss': 0.4931, 'learning_rate': 4.617135463845563e-06, 'epoch': 0.69}
+
69%|██████▉ | 8253/11952 [2:17:05<5:57:06, 5.79s/it]
69%|██████▉ | 8254/11952 [2:17:11<5:56:21, 5.78s/it]
{'loss': 0.4724, 'learning_rate': 4.614851856870673e-06, 'epoch': 0.69}
+
69%|██████▉ | 8254/11952 [2:17:11<5:56:21, 5.78s/it]
69%|██████▉ | 8255/11952 [2:17:17<6:01:45, 5.87s/it]
{'loss': 0.4771, 'learning_rate': 4.612568645358664e-06, 'epoch': 0.69}
+
69%|██████▉ | 8255/11952 [2:17:17<6:01:45, 5.87s/it]
69%|██████▉ | 8256/11952 [2:17:23<6:00:40, 5.86s/it]
{'loss': 0.4438, 'learning_rate': 4.6102858294772055e-06, 'epoch': 0.69}
+
69%|██████▉ | 8256/11952 [2:17:23<6:00:40, 5.86s/it]
69%|██████▉ | 8257/11952 [2:17:29<6:01:55, 5.88s/it]
{'loss': 0.49, 'learning_rate': 4.608003409393939e-06, 'epoch': 0.69}
+
69%|██████▉ | 8257/11952 [2:17:29<6:01:55, 5.88s/it]
69%|██████▉ | 8258/11952 [2:17:35<6:00:22, 5.85s/it]
{'loss': 0.4572, 'learning_rate': 4.60572138527647e-06, 'epoch': 0.69}
+
69%|██████▉ | 8258/11952 [2:17:35<6:00:22, 5.85s/it]
69%|██████▉ | 8259/11952 [2:17:41<5:58:13, 5.82s/it]
{'loss': 0.4596, 'learning_rate': 4.60343975729239e-06, 'epoch': 0.69}
+
69%|██████▉ | 8259/11952 [2:17:41<5:58:13, 5.82s/it]
69%|██████▉ | 8260/11952 [2:17:46<5:53:46, 5.75s/it]
{'loss': 0.4777, 'learning_rate': 4.601158525609245e-06, 'epoch': 0.69}
+
69%|██████▉ | 8260/11952 [2:17:46<5:53:46, 5.75s/it]
69%|██████▉ | 8261/11952 [2:17:52<5:53:18, 5.74s/it]
{'loss': 0.4661, 'learning_rate': 4.598877690394565e-06, 'epoch': 0.69}
+
69%|██████▉ | 8261/11952 [2:17:52<5:53:18, 5.74s/it]
69%|██████▉ | 8262/11952 [2:17:58<5:52:25, 5.73s/it]
{'loss': 0.458, 'learning_rate': 4.596597251815844e-06, 'epoch': 0.69}
+
69%|██████▉ | 8262/11952 [2:17:58<5:52:25, 5.73s/it]
69%|██████▉ | 8263/11952 [2:18:04<5:59:34, 5.85s/it]
{'loss': 0.4684, 'learning_rate': 4.5943172100405455e-06, 'epoch': 0.69}
+
69%|██████▉ | 8263/11952 [2:18:04<5:59:34, 5.85s/it]
69%|██████▉ | 8264/11952 [2:18:10<6:05:27, 5.95s/it]
{'loss': 0.4587, 'learning_rate': 4.592037565236108e-06, 'epoch': 0.69}
+
69%|██████▉ | 8264/11952 [2:18:10<6:05:27, 5.95s/it]
69%|██████▉ | 8265/11952 [2:18:16<6:03:58, 5.92s/it]
{'loss': 0.4612, 'learning_rate': 4.589758317569938e-06, 'epoch': 0.69}
+
69%|██████▉ | 8265/11952 [2:18:16<6:03:58, 5.92s/it]
69%|██████▉ | 8266/11952 [2:18:22<6:05:05, 5.94s/it]
{'loss': 0.475, 'learning_rate': 4.5874794672094135e-06, 'epoch': 0.69}
+
69%|██████▉ | 8266/11952 [2:18:22<6:05:05, 5.94s/it]
69%|██████▉ | 8267/11952 [2:18:28<6:01:29, 5.89s/it]
{'loss': 0.4665, 'learning_rate': 4.585201014321882e-06, 'epoch': 0.69}
+
69%|██████▉ | 8267/11952 [2:18:28<6:01:29, 5.89s/it]
69%|██████▉ | 8268/11952 [2:18:34<6:04:03, 5.93s/it]
{'loss': 0.4585, 'learning_rate': 4.582922959074668e-06, 'epoch': 0.69}
+
69%|██████▉ | 8268/11952 [2:18:34<6:04:03, 5.93s/it]
69%|██████▉ | 8269/11952 [2:18:39<6:02:14, 5.90s/it]
{'loss': 0.4705, 'learning_rate': 4.5806453016350584e-06, 'epoch': 0.69}
+
69%|██████▉ | 8269/11952 [2:18:39<6:02:14, 5.90s/it]
69%|██████▉ | 8270/11952 [2:18:45<6:03:35, 5.92s/it]
{'loss': 0.4901, 'learning_rate': 4.5783680421703205e-06, 'epoch': 0.69}
+
69%|██████▉ | 8270/11952 [2:18:45<6:03:35, 5.92s/it]
69%|██████▉ | 8271/11952 [2:18:51<6:03:02, 5.92s/it]
{'loss': 0.4554, 'learning_rate': 4.576091180847684e-06, 'epoch': 0.69}
+
69%|██████▉ | 8271/11952 [2:18:51<6:03:02, 5.92s/it]
69%|██████▉ | 8272/11952 [2:18:57<5:59:13, 5.86s/it]
{'loss': 0.4782, 'learning_rate': 4.57381471783435e-06, 'epoch': 0.69}
+
69%|██████▉ | 8272/11952 [2:18:57<5:59:13, 5.86s/it]
69%|██████▉ | 8273/11952 [2:19:03<6:01:55, 5.90s/it]
{'loss': 0.4807, 'learning_rate': 4.571538653297491e-06, 'epoch': 0.69}
+
69%|██████▉ | 8273/11952 [2:19:03<6:01:55, 5.90s/it]
69%|██████▉ | 8274/11952 [2:19:09<5:58:45, 5.85s/it]
{'loss': 0.4598, 'learning_rate': 4.5692629874042585e-06, 'epoch': 0.69}
+
69%|██████▉ | 8274/11952 [2:19:09<5:58:45, 5.85s/it]
69%|██████▉ | 8275/11952 [2:19:14<5:54:45, 5.79s/it]
{'loss': 0.4618, 'learning_rate': 4.566987720321764e-06, 'epoch': 0.69}
+
69%|██████▉ | 8275/11952 [2:19:14<5:54:45, 5.79s/it]
69%|██████▉ | 8276/11952 [2:19:20<5:56:53, 5.83s/it]
{'loss': 0.47, 'learning_rate': 4.564712852217094e-06, 'epoch': 0.69}
+
69%|██████▉ | 8276/11952 [2:19:20<5:56:53, 5.83s/it]
69%|██████▉ | 8277/11952 [2:19:26<6:02:12, 5.91s/it]
{'loss': 0.4723, 'learning_rate': 4.562438383257304e-06, 'epoch': 0.69}
+
69%|██████▉ | 8277/11952 [2:19:26<6:02:12, 5.91s/it]
69%|██████▉ | 8278/11952 [2:19:32<5:57:02, 5.83s/it]
{'loss': 0.4548, 'learning_rate': 4.5601643136094195e-06, 'epoch': 0.69}
+
69%|██████▉ | 8278/11952 [2:19:32<5:57:02, 5.83s/it]
69%|██████▉ | 8279/11952 [2:19:38<5:59:27, 5.87s/it]
{'loss': 0.4667, 'learning_rate': 4.557890643440445e-06, 'epoch': 0.69}
+
69%|██████▉ | 8279/11952 [2:19:38<5:59:27, 5.87s/it]
69%|██████▉ | 8280/11952 [2:19:44<5:58:50, 5.86s/it]
{'loss': 0.4726, 'learning_rate': 4.5556173729173434e-06, 'epoch': 0.69}
+
69%|██████▉ | 8280/11952 [2:19:44<5:58:50, 5.86s/it]
69%|██████▉ | 8281/11952 [2:19:50<5:58:06, 5.85s/it]
{'loss': 0.4704, 'learning_rate': 4.55334450220706e-06, 'epoch': 0.69}
+
69%|██████▉ | 8281/11952 [2:19:50<5:58:06, 5.85s/it]
69%|██████▉ | 8282/11952 [2:19:55<5:55:39, 5.81s/it]
{'loss': 0.4842, 'learning_rate': 4.551072031476504e-06, 'epoch': 0.69}
+
69%|██████▉ | 8282/11952 [2:19:55<5:55:39, 5.81s/it]
69%|██████▉ | 8283/11952 [2:20:01<5:54:30, 5.80s/it]
{'loss': 0.4802, 'learning_rate': 4.548799960892552e-06, 'epoch': 0.69}
+
69%|██████▉ | 8283/11952 [2:20:01<5:54:30, 5.80s/it]
69%|██████▉ | 8284/11952 [2:20:07<5:56:43, 5.84s/it]
{'loss': 0.4843, 'learning_rate': 4.546528290622058e-06, 'epoch': 0.69}
+
69%|██████▉ | 8284/11952 [2:20:07<5:56:43, 5.84s/it]
69%|██████▉ | 8285/11952 [2:20:13<5:56:29, 5.83s/it]
{'loss': 0.4921, 'learning_rate': 4.544257020831843e-06, 'epoch': 0.69}
+
69%|██████▉ | 8285/11952 [2:20:13<5:56:29, 5.83s/it]
69%|██████▉ | 8286/11952 [2:20:19<5:56:55, 5.84s/it]
{'loss': 0.4769, 'learning_rate': 4.541986151688702e-06, 'epoch': 0.69}
+
69%|██████▉ | 8286/11952 [2:20:19<5:56:55, 5.84s/it]
69%|██████▉ | 8287/11952 [2:20:25<5:58:29, 5.87s/it]
{'loss': 0.45, 'learning_rate': 4.539715683359391e-06, 'epoch': 0.69}
+
69%|██████▉ | 8287/11952 [2:20:25<5:58:29, 5.87s/it]
69%|██████▉ | 8288/11952 [2:20:31<6:01:22, 5.92s/it]
{'loss': 0.4646, 'learning_rate': 4.537445616010655e-06, 'epoch': 0.69}
+
69%|██████▉ | 8288/11952 [2:20:31<6:01:22, 5.92s/it]
69%|██████▉ | 8289/11952 [2:20:37<6:03:43, 5.96s/it]
{'loss': 0.4756, 'learning_rate': 4.535175949809188e-06, 'epoch': 0.69}
+
69%|██████▉ | 8289/11952 [2:20:37<6:03:43, 5.96s/it]
69%|██████▉ | 8290/11952 [2:20:43<6:03:38, 5.96s/it]
{'loss': 0.4601, 'learning_rate': 4.532906684921672e-06, 'epoch': 0.69}
+
69%|██████▉ | 8290/11952 [2:20:43<6:03:38, 5.96s/it]
69%|██████▉ | 8291/11952 [2:20:49<6:05:23, 5.99s/it]
{'loss': 0.486, 'learning_rate': 4.53063782151475e-06, 'epoch': 0.69}
+
69%|██████▉ | 8291/11952 [2:20:49<6:05:23, 5.99s/it]
69%|██████▉ | 8292/11952 [2:20:55<6:00:58, 5.92s/it]
{'loss': 0.4705, 'learning_rate': 4.5283693597550384e-06, 'epoch': 0.69}
+
69%|██████▉ | 8292/11952 [2:20:55<6:00:58, 5.92s/it]
69%|██████▉ | 8293/11952 [2:21:00<5:59:49, 5.90s/it]
{'loss': 0.4619, 'learning_rate': 4.526101299809122e-06, 'epoch': 0.69}
+
69%|██████▉ | 8293/11952 [2:21:00<5:59:49, 5.90s/it]
69%|██████▉ | 8294/11952 [2:21:06<6:01:22, 5.93s/it]
{'loss': 0.4683, 'learning_rate': 4.523833641843554e-06, 'epoch': 0.69}
+
69%|██████▉ | 8294/11952 [2:21:06<6:01:22, 5.93s/it]
69%|██████▉ | 8295/11952 [2:21:12<5:53:07, 5.79s/it]
{'loss': 0.4627, 'learning_rate': 4.521566386024871e-06, 'epoch': 0.69}
+
69%|██████▉ | 8295/11952 [2:21:12<5:53:07, 5.79s/it]
69%|██████▉ | 8296/11952 [2:21:18<5:56:06, 5.84s/it]
{'loss': 0.483, 'learning_rate': 4.519299532519566e-06, 'epoch': 0.69}
+
69%|██████▉ | 8296/11952 [2:21:18<5:56:06, 5.84s/it]
69%|██████▉ | 8297/11952 [2:21:24<5:56:21, 5.85s/it]
{'loss': 0.4766, 'learning_rate': 4.517033081494109e-06, 'epoch': 0.69}
+
69%|██████▉ | 8297/11952 [2:21:24<5:56:21, 5.85s/it]
69%|██████▉ | 8298/11952 [2:21:29<5:52:48, 5.79s/it]
{'loss': 0.4708, 'learning_rate': 4.514767033114935e-06, 'epoch': 0.69}
+
69%|██████▉ | 8298/11952 [2:21:29<5:52:48, 5.79s/it]
69%|██████▉ | 8299/11952 [2:21:35<5:55:29, 5.84s/it]
{'loss': 0.4741, 'learning_rate': 4.512501387548453e-06, 'epoch': 0.69}
+
69%|██████▉ | 8299/11952 [2:21:35<5:55:29, 5.84s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+50 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...4 AutoResumeHook: Checking whether to suspend...
+
+3 AutoResumeHook: Checking whether to suspend...
+
69%|██████▉ | 8300/11952 [2:21:41<5:54:03, 5.82s/it]7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4742, 'learning_rate': 4.510236144961047e-06, 'epoch': 0.69}
+
69%|██████▉ | 8300/11952 [2:21:41<5:54:03, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
69%|██████▉ | 8301/11952 [2:22:12<13:29:25, 13.30s/it]
{'loss': 0.4632, 'learning_rate': 4.507971305519062e-06, 'epoch': 0.69}
+
69%|██████▉ | 8301/11952 [2:22:12<13:29:25, 13.30s/it]
69%|██████▉ | 8302/11952 [2:22:17<11:06:25, 10.96s/it]
{'loss': 0.468, 'learning_rate': 4.505706869388825e-06, 'epoch': 0.69}
+
69%|██████▉ | 8302/11952 [2:22:17<11:06:25, 10.96s/it]
69%|██████▉ | 8303/11952 [2:22:23<9:34:28, 9.45s/it]
{'loss': 0.4569, 'learning_rate': 4.503442836736624e-06, 'epoch': 0.69}
+
69%|██████▉ | 8303/11952 [2:22:23<9:34:28, 9.45s/it]
69%|██████▉ | 8304/11952 [2:22:29<8:28:10, 8.36s/it]
{'loss': 0.4734, 'learning_rate': 4.5011792077287175e-06, 'epoch': 0.69}
+
69%|██████▉ | 8304/11952 [2:22:29<8:28:10, 8.36s/it]
69%|██████▉ | 8305/11952 [2:22:35<7:42:40, 7.61s/it]
{'loss': 0.4751, 'learning_rate': 4.498915982531339e-06, 'epoch': 0.69}
+
69%|██████▉ | 8305/11952 [2:22:35<7:42:40, 7.61s/it]
69%|██████▉ | 8306/11952 [2:22:41<7:10:46, 7.09s/it]
{'loss': 0.4773, 'learning_rate': 4.49665316131069e-06, 'epoch': 0.69}
+
69%|██████▉ | 8306/11952 [2:22:41<7:10:46, 7.09s/it]
70%|██████▉ | 8307/11952 [2:22:46<6:44:31, 6.66s/it]
{'loss': 0.4506, 'learning_rate': 4.494390744232943e-06, 'epoch': 0.7}
+
70%|██████▉ | 8307/11952 [2:22:46<6:44:31, 6.66s/it]
70%|██████▉ | 8308/11952 [2:22:52<6:27:15, 6.38s/it]
{'loss': 0.4594, 'learning_rate': 4.492128731464237e-06, 'epoch': 0.7}
+
70%|██████▉ | 8308/11952 [2:22:52<6:27:15, 6.38s/it]
70%|██████▉ | 8309/11952 [2:22:58<6:23:57, 6.32s/it]
{'loss': 0.4719, 'learning_rate': 4.489867123170692e-06, 'epoch': 0.7}
+
70%|██████▉ | 8309/11952 [2:22:58<6:23:57, 6.32s/it]
70%|██████▉ | 8310/11952 [2:23:04<6:15:54, 6.19s/it]
{'loss': 0.4808, 'learning_rate': 4.487605919518382e-06, 'epoch': 0.7}
+
70%|██████▉ | 8310/11952 [2:23:04<6:15:54, 6.19s/it]
70%|██████▉ | 8311/11952 [2:23:10<6:13:36, 6.16s/it]
{'loss': 0.4713, 'learning_rate': 4.485345120673369e-06, 'epoch': 0.7}
+
70%|██████▉ | 8311/11952 [2:23:10<6:13:36, 6.16s/it]
70%|██████▉ | 8312/11952 [2:23:16<6:11:11, 6.12s/it]
{'loss': 0.4824, 'learning_rate': 4.4830847268016745e-06, 'epoch': 0.7}
+
70%|██████▉ | 8312/11952 [2:23:16<6:11:11, 6.12s/it]
70%|██████▉ | 8313/11952 [2:23:22<6:09:21, 6.09s/it]
{'loss': 0.4813, 'learning_rate': 4.480824738069291e-06, 'epoch': 0.7}
+
70%|██████▉ | 8313/11952 [2:23:22<6:09:21, 6.09s/it]
70%|██████▉ | 8314/11952 [2:23:29<6:09:49, 6.10s/it]
{'loss': 0.477, 'learning_rate': 4.478565154642178e-06, 'epoch': 0.7}
+
70%|██████▉ | 8314/11952 [2:23:29<6:09:49, 6.10s/it]
70%|██████▉ | 8315/11952 [2:23:35<6:11:59, 6.14s/it]
{'loss': 0.4704, 'learning_rate': 4.476305976686279e-06, 'epoch': 0.7}
+
70%|██████▉ | 8315/11952 [2:23:35<6:11:59, 6.14s/it]
70%|██████▉ | 8316/11952 [2:23:41<6:05:02, 6.02s/it]
{'loss': 0.4748, 'learning_rate': 4.474047204367494e-06, 'epoch': 0.7}
+
70%|██████▉ | 8316/11952 [2:23:41<6:05:02, 6.02s/it]
70%|██████▉ | 8317/11952 [2:23:46<5:59:30, 5.93s/it]
{'loss': 0.454, 'learning_rate': 4.4717888378516986e-06, 'epoch': 0.7}
+
70%|██████▉ | 8317/11952 [2:23:46<5:59:30, 5.93s/it]
70%|██████▉ | 8318/11952 [2:23:52<5:56:30, 5.89s/it]
{'loss': 0.4577, 'learning_rate': 4.469530877304737e-06, 'epoch': 0.7}
+
70%|██████▉ | 8318/11952 [2:23:52<5:56:30, 5.89s/it]
70%|██████▉ | 8319/11952 [2:23:58<6:02:06, 5.98s/it]
{'loss': 0.4852, 'learning_rate': 4.467273322892421e-06, 'epoch': 0.7}
+
70%|██████▉ | 8319/11952 [2:23:58<6:02:06, 5.98s/it]
70%|██████▉ | 8320/11952 [2:24:04<5:59:08, 5.93s/it]
{'loss': 0.4551, 'learning_rate': 4.465016174780544e-06, 'epoch': 0.7}
+
70%|██████▉ | 8320/11952 [2:24:04<5:59:08, 5.93s/it]
70%|██████▉ | 8321/11952 [2:24:10<5:55:43, 5.88s/it]
{'loss': 0.4726, 'learning_rate': 4.462759433134855e-06, 'epoch': 0.7}
+
70%|██████▉ | 8321/11952 [2:24:10<5:55:43, 5.88s/it]
70%|██████▉ | 8322/11952 [2:24:16<5:57:52, 5.92s/it]
{'loss': 0.5028, 'learning_rate': 4.4605030981210824e-06, 'epoch': 0.7}
+
70%|██████▉ | 8322/11952 [2:24:16<5:57:52, 5.92s/it]
70%|██████▉ | 8323/11952 [2:24:22<5:56:32, 5.89s/it]
{'loss': 0.4718, 'learning_rate': 4.4582471699049245e-06, 'epoch': 0.7}
+
70%|██████▉ | 8323/11952 [2:24:22<5:56:32, 5.89s/it]
70%|██████▉ | 8324/11952 [2:24:27<5:52:03, 5.82s/it]
{'loss': 0.479, 'learning_rate': 4.455991648652044e-06, 'epoch': 0.7}
+
70%|██████▉ | 8324/11952 [2:24:27<5:52:03, 5.82s/it]
70%|██████▉ | 8325/11952 [2:24:33<5:56:00, 5.89s/it]
{'loss': 0.4514, 'learning_rate': 4.453736534528077e-06, 'epoch': 0.7}
+
70%|██████▉ | 8325/11952 [2:24:33<5:56:00, 5.89s/it]
70%|██████▉ | 8326/11952 [2:24:39<5:55:41, 5.89s/it]
{'loss': 0.467, 'learning_rate': 4.45148182769863e-06, 'epoch': 0.7}
+
70%|██████▉ | 8326/11952 [2:24:39<5:55:41, 5.89s/it]
70%|██████▉ | 8327/11952 [2:24:45<5:56:01, 5.89s/it]
{'loss': 0.489, 'learning_rate': 4.449227528329281e-06, 'epoch': 0.7}
+
70%|██████▉ | 8327/11952 [2:24:45<5:56:01, 5.89s/it]
70%|██████▉ | 8328/11952 [2:24:51<5:53:46, 5.86s/it]
{'loss': 0.4569, 'learning_rate': 4.446973636585571e-06, 'epoch': 0.7}
+
70%|██████▉ | 8328/11952 [2:24:51<5:53:46, 5.86s/it]
70%|██████▉ | 8329/11952 [2:24:57<5:51:40, 5.82s/it]
{'loss': 0.4732, 'learning_rate': 4.444720152633023e-06, 'epoch': 0.7}
+
70%|██████▉ | 8329/11952 [2:24:57<5:51:40, 5.82s/it]
70%|██████▉ | 8330/11952 [2:25:02<5:51:03, 5.82s/it]
{'loss': 0.4608, 'learning_rate': 4.442467076637121e-06, 'epoch': 0.7}
+
70%|██████▉ | 8330/11952 [2:25:02<5:51:03, 5.82s/it]
70%|██████▉ | 8331/11952 [2:25:08<5:50:55, 5.81s/it]
{'loss': 0.4619, 'learning_rate': 4.440214408763318e-06, 'epoch': 0.7}
+
70%|██████▉ | 8331/11952 [2:25:08<5:50:55, 5.81s/it]
70%|██████▉ | 8332/11952 [2:25:14<5:57:22, 5.92s/it]
{'loss': 0.469, 'learning_rate': 4.437962149177047e-06, 'epoch': 0.7}
+
70%|██████▉ | 8332/11952 [2:25:14<5:57:22, 5.92s/it]
70%|██████▉ | 8333/11952 [2:25:20<5:53:13, 5.86s/it]
{'loss': 0.4816, 'learning_rate': 4.435710298043703e-06, 'epoch': 0.7}
+
70%|██████▉ | 8333/11952 [2:25:20<5:53:13, 5.86s/it]
70%|██████▉ | 8334/11952 [2:25:26<5:55:07, 5.89s/it]
{'loss': 0.4489, 'learning_rate': 4.43345885552865e-06, 'epoch': 0.7}
+
70%|██████▉ | 8334/11952 [2:25:26<5:55:07, 5.89s/it]
70%|██████▉ | 8335/11952 [2:25:32<5:50:44, 5.82s/it]
{'loss': 0.4529, 'learning_rate': 4.431207821797222e-06, 'epoch': 0.7}
+
70%|██████▉ | 8335/11952 [2:25:32<5:50:44, 5.82s/it]
70%|██████▉ | 8336/11952 [2:25:38<5:49:56, 5.81s/it]
{'loss': 0.4827, 'learning_rate': 4.428957197014732e-06, 'epoch': 0.7}
+
70%|██████▉ | 8336/11952 [2:25:38<5:49:56, 5.81s/it]
70%|██████▉ | 8337/11952 [2:25:44<5:53:36, 5.87s/it]
{'loss': 0.4554, 'learning_rate': 4.426706981346456e-06, 'epoch': 0.7}
+
70%|██████▉ | 8337/11952 [2:25:44<5:53:36, 5.87s/it]
70%|██████▉ | 8338/11952 [2:25:49<5:53:51, 5.87s/it]
{'loss': 0.4698, 'learning_rate': 4.424457174957637e-06, 'epoch': 0.7}
+
70%|██████▉ | 8338/11952 [2:25:49<5:53:51, 5.87s/it]
70%|██████▉ | 8339/11952 [2:25:55<5:57:14, 5.93s/it]
{'loss': 0.4708, 'learning_rate': 4.422207778013493e-06, 'epoch': 0.7}
+
70%|██████▉ | 8339/11952 [2:25:55<5:57:14, 5.93s/it]
70%|██████▉ | 8340/11952 [2:26:01<5:53:32, 5.87s/it]
{'loss': 0.4747, 'learning_rate': 4.419958790679205e-06, 'epoch': 0.7}
+
70%|██████▉ | 8340/11952 [2:26:01<5:53:32, 5.87s/it]
70%|██████▉ | 8341/11952 [2:26:07<5:49:02, 5.80s/it]
{'loss': 0.4694, 'learning_rate': 4.4177102131199405e-06, 'epoch': 0.7}
+
70%|██████▉ | 8341/11952 [2:26:07<5:49:02, 5.80s/it]
70%|██████▉ | 8342/11952 [2:26:13<5:48:28, 5.79s/it]
{'loss': 0.4597, 'learning_rate': 4.415462045500813e-06, 'epoch': 0.7}
+
70%|██████▉ | 8342/11952 [2:26:13<5:48:28, 5.79s/it]
70%|██████▉ | 8343/11952 [2:26:19<5:50:00, 5.82s/it]
{'loss': 0.4661, 'learning_rate': 4.41321428798693e-06, 'epoch': 0.7}
+
70%|██████▉ | 8343/11952 [2:26:19<5:50:00, 5.82s/it]
70%|██████▉ | 8344/11952 [2:26:24<5:46:51, 5.77s/it]
{'loss': 0.4799, 'learning_rate': 4.410966940743353e-06, 'epoch': 0.7}
+
70%|██████▉ | 8344/11952 [2:26:24<5:46:51, 5.77s/it]
70%|██████▉ | 8345/11952 [2:26:30<5:49:26, 5.81s/it]
{'loss': 0.4642, 'learning_rate': 4.408720003935116e-06, 'epoch': 0.7}
+
70%|██████▉ | 8345/11952 [2:26:30<5:49:26, 5.81s/it]
70%|██████▉ | 8346/11952 [2:26:36<5:44:56, 5.74s/it]
{'loss': 0.4708, 'learning_rate': 4.406473477727228e-06, 'epoch': 0.7}
+
70%|██████▉ | 8346/11952 [2:26:36<5:44:56, 5.74s/it]
70%|██████▉ | 8347/11952 [2:26:41<5:42:13, 5.70s/it]
{'loss': 0.4911, 'learning_rate': 4.404227362284661e-06, 'epoch': 0.7}
+
70%|██████▉ | 8347/11952 [2:26:41<5:42:13, 5.70s/it]
70%|██████▉ | 8348/11952 [2:26:47<5:45:50, 5.76s/it]
{'loss': 0.4707, 'learning_rate': 4.401981657772359e-06, 'epoch': 0.7}
+
70%|██████▉ | 8348/11952 [2:26:47<5:45:50, 5.76s/it]
70%|██████▉ | 8349/11952 [2:26:53<5:43:31, 5.72s/it]
{'loss': 0.4633, 'learning_rate': 4.399736364355243e-06, 'epoch': 0.7}
+
70%|██████▉ | 8349/11952 [2:26:53<5:43:31, 5.72s/it]1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+72 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
70%|██████▉ | 8350/11952 [2:26:59<5:43:54, 5.73s/it]
{'loss': 0.4862, 'learning_rate': 4.397491482198195e-06, 'epoch': 0.7}
+
70%|██████▉ | 8350/11952 [2:26:59<5:43:54, 5.73s/it]
70%|██████▉ | 8351/11952 [2:27:04<5:41:58, 5.70s/it]
{'loss': 0.461, 'learning_rate': 4.395247011466067e-06, 'epoch': 0.7}
+
70%|██████▉ | 8351/11952 [2:27:04<5:41:58, 5.70s/it]
70%|██████▉ | 8352/11952 [2:27:10<5:41:59, 5.70s/it]
{'loss': 0.4619, 'learning_rate': 4.393002952323691e-06, 'epoch': 0.7}
+
70%|██████▉ | 8352/11952 [2:27:10<5:41:59, 5.70s/it]
70%|██████▉ | 8353/11952 [2:27:16<5:50:11, 5.84s/it]
{'loss': 0.4857, 'learning_rate': 4.3907593049358555e-06, 'epoch': 0.7}
+
70%|██████▉ | 8353/11952 [2:27:16<5:50:11, 5.84s/it]
70%|██████▉ | 8354/11952 [2:27:22<5:46:11, 5.77s/it]
{'loss': 0.482, 'learning_rate': 4.388516069467327e-06, 'epoch': 0.7}
+
70%|██████▉ | 8354/11952 [2:27:22<5:46:11, 5.77s/it]
70%|██████▉ | 8355/11952 [2:27:28<5:49:08, 5.82s/it]
{'loss': 0.4656, 'learning_rate': 4.386273246082834e-06, 'epoch': 0.7}
+
70%|██████▉ | 8355/11952 [2:27:28<5:49:08, 5.82s/it]
70%|██████▉ | 8356/11952 [2:27:34<5:54:31, 5.92s/it]
{'loss': 0.4777, 'learning_rate': 4.384030834947088e-06, 'epoch': 0.7}
+
70%|██████▉ | 8356/11952 [2:27:34<5:54:31, 5.92s/it]
70%|██████▉ | 8357/11952 [2:27:39<5:50:19, 5.85s/it]
{'loss': 0.4786, 'learning_rate': 4.381788836224759e-06, 'epoch': 0.7}
+
70%|██████▉ | 8357/11952 [2:27:39<5:50:19, 5.85s/it]
70%|██████▉ | 8358/11952 [2:27:45<5:46:57, 5.79s/it]
{'loss': 0.4525, 'learning_rate': 4.379547250080491e-06, 'epoch': 0.7}
+
70%|██████▉ | 8358/11952 [2:27:45<5:46:57, 5.79s/it]
70%|██████▉ | 8359/11952 [2:27:51<5:50:39, 5.86s/it]
{'loss': 0.4711, 'learning_rate': 4.377306076678895e-06, 'epoch': 0.7}
+
70%|██████▉ | 8359/11952 [2:27:51<5:50:39, 5.86s/it]
70%|██████▉ | 8360/11952 [2:27:57<5:47:27, 5.80s/it]
{'loss': 0.4986, 'learning_rate': 4.375065316184556e-06, 'epoch': 0.7}
+
70%|██████▉ | 8360/11952 [2:27:57<5:47:27, 5.80s/it]
70%|██████▉ | 8361/11952 [2:28:03<5:46:34, 5.79s/it]
{'loss': 0.4564, 'learning_rate': 4.372824968762019e-06, 'epoch': 0.7}
+
70%|██████▉ | 8361/11952 [2:28:03<5:46:34, 5.79s/it]
70%|██████▉ | 8362/11952 [2:28:08<5:45:42, 5.78s/it]
{'loss': 0.4666, 'learning_rate': 4.37058503457581e-06, 'epoch': 0.7}
+
70%|██████▉ | 8362/11952 [2:28:08<5:45:42, 5.78s/it]
70%|██████▉ | 8363/11952 [2:28:14<5:49:32, 5.84s/it]
{'loss': 0.4745, 'learning_rate': 4.368345513790427e-06, 'epoch': 0.7}
+
70%|██████▉ | 8363/11952 [2:28:14<5:49:32, 5.84s/it]
70%|██████▉ | 8364/11952 [2:28:20<5:45:56, 5.79s/it]
{'loss': 0.5115, 'learning_rate': 4.366106406570325e-06, 'epoch': 0.7}
+
70%|██████▉ | 8364/11952 [2:28:20<5:45:56, 5.79s/it]
70%|██████▉ | 8365/11952 [2:28:26<5:45:52, 5.79s/it]
{'loss': 0.4606, 'learning_rate': 4.363867713079935e-06, 'epoch': 0.7}
+
70%|██████▉ | 8365/11952 [2:28:26<5:45:52, 5.79s/it]
70%|██████▉ | 8366/11952 [2:28:32<5:56:30, 5.96s/it]
{'loss': 0.4698, 'learning_rate': 4.361629433483659e-06, 'epoch': 0.7}
+
70%|██████▉ | 8366/11952 [2:28:32<5:56:30, 5.96s/it]
70%|███████ | 8367/11952 [2:28:38<5:52:54, 5.91s/it]
{'loss': 0.4697, 'learning_rate': 4.3593915679458645e-06, 'epoch': 0.7}
+
70%|███████ | 8367/11952 [2:28:38<5:52:54, 5.91s/it]
70%|███████ | 8368/11952 [2:28:44<5:49:17, 5.85s/it]
{'loss': 0.4661, 'learning_rate': 4.3571541166308926e-06, 'epoch': 0.7}
+
70%|███████ | 8368/11952 [2:28:44<5:49:17, 5.85s/it]
70%|███████ | 8369/11952 [2:28:49<5:45:22, 5.78s/it]
{'loss': 0.4622, 'learning_rate': 4.354917079703049e-06, 'epoch': 0.7}
+
70%|███████ | 8369/11952 [2:28:49<5:45:22, 5.78s/it]
70%|███████ | 8370/11952 [2:28:55<5:43:21, 5.75s/it]
{'loss': 0.4748, 'learning_rate': 4.352680457326617e-06, 'epoch': 0.7}
+
70%|███████ | 8370/11952 [2:28:55<5:43:21, 5.75s/it]
70%|███████ | 8371/11952 [2:29:01<5:42:18, 5.74s/it]
{'loss': 0.4748, 'learning_rate': 4.350444249665845e-06, 'epoch': 0.7}
+
70%|███████ | 8371/11952 [2:29:01<5:42:18, 5.74s/it]
70%|███████ | 8372/11952 [2:29:06<5:39:26, 5.69s/it]
{'loss': 0.4493, 'learning_rate': 4.348208456884945e-06, 'epoch': 0.7}
+
70%|███████ | 8372/11952 [2:29:06<5:39:26, 5.69s/it]
70%|███████ | 8373/11952 [2:29:12<5:44:39, 5.78s/it]
{'loss': 0.486, 'learning_rate': 4.345973079148111e-06, 'epoch': 0.7}
+
70%|███████ | 8373/11952 [2:29:12<5:44:39, 5.78s/it]
70%|███████ | 8374/11952 [2:29:18<5:43:28, 5.76s/it]
{'loss': 0.4661, 'learning_rate': 4.343738116619499e-06, 'epoch': 0.7}
+
70%|███████ | 8374/11952 [2:29:18<5:43:28, 5.76s/it]
70%|███████ | 8375/11952 [2:29:23<5:40:06, 5.70s/it]
{'loss': 0.4423, 'learning_rate': 4.3415035694632326e-06, 'epoch': 0.7}
+
70%|███████ | 8375/11952 [2:29:23<5:40:06, 5.70s/it]
70%|███████ | 8376/11952 [2:29:29<5:37:46, 5.67s/it]
{'loss': 0.4572, 'learning_rate': 4.339269437843405e-06, 'epoch': 0.7}
+
70%|███████ | 8376/11952 [2:29:29<5:37:46, 5.67s/it]
70%|███████ | 8377/11952 [2:29:35<5:41:07, 5.73s/it]
{'loss': 0.4763, 'learning_rate': 4.337035721924089e-06, 'epoch': 0.7}
+
70%|███████ | 8377/11952 [2:29:35<5:41:07, 5.73s/it]
70%|███████ | 8378/11952 [2:29:41<5:47:17, 5.83s/it]
{'loss': 0.4874, 'learning_rate': 4.334802421869316e-06, 'epoch': 0.7}
+
70%|███████ | 8378/11952 [2:29:41<5:47:17, 5.83s/it]
70%|███████ | 8379/11952 [2:29:47<5:48:34, 5.85s/it]
{'loss': 0.4534, 'learning_rate': 4.332569537843089e-06, 'epoch': 0.7}
+
70%|███████ | 8379/11952 [2:29:47<5:48:34, 5.85s/it]
70%|███████ | 8380/11952 [2:29:53<5:46:40, 5.82s/it]
{'loss': 0.4533, 'learning_rate': 4.330337070009382e-06, 'epoch': 0.7}
+
70%|███████ | 8380/11952 [2:29:53<5:46:40, 5.82s/it]
70%|███████ | 8381/11952 [2:29:58<5:43:30, 5.77s/it]
{'loss': 0.461, 'learning_rate': 4.328105018532136e-06, 'epoch': 0.7}
+
70%|███████ | 8381/11952 [2:29:58<5:43:30, 5.77s/it]
70%|███████ | 8382/11952 [2:30:04<5:46:45, 5.83s/it]
{'loss': 0.4669, 'learning_rate': 4.32587338357527e-06, 'epoch': 0.7}
+
70%|███████ | 8382/11952 [2:30:04<5:46:45, 5.83s/it]
70%|███████ | 8383/11952 [2:30:10<5:50:20, 5.89s/it]
{'loss': 0.4619, 'learning_rate': 4.323642165302658e-06, 'epoch': 0.7}
+
70%|███████ | 8383/11952 [2:30:10<5:50:20, 5.89s/it]
70%|███████ | 8384/11952 [2:30:16<5:55:21, 5.98s/it]
{'loss': 0.4544, 'learning_rate': 4.321411363878159e-06, 'epoch': 0.7}
+
70%|███████ | 8384/11952 [2:30:16<5:55:21, 5.98s/it]
70%|███████ | 8385/11952 [2:30:22<5:50:29, 5.90s/it]
{'loss': 0.4866, 'learning_rate': 4.319180979465592e-06, 'epoch': 0.7}
+
70%|███████ | 8385/11952 [2:30:22<5:50:29, 5.90s/it]
70%|███████ | 8386/11952 [2:30:28<5:49:17, 5.88s/it]
{'loss': 0.4647, 'learning_rate': 4.316951012228744e-06, 'epoch': 0.7}
+
70%|███████ | 8386/11952 [2:30:28<5:49:17, 5.88s/it]
70%|███████ | 8387/11952 [2:30:34<5:53:49, 5.95s/it]
{'loss': 0.4605, 'learning_rate': 4.314721462331376e-06, 'epoch': 0.7}
+
70%|███████ | 8387/11952 [2:30:34<5:53:49, 5.95s/it]
70%|███████ | 8388/11952 [2:30:40<5:49:54, 5.89s/it]
{'loss': 0.4656, 'learning_rate': 4.312492329937218e-06, 'epoch': 0.7}
+
70%|███████ | 8388/11952 [2:30:40<5:49:54, 5.89s/it]
70%|███████ | 8389/11952 [2:30:46<5:50:29, 5.90s/it]
{'loss': 0.4996, 'learning_rate': 4.310263615209963e-06, 'epoch': 0.7}
+
70%|███████ | 8389/11952 [2:30:46<5:50:29, 5.90s/it]
70%|███████ | 8390/11952 [2:30:52<5:53:49, 5.96s/it]
{'loss': 0.4711, 'learning_rate': 4.308035318313286e-06, 'epoch': 0.7}
+
70%|███████ | 8390/11952 [2:30:52<5:53:49, 5.96s/it]
70%|███████ | 8391/11952 [2:30:58<5:51:26, 5.92s/it]
{'loss': 0.4672, 'learning_rate': 4.305807439410822e-06, 'epoch': 0.7}
+
70%|███████ | 8391/11952 [2:30:58<5:51:26, 5.92s/it]
70%|███████ | 8392/11952 [2:31:04<5:53:53, 5.96s/it]
{'loss': 0.4885, 'learning_rate': 4.30357997866617e-06, 'epoch': 0.7}
+
70%|███████ | 8392/11952 [2:31:04<5:53:53, 5.96s/it]
70%|███████ | 8393/11952 [2:31:09<5:48:59, 5.88s/it]
{'loss': 0.4748, 'learning_rate': 4.301352936242916e-06, 'epoch': 0.7}
+
70%|███████ | 8393/11952 [2:31:09<5:48:59, 5.88s/it]
70%|███████ | 8394/11952 [2:31:15<5:49:16, 5.89s/it]
{'loss': 0.4615, 'learning_rate': 4.2991263123046005e-06, 'epoch': 0.7}
+
70%|███████ | 8394/11952 [2:31:15<5:49:16, 5.89s/it]
70%|███████ | 8395/11952 [2:31:21<5:53:23, 5.96s/it]
{'loss': 0.4693, 'learning_rate': 4.296900107014735e-06, 'epoch': 0.7}
+
70%|███████ | 8395/11952 [2:31:21<5:53:23, 5.96s/it]
70%|███████ | 8396/11952 [2:31:27<5:51:54, 5.94s/it]
{'loss': 0.4776, 'learning_rate': 4.294674320536803e-06, 'epoch': 0.7}
+
70%|███████ | 8396/11952 [2:31:27<5:51:54, 5.94s/it]
70%|███████ | 8397/11952 [2:31:33<5:48:15, 5.88s/it]
{'loss': 0.4694, 'learning_rate': 4.292448953034261e-06, 'epoch': 0.7}
+
70%|███████ | 8397/11952 [2:31:33<5:48:15, 5.88s/it]
70%|███████ | 8398/11952 [2:31:39<5:48:40, 5.89s/it]
{'loss': 0.4633, 'learning_rate': 4.290224004670529e-06, 'epoch': 0.7}
+
70%|███████ | 8398/11952 [2:31:39<5:48:40, 5.89s/it]
70%|███████ | 8399/11952 [2:31:45<5:45:00, 5.83s/it]
{'loss': 0.4731, 'learning_rate': 4.287999475608997e-06, 'epoch': 0.7}
+
70%|███████ | 8399/11952 [2:31:45<5:45:00, 5.83s/it]4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
70%|███████ | 8400/11952 [2:31:50<5:40:29, 5.75s/it]
{'loss': 0.4514, 'learning_rate': 4.285775366013026e-06, 'epoch': 0.7}
+
70%|███████ | 8400/11952 [2:31:50<5:40:29, 5.75s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
70%|███████ | 8401/11952 [2:32:20<12:42:45, 12.89s/it]
{'loss': 0.4551, 'learning_rate': 4.283551676045945e-06, 'epoch': 0.7}
+
70%|███████ | 8401/11952 [2:32:20<12:42:45, 12.89s/it]
70%|███████ | 8402/11952 [2:32:26<10:38:00, 10.78s/it]
{'loss': 0.4775, 'learning_rate': 4.281328405871048e-06, 'epoch': 0.7}
+
70%|███████ | 8402/11952 [2:32:26<10:38:00, 10.78s/it]
70%|███████ | 8403/11952 [2:32:31<9:09:42, 9.29s/it]
{'loss': 0.4647, 'learning_rate': 4.279105555651608e-06, 'epoch': 0.7}
+
70%|███████ | 8403/11952 [2:32:32<9:09:42, 9.29s/it]
70%|███████ | 8404/11952 [2:32:37<8:06:52, 8.23s/it]
{'loss': 0.47, 'learning_rate': 4.276883125550864e-06, 'epoch': 0.7}
+
70%|███████ | 8404/11952 [2:32:37<8:06:52, 8.23s/it]
70%|███████ | 8405/11952 [2:32:43<7:17:29, 7.40s/it]
{'loss': 0.4737, 'learning_rate': 4.27466111573202e-06, 'epoch': 0.7}
+
70%|███████ | 8405/11952 [2:32:43<7:17:29, 7.40s/it]
70%|███████ | 8406/11952 [2:32:49<6:54:30, 7.01s/it]
{'loss': 0.4676, 'learning_rate': 4.272439526358249e-06, 'epoch': 0.7}
+
70%|███████ | 8406/11952 [2:32:49<6:54:30, 7.01s/it]
70%|███████ | 8407/11952 [2:32:55<6:31:57, 6.63s/it]
{'loss': 0.459, 'learning_rate': 4.270218357592696e-06, 'epoch': 0.7}
+
70%|███████ | 8407/11952 [2:32:55<6:31:57, 6.63s/it]
70%|███████ | 8408/11952 [2:33:00<6:18:05, 6.40s/it]
{'loss': 0.4788, 'learning_rate': 4.267997609598477e-06, 'epoch': 0.7}
+
70%|███████ | 8408/11952 [2:33:00<6:18:05, 6.40s/it]
70%|███████ | 8409/11952 [2:33:06<6:08:17, 6.24s/it]
{'loss': 0.4554, 'learning_rate': 4.26577728253867e-06, 'epoch': 0.7}
+
70%|███████ | 8409/11952 [2:33:06<6:08:17, 6.24s/it]
70%|███████ | 8410/11952 [2:33:12<6:03:58, 6.17s/it]
{'loss': 0.4793, 'learning_rate': 4.263557376576326e-06, 'epoch': 0.7}
+
70%|███████ | 8410/11952 [2:33:12<6:03:58, 6.17s/it]
70%|███████ | 8411/11952 [2:33:18<5:53:38, 5.99s/it]
{'loss': 0.4776, 'learning_rate': 4.261337891874473e-06, 'epoch': 0.7}
+
70%|███████ | 8411/11952 [2:33:18<5:53:38, 5.99s/it]
70%|███████ | 8412/11952 [2:33:24<5:49:06, 5.92s/it]
{'loss': 0.4613, 'learning_rate': 4.259118828596096e-06, 'epoch': 0.7}
+
70%|███████ | 8412/11952 [2:33:24<5:49:06, 5.92s/it]
70%|███████ | 8413/11952 [2:33:29<5:42:21, 5.80s/it]
{'loss': 0.4708, 'learning_rate': 4.25690018690415e-06, 'epoch': 0.7}
+
70%|███████ | 8413/11952 [2:33:29<5:42:21, 5.80s/it]
70%|███████ | 8414/11952 [2:33:35<5:37:03, 5.72s/it]
{'loss': 0.4675, 'learning_rate': 4.254681966961571e-06, 'epoch': 0.7}
+
70%|███████ | 8414/11952 [2:33:35<5:37:03, 5.72s/it]
70%|███████ | 8415/11952 [2:33:41<5:41:01, 5.78s/it]
{'loss': 0.4669, 'learning_rate': 4.2524641689312526e-06, 'epoch': 0.7}
+
70%|███████ | 8415/11952 [2:33:41<5:41:01, 5.78s/it]
70%|███████ | 8416/11952 [2:33:47<5:42:51, 5.82s/it]
{'loss': 0.4417, 'learning_rate': 4.250246792976058e-06, 'epoch': 0.7}
+
70%|███████ | 8416/11952 [2:33:47<5:42:51, 5.82s/it]
70%|███████ | 8417/11952 [2:33:53<5:48:43, 5.92s/it]
{'loss': 0.4719, 'learning_rate': 4.248029839258821e-06, 'epoch': 0.7}
+
70%|███████ | 8417/11952 [2:33:53<5:48:43, 5.92s/it]
70%|███████ | 8418/11952 [2:33:58<5:42:35, 5.82s/it]
{'loss': 0.4622, 'learning_rate': 4.245813307942354e-06, 'epoch': 0.7}
+
70%|███████ | 8418/11952 [2:33:58<5:42:35, 5.82s/it]
70%|███████ | 8419/11952 [2:34:04<5:44:28, 5.85s/it]
{'loss': 0.4852, 'learning_rate': 4.243597199189422e-06, 'epoch': 0.7}
+
70%|███████ | 8419/11952 [2:34:04<5:44:28, 5.85s/it]
70%|███████ | 8420/11952 [2:34:10<5:42:53, 5.82s/it]
{'loss': 0.4809, 'learning_rate': 4.241381513162769e-06, 'epoch': 0.7}
+
70%|███████ | 8420/11952 [2:34:10<5:42:53, 5.82s/it]
70%|███████ | 8421/11952 [2:34:16<5:38:28, 5.75s/it]
{'loss': 0.4711, 'learning_rate': 4.239166250025106e-06, 'epoch': 0.7}
+
70%|███████ | 8421/11952 [2:34:16<5:38:28, 5.75s/it]
70%|███████ | 8422/11952 [2:34:22<5:47:10, 5.90s/it]
{'loss': 0.4572, 'learning_rate': 4.236951409939109e-06, 'epoch': 0.7}
+
70%|███████ | 8422/11952 [2:34:22<5:47:10, 5.90s/it]
70%|███████ | 8423/11952 [2:34:28<5:45:12, 5.87s/it]
{'loss': 0.4833, 'learning_rate': 4.234736993067434e-06, 'epoch': 0.7}
+
70%|███████ | 8423/11952 [2:34:28<5:45:12, 5.87s/it]
70%|███████ | 8424/11952 [2:34:33<5:43:22, 5.84s/it]
{'loss': 0.4804, 'learning_rate': 4.2325229995726915e-06, 'epoch': 0.7}
+
70%|███████ | 8424/11952 [2:34:33<5:43:22, 5.84s/it]
70%|███████ | 8425/11952 [2:34:39<5:41:19, 5.81s/it]
{'loss': 0.456, 'learning_rate': 4.230309429617474e-06, 'epoch': 0.7}
+
70%|███████ | 8425/11952 [2:34:39<5:41:19, 5.81s/it]
70%|███████ | 8426/11952 [2:34:45<5:38:53, 5.77s/it]
{'loss': 0.4626, 'learning_rate': 4.228096283364335e-06, 'epoch': 0.7}
+
70%|███████ | 8426/11952 [2:34:45<5:38:53, 5.77s/it]
71%|███████ | 8427/11952 [2:34:51<5:45:50, 5.89s/it]
{'loss': 0.4777, 'learning_rate': 4.2258835609757965e-06, 'epoch': 0.71}
+
71%|███████ | 8427/11952 [2:34:51<5:45:50, 5.89s/it]
71%|███████ | 8428/11952 [2:34:57<5:46:10, 5.89s/it]
{'loss': 0.4482, 'learning_rate': 4.223671262614354e-06, 'epoch': 0.71}
+
71%|███████ | 8428/11952 [2:34:57<5:46:10, 5.89s/it]
71%|███████ | 8429/11952 [2:35:03<5:46:21, 5.90s/it]
{'loss': 0.4631, 'learning_rate': 4.221459388442467e-06, 'epoch': 0.71}
+
71%|███████ | 8429/11952 [2:35:03<5:46:21, 5.90s/it]
71%|███████ | 8430/11952 [2:35:08<5:41:45, 5.82s/it]
{'loss': 0.451, 'learning_rate': 4.219247938622566e-06, 'epoch': 0.71}
+
71%|███████ | 8430/11952 [2:35:08<5:41:45, 5.82s/it]
71%|███████ | 8431/11952 [2:35:14<5:43:16, 5.85s/it]
{'loss': 0.4781, 'learning_rate': 4.217036913317054e-06, 'epoch': 0.71}
+
71%|███████ | 8431/11952 [2:35:14<5:43:16, 5.85s/it]
71%|███████ | 8432/11952 [2:35:20<5:40:53, 5.81s/it]
{'loss': 0.4649, 'learning_rate': 4.214826312688299e-06, 'epoch': 0.71}
+
71%|███████ | 8432/11952 [2:35:20<5:40:53, 5.81s/it]
71%|███████ | 8433/11952 [2:35:26<5:36:26, 5.74s/it]
{'loss': 0.4937, 'learning_rate': 4.212616136898634e-06, 'epoch': 0.71}
+
71%|███████ | 8433/11952 [2:35:26<5:36:26, 5.74s/it]
71%|███████ | 8434/11952 [2:35:32<5:40:06, 5.80s/it]
{'loss': 0.4511, 'learning_rate': 4.210406386110371e-06, 'epoch': 0.71}
+
71%|███████ | 8434/11952 [2:35:32<5:40:06, 5.80s/it]
71%|███████ | 8435/11952 [2:35:37<5:40:53, 5.82s/it]
{'loss': 0.4606, 'learning_rate': 4.208197060485783e-06, 'epoch': 0.71}
+
71%|███████ | 8435/11952 [2:35:37<5:40:53, 5.82s/it]
71%|███████ | 8436/11952 [2:35:43<5:38:50, 5.78s/it]
{'loss': 0.4546, 'learning_rate': 4.205988160187113e-06, 'epoch': 0.71}
+
71%|███████ | 8436/11952 [2:35:43<5:38:50, 5.78s/it]
71%|███████ | 8437/11952 [2:35:49<5:37:08, 5.75s/it]
{'loss': 0.4751, 'learning_rate': 4.20377968537657e-06, 'epoch': 0.71}
+
71%|███████ | 8437/11952 [2:35:49<5:37:08, 5.75s/it]
71%|███████ | 8438/11952 [2:35:55<5:42:12, 5.84s/it]
{'loss': 0.4677, 'learning_rate': 4.201571636216343e-06, 'epoch': 0.71}
+
71%|███████ | 8438/11952 [2:35:55<5:42:12, 5.84s/it]
71%|███████ | 8439/11952 [2:36:01<5:44:08, 5.88s/it]
{'loss': 0.4771, 'learning_rate': 4.199364012868575e-06, 'epoch': 0.71}
+
71%|███████ | 8439/11952 [2:36:01<5:44:08, 5.88s/it]
71%|███████ | 8440/11952 [2:36:07<5:46:14, 5.92s/it]
{'loss': 0.4534, 'learning_rate': 4.197156815495389e-06, 'epoch': 0.71}
+
71%|███████ | 8440/11952 [2:36:07<5:46:14, 5.92s/it]
71%|███████ | 8441/11952 [2:36:13<5:44:58, 5.90s/it]
{'loss': 0.4552, 'learning_rate': 4.194950044258871e-06, 'epoch': 0.71}
+
71%|███████ | 8441/11952 [2:36:13<5:44:58, 5.90s/it]
71%|███████ | 8442/11952 [2:36:18<5:44:15, 5.88s/it]
{'loss': 0.4798, 'learning_rate': 4.192743699321075e-06, 'epoch': 0.71}
+
71%|███████ | 8442/11952 [2:36:18<5:44:15, 5.88s/it]
71%|███████ | 8443/11952 [2:36:24<5:39:21, 5.80s/it]
{'loss': 0.4611, 'learning_rate': 4.190537780844026e-06, 'epoch': 0.71}
+
71%|███████ | 8443/11952 [2:36:24<5:39:21, 5.80s/it]
71%|███████ | 8444/11952 [2:36:30<5:40:20, 5.82s/it]
{'loss': 0.4666, 'learning_rate': 4.188332288989721e-06, 'epoch': 0.71}
+
71%|███████ | 8444/11952 [2:36:30<5:40:20, 5.82s/it]
71%|███████ | 8445/11952 [2:36:36<5:39:37, 5.81s/it]
{'loss': 0.4572, 'learning_rate': 4.186127223920118e-06, 'epoch': 0.71}
+
71%|███████ | 8445/11952 [2:36:36<5:39:37, 5.81s/it]
71%|███████ | 8446/11952 [2:36:41<5:38:06, 5.79s/it]
{'loss': 0.4646, 'learning_rate': 4.183922585797152e-06, 'epoch': 0.71}
+
71%|███████ | 8446/11952 [2:36:41<5:38:06, 5.79s/it]
71%|███████ | 8447/11952 [2:36:47<5:39:24, 5.81s/it]
{'loss': 0.4711, 'learning_rate': 4.181718374782722e-06, 'epoch': 0.71}
+
71%|███████ | 8447/11952 [2:36:47<5:39:24, 5.81s/it]
71%|███████ | 8448/11952 [2:36:53<5:35:52, 5.75s/it]
{'loss': 0.4616, 'learning_rate': 4.179514591038692e-06, 'epoch': 0.71}
+
71%|███████ | 8448/11952 [2:36:53<5:35:52, 5.75s/it]
71%|███████ | 8449/11952 [2:36:59<5:34:51, 5.74s/it]
{'loss': 0.473, 'learning_rate': 4.177311234726904e-06, 'epoch': 0.71}
+
71%|███████ | 8449/11952 [2:36:59<5:34:51, 5.74s/it]1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
71%|███████ | 8450/11952 [2:37:04<5:35:00, 5.74s/it]
{'loss': 0.4671, 'learning_rate': 4.175108306009159e-06, 'epoch': 0.71}
+
71%|███████ | 8450/11952 [2:37:04<5:35:00, 5.74s/it]
71%|███████ | 8451/11952 [2:37:10<5:30:30, 5.66s/it]
{'loss': 0.4892, 'learning_rate': 4.172905805047229e-06, 'epoch': 0.71}
+
71%|███████ | 8451/11952 [2:37:10<5:30:30, 5.66s/it]
71%|███████ | 8452/11952 [2:37:16<5:34:41, 5.74s/it]
{'loss': 0.4654, 'learning_rate': 4.170703732002864e-06, 'epoch': 0.71}
+
71%|███████ | 8452/11952 [2:37:16<5:34:41, 5.74s/it]
71%|███████ | 8453/11952 [2:37:22<5:35:00, 5.74s/it]
{'loss': 0.4498, 'learning_rate': 4.168502087037771e-06, 'epoch': 0.71}
+
71%|███████ | 8453/11952 [2:37:22<5:35:00, 5.74s/it]
71%|███████ | 8454/11952 [2:37:27<5:34:25, 5.74s/it]
{'loss': 0.493, 'learning_rate': 4.166300870313625e-06, 'epoch': 0.71}
+
71%|███████ | 8454/11952 [2:37:27<5:34:25, 5.74s/it]
71%|███████ | 8455/11952 [2:37:33<5:35:57, 5.76s/it]
{'loss': 0.4726, 'learning_rate': 4.164100081992084e-06, 'epoch': 0.71}
+
71%|███████ | 8455/11952 [2:37:33<5:35:57, 5.76s/it]
71%|███████ | 8456/11952 [2:37:39<5:35:11, 5.75s/it]
{'loss': 0.4567, 'learning_rate': 4.161899722234759e-06, 'epoch': 0.71}
+
71%|███████ | 8456/11952 [2:37:39<5:35:11, 5.75s/it]
71%|███████ | 8457/11952 [2:37:45<5:39:46, 5.83s/it]
{'loss': 0.4695, 'learning_rate': 4.159699791203237e-06, 'epoch': 0.71}
+
71%|███████ | 8457/11952 [2:37:45<5:39:46, 5.83s/it]
71%|███████ | 8458/11952 [2:37:50<5:33:39, 5.73s/it]
{'loss': 0.4722, 'learning_rate': 4.157500289059065e-06, 'epoch': 0.71}
+
71%|███████ | 8458/11952 [2:37:50<5:33:39, 5.73s/it]
71%|███████ | 8459/11952 [2:37:56<5:37:29, 5.80s/it]
{'loss': 0.4779, 'learning_rate': 4.155301215963776e-06, 'epoch': 0.71}
+
71%|███████ | 8459/11952 [2:37:56<5:37:29, 5.80s/it]
71%|███████ | 8460/11952 [2:38:02<5:34:43, 5.75s/it]
{'loss': 0.4611, 'learning_rate': 4.153102572078855e-06, 'epoch': 0.71}
+
71%|███████ | 8460/11952 [2:38:02<5:34:43, 5.75s/it]
71%|███████ | 8461/11952 [2:38:08<5:39:46, 5.84s/it]
{'loss': 0.4846, 'learning_rate': 4.150904357565763e-06, 'epoch': 0.71}
+
71%|███████ | 8461/11952 [2:38:08<5:39:46, 5.84s/it]
71%|███████ | 8462/11952 [2:38:14<5:38:52, 5.83s/it]
{'loss': 0.4619, 'learning_rate': 4.148706572585927e-06, 'epoch': 0.71}
+
71%|███████ | 8462/11952 [2:38:14<5:38:52, 5.83s/it]
71%|███████ | 8463/11952 [2:38:20<5:45:13, 5.94s/it]
{'loss': 0.4694, 'learning_rate': 4.146509217300738e-06, 'epoch': 0.71}
+
71%|███████ | 8463/11952 [2:38:20<5:45:13, 5.94s/it]
71%|███████ | 8464/11952 [2:38:26<5:38:47, 5.83s/it]
{'loss': 0.4676, 'learning_rate': 4.14431229187157e-06, 'epoch': 0.71}
+
71%|███████ | 8464/11952 [2:38:26<5:38:47, 5.83s/it]
71%|███████ | 8465/11952 [2:38:31<5:37:08, 5.80s/it]
{'loss': 0.4772, 'learning_rate': 4.142115796459748e-06, 'epoch': 0.71}
+
71%|███████ | 8465/11952 [2:38:31<5:37:08, 5.80s/it]
71%|███████ | 8466/11952 [2:38:37<5:32:43, 5.73s/it]
{'loss': 0.4591, 'learning_rate': 4.13991973122658e-06, 'epoch': 0.71}
+
71%|███████ | 8466/11952 [2:38:37<5:32:43, 5.73s/it]
71%|███████ | 8467/11952 [2:38:43<5:36:30, 5.79s/it]
{'loss': 0.4703, 'learning_rate': 4.137724096333334e-06, 'epoch': 0.71}
+
71%|███████ | 8467/11952 [2:38:43<5:36:30, 5.79s/it]
71%|███████ | 8468/11952 [2:38:49<5:42:14, 5.89s/it]
{'loss': 0.4667, 'learning_rate': 4.135528891941246e-06, 'epoch': 0.71}
+
71%|███████ | 8468/11952 [2:38:49<5:42:14, 5.89s/it]
71%|███████ | 8469/11952 [2:38:55<5:38:06, 5.82s/it]
{'loss': 0.4814, 'learning_rate': 4.133334118211526e-06, 'epoch': 0.71}
+
71%|███████ | 8469/11952 [2:38:55<5:38:06, 5.82s/it]
71%|███████ | 8470/11952 [2:39:00<5:34:12, 5.76s/it]
{'loss': 0.463, 'learning_rate': 4.131139775305346e-06, 'epoch': 0.71}
+
71%|███████ | 8470/11952 [2:39:00<5:34:12, 5.76s/it]
71%|███████ | 8471/11952 [2:39:06<5:38:10, 5.83s/it]
{'loss': 0.4672, 'learning_rate': 4.128945863383846e-06, 'epoch': 0.71}
+
71%|███████ | 8471/11952 [2:39:06<5:38:10, 5.83s/it]
71%|███████ | 8472/11952 [2:39:12<5:39:18, 5.85s/it]
{'loss': 0.4525, 'learning_rate': 4.126752382608147e-06, 'epoch': 0.71}
+
71%|███████ | 8472/11952 [2:39:12<5:39:18, 5.85s/it]
71%|███████ | 8473/11952 [2:39:18<5:37:24, 5.82s/it]
{'loss': 0.4729, 'learning_rate': 4.124559333139324e-06, 'epoch': 0.71}
+
71%|███████ | 8473/11952 [2:39:18<5:37:24, 5.82s/it]
71%|███████ | 8474/11952 [2:39:23<5:34:02, 5.76s/it]
{'loss': 0.4727, 'learning_rate': 4.122366715138426e-06, 'epoch': 0.71}
+
71%|███████ | 8474/11952 [2:39:23<5:34:02, 5.76s/it]
71%|███████ | 8475/11952 [2:39:29<5:34:57, 5.78s/it]
{'loss': 0.4635, 'learning_rate': 4.1201745287664664e-06, 'epoch': 0.71}
+
71%|███████ | 8475/11952 [2:39:29<5:34:57, 5.78s/it]
71%|███████ | 8476/11952 [2:39:35<5:36:39, 5.81s/it]
{'loss': 0.4769, 'learning_rate': 4.117982774184436e-06, 'epoch': 0.71}
+
71%|███████ | 8476/11952 [2:39:35<5:36:39, 5.81s/it]
71%|███████ | 8477/11952 [2:39:41<5:37:16, 5.82s/it]
{'loss': 0.4583, 'learning_rate': 4.115791451553286e-06, 'epoch': 0.71}
+
71%|███████ | 8477/11952 [2:39:41<5:37:16, 5.82s/it]
71%|███████ | 8478/11952 [2:39:47<5:34:49, 5.78s/it]
{'loss': 0.476, 'learning_rate': 4.1136005610339335e-06, 'epoch': 0.71}
+
71%|███████ | 8478/11952 [2:39:47<5:34:49, 5.78s/it]
71%|███████ | 8479/11952 [2:39:52<5:32:35, 5.75s/it]
{'loss': 0.4648, 'learning_rate': 4.111410102787276e-06, 'epoch': 0.71}
+
71%|███████ | 8479/11952 [2:39:52<5:32:35, 5.75s/it]
71%|███████ | 8480/11952 [2:39:58<5:33:53, 5.77s/it]
{'loss': 0.4614, 'learning_rate': 4.109220076974168e-06, 'epoch': 0.71}
+
71%|███████ | 8480/11952 [2:39:58<5:33:53, 5.77s/it]
71%|███████ | 8481/11952 [2:40:04<5:37:24, 5.83s/it]
{'loss': 0.482, 'learning_rate': 4.107030483755436e-06, 'epoch': 0.71}
+
71%|███████ | 8481/11952 [2:40:04<5:37:24, 5.83s/it]
71%|███████ | 8482/11952 [2:40:10<5:42:01, 5.91s/it]
{'loss': 0.4816, 'learning_rate': 4.104841323291876e-06, 'epoch': 0.71}
+
71%|███████ | 8482/11952 [2:40:10<5:42:01, 5.91s/it]
71%|███████ | 8483/11952 [2:40:16<5:46:50, 6.00s/it]
{'loss': 0.4644, 'learning_rate': 4.102652595744248e-06, 'epoch': 0.71}
+
71%|███████ | 8483/11952 [2:40:16<5:46:50, 6.00s/it]
71%|███████ | 8484/11952 [2:40:23<5:48:20, 6.03s/it]
{'loss': 0.4676, 'learning_rate': 4.100464301273282e-06, 'epoch': 0.71}
+
71%|███████ | 8484/11952 [2:40:23<5:48:20, 6.03s/it]
71%|███████ | 8485/11952 [2:40:28<5:45:22, 5.98s/it]
{'loss': 0.4865, 'learning_rate': 4.098276440039681e-06, 'epoch': 0.71}
+
71%|███████ | 8485/11952 [2:40:28<5:45:22, 5.98s/it]
71%|███████ | 8486/11952 [2:40:34<5:44:15, 5.96s/it]
{'loss': 0.472, 'learning_rate': 4.0960890122041095e-06, 'epoch': 0.71}
+
71%|███████ | 8486/11952 [2:40:34<5:44:15, 5.96s/it]
71%|███████ | 8487/11952 [2:40:40<5:39:46, 5.88s/it]
{'loss': 0.4773, 'learning_rate': 4.093902017927208e-06, 'epoch': 0.71}
+
71%|███████ | 8487/11952 [2:40:40<5:39:46, 5.88s/it]
71%|███████ | 8488/11952 [2:40:46<5:44:54, 5.97s/it]
{'loss': 0.4894, 'learning_rate': 4.091715457369577e-06, 'epoch': 0.71}
+
71%|███████ | 8488/11952 [2:40:46<5:44:54, 5.97s/it]
71%|███████ | 8489/11952 [2:40:52<5:41:05, 5.91s/it]
{'loss': 0.4876, 'learning_rate': 4.089529330691789e-06, 'epoch': 0.71}
+
71%|███████ | 8489/11952 [2:40:52<5:41:05, 5.91s/it]
71%|███████ | 8490/11952 [2:40:58<5:40:23, 5.90s/it]
{'loss': 0.4657, 'learning_rate': 4.087343638054382e-06, 'epoch': 0.71}
+
71%|███████ | 8490/11952 [2:40:58<5:40:23, 5.90s/it]
71%|███████ | 8491/11952 [2:41:04<5:37:11, 5.85s/it]
{'loss': 0.4594, 'learning_rate': 4.085158379617866e-06, 'epoch': 0.71}
+
71%|███████ | 8491/11952 [2:41:04<5:37:11, 5.85s/it]
71%|███████ | 8492/11952 [2:41:09<5:32:08, 5.76s/it]
{'loss': 0.4669, 'learning_rate': 4.082973555542713e-06, 'epoch': 0.71}
+
71%|███████ | 8492/11952 [2:41:09<5:32:08, 5.76s/it]
71%|███████ | 8493/11952 [2:41:15<5:35:59, 5.83s/it]
{'loss': 0.484, 'learning_rate': 4.080789165989376e-06, 'epoch': 0.71}
+
71%|███████ | 8493/11952 [2:41:15<5:35:59, 5.83s/it]
71%|███████ | 8494/11952 [2:41:21<5:37:32, 5.86s/it]
{'loss': 0.4446, 'learning_rate': 4.0786052111182625e-06, 'epoch': 0.71}
+
71%|███████ | 8494/11952 [2:41:21<5:37:32, 5.86s/it]
71%|███████ | 8495/11952 [2:41:28<5:48:13, 6.04s/it]
{'loss': 0.4834, 'learning_rate': 4.0764216910897496e-06, 'epoch': 0.71}
+
71%|███████ | 8495/11952 [2:41:28<5:48:13, 6.04s/it]
71%|███████ | 8496/11952 [2:41:33<5:42:08, 5.94s/it]
{'loss': 0.4814, 'learning_rate': 4.074238606064194e-06, 'epoch': 0.71}
+
71%|███████ | 8496/11952 [2:41:33<5:42:08, 5.94s/it]
71%|███████ | 8497/11952 [2:41:39<5:37:22, 5.86s/it]
{'loss': 0.4433, 'learning_rate': 4.072055956201907e-06, 'epoch': 0.71}
+
71%|███████ | 8497/11952 [2:41:39<5:37:22, 5.86s/it]
71%|███████ | 8498/11952 [2:41:45<5:35:42, 5.83s/it]
{'loss': 0.466, 'learning_rate': 4.069873741663171e-06, 'epoch': 0.71}
+
71%|███████ | 8498/11952 [2:41:45<5:35:42, 5.83s/it]
71%|███████ | 8499/11952 [2:41:50<5:30:30, 5.74s/it]
{'loss': 0.4694, 'learning_rate': 4.067691962608245e-06, 'epoch': 0.71}
+
71%|███████ | 8499/11952 [2:41:50<5:30:30, 5.74s/it]1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
71%|███████ | 8500/11952 [2:41:56<5:26:45, 5.68s/it]
{'loss': 0.4718, 'learning_rate': 4.0655106191973485e-06, 'epoch': 0.71}
+
71%|███████ | 8500/11952 [2:41:56<5:26:45, 5.68s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
71%|███████ | 8501/11952 [2:42:24<11:59:31, 12.51s/it]
{'loss': 0.4776, 'learning_rate': 4.063329711590668e-06, 'epoch': 0.71}
+
71%|███████ | 8501/11952 [2:42:24<11:59:31, 12.51s/it]
71%|███████ | 8502/11952 [2:42:30<10:04:11, 10.51s/it]
{'loss': 0.4952, 'learning_rate': 4.061149239948361e-06, 'epoch': 0.71}
+
71%|███████ | 8502/11952 [2:42:30<10:04:11, 10.51s/it]
71%|███████ | 8503/11952 [2:42:36<8:43:12, 9.10s/it]
{'loss': 0.4696, 'learning_rate': 4.058969204430553e-06, 'epoch': 0.71}
+
71%|███████ | 8503/11952 [2:42:36<8:43:12, 9.10s/it]
71%|███████ | 8504/11952 [2:42:42<7:53:43, 8.24s/it]
{'loss': 0.4936, 'learning_rate': 4.056789605197335e-06, 'epoch': 0.71}
+
71%|███████ | 8504/11952 [2:42:42<7:53:43, 8.24s/it]
71%|███████ | 8505/11952 [2:42:48<7:14:44, 7.57s/it]
{'loss': 0.4689, 'learning_rate': 4.054610442408765e-06, 'epoch': 0.71}
+
71%|███████ | 8505/11952 [2:42:48<7:14:44, 7.57s/it]
71%|███████ | 8506/11952 [2:42:54<6:50:34, 7.15s/it]
{'loss': 0.4777, 'learning_rate': 4.052431716224876e-06, 'epoch': 0.71}
+
71%|███████ | 8506/11952 [2:42:54<6:50:34, 7.15s/it]
71%|███████ | 8507/11952 [2:43:00<6:28:33, 6.77s/it]
{'loss': 0.4714, 'learning_rate': 4.050253426805668e-06, 'epoch': 0.71}
+
71%|███████ | 8507/11952 [2:43:00<6:28:33, 6.77s/it]
71%|███████ | 8508/11952 [2:43:06<6:12:12, 6.48s/it]
{'loss': 0.4638, 'learning_rate': 4.048075574311101e-06, 'epoch': 0.71}
+
71%|███████ | 8508/11952 [2:43:06<6:12:12, 6.48s/it]
71%|███████ | 8509/11952 [2:43:12<6:05:11, 6.36s/it]
{'loss': 0.4809, 'learning_rate': 4.045898158901108e-06, 'epoch': 0.71}
+
71%|███████ | 8509/11952 [2:43:12<6:05:11, 6.36s/it]
71%|███████ | 8510/11952 [2:43:18<5:55:49, 6.20s/it]
{'loss': 0.4672, 'learning_rate': 4.043721180735589e-06, 'epoch': 0.71}
+
71%|███████ | 8510/11952 [2:43:18<5:55:49, 6.20s/it]
71%|███████ | 8511/11952 [2:43:24<5:51:06, 6.12s/it]
{'loss': 0.4507, 'learning_rate': 4.041544639974413e-06, 'epoch': 0.71}
+
71%|███████ | 8511/11952 [2:43:24<5:51:06, 6.12s/it]
71%|███████ | 8512/11952 [2:43:29<5:43:04, 5.98s/it]
{'loss': 0.4801, 'learning_rate': 4.03936853677741e-06, 'epoch': 0.71}
+
71%|███████ | 8512/11952 [2:43:29<5:43:04, 5.98s/it]
71%|███████ | 8513/11952 [2:43:35<5:40:50, 5.95s/it]
{'loss': 0.4604, 'learning_rate': 4.037192871304396e-06, 'epoch': 0.71}
+
71%|███████ | 8513/11952 [2:43:35<5:40:50, 5.95s/it]
71%|███████ | 8514/11952 [2:43:41<5:36:56, 5.88s/it]
{'loss': 0.462, 'learning_rate': 4.035017643715135e-06, 'epoch': 0.71}
+
71%|███████ | 8514/11952 [2:43:41<5:36:56, 5.88s/it]
71%|███████ | 8515/11952 [2:43:47<5:34:27, 5.84s/it]
{'loss': 0.465, 'learning_rate': 4.032842854169368e-06, 'epoch': 0.71}
+
71%|███████ | 8515/11952 [2:43:47<5:34:27, 5.84s/it]
71%|███████▏ | 8516/11952 [2:43:52<5:31:11, 5.78s/it]
{'loss': 0.4692, 'learning_rate': 4.030668502826799e-06, 'epoch': 0.71}
+
71%|███████▏ | 8516/11952 [2:43:52<5:31:11, 5.78s/it]
71%|███████▏ | 8517/11952 [2:43:58<5:29:19, 5.75s/it]
{'loss': 0.4676, 'learning_rate': 4.028494589847109e-06, 'epoch': 0.71}
+
71%|███████▏ | 8517/11952 [2:43:58<5:29:19, 5.75s/it]
71%|███████▏ | 8518/11952 [2:44:04<5:33:02, 5.82s/it]
{'loss': 0.475, 'learning_rate': 4.026321115389942e-06, 'epoch': 0.71}
+
71%|███████▏ | 8518/11952 [2:44:04<5:33:02, 5.82s/it]
71%|███████▏ | 8519/11952 [2:44:10<5:30:18, 5.77s/it]
{'loss': 0.4485, 'learning_rate': 4.0241480796149e-06, 'epoch': 0.71}
+
71%|███████▏ | 8519/11952 [2:44:10<5:30:18, 5.77s/it]
71%|███████▏ | 8520/11952 [2:44:16<5:33:37, 5.83s/it]
{'loss': 0.4837, 'learning_rate': 4.021975482681571e-06, 'epoch': 0.71}
+
71%|███████▏ | 8520/11952 [2:44:16<5:33:37, 5.83s/it]
71%|███████▏ | 8521/11952 [2:44:21<5:32:39, 5.82s/it]
{'loss': 0.4756, 'learning_rate': 4.0198033247494995e-06, 'epoch': 0.71}
+
71%|███████▏ | 8521/11952 [2:44:22<5:32:39, 5.82s/it]
71%|███████▏ | 8522/11952 [2:44:27<5:32:00, 5.81s/it]
{'loss': 0.4693, 'learning_rate': 4.017631605978198e-06, 'epoch': 0.71}
+
71%|███████▏ | 8522/11952 [2:44:27<5:32:00, 5.81s/it]
71%|███████▏ | 8523/11952 [2:44:33<5:31:00, 5.79s/it]
{'loss': 0.4934, 'learning_rate': 4.015460326527149e-06, 'epoch': 0.71}
+
71%|███████▏ | 8523/11952 [2:44:33<5:31:00, 5.79s/it]
71%|███████▏ | 8524/11952 [2:44:39<5:28:36, 5.75s/it]
{'loss': 0.4677, 'learning_rate': 4.013289486555801e-06, 'epoch': 0.71}
+
71%|███████▏ | 8524/11952 [2:44:39<5:28:36, 5.75s/it]
71%|███████▏ | 8525/11952 [2:44:45<5:41:30, 5.98s/it]
{'loss': 0.4588, 'learning_rate': 4.01111908622357e-06, 'epoch': 0.71}
+
71%|███████▏ | 8525/11952 [2:44:45<5:41:30, 5.98s/it]
71%|███████▏ | 8526/11952 [2:44:51<5:38:55, 5.94s/it]
{'loss': 0.4807, 'learning_rate': 4.008949125689846e-06, 'epoch': 0.71}
+
71%|███████▏ | 8526/11952 [2:44:51<5:38:55, 5.94s/it]
71%|███████▏ | 8527/11952 [2:44:57<5:34:08, 5.85s/it]
{'loss': 0.4802, 'learning_rate': 4.0067796051139775e-06, 'epoch': 0.71}
+
71%|███████▏ | 8527/11952 [2:44:57<5:34:08, 5.85s/it]
71%|███████▏ | 8528/11952 [2:45:02<5:30:24, 5.79s/it]
{'loss': 0.4561, 'learning_rate': 4.0046105246552895e-06, 'epoch': 0.71}
+
71%|███████▏ | 8528/11952 [2:45:02<5:30:24, 5.79s/it]
71%|███████▏ | 8529/11952 [2:45:08<5:36:28, 5.90s/it]
{'loss': 0.4578, 'learning_rate': 4.002441884473069e-06, 'epoch': 0.71}
+
71%|███████▏ | 8529/11952 [2:45:08<5:36:28, 5.90s/it]
71%|███████▏ | 8530/11952 [2:45:14<5:33:21, 5.84s/it]
{'loss': 0.469, 'learning_rate': 4.000273684726569e-06, 'epoch': 0.71}
+
71%|███████▏ | 8530/11952 [2:45:14<5:33:21, 5.84s/it]
71%|███████▏ | 8531/11952 [2:45:20<5:30:06, 5.79s/it]
{'loss': 0.4794, 'learning_rate': 3.998105925575017e-06, 'epoch': 0.71}
+
71%|███████▏ | 8531/11952 [2:45:20<5:30:06, 5.79s/it]
71%|███████▏ | 8532/11952 [2:45:26<5:28:56, 5.77s/it]
{'loss': 0.4589, 'learning_rate': 3.995938607177599e-06, 'epoch': 0.71}
+
71%|███████▏ | 8532/11952 [2:45:26<5:28:56, 5.77s/it]
71%|███████▏ | 8533/11952 [2:45:31<5:29:10, 5.78s/it]
{'loss': 0.4691, 'learning_rate': 3.993771729693476e-06, 'epoch': 0.71}
+
71%|███████▏ | 8533/11952 [2:45:31<5:29:10, 5.78s/it]
71%|███████▏ | 8534/11952 [2:45:37<5:29:24, 5.78s/it]
{'loss': 0.4729, 'learning_rate': 3.991605293281779e-06, 'epoch': 0.71}
+
71%|███████▏ | 8534/11952 [2:45:37<5:29:24, 5.78s/it]
71%|███████▏ | 8535/11952 [2:45:43<5:35:08, 5.88s/it]
{'loss': 0.477, 'learning_rate': 3.989439298101597e-06, 'epoch': 0.71}
+
71%|███████▏ | 8535/11952 [2:45:43<5:35:08, 5.88s/it]
71%|███████▏ | 8536/11952 [2:45:49<5:33:34, 5.86s/it]
{'loss': 0.4653, 'learning_rate': 3.9872737443119914e-06, 'epoch': 0.71}
+
71%|███████▏ | 8536/11952 [2:45:49<5:33:34, 5.86s/it]
71%|███████▏ | 8537/11952 [2:45:55<5:34:44, 5.88s/it]
{'loss': 0.4654, 'learning_rate': 3.985108632071995e-06, 'epoch': 0.71}
+
71%|███████▏ | 8537/11952 [2:45:55<5:34:44, 5.88s/it]
71%|███████▏ | 8538/11952 [2:46:01<5:34:37, 5.88s/it]
{'loss': 0.4591, 'learning_rate': 3.982943961540604e-06, 'epoch': 0.71}
+
71%|███████▏ | 8538/11952 [2:46:01<5:34:37, 5.88s/it]
71%|███████▏ | 8539/11952 [2:46:07<5:33:45, 5.87s/it]
{'loss': 0.4844, 'learning_rate': 3.980779732876777e-06, 'epoch': 0.71}
+
71%|███████▏ | 8539/11952 [2:46:07<5:33:45, 5.87s/it]
71%|███████▏ | 8540/11952 [2:46:13<5:40:42, 5.99s/it]
{'loss': 0.4753, 'learning_rate': 3.978615946239456e-06, 'epoch': 0.71}
+
71%|███████▏ | 8540/11952 [2:46:13<5:40:42, 5.99s/it]
71%|███████▏ | 8541/11952 [2:46:19<5:38:43, 5.96s/it]
{'loss': 0.4698, 'learning_rate': 3.9764526017875326e-06, 'epoch': 0.71}
+
71%|███████▏ | 8541/11952 [2:46:19<5:38:43, 5.96s/it]
71%|███████▏ | 8542/11952 [2:46:25<5:33:02, 5.86s/it]
{'loss': 0.4496, 'learning_rate': 3.974289699679879e-06, 'epoch': 0.71}
+
71%|███████▏ | 8542/11952 [2:46:25<5:33:02, 5.86s/it]
71%|███████▏ | 8543/11952 [2:46:30<5:28:45, 5.79s/it]
{'loss': 0.4753, 'learning_rate': 3.972127240075325e-06, 'epoch': 0.71}
+
71%|███████▏ | 8543/11952 [2:46:30<5:28:45, 5.79s/it]
71%|███████▏ | 8544/11952 [2:46:36<5:35:57, 5.91s/it]
{'loss': 0.4723, 'learning_rate': 3.969965223132675e-06, 'epoch': 0.71}
+
71%|███████▏ | 8544/11952 [2:46:36<5:35:57, 5.91s/it]
71%|███████▏ | 8545/11952 [2:46:42<5:31:18, 5.83s/it]
{'loss': 0.4615, 'learning_rate': 3.967803649010698e-06, 'epoch': 0.71}
+
71%|███████▏ | 8545/11952 [2:46:42<5:31:18, 5.83s/it]
72%|███████▏ | 8546/11952 [2:46:48<5:28:42, 5.79s/it]
{'loss': 0.4637, 'learning_rate': 3.965642517868129e-06, 'epoch': 0.71}
+
72%|███████▏ | 8546/11952 [2:46:48<5:28:42, 5.79s/it]
72%|███████▏ | 8547/11952 [2:46:53<5:26:16, 5.75s/it]
{'loss': 0.4717, 'learning_rate': 3.963481829863673e-06, 'epoch': 0.72}
+
72%|███████▏ | 8547/11952 [2:46:53<5:26:16, 5.75s/it]
72%|███████▏ | 8548/11952 [2:46:59<5:28:50, 5.80s/it]
{'loss': 0.4675, 'learning_rate': 3.9613215851560094e-06, 'epoch': 0.72}
+
72%|███████▏ | 8548/11952 [2:46:59<5:28:50, 5.80s/it]
72%|███████▏ | 8549/11952 [2:47:05<5:31:58, 5.85s/it]
{'loss': 0.4737, 'learning_rate': 3.95916178390377e-06, 'epoch': 0.72}
+
72%|███████▏ | 8549/11952 [2:47:05<5:31:58, 5.85s/it]61 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
72%|███████▏ | 8550/11952 [2:47:11<5:30:08, 5.82s/it]
{'loss': 0.4573, 'learning_rate': 3.957002426265564e-06, 'epoch': 0.72}
+
72%|███████▏ | 8550/11952 [2:47:11<5:30:08, 5.82s/it]
72%|███████▏ | 8551/11952 [2:47:17<5:25:23, 5.74s/it]
{'loss': 0.477, 'learning_rate': 3.954843512399965e-06, 'epoch': 0.72}
+
72%|███████▏ | 8551/11952 [2:47:17<5:25:23, 5.74s/it]
72%|███████▏ | 8552/11952 [2:47:23<5:31:06, 5.84s/it]
{'loss': 0.4955, 'learning_rate': 3.952685042465515e-06, 'epoch': 0.72}
+
72%|███████▏ | 8552/11952 [2:47:23<5:31:06, 5.84s/it]
72%|███████▏ | 8553/11952 [2:47:29<5:35:25, 5.92s/it]
{'loss': 0.4608, 'learning_rate': 3.950527016620719e-06, 'epoch': 0.72}
+
72%|███████▏ | 8553/11952 [2:47:29<5:35:25, 5.92s/it]
72%|███████▏ | 8554/11952 [2:47:35<5:34:41, 5.91s/it]
{'loss': 0.4601, 'learning_rate': 3.948369435024061e-06, 'epoch': 0.72}
+
72%|███████▏ | 8554/11952 [2:47:35<5:34:41, 5.91s/it]
72%|███████▏ | 8555/11952 [2:47:40<5:29:45, 5.82s/it]
{'loss': 0.4654, 'learning_rate': 3.9462122978339815e-06, 'epoch': 0.72}
+
72%|███████▏ | 8555/11952 [2:47:40<5:29:45, 5.82s/it]
72%|███████▏ | 8556/11952 [2:47:46<5:29:09, 5.82s/it]
{'loss': 0.4643, 'learning_rate': 3.944055605208891e-06, 'epoch': 0.72}
+
72%|███████▏ | 8556/11952 [2:47:46<5:29:09, 5.82s/it]
72%|███████▏ | 8557/11952 [2:47:52<5:29:40, 5.83s/it]
{'loss': 0.4667, 'learning_rate': 3.941899357307164e-06, 'epoch': 0.72}
+
72%|███████▏ | 8557/11952 [2:47:52<5:29:40, 5.83s/it]
72%|███████▏ | 8558/11952 [2:47:58<5:27:08, 5.78s/it]
{'loss': 0.4756, 'learning_rate': 3.939743554287154e-06, 'epoch': 0.72}
+
72%|███████▏ | 8558/11952 [2:47:58<5:27:08, 5.78s/it]
72%|███████▏ | 8559/11952 [2:48:03<5:25:09, 5.75s/it]
{'loss': 0.4816, 'learning_rate': 3.937588196307172e-06, 'epoch': 0.72}
+
72%|███████▏ | 8559/11952 [2:48:03<5:25:09, 5.75s/it]
72%|███████▏ | 8560/11952 [2:48:09<5:29:05, 5.82s/it]
{'loss': 0.4623, 'learning_rate': 3.9354332835254935e-06, 'epoch': 0.72}
+
72%|███████▏ | 8560/11952 [2:48:09<5:29:05, 5.82s/it]
72%|███████▏ | 8561/11952 [2:48:15<5:27:16, 5.79s/it]
{'loss': 0.468, 'learning_rate': 3.933278816100373e-06, 'epoch': 0.72}
+
72%|███████▏ | 8561/11952 [2:48:15<5:27:16, 5.79s/it]
72%|███████▏ | 8562/11952 [2:48:21<5:26:28, 5.78s/it]
{'loss': 0.4859, 'learning_rate': 3.9311247941900245e-06, 'epoch': 0.72}
+
72%|███████▏ | 8562/11952 [2:48:21<5:26:28, 5.78s/it]
72%|███████▏ | 8563/11952 [2:48:27<5:29:50, 5.84s/it]
{'loss': 0.4537, 'learning_rate': 3.9289712179526275e-06, 'epoch': 0.72}
+
72%|███████▏ | 8563/11952 [2:48:27<5:29:50, 5.84s/it]
72%|███████▏ | 8564/11952 [2:48:33<5:31:04, 5.86s/it]
{'loss': 0.4717, 'learning_rate': 3.926818087546333e-06, 'epoch': 0.72}
+
72%|███████▏ | 8564/11952 [2:48:33<5:31:04, 5.86s/it]
72%|███████▏ | 8565/11952 [2:48:39<5:32:32, 5.89s/it]
{'loss': 0.4674, 'learning_rate': 3.924665403129259e-06, 'epoch': 0.72}
+
72%|███████▏ | 8565/11952 [2:48:39<5:32:32, 5.89s/it]
72%|███████▏ | 8566/11952 [2:48:45<5:35:10, 5.94s/it]
{'loss': 0.4457, 'learning_rate': 3.9225131648594835e-06, 'epoch': 0.72}
+
72%|███████▏ | 8566/11952 [2:48:45<5:35:10, 5.94s/it]
72%|███████▏ | 8567/11952 [2:48:50<5:27:32, 5.81s/it]
{'loss': 0.4414, 'learning_rate': 3.920361372895067e-06, 'epoch': 0.72}
+
72%|███████▏ | 8567/11952 [2:48:50<5:27:32, 5.81s/it]
72%|███████▏ | 8568/11952 [2:48:56<5:30:20, 5.86s/it]
{'loss': 0.4717, 'learning_rate': 3.918210027394021e-06, 'epoch': 0.72}
+
72%|███████▏ | 8568/11952 [2:48:56<5:30:20, 5.86s/it]
72%|███████▏ | 8569/11952 [2:49:02<5:31:31, 5.88s/it]
{'loss': 0.462, 'learning_rate': 3.9160591285143375e-06, 'epoch': 0.72}
+
72%|███████▏ | 8569/11952 [2:49:02<5:31:31, 5.88s/it]
72%|███████▏ | 8570/11952 [2:49:08<5:35:41, 5.96s/it]
{'loss': 0.4642, 'learning_rate': 3.9139086764139675e-06, 'epoch': 0.72}
+
72%|███████▏ | 8570/11952 [2:49:08<5:35:41, 5.96s/it]
72%|███████▏ | 8571/11952 [2:49:14<5:30:32, 5.87s/it]
{'loss': 0.4636, 'learning_rate': 3.911758671250829e-06, 'epoch': 0.72}
+
72%|███████▏ | 8571/11952 [2:49:14<5:30:32, 5.87s/it]
72%|███████▏ | 8572/11952 [2:49:19<5:25:02, 5.77s/it]
{'loss': 0.462, 'learning_rate': 3.909609113182812e-06, 'epoch': 0.72}
+
72%|███████▏ | 8572/11952 [2:49:19<5:25:02, 5.77s/it]
72%|███████▏ | 8573/11952 [2:49:25<5:25:03, 5.77s/it]
{'loss': 0.4626, 'learning_rate': 3.907460002367766e-06, 'epoch': 0.72}
+
72%|███████▏ | 8573/11952 [2:49:25<5:25:03, 5.77s/it]
72%|███████▏ | 8574/11952 [2:49:31<5:26:36, 5.80s/it]
{'loss': 0.4717, 'learning_rate': 3.90531133896352e-06, 'epoch': 0.72}
+
72%|███████▏ | 8574/11952 [2:49:31<5:26:36, 5.80s/it]
72%|███████▏ | 8575/11952 [2:49:37<5:29:02, 5.85s/it]
{'loss': 0.4724, 'learning_rate': 3.90316312312786e-06, 'epoch': 0.72}
+
72%|███████▏ | 8575/11952 [2:49:37<5:29:02, 5.85s/it]
72%|███████▏ | 8576/11952 [2:49:43<5:28:42, 5.84s/it]
{'loss': 0.4667, 'learning_rate': 3.901015355018541e-06, 'epoch': 0.72}
+
72%|███████▏ | 8576/11952 [2:49:43<5:28:42, 5.84s/it]
72%|███████▏ | 8577/11952 [2:49:48<5:25:54, 5.79s/it]
{'loss': 0.4813, 'learning_rate': 3.8988680347932836e-06, 'epoch': 0.72}
+
72%|███████▏ | 8577/11952 [2:49:48<5:25:54, 5.79s/it]
72%|███████▏ | 8578/11952 [2:49:54<5:25:20, 5.79s/it]
{'loss': 0.4612, 'learning_rate': 3.896721162609785e-06, 'epoch': 0.72}
+
72%|███████▏ | 8578/11952 [2:49:54<5:25:20, 5.79s/it]
72%|███████▏ | 8579/11952 [2:50:00<5:24:35, 5.77s/it]
{'loss': 0.4741, 'learning_rate': 3.894574738625699e-06, 'epoch': 0.72}
+
72%|███████▏ | 8579/11952 [2:50:00<5:24:35, 5.77s/it]
72%|███████▏ | 8580/11952 [2:50:06<5:30:23, 5.88s/it]
{'loss': 0.4814, 'learning_rate': 3.892428762998644e-06, 'epoch': 0.72}
+
72%|███████▏ | 8580/11952 [2:50:06<5:30:23, 5.88s/it]
72%|███████▏ | 8581/11952 [2:50:12<5:34:37, 5.96s/it]
{'loss': 0.4944, 'learning_rate': 3.890283235886223e-06, 'epoch': 0.72}
+
72%|███████▏ | 8581/11952 [2:50:12<5:34:37, 5.96s/it]
72%|███████▏ | 8582/11952 [2:50:18<5:29:34, 5.87s/it]
{'loss': 0.433, 'learning_rate': 3.888138157445989e-06, 'epoch': 0.72}
+
72%|███████▏ | 8582/11952 [2:50:18<5:29:34, 5.87s/it]
72%|███████▏ | 8583/11952 [2:50:24<5:30:36, 5.89s/it]
{'loss': 0.4921, 'learning_rate': 3.885993527835466e-06, 'epoch': 0.72}
+
72%|███████▏ | 8583/11952 [2:50:24<5:30:36, 5.89s/it]
72%|███████▏ | 8584/11952 [2:50:29<5:26:36, 5.82s/it]
{'loss': 0.4568, 'learning_rate': 3.883849347212151e-06, 'epoch': 0.72}
+
72%|███████▏ | 8584/11952 [2:50:30<5:26:36, 5.82s/it]
72%|███████▏ | 8585/11952 [2:50:36<5:31:01, 5.90s/it]
{'loss': 0.4738, 'learning_rate': 3.8817056157334985e-06, 'epoch': 0.72}
+
72%|███████▏ | 8585/11952 [2:50:36<5:31:01, 5.90s/it]
72%|███████▏ | 8586/11952 [2:50:41<5:30:45, 5.90s/it]
{'loss': 0.4914, 'learning_rate': 3.879562333556939e-06, 'epoch': 0.72}
+
72%|███████▏ | 8586/11952 [2:50:41<5:30:45, 5.90s/it]
72%|███████▏ | 8587/11952 [2:50:47<5:29:24, 5.87s/it]
{'loss': 0.4677, 'learning_rate': 3.877419500839861e-06, 'epoch': 0.72}
+
72%|███████▏ | 8587/11952 [2:50:47<5:29:24, 5.87s/it]
72%|███████▏ | 8588/11952 [2:50:53<5:32:38, 5.93s/it]
{'loss': 0.4613, 'learning_rate': 3.875277117739632e-06, 'epoch': 0.72}
+
72%|███████▏ | 8588/11952 [2:50:53<5:32:38, 5.93s/it]
72%|███████▏ | 8589/11952 [2:50:59<5:27:02, 5.83s/it]
{'loss': 0.4628, 'learning_rate': 3.873135184413573e-06, 'epoch': 0.72}
+
72%|███████▏ | 8589/11952 [2:50:59<5:27:02, 5.83s/it]
72%|███████▏ | 8590/11952 [2:51:05<5:25:31, 5.81s/it]
{'loss': 0.4649, 'learning_rate': 3.870993701018988e-06, 'epoch': 0.72}
+
72%|███████▏ | 8590/11952 [2:51:05<5:25:31, 5.81s/it]
72%|███████▏ | 8591/11952 [2:51:10<5:23:29, 5.77s/it]
{'loss': 0.4456, 'learning_rate': 3.868852667713131e-06, 'epoch': 0.72}
+
72%|███████▏ | 8591/11952 [2:51:10<5:23:29, 5.77s/it]
72%|███████▏ | 8592/11952 [2:51:16<5:25:57, 5.82s/it]
{'loss': 0.4777, 'learning_rate': 3.8667120846532335e-06, 'epoch': 0.72}
+
72%|███████▏ | 8592/11952 [2:51:16<5:25:57, 5.82s/it]
72%|███████▏ | 8593/11952 [2:51:22<5:25:07, 5.81s/it]
{'loss': 0.476, 'learning_rate': 3.864571951996491e-06, 'epoch': 0.72}
+
72%|███████▏ | 8593/11952 [2:51:22<5:25:07, 5.81s/it]
72%|███████▏ | 8594/11952 [2:51:28<5:24:34, 5.80s/it]
{'loss': 0.4743, 'learning_rate': 3.862432269900062e-06, 'epoch': 0.72}
+
72%|███████▏ | 8594/11952 [2:51:28<5:24:34, 5.80s/it]
72%|███████▏ | 8595/11952 [2:51:33<5:20:02, 5.72s/it]
{'loss': 0.4484, 'learning_rate': 3.860293038521082e-06, 'epoch': 0.72}
+
72%|███████▏ | 8595/11952 [2:51:33<5:20:02, 5.72s/it]
72%|███████▏ | 8596/11952 [2:51:39<5:22:51, 5.77s/it]
{'loss': 0.4882, 'learning_rate': 3.858154258016643e-06, 'epoch': 0.72}
+
72%|███████▏ | 8596/11952 [2:51:39<5:22:51, 5.77s/it]
72%|███████▏ | 8597/11952 [2:51:45<5:20:45, 5.74s/it]
{'loss': 0.4718, 'learning_rate': 3.856015928543811e-06, 'epoch': 0.72}
+
72%|███████▏ | 8597/11952 [2:51:45<5:20:45, 5.74s/it]
72%|███████▏ | 8598/11952 [2:51:51<5:24:53, 5.81s/it]
{'loss': 0.4623, 'learning_rate': 3.85387805025961e-06, 'epoch': 0.72}
+
72%|███████▏ | 8598/11952 [2:51:51<5:24:53, 5.81s/it]
72%|███████▏ | 8599/11952 [2:51:57<5:22:36, 5.77s/it]
{'loss': 0.4816, 'learning_rate': 3.8517406233210445e-06, 'epoch': 0.72}
+
72%|███████▏ | 8599/11952 [2:51:57<5:22:36, 5.77s/it]4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+20 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
72%|███████▏ | 8600/11952 [2:52:02<5:23:41, 5.79s/it]
{'loss': 0.47, 'learning_rate': 3.849603647885076e-06, 'epoch': 0.72}
+
72%|███████▏ | 8600/11952 [2:52:03<5:23:41, 5.79s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
72%|███████▏ | 8601/11952 [2:52:31<11:47:17, 12.66s/it]
{'loss': 0.4653, 'learning_rate': 3.84746712410863e-06, 'epoch': 0.72}
+
72%|███████▏ | 8601/11952 [2:52:31<11:47:17, 12.66s/it]
72%|███████▏ | 8602/11952 [2:52:37<9:52:48, 10.62s/it]
{'loss': 0.4681, 'learning_rate': 3.845331052148612e-06, 'epoch': 0.72}
+
72%|███████▏ | 8602/11952 [2:52:37<9:52:48, 10.62s/it]
72%|███████▏ | 8603/11952 [2:52:43<8:34:37, 9.22s/it]
{'loss': 0.4579, 'learning_rate': 3.843195432161883e-06, 'epoch': 0.72}
+
72%|███████▏ | 8603/11952 [2:52:43<8:34:37, 9.22s/it]
72%|███████▏ | 8604/11952 [2:52:49<7:39:41, 8.24s/it]
{'loss': 0.4616, 'learning_rate': 3.841060264305272e-06, 'epoch': 0.72}
+
72%|███████▏ | 8604/11952 [2:52:49<7:39:41, 8.24s/it]
72%|███████▏ | 8605/11952 [2:52:55<6:58:43, 7.51s/it]
{'loss': 0.4761, 'learning_rate': 3.838925548735579e-06, 'epoch': 0.72}
+
72%|███████▏ | 8605/11952 [2:52:55<6:58:43, 7.51s/it]
72%|███████▏ | 8606/11952 [2:53:00<6:27:42, 6.95s/it]
{'loss': 0.4677, 'learning_rate': 3.836791285609568e-06, 'epoch': 0.72}
+
72%|███████▏ | 8606/11952 [2:53:00<6:27:42, 6.95s/it]
72%|███████▏ | 8607/11952 [2:53:06<6:05:27, 6.56s/it]
{'loss': 0.4562, 'learning_rate': 3.834657475083967e-06, 'epoch': 0.72}
+
72%|███████▏ | 8607/11952 [2:53:06<6:05:27, 6.56s/it]
72%|███████▏ | 8608/11952 [2:53:12<6:03:28, 6.52s/it]
{'loss': 0.492, 'learning_rate': 3.83252411731548e-06, 'epoch': 0.72}
+
72%|███████▏ | 8608/11952 [2:53:12<6:03:28, 6.52s/it]
72%|███████▏ | 8609/11952 [2:53:18<5:51:39, 6.31s/it]
{'loss': 0.4816, 'learning_rate': 3.830391212460767e-06, 'epoch': 0.72}
+
72%|███████▏ | 8609/11952 [2:53:18<5:51:39, 6.31s/it]
72%|███████▏ | 8610/11952 [2:53:24<5:44:46, 6.19s/it]
{'loss': 0.4645, 'learning_rate': 3.828258760676464e-06, 'epoch': 0.72}
+
72%|███████▏ | 8610/11952 [2:53:24<5:44:46, 6.19s/it]
72%|███████▏ | 8611/11952 [2:53:30<5:36:02, 6.03s/it]
{'loss': 0.4629, 'learning_rate': 3.826126762119169e-06, 'epoch': 0.72}
+
72%|███████▏ | 8611/11952 [2:53:30<5:36:02, 6.03s/it]
72%|███████▏ | 8612/11952 [2:53:36<5:31:50, 5.96s/it]
{'loss': 0.4651, 'learning_rate': 3.823995216945445e-06, 'epoch': 0.72}
+
72%|███████▏ | 8612/11952 [2:53:36<5:31:50, 5.96s/it]
72%|███████▏ | 8613/11952 [2:53:42<5:33:39, 6.00s/it]
{'loss': 0.4499, 'learning_rate': 3.821864125311824e-06, 'epoch': 0.72}
+
72%|███████▏ | 8613/11952 [2:53:42<5:33:39, 6.00s/it]
72%|███████▏ | 8614/11952 [2:53:48<5:32:56, 5.98s/it]
{'loss': 0.4697, 'learning_rate': 3.819733487374801e-06, 'epoch': 0.72}
+
72%|███████▏ | 8614/11952 [2:53:48<5:32:56, 5.98s/it]
72%|███████▏ | 8615/11952 [2:53:54<5:33:42, 6.00s/it]
{'loss': 0.4748, 'learning_rate': 3.81760330329085e-06, 'epoch': 0.72}
+
72%|███████▏ | 8615/11952 [2:53:54<5:33:42, 6.00s/it]
72%|███████▏ | 8616/11952 [2:54:00<5:31:25, 5.96s/it]
{'loss': 0.4666, 'learning_rate': 3.815473573216397e-06, 'epoch': 0.72}
+
72%|███████▏ | 8616/11952 [2:54:00<5:31:25, 5.96s/it]
72%|███████▏ | 8617/11952 [2:54:06<5:33:09, 5.99s/it]
{'loss': 0.4688, 'learning_rate': 3.8133442973078415e-06, 'epoch': 0.72}
+
72%|███████▏ | 8617/11952 [2:54:06<5:33:09, 5.99s/it]
72%|███████▏ | 8618/11952 [2:54:11<5:28:57, 5.92s/it]
{'loss': 0.4636, 'learning_rate': 3.811215475721548e-06, 'epoch': 0.72}
+
72%|███████▏ | 8618/11952 [2:54:11<5:28:57, 5.92s/it]
72%|███████▏ | 8619/11952 [2:54:17<5:25:32, 5.86s/it]
{'loss': 0.452, 'learning_rate': 3.809087108613846e-06, 'epoch': 0.72}
+
72%|███████▏ | 8619/11952 [2:54:17<5:25:32, 5.86s/it]
72%|███████▏ | 8620/11952 [2:54:23<5:24:28, 5.84s/it]
{'loss': 0.458, 'learning_rate': 3.8069591961410402e-06, 'epoch': 0.72}
+
72%|███████▏ | 8620/11952 [2:54:23<5:24:28, 5.84s/it]
72%|███████▏ | 8621/11952 [2:54:29<5:20:47, 5.78s/it]
{'loss': 0.4557, 'learning_rate': 3.804831738459388e-06, 'epoch': 0.72}
+
72%|███████▏ | 8621/11952 [2:54:29<5:20:47, 5.78s/it]
72%|███████▏ | 8622/11952 [2:54:34<5:21:45, 5.80s/it]
{'loss': 0.483, 'learning_rate': 3.80270473572513e-06, 'epoch': 0.72}
+
72%|███████▏ | 8622/11952 [2:54:34<5:21:45, 5.80s/it]
72%|███████▏ | 8623/11952 [2:54:40<5:22:42, 5.82s/it]
{'loss': 0.4682, 'learning_rate': 3.800578188094459e-06, 'epoch': 0.72}
+
72%|███████▏ | 8623/11952 [2:54:40<5:22:42, 5.82s/it]
72%|███████▏ | 8624/11952 [2:54:46<5:23:48, 5.84s/it]
{'loss': 0.4645, 'learning_rate': 3.7984520957235403e-06, 'epoch': 0.72}
+
72%|███████▏ | 8624/11952 [2:54:46<5:23:48, 5.84s/it]
72%|███████▏ | 8625/11952 [2:54:52<5:24:56, 5.86s/it]
{'loss': 0.4688, 'learning_rate': 3.7963264587685067e-06, 'epoch': 0.72}
+
72%|███████▏ | 8625/11952 [2:54:52<5:24:56, 5.86s/it]
72%|███████▏ | 8626/11952 [2:54:58<5:26:11, 5.88s/it]
{'loss': 0.4634, 'learning_rate': 3.7942012773854532e-06, 'epoch': 0.72}
+
72%|███████▏ | 8626/11952 [2:54:58<5:26:11, 5.88s/it]
72%|███████▏ | 8627/11952 [2:55:04<5:24:32, 5.86s/it]
{'loss': 0.4708, 'learning_rate': 3.792076551730447e-06, 'epoch': 0.72}
+
72%|███████▏ | 8627/11952 [2:55:04<5:24:32, 5.86s/it]
72%|███████▏ | 8628/11952 [2:55:10<5:22:59, 5.83s/it]
{'loss': 0.4622, 'learning_rate': 3.789952281959515e-06, 'epoch': 0.72}
+
72%|███████▏ | 8628/11952 [2:55:10<5:22:59, 5.83s/it]
72%|███████▏ | 8629/11952 [2:55:15<5:19:10, 5.76s/it]
{'loss': 0.4641, 'learning_rate': 3.7878284682286615e-06, 'epoch': 0.72}
+
72%|███████▏ | 8629/11952 [2:55:15<5:19:10, 5.76s/it]
72%|███████▏ | 8630/11952 [2:55:21<5:24:57, 5.87s/it]
{'loss': 0.4655, 'learning_rate': 3.7857051106938425e-06, 'epoch': 0.72}
+
72%|███████▏ | 8630/11952 [2:55:21<5:24:57, 5.87s/it]
72%|███████▏ | 8631/11952 [2:55:27<5:24:50, 5.87s/it]
{'loss': 0.4844, 'learning_rate': 3.7835822095109966e-06, 'epoch': 0.72}
+
72%|███████▏ | 8631/11952 [2:55:27<5:24:50, 5.87s/it]
72%|███████▏ | 8632/11952 [2:55:33<5:21:22, 5.81s/it]
{'loss': 0.4661, 'learning_rate': 3.7814597648360176e-06, 'epoch': 0.72}
+
72%|███████▏ | 8632/11952 [2:55:33<5:21:22, 5.81s/it]
72%|███████▏ | 8633/11952 [2:55:39<5:23:12, 5.84s/it]
{'loss': 0.4646, 'learning_rate': 3.7793377768247685e-06, 'epoch': 0.72}
+
72%|███████▏ | 8633/11952 [2:55:39<5:23:12, 5.84s/it]
72%|███████▏ | 8634/11952 [2:55:45<5:35:09, 6.06s/it]
{'loss': 0.49, 'learning_rate': 3.7772162456330796e-06, 'epoch': 0.72}
+
72%|███████▏ | 8634/11952 [2:55:45<5:35:09, 6.06s/it]
72%|███████▏ | 8635/11952 [2:55:51<5:30:17, 5.97s/it]
{'loss': 0.4759, 'learning_rate': 3.775095171416744e-06, 'epoch': 0.72}
+
72%|███████▏ | 8635/11952 [2:55:51<5:30:17, 5.97s/it]
72%|███████▏ | 8636/11952 [2:55:57<5:23:08, 5.85s/it]
{'loss': 0.4735, 'learning_rate': 3.77297455433153e-06, 'epoch': 0.72}
+
72%|███████▏ | 8636/11952 [2:55:57<5:23:08, 5.85s/it]
72%|███████▏ | 8637/11952 [2:56:03<5:24:09, 5.87s/it]
{'loss': 0.4817, 'learning_rate': 3.7708543945331654e-06, 'epoch': 0.72}
+
72%|███████▏ | 8637/11952 [2:56:03<5:24:09, 5.87s/it]
72%|███████▏ | 8638/11952 [2:56:08<5:20:49, 5.81s/it]
{'loss': 0.449, 'learning_rate': 3.768734692177345e-06, 'epoch': 0.72}
+
72%|███████▏ | 8638/11952 [2:56:08<5:20:49, 5.81s/it]
72%|███████▏ | 8639/11952 [2:56:14<5:22:08, 5.83s/it]
{'loss': 0.4656, 'learning_rate': 3.766615447419727e-06, 'epoch': 0.72}
+
72%|███████▏ | 8639/11952 [2:56:14<5:22:08, 5.83s/it]
72%|███████▏ | 8640/11952 [2:56:20<5:22:10, 5.84s/it]
{'loss': 0.4704, 'learning_rate': 3.764496660415948e-06, 'epoch': 0.72}
+
72%|███████▏ | 8640/11952 [2:56:20<5:22:10, 5.84s/it]
72%|███████▏ | 8641/11952 [2:56:26<5:21:32, 5.83s/it]
{'loss': 0.4846, 'learning_rate': 3.762378331321599e-06, 'epoch': 0.72}
+
72%|███████▏ | 8641/11952 [2:56:26<5:21:32, 5.83s/it]
72%|███████▏ | 8642/11952 [2:56:32<5:23:52, 5.87s/it]
{'loss': 0.4714, 'learning_rate': 3.7602604602922365e-06, 'epoch': 0.72}
+
72%|███████▏ | 8642/11952 [2:56:32<5:23:52, 5.87s/it]
72%|███████▏ | 8643/11952 [2:56:38<5:23:45, 5.87s/it]
{'loss': 0.4686, 'learning_rate': 3.758143047483398e-06, 'epoch': 0.72}
+
72%|███████▏ | 8643/11952 [2:56:38<5:23:45, 5.87s/it]
72%|███████▏ | 8644/11952 [2:56:43<5:21:33, 5.83s/it]
{'loss': 0.4748, 'learning_rate': 3.756026093050571e-06, 'epoch': 0.72}
+
72%|███████▏ | 8644/11952 [2:56:43<5:21:33, 5.83s/it]
72%|███████▏ | 8645/11952 [2:56:49<5:17:58, 5.77s/it]
{'loss': 0.4507, 'learning_rate': 3.7539095971492177e-06, 'epoch': 0.72}
+
72%|███████▏ | 8645/11952 [2:56:49<5:17:58, 5.77s/it]
72%|███████▏ | 8646/11952 [2:56:55<5:16:06, 5.74s/it]
{'loss': 0.4642, 'learning_rate': 3.7517935599347634e-06, 'epoch': 0.72}
+
72%|███████▏ | 8646/11952 [2:56:55<5:16:06, 5.74s/it]
72%|███████▏ | 8647/11952 [2:57:01<5:22:17, 5.85s/it]
{'loss': 0.4805, 'learning_rate': 3.7496779815626026e-06, 'epoch': 0.72}
+
72%|███████▏ | 8647/11952 [2:57:01<5:22:17, 5.85s/it]
72%|███████▏ | 8648/11952 [2:57:07<5:21:14, 5.83s/it]
{'loss': 0.4671, 'learning_rate': 3.74756286218809e-06, 'epoch': 0.72}
+
72%|███████▏ | 8648/11952 [2:57:07<5:21:14, 5.83s/it]
72%|███████▏ | 8649/11952 [2:57:13<5:25:48, 5.92s/it]
{'loss': 0.4739, 'learning_rate': 3.745448201966558e-06, 'epoch': 0.72}
+
72%|███████▏ | 8649/11952 [2:57:13<5:25:48, 5.92s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
72%|███████▏ | 8650/11952 [2:57:19<5:24:44, 5.90s/it]
{'loss': 0.4768, 'learning_rate': 3.7433340010532926e-06, 'epoch': 0.72}
+
72%|███████▏ | 8650/11952 [2:57:19<5:24:44, 5.90s/it]
72%|███████▏ | 8651/11952 [2:57:24<5:21:40, 5.85s/it]
{'loss': 0.4509, 'learning_rate': 3.7412202596035586e-06, 'epoch': 0.72}
+
72%|███████▏ | 8651/11952 [2:57:24<5:21:40, 5.85s/it]
72%|███████▏ | 8652/11952 [2:57:31<5:29:05, 5.98s/it]
{'loss': 0.4845, 'learning_rate': 3.739106977772575e-06, 'epoch': 0.72}
+
72%|███████▏ | 8652/11952 [2:57:31<5:29:05, 5.98s/it]
72%|███████▏ | 8653/11952 [2:57:37<5:31:18, 6.03s/it]
{'loss': 0.4621, 'learning_rate': 3.7369941557155354e-06, 'epoch': 0.72}
+
72%|███████▏ | 8653/11952 [2:57:37<5:31:18, 6.03s/it]
72%|███████▏ | 8654/11952 [2:57:43<5:28:08, 5.97s/it]
{'loss': 0.4534, 'learning_rate': 3.7348817935875947e-06, 'epoch': 0.72}
+
72%|███████▏ | 8654/11952 [2:57:43<5:28:08, 5.97s/it]
72%|███████▏ | 8655/11952 [2:57:48<5:27:41, 5.96s/it]
{'loss': 0.4751, 'learning_rate': 3.7327698915438725e-06, 'epoch': 0.72}
+
72%|███████▏ | 8655/11952 [2:57:48<5:27:41, 5.96s/it]
72%|███████▏ | 8656/11952 [2:57:54<5:21:22, 5.85s/it]
{'loss': 0.4679, 'learning_rate': 3.730658449739466e-06, 'epoch': 0.72}
+
72%|███████▏ | 8656/11952 [2:57:54<5:21:22, 5.85s/it]
72%|███████▏ | 8657/11952 [2:58:00<5:17:14, 5.78s/it]
{'loss': 0.4685, 'learning_rate': 3.7285474683294274e-06, 'epoch': 0.72}
+
72%|███████▏ | 8657/11952 [2:58:00<5:17:14, 5.78s/it]
72%|███████▏ | 8658/11952 [2:58:06<5:18:50, 5.81s/it]
{'loss': 0.4646, 'learning_rate': 3.7264369474687767e-06, 'epoch': 0.72}
+
72%|███████▏ | 8658/11952 [2:58:06<5:18:50, 5.81s/it]
72%|███████▏ | 8659/11952 [2:58:11<5:16:43, 5.77s/it]
{'loss': 0.4867, 'learning_rate': 3.7243268873125038e-06, 'epoch': 0.72}
+
72%|███████▏ | 8659/11952 [2:58:11<5:16:43, 5.77s/it]
72%|███████▏ | 8660/11952 [2:58:17<5:17:46, 5.79s/it]
{'loss': 0.473, 'learning_rate': 3.7222172880155585e-06, 'epoch': 0.72}
+
72%|███████▏ | 8660/11952 [2:58:17<5:17:46, 5.79s/it]
72%|███████▏ | 8661/11952 [2:58:23<5:20:32, 5.84s/it]
{'loss': 0.4919, 'learning_rate': 3.720108149732866e-06, 'epoch': 0.72}
+
72%|███████▏ | 8661/11952 [2:58:23<5:20:32, 5.84s/it]
72%|███████▏ | 8662/11952 [2:58:29<5:21:22, 5.86s/it]
{'loss': 0.4689, 'learning_rate': 3.717999472619309e-06, 'epoch': 0.72}
+
72%|███████▏ | 8662/11952 [2:58:29<5:21:22, 5.86s/it]
72%|███████▏ | 8663/11952 [2:58:35<5:18:59, 5.82s/it]
{'loss': 0.482, 'learning_rate': 3.7158912568297458e-06, 'epoch': 0.72}
+
72%|███████▏ | 8663/11952 [2:58:35<5:18:59, 5.82s/it]
72%|███████▏ | 8664/11952 [2:58:40<5:14:58, 5.75s/it]
{'loss': 0.4459, 'learning_rate': 3.7137835025189894e-06, 'epoch': 0.72}
+
72%|███████▏ | 8664/11952 [2:58:40<5:14:58, 5.75s/it]
72%|███████▏ | 8665/11952 [2:58:46<5:17:00, 5.79s/it]
{'loss': 0.4706, 'learning_rate': 3.711676209841828e-06, 'epoch': 0.72}
+
72%|███████▏ | 8665/11952 [2:58:46<5:17:00, 5.79s/it]
73%|███████▎ | 8666/11952 [2:58:52<5:15:54, 5.77s/it]
{'loss': 0.4603, 'learning_rate': 3.7095693789530096e-06, 'epoch': 0.73}
+
73%|███████▎ | 8666/11952 [2:58:52<5:15:54, 5.77s/it]
73%|███████▎ | 8667/11952 [2:58:58<5:15:43, 5.77s/it]
{'loss': 0.4563, 'learning_rate': 3.707463010007252e-06, 'epoch': 0.73}
+
73%|███████▎ | 8667/11952 [2:58:58<5:15:43, 5.77s/it]
73%|███████▎ | 8668/11952 [2:59:03<5:15:27, 5.76s/it]
{'loss': 0.4674, 'learning_rate': 3.7053571031592393e-06, 'epoch': 0.73}
+
73%|███████▎ | 8668/11952 [2:59:03<5:15:27, 5.76s/it]
73%|███████▎ | 8669/11952 [2:59:09<5:12:49, 5.72s/it]
{'loss': 0.4673, 'learning_rate': 3.703251658563615e-06, 'epoch': 0.73}
+
73%|███████▎ | 8669/11952 [2:59:09<5:12:49, 5.72s/it]
73%|███████▎ | 8670/11952 [2:59:15<5:13:33, 5.73s/it]
{'loss': 0.4479, 'learning_rate': 3.7011466763750026e-06, 'epoch': 0.73}
+
73%|███████▎ | 8670/11952 [2:59:15<5:13:33, 5.73s/it]
73%|███████▎ | 8671/11952 [2:59:20<5:12:49, 5.72s/it]
{'loss': 0.465, 'learning_rate': 3.6990421567479764e-06, 'epoch': 0.73}
+
73%|███████▎ | 8671/11952 [2:59:20<5:12:49, 5.72s/it]
73%|███████▎ | 8672/11952 [2:59:26<5:15:12, 5.77s/it]
{'loss': 0.4908, 'learning_rate': 3.6969380998370896e-06, 'epoch': 0.73}
+
73%|███████▎ | 8672/11952 [2:59:26<5:15:12, 5.77s/it]
73%|███████▎ | 8673/11952 [2:59:32<5:20:18, 5.86s/it]
{'loss': 0.4905, 'learning_rate': 3.6948345057968525e-06, 'epoch': 0.73}
+
73%|███████▎ | 8673/11952 [2:59:32<5:20:18, 5.86s/it]
73%|███████▎ | 8674/11952 [2:59:39<5:29:31, 6.03s/it]
{'loss': 0.4654, 'learning_rate': 3.692731374781744e-06, 'epoch': 0.73}
+
73%|███████▎ | 8674/11952 [2:59:39<5:29:31, 6.03s/it]
73%|███████▎ | 8675/11952 [2:59:45<5:24:52, 5.95s/it]
{'loss': 0.4858, 'learning_rate': 3.69062870694621e-06, 'epoch': 0.73}
+
73%|███████▎ | 8675/11952 [2:59:45<5:24:52, 5.95s/it]
73%|███████▎ | 8676/11952 [2:59:50<5:22:36, 5.91s/it]
{'loss': 0.4783, 'learning_rate': 3.688526502444657e-06, 'epoch': 0.73}
+
73%|███████▎ | 8676/11952 [2:59:50<5:22:36, 5.91s/it]
73%|███████▎ | 8677/11952 [2:59:56<5:21:33, 5.89s/it]
{'loss': 0.4673, 'learning_rate': 3.6864247614314696e-06, 'epoch': 0.73}
+
73%|███████▎ | 8677/11952 [2:59:56<5:21:33, 5.89s/it]
73%|███████▎ | 8678/11952 [3:00:02<5:21:45, 5.90s/it]
{'loss': 0.4805, 'learning_rate': 3.6843234840609877e-06, 'epoch': 0.73}
+
73%|███████▎ | 8678/11952 [3:00:02<5:21:45, 5.90s/it]
73%|███████▎ | 8679/11952 [3:00:08<5:19:36, 5.86s/it]
{'loss': 0.4687, 'learning_rate': 3.6822226704875208e-06, 'epoch': 0.73}
+
73%|███████▎ | 8679/11952 [3:00:08<5:19:36, 5.86s/it]
73%|███████▎ | 8680/11952 [3:00:14<5:17:45, 5.83s/it]
{'loss': 0.4843, 'learning_rate': 3.6801223208653392e-06, 'epoch': 0.73}
+
73%|███████▎ | 8680/11952 [3:00:14<5:17:45, 5.83s/it]
73%|███████▎ | 8681/11952 [3:00:20<5:21:03, 5.89s/it]
{'loss': 0.4707, 'learning_rate': 3.6780224353486916e-06, 'epoch': 0.73}
+
73%|███████▎ | 8681/11952 [3:00:20<5:21:03, 5.89s/it]
73%|███████▎ | 8682/11952 [3:00:25<5:18:34, 5.85s/it]
{'loss': 0.4632, 'learning_rate': 3.675923014091781e-06, 'epoch': 0.73}
+
73%|███████▎ | 8682/11952 [3:00:25<5:18:34, 5.85s/it]
73%|███████▎ | 8683/11952 [3:00:31<5:16:39, 5.81s/it]
{'loss': 0.4782, 'learning_rate': 3.673824057248778e-06, 'epoch': 0.73}
+
73%|███████▎ | 8683/11952 [3:00:31<5:16:39, 5.81s/it]
73%|███████▎ | 8684/11952 [3:00:37<5:14:48, 5.78s/it]
{'loss': 0.4764, 'learning_rate': 3.671725564973827e-06, 'epoch': 0.73}
+
73%|███████▎ | 8684/11952 [3:00:37<5:14:48, 5.78s/it]
73%|███████▎ | 8685/11952 [3:00:43<5:14:22, 5.77s/it]
{'loss': 0.4581, 'learning_rate': 3.669627537421029e-06, 'epoch': 0.73}
+
73%|███████▎ | 8685/11952 [3:00:43<5:14:22, 5.77s/it]
73%|███████▎ | 8686/11952 [3:00:48<5:15:07, 5.79s/it]
{'loss': 0.4726, 'learning_rate': 3.6675299747444536e-06, 'epoch': 0.73}
+
73%|███████▎ | 8686/11952 [3:00:48<5:15:07, 5.79s/it]
73%|███████▎ | 8687/11952 [3:00:54<5:17:11, 5.83s/it]
{'loss': 0.4647, 'learning_rate': 3.6654328770981396e-06, 'epoch': 0.73}
+
73%|███████▎ | 8687/11952 [3:00:54<5:17:11, 5.83s/it]
73%|███████▎ | 8688/11952 [3:01:00<5:13:58, 5.77s/it]
{'loss': 0.4703, 'learning_rate': 3.6633362446360865e-06, 'epoch': 0.73}
+
73%|███████▎ | 8688/11952 [3:01:00<5:13:58, 5.77s/it]
73%|███████▎ | 8689/11952 [3:01:06<5:12:35, 5.75s/it]
{'loss': 0.448, 'learning_rate': 3.6612400775122603e-06, 'epoch': 0.73}
+
73%|███████▎ | 8689/11952 [3:01:06<5:12:35, 5.75s/it]
73%|███████▎ | 8690/11952 [3:01:11<5:10:30, 5.71s/it]
{'loss': 0.4705, 'learning_rate': 3.659144375880602e-06, 'epoch': 0.73}
+
73%|███████▎ | 8690/11952 [3:01:11<5:10:30, 5.71s/it]
73%|███████▎ | 8691/11952 [3:01:17<5:08:20, 5.67s/it]
{'loss': 0.4516, 'learning_rate': 3.6570491398950038e-06, 'epoch': 0.73}
+
73%|███████▎ | 8691/11952 [3:01:17<5:08:20, 5.67s/it]
73%|███████▎ | 8692/11952 [3:01:23<5:11:56, 5.74s/it]
{'loss': 0.449, 'learning_rate': 3.654954369709337e-06, 'epoch': 0.73}
+
73%|███████▎ | 8692/11952 [3:01:23<5:11:56, 5.74s/it]
73%|███████▎ | 8693/11952 [3:01:29<5:14:36, 5.79s/it]
{'loss': 0.466, 'learning_rate': 3.6528600654774306e-06, 'epoch': 0.73}
+
73%|███████▎ | 8693/11952 [3:01:29<5:14:36, 5.79s/it]
73%|███████▎ | 8694/11952 [3:01:35<5:16:07, 5.82s/it]
{'loss': 0.464, 'learning_rate': 3.650766227353081e-06, 'epoch': 0.73}
+
73%|███████▎ | 8694/11952 [3:01:35<5:16:07, 5.82s/it]
73%|███████▎ | 8695/11952 [3:01:40<5:12:22, 5.75s/it]
{'loss': 0.4556, 'learning_rate': 3.648672855490052e-06, 'epoch': 0.73}
+
73%|███████▎ | 8695/11952 [3:01:40<5:12:22, 5.75s/it]
73%|███████▎ | 8696/11952 [3:01:46<5:16:00, 5.82s/it]
{'loss': 0.4629, 'learning_rate': 3.6465799500420673e-06, 'epoch': 0.73}
+
73%|███████▎ | 8696/11952 [3:01:46<5:16:00, 5.82s/it]
73%|███████▎ | 8697/11952 [3:01:52<5:14:56, 5.81s/it]
{'loss': 0.4737, 'learning_rate': 3.6444875111628287e-06, 'epoch': 0.73}
+
73%|███████▎ | 8697/11952 [3:01:52<5:14:56, 5.81s/it]
73%|███████▎ | 8698/11952 [3:01:58<5:17:30, 5.85s/it]
{'loss': 0.4636, 'learning_rate': 3.642395539005993e-06, 'epoch': 0.73}
+
73%|███████▎ | 8698/11952 [3:01:58<5:17:30, 5.85s/it]
73%|███████▎ | 8699/11952 [3:02:04<5:14:32, 5.80s/it]
{'loss': 0.4655, 'learning_rate': 3.640304033725185e-06, 'epoch': 0.73}
+
73%|███████▎ | 8699/11952 [3:02:04<5:14:32, 5.80s/it]61 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+70 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
73%|███████▎ | 8700/11952 [3:02:09<5:12:32, 5.77s/it]5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4755, 'learning_rate': 3.6382129954739975e-06, 'epoch': 0.73}
+
73%|███████▎ | 8700/11952 [3:02:09<5:12:32, 5.77s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
73%|███████▎ | 8701/11952 [3:02:40<12:05:32, 13.39s/it]
{'loss': 0.4662, 'learning_rate': 3.6361224244059823e-06, 'epoch': 0.73}
+
73%|███████▎ | 8701/11952 [3:02:40<12:05:32, 13.39s/it]
73%|███████▎ | 8702/11952 [3:02:46<9:58:45, 11.05s/it]
{'loss': 0.4579, 'learning_rate': 3.634032320674672e-06, 'epoch': 0.73}
+
73%|███████▎ | 8702/11952 [3:02:46<9:58:45, 11.05s/it]
73%|███████▎ | 8703/11952 [3:02:52<8:30:03, 9.42s/it]
{'loss': 0.4519, 'learning_rate': 3.631942684433546e-06, 'epoch': 0.73}
+
73%|███████▎ | 8703/11952 [3:02:52<8:30:03, 9.42s/it]
73%|███████▎ | 8704/11952 [3:02:58<7:33:54, 8.38s/it]
{'loss': 0.4656, 'learning_rate': 3.629853515836065e-06, 'epoch': 0.73}
+
73%|███████▎ | 8704/11952 [3:02:58<7:33:54, 8.38s/it]
73%|███████▎ | 8705/11952 [3:03:07<7:51:15, 8.71s/it]
{'loss': 0.463, 'learning_rate': 3.627764815035647e-06, 'epoch': 0.73}
+
73%|███████▎ | 8705/11952 [3:03:07<7:51:15, 8.71s/it]
73%|███████▎ | 8706/11952 [3:03:13<7:04:56, 7.85s/it]
{'loss': 0.4798, 'learning_rate': 3.6256765821856775e-06, 'epoch': 0.73}
+
73%|███████▎ | 8706/11952 [3:03:13<7:04:56, 7.85s/it]
73%|███████▎ | 8707/11952 [3:03:19<6:34:39, 7.30s/it]
{'loss': 0.4823, 'learning_rate': 3.6235888174395062e-06, 'epoch': 0.73}
+
73%|███████▎ | 8707/11952 [3:03:19<6:34:39, 7.30s/it]
73%|███████▎ | 8708/11952 [3:03:25<6:12:23, 6.89s/it]
{'loss': 0.4671, 'learning_rate': 3.621501520950451e-06, 'epoch': 0.73}
+
73%|███████▎ | 8708/11952 [3:03:25<6:12:23, 6.89s/it]
73%|███████▎ | 8709/11952 [3:03:31<5:54:49, 6.56s/it]
{'loss': 0.4839, 'learning_rate': 3.6194146928717942e-06, 'epoch': 0.73}
+
73%|███████▎ | 8709/11952 [3:03:31<5:54:49, 6.56s/it]
73%|███████▎ | 8710/11952 [3:03:36<5:41:36, 6.32s/it]
{'loss': 0.4805, 'learning_rate': 3.61732833335678e-06, 'epoch': 0.73}
+
73%|███████▎ | 8710/11952 [3:03:36<5:41:36, 6.32s/it]
73%|███████▎ | 8711/11952 [3:03:43<5:38:10, 6.26s/it]
{'loss': 0.4655, 'learning_rate': 3.6152424425586285e-06, 'epoch': 0.73}
+
73%|███████▎ | 8711/11952 [3:03:43<5:38:10, 6.26s/it]
73%|███████▎ | 8712/11952 [3:03:48<5:31:11, 6.13s/it]
{'loss': 0.4648, 'learning_rate': 3.613157020630512e-06, 'epoch': 0.73}
+
73%|███████▎ | 8712/11952 [3:03:48<5:31:11, 6.13s/it]
73%|███████▎ | 8713/11952 [3:03:54<5:23:51, 6.00s/it]
{'loss': 0.4541, 'learning_rate': 3.611072067725583e-06, 'epoch': 0.73}
+
73%|███████▎ | 8713/11952 [3:03:54<5:23:51, 6.00s/it]
73%|███████▎ | 8714/11952 [3:04:00<5:18:56, 5.91s/it]
{'loss': 0.4756, 'learning_rate': 3.608987583996948e-06, 'epoch': 0.73}
+
73%|███████▎ | 8714/11952 [3:04:00<5:18:56, 5.91s/it]
73%|███████▎ | 8715/11952 [3:04:06<5:22:08, 5.97s/it]
{'loss': 0.4576, 'learning_rate': 3.606903569597683e-06, 'epoch': 0.73}
+
73%|███████▎ | 8715/11952 [3:04:06<5:22:08, 5.97s/it]
73%|███████▎ | 8716/11952 [3:04:12<5:19:28, 5.92s/it]
{'loss': 0.4836, 'learning_rate': 3.6048200246808273e-06, 'epoch': 0.73}
+
73%|███████▎ | 8716/11952 [3:04:12<5:19:28, 5.92s/it]
73%|███████▎ | 8717/11952 [3:04:17<5:14:05, 5.83s/it]
{'loss': 0.473, 'learning_rate': 3.602736949399388e-06, 'epoch': 0.73}
+
73%|███████▎ | 8717/11952 [3:04:17<5:14:05, 5.83s/it]
73%|███████▎ | 8718/11952 [3:04:23<5:11:51, 5.79s/it]
{'loss': 0.4894, 'learning_rate': 3.600654343906341e-06, 'epoch': 0.73}
+
73%|███████▎ | 8718/11952 [3:04:23<5:11:51, 5.79s/it]
73%|███████▎ | 8719/11952 [3:04:29<5:09:11, 5.74s/it]
{'loss': 0.4522, 'learning_rate': 3.5985722083546228e-06, 'epoch': 0.73}
+
73%|███████▎ | 8719/11952 [3:04:29<5:09:11, 5.74s/it]
73%|███████▎ | 8720/11952 [3:04:34<5:09:47, 5.75s/it]
{'loss': 0.473, 'learning_rate': 3.5964905428971354e-06, 'epoch': 0.73}
+
73%|███████▎ | 8720/11952 [3:04:34<5:09:47, 5.75s/it]
73%|███████▎ | 8721/11952 [3:04:41<5:22:37, 5.99s/it]
{'loss': 0.4861, 'learning_rate': 3.594409347686746e-06, 'epoch': 0.73}
+
73%|███████▎ | 8721/11952 [3:04:41<5:22:37, 5.99s/it]
73%|███████▎ | 8722/11952 [3:04:47<5:21:08, 5.97s/it]
{'loss': 0.4682, 'learning_rate': 3.5923286228762934e-06, 'epoch': 0.73}
+
73%|███████▎ | 8722/11952 [3:04:47<5:21:08, 5.97s/it]
73%|███████▎ | 8723/11952 [3:04:52<5:13:43, 5.83s/it]
{'loss': 0.457, 'learning_rate': 3.5902483686185764e-06, 'epoch': 0.73}
+
73%|███████▎ | 8723/11952 [3:04:52<5:13:43, 5.83s/it]
73%|███████▎ | 8724/11952 [3:04:58<5:15:17, 5.86s/it]
{'loss': 0.4876, 'learning_rate': 3.588168585066355e-06, 'epoch': 0.73}
+
73%|███████▎ | 8724/11952 [3:04:58<5:15:17, 5.86s/it]
73%|███████▎ | 8725/11952 [3:05:04<5:14:08, 5.84s/it]
{'loss': 0.4721, 'learning_rate': 3.5860892723723674e-06, 'epoch': 0.73}
+
73%|███████▎ | 8725/11952 [3:05:04<5:14:08, 5.84s/it]
73%|███████▎ | 8726/11952 [3:05:10<5:13:39, 5.83s/it]
{'loss': 0.4603, 'learning_rate': 3.5840104306893055e-06, 'epoch': 0.73}
+
73%|███████▎ | 8726/11952 [3:05:10<5:13:39, 5.83s/it]
73%|███████▎ | 8727/11952 [3:05:16<5:11:10, 5.79s/it]
{'loss': 0.4653, 'learning_rate': 3.5819320601698324e-06, 'epoch': 0.73}
+
73%|███████▎ | 8727/11952 [3:05:16<5:11:10, 5.79s/it]
73%|███████▎ | 8728/11952 [3:05:21<5:06:19, 5.70s/it]
{'loss': 0.4754, 'learning_rate': 3.579854160966574e-06, 'epoch': 0.73}
+
73%|███████▎ | 8728/11952 [3:05:21<5:06:19, 5.70s/it]
73%|███████▎ | 8729/11952 [3:05:27<5:05:08, 5.68s/it]
{'loss': 0.4538, 'learning_rate': 3.5777767332321222e-06, 'epoch': 0.73}
+
73%|███████▎ | 8729/11952 [3:05:27<5:05:08, 5.68s/it]
73%|███████▎ | 8730/11952 [3:05:33<5:08:10, 5.74s/it]
{'loss': 0.4826, 'learning_rate': 3.5756997771190317e-06, 'epoch': 0.73}
+
73%|███████▎ | 8730/11952 [3:05:33<5:08:10, 5.74s/it]
73%|███████▎ | 8731/11952 [3:05:38<5:04:49, 5.68s/it]
{'loss': 0.4565, 'learning_rate': 3.573623292779832e-06, 'epoch': 0.73}
+
73%|███████▎ | 8731/11952 [3:05:38<5:04:49, 5.68s/it]
73%|███████▎ | 8732/11952 [3:05:44<5:08:34, 5.75s/it]
{'loss': 0.4866, 'learning_rate': 3.5715472803670092e-06, 'epoch': 0.73}
+
73%|███████▎ | 8732/11952 [3:05:44<5:08:34, 5.75s/it]
73%|███████▎ | 8733/11952 [3:05:50<5:07:01, 5.72s/it]
{'loss': 0.4571, 'learning_rate': 3.5694717400330125e-06, 'epoch': 0.73}
+
73%|███████▎ | 8733/11952 [3:05:50<5:07:01, 5.72s/it]
73%|███████▎ | 8734/11952 [3:05:55<5:06:32, 5.72s/it]
{'loss': 0.4778, 'learning_rate': 3.5673966719302677e-06, 'epoch': 0.73}
+
73%|███████▎ | 8734/11952 [3:05:55<5:06:32, 5.72s/it]
73%|███████▎ | 8735/11952 [3:06:01<5:07:47, 5.74s/it]
{'loss': 0.4611, 'learning_rate': 3.565322076211156e-06, 'epoch': 0.73}
+
73%|███████▎ | 8735/11952 [3:06:01<5:07:47, 5.74s/it][2025-06-10 23:54:41,056] [WARNING] [stage3.py:1850:step] 1 pytorch allocator cache flushes since last step. this happens when there is high memory pressure and is detrimental to performance. if this is happening frequently consider adjusting settings to reduce memory consumption. If you are unable to make the cache flushes go away consider adding get_accelerator().empty_cache() calls in your training loop to ensure that all ranks flush their caches at the same time
+
73%|███████▎ | 8736/11952 [3:06:11<6:05:22, 6.82s/it]
{'loss': 0.4616, 'learning_rate': 3.5632479530280273e-06, 'epoch': 0.73}
+
73%|███████▎ | 8736/11952 [3:06:11<6:05:22, 6.82s/it]
73%|███████▎ | 8737/11952 [3:06:17<5:50:50, 6.55s/it]
{'loss': 0.4913, 'learning_rate': 3.5611743025331933e-06, 'epoch': 0.73}
+
73%|███████▎ | 8737/11952 [3:06:17<5:50:50, 6.55s/it]
73%|███████▎ | 8738/11952 [3:06:22<5:37:00, 6.29s/it]
{'loss': 0.46, 'learning_rate': 3.559101124878941e-06, 'epoch': 0.73}
+
73%|███████▎ | 8738/11952 [3:06:22<5:37:00, 6.29s/it]
73%|███████▎ | 8739/11952 [3:06:28<5:31:14, 6.19s/it]
{'loss': 0.4664, 'learning_rate': 3.557028420217512e-06, 'epoch': 0.73}
+
73%|███████▎ | 8739/11952 [3:06:28<5:31:14, 6.19s/it]
73%|███████▎ | 8740/11952 [3:06:34<5:26:37, 6.10s/it]
{'loss': 0.47, 'learning_rate': 3.5549561887011186e-06, 'epoch': 0.73}
+
73%|███████▎ | 8740/11952 [3:06:34<5:26:37, 6.10s/it]
73%|███████▎ | 8741/11952 [3:06:40<5:21:21, 6.00s/it]
{'loss': 0.4343, 'learning_rate': 3.552884430481934e-06, 'epoch': 0.73}
+
73%|███████▎ | 8741/11952 [3:06:40<5:21:21, 6.00s/it]
73%|███████▎ | 8742/11952 [3:06:46<5:16:27, 5.92s/it]
{'loss': 0.4623, 'learning_rate': 3.5508131457120986e-06, 'epoch': 0.73}
+
73%|███████▎ | 8742/11952 [3:06:46<5:16:27, 5.92s/it]
73%|███████▎ | 8743/11952 [3:06:51<5:13:10, 5.86s/it]
{'loss': 0.4712, 'learning_rate': 3.5487423345437253e-06, 'epoch': 0.73}
+
73%|███████▎ | 8743/11952 [3:06:51<5:13:10, 5.86s/it]
73%|███████▎ | 8744/11952 [3:07:00<5:55:31, 6.65s/it]
{'loss': 0.4623, 'learning_rate': 3.546671997128879e-06, 'epoch': 0.73}
+
73%|███████▎ | 8744/11952 [3:07:00<5:55:31, 6.65s/it]
73%|███████▎ | 8745/11952 [3:07:05<5:40:38, 6.37s/it]
{'loss': 0.4617, 'learning_rate': 3.5446021336196024e-06, 'epoch': 0.73}
+
73%|███████▎ | 8745/11952 [3:07:05<5:40:38, 6.37s/it]
73%|███████▎ | 8746/11952 [3:07:11<5:28:29, 6.15s/it]
{'loss': 0.4594, 'learning_rate': 3.5425327441678956e-06, 'epoch': 0.73}
+
73%|███████▎ | 8746/11952 [3:07:11<5:28:29, 6.15s/it]
73%|███████▎ | 8747/11952 [3:07:17<5:31:15, 6.20s/it]
{'loss': 0.4785, 'learning_rate': 3.5404638289257256e-06, 'epoch': 0.73}
+
73%|███████▎ | 8747/11952 [3:07:17<5:31:15, 6.20s/it]
73%|███████▎ | 8748/11952 [3:07:27<6:22:00, 7.15s/it]
{'loss': 0.4682, 'learning_rate': 3.538395388045024e-06, 'epoch': 0.73}
+
73%|███████▎ | 8748/11952 [3:07:27<6:22:00, 7.15s/it]
73%|███████▎ | 8749/11952 [3:07:33<6:00:28, 6.75s/it]
{'loss': 0.4745, 'learning_rate': 3.53632742167769e-06, 'epoch': 0.73}
+
73%|███████▎ | 8749/11952 [3:07:33<6:00:28, 6.75s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+37 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+02 5AutoResumeHook: Checking whether to suspend...4
+AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
73%|███████▎ | 8750/11952 [3:07:41<6:27:52, 7.27s/it]
{'loss': 0.4562, 'learning_rate': 3.5342599299755854e-06, 'epoch': 0.73}
+
73%|███████▎ | 8750/11952 [3:07:41<6:27:52, 7.27s/it]
73%|███████▎ | 8751/11952 [3:07:50<7:00:56, 7.89s/it]
{'loss': 0.4783, 'learning_rate': 3.532192913090534e-06, 'epoch': 0.73}
+
73%|███████▎ | 8751/11952 [3:07:50<7:00:56, 7.89s/it]
73%|███████▎ | 8752/11952 [3:07:56<6:25:18, 7.22s/it]
{'loss': 0.4638, 'learning_rate': 3.5301263711743384e-06, 'epoch': 0.73}
+
73%|███████▎ | 8752/11952 [3:07:56<6:25:18, 7.22s/it]
73%|███████▎ | 8753/11952 [3:08:05<6:47:42, 7.65s/it]
{'loss': 0.4599, 'learning_rate': 3.528060304378749e-06, 'epoch': 0.73}
+
73%|███████▎ | 8753/11952 [3:08:05<6:47:42, 7.65s/it]
73%|███████▎ | 8754/11952 [3:08:11<6:23:58, 7.20s/it]
{'loss': 0.4589, 'learning_rate': 3.525994712855494e-06, 'epoch': 0.73}
+
73%|███████▎ | 8754/11952 [3:08:11<6:23:58, 7.20s/it]
73%|███████▎ | 8755/11952 [3:08:17<6:08:59, 6.93s/it]
{'loss': 0.4726, 'learning_rate': 3.5239295967562603e-06, 'epoch': 0.73}
+
73%|███████▎ | 8755/11952 [3:08:17<6:08:59, 6.93s/it]
73%|███████▎ | 8756/11952 [3:08:23<5:58:50, 6.74s/it]
{'loss': 0.492, 'learning_rate': 3.5218649562327e-06, 'epoch': 0.73}
+
73%|███████▎ | 8756/11952 [3:08:23<5:58:50, 6.74s/it]
73%|███████▎ | 8757/11952 [3:08:29<5:41:04, 6.41s/it]
{'loss': 0.45, 'learning_rate': 3.519800791436434e-06, 'epoch': 0.73}
+
73%|███████▎ | 8757/11952 [3:08:29<5:41:04, 6.41s/it]
73%|███████▎ | 8758/11952 [3:08:35<5:34:12, 6.28s/it]
{'loss': 0.4591, 'learning_rate': 3.517737102519041e-06, 'epoch': 0.73}
+
73%|███████▎ | 8758/11952 [3:08:35<5:34:12, 6.28s/it]
73%|███████▎ | 8759/11952 [3:08:41<5:25:09, 6.11s/it]
{'loss': 0.4785, 'learning_rate': 3.5156738896320773e-06, 'epoch': 0.73}
+
73%|███████▎ | 8759/11952 [3:08:41<5:25:09, 6.11s/it]
73%|███████▎ | 8760/11952 [3:08:47<5:19:57, 6.01s/it]
{'loss': 0.4613, 'learning_rate': 3.513611152927052e-06, 'epoch': 0.73}
+
73%|███████▎ | 8760/11952 [3:08:47<5:19:57, 6.01s/it]
73%|███████▎ | 8761/11952 [3:08:52<5:15:18, 5.93s/it]
{'loss': 0.46, 'learning_rate': 3.5115488925554453e-06, 'epoch': 0.73}
+
73%|███████▎ | 8761/11952 [3:08:52<5:15:18, 5.93s/it]
73%|███████▎ | 8762/11952 [3:08:58<5:17:50, 5.98s/it]
{'loss': 0.46, 'learning_rate': 3.5094871086686997e-06, 'epoch': 0.73}
+
73%|███████▎ | 8762/11952 [3:08:58<5:17:50, 5.98s/it]
73%|███████▎ | 8763/11952 [3:09:04<5:12:27, 5.88s/it]
{'loss': 0.4892, 'learning_rate': 3.507425801418223e-06, 'epoch': 0.73}
+
73%|███████▎ | 8763/11952 [3:09:04<5:12:27, 5.88s/it]
73%|███████▎ | 8764/11952 [3:09:10<5:12:16, 5.88s/it]
{'loss': 0.4579, 'learning_rate': 3.5053649709553893e-06, 'epoch': 0.73}
+
73%|███████▎ | 8764/11952 [3:09:10<5:12:16, 5.88s/it]
73%|███████▎ | 8765/11952 [3:09:16<5:15:07, 5.93s/it]
{'loss': 0.4607, 'learning_rate': 3.5033046174315422e-06, 'epoch': 0.73}
+
73%|███████▎ | 8765/11952 [3:09:16<5:15:07, 5.93s/it]
73%|███████▎ | 8766/11952 [3:09:22<5:11:13, 5.86s/it]
{'loss': 0.4775, 'learning_rate': 3.5012447409979832e-06, 'epoch': 0.73}
+
73%|███████▎ | 8766/11952 [3:09:22<5:11:13, 5.86s/it]
73%|███████▎ | 8767/11952 [3:09:28<5:10:22, 5.85s/it]
{'loss': 0.4502, 'learning_rate': 3.4991853418059798e-06, 'epoch': 0.73}
+
73%|███████▎ | 8767/11952 [3:09:28<5:10:22, 5.85s/it]
73%|███████▎ | 8768/11952 [3:09:33<5:10:34, 5.85s/it]
{'loss': 0.4841, 'learning_rate': 3.4971264200067657e-06, 'epoch': 0.73}
+
73%|███████▎ | 8768/11952 [3:09:33<5:10:34, 5.85s/it]
73%|███████▎ | 8769/11952 [3:09:39<5:09:22, 5.83s/it]
{'loss': 0.4704, 'learning_rate': 3.4950679757515395e-06, 'epoch': 0.73}
+
73%|███████▎ | 8769/11952 [3:09:39<5:09:22, 5.83s/it]
73%|███████▎ | 8770/11952 [3:09:45<5:08:56, 5.83s/it]
{'loss': 0.4668, 'learning_rate': 3.4930100091914655e-06, 'epoch': 0.73}
+
73%|███████▎ | 8770/11952 [3:09:45<5:08:56, 5.83s/it]
73%|███████▎ | 8771/11952 [3:09:51<5:09:59, 5.85s/it]
{'loss': 0.4685, 'learning_rate': 3.4909525204776684e-06, 'epoch': 0.73}
+
73%|███████▎ | 8771/11952 [3:09:51<5:09:59, 5.85s/it]
73%|███████▎ | 8772/11952 [3:09:57<5:15:30, 5.95s/it]
{'loss': 0.4771, 'learning_rate': 3.4888955097612487e-06, 'epoch': 0.73}
+
73%|███████▎ | 8772/11952 [3:09:57<5:15:30, 5.95s/it]
73%|███████▎ | 8773/11952 [3:10:03<5:12:23, 5.90s/it]
{'loss': 0.4739, 'learning_rate': 3.4868389771932608e-06, 'epoch': 0.73}
+
73%|███████▎ | 8773/11952 [3:10:03<5:12:23, 5.90s/it]
73%|███████▎ | 8774/11952 [3:10:09<5:10:10, 5.86s/it]
{'loss': 0.4764, 'learning_rate': 3.4847829229247243e-06, 'epoch': 0.73}
+
73%|███████▎ | 8774/11952 [3:10:09<5:10:10, 5.86s/it]
73%|███████▎ | 8775/11952 [3:10:15<5:11:32, 5.88s/it]
{'loss': 0.4639, 'learning_rate': 3.482727347106636e-06, 'epoch': 0.73}
+
73%|███████▎ | 8775/11952 [3:10:15<5:11:32, 5.88s/it]
73%|███████▎ | 8776/11952 [3:10:20<5:10:48, 5.87s/it]
{'loss': 0.4862, 'learning_rate': 3.4806722498899424e-06, 'epoch': 0.73}
+
73%|███████▎ | 8776/11952 [3:10:20<5:10:48, 5.87s/it]
73%|███████▎ | 8777/11952 [3:10:26<5:11:25, 5.89s/it]
{'loss': 0.4599, 'learning_rate': 3.4786176314255626e-06, 'epoch': 0.73}
+
73%|███████▎ | 8777/11952 [3:10:26<5:11:25, 5.89s/it]
73%|███████▎ | 8778/11952 [3:10:32<5:10:43, 5.87s/it]
{'loss': 0.4675, 'learning_rate': 3.4765634918643778e-06, 'epoch': 0.73}
+
73%|███████▎ | 8778/11952 [3:10:32<5:10:43, 5.87s/it]
73%|███████▎ | 8779/11952 [3:10:38<5:12:36, 5.91s/it]
{'loss': 0.4556, 'learning_rate': 3.474509831357239e-06, 'epoch': 0.73}
+
73%|███████▎ | 8779/11952 [3:10:38<5:12:36, 5.91s/it]
73%|███████▎ | 8780/11952 [3:10:44<5:10:41, 5.88s/it]
{'loss': 0.4535, 'learning_rate': 3.472456650054957e-06, 'epoch': 0.73}
+
73%|███████▎ | 8780/11952 [3:10:44<5:10:41, 5.88s/it]
73%|███████▎ | 8781/11952 [3:10:50<5:08:28, 5.84s/it]
{'loss': 0.4802, 'learning_rate': 3.4704039481083086e-06, 'epoch': 0.73}
+
73%|███████▎ | 8781/11952 [3:10:50<5:08:28, 5.84s/it]
73%|███████▎ | 8782/11952 [3:10:56<5:10:12, 5.87s/it]
{'loss': 0.4857, 'learning_rate': 3.4683517256680365e-06, 'epoch': 0.73}
+
73%|███████▎ | 8782/11952 [3:10:56<5:10:12, 5.87s/it]
73%|███████▎ | 8783/11952 [3:11:01<5:07:26, 5.82s/it]
{'loss': 0.4661, 'learning_rate': 3.466299982884842e-06, 'epoch': 0.73}
+
73%|███████▎ | 8783/11952 [3:11:01<5:07:26, 5.82s/it]
73%|███████▎ | 8784/11952 [3:11:07<5:12:22, 5.92s/it]
{'loss': 0.4644, 'learning_rate': 3.4642487199094042e-06, 'epoch': 0.73}
+
73%|███████▎ | 8784/11952 [3:11:07<5:12:22, 5.92s/it]
74%|███████▎ | 8785/11952 [3:11:13<5:06:21, 5.80s/it]
{'loss': 0.4719, 'learning_rate': 3.462197936892354e-06, 'epoch': 0.73}
+
74%|███████▎ | 8785/11952 [3:11:13<5:06:21, 5.80s/it]
74%|███████▎ | 8786/11952 [3:11:19<5:06:26, 5.81s/it]
{'loss': 0.4574, 'learning_rate': 3.4601476339842976e-06, 'epoch': 0.74}
+
74%|███████▎ | 8786/11952 [3:11:19<5:06:26, 5.81s/it]
74%|███████▎ | 8787/11952 [3:11:25<5:04:21, 5.77s/it]
{'loss': 0.4828, 'learning_rate': 3.4580978113357967e-06, 'epoch': 0.74}
+
74%|███████▎ | 8787/11952 [3:11:25<5:04:21, 5.77s/it]
74%|███████▎ | 8788/11952 [3:11:30<5:05:07, 5.79s/it]
{'loss': 0.4778, 'learning_rate': 3.4560484690973838e-06, 'epoch': 0.74}
+
74%|███████▎ | 8788/11952 [3:11:30<5:05:07, 5.79s/it]
74%|███████▎ | 8789/11952 [3:11:36<5:07:53, 5.84s/it]
{'loss': 0.4658, 'learning_rate': 3.4539996074195526e-06, 'epoch': 0.74}
+
74%|███████▎ | 8789/11952 [3:11:36<5:07:53, 5.84s/it]
74%|███████▎ | 8790/11952 [3:11:42<5:09:08, 5.87s/it]
{'loss': 0.4703, 'learning_rate': 3.4519512264527633e-06, 'epoch': 0.74}
+
74%|███████▎ | 8790/11952 [3:11:42<5:09:08, 5.87s/it]
74%|███████▎ | 8791/11952 [3:11:48<5:07:25, 5.84s/it]
{'loss': 0.4833, 'learning_rate': 3.44990332634744e-06, 'epoch': 0.74}
+
74%|███████▎ | 8791/11952 [3:11:48<5:07:25, 5.84s/it]
74%|███████▎ | 8792/11952 [3:11:54<5:08:51, 5.86s/it]
{'loss': 0.464, 'learning_rate': 3.447855907253971e-06, 'epoch': 0.74}
+
74%|███████▎ | 8792/11952 [3:11:54<5:08:51, 5.86s/it]
74%|███████▎ | 8793/11952 [3:11:59<5:03:57, 5.77s/it]
{'loss': 0.4666, 'learning_rate': 3.4458089693227127e-06, 'epoch': 0.74}
+
74%|███████▎ | 8793/11952 [3:11:59<5:03:57, 5.77s/it]
74%|███████▎ | 8794/11952 [3:12:05<5:05:09, 5.80s/it]
{'loss': 0.4895, 'learning_rate': 3.443762512703981e-06, 'epoch': 0.74}
+
74%|███████▎ | 8794/11952 [3:12:05<5:05:09, 5.80s/it]
74%|███████▎ | 8795/11952 [3:12:12<5:15:00, 5.99s/it]
{'loss': 0.4448, 'learning_rate': 3.4417165375480644e-06, 'epoch': 0.74}
+
74%|███████▎ | 8795/11952 [3:12:12<5:15:00, 5.99s/it]
74%|███████▎ | 8796/11952 [3:12:18<5:16:27, 6.02s/it]
{'loss': 0.4548, 'learning_rate': 3.439671044005206e-06, 'epoch': 0.74}
+
74%|███████▎ | 8796/11952 [3:12:18<5:16:27, 6.02s/it]
74%|███████▎ | 8797/11952 [3:12:24<5:12:33, 5.94s/it]
{'loss': 0.4647, 'learning_rate': 3.4376260322256207e-06, 'epoch': 0.74}
+
74%|███████▎ | 8797/11952 [3:12:24<5:12:33, 5.94s/it]
74%|███████▎ | 8798/11952 [3:12:30<5:11:09, 5.92s/it]
{'loss': 0.4641, 'learning_rate': 3.435581502359484e-06, 'epoch': 0.74}
+
74%|███████▎ | 8798/11952 [3:12:30<5:11:09, 5.92s/it]
74%|███████▎ | 8799/11952 [3:12:35<5:11:20, 5.92s/it]
{'loss': 0.4555, 'learning_rate': 3.4335374545569355e-06, 'epoch': 0.74}
+
74%|███████▎ | 8799/11952 [3:12:35<5:11:20, 5.92s/it]1 6AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+0473 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+25 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
74%|███████▎ | 8800/11952 [3:12:42<5:15:26, 6.00s/it]
{'loss': 0.4594, 'learning_rate': 3.431493888968087e-06, 'epoch': 0.74}
+
74%|███████▎ | 8800/11952 [3:12:42<5:15:26, 6.00s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
74%|███████▎ | 8801/11952 [3:13:11<11:22:15, 12.99s/it]
{'loss': 0.4741, 'learning_rate': 3.4294508057430077e-06, 'epoch': 0.74}
+
74%|███████▎ | 8801/11952 [3:13:11<11:22:15, 12.99s/it]
74%|███████▎ | 8802/11952 [3:13:17<9:37:21, 11.00s/it]
{'loss': 0.4444, 'learning_rate': 3.4274082050317324e-06, 'epoch': 0.74}
+
74%|███████▎ | 8802/11952 [3:13:17<9:37:21, 11.00s/it]
74%|███████▎ | 8803/11952 [3:13:23<8:16:21, 9.46s/it]
{'loss': 0.4935, 'learning_rate': 3.425366086984261e-06, 'epoch': 0.74}
+
74%|███████▎ | 8803/11952 [3:13:23<8:16:21, 9.46s/it]
74%|███████▎ | 8804/11952 [3:13:29<7:22:03, 8.43s/it]
{'loss': 0.4806, 'learning_rate': 3.4233244517505535e-06, 'epoch': 0.74}
+
74%|███████▎ | 8804/11952 [3:13:29<7:22:03, 8.43s/it]
74%|███████▎ | 8805/11952 [3:13:35<6:38:30, 7.60s/it]
{'loss': 0.4512, 'learning_rate': 3.4212832994805445e-06, 'epoch': 0.74}
+
74%|███████▎ | 8805/11952 [3:13:35<6:38:30, 7.60s/it]
74%|███████▎ | 8806/11952 [3:13:41<6:11:24, 7.08s/it]
{'loss': 0.4563, 'learning_rate': 3.419242630324131e-06, 'epoch': 0.74}
+
74%|███████▎ | 8806/11952 [3:13:41<6:11:24, 7.08s/it]
74%|███████▎ | 8807/11952 [3:13:46<5:49:32, 6.67s/it]
{'loss': 0.4666, 'learning_rate': 3.417202444431167e-06, 'epoch': 0.74}
+
74%|███████▎ | 8807/11952 [3:13:46<5:49:32, 6.67s/it]
74%|███████▎ | 8808/11952 [3:13:53<5:41:45, 6.52s/it]
{'loss': 0.4755, 'learning_rate': 3.4151627419514753e-06, 'epoch': 0.74}
+
74%|███████▎ | 8808/11952 [3:13:53<5:41:45, 6.52s/it]
74%|███████▎ | 8809/11952 [3:13:58<5:27:53, 6.26s/it]
{'loss': 0.4383, 'learning_rate': 3.4131235230348434e-06, 'epoch': 0.74}
+
74%|███████▎ | 8809/11952 [3:13:58<5:27:53, 6.26s/it]
74%|███████▎ | 8810/11952 [3:14:04<5:27:25, 6.25s/it]
{'loss': 0.4517, 'learning_rate': 3.411084787831024e-06, 'epoch': 0.74}
+
74%|███████▎ | 8810/11952 [3:14:04<5:27:25, 6.25s/it]
74%|███████▎ | 8811/11952 [3:14:10<5:23:52, 6.19s/it]
{'loss': 0.4664, 'learning_rate': 3.4090465364897317e-06, 'epoch': 0.74}
+
74%|███████▎ | 8811/11952 [3:14:10<5:23:52, 6.19s/it]
74%|███████▎ | 8812/11952 [3:14:16<5:16:38, 6.05s/it]
{'loss': 0.4844, 'learning_rate': 3.4070087691606446e-06, 'epoch': 0.74}
+
74%|███████▎ | 8812/11952 [3:14:16<5:16:38, 6.05s/it]
74%|███████▎ | 8813/11952 [3:14:23<5:20:08, 6.12s/it]
{'loss': 0.4634, 'learning_rate': 3.4049714859934144e-06, 'epoch': 0.74}
+
74%|███████▎ | 8813/11952 [3:14:23<5:20:08, 6.12s/it]
74%|███████▎ | 8814/11952 [3:14:29<5:20:54, 6.14s/it]
{'loss': 0.4492, 'learning_rate': 3.4029346871376477e-06, 'epoch': 0.74}
+
74%|███████▎ | 8814/11952 [3:14:29<5:20:54, 6.14s/it]
74%|███████▍ | 8815/11952 [3:14:34<5:14:10, 6.01s/it]
{'loss': 0.4665, 'learning_rate': 3.4008983727429147e-06, 'epoch': 0.74}
+
74%|███████▍ | 8815/11952 [3:14:34<5:14:10, 6.01s/it]
74%|███████▍ | 8816/11952 [3:14:40<5:15:17, 6.03s/it]
{'loss': 0.4744, 'learning_rate': 3.398862542958761e-06, 'epoch': 0.74}
+
74%|███████▍ | 8816/11952 [3:14:40<5:15:17, 6.03s/it]
74%|███████▍ | 8817/11952 [3:14:46<5:10:04, 5.93s/it]
{'loss': 0.4571, 'learning_rate': 3.3968271979346857e-06, 'epoch': 0.74}
+
74%|███████▍ | 8817/11952 [3:14:46<5:10:04, 5.93s/it]
74%|███████▍ | 8818/11952 [3:14:52<5:07:42, 5.89s/it]
{'loss': 0.4543, 'learning_rate': 3.3947923378201576e-06, 'epoch': 0.74}
+
74%|███████▍ | 8818/11952 [3:14:52<5:07:42, 5.89s/it]
74%|███████▍ | 8819/11952 [3:14:58<5:04:14, 5.83s/it]
{'loss': 0.4386, 'learning_rate': 3.3927579627646024e-06, 'epoch': 0.74}
+
74%|███████▍ | 8819/11952 [3:14:58<5:04:14, 5.83s/it]
74%|███████▍ | 8820/11952 [3:15:04<5:08:50, 5.92s/it]
{'loss': 0.4878, 'learning_rate': 3.390724072917424e-06, 'epoch': 0.74}
+
74%|███████▍ | 8820/11952 [3:15:04<5:08:50, 5.92s/it]
74%|███████▍ | 8821/11952 [3:15:10<5:15:08, 6.04s/it]
{'loss': 0.4807, 'learning_rate': 3.3886906684279806e-06, 'epoch': 0.74}
+
74%|███████▍ | 8821/11952 [3:15:10<5:15:08, 6.04s/it]
74%|███████▍ | 8822/11952 [3:15:16<5:13:32, 6.01s/it]
{'loss': 0.485, 'learning_rate': 3.3866577494455953e-06, 'epoch': 0.74}
+
74%|███████▍ | 8822/11952 [3:15:16<5:13:32, 6.01s/it]
74%|███████▍ | 8823/11952 [3:15:22<5:07:45, 5.90s/it]
{'loss': 0.46, 'learning_rate': 3.3846253161195584e-06, 'epoch': 0.74}
+
74%|███████▍ | 8823/11952 [3:15:22<5:07:45, 5.90s/it]
74%|███████▍ | 8824/11952 [3:15:28<5:09:53, 5.94s/it]
{'loss': 0.4907, 'learning_rate': 3.3825933685991184e-06, 'epoch': 0.74}
+
74%|███████▍ | 8824/11952 [3:15:28<5:09:53, 5.94s/it]
74%|███████▍ | 8825/11952 [3:15:34<5:22:12, 6.18s/it]
{'loss': 0.4913, 'learning_rate': 3.3805619070335026e-06, 'epoch': 0.74}
+
74%|███████▍ | 8825/11952 [3:15:34<5:22:12, 6.18s/it]
74%|███████▍ | 8826/11952 [3:15:40<5:14:24, 6.03s/it]
{'loss': 0.4608, 'learning_rate': 3.378530931571884e-06, 'epoch': 0.74}
+
74%|███████▍ | 8826/11952 [3:15:40<5:14:24, 6.03s/it]
74%|███████▍ | 8827/11952 [3:15:46<5:12:02, 5.99s/it]
{'loss': 0.4769, 'learning_rate': 3.3765004423634164e-06, 'epoch': 0.74}
+
74%|███████▍ | 8827/11952 [3:15:46<5:12:02, 5.99s/it]
74%|███████▍ | 8828/11952 [3:15:52<5:08:07, 5.92s/it]
{'loss': 0.4694, 'learning_rate': 3.374470439557207e-06, 'epoch': 0.74}
+
74%|███████▍ | 8828/11952 [3:15:52<5:08:07, 5.92s/it]
74%|███████▍ | 8829/11952 [3:15:57<5:03:25, 5.83s/it]
{'loss': 0.4434, 'learning_rate': 3.37244092330233e-06, 'epoch': 0.74}
+
74%|███████▍ | 8829/11952 [3:15:57<5:03:25, 5.83s/it]
74%|███████▍ | 8830/11952 [3:16:03<5:05:10, 5.86s/it]
{'loss': 0.4433, 'learning_rate': 3.370411893747827e-06, 'epoch': 0.74}
+
74%|███████▍ | 8830/11952 [3:16:03<5:05:10, 5.86s/it]
74%|███████▍ | 8831/11952 [3:16:09<5:04:23, 5.85s/it]
{'loss': 0.4656, 'learning_rate': 3.368383351042699e-06, 'epoch': 0.74}
+
74%|███████▍ | 8831/11952 [3:16:09<5:04:23, 5.85s/it]
74%|███████▍ | 8832/11952 [3:16:15<5:03:23, 5.83s/it]
{'loss': 0.4648, 'learning_rate': 3.366355295335915e-06, 'epoch': 0.74}
+
74%|███████▍ | 8832/11952 [3:16:15<5:03:23, 5.83s/it]
74%|███████▍ | 8833/11952 [3:16:21<5:06:06, 5.89s/it]
{'loss': 0.4587, 'learning_rate': 3.364327726776403e-06, 'epoch': 0.74}
+
74%|███████▍ | 8833/11952 [3:16:21<5:06:06, 5.89s/it]
74%|███████▍ | 8834/11952 [3:16:27<5:03:48, 5.85s/it]
{'loss': 0.4806, 'learning_rate': 3.362300645513067e-06, 'epoch': 0.74}
+
74%|███████▍ | 8834/11952 [3:16:27<5:03:48, 5.85s/it]
74%|███████▍ | 8835/11952 [3:16:33<5:06:35, 5.90s/it]
{'loss': 0.4774, 'learning_rate': 3.3602740516947595e-06, 'epoch': 0.74}
+
74%|███████▍ | 8835/11952 [3:16:33<5:06:35, 5.90s/it]
74%|███████▍ | 8836/11952 [3:16:39<5:09:08, 5.95s/it]
{'loss': 0.4611, 'learning_rate': 3.358247945470313e-06, 'epoch': 0.74}
+
74%|███████▍ | 8836/11952 [3:16:39<5:09:08, 5.95s/it]
74%|███████▍ | 8837/11952 [3:16:44<5:04:02, 5.86s/it]
{'loss': 0.4639, 'learning_rate': 3.356222326988512e-06, 'epoch': 0.74}
+
74%|███████▍ | 8837/11952 [3:16:44<5:04:02, 5.86s/it]
74%|███████▍ | 8838/11952 [3:16:50<5:00:58, 5.80s/it]
{'loss': 0.4685, 'learning_rate': 3.354197196398109e-06, 'epoch': 0.74}
+
74%|███████▍ | 8838/11952 [3:16:50<5:00:58, 5.80s/it]
74%|███████▍ | 8839/11952 [3:16:56<4:58:43, 5.76s/it]
{'loss': 0.4648, 'learning_rate': 3.352172553847819e-06, 'epoch': 0.74}
+
74%|███████▍ | 8839/11952 [3:16:56<4:58:43, 5.76s/it]
74%|███████▍ | 8840/11952 [3:17:02<5:02:36, 5.83s/it]
{'loss': 0.4667, 'learning_rate': 3.3501483994863293e-06, 'epoch': 0.74}
+
74%|███████▍ | 8840/11952 [3:17:02<5:02:36, 5.83s/it]
74%|███████▍ | 8841/11952 [3:17:08<5:02:09, 5.83s/it]
{'loss': 0.4724, 'learning_rate': 3.3481247334622822e-06, 'epoch': 0.74}
+
74%|███████▍ | 8841/11952 [3:17:08<5:02:09, 5.83s/it]
74%|███████▍ | 8842/11952 [3:17:14<5:04:16, 5.87s/it]
{'loss': 0.4687, 'learning_rate': 3.346101555924288e-06, 'epoch': 0.74}
+
74%|███████▍ | 8842/11952 [3:17:14<5:04:16, 5.87s/it]
74%|███████▍ | 8843/11952 [3:17:20<5:07:29, 5.93s/it]
{'loss': 0.4531, 'learning_rate': 3.34407886702092e-06, 'epoch': 0.74}
+
74%|███████▍ | 8843/11952 [3:17:20<5:07:29, 5.93s/it]
74%|███████▍ | 8844/11952 [3:17:25<5:04:09, 5.87s/it]
{'loss': 0.4567, 'learning_rate': 3.342056666900716e-06, 'epoch': 0.74}
+
74%|███████▍ | 8844/11952 [3:17:25<5:04:09, 5.87s/it]
74%|███████▍ | 8845/11952 [3:17:31<5:00:54, 5.81s/it]
{'loss': 0.4598, 'learning_rate': 3.3400349557121748e-06, 'epoch': 0.74}
+
74%|███████▍ | 8845/11952 [3:17:31<5:00:54, 5.81s/it]
74%|███████▍ | 8846/11952 [3:17:37<5:02:19, 5.84s/it]
{'loss': 0.489, 'learning_rate': 3.338013733603768e-06, 'epoch': 0.74}
+
74%|███████▍ | 8846/11952 [3:17:37<5:02:19, 5.84s/it]
74%|███████▍ | 8847/11952 [3:17:43<5:02:45, 5.85s/it]
{'loss': 0.4647, 'learning_rate': 3.3359930007239204e-06, 'epoch': 0.74}
+
74%|███████▍ | 8847/11952 [3:17:43<5:02:45, 5.85s/it]
74%|███████▍ | 8848/11952 [3:17:49<5:03:23, 5.86s/it]
{'loss': 0.4698, 'learning_rate': 3.3339727572210323e-06, 'epoch': 0.74}
+
74%|███████▍ | 8848/11952 [3:17:49<5:03:23, 5.86s/it]
74%|███████▍ | 8849/11952 [3:17:54<5:00:53, 5.82s/it]
{'loss': 0.4671, 'learning_rate': 3.3319530032434588e-06, 'epoch': 0.74}
+
74%|███████▍ | 8849/11952 [3:17:54<5:00:53, 5.82s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
74%|███████▍ | 8850/11952 [3:18:00<5:00:36, 5.81s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4578, 'learning_rate': 3.3299337389395225e-06, 'epoch': 0.74}
+
74%|███████▍ | 8850/11952 [3:18:00<5:00:36, 5.81s/it]
74%|███████▍ | 8851/11952 [3:18:06<4:58:06, 5.77s/it]
{'loss': 0.4684, 'learning_rate': 3.327914964457509e-06, 'epoch': 0.74}
+
74%|███████▍ | 8851/11952 [3:18:06<4:58:06, 5.77s/it]
74%|███████▍ | 8852/11952 [3:18:12<4:55:29, 5.72s/it]
{'loss': 0.4679, 'learning_rate': 3.3258966799456705e-06, 'epoch': 0.74}
+
74%|███████▍ | 8852/11952 [3:18:12<4:55:29, 5.72s/it]
74%|███████▍ | 8853/11952 [3:18:17<4:54:03, 5.69s/it]
{'loss': 0.4732, 'learning_rate': 3.3238788855522164e-06, 'epoch': 0.74}
+
74%|███████▍ | 8853/11952 [3:18:17<4:54:03, 5.69s/it]
74%|███████▍ | 8854/11952 [3:18:23<4:53:57, 5.69s/it]
{'loss': 0.471, 'learning_rate': 3.3218615814253306e-06, 'epoch': 0.74}
+
74%|███████▍ | 8854/11952 [3:18:23<4:53:57, 5.69s/it]
74%|███████▍ | 8855/11952 [3:18:29<4:59:26, 5.80s/it]
{'loss': 0.4485, 'learning_rate': 3.319844767713155e-06, 'epoch': 0.74}
+
74%|███████▍ | 8855/11952 [3:18:29<4:59:26, 5.80s/it]
74%|███████▍ | 8856/11952 [3:18:35<5:00:51, 5.83s/it]
{'loss': 0.4604, 'learning_rate': 3.317828444563792e-06, 'epoch': 0.74}
+
74%|███████▍ | 8856/11952 [3:18:35<5:00:51, 5.83s/it]
74%|███████▍ | 8857/11952 [3:18:41<4:59:22, 5.80s/it]
{'loss': 0.4795, 'learning_rate': 3.3158126121253178e-06, 'epoch': 0.74}
+
74%|███████▍ | 8857/11952 [3:18:41<4:59:22, 5.80s/it]
74%|███████▍ | 8858/11952 [3:18:46<4:57:01, 5.76s/it]
{'loss': 0.4728, 'learning_rate': 3.3137972705457632e-06, 'epoch': 0.74}
+
74%|███████▍ | 8858/11952 [3:18:46<4:57:01, 5.76s/it]
74%|███████▍ | 8859/11952 [3:18:52<4:55:26, 5.73s/it]
{'loss': 0.4833, 'learning_rate': 3.3117824199731274e-06, 'epoch': 0.74}
+
74%|███████▍ | 8859/11952 [3:18:52<4:55:26, 5.73s/it]
74%|███████▍ | 8860/11952 [3:18:58<4:54:19, 5.71s/it]
{'loss': 0.4926, 'learning_rate': 3.3097680605553697e-06, 'epoch': 0.74}
+
74%|███████▍ | 8860/11952 [3:18:58<4:54:19, 5.71s/it]
74%|███████▍ | 8861/11952 [3:19:04<5:02:55, 5.88s/it]
{'loss': 0.4609, 'learning_rate': 3.307754192440421e-06, 'epoch': 0.74}
+
74%|███████▍ | 8861/11952 [3:19:04<5:02:55, 5.88s/it]
74%|███████▍ | 8862/11952 [3:19:10<5:06:29, 5.95s/it]
{'loss': 0.4956, 'learning_rate': 3.3057408157761696e-06, 'epoch': 0.74}
+
74%|███████▍ | 8862/11952 [3:19:10<5:06:29, 5.95s/it]
74%|███████▍ | 8863/11952 [3:19:15<5:00:01, 5.83s/it]
{'loss': 0.4779, 'learning_rate': 3.3037279307104685e-06, 'epoch': 0.74}
+
74%|███████▍ | 8863/11952 [3:19:15<5:00:01, 5.83s/it]
74%|███████▍ | 8864/11952 [3:19:22<5:03:29, 5.90s/it]
{'loss': 0.4621, 'learning_rate': 3.3017155373911382e-06, 'epoch': 0.74}
+
74%|███████▍ | 8864/11952 [3:19:22<5:03:29, 5.90s/it]
74%|███████▍ | 8865/11952 [3:19:28<5:05:53, 5.95s/it]
{'loss': 0.4677, 'learning_rate': 3.299703635965953e-06, 'epoch': 0.74}
+
74%|███████▍ | 8865/11952 [3:19:28<5:05:53, 5.95s/it]
74%|███████▍ | 8866/11952 [3:19:33<4:59:58, 5.83s/it]
{'loss': 0.4607, 'learning_rate': 3.2976922265826695e-06, 'epoch': 0.74}
+
74%|███████▍ | 8866/11952 [3:19:33<4:59:58, 5.83s/it]
74%|███████▍ | 8867/11952 [3:19:39<4:58:33, 5.81s/it]
{'loss': 0.4671, 'learning_rate': 3.295681309388987e-06, 'epoch': 0.74}
+
74%|███████▍ | 8867/11952 [3:19:39<4:58:33, 5.81s/it]
74%|███████▍ | 8868/11952 [3:19:45<4:56:24, 5.77s/it]
{'loss': 0.4555, 'learning_rate': 3.2936708845325882e-06, 'epoch': 0.74}
+
74%|███████▍ | 8868/11952 [3:19:45<4:56:24, 5.77s/it]
74%|███████▍ | 8869/11952 [3:19:51<5:00:53, 5.86s/it]
{'loss': 0.4641, 'learning_rate': 3.2916609521611052e-06, 'epoch': 0.74}
+
74%|███████▍ | 8869/11952 [3:19:51<5:00:53, 5.86s/it]
74%|███████▍ | 8870/11952 [3:19:56<4:57:06, 5.78s/it]
{'loss': 0.4775, 'learning_rate': 3.2896515124221395e-06, 'epoch': 0.74}
+
74%|███████▍ | 8870/11952 [3:19:56<4:57:06, 5.78s/it]
74%|███████▍ | 8871/11952 [3:20:02<5:02:04, 5.88s/it]
{'loss': 0.4471, 'learning_rate': 3.287642565463257e-06, 'epoch': 0.74}
+
74%|███████▍ | 8871/11952 [3:20:02<5:02:04, 5.88s/it]
74%|███████▍ | 8872/11952 [3:20:08<5:02:26, 5.89s/it]
{'loss': 0.467, 'learning_rate': 3.2856341114319856e-06, 'epoch': 0.74}
+
74%|███████▍ | 8872/11952 [3:20:08<5:02:26, 5.89s/it]
74%|███████▍ | 8873/11952 [3:20:14<5:02:19, 5.89s/it]
{'loss': 0.4799, 'learning_rate': 3.283626150475818e-06, 'epoch': 0.74}
+
74%|███████▍ | 8873/11952 [3:20:14<5:02:19, 5.89s/it]
74%|███████▍ | 8874/11952 [3:20:20<5:05:16, 5.95s/it]
{'loss': 0.4601, 'learning_rate': 3.281618682742207e-06, 'epoch': 0.74}
+
74%|███████▍ | 8874/11952 [3:20:20<5:05:16, 5.95s/it]
74%|███████▍ | 8875/11952 [3:20:26<5:02:53, 5.91s/it]
{'loss': 0.4666, 'learning_rate': 3.2796117083785793e-06, 'epoch': 0.74}
+
74%|███████▍ | 8875/11952 [3:20:26<5:02:53, 5.91s/it]
74%|███████▍ | 8876/11952 [3:20:32<5:03:59, 5.93s/it]
{'loss': 0.461, 'learning_rate': 3.2776052275323155e-06, 'epoch': 0.74}
+
74%|███████▍ | 8876/11952 [3:20:32<5:03:59, 5.93s/it]
74%|███████▍ | 8877/11952 [3:20:38<5:02:57, 5.91s/it]
{'loss': 0.4508, 'learning_rate': 3.2755992403507595e-06, 'epoch': 0.74}
+
74%|███████▍ | 8877/11952 [3:20:38<5:02:57, 5.91s/it]
74%|███████▍ | 8878/11952 [3:20:44<5:00:46, 5.87s/it]
{'loss': 0.4643, 'learning_rate': 3.2735937469812308e-06, 'epoch': 0.74}
+
74%|███████▍ | 8878/11952 [3:20:44<5:00:46, 5.87s/it]
74%|███████▍ | 8879/11952 [3:20:49<4:56:16, 5.78s/it]
{'loss': 0.4558, 'learning_rate': 3.2715887475709994e-06, 'epoch': 0.74}
+
74%|███████▍ | 8879/11952 [3:20:49<4:56:16, 5.78s/it]
74%|███████▍ | 8880/11952 [3:20:55<4:51:30, 5.69s/it]
{'loss': 0.4459, 'learning_rate': 3.269584242267301e-06, 'epoch': 0.74}
+
74%|███████▍ | 8880/11952 [3:20:55<4:51:30, 5.69s/it]
74%|███████▍ | 8881/11952 [3:21:00<4:51:04, 5.69s/it]
{'loss': 0.4652, 'learning_rate': 3.2675802312173468e-06, 'epoch': 0.74}
+
74%|███████▍ | 8881/11952 [3:21:00<4:51:04, 5.69s/it]
74%|███████▍ | 8882/11952 [3:21:06<4:54:55, 5.76s/it]
{'loss': 0.4812, 'learning_rate': 3.265576714568296e-06, 'epoch': 0.74}
+
74%|███████▍ | 8882/11952 [3:21:06<4:54:55, 5.76s/it]
74%|███████▍ | 8883/11952 [3:21:12<4:59:41, 5.86s/it]
{'loss': 0.4507, 'learning_rate': 3.263573692467282e-06, 'epoch': 0.74}
+
74%|███████▍ | 8883/11952 [3:21:12<4:59:41, 5.86s/it]
74%|███████▍ | 8884/11952 [3:21:18<4:58:35, 5.84s/it]
{'loss': 0.4705, 'learning_rate': 3.2615711650613978e-06, 'epoch': 0.74}
+
74%|███████▍ | 8884/11952 [3:21:18<4:58:35, 5.84s/it]
74%|███████▍ | 8885/11952 [3:21:24<5:04:05, 5.95s/it]
{'loss': 0.4785, 'learning_rate': 3.2595691324976987e-06, 'epoch': 0.74}
+
74%|███████▍ | 8885/11952 [3:21:24<5:04:05, 5.95s/it]
74%|███████▍ | 8886/11952 [3:21:30<5:04:54, 5.97s/it]
{'loss': 0.4464, 'learning_rate': 3.2575675949232044e-06, 'epoch': 0.74}
+
74%|███████▍ | 8886/11952 [3:21:30<5:04:54, 5.97s/it]
74%|███████▍ | 8887/11952 [3:21:36<5:03:09, 5.93s/it]
{'loss': 0.4793, 'learning_rate': 3.2555665524849056e-06, 'epoch': 0.74}
+
74%|███████▍ | 8887/11952 [3:21:36<5:03:09, 5.93s/it]
74%|███████▍ | 8888/11952 [3:21:42<4:57:42, 5.83s/it]
{'loss': 0.467, 'learning_rate': 3.2535660053297426e-06, 'epoch': 0.74}
+
74%|███████▍ | 8888/11952 [3:21:42<4:57:42, 5.83s/it]
74%|███████▍ | 8889/11952 [3:21:48<4:57:05, 5.82s/it]
{'loss': 0.4741, 'learning_rate': 3.2515659536046362e-06, 'epoch': 0.74}
+
74%|███████▍ | 8889/11952 [3:21:48<4:57:05, 5.82s/it]
74%|███████▍ | 8890/11952 [3:21:54<4:58:20, 5.85s/it]
{'loss': 0.456, 'learning_rate': 3.249566397456456e-06, 'epoch': 0.74}
+
74%|███████▍ | 8890/11952 [3:21:54<4:58:20, 5.85s/it]
74%|███████▍ | 8891/11952 [3:22:00<5:02:32, 5.93s/it]
{'loss': 0.4789, 'learning_rate': 3.2475673370320437e-06, 'epoch': 0.74}
+
74%|███████▍ | 8891/11952 [3:22:00<5:02:32, 5.93s/it]
74%|███████▍ | 8892/11952 [3:22:06<4:59:50, 5.88s/it]
{'loss': 0.4689, 'learning_rate': 3.2455687724781993e-06, 'epoch': 0.74}
+
74%|███████▍ | 8892/11952 [3:22:06<4:59:50, 5.88s/it]
74%|███████▍ | 8893/11952 [3:22:12<5:02:19, 5.93s/it]
{'loss': 0.4554, 'learning_rate': 3.243570703941692e-06, 'epoch': 0.74}
+
74%|███████▍ | 8893/11952 [3:22:12<5:02:19, 5.93s/it]
74%|███████▍ | 8894/11952 [3:22:17<4:55:36, 5.80s/it]
{'loss': 0.4697, 'learning_rate': 3.2415731315692456e-06, 'epoch': 0.74}
+
74%|███████▍ | 8894/11952 [3:22:17<4:55:36, 5.80s/it]
74%|███████▍ | 8895/11952 [3:22:23<4:52:08, 5.73s/it]
{'loss': 0.4546, 'learning_rate': 3.2395760555075616e-06, 'epoch': 0.74}
+
74%|███████▍ | 8895/11952 [3:22:23<4:52:08, 5.73s/it]
74%|███████▍ | 8896/11952 [3:22:28<4:50:37, 5.71s/it]
{'loss': 0.4439, 'learning_rate': 3.237579475903294e-06, 'epoch': 0.74}
+
74%|███████▍ | 8896/11952 [3:22:28<4:50:37, 5.71s/it]
74%|███████▍ | 8897/11952 [3:22:34<4:52:15, 5.74s/it]
{'loss': 0.4737, 'learning_rate': 3.235583392903059e-06, 'epoch': 0.74}
+
74%|███████▍ | 8897/11952 [3:22:34<4:52:15, 5.74s/it]
74%|███████▍ | 8898/11952 [3:22:40<4:57:18, 5.84s/it]
{'loss': 0.4907, 'learning_rate': 3.2335878066534464e-06, 'epoch': 0.74}
+
74%|███████▍ | 8898/11952 [3:22:40<4:57:18, 5.84s/it]
74%|███████▍ | 8899/11952 [3:22:46<4:53:49, 5.77s/it]
{'loss': 0.4479, 'learning_rate': 3.231592717301003e-06, 'epoch': 0.74}
+
74%|███████▍ | 8899/11952 [3:22:46<4:53:49, 5.77s/it]3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 2AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+
74%|███████▍ | 8900/11952 [3:22:51<4:51:47, 5.74s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4761, 'learning_rate': 3.229598124992238e-06, 'epoch': 0.74}
+
74%|███████▍ | 8900/11952 [3:22:51<4:51:47, 5.74s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-8900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
74%|███████▍ | 8901/11952 [3:23:21<10:48:25, 12.75s/it]
{'loss': 0.4905, 'learning_rate': 3.2276040298736246e-06, 'epoch': 0.74}
+
74%|███████▍ | 8901/11952 [3:23:21<10:48:25, 12.75s/it]
74%|███████▍ | 8902/11952 [3:23:27<9:08:24, 10.79s/it]
{'loss': 0.4728, 'learning_rate': 3.225610432091604e-06, 'epoch': 0.74}
+
74%|███████▍ | 8902/11952 [3:23:27<9:08:24, 10.79s/it]
74%|███████▍ | 8903/11952 [3:23:33<7:55:52, 9.36s/it]
{'loss': 0.4552, 'learning_rate': 3.223617331792578e-06, 'epoch': 0.74}
+
74%|███████▍ | 8903/11952 [3:23:33<7:55:52, 9.36s/it]
74%|███████▍ | 8904/11952 [3:23:38<6:59:35, 8.26s/it]
{'loss': 0.4697, 'learning_rate': 3.2216247291229087e-06, 'epoch': 0.74}
+
74%|███████▍ | 8904/11952 [3:23:38<6:59:35, 8.26s/it]
75%|███████▍ | 8905/11952 [3:23:44<6:18:29, 7.45s/it]
{'loss': 0.4414, 'learning_rate': 3.2196326242289266e-06, 'epoch': 0.75}
+
75%|███████▍ | 8905/11952 [3:23:44<6:18:29, 7.45s/it]
75%|███████▍ | 8906/11952 [3:23:50<5:51:12, 6.92s/it]
{'loss': 0.4574, 'learning_rate': 3.217641017256923e-06, 'epoch': 0.75}
+
75%|███████▍ | 8906/11952 [3:23:50<5:51:12, 6.92s/it]
75%|███████▍ | 8907/11952 [3:23:56<5:39:05, 6.68s/it]
{'loss': 0.4696, 'learning_rate': 3.21564990835315e-06, 'epoch': 0.75}
+
75%|███████▍ | 8907/11952 [3:23:56<5:39:05, 6.68s/it]
75%|███████▍ | 8908/11952 [3:24:02<5:27:34, 6.46s/it]
{'loss': 0.4626, 'learning_rate': 3.2136592976638293e-06, 'epoch': 0.75}
+
75%|███████▍ | 8908/11952 [3:24:02<5:27:34, 6.46s/it]
75%|███████▍ | 8909/11952 [3:24:08<5:19:40, 6.30s/it]
{'loss': 0.448, 'learning_rate': 3.2116691853351455e-06, 'epoch': 0.75}
+
75%|███████▍ | 8909/11952 [3:24:08<5:19:40, 6.30s/it]
75%|███████▍ | 8910/11952 [3:24:14<5:12:28, 6.16s/it]
{'loss': 0.4561, 'learning_rate': 3.2096795715132436e-06, 'epoch': 0.75}
+
75%|███████▍ | 8910/11952 [3:24:14<5:12:28, 6.16s/it]
75%|███████▍ | 8911/11952 [3:24:19<5:03:35, 5.99s/it]
{'loss': 0.4295, 'learning_rate': 3.2076904563442303e-06, 'epoch': 0.75}
+
75%|███████▍ | 8911/11952 [3:24:19<5:03:35, 5.99s/it]
75%|███████▍ | 8912/11952 [3:24:25<5:04:20, 6.01s/it]
{'loss': 0.4665, 'learning_rate': 3.2057018399741777e-06, 'epoch': 0.75}
+
75%|███████▍ | 8912/11952 [3:24:25<5:04:20, 6.01s/it]
75%|███████▍ | 8913/11952 [3:24:31<5:03:34, 5.99s/it]
{'loss': 0.4557, 'learning_rate': 3.2037137225491233e-06, 'epoch': 0.75}
+
75%|███████▍ | 8913/11952 [3:24:31<5:03:34, 5.99s/it]
75%|███████▍ | 8914/11952 [3:24:37<5:00:42, 5.94s/it]
{'loss': 0.4629, 'learning_rate': 3.2017261042150625e-06, 'epoch': 0.75}
+
75%|███████▍ | 8914/11952 [3:24:37<5:00:42, 5.94s/it]
75%|███████▍ | 8915/11952 [3:24:43<4:57:15, 5.87s/it]
{'loss': 0.455, 'learning_rate': 3.199738985117963e-06, 'epoch': 0.75}
+
75%|███████▍ | 8915/11952 [3:24:43<4:57:15, 5.87s/it]
75%|███████▍ | 8916/11952 [3:24:48<4:55:27, 5.84s/it]
{'loss': 0.4552, 'learning_rate': 3.197752365403748e-06, 'epoch': 0.75}
+
75%|███████▍ | 8916/11952 [3:24:48<4:55:27, 5.84s/it]
75%|███████▍ | 8917/11952 [3:24:54<4:54:25, 5.82s/it]
{'loss': 0.469, 'learning_rate': 3.195766245218307e-06, 'epoch': 0.75}
+
75%|███████▍ | 8917/11952 [3:24:54<4:54:25, 5.82s/it]
75%|███████▍ | 8918/11952 [3:25:00<4:59:54, 5.93s/it]
{'loss': 0.4608, 'learning_rate': 3.1937806247074875e-06, 'epoch': 0.75}
+
75%|███████▍ | 8918/11952 [3:25:00<4:59:54, 5.93s/it]
75%|███████▍ | 8919/11952 [3:25:06<4:53:41, 5.81s/it]
{'loss': 0.4603, 'learning_rate': 3.1917955040171146e-06, 'epoch': 0.75}
+
75%|███████▍ | 8919/11952 [3:25:06<4:53:41, 5.81s/it]
75%|███████▍ | 8920/11952 [3:25:12<4:52:59, 5.80s/it]
{'loss': 0.4671, 'learning_rate': 3.189810883292961e-06, 'epoch': 0.75}
+
75%|███████▍ | 8920/11952 [3:25:12<4:52:59, 5.80s/it]
75%|███████▍ | 8921/11952 [3:25:18<4:55:42, 5.85s/it]
{'loss': 0.4597, 'learning_rate': 3.187826762680768e-06, 'epoch': 0.75}
+
75%|███████▍ | 8921/11952 [3:25:18<4:55:42, 5.85s/it]
75%|███████▍ | 8922/11952 [3:25:24<4:58:28, 5.91s/it]
{'loss': 0.4783, 'learning_rate': 3.185843142326247e-06, 'epoch': 0.75}
+
75%|███████▍ | 8922/11952 [3:25:24<4:58:28, 5.91s/it]
75%|███████▍ | 8923/11952 [3:25:30<4:58:28, 5.91s/it]
{'loss': 0.4879, 'learning_rate': 3.1838600223750625e-06, 'epoch': 0.75}
+
75%|███████▍ | 8923/11952 [3:25:30<4:58:28, 5.91s/it]
75%|███████▍ | 8924/11952 [3:25:35<4:54:36, 5.84s/it]
{'loss': 0.452, 'learning_rate': 3.181877402972848e-06, 'epoch': 0.75}
+
75%|███████▍ | 8924/11952 [3:25:35<4:54:36, 5.84s/it]
75%|███████▍ | 8925/11952 [3:25:41<4:53:22, 5.82s/it]
{'loss': 0.4763, 'learning_rate': 3.1798952842651985e-06, 'epoch': 0.75}
+
75%|███████▍ | 8925/11952 [3:25:41<4:53:22, 5.82s/it]
75%|███████▍ | 8926/11952 [3:25:47<4:54:57, 5.85s/it]
{'loss': 0.4543, 'learning_rate': 3.177913666397673e-06, 'epoch': 0.75}
+
75%|███████▍ | 8926/11952 [3:25:47<4:54:57, 5.85s/it]
75%|███████▍ | 8927/11952 [3:25:53<4:50:44, 5.77s/it]
{'loss': 0.4596, 'learning_rate': 3.175932549515789e-06, 'epoch': 0.75}
+
75%|███████▍ | 8927/11952 [3:25:53<4:50:44, 5.77s/it]
75%|███████▍ | 8928/11952 [3:25:58<4:52:36, 5.81s/it]
{'loss': 0.4473, 'learning_rate': 3.173951933765038e-06, 'epoch': 0.75}
+
75%|███████▍ | 8928/11952 [3:25:58<4:52:36, 5.81s/it]
75%|███████▍ | 8929/11952 [3:26:04<4:51:35, 5.79s/it]
{'loss': 0.4753, 'learning_rate': 3.171971819290862e-06, 'epoch': 0.75}
+
75%|███████▍ | 8929/11952 [3:26:04<4:51:35, 5.79s/it]
75%|███████▍ | 8930/11952 [3:26:10<4:57:41, 5.91s/it]
{'loss': 0.4606, 'learning_rate': 3.169992206238679e-06, 'epoch': 0.75}
+
75%|███████▍ | 8930/11952 [3:26:10<4:57:41, 5.91s/it]
75%|███████▍ | 8931/11952 [3:26:16<4:55:08, 5.86s/it]
{'loss': 0.4574, 'learning_rate': 3.16801309475386e-06, 'epoch': 0.75}
+
75%|███████▍ | 8931/11952 [3:26:16<4:55:08, 5.86s/it]
75%|███████▍ | 8932/11952 [3:26:22<4:51:41, 5.80s/it]
{'loss': 0.4675, 'learning_rate': 3.166034484981744e-06, 'epoch': 0.75}
+
75%|███████▍ | 8932/11952 [3:26:22<4:51:41, 5.80s/it]
75%|███████▍ | 8933/11952 [3:26:28<4:56:00, 5.88s/it]
{'loss': 0.473, 'learning_rate': 3.1640563770676305e-06, 'epoch': 0.75}
+
75%|███████▍ | 8933/11952 [3:26:28<4:56:00, 5.88s/it]
75%|███████▍ | 8934/11952 [3:26:34<5:01:01, 5.98s/it]
{'loss': 0.4408, 'learning_rate': 3.1620787711567823e-06, 'epoch': 0.75}
+
75%|███████▍ | 8934/11952 [3:26:34<5:01:01, 5.98s/it]
75%|███████▍ | 8935/11952 [3:26:40<4:58:42, 5.94s/it]
{'loss': 0.4406, 'learning_rate': 3.1601016673944262e-06, 'epoch': 0.75}
+
75%|███████▍ | 8935/11952 [3:26:40<4:58:42, 5.94s/it]
75%|███████▍ | 8936/11952 [3:26:46<4:56:33, 5.90s/it]
{'loss': 0.4783, 'learning_rate': 3.158125065925758e-06, 'epoch': 0.75}
+
75%|███████▍ | 8936/11952 [3:26:46<4:56:33, 5.90s/it]
75%|███████▍ | 8937/11952 [3:26:52<4:54:52, 5.87s/it]
{'loss': 0.4705, 'learning_rate': 3.1561489668959268e-06, 'epoch': 0.75}
+
75%|███████▍ | 8937/11952 [3:26:52<4:54:52, 5.87s/it]
75%|███████▍ | 8938/11952 [3:26:57<4:50:56, 5.79s/it]
{'loss': 0.4587, 'learning_rate': 3.1541733704500464e-06, 'epoch': 0.75}
+
75%|███████▍ | 8938/11952 [3:26:57<4:50:56, 5.79s/it]
75%|███████▍ | 8939/11952 [3:27:03<4:55:15, 5.88s/it]
{'loss': 0.4524, 'learning_rate': 3.1521982767332038e-06, 'epoch': 0.75}
+
75%|███████▍ | 8939/11952 [3:27:03<4:55:15, 5.88s/it]
75%|███████▍ | 8940/11952 [3:27:10<5:01:56, 6.01s/it]
{'loss': 0.4647, 'learning_rate': 3.150223685890437e-06, 'epoch': 0.75}
+
75%|███████▍ | 8940/11952 [3:27:10<5:01:56, 6.01s/it]
75%|███████▍ | 8941/11952 [3:27:15<4:55:45, 5.89s/it]
{'loss': 0.4681, 'learning_rate': 3.1482495980667516e-06, 'epoch': 0.75}
+
75%|███████▍ | 8941/11952 [3:27:15<4:55:45, 5.89s/it]
75%|███████▍ | 8942/11952 [3:27:21<4:59:13, 5.96s/it]
{'loss': 0.4533, 'learning_rate': 3.1462760134071145e-06, 'epoch': 0.75}
+
75%|███████▍ | 8942/11952 [3:27:21<4:59:13, 5.96s/it]
75%|███████▍ | 8943/11952 [3:27:27<4:58:55, 5.96s/it]
{'loss': 0.4697, 'learning_rate': 3.1443029320564642e-06, 'epoch': 0.75}
+
75%|███████▍ | 8943/11952 [3:27:27<4:58:55, 5.96s/it]
75%|███████▍ | 8944/11952 [3:27:33<5:01:00, 6.00s/it]
{'loss': 0.4745, 'learning_rate': 3.1423303541596904e-06, 'epoch': 0.75}
+
75%|███████▍ | 8944/11952 [3:27:33<5:01:00, 6.00s/it]
75%|███████▍ | 8945/11952 [3:27:39<5:01:22, 6.01s/it]
{'loss': 0.4818, 'learning_rate': 3.1403582798616527e-06, 'epoch': 0.75}
+
75%|███████▍ | 8945/11952 [3:27:39<5:01:22, 6.01s/it]
75%|███████▍ | 8946/11952 [3:27:45<4:59:34, 5.98s/it]
{'loss': 0.4557, 'learning_rate': 3.1383867093071717e-06, 'epoch': 0.75}
+
75%|███████▍ | 8946/11952 [3:27:45<4:59:34, 5.98s/it]
75%|███████▍ | 8947/11952 [3:27:51<4:56:49, 5.93s/it]
{'loss': 0.4594, 'learning_rate': 3.1364156426410307e-06, 'epoch': 0.75}
+
75%|███████▍ | 8947/11952 [3:27:51<4:56:49, 5.93s/it]
75%|███████▍ | 8948/11952 [3:27:57<4:52:48, 5.85s/it]
{'loss': 0.4624, 'learning_rate': 3.1344450800079753e-06, 'epoch': 0.75}
+
75%|███████▍ | 8948/11952 [3:27:57<4:52:48, 5.85s/it]
75%|███████▍ | 8949/11952 [3:28:03<4:51:50, 5.83s/it]
{'loss': 0.4538, 'learning_rate': 3.1324750215527157e-06, 'epoch': 0.75}
+
75%|███████▍ | 8949/11952 [3:28:03<4:51:50, 5.83s/it]1 3AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
75%|███████▍ | 8950/11952 [3:28:08<4:48:39, 5.77s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4745, 'learning_rate': 3.1305054674199297e-06, 'epoch': 0.75}
+
75%|███████▍ | 8950/11952 [3:28:08<4:48:39, 5.77s/it]
75%|███████▍ | 8951/11952 [3:28:14<4:47:15, 5.74s/it]
{'loss': 0.4548, 'learning_rate': 3.12853641775425e-06, 'epoch': 0.75}
+
75%|███████▍ | 8951/11952 [3:28:14<4:47:15, 5.74s/it]
75%|███████▍ | 8952/11952 [3:28:20<4:47:43, 5.75s/it]
{'loss': 0.4664, 'learning_rate': 3.1265678727002758e-06, 'epoch': 0.75}
+
75%|███████▍ | 8952/11952 [3:28:20<4:47:43, 5.75s/it]
75%|███████▍ | 8953/11952 [3:28:26<4:48:51, 5.78s/it]
{'loss': 0.459, 'learning_rate': 3.124599832402567e-06, 'epoch': 0.75}
+
75%|███████▍ | 8953/11952 [3:28:26<4:48:51, 5.78s/it]
75%|███████▍ | 8954/11952 [3:28:31<4:47:41, 5.76s/it]
{'loss': 0.4514, 'learning_rate': 3.122632297005651e-06, 'epoch': 0.75}
+
75%|███████▍ | 8954/11952 [3:28:31<4:47:41, 5.76s/it]
75%|███████▍ | 8955/11952 [3:28:37<4:51:12, 5.83s/it]
{'loss': 0.5009, 'learning_rate': 3.1206652666540107e-06, 'epoch': 0.75}
+
75%|███████▍ | 8955/11952 [3:28:37<4:51:12, 5.83s/it]
75%|███████▍ | 8956/11952 [3:28:43<4:49:40, 5.80s/it]
{'loss': 0.451, 'learning_rate': 3.1186987414921023e-06, 'epoch': 0.75}
+
75%|███████▍ | 8956/11952 [3:28:43<4:49:40, 5.80s/it]
75%|███████▍ | 8957/11952 [3:28:49<4:50:22, 5.82s/it]
{'loss': 0.4915, 'learning_rate': 3.1167327216643374e-06, 'epoch': 0.75}
+
75%|███████▍ | 8957/11952 [3:28:49<4:50:22, 5.82s/it]
75%|███████▍ | 8958/11952 [3:28:54<4:47:28, 5.76s/it]
{'loss': 0.4549, 'learning_rate': 3.1147672073150916e-06, 'epoch': 0.75}
+
75%|███████▍ | 8958/11952 [3:28:54<4:47:28, 5.76s/it]
75%|███████▍ | 8959/11952 [3:29:00<4:49:01, 5.79s/it]
{'loss': 0.4543, 'learning_rate': 3.1128021985887004e-06, 'epoch': 0.75}
+
75%|███████▍ | 8959/11952 [3:29:00<4:49:01, 5.79s/it]
75%|███████▍ | 8960/11952 [3:29:06<4:48:00, 5.78s/it]
{'loss': 0.4726, 'learning_rate': 3.110837695629473e-06, 'epoch': 0.75}
+
75%|███████▍ | 8960/11952 [3:29:06<4:48:00, 5.78s/it]
75%|███████▍ | 8961/11952 [3:29:12<4:49:53, 5.82s/it]
{'loss': 0.4673, 'learning_rate': 3.1088736985816716e-06, 'epoch': 0.75}
+
75%|███████▍ | 8961/11952 [3:29:12<4:49:53, 5.82s/it]
75%|███████▍ | 8962/11952 [3:29:18<4:50:38, 5.83s/it]
{'loss': 0.4575, 'learning_rate': 3.1069102075895207e-06, 'epoch': 0.75}
+
75%|███████▍ | 8962/11952 [3:29:18<4:50:38, 5.83s/it]
75%|███████▍ | 8963/11952 [3:29:24<4:49:07, 5.80s/it]
{'loss': 0.4507, 'learning_rate': 3.1049472227972157e-06, 'epoch': 0.75}
+
75%|███████▍ | 8963/11952 [3:29:24<4:49:07, 5.80s/it]
75%|███████▌ | 8964/11952 [3:29:29<4:47:17, 5.77s/it]
{'loss': 0.4733, 'learning_rate': 3.1029847443489093e-06, 'epoch': 0.75}
+
75%|███████▌ | 8964/11952 [3:29:29<4:47:17, 5.77s/it]
75%|███████▌ | 8965/11952 [3:29:35<4:49:52, 5.82s/it]
{'loss': 0.4522, 'learning_rate': 3.1010227723887153e-06, 'epoch': 0.75}
+
75%|███████▌ | 8965/11952 [3:29:35<4:49:52, 5.82s/it]
75%|███████▌ | 8966/11952 [3:29:41<4:49:33, 5.82s/it]
{'loss': 0.4629, 'learning_rate': 3.0990613070607145e-06, 'epoch': 0.75}
+
75%|███████▌ | 8966/11952 [3:29:41<4:49:33, 5.82s/it]
75%|███████▌ | 8967/11952 [3:29:47<4:48:34, 5.80s/it]
{'loss': 0.4818, 'learning_rate': 3.0971003485089477e-06, 'epoch': 0.75}
+
75%|███████▌ | 8967/11952 [3:29:47<4:48:34, 5.80s/it]
75%|███████▌ | 8968/11952 [3:29:53<4:50:08, 5.83s/it]
{'loss': 0.4479, 'learning_rate': 3.095139896877417e-06, 'epoch': 0.75}
+
75%|███████▌ | 8968/11952 [3:29:53<4:50:08, 5.83s/it]
75%|███████▌ | 8969/11952 [3:29:59<4:51:40, 5.87s/it]
{'loss': 0.4705, 'learning_rate': 3.093179952310096e-06, 'epoch': 0.75}
+
75%|███████▌ | 8969/11952 [3:29:59<4:51:40, 5.87s/it]
75%|███████▌ | 8970/11952 [3:30:04<4:51:33, 5.87s/it]
{'loss': 0.4932, 'learning_rate': 3.091220514950908e-06, 'epoch': 0.75}
+
75%|███████▌ | 8970/11952 [3:30:04<4:51:33, 5.87s/it]
75%|███████▌ | 8971/11952 [3:30:10<4:51:17, 5.86s/it]
{'loss': 0.4519, 'learning_rate': 3.0892615849437533e-06, 'epoch': 0.75}
+
75%|███████▌ | 8971/11952 [3:30:10<4:51:17, 5.86s/it]
75%|███████▌ | 8972/11952 [3:30:16<4:47:09, 5.78s/it]
{'loss': 0.4589, 'learning_rate': 3.0873031624324835e-06, 'epoch': 0.75}
+
75%|███████▌ | 8972/11952 [3:30:16<4:47:09, 5.78s/it]
75%|███████▌ | 8973/11952 [3:30:22<4:48:31, 5.81s/it]
{'loss': 0.4546, 'learning_rate': 3.085345247560918e-06, 'epoch': 0.75}
+
75%|███████▌ | 8973/11952 [3:30:22<4:48:31, 5.81s/it]
75%|███████▌ | 8974/11952 [3:30:27<4:46:15, 5.77s/it]
{'loss': 0.4622, 'learning_rate': 3.0833878404728366e-06, 'epoch': 0.75}
+
75%|███████▌ | 8974/11952 [3:30:27<4:46:15, 5.77s/it]
75%|███████▌ | 8975/11952 [3:30:34<4:51:12, 5.87s/it]
{'loss': 0.4992, 'learning_rate': 3.081430941311985e-06, 'epoch': 0.75}
+
75%|███████▌ | 8975/11952 [3:30:34<4:51:12, 5.87s/it]
75%|███████▌ | 8976/11952 [3:30:39<4:50:30, 5.86s/it]
{'loss': 0.4815, 'learning_rate': 3.0794745502220646e-06, 'epoch': 0.75}
+
75%|███████▌ | 8976/11952 [3:30:39<4:50:30, 5.86s/it]
75%|███████▌ | 8977/11952 [3:30:46<4:55:29, 5.96s/it]
{'loss': 0.4669, 'learning_rate': 3.077518667346752e-06, 'epoch': 0.75}
+
75%|███████▌ | 8977/11952 [3:30:46<4:55:29, 5.96s/it]
75%|███████▌ | 8978/11952 [3:30:52<4:54:48, 5.95s/it]
{'loss': 0.4699, 'learning_rate': 3.075563292829675e-06, 'epoch': 0.75}
+
75%|███████▌ | 8978/11952 [3:30:52<4:54:48, 5.95s/it]
75%|███████▌ | 8979/11952 [3:30:58<5:01:08, 6.08s/it]
{'loss': 0.4627, 'learning_rate': 3.0736084268144264e-06, 'epoch': 0.75}
+
75%|███████▌ | 8979/11952 [3:30:58<5:01:08, 6.08s/it]
75%|███████▌ | 8980/11952 [3:31:04<4:59:20, 6.04s/it]
{'loss': 0.4654, 'learning_rate': 3.0716540694445694e-06, 'epoch': 0.75}
+
75%|███████▌ | 8980/11952 [3:31:04<4:59:20, 6.04s/it]
75%|███████▌ | 8981/11952 [3:31:10<4:56:01, 5.98s/it]
{'loss': 0.4628, 'learning_rate': 3.0697002208636195e-06, 'epoch': 0.75}
+
75%|███████▌ | 8981/11952 [3:31:10<4:56:01, 5.98s/it]
75%|███████▌ | 8982/11952 [3:31:16<4:55:33, 5.97s/it]
{'loss': 0.4558, 'learning_rate': 3.0677468812150612e-06, 'epoch': 0.75}
+
75%|███████▌ | 8982/11952 [3:31:16<4:55:33, 5.97s/it]
75%|███████▌ | 8983/11952 [3:31:22<4:57:25, 6.01s/it]
{'loss': 0.4844, 'learning_rate': 3.0657940506423345e-06, 'epoch': 0.75}
+
75%|███████▌ | 8983/11952 [3:31:22<4:57:25, 6.01s/it]
75%|███████▌ | 8984/11952 [3:31:28<4:58:08, 6.03s/it]
{'loss': 0.4778, 'learning_rate': 3.0638417292888546e-06, 'epoch': 0.75}
+
75%|███████▌ | 8984/11952 [3:31:28<4:58:08, 6.03s/it]
75%|███████▌ | 8985/11952 [3:31:34<4:56:38, 6.00s/it]
{'loss': 0.4671, 'learning_rate': 3.0618899172979875e-06, 'epoch': 0.75}
+
75%|███████▌ | 8985/11952 [3:31:34<4:56:38, 6.00s/it]
75%|███████▌ | 8986/11952 [3:31:40<4:54:00, 5.95s/it]
{'loss': 0.4511, 'learning_rate': 3.0599386148130684e-06, 'epoch': 0.75}
+
75%|███████▌ | 8986/11952 [3:31:40<4:54:00, 5.95s/it]
75%|███████▌ | 8987/11952 [3:31:45<4:49:51, 5.87s/it]
{'loss': 0.4486, 'learning_rate': 3.0579878219773917e-06, 'epoch': 0.75}
+
75%|███████▌ | 8987/11952 [3:31:45<4:49:51, 5.87s/it]
75%|███████▌ | 8988/11952 [3:31:51<4:49:16, 5.86s/it]
{'loss': 0.4686, 'learning_rate': 3.0560375389342147e-06, 'epoch': 0.75}
+
75%|███████▌ | 8988/11952 [3:31:51<4:49:16, 5.86s/it]
75%|███████▌ | 8989/11952 [3:31:57<4:47:26, 5.82s/it]
{'loss': 0.4589, 'learning_rate': 3.0540877658267555e-06, 'epoch': 0.75}
+
75%|███████▌ | 8989/11952 [3:31:57<4:47:26, 5.82s/it]
75%|███████▌ | 8990/11952 [3:32:02<4:45:02, 5.77s/it]
{'loss': 0.4522, 'learning_rate': 3.0521385027982033e-06, 'epoch': 0.75}
+
75%|███████▌ | 8990/11952 [3:32:03<4:45:02, 5.77s/it]
75%|███████▌ | 8991/11952 [3:32:08<4:41:29, 5.70s/it]
{'loss': 0.4682, 'learning_rate': 3.050189749991699e-06, 'epoch': 0.75}
+
75%|███████▌ | 8991/11952 [3:32:08<4:41:29, 5.70s/it]
75%|███████▌ | 8992/11952 [3:32:14<4:41:15, 5.70s/it]
{'loss': 0.4816, 'learning_rate': 3.0482415075503556e-06, 'epoch': 0.75}
+
75%|███████▌ | 8992/11952 [3:32:14<4:41:15, 5.70s/it]
75%|███████▌ | 8993/11952 [3:32:20<4:43:29, 5.75s/it]
{'loss': 0.4533, 'learning_rate': 3.0462937756172417e-06, 'epoch': 0.75}
+
75%|███████▌ | 8993/11952 [3:32:20<4:43:29, 5.75s/it]
75%|███████▌ | 8994/11952 [3:32:25<4:45:18, 5.79s/it]
{'loss': 0.4747, 'learning_rate': 3.0443465543353902e-06, 'epoch': 0.75}
+
75%|███████▌ | 8994/11952 [3:32:25<4:45:18, 5.79s/it]
75%|███████▌ | 8995/11952 [3:32:31<4:45:49, 5.80s/it]
{'loss': 0.4747, 'learning_rate': 3.0423998438477964e-06, 'epoch': 0.75}
+
75%|███████▌ | 8995/11952 [3:32:31<4:45:49, 5.80s/it]
75%|███████▌ | 8996/11952 [3:32:37<4:42:49, 5.74s/it]
{'loss': 0.4568, 'learning_rate': 3.0404536442974165e-06, 'epoch': 0.75}
+
75%|███████▌ | 8996/11952 [3:32:37<4:42:49, 5.74s/it]
75%|███████▌ | 8997/11952 [3:32:43<4:45:11, 5.79s/it]
{'loss': 0.4665, 'learning_rate': 3.0385079558271768e-06, 'epoch': 0.75}
+
75%|███████▌ | 8997/11952 [3:32:43<4:45:11, 5.79s/it]
75%|███████▌ | 8998/11952 [3:32:49<4:48:30, 5.86s/it]
{'loss': 0.4617, 'learning_rate': 3.036562778579959e-06, 'epoch': 0.75}
+
75%|███████▌ | 8998/11952 [3:32:49<4:48:30, 5.86s/it]
75%|███████▌ | 8999/11952 [3:32:55<4:47:27, 5.84s/it]
{'loss': 0.4713, 'learning_rate': 3.0346181126986063e-06, 'epoch': 0.75}
+
75%|███████▌ | 8999/11952 [3:32:55<4:47:27, 5.84s/it]1 AutoResumeHook: Checking whether to suspend...7
+AutoResumeHook: Checking whether to suspend...3
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
75%|███████▌ | 9000/11952 [3:33:00<4:47:00, 5.83s/it]2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4868, 'learning_rate': 3.0326739583259255e-06, 'epoch': 0.75}
+
75%|███████▌ | 9000/11952 [3:33:00<4:47:00, 5.83s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
75%|███████▌ | 9001/11952 [3:33:30<10:44:14, 13.10s/it]
{'loss': 0.4813, 'learning_rate': 3.030730315604693e-06, 'epoch': 0.75}
+
75%|███████▌ | 9001/11952 [3:33:30<10:44:14, 13.10s/it]
75%|███████▌ | 9002/11952 [3:33:36<8:57:03, 10.92s/it]
{'loss': 0.4769, 'learning_rate': 3.0287871846776397e-06, 'epoch': 0.75}
+
75%|███████▌ | 9002/11952 [3:33:36<8:57:03, 10.92s/it]
75%|███████▌ | 9003/11952 [3:33:42<7:39:30, 9.35s/it]
{'loss': 0.4529, 'learning_rate': 3.0268445656874555e-06, 'epoch': 0.75}
+
75%|███████▌ | 9003/11952 [3:33:42<7:39:30, 9.35s/it]
75%|███████▌ | 9004/11952 [3:33:48<6:45:34, 8.25s/it]
{'loss': 0.4653, 'learning_rate': 3.0249024587768074e-06, 'epoch': 0.75}
+
75%|███████▌ | 9004/11952 [3:33:48<6:45:34, 8.25s/it]
75%|███████▌ | 9005/11952 [3:33:54<6:09:40, 7.53s/it]
{'loss': 0.4987, 'learning_rate': 3.02296086408831e-06, 'epoch': 0.75}
+
75%|███████▌ | 9005/11952 [3:33:54<6:09:40, 7.53s/it]
75%|███████▌ | 9006/11952 [3:33:59<5:43:15, 6.99s/it]
{'loss': 0.445, 'learning_rate': 3.0210197817645472e-06, 'epoch': 0.75}
+
75%|███████▌ | 9006/11952 [3:33:59<5:43:15, 6.99s/it]
75%|███████▌ | 9007/11952 [3:34:05<5:25:01, 6.62s/it]
{'loss': 0.4692, 'learning_rate': 3.0190792119480638e-06, 'epoch': 0.75}
+
75%|███████▌ | 9007/11952 [3:34:05<5:25:01, 6.62s/it]
75%|███████▌ | 9008/11952 [3:34:11<5:10:48, 6.33s/it]
{'loss': 0.4617, 'learning_rate': 3.017139154781368e-06, 'epoch': 0.75}
+
75%|███████▌ | 9008/11952 [3:34:11<5:10:48, 6.33s/it]
75%|███████▌ | 9009/11952 [3:34:16<5:01:22, 6.14s/it]
{'loss': 0.4727, 'learning_rate': 3.015199610406925e-06, 'epoch': 0.75}
+
75%|███████▌ | 9009/11952 [3:34:16<5:01:22, 6.14s/it]
75%|███████▌ | 9010/11952 [3:34:23<5:00:51, 6.14s/it]
{'loss': 0.4471, 'learning_rate': 3.0132605789671744e-06, 'epoch': 0.75}
+
75%|███████▌ | 9010/11952 [3:34:23<5:00:51, 6.14s/it]
75%|███████▌ | 9011/11952 [3:34:29<5:00:13, 6.13s/it]
{'loss': 0.4654, 'learning_rate': 3.0113220606045035e-06, 'epoch': 0.75}
+
75%|███████▌ | 9011/11952 [3:34:29<5:00:13, 6.13s/it]
75%|███████▌ | 9012/11952 [3:34:35<5:01:15, 6.15s/it]
{'loss': 0.4895, 'learning_rate': 3.0093840554612753e-06, 'epoch': 0.75}
+
75%|███████▌ | 9012/11952 [3:34:35<5:01:15, 6.15s/it]
75%|███████▌ | 9013/11952 [3:34:41<4:58:45, 6.10s/it]
{'loss': 0.4657, 'learning_rate': 3.0074465636798056e-06, 'epoch': 0.75}
+
75%|███████▌ | 9013/11952 [3:34:41<4:58:45, 6.10s/it]
75%|███████▌ | 9014/11952 [3:34:47<4:54:17, 6.01s/it]
{'loss': 0.483, 'learning_rate': 3.0055095854023764e-06, 'epoch': 0.75}
+
75%|███████▌ | 9014/11952 [3:34:47<4:54:17, 6.01s/it]
75%|███████▌ | 9015/11952 [3:34:52<4:50:01, 5.92s/it]
{'loss': 0.4526, 'learning_rate': 3.0035731207712305e-06, 'epoch': 0.75}
+
75%|███████▌ | 9015/11952 [3:34:52<4:50:01, 5.92s/it]
75%|███████▌ | 9016/11952 [3:34:58<4:46:58, 5.86s/it]
{'loss': 0.4655, 'learning_rate': 3.001637169928575e-06, 'epoch': 0.75}
+
75%|███████▌ | 9016/11952 [3:34:58<4:46:58, 5.86s/it]
75%|███████▌ | 9017/11952 [3:35:04<4:48:10, 5.89s/it]
{'loss': 0.4689, 'learning_rate': 2.9997017330165736e-06, 'epoch': 0.75}
+
75%|███████▌ | 9017/11952 [3:35:04<4:48:10, 5.89s/it]
75%|███████▌ | 9018/11952 [3:35:10<4:53:14, 6.00s/it]
{'loss': 0.4669, 'learning_rate': 2.9977668101773636e-06, 'epoch': 0.75}
+
75%|███████▌ | 9018/11952 [3:35:10<4:53:14, 6.00s/it]
75%|███████▌ | 9019/11952 [3:35:16<4:50:15, 5.94s/it]
{'loss': 0.4726, 'learning_rate': 2.995832401553035e-06, 'epoch': 0.75}
+
75%|███████▌ | 9019/11952 [3:35:16<4:50:15, 5.94s/it]
75%|███████▌ | 9020/11952 [3:35:22<4:51:27, 5.96s/it]
{'loss': 0.4629, 'learning_rate': 2.993898507285643e-06, 'epoch': 0.75}
+
75%|███████▌ | 9020/11952 [3:35:22<4:51:27, 5.96s/it]
75%|███████▌ | 9021/11952 [3:35:28<4:48:44, 5.91s/it]
{'loss': 0.4591, 'learning_rate': 2.9919651275172e-06, 'epoch': 0.75}
+
75%|███████▌ | 9021/11952 [3:35:28<4:48:44, 5.91s/it]
75%|███████▌ | 9022/11952 [3:35:34<4:46:24, 5.86s/it]
{'loss': 0.4758, 'learning_rate': 2.990032262389693e-06, 'epoch': 0.75}
+
75%|███████▌ | 9022/11952 [3:35:34<4:46:24, 5.86s/it]
75%|███████▌ | 9023/11952 [3:35:40<4:48:23, 5.91s/it]
{'loss': 0.4545, 'learning_rate': 2.9880999120450595e-06, 'epoch': 0.75}
+
75%|███████▌ | 9023/11952 [3:35:40<4:48:23, 5.91s/it]
76%|███████▌ | 9024/11952 [3:35:46<4:47:40, 5.90s/it]
{'loss': 0.4509, 'learning_rate': 2.9861680766252e-06, 'epoch': 0.75}
+
76%|███████▌ | 9024/11952 [3:35:46<4:47:40, 5.90s/it]
76%|███████▌ | 9025/11952 [3:35:52<4:50:38, 5.96s/it]
{'loss': 0.4604, 'learning_rate': 2.9842367562719887e-06, 'epoch': 0.76}
+
76%|███████▌ | 9025/11952 [3:35:52<4:50:38, 5.96s/it]
76%|███████▌ | 9026/11952 [3:35:58<4:50:09, 5.95s/it]
{'loss': 0.46, 'learning_rate': 2.982305951127249e-06, 'epoch': 0.76}
+
76%|███████▌ | 9026/11952 [3:35:58<4:50:09, 5.95s/it]
76%|███████▌ | 9027/11952 [3:36:03<4:48:54, 5.93s/it]
{'loss': 0.4715, 'learning_rate': 2.9803756613327704e-06, 'epoch': 0.76}
+
76%|███████▌ | 9027/11952 [3:36:03<4:48:54, 5.93s/it]
76%|███████▌ | 9028/11952 [3:36:09<4:43:13, 5.81s/it]
{'loss': 0.4413, 'learning_rate': 2.978445887030308e-06, 'epoch': 0.76}
+
76%|███████▌ | 9028/11952 [3:36:09<4:43:13, 5.81s/it]
76%|███████▌ | 9029/11952 [3:36:15<4:40:23, 5.76s/it]
{'loss': 0.4943, 'learning_rate': 2.976516628361574e-06, 'epoch': 0.76}
+
76%|███████▌ | 9029/11952 [3:36:15<4:40:23, 5.76s/it]
76%|███████▌ | 9030/11952 [3:36:20<4:41:37, 5.78s/it]
{'loss': 0.4575, 'learning_rate': 2.974587885468243e-06, 'epoch': 0.76}
+
76%|███████▌ | 9030/11952 [3:36:20<4:41:37, 5.78s/it]
76%|███████▌ | 9031/11952 [3:36:26<4:42:15, 5.80s/it]
{'loss': 0.4496, 'learning_rate': 2.9726596584919596e-06, 'epoch': 0.76}
+
76%|███████▌ | 9031/11952 [3:36:26<4:42:15, 5.80s/it]
76%|███████▌ | 9032/11952 [3:36:32<4:41:54, 5.79s/it]
{'loss': 0.4542, 'learning_rate': 2.970731947574319e-06, 'epoch': 0.76}
+
76%|███████▌ | 9032/11952 [3:36:32<4:41:54, 5.79s/it]
76%|███████▌ | 9033/11952 [3:36:38<4:45:26, 5.87s/it]
{'loss': 0.4855, 'learning_rate': 2.968804752856891e-06, 'epoch': 0.76}
+
76%|███████▌ | 9033/11952 [3:36:38<4:45:26, 5.87s/it]
76%|███████▌ | 9034/11952 [3:36:44<4:49:22, 5.95s/it]
{'loss': 0.4437, 'learning_rate': 2.9668780744811967e-06, 'epoch': 0.76}
+
76%|███████▌ | 9034/11952 [3:36:44<4:49:22, 5.95s/it]
76%|███████▌ | 9035/11952 [3:36:50<4:43:49, 5.84s/it]
{'loss': 0.4699, 'learning_rate': 2.9649519125887227e-06, 'epoch': 0.76}
+
76%|███████▌ | 9035/11952 [3:36:50<4:43:49, 5.84s/it]
76%|███████▌ | 9036/11952 [3:36:55<4:38:49, 5.74s/it]
{'loss': 0.4794, 'learning_rate': 2.96302626732092e-06, 'epoch': 0.76}
+
76%|███████▌ | 9036/11952 [3:36:55<4:38:49, 5.74s/it]
76%|███████▌ | 9037/11952 [3:37:01<4:43:30, 5.84s/it]
{'loss': 0.4607, 'learning_rate': 2.9611011388191956e-06, 'epoch': 0.76}
+
76%|███████▌ | 9037/11952 [3:37:01<4:43:30, 5.84s/it]
76%|███████▌ | 9038/11952 [3:37:07<4:39:08, 5.75s/it]
{'loss': 0.472, 'learning_rate': 2.9591765272249305e-06, 'epoch': 0.76}
+
76%|███████▌ | 9038/11952 [3:37:07<4:39:08, 5.75s/it]
76%|███████▌ | 9039/11952 [3:37:13<4:41:18, 5.79s/it]
{'loss': 0.4636, 'learning_rate': 2.9572524326794562e-06, 'epoch': 0.76}
+
76%|███████▌ | 9039/11952 [3:37:13<4:41:18, 5.79s/it]
76%|███████▌ | 9040/11952 [3:37:19<4:44:00, 5.85s/it]
{'loss': 0.4749, 'learning_rate': 2.9553288553240698e-06, 'epoch': 0.76}
+
76%|███████▌ | 9040/11952 [3:37:19<4:44:00, 5.85s/it]
76%|███████▌ | 9041/11952 [3:37:25<4:51:43, 6.01s/it]
{'loss': 0.4753, 'learning_rate': 2.9534057953000283e-06, 'epoch': 0.76}
+
76%|███████▌ | 9041/11952 [3:37:25<4:51:43, 6.01s/it]
76%|███████▌ | 9042/11952 [3:37:31<4:45:20, 5.88s/it]
{'loss': 0.4424, 'learning_rate': 2.9514832527485593e-06, 'epoch': 0.76}
+
76%|███████▌ | 9042/11952 [3:37:31<4:45:20, 5.88s/it]
76%|███████▌ | 9043/11952 [3:37:36<4:41:14, 5.80s/it]
{'loss': 0.4706, 'learning_rate': 2.949561227810843e-06, 'epoch': 0.76}
+
76%|███████▌ | 9043/11952 [3:37:36<4:41:14, 5.80s/it]
76%|███████▌ | 9044/11952 [3:37:42<4:39:01, 5.76s/it]
{'loss': 0.4448, 'learning_rate': 2.947639720628023e-06, 'epoch': 0.76}
+
76%|███████▌ | 9044/11952 [3:37:42<4:39:01, 5.76s/it]
76%|███████▌ | 9045/11952 [3:37:48<4:40:20, 5.79s/it]
{'loss': 0.4846, 'learning_rate': 2.945718731341212e-06, 'epoch': 0.76}
+
76%|███████▌ | 9045/11952 [3:37:48<4:40:20, 5.79s/it]
76%|███████▌ | 9046/11952 [3:37:54<4:40:49, 5.80s/it]
{'loss': 0.4563, 'learning_rate': 2.943798260091475e-06, 'epoch': 0.76}
+
76%|███████▌ | 9046/11952 [3:37:54<4:40:49, 5.80s/it]
76%|███████▌ | 9047/11952 [3:38:00<4:40:49, 5.80s/it]
{'loss': 0.4693, 'learning_rate': 2.9418783070198455e-06, 'epoch': 0.76}
+
76%|███████▌ | 9047/11952 [3:38:00<4:40:49, 5.80s/it]
76%|███████▌ | 9048/11952 [3:38:05<4:38:44, 5.76s/it]
{'loss': 0.4424, 'learning_rate': 2.9399588722673165e-06, 'epoch': 0.76}
+
76%|███████▌ | 9048/11952 [3:38:05<4:38:44, 5.76s/it]
76%|███████▌ | 9049/11952 [3:38:11<4:43:17, 5.86s/it]
{'loss': 0.4605, 'learning_rate': 2.938039955974843e-06, 'epoch': 0.76}
+
76%|███████▌ | 9049/11952 [3:38:11<4:43:17, 5.86s/it]1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...3
+ AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+
76%|███████▌ | 9050/11952 [3:38:17<4:42:06, 5.83s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.474, 'learning_rate': 2.9361215582833425e-06, 'epoch': 0.76}
+
76%|███████▌ | 9050/11952 [3:38:17<4:42:06, 5.83s/it]
76%|███████▌ | 9051/11952 [3:38:23<4:42:38, 5.85s/it]
{'loss': 0.4644, 'learning_rate': 2.9342036793336904e-06, 'epoch': 0.76}
+
76%|███████▌ | 9051/11952 [3:38:23<4:42:38, 5.85s/it]
76%|███████▌ | 9052/11952 [3:38:29<4:49:05, 5.98s/it]
{'loss': 0.4739, 'learning_rate': 2.9322863192667306e-06, 'epoch': 0.76}
+
76%|███████▌ | 9052/11952 [3:38:29<4:49:05, 5.98s/it]
76%|███████▌ | 9053/11952 [3:38:35<4:48:05, 5.96s/it]
{'loss': 0.451, 'learning_rate': 2.9303694782232706e-06, 'epoch': 0.76}
+
76%|███████▌ | 9053/11952 [3:38:35<4:48:05, 5.96s/it]
76%|███████▌ | 9054/11952 [3:38:41<4:44:07, 5.88s/it]
{'loss': 0.4632, 'learning_rate': 2.928453156344071e-06, 'epoch': 0.76}
+
76%|███████▌ | 9054/11952 [3:38:41<4:44:07, 5.88s/it]
76%|███████▌ | 9055/11952 [3:38:47<4:46:45, 5.94s/it]
{'loss': 0.4599, 'learning_rate': 2.9265373537698595e-06, 'epoch': 0.76}
+
76%|███████▌ | 9055/11952 [3:38:47<4:46:45, 5.94s/it]
76%|███████▌ | 9056/11952 [3:38:53<4:46:29, 5.94s/it]
{'loss': 0.4581, 'learning_rate': 2.924622070641323e-06, 'epoch': 0.76}
+
76%|███████▌ | 9056/11952 [3:38:53<4:46:29, 5.94s/it]
76%|███████▌ | 9057/11952 [3:38:59<4:43:17, 5.87s/it]
{'loss': 0.4745, 'learning_rate': 2.922707307099113e-06, 'epoch': 0.76}
+
76%|███████▌ | 9057/11952 [3:38:59<4:43:17, 5.87s/it]
76%|███████▌ | 9058/11952 [3:39:04<4:43:56, 5.89s/it]
{'loss': 0.4713, 'learning_rate': 2.920793063283839e-06, 'epoch': 0.76}
+
76%|███████▌ | 9058/11952 [3:39:04<4:43:56, 5.89s/it]
76%|███████▌ | 9059/11952 [3:39:10<4:44:07, 5.89s/it]
{'loss': 0.4605, 'learning_rate': 2.9188793393360813e-06, 'epoch': 0.76}
+
76%|███████▌ | 9059/11952 [3:39:10<4:44:07, 5.89s/it]
76%|███████▌ | 9060/11952 [3:39:17<4:47:23, 5.96s/it]
{'loss': 0.4687, 'learning_rate': 2.916966135396372e-06, 'epoch': 0.76}
+
76%|███████▌ | 9060/11952 [3:39:17<4:47:23, 5.96s/it]
76%|███████▌ | 9061/11952 [3:39:22<4:42:27, 5.86s/it]
{'loss': 0.4748, 'learning_rate': 2.9150534516052085e-06, 'epoch': 0.76}
+
76%|███████▌ | 9061/11952 [3:39:22<4:42:27, 5.86s/it]
76%|███████▌ | 9062/11952 [3:39:28<4:42:34, 5.87s/it]
{'loss': 0.454, 'learning_rate': 2.9131412881030487e-06, 'epoch': 0.76}
+
76%|███████▌ | 9062/11952 [3:39:28<4:42:34, 5.87s/it]
76%|███████▌ | 9063/11952 [3:39:34<4:40:54, 5.83s/it]
{'loss': 0.4901, 'learning_rate': 2.911229645030319e-06, 'epoch': 0.76}
+
76%|███████▌ | 9063/11952 [3:39:34<4:40:54, 5.83s/it]
76%|███████▌ | 9064/11952 [3:39:40<4:39:38, 5.81s/it]
{'loss': 0.4588, 'learning_rate': 2.909318522527397e-06, 'epoch': 0.76}
+
76%|███████▌ | 9064/11952 [3:39:40<4:39:38, 5.81s/it]
76%|███████▌ | 9065/11952 [3:39:45<4:41:28, 5.85s/it]
{'loss': 0.4642, 'learning_rate': 2.9074079207346328e-06, 'epoch': 0.76}
+
76%|███████▌ | 9065/11952 [3:39:45<4:41:28, 5.85s/it]
76%|███████▌ | 9066/11952 [3:39:51<4:42:37, 5.88s/it]
{'loss': 0.4733, 'learning_rate': 2.9054978397923306e-06, 'epoch': 0.76}
+
76%|███████▌ | 9066/11952 [3:39:51<4:42:37, 5.88s/it]
76%|███████▌ | 9067/11952 [3:39:57<4:45:35, 5.94s/it]
{'loss': 0.4799, 'learning_rate': 2.903588279840759e-06, 'epoch': 0.76}
+
76%|███████▌ | 9067/11952 [3:39:57<4:45:35, 5.94s/it]
76%|███████▌ | 9068/11952 [3:40:04<4:47:34, 5.98s/it]
{'loss': 0.472, 'learning_rate': 2.901679241020149e-06, 'epoch': 0.76}
+
76%|███████▌ | 9068/11952 [3:40:04<4:47:34, 5.98s/it]
76%|███████▌ | 9069/11952 [3:40:09<4:42:30, 5.88s/it]
{'loss': 0.4813, 'learning_rate': 2.8997707234706894e-06, 'epoch': 0.76}
+
76%|███████▌ | 9069/11952 [3:40:09<4:42:30, 5.88s/it]
76%|███████▌ | 9070/11952 [3:40:15<4:40:56, 5.85s/it]
{'loss': 0.4612, 'learning_rate': 2.8978627273325378e-06, 'epoch': 0.76}
+
76%|███████▌ | 9070/11952 [3:40:15<4:40:56, 5.85s/it]
76%|███████▌ | 9071/11952 [3:40:21<4:37:23, 5.78s/it]
{'loss': 0.4695, 'learning_rate': 2.8959552527458025e-06, 'epoch': 0.76}
+
76%|███████▌ | 9071/11952 [3:40:21<4:37:23, 5.78s/it]
76%|███████▌ | 9072/11952 [3:40:27<4:42:56, 5.89s/it]
{'loss': 0.4619, 'learning_rate': 2.8940482998505703e-06, 'epoch': 0.76}
+
76%|███████▌ | 9072/11952 [3:40:27<4:42:56, 5.89s/it]
76%|███████▌ | 9073/11952 [3:40:32<4:39:45, 5.83s/it]
{'loss': 0.452, 'learning_rate': 2.892141868786871e-06, 'epoch': 0.76}
+
76%|███████▌ | 9073/11952 [3:40:32<4:39:45, 5.83s/it]
76%|███████▌ | 9074/11952 [3:40:38<4:37:32, 5.79s/it]
{'loss': 0.4722, 'learning_rate': 2.8902359596947127e-06, 'epoch': 0.76}
+
76%|███████▌ | 9074/11952 [3:40:38<4:37:32, 5.79s/it]
76%|███████▌ | 9075/11952 [3:40:44<4:38:36, 5.81s/it]
{'loss': 0.442, 'learning_rate': 2.8883305727140533e-06, 'epoch': 0.76}
+
76%|███████▌ | 9075/11952 [3:40:44<4:38:36, 5.81s/it]
76%|███████▌ | 9076/11952 [3:40:50<4:36:41, 5.77s/it]
{'loss': 0.4708, 'learning_rate': 2.8864257079848166e-06, 'epoch': 0.76}
+
76%|███████▌ | 9076/11952 [3:40:50<4:36:41, 5.77s/it]
76%|███████▌ | 9077/11952 [3:40:55<4:32:32, 5.69s/it]
{'loss': 0.4646, 'learning_rate': 2.8845213656468896e-06, 'epoch': 0.76}
+
76%|███████▌ | 9077/11952 [3:40:55<4:32:32, 5.69s/it]
76%|███████▌ | 9078/11952 [3:41:01<4:36:00, 5.76s/it]
{'loss': 0.4648, 'learning_rate': 2.882617545840114e-06, 'epoch': 0.76}
+
76%|███████▌ | 9078/11952 [3:41:01<4:36:00, 5.76s/it]
76%|███████▌ | 9079/11952 [3:41:07<4:40:42, 5.86s/it]
{'loss': 0.4804, 'learning_rate': 2.8807142487043047e-06, 'epoch': 0.76}
+
76%|███████▌ | 9079/11952 [3:41:07<4:40:42, 5.86s/it]
76%|███████▌ | 9080/11952 [3:41:13<4:37:40, 5.80s/it]
{'loss': 0.46, 'learning_rate': 2.8788114743792317e-06, 'epoch': 0.76}
+
76%|███████▌ | 9080/11952 [3:41:13<4:37:40, 5.80s/it]
76%|███████▌ | 9081/11952 [3:41:18<4:33:27, 5.71s/it]
{'loss': 0.455, 'learning_rate': 2.8769092230046236e-06, 'epoch': 0.76}
+
76%|███████▌ | 9081/11952 [3:41:18<4:33:27, 5.71s/it]
76%|███████▌ | 9082/11952 [3:41:24<4:36:55, 5.79s/it]
{'loss': 0.4514, 'learning_rate': 2.875007494720171e-06, 'epoch': 0.76}
+
76%|███████▌ | 9082/11952 [3:41:24<4:36:55, 5.79s/it]
76%|███████▌ | 9083/11952 [3:41:30<4:40:01, 5.86s/it]
{'loss': 0.4745, 'learning_rate': 2.8731062896655383e-06, 'epoch': 0.76}
+
76%|███████▌ | 9083/11952 [3:41:30<4:40:01, 5.86s/it]
76%|███████▌ | 9084/11952 [3:41:36<4:38:43, 5.83s/it]
{'loss': 0.4647, 'learning_rate': 2.871205607980335e-06, 'epoch': 0.76}
+
76%|███████▌ | 9084/11952 [3:41:36<4:38:43, 5.83s/it]
76%|███████▌ | 9085/11952 [3:41:42<4:37:51, 5.81s/it]
{'loss': 0.4675, 'learning_rate': 2.8693054498041383e-06, 'epoch': 0.76}
+
76%|███████▌ | 9085/11952 [3:41:42<4:37:51, 5.81s/it]
76%|███████▌ | 9086/11952 [3:41:48<4:34:48, 5.75s/it]
{'loss': 0.4572, 'learning_rate': 2.867405815276494e-06, 'epoch': 0.76}
+
76%|███████▌ | 9086/11952 [3:41:48<4:34:48, 5.75s/it]
76%|███████▌ | 9087/11952 [3:41:53<4:31:23, 5.68s/it]
{'loss': 0.4301, 'learning_rate': 2.865506704536899e-06, 'epoch': 0.76}
+
76%|███████▌ | 9087/11952 [3:41:53<4:31:23, 5.68s/it]
76%|███████▌ | 9088/11952 [3:41:59<4:29:16, 5.64s/it]
{'loss': 0.4656, 'learning_rate': 2.8636081177248176e-06, 'epoch': 0.76}
+
76%|███████▌ | 9088/11952 [3:41:59<4:29:16, 5.64s/it]
76%|███████▌ | 9089/11952 [3:42:04<4:32:57, 5.72s/it]
{'loss': 0.4682, 'learning_rate': 2.861710054979674e-06, 'epoch': 0.76}
+
76%|███████▌ | 9089/11952 [3:42:04<4:32:57, 5.72s/it]
76%|███████▌ | 9090/11952 [3:42:10<4:36:30, 5.80s/it]
{'loss': 0.4671, 'learning_rate': 2.859812516440853e-06, 'epoch': 0.76}
+
76%|███████▌ | 9090/11952 [3:42:10<4:36:30, 5.80s/it]
76%|███████▌ | 9091/11952 [3:42:16<4:33:56, 5.75s/it]
{'loss': 0.4713, 'learning_rate': 2.8579155022477024e-06, 'epoch': 0.76}
+
76%|███████▌ | 9091/11952 [3:42:16<4:33:56, 5.75s/it]
76%|███████▌ | 9092/11952 [3:42:22<4:38:01, 5.83s/it]
{'loss': 0.4732, 'learning_rate': 2.856019012539528e-06, 'epoch': 0.76}
+
76%|███████▌ | 9092/11952 [3:42:22<4:38:01, 5.83s/it]
76%|███████▌ | 9093/11952 [3:42:28<4:43:03, 5.94s/it]
{'loss': 0.4658, 'learning_rate': 2.8541230474556035e-06, 'epoch': 0.76}
+
76%|███████▌ | 9093/11952 [3:42:28<4:43:03, 5.94s/it]
76%|███████▌ | 9094/11952 [3:42:35<4:48:10, 6.05s/it]
{'loss': 0.4677, 'learning_rate': 2.852227607135164e-06, 'epoch': 0.76}
+
76%|███████▌ | 9094/11952 [3:42:35<4:48:10, 6.05s/it]
76%|███████▌ | 9095/11952 [3:42:40<4:43:45, 5.96s/it]
{'loss': 0.4676, 'learning_rate': 2.850332691717399e-06, 'epoch': 0.76}
+
76%|███████▌ | 9095/11952 [3:42:40<4:43:45, 5.96s/it]
76%|███████▌ | 9096/11952 [3:42:46<4:45:01, 5.99s/it]
{'loss': 0.4892, 'learning_rate': 2.8484383013414627e-06, 'epoch': 0.76}
+
76%|███████▌ | 9096/11952 [3:42:46<4:45:01, 5.99s/it]
76%|███████▌ | 9097/11952 [3:42:52<4:44:50, 5.99s/it]
{'loss': 0.4541, 'learning_rate': 2.846544436146473e-06, 'epoch': 0.76}
+
76%|███████▌ | 9097/11952 [3:42:52<4:44:50, 5.99s/it]
76%|███████▌ | 9098/11952 [3:42:58<4:39:09, 5.87s/it]
{'loss': 0.464, 'learning_rate': 2.8446510962715055e-06, 'epoch': 0.76}
+
76%|███████▌ | 9098/11952 [3:42:58<4:39:09, 5.87s/it]
76%|███████▌ | 9099/11952 [3:43:04<4:37:17, 5.83s/it]
{'loss': 0.4755, 'learning_rate': 2.8427582818555976e-06, 'epoch': 0.76}
+
76%|███████▌ | 9099/11952 [3:43:04<4:37:17, 5.83s/it]1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
76%|███████▌ | 9100/11952 [3:43:09<4:34:34, 5.78s/it]
{'loss': 0.4582, 'learning_rate': 2.8408659930377556e-06, 'epoch': 0.76}
+
76%|███████▌ | 9100/11952 [3:43:09<4:34:34, 5.78s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
76%|███████▌ | 9101/11952 [3:43:40<10:26:22, 13.18s/it]
{'loss': 0.4648, 'learning_rate': 2.838974229956938e-06, 'epoch': 0.76}
+
76%|███████▌ | 9101/11952 [3:43:40<10:26:22, 13.18s/it]
76%|███████▌ | 9102/11952 [3:43:46<8:41:02, 10.97s/it]
{'loss': 0.4542, 'learning_rate': 2.837082992752067e-06, 'epoch': 0.76}
+
76%|███████▌ | 9102/11952 [3:43:46<8:41:02, 10.97s/it]
76%|███████▌ | 9103/11952 [3:43:51<7:23:50, 9.35s/it]
{'loss': 0.4401, 'learning_rate': 2.835192281562027e-06, 'epoch': 0.76}
+
76%|███████▌ | 9103/11952 [3:43:51<7:23:50, 9.35s/it]
76%|███████▌ | 9104/11952 [3:43:57<6:34:21, 8.31s/it]
{'loss': 0.4844, 'learning_rate': 2.8333020965256666e-06, 'epoch': 0.76}
+
76%|███████▌ | 9104/11952 [3:43:57<6:34:21, 8.31s/it]
76%|███████▌ | 9105/11952 [3:44:04<6:07:27, 7.74s/it]
{'loss': 0.4815, 'learning_rate': 2.8314124377817888e-06, 'epoch': 0.76}
+
76%|███████▌ | 9105/11952 [3:44:04<6:07:27, 7.74s/it]
76%|███████▌ | 9106/11952 [3:44:10<5:42:30, 7.22s/it]
{'loss': 0.479, 'learning_rate': 2.8295233054691685e-06, 'epoch': 0.76}
+
76%|███████▌ | 9106/11952 [3:44:10<5:42:30, 7.22s/it]
76%|███████▌ | 9107/11952 [3:44:15<5:19:35, 6.74s/it]
{'loss': 0.4473, 'learning_rate': 2.8276346997265324e-06, 'epoch': 0.76}
+
76%|███████▌ | 9107/11952 [3:44:15<5:19:35, 6.74s/it]
76%|███████▌ | 9108/11952 [3:44:21<5:06:40, 6.47s/it]
{'loss': 0.4676, 'learning_rate': 2.8257466206925723e-06, 'epoch': 0.76}
+
76%|███████▌ | 9108/11952 [3:44:21<5:06:40, 6.47s/it]
76%|███████▌ | 9109/11952 [3:44:27<4:54:51, 6.22s/it]
{'loss': 0.4612, 'learning_rate': 2.82385906850594e-06, 'epoch': 0.76}
+
76%|███████▌ | 9109/11952 [3:44:27<4:54:51, 6.22s/it]
76%|███████▌ | 9110/11952 [3:44:32<4:47:52, 6.08s/it]
{'loss': 0.4752, 'learning_rate': 2.82197204330525e-06, 'epoch': 0.76}
+
76%|███████▌ | 9110/11952 [3:44:32<4:47:52, 6.08s/it]
76%|███████▌ | 9111/11952 [3:44:38<4:40:28, 5.92s/it]
{'loss': 0.4496, 'learning_rate': 2.820085545229078e-06, 'epoch': 0.76}
+
76%|███████▌ | 9111/11952 [3:44:38<4:40:28, 5.92s/it]
76%|███████▌ | 9112/11952 [3:44:44<4:36:13, 5.84s/it]
{'loss': 0.4537, 'learning_rate': 2.8181995744159553e-06, 'epoch': 0.76}
+
76%|███████▌ | 9112/11952 [3:44:44<4:36:13, 5.84s/it]
76%|███████▌ | 9113/11952 [3:44:49<4:34:50, 5.81s/it]
{'loss': 0.4666, 'learning_rate': 2.8163141310043886e-06, 'epoch': 0.76}
+
76%|███████▌ | 9113/11952 [3:44:49<4:34:50, 5.81s/it]
76%|███████▋ | 9114/11952 [3:44:55<4:32:44, 5.77s/it]
{'loss': 0.4734, 'learning_rate': 2.81442921513283e-06, 'epoch': 0.76}
+
76%|███████▋ | 9114/11952 [3:44:55<4:32:44, 5.77s/it]
76%|███████▋ | 9115/11952 [3:45:01<4:29:17, 5.70s/it]
{'loss': 0.4739, 'learning_rate': 2.812544826939706e-06, 'epoch': 0.76}
+
76%|███████▋ | 9115/11952 [3:45:01<4:29:17, 5.70s/it]
76%|███████▋ | 9116/11952 [3:45:06<4:30:16, 5.72s/it]
{'loss': 0.4542, 'learning_rate': 2.8106609665633943e-06, 'epoch': 0.76}
+
76%|███████▋ | 9116/11952 [3:45:06<4:30:16, 5.72s/it]
76%|███████▋ | 9117/11952 [3:45:12<4:34:31, 5.81s/it]
{'loss': 0.4808, 'learning_rate': 2.808777634142239e-06, 'epoch': 0.76}
+
76%|███████▋ | 9117/11952 [3:45:12<4:34:31, 5.81s/it]
76%|███████▋ | 9118/11952 [3:45:18<4:34:58, 5.82s/it]
{'loss': 0.4737, 'learning_rate': 2.8068948298145437e-06, 'epoch': 0.76}
+
76%|███████▋ | 9118/11952 [3:45:18<4:34:58, 5.82s/it]
76%|███████▋ | 9119/11952 [3:45:24<4:36:55, 5.87s/it]
{'loss': 0.453, 'learning_rate': 2.80501255371857e-06, 'epoch': 0.76}
+
76%|███████▋ | 9119/11952 [3:45:24<4:36:55, 5.87s/it]
76%|███████▋ | 9120/11952 [3:45:30<4:35:27, 5.84s/it]
{'loss': 0.4852, 'learning_rate': 2.803130805992552e-06, 'epoch': 0.76}
+
76%|███████▋ | 9120/11952 [3:45:30<4:35:27, 5.84s/it]
76%|███████▋ | 9121/11952 [3:45:35<4:31:45, 5.76s/it]
{'loss': 0.4509, 'learning_rate': 2.8012495867746735e-06, 'epoch': 0.76}
+
76%|███████▋ | 9121/11952 [3:45:35<4:31:45, 5.76s/it]
76%|███████▋ | 9122/11952 [3:45:41<4:32:06, 5.77s/it]
{'loss': 0.447, 'learning_rate': 2.799368896203084e-06, 'epoch': 0.76}
+
76%|███████▋ | 9122/11952 [3:45:41<4:32:06, 5.77s/it]
76%|███████▋ | 9123/11952 [3:45:47<4:26:49, 5.66s/it]
{'loss': 0.4753, 'learning_rate': 2.7974887344158897e-06, 'epoch': 0.76}
+
76%|███████▋ | 9123/11952 [3:45:47<4:26:49, 5.66s/it]
76%|███████▋ | 9124/11952 [3:45:53<4:29:40, 5.72s/it]
{'loss': 0.4621, 'learning_rate': 2.7956091015511676e-06, 'epoch': 0.76}
+
76%|███████▋ | 9124/11952 [3:45:53<4:29:40, 5.72s/it]
76%|███████▋ | 9125/11952 [3:45:58<4:30:50, 5.75s/it]
{'loss': 0.4722, 'learning_rate': 2.793729997746948e-06, 'epoch': 0.76}
+
76%|███████▋ | 9125/11952 [3:45:58<4:30:50, 5.75s/it]
76%|███████▋ | 9126/11952 [3:46:04<4:27:55, 5.69s/it]
{'loss': 0.4903, 'learning_rate': 2.791851423141222e-06, 'epoch': 0.76}
+
76%|███████▋ | 9126/11952 [3:46:04<4:27:55, 5.69s/it]
76%|███████▋ | 9127/11952 [3:46:10<4:28:12, 5.70s/it]
{'loss': 0.4797, 'learning_rate': 2.7899733778719483e-06, 'epoch': 0.76}
+
76%|███████▋ | 9127/11952 [3:46:10<4:28:12, 5.70s/it]
76%|███████▋ | 9128/11952 [3:46:15<4:28:39, 5.71s/it]
{'loss': 0.4619, 'learning_rate': 2.7880958620770415e-06, 'epoch': 0.76}
+
76%|███████▋ | 9128/11952 [3:46:15<4:28:39, 5.71s/it]
76%|███████▋ | 9129/11952 [3:46:21<4:28:44, 5.71s/it]
{'loss': 0.4626, 'learning_rate': 2.7862188758943788e-06, 'epoch': 0.76}
+
76%|███████▋ | 9129/11952 [3:46:21<4:28:44, 5.71s/it]
76%|███████▋ | 9130/11952 [3:46:27<4:30:04, 5.74s/it]
{'loss': 0.4839, 'learning_rate': 2.7843424194617964e-06, 'epoch': 0.76}
+
76%|███████▋ | 9130/11952 [3:46:27<4:30:04, 5.74s/it]
76%|███████▋ | 9131/11952 [3:46:33<4:33:59, 5.83s/it]
{'loss': 0.4832, 'learning_rate': 2.7824664929170953e-06, 'epoch': 0.76}
+
76%|███████▋ | 9131/11952 [3:46:33<4:33:59, 5.83s/it]
76%|███████▋ | 9132/11952 [3:46:39<4:37:06, 5.90s/it]
{'loss': 0.5038, 'learning_rate': 2.7805910963980343e-06, 'epoch': 0.76}
+
76%|███████▋ | 9132/11952 [3:46:39<4:37:06, 5.90s/it]
76%|███████▋ | 9133/11952 [3:46:45<4:44:29, 6.06s/it]
{'loss': 0.4822, 'learning_rate': 2.778716230042333e-06, 'epoch': 0.76}
+
76%|███████▋ | 9133/11952 [3:46:45<4:44:29, 6.06s/it]
76%|███████▋ | 9134/11952 [3:46:51<4:39:34, 5.95s/it]
{'loss': 0.4542, 'learning_rate': 2.7768418939876794e-06, 'epoch': 0.76}
+
76%|███████▋ | 9134/11952 [3:46:51<4:39:34, 5.95s/it]
76%|███████▋ | 9135/11952 [3:46:57<4:37:03, 5.90s/it]
{'loss': 0.4602, 'learning_rate': 2.7749680883717102e-06, 'epoch': 0.76}
+
76%|███████▋ | 9135/11952 [3:46:57<4:37:03, 5.90s/it]
76%|███████▋ | 9136/11952 [3:47:03<4:37:12, 5.91s/it]
{'loss': 0.4747, 'learning_rate': 2.773094813332037e-06, 'epoch': 0.76}
+
76%|███████▋ | 9136/11952 [3:47:03<4:37:12, 5.91s/it]
76%|███████▋ | 9137/11952 [3:47:09<4:37:03, 5.91s/it]
{'loss': 0.4595, 'learning_rate': 2.7712220690062208e-06, 'epoch': 0.76}
+
76%|███████▋ | 9137/11952 [3:47:09<4:37:03, 5.91s/it]
76%|███████▋ | 9138/11952 [3:47:15<4:35:40, 5.88s/it]
{'loss': 0.4627, 'learning_rate': 2.769349855531789e-06, 'epoch': 0.76}
+
76%|███████▋ | 9138/11952 [3:47:15<4:35:40, 5.88s/it]
76%|███████▋ | 9139/11952 [3:47:20<4:32:29, 5.81s/it]
{'loss': 0.4563, 'learning_rate': 2.7674781730462273e-06, 'epoch': 0.76}
+
76%|███████▋ | 9139/11952 [3:47:20<4:32:29, 5.81s/it]
76%|███████▋ | 9140/11952 [3:47:26<4:32:41, 5.82s/it]
{'loss': 0.4852, 'learning_rate': 2.765607021686989e-06, 'epoch': 0.76}
+
76%|███████▋ | 9140/11952 [3:47:26<4:32:41, 5.82s/it]
76%|███████▋ | 9141/11952 [3:47:32<4:35:26, 5.88s/it]
{'loss': 0.4463, 'learning_rate': 2.7637364015914803e-06, 'epoch': 0.76}
+
76%|███████▋ | 9141/11952 [3:47:32<4:35:26, 5.88s/it]
76%|███████▋ | 9142/11952 [3:47:38<4:33:24, 5.84s/it]
{'loss': 0.4673, 'learning_rate': 2.7618663128970722e-06, 'epoch': 0.76}
+
76%|███████▋ | 9142/11952 [3:47:38<4:33:24, 5.84s/it]
76%|███████▋ | 9143/11952 [3:47:44<4:35:39, 5.89s/it]
{'loss': 0.446, 'learning_rate': 2.759996755741098e-06, 'epoch': 0.76}
+
76%|███████▋ | 9143/11952 [3:47:44<4:35:39, 5.89s/it]
77%|███████▋ | 9144/11952 [3:47:50<4:35:49, 5.89s/it]
{'loss': 0.4693, 'learning_rate': 2.7581277302608446e-06, 'epoch': 0.77}
+
77%|███████▋ | 9144/11952 [3:47:50<4:35:49, 5.89s/it]
77%|███████▋ | 9145/11952 [3:47:56<4:36:59, 5.92s/it]
{'loss': 0.4751, 'learning_rate': 2.7562592365935724e-06, 'epoch': 0.77}
+
77%|███████▋ | 9145/11952 [3:47:56<4:36:59, 5.92s/it]
77%|███████▋ | 9146/11952 [3:48:02<4:36:46, 5.92s/it]
{'loss': 0.4539, 'learning_rate': 2.75439127487649e-06, 'epoch': 0.77}
+
77%|███████▋ | 9146/11952 [3:48:02<4:36:46, 5.92s/it]
77%|███████▋ | 9147/11952 [3:48:07<4:33:01, 5.84s/it]
{'loss': 0.4628, 'learning_rate': 2.7525238452467783e-06, 'epoch': 0.77}
+
77%|███████▋ | 9147/11952 [3:48:07<4:33:01, 5.84s/it]
77%|███████▋ | 9148/11952 [3:48:13<4:33:04, 5.84s/it]
{'loss': 0.4756, 'learning_rate': 2.7506569478415713e-06, 'epoch': 0.77}
+
77%|███████▋ | 9148/11952 [3:48:13<4:33:04, 5.84s/it]
77%|███████▋ | 9149/11952 [3:48:19<4:30:40, 5.79s/it]
{'loss': 0.4652, 'learning_rate': 2.7487905827979654e-06, 'epoch': 0.77}
+
77%|███████▋ | 9149/11952 [3:48:19<4:30:40, 5.79s/it]1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
77%|███████▋ | 9150/11952 [3:48:24<4:29:35, 5.77s/it]
{'loss': 0.4361, 'learning_rate': 2.7469247502530194e-06, 'epoch': 0.77}
+
77%|███████▋ | 9150/11952 [3:48:24<4:29:35, 5.77s/it]
77%|███████▋ | 9151/11952 [3:48:30<4:26:39, 5.71s/it]
{'loss': 0.4724, 'learning_rate': 2.745059450343752e-06, 'epoch': 0.77}
+
77%|███████▋ | 9151/11952 [3:48:30<4:26:39, 5.71s/it]
77%|███████▋ | 9152/11952 [3:48:36<4:29:19, 5.77s/it]
{'loss': 0.4707, 'learning_rate': 2.7431946832071433e-06, 'epoch': 0.77}
+
77%|███████▋ | 9152/11952 [3:48:36<4:29:19, 5.77s/it]
77%|███████▋ | 9153/11952 [3:48:42<4:32:43, 5.85s/it]
{'loss': 0.4704, 'learning_rate': 2.7413304489801296e-06, 'epoch': 0.77}
+
77%|███████▋ | 9153/11952 [3:48:42<4:32:43, 5.85s/it]
77%|███████▋ | 9154/11952 [3:48:48<4:31:21, 5.82s/it]
{'loss': 0.4542, 'learning_rate': 2.7394667477996207e-06, 'epoch': 0.77}
+
77%|███████▋ | 9154/11952 [3:48:48<4:31:21, 5.82s/it]
77%|███████▋ | 9155/11952 [3:48:53<4:28:31, 5.76s/it]
{'loss': 0.4505, 'learning_rate': 2.737603579802471e-06, 'epoch': 0.77}
+
77%|███████▋ | 9155/11952 [3:48:53<4:28:31, 5.76s/it]
77%|███████▋ | 9156/11952 [3:48:59<4:29:12, 5.78s/it]
{'loss': 0.458, 'learning_rate': 2.7357409451255113e-06, 'epoch': 0.77}
+
77%|███████▋ | 9156/11952 [3:48:59<4:29:12, 5.78s/it]
77%|███████▋ | 9157/11952 [3:49:05<4:32:30, 5.85s/it]
{'loss': 0.4673, 'learning_rate': 2.733878843905523e-06, 'epoch': 0.77}
+
77%|███████▋ | 9157/11952 [3:49:05<4:32:30, 5.85s/it]
77%|███████▋ | 9158/11952 [3:49:11<4:34:23, 5.89s/it]
{'loss': 0.4914, 'learning_rate': 2.7320172762792497e-06, 'epoch': 0.77}
+
77%|███████▋ | 9158/11952 [3:49:11<4:34:23, 5.89s/it]
77%|███████▋ | 9159/11952 [3:49:17<4:30:03, 5.80s/it]
{'loss': 0.4658, 'learning_rate': 2.7301562423833985e-06, 'epoch': 0.77}
+
77%|███████▋ | 9159/11952 [3:49:17<4:30:03, 5.80s/it]
77%|███████▋ | 9160/11952 [3:49:22<4:28:04, 5.76s/it]
{'loss': 0.449, 'learning_rate': 2.728295742354631e-06, 'epoch': 0.77}
+
77%|███████▋ | 9160/11952 [3:49:22<4:28:04, 5.76s/it]
77%|███████▋ | 9161/11952 [3:49:28<4:30:18, 5.81s/it]
{'loss': 0.4757, 'learning_rate': 2.7264357763295822e-06, 'epoch': 0.77}
+
77%|███████▋ | 9161/11952 [3:49:28<4:30:18, 5.81s/it]
77%|███████▋ | 9162/11952 [3:49:34<4:29:26, 5.79s/it]
{'loss': 0.4689, 'learning_rate': 2.7245763444448383e-06, 'epoch': 0.77}
+
77%|███████▋ | 9162/11952 [3:49:34<4:29:26, 5.79s/it]
77%|███████▋ | 9163/11952 [3:49:40<4:31:03, 5.83s/it]
{'loss': 0.4551, 'learning_rate': 2.7227174468369454e-06, 'epoch': 0.77}
+
77%|███████▋ | 9163/11952 [3:49:40<4:31:03, 5.83s/it]
77%|███████▋ | 9164/11952 [3:49:46<4:35:13, 5.92s/it]
{'loss': 0.4712, 'learning_rate': 2.720859083642415e-06, 'epoch': 0.77}
+
77%|███████▋ | 9164/11952 [3:49:46<4:35:13, 5.92s/it]
77%|███████▋ | 9165/11952 [3:49:52<4:36:58, 5.96s/it]
{'loss': 0.4821, 'learning_rate': 2.7190012549977153e-06, 'epoch': 0.77}
+
77%|███████▋ | 9165/11952 [3:49:52<4:36:58, 5.96s/it]
77%|███████▋ | 9166/11952 [3:49:58<4:37:02, 5.97s/it]
{'loss': 0.4558, 'learning_rate': 2.7171439610392815e-06, 'epoch': 0.77}
+
77%|███████▋ | 9166/11952 [3:49:58<4:37:02, 5.97s/it]
77%|███████▋ | 9167/11952 [3:50:04<4:36:25, 5.96s/it]
{'loss': 0.4696, 'learning_rate': 2.7152872019035005e-06, 'epoch': 0.77}
+
77%|███████▋ | 9167/11952 [3:50:04<4:36:25, 5.96s/it]
77%|███████▋ | 9168/11952 [3:50:10<4:31:26, 5.85s/it]
{'loss': 0.4633, 'learning_rate': 2.7134309777267307e-06, 'epoch': 0.77}
+
77%|███████▋ | 9168/11952 [3:50:10<4:31:26, 5.85s/it]
77%|███████▋ | 9169/11952 [3:50:16<4:32:59, 5.89s/it]
{'loss': 0.4628, 'learning_rate': 2.711575288645284e-06, 'epoch': 0.77}
+
77%|███████▋ | 9169/11952 [3:50:16<4:32:59, 5.89s/it]
77%|███████▋ | 9170/11952 [3:50:21<4:31:06, 5.85s/it]
{'loss': 0.466, 'learning_rate': 2.7097201347954318e-06, 'epoch': 0.77}
+
77%|███████▋ | 9170/11952 [3:50:21<4:31:06, 5.85s/it]
77%|███████▋ | 9171/11952 [3:50:27<4:30:45, 5.84s/it]
{'loss': 0.4747, 'learning_rate': 2.7078655163134117e-06, 'epoch': 0.77}
+
77%|███████▋ | 9171/11952 [3:50:27<4:30:45, 5.84s/it]
77%|███████▋ | 9172/11952 [3:50:33<4:28:21, 5.79s/it]
{'loss': 0.4617, 'learning_rate': 2.706011433335417e-06, 'epoch': 0.77}
+
77%|███████▋ | 9172/11952 [3:50:33<4:28:21, 5.79s/it]
77%|███████▋ | 9173/11952 [3:50:39<4:30:33, 5.84s/it]
{'loss': 0.4672, 'learning_rate': 2.704157885997605e-06, 'epoch': 0.77}
+
77%|███████▋ | 9173/11952 [3:50:39<4:30:33, 5.84s/it]
77%|███████▋ | 9174/11952 [3:50:45<4:32:08, 5.88s/it]
{'loss': 0.453, 'learning_rate': 2.702304874436089e-06, 'epoch': 0.77}
+
77%|███████▋ | 9174/11952 [3:50:45<4:32:08, 5.88s/it]
77%|███████▋ | 9175/11952 [3:50:51<4:29:30, 5.82s/it]
{'loss': 0.4688, 'learning_rate': 2.7004523987869526e-06, 'epoch': 0.77}
+
77%|███████▋ | 9175/11952 [3:50:51<4:29:30, 5.82s/it]
77%|███████▋ | 9176/11952 [3:50:57<4:30:43, 5.85s/it]
{'loss': 0.4595, 'learning_rate': 2.698600459186228e-06, 'epoch': 0.77}
+
77%|███████▋ | 9176/11952 [3:50:57<4:30:43, 5.85s/it]
77%|███████▋ | 9177/11952 [3:51:02<4:27:00, 5.77s/it]
{'loss': 0.4421, 'learning_rate': 2.6967490557699196e-06, 'epoch': 0.77}
+
77%|███████▋ | 9177/11952 [3:51:02<4:27:00, 5.77s/it]
77%|███████▋ | 9178/11952 [3:51:08<4:27:11, 5.78s/it]
{'loss': 0.4677, 'learning_rate': 2.6948981886739846e-06, 'epoch': 0.77}
+
77%|███████▋ | 9178/11952 [3:51:08<4:27:11, 5.78s/it]
77%|███████▋ | 9179/11952 [3:51:14<4:34:14, 5.93s/it]
{'loss': 0.4797, 'learning_rate': 2.693047858034342e-06, 'epoch': 0.77}
+
77%|███████▋ | 9179/11952 [3:51:14<4:34:14, 5.93s/it]
77%|███████▋ | 9180/11952 [3:51:20<4:30:00, 5.84s/it]
{'loss': 0.4518, 'learning_rate': 2.6911980639868696e-06, 'epoch': 0.77}
+
77%|███████▋ | 9180/11952 [3:51:20<4:30:00, 5.84s/it]
77%|███████▋ | 9181/11952 [3:51:26<4:31:30, 5.88s/it]
{'loss': 0.4681, 'learning_rate': 2.6893488066674154e-06, 'epoch': 0.77}
+
77%|███████▋ | 9181/11952 [3:51:26<4:31:30, 5.88s/it]
77%|███████▋ | 9182/11952 [3:51:31<4:29:01, 5.83s/it]
{'loss': 0.4684, 'learning_rate': 2.687500086211777e-06, 'epoch': 0.77}
+
77%|███████▋ | 9182/11952 [3:51:31<4:29:01, 5.83s/it]
77%|███████▋ | 9183/11952 [3:51:37<4:25:55, 5.76s/it]
{'loss': 0.465, 'learning_rate': 2.685651902755717e-06, 'epoch': 0.77}
+
77%|███████▋ | 9183/11952 [3:51:37<4:25:55, 5.76s/it]
77%|███████▋ | 9184/11952 [3:51:43<4:25:47, 5.76s/it]
{'loss': 0.4633, 'learning_rate': 2.6838042564349597e-06, 'epoch': 0.77}
+
77%|███████▋ | 9184/11952 [3:51:43<4:25:47, 5.76s/it]
77%|███████▋ | 9185/11952 [3:51:49<4:26:37, 5.78s/it]
{'loss': 0.4565, 'learning_rate': 2.6819571473851836e-06, 'epoch': 0.77}
+
77%|███████▋ | 9185/11952 [3:51:49<4:26:37, 5.78s/it]
77%|███████▋ | 9186/11952 [3:51:55<4:28:40, 5.83s/it]
{'loss': 0.4577, 'learning_rate': 2.6801105757420397e-06, 'epoch': 0.77}
+
77%|███████▋ | 9186/11952 [3:51:55<4:28:40, 5.83s/it]
77%|███████▋ | 9187/11952 [3:52:01<4:33:43, 5.94s/it]
{'loss': 0.4726, 'learning_rate': 2.6782645416411267e-06, 'epoch': 0.77}
+
77%|███████▋ | 9187/11952 [3:52:01<4:33:43, 5.94s/it]
77%|███████▋ | 9188/11952 [3:52:07<4:32:38, 5.92s/it]
{'loss': 0.4555, 'learning_rate': 2.676419045218016e-06, 'epoch': 0.77}
+
77%|███████▋ | 9188/11952 [3:52:07<4:32:38, 5.92s/it]
77%|███████▋ | 9189/11952 [3:52:13<4:35:35, 5.98s/it]
{'loss': 0.4847, 'learning_rate': 2.674574086608228e-06, 'epoch': 0.77}
+
77%|███████▋ | 9189/11952 [3:52:13<4:35:35, 5.98s/it]
77%|███████▋ | 9190/11952 [3:52:19<4:37:45, 6.03s/it]
{'loss': 0.4464, 'learning_rate': 2.672729665947251e-06, 'epoch': 0.77}
+
77%|███████▋ | 9190/11952 [3:52:19<4:37:45, 6.03s/it]
77%|███████▋ | 9191/11952 [3:52:25<4:32:28, 5.92s/it]
{'loss': 0.4601, 'learning_rate': 2.6708857833705315e-06, 'epoch': 0.77}
+
77%|███████▋ | 9191/11952 [3:52:25<4:32:28, 5.92s/it]
77%|███████▋ | 9192/11952 [3:52:30<4:30:59, 5.89s/it]
{'loss': 0.4795, 'learning_rate': 2.669042439013476e-06, 'epoch': 0.77}
+
77%|███████▋ | 9192/11952 [3:52:30<4:30:59, 5.89s/it]
77%|███████▋ | 9193/11952 [3:52:36<4:26:51, 5.80s/it]
{'loss': 0.4571, 'learning_rate': 2.6671996330114514e-06, 'epoch': 0.77}
+
77%|███████▋ | 9193/11952 [3:52:36<4:26:51, 5.80s/it]
77%|███████▋ | 9194/11952 [3:52:42<4:27:48, 5.83s/it]
{'loss': 0.4686, 'learning_rate': 2.6653573654997835e-06, 'epoch': 0.77}
+
77%|███████▋ | 9194/11952 [3:52:42<4:27:48, 5.83s/it]
77%|███████▋ | 9195/11952 [3:52:48<4:24:08, 5.75s/it]
{'loss': 0.4599, 'learning_rate': 2.6635156366137672e-06, 'epoch': 0.77}
+
77%|███████▋ | 9195/11952 [3:52:48<4:24:08, 5.75s/it]
77%|███████▋ | 9196/11952 [3:52:54<4:27:39, 5.83s/it]
{'loss': 0.4802, 'learning_rate': 2.6616744464886437e-06, 'epoch': 0.77}
+
77%|███████▋ | 9196/11952 [3:52:54<4:27:39, 5.83s/it]
77%|███████▋ | 9197/11952 [3:52:59<4:29:02, 5.86s/it]
{'loss': 0.4669, 'learning_rate': 2.65983379525963e-06, 'epoch': 0.77}
+
77%|███████▋ | 9197/11952 [3:52:59<4:29:02, 5.86s/it]
77%|███████▋ | 9198/11952 [3:53:05<4:25:08, 5.78s/it]
{'loss': 0.4458, 'learning_rate': 2.6579936830618926e-06, 'epoch': 0.77}
+
77%|███████▋ | 9198/11952 [3:53:05<4:25:08, 5.78s/it]
77%|███████▋ | 9199/11952 [3:53:11<4:25:29, 5.79s/it]
{'loss': 0.466, 'learning_rate': 2.656154110030561e-06, 'epoch': 0.77}
+
77%|███████▋ | 9199/11952 [3:53:11<4:25:29, 5.79s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+
77%|███████▋ | 9200/11952 [3:53:17<4:27:18, 5.83s/it]
{'loss': 0.4608, 'learning_rate': 2.6543150763007265e-06, 'epoch': 0.77}
+
77%|███████▋ | 9200/11952 [3:53:17<4:27:18, 5.83s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
77%|███████▋ | 9201/11952 [3:53:47<10:05:01, 13.20s/it]
{'loss': 0.4676, 'learning_rate': 2.652476582007436e-06, 'epoch': 0.77}
+
77%|███████▋ | 9201/11952 [3:53:47<10:05:01, 13.20s/it]
77%|███████▋ | 9202/11952 [3:53:53<8:25:32, 11.03s/it]
{'loss': 0.4695, 'learning_rate': 2.6506386272857086e-06, 'epoch': 0.77}
+
77%|███████▋ | 9202/11952 [3:53:53<8:25:32, 11.03s/it]
77%|███████▋ | 9203/11952 [3:53:59<7:13:14, 9.46s/it]
{'loss': 0.463, 'learning_rate': 2.648801212270512e-06, 'epoch': 0.77}
+
77%|███████▋ | 9203/11952 [3:53:59<7:13:14, 9.46s/it]
77%|███████▋ | 9204/11952 [3:54:05<6:23:54, 8.38s/it]
{'loss': 0.4483, 'learning_rate': 2.646964337096778e-06, 'epoch': 0.77}
+
77%|███████▋ | 9204/11952 [3:54:05<6:23:54, 8.38s/it]
77%|███████▋ | 9205/11952 [3:54:10<5:46:25, 7.57s/it]
{'loss': 0.4567, 'learning_rate': 2.6451280018993996e-06, 'epoch': 0.77}
+
77%|███████▋ | 9205/11952 [3:54:10<5:46:25, 7.57s/it]
77%|███████▋ | 9206/11952 [3:54:16<5:20:50, 7.01s/it]
{'loss': 0.4826, 'learning_rate': 2.643292206813227e-06, 'epoch': 0.77}
+
77%|███████▋ | 9206/11952 [3:54:16<5:20:50, 7.01s/it]
77%|███████▋ | 9207/11952 [3:54:22<5:02:26, 6.61s/it]
{'loss': 0.4526, 'learning_rate': 2.6414569519730793e-06, 'epoch': 0.77}
+
77%|███████▋ | 9207/11952 [3:54:22<5:02:26, 6.61s/it]
77%|███████▋ | 9208/11952 [3:54:28<4:52:00, 6.38s/it]
{'loss': 0.4555, 'learning_rate': 2.6396222375137227e-06, 'epoch': 0.77}
+
77%|███████▋ | 9208/11952 [3:54:28<4:52:00, 6.38s/it]
77%|███████▋ | 9209/11952 [3:54:33<4:43:25, 6.20s/it]
{'loss': 0.4822, 'learning_rate': 2.6377880635698973e-06, 'epoch': 0.77}
+
77%|███████▋ | 9209/11952 [3:54:33<4:43:25, 6.20s/it]Jun 11 00:43:04.327229 457664 slurmstepd 0x155550ab8700: error: *** STEP 8837928.0 ON batch-block1-0069 CANCELLED AT 2025-06-11T00:43:04 DUE TO TIME LIMIT ***
+srun: Job step aborted: Waiting up to 122 seconds for job step to finish.
+srun: error: batch-block1-0069: task 0: Terminated
+srun: Terminating StepId=8837928.0
+srun: job 8846993 queued and waiting for resources
+srun: job 8846993 has been allocated resources
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+MASTER_ADDR=batch-block1-0082
+JobID: 8846993 | Full list: batch-block1-0082
+NETWORK=Efficient-Large-Model/VILA1.5-3b
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
+*****************************************
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+[2025-06-11 00:45:39,727] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:39,727] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:39,727] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:39,741] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:39,741] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:39,741] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:39,741] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:39,741] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 00:45:40,918] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 00:45:40,918] [INFO] [comm.py:625:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+[2025-06-11 00:45:40,918] [INFO] [comm.py:594:init_distributed] cdb=None
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+[2025-06-11 00:45:50,002] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 2.70B parameters
+
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.57s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.57s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.58s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.59s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.60s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.61s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:05<00:05, 5.62s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.50s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.96s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.50s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.96s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.97s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.97s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.97s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.52s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.98s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.52s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.99s/it]
+
Loading checkpoint shards: 50%|█████ | 1/2 [00:07<00:07, 7.66s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:08<00:00, 3.58s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:08<00:00, 4.20s/it]
+[2025-06-11 00:45:58,777] [WARNING] [partition_parameters.py:836:_post_init_method] param `probe` in SiglipMultiheadAttentionPoolingHead not on GPU so was not broadcasted from rank 0
+[2025-06-11 00:45:58,778] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.13B parameters
+[2025-06-11 00:46:00,365] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.15B parameters
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[dist-0-of-8] LlavaLlamaModel(
+ (llm): LlamaForCausalLM(
+ (model): LlamaModel(
+ (embed_tokens): Embedding(32000, 2560, padding_idx=0)
+ (layers): ModuleList(
+ (0-31): 32 x LlamaDecoderLayer(
+ (self_attn): LlamaFlashAttention2(
+ (q_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (k_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (v_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (o_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (rotary_emb): LlamaRotaryEmbedding()
+ )
+ (mlp): LlamaMLP(
+ (gate_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (up_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (down_proj): Linear(in_features=6912, out_features=2560, bias=False)
+ (act_fn): SiLU()
+ )
+ (input_layernorm): LlamaRMSNorm()
+ (post_attention_layernorm): LlamaRMSNorm()
+ )
+ )
+ (norm): LlamaRMSNorm()
+ )
+ (lm_head): Linear(in_features=2560, out_features=32000, bias=False)
+ )
+ (vision_tower): SiglipVisionTower(
+ (vision_tower): SiglipVisionModel(
+ (vision_model): SiglipVisionTransformer(
+ (embeddings): SiglipVisionEmbeddings(
+ (patch_embedding): Conv2d(3, 1152, kernel_size=(14, 14), stride=(14, 14), padding=valid)
+ (position_embedding): Embedding(729, 1152)
+ )
+ (encoder): SiglipEncoder(
+ (layers): ModuleList(
+ (0-26): 27 x SiglipEncoderLayer(
+ (self_attn): SiglipAttention(
+ (k_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (v_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (q_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (out_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layer_norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ (layer_norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ )
+ )
+ )
+ (post_layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (head): SiglipMultiheadAttentionPoolingHead(
+ (attention): MultiheadAttention(
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ )
+ )
+ )
+ )
+ (mm_projector): MultimodalProjector(
+ (layers): Sequential(
+ (0): DownSampleBlock()
+ (1): LayerNorm((4608,), eps=1e-05, elementwise_affine=True)
+ (2): Linear(in_features=4608, out_features=2560, bias=True)
+ (3): GELU(approximate='none')
+ (4): Linear(in_features=2560, out_features=2560, bias=True)
+ )
+ )
+)
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[dist-0-of-8] Tunable parameters:
+language model True
+[dist-0-of-8] vision tower True
+[dist-0-of-8] mm projector True
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8297052383422852
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8338541984558105
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8286662101745605
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8251566886901855
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8346171379089355
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8409953117370605
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8248209953308105
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8342814445495605
+Parameter Offload: Total persistent parameters: 593856 in 349 params
+wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.18.7
+wandb: Run data is saved locally in /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/wandb/run-20250611_004724-puxfn2f9
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run vila_3b_path_mask
+wandb: ⭐️ View project at https://wandb.ai/memmelma/VILA
+wandb: 🚀 View run at https://wandb.ai/memmelma/VILA/runs/puxfn2f9
+
0%| | 0/11952 [00:00, ?it/s]Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+
77%|███████▋ | 9201/11952 [00:24<00:07, 383.00it/s]
{'loss': 0.4676, 'learning_rate': 2.652476582007436e-06, 'epoch': 0.77}
+
77%|███████▋ | 9201/11952 [00:24<00:07, 383.00it/s]
{'loss': 0.4696, 'learning_rate': 2.6506386272857086e-06, 'epoch': 0.77}
+
77%|███████▋ | 9202/11952 [00:30<00:07, 383.00it/s]
{'loss': 0.463, 'learning_rate': 2.648801212270512e-06, 'epoch': 0.77}
+
77%|███████▋ | 9203/11952 [00:35<00:07, 383.00it/s]
77%|███████▋ | 9203/11952 [00:39<00:07, 383.00it/s]
77%|███████▋ | 9204/11952 [00:41<00:14, 186.90it/s]
{'loss': 0.4484, 'learning_rate': 2.646964337096778e-06, 'epoch': 0.77}
+
77%|███████▋ | 9204/11952 [00:41<00:14, 186.90it/s]
77%|███████▋ | 9205/11952 [00:47<00:18, 151.45it/s]
{'loss': 0.4569, 'learning_rate': 2.6451280018993996e-06, 'epoch': 0.77}
+
77%|███████▋ | 9205/11952 [00:47<00:18, 151.45it/s]
77%|███████▋ | 9206/11952 [00:53<00:23, 118.92it/s]
{'loss': 0.4825, 'learning_rate': 2.643292206813227e-06, 'epoch': 0.77}
+
77%|███████▋ | 9206/11952 [00:53<00:23, 118.92it/s]
77%|███████▋ | 9207/11952 [00:58<00:30, 90.92it/s]
{'loss': 0.4526, 'learning_rate': 2.6414569519730793e-06, 'epoch': 0.77}
+
77%|███████▋ | 9207/11952 [00:58<00:30, 90.92it/s]
77%|███████▋ | 9208/11952 [01:04<00:40, 67.60it/s]
{'loss': 0.4555, 'learning_rate': 2.6396222375137227e-06, 'epoch': 0.77}
+
77%|███████▋ | 9208/11952 [01:04<00:40, 67.60it/s]
77%|███████▋ | 9209/11952 [01:10<00:55, 49.63it/s]
{'loss': 0.4824, 'learning_rate': 2.6377880635698973e-06, 'epoch': 0.77}
+
77%|███████▋ | 9209/11952 [01:10<00:55, 49.63it/s]
77%|███████▋ | 9210/11952 [01:16<01:16, 35.97it/s]
{'loss': 0.4683, 'learning_rate': 2.635954430276296e-06, 'epoch': 0.77}
+
77%|███████▋ | 9210/11952 [01:16<01:16, 35.97it/s]
77%|███████▋ | 9211/11952 [01:22<01:47, 25.49it/s]
{'loss': 0.4648, 'learning_rate': 2.634121337767571e-06, 'epoch': 0.77}
+
77%|███████▋ | 9211/11952 [01:22<01:47, 25.49it/s]
77%|███████▋ | 9212/11952 [01:28<02:28, 18.43it/s]
{'loss': 0.4767, 'learning_rate': 2.6322887861783385e-06, 'epoch': 0.77}
+
77%|███████▋ | 9212/11952 [01:28<02:28, 18.43it/s]
77%|███████▋ | 9213/11952 [01:33<03:27, 13.22it/s]
{'loss': 0.4557, 'learning_rate': 2.630456775643173e-06, 'epoch': 0.77}
+
77%|███████▋ | 9213/11952 [01:33<03:27, 13.22it/s]
77%|███████▋ | 9214/11952 [01:39<04:53, 9.34it/s]
{'loss': 0.4721, 'learning_rate': 2.6286253062966096e-06, 'epoch': 0.77}
+
77%|███████▋ | 9214/11952 [01:39<04:53, 9.34it/s]
77%|███████▋ | 9215/11952 [01:46<07:02, 6.47it/s]
{'loss': 0.4695, 'learning_rate': 2.6267943782731407e-06, 'epoch': 0.77}
+
77%|███████▋ | 9215/11952 [01:46<07:02, 6.47it/s]
77%|███████▋ | 9216/11952 [01:51<09:50, 4.63it/s]
{'loss': 0.4559, 'learning_rate': 2.624963991707228e-06, 'epoch': 0.77}
+
77%|███████▋ | 9216/11952 [01:51<09:50, 4.63it/s]
77%|███████▋ | 9217/11952 [01:57<13:45, 3.31it/s]
{'loss': 0.477, 'learning_rate': 2.6231341467332827e-06, 'epoch': 0.77}
+
77%|███████▋ | 9217/11952 [01:57<13:45, 3.31it/s]
77%|███████▋ | 9218/11952 [02:03<19:26, 2.34it/s]
{'loss': 0.4626, 'learning_rate': 2.6213048434856846e-06, 'epoch': 0.77}
+
77%|███████▋ | 9218/11952 [02:03<19:26, 2.34it/s]
77%|███████▋ | 9219/11952 [02:10<27:07, 1.68it/s]
{'loss': 0.4592, 'learning_rate': 2.61947608209877e-06, 'epoch': 0.77}
+
77%|███████▋ | 9219/11952 [02:10<27:07, 1.68it/s]
77%|███████▋ | 9220/11952 [02:15<36:38, 1.24it/s]
{'loss': 0.5004, 'learning_rate': 2.6176478627068324e-06, 'epoch': 0.77}
+
77%|███████▋ | 9220/11952 [02:15<36:38, 1.24it/s]
77%|███████▋ | 9221/11952 [02:21<49:05, 1.08s/it]
{'loss': 0.488, 'learning_rate': 2.615820185444128e-06, 'epoch': 0.77}
+
77%|███████▋ | 9221/11952 [02:21<49:05, 1.08s/it]
77%|███████▋ | 9222/11952 [02:27<1:04:34, 1.42s/it]
{'loss': 0.4704, 'learning_rate': 2.6139930504448785e-06, 'epoch': 0.77}
+
77%|███████▋ | 9222/11952 [02:27<1:04:34, 1.42s/it]
77%|███████▋ | 9223/11952 [02:33<1:24:20, 1.85s/it]
{'loss': 0.4755, 'learning_rate': 2.6121664578432593e-06, 'epoch': 0.77}
+
77%|███████▋ | 9223/11952 [02:33<1:24:20, 1.85s/it]
77%|███████▋ | 9224/11952 [02:39<1:44:53, 2.31s/it]
{'loss': 0.4581, 'learning_rate': 2.6103404077734075e-06, 'epoch': 0.77}
+
77%|███████▋ | 9224/11952 [02:39<1:44:53, 2.31s/it]
77%|███████▋ | 9225/11952 [02:45<2:08:45, 2.83s/it]
{'loss': 0.4553, 'learning_rate': 2.60851490036942e-06, 'epoch': 0.77}
+
77%|███████▋ | 9225/11952 [02:45<2:08:45, 2.83s/it]
77%|███████▋ | 9226/11952 [02:51<2:34:48, 3.41s/it]
{'loss': 0.4777, 'learning_rate': 2.606689935765351e-06, 'epoch': 0.77}
+
77%|███████▋ | 9226/11952 [02:51<2:34:48, 3.41s/it]
77%|███████▋ | 9227/11952 [02:57<2:57:40, 3.91s/it]
{'loss': 0.4676, 'learning_rate': 2.604865514095225e-06, 'epoch': 0.77}
+
77%|███████▋ | 9227/11952 [02:57<2:57:40, 3.91s/it]
77%|███████▋ | 9228/11952 [03:02<3:14:45, 4.29s/it]
{'loss': 0.4463, 'learning_rate': 2.6030416354930154e-06, 'epoch': 0.77}
+
77%|███████▋ | 9228/11952 [03:02<3:14:45, 4.29s/it]
77%|███████▋ | 9229/11952 [03:08<3:31:27, 4.66s/it]
{'loss': 0.4546, 'learning_rate': 2.6012183000926638e-06, 'epoch': 0.77}
+
77%|███████▋ | 9229/11952 [03:08<3:31:27, 4.66s/it]
77%|███████▋ | 9230/11952 [03:15<3:49:43, 5.06s/it]
{'loss': 0.483, 'learning_rate': 2.5993955080280663e-06, 'epoch': 0.77}
+
77%|███████▋ | 9230/11952 [03:15<3:49:43, 5.06s/it]
77%|███████▋ | 9231/11952 [03:20<3:56:31, 5.22s/it]
{'loss': 0.4715, 'learning_rate': 2.5975732594330816e-06, 'epoch': 0.77}
+
77%|███████▋ | 9231/11952 [03:20<3:56:31, 5.22s/it]
77%|███████▋ | 9232/11952 [03:26<4:02:49, 5.36s/it]
{'loss': 0.4556, 'learning_rate': 2.595751554441527e-06, 'epoch': 0.77}
+
77%|███████▋ | 9232/11952 [03:26<4:02:49, 5.36s/it]
77%|███████▋ | 9233/11952 [03:32<4:14:12, 5.61s/it]
{'loss': 0.4788, 'learning_rate': 2.5939303931871827e-06, 'epoch': 0.77}
+
77%|███████▋ | 9233/11952 [03:32<4:14:12, 5.61s/it]
77%|███████▋ | 9234/11952 [03:38<4:15:18, 5.64s/it]
{'loss': 0.4724, 'learning_rate': 2.592109775803785e-06, 'epoch': 0.77}
+
77%|███████▋ | 9234/11952 [03:38<4:15:18, 5.64s/it]
77%|███████▋ | 9235/11952 [03:44<4:17:00, 5.68s/it]
{'loss': 0.4611, 'learning_rate': 2.590289702425032e-06, 'epoch': 0.77}
+
77%|███████▋ | 9235/11952 [03:44<4:17:00, 5.68s/it]
77%|███████▋ | 9236/11952 [03:50<4:23:07, 5.81s/it]
{'loss': 0.4714, 'learning_rate': 2.5884701731845862e-06, 'epoch': 0.77}
+
77%|███████▋ | 9236/11952 [03:50<4:23:07, 5.81s/it]
77%|███████▋ | 9237/11952 [03:56<4:22:13, 5.80s/it]
{'loss': 0.4642, 'learning_rate': 2.5866511882160604e-06, 'epoch': 0.77}
+
77%|███████▋ | 9237/11952 [03:56<4:22:13, 5.80s/it]
77%|███████▋ | 9238/11952 [04:02<4:26:59, 5.90s/it]
{'loss': 0.4718, 'learning_rate': 2.584832747653041e-06, 'epoch': 0.77}
+
77%|███████▋ | 9238/11952 [04:02<4:26:59, 5.90s/it]
77%|███████▋ | 9239/11952 [04:07<4:25:07, 5.86s/it]
{'loss': 0.4696, 'learning_rate': 2.583014851629062e-06, 'epoch': 0.77}
+
77%|███████▋ | 9239/11952 [04:07<4:25:07, 5.86s/it]
77%|███████▋ | 9240/11952 [04:13<4:23:04, 5.82s/it]
{'loss': 0.4488, 'learning_rate': 2.5811975002776233e-06, 'epoch': 0.77}
+
77%|███████▋ | 9240/11952 [04:13<4:23:04, 5.82s/it]
77%|███████▋ | 9241/11952 [04:19<4:26:26, 5.90s/it]
{'loss': 0.4678, 'learning_rate': 2.579380693732183e-06, 'epoch': 0.77}
+
77%|███████▋ | 9241/11952 [04:19<4:26:26, 5.90s/it]
77%|███████▋ | 9242/11952 [04:25<4:24:15, 5.85s/it]
{'loss': 0.4598, 'learning_rate': 2.577564432126156e-06, 'epoch': 0.77}
+
77%|███████▋ | 9242/11952 [04:25<4:24:15, 5.85s/it]
77%|███████▋ | 9243/11952 [04:31<4:29:39, 5.97s/it]
{'loss': 0.482, 'learning_rate': 2.5757487155929285e-06, 'epoch': 0.77}
+
77%|███████▋ | 9243/11952 [04:31<4:29:39, 5.97s/it]
77%|███████▋ | 9244/11952 [04:37<4:27:18, 5.92s/it]
{'loss': 0.4572, 'learning_rate': 2.573933544265835e-06, 'epoch': 0.77}
+
77%|███████▋ | 9244/11952 [04:37<4:27:18, 5.92s/it]
77%|███████▋ | 9245/11952 [04:43<4:25:32, 5.89s/it]
{'loss': 0.4634, 'learning_rate': 2.572118918278176e-06, 'epoch': 0.77}
+
77%|███████▋ | 9245/11952 [04:43<4:25:32, 5.89s/it]
77%|███████▋ | 9246/11952 [04:49<4:27:14, 5.93s/it]
{'loss': 0.4784, 'learning_rate': 2.570304837763208e-06, 'epoch': 0.77}
+
77%|███████▋ | 9246/11952 [04:49<4:27:14, 5.93s/it]
77%|███████▋ | 9247/11952 [04:55<4:32:40, 6.05s/it]
{'loss': 0.458, 'learning_rate': 2.568491302854147e-06, 'epoch': 0.77}
+
77%|███████▋ | 9247/11952 [04:55<4:32:40, 6.05s/it]
77%|███████▋ | 9248/11952 [05:01<4:27:25, 5.93s/it]
{'loss': 0.4777, 'learning_rate': 2.5666783136841777e-06, 'epoch': 0.77}
+
77%|███████▋ | 9248/11952 [05:01<4:27:25, 5.93s/it]
77%|███████▋ | 9249/11952 [05:07<4:23:53, 5.86s/it]
{'loss': 0.4558, 'learning_rate': 2.564865870386433e-06, 'epoch': 0.77}
+
77%|███████▋ | 9249/11952 [05:07<4:23:53, 5.86s/it]5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+46 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+3 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
77%|███████▋ | 9250/11952 [05:12<4:22:07, 5.82s/it]
{'loss': 0.4666, 'learning_rate': 2.5630539730940163e-06, 'epoch': 0.77}
+
77%|███████▋ | 9250/11952 [05:12<4:22:07, 5.82s/it]
77%|███████▋ | 9251/11952 [05:18<4:19:23, 5.76s/it]
{'loss': 0.4487, 'learning_rate': 2.5612426219399834e-06, 'epoch': 0.77}
+
77%|███████▋ | 9251/11952 [05:18<4:19:23, 5.76s/it]
77%|███████▋ | 9252/11952 [05:23<4:16:40, 5.70s/it]
{'loss': 0.4581, 'learning_rate': 2.5594318170573527e-06, 'epoch': 0.77}
+
77%|███████▋ | 9252/11952 [05:23<4:16:40, 5.70s/it]
77%|███████▋ | 9253/11952 [05:29<4:19:38, 5.77s/it]
{'loss': 0.4659, 'learning_rate': 2.5576215585791007e-06, 'epoch': 0.77}
+
77%|███████▋ | 9253/11952 [05:29<4:19:38, 5.77s/it]
77%|███████▋ | 9254/11952 [05:35<4:21:06, 5.81s/it]
{'loss': 0.4502, 'learning_rate': 2.5558118466381675e-06, 'epoch': 0.77}
+
77%|███████▋ | 9254/11952 [05:35<4:21:06, 5.81s/it]
77%|███████▋ | 9255/11952 [05:41<4:21:50, 5.83s/it]
{'loss': 0.4941, 'learning_rate': 2.5540026813674458e-06, 'epoch': 0.77}
+
77%|███████▋ | 9255/11952 [05:41<4:21:50, 5.83s/it]
77%|███████▋ | 9256/11952 [05:47<4:27:04, 5.94s/it]
{'loss': 0.4728, 'learning_rate': 2.5521940628998e-06, 'epoch': 0.77}
+
77%|███████▋ | 9256/11952 [05:47<4:27:04, 5.94s/it]
77%|███████▋ | 9257/11952 [05:53<4:25:06, 5.90s/it]
{'loss': 0.4579, 'learning_rate': 2.550385991368044e-06, 'epoch': 0.77}
+
77%|███████▋ | 9257/11952 [05:53<4:25:06, 5.90s/it]
77%|███████▋ | 9258/11952 [05:59<4:23:25, 5.87s/it]
{'loss': 0.4819, 'learning_rate': 2.548578466904953e-06, 'epoch': 0.77}
+
77%|███████▋ | 9258/11952 [05:59<4:23:25, 5.87s/it]
77%|███████▋ | 9259/11952 [06:05<4:24:29, 5.89s/it]
{'loss': 0.4623, 'learning_rate': 2.5467714896432704e-06, 'epoch': 0.77}
+
77%|███████▋ | 9259/11952 [06:05<4:24:29, 5.89s/it]
77%|███████▋ | 9260/11952 [06:11<4:24:34, 5.90s/it]
{'loss': 0.4512, 'learning_rate': 2.5449650597156884e-06, 'epoch': 0.77}
+
77%|███████▋ | 9260/11952 [06:11<4:24:34, 5.90s/it]
77%|███████▋ | 9261/11952 [06:17<4:25:36, 5.92s/it]
{'loss': 0.469, 'learning_rate': 2.5431591772548647e-06, 'epoch': 0.77}
+
77%|███████▋ | 9261/11952 [06:17<4:25:36, 5.92s/it]
77%|███████▋ | 9262/11952 [06:23<4:26:15, 5.94s/it]
{'loss': 0.4628, 'learning_rate': 2.5413538423934125e-06, 'epoch': 0.77}
+
77%|███████▋ | 9262/11952 [06:23<4:26:15, 5.94s/it]
78%|███████▊ | 9263/11952 [06:28<4:22:35, 5.86s/it]
{'loss': 0.4641, 'learning_rate': 2.5395490552639145e-06, 'epoch': 0.77}
+
78%|███████▊ | 9263/11952 [06:28<4:22:35, 5.86s/it]
78%|███████▊ | 9264/11952 [06:35<4:27:14, 5.97s/it]
{'loss': 0.458, 'learning_rate': 2.5377448159989037e-06, 'epoch': 0.78}
+
78%|███████▊ | 9264/11952 [06:35<4:27:14, 5.97s/it]
78%|███████▊ | 9265/11952 [06:41<4:28:15, 5.99s/it]
{'loss': 0.4823, 'learning_rate': 2.5359411247308753e-06, 'epoch': 0.78}
+
78%|███████▊ | 9265/11952 [06:41<4:28:15, 5.99s/it]
78%|███████▊ | 9266/11952 [06:47<4:30:47, 6.05s/it]
{'loss': 0.467, 'learning_rate': 2.5341379815922853e-06, 'epoch': 0.78}
+
78%|███████▊ | 9266/11952 [06:47<4:30:47, 6.05s/it]
78%|███████▊ | 9267/11952 [06:53<4:27:28, 5.98s/it]
{'loss': 0.4686, 'learning_rate': 2.5323353867155465e-06, 'epoch': 0.78}
+
78%|███████▊ | 9267/11952 [06:53<4:27:28, 5.98s/it]
78%|███████▊ | 9268/11952 [06:59<4:28:03, 5.99s/it]
{'loss': 0.4559, 'learning_rate': 2.53053334023304e-06, 'epoch': 0.78}
+
78%|███████▊ | 9268/11952 [06:59<4:28:03, 5.99s/it]
78%|███████▊ | 9269/11952 [07:05<4:27:27, 5.98s/it]
{'loss': 0.4608, 'learning_rate': 2.5287318422770934e-06, 'epoch': 0.78}
+
78%|███████▊ | 9269/11952 [07:05<4:27:27, 5.98s/it]
78%|███████▊ | 9270/11952 [07:11<4:25:33, 5.94s/it]
{'loss': 0.4619, 'learning_rate': 2.5269308929800084e-06, 'epoch': 0.78}
+
78%|███████▊ | 9270/11952 [07:11<4:25:33, 5.94s/it]
78%|███████▊ | 9271/11952 [07:16<4:24:06, 5.91s/it]
{'loss': 0.4805, 'learning_rate': 2.525130492474035e-06, 'epoch': 0.78}
+
78%|███████▊ | 9271/11952 [07:16<4:24:06, 5.91s/it]
78%|███████▊ | 9272/11952 [07:22<4:23:50, 5.91s/it]
{'loss': 0.4584, 'learning_rate': 2.523330640891388e-06, 'epoch': 0.78}
+
78%|███████▊ | 9272/11952 [07:22<4:23:50, 5.91s/it]
78%|███████▊ | 9273/11952 [07:28<4:26:14, 5.96s/it]
{'loss': 0.4771, 'learning_rate': 2.5215313383642414e-06, 'epoch': 0.78}
+
78%|███████▊ | 9273/11952 [07:28<4:26:14, 5.96s/it]
78%|███████▊ | 9274/11952 [07:34<4:26:48, 5.98s/it]
{'loss': 0.4555, 'learning_rate': 2.519732585024729e-06, 'epoch': 0.78}
+
78%|███████▊ | 9274/11952 [07:34<4:26:48, 5.98s/it]
78%|███████▊ | 9275/11952 [07:40<4:26:59, 5.98s/it]
{'loss': 0.466, 'learning_rate': 2.5179343810049418e-06, 'epoch': 0.78}
+
78%|███████▊ | 9275/11952 [07:40<4:26:59, 5.98s/it]
78%|███████▊ | 9276/11952 [07:46<4:24:50, 5.94s/it]
{'loss': 0.4694, 'learning_rate': 2.5161367264369296e-06, 'epoch': 0.78}
+
78%|███████▊ | 9276/11952 [07:46<4:24:50, 5.94s/it]
78%|███████▊ | 9277/11952 [07:52<4:26:19, 5.97s/it]
{'loss': 0.4603, 'learning_rate': 2.5143396214527127e-06, 'epoch': 0.78}
+
78%|███████▊ | 9277/11952 [07:52<4:26:19, 5.97s/it]
78%|███████▊ | 9278/11952 [07:58<4:28:38, 6.03s/it]
{'loss': 0.4644, 'learning_rate': 2.5125430661842587e-06, 'epoch': 0.78}
+
78%|███████▊ | 9278/11952 [07:58<4:28:38, 6.03s/it]
78%|███████▊ | 9279/11952 [08:04<4:25:24, 5.96s/it]
{'loss': 0.4647, 'learning_rate': 2.5107470607634956e-06, 'epoch': 0.78}
+
78%|███████▊ | 9279/11952 [08:04<4:25:24, 5.96s/it]
78%|███████▊ | 9280/11952 [08:10<4:26:21, 5.98s/it]
{'loss': 0.4704, 'learning_rate': 2.5089516053223216e-06, 'epoch': 0.78}
+
78%|███████▊ | 9280/11952 [08:10<4:26:21, 5.98s/it]
78%|███████▊ | 9281/11952 [08:16<4:24:13, 5.94s/it]
{'loss': 0.4869, 'learning_rate': 2.5071566999925833e-06, 'epoch': 0.78}
+
78%|███████▊ | 9281/11952 [08:16<4:24:13, 5.94s/it]
78%|███████▊ | 9282/11952 [08:22<4:24:24, 5.94s/it]
{'loss': 0.4826, 'learning_rate': 2.5053623449060927e-06, 'epoch': 0.78}
+
78%|███████▊ | 9282/11952 [08:22<4:24:24, 5.94s/it]
78%|███████▊ | 9283/11952 [08:28<4:24:00, 5.93s/it]
{'loss': 0.4694, 'learning_rate': 2.5035685401946163e-06, 'epoch': 0.78}
+
78%|███████▊ | 9283/11952 [08:28<4:24:00, 5.93s/it]
78%|███████▊ | 9284/11952 [08:34<4:21:31, 5.88s/it]
{'loss': 0.4598, 'learning_rate': 2.5017752859898892e-06, 'epoch': 0.78}
+
78%|███████▊ | 9284/11952 [08:34<4:21:31, 5.88s/it]
78%|███████▊ | 9285/11952 [08:39<4:19:18, 5.83s/it]
{'loss': 0.4522, 'learning_rate': 2.499982582423597e-06, 'epoch': 0.78}
+
78%|███████▊ | 9285/11952 [08:39<4:19:18, 5.83s/it]
78%|███████▊ | 9286/11952 [08:45<4:19:57, 5.85s/it]
{'loss': 0.4609, 'learning_rate': 2.4981904296273884e-06, 'epoch': 0.78}
+
78%|███████▊ | 9286/11952 [08:45<4:19:57, 5.85s/it]
78%|███████▊ | 9287/11952 [08:52<4:25:24, 5.98s/it]
{'loss': 0.4702, 'learning_rate': 2.4963988277328733e-06, 'epoch': 0.78}
+
78%|███████▊ | 9287/11952 [08:52<4:25:24, 5.98s/it]
78%|███████▊ | 9288/11952 [08:58<4:29:22, 6.07s/it]
{'loss': 0.4667, 'learning_rate': 2.494607776871616e-06, 'epoch': 0.78}
+
78%|███████▊ | 9288/11952 [08:58<4:29:22, 6.07s/it]
78%|███████▊ | 9289/11952 [09:04<4:35:34, 6.21s/it]
{'loss': 0.4737, 'learning_rate': 2.492817277175148e-06, 'epoch': 0.78}
+
78%|███████▊ | 9289/11952 [09:04<4:35:34, 6.21s/it]
78%|███████▊ | 9290/11952 [09:10<4:30:37, 6.10s/it]
{'loss': 0.4664, 'learning_rate': 2.491027328774952e-06, 'epoch': 0.78}
+
78%|███████▊ | 9290/11952 [09:10<4:30:37, 6.10s/it]
78%|███████▊ | 9291/11952 [09:16<4:24:41, 5.97s/it]
{'loss': 0.4345, 'learning_rate': 2.4892379318024806e-06, 'epoch': 0.78}
+
78%|███████▊ | 9291/11952 [09:16<4:24:41, 5.97s/it]
78%|███████▊ | 9292/11952 [09:22<4:23:52, 5.95s/it]
{'loss': 0.4877, 'learning_rate': 2.4874490863891355e-06, 'epoch': 0.78}
+
78%|███████▊ | 9292/11952 [09:22<4:23:52, 5.95s/it]
78%|███████▊ | 9293/11952 [09:28<4:20:28, 5.88s/it]
{'loss': 0.4726, 'learning_rate': 2.485660792666281e-06, 'epoch': 0.78}
+
78%|███████▊ | 9293/11952 [09:28<4:20:28, 5.88s/it]
78%|███████▊ | 9294/11952 [09:33<4:18:02, 5.82s/it]
{'loss': 0.4508, 'learning_rate': 2.4838730507652455e-06, 'epoch': 0.78}
+
78%|███████▊ | 9294/11952 [09:33<4:18:02, 5.82s/it]
78%|███████▊ | 9295/11952 [09:39<4:15:05, 5.76s/it]
{'loss': 0.4623, 'learning_rate': 2.482085860817309e-06, 'epoch': 0.78}
+
78%|███████▊ | 9295/11952 [09:39<4:15:05, 5.76s/it]
78%|███████▊ | 9296/11952 [09:45<4:13:57, 5.74s/it]
{'loss': 0.4561, 'learning_rate': 2.480299222953716e-06, 'epoch': 0.78}
+
78%|███████▊ | 9296/11952 [09:45<4:13:57, 5.74s/it]
78%|███████▊ | 9297/11952 [09:51<4:18:11, 5.83s/it]
{'loss': 0.4565, 'learning_rate': 2.478513137305675e-06, 'epoch': 0.78}
+
78%|███████▊ | 9297/11952 [09:51<4:18:11, 5.83s/it]
78%|███████▊ | 9298/11952 [09:56<4:17:26, 5.82s/it]
{'loss': 0.4553, 'learning_rate': 2.4767276040043433e-06, 'epoch': 0.78}
+
78%|███████▊ | 9298/11952 [09:56<4:17:26, 5.82s/it]
78%|███████▊ | 9299/11952 [10:02<4:18:30, 5.85s/it]
{'loss': 0.4781, 'learning_rate': 2.4749426231808427e-06, 'epoch': 0.78}
+
78%|███████▊ | 9299/11952 [10:02<4:18:30, 5.85s/it]35 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
78%|███████▊ | 9300/11952 [10:08<4:19:17, 5.87s/it]
{'loss': 0.4629, 'learning_rate': 2.4731581949662597e-06, 'epoch': 0.78}
+
78%|███████▊ | 9300/11952 [10:08<4:19:17, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
78%|███████▊ | 9301/11952 [10:41<10:12:03, 13.85s/it]
{'loss': 0.4546, 'learning_rate': 2.4713743194916318e-06, 'epoch': 0.78}
+
78%|███████▊ | 9301/11952 [10:41<10:12:03, 13.85s/it]
78%|███████▊ | 9302/11952 [10:47<8:29:17, 11.53s/it]
{'loss': 0.466, 'learning_rate': 2.4695909968879607e-06, 'epoch': 0.78}
+
78%|███████▊ | 9302/11952 [10:47<8:29:17, 11.53s/it]
78%|███████▊ | 9303/11952 [10:53<7:12:48, 9.80s/it]
{'loss': 0.4552, 'learning_rate': 2.4678082272862025e-06, 'epoch': 0.78}
+
78%|███████▊ | 9303/11952 [10:53<7:12:48, 9.80s/it]
78%|███████▊ | 9304/11952 [10:58<6:20:00, 8.61s/it]
{'loss': 0.4513, 'learning_rate': 2.4660260108172816e-06, 'epoch': 0.78}
+
78%|███████▊ | 9304/11952 [10:58<6:20:00, 8.61s/it]
78%|███████▊ | 9305/11952 [11:04<5:40:25, 7.72s/it]
{'loss': 0.4539, 'learning_rate': 2.4642443476120746e-06, 'epoch': 0.78}
+
78%|███████▊ | 9305/11952 [11:04<5:40:25, 7.72s/it]
78%|███████▊ | 9306/11952 [11:10<5:18:20, 7.22s/it]
{'loss': 0.4682, 'learning_rate': 2.462463237801419e-06, 'epoch': 0.78}
+
78%|███████▊ | 9306/11952 [11:10<5:18:20, 7.22s/it]
78%|███████▊ | 9307/11952 [11:16<4:57:56, 6.76s/it]
{'loss': 0.453, 'learning_rate': 2.460682681516112e-06, 'epoch': 0.78}
+
78%|███████▊ | 9307/11952 [11:16<4:57:56, 6.76s/it]
78%|███████▊ | 9308/11952 [11:22<4:46:11, 6.49s/it]
{'loss': 0.4768, 'learning_rate': 2.4589026788869117e-06, 'epoch': 0.78}
+
78%|███████▊ | 9308/11952 [11:22<4:46:11, 6.49s/it]
78%|███████▊ | 9309/11952 [11:28<4:38:33, 6.32s/it]
{'loss': 0.4839, 'learning_rate': 2.4571232300445293e-06, 'epoch': 0.78}
+
78%|███████▊ | 9309/11952 [11:28<4:38:33, 6.32s/it]
78%|███████▊ | 9310/11952 [11:34<4:33:48, 6.22s/it]
{'loss': 0.4596, 'learning_rate': 2.4553443351196426e-06, 'epoch': 0.78}
+
78%|███████▊ | 9310/11952 [11:34<4:33:48, 6.22s/it]
78%|███████▊ | 9311/11952 [11:39<4:26:37, 6.06s/it]
{'loss': 0.4595, 'learning_rate': 2.453565994242891e-06, 'epoch': 0.78}
+
78%|███████▊ | 9311/11952 [11:39<4:26:37, 6.06s/it]
78%|███████▊ | 9312/11952 [11:45<4:23:01, 5.98s/it]
{'loss': 0.4475, 'learning_rate': 2.4517882075448663e-06, 'epoch': 0.78}
+
78%|███████▊ | 9312/11952 [11:45<4:23:01, 5.98s/it]
78%|███████▊ | 9313/11952 [11:51<4:25:07, 6.03s/it]
{'loss': 0.4539, 'learning_rate': 2.4500109751561187e-06, 'epoch': 0.78}
+
78%|███████▊ | 9313/11952 [11:51<4:25:07, 6.03s/it]
78%|███████▊ | 9314/11952 [11:57<4:21:51, 5.96s/it]
{'loss': 0.4622, 'learning_rate': 2.4482342972071626e-06, 'epoch': 0.78}
+
78%|███████▊ | 9314/11952 [11:57<4:21:51, 5.96s/it]
78%|███████▊ | 9315/11952 [12:03<4:21:05, 5.94s/it]
{'loss': 0.4861, 'learning_rate': 2.44645817382847e-06, 'epoch': 0.78}
+
78%|███████▊ | 9315/11952 [12:03<4:21:05, 5.94s/it]
78%|███████▊ | 9316/11952 [12:09<4:19:44, 5.91s/it]
{'loss': 0.4707, 'learning_rate': 2.444682605150471e-06, 'epoch': 0.78}
+
78%|███████▊ | 9316/11952 [12:09<4:19:44, 5.91s/it]
78%|███████▊ | 9317/11952 [12:15<4:20:59, 5.94s/it]
{'loss': 0.479, 'learning_rate': 2.442907591303554e-06, 'epoch': 0.78}
+
78%|███████▊ | 9317/11952 [12:15<4:20:59, 5.94s/it]
78%|███████▊ | 9318/11952 [12:20<4:18:22, 5.89s/it]
{'loss': 0.4697, 'learning_rate': 2.441133132418073e-06, 'epoch': 0.78}
+
78%|███████▊ | 9318/11952 [12:20<4:18:22, 5.89s/it]
78%|███████▊ | 9319/11952 [12:26<4:17:36, 5.87s/it]
{'loss': 0.4657, 'learning_rate': 2.4393592286243363e-06, 'epoch': 0.78}
+
78%|███████▊ | 9319/11952 [12:26<4:17:36, 5.87s/it]
78%|███████▊ | 9320/11952 [12:33<4:21:56, 5.97s/it]
{'loss': 0.4666, 'learning_rate': 2.4375858800526077e-06, 'epoch': 0.78}
+
78%|███████▊ | 9320/11952 [12:33<4:21:56, 5.97s/it]
78%|███████▊ | 9321/11952 [12:38<4:19:14, 5.91s/it]
{'loss': 0.4637, 'learning_rate': 2.43581308683312e-06, 'epoch': 0.78}
+
78%|███████▊ | 9321/11952 [12:38<4:19:14, 5.91s/it]
78%|███████▊ | 9322/11952 [12:44<4:22:22, 5.99s/it]
{'loss': 0.4706, 'learning_rate': 2.4340408490960575e-06, 'epoch': 0.78}
+
78%|███████▊ | 9322/11952 [12:44<4:22:22, 5.99s/it]
78%|███████▊ | 9323/11952 [12:50<4:18:05, 5.89s/it]
{'loss': 0.4753, 'learning_rate': 2.432269166971567e-06, 'epoch': 0.78}
+
78%|███████▊ | 9323/11952 [12:50<4:18:05, 5.89s/it]
78%|███████▊ | 9324/11952 [12:56<4:16:29, 5.86s/it]
{'loss': 0.4751, 'learning_rate': 2.4304980405897483e-06, 'epoch': 0.78}
+
78%|███████▊ | 9324/11952 [12:56<4:16:29, 5.86s/it]
78%|███████▊ | 9325/11952 [13:02<4:16:02, 5.85s/it]
{'loss': 0.4541, 'learning_rate': 2.4287274700806727e-06, 'epoch': 0.78}
+
78%|███████▊ | 9325/11952 [13:02<4:16:02, 5.85s/it]
78%|███████▊ | 9326/11952 [13:07<4:12:38, 5.77s/it]
{'loss': 0.4487, 'learning_rate': 2.42695745557436e-06, 'epoch': 0.78}
+
78%|███████▊ | 9326/11952 [13:07<4:12:38, 5.77s/it]
78%|███████▊ | 9327/11952 [13:13<4:12:10, 5.76s/it]
{'loss': 0.4575, 'learning_rate': 2.4251879972007943e-06, 'epoch': 0.78}
+
78%|███████▊ | 9327/11952 [13:13<4:12:10, 5.76s/it]
78%|███████▊ | 9328/11952 [13:19<4:15:35, 5.84s/it]
{'loss': 0.4677, 'learning_rate': 2.423419095089915e-06, 'epoch': 0.78}
+
78%|███████▊ | 9328/11952 [13:19<4:15:35, 5.84s/it]
78%|███████▊ | 9329/11952 [13:25<4:17:28, 5.89s/it]
{'loss': 0.4627, 'learning_rate': 2.4216507493716213e-06, 'epoch': 0.78}
+
78%|███████▊ | 9329/11952 [13:25<4:17:28, 5.89s/it]
78%|███████▊ | 9330/11952 [13:31<4:15:50, 5.85s/it]
{'loss': 0.4684, 'learning_rate': 2.4198829601757787e-06, 'epoch': 0.78}
+
78%|███████▊ | 9330/11952 [13:31<4:15:50, 5.85s/it]
78%|███████▊ | 9331/11952 [13:37<4:15:20, 5.85s/it]
{'loss': 0.4892, 'learning_rate': 2.418115727632201e-06, 'epoch': 0.78}
+
78%|███████▊ | 9331/11952 [13:37<4:15:20, 5.85s/it]
78%|███████▊ | 9332/11952 [13:43<4:15:34, 5.85s/it]
{'loss': 0.4636, 'learning_rate': 2.4163490518706713e-06, 'epoch': 0.78}
+
78%|███████▊ | 9332/11952 [13:43<4:15:34, 5.85s/it]
78%|███████▊ | 9333/11952 [13:48<4:13:37, 5.81s/it]
{'loss': 0.459, 'learning_rate': 2.414582933020924e-06, 'epoch': 0.78}
+
78%|███████▊ | 9333/11952 [13:48<4:13:37, 5.81s/it]
78%|███████▊ | 9334/11952 [13:54<4:12:14, 5.78s/it]
{'loss': 0.4632, 'learning_rate': 2.412817371212657e-06, 'epoch': 0.78}
+
78%|███████▊ | 9334/11952 [13:54<4:12:14, 5.78s/it]
78%|███████▊ | 9335/11952 [14:00<4:11:03, 5.76s/it]
{'loss': 0.4559, 'learning_rate': 2.4110523665755236e-06, 'epoch': 0.78}
+
78%|███████▊ | 9335/11952 [14:00<4:11:03, 5.76s/it]
78%|███████▊ | 9336/11952 [14:05<4:10:18, 5.74s/it]
{'loss': 0.4697, 'learning_rate': 2.4092879192391406e-06, 'epoch': 0.78}
+
78%|███████▊ | 9336/11952 [14:05<4:10:18, 5.74s/it]
78%|███████▊ | 9337/11952 [14:11<4:09:42, 5.73s/it]
{'loss': 0.4719, 'learning_rate': 2.407524029333077e-06, 'epoch': 0.78}
+
78%|███████▊ | 9337/11952 [14:11<4:09:42, 5.73s/it]
78%|███████▊ | 9338/11952 [14:17<4:10:01, 5.74s/it]
{'loss': 0.4609, 'learning_rate': 2.405760696986873e-06, 'epoch': 0.78}
+
78%|███████▊ | 9338/11952 [14:17<4:10:01, 5.74s/it]
78%|███████▊ | 9339/11952 [14:22<4:06:42, 5.67s/it]
{'loss': 0.4663, 'learning_rate': 2.403997922330016e-06, 'epoch': 0.78}
+
78%|███████▊ | 9339/11952 [14:22<4:06:42, 5.67s/it]
78%|███████▊ | 9340/11952 [14:28<4:07:36, 5.69s/it]
{'loss': 0.4537, 'learning_rate': 2.4022357054919545e-06, 'epoch': 0.78}
+
78%|███████▊ | 9340/11952 [14:28<4:07:36, 5.69s/it]
78%|███████▊ | 9341/11952 [14:34<4:06:57, 5.68s/it]
{'loss': 0.4711, 'learning_rate': 2.4004740466021047e-06, 'epoch': 0.78}
+
78%|███████▊ | 9341/11952 [14:34<4:06:57, 5.68s/it]
78%|███████▊ | 9342/11952 [14:40<4:12:53, 5.81s/it]
{'loss': 0.4591, 'learning_rate': 2.398712945789832e-06, 'epoch': 0.78}
+
78%|███████▊ | 9342/11952 [14:40<4:12:53, 5.81s/it]
78%|███████▊ | 9343/11952 [14:46<4:14:36, 5.86s/it]
{'loss': 0.4759, 'learning_rate': 2.3969524031844638e-06, 'epoch': 0.78}
+
78%|███████▊ | 9343/11952 [14:46<4:14:36, 5.86s/it]
78%|███████▊ | 9344/11952 [14:51<4:11:36, 5.79s/it]
{'loss': 0.4557, 'learning_rate': 2.3951924189152854e-06, 'epoch': 0.78}
+
78%|███████▊ | 9344/11952 [14:51<4:11:36, 5.79s/it]
78%|███████▊ | 9345/11952 [14:58<4:16:55, 5.91s/it]
{'loss': 0.4759, 'learning_rate': 2.3934329931115474e-06, 'epoch': 0.78}
+
78%|███████▊ | 9345/11952 [14:58<4:16:55, 5.91s/it]
78%|███████▊ | 9346/11952 [15:03<4:12:07, 5.80s/it]
{'loss': 0.4565, 'learning_rate': 2.391674125902452e-06, 'epoch': 0.78}
+
78%|███████▊ | 9346/11952 [15:03<4:12:07, 5.80s/it]
78%|███████▊ | 9347/11952 [15:09<4:12:13, 5.81s/it]
{'loss': 0.4823, 'learning_rate': 2.3899158174171644e-06, 'epoch': 0.78}
+
78%|███████▊ | 9347/11952 [15:09<4:12:13, 5.81s/it]
78%|███████▊ | 9348/11952 [15:15<4:12:50, 5.83s/it]
{'loss': 0.4724, 'learning_rate': 2.388158067784806e-06, 'epoch': 0.78}
+
78%|███████▊ | 9348/11952 [15:15<4:12:50, 5.83s/it]
78%|███████▊ | 9349/11952 [15:21<4:12:23, 5.82s/it]
{'loss': 0.4682, 'learning_rate': 2.3864008771344595e-06, 'epoch': 0.78}
+
78%|███████▊ | 9349/11952 [15:21<4:12:23, 5.82s/it]4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
78%|███████▊ | 9350/11952 [15:27<4:14:20, 5.87s/it]
{'loss': 0.4776, 'learning_rate': 2.3846442455951612e-06, 'epoch': 0.78}
+
78%|███████▊ | 9350/11952 [15:27<4:14:20, 5.87s/it]
78%|███████▊ | 9351/11952 [15:33<4:19:19, 5.98s/it]
{'loss': 0.4587, 'learning_rate': 2.3828881732959163e-06, 'epoch': 0.78}
+
78%|███████▊ | 9351/11952 [15:33<4:19:19, 5.98s/it]
78%|███████▊ | 9352/11952 [15:39<4:19:05, 5.98s/it]
{'loss': 0.4814, 'learning_rate': 2.381132660365684e-06, 'epoch': 0.78}
+
78%|███████▊ | 9352/11952 [15:39<4:19:05, 5.98s/it]
78%|███████▊ | 9353/11952 [15:45<4:20:16, 6.01s/it]
{'loss': 0.4737, 'learning_rate': 2.37937770693338e-06, 'epoch': 0.78}
+
78%|███████▊ | 9353/11952 [15:45<4:20:16, 6.01s/it]
78%|███████▊ | 9354/11952 [15:51<4:17:34, 5.95s/it]
{'loss': 0.447, 'learning_rate': 2.3776233131278805e-06, 'epoch': 0.78}
+
78%|███████▊ | 9354/11952 [15:51<4:17:34, 5.95s/it]
78%|███████▊ | 9355/11952 [15:56<4:11:51, 5.82s/it]
{'loss': 0.4658, 'learning_rate': 2.3758694790780214e-06, 'epoch': 0.78}
+
78%|███████▊ | 9355/11952 [15:56<4:11:51, 5.82s/it]
78%|███████▊ | 9356/11952 [16:02<4:13:48, 5.87s/it]
{'loss': 0.4719, 'learning_rate': 2.3741162049125964e-06, 'epoch': 0.78}
+
78%|███████▊ | 9356/11952 [16:02<4:13:48, 5.87s/it]
78%|███████▊ | 9357/11952 [16:08<4:14:36, 5.89s/it]
{'loss': 0.4448, 'learning_rate': 2.372363490760359e-06, 'epoch': 0.78}
+
78%|███████▊ | 9357/11952 [16:08<4:14:36, 5.89s/it]
78%|███████▊ | 9358/11952 [16:14<4:14:47, 5.89s/it]
{'loss': 0.4582, 'learning_rate': 2.3706113367500183e-06, 'epoch': 0.78}
+
78%|███████▊ | 9358/11952 [16:14<4:14:47, 5.89s/it]
78%|███████▊ | 9359/11952 [16:20<4:13:44, 5.87s/it]
{'loss': 0.4683, 'learning_rate': 2.36885974301025e-06, 'epoch': 0.78}
+
78%|███████▊ | 9359/11952 [16:20<4:13:44, 5.87s/it]
78%|███████▊ | 9360/11952 [16:26<4:12:08, 5.84s/it]
{'loss': 0.4571, 'learning_rate': 2.367108709669683e-06, 'epoch': 0.78}
+
78%|███████▊ | 9360/11952 [16:26<4:12:08, 5.84s/it]
78%|███████▊ | 9361/11952 [16:32<4:15:54, 5.93s/it]
{'loss': 0.4503, 'learning_rate': 2.3653582368569017e-06, 'epoch': 0.78}
+
78%|███████▊ | 9361/11952 [16:32<4:15:54, 5.93s/it]
78%|███████▊ | 9362/11952 [16:38<4:20:05, 6.03s/it]
{'loss': 0.4537, 'learning_rate': 2.3636083247004592e-06, 'epoch': 0.78}
+
78%|███████▊ | 9362/11952 [16:38<4:20:05, 6.03s/it]
78%|███████▊ | 9363/11952 [16:44<4:21:10, 6.05s/it]
{'loss': 0.4668, 'learning_rate': 2.3618589733288588e-06, 'epoch': 0.78}
+
78%|███████▊ | 9363/11952 [16:44<4:21:10, 6.05s/it]
78%|███████▊ | 9364/11952 [16:50<4:16:15, 5.94s/it]
{'loss': 0.4526, 'learning_rate': 2.3601101828705664e-06, 'epoch': 0.78}
+
78%|███████▊ | 9364/11952 [16:50<4:16:15, 5.94s/it]
78%|███████▊ | 9365/11952 [16:55<4:11:22, 5.83s/it]
{'loss': 0.478, 'learning_rate': 2.358361953454004e-06, 'epoch': 0.78}
+
78%|███████▊ | 9365/11952 [16:55<4:11:22, 5.83s/it]
78%|███████▊ | 9366/11952 [17:01<4:11:03, 5.83s/it]
{'loss': 0.4649, 'learning_rate': 2.356614285207557e-06, 'epoch': 0.78}
+
78%|███████▊ | 9366/11952 [17:01<4:11:03, 5.83s/it]
78%|███████▊ | 9367/11952 [17:07<4:11:17, 5.83s/it]
{'loss': 0.4418, 'learning_rate': 2.3548671782595655e-06, 'epoch': 0.78}
+
78%|███████▊ | 9367/11952 [17:07<4:11:17, 5.83s/it]
78%|███████▊ | 9368/11952 [17:13<4:12:57, 5.87s/it]
{'loss': 0.4629, 'learning_rate': 2.3531206327383305e-06, 'epoch': 0.78}
+
78%|███████▊ | 9368/11952 [17:13<4:12:57, 5.87s/it]
78%|███████▊ | 9369/11952 [17:19<4:13:11, 5.88s/it]
{'loss': 0.4576, 'learning_rate': 2.35137464877211e-06, 'epoch': 0.78}
+
78%|███████▊ | 9369/11952 [17:19<4:13:11, 5.88s/it]
78%|███████▊ | 9370/11952 [17:25<4:17:06, 5.97s/it]
{'loss': 0.4573, 'learning_rate': 2.3496292264891194e-06, 'epoch': 0.78}
+
78%|███████▊ | 9370/11952 [17:25<4:17:06, 5.97s/it]
78%|███████▊ | 9371/11952 [17:31<4:12:43, 5.87s/it]
{'loss': 0.4696, 'learning_rate': 2.3478843660175423e-06, 'epoch': 0.78}
+
78%|███████▊ | 9371/11952 [17:31<4:12:43, 5.87s/it]
78%|███████▊ | 9372/11952 [17:37<4:13:49, 5.90s/it]
{'loss': 0.4837, 'learning_rate': 2.346140067485506e-06, 'epoch': 0.78}
+
78%|███████▊ | 9372/11952 [17:37<4:13:49, 5.90s/it]
78%|███████▊ | 9373/11952 [17:43<4:14:23, 5.92s/it]
{'loss': 0.476, 'learning_rate': 2.3443963310211105e-06, 'epoch': 0.78}
+
78%|███████▊ | 9373/11952 [17:43<4:14:23, 5.92s/it]
78%|███████▊ | 9374/11952 [17:48<4:11:22, 5.85s/it]
{'loss': 0.4577, 'learning_rate': 2.342653156752408e-06, 'epoch': 0.78}
+
78%|███████▊ | 9374/11952 [17:48<4:11:22, 5.85s/it]
78%|███████▊ | 9375/11952 [17:54<4:10:30, 5.83s/it]
{'loss': 0.4761, 'learning_rate': 2.3409105448074067e-06, 'epoch': 0.78}
+
78%|███████▊ | 9375/11952 [17:54<4:10:30, 5.83s/it]
78%|███████▊ | 9376/11952 [18:00<4:09:20, 5.81s/it]
{'loss': 0.4755, 'learning_rate': 2.339168495314079e-06, 'epoch': 0.78}
+
78%|███████▊ | 9376/11952 [18:00<4:09:20, 5.81s/it]
78%|███████▊ | 9377/11952 [18:06<4:07:56, 5.78s/it]
{'loss': 0.4652, 'learning_rate': 2.3374270084003535e-06, 'epoch': 0.78}
+
78%|███████▊ | 9377/11952 [18:06<4:07:56, 5.78s/it]
78%|███████▊ | 9378/11952 [18:12<4:10:21, 5.84s/it]
{'loss': 0.4781, 'learning_rate': 2.3356860841941152e-06, 'epoch': 0.78}
+
78%|███████▊ | 9378/11952 [18:12<4:10:21, 5.84s/it]
78%|███████▊ | 9379/11952 [18:17<4:09:27, 5.82s/it]
{'loss': 0.4703, 'learning_rate': 2.3339457228232142e-06, 'epoch': 0.78}
+
78%|███████▊ | 9379/11952 [18:17<4:09:27, 5.82s/it]
78%|███████▊ | 9380/11952 [18:23<4:07:33, 5.77s/it]
{'loss': 0.4699, 'learning_rate': 2.332205924415455e-06, 'epoch': 0.78}
+
78%|███████▊ | 9380/11952 [18:23<4:07:33, 5.77s/it]
78%|███████▊ | 9381/11952 [18:29<4:07:17, 5.77s/it]
{'loss': 0.4769, 'learning_rate': 2.330466689098596e-06, 'epoch': 0.78}
+
78%|███████▊ | 9381/11952 [18:29<4:07:17, 5.77s/it]
78%|███████▊ | 9382/11952 [18:35<4:06:25, 5.75s/it]
{'loss': 0.47, 'learning_rate': 2.328728017000367e-06, 'epoch': 0.78}
+
78%|███████▊ | 9382/11952 [18:35<4:06:25, 5.75s/it]
79%|███████▊ | 9383/11952 [18:40<4:08:15, 5.80s/it]
{'loss': 0.4821, 'learning_rate': 2.3269899082484447e-06, 'epoch': 0.79}
+
79%|███████▊ | 9383/11952 [18:40<4:08:15, 5.80s/it]
79%|███████▊ | 9384/11952 [18:46<4:10:17, 5.85s/it]
{'loss': 0.4785, 'learning_rate': 2.325252362970469e-06, 'epoch': 0.79}
+
79%|███████▊ | 9384/11952 [18:46<4:10:17, 5.85s/it]
79%|███████▊ | 9385/11952 [18:52<4:08:22, 5.81s/it]
{'loss': 0.4489, 'learning_rate': 2.3235153812940357e-06, 'epoch': 0.79}
+
79%|███████▊ | 9385/11952 [18:52<4:08:22, 5.81s/it]
79%|███████▊ | 9386/11952 [18:58<4:10:00, 5.85s/it]
{'loss': 0.4619, 'learning_rate': 2.321778963346707e-06, 'epoch': 0.79}
+
79%|███████▊ | 9386/11952 [18:58<4:10:00, 5.85s/it]
79%|███████▊ | 9387/11952 [19:04<4:14:21, 5.95s/it]
{'loss': 0.4659, 'learning_rate': 2.3200431092559948e-06, 'epoch': 0.79}
+
79%|███████▊ | 9387/11952 [19:04<4:14:21, 5.95s/it]
79%|███████▊ | 9388/11952 [19:10<4:17:19, 6.02s/it]
{'loss': 0.4701, 'learning_rate': 2.3183078191493734e-06, 'epoch': 0.79}
+
79%|███████▊ | 9388/11952 [19:10<4:17:19, 6.02s/it]
79%|███████▊ | 9389/11952 [19:16<4:12:49, 5.92s/it]
{'loss': 0.4658, 'learning_rate': 2.3165730931542753e-06, 'epoch': 0.79}
+
79%|███████▊ | 9389/11952 [19:16<4:12:49, 5.92s/it]
79%|███████▊ | 9390/11952 [19:22<4:16:48, 6.01s/it]
{'loss': 0.4866, 'learning_rate': 2.3148389313980912e-06, 'epoch': 0.79}
+
79%|███████▊ | 9390/11952 [19:22<4:16:48, 6.01s/it]
79%|███████▊ | 9391/11952 [19:28<4:15:50, 5.99s/it]
{'loss': 0.4773, 'learning_rate': 2.3131053340081675e-06, 'epoch': 0.79}
+
79%|███████▊ | 9391/11952 [19:28<4:15:50, 5.99s/it]
79%|███████▊ | 9392/11952 [19:35<4:18:19, 6.05s/it]
{'loss': 0.4558, 'learning_rate': 2.3113723011118196e-06, 'epoch': 0.79}
+
79%|███████▊ | 9392/11952 [19:35<4:18:19, 6.05s/it]
79%|███████▊ | 9393/11952 [19:41<4:17:07, 6.03s/it]
{'loss': 0.4641, 'learning_rate': 2.3096398328363078e-06, 'epoch': 0.79}
+
79%|███████▊ | 9393/11952 [19:41<4:17:07, 6.03s/it]
79%|███████▊ | 9394/11952 [19:47<4:18:19, 6.06s/it]
{'loss': 0.4733, 'learning_rate': 2.3079079293088623e-06, 'epoch': 0.79}
+
79%|███████▊ | 9394/11952 [19:47<4:18:19, 6.06s/it]
79%|███████▊ | 9395/11952 [19:52<4:15:28, 5.99s/it]
{'loss': 0.4505, 'learning_rate': 2.3061765906566644e-06, 'epoch': 0.79}
+
79%|███████▊ | 9395/11952 [19:52<4:15:28, 5.99s/it]
79%|███████▊ | 9396/11952 [19:58<4:12:07, 5.92s/it]
{'loss': 0.4527, 'learning_rate': 2.304445817006857e-06, 'epoch': 0.79}
+
79%|███████▊ | 9396/11952 [19:58<4:12:07, 5.92s/it]
79%|███████▊ | 9397/11952 [20:04<4:08:36, 5.84s/it]
{'loss': 0.4698, 'learning_rate': 2.302715608486541e-06, 'epoch': 0.79}
+
79%|███████▊ | 9397/11952 [20:04<4:08:36, 5.84s/it]
79%|███████▊ | 9398/11952 [20:10<4:14:29, 5.98s/it]
{'loss': 0.4587, 'learning_rate': 2.300985965222775e-06, 'epoch': 0.79}
+
79%|███████▊ | 9398/11952 [20:10<4:14:29, 5.98s/it]
79%|███████▊ | 9399/11952 [20:16<4:11:14, 5.90s/it]
{'loss': 0.4571, 'learning_rate': 2.2992568873425746e-06, 'epoch': 0.79}
+
79%|███████▊ | 9399/11952 [20:16<4:11:14, 5.90s/it]5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+24 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+76 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
79%|███████▊ | 9400/11952 [20:22<4:14:15, 5.98s/it]
{'loss': 0.4801, 'learning_rate': 2.2975283749729205e-06, 'epoch': 0.79}
+
79%|███████▊ | 9400/11952 [20:22<4:14:15, 5.98s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
79%|███████▊ | 9401/11952 [20:52<9:23:17, 13.25s/it]
{'loss': 0.464, 'learning_rate': 2.2958004282407466e-06, 'epoch': 0.79}
+
79%|███████▊ | 9401/11952 [20:52<9:23:17, 13.25s/it]
79%|███████▊ | 9402/11952 [20:58<7:50:10, 11.06s/it]
{'loss': 0.4576, 'learning_rate': 2.2940730472729423e-06, 'epoch': 0.79}
+
79%|███████▊ | 9402/11952 [20:58<7:50:10, 11.06s/it]
79%|███████▊ | 9403/11952 [21:04<6:42:00, 9.46s/it]
{'loss': 0.468, 'learning_rate': 2.292346232196364e-06, 'epoch': 0.79}
+
79%|███████▊ | 9403/11952 [21:04<6:42:00, 9.46s/it]
79%|███████▊ | 9404/11952 [21:10<5:56:20, 8.39s/it]
{'loss': 0.4632, 'learning_rate': 2.2906199831378194e-06, 'epoch': 0.79}
+
79%|███████▊ | 9404/11952 [21:10<5:56:20, 8.39s/it]
79%|███████▊ | 9405/11952 [21:16<5:24:14, 7.64s/it]
{'loss': 0.4746, 'learning_rate': 2.288894300224076e-06, 'epoch': 0.79}
+
79%|███████▊ | 9405/11952 [21:16<5:24:14, 7.64s/it]
79%|███████▊ | 9406/11952 [21:21<4:59:40, 7.06s/it]
{'loss': 0.4696, 'learning_rate': 2.2871691835818642e-06, 'epoch': 0.79}
+
79%|███████▊ | 9406/11952 [21:21<4:59:40, 7.06s/it]
79%|███████▊ | 9407/11952 [21:28<4:48:06, 6.79s/it]
{'loss': 0.4789, 'learning_rate': 2.285444633337869e-06, 'epoch': 0.79}
+
79%|███████▊ | 9407/11952 [21:28<4:48:06, 6.79s/it]
79%|███████▊ | 9408/11952 [21:34<4:38:15, 6.56s/it]
{'loss': 0.4654, 'learning_rate': 2.2837206496187314e-06, 'epoch': 0.79}
+
79%|███████▊ | 9408/11952 [21:34<4:38:15, 6.56s/it]
79%|███████▊ | 9409/11952 [21:40<4:31:40, 6.41s/it]
{'loss': 0.4687, 'learning_rate': 2.281997232551055e-06, 'epoch': 0.79}
+
79%|███████▊ | 9409/11952 [21:40<4:31:40, 6.41s/it]
79%|███████▊ | 9410/11952 [21:46<4:25:01, 6.26s/it]
{'loss': 0.4548, 'learning_rate': 2.2802743822614003e-06, 'epoch': 0.79}
+
79%|███████▊ | 9410/11952 [21:46<4:25:01, 6.26s/it]
79%|███████▊ | 9411/11952 [21:51<4:16:49, 6.06s/it]
{'loss': 0.4527, 'learning_rate': 2.2785520988762833e-06, 'epoch': 0.79}
+
79%|███████▊ | 9411/11952 [21:51<4:16:49, 6.06s/it]
79%|███████▊ | 9412/11952 [21:57<4:16:38, 6.06s/it]
{'loss': 0.4528, 'learning_rate': 2.276830382522187e-06, 'epoch': 0.79}
+
79%|███████▊ | 9412/11952 [21:57<4:16:38, 6.06s/it]
79%|███████▉ | 9413/11952 [22:03<4:16:36, 6.06s/it]
{'loss': 0.4684, 'learning_rate': 2.275109233325542e-06, 'epoch': 0.79}
+
79%|███████▉ | 9413/11952 [22:03<4:16:36, 6.06s/it]
79%|███████▉ | 9414/11952 [22:09<4:16:17, 6.06s/it]
{'loss': 0.4661, 'learning_rate': 2.2733886514127466e-06, 'epoch': 0.79}
+
79%|███████▉ | 9414/11952 [22:09<4:16:17, 6.06s/it]
79%|███████▉ | 9415/11952 [22:15<4:13:55, 6.01s/it]
{'loss': 0.4706, 'learning_rate': 2.2716686369101525e-06, 'epoch': 0.79}
+
79%|███████▉ | 9415/11952 [22:15<4:13:55, 6.01s/it]
79%|███████▉ | 9416/11952 [22:21<4:11:14, 5.94s/it]
{'loss': 0.4721, 'learning_rate': 2.2699491899440683e-06, 'epoch': 0.79}
+
79%|███████▉ | 9416/11952 [22:21<4:11:14, 5.94s/it]
79%|███████▉ | 9417/11952 [22:27<4:08:57, 5.89s/it]
{'loss': 0.4519, 'learning_rate': 2.2682303106407645e-06, 'epoch': 0.79}
+
79%|███████▉ | 9417/11952 [22:27<4:08:57, 5.89s/it]
79%|███████▉ | 9418/11952 [22:33<4:08:55, 5.89s/it]
{'loss': 0.4758, 'learning_rate': 2.2665119991264673e-06, 'epoch': 0.79}
+
79%|███████▉ | 9418/11952 [22:33<4:08:55, 5.89s/it]
79%|███████▉ | 9419/11952 [22:38<4:05:31, 5.82s/it]
{'loss': 0.4432, 'learning_rate': 2.2647942555273592e-06, 'epoch': 0.79}
+
79%|███████▉ | 9419/11952 [22:38<4:05:31, 5.82s/it]
79%|███████▉ | 9420/11952 [22:44<4:09:20, 5.91s/it]
{'loss': 0.4654, 'learning_rate': 2.2630770799695922e-06, 'epoch': 0.79}
+
79%|███████▉ | 9420/11952 [22:45<4:09:20, 5.91s/it]
79%|███████▉ | 9421/11952 [22:51<4:12:17, 5.98s/it]
{'loss': 0.4654, 'learning_rate': 2.2613604725792636e-06, 'epoch': 0.79}
+
79%|███████▉ | 9421/11952 [22:51<4:12:17, 5.98s/it]
79%|███████▉ | 9422/11952 [22:56<4:09:33, 5.92s/it]
{'loss': 0.4582, 'learning_rate': 2.259644433482434e-06, 'epoch': 0.79}
+
79%|███████▉ | 9422/11952 [22:56<4:09:33, 5.92s/it]
79%|███████▉ | 9423/11952 [23:03<4:13:31, 6.01s/it]
{'loss': 0.4455, 'learning_rate': 2.2579289628051203e-06, 'epoch': 0.79}
+
79%|███████▉ | 9423/11952 [23:03<4:13:31, 6.01s/it]
79%|███████▉ | 9424/11952 [23:09<4:11:52, 5.98s/it]
{'loss': 0.4711, 'learning_rate': 2.256214060673305e-06, 'epoch': 0.79}
+
79%|███████▉ | 9424/11952 [23:09<4:11:52, 5.98s/it]
79%|███████▉ | 9425/11952 [23:14<4:07:28, 5.88s/it]
{'loss': 0.4694, 'learning_rate': 2.2544997272129197e-06, 'epoch': 0.79}
+
79%|███████▉ | 9425/11952 [23:14<4:07:28, 5.88s/it]
79%|███████▉ | 9426/11952 [23:20<4:09:23, 5.92s/it]
{'loss': 0.4452, 'learning_rate': 2.252785962549856e-06, 'epoch': 0.79}
+
79%|███████▉ | 9426/11952 [23:20<4:09:23, 5.92s/it]
79%|███████▉ | 9427/11952 [23:26<4:08:08, 5.90s/it]
{'loss': 0.4767, 'learning_rate': 2.2510727668099706e-06, 'epoch': 0.79}
+
79%|███████▉ | 9427/11952 [23:26<4:08:08, 5.90s/it]
79%|███████▉ | 9428/11952 [23:32<4:09:41, 5.94s/it]
{'loss': 0.4607, 'learning_rate': 2.2493601401190723e-06, 'epoch': 0.79}
+
79%|███████▉ | 9428/11952 [23:32<4:09:41, 5.94s/it]
79%|███████▉ | 9429/11952 [23:38<4:12:34, 6.01s/it]
{'loss': 0.4478, 'learning_rate': 2.247648082602927e-06, 'epoch': 0.79}
+
79%|███████▉ | 9429/11952 [23:38<4:12:34, 6.01s/it]
79%|███████▉ | 9430/11952 [23:44<4:09:00, 5.92s/it]
{'loss': 0.4754, 'learning_rate': 2.2459365943872613e-06, 'epoch': 0.79}
+
79%|███████▉ | 9430/11952 [23:44<4:09:00, 5.92s/it]
79%|███████▉ | 9431/11952 [23:50<4:09:04, 5.93s/it]
{'loss': 0.4856, 'learning_rate': 2.244225675597761e-06, 'epoch': 0.79}
+
79%|███████▉ | 9431/11952 [23:50<4:09:04, 5.93s/it]
79%|███████▉ | 9432/11952 [23:56<4:07:13, 5.89s/it]
{'loss': 0.4694, 'learning_rate': 2.242515326360066e-06, 'epoch': 0.79}
+
79%|███████▉ | 9432/11952 [23:56<4:07:13, 5.89s/it]
79%|███████▉ | 9433/11952 [24:02<4:11:06, 5.98s/it]
{'loss': 0.4513, 'learning_rate': 2.2408055467997823e-06, 'epoch': 0.79}
+
79%|███████▉ | 9433/11952 [24:02<4:11:06, 5.98s/it]
79%|███████▉ | 9434/11952 [24:08<4:11:16, 5.99s/it]
{'loss': 0.4721, 'learning_rate': 2.2390963370424635e-06, 'epoch': 0.79}
+
79%|███████▉ | 9434/11952 [24:08<4:11:16, 5.99s/it]
79%|███████▉ | 9435/11952 [24:14<4:10:42, 5.98s/it]
{'loss': 0.4726, 'learning_rate': 2.237387697213632e-06, 'epoch': 0.79}
+
79%|███████▉ | 9435/11952 [24:14<4:10:42, 5.98s/it]
79%|███████▉ | 9436/11952 [24:20<4:13:09, 6.04s/it]
{'loss': 0.4632, 'learning_rate': 2.2356796274387617e-06, 'epoch': 0.79}
+
79%|███████▉ | 9436/11952 [24:20<4:13:09, 6.04s/it]
79%|███████▉ | 9437/11952 [24:26<4:12:24, 6.02s/it]
{'loss': 0.4877, 'learning_rate': 2.2339721278432847e-06, 'epoch': 0.79}
+
79%|███████▉ | 9437/11952 [24:26<4:12:24, 6.02s/it]
79%|███████▉ | 9438/11952 [24:32<4:10:04, 5.97s/it]
{'loss': 0.4796, 'learning_rate': 2.2322651985525932e-06, 'epoch': 0.79}
+
79%|███████▉ | 9438/11952 [24:32<4:10:04, 5.97s/it]
79%|███████▉ | 9439/11952 [24:38<4:07:59, 5.92s/it]
{'loss': 0.4482, 'learning_rate': 2.2305588396920375e-06, 'epoch': 0.79}
+
79%|███████▉ | 9439/11952 [24:38<4:07:59, 5.92s/it]
79%|███████▉ | 9440/11952 [24:43<4:06:09, 5.88s/it]
{'loss': 0.4621, 'learning_rate': 2.228853051386922e-06, 'epoch': 0.79}
+
79%|███████▉ | 9440/11952 [24:43<4:06:09, 5.88s/it]
79%|███████▉ | 9441/11952 [24:49<4:06:33, 5.89s/it]
{'loss': 0.4697, 'learning_rate': 2.22714783376252e-06, 'epoch': 0.79}
+
79%|███████▉ | 9441/11952 [24:49<4:06:33, 5.89s/it]
79%|███████▉ | 9442/11952 [24:55<4:06:54, 5.90s/it]
{'loss': 0.4766, 'learning_rate': 2.2254431869440496e-06, 'epoch': 0.79}
+
79%|███████▉ | 9442/11952 [24:55<4:06:54, 5.90s/it]
79%|███████▉ | 9443/11952 [25:01<4:07:27, 5.92s/it]
{'loss': 0.4686, 'learning_rate': 2.223739111056692e-06, 'epoch': 0.79}
+
79%|███████▉ | 9443/11952 [25:01<4:07:27, 5.92s/it]
79%|███████▉ | 9444/11952 [25:07<4:05:00, 5.86s/it]
{'loss': 0.46, 'learning_rate': 2.222035606225593e-06, 'epoch': 0.79}
+
79%|███████▉ | 9444/11952 [25:07<4:05:00, 5.86s/it]
79%|███████▉ | 9445/11952 [25:13<4:01:51, 5.79s/it]
{'loss': 0.4642, 'learning_rate': 2.220332672575849e-06, 'epoch': 0.79}
+
79%|███████▉ | 9445/11952 [25:13<4:01:51, 5.79s/it]
79%|███████▉ | 9446/11952 [25:18<4:02:35, 5.81s/it]
{'loss': 0.4591, 'learning_rate': 2.2186303102325125e-06, 'epoch': 0.79}
+
79%|███████▉ | 9446/11952 [25:18<4:02:35, 5.81s/it]
79%|███████▉ | 9447/11952 [25:25<4:08:08, 5.94s/it]
{'loss': 0.4726, 'learning_rate': 2.2169285193206038e-06, 'epoch': 0.79}
+
79%|███████▉ | 9447/11952 [25:25<4:08:08, 5.94s/it]
79%|███████▉ | 9448/11952 [25:30<4:05:46, 5.89s/it]
{'loss': 0.4684, 'learning_rate': 2.2152272999650916e-06, 'epoch': 0.79}
+
79%|███████▉ | 9448/11952 [25:30<4:05:46, 5.89s/it]
79%|███████▉ | 9449/11952 [25:36<4:07:03, 5.92s/it]
{'loss': 0.491, 'learning_rate': 2.2135266522909073e-06, 'epoch': 0.79}
+
79%|███████▉ | 9449/11952 [25:36<4:07:03, 5.92s/it]4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...3
+ AutoResumeHook: Checking whether to suspend...0
+ 1 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
79%|███████▉ | 9450/11952 [25:42<4:05:32, 5.89s/it]
{'loss': 0.4728, 'learning_rate': 2.2118265764229396e-06, 'epoch': 0.79}
+
79%|███████▉ | 9450/11952 [25:42<4:05:32, 5.89s/it]
79%|███████▉ | 9451/11952 [25:48<4:09:09, 5.98s/it]
{'loss': 0.4598, 'learning_rate': 2.2101270724860345e-06, 'epoch': 0.79}
+
79%|███████▉ | 9451/11952 [25:48<4:09:09, 5.98s/it]
79%|███████▉ | 9452/11952 [25:54<4:08:42, 5.97s/it]
{'loss': 0.4708, 'learning_rate': 2.2084281406049966e-06, 'epoch': 0.79}
+
79%|███████▉ | 9452/11952 [25:54<4:08:42, 5.97s/it]
79%|███████▉ | 9453/11952 [26:00<4:08:10, 5.96s/it]
{'loss': 0.4778, 'learning_rate': 2.2067297809045863e-06, 'epoch': 0.79}
+
79%|███████▉ | 9453/11952 [26:00<4:08:10, 5.96s/it]
79%|███████▉ | 9454/11952 [26:06<4:06:32, 5.92s/it]
{'loss': 0.4637, 'learning_rate': 2.2050319935095254e-06, 'epoch': 0.79}
+
79%|███████▉ | 9454/11952 [26:06<4:06:32, 5.92s/it]
79%|███████▉ | 9455/11952 [26:12<4:07:12, 5.94s/it]
{'loss': 0.4553, 'learning_rate': 2.203334778544497e-06, 'epoch': 0.79}
+
79%|███████▉ | 9455/11952 [26:12<4:07:12, 5.94s/it]
79%|███████▉ | 9456/11952 [26:18<4:04:20, 5.87s/it]
{'loss': 0.4488, 'learning_rate': 2.201638136134132e-06, 'epoch': 0.79}
+
79%|███████▉ | 9456/11952 [26:18<4:04:20, 5.87s/it]
79%|███████▉ | 9457/11952 [26:24<4:06:05, 5.92s/it]
{'loss': 0.4643, 'learning_rate': 2.199942066403028e-06, 'epoch': 0.79}
+
79%|███████▉ | 9457/11952 [26:24<4:06:05, 5.92s/it]
79%|███████▉ | 9458/11952 [26:30<4:08:22, 5.98s/it]
{'loss': 0.4453, 'learning_rate': 2.198246569475735e-06, 'epoch': 0.79}
+
79%|███████▉ | 9458/11952 [26:30<4:08:22, 5.98s/it]
79%|███████▉ | 9459/11952 [26:36<4:03:58, 5.87s/it]
{'loss': 0.4703, 'learning_rate': 2.1965516454767645e-06, 'epoch': 0.79}
+
79%|███████▉ | 9459/11952 [26:36<4:03:58, 5.87s/it]
79%|███████▉ | 9460/11952 [26:42<4:09:23, 6.00s/it]
{'loss': 0.4579, 'learning_rate': 2.1948572945305813e-06, 'epoch': 0.79}
+
79%|███████▉ | 9460/11952 [26:42<4:09:23, 6.00s/it]
79%|███████▉ | 9461/11952 [26:48<4:05:28, 5.91s/it]
{'loss': 0.4486, 'learning_rate': 2.193163516761617e-06, 'epoch': 0.79}
+
79%|███████▉ | 9461/11952 [26:48<4:05:28, 5.91s/it]
79%|███████▉ | 9462/11952 [26:54<4:06:02, 5.93s/it]
{'loss': 0.4719, 'learning_rate': 2.1914703122942525e-06, 'epoch': 0.79}
+
79%|███████▉ | 9462/11952 [26:54<4:06:02, 5.93s/it]
79%|███████▉ | 9463/11952 [27:00<4:07:21, 5.96s/it]
{'loss': 0.4651, 'learning_rate': 2.1897776812528317e-06, 'epoch': 0.79}
+
79%|███████▉ | 9463/11952 [27:00<4:07:21, 5.96s/it]
79%|███████▉ | 9464/11952 [27:06<4:07:32, 5.97s/it]
{'loss': 0.4757, 'learning_rate': 2.188085623761649e-06, 'epoch': 0.79}
+
79%|███████▉ | 9464/11952 [27:06<4:07:32, 5.97s/it]
79%|███████▉ | 9465/11952 [27:12<4:06:29, 5.95s/it]
{'loss': 0.4875, 'learning_rate': 2.1863941399449685e-06, 'epoch': 0.79}
+
79%|███████▉ | 9465/11952 [27:12<4:06:29, 5.95s/it]
79%|███████▉ | 9466/11952 [27:17<4:03:01, 5.87s/it]
{'loss': 0.4704, 'learning_rate': 2.1847032299270032e-06, 'epoch': 0.79}
+
79%|███████▉ | 9466/11952 [27:17<4:03:01, 5.87s/it]
79%|███████▉ | 9467/11952 [27:23<4:01:46, 5.84s/it]
{'loss': 0.455, 'learning_rate': 2.1830128938319238e-06, 'epoch': 0.79}
+
79%|███████▉ | 9467/11952 [27:23<4:01:46, 5.84s/it]
79%|███████▉ | 9468/11952 [27:29<4:04:28, 5.91s/it]
{'loss': 0.4656, 'learning_rate': 2.1813231317838667e-06, 'epoch': 0.79}
+
79%|███████▉ | 9468/11952 [27:29<4:04:28, 5.91s/it]
79%|███████▉ | 9469/11952 [27:35<4:04:09, 5.90s/it]
{'loss': 0.454, 'learning_rate': 2.179633943906918e-06, 'epoch': 0.79}
+
79%|███████▉ | 9469/11952 [27:35<4:04:09, 5.90s/it]
79%|███████▉ | 9470/11952 [27:41<4:02:05, 5.85s/it]
{'loss': 0.4647, 'learning_rate': 2.1779453303251262e-06, 'epoch': 0.79}
+
79%|███████▉ | 9470/11952 [27:41<4:02:05, 5.85s/it]
79%|███████▉ | 9471/11952 [27:47<4:05:13, 5.93s/it]
{'loss': 0.4512, 'learning_rate': 2.176257291162495e-06, 'epoch': 0.79}
+
79%|███████▉ | 9471/11952 [27:47<4:05:13, 5.93s/it]
79%|███████▉ | 9472/11952 [27:53<4:04:44, 5.92s/it]
{'loss': 0.473, 'learning_rate': 2.174569826542986e-06, 'epoch': 0.79}
+
79%|███████▉ | 9472/11952 [27:53<4:04:44, 5.92s/it]
79%|███████▉ | 9473/11952 [27:59<4:05:11, 5.93s/it]
{'loss': 0.4463, 'learning_rate': 2.172882936590518e-06, 'epoch': 0.79}
+
79%|███████▉ | 9473/11952 [27:59<4:05:11, 5.93s/it]
79%|███████▉ | 9474/11952 [28:04<4:02:47, 5.88s/it]
{'loss': 0.4627, 'learning_rate': 2.1711966214289747e-06, 'epoch': 0.79}
+
79%|███████▉ | 9474/11952 [28:04<4:02:47, 5.88s/it]
79%|███████▉ | 9475/11952 [28:10<4:04:22, 5.92s/it]
{'loss': 0.4592, 'learning_rate': 2.1695108811821863e-06, 'epoch': 0.79}
+
79%|███████▉ | 9475/11952 [28:10<4:04:22, 5.92s/it]
79%|███████▉ | 9476/11952 [28:16<4:02:37, 5.88s/it]
{'loss': 0.4872, 'learning_rate': 2.1678257159739524e-06, 'epoch': 0.79}
+
79%|███████▉ | 9476/11952 [28:16<4:02:37, 5.88s/it]
79%|███████▉ | 9477/11952 [28:22<4:03:00, 5.89s/it]
{'loss': 0.4719, 'learning_rate': 2.1661411259280206e-06, 'epoch': 0.79}
+
79%|███████▉ | 9477/11952 [28:22<4:03:00, 5.89s/it]
79%|███████▉ | 9478/11952 [28:28<4:01:41, 5.86s/it]
{'loss': 0.4569, 'learning_rate': 2.1644571111681023e-06, 'epoch': 0.79}
+
79%|███████▉ | 9478/11952 [28:28<4:01:41, 5.86s/it]
79%|███████▉ | 9479/11952 [28:34<4:01:49, 5.87s/it]
{'loss': 0.4524, 'learning_rate': 2.1627736718178626e-06, 'epoch': 0.79}
+
79%|███████▉ | 9479/11952 [28:34<4:01:49, 5.87s/it]
79%|███████▉ | 9480/11952 [28:40<3:59:50, 5.82s/it]
{'loss': 0.4584, 'learning_rate': 2.161090808000924e-06, 'epoch': 0.79}
+
79%|███████▉ | 9480/11952 [28:40<3:59:50, 5.82s/it]
79%|███████▉ | 9481/11952 [28:45<4:01:07, 5.86s/it]
{'loss': 0.4599, 'learning_rate': 2.1594085198408756e-06, 'epoch': 0.79}
+
79%|███████▉ | 9481/11952 [28:45<4:01:07, 5.86s/it]
79%|███████▉ | 9482/11952 [28:51<4:00:55, 5.85s/it]
{'loss': 0.4763, 'learning_rate': 2.1577268074612535e-06, 'epoch': 0.79}
+
79%|███████▉ | 9482/11952 [28:51<4:00:55, 5.85s/it]
79%|███████▉ | 9483/11952 [28:57<4:01:09, 5.86s/it]
{'loss': 0.4584, 'learning_rate': 2.156045670985556e-06, 'epoch': 0.79}
+
79%|███████▉ | 9483/11952 [28:57<4:01:09, 5.86s/it]
79%|███████▉ | 9484/11952 [29:03<4:02:35, 5.90s/it]
{'loss': 0.4735, 'learning_rate': 2.1543651105372352e-06, 'epoch': 0.79}
+
79%|███████▉ | 9484/11952 [29:03<4:02:35, 5.90s/it]
79%|███████▉ | 9485/11952 [29:09<4:00:11, 5.84s/it]
{'loss': 0.4688, 'learning_rate': 2.152685126239713e-06, 'epoch': 0.79}
+
79%|███████▉ | 9485/11952 [29:09<4:00:11, 5.84s/it]
79%|███████▉ | 9486/11952 [29:15<4:01:16, 5.87s/it]
{'loss': 0.4492, 'learning_rate': 2.1510057182163547e-06, 'epoch': 0.79}
+
79%|███████▉ | 9486/11952 [29:15<4:01:16, 5.87s/it]
79%|███████▉ | 9487/11952 [29:21<4:05:05, 5.97s/it]
{'loss': 0.4916, 'learning_rate': 2.1493268865904872e-06, 'epoch': 0.79}
+
79%|███████▉ | 9487/11952 [29:21<4:05:05, 5.97s/it]
79%|███████▉ | 9488/11952 [29:27<4:05:09, 5.97s/it]
{'loss': 0.4659, 'learning_rate': 2.1476486314854027e-06, 'epoch': 0.79}
+
79%|███████▉ | 9488/11952 [29:27<4:05:09, 5.97s/it]
79%|███████▉ | 9489/11952 [29:33<4:07:10, 6.02s/it]
{'loss': 0.4438, 'learning_rate': 2.1459709530243423e-06, 'epoch': 0.79}
+
79%|███████▉ | 9489/11952 [29:33<4:07:10, 6.02s/it]
79%|███████▉ | 9490/11952 [29:39<4:06:19, 6.00s/it]
{'loss': 0.4826, 'learning_rate': 2.144293851330508e-06, 'epoch': 0.79}
+
79%|███████▉ | 9490/11952 [29:39<4:06:19, 6.00s/it]
79%|███████▉ | 9491/11952 [29:45<4:05:27, 5.98s/it]
{'loss': 0.4829, 'learning_rate': 2.1426173265270578e-06, 'epoch': 0.79}
+
79%|███████▉ | 9491/11952 [29:45<4:05:27, 5.98s/it]
79%|███████▉ | 9492/11952 [29:51<4:03:50, 5.95s/it]
{'loss': 0.4722, 'learning_rate': 2.1409413787371114e-06, 'epoch': 0.79}
+
79%|███████▉ | 9492/11952 [29:51<4:03:50, 5.95s/it]
79%|███████▉ | 9493/11952 [29:57<4:04:33, 5.97s/it]
{'loss': 0.4796, 'learning_rate': 2.13926600808374e-06, 'epoch': 0.79}
+
79%|███████▉ | 9493/11952 [29:57<4:04:33, 5.97s/it]
79%|███████▉ | 9494/11952 [30:03<4:01:11, 5.89s/it]
{'loss': 0.4647, 'learning_rate': 2.1375912146899767e-06, 'epoch': 0.79}
+
79%|███████▉ | 9494/11952 [30:03<4:01:11, 5.89s/it]
79%|███████▉ | 9495/11952 [30:09<4:02:23, 5.92s/it]
{'loss': 0.4497, 'learning_rate': 2.135916998678812e-06, 'epoch': 0.79}
+
79%|███████▉ | 9495/11952 [30:09<4:02:23, 5.92s/it]
79%|███████▉ | 9496/11952 [30:15<4:04:08, 5.96s/it]
{'loss': 0.4972, 'learning_rate': 2.134243360173196e-06, 'epoch': 0.79}
+
79%|███████▉ | 9496/11952 [30:15<4:04:08, 5.96s/it]
79%|███████▉ | 9497/11952 [30:20<4:00:47, 5.89s/it]
{'loss': 0.4788, 'learning_rate': 2.1325702992960317e-06, 'epoch': 0.79}
+
79%|███████▉ | 9497/11952 [30:20<4:00:47, 5.89s/it]
79%|███████▉ | 9498/11952 [30:27<4:06:41, 6.03s/it]
{'loss': 0.4516, 'learning_rate': 2.130897816170181e-06, 'epoch': 0.79}
+
79%|███████▉ | 9498/11952 [30:27<4:06:41, 6.03s/it]
79%|███████▉ | 9499/11952 [30:33<4:06:18, 6.02s/it]
{'loss': 0.4556, 'learning_rate': 2.1292259109184654e-06, 'epoch': 0.79}
+
79%|███████▉ | 9499/11952 [30:33<4:06:18, 6.02s/it]4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+ 2 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
79%|███████▉ | 9500/11952 [30:38<4:01:31, 5.91s/it]
{'loss': 0.4519, 'learning_rate': 2.1275545836636625e-06, 'epoch': 0.79}
+
79%|███████▉ | 9500/11952 [30:38<4:01:31, 5.91s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
79%|███████▉ | 9501/11952 [31:09<9:01:32, 13.26s/it]
{'loss': 0.4905, 'learning_rate': 2.1258838345285027e-06, 'epoch': 0.79}
+
79%|███████▉ | 9501/11952 [31:09<9:01:32, 13.26s/it]
80%|███████▉ | 9502/11952 [31:15<7:38:25, 11.23s/it]
{'loss': 0.4682, 'learning_rate': 2.124213663635687e-06, 'epoch': 0.79}
+
80%|███████▉ | 9502/11952 [31:15<7:38:25, 11.23s/it]
80%|███████▉ | 9503/11952 [31:21<6:29:46, 9.55s/it]
{'loss': 0.4862, 'learning_rate': 2.1225440711078615e-06, 'epoch': 0.8}
+
80%|███████▉ | 9503/11952 [31:21<6:29:46, 9.55s/it]
80%|███████▉ | 9504/11952 [31:27<5:44:07, 8.43s/it]
{'loss': 0.4761, 'learning_rate': 2.120875057067635e-06, 'epoch': 0.8}
+
80%|███████▉ | 9504/11952 [31:27<5:44:07, 8.43s/it]
80%|███████▉ | 9505/11952 [31:33<5:14:56, 7.72s/it]
{'loss': 0.4625, 'learning_rate': 2.1192066216375695e-06, 'epoch': 0.8}
+
80%|███████▉ | 9505/11952 [31:33<5:14:56, 7.72s/it]
80%|███████▉ | 9506/11952 [31:39<4:52:38, 7.18s/it]
{'loss': 0.4456, 'learning_rate': 2.1175387649401935e-06, 'epoch': 0.8}
+
80%|███████▉ | 9506/11952 [31:39<4:52:38, 7.18s/it]
80%|███████▉ | 9507/11952 [31:44<4:32:55, 6.70s/it]
{'loss': 0.4596, 'learning_rate': 2.1158714870979856e-06, 'epoch': 0.8}
+
80%|███████▉ | 9507/11952 [31:44<4:32:55, 6.70s/it]
80%|███████▉ | 9508/11952 [31:50<4:21:07, 6.41s/it]
{'loss': 0.4775, 'learning_rate': 2.114204788233379e-06, 'epoch': 0.8}
+
80%|███████▉ | 9508/11952 [31:50<4:21:07, 6.41s/it]
80%|███████▉ | 9509/11952 [31:56<4:13:07, 6.22s/it]
{'loss': 0.4652, 'learning_rate': 2.1125386684687774e-06, 'epoch': 0.8}
+
80%|███████▉ | 9509/11952 [31:56<4:13:07, 6.22s/it]
80%|███████▉ | 9510/11952 [32:01<4:06:12, 6.05s/it]
{'loss': 0.4516, 'learning_rate': 2.110873127926529e-06, 'epoch': 0.8}
+
80%|███████▉ | 9510/11952 [32:01<4:06:12, 6.05s/it]
80%|███████▉ | 9511/11952 [32:08<4:08:12, 6.10s/it]
{'loss': 0.4667, 'learning_rate': 2.1092081667289454e-06, 'epoch': 0.8}
+
80%|███████▉ | 9511/11952 [32:08<4:08:12, 6.10s/it]
80%|███████▉ | 9512/11952 [32:13<4:03:27, 5.99s/it]
{'loss': 0.4646, 'learning_rate': 2.1075437849982937e-06, 'epoch': 0.8}
+
80%|███████▉ | 9512/11952 [32:13<4:03:27, 5.99s/it]
80%|███████▉ | 9513/11952 [32:19<4:00:04, 5.91s/it]
{'loss': 0.473, 'learning_rate': 2.105879982856799e-06, 'epoch': 0.8}
+
80%|███████▉ | 9513/11952 [32:19<4:00:04, 5.91s/it]
80%|███████▉ | 9514/11952 [32:25<3:58:50, 5.88s/it]
{'loss': 0.4532, 'learning_rate': 2.1042167604266415e-06, 'epoch': 0.8}
+
80%|███████▉ | 9514/11952 [32:25<3:58:50, 5.88s/it]
80%|███████▉ | 9515/11952 [32:31<3:58:52, 5.88s/it]
{'loss': 0.4778, 'learning_rate': 2.102554117829967e-06, 'epoch': 0.8}
+
80%|███████▉ | 9515/11952 [32:31<3:58:52, 5.88s/it]
80%|███████▉ | 9516/11952 [32:37<4:02:49, 5.98s/it]
{'loss': 0.4789, 'learning_rate': 2.100892055188867e-06, 'epoch': 0.8}
+
80%|███████▉ | 9516/11952 [32:37<4:02:49, 5.98s/it]
80%|███████▉ | 9517/11952 [32:43<4:02:31, 5.98s/it]
{'loss': 0.4668, 'learning_rate': 2.0992305726254026e-06, 'epoch': 0.8}
+
80%|███████▉ | 9517/11952 [32:43<4:02:31, 5.98s/it]
80%|███████▉ | 9518/11952 [32:49<4:00:40, 5.93s/it]
{'loss': 0.483, 'learning_rate': 2.0975696702615823e-06, 'epoch': 0.8}
+
80%|███████▉ | 9518/11952 [32:49<4:00:40, 5.93s/it]
80%|███████▉ | 9519/11952 [32:55<4:00:35, 5.93s/it]
{'loss': 0.4624, 'learning_rate': 2.0959093482193783e-06, 'epoch': 0.8}
+
80%|███████▉ | 9519/11952 [32:55<4:00:35, 5.93s/it]
80%|███████▉ | 9520/11952 [33:01<4:00:05, 5.92s/it]
{'loss': 0.4581, 'learning_rate': 2.094249606620715e-06, 'epoch': 0.8}
+
80%|███████▉ | 9520/11952 [33:01<4:00:05, 5.92s/it]
80%|███████▉ | 9521/11952 [33:07<4:02:42, 5.99s/it]
{'loss': 0.4768, 'learning_rate': 2.092590445587476e-06, 'epoch': 0.8}
+
80%|███████▉ | 9521/11952 [33:07<4:02:42, 5.99s/it]
80%|███████▉ | 9522/11952 [33:13<4:05:58, 6.07s/it]
{'loss': 0.4691, 'learning_rate': 2.0909318652415078e-06, 'epoch': 0.8}
+
80%|███████▉ | 9522/11952 [33:13<4:05:58, 6.07s/it]
80%|███████▉ | 9523/11952 [33:19<3:59:21, 5.91s/it]
{'loss': 0.4657, 'learning_rate': 2.0892738657046065e-06, 'epoch': 0.8}
+
80%|███████▉ | 9523/11952 [33:19<3:59:21, 5.91s/it]
80%|███████▉ | 9524/11952 [33:24<3:56:33, 5.85s/it]
{'loss': 0.4549, 'learning_rate': 2.0876164470985305e-06, 'epoch': 0.8}
+
80%|███████▉ | 9524/11952 [33:24<3:56:33, 5.85s/it]
80%|███████▉ | 9525/11952 [33:30<3:56:23, 5.84s/it]
{'loss': 0.4605, 'learning_rate': 2.0859596095449886e-06, 'epoch': 0.8}
+
80%|███████▉ | 9525/11952 [33:30<3:56:23, 5.84s/it]
80%|███████▉ | 9526/11952 [33:36<3:53:42, 5.78s/it]
{'loss': 0.4536, 'learning_rate': 2.0843033531656596e-06, 'epoch': 0.8}
+
80%|███████▉ | 9526/11952 [33:36<3:53:42, 5.78s/it]
80%|███████▉ | 9527/11952 [33:42<3:57:27, 5.88s/it]
{'loss': 0.4656, 'learning_rate': 2.0826476780821683e-06, 'epoch': 0.8}
+
80%|███████▉ | 9527/11952 [33:42<3:57:27, 5.88s/it]
80%|███████▉ | 9528/11952 [33:48<3:55:01, 5.82s/it]
{'loss': 0.4637, 'learning_rate': 2.080992584416097e-06, 'epoch': 0.8}
+
80%|███████▉ | 9528/11952 [33:48<3:55:01, 5.82s/it]
80%|███████▉ | 9529/11952 [33:54<3:58:09, 5.90s/it]
{'loss': 0.4756, 'learning_rate': 2.079338072288997e-06, 'epoch': 0.8}
+
80%|███████▉ | 9529/11952 [33:54<3:58:09, 5.90s/it]
80%|███████▉ | 9530/11952 [33:59<3:57:15, 5.88s/it]
{'loss': 0.4659, 'learning_rate': 2.0776841418223635e-06, 'epoch': 0.8}
+
80%|███████▉ | 9530/11952 [33:59<3:57:15, 5.88s/it]
80%|███████▉ | 9531/11952 [34:05<3:56:41, 5.87s/it]
{'loss': 0.4654, 'learning_rate': 2.0760307931376555e-06, 'epoch': 0.8}
+
80%|███████▉ | 9531/11952 [34:05<3:56:41, 5.87s/it]
80%|███████▉ | 9532/11952 [34:11<3:57:54, 5.90s/it]
{'loss': 0.4624, 'learning_rate': 2.0743780263562884e-06, 'epoch': 0.8}
+
80%|███████▉ | 9532/11952 [34:11<3:57:54, 5.90s/it]
80%|███████▉ | 9533/11952 [34:17<3:57:22, 5.89s/it]
{'loss': 0.4591, 'learning_rate': 2.0727258415996334e-06, 'epoch': 0.8}
+
80%|███████▉ | 9533/11952 [34:17<3:57:22, 5.89s/it]
80%|███████▉ | 9534/11952 [34:23<3:57:51, 5.90s/it]
{'loss': 0.4664, 'learning_rate': 2.0710742389890205e-06, 'epoch': 0.8}
+
80%|███████▉ | 9534/11952 [34:23<3:57:51, 5.90s/it]
80%|███████▉ | 9535/11952 [34:29<3:55:05, 5.84s/it]
{'loss': 0.4513, 'learning_rate': 2.069423218645734e-06, 'epoch': 0.8}
+
80%|███████▉ | 9535/11952 [34:29<3:55:05, 5.84s/it]
80%|███████▉ | 9536/11952 [34:35<3:56:33, 5.87s/it]
{'loss': 0.4584, 'learning_rate': 2.067772780691023e-06, 'epoch': 0.8}
+
80%|███████▉ | 9536/11952 [34:35<3:56:33, 5.87s/it]
80%|███████▉ | 9537/11952 [34:41<3:57:34, 5.90s/it]
{'loss': 0.4804, 'learning_rate': 2.0661229252460835e-06, 'epoch': 0.8}
+
80%|███████▉ | 9537/11952 [34:41<3:57:34, 5.90s/it]
80%|███████▉ | 9538/11952 [34:47<3:56:42, 5.88s/it]
{'loss': 0.4685, 'learning_rate': 2.064473652432081e-06, 'epoch': 0.8}
+
80%|███████▉ | 9538/11952 [34:47<3:56:42, 5.88s/it]
80%|███████▉ | 9539/11952 [34:52<3:55:16, 5.85s/it]
{'loss': 0.457, 'learning_rate': 2.0628249623701255e-06, 'epoch': 0.8}
+
80%|███████▉ | 9539/11952 [34:52<3:55:16, 5.85s/it]
80%|███████▉ | 9540/11952 [34:58<3:58:58, 5.94s/it]
{'loss': 0.4696, 'learning_rate': 2.061176855181293e-06, 'epoch': 0.8}
+
80%|███████▉ | 9540/11952 [34:58<3:58:58, 5.94s/it]
80%|███████▉ | 9541/11952 [35:04<3:58:53, 5.94s/it]
{'loss': 0.4725, 'learning_rate': 2.0595293309866107e-06, 'epoch': 0.8}
+
80%|███████▉ | 9541/11952 [35:04<3:58:53, 5.94s/it]
80%|███████▉ | 9542/11952 [35:10<3:56:26, 5.89s/it]
{'loss': 0.4579, 'learning_rate': 2.0578823899070653e-06, 'epoch': 0.8}
+
80%|███████▉ | 9542/11952 [35:10<3:56:26, 5.89s/it]
80%|███████▉ | 9543/11952 [35:16<3:57:54, 5.93s/it]
{'loss': 0.4803, 'learning_rate': 2.0562360320636064e-06, 'epoch': 0.8}
+
80%|███████▉ | 9543/11952 [35:16<3:57:54, 5.93s/it]
80%|███████▉ | 9544/11952 [35:22<3:53:05, 5.81s/it]
{'loss': 0.4821, 'learning_rate': 2.0545902575771326e-06, 'epoch': 0.8}
+
80%|███████▉ | 9544/11952 [35:22<3:53:05, 5.81s/it]
80%|███████▉ | 9545/11952 [35:28<4:01:28, 6.02s/it]
{'loss': 0.4638, 'learning_rate': 2.0529450665685023e-06, 'epoch': 0.8}
+
80%|███████▉ | 9545/11952 [35:28<4:01:28, 6.02s/it]
80%|███████▉ | 9546/11952 [35:34<3:58:37, 5.95s/it]
{'loss': 0.4593, 'learning_rate': 2.0513004591585305e-06, 'epoch': 0.8}
+
80%|███████▉ | 9546/11952 [35:34<3:58:37, 5.95s/it]
80%|███████▉ | 9547/11952 [35:40<3:57:26, 5.92s/it]
{'loss': 0.473, 'learning_rate': 2.049656435467994e-06, 'epoch': 0.8}
+
80%|███████▉ | 9547/11952 [35:40<3:57:26, 5.92s/it]
80%|███████▉ | 9548/11952 [35:46<4:00:36, 6.01s/it]
{'loss': 0.4585, 'learning_rate': 2.04801299561762e-06, 'epoch': 0.8}
+
80%|███████▉ | 9548/11952 [35:46<4:00:36, 6.01s/it]
80%|███████▉ | 9549/11952 [35:52<3:59:59, 5.99s/it]
{'loss': 0.4658, 'learning_rate': 2.0463701397280953e-06, 'epoch': 0.8}
+
80%|███████▉ | 9549/11952 [35:52<3:59:59, 5.99s/it]4 AutoResumeHook: Checking whether to suspend...
+23 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
80%|███████▉ | 9550/11952 [35:58<4:02:31, 6.06s/it]
{'loss': 0.4673, 'learning_rate': 2.0447278679200676e-06, 'epoch': 0.8}
+
80%|███████▉ | 9550/11952 [35:58<4:02:31, 6.06s/it]
80%|███████▉ | 9551/11952 [36:04<4:01:33, 6.04s/it]
{'loss': 0.4683, 'learning_rate': 2.0430861803141377e-06, 'epoch': 0.8}
+
80%|███████▉ | 9551/11952 [36:04<4:01:33, 6.04s/it]
80%|███████▉ | 9552/11952 [36:10<4:00:49, 6.02s/it]
{'loss': 0.4636, 'learning_rate': 2.0414450770308638e-06, 'epoch': 0.8}
+
80%|███████▉ | 9552/11952 [36:10<4:00:49, 6.02s/it]
80%|███████▉ | 9553/11952 [36:17<4:03:36, 6.09s/it]
{'loss': 0.4777, 'learning_rate': 2.03980455819076e-06, 'epoch': 0.8}
+
80%|███████▉ | 9553/11952 [36:17<4:03:36, 6.09s/it]
80%|███████▉ | 9554/11952 [36:22<4:02:05, 6.06s/it]
{'loss': 0.453, 'learning_rate': 2.0381646239143017e-06, 'epoch': 0.8}
+
80%|███████▉ | 9554/11952 [36:22<4:02:05, 6.06s/it]
80%|███████▉ | 9555/11952 [36:28<3:58:57, 5.98s/it]
{'loss': 0.4474, 'learning_rate': 2.0365252743219143e-06, 'epoch': 0.8}
+
80%|███████▉ | 9555/11952 [36:28<3:58:57, 5.98s/it]
80%|███████▉ | 9556/11952 [36:35<4:01:54, 6.06s/it]
{'loss': 0.4671, 'learning_rate': 2.034886509533991e-06, 'epoch': 0.8}
+
80%|███████▉ | 9556/11952 [36:35<4:01:54, 6.06s/it]
80%|███████▉ | 9557/11952 [36:40<3:59:11, 5.99s/it]
{'loss': 0.4719, 'learning_rate': 2.0332483296708693e-06, 'epoch': 0.8}
+
80%|███████▉ | 9557/11952 [36:40<3:59:11, 5.99s/it]
80%|███████▉ | 9558/11952 [36:47<4:01:01, 6.04s/it]
{'loss': 0.4555, 'learning_rate': 2.031610734852858e-06, 'epoch': 0.8}
+
80%|███████▉ | 9558/11952 [36:47<4:01:01, 6.04s/it]
80%|███████▉ | 9559/11952 [36:53<4:00:47, 6.04s/it]
{'loss': 0.4698, 'learning_rate': 2.029973725200212e-06, 'epoch': 0.8}
+
80%|███████▉ | 9559/11952 [36:53<4:00:47, 6.04s/it]
80%|███████▉ | 9560/11952 [36:58<3:56:31, 5.93s/it]
{'loss': 0.4783, 'learning_rate': 2.028337300833144e-06, 'epoch': 0.8}
+
80%|███████▉ | 9560/11952 [36:58<3:56:31, 5.93s/it]
80%|███████▉ | 9561/11952 [37:04<3:55:18, 5.90s/it]
{'loss': 0.4447, 'learning_rate': 2.0267014618718295e-06, 'epoch': 0.8}
+
80%|███████▉ | 9561/11952 [37:04<3:55:18, 5.90s/it]
80%|████████ | 9562/11952 [37:10<3:53:41, 5.87s/it]
{'loss': 0.4752, 'learning_rate': 2.0250662084363928e-06, 'epoch': 0.8}
+
80%|████████ | 9562/11952 [37:10<3:53:41, 5.87s/it]
80%|████████ | 9563/11952 [37:15<3:49:34, 5.77s/it]
{'loss': 0.4757, 'learning_rate': 2.023431540646926e-06, 'epoch': 0.8}
+
80%|████████ | 9563/11952 [37:15<3:49:34, 5.77s/it]
80%|████████ | 9564/11952 [37:21<3:51:00, 5.80s/it]
{'loss': 0.4496, 'learning_rate': 2.02179745862347e-06, 'epoch': 0.8}
+
80%|████████ | 9564/11952 [37:21<3:51:00, 5.80s/it]
80%|████████ | 9565/11952 [37:27<3:51:29, 5.82s/it]
{'loss': 0.4651, 'learning_rate': 2.0201639624860246e-06, 'epoch': 0.8}
+
80%|████████ | 9565/11952 [37:27<3:51:29, 5.82s/it]
80%|████████ | 9566/11952 [37:33<3:51:30, 5.82s/it]
{'loss': 0.4539, 'learning_rate': 2.0185310523545475e-06, 'epoch': 0.8}
+
80%|████████ | 9566/11952 [37:33<3:51:30, 5.82s/it]
80%|████████ | 9567/11952 [37:39<3:54:02, 5.89s/it]
{'loss': 0.4631, 'learning_rate': 2.0168987283489494e-06, 'epoch': 0.8}
+
80%|████████ | 9567/11952 [37:39<3:54:02, 5.89s/it]
80%|████████ | 9568/11952 [37:45<3:51:50, 5.83s/it]
{'loss': 0.4478, 'learning_rate': 2.0152669905891075e-06, 'epoch': 0.8}
+
80%|████████ | 9568/11952 [37:45<3:51:50, 5.83s/it]
80%|████████ | 9569/11952 [37:50<3:49:34, 5.78s/it]
{'loss': 0.4758, 'learning_rate': 2.013635839194844e-06, 'epoch': 0.8}
+
80%|████████ | 9569/11952 [37:50<3:49:34, 5.78s/it]
80%|████████ | 9570/11952 [37:56<3:48:53, 5.77s/it]
{'loss': 0.4786, 'learning_rate': 2.0120052742859497e-06, 'epoch': 0.8}
+
80%|████████ | 9570/11952 [37:56<3:48:53, 5.77s/it]
80%|████████ | 9571/11952 [38:02<3:51:13, 5.83s/it]
{'loss': 0.4593, 'learning_rate': 2.010375295982163e-06, 'epoch': 0.8}
+
80%|████████ | 9571/11952 [38:02<3:51:13, 5.83s/it]
80%|████████ | 9572/11952 [38:08<3:49:41, 5.79s/it]
{'loss': 0.466, 'learning_rate': 2.0087459044031843e-06, 'epoch': 0.8}
+
80%|████████ | 9572/11952 [38:08<3:49:41, 5.79s/it]
80%|████████ | 9573/11952 [38:14<3:49:34, 5.79s/it]
{'loss': 0.4639, 'learning_rate': 2.0071170996686674e-06, 'epoch': 0.8}
+
80%|████████ | 9573/11952 [38:14<3:49:34, 5.79s/it]
80%|████████ | 9574/11952 [38:20<3:51:46, 5.85s/it]
{'loss': 0.4788, 'learning_rate': 2.0054888818982254e-06, 'epoch': 0.8}
+
80%|████████ | 9574/11952 [38:20<3:51:46, 5.85s/it]
80%|████████ | 9575/11952 [38:25<3:48:54, 5.78s/it]
{'loss': 0.4549, 'learning_rate': 2.0038612512114285e-06, 'epoch': 0.8}
+
80%|████████ | 9575/11952 [38:25<3:48:54, 5.78s/it]
80%|████████ | 9576/11952 [38:31<3:48:57, 5.78s/it]
{'loss': 0.454, 'learning_rate': 2.0022342077278014e-06, 'epoch': 0.8}
+
80%|████████ | 9576/11952 [38:31<3:48:57, 5.78s/it]
80%|████████ | 9577/11952 [38:37<3:49:23, 5.80s/it]
{'loss': 0.4759, 'learning_rate': 2.00060775156683e-06, 'epoch': 0.8}
+
80%|████████ | 9577/11952 [38:37<3:49:23, 5.80s/it]
80%|████████ | 9578/11952 [38:42<3:47:46, 5.76s/it]
{'loss': 0.4794, 'learning_rate': 1.998981882847951e-06, 'epoch': 0.8}
+
80%|████████ | 9578/11952 [38:42<3:47:46, 5.76s/it]
80%|████████ | 9579/11952 [38:48<3:49:02, 5.79s/it]
{'loss': 0.4785, 'learning_rate': 1.9973566016905666e-06, 'epoch': 0.8}
+
80%|████████ | 9579/11952 [38:48<3:49:02, 5.79s/it]
80%|████████ | 9580/11952 [38:54<3:52:24, 5.88s/it]
{'loss': 0.4464, 'learning_rate': 1.995731908214028e-06, 'epoch': 0.8}
+
80%|████████ | 9580/11952 [38:54<3:52:24, 5.88s/it]
80%|████████ | 9581/11952 [39:00<3:52:09, 5.87s/it]
{'loss': 0.4696, 'learning_rate': 1.994107802537646e-06, 'epoch': 0.8}
+
80%|████████ | 9581/11952 [39:00<3:52:09, 5.87s/it]
80%|████████ | 9582/11952 [39:06<3:49:25, 5.81s/it]
{'loss': 0.4567, 'learning_rate': 1.9924842847806867e-06, 'epoch': 0.8}
+
80%|████████ | 9582/11952 [39:06<3:49:25, 5.81s/it]
80%|████████ | 9583/11952 [39:12<3:48:11, 5.78s/it]
{'loss': 0.4601, 'learning_rate': 1.9908613550623746e-06, 'epoch': 0.8}
+
80%|████████ | 9583/11952 [39:12<3:48:11, 5.78s/it]
80%|████████ | 9584/11952 [39:17<3:47:16, 5.76s/it]
{'loss': 0.4741, 'learning_rate': 1.9892390135018945e-06, 'epoch': 0.8}
+
80%|████████ | 9584/11952 [39:17<3:47:16, 5.76s/it]
80%|████████ | 9585/11952 [39:23<3:47:14, 5.76s/it]
{'loss': 0.4543, 'learning_rate': 1.987617260218382e-06, 'epoch': 0.8}
+
80%|████████ | 9585/11952 [39:23<3:47:14, 5.76s/it]
80%|████████ | 9586/11952 [39:29<3:54:21, 5.94s/it]
{'loss': 0.4632, 'learning_rate': 1.985996095330931e-06, 'epoch': 0.8}
+
80%|████████ | 9586/11952 [39:29<3:54:21, 5.94s/it]
80%|████████ | 9587/11952 [39:35<3:50:41, 5.85s/it]
{'loss': 0.4491, 'learning_rate': 1.984375518958592e-06, 'epoch': 0.8}
+
80%|████████ | 9587/11952 [39:35<3:50:41, 5.85s/it]
80%|████████ | 9588/11952 [39:41<3:53:44, 5.93s/it]
{'loss': 0.4767, 'learning_rate': 1.9827555312203785e-06, 'epoch': 0.8}
+
80%|████████ | 9588/11952 [39:41<3:53:44, 5.93s/it]
80%|████████ | 9589/11952 [39:47<3:52:54, 5.91s/it]
{'loss': 0.473, 'learning_rate': 1.9811361322352517e-06, 'epoch': 0.8}
+
80%|████████ | 9589/11952 [39:47<3:52:54, 5.91s/it]
80%|████████ | 9590/11952 [39:53<3:52:48, 5.91s/it]
{'loss': 0.4599, 'learning_rate': 1.9795173221221318e-06, 'epoch': 0.8}
+
80%|████████ | 9590/11952 [39:53<3:52:48, 5.91s/it]
80%|████████ | 9591/11952 [39:59<3:51:51, 5.89s/it]
{'loss': 0.482, 'learning_rate': 1.9778991009999036e-06, 'epoch': 0.8}
+
80%|████████ | 9591/11952 [39:59<3:51:51, 5.89s/it]
80%|████████ | 9592/11952 [40:05<3:51:07, 5.88s/it]
{'loss': 0.4809, 'learning_rate': 1.9762814689873987e-06, 'epoch': 0.8}
+
80%|████████ | 9592/11952 [40:05<3:51:07, 5.88s/it]
80%|████████ | 9593/11952 [40:11<3:53:23, 5.94s/it]
{'loss': 0.4695, 'learning_rate': 1.974664426203409e-06, 'epoch': 0.8}
+
80%|████████ | 9593/11952 [40:11<3:53:23, 5.94s/it]
80%|████████ | 9594/11952 [40:17<3:54:32, 5.97s/it]
{'loss': 0.4676, 'learning_rate': 1.973047972766684e-06, 'epoch': 0.8}
+
80%|████████ | 9594/11952 [40:17<3:54:32, 5.97s/it]
80%|████████ | 9595/11952 [40:23<3:53:51, 5.95s/it]
{'loss': 0.4593, 'learning_rate': 1.9714321087959296e-06, 'epoch': 0.8}
+
80%|████████ | 9595/11952 [40:23<3:53:51, 5.95s/it]
80%|████████ | 9596/11952 [40:29<3:54:22, 5.97s/it]
{'loss': 0.4615, 'learning_rate': 1.9698168344098056e-06, 'epoch': 0.8}
+
80%|████████ | 9596/11952 [40:29<3:54:22, 5.97s/it]
80%|████████ | 9597/11952 [40:35<3:57:49, 6.06s/it]
{'loss': 0.4768, 'learning_rate': 1.9682021497269357e-06, 'epoch': 0.8}
+
80%|████████ | 9597/11952 [40:35<3:57:49, 6.06s/it]
80%|████████ | 9598/11952 [40:41<3:54:12, 5.97s/it]
{'loss': 0.457, 'learning_rate': 1.9665880548658888e-06, 'epoch': 0.8}
+
80%|████████ | 9598/11952 [40:41<3:54:12, 5.97s/it]
80%|████████ | 9599/11952 [40:47<3:51:31, 5.90s/it]
{'loss': 0.4568, 'learning_rate': 1.9649745499452067e-06, 'epoch': 0.8}
+
80%|████████ | 9599/11952 [40:47<3:51:31, 5.90s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
80%|████████ | 9600/11952 [40:52<3:50:12, 5.87s/it]
{'loss': 0.4788, 'learning_rate': 1.9633616350833717e-06, 'epoch': 0.8}
+
80%|████████ | 9600/11952 [40:52<3:50:12, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
80%|████████ | 9601/11952 [41:22<8:33:13, 13.10s/it]
{'loss': 0.4911, 'learning_rate': 1.961749310398833e-06, 'epoch': 0.8}
+
80%|████████ | 9601/11952 [41:22<8:33:13, 13.10s/it]
80%|████████ | 9602/11952 [41:28<7:11:27, 11.02s/it]
{'loss': 0.4736, 'learning_rate': 1.9601375760099895e-06, 'epoch': 0.8}
+
80%|████████ | 9602/11952 [41:28<7:11:27, 11.02s/it]
80%|████████ | 9603/11952 [41:34<6:11:46, 9.50s/it]
{'loss': 0.464, 'learning_rate': 1.9585264320352003e-06, 'epoch': 0.8}
+
80%|████████ | 9603/11952 [41:34<6:11:46, 9.50s/it]
80%|████████ | 9604/11952 [41:40<5:31:26, 8.47s/it]
{'loss': 0.4649, 'learning_rate': 1.9569158785927867e-06, 'epoch': 0.8}
+
80%|████████ | 9604/11952 [41:40<5:31:26, 8.47s/it]
80%|████████ | 9605/11952 [41:46<4:58:15, 7.62s/it]
{'loss': 0.4484, 'learning_rate': 1.955305915801016e-06, 'epoch': 0.8}
+
80%|████████ | 9605/11952 [41:46<4:58:15, 7.62s/it]
80%|████████ | 9606/11952 [41:52<4:38:49, 7.13s/it]
{'loss': 0.4635, 'learning_rate': 1.9536965437781186e-06, 'epoch': 0.8}
+
80%|████████ | 9606/11952 [41:52<4:38:49, 7.13s/it]
80%|████████ | 9607/11952 [41:58<4:24:28, 6.77s/it]
{'loss': 0.4572, 'learning_rate': 1.9520877626422794e-06, 'epoch': 0.8}
+
80%|████████ | 9607/11952 [41:58<4:24:28, 6.77s/it]
80%|████████ | 9608/11952 [42:04<4:18:50, 6.63s/it]
{'loss': 0.4729, 'learning_rate': 1.95047957251164e-06, 'epoch': 0.8}
+
80%|████████ | 9608/11952 [42:04<4:18:50, 6.63s/it]
80%|████████ | 9609/11952 [42:10<4:09:46, 6.40s/it]
{'loss': 0.4615, 'learning_rate': 1.9488719735043018e-06, 'epoch': 0.8}
+
80%|████████ | 9609/11952 [42:10<4:09:46, 6.40s/it]
80%|████████ | 9610/11952 [42:16<4:04:40, 6.27s/it]
{'loss': 0.4654, 'learning_rate': 1.9472649657383157e-06, 'epoch': 0.8}
+
80%|████████ | 9610/11952 [42:16<4:04:40, 6.27s/it]
80%|████████ | 9611/11952 [42:22<3:58:22, 6.11s/it]
{'loss': 0.4707, 'learning_rate': 1.9456585493317004e-06, 'epoch': 0.8}
+
80%|████████ | 9611/11952 [42:22<3:58:22, 6.11s/it]
80%|████████ | 9612/11952 [42:28<3:53:44, 5.99s/it]
{'loss': 0.4773, 'learning_rate': 1.94405272440242e-06, 'epoch': 0.8}
+
80%|████████ | 9612/11952 [42:28<3:53:44, 5.99s/it]
80%|████████ | 9613/11952 [42:34<3:52:52, 5.97s/it]
{'loss': 0.4667, 'learning_rate': 1.942447491068401e-06, 'epoch': 0.8}
+
80%|████████ | 9613/11952 [42:34<3:52:52, 5.97s/it]
80%|████████ | 9614/11952 [42:39<3:51:15, 5.93s/it]
{'loss': 0.4603, 'learning_rate': 1.940842849447524e-06, 'epoch': 0.8}
+
80%|████████ | 9614/11952 [42:39<3:51:15, 5.93s/it]
80%|████████ | 9615/11952 [42:45<3:49:55, 5.90s/it]
{'loss': 0.4447, 'learning_rate': 1.9392387996576277e-06, 'epoch': 0.8}
+
80%|████████ | 9615/11952 [42:45<3:49:55, 5.90s/it]
80%|████████ | 9616/11952 [42:51<3:51:20, 5.94s/it]
{'loss': 0.4665, 'learning_rate': 1.937635341816506e-06, 'epoch': 0.8}
+
80%|████████ | 9616/11952 [42:51<3:51:20, 5.94s/it]
80%|████████ | 9617/11952 [42:57<3:48:55, 5.88s/it]
{'loss': 0.4667, 'learning_rate': 1.9360324760419093e-06, 'epoch': 0.8}
+
80%|████████ | 9617/11952 [42:57<3:48:55, 5.88s/it]WARNING: tokenization mismatch: 1 vs. 70. [[{'from': 'human', 'value': '\nWould this person be more likely to be a type a or b person?\nAnswer the question using a single word or phrase.'}, {'from': 'gpt', 'value': ''}]] (ignored)
+
80%|████████ | 9618/11952 [43:03<3:49:01, 5.89s/it]
{'loss': 0.454, 'learning_rate': 1.934430202451549e-06, 'epoch': 0.8}
+
80%|████████ | 9618/11952 [43:03<3:49:01, 5.89s/it]
80%|████████ | 9619/11952 [43:09<3:53:13, 6.00s/it]
{'loss': 0.4657, 'learning_rate': 1.9328285211630847e-06, 'epoch': 0.8}
+
80%|████████ | 9619/11952 [43:09<3:53:13, 6.00s/it]
80%|████████ | 9620/11952 [43:15<3:51:35, 5.96s/it]
{'loss': 0.4621, 'learning_rate': 1.9312274322941426e-06, 'epoch': 0.8}
+
80%|████████ | 9620/11952 [43:15<3:51:35, 5.96s/it]
80%|████████ | 9621/11952 [43:21<3:51:02, 5.95s/it]
{'loss': 0.457, 'learning_rate': 1.9296269359622977e-06, 'epoch': 0.8}
+
80%|████████ | 9621/11952 [43:21<3:51:02, 5.95s/it]
81%|████████ | 9622/11952 [43:27<3:47:32, 5.86s/it]
{'loss': 0.4572, 'learning_rate': 1.9280270322850836e-06, 'epoch': 0.81}
+
81%|████████ | 9622/11952 [43:27<3:47:32, 5.86s/it]
81%|████████ | 9623/11952 [43:32<3:46:57, 5.85s/it]
{'loss': 0.4614, 'learning_rate': 1.92642772137999e-06, 'epoch': 0.81}
+
81%|████████ | 9623/11952 [43:32<3:46:57, 5.85s/it]
81%|████████ | 9624/11952 [43:38<3:46:02, 5.83s/it]
{'loss': 0.4545, 'learning_rate': 1.9248290033644614e-06, 'epoch': 0.81}
+
81%|████████ | 9624/11952 [43:38<3:46:02, 5.83s/it]
81%|████████ | 9625/11952 [43:44<3:47:19, 5.86s/it]
{'loss': 0.4749, 'learning_rate': 1.9232308783559064e-06, 'epoch': 0.81}
+
81%|████████ | 9625/11952 [43:44<3:47:19, 5.86s/it]
81%|████████ | 9626/11952 [43:50<3:43:25, 5.76s/it]
{'loss': 0.4872, 'learning_rate': 1.9216333464716817e-06, 'epoch': 0.81}
+
81%|████████ | 9626/11952 [43:50<3:43:25, 5.76s/it]
81%|████████ | 9627/11952 [43:56<3:47:34, 5.87s/it]
{'loss': 0.4565, 'learning_rate': 1.9200364078291032e-06, 'epoch': 0.81}
+
81%|████████ | 9627/11952 [43:56<3:47:34, 5.87s/it]
81%|████████ | 9628/11952 [44:02<3:46:18, 5.84s/it]
{'loss': 0.4787, 'learning_rate': 1.9184400625454413e-06, 'epoch': 0.81}
+
81%|████████ | 9628/11952 [44:02<3:46:18, 5.84s/it]
81%|████████ | 9629/11952 [44:07<3:45:41, 5.83s/it]
{'loss': 0.4553, 'learning_rate': 1.916844310737931e-06, 'epoch': 0.81}
+
81%|████████ | 9629/11952 [44:07<3:45:41, 5.83s/it]
81%|████████ | 9630/11952 [44:13<3:45:46, 5.83s/it]
{'loss': 0.4542, 'learning_rate': 1.9152491525237504e-06, 'epoch': 0.81}
+
81%|████████ | 9630/11952 [44:13<3:45:46, 5.83s/it]
81%|████████ | 9631/11952 [44:19<3:48:05, 5.90s/it]
{'loss': 0.4756, 'learning_rate': 1.9136545880200484e-06, 'epoch': 0.81}
+
81%|████████ | 9631/11952 [44:19<3:48:05, 5.90s/it]
81%|████████ | 9632/11952 [44:25<3:45:41, 5.84s/it]
{'loss': 0.4579, 'learning_rate': 1.912060617343919e-06, 'epoch': 0.81}
+
81%|████████ | 9632/11952 [44:25<3:45:41, 5.84s/it]
81%|████████ | 9633/11952 [44:31<3:43:40, 5.79s/it]
{'loss': 0.4656, 'learning_rate': 1.910467240612419e-06, 'epoch': 0.81}
+
81%|████████ | 9633/11952 [44:31<3:43:40, 5.79s/it]
81%|████████ | 9634/11952 [44:36<3:43:28, 5.78s/it]
{'loss': 0.4556, 'learning_rate': 1.9088744579425567e-06, 'epoch': 0.81}
+
81%|████████ | 9634/11952 [44:36<3:43:28, 5.78s/it]
81%|████████ | 9635/11952 [44:42<3:42:30, 5.76s/it]
{'loss': 0.4717, 'learning_rate': 1.9072822694513016e-06, 'epoch': 0.81}
+
81%|████████ | 9635/11952 [44:42<3:42:30, 5.76s/it]
81%|████████ | 9636/11952 [44:48<3:42:12, 5.76s/it]
{'loss': 0.4633, 'learning_rate': 1.9056906752555759e-06, 'epoch': 0.81}
+
81%|████████ | 9636/11952 [44:48<3:42:12, 5.76s/it]
81%|████████ | 9637/11952 [44:54<3:44:11, 5.81s/it]
{'loss': 0.4566, 'learning_rate': 1.9040996754722574e-06, 'epoch': 0.81}
+
81%|████████ | 9637/11952 [44:54<3:44:11, 5.81s/it]
81%|████████ | 9638/11952 [45:00<3:44:31, 5.82s/it]
{'loss': 0.4552, 'learning_rate': 1.902509270218189e-06, 'epoch': 0.81}
+
81%|████████ | 9638/11952 [45:00<3:44:31, 5.82s/it]
81%|████████ | 9639/11952 [45:05<3:41:43, 5.75s/it]
{'loss': 0.4667, 'learning_rate': 1.9009194596101566e-06, 'epoch': 0.81}
+
81%|████████ | 9639/11952 [45:05<3:41:43, 5.75s/it]
81%|████████ | 9640/11952 [45:11<3:45:20, 5.85s/it]
{'loss': 0.4566, 'learning_rate': 1.8993302437649143e-06, 'epoch': 0.81}
+
81%|████████ | 9640/11952 [45:11<3:45:20, 5.85s/it]
81%|████████ | 9641/11952 [45:17<3:43:37, 5.81s/it]
{'loss': 0.4585, 'learning_rate': 1.8977416227991663e-06, 'epoch': 0.81}
+
81%|████████ | 9641/11952 [45:17<3:43:37, 5.81s/it]
81%|████████ | 9642/11952 [45:23<3:42:01, 5.77s/it]
{'loss': 0.4518, 'learning_rate': 1.896153596829574e-06, 'epoch': 0.81}
+
81%|████████ | 9642/11952 [45:23<3:42:01, 5.77s/it]
81%|████████ | 9643/11952 [45:29<3:49:58, 5.98s/it]
{'loss': 0.4677, 'learning_rate': 1.8945661659727555e-06, 'epoch': 0.81}
+
81%|████████ | 9643/11952 [45:29<3:49:58, 5.98s/it]
81%|████████ | 9644/11952 [45:35<3:49:45, 5.97s/it]
{'loss': 0.4731, 'learning_rate': 1.8929793303452814e-06, 'epoch': 0.81}
+
81%|████████ | 9644/11952 [45:35<3:49:45, 5.97s/it]
81%|████████ | 9645/11952 [45:41<3:50:49, 6.00s/it]
{'loss': 0.4661, 'learning_rate': 1.891393090063688e-06, 'epoch': 0.81}
+
81%|████████ | 9645/11952 [45:41<3:50:49, 6.00s/it]
81%|████████ | 9646/11952 [45:47<3:48:51, 5.95s/it]
{'loss': 0.4539, 'learning_rate': 1.8898074452444604e-06, 'epoch': 0.81}
+
81%|████████ | 9646/11952 [45:47<3:48:51, 5.95s/it]
81%|████████ | 9647/11952 [45:53<3:51:35, 6.03s/it]
{'loss': 0.4814, 'learning_rate': 1.8882223960040413e-06, 'epoch': 0.81}
+
81%|████████ | 9647/11952 [45:53<3:51:35, 6.03s/it]
81%|████████ | 9648/11952 [45:59<3:52:50, 6.06s/it]
{'loss': 0.4711, 'learning_rate': 1.8866379424588287e-06, 'epoch': 0.81}
+
81%|████████ | 9648/11952 [45:59<3:52:50, 6.06s/it]
81%|████████ | 9649/11952 [46:05<3:49:14, 5.97s/it]
{'loss': 0.4454, 'learning_rate': 1.8850540847251786e-06, 'epoch': 0.81}
+
81%|████████ | 9649/11952 [46:05<3:49:14, 5.97s/it]6 AutoResumeHook: Checking whether to suspend...
+71 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
81%|████████ | 9650/11952 [46:11<3:52:14, 6.05s/it]
{'loss': 0.4759, 'learning_rate': 1.8834708229194054e-06, 'epoch': 0.81}
+
81%|████████ | 9650/11952 [46:11<3:52:14, 6.05s/it]
81%|████████ | 9651/11952 [46:17<3:49:23, 5.98s/it]
{'loss': 0.4592, 'learning_rate': 1.8818881571577741e-06, 'epoch': 0.81}
+
81%|████████ | 9651/11952 [46:17<3:49:23, 5.98s/it]
81%|████████ | 9652/11952 [46:23<3:45:04, 5.87s/it]
{'loss': 0.4533, 'learning_rate': 1.8803060875565127e-06, 'epoch': 0.81}
+
81%|████████ | 9652/11952 [46:23<3:45:04, 5.87s/it]
81%|████████ | 9653/11952 [46:29<3:48:14, 5.96s/it]
{'loss': 0.484, 'learning_rate': 1.8787246142318006e-06, 'epoch': 0.81}
+
81%|████████ | 9653/11952 [46:29<3:48:14, 5.96s/it]
81%|████████ | 9654/11952 [46:35<3:46:39, 5.92s/it]
{'loss': 0.4713, 'learning_rate': 1.8771437372997736e-06, 'epoch': 0.81}
+
81%|████████ | 9654/11952 [46:35<3:46:39, 5.92s/it]
81%|████████ | 9655/11952 [46:41<3:50:52, 6.03s/it]
{'loss': 0.4474, 'learning_rate': 1.8755634568765246e-06, 'epoch': 0.81}
+
81%|████████ | 9655/11952 [46:41<3:50:52, 6.03s/it]
81%|████████ | 9656/11952 [46:47<3:46:32, 5.92s/it]
{'loss': 0.4372, 'learning_rate': 1.8739837730781029e-06, 'epoch': 0.81}
+
81%|████████ | 9656/11952 [46:47<3:46:32, 5.92s/it]
81%|████████ | 9657/11952 [46:52<3:43:45, 5.85s/it]
{'loss': 0.4562, 'learning_rate': 1.872404686020516e-06, 'epoch': 0.81}
+
81%|████████ | 9657/11952 [46:52<3:43:45, 5.85s/it]
81%|████████ | 9658/11952 [46:58<3:42:41, 5.82s/it]
{'loss': 0.4659, 'learning_rate': 1.8708261958197193e-06, 'epoch': 0.81}
+
81%|████████ | 9658/11952 [46:58<3:42:41, 5.82s/it]
81%|████████ | 9659/11952 [47:04<3:45:21, 5.90s/it]
{'loss': 0.4809, 'learning_rate': 1.8692483025916387e-06, 'epoch': 0.81}
+
81%|████████ | 9659/11952 [47:04<3:45:21, 5.90s/it]
81%|████████ | 9660/11952 [47:10<3:43:43, 5.86s/it]
{'loss': 0.4592, 'learning_rate': 1.8676710064521409e-06, 'epoch': 0.81}
+
81%|████████ | 9660/11952 [47:10<3:43:43, 5.86s/it]
81%|████████ | 9661/11952 [47:16<3:44:00, 5.87s/it]
{'loss': 0.4448, 'learning_rate': 1.8660943075170634e-06, 'epoch': 0.81}
+
81%|████████ | 9661/11952 [47:16<3:44:00, 5.87s/it]
81%|████████ | 9662/11952 [47:22<3:46:31, 5.94s/it]
{'loss': 0.4631, 'learning_rate': 1.864518205902187e-06, 'epoch': 0.81}
+
81%|████████ | 9662/11952 [47:22<3:46:31, 5.94s/it]
81%|████████ | 9663/11952 [47:28<3:47:54, 5.97s/it]
{'loss': 0.4671, 'learning_rate': 1.862942701723257e-06, 'epoch': 0.81}
+
81%|████████ | 9663/11952 [47:28<3:47:54, 5.97s/it]
81%|████████ | 9664/11952 [47:34<3:48:11, 5.98s/it]
{'loss': 0.4527, 'learning_rate': 1.8613677950959697e-06, 'epoch': 0.81}
+
81%|████████ | 9664/11952 [47:34<3:48:11, 5.98s/it]
81%|████████ | 9665/11952 [47:40<3:47:46, 5.98s/it]
{'loss': 0.4446, 'learning_rate': 1.8597934861359779e-06, 'epoch': 0.81}
+
81%|████████ | 9665/11952 [47:40<3:47:46, 5.98s/it]
81%|████████ | 9666/11952 [47:46<3:45:05, 5.91s/it]
{'loss': 0.4743, 'learning_rate': 1.858219774958897e-06, 'epoch': 0.81}
+
81%|████████ | 9666/11952 [47:46<3:45:05, 5.91s/it]
81%|████████ | 9667/11952 [47:51<3:41:56, 5.83s/it]
{'loss': 0.4744, 'learning_rate': 1.8566466616802914e-06, 'epoch': 0.81}
+
81%|████████ | 9667/11952 [47:51<3:41:56, 5.83s/it]
81%|████████ | 9668/11952 [47:57<3:40:36, 5.80s/it]
{'loss': 0.4457, 'learning_rate': 1.855074146415685e-06, 'epoch': 0.81}
+
81%|████████ | 9668/11952 [47:57<3:40:36, 5.80s/it]
81%|████████ | 9669/11952 [48:03<3:43:47, 5.88s/it]
{'loss': 0.4582, 'learning_rate': 1.8535022292805539e-06, 'epoch': 0.81}
+
81%|████████ | 9669/11952 [48:03<3:43:47, 5.88s/it]
81%|████████ | 9670/11952 [48:09<3:41:59, 5.84s/it]
{'loss': 0.4666, 'learning_rate': 1.851930910390337e-06, 'epoch': 0.81}
+
81%|████████ | 9670/11952 [48:09<3:41:59, 5.84s/it]
81%|████████ | 9671/11952 [48:15<3:42:42, 5.86s/it]
{'loss': 0.4709, 'learning_rate': 1.8503601898604207e-06, 'epoch': 0.81}
+
81%|████████ | 9671/11952 [48:15<3:42:42, 5.86s/it]
81%|████████ | 9672/11952 [48:21<3:44:02, 5.90s/it]
{'loss': 0.4568, 'learning_rate': 1.8487900678061588e-06, 'epoch': 0.81}
+
81%|████████ | 9672/11952 [48:21<3:44:02, 5.90s/it]
81%|████████ | 9673/11952 [48:27<3:50:19, 6.06s/it]
{'loss': 0.4638, 'learning_rate': 1.8472205443428504e-06, 'epoch': 0.81}
+
81%|████████ | 9673/11952 [48:27<3:50:19, 6.06s/it]
81%|████████ | 9674/11952 [48:33<3:48:38, 6.02s/it]
{'loss': 0.4657, 'learning_rate': 1.8456516195857543e-06, 'epoch': 0.81}
+
81%|████████ | 9674/11952 [48:33<3:48:38, 6.02s/it]
81%|████████ | 9675/11952 [48:39<3:45:03, 5.93s/it]
{'loss': 0.4578, 'learning_rate': 1.8440832936500875e-06, 'epoch': 0.81}
+
81%|████████ | 9675/11952 [48:39<3:45:03, 5.93s/it]
81%|████████ | 9676/11952 [48:45<3:44:34, 5.92s/it]
{'loss': 0.4629, 'learning_rate': 1.842515566651021e-06, 'epoch': 0.81}
+
81%|████████ | 9676/11952 [48:45<3:44:34, 5.92s/it]
81%|████████ | 9677/11952 [48:51<3:44:26, 5.92s/it]
{'loss': 0.4413, 'learning_rate': 1.8409484387036813e-06, 'epoch': 0.81}
+
81%|████████ | 9677/11952 [48:51<3:44:26, 5.92s/it]
81%|████████ | 9678/11952 [48:57<3:43:09, 5.89s/it]
{'loss': 0.4732, 'learning_rate': 1.8393819099231503e-06, 'epoch': 0.81}
+
81%|████████ | 9678/11952 [48:57<3:43:09, 5.89s/it]
81%|████████ | 9679/11952 [49:03<3:44:26, 5.92s/it]
{'loss': 0.4708, 'learning_rate': 1.837815980424471e-06, 'epoch': 0.81}
+
81%|████████ | 9679/11952 [49:03<3:44:26, 5.92s/it]
81%|████████ | 9680/11952 [49:09<3:44:29, 5.93s/it]
{'loss': 0.483, 'learning_rate': 1.8362506503226374e-06, 'epoch': 0.81}
+
81%|████████ | 9680/11952 [49:09<3:44:29, 5.93s/it]
81%|████████ | 9681/11952 [49:14<3:43:22, 5.90s/it]
{'loss': 0.4639, 'learning_rate': 1.8346859197325984e-06, 'epoch': 0.81}
+
81%|████████ | 9681/11952 [49:14<3:43:22, 5.90s/it]
81%|████████ | 9682/11952 [49:21<3:48:06, 6.03s/it]
{'loss': 0.4756, 'learning_rate': 1.8331217887692653e-06, 'epoch': 0.81}
+
81%|████████ | 9682/11952 [49:21<3:48:06, 6.03s/it]
81%|████████ | 9683/11952 [49:27<3:48:47, 6.05s/it]
{'loss': 0.4638, 'learning_rate': 1.8315582575475e-06, 'epoch': 0.81}
+
81%|████████ | 9683/11952 [49:27<3:48:47, 6.05s/it]
81%|████████ | 9684/11952 [49:33<3:49:06, 6.06s/it]
{'loss': 0.4641, 'learning_rate': 1.8299953261821202e-06, 'epoch': 0.81}
+
81%|████████ | 9684/11952 [49:33<3:49:06, 6.06s/it]
81%|████████ | 9685/11952 [49:39<3:48:56, 6.06s/it]
{'loss': 0.4882, 'learning_rate': 1.8284329947878999e-06, 'epoch': 0.81}
+
81%|████████ | 9685/11952 [49:39<3:48:56, 6.06s/it]
81%|████████ | 9686/11952 [49:45<3:46:20, 5.99s/it]
{'loss': 0.4464, 'learning_rate': 1.8268712634795749e-06, 'epoch': 0.81}
+
81%|████████ | 9686/11952 [49:45<3:46:20, 5.99s/it]
81%|████████ | 9687/11952 [49:51<3:44:13, 5.94s/it]
{'loss': 0.4501, 'learning_rate': 1.8253101323718303e-06, 'epoch': 0.81}
+
81%|████████ | 9687/11952 [49:51<3:44:13, 5.94s/it]
81%|████████ | 9688/11952 [49:56<3:41:00, 5.86s/it]
{'loss': 0.4642, 'learning_rate': 1.8237496015793077e-06, 'epoch': 0.81}
+
81%|████████ | 9688/11952 [49:56<3:41:00, 5.86s/it]
81%|████████ | 9689/11952 [50:02<3:41:39, 5.88s/it]
{'loss': 0.4618, 'learning_rate': 1.8221896712166075e-06, 'epoch': 0.81}
+
81%|████████ | 9689/11952 [50:02<3:41:39, 5.88s/it]
81%|████████ | 9690/11952 [50:08<3:42:39, 5.91s/it]
{'loss': 0.4548, 'learning_rate': 1.8206303413982806e-06, 'epoch': 0.81}
+
81%|████████ | 9690/11952 [50:08<3:42:39, 5.91s/it]
81%|████████ | 9691/11952 [50:14<3:38:42, 5.80s/it]
{'loss': 0.4565, 'learning_rate': 1.819071612238843e-06, 'epoch': 0.81}
+
81%|████████ | 9691/11952 [50:14<3:38:42, 5.80s/it]
81%|████████ | 9692/11952 [50:19<3:37:58, 5.79s/it]
{'loss': 0.4589, 'learning_rate': 1.8175134838527575e-06, 'epoch': 0.81}
+
81%|████████ | 9692/11952 [50:19<3:37:58, 5.79s/it]
81%|████████ | 9693/11952 [50:26<3:42:05, 5.90s/it]
{'loss': 0.4569, 'learning_rate': 1.8159559563544504e-06, 'epoch': 0.81}
+
81%|████████ | 9693/11952 [50:26<3:42:05, 5.90s/it]
81%|████████ | 9694/11952 [50:32<3:46:32, 6.02s/it]
{'loss': 0.4753, 'learning_rate': 1.814399029858298e-06, 'epoch': 0.81}
+
81%|████████ | 9694/11952 [50:32<3:46:32, 6.02s/it]
81%|████████ | 9695/11952 [50:38<3:46:59, 6.03s/it]
{'loss': 0.4571, 'learning_rate': 1.8128427044786345e-06, 'epoch': 0.81}
+
81%|████████ | 9695/11952 [50:38<3:46:59, 6.03s/it]
81%|████████ | 9696/11952 [50:44<3:43:04, 5.93s/it]
{'loss': 0.4539, 'learning_rate': 1.8112869803297494e-06, 'epoch': 0.81}
+
81%|████████ | 9696/11952 [50:44<3:43:04, 5.93s/it]
81%|████████ | 9697/11952 [50:50<3:43:43, 5.95s/it]
{'loss': 0.4814, 'learning_rate': 1.8097318575258894e-06, 'epoch': 0.81}
+
81%|████████ | 9697/11952 [50:50<3:43:43, 5.95s/it]
81%|████████ | 9698/11952 [50:56<3:43:28, 5.95s/it]
{'loss': 0.4669, 'learning_rate': 1.808177336181256e-06, 'epoch': 0.81}
+
81%|████████ | 9698/11952 [50:56<3:43:28, 5.95s/it]
81%|████████ | 9699/11952 [51:02<3:43:21, 5.95s/it]
{'loss': 0.4593, 'learning_rate': 1.8066234164100038e-06, 'epoch': 0.81}
+
81%|████████ | 9699/11952 [51:02<3:43:21, 5.95s/it]6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
81%|████████ | 9700/11952 [51:07<3:41:44, 5.91s/it]
{'loss': 0.4782, 'learning_rate': 1.8050700983262526e-06, 'epoch': 0.81}
+
81%|████████ | 9700/11952 [51:07<3:41:44, 5.91s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
81%|████████ | 9701/11952 [51:39<8:30:09, 13.60s/it]
{'loss': 0.4736, 'learning_rate': 1.8035173820440643e-06, 'epoch': 0.81}
+
81%|████████ | 9701/11952 [51:39<8:30:09, 13.60s/it]
81%|████████ | 9702/11952 [51:45<7:04:26, 11.32s/it]
{'loss': 0.4838, 'learning_rate': 1.8019652676774703e-06, 'epoch': 0.81}
+
81%|████████ | 9702/11952 [51:45<7:04:26, 11.32s/it]
81%|████████ | 9703/11952 [51:51<6:01:20, 9.64s/it]
{'loss': 0.4489, 'learning_rate': 1.8004137553404498e-06, 'epoch': 0.81}
+
81%|████████ | 9703/11952 [51:51<6:01:20, 9.64s/it]
81%|████████ | 9704/11952 [51:57<5:22:13, 8.60s/it]
{'loss': 0.4896, 'learning_rate': 1.798862845146938e-06, 'epoch': 0.81}
+
81%|████████ | 9704/11952 [51:57<5:22:13, 8.60s/it]
81%|████████ | 9705/11952 [52:03<4:52:55, 7.82s/it]
{'loss': 0.4669, 'learning_rate': 1.797312537210827e-06, 'epoch': 0.81}
+
81%|████████ | 9705/11952 [52:03<4:52:55, 7.82s/it]
81%|████████ | 9706/11952 [52:09<4:32:12, 7.27s/it]
{'loss': 0.4614, 'learning_rate': 1.795762831645964e-06, 'epoch': 0.81}
+
81%|████████ | 9706/11952 [52:09<4:32:12, 7.27s/it]
81%|████████ | 9707/11952 [52:15<4:19:42, 6.94s/it]
{'loss': 0.4606, 'learning_rate': 1.7942137285661576e-06, 'epoch': 0.81}
+
81%|████████ | 9707/11952 [52:15<4:19:42, 6.94s/it]
81%|████████ | 9708/11952 [52:21<4:09:52, 6.68s/it]
{'loss': 0.4639, 'learning_rate': 1.7926652280851642e-06, 'epoch': 0.81}
+
81%|████████ | 9708/11952 [52:21<4:09:52, 6.68s/it]
81%|████████ | 9709/11952 [52:27<3:58:49, 6.39s/it]
{'loss': 0.4593, 'learning_rate': 1.7911173303166985e-06, 'epoch': 0.81}
+
81%|████████ | 9709/11952 [52:27<3:58:49, 6.39s/it]
81%|████████ | 9710/11952 [52:33<3:57:18, 6.35s/it]
{'loss': 0.4639, 'learning_rate': 1.789570035374434e-06, 'epoch': 0.81}
+
81%|████████ | 9710/11952 [52:33<3:57:18, 6.35s/it]
81%|████████▏ | 9711/11952 [52:39<3:51:09, 6.19s/it]
{'loss': 0.4737, 'learning_rate': 1.7880233433719929e-06, 'epoch': 0.81}
+
81%|████████▏ | 9711/11952 [52:39<3:51:09, 6.19s/it]
81%|████████▏ | 9712/11952 [52:45<3:50:34, 6.18s/it]
{'loss': 0.4641, 'learning_rate': 1.7864772544229626e-06, 'epoch': 0.81}
+
81%|████████▏ | 9712/11952 [52:45<3:50:34, 6.18s/it]
81%|████████▏ | 9713/11952 [52:51<3:48:00, 6.11s/it]
{'loss': 0.4718, 'learning_rate': 1.7849317686408817e-06, 'epoch': 0.81}
+
81%|████████▏ | 9713/11952 [52:51<3:48:00, 6.11s/it]
81%|████████▏ | 9714/11952 [52:57<3:42:44, 5.97s/it]
{'loss': 0.4658, 'learning_rate': 1.7833868861392423e-06, 'epoch': 0.81}
+
81%|████████▏ | 9714/11952 [52:57<3:42:44, 5.97s/it]
81%|████████▏ | 9715/11952 [53:02<3:41:06, 5.93s/it]
{'loss': 0.4595, 'learning_rate': 1.7818426070314953e-06, 'epoch': 0.81}
+
81%|████████▏ | 9715/11952 [53:02<3:41:06, 5.93s/it]
81%|████████▏ | 9716/11952 [53:08<3:40:53, 5.93s/it]
{'loss': 0.4852, 'learning_rate': 1.7802989314310449e-06, 'epoch': 0.81}
+
81%|████████▏ | 9716/11952 [53:08<3:40:53, 5.93s/it]
81%|████████▏ | 9717/11952 [53:14<3:38:59, 5.88s/it]
{'loss': 0.4482, 'learning_rate': 1.7787558594512533e-06, 'epoch': 0.81}
+
81%|████████▏ | 9717/11952 [53:14<3:38:59, 5.88s/it]
81%|████████▏ | 9718/11952 [53:20<3:38:28, 5.87s/it]
{'loss': 0.4569, 'learning_rate': 1.7772133912054367e-06, 'epoch': 0.81}
+
81%|████████▏ | 9718/11952 [53:20<3:38:28, 5.87s/it]
81%|████████▏ | 9719/11952 [53:26<3:40:04, 5.91s/it]
{'loss': 0.4792, 'learning_rate': 1.7756715268068635e-06, 'epoch': 0.81}
+
81%|████████▏ | 9719/11952 [53:26<3:40:04, 5.91s/it]
81%|████████▏ | 9720/11952 [53:32<3:39:30, 5.90s/it]
{'loss': 0.4654, 'learning_rate': 1.7741302663687697e-06, 'epoch': 0.81}
+
81%|████████▏ | 9720/11952 [53:32<3:39:30, 5.90s/it]
81%|████████▏ | 9721/11952 [53:37<3:36:37, 5.83s/it]
{'loss': 0.4532, 'learning_rate': 1.7725896100043349e-06, 'epoch': 0.81}
+
81%|████████▏ | 9721/11952 [53:37<3:36:37, 5.83s/it]
81%|████████▏ | 9722/11952 [53:44<3:39:14, 5.90s/it]
{'loss': 0.4619, 'learning_rate': 1.7710495578266963e-06, 'epoch': 0.81}
+
81%|████████▏ | 9722/11952 [53:44<3:39:14, 5.90s/it]
81%|████████▏ | 9723/11952 [53:49<3:38:49, 5.89s/it]
{'loss': 0.4695, 'learning_rate': 1.7695101099489542e-06, 'epoch': 0.81}
+
81%|████████▏ | 9723/11952 [53:49<3:38:49, 5.89s/it]
81%|████████▏ | 9724/11952 [53:56<3:41:09, 5.96s/it]
{'loss': 0.465, 'learning_rate': 1.7679712664841554e-06, 'epoch': 0.81}
+
81%|████████▏ | 9724/11952 [53:56<3:41:09, 5.96s/it]
81%|████████▏ | 9725/11952 [54:01<3:39:20, 5.91s/it]
{'loss': 0.4712, 'learning_rate': 1.766433027545308e-06, 'epoch': 0.81}
+
81%|████████▏ | 9725/11952 [54:01<3:39:20, 5.91s/it]
81%|████████▏ | 9726/11952 [54:07<3:38:00, 5.88s/it]
{'loss': 0.4926, 'learning_rate': 1.7648953932453706e-06, 'epoch': 0.81}
+
81%|████████▏ | 9726/11952 [54:07<3:38:00, 5.88s/it]
81%|████████▏ | 9727/11952 [54:13<3:37:35, 5.87s/it]
{'loss': 0.4681, 'learning_rate': 1.763358363697265e-06, 'epoch': 0.81}
+
81%|████████▏ | 9727/11952 [54:13<3:37:35, 5.87s/it]
81%|████████▏ | 9728/11952 [54:19<3:40:22, 5.95s/it]
{'loss': 0.4721, 'learning_rate': 1.7618219390138635e-06, 'epoch': 0.81}
+
81%|████████▏ | 9728/11952 [54:19<3:40:22, 5.95s/it]
81%|████████▏ | 9729/11952 [54:25<3:36:07, 5.83s/it]
{'loss': 0.4555, 'learning_rate': 1.7602861193079922e-06, 'epoch': 0.81}
+
81%|████████▏ | 9729/11952 [54:25<3:36:07, 5.83s/it]
81%|████████▏ | 9730/11952 [54:30<3:34:06, 5.78s/it]
{'loss': 0.4666, 'learning_rate': 1.7587509046924378e-06, 'epoch': 0.81}
+
81%|████████▏ | 9730/11952 [54:30<3:34:06, 5.78s/it]
81%|████████▏ | 9731/11952 [54:36<3:33:06, 5.76s/it]
{'loss': 0.4645, 'learning_rate': 1.7572162952799366e-06, 'epoch': 0.81}
+
81%|████████▏ | 9731/11952 [54:36<3:33:06, 5.76s/it]
81%|████████▏ | 9732/11952 [54:42<3:33:39, 5.77s/it]
{'loss': 0.4613, 'learning_rate': 1.7556822911831882e-06, 'epoch': 0.81}
+
81%|████████▏ | 9732/11952 [54:42<3:33:39, 5.77s/it]
81%|████████▏ | 9733/11952 [54:48<3:33:38, 5.78s/it]
{'loss': 0.4739, 'learning_rate': 1.7541488925148397e-06, 'epoch': 0.81}
+
81%|████████▏ | 9733/11952 [54:48<3:33:38, 5.78s/it]
81%|████████▏ | 9734/11952 [54:53<3:34:17, 5.80s/it]
{'loss': 0.455, 'learning_rate': 1.752616099387502e-06, 'epoch': 0.81}
+
81%|████████▏ | 9734/11952 [54:53<3:34:17, 5.80s/it]
81%|████████▏ | 9735/11952 [54:59<3:35:35, 5.83s/it]
{'loss': 0.4624, 'learning_rate': 1.7510839119137347e-06, 'epoch': 0.81}
+
81%|████████▏ | 9735/11952 [54:59<3:35:35, 5.83s/it]
81%|████████▏ | 9736/11952 [55:05<3:33:49, 5.79s/it]
{'loss': 0.4691, 'learning_rate': 1.7495523302060546e-06, 'epoch': 0.81}
+
81%|████████▏ | 9736/11952 [55:05<3:33:49, 5.79s/it]
81%|████████▏ | 9737/11952 [55:11<3:35:25, 5.84s/it]
{'loss': 0.4729, 'learning_rate': 1.7480213543769343e-06, 'epoch': 0.81}
+
81%|████████▏ | 9737/11952 [55:11<3:35:25, 5.84s/it]
81%|████████▏ | 9738/11952 [55:17<3:36:46, 5.87s/it]
{'loss': 0.4682, 'learning_rate': 1.7464909845388045e-06, 'epoch': 0.81}
+
81%|████████▏ | 9738/11952 [55:17<3:36:46, 5.87s/it]
81%|████████▏ | 9739/11952 [55:23<3:37:28, 5.90s/it]
{'loss': 0.4588, 'learning_rate': 1.7449612208040479e-06, 'epoch': 0.81}
+
81%|████████▏ | 9739/11952 [55:23<3:37:28, 5.90s/it]
81%|████████▏ | 9740/11952 [55:29<3:37:21, 5.90s/it]
{'loss': 0.464, 'learning_rate': 1.743432063285001e-06, 'epoch': 0.81}
+
81%|████████▏ | 9740/11952 [55:29<3:37:21, 5.90s/it]
82%|████████▏ | 9741/11952 [55:35<3:36:49, 5.88s/it]
{'loss': 0.4633, 'learning_rate': 1.7419035120939642e-06, 'epoch': 0.81}
+
82%|████████▏ | 9741/11952 [55:35<3:36:49, 5.88s/it]
82%|████████▏ | 9742/11952 [55:41<3:37:00, 5.89s/it]
{'loss': 0.4697, 'learning_rate': 1.740375567343182e-06, 'epoch': 0.82}
+
82%|████████▏ | 9742/11952 [55:41<3:37:00, 5.89s/it]
82%|████████▏ | 9743/11952 [55:46<3:34:49, 5.83s/it]
{'loss': 0.4564, 'learning_rate': 1.7388482291448684e-06, 'epoch': 0.82}
+
82%|████████▏ | 9743/11952 [55:46<3:34:49, 5.83s/it]
82%|████████▏ | 9744/11952 [55:52<3:31:36, 5.75s/it]
{'loss': 0.4541, 'learning_rate': 1.7373214976111786e-06, 'epoch': 0.82}
+
82%|████████▏ | 9744/11952 [55:52<3:31:36, 5.75s/it]
82%|████████▏ | 9745/11952 [55:58<3:31:29, 5.75s/it]
{'loss': 0.4673, 'learning_rate': 1.735795372854231e-06, 'epoch': 0.82}
+
82%|████████▏ | 9745/11952 [55:58<3:31:29, 5.75s/it]
82%|████████▏ | 9746/11952 [56:04<3:34:36, 5.84s/it]
{'loss': 0.4842, 'learning_rate': 1.7342698549860958e-06, 'epoch': 0.82}
+
82%|████████▏ | 9746/11952 [56:04<3:34:36, 5.84s/it]
82%|████████▏ | 9747/11952 [56:09<3:34:12, 5.83s/it]
{'loss': 0.459, 'learning_rate': 1.732744944118805e-06, 'epoch': 0.82}
+
82%|████████▏ | 9747/11952 [56:09<3:34:12, 5.83s/it]
82%|████████▏ | 9748/11952 [56:15<3:34:11, 5.83s/it]
{'loss': 0.4632, 'learning_rate': 1.7312206403643395e-06, 'epoch': 0.82}
+
82%|████████▏ | 9748/11952 [56:15<3:34:11, 5.83s/it]
82%|████████▏ | 9749/11952 [56:21<3:33:51, 5.82s/it]
{'loss': 0.4745, 'learning_rate': 1.7296969438346378e-06, 'epoch': 0.82}
+
82%|████████▏ | 9749/11952 [56:21<3:33:51, 5.82s/it]4 2AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
82%|████████▏ | 9750/11952 [56:27<3:35:07, 5.86s/it]
{'loss': 0.4645, 'learning_rate': 1.7281738546415938e-06, 'epoch': 0.82}
+
82%|████████▏ | 9750/11952 [56:27<3:35:07, 5.86s/it]
82%|████████▏ | 9751/11952 [56:33<3:40:17, 6.01s/it]
{'loss': 0.4611, 'learning_rate': 1.726651372897057e-06, 'epoch': 0.82}
+
82%|████████▏ | 9751/11952 [56:33<3:40:17, 6.01s/it]
82%|████████▏ | 9752/11952 [56:40<3:42:57, 6.08s/it]
{'loss': 0.4632, 'learning_rate': 1.7251294987128287e-06, 'epoch': 0.82}
+
82%|████████▏ | 9752/11952 [56:40<3:42:57, 6.08s/it]
82%|████████▏ | 9753/11952 [56:46<3:43:28, 6.10s/it]
{'loss': 0.4493, 'learning_rate': 1.723608232200673e-06, 'epoch': 0.82}
+
82%|████████▏ | 9753/11952 [56:46<3:43:28, 6.10s/it]
82%|████████▏ | 9754/11952 [56:52<3:40:11, 6.01s/it]
{'loss': 0.4455, 'learning_rate': 1.7220875734723063e-06, 'epoch': 0.82}
+
82%|████████▏ | 9754/11952 [56:52<3:40:11, 6.01s/it]
82%|████████▏ | 9755/11952 [56:58<3:39:50, 6.00s/it]
{'loss': 0.4785, 'learning_rate': 1.720567522639398e-06, 'epoch': 0.82}
+
82%|████████▏ | 9755/11952 [56:58<3:39:50, 6.00s/it]
82%|████████▏ | 9756/11952 [57:03<3:36:41, 5.92s/it]
{'loss': 0.4574, 'learning_rate': 1.7190480798135745e-06, 'epoch': 0.82}
+
82%|████████▏ | 9756/11952 [57:03<3:36:41, 5.92s/it]
82%|████████▏ | 9757/11952 [57:10<3:41:54, 6.07s/it]
{'loss': 0.4784, 'learning_rate': 1.7175292451064174e-06, 'epoch': 0.82}
+
82%|████████▏ | 9757/11952 [57:10<3:41:54, 6.07s/it]
82%|████████▏ | 9758/11952 [57:15<3:38:24, 5.97s/it]
{'loss': 0.4608, 'learning_rate': 1.716011018629462e-06, 'epoch': 0.82}
+
82%|████████▏ | 9758/11952 [57:15<3:38:24, 5.97s/it]
82%|████████▏ | 9759/11952 [57:21<3:38:34, 5.98s/it]
{'loss': 0.4531, 'learning_rate': 1.7144934004942027e-06, 'epoch': 0.82}
+
82%|████████▏ | 9759/11952 [57:21<3:38:34, 5.98s/it]
82%|████████▏ | 9760/11952 [57:27<3:36:27, 5.92s/it]
{'loss': 0.4734, 'learning_rate': 1.7129763908120823e-06, 'epoch': 0.82}
+
82%|████████▏ | 9760/11952 [57:27<3:36:27, 5.92s/it]
82%|████████▏ | 9761/11952 [57:33<3:31:35, 5.79s/it]
{'loss': 0.4574, 'learning_rate': 1.7114599896945105e-06, 'epoch': 0.82}
+
82%|████████▏ | 9761/11952 [57:33<3:31:35, 5.79s/it]
82%|████████▏ | 9762/11952 [57:38<3:30:57, 5.78s/it]
{'loss': 0.4479, 'learning_rate': 1.709944197252843e-06, 'epoch': 0.82}
+
82%|████████▏ | 9762/11952 [57:38<3:30:57, 5.78s/it]
82%|████████▏ | 9763/11952 [57:44<3:28:50, 5.72s/it]
{'loss': 0.4544, 'learning_rate': 1.7084290135983895e-06, 'epoch': 0.82}
+
82%|████████▏ | 9763/11952 [57:44<3:28:50, 5.72s/it]
82%|████████▏ | 9764/11952 [57:50<3:33:42, 5.86s/it]
{'loss': 0.4866, 'learning_rate': 1.7069144388424253e-06, 'epoch': 0.82}
+
82%|████████▏ | 9764/11952 [57:50<3:33:42, 5.86s/it]
82%|████████▏ | 9765/11952 [57:56<3:35:02, 5.90s/it]
{'loss': 0.4746, 'learning_rate': 1.7054004730961704e-06, 'epoch': 0.82}
+
82%|████████▏ | 9765/11952 [57:56<3:35:02, 5.90s/it]
82%|████████▏ | 9766/11952 [58:02<3:34:32, 5.89s/it]
{'loss': 0.4562, 'learning_rate': 1.7038871164708059e-06, 'epoch': 0.82}
+
82%|████████▏ | 9766/11952 [58:02<3:34:32, 5.89s/it]
82%|████████▏ | 9767/11952 [58:08<3:35:17, 5.91s/it]
{'loss': 0.4627, 'learning_rate': 1.7023743690774619e-06, 'epoch': 0.82}
+
82%|████████▏ | 9767/11952 [58:08<3:35:17, 5.91s/it]
82%|████████▏ | 9768/11952 [58:14<3:34:23, 5.89s/it]
{'loss': 0.4512, 'learning_rate': 1.7008622310272349e-06, 'epoch': 0.82}
+
82%|████████▏ | 9768/11952 [58:14<3:34:23, 5.89s/it]
82%|████████▏ | 9769/11952 [58:20<3:31:24, 5.81s/it]
{'loss': 0.4584, 'learning_rate': 1.6993507024311661e-06, 'epoch': 0.82}
+
82%|████████▏ | 9769/11952 [58:20<3:31:24, 5.81s/it]
82%|████████▏ | 9770/11952 [58:25<3:29:12, 5.75s/it]
{'loss': 0.4578, 'learning_rate': 1.697839783400258e-06, 'epoch': 0.82}
+
82%|████████▏ | 9770/11952 [58:25<3:29:12, 5.75s/it]
82%|████████▏ | 9771/11952 [58:31<3:30:56, 5.80s/it]
{'loss': 0.4818, 'learning_rate': 1.6963294740454638e-06, 'epoch': 0.82}
+
82%|████████▏ | 9771/11952 [58:31<3:30:56, 5.80s/it]
82%|████████▏ | 9772/11952 [58:37<3:31:58, 5.83s/it]
{'loss': 0.4753, 'learning_rate': 1.694819774477694e-06, 'epoch': 0.82}
+
82%|████████▏ | 9772/11952 [58:37<3:31:58, 5.83s/it]
82%|████████▏ | 9773/11952 [58:43<3:33:23, 5.88s/it]
{'loss': 0.4678, 'learning_rate': 1.6933106848078174e-06, 'epoch': 0.82}
+
82%|████████▏ | 9773/11952 [58:43<3:33:23, 5.88s/it]
82%|████████▏ | 9774/11952 [58:49<3:31:29, 5.83s/it]
{'loss': 0.4589, 'learning_rate': 1.691802205146652e-06, 'epoch': 0.82}
+
82%|████████▏ | 9774/11952 [58:49<3:31:29, 5.83s/it]
82%|████████▏ | 9775/11952 [58:54<3:30:16, 5.80s/it]
{'loss': 0.4672, 'learning_rate': 1.6902943356049796e-06, 'epoch': 0.82}
+
82%|████████▏ | 9775/11952 [58:54<3:30:16, 5.80s/it]
82%|████████▏ | 9776/11952 [59:00<3:30:54, 5.82s/it]
{'loss': 0.4603, 'learning_rate': 1.6887870762935276e-06, 'epoch': 0.82}
+
82%|████████▏ | 9776/11952 [59:00<3:30:54, 5.82s/it]
82%|████████▏ | 9777/11952 [59:06<3:35:06, 5.93s/it]
{'loss': 0.4586, 'learning_rate': 1.6872804273229838e-06, 'epoch': 0.82}
+
82%|████████▏ | 9777/11952 [59:06<3:35:06, 5.93s/it]
82%|████████▏ | 9778/11952 [59:12<3:33:41, 5.90s/it]
{'loss': 0.4551, 'learning_rate': 1.6857743888039902e-06, 'epoch': 0.82}
+
82%|████████▏ | 9778/11952 [59:12<3:33:41, 5.90s/it]
82%|████████▏ | 9779/11952 [59:18<3:34:14, 5.92s/it]
{'loss': 0.4649, 'learning_rate': 1.6842689608471451e-06, 'epoch': 0.82}
+
82%|████████▏ | 9779/11952 [59:18<3:34:14, 5.92s/it]
82%|████████▏ | 9780/11952 [59:24<3:36:45, 5.99s/it]
{'loss': 0.4798, 'learning_rate': 1.6827641435629983e-06, 'epoch': 0.82}
+
82%|████████▏ | 9780/11952 [59:24<3:36:45, 5.99s/it]
82%|████████▏ | 9781/11952 [59:30<3:35:14, 5.95s/it]
{'loss': 0.4601, 'learning_rate': 1.6812599370620574e-06, 'epoch': 0.82}
+
82%|████████▏ | 9781/11952 [59:30<3:35:14, 5.95s/it]
82%|████████▏ | 9782/11952 [59:36<3:32:49, 5.88s/it]
{'loss': 0.4397, 'learning_rate': 1.679756341454788e-06, 'epoch': 0.82}
+
82%|████████▏ | 9782/11952 [59:36<3:32:49, 5.88s/it]
82%|████████▏ | 9783/11952 [59:42<3:33:39, 5.91s/it]
{'loss': 0.4517, 'learning_rate': 1.6782533568516047e-06, 'epoch': 0.82}
+
82%|████████▏ | 9783/11952 [59:42<3:33:39, 5.91s/it]
82%|████████▏ | 9784/11952 [59:48<3:36:34, 5.99s/it]
{'loss': 0.4718, 'learning_rate': 1.6767509833628847e-06, 'epoch': 0.82}
+
82%|████████▏ | 9784/11952 [59:48<3:36:34, 5.99s/it]
82%|████████▏ | 9785/11952 [59:54<3:34:35, 5.94s/it]
{'loss': 0.4713, 'learning_rate': 1.6752492210989523e-06, 'epoch': 0.82}
+
82%|████████▏ | 9785/11952 [59:54<3:34:35, 5.94s/it]
82%|████████▏ | 9786/11952 [1:00:00<3:33:01, 5.90s/it]
{'loss': 0.4593, 'learning_rate': 1.6737480701700936e-06, 'epoch': 0.82}
+
82%|████████▏ | 9786/11952 [1:00:00<3:33:01, 5.90s/it]
82%|████████▏ | 9787/11952 [1:00:06<3:35:31, 5.97s/it]
{'loss': 0.4871, 'learning_rate': 1.6722475306865415e-06, 'epoch': 0.82}
+
82%|████████▏ | 9787/11952 [1:00:06<3:35:31, 5.97s/it]
82%|████████▏ | 9788/11952 [1:00:12<3:34:24, 5.94s/it]
{'loss': 0.4819, 'learning_rate': 1.6707476027584956e-06, 'epoch': 0.82}
+
82%|████████▏ | 9788/11952 [1:00:12<3:34:24, 5.94s/it]
82%|████████▏ | 9789/11952 [1:00:18<3:35:20, 5.97s/it]
{'loss': 0.4736, 'learning_rate': 1.6692482864961024e-06, 'epoch': 0.82}
+
82%|████████▏ | 9789/11952 [1:00:18<3:35:20, 5.97s/it]
82%|████████▏ | 9790/11952 [1:00:23<3:31:38, 5.87s/it]
{'loss': 0.4608, 'learning_rate': 1.6677495820094635e-06, 'epoch': 0.82}
+
82%|████████▏ | 9790/11952 [1:00:23<3:31:38, 5.87s/it]
82%|████████▏ | 9791/11952 [1:00:29<3:33:06, 5.92s/it]
{'loss': 0.4389, 'learning_rate': 1.6662514894086402e-06, 'epoch': 0.82}
+
82%|████████▏ | 9791/11952 [1:00:29<3:33:06, 5.92s/it]
82%|████████▏ | 9792/11952 [1:00:36<3:36:39, 6.02s/it]
{'loss': 0.4748, 'learning_rate': 1.664754008803644e-06, 'epoch': 0.82}
+
82%|████████▏ | 9792/11952 [1:00:36<3:36:39, 6.02s/it]
82%|████████▏ | 9793/11952 [1:00:42<3:34:47, 5.97s/it]
{'loss': 0.4592, 'learning_rate': 1.6632571403044429e-06, 'epoch': 0.82}
+
82%|████████▏ | 9793/11952 [1:00:42<3:34:47, 5.97s/it]
82%|████████▏ | 9794/11952 [1:00:47<3:33:27, 5.94s/it]
{'loss': 0.4609, 'learning_rate': 1.6617608840209642e-06, 'epoch': 0.82}
+
82%|████████▏ | 9794/11952 [1:00:47<3:33:27, 5.94s/it]
82%|████████▏ | 9795/11952 [1:00:53<3:32:13, 5.90s/it]
{'loss': 0.4567, 'learning_rate': 1.6602652400630825e-06, 'epoch': 0.82}
+
82%|████████▏ | 9795/11952 [1:00:53<3:32:13, 5.90s/it]
82%|████████▏ | 9796/11952 [1:00:59<3:31:42, 5.89s/it]
{'loss': 0.5012, 'learning_rate': 1.6587702085406366e-06, 'epoch': 0.82}
+
82%|████████▏ | 9796/11952 [1:00:59<3:31:42, 5.89s/it]
82%|████████▏ | 9797/11952 [1:01:05<3:30:28, 5.86s/it]
{'loss': 0.4571, 'learning_rate': 1.6572757895634117e-06, 'epoch': 0.82}
+
82%|████████▏ | 9797/11952 [1:01:05<3:30:28, 5.86s/it]
82%|████████▏ | 9798/11952 [1:01:11<3:28:56, 5.82s/it]
{'loss': 0.4843, 'learning_rate': 1.6557819832411537e-06, 'epoch': 0.82}
+
82%|████████▏ | 9798/11952 [1:01:11<3:28:56, 5.82s/it]
82%|████████▏ | 9799/11952 [1:01:17<3:29:25, 5.84s/it]
{'loss': 0.4747, 'learning_rate': 1.6542887896835614e-06, 'epoch': 0.82}
+
82%|████████▏ | 9799/11952 [1:01:17<3:29:25, 5.84s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
82%|████████▏ | 9800/11952 [1:01:23<3:32:29, 5.92s/it]
{'loss': 0.4576, 'learning_rate': 1.652796209000287e-06, 'epoch': 0.82}
+
82%|████████▏ | 9800/11952 [1:01:23<3:32:29, 5.92s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
82%|████████▏ | 9801/11952 [1:01:52<7:39:23, 12.81s/it]
{'loss': 0.4586, 'learning_rate': 1.6513042413009383e-06, 'epoch': 0.82}
+
82%|████████▏ | 9801/11952 [1:01:52<7:39:23, 12.81s/it]
82%|████████▏ | 9802/11952 [1:01:58<6:25:18, 10.75s/it]
{'loss': 0.4844, 'learning_rate': 1.6498128866950835e-06, 'epoch': 0.82}
+
82%|████████▏ | 9802/11952 [1:01:58<6:25:18, 10.75s/it]
82%|████████▏ | 9803/11952 [1:02:03<5:33:13, 9.30s/it]
{'loss': 0.4594, 'learning_rate': 1.6483221452922394e-06, 'epoch': 0.82}
+
82%|████████▏ | 9803/11952 [1:02:03<5:33:13, 9.30s/it]
82%|████████▏ | 9804/11952 [1:02:09<4:53:31, 8.20s/it]
{'loss': 0.4692, 'learning_rate': 1.646832017201877e-06, 'epoch': 0.82}
+
82%|████████▏ | 9804/11952 [1:02:09<4:53:31, 8.20s/it]
82%|████████▏ | 9805/11952 [1:02:15<4:28:08, 7.49s/it]
{'loss': 0.4718, 'learning_rate': 1.6453425025334302e-06, 'epoch': 0.82}
+
82%|████████▏ | 9805/11952 [1:02:15<4:28:08, 7.49s/it]
82%|████████▏ | 9806/11952 [1:02:21<4:08:19, 6.94s/it]
{'loss': 0.4611, 'learning_rate': 1.6438536013962814e-06, 'epoch': 0.82}
+
82%|████████▏ | 9806/11952 [1:02:21<4:08:19, 6.94s/it]
82%|████████▏ | 9807/11952 [1:02:26<3:54:24, 6.56s/it]
{'loss': 0.4661, 'learning_rate': 1.6423653138997675e-06, 'epoch': 0.82}
+
82%|████████▏ | 9807/11952 [1:02:26<3:54:24, 6.56s/it]
82%|████████▏ | 9808/11952 [1:02:32<3:46:24, 6.34s/it]
{'loss': 0.4553, 'learning_rate': 1.64087764015318e-06, 'epoch': 0.82}
+
82%|████████▏ | 9808/11952 [1:02:32<3:46:24, 6.34s/it]
82%|████████▏ | 9809/11952 [1:02:38<3:43:06, 6.25s/it]
{'loss': 0.4626, 'learning_rate': 1.639390580265774e-06, 'epoch': 0.82}
+
82%|████████▏ | 9809/11952 [1:02:38<3:43:06, 6.25s/it]
82%|████████▏ | 9810/11952 [1:02:44<3:37:37, 6.10s/it]
{'loss': 0.4576, 'learning_rate': 1.6379041343467484e-06, 'epoch': 0.82}
+
82%|████████▏ | 9810/11952 [1:02:44<3:37:37, 6.10s/it]
82%|████████▏ | 9811/11952 [1:02:50<3:41:01, 6.19s/it]
{'loss': 0.4766, 'learning_rate': 1.6364183025052626e-06, 'epoch': 0.82}
+
82%|████████▏ | 9811/11952 [1:02:50<3:41:01, 6.19s/it]
82%|████████▏ | 9812/11952 [1:02:56<3:40:01, 6.17s/it]
{'loss': 0.4571, 'learning_rate': 1.6349330848504308e-06, 'epoch': 0.82}
+
82%|████████▏ | 9812/11952 [1:02:56<3:40:01, 6.17s/it]
82%|████████▏ | 9813/11952 [1:03:02<3:37:35, 6.10s/it]
{'loss': 0.4734, 'learning_rate': 1.6334484814913165e-06, 'epoch': 0.82}
+
82%|████████▏ | 9813/11952 [1:03:02<3:37:35, 6.10s/it]
82%|████████▏ | 9814/11952 [1:03:08<3:35:36, 6.05s/it]
{'loss': 0.4534, 'learning_rate': 1.6319644925369504e-06, 'epoch': 0.82}
+
82%|████████▏ | 9814/11952 [1:03:08<3:35:36, 6.05s/it]
82%|████████▏ | 9815/11952 [1:03:14<3:32:12, 5.96s/it]
{'loss': 0.4627, 'learning_rate': 1.6304811180963032e-06, 'epoch': 0.82}
+
82%|████████▏ | 9815/11952 [1:03:14<3:32:12, 5.96s/it]
82%|████████▏ | 9816/11952 [1:03:20<3:32:13, 5.96s/it]
{'loss': 0.4361, 'learning_rate': 1.6289983582783142e-06, 'epoch': 0.82}
+
82%|████████▏ | 9816/11952 [1:03:20<3:32:13, 5.96s/it]
82%|████████▏ | 9817/11952 [1:03:26<3:31:49, 5.95s/it]
{'loss': 0.4706, 'learning_rate': 1.6275162131918688e-06, 'epoch': 0.82}
+
82%|████████▏ | 9817/11952 [1:03:26<3:31:49, 5.95s/it]
82%|████████▏ | 9818/11952 [1:03:32<3:29:31, 5.89s/it]
{'loss': 0.4615, 'learning_rate': 1.6260346829458084e-06, 'epoch': 0.82}
+
82%|████████▏ | 9818/11952 [1:03:32<3:29:31, 5.89s/it]
82%|████████▏ | 9819/11952 [1:03:37<3:27:07, 5.83s/it]
{'loss': 0.4508, 'learning_rate': 1.624553767648931e-06, 'epoch': 0.82}
+
82%|████████▏ | 9819/11952 [1:03:37<3:27:07, 5.83s/it]
82%|████████▏ | 9820/11952 [1:03:43<3:24:29, 5.75s/it]
{'loss': 0.4657, 'learning_rate': 1.623073467409988e-06, 'epoch': 0.82}
+
82%|████████▏ | 9820/11952 [1:03:43<3:24:29, 5.75s/it]
82%|████████▏ | 9821/11952 [1:03:49<3:26:27, 5.81s/it]
{'loss': 0.4634, 'learning_rate': 1.621593782337686e-06, 'epoch': 0.82}
+
82%|████████▏ | 9821/11952 [1:03:49<3:26:27, 5.81s/it]
82%|████████▏ | 9822/11952 [1:03:55<3:25:37, 5.79s/it]
{'loss': 0.4603, 'learning_rate': 1.62011471254069e-06, 'epoch': 0.82}
+
82%|████████▏ | 9822/11952 [1:03:55<3:25:37, 5.79s/it]
82%|████████▏ | 9823/11952 [1:04:01<3:28:03, 5.86s/it]
{'loss': 0.4654, 'learning_rate': 1.618636258127615e-06, 'epoch': 0.82}
+
82%|████████▏ | 9823/11952 [1:04:01<3:28:03, 5.86s/it]
82%|████████▏ | 9824/11952 [1:04:07<3:30:17, 5.93s/it]
{'loss': 0.46, 'learning_rate': 1.6171584192070322e-06, 'epoch': 0.82}
+
82%|████████▏ | 9824/11952 [1:04:07<3:30:17, 5.93s/it]
82%|████████▏ | 9825/11952 [1:04:12<3:28:58, 5.89s/it]
{'loss': 0.478, 'learning_rate': 1.6156811958874664e-06, 'epoch': 0.82}
+
82%|████████▏ | 9825/11952 [1:04:12<3:28:58, 5.89s/it]
82%|████████▏ | 9826/11952 [1:04:18<3:28:45, 5.89s/it]
{'loss': 0.4481, 'learning_rate': 1.6142045882774027e-06, 'epoch': 0.82}
+
82%|████████▏ | 9826/11952 [1:04:18<3:28:45, 5.89s/it]
82%|████████▏ | 9827/11952 [1:04:24<3:30:12, 5.94s/it]
{'loss': 0.4746, 'learning_rate': 1.6127285964852758e-06, 'epoch': 0.82}
+
82%|████████▏ | 9827/11952 [1:04:24<3:30:12, 5.94s/it]
82%|████████▏ | 9828/11952 [1:04:30<3:29:20, 5.91s/it]
{'loss': 0.4595, 'learning_rate': 1.6112532206194719e-06, 'epoch': 0.82}
+
82%|████████▏ | 9828/11952 [1:04:30<3:29:20, 5.91s/it]
82%|████████▏ | 9829/11952 [1:04:36<3:27:47, 5.87s/it]
{'loss': 0.4624, 'learning_rate': 1.6097784607883427e-06, 'epoch': 0.82}
+
82%|████████▏ | 9829/11952 [1:04:36<3:27:47, 5.87s/it]
82%|████████▏ | 9830/11952 [1:04:42<3:26:32, 5.84s/it]
{'loss': 0.4669, 'learning_rate': 1.6083043171001856e-06, 'epoch': 0.82}
+
82%|████████▏ | 9830/11952 [1:04:42<3:26:32, 5.84s/it]
82%|████████▏ | 9831/11952 [1:04:48<3:29:13, 5.92s/it]
{'loss': 0.456, 'learning_rate': 1.6068307896632562e-06, 'epoch': 0.82}
+
82%|████████▏ | 9831/11952 [1:04:48<3:29:13, 5.92s/it]
82%|████████▏ | 9832/11952 [1:04:54<3:27:49, 5.88s/it]
{'loss': 0.4572, 'learning_rate': 1.6053578785857637e-06, 'epoch': 0.82}
+
82%|████████▏ | 9832/11952 [1:04:54<3:27:49, 5.88s/it]
82%|████████▏ | 9833/11952 [1:04:59<3:24:41, 5.80s/it]
{'loss': 0.4696, 'learning_rate': 1.6038855839758727e-06, 'epoch': 0.82}
+
82%|████████▏ | 9833/11952 [1:04:59<3:24:41, 5.80s/it]
82%|████████▏ | 9834/11952 [1:05:05<3:25:27, 5.82s/it]
{'loss': 0.4707, 'learning_rate': 1.6024139059417e-06, 'epoch': 0.82}
+
82%|████████▏ | 9834/11952 [1:05:05<3:25:27, 5.82s/it]
82%|████████▏ | 9835/11952 [1:05:11<3:23:33, 5.77s/it]
{'loss': 0.4542, 'learning_rate': 1.6009428445913245e-06, 'epoch': 0.82}
+
82%|████████▏ | 9835/11952 [1:05:11<3:23:33, 5.77s/it]
82%|████████▏ | 9836/11952 [1:05:17<3:24:19, 5.79s/it]
{'loss': 0.4657, 'learning_rate': 1.5994724000327689e-06, 'epoch': 0.82}
+
82%|████████▏ | 9836/11952 [1:05:17<3:24:19, 5.79s/it]
82%|████████▏ | 9837/11952 [1:05:23<3:27:09, 5.88s/it]
{'loss': 0.4558, 'learning_rate': 1.5980025723740222e-06, 'epoch': 0.82}
+
82%|████████▏ | 9837/11952 [1:05:23<3:27:09, 5.88s/it]
82%|████████▏ | 9838/11952 [1:05:29<3:27:27, 5.89s/it]
{'loss': 0.4499, 'learning_rate': 1.5965333617230206e-06, 'epoch': 0.82}
+
82%|████████▏ | 9838/11952 [1:05:29<3:27:27, 5.89s/it]
82%|████████▏ | 9839/11952 [1:05:34<3:25:40, 5.84s/it]
{'loss': 0.4672, 'learning_rate': 1.5950647681876564e-06, 'epoch': 0.82}
+
82%|████████▏ | 9839/11952 [1:05:34<3:25:40, 5.84s/it]
82%|████████▏ | 9840/11952 [1:05:40<3:27:31, 5.90s/it]
{'loss': 0.4803, 'learning_rate': 1.5935967918757766e-06, 'epoch': 0.82}
+
82%|████████▏ | 9840/11952 [1:05:40<3:27:31, 5.90s/it]
82%|████████▏ | 9841/11952 [1:05:46<3:27:29, 5.90s/it]
{'loss': 0.4685, 'learning_rate': 1.5921294328951842e-06, 'epoch': 0.82}
+
82%|████████▏ | 9841/11952 [1:05:46<3:27:29, 5.90s/it]
82%|████████▏ | 9842/11952 [1:05:52<3:26:22, 5.87s/it]
{'loss': 0.4913, 'learning_rate': 1.5906626913536315e-06, 'epoch': 0.82}
+
82%|████████▏ | 9842/11952 [1:05:52<3:26:22, 5.87s/it]
82%|████████▏ | 9843/11952 [1:05:58<3:29:09, 5.95s/it]
{'loss': 0.4623, 'learning_rate': 1.5891965673588371e-06, 'epoch': 0.82}
+
82%|████████▏ | 9843/11952 [1:05:58<3:29:09, 5.95s/it]
82%|████████▏ | 9844/11952 [1:06:04<3:28:20, 5.93s/it]
{'loss': 0.467, 'learning_rate': 1.5877310610184638e-06, 'epoch': 0.82}
+
82%|████████▏ | 9844/11952 [1:06:04<3:28:20, 5.93s/it]
82%|████████▏ | 9845/11952 [1:06:10<3:26:55, 5.89s/it]
{'loss': 0.4534, 'learning_rate': 1.5862661724401296e-06, 'epoch': 0.82}
+
82%|████████▏ | 9845/11952 [1:06:10<3:26:55, 5.89s/it]
82%|████████▏ | 9846/11952 [1:06:16<3:25:52, 5.87s/it]
{'loss': 0.4589, 'learning_rate': 1.5848019017314143e-06, 'epoch': 0.82}
+
82%|████████▏ | 9846/11952 [1:06:16<3:25:52, 5.87s/it]
82%|████████▏ | 9847/11952 [1:06:22<3:29:20, 5.97s/it]
{'loss': 0.4532, 'learning_rate': 1.5833382489998461e-06, 'epoch': 0.82}
+
82%|████████▏ | 9847/11952 [1:06:22<3:29:20, 5.97s/it]
82%|████████▏ | 9848/11952 [1:06:28<3:27:04, 5.90s/it]
{'loss': 0.4563, 'learning_rate': 1.5818752143529092e-06, 'epoch': 0.82}
+
82%|████████▏ | 9848/11952 [1:06:28<3:27:04, 5.90s/it]
82%|████████▏ | 9849/11952 [1:06:34<3:27:16, 5.91s/it]
{'loss': 0.4748, 'learning_rate': 1.580412797898041e-06, 'epoch': 0.82}
+
82%|████████▏ | 9849/11952 [1:06:34<3:27:16, 5.91s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
82%|████████▏ | 9850/11952 [1:06:40<3:29:53, 5.99s/it]
{'loss': 0.4534, 'learning_rate': 1.578950999742639e-06, 'epoch': 0.82}
+
82%|████████▏ | 9850/11952 [1:06:40<3:29:53, 5.99s/it]
82%|████████▏ | 9851/11952 [1:06:46<3:26:28, 5.90s/it]
{'loss': 0.4749, 'learning_rate': 1.5774898199940503e-06, 'epoch': 0.82}
+
82%|████████▏ | 9851/11952 [1:06:46<3:26:28, 5.90s/it]
82%|████████▏ | 9852/11952 [1:06:51<3:26:02, 5.89s/it]
{'loss': 0.4571, 'learning_rate': 1.576029258759577e-06, 'epoch': 0.82}
+
82%|████████▏ | 9852/11952 [1:06:51<3:26:02, 5.89s/it]
82%|████████▏ | 9853/11952 [1:06:57<3:28:21, 5.96s/it]
{'loss': 0.4619, 'learning_rate': 1.574569316146477e-06, 'epoch': 0.82}
+
82%|████████▏ | 9853/11952 [1:06:57<3:28:21, 5.96s/it]
82%|████████▏ | 9854/11952 [1:07:03<3:25:58, 5.89s/it]
{'loss': 0.4568, 'learning_rate': 1.573109992261963e-06, 'epoch': 0.82}
+
82%|████████▏ | 9854/11952 [1:07:03<3:25:58, 5.89s/it]
82%|████████▏ | 9855/11952 [1:07:09<3:22:28, 5.79s/it]
{'loss': 0.46, 'learning_rate': 1.5716512872131983e-06, 'epoch': 0.82}
+
82%|████████▏ | 9855/11952 [1:07:09<3:22:28, 5.79s/it]
82%|████████▏ | 9856/11952 [1:07:15<3:23:38, 5.83s/it]
{'loss': 0.464, 'learning_rate': 1.5701932011073072e-06, 'epoch': 0.82}
+
82%|████████▏ | 9856/11952 [1:07:15<3:23:38, 5.83s/it]
82%|████████▏ | 9857/11952 [1:07:21<3:26:13, 5.91s/it]
{'loss': 0.4505, 'learning_rate': 1.5687357340513676e-06, 'epoch': 0.82}
+
82%|████████▏ | 9857/11952 [1:07:21<3:26:13, 5.91s/it]
82%|████████▏ | 9858/11952 [1:07:27<3:24:28, 5.86s/it]
{'loss': 0.4821, 'learning_rate': 1.567278886152407e-06, 'epoch': 0.82}
+
82%|████████▏ | 9858/11952 [1:07:27<3:24:28, 5.86s/it]
82%|████████▏ | 9859/11952 [1:07:32<3:23:15, 5.83s/it]
{'loss': 0.4536, 'learning_rate': 1.5658226575174107e-06, 'epoch': 0.82}
+
82%|████████▏ | 9859/11952 [1:07:32<3:23:15, 5.83s/it]
82%|████████▏ | 9860/11952 [1:07:38<3:21:15, 5.77s/it]
{'loss': 0.4568, 'learning_rate': 1.564367048253318e-06, 'epoch': 0.82}
+
82%|████████▏ | 9860/11952 [1:07:38<3:21:15, 5.77s/it]
83%|████████▎ | 9861/11952 [1:07:44<3:19:22, 5.72s/it]
{'loss': 0.4723, 'learning_rate': 1.5629120584670233e-06, 'epoch': 0.83}
+
83%|████████▎ | 9861/11952 [1:07:44<3:19:22, 5.72s/it]
83%|████████▎ | 9862/11952 [1:07:49<3:20:49, 5.77s/it]
{'loss': 0.4438, 'learning_rate': 1.561457688265372e-06, 'epoch': 0.83}
+
83%|████████▎ | 9862/11952 [1:07:49<3:20:49, 5.77s/it]
83%|████████▎ | 9863/11952 [1:07:56<3:24:35, 5.88s/it]
{'loss': 0.4778, 'learning_rate': 1.5600039377551713e-06, 'epoch': 0.83}
+
83%|████████▎ | 9863/11952 [1:07:56<3:24:35, 5.88s/it]
83%|████████▎ | 9864/11952 [1:08:02<3:26:35, 5.94s/it]
{'loss': 0.4595, 'learning_rate': 1.5585508070431777e-06, 'epoch': 0.83}
+
83%|████████▎ | 9864/11952 [1:08:02<3:26:35, 5.94s/it]
83%|████████▎ | 9865/11952 [1:08:07<3:25:08, 5.90s/it]
{'loss': 0.4779, 'learning_rate': 1.5570982962361014e-06, 'epoch': 0.83}
+
83%|████████▎ | 9865/11952 [1:08:07<3:25:08, 5.90s/it]
83%|████████▎ | 9866/11952 [1:08:13<3:26:14, 5.93s/it]
{'loss': 0.4676, 'learning_rate': 1.5556464054406084e-06, 'epoch': 0.83}
+
83%|████████▎ | 9866/11952 [1:08:13<3:26:14, 5.93s/it]
83%|████████▎ | 9867/11952 [1:08:19<3:23:48, 5.86s/it]
{'loss': 0.4708, 'learning_rate': 1.5541951347633222e-06, 'epoch': 0.83}
+
83%|████████▎ | 9867/11952 [1:08:19<3:23:48, 5.86s/it]
83%|████████▎ | 9868/11952 [1:08:25<3:21:48, 5.81s/it]
{'loss': 0.4505, 'learning_rate': 1.5527444843108164e-06, 'epoch': 0.83}
+
83%|████████▎ | 9868/11952 [1:08:25<3:21:48, 5.81s/it]
83%|████████▎ | 9869/11952 [1:08:31<3:24:27, 5.89s/it]
{'loss': 0.4521, 'learning_rate': 1.5512944541896192e-06, 'epoch': 0.83}
+
83%|████████▎ | 9869/11952 [1:08:31<3:24:27, 5.89s/it]
83%|████████▎ | 9870/11952 [1:08:37<3:22:58, 5.85s/it]
{'loss': 0.4528, 'learning_rate': 1.5498450445062185e-06, 'epoch': 0.83}
+
83%|████████▎ | 9870/11952 [1:08:37<3:22:58, 5.85s/it]
83%|████████▎ | 9871/11952 [1:08:42<3:20:17, 5.77s/it]
{'loss': 0.4653, 'learning_rate': 1.5483962553670507e-06, 'epoch': 0.83}
+
83%|████████▎ | 9871/11952 [1:08:42<3:20:17, 5.77s/it]
83%|████████▎ | 9872/11952 [1:08:48<3:20:04, 5.77s/it]
{'loss': 0.4514, 'learning_rate': 1.5469480868785092e-06, 'epoch': 0.83}
+
83%|████████▎ | 9872/11952 [1:08:48<3:20:04, 5.77s/it]
83%|████████▎ | 9873/11952 [1:08:54<3:19:42, 5.76s/it]
{'loss': 0.4529, 'learning_rate': 1.5455005391469414e-06, 'epoch': 0.83}
+
83%|████████▎ | 9873/11952 [1:08:54<3:19:42, 5.76s/it]
83%|████████▎ | 9874/11952 [1:09:00<3:22:31, 5.85s/it]
{'loss': 0.4503, 'learning_rate': 1.5440536122786487e-06, 'epoch': 0.83}
+
83%|████████▎ | 9874/11952 [1:09:00<3:22:31, 5.85s/it]
83%|████████▎ | 9875/11952 [1:09:05<3:19:40, 5.77s/it]
{'loss': 0.4638, 'learning_rate': 1.5426073063798853e-06, 'epoch': 0.83}
+
83%|████████▎ | 9875/11952 [1:09:05<3:19:40, 5.77s/it]
83%|████████▎ | 9876/11952 [1:09:11<3:21:51, 5.83s/it]
{'loss': 0.4875, 'learning_rate': 1.541161621556867e-06, 'epoch': 0.83}
+
83%|████████▎ | 9876/11952 [1:09:11<3:21:51, 5.83s/it]
83%|████████▎ | 9877/11952 [1:09:18<3:26:17, 5.96s/it]
{'loss': 0.4691, 'learning_rate': 1.5397165579157547e-06, 'epoch': 0.83}
+
83%|████████▎ | 9877/11952 [1:09:18<3:26:17, 5.96s/it]
83%|████████▎ | 9878/11952 [1:09:24<3:27:50, 6.01s/it]
{'loss': 0.4669, 'learning_rate': 1.5382721155626701e-06, 'epoch': 0.83}
+
83%|████████▎ | 9878/11952 [1:09:24<3:27:50, 6.01s/it]
83%|████████▎ | 9879/11952 [1:09:30<3:26:09, 5.97s/it]
{'loss': 0.4839, 'learning_rate': 1.5368282946036884e-06, 'epoch': 0.83}
+
83%|████████▎ | 9879/11952 [1:09:30<3:26:09, 5.97s/it]
83%|████████▎ | 9880/11952 [1:09:36<3:25:47, 5.96s/it]
{'loss': 0.45, 'learning_rate': 1.5353850951448346e-06, 'epoch': 0.83}
+
83%|████████▎ | 9880/11952 [1:09:36<3:25:47, 5.96s/it]
83%|████████▎ | 9881/11952 [1:09:42<3:25:49, 5.96s/it]
{'loss': 0.4832, 'learning_rate': 1.533942517292092e-06, 'epoch': 0.83}
+
83%|████████▎ | 9881/11952 [1:09:42<3:25:49, 5.96s/it]
83%|████████▎ | 9882/11952 [1:09:47<3:22:35, 5.87s/it]
{'loss': 0.4552, 'learning_rate': 1.5325005611513988e-06, 'epoch': 0.83}
+
83%|████████▎ | 9882/11952 [1:09:47<3:22:35, 5.87s/it]
83%|████████▎ | 9883/11952 [1:09:53<3:23:29, 5.90s/it]
{'loss': 0.4636, 'learning_rate': 1.5310592268286427e-06, 'epoch': 0.83}
+
83%|████████▎ | 9883/11952 [1:09:53<3:23:29, 5.90s/it]
83%|████████▎ | 9884/11952 [1:09:59<3:24:48, 5.94s/it]
{'loss': 0.4557, 'learning_rate': 1.5296185144296737e-06, 'epoch': 0.83}
+
83%|████████▎ | 9884/11952 [1:09:59<3:24:48, 5.94s/it]
83%|████████▎ | 9885/11952 [1:10:05<3:24:44, 5.94s/it]
{'loss': 0.4538, 'learning_rate': 1.5281784240602915e-06, 'epoch': 0.83}
+
83%|████████▎ | 9885/11952 [1:10:05<3:24:44, 5.94s/it]
83%|████████▎ | 9886/11952 [1:10:11<3:22:20, 5.88s/it]
{'loss': 0.4727, 'learning_rate': 1.5267389558262458e-06, 'epoch': 0.83}
+
83%|████████▎ | 9886/11952 [1:10:11<3:22:20, 5.88s/it]
83%|████████▎ | 9887/11952 [1:10:17<3:21:00, 5.84s/it]
{'loss': 0.468, 'learning_rate': 1.525300109833251e-06, 'epoch': 0.83}
+
83%|████████▎ | 9887/11952 [1:10:17<3:21:00, 5.84s/it]
83%|████████▎ | 9888/11952 [1:10:22<3:20:03, 5.82s/it]
{'loss': 0.4555, 'learning_rate': 1.5238618861869657e-06, 'epoch': 0.83}
+
83%|████████▎ | 9888/11952 [1:10:22<3:20:03, 5.82s/it]
83%|████████▎ | 9889/11952 [1:10:28<3:21:31, 5.86s/it]
{'loss': 0.4554, 'learning_rate': 1.5224242849930104e-06, 'epoch': 0.83}
+
83%|████████▎ | 9889/11952 [1:10:28<3:21:31, 5.86s/it]
83%|████████▎ | 9890/11952 [1:10:34<3:22:30, 5.89s/it]
{'loss': 0.461, 'learning_rate': 1.5209873063569514e-06, 'epoch': 0.83}
+
83%|████████▎ | 9890/11952 [1:10:34<3:22:30, 5.89s/it]
83%|████████▎ | 9891/11952 [1:10:40<3:22:01, 5.88s/it]
{'loss': 0.4678, 'learning_rate': 1.5195509503843198e-06, 'epoch': 0.83}
+
83%|████████▎ | 9891/11952 [1:10:40<3:22:01, 5.88s/it]
83%|████████▎ | 9892/11952 [1:10:46<3:24:05, 5.94s/it]
{'loss': 0.4675, 'learning_rate': 1.5181152171805946e-06, 'epoch': 0.83}
+
83%|████████▎ | 9892/11952 [1:10:46<3:24:05, 5.94s/it]
83%|████████▎ | 9893/11952 [1:10:52<3:20:11, 5.83s/it]
{'loss': 0.4785, 'learning_rate': 1.5166801068512083e-06, 'epoch': 0.83}
+
83%|████████▎ | 9893/11952 [1:10:52<3:20:11, 5.83s/it]
83%|████████▎ | 9894/11952 [1:10:58<3:22:08, 5.89s/it]
{'loss': 0.4646, 'learning_rate': 1.5152456195015508e-06, 'epoch': 0.83}
+
83%|████████▎ | 9894/11952 [1:10:58<3:22:08, 5.89s/it]
83%|████████▎ | 9895/11952 [1:11:04<3:24:03, 5.95s/it]
{'loss': 0.4579, 'learning_rate': 1.5138117552369636e-06, 'epoch': 0.83}
+
83%|████████▎ | 9895/11952 [1:11:04<3:24:03, 5.95s/it]
83%|████████▎ | 9896/11952 [1:11:10<3:27:00, 6.04s/it]
{'loss': 0.4778, 'learning_rate': 1.5123785141627422e-06, 'epoch': 0.83}
+
83%|████████▎ | 9896/11952 [1:11:10<3:27:00, 6.04s/it]
83%|████████▎ | 9897/11952 [1:11:16<3:24:20, 5.97s/it]
{'loss': 0.4539, 'learning_rate': 1.5109458963841405e-06, 'epoch': 0.83}
+
83%|████████▎ | 9897/11952 [1:11:16<3:24:20, 5.97s/it]
83%|████████▎ | 9898/11952 [1:11:22<3:25:07, 5.99s/it]
{'loss': 0.4777, 'learning_rate': 1.5095139020063654e-06, 'epoch': 0.83}
+
83%|████████▎ | 9898/11952 [1:11:22<3:25:07, 5.99s/it]
83%|████████▎ | 9899/11952 [1:11:28<3:24:41, 5.98s/it]
{'loss': 0.4639, 'learning_rate': 1.5080825311345748e-06, 'epoch': 0.83}
+
83%|████████▎ | 9899/11952 [1:11:28<3:24:41, 5.98s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+14 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
83%|████████▎ | 9900/11952 [1:11:34<3:28:12, 6.09s/it]
{'loss': 0.4715, 'learning_rate': 1.5066517838738826e-06, 'epoch': 0.83}
+
83%|████████▎ | 9900/11952 [1:11:34<3:28:12, 6.09s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-9900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
83%|████████▎ | 9901/11952 [1:12:04<7:29:11, 13.14s/it]
{'loss': 0.4642, 'learning_rate': 1.5052216603293567e-06, 'epoch': 0.83}
+
83%|████████▎ | 9901/11952 [1:12:04<7:29:11, 13.14s/it]
83%|████████▎ | 9902/11952 [1:12:10<6:16:27, 11.02s/it]
{'loss': 0.4706, 'learning_rate': 1.5037921606060201e-06, 'epoch': 0.83}
+
83%|████████▎ | 9902/11952 [1:12:10<6:16:27, 11.02s/it]
83%|████████▎ | 9903/11952 [1:12:16<5:22:38, 9.45s/it]
{'loss': 0.4704, 'learning_rate': 1.5023632848088466e-06, 'epoch': 0.83}
+
83%|████████▎ | 9903/11952 [1:12:16<5:22:38, 9.45s/it]
83%|████████▎ | 9904/11952 [1:12:22<4:44:11, 8.33s/it]
{'loss': 0.4681, 'learning_rate': 1.5009350330427707e-06, 'epoch': 0.83}
+
83%|████████▎ | 9904/11952 [1:12:22<4:44:11, 8.33s/it]
83%|████████▎ | 9905/11952 [1:12:27<4:17:05, 7.54s/it]
{'loss': 0.4892, 'learning_rate': 1.4995074054126758e-06, 'epoch': 0.83}
+
83%|████████▎ | 9905/11952 [1:12:27<4:17:05, 7.54s/it]
83%|████████▎ | 9906/11952 [1:12:33<4:00:38, 7.06s/it]
{'loss': 0.4726, 'learning_rate': 1.4980804020234018e-06, 'epoch': 0.83}
+
83%|████████▎ | 9906/11952 [1:12:33<4:00:38, 7.06s/it]
83%|████████▎ | 9907/11952 [1:12:39<3:48:44, 6.71s/it]
{'loss': 0.449, 'learning_rate': 1.4966540229797377e-06, 'epoch': 0.83}
+
83%|████████▎ | 9907/11952 [1:12:39<3:48:44, 6.71s/it]
83%|████████▎ | 9908/11952 [1:12:45<3:41:47, 6.51s/it]
{'loss': 0.4921, 'learning_rate': 1.495228268386436e-06, 'epoch': 0.83}
+
83%|████████▎ | 9908/11952 [1:12:45<3:41:47, 6.51s/it]
83%|████████▎ | 9909/11952 [1:12:51<3:33:24, 6.27s/it]
{'loss': 0.4561, 'learning_rate': 1.4938031383481976e-06, 'epoch': 0.83}
+
83%|████████▎ | 9909/11952 [1:12:51<3:33:24, 6.27s/it]
83%|████████▎ | 9910/11952 [1:12:57<3:29:22, 6.15s/it]
{'loss': 0.4515, 'learning_rate': 1.4923786329696732e-06, 'epoch': 0.83}
+
83%|████████▎ | 9910/11952 [1:12:57<3:29:22, 6.15s/it]
83%|████████▎ | 9911/11952 [1:13:03<3:27:38, 6.10s/it]
{'loss': 0.4636, 'learning_rate': 1.490954752355479e-06, 'epoch': 0.83}
+
83%|████████▎ | 9911/11952 [1:13:03<3:27:38, 6.10s/it]
83%|████████▎ | 9912/11952 [1:13:09<3:26:37, 6.08s/it]
{'loss': 0.4696, 'learning_rate': 1.4895314966101771e-06, 'epoch': 0.83}
+
83%|████████▎ | 9912/11952 [1:13:09<3:26:37, 6.08s/it]
83%|████████▎ | 9913/11952 [1:13:14<3:22:50, 5.97s/it]
{'loss': 0.46, 'learning_rate': 1.4881088658382825e-06, 'epoch': 0.83}
+
83%|████████▎ | 9913/11952 [1:13:14<3:22:50, 5.97s/it]
83%|████████▎ | 9914/11952 [1:13:20<3:20:54, 5.91s/it]
{'loss': 0.4571, 'learning_rate': 1.4866868601442708e-06, 'epoch': 0.83}
+
83%|████████▎ | 9914/11952 [1:13:20<3:20:54, 5.91s/it]
83%|████████▎ | 9915/11952 [1:13:26<3:21:23, 5.93s/it]
{'loss': 0.4791, 'learning_rate': 1.4852654796325649e-06, 'epoch': 0.83}
+
83%|████████▎ | 9915/11952 [1:13:26<3:21:23, 5.93s/it]
83%|████████▎ | 9916/11952 [1:13:32<3:22:15, 5.96s/it]
{'loss': 0.4548, 'learning_rate': 1.483844724407546e-06, 'epoch': 0.83}
+
83%|████████▎ | 9916/11952 [1:13:32<3:22:15, 5.96s/it]
83%|████████▎ | 9917/11952 [1:13:38<3:22:17, 5.96s/it]
{'loss': 0.4757, 'learning_rate': 1.4824245945735504e-06, 'epoch': 0.83}
+
83%|████████▎ | 9917/11952 [1:13:38<3:22:17, 5.96s/it]
83%|████████▎ | 9918/11952 [1:13:44<3:19:56, 5.90s/it]
{'loss': 0.4646, 'learning_rate': 1.4810050902348637e-06, 'epoch': 0.83}
+
83%|████████▎ | 9918/11952 [1:13:44<3:19:56, 5.90s/it]
83%|████████▎ | 9919/11952 [1:13:50<3:20:14, 5.91s/it]
{'loss': 0.4581, 'learning_rate': 1.4795862114957316e-06, 'epoch': 0.83}
+
83%|████████▎ | 9919/11952 [1:13:50<3:20:14, 5.91s/it]
83%|████████▎ | 9920/11952 [1:13:56<3:19:03, 5.88s/it]
{'loss': 0.4629, 'learning_rate': 1.4781679584603502e-06, 'epoch': 0.83}
+
83%|████████▎ | 9920/11952 [1:13:56<3:19:03, 5.88s/it]
83%|████████▎ | 9921/11952 [1:14:01<3:18:33, 5.87s/it]
{'loss': 0.4577, 'learning_rate': 1.476750331232868e-06, 'epoch': 0.83}
+
83%|████████▎ | 9921/11952 [1:14:01<3:18:33, 5.87s/it]
83%|████████▎ | 9922/11952 [1:14:08<3:22:59, 6.00s/it]
{'loss': 0.4527, 'learning_rate': 1.475333329917391e-06, 'epoch': 0.83}
+
83%|████████▎ | 9922/11952 [1:14:08<3:22:59, 6.00s/it]
83%|████████▎ | 9923/11952 [1:14:14<3:21:56, 5.97s/it]
{'loss': 0.4807, 'learning_rate': 1.4739169546179765e-06, 'epoch': 0.83}
+
83%|████████▎ | 9923/11952 [1:14:14<3:21:56, 5.97s/it]
83%|████████▎ | 9924/11952 [1:14:20<3:22:53, 6.00s/it]
{'loss': 0.4923, 'learning_rate': 1.4725012054386378e-06, 'epoch': 0.83}
+
83%|████████▎ | 9924/11952 [1:14:20<3:22:53, 6.00s/it]
83%|████████▎ | 9925/11952 [1:14:26<3:20:43, 5.94s/it]
{'loss': 0.4598, 'learning_rate': 1.471086082483343e-06, 'epoch': 0.83}
+
83%|████████▎ | 9925/11952 [1:14:26<3:20:43, 5.94s/it]
83%|████████▎ | 9926/11952 [1:14:31<3:19:45, 5.92s/it]
{'loss': 0.4665, 'learning_rate': 1.4696715858560117e-06, 'epoch': 0.83}
+
83%|████████▎ | 9926/11952 [1:14:31<3:19:45, 5.92s/it]
83%|████████▎ | 9927/11952 [1:14:37<3:17:39, 5.86s/it]
{'loss': 0.4629, 'learning_rate': 1.4682577156605172e-06, 'epoch': 0.83}
+
83%|████████▎ | 9927/11952 [1:14:37<3:17:39, 5.86s/it]
83%|████████▎ | 9928/11952 [1:14:43<3:17:12, 5.85s/it]
{'loss': 0.4601, 'learning_rate': 1.4668444720006925e-06, 'epoch': 0.83}
+
83%|████████▎ | 9928/11952 [1:14:43<3:17:12, 5.85s/it]
83%|████████▎ | 9929/11952 [1:14:49<3:18:39, 5.89s/it]
{'loss': 0.4491, 'learning_rate': 1.465431854980317e-06, 'epoch': 0.83}
+
83%|████████▎ | 9929/11952 [1:14:49<3:18:39, 5.89s/it]
83%|████████▎ | 9930/11952 [1:14:55<3:17:19, 5.86s/it]
{'loss': 0.4712, 'learning_rate': 1.464019864703128e-06, 'epoch': 0.83}
+
83%|████████▎ | 9930/11952 [1:14:55<3:17:19, 5.86s/it]
83%|████████▎ | 9931/11952 [1:15:01<3:19:04, 5.91s/it]
{'loss': 0.4774, 'learning_rate': 1.462608501272814e-06, 'epoch': 0.83}
+
83%|████████▎ | 9931/11952 [1:15:01<3:19:04, 5.91s/it]
83%|████████▎ | 9932/11952 [1:15:07<3:18:55, 5.91s/it]
{'loss': 0.4513, 'learning_rate': 1.4611977647930253e-06, 'epoch': 0.83}
+
83%|████████▎ | 9932/11952 [1:15:07<3:18:55, 5.91s/it]
83%|████████▎ | 9933/11952 [1:15:12<3:17:02, 5.86s/it]
{'loss': 0.4563, 'learning_rate': 1.4597876553673563e-06, 'epoch': 0.83}
+
83%|████████▎ | 9933/11952 [1:15:12<3:17:02, 5.86s/it]
83%|████████▎ | 9934/11952 [1:15:18<3:17:30, 5.87s/it]
{'loss': 0.499, 'learning_rate': 1.4583781730993608e-06, 'epoch': 0.83}
+
83%|████████▎ | 9934/11952 [1:15:18<3:17:30, 5.87s/it]
83%|████████▎ | 9935/11952 [1:15:24<3:14:11, 5.78s/it]
{'loss': 0.4526, 'learning_rate': 1.4569693180925448e-06, 'epoch': 0.83}
+
83%|████████▎ | 9935/11952 [1:15:24<3:14:11, 5.78s/it]
83%|████████▎ | 9936/11952 [1:15:30<3:18:07, 5.90s/it]
{'loss': 0.4584, 'learning_rate': 1.4555610904503693e-06, 'epoch': 0.83}
+
83%|████████▎ | 9936/11952 [1:15:30<3:18:07, 5.90s/it]
83%|████████▎ | 9937/11952 [1:15:36<3:19:49, 5.95s/it]
{'loss': 0.4796, 'learning_rate': 1.4541534902762454e-06, 'epoch': 0.83}
+
83%|████████▎ | 9937/11952 [1:15:36<3:19:49, 5.95s/it]
83%|████████▎ | 9938/11952 [1:15:42<3:16:05, 5.84s/it]
{'loss': 0.4667, 'learning_rate': 1.4527465176735468e-06, 'epoch': 0.83}
+
83%|████████▎ | 9938/11952 [1:15:42<3:16:05, 5.84s/it]
83%|████████▎ | 9939/11952 [1:15:47<3:13:59, 5.78s/it]
{'loss': 0.4605, 'learning_rate': 1.4513401727455912e-06, 'epoch': 0.83}
+
83%|████████▎ | 9939/11952 [1:15:47<3:13:59, 5.78s/it]
83%|████████▎ | 9940/11952 [1:15:53<3:15:34, 5.83s/it]
{'loss': 0.4599, 'learning_rate': 1.4499344555956596e-06, 'epoch': 0.83}
+
83%|████████▎ | 9940/11952 [1:15:53<3:15:34, 5.83s/it]
83%|████████▎ | 9941/11952 [1:15:59<3:13:33, 5.77s/it]
{'loss': 0.4705, 'learning_rate': 1.4485293663269784e-06, 'epoch': 0.83}
+
83%|████████▎ | 9941/11952 [1:15:59<3:13:33, 5.77s/it]
83%|████████▎ | 9942/11952 [1:16:05<3:17:34, 5.90s/it]
{'loss': 0.4587, 'learning_rate': 1.4471249050427327e-06, 'epoch': 0.83}
+
83%|████████▎ | 9942/11952 [1:16:05<3:17:34, 5.90s/it]
83%|████████▎ | 9943/11952 [1:16:11<3:17:39, 5.90s/it]
{'loss': 0.4666, 'learning_rate': 1.445721071846059e-06, 'epoch': 0.83}
+
83%|████████▎ | 9943/11952 [1:16:11<3:17:39, 5.90s/it]
83%|████████▎ | 9944/11952 [1:16:17<3:17:54, 5.91s/it]
{'loss': 0.4746, 'learning_rate': 1.4443178668400482e-06, 'epoch': 0.83}
+
83%|████████▎ | 9944/11952 [1:16:17<3:17:54, 5.91s/it]
83%|████████▎ | 9945/11952 [1:16:23<3:16:53, 5.89s/it]
{'loss': 0.4541, 'learning_rate': 1.44291529012775e-06, 'epoch': 0.83}
+
83%|████████▎ | 9945/11952 [1:16:23<3:16:53, 5.89s/it]
83%|████████▎ | 9946/11952 [1:16:29<3:15:15, 5.84s/it]
{'loss': 0.4601, 'learning_rate': 1.4415133418121607e-06, 'epoch': 0.83}
+
83%|████████▎ | 9946/11952 [1:16:29<3:15:15, 5.84s/it]
83%|████████▎ | 9947/11952 [1:16:35<3:17:17, 5.90s/it]
{'loss': 0.4644, 'learning_rate': 1.440112021996235e-06, 'epoch': 0.83}
+
83%|████████▎ | 9947/11952 [1:16:35<3:17:17, 5.90s/it]
83%|████████▎ | 9948/11952 [1:16:40<3:13:19, 5.79s/it]
{'loss': 0.4746, 'learning_rate': 1.438711330782877e-06, 'epoch': 0.83}
+
83%|████████▎ | 9948/11952 [1:16:40<3:13:19, 5.79s/it]
83%|████████▎ | 9949/11952 [1:16:46<3:14:41, 5.83s/it]
{'loss': 0.453, 'learning_rate': 1.4373112682749513e-06, 'epoch': 0.83}
+
83%|████████▎ | 9949/11952 [1:16:46<3:14:41, 5.83s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+35 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+41 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
83%|████████▎ | 9950/11952 [1:16:52<3:13:16, 5.79s/it]
{'loss': 0.4469, 'learning_rate': 1.435911834575271e-06, 'epoch': 0.83}
+
83%|████████▎ | 9950/11952 [1:16:52<3:13:16, 5.79s/it]
83%|████████▎ | 9951/11952 [1:16:58<3:15:59, 5.88s/it]
{'loss': 0.4831, 'learning_rate': 1.4345130297866028e-06, 'epoch': 0.83}
+
83%|████████▎ | 9951/11952 [1:16:58<3:15:59, 5.88s/it]
83%|████████▎ | 9952/11952 [1:17:04<3:19:29, 5.98s/it]
{'loss': 0.4721, 'learning_rate': 1.4331148540116736e-06, 'epoch': 0.83}
+
83%|████████▎ | 9952/11952 [1:17:04<3:19:29, 5.98s/it]
83%|████████▎ | 9953/11952 [1:17:10<3:18:16, 5.95s/it]
{'loss': 0.4719, 'learning_rate': 1.4317173073531577e-06, 'epoch': 0.83}
+
83%|████████▎ | 9953/11952 [1:17:10<3:18:16, 5.95s/it]
83%|████████▎ | 9954/11952 [1:17:16<3:22:18, 6.08s/it]
{'loss': 0.4573, 'learning_rate': 1.4303203899136841e-06, 'epoch': 0.83}
+
83%|████████▎ | 9954/11952 [1:17:16<3:22:18, 6.08s/it]
83%|████████▎ | 9955/11952 [1:17:22<3:16:39, 5.91s/it]
{'loss': 0.4556, 'learning_rate': 1.4289241017958366e-06, 'epoch': 0.83}
+
83%|████████▎ | 9955/11952 [1:17:22<3:16:39, 5.91s/it]
83%|████████▎ | 9956/11952 [1:17:28<3:15:43, 5.88s/it]
{'loss': 0.4715, 'learning_rate': 1.4275284431021541e-06, 'epoch': 0.83}
+
83%|████████▎ | 9956/11952 [1:17:28<3:15:43, 5.88s/it]
83%|████████▎ | 9957/11952 [1:17:33<3:13:39, 5.82s/it]
{'loss': 0.4622, 'learning_rate': 1.4261334139351269e-06, 'epoch': 0.83}
+
83%|████████▎ | 9957/11952 [1:17:33<3:13:39, 5.82s/it]
83%|████████▎ | 9958/11952 [1:17:39<3:13:38, 5.83s/it]
{'loss': 0.4679, 'learning_rate': 1.4247390143971972e-06, 'epoch': 0.83}
+
83%|████████▎ | 9958/11952 [1:17:39<3:13:38, 5.83s/it]
83%|████████▎ | 9959/11952 [1:17:45<3:15:44, 5.89s/it]
{'loss': 0.4744, 'learning_rate': 1.423345244590768e-06, 'epoch': 0.83}
+
83%|████████▎ | 9959/11952 [1:17:45<3:15:44, 5.89s/it]
83%|████████▎ | 9960/11952 [1:17:51<3:14:26, 5.86s/it]
{'loss': 0.4441, 'learning_rate': 1.4219521046181928e-06, 'epoch': 0.83}
+
83%|████████▎ | 9960/11952 [1:17:51<3:14:26, 5.86s/it]
83%|████████▎ | 9961/11952 [1:17:57<3:14:51, 5.87s/it]
{'loss': 0.4609, 'learning_rate': 1.4205595945817773e-06, 'epoch': 0.83}
+
83%|████████▎ | 9961/11952 [1:17:57<3:14:51, 5.87s/it]
83%|████████▎ | 9962/11952 [1:18:03<3:14:12, 5.86s/it]
{'loss': 0.4812, 'learning_rate': 1.41916771458378e-06, 'epoch': 0.83}
+
83%|████████▎ | 9962/11952 [1:18:03<3:14:12, 5.86s/it]
83%|████████▎ | 9963/11952 [1:18:09<3:18:10, 5.98s/it]
{'loss': 0.4526, 'learning_rate': 1.4177764647264148e-06, 'epoch': 0.83}
+
83%|████████▎ | 9963/11952 [1:18:09<3:18:10, 5.98s/it]
83%|████████▎ | 9964/11952 [1:18:15<3:16:27, 5.93s/it]
{'loss': 0.4531, 'learning_rate': 1.4163858451118506e-06, 'epoch': 0.83}
+
83%|████████▎ | 9964/11952 [1:18:15<3:16:27, 5.93s/it]
83%|████████▎ | 9965/11952 [1:18:20<3:13:17, 5.84s/it]
{'loss': 0.4603, 'learning_rate': 1.414995855842205e-06, 'epoch': 0.83}
+
83%|████████▎ | 9965/11952 [1:18:20<3:13:17, 5.84s/it]
83%|████████▎ | 9966/11952 [1:18:26<3:14:14, 5.87s/it]
{'loss': 0.447, 'learning_rate': 1.4136064970195595e-06, 'epoch': 0.83}
+
83%|████████▎ | 9966/11952 [1:18:26<3:14:14, 5.87s/it]
83%|████████▎ | 9967/11952 [1:18:32<3:12:07, 5.81s/it]
{'loss': 0.4504, 'learning_rate': 1.4122177687459382e-06, 'epoch': 0.83}
+
83%|████████▎ | 9967/11952 [1:18:32<3:12:07, 5.81s/it]
83%|████████▎ | 9968/11952 [1:18:38<3:11:30, 5.79s/it]
{'loss': 0.461, 'learning_rate': 1.4108296711233249e-06, 'epoch': 0.83}
+
83%|████████▎ | 9968/11952 [1:18:38<3:11:30, 5.79s/it]
83%|████████▎ | 9969/11952 [1:18:44<3:12:37, 5.83s/it]
{'loss': 0.458, 'learning_rate': 1.4094422042536538e-06, 'epoch': 0.83}
+
83%|████████▎ | 9969/11952 [1:18:44<3:12:37, 5.83s/it]
83%|████████▎ | 9970/11952 [1:18:49<3:10:49, 5.78s/it]
{'loss': 0.4563, 'learning_rate': 1.4080553682388188e-06, 'epoch': 0.83}
+
83%|████████▎ | 9970/11952 [1:18:49<3:10:49, 5.78s/it]
83%|████████▎ | 9971/11952 [1:18:55<3:09:34, 5.74s/it]
{'loss': 0.4701, 'learning_rate': 1.4066691631806574e-06, 'epoch': 0.83}
+
83%|████████▎ | 9971/11952 [1:18:55<3:09:34, 5.74s/it]
83%|████████▎ | 9972/11952 [1:19:01<3:15:41, 5.93s/it]
{'loss': 0.4579, 'learning_rate': 1.4052835891809735e-06, 'epoch': 0.83}
+
83%|████████▎ | 9972/11952 [1:19:01<3:15:41, 5.93s/it]
83%|████████▎ | 9973/11952 [1:19:07<3:14:10, 5.89s/it]
{'loss': 0.4772, 'learning_rate': 1.403898646341515e-06, 'epoch': 0.83}
+
83%|████████▎ | 9973/11952 [1:19:07<3:14:10, 5.89s/it]
83%|████████▎ | 9974/11952 [1:19:13<3:14:17, 5.89s/it]
{'loss': 0.467, 'learning_rate': 1.4025143347639858e-06, 'epoch': 0.83}
+
83%|████████▎ | 9974/11952 [1:19:13<3:14:17, 5.89s/it]
83%|████████▎ | 9975/11952 [1:19:19<3:13:49, 5.88s/it]
{'loss': 0.4744, 'learning_rate': 1.4011306545500435e-06, 'epoch': 0.83}
+
83%|████████▎ | 9975/11952 [1:19:19<3:13:49, 5.88s/it]
83%|████████▎ | 9976/11952 [1:19:25<3:14:16, 5.90s/it]
{'loss': 0.4634, 'learning_rate': 1.3997476058013016e-06, 'epoch': 0.83}
+
83%|████████▎ | 9976/11952 [1:19:25<3:14:16, 5.90s/it]
83%|████████▎ | 9977/11952 [1:19:31<3:13:35, 5.88s/it]
{'loss': 0.4809, 'learning_rate': 1.398365188619324e-06, 'epoch': 0.83}
+
83%|████████▎ | 9977/11952 [1:19:31<3:13:35, 5.88s/it]
83%|████████▎ | 9978/11952 [1:19:36<3:11:39, 5.83s/it]
{'loss': 0.4474, 'learning_rate': 1.3969834031056273e-06, 'epoch': 0.83}
+
83%|████████▎ | 9978/11952 [1:19:36<3:11:39, 5.83s/it]
83%|████████▎ | 9979/11952 [1:19:42<3:09:36, 5.77s/it]
{'loss': 0.4512, 'learning_rate': 1.3956022493616895e-06, 'epoch': 0.83}
+
83%|████████▎ | 9979/11952 [1:19:42<3:09:36, 5.77s/it]
84%|████████▎ | 9980/11952 [1:19:48<3:12:19, 5.85s/it]
{'loss': 0.4772, 'learning_rate': 1.3942217274889325e-06, 'epoch': 0.83}
+
84%|████████▎ | 9980/11952 [1:19:48<3:12:19, 5.85s/it]
84%|████████▎ | 9981/11952 [1:19:54<3:13:09, 5.88s/it]
{'loss': 0.4751, 'learning_rate': 1.3928418375887388e-06, 'epoch': 0.84}
+
84%|████████▎ | 9981/11952 [1:19:54<3:13:09, 5.88s/it]
84%|████████▎ | 9982/11952 [1:20:00<3:16:33, 5.99s/it]
{'loss': 0.4361, 'learning_rate': 1.3914625797624415e-06, 'epoch': 0.84}
+
84%|████████▎ | 9982/11952 [1:20:00<3:16:33, 5.99s/it]
84%|████████▎ | 9983/11952 [1:20:06<3:17:35, 6.02s/it]
{'loss': 0.4814, 'learning_rate': 1.3900839541113265e-06, 'epoch': 0.84}
+
84%|████████▎ | 9983/11952 [1:20:06<3:17:35, 6.02s/it]
84%|████████▎ | 9984/11952 [1:20:12<3:14:55, 5.94s/it]
{'loss': 0.4506, 'learning_rate': 1.3887059607366338e-06, 'epoch': 0.84}
+
84%|████████▎ | 9984/11952 [1:20:12<3:14:55, 5.94s/it]
84%|████████▎ | 9985/11952 [1:20:18<3:13:32, 5.90s/it]
{'loss': 0.4521, 'learning_rate': 1.3873285997395569e-06, 'epoch': 0.84}
+
84%|████████▎ | 9985/11952 [1:20:18<3:13:32, 5.90s/it]
84%|████████▎ | 9986/11952 [1:20:24<3:11:50, 5.85s/it]
{'loss': 0.4759, 'learning_rate': 1.3859518712212473e-06, 'epoch': 0.84}
+
84%|████████▎ | 9986/11952 [1:20:24<3:11:50, 5.85s/it]
84%|████████▎ | 9987/11952 [1:20:30<3:13:35, 5.91s/it]
{'loss': 0.4694, 'learning_rate': 1.3845757752828037e-06, 'epoch': 0.84}
+
84%|████████▎ | 9987/11952 [1:20:30<3:13:35, 5.91s/it]
84%|████████▎ | 9988/11952 [1:20:36<3:13:27, 5.91s/it]
{'loss': 0.4438, 'learning_rate': 1.3832003120252801e-06, 'epoch': 0.84}
+
84%|████████▎ | 9988/11952 [1:20:36<3:13:27, 5.91s/it]
84%|████████▎ | 9989/11952 [1:20:41<3:11:49, 5.86s/it]
{'loss': 0.4566, 'learning_rate': 1.3818254815496846e-06, 'epoch': 0.84}
+
84%|████████▎ | 9989/11952 [1:20:41<3:11:49, 5.86s/it]
84%|████████▎ | 9990/11952 [1:20:47<3:11:48, 5.87s/it]
{'loss': 0.4699, 'learning_rate': 1.3804512839569805e-06, 'epoch': 0.84}
+
84%|████████▎ | 9990/11952 [1:20:47<3:11:48, 5.87s/it]
84%|████████▎ | 9991/11952 [1:20:53<3:15:03, 5.97s/it]
{'loss': 0.4585, 'learning_rate': 1.3790777193480842e-06, 'epoch': 0.84}
+
84%|████████▎ | 9991/11952 [1:20:53<3:15:03, 5.97s/it]
84%|████████▎ | 9992/11952 [1:21:00<3:15:58, 6.00s/it]
{'loss': 0.4504, 'learning_rate': 1.3777047878238603e-06, 'epoch': 0.84}
+
84%|████████▎ | 9992/11952 [1:21:00<3:15:58, 6.00s/it]
84%|████████▎ | 9993/11952 [1:21:05<3:13:29, 5.93s/it]
{'loss': 0.4583, 'learning_rate': 1.3763324894851371e-06, 'epoch': 0.84}
+
84%|████████▎ | 9993/11952 [1:21:05<3:13:29, 5.93s/it]
84%|████████▎ | 9994/11952 [1:21:11<3:13:37, 5.93s/it]
{'loss': 0.461, 'learning_rate': 1.3749608244326862e-06, 'epoch': 0.84}
+
84%|████████▎ | 9994/11952 [1:21:11<3:13:37, 5.93s/it]
84%|████████▎ | 9995/11952 [1:21:17<3:12:46, 5.91s/it]
{'loss': 0.4712, 'learning_rate': 1.373589792767238e-06, 'epoch': 0.84}
+
84%|████████▎ | 9995/11952 [1:21:17<3:12:46, 5.91s/it]
84%|████████▎ | 9996/11952 [1:21:23<3:11:53, 5.89s/it]
{'loss': 0.4688, 'learning_rate': 1.372219394589477e-06, 'epoch': 0.84}
+
84%|████████▎ | 9996/11952 [1:21:23<3:11:53, 5.89s/it]
84%|████████▎ | 9997/11952 [1:21:29<3:12:17, 5.90s/it]
{'loss': 0.479, 'learning_rate': 1.3708496300000363e-06, 'epoch': 0.84}
+
84%|████████▎ | 9997/11952 [1:21:29<3:12:17, 5.90s/it]
84%|████████▎ | 9998/11952 [1:21:35<3:12:15, 5.90s/it]
{'loss': 0.4624, 'learning_rate': 1.369480499099508e-06, 'epoch': 0.84}
+
84%|████████▎ | 9998/11952 [1:21:35<3:12:15, 5.90s/it]
84%|████████▎ | 9999/11952 [1:21:41<3:12:20, 5.91s/it]
{'loss': 0.4708, 'learning_rate': 1.3681120019884331e-06, 'epoch': 0.84}
+
84%|████████▎ | 9999/11952 [1:21:41<3:12:20, 5.91s/it]6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
84%|████████▎ | 10000/11952 [1:21:46<3:11:12, 5.88s/it]
{'loss': 0.4821, 'learning_rate': 1.3667441387673098e-06, 'epoch': 0.84}
+
84%|████████▎ | 10000/11952 [1:21:46<3:11:12, 5.88s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
84%|████████▎ | 10001/11952 [1:22:16<7:05:33, 13.09s/it]
{'loss': 0.4553, 'learning_rate': 1.36537690953659e-06, 'epoch': 0.84}
+
84%|████████▎ | 10001/11952 [1:22:16<7:05:33, 13.09s/it]
84%|████████▎ | 10002/11952 [1:22:22<5:55:57, 10.95s/it]
{'loss': 0.4771, 'learning_rate': 1.3640103143966765e-06, 'epoch': 0.84}
+
84%|████████▎ | 10002/11952 [1:22:22<5:55:57, 10.95s/it]
84%|████████▎ | 10003/11952 [1:22:28<5:04:00, 9.36s/it]
{'loss': 0.4618, 'learning_rate': 1.3626443534479262e-06, 'epoch': 0.84}
+
84%|████████▎ | 10003/11952 [1:22:28<5:04:00, 9.36s/it]
84%|████████▎ | 10004/11952 [1:22:34<4:29:29, 8.30s/it]
{'loss': 0.4534, 'learning_rate': 1.3612790267906484e-06, 'epoch': 0.84}
+
84%|████████▎ | 10004/11952 [1:22:34<4:29:29, 8.30s/it]
84%|████████▎ | 10005/11952 [1:22:40<4:10:35, 7.72s/it]
{'loss': 0.4711, 'learning_rate': 1.3599143345251075e-06, 'epoch': 0.84}
+
84%|████████▎ | 10005/11952 [1:22:40<4:10:35, 7.72s/it]
84%|████████▎ | 10006/11952 [1:22:46<3:51:07, 7.13s/it]
{'loss': 0.4506, 'learning_rate': 1.35855027675152e-06, 'epoch': 0.84}
+
84%|████████▎ | 10006/11952 [1:22:46<3:51:07, 7.13s/it]
84%|████████▎ | 10007/11952 [1:22:52<3:39:12, 6.76s/it]
{'loss': 0.4574, 'learning_rate': 1.3571868535700595e-06, 'epoch': 0.84}
+
84%|████████▎ | 10007/11952 [1:22:52<3:39:12, 6.76s/it]
84%|████████▎ | 10008/11952 [1:22:58<3:30:02, 6.48s/it]
{'loss': 0.4485, 'learning_rate': 1.3558240650808473e-06, 'epoch': 0.84}
+
84%|████████▎ | 10008/11952 [1:22:58<3:30:02, 6.48s/it]
84%|████████▎ | 10009/11952 [1:23:03<3:22:56, 6.27s/it]
{'loss': 0.4536, 'learning_rate': 1.354461911383963e-06, 'epoch': 0.84}
+
84%|████████▎ | 10009/11952 [1:23:03<3:22:56, 6.27s/it]
84%|████████▍ | 10010/11952 [1:23:09<3:19:34, 6.17s/it]
{'loss': 0.467, 'learning_rate': 1.353100392579434e-06, 'epoch': 0.84}
+
84%|████████▍ | 10010/11952 [1:23:09<3:19:34, 6.17s/it]
84%|████████▍ | 10011/11952 [1:23:16<3:18:59, 6.15s/it]
{'loss': 0.4719, 'learning_rate': 1.351739508767249e-06, 'epoch': 0.84}
+
84%|████████▍ | 10011/11952 [1:23:16<3:18:59, 6.15s/it]
84%|████████▍ | 10012/11952 [1:23:21<3:15:37, 6.05s/it]
{'loss': 0.4611, 'learning_rate': 1.3503792600473408e-06, 'epoch': 0.84}
+
84%|████████▍ | 10012/11952 [1:23:21<3:15:37, 6.05s/it]
84%|████████▍ | 10013/11952 [1:23:27<3:12:24, 5.95s/it]
{'loss': 0.4513, 'learning_rate': 1.349019646519607e-06, 'epoch': 0.84}
+
84%|████████▍ | 10013/11952 [1:23:27<3:12:24, 5.95s/it]
84%|████████▍ | 10014/11952 [1:23:33<3:09:47, 5.88s/it]
{'loss': 0.4686, 'learning_rate': 1.3476606682838866e-06, 'epoch': 0.84}
+
84%|████████▍ | 10014/11952 [1:23:33<3:09:47, 5.88s/it]
84%|████████▍ | 10015/11952 [1:23:38<3:08:19, 5.83s/it]
{'loss': 0.4681, 'learning_rate': 1.3463023254399798e-06, 'epoch': 0.84}
+
84%|████████▍ | 10015/11952 [1:23:38<3:08:19, 5.83s/it]
84%|████████▍ | 10016/11952 [1:23:44<3:08:01, 5.83s/it]
{'loss': 0.4556, 'learning_rate': 1.3449446180876369e-06, 'epoch': 0.84}
+
84%|████████▍ | 10016/11952 [1:23:44<3:08:01, 5.83s/it]
84%|████████▍ | 10017/11952 [1:23:50<3:09:08, 5.86s/it]
{'loss': 0.4678, 'learning_rate': 1.3435875463265624e-06, 'epoch': 0.84}
+
84%|████████▍ | 10017/11952 [1:23:50<3:09:08, 5.86s/it]
84%|████████▍ | 10018/11952 [1:23:56<3:08:07, 5.84s/it]
{'loss': 0.4727, 'learning_rate': 1.3422311102564134e-06, 'epoch': 0.84}
+
84%|████████▍ | 10018/11952 [1:23:56<3:08:07, 5.84s/it]
84%|████████▍ | 10019/11952 [1:24:02<3:07:40, 5.83s/it]
{'loss': 0.4818, 'learning_rate': 1.340875309976799e-06, 'epoch': 0.84}
+
84%|████████▍ | 10019/11952 [1:24:02<3:07:40, 5.83s/it]
84%|████████▍ | 10020/11952 [1:24:08<3:09:04, 5.87s/it]
{'loss': 0.4737, 'learning_rate': 1.3395201455872886e-06, 'epoch': 0.84}
+
84%|████████▍ | 10020/11952 [1:24:08<3:09:04, 5.87s/it]
84%|████████▍ | 10021/11952 [1:24:14<3:08:27, 5.86s/it]
{'loss': 0.4683, 'learning_rate': 1.3381656171873936e-06, 'epoch': 0.84}
+
84%|████████▍ | 10021/11952 [1:24:14<3:08:27, 5.86s/it]
84%|████████▍ | 10022/11952 [1:24:20<3:09:11, 5.88s/it]
{'loss': 0.4708, 'learning_rate': 1.336811724876592e-06, 'epoch': 0.84}
+
84%|████████▍ | 10022/11952 [1:24:20<3:09:11, 5.88s/it]
84%|████████▍ | 10023/11952 [1:24:26<3:10:12, 5.92s/it]
{'loss': 0.4664, 'learning_rate': 1.3354584687543037e-06, 'epoch': 0.84}
+
84%|████████▍ | 10023/11952 [1:24:26<3:10:12, 5.92s/it]
84%|████████▍ | 10024/11952 [1:24:31<3:10:00, 5.91s/it]
{'loss': 0.4535, 'learning_rate': 1.3341058489199065e-06, 'epoch': 0.84}
+
84%|████████▍ | 10024/11952 [1:24:31<3:10:00, 5.91s/it]
84%|████████▍ | 10025/11952 [1:24:38<3:12:01, 5.98s/it]
{'loss': 0.4832, 'learning_rate': 1.3327538654727323e-06, 'epoch': 0.84}
+
84%|████████▍ | 10025/11952 [1:24:38<3:12:01, 5.98s/it]
84%|████████▍ | 10026/11952 [1:24:44<3:12:30, 6.00s/it]
{'loss': 0.4402, 'learning_rate': 1.3314025185120616e-06, 'epoch': 0.84}
+
84%|████████▍ | 10026/11952 [1:24:44<3:12:30, 6.00s/it]
84%|████████▍ | 10027/11952 [1:24:49<3:09:34, 5.91s/it]
{'loss': 0.4713, 'learning_rate': 1.3300518081371373e-06, 'epoch': 0.84}
+
84%|████████▍ | 10027/11952 [1:24:49<3:09:34, 5.91s/it]
84%|████████▍ | 10028/11952 [1:24:55<3:07:19, 5.84s/it]
{'loss': 0.4847, 'learning_rate': 1.3287017344471477e-06, 'epoch': 0.84}
+
84%|████████▍ | 10028/11952 [1:24:55<3:07:19, 5.84s/it]
84%|████████▍ | 10029/11952 [1:25:01<3:08:39, 5.89s/it]
{'loss': 0.485, 'learning_rate': 1.3273522975412344e-06, 'epoch': 0.84}
+
84%|████████▍ | 10029/11952 [1:25:01<3:08:39, 5.89s/it]
84%|████████▍ | 10030/11952 [1:25:07<3:11:08, 5.97s/it]
{'loss': 0.4526, 'learning_rate': 1.3260034975184955e-06, 'epoch': 0.84}
+
84%|████████▍ | 10030/11952 [1:25:07<3:11:08, 5.97s/it]
84%|████████▍ | 10031/11952 [1:25:13<3:07:52, 5.87s/it]
{'loss': 0.4636, 'learning_rate': 1.3246553344779834e-06, 'epoch': 0.84}
+
84%|████████▍ | 10031/11952 [1:25:13<3:07:52, 5.87s/it]
84%|████████▍ | 10032/11952 [1:25:19<3:06:49, 5.84s/it]
{'loss': 0.4618, 'learning_rate': 1.3233078085187002e-06, 'epoch': 0.84}
+
84%|████████▍ | 10032/11952 [1:25:19<3:06:49, 5.84s/it]
84%|████████▍ | 10033/11952 [1:25:24<3:06:22, 5.83s/it]
{'loss': 0.4777, 'learning_rate': 1.3219609197396e-06, 'epoch': 0.84}
+
84%|████████▍ | 10033/11952 [1:25:24<3:06:22, 5.83s/it]
84%|████████▍ | 10034/11952 [1:25:30<3:07:54, 5.88s/it]
{'loss': 0.4768, 'learning_rate': 1.3206146682395983e-06, 'epoch': 0.84}
+
84%|████████▍ | 10034/11952 [1:25:30<3:07:54, 5.88s/it]
84%|████████▍ | 10035/11952 [1:25:36<3:06:39, 5.84s/it]
{'loss': 0.469, 'learning_rate': 1.3192690541175536e-06, 'epoch': 0.84}
+
84%|████████▍ | 10035/11952 [1:25:36<3:06:39, 5.84s/it]
84%|████████▍ | 10036/11952 [1:25:42<3:06:10, 5.83s/it]
{'loss': 0.4677, 'learning_rate': 1.3179240774722845e-06, 'epoch': 0.84}
+
84%|████████▍ | 10036/11952 [1:25:42<3:06:10, 5.83s/it]
84%|████████▍ | 10037/11952 [1:25:48<3:08:26, 5.90s/it]
{'loss': 0.4521, 'learning_rate': 1.3165797384025602e-06, 'epoch': 0.84}
+
84%|████████▍ | 10037/11952 [1:25:48<3:08:26, 5.90s/it]
84%|████████▍ | 10038/11952 [1:25:54<3:05:30, 5.82s/it]
{'loss': 0.458, 'learning_rate': 1.3152360370071016e-06, 'epoch': 0.84}
+
84%|████████▍ | 10038/11952 [1:25:54<3:05:30, 5.82s/it]
84%|████████▍ | 10039/11952 [1:26:00<3:06:42, 5.86s/it]
{'loss': 0.4684, 'learning_rate': 1.3138929733845873e-06, 'epoch': 0.84}
+
84%|████████▍ | 10039/11952 [1:26:00<3:06:42, 5.86s/it]
84%|████████▍ | 10040/11952 [1:26:05<3:07:03, 5.87s/it]
{'loss': 0.4928, 'learning_rate': 1.3125505476336408e-06, 'epoch': 0.84}
+
84%|████████▍ | 10040/11952 [1:26:05<3:07:03, 5.87s/it]
84%|████████▍ | 10041/11952 [1:26:11<3:07:37, 5.89s/it]
{'loss': 0.4457, 'learning_rate': 1.31120875985285e-06, 'epoch': 0.84}
+
84%|████████▍ | 10041/11952 [1:26:11<3:07:37, 5.89s/it]
84%|████████▍ | 10042/11952 [1:26:17<3:07:06, 5.88s/it]
{'loss': 0.4711, 'learning_rate': 1.3098676101407493e-06, 'epoch': 0.84}
+
84%|████████▍ | 10042/11952 [1:26:17<3:07:06, 5.88s/it]
84%|████████▍ | 10043/11952 [1:26:23<3:04:21, 5.79s/it]
{'loss': 0.4534, 'learning_rate': 1.3085270985958276e-06, 'epoch': 0.84}
+
84%|████████▍ | 10043/11952 [1:26:23<3:04:21, 5.79s/it]
84%|████████▍ | 10044/11952 [1:26:29<3:08:28, 5.93s/it]
{'loss': 0.4645, 'learning_rate': 1.307187225316524e-06, 'epoch': 0.84}
+
84%|████████▍ | 10044/11952 [1:26:29<3:08:28, 5.93s/it]
84%|████████▍ | 10045/11952 [1:26:35<3:09:07, 5.95s/it]
{'loss': 0.4482, 'learning_rate': 1.3058479904012356e-06, 'epoch': 0.84}
+
84%|████████▍ | 10045/11952 [1:26:35<3:09:07, 5.95s/it]
84%|████████▍ | 10046/11952 [1:26:41<3:10:30, 6.00s/it]
{'loss': 0.4551, 'learning_rate': 1.3045093939483066e-06, 'epoch': 0.84}
+
84%|████████▍ | 10046/11952 [1:26:41<3:10:30, 6.00s/it]
84%|████████▍ | 10047/11952 [1:26:47<3:10:18, 5.99s/it]
{'loss': 0.4767, 'learning_rate': 1.303171436056042e-06, 'epoch': 0.84}
+
84%|████████▍ | 10047/11952 [1:26:47<3:10:18, 5.99s/it]
84%|████████▍ | 10048/11952 [1:26:53<3:08:30, 5.94s/it]
{'loss': 0.4526, 'learning_rate': 1.3018341168226944e-06, 'epoch': 0.84}
+
84%|████████▍ | 10048/11952 [1:26:53<3:08:30, 5.94s/it]
84%|████████▍ | 10049/11952 [1:26:59<3:05:58, 5.86s/it]
{'loss': 0.4568, 'learning_rate': 1.3004974363464717e-06, 'epoch': 0.84}
+
84%|████████▍ | 10049/11952 [1:26:59<3:05:58, 5.86s/it]5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
84%|████████▍ | 10050/11952 [1:27:05<3:05:30, 5.85s/it]
{'loss': 0.4566, 'learning_rate': 1.2991613947255321e-06, 'epoch': 0.84}
+
84%|████████▍ | 10050/11952 [1:27:05<3:05:30, 5.85s/it]
84%|████████▍ | 10051/11952 [1:27:10<3:04:25, 5.82s/it]
{'loss': 0.4475, 'learning_rate': 1.2978259920579895e-06, 'epoch': 0.84}
+
84%|████████▍ | 10051/11952 [1:27:10<3:04:25, 5.82s/it]
84%|████████▍ | 10052/11952 [1:27:16<3:05:02, 5.84s/it]
{'loss': 0.4601, 'learning_rate': 1.2964912284419119e-06, 'epoch': 0.84}
+
84%|████████▍ | 10052/11952 [1:27:16<3:05:02, 5.84s/it]
84%|████████▍ | 10053/11952 [1:27:22<3:04:35, 5.83s/it]
{'loss': 0.4661, 'learning_rate': 1.2951571039753163e-06, 'epoch': 0.84}
+
84%|████████▍ | 10053/11952 [1:27:22<3:04:35, 5.83s/it]
84%|████████▍ | 10054/11952 [1:27:28<3:04:33, 5.83s/it]
{'loss': 0.4581, 'learning_rate': 1.2938236187561782e-06, 'epoch': 0.84}
+
84%|████████▍ | 10054/11952 [1:27:28<3:04:33, 5.83s/it]
84%|████████▍ | 10055/11952 [1:27:34<3:09:04, 5.98s/it]
{'loss': 0.4995, 'learning_rate': 1.292490772882422e-06, 'epoch': 0.84}
+
84%|████████▍ | 10055/11952 [1:27:34<3:09:04, 5.98s/it]
84%|████████▍ | 10056/11952 [1:27:40<3:07:21, 5.93s/it]
{'loss': 0.4664, 'learning_rate': 1.2911585664519267e-06, 'epoch': 0.84}
+
84%|████████▍ | 10056/11952 [1:27:40<3:07:21, 5.93s/it]
84%|████████▍ | 10057/11952 [1:27:46<3:06:06, 5.89s/it]
{'loss': 0.4653, 'learning_rate': 1.2898269995625234e-06, 'epoch': 0.84}
+
84%|████████▍ | 10057/11952 [1:27:46<3:06:06, 5.89s/it]
84%|████████▍ | 10058/11952 [1:27:52<3:05:12, 5.87s/it]
{'loss': 0.4812, 'learning_rate': 1.2884960723119978e-06, 'epoch': 0.84}
+
84%|████████▍ | 10058/11952 [1:27:52<3:05:12, 5.87s/it]
84%|████████▍ | 10059/11952 [1:27:58<3:07:33, 5.94s/it]
{'loss': 0.4597, 'learning_rate': 1.2871657847980856e-06, 'epoch': 0.84}
+
84%|████████▍ | 10059/11952 [1:27:58<3:07:33, 5.94s/it]
84%|████████▍ | 10060/11952 [1:28:04<3:09:21, 6.00s/it]
{'loss': 0.4648, 'learning_rate': 1.285836137118477e-06, 'epoch': 0.84}
+
84%|████████▍ | 10060/11952 [1:28:04<3:09:21, 6.00s/it]
84%|████████▍ | 10061/11952 [1:28:10<3:08:03, 5.97s/it]
{'loss': 0.4471, 'learning_rate': 1.2845071293708188e-06, 'epoch': 0.84}
+
84%|████████▍ | 10061/11952 [1:28:10<3:08:03, 5.97s/it]
84%|████████▍ | 10062/11952 [1:28:16<3:07:46, 5.96s/it]
{'loss': 0.4796, 'learning_rate': 1.2831787616527058e-06, 'epoch': 0.84}
+
84%|████████▍ | 10062/11952 [1:28:16<3:07:46, 5.96s/it]
84%|████████▍ | 10063/11952 [1:28:22<3:11:05, 6.07s/it]
{'loss': 0.4558, 'learning_rate': 1.2818510340616896e-06, 'epoch': 0.84}
+
84%|████████▍ | 10063/11952 [1:28:22<3:11:05, 6.07s/it]
84%|████████▍ | 10064/11952 [1:28:28<3:10:56, 6.07s/it]
{'loss': 0.4706, 'learning_rate': 1.2805239466952723e-06, 'epoch': 0.84}
+
84%|████████▍ | 10064/11952 [1:28:28<3:10:56, 6.07s/it]
84%|████████▍ | 10065/11952 [1:28:34<3:10:37, 6.06s/it]
{'loss': 0.4646, 'learning_rate': 1.2791974996509094e-06, 'epoch': 0.84}
+
84%|████████▍ | 10065/11952 [1:28:34<3:10:37, 6.06s/it]
84%|████████▍ | 10066/11952 [1:28:40<3:09:39, 6.03s/it]
{'loss': 0.4734, 'learning_rate': 1.2778716930260105e-06, 'epoch': 0.84}
+
84%|████████▍ | 10066/11952 [1:28:40<3:09:39, 6.03s/it]
84%|████████▍ | 10067/11952 [1:28:46<3:12:17, 6.12s/it]
{'loss': 0.4534, 'learning_rate': 1.2765465269179334e-06, 'epoch': 0.84}
+
84%|████████▍ | 10067/11952 [1:28:46<3:12:17, 6.12s/it]
84%|████████▍ | 10068/11952 [1:28:52<3:07:57, 5.99s/it]
{'loss': 0.4768, 'learning_rate': 1.275222001423998e-06, 'epoch': 0.84}
+
84%|████████▍ | 10068/11952 [1:28:52<3:07:57, 5.99s/it]
84%|████████▍ | 10069/11952 [1:28:58<3:05:39, 5.92s/it]
{'loss': 0.467, 'learning_rate': 1.2738981166414688e-06, 'epoch': 0.84}
+
84%|████████▍ | 10069/11952 [1:28:58<3:05:39, 5.92s/it]
84%|████████▍ | 10070/11952 [1:29:04<3:08:12, 6.00s/it]
{'loss': 0.4768, 'learning_rate': 1.2725748726675691e-06, 'epoch': 0.84}
+
84%|████████▍ | 10070/11952 [1:29:04<3:08:12, 6.00s/it]
84%|████████▍ | 10071/11952 [1:29:10<3:05:38, 5.92s/it]
{'loss': 0.4946, 'learning_rate': 1.2712522695994666e-06, 'epoch': 0.84}
+
84%|████████▍ | 10071/11952 [1:29:10<3:05:38, 5.92s/it]
84%|████████▍ | 10072/11952 [1:29:16<3:07:13, 5.98s/it]
{'loss': 0.4539, 'learning_rate': 1.269930307534295e-06, 'epoch': 0.84}
+
84%|████████▍ | 10072/11952 [1:29:16<3:07:13, 5.98s/it]
84%|████████▍ | 10073/11952 [1:29:22<3:10:27, 6.08s/it]
{'loss': 0.4647, 'learning_rate': 1.268608986569131e-06, 'epoch': 0.84}
+
84%|████████▍ | 10073/11952 [1:29:22<3:10:27, 6.08s/it]
84%|████████▍ | 10074/11952 [1:29:28<3:08:06, 6.01s/it]
{'loss': 0.4726, 'learning_rate': 1.2672883068010033e-06, 'epoch': 0.84}
+
84%|████████▍ | 10074/11952 [1:29:28<3:08:06, 6.01s/it]
84%|████████▍ | 10075/11952 [1:29:34<3:09:20, 6.05s/it]
{'loss': 0.4771, 'learning_rate': 1.2659682683269036e-06, 'epoch': 0.84}
+
84%|████████▍ | 10075/11952 [1:29:34<3:09:20, 6.05s/it]
84%|████████▍ | 10076/11952 [1:29:40<3:06:04, 5.95s/it]
{'loss': 0.4556, 'learning_rate': 1.2646488712437654e-06, 'epoch': 0.84}
+
84%|████████▍ | 10076/11952 [1:29:40<3:06:04, 5.95s/it]
84%|████████▍ | 10077/11952 [1:29:46<3:06:21, 5.96s/it]
{'loss': 0.4647, 'learning_rate': 1.2633301156484822e-06, 'epoch': 0.84}
+
84%|████████▍ | 10077/11952 [1:29:46<3:06:21, 5.96s/it]
84%|████████▍ | 10078/11952 [1:29:51<3:03:04, 5.86s/it]
{'loss': 0.4549, 'learning_rate': 1.2620120016378956e-06, 'epoch': 0.84}
+
84%|████████▍ | 10078/11952 [1:29:51<3:03:04, 5.86s/it]
84%|████████▍ | 10079/11952 [1:29:57<3:02:47, 5.86s/it]
{'loss': 0.4467, 'learning_rate': 1.2606945293088047e-06, 'epoch': 0.84}
+
84%|████████▍ | 10079/11952 [1:29:57<3:02:47, 5.86s/it]
84%|████████▍ | 10080/11952 [1:30:03<3:01:31, 5.82s/it]
{'loss': 0.4639, 'learning_rate': 1.2593776987579576e-06, 'epoch': 0.84}
+
84%|████████▍ | 10080/11952 [1:30:03<3:01:31, 5.82s/it]
84%|████████▍ | 10081/11952 [1:30:09<3:02:49, 5.86s/it]
{'loss': 0.4664, 'learning_rate': 1.2580615100820548e-06, 'epoch': 0.84}
+
84%|████████▍ | 10081/11952 [1:30:09<3:02:49, 5.86s/it]
84%|████████▍ | 10082/11952 [1:30:15<3:08:03, 6.03s/it]
{'loss': 0.4634, 'learning_rate': 1.2567459633777567e-06, 'epoch': 0.84}
+
84%|████████▍ | 10082/11952 [1:30:15<3:08:03, 6.03s/it]
84%|████████▍ | 10083/11952 [1:30:21<3:05:48, 5.96s/it]
{'loss': 0.4713, 'learning_rate': 1.2554310587416674e-06, 'epoch': 0.84}
+
84%|████████▍ | 10083/11952 [1:30:21<3:05:48, 5.96s/it]
84%|████████▍ | 10084/11952 [1:30:27<3:07:19, 6.02s/it]
{'loss': 0.4783, 'learning_rate': 1.2541167962703515e-06, 'epoch': 0.84}
+
84%|████████▍ | 10084/11952 [1:30:27<3:07:19, 6.02s/it]
84%|████████▍ | 10085/11952 [1:30:33<3:05:52, 5.97s/it]
{'loss': 0.4557, 'learning_rate': 1.252803176060321e-06, 'epoch': 0.84}
+
84%|████████▍ | 10085/11952 [1:30:33<3:05:52, 5.97s/it]
84%|████████▍ | 10086/11952 [1:30:39<3:03:14, 5.89s/it]
{'loss': 0.4748, 'learning_rate': 1.251490198208043e-06, 'epoch': 0.84}
+
84%|████████▍ | 10086/11952 [1:30:39<3:03:14, 5.89s/it]
84%|████████▍ | 10087/11952 [1:30:45<3:04:55, 5.95s/it]
{'loss': 0.4805, 'learning_rate': 1.2501778628099349e-06, 'epoch': 0.84}
+
84%|████████▍ | 10087/11952 [1:30:45<3:04:55, 5.95s/it]
84%|████████▍ | 10088/11952 [1:30:51<3:03:33, 5.91s/it]
{'loss': 0.4657, 'learning_rate': 1.2488661699623739e-06, 'epoch': 0.84}
+
84%|████████▍ | 10088/11952 [1:30:51<3:03:33, 5.91s/it]
84%|████████▍ | 10089/11952 [1:30:57<3:02:43, 5.88s/it]
{'loss': 0.4644, 'learning_rate': 1.247555119761682e-06, 'epoch': 0.84}
+
84%|████████▍ | 10089/11952 [1:30:57<3:02:43, 5.88s/it]
84%|████████▍ | 10090/11952 [1:31:03<3:04:12, 5.94s/it]
{'loss': 0.464, 'learning_rate': 1.2462447123041388e-06, 'epoch': 0.84}
+
84%|████████▍ | 10090/11952 [1:31:03<3:04:12, 5.94s/it]
84%|████████▍ | 10091/11952 [1:31:09<3:04:30, 5.95s/it]
{'loss': 0.4735, 'learning_rate': 1.244934947685974e-06, 'epoch': 0.84}
+
84%|████████▍ | 10091/11952 [1:31:09<3:04:30, 5.95s/it]
84%|████████▍ | 10092/11952 [1:31:14<3:02:41, 5.89s/it]
{'loss': 0.4721, 'learning_rate': 1.2436258260033696e-06, 'epoch': 0.84}
+
84%|████████▍ | 10092/11952 [1:31:14<3:02:41, 5.89s/it]
84%|████████▍ | 10093/11952 [1:31:20<3:00:13, 5.82s/it]
{'loss': 0.4823, 'learning_rate': 1.2423173473524653e-06, 'epoch': 0.84}
+
84%|████████▍ | 10093/11952 [1:31:20<3:00:13, 5.82s/it]
84%|████████▍ | 10094/11952 [1:31:26<3:02:19, 5.89s/it]
{'loss': 0.4499, 'learning_rate': 1.2410095118293475e-06, 'epoch': 0.84}
+
84%|████████▍ | 10094/11952 [1:31:26<3:02:19, 5.89s/it]
84%|████████▍ | 10095/11952 [1:31:32<3:04:22, 5.96s/it]
{'loss': 0.4769, 'learning_rate': 1.2397023195300618e-06, 'epoch': 0.84}
+
84%|████████▍ | 10095/11952 [1:31:32<3:04:22, 5.96s/it]
84%|████████▍ | 10096/11952 [1:31:38<3:01:27, 5.87s/it]
{'loss': 0.4584, 'learning_rate': 1.238395770550601e-06, 'epoch': 0.84}
+
84%|████████▍ | 10096/11952 [1:31:38<3:01:27, 5.87s/it]
84%|████████▍ | 10097/11952 [1:31:44<3:04:12, 5.96s/it]
{'loss': 0.4785, 'learning_rate': 1.2370898649869122e-06, 'epoch': 0.84}
+
84%|████████▍ | 10097/11952 [1:31:44<3:04:12, 5.96s/it]
84%|████████▍ | 10098/11952 [1:31:50<3:06:18, 6.03s/it]
{'loss': 0.461, 'learning_rate': 1.2357846029348975e-06, 'epoch': 0.84}
+
84%|████████▍ | 10098/11952 [1:31:50<3:06:18, 6.03s/it]
84%|████████▍ | 10099/11952 [1:31:56<3:05:17, 6.00s/it]
{'loss': 0.4563, 'learning_rate': 1.2344799844904065e-06, 'epoch': 0.84}
+
84%|████████▍ | 10099/11952 [1:31:56<3:05:17, 6.00s/it]2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+17 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+0 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
85%|████████▍ | 10100/11952 [1:32:02<3:06:37, 6.05s/it]
{'loss': 0.4628, 'learning_rate': 1.2331760097492485e-06, 'epoch': 0.85}
+
85%|████████▍ | 10100/11952 [1:32:02<3:06:37, 6.05s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
85%|████████▍ | 10101/11952 [1:32:34<6:59:33, 13.60s/it]
{'loss': 0.4704, 'learning_rate': 1.2318726788071767e-06, 'epoch': 0.85}
+
85%|████████▍ | 10101/11952 [1:32:34<6:59:33, 13.60s/it]
85%|████████▍ | 10102/11952 [1:32:40<5:48:31, 11.30s/it]
{'loss': 0.473, 'learning_rate': 1.230569991759909e-06, 'epoch': 0.85}
+
85%|████████▍ | 10102/11952 [1:32:40<5:48:31, 11.30s/it]
85%|████████▍ | 10103/11952 [1:32:45<4:56:33, 9.62s/it]
{'loss': 0.4632, 'learning_rate': 1.2292679487031045e-06, 'epoch': 0.85}
+
85%|████████▍ | 10103/11952 [1:32:45<4:56:33, 9.62s/it]
85%|████████▍ | 10104/11952 [1:32:51<4:22:50, 8.53s/it]
{'loss': 0.4495, 'learning_rate': 1.2279665497323835e-06, 'epoch': 0.85}
+
85%|████████▍ | 10104/11952 [1:32:51<4:22:50, 8.53s/it]
85%|████████▍ | 10105/11952 [1:32:58<4:01:33, 7.85s/it]
{'loss': 0.4662, 'learning_rate': 1.2266657949433135e-06, 'epoch': 0.85}
+
85%|████████▍ | 10105/11952 [1:32:58<4:01:33, 7.85s/it]
85%|████████▍ | 10106/11952 [1:33:03<3:42:28, 7.23s/it]
{'loss': 0.4628, 'learning_rate': 1.2253656844314155e-06, 'epoch': 0.85}
+
85%|████████▍ | 10106/11952 [1:33:03<3:42:28, 7.23s/it]
85%|████████▍ | 10107/11952 [1:33:09<3:29:55, 6.83s/it]
{'loss': 0.4859, 'learning_rate': 1.224066218292167e-06, 'epoch': 0.85}
+
85%|████████▍ | 10107/11952 [1:33:09<3:29:55, 6.83s/it]
85%|████████▍ | 10108/11952 [1:33:16<3:28:11, 6.77s/it]
{'loss': 0.4671, 'learning_rate': 1.2227673966209896e-06, 'epoch': 0.85}
+
85%|████████▍ | 10108/11952 [1:33:16<3:28:11, 6.77s/it]
85%|████████▍ | 10109/11952 [1:33:22<3:19:05, 6.48s/it]
{'loss': 0.4454, 'learning_rate': 1.2214692195132705e-06, 'epoch': 0.85}
+
85%|████████▍ | 10109/11952 [1:33:22<3:19:05, 6.48s/it]
85%|████████▍ | 10110/11952 [1:33:28<3:16:33, 6.40s/it]
{'loss': 0.458, 'learning_rate': 1.2201716870643388e-06, 'epoch': 0.85}
+
85%|████████▍ | 10110/11952 [1:33:28<3:16:33, 6.40s/it]
85%|████████▍ | 10111/11952 [1:33:33<3:09:16, 6.17s/it]
{'loss': 0.452, 'learning_rate': 1.2188747993694805e-06, 'epoch': 0.85}
+
85%|████████▍ | 10111/11952 [1:33:33<3:09:16, 6.17s/it]
85%|████████▍ | 10112/11952 [1:33:39<3:06:51, 6.09s/it]
{'loss': 0.4621, 'learning_rate': 1.217578556523934e-06, 'epoch': 0.85}
+
85%|████████▍ | 10112/11952 [1:33:39<3:06:51, 6.09s/it]
85%|████████▍ | 10113/11952 [1:33:45<3:03:37, 5.99s/it]
{'loss': 0.4471, 'learning_rate': 1.2162829586228874e-06, 'epoch': 0.85}
+
85%|████████▍ | 10113/11952 [1:33:45<3:03:37, 5.99s/it]
85%|████████▍ | 10114/11952 [1:33:51<3:01:55, 5.94s/it]
{'loss': 0.4653, 'learning_rate': 1.214988005761487e-06, 'epoch': 0.85}
+
85%|████████▍ | 10114/11952 [1:33:51<3:01:55, 5.94s/it]
85%|████████▍ | 10115/11952 [1:33:57<3:00:19, 5.89s/it]
{'loss': 0.4649, 'learning_rate': 1.2136936980348267e-06, 'epoch': 0.85}
+
85%|████████▍ | 10115/11952 [1:33:57<3:00:19, 5.89s/it]
85%|████████▍ | 10116/11952 [1:34:03<2:59:53, 5.88s/it]
{'loss': 0.4577, 'learning_rate': 1.2124000355379583e-06, 'epoch': 0.85}
+
85%|████████▍ | 10116/11952 [1:34:03<2:59:53, 5.88s/it]
85%|████████▍ | 10117/11952 [1:34:09<3:00:10, 5.89s/it]
{'loss': 0.4553, 'learning_rate': 1.21110701836588e-06, 'epoch': 0.85}
+
85%|████████▍ | 10117/11952 [1:34:09<3:00:10, 5.89s/it]
85%|████████▍ | 10118/11952 [1:34:14<3:00:38, 5.91s/it]
{'loss': 0.4912, 'learning_rate': 1.2098146466135475e-06, 'epoch': 0.85}
+
85%|████████▍ | 10118/11952 [1:34:14<3:00:38, 5.91s/it]
85%|████████▍ | 10119/11952 [1:34:20<3:01:20, 5.94s/it]
{'loss': 0.4616, 'learning_rate': 1.2085229203758663e-06, 'epoch': 0.85}
+
85%|████████▍ | 10119/11952 [1:34:20<3:01:20, 5.94s/it]
85%|████████▍ | 10120/11952 [1:34:26<2:59:28, 5.88s/it]
{'loss': 0.4577, 'learning_rate': 1.2072318397476945e-06, 'epoch': 0.85}
+
85%|████████▍ | 10120/11952 [1:34:26<2:59:28, 5.88s/it]
85%|████████▍ | 10121/11952 [1:34:32<2:59:46, 5.89s/it]
{'loss': 0.4583, 'learning_rate': 1.2059414048238437e-06, 'epoch': 0.85}
+
85%|████████▍ | 10121/11952 [1:34:32<2:59:46, 5.89s/it]
85%|████████▍ | 10122/11952 [1:34:38<2:59:11, 5.88s/it]
{'loss': 0.4592, 'learning_rate': 1.2046516156990796e-06, 'epoch': 0.85}
+
85%|████████▍ | 10122/11952 [1:34:38<2:59:11, 5.88s/it]
85%|████████▍ | 10123/11952 [1:34:44<2:58:25, 5.85s/it]
{'loss': 0.468, 'learning_rate': 1.2033624724681191e-06, 'epoch': 0.85}
+
85%|████████▍ | 10123/11952 [1:34:44<2:58:25, 5.85s/it]
85%|████████▍ | 10124/11952 [1:34:49<2:56:38, 5.80s/it]
{'loss': 0.4817, 'learning_rate': 1.2020739752256282e-06, 'epoch': 0.85}
+
85%|████████▍ | 10124/11952 [1:34:49<2:56:38, 5.80s/it]
85%|████████▍ | 10125/11952 [1:34:55<2:57:29, 5.83s/it]
{'loss': 0.4542, 'learning_rate': 1.2007861240662334e-06, 'epoch': 0.85}
+
85%|████████▍ | 10125/11952 [1:34:55<2:57:29, 5.83s/it]
85%|████████▍ | 10126/11952 [1:35:01<2:57:20, 5.83s/it]
{'loss': 0.4465, 'learning_rate': 1.1994989190845075e-06, 'epoch': 0.85}
+
85%|████████▍ | 10126/11952 [1:35:01<2:57:20, 5.83s/it]
85%|████████▍ | 10127/11952 [1:35:07<2:55:23, 5.77s/it]
{'loss': 0.455, 'learning_rate': 1.1982123603749762e-06, 'epoch': 0.85}
+
85%|████████▍ | 10127/11952 [1:35:07<2:55:23, 5.77s/it]
85%|████████▍ | 10128/11952 [1:35:13<2:56:34, 5.81s/it]
{'loss': 0.465, 'learning_rate': 1.1969264480321175e-06, 'epoch': 0.85}
+
85%|████████▍ | 10128/11952 [1:35:13<2:56:34, 5.81s/it]
85%|████████▍ | 10129/11952 [1:35:19<2:57:42, 5.85s/it]
{'loss': 0.462, 'learning_rate': 1.1956411821503688e-06, 'epoch': 0.85}
+
85%|████████▍ | 10129/11952 [1:35:19<2:57:42, 5.85s/it]
85%|████████▍ | 10130/11952 [1:35:24<2:57:05, 5.83s/it]
{'loss': 0.4554, 'learning_rate': 1.1943565628241105e-06, 'epoch': 0.85}
+
85%|████████▍ | 10130/11952 [1:35:24<2:57:05, 5.83s/it]
85%|████████▍ | 10131/11952 [1:35:30<2:56:31, 5.82s/it]
{'loss': 0.4542, 'learning_rate': 1.1930725901476814e-06, 'epoch': 0.85}
+
85%|████████▍ | 10131/11952 [1:35:30<2:56:31, 5.82s/it]
85%|████████▍ | 10132/11952 [1:35:36<2:57:31, 5.85s/it]
{'loss': 0.469, 'learning_rate': 1.1917892642153706e-06, 'epoch': 0.85}
+
85%|████████▍ | 10132/11952 [1:35:36<2:57:31, 5.85s/it]
85%|████████▍ | 10133/11952 [1:35:42<3:00:01, 5.94s/it]
{'loss': 0.4819, 'learning_rate': 1.190506585121418e-06, 'epoch': 0.85}
+
85%|████████▍ | 10133/11952 [1:35:42<3:00:01, 5.94s/it]
85%|████████▍ | 10134/11952 [1:35:48<2:58:02, 5.88s/it]
{'loss': 0.4757, 'learning_rate': 1.1892245529600222e-06, 'epoch': 0.85}
+
85%|████████▍ | 10134/11952 [1:35:48<2:58:02, 5.88s/it]
85%|████████▍ | 10135/11952 [1:35:54<2:56:18, 5.82s/it]
{'loss': 0.4704, 'learning_rate': 1.1879431678253261e-06, 'epoch': 0.85}
+
85%|████████▍ | 10135/11952 [1:35:54<2:56:18, 5.82s/it]
85%|████████▍ | 10136/11952 [1:36:00<2:57:37, 5.87s/it]
{'loss': 0.459, 'learning_rate': 1.1866624298114338e-06, 'epoch': 0.85}
+
85%|████████▍ | 10136/11952 [1:36:00<2:57:37, 5.87s/it]
85%|████████▍ | 10137/11952 [1:36:06<2:58:38, 5.91s/it]
{'loss': 0.4646, 'learning_rate': 1.1853823390123964e-06, 'epoch': 0.85}
+
85%|████████▍ | 10137/11952 [1:36:06<2:58:38, 5.91s/it]
85%|████████▍ | 10138/11952 [1:36:12<2:57:44, 5.88s/it]
{'loss': 0.4662, 'learning_rate': 1.1841028955222155e-06, 'epoch': 0.85}
+
85%|████████▍ | 10138/11952 [1:36:12<2:57:44, 5.88s/it]
85%|████████▍ | 10139/11952 [1:36:18<2:59:44, 5.95s/it]
{'loss': 0.4671, 'learning_rate': 1.1828240994348517e-06, 'epoch': 0.85}
+
85%|████████▍ | 10139/11952 [1:36:18<2:59:44, 5.95s/it]
85%|████████▍ | 10140/11952 [1:36:23<2:58:50, 5.92s/it]
{'loss': 0.4511, 'learning_rate': 1.1815459508442118e-06, 'epoch': 0.85}
+
85%|████████▍ | 10140/11952 [1:36:23<2:58:50, 5.92s/it]
85%|████████▍ | 10141/11952 [1:36:30<3:00:32, 5.98s/it]
{'loss': 0.4797, 'learning_rate': 1.1802684498441585e-06, 'epoch': 0.85}
+
85%|████████▍ | 10141/11952 [1:36:30<3:00:32, 5.98s/it]
85%|████████▍ | 10142/11952 [1:36:35<2:58:13, 5.91s/it]
{'loss': 0.4553, 'learning_rate': 1.1789915965285037e-06, 'epoch': 0.85}
+
85%|████████▍ | 10142/11952 [1:36:35<2:58:13, 5.91s/it]
85%|████████▍ | 10143/11952 [1:36:42<3:00:32, 5.99s/it]
{'loss': 0.4775, 'learning_rate': 1.177715390991019e-06, 'epoch': 0.85}
+
85%|████████▍ | 10143/11952 [1:36:42<3:00:32, 5.99s/it]
85%|████████▍ | 10144/11952 [1:36:47<2:58:20, 5.92s/it]
{'loss': 0.4567, 'learning_rate': 1.1764398333254202e-06, 'epoch': 0.85}
+
85%|████████▍ | 10144/11952 [1:36:47<2:58:20, 5.92s/it]
85%|████████▍ | 10145/11952 [1:36:53<2:58:25, 5.92s/it]
{'loss': 0.4767, 'learning_rate': 1.1751649236253815e-06, 'epoch': 0.85}
+
85%|████████▍ | 10145/11952 [1:36:53<2:58:25, 5.92s/it]
85%|████████▍ | 10146/11952 [1:36:59<3:01:03, 6.02s/it]
{'loss': 0.4722, 'learning_rate': 1.1738906619845248e-06, 'epoch': 0.85}
+
85%|████████▍ | 10146/11952 [1:36:59<3:01:03, 6.02s/it]
85%|████████▍ | 10147/11952 [1:37:06<3:01:55, 6.05s/it]
{'loss': 0.4849, 'learning_rate': 1.1726170484964282e-06, 'epoch': 0.85}
+
85%|████████▍ | 10147/11952 [1:37:06<3:01:55, 6.05s/it]
85%|████████▍ | 10148/11952 [1:37:11<2:58:56, 5.95s/it]
{'loss': 0.4432, 'learning_rate': 1.1713440832546196e-06, 'epoch': 0.85}
+
85%|████████▍ | 10148/11952 [1:37:11<2:58:56, 5.95s/it]
85%|████████▍ | 10149/11952 [1:37:17<2:58:33, 5.94s/it]
{'loss': 0.4562, 'learning_rate': 1.1700717663525784e-06, 'epoch': 0.85}
+
85%|████████▍ | 10149/11952 [1:37:17<2:58:33, 5.94s/it]7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
85%|████████▍ | 10150/11952 [1:37:23<2:58:09, 5.93s/it]
{'loss': 0.478, 'learning_rate': 1.1688000978837423e-06, 'epoch': 0.85}
+
85%|████████▍ | 10150/11952 [1:37:23<2:58:09, 5.93s/it]
85%|████████▍ | 10151/11952 [1:37:29<2:56:44, 5.89s/it]
{'loss': 0.4653, 'learning_rate': 1.1675290779414949e-06, 'epoch': 0.85}
+
85%|████████▍ | 10151/11952 [1:37:29<2:56:44, 5.89s/it]
85%|████████▍ | 10152/11952 [1:37:35<2:56:35, 5.89s/it]
{'loss': 0.4584, 'learning_rate': 1.1662587066191755e-06, 'epoch': 0.85}
+
85%|████████▍ | 10152/11952 [1:37:35<2:56:35, 5.89s/it]
85%|████████▍ | 10153/11952 [1:37:41<2:56:42, 5.89s/it]
{'loss': 0.4666, 'learning_rate': 1.1649889840100737e-06, 'epoch': 0.85}
+
85%|████████▍ | 10153/11952 [1:37:41<2:56:42, 5.89s/it]
85%|████████▍ | 10154/11952 [1:37:46<2:53:29, 5.79s/it]
{'loss': 0.4629, 'learning_rate': 1.1637199102074326e-06, 'epoch': 0.85}
+
85%|████████▍ | 10154/11952 [1:37:46<2:53:29, 5.79s/it]
85%|████████▍ | 10155/11952 [1:37:52<2:56:17, 5.89s/it]
{'loss': 0.4594, 'learning_rate': 1.1624514853044488e-06, 'epoch': 0.85}
+
85%|████████▍ | 10155/11952 [1:37:52<2:56:17, 5.89s/it]
85%|████████▍ | 10156/11952 [1:37:58<2:54:36, 5.83s/it]
{'loss': 0.4912, 'learning_rate': 1.1611837093942691e-06, 'epoch': 0.85}
+
85%|████████▍ | 10156/11952 [1:37:58<2:54:36, 5.83s/it]
85%|████████▍ | 10157/11952 [1:38:04<2:57:01, 5.92s/it]
{'loss': 0.4794, 'learning_rate': 1.1599165825699955e-06, 'epoch': 0.85}
+
85%|████████▍ | 10157/11952 [1:38:04<2:57:01, 5.92s/it]
85%|████████▍ | 10158/11952 [1:38:10<2:55:02, 5.85s/it]
{'loss': 0.4589, 'learning_rate': 1.1586501049246801e-06, 'epoch': 0.85}
+
85%|████████▍ | 10158/11952 [1:38:10<2:55:02, 5.85s/it]
85%|████████▍ | 10159/11952 [1:38:16<2:54:02, 5.82s/it]
{'loss': 0.4812, 'learning_rate': 1.1573842765513266e-06, 'epoch': 0.85}
+
85%|████████▍ | 10159/11952 [1:38:16<2:54:02, 5.82s/it]
85%|████████▌ | 10160/11952 [1:38:22<2:55:10, 5.87s/it]
{'loss': 0.4629, 'learning_rate': 1.1561190975428926e-06, 'epoch': 0.85}
+
85%|████████▌ | 10160/11952 [1:38:22<2:55:10, 5.87s/it]
85%|████████▌ | 10161/11952 [1:38:27<2:55:05, 5.87s/it]
{'loss': 0.4512, 'learning_rate': 1.1548545679922885e-06, 'epoch': 0.85}
+
85%|████████▌ | 10161/11952 [1:38:27<2:55:05, 5.87s/it]
85%|████████▌ | 10162/11952 [1:38:33<2:52:30, 5.78s/it]
{'loss': 0.4553, 'learning_rate': 1.153590687992372e-06, 'epoch': 0.85}
+
85%|████████▌ | 10162/11952 [1:38:33<2:52:30, 5.78s/it]
85%|████████▌ | 10163/11952 [1:38:39<2:52:50, 5.80s/it]
{'loss': 0.4647, 'learning_rate': 1.1523274576359633e-06, 'epoch': 0.85}
+
85%|████████▌ | 10163/11952 [1:38:39<2:52:50, 5.80s/it]
85%|████████▌ | 10164/11952 [1:38:45<2:52:07, 5.78s/it]
{'loss': 0.4667, 'learning_rate': 1.151064877015825e-06, 'epoch': 0.85}
+
85%|████████▌ | 10164/11952 [1:38:45<2:52:07, 5.78s/it]
85%|████████▌ | 10165/11952 [1:38:51<2:53:46, 5.83s/it]
{'loss': 0.4664, 'learning_rate': 1.1498029462246752e-06, 'epoch': 0.85}
+
85%|████████▌ | 10165/11952 [1:38:51<2:53:46, 5.83s/it]
85%|████████▌ | 10166/11952 [1:38:57<2:54:40, 5.87s/it]
{'loss': 0.459, 'learning_rate': 1.1485416653551884e-06, 'epoch': 0.85}
+
85%|████████▌ | 10166/11952 [1:38:57<2:54:40, 5.87s/it]
85%|████████▌ | 10167/11952 [1:39:02<2:53:03, 5.82s/it]
{'loss': 0.4335, 'learning_rate': 1.1472810344999852e-06, 'epoch': 0.85}
+
85%|████████▌ | 10167/11952 [1:39:02<2:53:03, 5.82s/it]
85%|████████▌ | 10168/11952 [1:39:09<2:58:31, 6.00s/it]
{'loss': 0.4746, 'learning_rate': 1.1460210537516426e-06, 'epoch': 0.85}
+
85%|████████▌ | 10168/11952 [1:39:09<2:58:31, 6.00s/it]
85%|████████▌ | 10169/11952 [1:39:15<2:58:49, 6.02s/it]
{'loss': 0.4671, 'learning_rate': 1.1447617232026842e-06, 'epoch': 0.85}
+
85%|████████▌ | 10169/11952 [1:39:15<2:58:49, 6.02s/it]
85%|████████▌ | 10170/11952 [1:39:21<2:57:32, 5.98s/it]
{'loss': 0.4687, 'learning_rate': 1.1435030429455951e-06, 'epoch': 0.85}
+
85%|████████▌ | 10170/11952 [1:39:21<2:57:32, 5.98s/it]
85%|████████▌ | 10171/11952 [1:39:26<2:55:51, 5.92s/it]
{'loss': 0.4722, 'learning_rate': 1.1422450130728069e-06, 'epoch': 0.85}
+
85%|████████▌ | 10171/11952 [1:39:26<2:55:51, 5.92s/it]
85%|████████▌ | 10172/11952 [1:39:32<2:56:03, 5.93s/it]
{'loss': 0.4592, 'learning_rate': 1.1409876336767013e-06, 'epoch': 0.85}
+
85%|████████▌ | 10172/11952 [1:39:32<2:56:03, 5.93s/it]
85%|████████▌ | 10173/11952 [1:39:38<2:54:18, 5.88s/it]
{'loss': 0.4744, 'learning_rate': 1.1397309048496174e-06, 'epoch': 0.85}
+
85%|████████▌ | 10173/11952 [1:39:38<2:54:18, 5.88s/it]
85%|████████▌ | 10174/11952 [1:39:44<2:53:15, 5.85s/it]
{'loss': 0.4578, 'learning_rate': 1.1384748266838408e-06, 'epoch': 0.85}
+
85%|████████▌ | 10174/11952 [1:39:44<2:53:15, 5.85s/it]
85%|████████▌ | 10175/11952 [1:39:50<2:51:36, 5.79s/it]
{'loss': 0.467, 'learning_rate': 1.1372193992716175e-06, 'epoch': 0.85}
+
85%|████████▌ | 10175/11952 [1:39:50<2:51:36, 5.79s/it]
85%|████████▌ | 10176/11952 [1:39:56<2:53:07, 5.85s/it]
{'loss': 0.4537, 'learning_rate': 1.1359646227051357e-06, 'epoch': 0.85}
+
85%|████████▌ | 10176/11952 [1:39:56<2:53:07, 5.85s/it]
85%|████████▌ | 10177/11952 [1:40:02<2:57:20, 5.99s/it]
{'loss': 0.454, 'learning_rate': 1.1347104970765466e-06, 'epoch': 0.85}
+
85%|████████▌ | 10177/11952 [1:40:02<2:57:20, 5.99s/it]
85%|████████▌ | 10178/11952 [1:40:08<3:00:00, 6.09s/it]
{'loss': 0.475, 'learning_rate': 1.133457022477945e-06, 'epoch': 0.85}
+
85%|████████▌ | 10178/11952 [1:40:08<3:00:00, 6.09s/it]
85%|████████▌ | 10179/11952 [1:40:14<2:58:58, 6.06s/it]
{'loss': 0.4638, 'learning_rate': 1.1322041990013798e-06, 'epoch': 0.85}
+
85%|████████▌ | 10179/11952 [1:40:14<2:58:58, 6.06s/it]
85%|████████▌ | 10180/11952 [1:40:20<2:56:36, 5.98s/it]
{'loss': 0.4609, 'learning_rate': 1.130952026738855e-06, 'epoch': 0.85}
+
85%|████████▌ | 10180/11952 [1:40:20<2:56:36, 5.98s/it]
85%|████████▌ | 10181/11952 [1:40:26<2:55:08, 5.93s/it]
{'loss': 0.4676, 'learning_rate': 1.1297005057823251e-06, 'epoch': 0.85}
+
85%|████████▌ | 10181/11952 [1:40:26<2:55:08, 5.93s/it]
85%|████████▌ | 10182/11952 [1:40:32<2:53:56, 5.90s/it]
{'loss': 0.4789, 'learning_rate': 1.1284496362236952e-06, 'epoch': 0.85}
+
85%|████████▌ | 10182/11952 [1:40:32<2:53:56, 5.90s/it]
85%|████████▌ | 10183/11952 [1:40:38<2:54:52, 5.93s/it]
{'loss': 0.4718, 'learning_rate': 1.1271994181548217e-06, 'epoch': 0.85}
+
85%|████████▌ | 10183/11952 [1:40:38<2:54:52, 5.93s/it]
85%|████████▌ | 10184/11952 [1:40:43<2:52:45, 5.86s/it]
{'loss': 0.4717, 'learning_rate': 1.1259498516675204e-06, 'epoch': 0.85}
+
85%|████████▌ | 10184/11952 [1:40:43<2:52:45, 5.86s/it]
85%|████████▌ | 10185/11952 [1:40:49<2:51:15, 5.82s/it]
{'loss': 0.4607, 'learning_rate': 1.12470093685355e-06, 'epoch': 0.85}
+
85%|████████▌ | 10185/11952 [1:40:49<2:51:15, 5.82s/it]
85%|████████▌ | 10186/11952 [1:40:55<2:51:20, 5.82s/it]
{'loss': 0.4358, 'learning_rate': 1.1234526738046303e-06, 'epoch': 0.85}
+
85%|████████▌ | 10186/11952 [1:40:55<2:51:20, 5.82s/it]
85%|████████▌ | 10187/11952 [1:41:01<2:51:07, 5.82s/it]
{'loss': 0.474, 'learning_rate': 1.122205062612426e-06, 'epoch': 0.85}
+
85%|████████▌ | 10187/11952 [1:41:01<2:51:07, 5.82s/it]
85%|████████▌ | 10188/11952 [1:41:07<2:53:53, 5.91s/it]
{'loss': 0.4668, 'learning_rate': 1.1209581033685558e-06, 'epoch': 0.85}
+
85%|████████▌ | 10188/11952 [1:41:07<2:53:53, 5.91s/it]
85%|████████▌ | 10189/11952 [1:41:13<2:55:05, 5.96s/it]
{'loss': 0.4598, 'learning_rate': 1.1197117961645921e-06, 'epoch': 0.85}
+
85%|████████▌ | 10189/11952 [1:41:13<2:55:05, 5.96s/it]
85%|████████▌ | 10190/11952 [1:41:19<2:53:50, 5.92s/it]
{'loss': 0.4466, 'learning_rate': 1.118466141092055e-06, 'epoch': 0.85}
+
85%|████████▌ | 10190/11952 [1:41:19<2:53:50, 5.92s/it]
85%|████████▌ | 10191/11952 [1:41:25<2:52:59, 5.89s/it]
{'loss': 0.4796, 'learning_rate': 1.1172211382424269e-06, 'epoch': 0.85}
+
85%|████████▌ | 10191/11952 [1:41:25<2:52:59, 5.89s/it]
85%|████████▌ | 10192/11952 [1:41:30<2:52:37, 5.88s/it]
{'loss': 0.461, 'learning_rate': 1.1159767877071314e-06, 'epoch': 0.85}
+
85%|████████▌ | 10192/11952 [1:41:30<2:52:37, 5.88s/it]
85%|████████▌ | 10193/11952 [1:41:36<2:54:26, 5.95s/it]
{'loss': 0.472, 'learning_rate': 1.1147330895775498e-06, 'epoch': 0.85}
+
85%|████████▌ | 10193/11952 [1:41:36<2:54:26, 5.95s/it]
85%|████████▌ | 10194/11952 [1:41:42<2:53:09, 5.91s/it]
{'loss': 0.4753, 'learning_rate': 1.1134900439450124e-06, 'epoch': 0.85}
+
85%|████████▌ | 10194/11952 [1:41:42<2:53:09, 5.91s/it]
85%|████████▌ | 10195/11952 [1:41:48<2:52:26, 5.89s/it]
{'loss': 0.449, 'learning_rate': 1.112247650900804e-06, 'epoch': 0.85}
+
85%|████████▌ | 10195/11952 [1:41:48<2:52:26, 5.89s/it]
85%|████████▌ | 10196/11952 [1:41:54<2:50:00, 5.81s/it]
{'loss': 0.4559, 'learning_rate': 1.1110059105361616e-06, 'epoch': 0.85}
+
85%|████████▌ | 10196/11952 [1:41:54<2:50:00, 5.81s/it]
85%|████████▌ | 10197/11952 [1:41:59<2:48:38, 5.77s/it]
{'loss': 0.4649, 'learning_rate': 1.1097648229422719e-06, 'epoch': 0.85}
+
85%|████████▌ | 10197/11952 [1:41:59<2:48:38, 5.77s/it]
85%|████████▌ | 10198/11952 [1:42:06<2:52:20, 5.90s/it]
{'loss': 0.4535, 'learning_rate': 1.108524388210278e-06, 'epoch': 0.85}
+
85%|████████▌ | 10198/11952 [1:42:06<2:52:20, 5.90s/it]
85%|████████▌ | 10199/11952 [1:42:11<2:50:21, 5.83s/it]
{'loss': 0.4645, 'learning_rate': 1.1072846064312715e-06, 'epoch': 0.85}
+
85%|████████▌ | 10199/11952 [1:42:11<2:50:21, 5.83s/it]6 AutoResumeHook: Checking whether to suspend...
+57 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+2 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...1
+ AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
85%|████████▌ | 10200/11952 [1:42:17<2:49:54, 5.82s/it]
{'loss': 0.4628, 'learning_rate': 1.1060454776962947e-06, 'epoch': 0.85}
+
85%|████████▌ | 10200/11952 [1:42:17<2:49:54, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
85%|████████▌ | 10201/11952 [1:42:48<6:26:06, 13.23s/it]
{'loss': 0.4658, 'learning_rate': 1.1048070020963453e-06, 'epoch': 0.85}
+
85%|████████▌ | 10201/11952 [1:42:48<6:26:06, 13.23s/it]
85%|████████▌ | 10202/11952 [1:42:54<5:24:49, 11.14s/it]
{'loss': 0.4706, 'learning_rate': 1.1035691797223724e-06, 'epoch': 0.85}
+
85%|████████▌ | 10202/11952 [1:42:54<5:24:49, 11.14s/it]
85%|████████▌ | 10203/11952 [1:43:00<4:37:22, 9.52s/it]
{'loss': 0.4566, 'learning_rate': 1.1023320106652735e-06, 'epoch': 0.85}
+
85%|████████▌ | 10203/11952 [1:43:00<4:37:22, 9.52s/it]
85%|████████▌ | 10204/11952 [1:43:05<4:05:15, 8.42s/it]
{'loss': 0.4699, 'learning_rate': 1.1010954950159058e-06, 'epoch': 0.85}
+
85%|████████▌ | 10204/11952 [1:43:05<4:05:15, 8.42s/it]
85%|████████▌ | 10205/11952 [1:43:11<3:42:09, 7.63s/it]
{'loss': 0.4587, 'learning_rate': 1.0998596328650724e-06, 'epoch': 0.85}
+
85%|████████▌ | 10205/11952 [1:43:11<3:42:09, 7.63s/it]
85%|████████▌ | 10206/11952 [1:43:17<3:25:35, 7.07s/it]
{'loss': 0.4722, 'learning_rate': 1.098624424303526e-06, 'epoch': 0.85}
+
85%|████████▌ | 10206/11952 [1:43:17<3:25:35, 7.07s/it]
85%|████████▌ | 10207/11952 [1:43:23<3:12:58, 6.64s/it]
{'loss': 0.4548, 'learning_rate': 1.0973898694219809e-06, 'epoch': 0.85}
+
85%|████████▌ | 10207/11952 [1:43:23<3:12:58, 6.64s/it]
85%|████████▌ | 10208/11952 [1:43:29<3:10:28, 6.55s/it]
{'loss': 0.4523, 'learning_rate': 1.0961559683110946e-06, 'epoch': 0.85}
+
85%|████████▌ | 10208/11952 [1:43:29<3:10:28, 6.55s/it]
85%|████████▌ | 10209/11952 [1:43:35<3:02:21, 6.28s/it]
{'loss': 0.4467, 'learning_rate': 1.0949227210614798e-06, 'epoch': 0.85}
+
85%|████████▌ | 10209/11952 [1:43:35<3:02:21, 6.28s/it]
85%|████████▌ | 10210/11952 [1:43:41<3:02:19, 6.28s/it]
{'loss': 0.4952, 'learning_rate': 1.0936901277637002e-06, 'epoch': 0.85}
+
85%|████████▌ | 10210/11952 [1:43:41<3:02:19, 6.28s/it]
85%|████████▌ | 10211/11952 [1:43:47<3:00:35, 6.22s/it]
{'loss': 0.4745, 'learning_rate': 1.0924581885082753e-06, 'epoch': 0.85}
+
85%|████████▌ | 10211/11952 [1:43:47<3:00:35, 6.22s/it]
85%|████████▌ | 10212/11952 [1:43:53<2:58:14, 6.15s/it]
{'loss': 0.45, 'learning_rate': 1.0912269033856716e-06, 'epoch': 0.85}
+
85%|████████▌ | 10212/11952 [1:43:53<2:58:14, 6.15s/it]
85%|████████▌ | 10213/11952 [1:43:59<2:53:22, 5.98s/it]
{'loss': 0.4564, 'learning_rate': 1.089996272486309e-06, 'epoch': 0.85}
+
85%|████████▌ | 10213/11952 [1:43:59<2:53:22, 5.98s/it]
85%|████████▌ | 10214/11952 [1:44:04<2:52:16, 5.95s/it]
{'loss': 0.4536, 'learning_rate': 1.088766295900562e-06, 'epoch': 0.85}
+
85%|████████▌ | 10214/11952 [1:44:04<2:52:16, 5.95s/it]
85%|████████▌ | 10215/11952 [1:44:10<2:49:31, 5.86s/it]
{'loss': 0.4627, 'learning_rate': 1.0875369737187502e-06, 'epoch': 0.85}
+
85%|████████▌ | 10215/11952 [1:44:10<2:49:31, 5.86s/it]
85%|████████▌ | 10216/11952 [1:44:16<2:50:37, 5.90s/it]
{'loss': 0.4539, 'learning_rate': 1.0863083060311563e-06, 'epoch': 0.85}
+
85%|████████▌ | 10216/11952 [1:44:16<2:50:37, 5.90s/it]
85%|████████▌ | 10217/11952 [1:44:22<2:54:16, 6.03s/it]
{'loss': 0.474, 'learning_rate': 1.0850802929280034e-06, 'epoch': 0.85}
+
85%|████████▌ | 10217/11952 [1:44:22<2:54:16, 6.03s/it]
85%|████████▌ | 10218/11952 [1:44:28<2:53:41, 6.01s/it]
{'loss': 0.4448, 'learning_rate': 1.0838529344994763e-06, 'epoch': 0.85}
+
85%|████████▌ | 10218/11952 [1:44:28<2:53:41, 6.01s/it]
86%|████████▌ | 10219/11952 [1:44:34<2:51:21, 5.93s/it]
{'loss': 0.4548, 'learning_rate': 1.0826262308357038e-06, 'epoch': 0.85}
+
86%|████████▌ | 10219/11952 [1:44:34<2:51:21, 5.93s/it]
86%|████████▌ | 10220/11952 [1:44:40<2:50:33, 5.91s/it]
{'loss': 0.4531, 'learning_rate': 1.0814001820267717e-06, 'epoch': 0.86}
+
86%|████████▌ | 10220/11952 [1:44:40<2:50:33, 5.91s/it]
86%|████████▌ | 10221/11952 [1:44:46<2:51:43, 5.95s/it]
{'loss': 0.4624, 'learning_rate': 1.0801747881627134e-06, 'epoch': 0.86}
+
86%|████████▌ | 10221/11952 [1:44:46<2:51:43, 5.95s/it]
86%|████████▌ | 10222/11952 [1:44:52<2:51:20, 5.94s/it]
{'loss': 0.4819, 'learning_rate': 1.0789500493335191e-06, 'epoch': 0.86}
+
86%|████████▌ | 10222/11952 [1:44:52<2:51:20, 5.94s/it]
86%|████████▌ | 10223/11952 [1:44:58<2:50:31, 5.92s/it]
{'loss': 0.4558, 'learning_rate': 1.0777259656291284e-06, 'epoch': 0.86}
+
86%|████████▌ | 10223/11952 [1:44:58<2:50:31, 5.92s/it]
86%|████████▌ | 10224/11952 [1:45:04<2:52:39, 6.00s/it]
{'loss': 0.4588, 'learning_rate': 1.07650253713943e-06, 'epoch': 0.86}
+
86%|████████▌ | 10224/11952 [1:45:04<2:52:39, 6.00s/it]
86%|████████▌ | 10225/11952 [1:45:10<2:50:29, 5.92s/it]
{'loss': 0.4649, 'learning_rate': 1.0752797639542712e-06, 'epoch': 0.86}
+
86%|████████▌ | 10225/11952 [1:45:10<2:50:29, 5.92s/it]
86%|████████▌ | 10226/11952 [1:45:16<2:49:48, 5.90s/it]
{'loss': 0.4855, 'learning_rate': 1.0740576461634466e-06, 'epoch': 0.86}
+
86%|████████▌ | 10226/11952 [1:45:16<2:49:48, 5.90s/it]
86%|████████▌ | 10227/11952 [1:45:22<2:51:12, 5.95s/it]
{'loss': 0.4787, 'learning_rate': 1.0728361838567003e-06, 'epoch': 0.86}
+
86%|████████▌ | 10227/11952 [1:45:22<2:51:12, 5.95s/it]
86%|████████▌ | 10228/11952 [1:45:27<2:48:30, 5.86s/it]
{'loss': 0.4544, 'learning_rate': 1.0716153771237359e-06, 'epoch': 0.86}
+
86%|████████▌ | 10228/11952 [1:45:27<2:48:30, 5.86s/it]
86%|████████▌ | 10229/11952 [1:45:33<2:49:31, 5.90s/it]
{'loss': 0.4666, 'learning_rate': 1.0703952260542016e-06, 'epoch': 0.86}
+
86%|████████▌ | 10229/11952 [1:45:33<2:49:31, 5.90s/it]
86%|████████▌ | 10230/11952 [1:45:40<2:53:03, 6.03s/it]
{'loss': 0.4757, 'learning_rate': 1.0691757307377014e-06, 'epoch': 0.86}
+
86%|████████▌ | 10230/11952 [1:45:40<2:53:03, 6.03s/it]
86%|████████▌ | 10231/11952 [1:45:46<2:53:28, 6.05s/it]
{'loss': 0.4772, 'learning_rate': 1.0679568912637872e-06, 'epoch': 0.86}
+
86%|████████▌ | 10231/11952 [1:45:46<2:53:28, 6.05s/it]
86%|████████▌ | 10232/11952 [1:45:52<2:51:36, 5.99s/it]
{'loss': 0.4798, 'learning_rate': 1.0667387077219704e-06, 'epoch': 0.86}
+
86%|████████▌ | 10232/11952 [1:45:52<2:51:36, 5.99s/it]
86%|████████▌ | 10233/11952 [1:45:57<2:49:04, 5.90s/it]
{'loss': 0.4355, 'learning_rate': 1.0655211802017052e-06, 'epoch': 0.86}
+
86%|████████▌ | 10233/11952 [1:45:57<2:49:04, 5.90s/it]
86%|████████▌ | 10234/11952 [1:46:03<2:49:04, 5.90s/it]
{'loss': 0.4507, 'learning_rate': 1.0643043087924043e-06, 'epoch': 0.86}
+
86%|████████▌ | 10234/11952 [1:46:03<2:49:04, 5.90s/it]
86%|████████▌ | 10235/11952 [1:46:09<2:49:12, 5.91s/it]
{'loss': 0.4636, 'learning_rate': 1.0630880935834286e-06, 'epoch': 0.86}
+
86%|████████▌ | 10235/11952 [1:46:09<2:49:12, 5.91s/it]
86%|████████▌ | 10236/11952 [1:46:15<2:50:49, 5.97s/it]
{'loss': 0.4574, 'learning_rate': 1.0618725346640902e-06, 'epoch': 0.86}
+
86%|████████▌ | 10236/11952 [1:46:15<2:50:49, 5.97s/it]
86%|████████▌ | 10237/11952 [1:46:21<2:52:32, 6.04s/it]
{'loss': 0.473, 'learning_rate': 1.0606576321236585e-06, 'epoch': 0.86}
+
86%|████████▌ | 10237/11952 [1:46:21<2:52:32, 6.04s/it]
86%|████████▌ | 10238/11952 [1:46:27<2:50:30, 5.97s/it]
{'loss': 0.458, 'learning_rate': 1.0594433860513452e-06, 'epoch': 0.86}
+
86%|████████▌ | 10238/11952 [1:46:27<2:50:30, 5.97s/it]
86%|████████▌ | 10239/11952 [1:46:33<2:50:08, 5.96s/it]
{'loss': 0.4414, 'learning_rate': 1.0582297965363264e-06, 'epoch': 0.86}
+
86%|████████▌ | 10239/11952 [1:46:33<2:50:08, 5.96s/it]
86%|████████▌ | 10240/11952 [1:46:39<2:49:48, 5.95s/it]
{'loss': 0.4564, 'learning_rate': 1.0570168636677191e-06, 'epoch': 0.86}
+
86%|████████▌ | 10240/11952 [1:46:39<2:49:48, 5.95s/it]
86%|████████▌ | 10241/11952 [1:46:45<2:49:40, 5.95s/it]
{'loss': 0.4609, 'learning_rate': 1.055804587534598e-06, 'epoch': 0.86}
+
86%|████████▌ | 10241/11952 [1:46:45<2:49:40, 5.95s/it]
86%|████████▌ | 10242/11952 [1:46:51<2:50:12, 5.97s/it]
{'loss': 0.4552, 'learning_rate': 1.0545929682259847e-06, 'epoch': 0.86}
+
86%|████████▌ | 10242/11952 [1:46:51<2:50:12, 5.97s/it]
86%|████████▌ | 10243/11952 [1:46:57<2:51:09, 6.01s/it]
{'loss': 0.487, 'learning_rate': 1.0533820058308576e-06, 'epoch': 0.86}
+
86%|████████▌ | 10243/11952 [1:46:57<2:51:09, 6.01s/it]
86%|████████▌ | 10244/11952 [1:47:03<2:48:19, 5.91s/it]
{'loss': 0.4707, 'learning_rate': 1.0521717004381427e-06, 'epoch': 0.86}
+
86%|████████▌ | 10244/11952 [1:47:03<2:48:19, 5.91s/it]
86%|████████▌ | 10245/11952 [1:47:09<2:46:53, 5.87s/it]
{'loss': 0.4729, 'learning_rate': 1.0509620521367225e-06, 'epoch': 0.86}
+
86%|████████▌ | 10245/11952 [1:47:09<2:46:53, 5.87s/it]
86%|████████▌ | 10246/11952 [1:47:14<2:45:51, 5.83s/it]
{'loss': 0.4663, 'learning_rate': 1.0497530610154283e-06, 'epoch': 0.86}
+
86%|████████▌ | 10246/11952 [1:47:14<2:45:51, 5.83s/it]
86%|████████▌ | 10247/11952 [1:47:20<2:46:57, 5.88s/it]
{'loss': 0.4829, 'learning_rate': 1.04854472716304e-06, 'epoch': 0.86}
+
86%|████████▌ | 10247/11952 [1:47:20<2:46:57, 5.88s/it]
86%|████████▌ | 10248/11952 [1:47:27<2:49:41, 5.98s/it]
{'loss': 0.4565, 'learning_rate': 1.0473370506682968e-06, 'epoch': 0.86}
+
86%|████████▌ | 10248/11952 [1:47:27<2:49:41, 5.98s/it]
86%|████████▌ | 10249/11952 [1:47:32<2:47:22, 5.90s/it]
{'loss': 0.4666, 'learning_rate': 1.046130031619883e-06, 'epoch': 0.86}
+
86%|████████▌ | 10249/11952 [1:47:32<2:47:22, 5.90s/it]76 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
86%|████████▌ | 10250/11952 [1:47:38<2:46:44, 5.88s/it]
{'loss': 0.4489, 'learning_rate': 1.044923670106439e-06, 'epoch': 0.86}
+
86%|████████▌ | 10250/11952 [1:47:38<2:46:44, 5.88s/it]
86%|████████▌ | 10251/11952 [1:47:44<2:48:34, 5.95s/it]
{'loss': 0.4793, 'learning_rate': 1.0437179662165508e-06, 'epoch': 0.86}
+
86%|████████▌ | 10251/11952 [1:47:44<2:48:34, 5.95s/it]
86%|████████▌ | 10252/11952 [1:47:50<2:50:44, 6.03s/it]
{'loss': 0.4564, 'learning_rate': 1.0425129200387662e-06, 'epoch': 0.86}
+
86%|████████▌ | 10252/11952 [1:47:50<2:50:44, 6.03s/it]
86%|████████▌ | 10253/11952 [1:47:56<2:49:00, 5.97s/it]
{'loss': 0.47, 'learning_rate': 1.0413085316615745e-06, 'epoch': 0.86}
+
86%|████████▌ | 10253/11952 [1:47:56<2:49:00, 5.97s/it]
86%|████████▌ | 10254/11952 [1:48:02<2:48:12, 5.94s/it]
{'loss': 0.4469, 'learning_rate': 1.0401048011734227e-06, 'epoch': 0.86}
+
86%|████████▌ | 10254/11952 [1:48:02<2:48:12, 5.94s/it]
86%|████████▌ | 10255/11952 [1:48:08<2:47:40, 5.93s/it]
{'loss': 0.4772, 'learning_rate': 1.0389017286627078e-06, 'epoch': 0.86}
+
86%|████████▌ | 10255/11952 [1:48:08<2:47:40, 5.93s/it]
86%|████████▌ | 10256/11952 [1:48:14<2:49:02, 5.98s/it]
{'loss': 0.475, 'learning_rate': 1.0376993142177771e-06, 'epoch': 0.86}
+
86%|████████▌ | 10256/11952 [1:48:14<2:49:02, 5.98s/it]
86%|████████▌ | 10257/11952 [1:48:20<2:45:13, 5.85s/it]
{'loss': 0.4524, 'learning_rate': 1.036497557926931e-06, 'epoch': 0.86}
+
86%|████████▌ | 10257/11952 [1:48:20<2:45:13, 5.85s/it]
86%|████████▌ | 10258/11952 [1:48:26<2:45:26, 5.86s/it]
{'loss': 0.4645, 'learning_rate': 1.035296459878421e-06, 'epoch': 0.86}
+
86%|████████▌ | 10258/11952 [1:48:26<2:45:26, 5.86s/it]
86%|████████▌ | 10259/11952 [1:48:31<2:45:28, 5.86s/it]
{'loss': 0.4579, 'learning_rate': 1.0340960201604544e-06, 'epoch': 0.86}
+
86%|████████▌ | 10259/11952 [1:48:31<2:45:28, 5.86s/it]
86%|████████▌ | 10260/11952 [1:48:37<2:46:20, 5.90s/it]
{'loss': 0.4659, 'learning_rate': 1.0328962388611841e-06, 'epoch': 0.86}
+
86%|████████▌ | 10260/11952 [1:48:37<2:46:20, 5.90s/it]
86%|████████▌ | 10261/11952 [1:48:43<2:45:34, 5.87s/it]
{'loss': 0.4552, 'learning_rate': 1.0316971160687172e-06, 'epoch': 0.86}
+
86%|████████▌ | 10261/11952 [1:48:43<2:45:34, 5.87s/it]
86%|████████▌ | 10262/11952 [1:48:49<2:45:14, 5.87s/it]
{'loss': 0.452, 'learning_rate': 1.0304986518711124e-06, 'epoch': 0.86}
+
86%|████████▌ | 10262/11952 [1:48:49<2:45:14, 5.87s/it]
86%|████████▌ | 10263/11952 [1:48:55<2:47:02, 5.93s/it]
{'loss': 0.4648, 'learning_rate': 1.029300846356379e-06, 'epoch': 0.86}
+
86%|████████▌ | 10263/11952 [1:48:55<2:47:02, 5.93s/it]
86%|████████▌ | 10264/11952 [1:49:01<2:47:01, 5.94s/it]
{'loss': 0.4696, 'learning_rate': 1.0281036996124793e-06, 'epoch': 0.86}
+
86%|████████▌ | 10264/11952 [1:49:01<2:47:01, 5.94s/it]
86%|████████▌ | 10265/11952 [1:49:07<2:44:45, 5.86s/it]
{'loss': 0.4558, 'learning_rate': 1.026907211727326e-06, 'epoch': 0.86}
+
86%|████████▌ | 10265/11952 [1:49:07<2:44:45, 5.86s/it]
86%|████████▌ | 10266/11952 [1:49:13<2:44:19, 5.85s/it]
{'loss': 0.4506, 'learning_rate': 1.0257113827887865e-06, 'epoch': 0.86}
+
86%|████████▌ | 10266/11952 [1:49:13<2:44:19, 5.85s/it]
86%|████████▌ | 10267/11952 [1:49:18<2:43:04, 5.81s/it]
{'loss': 0.4555, 'learning_rate': 1.0245162128846764e-06, 'epoch': 0.86}
+
86%|████████▌ | 10267/11952 [1:49:18<2:43:04, 5.81s/it]
86%|████████▌ | 10268/11952 [1:49:24<2:42:34, 5.79s/it]
{'loss': 0.4706, 'learning_rate': 1.023321702102762e-06, 'epoch': 0.86}
+
86%|████████▌ | 10268/11952 [1:49:24<2:42:34, 5.79s/it]
86%|████████▌ | 10269/11952 [1:49:30<2:41:30, 5.76s/it]
{'loss': 0.4593, 'learning_rate': 1.0221278505307665e-06, 'epoch': 0.86}
+
86%|████████▌ | 10269/11952 [1:49:30<2:41:30, 5.76s/it]
86%|████████▌ | 10270/11952 [1:49:35<2:40:08, 5.71s/it]
{'loss': 0.4606, 'learning_rate': 1.0209346582563596e-06, 'epoch': 0.86}
+
86%|████████▌ | 10270/11952 [1:49:35<2:40:08, 5.71s/it]
86%|████████▌ | 10271/11952 [1:49:41<2:42:52, 5.81s/it]
{'loss': 0.458, 'learning_rate': 1.0197421253671646e-06, 'epoch': 0.86}
+
86%|████████▌ | 10271/11952 [1:49:41<2:42:52, 5.81s/it]
86%|████████▌ | 10272/11952 [1:49:47<2:43:26, 5.84s/it]
{'loss': 0.4643, 'learning_rate': 1.018550251950755e-06, 'epoch': 0.86}
+
86%|████████▌ | 10272/11952 [1:49:47<2:43:26, 5.84s/it]
86%|████████▌ | 10273/11952 [1:49:53<2:43:54, 5.86s/it]
{'loss': 0.497, 'learning_rate': 1.0173590380946596e-06, 'epoch': 0.86}
+
86%|████████▌ | 10273/11952 [1:49:53<2:43:54, 5.86s/it]
86%|████████▌ | 10274/11952 [1:49:59<2:44:22, 5.88s/it]
{'loss': 0.4946, 'learning_rate': 1.016168483886356e-06, 'epoch': 0.86}
+
86%|████████▌ | 10274/11952 [1:49:59<2:44:22, 5.88s/it]
86%|████████▌ | 10275/11952 [1:50:05<2:46:14, 5.95s/it]
{'loss': 0.4545, 'learning_rate': 1.0149785894132714e-06, 'epoch': 0.86}
+
86%|████████▌ | 10275/11952 [1:50:05<2:46:14, 5.95s/it]
86%|████████▌ | 10276/11952 [1:50:11<2:44:32, 5.89s/it]
{'loss': 0.4669, 'learning_rate': 1.0137893547627875e-06, 'epoch': 0.86}
+
86%|████████▌ | 10276/11952 [1:50:11<2:44:32, 5.89s/it]
86%|████████▌ | 10277/11952 [1:50:17<2:45:22, 5.92s/it]
{'loss': 0.4839, 'learning_rate': 1.0126007800222347e-06, 'epoch': 0.86}
+
86%|████████▌ | 10277/11952 [1:50:17<2:45:22, 5.92s/it]
86%|████████▌ | 10278/11952 [1:50:23<2:46:01, 5.95s/it]
{'loss': 0.4633, 'learning_rate': 1.0114128652789023e-06, 'epoch': 0.86}
+
86%|████████▌ | 10278/11952 [1:50:23<2:46:01, 5.95s/it]
86%|████████▌ | 10279/11952 [1:50:29<2:46:59, 5.99s/it]
{'loss': 0.4627, 'learning_rate': 1.0102256106200203e-06, 'epoch': 0.86}
+
86%|████████▌ | 10279/11952 [1:50:29<2:46:59, 5.99s/it]
86%|████████▌ | 10280/11952 [1:50:35<2:48:58, 6.06s/it]
{'loss': 0.4656, 'learning_rate': 1.0090390161327801e-06, 'epoch': 0.86}
+
86%|████████▌ | 10280/11952 [1:50:35<2:48:58, 6.06s/it]
86%|████████▌ | 10281/11952 [1:50:41<2:47:45, 6.02s/it]
{'loss': 0.4692, 'learning_rate': 1.0078530819043174e-06, 'epoch': 0.86}
+
86%|████████▌ | 10281/11952 [1:50:41<2:47:45, 6.02s/it]
86%|████████▌ | 10282/11952 [1:50:47<2:46:03, 5.97s/it]
{'loss': 0.4646, 'learning_rate': 1.006667808021725e-06, 'epoch': 0.86}
+
86%|████████▌ | 10282/11952 [1:50:47<2:46:03, 5.97s/it]
86%|████████▌ | 10283/11952 [1:50:53<2:48:11, 6.05s/it]
{'loss': 0.4597, 'learning_rate': 1.0054831945720411e-06, 'epoch': 0.86}
+
86%|████████▌ | 10283/11952 [1:50:53<2:48:11, 6.05s/it]
86%|████████▌ | 10284/11952 [1:50:59<2:48:59, 6.08s/it]
{'loss': 0.4651, 'learning_rate': 1.0042992416422614e-06, 'epoch': 0.86}
+
86%|████████▌ | 10284/11952 [1:50:59<2:48:59, 6.08s/it]
86%|████████▌ | 10285/11952 [1:51:06<2:51:04, 6.16s/it]
{'loss': 0.4696, 'learning_rate': 1.0031159493193277e-06, 'epoch': 0.86}
+
86%|████████▌ | 10285/11952 [1:51:06<2:51:04, 6.16s/it]
86%|████████▌ | 10286/11952 [1:51:12<2:47:10, 6.02s/it]
{'loss': 0.4727, 'learning_rate': 1.001933317690139e-06, 'epoch': 0.86}
+
86%|████████▌ | 10286/11952 [1:51:12<2:47:10, 6.02s/it]
86%|████████▌ | 10287/11952 [1:51:17<2:43:45, 5.90s/it]
{'loss': 0.4629, 'learning_rate': 1.000751346841542e-06, 'epoch': 0.86}
+
86%|████████▌ | 10287/11952 [1:51:17<2:43:45, 5.90s/it]
86%|████████▌ | 10288/11952 [1:51:23<2:44:50, 5.94s/it]
{'loss': 0.4629, 'learning_rate': 9.995700368603333e-07, 'epoch': 0.86}
+
86%|████████▌ | 10288/11952 [1:51:23<2:44:50, 5.94s/it]
86%|████████▌ | 10289/11952 [1:51:29<2:44:50, 5.95s/it]
{'loss': 0.4644, 'learning_rate': 9.983893878332674e-07, 'epoch': 0.86}
+
86%|████████▌ | 10289/11952 [1:51:29<2:44:50, 5.95s/it]
86%|████████▌ | 10290/11952 [1:51:35<2:44:02, 5.92s/it]
{'loss': 0.4686, 'learning_rate': 9.972093998470444e-07, 'epoch': 0.86}
+
86%|████████▌ | 10290/11952 [1:51:35<2:44:02, 5.92s/it]
86%|████████▌ | 10291/11952 [1:51:41<2:43:38, 5.91s/it]
{'loss': 0.4609, 'learning_rate': 9.960300729883177e-07, 'epoch': 0.86}
+
86%|████████▌ | 10291/11952 [1:51:41<2:43:38, 5.91s/it]
86%|████████▌ | 10292/11952 [1:51:47<2:42:40, 5.88s/it]
{'loss': 0.4454, 'learning_rate': 9.9485140734369e-07, 'epoch': 0.86}
+
86%|████████▌ | 10292/11952 [1:51:47<2:42:40, 5.88s/it]
86%|████████▌ | 10293/11952 [1:51:53<2:45:01, 5.97s/it]
{'loss': 0.4597, 'learning_rate': 9.936734029997218e-07, 'epoch': 0.86}
+
86%|████████▌ | 10293/11952 [1:51:53<2:45:01, 5.97s/it]
86%|████████▌ | 10294/11952 [1:51:59<2:43:52, 5.93s/it]
{'loss': 0.4802, 'learning_rate': 9.92496060042919e-07, 'epoch': 0.86}
+
86%|████████▌ | 10294/11952 [1:51:59<2:43:52, 5.93s/it]
86%|████████▌ | 10295/11952 [1:52:05<2:45:13, 5.98s/it]
{'loss': 0.4629, 'learning_rate': 9.913193785597396e-07, 'epoch': 0.86}
+
86%|████████▌ | 10295/11952 [1:52:05<2:45:13, 5.98s/it]
86%|████████▌ | 10296/11952 [1:52:11<2:48:24, 6.10s/it]
{'loss': 0.4501, 'learning_rate': 9.90143358636596e-07, 'epoch': 0.86}
+
86%|████████▌ | 10296/11952 [1:52:11<2:48:24, 6.10s/it]
86%|████████▌ | 10297/11952 [1:52:17<2:45:55, 6.02s/it]
{'loss': 0.4537, 'learning_rate': 9.88968000359849e-07, 'epoch': 0.86}
+
86%|████████▌ | 10297/11952 [1:52:17<2:45:55, 6.02s/it]
86%|████████▌ | 10298/11952 [1:52:23<2:47:04, 6.06s/it]
{'loss': 0.464, 'learning_rate': 9.877933038158105e-07, 'epoch': 0.86}
+
86%|████████▌ | 10298/11952 [1:52:23<2:47:04, 6.06s/it]
86%|████████▌ | 10299/11952 [1:52:29<2:43:39, 5.94s/it]
{'loss': 0.4678, 'learning_rate': 9.866192690907472e-07, 'epoch': 0.86}
+
86%|████████▌ | 10299/11952 [1:52:29<2:43:39, 5.94s/it]4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+31 AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+0 AutoResumeHook: Checking whether to suspend...
+
86%|████████▌ | 10300/11952 [1:52:35<2:46:35, 6.05s/it]2 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4739, 'learning_rate': 9.85445896270878e-07, 'epoch': 0.86}
+
86%|████████▌ | 10300/11952 [1:52:35<2:46:35, 6.05s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
86%|████████▌ | 10301/11952 [1:53:06<6:09:29, 13.43s/it]
{'loss': 0.4806, 'learning_rate': 9.84273185442367e-07, 'epoch': 0.86}
+
86%|████████▌ | 10301/11952 [1:53:06<6:09:29, 13.43s/it]
86%|████████▌ | 10302/11952 [1:53:12<5:06:33, 11.15s/it]
{'loss': 0.4504, 'learning_rate': 9.831011366913335e-07, 'epoch': 0.86}
+
86%|████████▌ | 10302/11952 [1:53:12<5:06:33, 11.15s/it]
86%|████████▌ | 10303/11952 [1:53:17<4:20:31, 9.48s/it]
{'loss': 0.4628, 'learning_rate': 9.819297501038494e-07, 'epoch': 0.86}
+
86%|████████▌ | 10303/11952 [1:53:17<4:20:31, 9.48s/it]
86%|████████▌ | 10304/11952 [1:53:23<3:51:40, 8.43s/it]
{'loss': 0.4659, 'learning_rate': 9.80759025765935e-07, 'epoch': 0.86}
+
86%|████████▌ | 10304/11952 [1:53:23<3:51:40, 8.43s/it]
86%|████████▌ | 10305/11952 [1:53:29<3:31:50, 7.72s/it]
{'loss': 0.4496, 'learning_rate': 9.795889637635636e-07, 'epoch': 0.86}
+
86%|████████▌ | 10305/11952 [1:53:29<3:31:50, 7.72s/it]
86%|████████▌ | 10306/11952 [1:53:35<3:14:37, 7.09s/it]
{'loss': 0.4522, 'learning_rate': 9.78419564182659e-07, 'epoch': 0.86}
+
86%|████████▌ | 10306/11952 [1:53:35<3:14:37, 7.09s/it]
86%|████████▌ | 10307/11952 [1:53:41<3:06:23, 6.80s/it]
{'loss': 0.4757, 'learning_rate': 9.772508271090997e-07, 'epoch': 0.86}
+
86%|████████▌ | 10307/11952 [1:53:41<3:06:23, 6.80s/it]
86%|████████▌ | 10308/11952 [1:53:47<2:59:32, 6.55s/it]
{'loss': 0.4711, 'learning_rate': 9.760827526287108e-07, 'epoch': 0.86}
+
86%|████████▌ | 10308/11952 [1:53:47<2:59:32, 6.55s/it]
86%|████████▋ | 10309/11952 [1:53:53<2:52:36, 6.30s/it]
{'loss': 0.4507, 'learning_rate': 9.749153408272693e-07, 'epoch': 0.86}
+
86%|████████▋ | 10309/11952 [1:53:53<2:52:36, 6.30s/it]
86%|████████▋ | 10310/11952 [1:54:00<3:01:10, 6.62s/it]
{'loss': 0.4604, 'learning_rate': 9.737485917905088e-07, 'epoch': 0.86}
+
86%|████████▋ | 10310/11952 [1:54:00<3:01:10, 6.62s/it]
86%|████████▋ | 10311/11952 [1:54:06<2:55:46, 6.43s/it]
{'loss': 0.4598, 'learning_rate': 9.725825056041094e-07, 'epoch': 0.86}
+
86%|████████▋ | 10311/11952 [1:54:06<2:55:46, 6.43s/it]
86%|████████▋ | 10312/11952 [1:54:12<2:51:02, 6.26s/it]
{'loss': 0.471, 'learning_rate': 9.714170823537007e-07, 'epoch': 0.86}
+
86%|████████▋ | 10312/11952 [1:54:12<2:51:02, 6.26s/it]
86%|████████▋ | 10313/11952 [1:54:18<2:47:15, 6.12s/it]
{'loss': 0.4624, 'learning_rate': 9.702523221248706e-07, 'epoch': 0.86}
+
86%|████████▋ | 10313/11952 [1:54:18<2:47:15, 6.12s/it]
86%|████████▋ | 10314/11952 [1:54:24<2:44:49, 6.04s/it]
{'loss': 0.4548, 'learning_rate': 9.69088225003152e-07, 'epoch': 0.86}
+
86%|████████▋ | 10314/11952 [1:54:24<2:44:49, 6.04s/it]
86%|████████▋ | 10315/11952 [1:54:29<2:42:24, 5.95s/it]
{'loss': 0.4672, 'learning_rate': 9.679247910740331e-07, 'epoch': 0.86}
+
86%|████████▋ | 10315/11952 [1:54:29<2:42:24, 5.95s/it]
86%|████████▋ | 10316/11952 [1:54:35<2:41:43, 5.93s/it]
{'loss': 0.4596, 'learning_rate': 9.667620204229488e-07, 'epoch': 0.86}
+
86%|████████▋ | 10316/11952 [1:54:35<2:41:43, 5.93s/it]
86%|████████▋ | 10317/11952 [1:54:41<2:39:48, 5.86s/it]
{'loss': 0.447, 'learning_rate': 9.6559991313529e-07, 'epoch': 0.86}
+
86%|████████▋ | 10317/11952 [1:54:41<2:39:48, 5.86s/it]
86%|████████▋ | 10318/11952 [1:54:47<2:40:47, 5.90s/it]
{'loss': 0.4531, 'learning_rate': 9.64438469296396e-07, 'epoch': 0.86}
+
86%|████████▋ | 10318/11952 [1:54:47<2:40:47, 5.90s/it]
86%|████████▋ | 10319/11952 [1:54:52<2:37:49, 5.80s/it]
{'loss': 0.4692, 'learning_rate': 9.632776889915595e-07, 'epoch': 0.86}
+
86%|████████▋ | 10319/11952 [1:54:52<2:37:49, 5.80s/it]
86%|████████▋ | 10320/11952 [1:54:58<2:38:55, 5.84s/it]
{'loss': 0.4731, 'learning_rate': 9.621175723060216e-07, 'epoch': 0.86}
+
86%|████████▋ | 10320/11952 [1:54:58<2:38:55, 5.84s/it]
86%|████████▋ | 10321/11952 [1:55:04<2:39:01, 5.85s/it]
{'loss': 0.4477, 'learning_rate': 9.609581193249794e-07, 'epoch': 0.86}
+
86%|████████▋ | 10321/11952 [1:55:04<2:39:01, 5.85s/it]
86%|████████▋ | 10322/11952 [1:55:10<2:39:49, 5.88s/it]
{'loss': 0.48, 'learning_rate': 9.597993301335773e-07, 'epoch': 0.86}
+
86%|████████▋ | 10322/11952 [1:55:10<2:39:49, 5.88s/it]
86%|████████▋ | 10323/11952 [1:55:16<2:38:50, 5.85s/it]
{'loss': 0.4617, 'learning_rate': 9.586412048169114e-07, 'epoch': 0.86}
+
86%|████████▋ | 10323/11952 [1:55:16<2:38:50, 5.85s/it]
86%|████████▋ | 10324/11952 [1:55:22<2:40:30, 5.92s/it]
{'loss': 0.4565, 'learning_rate': 9.574837434600293e-07, 'epoch': 0.86}
+
86%|████████▋ | 10324/11952 [1:55:22<2:40:30, 5.92s/it]
86%|████████▋ | 10325/11952 [1:55:28<2:38:26, 5.84s/it]
{'loss': 0.4485, 'learning_rate': 9.563269461479307e-07, 'epoch': 0.86}
+
86%|████████▋ | 10325/11952 [1:55:28<2:38:26, 5.84s/it]
86%|████████▋ | 10326/11952 [1:55:34<2:37:54, 5.83s/it]
{'loss': 0.4653, 'learning_rate': 9.551708129655635e-07, 'epoch': 0.86}
+
86%|████████▋ | 10326/11952 [1:55:34<2:37:54, 5.83s/it]
86%|████████▋ | 10327/11952 [1:55:39<2:38:22, 5.85s/it]
{'loss': 0.46, 'learning_rate': 9.54015343997834e-07, 'epoch': 0.86}
+
86%|████████▋ | 10327/11952 [1:55:39<2:38:22, 5.85s/it]
86%|████████▋ | 10328/11952 [1:55:46<2:44:27, 6.08s/it]
{'loss': 0.4716, 'learning_rate': 9.528605393295909e-07, 'epoch': 0.86}
+
86%|████████▋ | 10328/11952 [1:55:46<2:44:27, 6.08s/it]
86%|████████▋ | 10329/11952 [1:55:52<2:43:58, 6.06s/it]
{'loss': 0.4637, 'learning_rate': 9.517063990456399e-07, 'epoch': 0.86}
+
86%|████████▋ | 10329/11952 [1:55:52<2:43:58, 6.06s/it]
86%|████████▋ | 10330/11952 [1:55:58<2:42:55, 6.03s/it]
{'loss': 0.4507, 'learning_rate': 9.505529232307376e-07, 'epoch': 0.86}
+
86%|████████▋ | 10330/11952 [1:55:58<2:42:55, 6.03s/it]
86%|████████▋ | 10331/11952 [1:56:04<2:42:26, 6.01s/it]
{'loss': 0.4772, 'learning_rate': 9.494001119695884e-07, 'epoch': 0.86}
+
86%|████████▋ | 10331/11952 [1:56:04<2:42:26, 6.01s/it]
86%|████████▋ | 10332/11952 [1:56:10<2:40:00, 5.93s/it]
{'loss': 0.4558, 'learning_rate': 9.482479653468512e-07, 'epoch': 0.86}
+
86%|████████▋ | 10332/11952 [1:56:10<2:40:00, 5.93s/it]
86%|████████▋ | 10333/11952 [1:56:16<2:39:51, 5.92s/it]
{'loss': 0.4491, 'learning_rate': 9.47096483447133e-07, 'epoch': 0.86}
+
86%|████████▋ | 10333/11952 [1:56:16<2:39:51, 5.92s/it]
86%|████████▋ | 10334/11952 [1:56:22<2:39:33, 5.92s/it]
{'loss': 0.4573, 'learning_rate': 9.459456663549959e-07, 'epoch': 0.86}
+
86%|████████▋ | 10334/11952 [1:56:22<2:39:33, 5.92s/it]
86%|████████▋ | 10335/11952 [1:56:27<2:37:18, 5.84s/it]
{'loss': 0.4429, 'learning_rate': 9.447955141549514e-07, 'epoch': 0.86}
+
86%|████████▋ | 10335/11952 [1:56:27<2:37:18, 5.84s/it]
86%|████████▋ | 10336/11952 [1:56:33<2:38:59, 5.90s/it]
{'loss': 0.4629, 'learning_rate': 9.436460269314607e-07, 'epoch': 0.86}
+
86%|████████▋ | 10336/11952 [1:56:33<2:38:59, 5.90s/it]
86%|████████▋ | 10337/11952 [1:56:39<2:38:24, 5.89s/it]
{'loss': 0.4625, 'learning_rate': 9.424972047689374e-07, 'epoch': 0.86}
+
86%|████████▋ | 10337/11952 [1:56:39<2:38:24, 5.89s/it]
86%|████████▋ | 10338/11952 [1:56:45<2:39:18, 5.92s/it]
{'loss': 0.4684, 'learning_rate': 9.413490477517462e-07, 'epoch': 0.86}
+
86%|████████▋ | 10338/11952 [1:56:45<2:39:18, 5.92s/it]
87%|████████▋ | 10339/11952 [1:56:51<2:37:54, 5.87s/it]
{'loss': 0.4807, 'learning_rate': 9.402015559642019e-07, 'epoch': 0.87}
+
87%|████████▋ | 10339/11952 [1:56:51<2:37:54, 5.87s/it]
87%|████████▋ | 10340/11952 [1:56:57<2:39:14, 5.93s/it]
{'loss': 0.4669, 'learning_rate': 9.390547294905739e-07, 'epoch': 0.87}
+
87%|████████▋ | 10340/11952 [1:56:57<2:39:14, 5.93s/it]
87%|████████▋ | 10341/11952 [1:57:03<2:38:52, 5.92s/it]
{'loss': 0.4493, 'learning_rate': 9.379085684150779e-07, 'epoch': 0.87}
+
87%|████████▋ | 10341/11952 [1:57:03<2:38:52, 5.92s/it]
87%|████████▋ | 10342/11952 [1:57:09<2:40:31, 5.98s/it]
{'loss': 0.4639, 'learning_rate': 9.367630728218868e-07, 'epoch': 0.87}
+
87%|████████▋ | 10342/11952 [1:57:09<2:40:31, 5.98s/it]
87%|████████▋ | 10343/11952 [1:57:15<2:40:51, 6.00s/it]
{'loss': 0.4678, 'learning_rate': 9.356182427951188e-07, 'epoch': 0.87}
+
87%|████████▋ | 10343/11952 [1:57:15<2:40:51, 6.00s/it]
87%|████████▋ | 10344/11952 [1:57:21<2:37:45, 5.89s/it]
{'loss': 0.4619, 'learning_rate': 9.344740784188445e-07, 'epoch': 0.87}
+
87%|████████▋ | 10344/11952 [1:57:21<2:37:45, 5.89s/it]
87%|████████▋ | 10345/11952 [1:57:26<2:35:47, 5.82s/it]
{'loss': 0.489, 'learning_rate': 9.333305797770887e-07, 'epoch': 0.87}
+
87%|████████▋ | 10345/11952 [1:57:26<2:35:47, 5.82s/it]
87%|████████▋ | 10346/11952 [1:57:32<2:36:03, 5.83s/it]
{'loss': 0.4565, 'learning_rate': 9.321877469538232e-07, 'epoch': 0.87}
+
87%|████████▋ | 10346/11952 [1:57:32<2:36:03, 5.83s/it]
87%|████████▋ | 10347/11952 [1:57:38<2:35:37, 5.82s/it]
{'loss': 0.4754, 'learning_rate': 9.31045580032972e-07, 'epoch': 0.87}
+
87%|████████▋ | 10347/11952 [1:57:38<2:35:37, 5.82s/it]
87%|████████▋ | 10348/11952 [1:57:44<2:36:03, 5.84s/it]
{'loss': 0.4564, 'learning_rate': 9.299040790984137e-07, 'epoch': 0.87}
+
87%|████████▋ | 10348/11952 [1:57:44<2:36:03, 5.84s/it]
87%|████████▋ | 10349/11952 [1:57:50<2:36:03, 5.84s/it]
{'loss': 0.472, 'learning_rate': 9.287632442339756e-07, 'epoch': 0.87}
+
87%|████████▋ | 10349/11952 [1:57:50<2:36:03, 5.84s/it]4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
87%|████████▋ | 10350/11952 [1:57:56<2:38:34, 5.94s/it]
{'loss': 0.4752, 'learning_rate': 9.276230755234328e-07, 'epoch': 0.87}
+
87%|████████▋ | 10350/11952 [1:57:56<2:38:34, 5.94s/it]
87%|████████▋ | 10351/11952 [1:58:02<2:39:36, 5.98s/it]
{'loss': 0.4529, 'learning_rate': 9.264835730505184e-07, 'epoch': 0.87}
+
87%|████████▋ | 10351/11952 [1:58:02<2:39:36, 5.98s/it]
87%|████████▋ | 10352/11952 [1:58:08<2:38:36, 5.95s/it]
{'loss': 0.4372, 'learning_rate': 9.25344736898911e-07, 'epoch': 0.87}
+
87%|████████▋ | 10352/11952 [1:58:08<2:38:36, 5.95s/it]
87%|████████▋ | 10353/11952 [1:58:14<2:37:36, 5.91s/it]
{'loss': 0.4867, 'learning_rate': 9.242065671522393e-07, 'epoch': 0.87}
+
87%|████████▋ | 10353/11952 [1:58:14<2:37:36, 5.91s/it]
87%|████████▋ | 10354/11952 [1:58:20<2:38:36, 5.96s/it]
{'loss': 0.4552, 'learning_rate': 9.230690638940898e-07, 'epoch': 0.87}
+
87%|████████▋ | 10354/11952 [1:58:20<2:38:36, 5.96s/it]
87%|████████▋ | 10355/11952 [1:58:26<2:40:40, 6.04s/it]
{'loss': 0.47, 'learning_rate': 9.219322272079955e-07, 'epoch': 0.87}
+
87%|████████▋ | 10355/11952 [1:58:26<2:40:40, 6.04s/it]
87%|████████▋ | 10356/11952 [1:58:32<2:37:59, 5.94s/it]
{'loss': 0.459, 'learning_rate': 9.207960571774388e-07, 'epoch': 0.87}
+
87%|████████▋ | 10356/11952 [1:58:32<2:37:59, 5.94s/it]
87%|████████▋ | 10357/11952 [1:58:37<2:37:44, 5.93s/it]
{'loss': 0.4625, 'learning_rate': 9.196605538858571e-07, 'epoch': 0.87}
+
87%|████████▋ | 10357/11952 [1:58:37<2:37:44, 5.93s/it]
87%|████████▋ | 10358/11952 [1:58:43<2:38:05, 5.95s/it]
{'loss': 0.4528, 'learning_rate': 9.185257174166362e-07, 'epoch': 0.87}
+
87%|████████▋ | 10358/11952 [1:58:43<2:38:05, 5.95s/it]
87%|████████▋ | 10359/11952 [1:58:49<2:36:49, 5.91s/it]
{'loss': 0.4446, 'learning_rate': 9.173915478531148e-07, 'epoch': 0.87}
+
87%|████████▋ | 10359/11952 [1:58:49<2:36:49, 5.91s/it]
87%|████████▋ | 10360/11952 [1:58:55<2:35:37, 5.87s/it]
{'loss': 0.477, 'learning_rate': 9.162580452785775e-07, 'epoch': 0.87}
+
87%|████████▋ | 10360/11952 [1:58:55<2:35:37, 5.87s/it]
87%|████████▋ | 10361/11952 [1:59:01<2:34:05, 5.81s/it]
{'loss': 0.4613, 'learning_rate': 9.151252097762675e-07, 'epoch': 0.87}
+
87%|████████▋ | 10361/11952 [1:59:01<2:34:05, 5.81s/it]
87%|████████▋ | 10362/11952 [1:59:07<2:35:47, 5.88s/it]
{'loss': 0.4511, 'learning_rate': 9.139930414293774e-07, 'epoch': 0.87}
+
87%|████████▋ | 10362/11952 [1:59:07<2:35:47, 5.88s/it]
87%|████████▋ | 10363/11952 [1:59:12<2:34:06, 5.82s/it]
{'loss': 0.4492, 'learning_rate': 9.128615403210472e-07, 'epoch': 0.87}
+
87%|████████▋ | 10363/11952 [1:59:12<2:34:06, 5.82s/it]
87%|████████▋ | 10364/11952 [1:59:19<2:36:01, 5.89s/it]
{'loss': 0.4666, 'learning_rate': 9.117307065343683e-07, 'epoch': 0.87}
+
87%|████████▋ | 10364/11952 [1:59:19<2:36:01, 5.89s/it]
87%|████████▋ | 10365/11952 [1:59:25<2:39:14, 6.02s/it]
{'loss': 0.4672, 'learning_rate': 9.106005401523865e-07, 'epoch': 0.87}
+
87%|████████▋ | 10365/11952 [1:59:25<2:39:14, 6.02s/it]
87%|████████▋ | 10366/11952 [1:59:31<2:39:01, 6.02s/it]
{'loss': 0.4787, 'learning_rate': 9.094710412580942e-07, 'epoch': 0.87}
+
87%|████████▋ | 10366/11952 [1:59:31<2:39:01, 6.02s/it]
87%|████████▋ | 10367/11952 [1:59:37<2:38:43, 6.01s/it]
{'loss': 0.4664, 'learning_rate': 9.083422099344375e-07, 'epoch': 0.87}
+
87%|████████▋ | 10367/11952 [1:59:37<2:38:43, 6.01s/it]
87%|████████▋ | 10368/11952 [1:59:43<2:41:46, 6.13s/it]
{'loss': 0.4515, 'learning_rate': 9.072140462643154e-07, 'epoch': 0.87}
+
87%|████████▋ | 10368/11952 [1:59:43<2:41:46, 6.13s/it]
87%|████████▋ | 10369/11952 [1:59:50<2:42:43, 6.17s/it]
{'loss': 0.4508, 'learning_rate': 9.060865503305738e-07, 'epoch': 0.87}
+
87%|████████▋ | 10369/11952 [1:59:50<2:42:43, 6.17s/it]
87%|████████▋ | 10370/11952 [1:59:55<2:40:25, 6.08s/it]
{'loss': 0.4644, 'learning_rate': 9.049597222160111e-07, 'epoch': 0.87}
+
87%|████████▋ | 10370/11952 [1:59:55<2:40:25, 6.08s/it]
87%|████████▋ | 10371/11952 [2:00:01<2:37:57, 5.99s/it]
{'loss': 0.4454, 'learning_rate': 9.038335620033756e-07, 'epoch': 0.87}
+
87%|████████▋ | 10371/11952 [2:00:01<2:37:57, 5.99s/it]
87%|████████▋ | 10372/11952 [2:00:07<2:37:31, 5.98s/it]
{'loss': 0.4649, 'learning_rate': 9.02708069775372e-07, 'epoch': 0.87}
+
87%|████████▋ | 10372/11952 [2:00:07<2:37:31, 5.98s/it]
87%|████████▋ | 10373/11952 [2:00:13<2:39:39, 6.07s/it]
{'loss': 0.4778, 'learning_rate': 9.015832456146489e-07, 'epoch': 0.87}
+
87%|████████▋ | 10373/11952 [2:00:13<2:39:39, 6.07s/it]
87%|████████▋ | 10374/11952 [2:00:19<2:36:58, 5.97s/it]
{'loss': 0.4462, 'learning_rate': 9.004590896038068e-07, 'epoch': 0.87}
+
87%|████████▋ | 10374/11952 [2:00:19<2:36:58, 5.97s/it]
87%|████████▋ | 10375/11952 [2:00:25<2:34:51, 5.89s/it]
{'loss': 0.4462, 'learning_rate': 8.99335601825404e-07, 'epoch': 0.87}
+
87%|████████▋ | 10375/11952 [2:00:25<2:34:51, 5.89s/it]
87%|████████▋ | 10376/11952 [2:00:31<2:34:57, 5.90s/it]
{'loss': 0.4594, 'learning_rate': 8.982127823619413e-07, 'epoch': 0.87}
+
87%|████████▋ | 10376/11952 [2:00:31<2:34:57, 5.90s/it]
87%|████████▋ | 10377/11952 [2:00:37<2:38:22, 6.03s/it]
{'loss': 0.4522, 'learning_rate': 8.970906312958749e-07, 'epoch': 0.87}
+
87%|████████▋ | 10377/11952 [2:00:37<2:38:22, 6.03s/it]
87%|████████▋ | 10378/11952 [2:00:43<2:36:09, 5.95s/it]
{'loss': 0.482, 'learning_rate': 8.959691487096111e-07, 'epoch': 0.87}
+
87%|████████▋ | 10378/11952 [2:00:43<2:36:09, 5.95s/it]
87%|████████▋ | 10379/11952 [2:00:49<2:36:51, 5.98s/it]
{'loss': 0.4502, 'learning_rate': 8.948483346855064e-07, 'epoch': 0.87}
+
87%|████████▋ | 10379/11952 [2:00:49<2:36:51, 5.98s/it]
87%|████████▋ | 10380/11952 [2:00:55<2:35:11, 5.92s/it]
{'loss': 0.4623, 'learning_rate': 8.937281893058658e-07, 'epoch': 0.87}
+
87%|████████▋ | 10380/11952 [2:00:55<2:35:11, 5.92s/it]
87%|████████▋ | 10381/11952 [2:01:01<2:38:09, 6.04s/it]
{'loss': 0.4559, 'learning_rate': 8.926087126529548e-07, 'epoch': 0.87}
+
87%|████████▋ | 10381/11952 [2:01:01<2:38:09, 6.04s/it]
87%|████████▋ | 10382/11952 [2:01:07<2:37:44, 6.03s/it]
{'loss': 0.4734, 'learning_rate': 8.914899048089765e-07, 'epoch': 0.87}
+
87%|████████▋ | 10382/11952 [2:01:07<2:37:44, 6.03s/it]
87%|████████▋ | 10383/11952 [2:01:13<2:35:41, 5.95s/it]
{'loss': 0.4638, 'learning_rate': 8.903717658560961e-07, 'epoch': 0.87}
+
87%|████████▋ | 10383/11952 [2:01:13<2:35:41, 5.95s/it]
87%|████████▋ | 10384/11952 [2:01:18<2:32:59, 5.85s/it]
{'loss': 0.4368, 'learning_rate': 8.892542958764238e-07, 'epoch': 0.87}
+
87%|████████▋ | 10384/11952 [2:01:18<2:32:59, 5.85s/it]
87%|████████▋ | 10385/11952 [2:01:25<2:35:17, 5.95s/it]
{'loss': 0.4844, 'learning_rate': 8.881374949520216e-07, 'epoch': 0.87}
+
87%|████████▋ | 10385/11952 [2:01:25<2:35:17, 5.95s/it]
87%|████████▋ | 10386/11952 [2:01:31<2:35:22, 5.95s/it]
{'loss': 0.4673, 'learning_rate': 8.870213631649038e-07, 'epoch': 0.87}
+
87%|████████▋ | 10386/11952 [2:01:31<2:35:22, 5.95s/it]
87%|████████▋ | 10387/11952 [2:01:37<2:36:17, 5.99s/it]
{'loss': 0.4555, 'learning_rate': 8.859059005970305e-07, 'epoch': 0.87}
+
87%|████████▋ | 10387/11952 [2:01:37<2:36:17, 5.99s/it]
87%|████████▋ | 10388/11952 [2:01:43<2:36:43, 6.01s/it]
{'loss': 0.4701, 'learning_rate': 8.847911073303206e-07, 'epoch': 0.87}
+
87%|████████▋ | 10388/11952 [2:01:43<2:36:43, 6.01s/it]
87%|████████▋ | 10389/11952 [2:01:49<2:39:04, 6.11s/it]
{'loss': 0.4677, 'learning_rate': 8.836769834466397e-07, 'epoch': 0.87}
+
87%|████████▋ | 10389/11952 [2:01:49<2:39:04, 6.11s/it]
87%|████████▋ | 10390/11952 [2:01:55<2:38:14, 6.08s/it]
{'loss': 0.4631, 'learning_rate': 8.825635290278034e-07, 'epoch': 0.87}
+
87%|████████▋ | 10390/11952 [2:01:55<2:38:14, 6.08s/it]
87%|████████▋ | 10391/11952 [2:02:01<2:37:02, 6.04s/it]
{'loss': 0.4691, 'learning_rate': 8.814507441555775e-07, 'epoch': 0.87}
+
87%|████████▋ | 10391/11952 [2:02:01<2:37:02, 6.04s/it]
87%|████████▋ | 10392/11952 [2:02:07<2:34:57, 5.96s/it]
{'loss': 0.4743, 'learning_rate': 8.803386289116833e-07, 'epoch': 0.87}
+
87%|████████▋ | 10392/11952 [2:02:07<2:34:57, 5.96s/it]
87%|████████▋ | 10393/11952 [2:02:13<2:35:08, 5.97s/it]
{'loss': 0.4724, 'learning_rate': 8.792271833777888e-07, 'epoch': 0.87}
+
87%|████████▋ | 10393/11952 [2:02:13<2:35:08, 5.97s/it]
87%|████████▋ | 10394/11952 [2:02:19<2:34:14, 5.94s/it]
{'loss': 0.4461, 'learning_rate': 8.78116407635512e-07, 'epoch': 0.87}
+
87%|████████▋ | 10394/11952 [2:02:19<2:34:14, 5.94s/it]
87%|████████▋ | 10395/11952 [2:02:25<2:34:56, 5.97s/it]
{'loss': 0.4705, 'learning_rate': 8.770063017664276e-07, 'epoch': 0.87}
+
87%|████████▋ | 10395/11952 [2:02:25<2:34:56, 5.97s/it]
87%|████████▋ | 10396/11952 [2:02:31<2:35:29, 6.00s/it]
{'loss': 0.4547, 'learning_rate': 8.75896865852055e-07, 'epoch': 0.87}
+
87%|████████▋ | 10396/11952 [2:02:31<2:35:29, 6.00s/it]
87%|████████▋ | 10397/11952 [2:02:37<2:33:47, 5.93s/it]
{'loss': 0.4837, 'learning_rate': 8.747880999738667e-07, 'epoch': 0.87}
+
87%|████████▋ | 10397/11952 [2:02:37<2:33:47, 5.93s/it]
87%|████████▋ | 10398/11952 [2:02:42<2:32:47, 5.90s/it]
{'loss': 0.4696, 'learning_rate': 8.736800042132853e-07, 'epoch': 0.87}
+
87%|████████▋ | 10398/11952 [2:02:42<2:32:47, 5.90s/it]
87%|████████▋ | 10399/11952 [2:02:49<2:35:25, 6.01s/it]
{'loss': 0.4605, 'learning_rate': 8.725725786516858e-07, 'epoch': 0.87}
+
87%|████████▋ | 10399/11952 [2:02:49<2:35:25, 6.01s/it]0 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
87%|████████▋ | 10400/11952 [2:02:55<2:36:18, 6.04s/it]6 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4868, 'learning_rate': 8.714658233703921e-07, 'epoch': 0.87}
+
87%|████████▋ | 10400/11952 [2:02:55<2:36:18, 6.04s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
87%|████████▋ | 10401/11952 [2:03:25<5:42:51, 13.26s/it]
{'loss': 0.4542, 'learning_rate': 8.703597384506779e-07, 'epoch': 0.87}
+
87%|████████▋ | 10401/11952 [2:03:25<5:42:51, 13.26s/it]
87%|████████▋ | 10402/11952 [2:03:31<4:47:07, 11.11s/it]
{'loss': 0.4542, 'learning_rate': 8.692543239737706e-07, 'epoch': 0.87}
+
87%|████████▋ | 10402/11952 [2:03:31<4:47:07, 11.11s/it]
87%|████████▋ | 10403/11952 [2:03:37<4:04:52, 9.49s/it]
{'loss': 0.4587, 'learning_rate': 8.681495800208517e-07, 'epoch': 0.87}
+
87%|████████▋ | 10403/11952 [2:03:37<4:04:52, 9.49s/it]
87%|████████▋ | 10404/11952 [2:03:43<3:38:04, 8.45s/it]
{'loss': 0.4659, 'learning_rate': 8.670455066730444e-07, 'epoch': 0.87}
+
87%|████████▋ | 10404/11952 [2:03:43<3:38:04, 8.45s/it]
87%|████████▋ | 10405/11952 [2:03:49<3:18:40, 7.71s/it]
{'loss': 0.474, 'learning_rate': 8.65942104011428e-07, 'epoch': 0.87}
+
87%|████████▋ | 10405/11952 [2:03:49<3:18:40, 7.71s/it]
87%|████████▋ | 10406/11952 [2:03:55<3:07:07, 7.26s/it]
{'loss': 0.4734, 'learning_rate': 8.648393721170323e-07, 'epoch': 0.87}
+
87%|████████▋ | 10406/11952 [2:03:55<3:07:07, 7.26s/it]
87%|████████▋ | 10407/11952 [2:04:01<2:57:32, 6.90s/it]
{'loss': 0.4765, 'learning_rate': 8.63737311070837e-07, 'epoch': 0.87}
+
87%|████████▋ | 10407/11952 [2:04:01<2:57:32, 6.90s/it]
87%|████████▋ | 10408/11952 [2:04:07<2:49:39, 6.59s/it]
{'loss': 0.4577, 'learning_rate': 8.626359209537716e-07, 'epoch': 0.87}
+
87%|████████▋ | 10408/11952 [2:04:07<2:49:39, 6.59s/it]
87%|████████▋ | 10409/11952 [2:04:13<2:44:31, 6.40s/it]
{'loss': 0.4625, 'learning_rate': 8.615352018467204e-07, 'epoch': 0.87}
+
87%|████████▋ | 10409/11952 [2:04:13<2:44:31, 6.40s/it]
87%|████████▋ | 10410/11952 [2:04:19<2:41:30, 6.28s/it]
{'loss': 0.4697, 'learning_rate': 8.604351538305156e-07, 'epoch': 0.87}
+
87%|████████▋ | 10410/11952 [2:04:19<2:41:30, 6.28s/it]
87%|████████▋ | 10411/11952 [2:04:24<2:36:27, 6.09s/it]
{'loss': 0.4622, 'learning_rate': 8.593357769859368e-07, 'epoch': 0.87}
+
87%|████████▋ | 10411/11952 [2:04:24<2:36:27, 6.09s/it]
87%|████████▋ | 10412/11952 [2:04:30<2:35:15, 6.05s/it]
{'loss': 0.4769, 'learning_rate': 8.582370713937193e-07, 'epoch': 0.87}
+
87%|████████▋ | 10412/11952 [2:04:30<2:35:15, 6.05s/it]
87%|████████▋ | 10413/11952 [2:04:36<2:32:59, 5.96s/it]
{'loss': 0.4899, 'learning_rate': 8.571390371345489e-07, 'epoch': 0.87}
+
87%|████████▋ | 10413/11952 [2:04:36<2:32:59, 5.96s/it]
87%|████████▋ | 10414/11952 [2:04:42<2:33:43, 6.00s/it]
{'loss': 0.4746, 'learning_rate': 8.560416742890599e-07, 'epoch': 0.87}
+
87%|████████▋ | 10414/11952 [2:04:42<2:33:43, 6.00s/it]
87%|████████▋ | 10415/11952 [2:04:48<2:36:06, 6.09s/it]
{'loss': 0.4566, 'learning_rate': 8.549449829378354e-07, 'epoch': 0.87}
+
87%|████████▋ | 10415/11952 [2:04:48<2:36:06, 6.09s/it]
87%|████████▋ | 10416/11952 [2:04:54<2:34:52, 6.05s/it]
{'loss': 0.4804, 'learning_rate': 8.538489631614167e-07, 'epoch': 0.87}
+
87%|████████▋ | 10416/11952 [2:04:54<2:34:52, 6.05s/it]
87%|████████▋ | 10417/11952 [2:05:01<2:35:22, 6.07s/it]
{'loss': 0.4592, 'learning_rate': 8.527536150402882e-07, 'epoch': 0.87}
+
87%|████████▋ | 10417/11952 [2:05:01<2:35:22, 6.07s/it]
87%|████████▋ | 10418/11952 [2:05:06<2:33:52, 6.02s/it]
{'loss': 0.4471, 'learning_rate': 8.516589386548879e-07, 'epoch': 0.87}
+
87%|████████▋ | 10418/11952 [2:05:06<2:33:52, 6.02s/it]
87%|████████▋ | 10419/11952 [2:05:13<2:36:37, 6.13s/it]
{'loss': 0.4799, 'learning_rate': 8.505649340856048e-07, 'epoch': 0.87}
+
87%|████████▋ | 10419/11952 [2:05:13<2:36:37, 6.13s/it]
87%|████████▋ | 10420/11952 [2:05:19<2:37:05, 6.15s/it]
{'loss': 0.4877, 'learning_rate': 8.494716014127768e-07, 'epoch': 0.87}
+
87%|████████▋ | 10420/11952 [2:05:19<2:37:05, 6.15s/it]
87%|████████▋ | 10421/11952 [2:05:25<2:35:20, 6.09s/it]
{'loss': 0.4582, 'learning_rate': 8.483789407166932e-07, 'epoch': 0.87}
+
87%|████████▋ | 10421/11952 [2:05:25<2:35:20, 6.09s/it]
87%|████████▋ | 10422/11952 [2:05:31<2:33:33, 6.02s/it]
{'loss': 0.4554, 'learning_rate': 8.472869520775972e-07, 'epoch': 0.87}
+
87%|████████▋ | 10422/11952 [2:05:31<2:33:33, 6.02s/it]
87%|████████▋ | 10423/11952 [2:05:37<2:30:41, 5.91s/it]
{'loss': 0.4487, 'learning_rate': 8.461956355756772e-07, 'epoch': 0.87}
+
87%|████████▋ | 10423/11952 [2:05:37<2:30:41, 5.91s/it]
87%|████████▋ | 10424/11952 [2:05:42<2:30:20, 5.90s/it]
{'loss': 0.4454, 'learning_rate': 8.451049912910769e-07, 'epoch': 0.87}
+
87%|████████▋ | 10424/11952 [2:05:42<2:30:20, 5.90s/it]
87%|████████▋ | 10425/11952 [2:05:48<2:29:51, 5.89s/it]
{'loss': 0.4578, 'learning_rate': 8.440150193038888e-07, 'epoch': 0.87}
+
87%|████████▋ | 10425/11952 [2:05:48<2:29:51, 5.89s/it]
87%|████████▋ | 10426/11952 [2:05:54<2:29:46, 5.89s/it]
{'loss': 0.4786, 'learning_rate': 8.429257196941554e-07, 'epoch': 0.87}
+
87%|████████▋ | 10426/11952 [2:05:54<2:29:46, 5.89s/it]
87%|████████▋ | 10427/11952 [2:06:00<2:27:57, 5.82s/it]
{'loss': 0.4635, 'learning_rate': 8.418370925418695e-07, 'epoch': 0.87}
+
87%|████████▋ | 10427/11952 [2:06:00<2:27:57, 5.82s/it]
87%|████████▋ | 10428/11952 [2:06:05<2:26:46, 5.78s/it]
{'loss': 0.4748, 'learning_rate': 8.407491379269739e-07, 'epoch': 0.87}
+
87%|████████▋ | 10428/11952 [2:06:05<2:26:46, 5.78s/it]
87%|████████▋ | 10429/11952 [2:06:12<2:30:05, 5.91s/it]
{'loss': 0.4652, 'learning_rate': 8.396618559293679e-07, 'epoch': 0.87}
+
87%|████████▋ | 10429/11952 [2:06:12<2:30:05, 5.91s/it]
87%|████████▋ | 10430/11952 [2:06:18<2:29:46, 5.90s/it]
{'loss': 0.4624, 'learning_rate': 8.385752466288933e-07, 'epoch': 0.87}
+
87%|████████▋ | 10430/11952 [2:06:18<2:29:46, 5.90s/it]
87%|████████▋ | 10431/11952 [2:06:23<2:28:45, 5.87s/it]
{'loss': 0.4563, 'learning_rate': 8.374893101053482e-07, 'epoch': 0.87}
+
87%|████████▋ | 10431/11952 [2:06:23<2:28:45, 5.87s/it]
87%|████████▋ | 10432/11952 [2:06:29<2:28:57, 5.88s/it]
{'loss': 0.4677, 'learning_rate': 8.364040464384771e-07, 'epoch': 0.87}
+
87%|████████▋ | 10432/11952 [2:06:29<2:28:57, 5.88s/it]
87%|████████▋ | 10433/11952 [2:06:35<2:28:50, 5.88s/it]
{'loss': 0.4588, 'learning_rate': 8.353194557079791e-07, 'epoch': 0.87}
+
87%|████████▋ | 10433/11952 [2:06:35<2:28:50, 5.88s/it]
87%|████████▋ | 10434/11952 [2:06:41<2:28:20, 5.86s/it]
{'loss': 0.4498, 'learning_rate': 8.34235537993503e-07, 'epoch': 0.87}
+
87%|████████▋ | 10434/11952 [2:06:41<2:28:20, 5.86s/it]
87%|████████▋ | 10435/11952 [2:06:47<2:26:53, 5.81s/it]
{'loss': 0.4734, 'learning_rate': 8.331522933746428e-07, 'epoch': 0.87}
+
87%|████████▋ | 10435/11952 [2:06:47<2:26:53, 5.81s/it]
87%|████████▋ | 10436/11952 [2:06:53<2:27:20, 5.83s/it]
{'loss': 0.4523, 'learning_rate': 8.320697219309526e-07, 'epoch': 0.87}
+
87%|████████▋ | 10436/11952 [2:06:53<2:27:20, 5.83s/it]
87%|████████▋ | 10437/11952 [2:06:58<2:25:46, 5.77s/it]
{'loss': 0.4687, 'learning_rate': 8.309878237419289e-07, 'epoch': 0.87}
+
87%|████████▋ | 10437/11952 [2:06:58<2:25:46, 5.77s/it]
87%|████████▋ | 10438/11952 [2:07:04<2:29:26, 5.92s/it]
{'loss': 0.4675, 'learning_rate': 8.299065988870236e-07, 'epoch': 0.87}
+
87%|████████▋ | 10438/11952 [2:07:04<2:29:26, 5.92s/it]
87%|████████▋ | 10439/11952 [2:07:10<2:27:32, 5.85s/it]
{'loss': 0.4673, 'learning_rate': 8.288260474456367e-07, 'epoch': 0.87}
+
87%|████████▋ | 10439/11952 [2:07:10<2:27:32, 5.85s/it]
87%|████████▋ | 10440/11952 [2:07:16<2:26:05, 5.80s/it]
{'loss': 0.4436, 'learning_rate': 8.277461694971178e-07, 'epoch': 0.87}
+
87%|████████▋ | 10440/11952 [2:07:16<2:26:05, 5.80s/it]
87%|████████▋ | 10441/11952 [2:07:22<2:26:30, 5.82s/it]
{'loss': 0.4659, 'learning_rate': 8.266669651207704e-07, 'epoch': 0.87}
+
87%|████████▋ | 10441/11952 [2:07:22<2:26:30, 5.82s/it]
87%|████████▋ | 10442/11952 [2:07:28<2:29:44, 5.95s/it]
{'loss': 0.4867, 'learning_rate': 8.255884343958453e-07, 'epoch': 0.87}
+
87%|████████▋ | 10442/11952 [2:07:28<2:29:44, 5.95s/it]
87%|████████▋ | 10443/11952 [2:07:34<2:30:56, 6.00s/it]
{'loss': 0.4468, 'learning_rate': 8.245105774015461e-07, 'epoch': 0.87}
+
87%|████████▋ | 10443/11952 [2:07:34<2:30:56, 6.00s/it]
87%|████████▋ | 10444/11952 [2:07:40<2:28:31, 5.91s/it]
{'loss': 0.4678, 'learning_rate': 8.234333942170281e-07, 'epoch': 0.87}
+
87%|████████▋ | 10444/11952 [2:07:40<2:28:31, 5.91s/it]
87%|████████▋ | 10445/11952 [2:07:45<2:25:39, 5.80s/it]
{'loss': 0.4726, 'learning_rate': 8.223568849213925e-07, 'epoch': 0.87}
+
87%|████████▋ | 10445/11952 [2:07:45<2:25:39, 5.80s/it]
87%|████████▋ | 10446/11952 [2:07:51<2:25:40, 5.80s/it]
{'loss': 0.4651, 'learning_rate': 8.212810495936952e-07, 'epoch': 0.87}
+
87%|████████▋ | 10446/11952 [2:07:51<2:25:40, 5.80s/it]
87%|████████▋ | 10447/11952 [2:07:57<2:27:15, 5.87s/it]
{'loss': 0.474, 'learning_rate': 8.202058883129404e-07, 'epoch': 0.87}
+
87%|████████▋ | 10447/11952 [2:07:57<2:27:15, 5.87s/it]
87%|████████▋ | 10448/11952 [2:08:03<2:29:20, 5.96s/it]
{'loss': 0.4809, 'learning_rate': 8.191314011580842e-07, 'epoch': 0.87}
+
87%|████████▋ | 10448/11952 [2:08:03<2:29:20, 5.96s/it]
87%|████████▋ | 10449/11952 [2:08:09<2:27:33, 5.89s/it]
{'loss': 0.4541, 'learning_rate': 8.180575882080288e-07, 'epoch': 0.87}
+
87%|████████▋ | 10449/11952 [2:08:09<2:27:33, 5.89s/it]4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
87%|████████▋ | 10450/11952 [2:08:15<2:26:20, 5.85s/it]
{'loss': 0.4656, 'learning_rate': 8.169844495416368e-07, 'epoch': 0.87}
+
87%|████████▋ | 10450/11952 [2:08:15<2:26:20, 5.85s/it]
87%|████████▋ | 10451/11952 [2:08:21<2:26:54, 5.87s/it]
{'loss': 0.4456, 'learning_rate': 8.159119852377106e-07, 'epoch': 0.87}
+
87%|████████▋ | 10451/11952 [2:08:21<2:26:54, 5.87s/it]
87%|████████▋ | 10452/11952 [2:08:27<2:28:41, 5.95s/it]
{'loss': 0.4625, 'learning_rate': 8.148401953750096e-07, 'epoch': 0.87}
+
87%|████████▋ | 10452/11952 [2:08:27<2:28:41, 5.95s/it]
87%|████████▋ | 10453/11952 [2:08:33<2:29:42, 5.99s/it]
{'loss': 0.4638, 'learning_rate': 8.137690800322384e-07, 'epoch': 0.87}
+
87%|████████▋ | 10453/11952 [2:08:33<2:29:42, 5.99s/it]
87%|████████▋ | 10454/11952 [2:08:39<2:29:54, 6.00s/it]
{'loss': 0.4811, 'learning_rate': 8.126986392880587e-07, 'epoch': 0.87}
+
87%|████████▋ | 10454/11952 [2:08:39<2:29:54, 6.00s/it]
87%|████████▋ | 10455/11952 [2:08:45<2:32:08, 6.10s/it]
{'loss': 0.4776, 'learning_rate': 8.116288732210787e-07, 'epoch': 0.87}
+
87%|████████▋ | 10455/11952 [2:08:45<2:32:08, 6.10s/it]
87%|████████▋ | 10456/11952 [2:08:51<2:30:56, 6.05s/it]
{'loss': 0.4533, 'learning_rate': 8.105597819098554e-07, 'epoch': 0.87}
+
87%|████████▋ | 10456/11952 [2:08:51<2:30:56, 6.05s/it]
87%|████████▋ | 10457/11952 [2:08:57<2:28:58, 5.98s/it]
{'loss': 0.4689, 'learning_rate': 8.094913654329018e-07, 'epoch': 0.87}
+
87%|████████▋ | 10457/11952 [2:08:57<2:28:58, 5.98s/it]
88%|████████▊ | 10458/11952 [2:09:03<2:28:10, 5.95s/it]
{'loss': 0.4605, 'learning_rate': 8.08423623868676e-07, 'epoch': 0.87}
+
88%|████████▊ | 10458/11952 [2:09:03<2:28:10, 5.95s/it]
88%|████████▊ | 10459/11952 [2:09:09<2:29:59, 6.03s/it]
{'loss': 0.4652, 'learning_rate': 8.073565572955877e-07, 'epoch': 0.88}
+
88%|████████▊ | 10459/11952 [2:09:09<2:29:59, 6.03s/it]
88%|████████▊ | 10460/11952 [2:09:15<2:29:09, 6.00s/it]
{'loss': 0.4584, 'learning_rate': 8.062901657919998e-07, 'epoch': 0.88}
+
88%|████████▊ | 10460/11952 [2:09:15<2:29:09, 6.00s/it]
88%|████████▊ | 10461/11952 [2:09:21<2:28:43, 5.98s/it]
{'loss': 0.4699, 'learning_rate': 8.052244494362227e-07, 'epoch': 0.88}
+
88%|████████▊ | 10461/11952 [2:09:21<2:28:43, 5.98s/it]
88%|████████▊ | 10462/11952 [2:09:27<2:30:17, 6.05s/it]
{'loss': 0.4525, 'learning_rate': 8.041594083065152e-07, 'epoch': 0.88}
+
88%|████████▊ | 10462/11952 [2:09:27<2:30:17, 6.05s/it]
88%|████████▊ | 10463/11952 [2:09:33<2:28:06, 5.97s/it]
{'loss': 0.476, 'learning_rate': 8.030950424810946e-07, 'epoch': 0.88}
+
88%|████████▊ | 10463/11952 [2:09:33<2:28:06, 5.97s/it]
88%|████████▊ | 10464/11952 [2:09:39<2:26:08, 5.89s/it]
{'loss': 0.4795, 'learning_rate': 8.020313520381206e-07, 'epoch': 0.88}
+
88%|████████▊ | 10464/11952 [2:09:39<2:26:08, 5.89s/it]
88%|████████▊ | 10465/11952 [2:09:44<2:25:17, 5.86s/it]
{'loss': 0.4751, 'learning_rate': 8.009683370557075e-07, 'epoch': 0.88}
+
88%|████████▊ | 10465/11952 [2:09:44<2:25:17, 5.86s/it]
88%|████████▊ | 10466/11952 [2:09:51<2:27:07, 5.94s/it]
{'loss': 0.4427, 'learning_rate': 7.999059976119183e-07, 'epoch': 0.88}
+
88%|████████▊ | 10466/11952 [2:09:51<2:27:07, 5.94s/it]
88%|████████▊ | 10467/11952 [2:09:56<2:25:03, 5.86s/it]
{'loss': 0.4616, 'learning_rate': 7.988443337847673e-07, 'epoch': 0.88}
+
88%|████████▊ | 10467/11952 [2:09:56<2:25:03, 5.86s/it]
88%|████████▊ | 10468/11952 [2:10:02<2:26:02, 5.90s/it]
{'loss': 0.4687, 'learning_rate': 7.977833456522166e-07, 'epoch': 0.88}
+
88%|████████▊ | 10468/11952 [2:10:02<2:26:02, 5.90s/it]
88%|████████▊ | 10469/11952 [2:10:09<2:29:31, 6.05s/it]
{'loss': 0.4731, 'learning_rate': 7.967230332921816e-07, 'epoch': 0.88}
+
88%|████████▊ | 10469/11952 [2:10:09<2:29:31, 6.05s/it]
88%|████████▊ | 10470/11952 [2:10:15<2:30:46, 6.10s/it]
{'loss': 0.4715, 'learning_rate': 7.956633967825289e-07, 'epoch': 0.88}
+
88%|████████▊ | 10470/11952 [2:10:15<2:30:46, 6.10s/it]
88%|████████▊ | 10471/11952 [2:10:21<2:29:12, 6.05s/it]
{'loss': 0.4532, 'learning_rate': 7.946044362010718e-07, 'epoch': 0.88}
+
88%|████████▊ | 10471/11952 [2:10:21<2:29:12, 6.05s/it]
88%|████████▊ | 10472/11952 [2:10:27<2:30:38, 6.11s/it]
{'loss': 0.4768, 'learning_rate': 7.935461516255782e-07, 'epoch': 0.88}
+
88%|████████▊ | 10472/11952 [2:10:27<2:30:38, 6.11s/it]
88%|████████▊ | 10473/11952 [2:10:33<2:31:12, 6.13s/it]
{'loss': 0.4527, 'learning_rate': 7.924885431337604e-07, 'epoch': 0.88}
+
88%|████████▊ | 10473/11952 [2:10:33<2:31:12, 6.13s/it]
88%|████████▊ | 10474/11952 [2:10:39<2:31:41, 6.16s/it]
{'loss': 0.4693, 'learning_rate': 7.914316108032882e-07, 'epoch': 0.88}
+
88%|████████▊ | 10474/11952 [2:10:39<2:31:41, 6.16s/it]
88%|████████▊ | 10475/11952 [2:10:46<2:30:50, 6.13s/it]
{'loss': 0.4768, 'learning_rate': 7.903753547117788e-07, 'epoch': 0.88}
+
88%|████████▊ | 10475/11952 [2:10:46<2:30:50, 6.13s/it]
88%|████████▊ | 10476/11952 [2:10:51<2:28:06, 6.02s/it]
{'loss': 0.4678, 'learning_rate': 7.893197749367943e-07, 'epoch': 0.88}
+
88%|████████▊ | 10476/11952 [2:10:51<2:28:06, 6.02s/it]
88%|████████▊ | 10477/11952 [2:10:57<2:26:23, 5.96s/it]
{'loss': 0.4589, 'learning_rate': 7.882648715558583e-07, 'epoch': 0.88}
+
88%|████████▊ | 10477/11952 [2:10:57<2:26:23, 5.96s/it]
88%|████████▊ | 10478/11952 [2:11:03<2:25:05, 5.91s/it]
{'loss': 0.4649, 'learning_rate': 7.872106446464345e-07, 'epoch': 0.88}
+
88%|████████▊ | 10478/11952 [2:11:03<2:25:05, 5.91s/it]
88%|████████▊ | 10479/11952 [2:11:09<2:24:37, 5.89s/it]
{'loss': 0.4652, 'learning_rate': 7.861570942859431e-07, 'epoch': 0.88}
+
88%|████████▊ | 10479/11952 [2:11:09<2:24:37, 5.89s/it]
88%|████████▊ | 10480/11952 [2:11:15<2:26:34, 5.97s/it]
{'loss': 0.4853, 'learning_rate': 7.851042205517512e-07, 'epoch': 0.88}
+
88%|████████▊ | 10480/11952 [2:11:15<2:26:34, 5.97s/it]
88%|████████▊ | 10481/11952 [2:11:21<2:27:46, 6.03s/it]
{'loss': 0.4503, 'learning_rate': 7.840520235211768e-07, 'epoch': 0.88}
+
88%|████████▊ | 10481/11952 [2:11:21<2:27:46, 6.03s/it]
88%|████████▊ | 10482/11952 [2:11:27<2:24:55, 5.92s/it]
{'loss': 0.463, 'learning_rate': 7.830005032714905e-07, 'epoch': 0.88}
+
88%|████████▊ | 10482/11952 [2:11:27<2:24:55, 5.92s/it]
88%|████████▊ | 10483/11952 [2:11:33<2:25:28, 5.94s/it]
{'loss': 0.4523, 'learning_rate': 7.819496598799093e-07, 'epoch': 0.88}
+
88%|████████▊ | 10483/11952 [2:11:33<2:25:28, 5.94s/it]
88%|████████▊ | 10484/11952 [2:11:39<2:25:00, 5.93s/it]
{'loss': 0.4681, 'learning_rate': 7.808994934236058e-07, 'epoch': 0.88}
+
88%|████████▊ | 10484/11952 [2:11:39<2:25:00, 5.93s/it]
88%|████████▊ | 10485/11952 [2:11:45<2:24:34, 5.91s/it]
{'loss': 0.4989, 'learning_rate': 7.798500039796974e-07, 'epoch': 0.88}
+
88%|████████▊ | 10485/11952 [2:11:45<2:24:34, 5.91s/it]
88%|████████▊ | 10486/11952 [2:11:50<2:22:38, 5.84s/it]
{'loss': 0.4629, 'learning_rate': 7.788011916252558e-07, 'epoch': 0.88}
+
88%|████████▊ | 10486/11952 [2:11:50<2:22:38, 5.84s/it]
88%|████████▊ | 10487/11952 [2:11:56<2:23:15, 5.87s/it]
{'loss': 0.4475, 'learning_rate': 7.777530564373015e-07, 'epoch': 0.88}
+
88%|████████▊ | 10487/11952 [2:11:56<2:23:15, 5.87s/it]
88%|████████▊ | 10488/11952 [2:12:02<2:22:14, 5.83s/it]
{'loss': 0.4632, 'learning_rate': 7.767055984928041e-07, 'epoch': 0.88}
+
88%|████████▊ | 10488/11952 [2:12:02<2:22:14, 5.83s/it]
88%|████████▊ | 10489/11952 [2:12:08<2:23:57, 5.90s/it]
{'loss': 0.4704, 'learning_rate': 7.756588178686853e-07, 'epoch': 0.88}
+
88%|████████▊ | 10489/11952 [2:12:08<2:23:57, 5.90s/it]
88%|████████▊ | 10490/11952 [2:12:14<2:24:35, 5.93s/it]
{'loss': 0.4527, 'learning_rate': 7.746127146418148e-07, 'epoch': 0.88}
+
88%|████████▊ | 10490/11952 [2:12:14<2:24:35, 5.93s/it]
88%|████████▊ | 10491/11952 [2:12:20<2:24:58, 5.95s/it]
{'loss': 0.4651, 'learning_rate': 7.735672888890155e-07, 'epoch': 0.88}
+
88%|████████▊ | 10491/11952 [2:12:20<2:24:58, 5.95s/it]
88%|████████▊ | 10492/11952 [2:12:26<2:23:49, 5.91s/it]
{'loss': 0.4569, 'learning_rate': 7.725225406870607e-07, 'epoch': 0.88}
+
88%|████████▊ | 10492/11952 [2:12:26<2:23:49, 5.91s/it]
88%|████████▊ | 10493/11952 [2:12:32<2:24:28, 5.94s/it]
{'loss': 0.464, 'learning_rate': 7.714784701126687e-07, 'epoch': 0.88}
+
88%|████████▊ | 10493/11952 [2:12:32<2:24:28, 5.94s/it]
88%|████████▊ | 10494/11952 [2:12:38<2:23:02, 5.89s/it]
{'loss': 0.4621, 'learning_rate': 7.704350772425129e-07, 'epoch': 0.88}
+
88%|████████▊ | 10494/11952 [2:12:38<2:23:02, 5.89s/it]
88%|████████▊ | 10495/11952 [2:12:43<2:22:23, 5.86s/it]
{'loss': 0.4683, 'learning_rate': 7.693923621532184e-07, 'epoch': 0.88}
+
88%|████████▊ | 10495/11952 [2:12:43<2:22:23, 5.86s/it]
88%|████████▊ | 10496/11952 [2:12:49<2:23:12, 5.90s/it]
{'loss': 0.4905, 'learning_rate': 7.683503249213554e-07, 'epoch': 0.88}
+
88%|████████▊ | 10496/11952 [2:12:49<2:23:12, 5.90s/it]
88%|████████▊ | 10497/11952 [2:12:55<2:24:57, 5.98s/it]
{'loss': 0.4562, 'learning_rate': 7.673089656234456e-07, 'epoch': 0.88}
+
88%|████████▊ | 10497/11952 [2:12:55<2:24:57, 5.98s/it]
88%|████████▊ | 10498/11952 [2:13:01<2:22:15, 5.87s/it]
{'loss': 0.4489, 'learning_rate': 7.662682843359648e-07, 'epoch': 0.88}
+
88%|████████▊ | 10498/11952 [2:13:01<2:22:15, 5.87s/it]
88%|████████▊ | 10499/11952 [2:13:07<2:21:30, 5.84s/it]
{'loss': 0.4638, 'learning_rate': 7.652282811353362e-07, 'epoch': 0.88}
+
88%|████████▊ | 10499/11952 [2:13:07<2:21:30, 5.84s/it]7 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+01 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
88%|████████▊ | 10500/11952 [2:13:13<2:21:19, 5.84s/it]6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4682, 'learning_rate': 7.641889560979321e-07, 'epoch': 0.88}
+
88%|████████▊ | 10500/11952 [2:13:13<2:21:19, 5.84s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
88%|████████▊ | 10501/11952 [2:13:42<5:11:33, 12.88s/it]
{'loss': 0.4702, 'learning_rate': 7.631503093000758e-07, 'epoch': 0.88}
+
88%|████████▊ | 10501/11952 [2:13:42<5:11:33, 12.88s/it]
88%|████████▊ | 10502/11952 [2:13:48<4:20:45, 10.79s/it]
{'loss': 0.4686, 'learning_rate': 7.621123408180419e-07, 'epoch': 0.88}
+
88%|████████▊ | 10502/11952 [2:13:48<4:20:45, 10.79s/it]
88%|████████▊ | 10503/11952 [2:13:54<3:43:12, 9.24s/it]
{'loss': 0.452, 'learning_rate': 7.61075050728054e-07, 'epoch': 0.88}
+
88%|████████▊ | 10503/11952 [2:13:54<3:43:12, 9.24s/it]
88%|████████▊ | 10504/11952 [2:13:59<3:18:13, 8.21s/it]
{'loss': 0.4584, 'learning_rate': 7.600384391062865e-07, 'epoch': 0.88}
+
88%|████████▊ | 10504/11952 [2:13:59<3:18:13, 8.21s/it]
88%|████████▊ | 10505/11952 [2:14:05<3:02:39, 7.57s/it]
{'loss': 0.4783, 'learning_rate': 7.590025060288642e-07, 'epoch': 0.88}
+
88%|████████▊ | 10505/11952 [2:14:05<3:02:39, 7.57s/it]
88%|████████▊ | 10506/11952 [2:14:11<2:50:45, 7.09s/it]
{'loss': 0.4468, 'learning_rate': 7.579672515718628e-07, 'epoch': 0.88}
+
88%|████████▊ | 10506/11952 [2:14:11<2:50:45, 7.09s/it]
88%|████████▊ | 10507/11952 [2:14:17<2:42:45, 6.76s/it]
{'loss': 0.4802, 'learning_rate': 7.569326758113049e-07, 'epoch': 0.88}
+
88%|████████▊ | 10507/11952 [2:14:17<2:42:45, 6.76s/it]
88%|████████▊ | 10508/11952 [2:14:23<2:35:18, 6.45s/it]
{'loss': 0.4594, 'learning_rate': 7.558987788231675e-07, 'epoch': 0.88}
+
88%|████████▊ | 10508/11952 [2:14:23<2:35:18, 6.45s/it]
88%|████████▊ | 10509/11952 [2:14:29<2:30:14, 6.25s/it]
{'loss': 0.4826, 'learning_rate': 7.548655606833755e-07, 'epoch': 0.88}
+
88%|████████▊ | 10509/11952 [2:14:29<2:30:14, 6.25s/it]
88%|████████▊ | 10510/11952 [2:14:35<2:26:20, 6.09s/it]
{'loss': 0.4664, 'learning_rate': 7.538330214678002e-07, 'epoch': 0.88}
+
88%|████████▊ | 10510/11952 [2:14:35<2:26:20, 6.09s/it]
88%|████████▊ | 10511/11952 [2:14:40<2:23:11, 5.96s/it]
{'loss': 0.4502, 'learning_rate': 7.528011612522723e-07, 'epoch': 0.88}
+
88%|████████▊ | 10511/11952 [2:14:40<2:23:11, 5.96s/it]
88%|████████▊ | 10512/11952 [2:14:46<2:22:55, 5.96s/it]
{'loss': 0.45, 'learning_rate': 7.517699801125655e-07, 'epoch': 0.88}
+
88%|████████▊ | 10512/11952 [2:14:46<2:22:55, 5.96s/it]
88%|████████▊ | 10513/11952 [2:14:52<2:21:04, 5.88s/it]
{'loss': 0.4798, 'learning_rate': 7.507394781244038e-07, 'epoch': 0.88}
+
88%|████████▊ | 10513/11952 [2:14:52<2:21:04, 5.88s/it]
88%|████████▊ | 10514/11952 [2:14:58<2:19:21, 5.81s/it]
{'loss': 0.4694, 'learning_rate': 7.497096553634653e-07, 'epoch': 0.88}
+
88%|████████▊ | 10514/11952 [2:14:58<2:19:21, 5.81s/it]
88%|████████▊ | 10515/11952 [2:15:03<2:19:52, 5.84s/it]
{'loss': 0.4539, 'learning_rate': 7.48680511905373e-07, 'epoch': 0.88}
+
88%|████████▊ | 10515/11952 [2:15:03<2:19:52, 5.84s/it]
88%|████████▊ | 10516/11952 [2:15:10<2:22:25, 5.95s/it]
{'loss': 0.466, 'learning_rate': 7.476520478257065e-07, 'epoch': 0.88}
+
88%|████████▊ | 10516/11952 [2:15:10<2:22:25, 5.95s/it]
88%|████████▊ | 10517/11952 [2:15:16<2:22:04, 5.94s/it]
{'loss': 0.4647, 'learning_rate': 7.466242631999887e-07, 'epoch': 0.88}
+
88%|████████▊ | 10517/11952 [2:15:16<2:22:04, 5.94s/it]
88%|████████▊ | 10518/11952 [2:15:22<2:24:19, 6.04s/it]
{'loss': 0.4704, 'learning_rate': 7.455971581036991e-07, 'epoch': 0.88}
+
88%|████████▊ | 10518/11952 [2:15:22<2:24:19, 6.04s/it]
88%|████████▊ | 10519/11952 [2:15:28<2:22:52, 5.98s/it]
{'loss': 0.4576, 'learning_rate': 7.44570732612262e-07, 'epoch': 0.88}
+
88%|████████▊ | 10519/11952 [2:15:28<2:22:52, 5.98s/it]
88%|████████▊ | 10520/11952 [2:15:33<2:20:57, 5.91s/it]
{'loss': 0.4648, 'learning_rate': 7.435449868010535e-07, 'epoch': 0.88}
+
88%|████████▊ | 10520/11952 [2:15:33<2:20:57, 5.91s/it]
88%|████████▊ | 10521/11952 [2:15:39<2:20:29, 5.89s/it]
{'loss': 0.4485, 'learning_rate': 7.425199207454014e-07, 'epoch': 0.88}
+
88%|████████▊ | 10521/11952 [2:15:39<2:20:29, 5.89s/it]
88%|████████▊ | 10522/11952 [2:15:45<2:18:34, 5.81s/it]
{'loss': 0.4636, 'learning_rate': 7.41495534520581e-07, 'epoch': 0.88}
+
88%|████████▊ | 10522/11952 [2:15:45<2:18:34, 5.81s/it]
88%|████████▊ | 10523/11952 [2:15:51<2:18:09, 5.80s/it]
{'loss': 0.4768, 'learning_rate': 7.404718282018197e-07, 'epoch': 0.88}
+
88%|████████▊ | 10523/11952 [2:15:51<2:18:09, 5.80s/it]
88%|████████▊ | 10524/11952 [2:15:56<2:17:01, 5.76s/it]
{'loss': 0.4482, 'learning_rate': 7.394488018642931e-07, 'epoch': 0.88}
+
88%|████████▊ | 10524/11952 [2:15:56<2:17:01, 5.76s/it]
88%|████████▊ | 10525/11952 [2:16:02<2:16:17, 5.73s/it]
{'loss': 0.4373, 'learning_rate': 7.3842645558313e-07, 'epoch': 0.88}
+
88%|████████▊ | 10525/11952 [2:16:02<2:16:17, 5.73s/it]
88%|████████▊ | 10526/11952 [2:16:08<2:17:54, 5.80s/it]
{'loss': 0.4618, 'learning_rate': 7.374047894334047e-07, 'epoch': 0.88}
+
88%|████████▊ | 10526/11952 [2:16:08<2:17:54, 5.80s/it]
88%|████████▊ | 10527/11952 [2:16:14<2:17:25, 5.79s/it]
{'loss': 0.4681, 'learning_rate': 7.363838034901471e-07, 'epoch': 0.88}
+
88%|████████▊ | 10527/11952 [2:16:14<2:17:25, 5.79s/it]
88%|████████▊ | 10528/11952 [2:16:20<2:17:28, 5.79s/it]
{'loss': 0.4577, 'learning_rate': 7.35363497828333e-07, 'epoch': 0.88}
+
88%|████████▊ | 10528/11952 [2:16:20<2:17:28, 5.79s/it]
88%|████████▊ | 10529/11952 [2:16:25<2:18:01, 5.82s/it]
{'loss': 0.4653, 'learning_rate': 7.343438725228891e-07, 'epoch': 0.88}
+
88%|████████▊ | 10529/11952 [2:16:25<2:18:01, 5.82s/it]
88%|████████▊ | 10530/11952 [2:16:31<2:19:09, 5.87s/it]
{'loss': 0.4989, 'learning_rate': 7.33324927648692e-07, 'epoch': 0.88}
+
88%|████████▊ | 10530/11952 [2:16:31<2:19:09, 5.87s/it]
88%|████████▊ | 10531/11952 [2:16:37<2:19:43, 5.90s/it]
{'loss': 0.4368, 'learning_rate': 7.323066632805676e-07, 'epoch': 0.88}
+
88%|████████▊ | 10531/11952 [2:16:37<2:19:43, 5.90s/it]
88%|████████▊ | 10532/11952 [2:16:43<2:17:31, 5.81s/it]
{'loss': 0.4771, 'learning_rate': 7.312890794932969e-07, 'epoch': 0.88}
+
88%|████████▊ | 10532/11952 [2:16:43<2:17:31, 5.81s/it]
88%|████████▊ | 10533/11952 [2:16:49<2:17:32, 5.82s/it]
{'loss': 0.4751, 'learning_rate': 7.302721763616039e-07, 'epoch': 0.88}
+
88%|████████▊ | 10533/11952 [2:16:49<2:17:32, 5.82s/it]
88%|████████▊ | 10534/11952 [2:16:55<2:17:17, 5.81s/it]
{'loss': 0.4537, 'learning_rate': 7.292559539601674e-07, 'epoch': 0.88}
+
88%|████████▊ | 10534/11952 [2:16:55<2:17:17, 5.81s/it]
88%|████████▊ | 10535/11952 [2:17:01<2:18:05, 5.85s/it]
{'loss': 0.4543, 'learning_rate': 7.28240412363611e-07, 'epoch': 0.88}
+
88%|████████▊ | 10535/11952 [2:17:01<2:18:05, 5.85s/it]
88%|████████▊ | 10536/11952 [2:17:07<2:20:29, 5.95s/it]
{'loss': 0.4839, 'learning_rate': 7.272255516465176e-07, 'epoch': 0.88}
+
88%|████████▊ | 10536/11952 [2:17:07<2:20:29, 5.95s/it]
88%|████████▊ | 10537/11952 [2:17:13<2:22:21, 6.04s/it]
{'loss': 0.4525, 'learning_rate': 7.262113718834086e-07, 'epoch': 0.88}
+
88%|████████▊ | 10537/11952 [2:17:13<2:22:21, 6.04s/it]
88%|████████▊ | 10538/11952 [2:17:19<2:20:32, 5.96s/it]
{'loss': 0.4823, 'learning_rate': 7.251978731487664e-07, 'epoch': 0.88}
+
88%|████████▊ | 10538/11952 [2:17:19<2:20:32, 5.96s/it]
88%|████████▊ | 10539/11952 [2:17:25<2:19:11, 5.91s/it]
{'loss': 0.4638, 'learning_rate': 7.241850555170149e-07, 'epoch': 0.88}
+
88%|████████▊ | 10539/11952 [2:17:25<2:19:11, 5.91s/it]
88%|████████▊ | 10540/11952 [2:17:30<2:18:12, 5.87s/it]
{'loss': 0.4807, 'learning_rate': 7.231729190625314e-07, 'epoch': 0.88}
+
88%|████████▊ | 10540/11952 [2:17:30<2:18:12, 5.87s/it]
88%|████████▊ | 10541/11952 [2:17:36<2:18:59, 5.91s/it]
{'loss': 0.4729, 'learning_rate': 7.221614638596441e-07, 'epoch': 0.88}
+
88%|████████▊ | 10541/11952 [2:17:36<2:18:59, 5.91s/it]
88%|████████▊ | 10542/11952 [2:17:42<2:17:41, 5.86s/it]
{'loss': 0.4802, 'learning_rate': 7.211506899826304e-07, 'epoch': 0.88}
+
88%|████████▊ | 10542/11952 [2:17:42<2:17:41, 5.86s/it]
88%|████████▊ | 10543/11952 [2:17:48<2:15:12, 5.76s/it]
{'loss': 0.4365, 'learning_rate': 7.201405975057152e-07, 'epoch': 0.88}
+
88%|████████▊ | 10543/11952 [2:17:48<2:15:12, 5.76s/it]
88%|████████▊ | 10544/11952 [2:17:54<2:16:35, 5.82s/it]
{'loss': 0.4644, 'learning_rate': 7.191311865030748e-07, 'epoch': 0.88}
+
88%|████████▊ | 10544/11952 [2:17:54<2:16:35, 5.82s/it]
88%|████████▊ | 10545/11952 [2:17:59<2:16:55, 5.84s/it]
{'loss': 0.4555, 'learning_rate': 7.18122457048841e-07, 'epoch': 0.88}
+
88%|████████▊ | 10545/11952 [2:17:59<2:16:55, 5.84s/it]
88%|████████▊ | 10546/11952 [2:18:05<2:16:09, 5.81s/it]
{'loss': 0.4495, 'learning_rate': 7.171144092170845e-07, 'epoch': 0.88}
+
88%|████████▊ | 10546/11952 [2:18:05<2:16:09, 5.81s/it]
88%|████████▊ | 10547/11952 [2:18:11<2:17:53, 5.89s/it]
{'loss': 0.4348, 'learning_rate': 7.161070430818385e-07, 'epoch': 0.88}
+
88%|████████▊ | 10547/11952 [2:18:11<2:17:53, 5.89s/it]
88%|████████▊ | 10548/11952 [2:18:17<2:18:16, 5.91s/it]
{'loss': 0.4765, 'learning_rate': 7.151003587170757e-07, 'epoch': 0.88}
+
88%|████████▊ | 10548/11952 [2:18:17<2:18:16, 5.91s/it]
88%|████████▊ | 10549/11952 [2:18:23<2:18:22, 5.92s/it]
{'loss': 0.4557, 'learning_rate': 7.14094356196724e-07, 'epoch': 0.88}
+
88%|████████▊ | 10549/11952 [2:18:23<2:18:22, 5.92s/it]4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+02 5AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+ 1AutoResumeHook: Checking whether to suspend... AutoResumeHook: Checking whether to suspend...
+
+
88%|████████▊ | 10550/11952 [2:18:29<2:19:28, 5.97s/it]3 6AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4436, 'learning_rate': 7.130890355946596e-07, 'epoch': 0.88}
+
88%|████████▊ | 10550/11952 [2:18:29<2:19:28, 5.97s/it]
88%|████████▊ | 10551/11952 [2:18:35<2:17:16, 5.88s/it]
{'loss': 0.4619, 'learning_rate': 7.12084396984708e-07, 'epoch': 0.88}
+
88%|████████▊ | 10551/11952 [2:18:35<2:17:16, 5.88s/it]
88%|████████▊ | 10552/11952 [2:18:41<2:17:35, 5.90s/it]
{'loss': 0.4572, 'learning_rate': 7.11080440440648e-07, 'epoch': 0.88}
+
88%|████████▊ | 10552/11952 [2:18:41<2:17:35, 5.90s/it]
88%|████████▊ | 10553/11952 [2:18:47<2:17:01, 5.88s/it]
{'loss': 0.464, 'learning_rate': 7.100771660362061e-07, 'epoch': 0.88}
+
88%|████████▊ | 10553/11952 [2:18:47<2:17:01, 5.88s/it]
88%|████████▊ | 10554/11952 [2:18:53<2:17:47, 5.91s/it]
{'loss': 0.465, 'learning_rate': 7.090745738450566e-07, 'epoch': 0.88}
+
88%|████████▊ | 10554/11952 [2:18:53<2:17:47, 5.91s/it]
88%|████████▊ | 10555/11952 [2:18:59<2:18:40, 5.96s/it]
{'loss': 0.4505, 'learning_rate': 7.080726639408264e-07, 'epoch': 0.88}
+
88%|████████▊ | 10555/11952 [2:18:59<2:18:40, 5.96s/it]
88%|████████▊ | 10556/11952 [2:19:05<2:17:28, 5.91s/it]
{'loss': 0.458, 'learning_rate': 7.070714363970899e-07, 'epoch': 0.88}
+
88%|████████▊ | 10556/11952 [2:19:05<2:17:28, 5.91s/it]
88%|████████▊ | 10557/11952 [2:19:10<2:15:41, 5.84s/it]
{'loss': 0.4661, 'learning_rate': 7.060708912873771e-07, 'epoch': 0.88}
+
88%|████████▊ | 10557/11952 [2:19:10<2:15:41, 5.84s/it]
88%|████████▊ | 10558/11952 [2:19:16<2:15:21, 5.83s/it]
{'loss': 0.4561, 'learning_rate': 7.050710286851603e-07, 'epoch': 0.88}
+
88%|████████▊ | 10558/11952 [2:19:16<2:15:21, 5.83s/it]
88%|████████▊ | 10559/11952 [2:19:22<2:16:30, 5.88s/it]
{'loss': 0.4619, 'learning_rate': 7.040718486638676e-07, 'epoch': 0.88}
+
88%|████████▊ | 10559/11952 [2:19:22<2:16:30, 5.88s/it]
88%|████████▊ | 10560/11952 [2:19:28<2:16:24, 5.88s/it]
{'loss': 0.4623, 'learning_rate': 7.030733512968735e-07, 'epoch': 0.88}
+
88%|████████▊ | 10560/11952 [2:19:28<2:16:24, 5.88s/it]
88%|████████▊ | 10561/11952 [2:19:34<2:16:28, 5.89s/it]
{'loss': 0.4636, 'learning_rate': 7.020755366575038e-07, 'epoch': 0.88}
+
88%|████████▊ | 10561/11952 [2:19:34<2:16:28, 5.89s/it]
88%|████████▊ | 10562/11952 [2:19:39<2:13:43, 5.77s/it]
{'loss': 0.4576, 'learning_rate': 7.010784048190344e-07, 'epoch': 0.88}
+
88%|████████▊ | 10562/11952 [2:19:39<2:13:43, 5.77s/it]
88%|████████▊ | 10563/11952 [2:19:45<2:14:24, 5.81s/it]
{'loss': 0.4482, 'learning_rate': 7.000819558546901e-07, 'epoch': 0.88}
+
88%|████████▊ | 10563/11952 [2:19:45<2:14:24, 5.81s/it]
88%|████████▊ | 10564/11952 [2:19:51<2:14:11, 5.80s/it]
{'loss': 0.4662, 'learning_rate': 6.990861898376444e-07, 'epoch': 0.88}
+
88%|████████▊ | 10564/11952 [2:19:51<2:14:11, 5.80s/it]
88%|████████▊ | 10565/11952 [2:19:57<2:13:06, 5.76s/it]
{'loss': 0.4577, 'learning_rate': 6.980911068410224e-07, 'epoch': 0.88}
+
88%|████████▊ | 10565/11952 [2:19:57<2:13:06, 5.76s/it]
88%|████████▊ | 10566/11952 [2:20:03<2:16:33, 5.91s/it]
{'loss': 0.4521, 'learning_rate': 6.97096706937902e-07, 'epoch': 0.88}
+
88%|████████▊ | 10566/11952 [2:20:03<2:16:33, 5.91s/it]
88%|████████▊ | 10567/11952 [2:20:09<2:16:03, 5.89s/it]
{'loss': 0.452, 'learning_rate': 6.961029902013039e-07, 'epoch': 0.88}
+
88%|████████▊ | 10567/11952 [2:20:09<2:16:03, 5.89s/it]
88%|████████▊ | 10568/11952 [2:20:14<2:13:46, 5.80s/it]
{'loss': 0.4763, 'learning_rate': 6.951099567042052e-07, 'epoch': 0.88}
+
88%|████████▊ | 10568/11952 [2:20:14<2:13:46, 5.80s/it]
88%|████████▊ | 10569/11952 [2:20:20<2:15:28, 5.88s/it]
{'loss': 0.4561, 'learning_rate': 6.941176065195299e-07, 'epoch': 0.88}
+
88%|████████▊ | 10569/11952 [2:20:20<2:15:28, 5.88s/it]
88%|████████▊ | 10570/11952 [2:20:26<2:13:28, 5.79s/it]
{'loss': 0.4594, 'learning_rate': 6.931259397201517e-07, 'epoch': 0.88}
+
88%|████████▊ | 10570/11952 [2:20:26<2:13:28, 5.79s/it]
88%|████████▊ | 10571/11952 [2:20:32<2:13:22, 5.79s/it]
{'loss': 0.4663, 'learning_rate': 6.921349563788949e-07, 'epoch': 0.88}
+
88%|████████▊ | 10571/11952 [2:20:32<2:13:22, 5.79s/it]
88%|████████▊ | 10572/11952 [2:20:38<2:12:49, 5.77s/it]
{'loss': 0.4581, 'learning_rate': 6.911446565685298e-07, 'epoch': 0.88}
+
88%|████████▊ | 10572/11952 [2:20:38<2:12:49, 5.77s/it]
88%|████████▊ | 10573/11952 [2:20:44<2:15:55, 5.91s/it]
{'loss': 0.4803, 'learning_rate': 6.901550403617852e-07, 'epoch': 0.88}
+
88%|████████▊ | 10573/11952 [2:20:44<2:15:55, 5.91s/it]
88%|████████▊ | 10574/11952 [2:20:50<2:16:34, 5.95s/it]
{'loss': 0.4621, 'learning_rate': 6.891661078313317e-07, 'epoch': 0.88}
+
88%|████████▊ | 10574/11952 [2:20:50<2:16:34, 5.95s/it]
88%|████████▊ | 10575/11952 [2:20:56<2:15:01, 5.88s/it]
{'loss': 0.4698, 'learning_rate': 6.881778590497923e-07, 'epoch': 0.88}
+
88%|████████▊ | 10575/11952 [2:20:56<2:15:01, 5.88s/it]
88%|████████▊ | 10576/11952 [2:21:01<2:15:10, 5.89s/it]
{'loss': 0.4748, 'learning_rate': 6.87190294089738e-07, 'epoch': 0.88}
+
88%|████████▊ | 10576/11952 [2:21:01<2:15:10, 5.89s/it]
88%|████████▊ | 10577/11952 [2:21:07<2:14:09, 5.85s/it]
{'loss': 0.453, 'learning_rate': 6.86203413023696e-07, 'epoch': 0.88}
+
88%|████████▊ | 10577/11952 [2:21:07<2:14:09, 5.85s/it]
89%|████████▊ | 10578/11952 [2:21:13<2:13:49, 5.84s/it]
{'loss': 0.4714, 'learning_rate': 6.852172159241343e-07, 'epoch': 0.89}
+
89%|████████▊ | 10578/11952 [2:21:13<2:13:49, 5.84s/it]
89%|████████▊ | 10579/11952 [2:21:19<2:14:53, 5.89s/it]
{'loss': 0.4762, 'learning_rate': 6.842317028634793e-07, 'epoch': 0.89}
+
89%|████████▊ | 10579/11952 [2:21:19<2:14:53, 5.89s/it]
89%|████████▊ | 10580/11952 [2:21:25<2:13:24, 5.83s/it]
{'loss': 0.4559, 'learning_rate': 6.832468739141007e-07, 'epoch': 0.89}
+
89%|████████▊ | 10580/11952 [2:21:25<2:13:24, 5.83s/it]
89%|████████▊ | 10581/11952 [2:21:31<2:13:50, 5.86s/it]
{'loss': 0.4699, 'learning_rate': 6.822627291483197e-07, 'epoch': 0.89}
+
89%|████████▊ | 10581/11952 [2:21:31<2:13:50, 5.86s/it]
89%|████████▊ | 10582/11952 [2:21:37<2:13:52, 5.86s/it]
{'loss': 0.4521, 'learning_rate': 6.812792686384095e-07, 'epoch': 0.89}
+
89%|████████▊ | 10582/11952 [2:21:37<2:13:52, 5.86s/it]
89%|████████▊ | 10583/11952 [2:21:43<2:14:52, 5.91s/it]
{'loss': 0.4515, 'learning_rate': 6.802964924565891e-07, 'epoch': 0.89}
+
89%|████████▊ | 10583/11952 [2:21:43<2:14:52, 5.91s/it]
89%|████████▊ | 10584/11952 [2:21:48<2:14:36, 5.90s/it]
{'loss': 0.4689, 'learning_rate': 6.793144006750318e-07, 'epoch': 0.89}
+
89%|████████▊ | 10584/11952 [2:21:48<2:14:36, 5.90s/it]
89%|████████▊ | 10585/11952 [2:21:54<2:13:44, 5.87s/it]
{'loss': 0.4531, 'learning_rate': 6.783329933658555e-07, 'epoch': 0.89}
+
89%|████████▊ | 10585/11952 [2:21:54<2:13:44, 5.87s/it]
89%|████████▊ | 10586/11952 [2:22:00<2:12:56, 5.84s/it]
{'loss': 0.4877, 'learning_rate': 6.773522706011337e-07, 'epoch': 0.89}
+
89%|████████▊ | 10586/11952 [2:22:00<2:12:56, 5.84s/it]
89%|████████▊ | 10587/11952 [2:22:06<2:14:19, 5.90s/it]
{'loss': 0.4599, 'learning_rate': 6.763722324528843e-07, 'epoch': 0.89}
+
89%|████████▊ | 10587/11952 [2:22:06<2:14:19, 5.90s/it]
89%|████████▊ | 10588/11952 [2:22:12<2:15:15, 5.95s/it]
{'loss': 0.469, 'learning_rate': 6.753928789930797e-07, 'epoch': 0.89}
+
89%|████████▊ | 10588/11952 [2:22:12<2:15:15, 5.95s/it]
89%|████████▊ | 10589/11952 [2:22:18<2:13:49, 5.89s/it]
{'loss': 0.4548, 'learning_rate': 6.74414210293638e-07, 'epoch': 0.89}
+
89%|████████▊ | 10589/11952 [2:22:18<2:13:49, 5.89s/it]
89%|████████▊ | 10590/11952 [2:22:24<2:14:57, 5.95s/it]
{'loss': 0.4717, 'learning_rate': 6.734362264264283e-07, 'epoch': 0.89}
+
89%|████████▊ | 10590/11952 [2:22:24<2:14:57, 5.95s/it]
89%|████████▊ | 10591/11952 [2:22:30<2:12:58, 5.86s/it]
{'loss': 0.4463, 'learning_rate': 6.724589274632698e-07, 'epoch': 0.89}
+
89%|████████▊ | 10591/11952 [2:22:30<2:12:58, 5.86s/it]
89%|████████▊ | 10592/11952 [2:22:35<2:12:15, 5.83s/it]
{'loss': 0.4454, 'learning_rate': 6.714823134759307e-07, 'epoch': 0.89}
+
89%|████████▊ | 10592/11952 [2:22:35<2:12:15, 5.83s/it]WARNING: tokenization mismatch: 1 vs. 737. [[{'from': 'human', 'value': 'ASSISTANT: You are a top consultant specialising in advising tax firms and have the following skills and qualities.\n\nKNOWLEDGE: Consultant in a top consulting firm specialising in tax consulting, senior strategist, digital expert.\n\nCHARACTERISTICS: Customer-focused, empathetic, solution-oriented, personable, persuasive, creative.\n\nTASK: Use your knowledge to develop 10 measures to encourage clients to submit their documents digitally instead of by post. The measures should be formulated in such a way that the client recognises the advantages of digital filing. The law firm is digitised and can accept digital documents.\n\nOUTPUT: A list of the 10 actions, each with the name of the action as a heading and 2 short additional bullet points.\n\nOUTPUT LANGUAGE: German'}, {'from': 'gpt', 'value': '1. Persönlicher Kontakt und Beratung:\n\t* Persönliche Beratung und Unterstützung bei der Umstellung auf digitales Einreichen\n\t* Betonung der Vorteile, wie Zeit- und Kosteneinsparungen\n2. Schulung und Unterstützung:\n\t* Schulungen für die digitale Einreichung von Dokumenten\n\t* Anleitung zur Nutzung von Tools und Software\n3. Anreize schaffen:\n\t* Ermäßigung bei der Beauftragung digitaler Dienstleistungen\n\t* Sonderangebote für Kunden, die ihre Dokumente digital einreichen\n4. Informationen bereitstellen:\n\t* Veröffentlichung von Leitfäden und Handbüchern für die digitale Einreichung von Dokumenten\n\t* FAQ-Liste für häufig gestellte Fragen zum digitalen Einreichen\n5. Klare Kommunikation:\n\t* Verständliche Kommunikation der Vorteile der digitalen Einreichung\n\t* Bereitstellung von Informationen über die Sicherheit der digitalen Übermittlung\n6. Einfache Zugänglichkeit:\n\t* Vereinfachung des digitalen Einreichungsprozesses durch intuitive Online-Plattformen\n\t* Bereitstellung von Unterstützung für den Fall technischer Schwierigkeiten\n7. Zeitersparnis betonen:\n\t* Betonung der Vorteile von Zeitersparnis durch digitales Einreichen\n\t* Erinnerungen an Fristen und den Nutzen der pünktlichen Einreichung\n8. Umweltbewusstsein:\n\t* Betonung des Umweltvorteils durch digitales Einreichen von Dokumenten\n\t* Verweis auf die Möglichkeit, Papierverbrauch zu reduzieren\n9. Kosteneffizienz:\n\t* Betonung der Vorteile von Kosteneinsparungen durch digitales Einreichen\n\t* Verweis auf die Möglichkeit, Papier- und Portokosten zu sparen\n10. Feedback einholen:\n* Umfrage zur Bewertung des digitalen Einreichungsprozesses\n* Analyse der Ergebnisse zur Verbesserung der digitalen Dienstleistungen'}]] (ignored)
+
89%|████████▊ | 10593/11952 [2:22:41<2:12:23, 5.85s/it]
{'loss': 0.4723, 'learning_rate': 6.705063845361315e-07, 'epoch': 0.89}
+
89%|████████▊ | 10593/11952 [2:22:41<2:12:23, 5.85s/it]
89%|████████▊ | 10594/11952 [2:22:47<2:11:24, 5.81s/it]
{'loss': 0.4621, 'learning_rate': 6.695311407155391e-07, 'epoch': 0.89}
+
89%|████████▊ | 10594/11952 [2:22:47<2:11:24, 5.81s/it]
89%|████████▊ | 10595/11952 [2:22:53<2:11:51, 5.83s/it]
{'loss': 0.4683, 'learning_rate': 6.68556582085772e-07, 'epoch': 0.89}
+
89%|████████▊ | 10595/11952 [2:22:53<2:11:51, 5.83s/it]
89%|████████▊ | 10596/11952 [2:22:59<2:11:47, 5.83s/it]
{'loss': 0.4772, 'learning_rate': 6.675827087183961e-07, 'epoch': 0.89}
+
89%|████████▊ | 10596/11952 [2:22:59<2:11:47, 5.83s/it]
89%|████████▊ | 10597/11952 [2:23:05<2:12:11, 5.85s/it]
{'loss': 0.4646, 'learning_rate': 6.666095206849288e-07, 'epoch': 0.89}
+
89%|████████▊ | 10597/11952 [2:23:05<2:12:11, 5.85s/it]
89%|████████▊ | 10598/11952 [2:23:10<2:12:05, 5.85s/it]
{'loss': 0.4574, 'learning_rate': 6.656370180568395e-07, 'epoch': 0.89}
+
89%|████████▊ | 10598/11952 [2:23:10<2:12:05, 5.85s/it]
89%|████████▊ | 10599/11952 [2:23:16<2:10:26, 5.78s/it]
{'loss': 0.4854, 'learning_rate': 6.646652009055409e-07, 'epoch': 0.89}
+
89%|████████▊ | 10599/11952 [2:23:16<2:10:26, 5.78s/it]7 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
89%|████████▊ | 10600/11952 [2:23:22<2:12:16, 5.87s/it]6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4795, 'learning_rate': 6.63694069302403e-07, 'epoch': 0.89}
+
89%|████████▊ | 10600/11952 [2:23:22<2:12:16, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
89%|████████▊ | 10601/11952 [2:23:52<4:51:35, 12.95s/it]
{'loss': 0.4678, 'learning_rate': 6.627236233187407e-07, 'epoch': 0.89}
+
89%|████████▊ | 10601/11952 [2:23:52<4:51:35, 12.95s/it]
89%|████████▊ | 10602/11952 [2:23:58<4:03:55, 10.84s/it]
{'loss': 0.4546, 'learning_rate': 6.61753863025818e-07, 'epoch': 0.89}
+
89%|████████▊ | 10602/11952 [2:23:58<4:03:55, 10.84s/it]
89%|████████▊ | 10603/11952 [2:24:04<3:31:31, 9.41s/it]
{'loss': 0.4514, 'learning_rate': 6.607847884948515e-07, 'epoch': 0.89}
+
89%|████████▊ | 10603/11952 [2:24:04<3:31:31, 9.41s/it]
89%|████████▊ | 10604/11952 [2:24:10<3:08:08, 8.37s/it]
{'loss': 0.4607, 'learning_rate': 6.598163997970053e-07, 'epoch': 0.89}
+
89%|████████▊ | 10604/11952 [2:24:10<3:08:08, 8.37s/it]
89%|████████▊ | 10605/11952 [2:24:16<2:52:03, 7.66s/it]
{'loss': 0.467, 'learning_rate': 6.588486970033936e-07, 'epoch': 0.89}
+
89%|████████▊ | 10605/11952 [2:24:16<2:52:03, 7.66s/it]
89%|████████▊ | 10606/11952 [2:24:22<2:40:45, 7.17s/it]
{'loss': 0.461, 'learning_rate': 6.578816801850796e-07, 'epoch': 0.89}
+
89%|████████▊ | 10606/11952 [2:24:22<2:40:45, 7.17s/it]
89%|████████▊ | 10607/11952 [2:24:28<2:33:03, 6.83s/it]
{'loss': 0.4654, 'learning_rate': 6.569153494130798e-07, 'epoch': 0.89}
+
89%|████████▊ | 10607/11952 [2:24:28<2:33:03, 6.83s/it]
89%|████████▉ | 10608/11952 [2:24:34<2:29:27, 6.67s/it]
{'loss': 0.485, 'learning_rate': 6.55949704758354e-07, 'epoch': 0.89}
+
89%|████████▉ | 10608/11952 [2:24:34<2:29:27, 6.67s/it]
89%|████████▉ | 10609/11952 [2:24:40<2:24:50, 6.47s/it]
{'loss': 0.4681, 'learning_rate': 6.549847462918191e-07, 'epoch': 0.89}
+
89%|████████▉ | 10609/11952 [2:24:40<2:24:50, 6.47s/it]
89%|████████▉ | 10610/11952 [2:24:46<2:21:47, 6.34s/it]
{'loss': 0.4647, 'learning_rate': 6.540204740843348e-07, 'epoch': 0.89}
+
89%|████████▉ | 10610/11952 [2:24:46<2:21:47, 6.34s/it]
89%|████████▉ | 10611/11952 [2:24:52<2:18:02, 6.18s/it]
{'loss': 0.4694, 'learning_rate': 6.530568882067145e-07, 'epoch': 0.89}
+
89%|████████▉ | 10611/11952 [2:24:52<2:18:02, 6.18s/it]
89%|████████▉ | 10612/11952 [2:24:58<2:15:13, 6.05s/it]
{'loss': 0.4592, 'learning_rate': 6.520939887297184e-07, 'epoch': 0.89}
+
89%|████████▉ | 10612/11952 [2:24:58<2:15:13, 6.05s/it]
89%|████████▉ | 10613/11952 [2:25:04<2:14:44, 6.04s/it]
{'loss': 0.4805, 'learning_rate': 6.511317757240598e-07, 'epoch': 0.89}
+
89%|████████▉ | 10613/11952 [2:25:04<2:14:44, 6.04s/it]
89%|████████▉ | 10614/11952 [2:25:10<2:14:30, 6.03s/it]
{'loss': 0.4699, 'learning_rate': 6.50170249260399e-07, 'epoch': 0.89}
+
89%|████████▉ | 10614/11952 [2:25:10<2:14:30, 6.03s/it]
89%|████████▉ | 10615/11952 [2:25:15<2:12:52, 5.96s/it]
{'loss': 0.4552, 'learning_rate': 6.492094094093459e-07, 'epoch': 0.89}
+
89%|████████▉ | 10615/11952 [2:25:15<2:12:52, 5.96s/it]
89%|████████▉ | 10616/11952 [2:25:21<2:12:24, 5.95s/it]
{'loss': 0.4495, 'learning_rate': 6.482492562414621e-07, 'epoch': 0.89}
+
89%|████████▉ | 10616/11952 [2:25:21<2:12:24, 5.95s/it]
89%|████████▉ | 10617/11952 [2:25:27<2:12:17, 5.95s/it]
{'loss': 0.4724, 'learning_rate': 6.472897898272534e-07, 'epoch': 0.89}
+
89%|████████▉ | 10617/11952 [2:25:27<2:12:17, 5.95s/it]
89%|████████▉ | 10618/11952 [2:25:33<2:12:28, 5.96s/it]
{'loss': 0.4603, 'learning_rate': 6.463310102371834e-07, 'epoch': 0.89}
+
89%|████████▉ | 10618/11952 [2:25:33<2:12:28, 5.96s/it]
89%|████████▉ | 10619/11952 [2:25:39<2:12:34, 5.97s/it]
{'loss': 0.4423, 'learning_rate': 6.453729175416579e-07, 'epoch': 0.89}
+
89%|████████▉ | 10619/11952 [2:25:39<2:12:34, 5.97s/it]
89%|████████▉ | 10620/11952 [2:25:45<2:11:11, 5.91s/it]
{'loss': 0.4421, 'learning_rate': 6.444155118110373e-07, 'epoch': 0.89}
+
89%|████████▉ | 10620/11952 [2:25:45<2:11:11, 5.91s/it]
89%|████████▉ | 10621/11952 [2:25:51<2:10:35, 5.89s/it]
{'loss': 0.4656, 'learning_rate': 6.434587931156299e-07, 'epoch': 0.89}
+
89%|████████▉ | 10621/11952 [2:25:51<2:10:35, 5.89s/it]
89%|████████▉ | 10622/11952 [2:25:57<2:10:57, 5.91s/it]
{'loss': 0.4639, 'learning_rate': 6.425027615256907e-07, 'epoch': 0.89}
+
89%|████████▉ | 10622/11952 [2:25:57<2:10:57, 5.91s/it]
89%|████████▉ | 10623/11952 [2:26:03<2:11:08, 5.92s/it]
{'loss': 0.4575, 'learning_rate': 6.415474171114288e-07, 'epoch': 0.89}
+
89%|████████▉ | 10623/11952 [2:26:03<2:11:08, 5.92s/it]
89%|████████▉ | 10624/11952 [2:26:09<2:10:41, 5.90s/it]
{'loss': 0.4592, 'learning_rate': 6.405927599429995e-07, 'epoch': 0.89}
+
89%|████████▉ | 10624/11952 [2:26:09<2:10:41, 5.90s/it]
89%|████████▉ | 10625/11952 [2:26:15<2:11:31, 5.95s/it]
{'loss': 0.4616, 'learning_rate': 6.396387900905099e-07, 'epoch': 0.89}
+
89%|████████▉ | 10625/11952 [2:26:15<2:11:31, 5.95s/it]
89%|████████▉ | 10626/11952 [2:26:20<2:09:25, 5.86s/it]
{'loss': 0.4553, 'learning_rate': 6.386855076240117e-07, 'epoch': 0.89}
+
89%|████████▉ | 10626/11952 [2:26:20<2:09:25, 5.86s/it]
89%|████████▉ | 10627/11952 [2:26:26<2:09:01, 5.84s/it]
{'loss': 0.4603, 'learning_rate': 6.377329126135168e-07, 'epoch': 0.89}
+
89%|████████▉ | 10627/11952 [2:26:26<2:09:01, 5.84s/it]
89%|████████▉ | 10628/11952 [2:26:32<2:10:16, 5.90s/it]
{'loss': 0.4622, 'learning_rate': 6.367810051289746e-07, 'epoch': 0.89}
+
89%|████████▉ | 10628/11952 [2:26:32<2:10:16, 5.90s/it]
89%|████████▉ | 10629/11952 [2:26:38<2:11:33, 5.97s/it]
{'loss': 0.4787, 'learning_rate': 6.358297852402894e-07, 'epoch': 0.89}
+
89%|████████▉ | 10629/11952 [2:26:38<2:11:33, 5.97s/it]
89%|████████▉ | 10630/11952 [2:26:44<2:12:38, 6.02s/it]
{'loss': 0.4648, 'learning_rate': 6.348792530173187e-07, 'epoch': 0.89}
+
89%|████████▉ | 10630/11952 [2:26:44<2:12:38, 6.02s/it]
89%|████████▉ | 10631/11952 [2:26:50<2:11:05, 5.95s/it]
{'loss': 0.4586, 'learning_rate': 6.339294085298631e-07, 'epoch': 0.89}
+
89%|████████▉ | 10631/11952 [2:26:50<2:11:05, 5.95s/it]
89%|████████▉ | 10632/11952 [2:26:56<2:11:18, 5.97s/it]
{'loss': 0.464, 'learning_rate': 6.329802518476746e-07, 'epoch': 0.89}
+
89%|████████▉ | 10632/11952 [2:26:56<2:11:18, 5.97s/it]
89%|████████▉ | 10633/11952 [2:27:02<2:11:23, 5.98s/it]
{'loss': 0.4964, 'learning_rate': 6.320317830404554e-07, 'epoch': 0.89}
+
89%|████████▉ | 10633/11952 [2:27:02<2:11:23, 5.98s/it]
89%|████████▉ | 10634/11952 [2:27:08<2:10:40, 5.95s/it]
{'loss': 0.4679, 'learning_rate': 6.310840021778586e-07, 'epoch': 0.89}
+
89%|████████▉ | 10634/11952 [2:27:08<2:10:40, 5.95s/it]
89%|████████▉ | 10635/11952 [2:27:14<2:08:16, 5.84s/it]
{'loss': 0.4348, 'learning_rate': 6.30136909329484e-07, 'epoch': 0.89}
+
89%|████████▉ | 10635/11952 [2:27:14<2:08:16, 5.84s/it]
89%|████████▉ | 10636/11952 [2:27:19<2:07:57, 5.83s/it]
{'loss': 0.4809, 'learning_rate': 6.291905045648839e-07, 'epoch': 0.89}
+
89%|████████▉ | 10636/11952 [2:27:19<2:07:57, 5.83s/it]
89%|████████▉ | 10637/11952 [2:27:25<2:07:50, 5.83s/it]
{'loss': 0.4575, 'learning_rate': 6.282447879535558e-07, 'epoch': 0.89}
+
89%|████████▉ | 10637/11952 [2:27:25<2:07:50, 5.83s/it]
89%|████████▉ | 10638/11952 [2:27:31<2:07:47, 5.84s/it]
{'loss': 0.4739, 'learning_rate': 6.272997595649499e-07, 'epoch': 0.89}
+
89%|████████▉ | 10638/11952 [2:27:31<2:07:47, 5.84s/it]
89%|████████▉ | 10639/11952 [2:27:37<2:06:29, 5.78s/it]
{'loss': 0.4522, 'learning_rate': 6.263554194684662e-07, 'epoch': 0.89}
+
89%|████████▉ | 10639/11952 [2:27:37<2:06:29, 5.78s/it]
89%|████████▉ | 10640/11952 [2:27:43<2:06:12, 5.77s/it]
{'loss': 0.4417, 'learning_rate': 6.254117677334514e-07, 'epoch': 0.89}
+
89%|████████▉ | 10640/11952 [2:27:43<2:06:12, 5.77s/it]
89%|████████▉ | 10641/11952 [2:27:49<2:07:28, 5.83s/it]
{'loss': 0.4564, 'learning_rate': 6.244688044292058e-07, 'epoch': 0.89}
+
89%|████████▉ | 10641/11952 [2:27:49<2:07:28, 5.83s/it]
89%|████████▉ | 10642/11952 [2:27:55<2:10:27, 5.98s/it]
{'loss': 0.4505, 'learning_rate': 6.23526529624976e-07, 'epoch': 0.89}
+
89%|████████▉ | 10642/11952 [2:27:55<2:10:27, 5.98s/it]
89%|████████▉ | 10643/11952 [2:28:01<2:11:32, 6.03s/it]
{'loss': 0.4596, 'learning_rate': 6.225849433899578e-07, 'epoch': 0.89}
+
89%|████████▉ | 10643/11952 [2:28:01<2:11:32, 6.03s/it]
89%|████████▉ | 10644/11952 [2:28:07<2:10:07, 5.97s/it]
{'loss': 0.4338, 'learning_rate': 6.216440457932981e-07, 'epoch': 0.89}
+
89%|████████▉ | 10644/11952 [2:28:07<2:10:07, 5.97s/it]
89%|████████▉ | 10645/11952 [2:28:13<2:08:38, 5.91s/it]
{'loss': 0.4676, 'learning_rate': 6.207038369040918e-07, 'epoch': 0.89}
+
89%|████████▉ | 10645/11952 [2:28:13<2:08:38, 5.91s/it]
89%|████████▉ | 10646/11952 [2:28:18<2:08:06, 5.89s/it]
{'loss': 0.4753, 'learning_rate': 6.197643167913847e-07, 'epoch': 0.89}
+
89%|████████▉ | 10646/11952 [2:28:18<2:08:06, 5.89s/it]
89%|████████▉ | 10647/11952 [2:28:24<2:07:28, 5.86s/it]
{'loss': 0.4584, 'learning_rate': 6.188254855241693e-07, 'epoch': 0.89}
+
89%|████████▉ | 10647/11952 [2:28:24<2:07:28, 5.86s/it]
89%|████████▉ | 10648/11952 [2:28:30<2:07:14, 5.85s/it]
{'loss': 0.4765, 'learning_rate': 6.178873431713928e-07, 'epoch': 0.89}
+
89%|████████▉ | 10648/11952 [2:28:30<2:07:14, 5.85s/it]
89%|████████▉ | 10649/11952 [2:28:36<2:06:30, 5.83s/it]
{'loss': 0.4592, 'learning_rate': 6.169498898019443e-07, 'epoch': 0.89}
+
89%|████████▉ | 10649/11952 [2:28:36<2:06:30, 5.83s/it]01 AutoResumeHook: Checking whether to suspend...
+ 5 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
89%|████████▉ | 10650/11952 [2:28:42<2:05:42, 5.79s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4643, 'learning_rate': 6.160131254846702e-07, 'epoch': 0.89}
+
89%|████████▉ | 10650/11952 [2:28:42<2:05:42, 5.79s/it]
89%|████████▉ | 10651/11952 [2:28:47<2:05:16, 5.78s/it]
{'loss': 0.4684, 'learning_rate': 6.150770502883618e-07, 'epoch': 0.89}
+
89%|████████▉ | 10651/11952 [2:28:47<2:05:16, 5.78s/it]
89%|████████▉ | 10652/11952 [2:28:53<2:06:25, 5.84s/it]
{'loss': 0.4886, 'learning_rate': 6.141416642817599e-07, 'epoch': 0.89}
+
89%|████████▉ | 10652/11952 [2:28:53<2:06:25, 5.84s/it]
89%|████████▉ | 10653/11952 [2:28:59<2:05:48, 5.81s/it]
{'loss': 0.4641, 'learning_rate': 6.13206967533555e-07, 'epoch': 0.89}
+
89%|████████▉ | 10653/11952 [2:28:59<2:05:48, 5.81s/it]
89%|████████▉ | 10654/11952 [2:29:05<2:05:18, 5.79s/it]
{'loss': 0.4639, 'learning_rate': 6.122729601123878e-07, 'epoch': 0.89}
+
89%|████████▉ | 10654/11952 [2:29:05<2:05:18, 5.79s/it]
89%|████████▉ | 10655/11952 [2:29:11<2:07:08, 5.88s/it]
{'loss': 0.4511, 'learning_rate': 6.113396420868489e-07, 'epoch': 0.89}
+
89%|████████▉ | 10655/11952 [2:29:11<2:07:08, 5.88s/it]
89%|████████▉ | 10656/11952 [2:29:17<2:07:33, 5.91s/it]
{'loss': 0.4748, 'learning_rate': 6.104070135254758e-07, 'epoch': 0.89}
+
89%|████████▉ | 10656/11952 [2:29:17<2:07:33, 5.91s/it]
89%|████████▉ | 10657/11952 [2:29:23<2:09:44, 6.01s/it]
{'loss': 0.4607, 'learning_rate': 6.09475074496757e-07, 'epoch': 0.89}
+
89%|████████▉ | 10657/11952 [2:29:23<2:09:44, 6.01s/it]
89%|████████▉ | 10658/11952 [2:29:29<2:10:11, 6.04s/it]
{'loss': 0.4689, 'learning_rate': 6.085438250691311e-07, 'epoch': 0.89}
+
89%|████████▉ | 10658/11952 [2:29:29<2:10:11, 6.04s/it]
89%|████████▉ | 10659/11952 [2:29:35<2:08:09, 5.95s/it]
{'loss': 0.4497, 'learning_rate': 6.076132653109834e-07, 'epoch': 0.89}
+
89%|████████▉ | 10659/11952 [2:29:35<2:08:09, 5.95s/it]
89%|████████▉ | 10660/11952 [2:29:41<2:07:40, 5.93s/it]
{'loss': 0.4615, 'learning_rate': 6.066833952906515e-07, 'epoch': 0.89}
+
89%|████████▉ | 10660/11952 [2:29:41<2:07:40, 5.93s/it]
89%|████████▉ | 10661/11952 [2:29:47<2:09:17, 6.01s/it]
{'loss': 0.4654, 'learning_rate': 6.057542150764218e-07, 'epoch': 0.89}
+
89%|████████▉ | 10661/11952 [2:29:47<2:09:17, 6.01s/it]
89%|████████▉ | 10662/11952 [2:29:53<2:06:52, 5.90s/it]
{'loss': 0.4703, 'learning_rate': 6.048257247365297e-07, 'epoch': 0.89}
+
89%|████████▉ | 10662/11952 [2:29:53<2:06:52, 5.90s/it]
89%|████████▉ | 10663/11952 [2:29:59<2:09:00, 6.01s/it]
{'loss': 0.4581, 'learning_rate': 6.038979243391597e-07, 'epoch': 0.89}
+
89%|████████▉ | 10663/11952 [2:29:59<2:09:00, 6.01s/it]
89%|████████▉ | 10664/11952 [2:30:04<2:06:25, 5.89s/it]
{'loss': 0.4653, 'learning_rate': 6.029708139524438e-07, 'epoch': 0.89}
+
89%|████████▉ | 10664/11952 [2:30:04<2:06:25, 5.89s/it]
89%|████████▉ | 10665/11952 [2:30:10<2:06:38, 5.90s/it]
{'loss': 0.4835, 'learning_rate': 6.020443936444664e-07, 'epoch': 0.89}
+
89%|████████▉ | 10665/11952 [2:30:10<2:06:38, 5.90s/it]
89%|████████▉ | 10666/11952 [2:30:16<2:06:45, 5.91s/it]
{'loss': 0.4538, 'learning_rate': 6.0111866348326e-07, 'epoch': 0.89}
+
89%|████████▉ | 10666/11952 [2:30:16<2:06:45, 5.91s/it]
89%|████████▉ | 10667/11952 [2:30:22<2:07:25, 5.95s/it]
{'loss': 0.4771, 'learning_rate': 6.001936235368044e-07, 'epoch': 0.89}
+
89%|████████▉ | 10667/11952 [2:30:22<2:07:25, 5.95s/it]
89%|████████▉ | 10668/11952 [2:30:28<2:07:54, 5.98s/it]
{'loss': 0.4604, 'learning_rate': 5.992692738730332e-07, 'epoch': 0.89}
+
89%|████████▉ | 10668/11952 [2:30:28<2:07:54, 5.98s/it]
89%|████████▉ | 10669/11952 [2:30:34<2:06:06, 5.90s/it]
{'loss': 0.4592, 'learning_rate': 5.983456145598266e-07, 'epoch': 0.89}
+
89%|████████▉ | 10669/11952 [2:30:34<2:06:06, 5.90s/it]
89%|████████▉ | 10670/11952 [2:30:40<2:06:09, 5.90s/it]
{'loss': 0.4773, 'learning_rate': 5.974226456650123e-07, 'epoch': 0.89}
+
89%|████████▉ | 10670/11952 [2:30:40<2:06:09, 5.90s/it]
89%|████████▉ | 10671/11952 [2:30:46<2:04:51, 5.85s/it]
{'loss': 0.472, 'learning_rate': 5.965003672563719e-07, 'epoch': 0.89}
+
89%|████████▉ | 10671/11952 [2:30:46<2:04:51, 5.85s/it]
89%|████████▉ | 10672/11952 [2:30:52<2:04:31, 5.84s/it]
{'loss': 0.4521, 'learning_rate': 5.955787794016321e-07, 'epoch': 0.89}
+
89%|████████▉ | 10672/11952 [2:30:52<2:04:31, 5.84s/it]
89%|████████▉ | 10673/11952 [2:30:57<2:03:31, 5.79s/it]
{'loss': 0.4492, 'learning_rate': 5.946578821684713e-07, 'epoch': 0.89}
+
89%|████████▉ | 10673/11952 [2:30:57<2:03:31, 5.79s/it]
89%|████████▉ | 10674/11952 [2:31:03<2:05:06, 5.87s/it]
{'loss': 0.4726, 'learning_rate': 5.937376756245139e-07, 'epoch': 0.89}
+
89%|████████▉ | 10674/11952 [2:31:03<2:05:06, 5.87s/it]
89%|████████▉ | 10675/11952 [2:31:09<2:05:18, 5.89s/it]
{'loss': 0.4556, 'learning_rate': 5.928181598373395e-07, 'epoch': 0.89}
+
89%|████████▉ | 10675/11952 [2:31:09<2:05:18, 5.89s/it]
89%|████████▉ | 10676/11952 [2:31:15<2:02:51, 5.78s/it]
{'loss': 0.4523, 'learning_rate': 5.918993348744728e-07, 'epoch': 0.89}
+
89%|████████▉ | 10676/11952 [2:31:15<2:02:51, 5.78s/it]
89%|████████▉ | 10677/11952 [2:31:21<2:03:37, 5.82s/it]
{'loss': 0.461, 'learning_rate': 5.909812008033866e-07, 'epoch': 0.89}
+
89%|████████▉ | 10677/11952 [2:31:21<2:03:37, 5.82s/it]
89%|████████▉ | 10678/11952 [2:31:26<2:02:52, 5.79s/it]
{'loss': 0.4729, 'learning_rate': 5.900637576915069e-07, 'epoch': 0.89}
+
89%|████████▉ | 10678/11952 [2:31:26<2:02:52, 5.79s/it]
89%|████████▉ | 10679/11952 [2:31:32<2:02:04, 5.75s/it]
{'loss': 0.4656, 'learning_rate': 5.891470056062043e-07, 'epoch': 0.89}
+
89%|████████▉ | 10679/11952 [2:31:32<2:02:04, 5.75s/it]
89%|████████▉ | 10680/11952 [2:31:38<2:02:53, 5.80s/it]
{'loss': 0.4639, 'learning_rate': 5.882309446148038e-07, 'epoch': 0.89}
+
89%|████████▉ | 10680/11952 [2:31:38<2:02:53, 5.80s/it]
89%|████████▉ | 10681/11952 [2:31:44<2:03:40, 5.84s/it]
{'loss': 0.4651, 'learning_rate': 5.87315574784576e-07, 'epoch': 0.89}
+
89%|████████▉ | 10681/11952 [2:31:44<2:03:40, 5.84s/it]
89%|████████▉ | 10682/11952 [2:31:50<2:05:09, 5.91s/it]
{'loss': 0.4665, 'learning_rate': 5.864008961827428e-07, 'epoch': 0.89}
+
89%|████████▉ | 10682/11952 [2:31:50<2:05:09, 5.91s/it]
89%|████████▉ | 10683/11952 [2:31:56<2:02:57, 5.81s/it]
{'loss': 0.4629, 'learning_rate': 5.854869088764737e-07, 'epoch': 0.89}
+
89%|████████▉ | 10683/11952 [2:31:56<2:02:57, 5.81s/it]
89%|████████▉ | 10684/11952 [2:32:02<2:04:05, 5.87s/it]
{'loss': 0.4569, 'learning_rate': 5.845736129328883e-07, 'epoch': 0.89}
+
89%|████████▉ | 10684/11952 [2:32:02<2:04:05, 5.87s/it]
89%|████████▉ | 10685/11952 [2:32:07<2:03:03, 5.83s/it]
{'loss': 0.455, 'learning_rate': 5.836610084190541e-07, 'epoch': 0.89}
+
89%|████████▉ | 10685/11952 [2:32:07<2:03:03, 5.83s/it]
89%|████████▉ | 10686/11952 [2:32:13<2:02:26, 5.80s/it]
{'loss': 0.4809, 'learning_rate': 5.82749095401991e-07, 'epoch': 0.89}
+
89%|████████▉ | 10686/11952 [2:32:13<2:02:26, 5.80s/it]
89%|████████▉ | 10687/11952 [2:32:19<2:03:09, 5.84s/it]
{'loss': 0.4639, 'learning_rate': 5.81837873948663e-07, 'epoch': 0.89}
+
89%|████████▉ | 10687/11952 [2:32:19<2:03:09, 5.84s/it]
89%|████████▉ | 10688/11952 [2:32:25<2:02:23, 5.81s/it]
{'loss': 0.4451, 'learning_rate': 5.809273441259899e-07, 'epoch': 0.89}
+
89%|████████▉ | 10688/11952 [2:32:25<2:02:23, 5.81s/it]
89%|████████▉ | 10689/11952 [2:32:30<2:01:48, 5.79s/it]
{'loss': 0.4691, 'learning_rate': 5.800175060008362e-07, 'epoch': 0.89}
+
89%|████████▉ | 10689/11952 [2:32:30<2:01:48, 5.79s/it]
89%|████████▉ | 10690/11952 [2:32:36<2:01:49, 5.79s/it]
{'loss': 0.467, 'learning_rate': 5.791083596400148e-07, 'epoch': 0.89}
+
89%|████████▉ | 10690/11952 [2:32:36<2:01:49, 5.79s/it]
89%|████████▉ | 10691/11952 [2:32:42<2:04:07, 5.91s/it]
{'loss': 0.463, 'learning_rate': 5.781999051102927e-07, 'epoch': 0.89}
+
89%|████████▉ | 10691/11952 [2:32:42<2:04:07, 5.91s/it]
89%|████████▉ | 10692/11952 [2:32:48<2:04:46, 5.94s/it]
{'loss': 0.4638, 'learning_rate': 5.772921424783806e-07, 'epoch': 0.89}
+
89%|████████▉ | 10692/11952 [2:32:48<2:04:46, 5.94s/it]
89%|████████▉ | 10693/11952 [2:32:54<2:03:06, 5.87s/it]
{'loss': 0.475, 'learning_rate': 5.763850718109421e-07, 'epoch': 0.89}
+
89%|████████▉ | 10693/11952 [2:32:54<2:03:06, 5.87s/it]
89%|████████▉ | 10694/11952 [2:33:00<2:03:58, 5.91s/it]
{'loss': 0.4652, 'learning_rate': 5.754786931745859e-07, 'epoch': 0.89}
+
89%|████████▉ | 10694/11952 [2:33:00<2:03:58, 5.91s/it]
89%|████████▉ | 10695/11952 [2:33:06<2:01:40, 5.81s/it]
{'loss': 0.4622, 'learning_rate': 5.745730066358779e-07, 'epoch': 0.89}
+
89%|████████▉ | 10695/11952 [2:33:06<2:01:40, 5.81s/it]
89%|████████▉ | 10696/11952 [2:33:12<2:02:09, 5.84s/it]
{'loss': 0.4608, 'learning_rate': 5.736680122613237e-07, 'epoch': 0.89}
+
89%|████████▉ | 10696/11952 [2:33:12<2:02:09, 5.84s/it]
89%|████████▉ | 10697/11952 [2:33:17<2:02:07, 5.84s/it]
{'loss': 0.4586, 'learning_rate': 5.727637101173844e-07, 'epoch': 0.89}
+
89%|████████▉ | 10697/11952 [2:33:17<2:02:07, 5.84s/it]
90%|████████▉ | 10698/11952 [2:33:23<2:02:06, 5.84s/it]
{'loss': 0.442, 'learning_rate': 5.718601002704671e-07, 'epoch': 0.9}
+
90%|████████▉ | 10698/11952 [2:33:23<2:02:06, 5.84s/it]
90%|████████▉ | 10699/11952 [2:33:29<2:02:33, 5.87s/it]
{'loss': 0.4706, 'learning_rate': 5.709571827869287e-07, 'epoch': 0.9}
+
90%|████████▉ | 10699/11952 [2:33:29<2:02:33, 5.87s/it]4 AutoResumeHook: Checking whether to suspend...
+05 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
90%|████████▉ | 10700/11952 [2:33:36<2:05:11, 6.00s/it]1 76AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4871, 'learning_rate': 5.70054957733076e-07, 'epoch': 0.9}
+
90%|████████▉ | 10700/11952 [2:33:36<2:05:11, 6.00s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
90%|████████▉ | 10701/11952 [2:34:06<4:35:42, 13.22s/it]
{'loss': 0.4701, 'learning_rate': 5.691534251751652e-07, 'epoch': 0.9}
+
90%|████████▉ | 10701/11952 [2:34:06<4:35:42, 13.22s/it]
90%|████████▉ | 10702/11952 [2:34:11<3:48:12, 10.95s/it]
{'loss': 0.4756, 'learning_rate': 5.682525851794019e-07, 'epoch': 0.9}
+
90%|████████▉ | 10702/11952 [2:34:11<3:48:12, 10.95s/it]
90%|████████▉ | 10703/11952 [2:34:17<3:16:37, 9.45s/it]
{'loss': 0.4662, 'learning_rate': 5.673524378119388e-07, 'epoch': 0.9}
+
90%|████████▉ | 10703/11952 [2:34:17<3:16:37, 9.45s/it]
90%|████████▉ | 10704/11952 [2:34:23<2:53:47, 8.36s/it]
{'loss': 0.4683, 'learning_rate': 5.664529831388799e-07, 'epoch': 0.9}
+
90%|████████▉ | 10704/11952 [2:34:23<2:53:47, 8.36s/it]
90%|████████▉ | 10705/11952 [2:34:29<2:37:09, 7.56s/it]
{'loss': 0.4452, 'learning_rate': 5.655542212262766e-07, 'epoch': 0.9}
+
90%|████████▉ | 10705/11952 [2:34:29<2:37:09, 7.56s/it]
90%|████████▉ | 10706/11952 [2:34:35<2:28:45, 7.16s/it]
{'loss': 0.4809, 'learning_rate': 5.646561521401317e-07, 'epoch': 0.9}
+
90%|████████▉ | 10706/11952 [2:34:35<2:28:45, 7.16s/it]
90%|████████▉ | 10707/11952 [2:34:41<2:21:21, 6.81s/it]
{'loss': 0.4604, 'learning_rate': 5.637587759463925e-07, 'epoch': 0.9}
+
90%|████████▉ | 10707/11952 [2:34:41<2:21:21, 6.81s/it]
90%|████████▉ | 10708/11952 [2:34:47<2:15:35, 6.54s/it]
{'loss': 0.4794, 'learning_rate': 5.628620927109607e-07, 'epoch': 0.9}
+
90%|████████▉ | 10708/11952 [2:34:47<2:15:35, 6.54s/it]
90%|████████▉ | 10709/11952 [2:34:53<2:10:15, 6.29s/it]
{'loss': 0.4603, 'learning_rate': 5.619661024996848e-07, 'epoch': 0.9}
+
90%|████████▉ | 10709/11952 [2:34:53<2:10:15, 6.29s/it]
90%|████████▉ | 10710/11952 [2:34:59<2:08:17, 6.20s/it]
{'loss': 0.4669, 'learning_rate': 5.610708053783642e-07, 'epoch': 0.9}
+
90%|████████▉ | 10710/11952 [2:34:59<2:08:17, 6.20s/it]
90%|████████▉ | 10711/11952 [2:35:04<2:05:47, 6.08s/it]
{'loss': 0.471, 'learning_rate': 5.60176201412741e-07, 'epoch': 0.9}
+
90%|████████▉ | 10711/11952 [2:35:04<2:05:47, 6.08s/it]
90%|████████▉ | 10712/11952 [2:35:10<2:04:44, 6.04s/it]
{'loss': 0.4629, 'learning_rate': 5.59282290668517e-07, 'epoch': 0.9}
+
90%|████████▉ | 10712/11952 [2:35:10<2:04:44, 6.04s/it]
90%|████████▉ | 10713/11952 [2:35:16<2:02:23, 5.93s/it]
{'loss': 0.4513, 'learning_rate': 5.58389073211335e-07, 'epoch': 0.9}
+
90%|████████▉ | 10713/11952 [2:35:16<2:02:23, 5.93s/it]
90%|████████▉ | 10714/11952 [2:35:22<2:02:03, 5.92s/it]
{'loss': 0.5152, 'learning_rate': 5.574965491067874e-07, 'epoch': 0.9}
+
90%|████████▉ | 10714/11952 [2:35:22<2:02:03, 5.92s/it]
90%|████████▉ | 10715/11952 [2:35:28<2:01:24, 5.89s/it]
{'loss': 0.4614, 'learning_rate': 5.566047184204182e-07, 'epoch': 0.9}
+
90%|████████▉ | 10715/11952 [2:35:28<2:01:24, 5.89s/it]
90%|████████▉ | 10716/11952 [2:35:34<2:01:23, 5.89s/it]
{'loss': 0.4401, 'learning_rate': 5.557135812177228e-07, 'epoch': 0.9}
+
90%|████████▉ | 10716/11952 [2:35:34<2:01:23, 5.89s/it]
90%|████████▉ | 10717/11952 [2:35:39<2:01:08, 5.89s/it]
{'loss': 0.4655, 'learning_rate': 5.548231375641389e-07, 'epoch': 0.9}
+
90%|████████▉ | 10717/11952 [2:35:39<2:01:08, 5.89s/it]
90%|████████▉ | 10718/11952 [2:35:46<2:02:24, 5.95s/it]
{'loss': 0.4761, 'learning_rate': 5.539333875250596e-07, 'epoch': 0.9}
+
90%|████████▉ | 10718/11952 [2:35:46<2:02:24, 5.95s/it]
90%|████████▉ | 10719/11952 [2:35:52<2:02:38, 5.97s/it]
{'loss': 0.4628, 'learning_rate': 5.530443311658218e-07, 'epoch': 0.9}
+
90%|████████▉ | 10719/11952 [2:35:52<2:02:38, 5.97s/it]
90%|████████▉ | 10720/11952 [2:35:58<2:02:22, 5.96s/it]
{'loss': 0.4645, 'learning_rate': 5.521559685517153e-07, 'epoch': 0.9}
+
90%|████████▉ | 10720/11952 [2:35:58<2:02:22, 5.96s/it]
90%|████████▉ | 10721/11952 [2:36:03<2:01:37, 5.93s/it]
{'loss': 0.4947, 'learning_rate': 5.51268299747978e-07, 'epoch': 0.9}
+
90%|████████▉ | 10721/11952 [2:36:03<2:01:37, 5.93s/it]
90%|████████▉ | 10722/11952 [2:36:09<1:59:37, 5.84s/it]
{'loss': 0.4574, 'learning_rate': 5.503813248197965e-07, 'epoch': 0.9}
+
90%|████████▉ | 10722/11952 [2:36:09<1:59:37, 5.84s/it]
90%|████████▉ | 10723/11952 [2:36:15<1:58:55, 5.81s/it]
{'loss': 0.4685, 'learning_rate': 5.494950438323077e-07, 'epoch': 0.9}
+
90%|████████▉ | 10723/11952 [2:36:15<1:58:55, 5.81s/it]
90%|████████▉ | 10724/11952 [2:36:21<2:00:34, 5.89s/it]
{'loss': 0.4751, 'learning_rate': 5.48609456850594e-07, 'epoch': 0.9}
+
90%|████████▉ | 10724/11952 [2:36:21<2:00:34, 5.89s/it]
90%|████████▉ | 10725/11952 [2:36:26<1:58:29, 5.79s/it]
{'loss': 0.4682, 'learning_rate': 5.477245639396922e-07, 'epoch': 0.9}
+
90%|████████▉ | 10725/11952 [2:36:26<1:58:29, 5.79s/it]
90%|████████▉ | 10726/11952 [2:36:32<1:58:14, 5.79s/it]
{'loss': 0.4474, 'learning_rate': 5.468403651645826e-07, 'epoch': 0.9}
+
90%|████████▉ | 10726/11952 [2:36:32<1:58:14, 5.79s/it]
90%|████████▉ | 10727/11952 [2:36:38<1:59:56, 5.87s/it]
{'loss': 0.4704, 'learning_rate': 5.459568605901977e-07, 'epoch': 0.9}
+
90%|████████▉ | 10727/11952 [2:36:38<1:59:56, 5.87s/it]
90%|████████▉ | 10728/11952 [2:36:44<2:00:14, 5.89s/it]
{'loss': 0.4847, 'learning_rate': 5.450740502814178e-07, 'epoch': 0.9}
+
90%|████████▉ | 10728/11952 [2:36:44<2:00:14, 5.89s/it]
90%|████████▉ | 10729/11952 [2:36:50<2:00:52, 5.93s/it]
{'loss': 0.4695, 'learning_rate': 5.441919343030744e-07, 'epoch': 0.9}
+
90%|████████▉ | 10729/11952 [2:36:50<2:00:52, 5.93s/it]
90%|████████▉ | 10730/11952 [2:36:56<2:02:35, 6.02s/it]
{'loss': 0.4646, 'learning_rate': 5.433105127199467e-07, 'epoch': 0.9}
+
90%|████████▉ | 10730/11952 [2:36:56<2:02:35, 6.02s/it]
90%|████████▉ | 10731/11952 [2:37:02<2:01:56, 5.99s/it]
{'loss': 0.4771, 'learning_rate': 5.424297855967597e-07, 'epoch': 0.9}
+
90%|████████▉ | 10731/11952 [2:37:02<2:01:56, 5.99s/it]
90%|████████▉ | 10732/11952 [2:37:08<2:02:44, 6.04s/it]
{'loss': 0.4748, 'learning_rate': 5.415497529981928e-07, 'epoch': 0.9}
+
90%|████████▉ | 10732/11952 [2:37:08<2:02:44, 6.04s/it]
90%|████████▉ | 10733/11952 [2:37:14<2:00:53, 5.95s/it]
{'loss': 0.4688, 'learning_rate': 5.40670414988872e-07, 'epoch': 0.9}
+
90%|████████▉ | 10733/11952 [2:37:14<2:00:53, 5.95s/it]
90%|████████▉ | 10734/11952 [2:37:20<1:59:54, 5.91s/it]
{'loss': 0.4381, 'learning_rate': 5.397917716333723e-07, 'epoch': 0.9}
+
90%|████████▉ | 10734/11952 [2:37:20<1:59:54, 5.91s/it]
90%|████████▉ | 10735/11952 [2:37:26<1:58:58, 5.87s/it]
{'loss': 0.4684, 'learning_rate': 5.389138229962155e-07, 'epoch': 0.9}
+
90%|████████▉ | 10735/11952 [2:37:26<1:58:58, 5.87s/it]
90%|████████▉ | 10736/11952 [2:37:32<1:59:19, 5.89s/it]
{'loss': 0.4519, 'learning_rate': 5.380365691418765e-07, 'epoch': 0.9}
+
90%|████████▉ | 10736/11952 [2:37:32<1:59:19, 5.89s/it]
90%|████████▉ | 10737/11952 [2:37:37<1:58:09, 5.83s/it]
{'loss': 0.4714, 'learning_rate': 5.371600101347763e-07, 'epoch': 0.9}
+
90%|████████▉ | 10737/11952 [2:37:37<1:58:09, 5.83s/it]
90%|████████▉ | 10738/11952 [2:37:43<1:57:50, 5.82s/it]
{'loss': 0.4653, 'learning_rate': 5.362841460392875e-07, 'epoch': 0.9}
+
90%|████████▉ | 10738/11952 [2:37:43<1:57:50, 5.82s/it]
90%|████████▉ | 10739/11952 [2:37:49<1:58:15, 5.85s/it]
{'loss': 0.4803, 'learning_rate': 5.354089769197268e-07, 'epoch': 0.9}
+
90%|████████▉ | 10739/11952 [2:37:49<1:58:15, 5.85s/it]
90%|████████▉ | 10740/11952 [2:37:55<1:56:20, 5.76s/it]
{'loss': 0.4518, 'learning_rate': 5.345345028403659e-07, 'epoch': 0.9}
+
90%|████████▉ | 10740/11952 [2:37:55<1:56:20, 5.76s/it]
90%|████████▉ | 10741/11952 [2:38:01<1:56:42, 5.78s/it]
{'loss': 0.4649, 'learning_rate': 5.33660723865419e-07, 'epoch': 0.9}
+
90%|████████▉ | 10741/11952 [2:38:01<1:56:42, 5.78s/it]
90%|████████▉ | 10742/11952 [2:38:06<1:56:19, 5.77s/it]
{'loss': 0.461, 'learning_rate': 5.32787640059057e-07, 'epoch': 0.9}
+
90%|████████▉ | 10742/11952 [2:38:06<1:56:19, 5.77s/it]
90%|████████▉ | 10743/11952 [2:38:13<1:59:25, 5.93s/it]
{'loss': 0.4962, 'learning_rate': 5.31915251485392e-07, 'epoch': 0.9}
+
90%|████████▉ | 10743/11952 [2:38:13<1:59:25, 5.93s/it]
90%|████████▉ | 10744/11952 [2:38:19<2:01:21, 6.03s/it]
{'loss': 0.4649, 'learning_rate': 5.310435582084917e-07, 'epoch': 0.9}
+
90%|████████▉ | 10744/11952 [2:38:19<2:01:21, 6.03s/it]
90%|████████▉ | 10745/11952 [2:38:25<2:00:26, 5.99s/it]
{'loss': 0.4624, 'learning_rate': 5.301725602923691e-07, 'epoch': 0.9}
+
90%|████████▉ | 10745/11952 [2:38:25<2:00:26, 5.99s/it]
90%|████████▉ | 10746/11952 [2:38:31<2:00:00, 5.97s/it]
{'loss': 0.467, 'learning_rate': 5.293022578009843e-07, 'epoch': 0.9}
+
90%|████████▉ | 10746/11952 [2:38:31<2:00:00, 5.97s/it]
90%|████████▉ | 10747/11952 [2:38:36<1:57:52, 5.87s/it]
{'loss': 0.4678, 'learning_rate': 5.284326507982507e-07, 'epoch': 0.9}
+
90%|████████▉ | 10747/11952 [2:38:36<1:57:52, 5.87s/it]
90%|████████▉ | 10748/11952 [2:38:42<1:57:34, 5.86s/it]
{'loss': 0.4608, 'learning_rate': 5.275637393480282e-07, 'epoch': 0.9}
+
90%|████████▉ | 10748/11952 [2:38:42<1:57:34, 5.86s/it]
90%|████████▉ | 10749/11952 [2:38:48<1:57:42, 5.87s/it]
{'loss': 0.4783, 'learning_rate': 5.266955235141235e-07, 'epoch': 0.9}
+
90%|████████▉ | 10749/11952 [2:38:48<1:57:42, 5.87s/it]07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
90%|████████▉ | 10750/11952 [2:38:54<1:55:47, 5.78s/it]4 AutoResumeHook: Checking whether to suspend...
+25 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4863, 'learning_rate': 5.258280033602992e-07, 'epoch': 0.9}
+
90%|████████▉ | 10750/11952 [2:38:54<1:55:47, 5.78s/it]
90%|████████▉ | 10751/11952 [2:38:59<1:55:46, 5.78s/it]
{'loss': 0.4491, 'learning_rate': 5.249611789502607e-07, 'epoch': 0.9}
+
90%|████████▉ | 10751/11952 [2:38:59<1:55:46, 5.78s/it]
90%|████████▉ | 10752/11952 [2:39:06<1:58:56, 5.95s/it]
{'loss': 0.4695, 'learning_rate': 5.240950503476616e-07, 'epoch': 0.9}
+
90%|████████▉ | 10752/11952 [2:39:06<1:58:56, 5.95s/it]
90%|████████▉ | 10753/11952 [2:39:12<2:00:04, 6.01s/it]
{'loss': 0.4812, 'learning_rate': 5.232296176161101e-07, 'epoch': 0.9}
+
90%|████████▉ | 10753/11952 [2:39:12<2:00:04, 6.01s/it]
90%|████████▉ | 10754/11952 [2:39:18<1:59:17, 5.97s/it]
{'loss': 0.4459, 'learning_rate': 5.223648808191584e-07, 'epoch': 0.9}
+
90%|████████▉ | 10754/11952 [2:39:18<1:59:17, 5.97s/it]
90%|████████▉ | 10755/11952 [2:39:24<2:00:24, 6.04s/it]
{'loss': 0.4771, 'learning_rate': 5.215008400203103e-07, 'epoch': 0.9}
+
90%|████████▉ | 10755/11952 [2:39:24<2:00:24, 6.04s/it]
90%|████████▉ | 10756/11952 [2:39:30<2:01:21, 6.09s/it]
{'loss': 0.4675, 'learning_rate': 5.20637495283014e-07, 'epoch': 0.9}
+
90%|████████▉ | 10756/11952 [2:39:30<2:01:21, 6.09s/it]
90%|█████████ | 10757/11952 [2:39:36<2:00:00, 6.03s/it]
{'loss': 0.4509, 'learning_rate': 5.197748466706742e-07, 'epoch': 0.9}
+
90%|█████████ | 10757/11952 [2:39:36<2:00:00, 6.03s/it]
90%|█████████ | 10758/11952 [2:39:42<1:57:23, 5.90s/it]
{'loss': 0.4566, 'learning_rate': 5.189128942466393e-07, 'epoch': 0.9}
+
90%|█████████ | 10758/11952 [2:39:42<1:57:23, 5.90s/it]
90%|█████████ | 10759/11952 [2:39:47<1:56:49, 5.88s/it]
{'loss': 0.4632, 'learning_rate': 5.180516380742051e-07, 'epoch': 0.9}
+
90%|█████████ | 10759/11952 [2:39:47<1:56:49, 5.88s/it]
90%|█████████ | 10760/11952 [2:39:53<1:56:15, 5.85s/it]
{'loss': 0.4563, 'learning_rate': 5.171910782166212e-07, 'epoch': 0.9}
+
90%|█████████ | 10760/11952 [2:39:53<1:56:15, 5.85s/it]
90%|█████████ | 10761/11952 [2:39:59<1:57:19, 5.91s/it]
{'loss': 0.4507, 'learning_rate': 5.163312147370824e-07, 'epoch': 0.9}
+
90%|█████████ | 10761/11952 [2:39:59<1:57:19, 5.91s/it]
90%|█████████ | 10762/11952 [2:40:05<1:56:39, 5.88s/it]
{'loss': 0.4547, 'learning_rate': 5.154720476987329e-07, 'epoch': 0.9}
+
90%|█████████ | 10762/11952 [2:40:05<1:56:39, 5.88s/it]
90%|█████████ | 10763/11952 [2:40:11<1:56:57, 5.90s/it]
{'loss': 0.4596, 'learning_rate': 5.146135771646655e-07, 'epoch': 0.9}
+
90%|█████████ | 10763/11952 [2:40:11<1:56:57, 5.90s/it]
90%|█████████ | 10764/11952 [2:40:17<1:57:53, 5.95s/it]
{'loss': 0.4456, 'learning_rate': 5.137558031979273e-07, 'epoch': 0.9}
+
90%|█████████ | 10764/11952 [2:40:17<1:57:53, 5.95s/it]
90%|█████████ | 10765/11952 [2:40:23<1:56:23, 5.88s/it]
{'loss': 0.4591, 'learning_rate': 5.128987258615059e-07, 'epoch': 0.9}
+
90%|█████████ | 10765/11952 [2:40:23<1:56:23, 5.88s/it]
90%|█████████ | 10766/11952 [2:40:29<1:56:49, 5.91s/it]
{'loss': 0.4841, 'learning_rate': 5.12042345218342e-07, 'epoch': 0.9}
+
90%|█████████ | 10766/11952 [2:40:29<1:56:49, 5.91s/it]
90%|█████████ | 10767/11952 [2:40:34<1:55:12, 5.83s/it]
{'loss': 0.4637, 'learning_rate': 5.111866613313255e-07, 'epoch': 0.9}
+
90%|█████████ | 10767/11952 [2:40:34<1:55:12, 5.83s/it]
90%|█████████ | 10768/11952 [2:40:41<1:56:53, 5.92s/it]
{'loss': 0.4692, 'learning_rate': 5.103316742632935e-07, 'epoch': 0.9}
+
90%|█████████ | 10768/11952 [2:40:41<1:56:53, 5.92s/it]
90%|█████████ | 10769/11952 [2:40:47<1:58:03, 5.99s/it]
{'loss': 0.4977, 'learning_rate': 5.094773840770306e-07, 'epoch': 0.9}
+
90%|█████████ | 10769/11952 [2:40:47<1:58:03, 5.99s/it]
90%|█████████ | 10770/11952 [2:40:53<1:57:59, 5.99s/it]
{'loss': 0.4727, 'learning_rate': 5.086237908352776e-07, 'epoch': 0.9}
+
90%|█████████ | 10770/11952 [2:40:53<1:57:59, 5.99s/it]
90%|█████████ | 10771/11952 [2:40:58<1:56:05, 5.90s/it]
{'loss': 0.4818, 'learning_rate': 5.077708946007143e-07, 'epoch': 0.9}
+
90%|█████████ | 10771/11952 [2:40:58<1:56:05, 5.90s/it]
90%|█████████ | 10772/11952 [2:41:04<1:54:50, 5.84s/it]
{'loss': 0.4501, 'learning_rate': 5.069186954359761e-07, 'epoch': 0.9}
+
90%|█████████ | 10772/11952 [2:41:04<1:54:50, 5.84s/it]
90%|█████████ | 10773/11952 [2:41:10<1:55:48, 5.89s/it]
{'loss': 0.4501, 'learning_rate': 5.060671934036421e-07, 'epoch': 0.9}
+
90%|█████████ | 10773/11952 [2:41:10<1:55:48, 5.89s/it]
90%|█████████ | 10774/11952 [2:41:16<1:54:54, 5.85s/it]
{'loss': 0.4629, 'learning_rate': 5.052163885662476e-07, 'epoch': 0.9}
+
90%|█████████ | 10774/11952 [2:41:16<1:54:54, 5.85s/it]
90%|█████████ | 10775/11952 [2:41:22<1:55:21, 5.88s/it]
{'loss': 0.4542, 'learning_rate': 5.043662809862692e-07, 'epoch': 0.9}
+
90%|█████████ | 10775/11952 [2:41:22<1:55:21, 5.88s/it]
90%|█████████ | 10776/11952 [2:41:28<1:54:20, 5.83s/it]
{'loss': 0.4559, 'learning_rate': 5.03516870726134e-07, 'epoch': 0.9}
+
90%|█████████ | 10776/11952 [2:41:28<1:54:20, 5.83s/it]
90%|█████████ | 10777/11952 [2:41:34<1:56:12, 5.93s/it]
{'loss': 0.4821, 'learning_rate': 5.026681578482229e-07, 'epoch': 0.9}
+
90%|█████████ | 10777/11952 [2:41:34<1:56:12, 5.93s/it]
90%|█████████ | 10778/11952 [2:41:40<1:55:29, 5.90s/it]
{'loss': 0.4764, 'learning_rate': 5.018201424148606e-07, 'epoch': 0.9}
+
90%|█████████ | 10778/11952 [2:41:40<1:55:29, 5.90s/it]
90%|█████████ | 10779/11952 [2:41:46<1:57:10, 5.99s/it]
{'loss': 0.4775, 'learning_rate': 5.009728244883205e-07, 'epoch': 0.9}
+
90%|█████████ | 10779/11952 [2:41:46<1:57:10, 5.99s/it]
90%|█████████ | 10780/11952 [2:41:52<1:57:15, 6.00s/it]
{'loss': 0.4691, 'learning_rate': 5.001262041308263e-07, 'epoch': 0.9}
+
90%|█████████ | 10780/11952 [2:41:52<1:57:15, 6.00s/it]
90%|█████████ | 10781/11952 [2:41:58<1:56:12, 5.95s/it]
{'loss': 0.4439, 'learning_rate': 4.992802814045505e-07, 'epoch': 0.9}
+
90%|█████████ | 10781/11952 [2:41:58<1:56:12, 5.95s/it]
90%|█████████ | 10782/11952 [2:42:04<1:56:47, 5.99s/it]
{'loss': 0.4732, 'learning_rate': 4.984350563716145e-07, 'epoch': 0.9}
+
90%|█████████ | 10782/11952 [2:42:04<1:56:47, 5.99s/it]
90%|█████████ | 10783/11952 [2:42:10<1:56:13, 5.97s/it]
{'loss': 0.4788, 'learning_rate': 4.975905290940874e-07, 'epoch': 0.9}
+
90%|█████████ | 10783/11952 [2:42:10<1:56:13, 5.97s/it]
90%|█████████ | 10784/11952 [2:42:16<1:56:43, 6.00s/it]
{'loss': 0.471, 'learning_rate': 4.967466996339887e-07, 'epoch': 0.9}
+
90%|█████████ | 10784/11952 [2:42:16<1:56:43, 6.00s/it]
90%|█████████ | 10785/11952 [2:42:22<1:57:43, 6.05s/it]
{'loss': 0.4454, 'learning_rate': 4.959035680532854e-07, 'epoch': 0.9}
+
90%|█████████ | 10785/11952 [2:42:22<1:57:43, 6.05s/it]
90%|█████████ | 10786/11952 [2:42:28<1:56:36, 6.00s/it]
{'loss': 0.4511, 'learning_rate': 4.950611344138945e-07, 'epoch': 0.9}
+
90%|█████████ | 10786/11952 [2:42:28<1:56:36, 6.00s/it]
90%|█████████ | 10787/11952 [2:42:34<1:55:58, 5.97s/it]
{'loss': 0.4767, 'learning_rate': 4.9421939877768e-07, 'epoch': 0.9}
+
90%|█████████ | 10787/11952 [2:42:34<1:55:58, 5.97s/it]
90%|█████████ | 10788/11952 [2:42:39<1:53:38, 5.86s/it]
{'loss': 0.4464, 'learning_rate': 4.933783612064546e-07, 'epoch': 0.9}
+
90%|█████████ | 10788/11952 [2:42:39<1:53:38, 5.86s/it]
90%|█████████ | 10789/11952 [2:42:45<1:53:39, 5.86s/it]
{'loss': 0.4537, 'learning_rate': 4.925380217619813e-07, 'epoch': 0.9}
+
90%|█████████ | 10789/11952 [2:42:45<1:53:39, 5.86s/it]
90%|█████████ | 10790/11952 [2:42:51<1:55:44, 5.98s/it]
{'loss': 0.4717, 'learning_rate': 4.916983805059705e-07, 'epoch': 0.9}
+
90%|█████████ | 10790/11952 [2:42:51<1:55:44, 5.98s/it]
90%|█████████ | 10791/11952 [2:42:57<1:55:20, 5.96s/it]
{'loss': 0.4549, 'learning_rate': 4.90859437500083e-07, 'epoch': 0.9}
+
90%|█████████ | 10791/11952 [2:42:57<1:55:20, 5.96s/it]
90%|█████████ | 10792/11952 [2:43:03<1:56:09, 6.01s/it]
{'loss': 0.4547, 'learning_rate': 4.900211928059284e-07, 'epoch': 0.9}
+
90%|█████████ | 10792/11952 [2:43:03<1:56:09, 6.01s/it]
90%|█████████ | 10793/11952 [2:43:09<1:54:30, 5.93s/it]
{'loss': 0.4571, 'learning_rate': 4.891836464850596e-07, 'epoch': 0.9}
+
90%|█████████ | 10793/11952 [2:43:09<1:54:30, 5.93s/it]
90%|█████████ | 10794/11952 [2:43:15<1:52:39, 5.84s/it]
{'loss': 0.4762, 'learning_rate': 4.883467985989876e-07, 'epoch': 0.9}
+
90%|█████████ | 10794/11952 [2:43:15<1:52:39, 5.84s/it]
90%|█████████ | 10795/11952 [2:43:21<1:53:47, 5.90s/it]
{'loss': 0.4692, 'learning_rate': 4.875106492091642e-07, 'epoch': 0.9}
+
90%|█████████ | 10795/11952 [2:43:21<1:53:47, 5.90s/it]
90%|█████████ | 10796/11952 [2:43:27<1:53:11, 5.88s/it]
{'loss': 0.4702, 'learning_rate': 4.866751983769935e-07, 'epoch': 0.9}
+
90%|█████████ | 10796/11952 [2:43:27<1:53:11, 5.88s/it]
90%|█████████ | 10797/11952 [2:43:33<1:53:23, 5.89s/it]
{'loss': 0.4569, 'learning_rate': 4.858404461638266e-07, 'epoch': 0.9}
+
90%|█████████ | 10797/11952 [2:43:33<1:53:23, 5.89s/it]
90%|█████████ | 10798/11952 [2:43:39<1:53:47, 5.92s/it]
{'loss': 0.4488, 'learning_rate': 4.850063926309657e-07, 'epoch': 0.9}
+
90%|█████████ | 10798/11952 [2:43:39<1:53:47, 5.92s/it]
90%|█████████ | 10799/11952 [2:43:44<1:53:07, 5.89s/it]
{'loss': 0.4586, 'learning_rate': 4.841730378396592e-07, 'epoch': 0.9}
+
90%|█████████ | 10799/11952 [2:43:44<1:53:07, 5.89s/it]03 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
90%|█████████ | 10800/11952 [2:43:50<1:52:01, 5.83s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4559, 'learning_rate': 4.833403818511062e-07, 'epoch': 0.9}
+
90%|█████████ | 10800/11952 [2:43:50<1:52:01, 5.83s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
90%|█████████ | 10801/11952 [2:44:28<4:54:16, 15.34s/it]
{'loss': 0.4566, 'learning_rate': 4.825084247264522e-07, 'epoch': 0.9}
+
90%|█████████ | 10801/11952 [2:44:28<4:54:16, 15.34s/it]
90%|█████████ | 10802/11952 [2:44:33<3:58:15, 12.43s/it]
{'loss': 0.4449, 'learning_rate': 4.816771665267939e-07, 'epoch': 0.9}
+
90%|█████████ | 10802/11952 [2:44:33<3:58:15, 12.43s/it]
90%|█████████ | 10803/11952 [2:44:39<3:19:39, 10.43s/it]
{'loss': 0.4585, 'learning_rate': 4.808466073131735e-07, 'epoch': 0.9}
+
90%|█████████ | 10803/11952 [2:44:39<3:19:39, 10.43s/it]
90%|█████████ | 10804/11952 [2:44:45<2:53:24, 9.06s/it]
{'loss': 0.4537, 'learning_rate': 4.800167471465844e-07, 'epoch': 0.9}
+
90%|█████████ | 10804/11952 [2:44:45<2:53:24, 9.06s/it]
90%|█████████ | 10805/11952 [2:44:50<2:33:19, 8.02s/it]
{'loss': 0.4585, 'learning_rate': 4.791875860879703e-07, 'epoch': 0.9}
+
90%|█████████ | 10805/11952 [2:44:50<2:33:19, 8.02s/it]
90%|█████████ | 10806/11952 [2:44:57<2:22:33, 7.46s/it]
{'loss': 0.4525, 'learning_rate': 4.783591241982199e-07, 'epoch': 0.9}
+
90%|█████████ | 10806/11952 [2:44:57<2:22:33, 7.46s/it]
90%|█████████ | 10807/11952 [2:45:03<2:14:30, 7.05s/it]
{'loss': 0.4708, 'learning_rate': 4.775313615381716e-07, 'epoch': 0.9}
+
90%|█████████ | 10807/11952 [2:45:03<2:14:30, 7.05s/it]
90%|█████████ | 10808/11952 [2:45:08<2:07:02, 6.66s/it]
{'loss': 0.4424, 'learning_rate': 4.767042981686143e-07, 'epoch': 0.9}
+
90%|█████████ | 10808/11952 [2:45:08<2:07:02, 6.66s/it]
90%|█████████ | 10809/11952 [2:45:14<2:01:32, 6.38s/it]
{'loss': 0.47, 'learning_rate': 4.758779341502817e-07, 'epoch': 0.9}
+
90%|█████████ | 10809/11952 [2:45:14<2:01:32, 6.38s/it]
90%|█████████ | 10810/11952 [2:45:20<1:59:06, 6.26s/it]
{'loss': 0.453, 'learning_rate': 4.750522695438597e-07, 'epoch': 0.9}
+
90%|█████████ | 10810/11952 [2:45:20<1:59:06, 6.26s/it]
90%|█████████ | 10811/11952 [2:45:26<1:56:13, 6.11s/it]
{'loss': 0.4558, 'learning_rate': 4.742273044099821e-07, 'epoch': 0.9}
+
90%|█████████ | 10811/11952 [2:45:26<1:56:13, 6.11s/it]
90%|█████████ | 10812/11952 [2:45:32<1:54:37, 6.03s/it]
{'loss': 0.4708, 'learning_rate': 4.7340303880923145e-07, 'epoch': 0.9}
+
90%|█████████ | 10812/11952 [2:45:32<1:54:37, 6.03s/it]
90%|█████████ | 10813/11952 [2:45:38<1:54:41, 6.04s/it]
{'loss': 0.4453, 'learning_rate': 4.7257947280213713e-07, 'epoch': 0.9}
+
90%|█████████ | 10813/11952 [2:45:38<1:54:41, 6.04s/it]
90%|█████████ | 10814/11952 [2:45:44<1:54:15, 6.02s/it]
{'loss': 0.4709, 'learning_rate': 4.7175660644917745e-07, 'epoch': 0.9}
+
90%|█████████ | 10814/11952 [2:45:44<1:54:15, 6.02s/it]
90%|█████████ | 10815/11952 [2:45:50<1:54:31, 6.04s/it]
{'loss': 0.4792, 'learning_rate': 4.709344398107829e-07, 'epoch': 0.9}
+
90%|█████████ | 10815/11952 [2:45:50<1:54:31, 6.04s/it]
90%|█████████ | 10816/11952 [2:45:56<1:53:33, 6.00s/it]
{'loss': 0.4693, 'learning_rate': 4.701129729473286e-07, 'epoch': 0.9}
+
90%|█████████ | 10816/11952 [2:45:56<1:53:33, 6.00s/it]
91%|█████████ | 10817/11952 [2:46:02<1:55:22, 6.10s/it]
{'loss': 0.4548, 'learning_rate': 4.6929220591913847e-07, 'epoch': 0.9}
+
91%|█████████ | 10817/11952 [2:46:02<1:55:22, 6.10s/it]
91%|█████████ | 10818/11952 [2:46:08<1:53:38, 6.01s/it]
{'loss': 0.4827, 'learning_rate': 4.6847213878648876e-07, 'epoch': 0.91}
+
91%|█████████ | 10818/11952 [2:46:08<1:53:38, 6.01s/it]
91%|█████████ | 10819/11952 [2:46:14<1:54:32, 6.07s/it]
{'loss': 0.4751, 'learning_rate': 4.6765277160960133e-07, 'epoch': 0.91}
+
91%|█████████ | 10819/11952 [2:46:14<1:54:32, 6.07s/it]
91%|█████████ | 10820/11952 [2:46:20<1:53:54, 6.04s/it]
{'loss': 0.4529, 'learning_rate': 4.6683410444864573e-07, 'epoch': 0.91}
+
91%|█████████ | 10820/11952 [2:46:20<1:53:54, 6.04s/it]
91%|█████████ | 10821/11952 [2:46:26<1:53:42, 6.03s/it]
{'loss': 0.4748, 'learning_rate': 4.6601613736374173e-07, 'epoch': 0.91}
+
91%|█████████ | 10821/11952 [2:46:26<1:53:42, 6.03s/it]
91%|█████████ | 10822/11952 [2:46:32<1:53:41, 6.04s/it]
{'loss': 0.4607, 'learning_rate': 4.6519887041495905e-07, 'epoch': 0.91}
+
91%|█████████ | 10822/11952 [2:46:32<1:53:41, 6.04s/it]
91%|█████████ | 10823/11952 [2:46:38<1:51:58, 5.95s/it]
{'loss': 0.4451, 'learning_rate': 4.6438230366231075e-07, 'epoch': 0.91}
+
91%|█████████ | 10823/11952 [2:46:38<1:51:58, 5.95s/it]
91%|█████████ | 10824/11952 [2:46:44<1:50:42, 5.89s/it]
{'loss': 0.4693, 'learning_rate': 4.6356643716576557e-07, 'epoch': 0.91}
+
91%|█████████ | 10824/11952 [2:46:44<1:50:42, 5.89s/it]
91%|█████████ | 10825/11952 [2:46:50<1:53:20, 6.03s/it]
{'loss': 0.4662, 'learning_rate': 4.627512709852355e-07, 'epoch': 0.91}
+
91%|█████████ | 10825/11952 [2:46:50<1:53:20, 6.03s/it]
91%|█████████ | 10826/11952 [2:46:56<1:52:22, 5.99s/it]
{'loss': 0.4448, 'learning_rate': 4.61936805180585e-07, 'epoch': 0.91}
+
91%|█████████ | 10826/11952 [2:46:56<1:52:22, 5.99s/it]
91%|█████████ | 10827/11952 [2:47:02<1:50:34, 5.90s/it]
{'loss': 0.47, 'learning_rate': 4.611230398116229e-07, 'epoch': 0.91}
+
91%|█████████ | 10827/11952 [2:47:02<1:50:34, 5.90s/it]
91%|█████████ | 10828/11952 [2:47:08<1:51:39, 5.96s/it]
{'loss': 0.4645, 'learning_rate': 4.6030997493811126e-07, 'epoch': 0.91}
+
91%|█████████ | 10828/11952 [2:47:08<1:51:39, 5.96s/it]
91%|█████████ | 10829/11952 [2:47:13<1:49:11, 5.83s/it]
{'loss': 0.435, 'learning_rate': 4.594976106197546e-07, 'epoch': 0.91}
+
91%|█████████ | 10829/11952 [2:47:13<1:49:11, 5.83s/it]
91%|█████████ | 10830/11952 [2:47:19<1:49:33, 5.86s/it]
{'loss': 0.4691, 'learning_rate': 4.5868594691621304e-07, 'epoch': 0.91}
+
91%|█████████ | 10830/11952 [2:47:19<1:49:33, 5.86s/it]
91%|█████████ | 10831/11952 [2:47:25<1:48:34, 5.81s/it]
{'loss': 0.4661, 'learning_rate': 4.5787498388708774e-07, 'epoch': 0.91}
+
91%|█████████ | 10831/11952 [2:47:25<1:48:34, 5.81s/it]
91%|█████████ | 10832/11952 [2:47:31<1:49:23, 5.86s/it]
{'loss': 0.4651, 'learning_rate': 4.570647215919366e-07, 'epoch': 0.91}
+
91%|█████████ | 10832/11952 [2:47:31<1:49:23, 5.86s/it]
91%|█████████ | 10833/11952 [2:47:37<1:48:25, 5.81s/it]
{'loss': 0.4573, 'learning_rate': 4.5625516009026095e-07, 'epoch': 0.91}
+
91%|█████████ | 10833/11952 [2:47:37<1:48:25, 5.81s/it]
91%|█████████ | 10834/11952 [2:47:43<1:49:06, 5.86s/it]
{'loss': 0.4668, 'learning_rate': 4.5544629944150876e-07, 'epoch': 0.91}
+
91%|█████████ | 10834/11952 [2:47:43<1:49:06, 5.86s/it]
91%|█████████ | 10835/11952 [2:47:48<1:48:28, 5.83s/it]
{'loss': 0.461, 'learning_rate': 4.5463813970508364e-07, 'epoch': 0.91}
+
91%|█████████ | 10835/11952 [2:47:48<1:48:28, 5.83s/it]
91%|█████████ | 10836/11952 [2:47:54<1:48:22, 5.83s/it]
{'loss': 0.4437, 'learning_rate': 4.5383068094033036e-07, 'epoch': 0.91}
+
91%|█████████ | 10836/11952 [2:47:54<1:48:22, 5.83s/it]
91%|█████████ | 10837/11952 [2:48:00<1:49:35, 5.90s/it]
{'loss': 0.4601, 'learning_rate': 4.53023923206547e-07, 'epoch': 0.91}
+
91%|█████████ | 10837/11952 [2:48:00<1:49:35, 5.90s/it]
91%|█████████ | 10838/11952 [2:48:06<1:49:07, 5.88s/it]
{'loss': 0.4662, 'learning_rate': 4.5221786656297727e-07, 'epoch': 0.91}
+
91%|█████████ | 10838/11952 [2:48:06<1:49:07, 5.88s/it]
91%|█████████ | 10839/11952 [2:48:12<1:47:46, 5.81s/it]
{'loss': 0.4571, 'learning_rate': 4.51412511068815e-07, 'epoch': 0.91}
+
91%|█████████ | 10839/11952 [2:48:12<1:47:46, 5.81s/it]
91%|█████████ | 10840/11952 [2:48:18<1:48:43, 5.87s/it]
{'loss': 0.4747, 'learning_rate': 4.5060785678320397e-07, 'epoch': 0.91}
+
91%|█████████ | 10840/11952 [2:48:18<1:48:43, 5.87s/it]
91%|█████████ | 10841/11952 [2:48:23<1:48:12, 5.84s/it]
{'loss': 0.4635, 'learning_rate': 4.498039037652313e-07, 'epoch': 0.91}
+
91%|█████████ | 10841/11952 [2:48:23<1:48:12, 5.84s/it]
91%|█████████ | 10842/11952 [2:48:29<1:46:38, 5.76s/it]
{'loss': 0.4445, 'learning_rate': 4.490006520739387e-07, 'epoch': 0.91}
+
91%|█████████ | 10842/11952 [2:48:29<1:46:38, 5.76s/it]
91%|█████████ | 10843/11952 [2:48:35<1:46:56, 5.79s/it]
{'loss': 0.4579, 'learning_rate': 4.4819810176831235e-07, 'epoch': 0.91}
+
91%|█████████ | 10843/11952 [2:48:35<1:46:56, 5.79s/it]
91%|█████████ | 10844/11952 [2:48:41<1:46:44, 5.78s/it]
{'loss': 0.4499, 'learning_rate': 4.473962529072873e-07, 'epoch': 0.91}
+
91%|█████████ | 10844/11952 [2:48:41<1:46:44, 5.78s/it]
91%|█████████ | 10845/11952 [2:48:47<1:47:14, 5.81s/it]
{'loss': 0.4692, 'learning_rate': 4.465951055497497e-07, 'epoch': 0.91}
+
91%|█████████ | 10845/11952 [2:48:47<1:47:14, 5.81s/it]
91%|█████████ | 10846/11952 [2:48:52<1:47:18, 5.82s/it]
{'loss': 0.4776, 'learning_rate': 4.4579465975453264e-07, 'epoch': 0.91}
+
91%|█████████ | 10846/11952 [2:48:52<1:47:18, 5.82s/it]
91%|█████████ | 10847/11952 [2:48:58<1:48:29, 5.89s/it]
{'loss': 0.4795, 'learning_rate': 4.4499491558041673e-07, 'epoch': 0.91}
+
91%|█████████ | 10847/11952 [2:48:58<1:48:29, 5.89s/it]
91%|█████████ | 10848/11952 [2:49:04<1:48:20, 5.89s/it]
{'loss': 0.4559, 'learning_rate': 4.4419587308613285e-07, 'epoch': 0.91}
+
91%|█████████ | 10848/11952 [2:49:04<1:48:20, 5.89s/it]
91%|█████████ | 10849/11952 [2:49:10<1:48:28, 5.90s/it]
{'loss': 0.4781, 'learning_rate': 4.433975323303574e-07, 'epoch': 0.91}
+
91%|█████████ | 10849/11952 [2:49:10<1:48:28, 5.90s/it]2 AutoResumeHook: Checking whether to suspend...
+50 4AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...3 AutoResumeHook: Checking whether to suspend...
+
+
91%|█████████ | 10850/11952 [2:49:16<1:48:22, 5.90s/it]6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4636, 'learning_rate': 4.42599893371719e-07, 'epoch': 0.91}
+
91%|█████████ | 10850/11952 [2:49:16<1:48:22, 5.90s/it]
91%|█████████ | 10851/11952 [2:49:22<1:49:13, 5.95s/it]
{'loss': 0.462, 'learning_rate': 4.418029562687898e-07, 'epoch': 0.91}
+
91%|█████████ | 10851/11952 [2:49:22<1:49:13, 5.95s/it]
91%|█████████ | 10852/11952 [2:49:28<1:47:16, 5.85s/it]
{'loss': 0.4626, 'learning_rate': 4.4100672108009837e-07, 'epoch': 0.91}
+
91%|█████████ | 10852/11952 [2:49:28<1:47:16, 5.85s/it]
91%|█████████ | 10853/11952 [2:49:34<1:48:47, 5.94s/it]
{'loss': 0.4657, 'learning_rate': 4.4021118786411465e-07, 'epoch': 0.91}
+
91%|█████████ | 10853/11952 [2:49:34<1:48:47, 5.94s/it]
91%|█████████ | 10854/11952 [2:49:40<1:47:48, 5.89s/it]
{'loss': 0.4566, 'learning_rate': 4.3941635667925866e-07, 'epoch': 0.91}
+
91%|█████████ | 10854/11952 [2:49:40<1:47:48, 5.89s/it]
91%|█████████ | 10855/11952 [2:49:46<1:47:23, 5.87s/it]
{'loss': 0.4768, 'learning_rate': 4.3862222758389806e-07, 'epoch': 0.91}
+
91%|█████████ | 10855/11952 [2:49:46<1:47:23, 5.87s/it]
91%|█████████ | 10856/11952 [2:49:51<1:46:42, 5.84s/it]
{'loss': 0.4521, 'learning_rate': 4.3782880063635403e-07, 'epoch': 0.91}
+
91%|█████████ | 10856/11952 [2:49:51<1:46:42, 5.84s/it]
91%|█████████ | 10857/11952 [2:49:58<1:49:26, 6.00s/it]
{'loss': 0.471, 'learning_rate': 4.3703607589489105e-07, 'epoch': 0.91}
+
91%|█████████ | 10857/11952 [2:49:58<1:49:26, 6.00s/it]
91%|█████████ | 10858/11952 [2:50:04<1:48:38, 5.96s/it]
{'loss': 0.4468, 'learning_rate': 4.362440534177226e-07, 'epoch': 0.91}
+
91%|█████████ | 10858/11952 [2:50:04<1:48:38, 5.96s/it]
91%|█████████ | 10859/11952 [2:50:09<1:47:46, 5.92s/it]
{'loss': 0.4578, 'learning_rate': 4.3545273326301205e-07, 'epoch': 0.91}
+
91%|█████████ | 10859/11952 [2:50:09<1:47:46, 5.92s/it]
91%|█████████ | 10860/11952 [2:50:15<1:47:20, 5.90s/it]
{'loss': 0.4488, 'learning_rate': 4.3466211548887195e-07, 'epoch': 0.91}
+
91%|█████████ | 10860/11952 [2:50:15<1:47:20, 5.90s/it]
91%|█████████ | 10861/11952 [2:50:21<1:48:20, 5.96s/it]
{'loss': 0.4784, 'learning_rate': 4.338722001533602e-07, 'epoch': 0.91}
+
91%|█████████ | 10861/11952 [2:50:21<1:48:20, 5.96s/it]
91%|█████████ | 10862/11952 [2:50:27<1:46:15, 5.85s/it]
{'loss': 0.4639, 'learning_rate': 4.3308298731448596e-07, 'epoch': 0.91}
+
91%|█████████ | 10862/11952 [2:50:27<1:46:15, 5.85s/it]
91%|█████████ | 10863/11952 [2:50:33<1:45:29, 5.81s/it]
{'loss': 0.4591, 'learning_rate': 4.322944770302051e-07, 'epoch': 0.91}
+
91%|█████████ | 10863/11952 [2:50:33<1:45:29, 5.81s/it]
91%|█████████ | 10864/11952 [2:50:38<1:45:10, 5.80s/it]
{'loss': 0.4511, 'learning_rate': 4.3150666935842243e-07, 'epoch': 0.91}
+
91%|█████████ | 10864/11952 [2:50:38<1:45:10, 5.80s/it]
91%|█████████ | 10865/11952 [2:50:44<1:44:37, 5.77s/it]
{'loss': 0.459, 'learning_rate': 4.307195643569917e-07, 'epoch': 0.91}
+
91%|█████████ | 10865/11952 [2:50:44<1:44:37, 5.77s/it]
91%|█████████ | 10866/11952 [2:50:50<1:44:47, 5.79s/it]
{'loss': 0.4785, 'learning_rate': 4.299331620837133e-07, 'epoch': 0.91}
+
91%|█████████ | 10866/11952 [2:50:50<1:44:47, 5.79s/it]
91%|█████████ | 10867/11952 [2:50:56<1:44:13, 5.76s/it]
{'loss': 0.4438, 'learning_rate': 4.29147462596341e-07, 'epoch': 0.91}
+
91%|█████████ | 10867/11952 [2:50:56<1:44:13, 5.76s/it]
91%|█████████ | 10868/11952 [2:51:02<1:45:19, 5.83s/it]
{'loss': 0.465, 'learning_rate': 4.283624659525698e-07, 'epoch': 0.91}
+
91%|█████████ | 10868/11952 [2:51:02<1:45:19, 5.83s/it]
91%|█████████ | 10869/11952 [2:51:08<1:46:48, 5.92s/it]
{'loss': 0.4592, 'learning_rate': 4.2757817221004803e-07, 'epoch': 0.91}
+
91%|█████████ | 10869/11952 [2:51:08<1:46:48, 5.92s/it]
91%|█████████ | 10870/11952 [2:51:14<1:47:49, 5.98s/it]
{'loss': 0.4657, 'learning_rate': 4.267945814263708e-07, 'epoch': 0.91}
+
91%|█████████ | 10870/11952 [2:51:14<1:47:49, 5.98s/it]
91%|█████████ | 10871/11952 [2:51:20<1:48:18, 6.01s/it]
{'loss': 0.4765, 'learning_rate': 4.2601169365908077e-07, 'epoch': 0.91}
+
91%|█████████ | 10871/11952 [2:51:20<1:48:18, 6.01s/it]
91%|█████████ | 10872/11952 [2:51:26<1:47:34, 5.98s/it]
{'loss': 0.4664, 'learning_rate': 4.2522950896566994e-07, 'epoch': 0.91}
+
91%|█████████ | 10872/11952 [2:51:26<1:47:34, 5.98s/it]
91%|█████████ | 10873/11952 [2:51:32<1:46:38, 5.93s/it]
{'loss': 0.4634, 'learning_rate': 4.2444802740358114e-07, 'epoch': 0.91}
+
91%|█████████ | 10873/11952 [2:51:32<1:46:38, 5.93s/it]
91%|█████████ | 10874/11952 [2:51:38<1:47:21, 5.98s/it]
{'loss': 0.4695, 'learning_rate': 4.2366724903020076e-07, 'epoch': 0.91}
+
91%|█████████ | 10874/11952 [2:51:38<1:47:21, 5.98s/it]
91%|█████████ | 10875/11952 [2:51:44<1:47:29, 5.99s/it]
{'loss': 0.4691, 'learning_rate': 4.2288717390286614e-07, 'epoch': 0.91}
+
91%|█████████ | 10875/11952 [2:51:44<1:47:29, 5.99s/it]
91%|█████████ | 10876/11952 [2:51:50<1:47:52, 6.02s/it]
{'loss': 0.4936, 'learning_rate': 4.2210780207886383e-07, 'epoch': 0.91}
+
91%|█████████ | 10876/11952 [2:51:50<1:47:52, 6.02s/it]
91%|█████████ | 10877/11952 [2:51:56<1:45:50, 5.91s/it]
{'loss': 0.4619, 'learning_rate': 4.2132913361542683e-07, 'epoch': 0.91}
+
91%|█████████ | 10877/11952 [2:51:56<1:45:50, 5.91s/it]
91%|█████████ | 10878/11952 [2:52:02<1:47:53, 6.03s/it]
{'loss': 0.4653, 'learning_rate': 4.205511685697372e-07, 'epoch': 0.91}
+
91%|█████████ | 10878/11952 [2:52:02<1:47:53, 6.03s/it]
91%|█████████ | 10879/11952 [2:52:08<1:46:32, 5.96s/it]
{'loss': 0.4641, 'learning_rate': 4.1977390699892706e-07, 'epoch': 0.91}
+
91%|█████████ | 10879/11952 [2:52:08<1:46:32, 5.96s/it]
91%|█████████ | 10880/11952 [2:52:14<1:46:45, 5.97s/it]
{'loss': 0.4697, 'learning_rate': 4.1899734896007404e-07, 'epoch': 0.91}
+
91%|█████████ | 10880/11952 [2:52:14<1:46:45, 5.97s/it]
91%|█████████ | 10881/11952 [2:52:19<1:45:17, 5.90s/it]
{'loss': 0.4413, 'learning_rate': 4.1822149451020475e-07, 'epoch': 0.91}
+
91%|█████████ | 10881/11952 [2:52:19<1:45:17, 5.90s/it]
91%|█████████ | 10882/11952 [2:52:25<1:44:09, 5.84s/it]
{'loss': 0.4594, 'learning_rate': 4.1744634370629587e-07, 'epoch': 0.91}
+
91%|█████████ | 10882/11952 [2:52:25<1:44:09, 5.84s/it]
91%|█████████ | 10883/11952 [2:52:31<1:45:23, 5.92s/it]
{'loss': 0.4503, 'learning_rate': 4.166718966052696e-07, 'epoch': 0.91}
+
91%|█████████ | 10883/11952 [2:52:31<1:45:23, 5.92s/it]
91%|█████████ | 10884/11952 [2:52:37<1:45:44, 5.94s/it]
{'loss': 0.4772, 'learning_rate': 4.158981532640005e-07, 'epoch': 0.91}
+
91%|█████████ | 10884/11952 [2:52:37<1:45:44, 5.94s/it]
91%|█████████ | 10885/11952 [2:52:43<1:45:11, 5.92s/it]
{'loss': 0.4692, 'learning_rate': 4.1512511373930533e-07, 'epoch': 0.91}
+
91%|█████████ | 10885/11952 [2:52:43<1:45:11, 5.92s/it]
91%|█████████ | 10886/11952 [2:52:49<1:46:41, 6.01s/it]
{'loss': 0.4666, 'learning_rate': 4.143527780879575e-07, 'epoch': 0.91}
+
91%|█████████ | 10886/11952 [2:52:49<1:46:41, 6.01s/it]
91%|█████████ | 10887/11952 [2:52:55<1:45:40, 5.95s/it]
{'loss': 0.4712, 'learning_rate': 4.1358114636667056e-07, 'epoch': 0.91}
+
91%|█████████ | 10887/11952 [2:52:55<1:45:40, 5.95s/it]
91%|█████████ | 10888/11952 [2:53:01<1:45:50, 5.97s/it]
{'loss': 0.4737, 'learning_rate': 4.128102186321126e-07, 'epoch': 0.91}
+
91%|█████████ | 10888/11952 [2:53:01<1:45:50, 5.97s/it]
91%|█████████ | 10889/11952 [2:53:07<1:44:44, 5.91s/it]
{'loss': 0.45, 'learning_rate': 4.1203999494089596e-07, 'epoch': 0.91}
+
91%|█████████ | 10889/11952 [2:53:07<1:44:44, 5.91s/it]
91%|█████████ | 10890/11952 [2:53:13<1:45:21, 5.95s/it]
{'loss': 0.4695, 'learning_rate': 4.112704753495822e-07, 'epoch': 0.91}
+
91%|█████████ | 10890/11952 [2:53:13<1:45:21, 5.95s/it]
91%|█████████ | 10891/11952 [2:53:19<1:45:24, 5.96s/it]
{'loss': 0.4741, 'learning_rate': 4.1050165991468273e-07, 'epoch': 0.91}
+
91%|█████████ | 10891/11952 [2:53:19<1:45:24, 5.96s/it]
91%|█████████ | 10892/11952 [2:53:25<1:45:54, 5.99s/it]
{'loss': 0.4438, 'learning_rate': 4.097335486926546e-07, 'epoch': 0.91}
+
91%|█████████ | 10892/11952 [2:53:25<1:45:54, 5.99s/it]
91%|█████████ | 10893/11952 [2:53:31<1:45:17, 5.97s/it]
{'loss': 0.4623, 'learning_rate': 4.08966141739906e-07, 'epoch': 0.91}
+
91%|█████████ | 10893/11952 [2:53:31<1:45:17, 5.97s/it]
91%|█████████ | 10894/11952 [2:53:37<1:44:20, 5.92s/it]
{'loss': 0.4615, 'learning_rate': 4.08199439112793e-07, 'epoch': 0.91}
+
91%|█████████ | 10894/11952 [2:53:37<1:44:20, 5.92s/it]
91%|█████████ | 10895/11952 [2:53:42<1:43:29, 5.87s/it]
{'loss': 0.4557, 'learning_rate': 4.0743344086761725e-07, 'epoch': 0.91}
+
91%|█████████ | 10895/11952 [2:53:42<1:43:29, 5.87s/it]
91%|█████████ | 10896/11952 [2:53:48<1:42:42, 5.84s/it]
{'loss': 0.482, 'learning_rate': 4.066681470606304e-07, 'epoch': 0.91}
+
91%|█████████ | 10896/11952 [2:53:48<1:42:42, 5.84s/it]
91%|█████████ | 10897/11952 [2:53:54<1:44:07, 5.92s/it]
{'loss': 0.4708, 'learning_rate': 4.0590355774803416e-07, 'epoch': 0.91}
+
91%|█████████ | 10897/11952 [2:53:54<1:44:07, 5.92s/it]
91%|█████████ | 10898/11952 [2:54:00<1:43:58, 5.92s/it]
{'loss': 0.4756, 'learning_rate': 4.051396729859758e-07, 'epoch': 0.91}
+
91%|█████████ | 10898/11952 [2:54:00<1:43:58, 5.92s/it]
91%|█████████ | 10899/11952 [2:54:06<1:44:26, 5.95s/it]
{'loss': 0.466, 'learning_rate': 4.043764928305505e-07, 'epoch': 0.91}
+
91%|█████████ | 10899/11952 [2:54:06<1:44:26, 5.95s/it]1 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+5 2AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+ 7 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
91%|█████████ | 10900/11952 [2:54:12<1:43:59, 5.93s/it]
{'loss': 0.4491, 'learning_rate': 4.036140173378045e-07, 'epoch': 0.91}
+
91%|█████████ | 10900/11952 [2:54:12<1:43:59, 5.93s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-10900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
91%|█████████ | 10901/11952 [2:54:44<3:59:18, 13.66s/it]
{'loss': 0.4952, 'learning_rate': 4.028522465637319e-07, 'epoch': 0.91}
+
91%|█████████ | 10901/11952 [2:54:44<3:59:18, 13.66s/it]
91%|█████████ | 10902/11952 [2:54:50<3:17:53, 11.31s/it]
{'loss': 0.4506, 'learning_rate': 4.0209118056427356e-07, 'epoch': 0.91}
+
91%|█████████ | 10902/11952 [2:54:50<3:17:53, 11.31s/it]
91%|█████████ | 10903/11952 [2:54:55<2:48:30, 9.64s/it]
{'loss': 0.4513, 'learning_rate': 4.013308193953169e-07, 'epoch': 0.91}
+
91%|█████████ | 10903/11952 [2:54:55<2:48:30, 9.64s/it]
91%|█████████ | 10904/11952 [2:55:01<2:28:04, 8.48s/it]
{'loss': 0.4536, 'learning_rate': 4.0057116311270073e-07, 'epoch': 0.91}
+
91%|█████████ | 10904/11952 [2:55:01<2:28:04, 8.48s/it]
91%|█████████ | 10905/11952 [2:55:07<2:14:09, 7.69s/it]
{'loss': 0.4479, 'learning_rate': 3.998122117722125e-07, 'epoch': 0.91}
+
91%|█████████ | 10905/11952 [2:55:07<2:14:09, 7.69s/it]
91%|█████████ | 10906/11952 [2:55:13<2:03:28, 7.08s/it]
{'loss': 0.4539, 'learning_rate': 3.990539654295833e-07, 'epoch': 0.91}
+
91%|█████████ | 10906/11952 [2:55:13<2:03:28, 7.08s/it]
91%|█████████▏| 10907/11952 [2:55:18<1:56:04, 6.66s/it]
{'loss': 0.4578, 'learning_rate': 3.982964241404974e-07, 'epoch': 0.91}
+
91%|█████████▏| 10907/11952 [2:55:18<1:56:04, 6.66s/it]
91%|█████████▏| 10908/11952 [2:55:25<1:53:31, 6.52s/it]
{'loss': 0.4572, 'learning_rate': 3.975395879605881e-07, 'epoch': 0.91}
+
91%|█████████▏| 10908/11952 [2:55:25<1:53:31, 6.52s/it]
91%|█████████▏| 10909/11952 [2:55:30<1:49:47, 6.32s/it]
{'loss': 0.4333, 'learning_rate': 3.96783456945431e-07, 'epoch': 0.91}
+
91%|█████████▏| 10909/11952 [2:55:30<1:49:47, 6.32s/it]
91%|█████████▏| 10910/11952 [2:55:36<1:46:04, 6.11s/it]
{'loss': 0.4491, 'learning_rate': 3.960280311505538e-07, 'epoch': 0.91}
+
91%|█████████▏| 10910/11952 [2:55:36<1:46:04, 6.11s/it]
91%|█████████▏| 10911/11952 [2:55:42<1:44:55, 6.05s/it]
{'loss': 0.4693, 'learning_rate': 3.9527331063143215e-07, 'epoch': 0.91}
+
91%|█████████▏| 10911/11952 [2:55:42<1:44:55, 6.05s/it]
91%|█████████▏| 10912/11952 [2:55:48<1:43:15, 5.96s/it]
{'loss': 0.4599, 'learning_rate': 3.9451929544348956e-07, 'epoch': 0.91}
+
91%|█████████▏| 10912/11952 [2:55:48<1:43:15, 5.96s/it]
91%|█████████▏| 10913/11952 [2:55:53<1:41:58, 5.89s/it]
{'loss': 0.4722, 'learning_rate': 3.9376598564209614e-07, 'epoch': 0.91}
+
91%|█████████▏| 10913/11952 [2:55:53<1:41:58, 5.89s/it]
91%|█████████▏| 10914/11952 [2:56:00<1:43:26, 5.98s/it]
{'loss': 0.4704, 'learning_rate': 3.9301338128257536e-07, 'epoch': 0.91}
+
91%|█████████▏| 10914/11952 [2:56:00<1:43:26, 5.98s/it]
91%|█████████▏| 10915/11952 [2:56:06<1:43:08, 5.97s/it]
{'loss': 0.4599, 'learning_rate': 3.922614824201931e-07, 'epoch': 0.91}
+
91%|█████████▏| 10915/11952 [2:56:06<1:43:08, 5.97s/it]
91%|█████████▏| 10916/11952 [2:56:11<1:41:28, 5.88s/it]
{'loss': 0.4563, 'learning_rate': 3.915102891101652e-07, 'epoch': 0.91}
+
91%|█████████▏| 10916/11952 [2:56:11<1:41:28, 5.88s/it]
91%|█████████▏| 10917/11952 [2:56:17<1:41:07, 5.86s/it]
{'loss': 0.4605, 'learning_rate': 3.9075980140765637e-07, 'epoch': 0.91}
+
91%|█████████▏| 10917/11952 [2:56:17<1:41:07, 5.86s/it]
91%|█████████▏| 10918/11952 [2:56:23<1:41:51, 5.91s/it]
{'loss': 0.4588, 'learning_rate': 3.900100193677814e-07, 'epoch': 0.91}
+
91%|█████████▏| 10918/11952 [2:56:23<1:41:51, 5.91s/it]
91%|█████████▏| 10919/11952 [2:56:29<1:42:22, 5.95s/it]
{'loss': 0.4697, 'learning_rate': 3.892609430455985e-07, 'epoch': 0.91}
+
91%|█████████▏| 10919/11952 [2:56:29<1:42:22, 5.95s/it]
91%|█████████▏| 10920/11952 [2:56:35<1:42:11, 5.94s/it]
{'loss': 0.4797, 'learning_rate': 3.885125724961192e-07, 'epoch': 0.91}
+
91%|█████████▏| 10920/11952 [2:56:35<1:42:11, 5.94s/it]
91%|█████████▏| 10921/11952 [2:56:41<1:41:55, 5.93s/it]
{'loss': 0.4523, 'learning_rate': 3.877649077742984e-07, 'epoch': 0.91}
+
91%|█████████▏| 10921/11952 [2:56:41<1:41:55, 5.93s/it]
91%|█████████▏| 10922/11952 [2:56:47<1:40:59, 5.88s/it]
{'loss': 0.4725, 'learning_rate': 3.8701794893504343e-07, 'epoch': 0.91}
+
91%|█████████▏| 10922/11952 [2:56:47<1:40:59, 5.88s/it]
91%|█████████▏| 10923/11952 [2:56:53<1:41:21, 5.91s/it]
{'loss': 0.4492, 'learning_rate': 3.862716960332058e-07, 'epoch': 0.91}
+
91%|█████████▏| 10923/11952 [2:56:53<1:41:21, 5.91s/it]
91%|█████████▏| 10924/11952 [2:56:58<1:40:11, 5.85s/it]
{'loss': 0.435, 'learning_rate': 3.8552614912358956e-07, 'epoch': 0.91}
+
91%|█████████▏| 10924/11952 [2:56:58<1:40:11, 5.85s/it]
91%|█████████▏| 10925/11952 [2:57:05<1:42:53, 6.01s/it]
{'loss': 0.4606, 'learning_rate': 3.8478130826094307e-07, 'epoch': 0.91}
+
91%|█████████▏| 10925/11952 [2:57:05<1:42:53, 6.01s/it]
91%|█████████▏| 10926/11952 [2:57:11<1:44:04, 6.09s/it]
{'loss': 0.4684, 'learning_rate': 3.8403717349996263e-07, 'epoch': 0.91}
+
91%|█████████▏| 10926/11952 [2:57:11<1:44:04, 6.09s/it]
91%|█████████▏| 10927/11952 [2:57:17<1:44:27, 6.11s/it]
{'loss': 0.4579, 'learning_rate': 3.832937448952978e-07, 'epoch': 0.91}
+
91%|█████████▏| 10927/11952 [2:57:17<1:44:27, 6.11s/it]
91%|█████████▏| 10928/11952 [2:57:23<1:44:16, 6.11s/it]
{'loss': 0.4772, 'learning_rate': 3.8255102250154054e-07, 'epoch': 0.91}
+
91%|█████████▏| 10928/11952 [2:57:23<1:44:16, 6.11s/it]
91%|█████████▏| 10929/11952 [2:57:29<1:42:57, 6.04s/it]
{'loss': 0.4719, 'learning_rate': 3.81809006373236e-07, 'epoch': 0.91}
+
91%|█████████▏| 10929/11952 [2:57:29<1:42:57, 6.04s/it]
91%|█████████▏| 10930/11952 [2:57:35<1:41:02, 5.93s/it]
{'loss': 0.4419, 'learning_rate': 3.8106769656487184e-07, 'epoch': 0.91}
+
91%|█████████▏| 10930/11952 [2:57:35<1:41:02, 5.93s/it]
91%|█████████▏| 10931/11952 [2:57:41<1:41:17, 5.95s/it]
{'loss': 0.4684, 'learning_rate': 3.803270931308889e-07, 'epoch': 0.91}
+
91%|█████████▏| 10931/11952 [2:57:41<1:41:17, 5.95s/it]
91%|█████████▏| 10932/11952 [2:57:47<1:40:30, 5.91s/it]
{'loss': 0.4569, 'learning_rate': 3.795871961256725e-07, 'epoch': 0.91}
+
91%|█████████▏| 10932/11952 [2:57:47<1:40:30, 5.91s/it]
91%|█████████▏| 10933/11952 [2:57:52<1:39:57, 5.89s/it]
{'loss': 0.4644, 'learning_rate': 3.788480056035571e-07, 'epoch': 0.91}
+
91%|█████████▏| 10933/11952 [2:57:52<1:39:57, 5.89s/it]
91%|█████████▏| 10934/11952 [2:57:59<1:42:16, 6.03s/it]
{'loss': 0.4834, 'learning_rate': 3.78109521618828e-07, 'epoch': 0.91}
+
91%|█████████▏| 10934/11952 [2:57:59<1:42:16, 6.03s/it]
91%|█████████▏| 10935/11952 [2:58:05<1:41:26, 5.98s/it]
{'loss': 0.4578, 'learning_rate': 3.773717442257141e-07, 'epoch': 0.91}
+
91%|█████████▏| 10935/11952 [2:58:05<1:41:26, 5.98s/it]
91%|█████████▏| 10936/11952 [2:58:11<1:40:26, 5.93s/it]
{'loss': 0.4573, 'learning_rate': 3.7663467347839766e-07, 'epoch': 0.91}
+
91%|█████████▏| 10936/11952 [2:58:11<1:40:26, 5.93s/it]
92%|█████████▏| 10937/11952 [2:58:16<1:38:33, 5.83s/it]
{'loss': 0.4669, 'learning_rate': 3.7589830943100205e-07, 'epoch': 0.92}
+
92%|█████████▏| 10937/11952 [2:58:16<1:38:33, 5.83s/it]
92%|█████████▏| 10938/11952 [2:58:22<1:37:32, 5.77s/it]
{'loss': 0.4479, 'learning_rate': 3.7516265213760507e-07, 'epoch': 0.92}
+
92%|█████████▏| 10938/11952 [2:58:22<1:37:32, 5.77s/it]
92%|█████████▏| 10939/11952 [2:58:28<1:40:10, 5.93s/it]
{'loss': 0.4579, 'learning_rate': 3.7442770165223133e-07, 'epoch': 0.92}
+
92%|█████████▏| 10939/11952 [2:58:28<1:40:10, 5.93s/it]
92%|█████████▏| 10940/11952 [2:58:34<1:39:21, 5.89s/it]
{'loss': 0.4696, 'learning_rate': 3.7369345802885095e-07, 'epoch': 0.92}
+
92%|█████████▏| 10940/11952 [2:58:34<1:39:21, 5.89s/it]
92%|█████████▏| 10941/11952 [2:58:40<1:38:34, 5.85s/it]
{'loss': 0.4632, 'learning_rate': 3.7295992132138416e-07, 'epoch': 0.92}
+
92%|█████████▏| 10941/11952 [2:58:40<1:38:34, 5.85s/it]
92%|█████████▏| 10942/11952 [2:58:45<1:38:37, 5.86s/it]
{'loss': 0.4405, 'learning_rate': 3.7222709158369895e-07, 'epoch': 0.92}
+
92%|█████████▏| 10942/11952 [2:58:46<1:38:37, 5.86s/it]
92%|█████████▏| 10943/11952 [2:58:52<1:39:45, 5.93s/it]
{'loss': 0.4644, 'learning_rate': 3.714949688696123e-07, 'epoch': 0.92}
+
92%|█████████▏| 10943/11952 [2:58:52<1:39:45, 5.93s/it]
92%|█████████▏| 10944/11952 [2:58:58<1:40:22, 5.97s/it]
{'loss': 0.4782, 'learning_rate': 3.707635532328857e-07, 'epoch': 0.92}
+
92%|█████████▏| 10944/11952 [2:58:58<1:40:22, 5.97s/it]
92%|█████████▏| 10945/11952 [2:59:03<1:39:22, 5.92s/it]
{'loss': 0.4324, 'learning_rate': 3.700328447272339e-07, 'epoch': 0.92}
+
92%|█████████▏| 10945/11952 [2:59:03<1:39:22, 5.92s/it]
92%|█████████▏| 10946/11952 [2:59:09<1:38:32, 5.88s/it]
{'loss': 0.4569, 'learning_rate': 3.693028434063151e-07, 'epoch': 0.92}
+
92%|█████████▏| 10946/11952 [2:59:09<1:38:32, 5.88s/it]
92%|█████████▏| 10947/11952 [2:59:15<1:40:08, 5.98s/it]
{'loss': 0.454, 'learning_rate': 3.6857354932373857e-07, 'epoch': 0.92}
+
92%|█████████▏| 10947/11952 [2:59:15<1:40:08, 5.98s/it]
92%|█████████▏| 10948/11952 [2:59:21<1:38:07, 5.86s/it]
{'loss': 0.4474, 'learning_rate': 3.6784496253305937e-07, 'epoch': 0.92}
+
92%|█████████▏| 10948/11952 [2:59:21<1:38:07, 5.86s/it]
92%|█████████▏| 10949/11952 [2:59:27<1:39:09, 5.93s/it]
{'loss': 0.4524, 'learning_rate': 3.671170830877846e-07, 'epoch': 0.92}
+
92%|█████████▏| 10949/11952 [2:59:27<1:39:09, 5.93s/it]4 AutoResumeHook: Checking whether to suspend...
+012 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ 5 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+
92%|█████████▏| 10950/11952 [2:59:33<1:39:08, 5.94s/it]3 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4726, 'learning_rate': 3.663899110413638e-07, 'epoch': 0.92}
+
92%|█████████▏| 10950/11952 [2:59:33<1:39:08, 5.94s/it]
92%|█████████▏| 10951/11952 [2:59:39<1:37:37, 5.85s/it]
{'loss': 0.4711, 'learning_rate': 3.6566344644719974e-07, 'epoch': 0.92}
+
92%|█████████▏| 10951/11952 [2:59:39<1:37:37, 5.85s/it]
92%|█████████▏| 10952/11952 [2:59:45<1:37:31, 5.85s/it]
{'loss': 0.441, 'learning_rate': 3.649376893586398e-07, 'epoch': 0.92}
+
92%|█████████▏| 10952/11952 [2:59:45<1:37:31, 5.85s/it]
92%|█████████▏| 10953/11952 [2:59:50<1:37:07, 5.83s/it]
{'loss': 0.4742, 'learning_rate': 3.6421263982898023e-07, 'epoch': 0.92}
+
92%|█████████▏| 10953/11952 [2:59:50<1:37:07, 5.83s/it]
92%|█████████▏| 10954/11952 [2:59:57<1:39:54, 6.01s/it]
{'loss': 0.4701, 'learning_rate': 3.634882979114662e-07, 'epoch': 0.92}
+
92%|█████████▏| 10954/11952 [2:59:57<1:39:54, 6.01s/it]
92%|█████████▏| 10955/11952 [3:00:03<1:38:18, 5.92s/it]
{'loss': 0.4461, 'learning_rate': 3.627646636592919e-07, 'epoch': 0.92}
+
92%|█████████▏| 10955/11952 [3:00:03<1:38:18, 5.92s/it]
92%|█████████▏| 10956/11952 [3:00:09<1:39:15, 5.98s/it]
{'loss': 0.4677, 'learning_rate': 3.6204173712559464e-07, 'epoch': 0.92}
+
92%|█████████▏| 10956/11952 [3:00:09<1:39:15, 5.98s/it]
92%|█████████▏| 10957/11952 [3:00:15<1:38:55, 5.97s/it]
{'loss': 0.4643, 'learning_rate': 3.6131951836346544e-07, 'epoch': 0.92}
+
92%|█████████▏| 10957/11952 [3:00:15<1:38:55, 5.97s/it]
92%|█████████▏| 10958/11952 [3:00:20<1:37:57, 5.91s/it]
{'loss': 0.4507, 'learning_rate': 3.6059800742593963e-07, 'epoch': 0.92}
+
92%|█████████▏| 10958/11952 [3:00:20<1:37:57, 5.91s/it]
92%|█████████▏| 10959/11952 [3:00:26<1:37:59, 5.92s/it]
{'loss': 0.4745, 'learning_rate': 3.5987720436600483e-07, 'epoch': 0.92}
+
92%|█████████▏| 10959/11952 [3:00:26<1:37:59, 5.92s/it]
92%|█████████▏| 10960/11952 [3:00:32<1:36:59, 5.87s/it]
{'loss': 0.4839, 'learning_rate': 3.5915710923658974e-07, 'epoch': 0.92}
+
92%|█████████▏| 10960/11952 [3:00:32<1:36:59, 5.87s/it]
92%|█████████▏| 10961/11952 [3:00:38<1:36:53, 5.87s/it]
{'loss': 0.458, 'learning_rate': 3.584377220905788e-07, 'epoch': 0.92}
+
92%|█████████▏| 10961/11952 [3:00:38<1:36:53, 5.87s/it]
92%|█████████▏| 10962/11952 [3:00:44<1:36:56, 5.88s/it]
{'loss': 0.4535, 'learning_rate': 3.5771904298079864e-07, 'epoch': 0.92}
+
92%|█████████▏| 10962/11952 [3:00:44<1:36:56, 5.88s/it]
92%|█████████▏| 10963/11952 [3:00:49<1:35:12, 5.78s/it]
{'loss': 0.443, 'learning_rate': 3.57001071960027e-07, 'epoch': 0.92}
+
92%|█████████▏| 10963/11952 [3:00:49<1:35:12, 5.78s/it]
92%|█████████▏| 10964/11952 [3:00:55<1:34:35, 5.74s/it]
{'loss': 0.4507, 'learning_rate': 3.562838090809884e-07, 'epoch': 0.92}
+
92%|█████████▏| 10964/11952 [3:00:55<1:34:35, 5.74s/it]
92%|█████████▏| 10965/11952 [3:01:01<1:35:47, 5.82s/it]
{'loss': 0.4554, 'learning_rate': 3.555672543963562e-07, 'epoch': 0.92}
+
92%|█████████▏| 10965/11952 [3:01:01<1:35:47, 5.82s/it]
92%|█████████▏| 10966/11952 [3:01:07<1:36:19, 5.86s/it]
{'loss': 0.4864, 'learning_rate': 3.548514079587495e-07, 'epoch': 0.92}
+
92%|█████████▏| 10966/11952 [3:01:07<1:36:19, 5.86s/it]
92%|█████████▏| 10967/11952 [3:01:13<1:36:01, 5.85s/it]
{'loss': 0.4705, 'learning_rate': 3.541362698207373e-07, 'epoch': 0.92}
+
92%|█████████▏| 10967/11952 [3:01:13<1:36:01, 5.85s/it]
92%|█████████▏| 10968/11952 [3:01:18<1:34:51, 5.78s/it]
{'loss': 0.451, 'learning_rate': 3.5342184003483884e-07, 'epoch': 0.92}
+
92%|█████████▏| 10968/11952 [3:01:18<1:34:51, 5.78s/it]
92%|█████████▏| 10969/11952 [3:01:24<1:35:58, 5.86s/it]
{'loss': 0.4559, 'learning_rate': 3.527081186535164e-07, 'epoch': 0.92}
+
92%|█████████▏| 10969/11952 [3:01:24<1:35:58, 5.86s/it]
92%|█████████▏| 10970/11952 [3:01:31<1:36:56, 5.92s/it]
{'loss': 0.4681, 'learning_rate': 3.5199510572918484e-07, 'epoch': 0.92}
+
92%|█████████▏| 10970/11952 [3:01:31<1:36:56, 5.92s/it]
92%|█████████▏| 10971/11952 [3:01:36<1:36:01, 5.87s/it]
{'loss': 0.4597, 'learning_rate': 3.5128280131420333e-07, 'epoch': 0.92}
+
92%|█████████▏| 10971/11952 [3:01:36<1:36:01, 5.87s/it]
92%|█████████▏| 10972/11952 [3:01:42<1:36:47, 5.93s/it]
{'loss': 0.4551, 'learning_rate': 3.505712054608801e-07, 'epoch': 0.92}
+
92%|█████████▏| 10972/11952 [3:01:42<1:36:47, 5.93s/it]
92%|█████████▏| 10973/11952 [3:01:48<1:36:10, 5.89s/it]
{'loss': 0.4646, 'learning_rate': 3.4986031822147325e-07, 'epoch': 0.92}
+
92%|█████████▏| 10973/11952 [3:01:48<1:36:10, 5.89s/it]
92%|█████████▏| 10974/11952 [3:01:54<1:36:59, 5.95s/it]
{'loss': 0.4706, 'learning_rate': 3.4915013964818556e-07, 'epoch': 0.92}
+
92%|█████████▏| 10974/11952 [3:01:54<1:36:59, 5.95s/it]
92%|█████████▏| 10975/11952 [3:02:00<1:35:19, 5.85s/it]
{'loss': 0.4488, 'learning_rate': 3.4844066979317193e-07, 'epoch': 0.92}
+
92%|█████████▏| 10975/11952 [3:02:00<1:35:19, 5.85s/it]
92%|█████████▏| 10976/11952 [3:02:06<1:36:07, 5.91s/it]
{'loss': 0.4767, 'learning_rate': 3.477319087085318e-07, 'epoch': 0.92}
+
92%|█████████▏| 10976/11952 [3:02:06<1:36:07, 5.91s/it]
92%|█████████▏| 10977/11952 [3:02:12<1:36:40, 5.95s/it]
{'loss': 0.4695, 'learning_rate': 3.470238564463135e-07, 'epoch': 0.92}
+
92%|█████████▏| 10977/11952 [3:02:12<1:36:40, 5.95s/it]
92%|█████████▏| 10978/11952 [3:02:18<1:36:43, 5.96s/it]
{'loss': 0.4663, 'learning_rate': 3.4631651305851224e-07, 'epoch': 0.92}
+
92%|█████████▏| 10978/11952 [3:02:18<1:36:43, 5.96s/it]
92%|█████████▏| 10979/11952 [3:02:24<1:35:04, 5.86s/it]
{'loss': 0.455, 'learning_rate': 3.4560987859707407e-07, 'epoch': 0.92}
+
92%|█████████▏| 10979/11952 [3:02:24<1:35:04, 5.86s/it]
92%|█████████▏| 10980/11952 [3:02:29<1:34:59, 5.86s/it]
{'loss': 0.4549, 'learning_rate': 3.44903953113892e-07, 'epoch': 0.92}
+
92%|█████████▏| 10980/11952 [3:02:29<1:34:59, 5.86s/it]
92%|█████████▏| 10981/11952 [3:02:36<1:36:21, 5.95s/it]
{'loss': 0.4622, 'learning_rate': 3.4419873666080237e-07, 'epoch': 0.92}
+
92%|█████████▏| 10981/11952 [3:02:36<1:36:21, 5.95s/it]
92%|█████████▏| 10982/11952 [3:02:42<1:36:42, 5.98s/it]
{'loss': 0.4688, 'learning_rate': 3.434942292895982e-07, 'epoch': 0.92}
+
92%|█████████▏| 10982/11952 [3:02:42<1:36:42, 5.98s/it]
92%|█████████▏| 10983/11952 [3:02:48<1:36:15, 5.96s/it]
{'loss': 0.4463, 'learning_rate': 3.427904310520136e-07, 'epoch': 0.92}
+
92%|█████████▏| 10983/11952 [3:02:48<1:36:15, 5.96s/it]
92%|█████████▏| 10984/11952 [3:02:53<1:35:36, 5.93s/it]
{'loss': 0.4726, 'learning_rate': 3.420873419997317e-07, 'epoch': 0.92}
+
92%|█████████▏| 10984/11952 [3:02:53<1:35:36, 5.93s/it]
92%|█████████▏| 10985/11952 [3:02:59<1:34:28, 5.86s/it]
{'loss': 0.4541, 'learning_rate': 3.413849621843857e-07, 'epoch': 0.92}
+
92%|█████████▏| 10985/11952 [3:02:59<1:34:28, 5.86s/it]
92%|█████████▏| 10986/11952 [3:03:05<1:35:14, 5.92s/it]
{'loss': 0.4545, 'learning_rate': 3.406832916575542e-07, 'epoch': 0.92}
+
92%|█████████▏| 10986/11952 [3:03:05<1:35:14, 5.92s/it]
92%|█████████▏| 10987/11952 [3:03:11<1:36:05, 5.97s/it]
{'loss': 0.449, 'learning_rate': 3.3998233047076613e-07, 'epoch': 0.92}
+
92%|█████████▏| 10987/11952 [3:03:11<1:36:05, 5.97s/it]
92%|█████████▏| 10988/11952 [3:03:17<1:35:47, 5.96s/it]
{'loss': 0.4896, 'learning_rate': 3.3928207867549467e-07, 'epoch': 0.92}
+
92%|█████████▏| 10988/11952 [3:03:17<1:35:47, 5.96s/it]
92%|█████████▏| 10989/11952 [3:03:23<1:34:42, 5.90s/it]
{'loss': 0.4583, 'learning_rate': 3.385825363231665e-07, 'epoch': 0.92}
+
92%|█████████▏| 10989/11952 [3:03:23<1:34:42, 5.90s/it]
92%|█████████▏| 10990/11952 [3:03:29<1:33:21, 5.82s/it]
{'loss': 0.4388, 'learning_rate': 3.3788370346515274e-07, 'epoch': 0.92}
+
92%|█████████▏| 10990/11952 [3:03:29<1:33:21, 5.82s/it]
92%|█████████▏| 10991/11952 [3:03:35<1:34:23, 5.89s/it]
{'loss': 0.4818, 'learning_rate': 3.3718558015277237e-07, 'epoch': 0.92}
+
92%|█████████▏| 10991/11952 [3:03:35<1:34:23, 5.89s/it]
92%|█████████▏| 10992/11952 [3:03:40<1:34:01, 5.88s/it]
{'loss': 0.4601, 'learning_rate': 3.3648816643729207e-07, 'epoch': 0.92}
+
92%|█████████▏| 10992/11952 [3:03:40<1:34:01, 5.88s/it]
92%|█████████▏| 10993/11952 [3:03:47<1:34:33, 5.92s/it]
{'loss': 0.4561, 'learning_rate': 3.357914623699265e-07, 'epoch': 0.92}
+
92%|█████████▏| 10993/11952 [3:03:47<1:34:33, 5.92s/it]
92%|█████████▏| 10994/11952 [3:03:52<1:34:05, 5.89s/it]
{'loss': 0.4834, 'learning_rate': 3.3509546800183923e-07, 'epoch': 0.92}
+
92%|█████████▏| 10994/11952 [3:03:52<1:34:05, 5.89s/it]
92%|█████████▏| 10995/11952 [3:03:58<1:33:44, 5.88s/it]
{'loss': 0.4675, 'learning_rate': 3.344001833841426e-07, 'epoch': 0.92}
+
92%|█████████▏| 10995/11952 [3:03:58<1:33:44, 5.88s/it]
92%|█████████▏| 10996/11952 [3:04:04<1:33:03, 5.84s/it]
{'loss': 0.4454, 'learning_rate': 3.337056085678936e-07, 'epoch': 0.92}
+
92%|█████████▏| 10996/11952 [3:04:04<1:33:03, 5.84s/it]
92%|█████████▏| 10997/11952 [3:04:10<1:32:53, 5.84s/it]
{'loss': 0.4625, 'learning_rate': 3.3301174360410026e-07, 'epoch': 0.92}
+
92%|█████████▏| 10997/11952 [3:04:10<1:32:53, 5.84s/it]
92%|█████████▏| 10998/11952 [3:04:16<1:33:01, 5.85s/it]
{'loss': 0.462, 'learning_rate': 3.3231858854371634e-07, 'epoch': 0.92}
+
92%|█████████▏| 10998/11952 [3:04:16<1:33:01, 5.85s/it]
92%|█████████▏| 10999/11952 [3:04:21<1:32:21, 5.81s/it]
{'loss': 0.4516, 'learning_rate': 3.3162614343764334e-07, 'epoch': 0.92}
+
92%|█████████▏| 10999/11952 [3:04:21<1:32:21, 5.81s/it]2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+076 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+1 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
92%|█████████▏| 11000/11952 [3:04:28<1:33:48, 5.91s/it]
{'loss': 0.4705, 'learning_rate': 3.309344083367327e-07, 'epoch': 0.92}
+
92%|█████████▏| 11000/11952 [3:04:28<1:33:48, 5.91s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11000/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11000/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11000/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
92%|█████████▏| 11001/11952 [3:05:00<3:41:59, 14.01s/it]
{'loss': 0.4631, 'learning_rate': 3.3024338329178285e-07, 'epoch': 0.92}
+
92%|█████████▏| 11001/11952 [3:05:00<3:41:59, 14.01s/it]
92%|█████████▏| 11002/11952 [3:05:06<3:01:47, 11.48s/it]
{'loss': 0.4625, 'learning_rate': 3.2955306835353863e-07, 'epoch': 0.92}
+
92%|█████████▏| 11002/11952 [3:05:06<3:01:47, 11.48s/it]
92%|█████████▏| 11003/11952 [3:05:12<2:37:41, 9.97s/it]
{'loss': 0.4815, 'learning_rate': 3.2886346357269614e-07, 'epoch': 0.92}
+
92%|█████████▏| 11003/11952 [3:05:12<2:37:41, 9.97s/it]
92%|█████████▏| 11004/11952 [3:05:19<2:19:07, 8.80s/it]
{'loss': 0.4582, 'learning_rate': 3.28174568999895e-07, 'epoch': 0.92}
+
92%|█████████▏| 11004/11952 [3:05:19<2:19:07, 8.80s/it]
92%|█████████▏| 11005/11952 [3:05:24<2:05:01, 7.92s/it]
{'loss': 0.4654, 'learning_rate': 3.274863846857257e-07, 'epoch': 0.92}
+
92%|█████████▏| 11005/11952 [3:05:24<2:05:01, 7.92s/it]
92%|█████████▏| 11006/11952 [3:05:30<1:53:54, 7.22s/it]
{'loss': 0.4465, 'learning_rate': 3.2679891068072566e-07, 'epoch': 0.92}
+
92%|█████████▏| 11006/11952 [3:05:30<1:53:54, 7.22s/it]
92%|█████████▏| 11007/11952 [3:05:36<1:46:29, 6.76s/it]
{'loss': 0.4808, 'learning_rate': 3.26112147035379e-07, 'epoch': 0.92}
+
92%|█████████▏| 11007/11952 [3:05:36<1:46:29, 6.76s/it]
92%|█████████▏| 11008/11952 [3:05:41<1:41:35, 6.46s/it]
{'loss': 0.4494, 'learning_rate': 3.254260938001186e-07, 'epoch': 0.92}
+
92%|█████████▏| 11008/11952 [3:05:41<1:41:35, 6.46s/it]
92%|█████████▏| 11009/11952 [3:05:47<1:39:18, 6.32s/it]
{'loss': 0.4643, 'learning_rate': 3.2474075102532756e-07, 'epoch': 0.92}
+
92%|█████████▏| 11009/11952 [3:05:47<1:39:18, 6.32s/it]
92%|█████████▏| 11010/11952 [3:05:53<1:37:35, 6.22s/it]
{'loss': 0.4687, 'learning_rate': 3.240561187613323e-07, 'epoch': 0.92}
+
92%|█████████▏| 11010/11952 [3:05:53<1:37:35, 6.22s/it]
92%|█████████▏| 11011/11952 [3:05:59<1:35:18, 6.08s/it]
{'loss': 0.4417, 'learning_rate': 3.233721970584114e-07, 'epoch': 0.92}
+
92%|█████████▏| 11011/11952 [3:05:59<1:35:18, 6.08s/it]
92%|█████████▏| 11012/11952 [3:06:05<1:34:48, 6.05s/it]
{'loss': 0.4668, 'learning_rate': 3.226889859667881e-07, 'epoch': 0.92}
+
92%|█████████▏| 11012/11952 [3:06:05<1:34:48, 6.05s/it]
92%|█████████▏| 11013/11952 [3:06:11<1:34:35, 6.04s/it]
{'loss': 0.4714, 'learning_rate': 3.220064855366345e-07, 'epoch': 0.92}
+
92%|█████████▏| 11013/11952 [3:06:11<1:34:35, 6.04s/it]
92%|█████████▏| 11014/11952 [3:06:17<1:33:37, 5.99s/it]
{'loss': 0.4715, 'learning_rate': 3.2132469581807046e-07, 'epoch': 0.92}
+
92%|█████████▏| 11014/11952 [3:06:17<1:33:37, 5.99s/it]
92%|█████████▏| 11015/11952 [3:06:23<1:34:32, 6.05s/it]
{'loss': 0.4557, 'learning_rate': 3.2064361686116377e-07, 'epoch': 0.92}
+
92%|█████████▏| 11015/11952 [3:06:23<1:34:32, 6.05s/it]
92%|█████████▏| 11016/11952 [3:06:29<1:34:59, 6.09s/it]
{'loss': 0.4709, 'learning_rate': 3.199632487159321e-07, 'epoch': 0.92}
+
92%|█████████▏| 11016/11952 [3:06:29<1:34:59, 6.09s/it]
92%|█████████▏| 11017/11952 [3:06:35<1:33:33, 6.00s/it]
{'loss': 0.4687, 'learning_rate': 3.1928359143233556e-07, 'epoch': 0.92}
+
92%|█████████▏| 11017/11952 [3:06:35<1:33:33, 6.00s/it]
92%|█████████▏| 11018/11952 [3:06:41<1:33:08, 5.98s/it]
{'loss': 0.4549, 'learning_rate': 3.1860464506028865e-07, 'epoch': 0.92}
+
92%|█████████▏| 11018/11952 [3:06:41<1:33:08, 5.98s/it]
92%|█████████▏| 11019/11952 [3:06:47<1:32:24, 5.94s/it]
{'loss': 0.4747, 'learning_rate': 3.1792640964964593e-07, 'epoch': 0.92}
+
92%|█████████▏| 11019/11952 [3:06:47<1:32:24, 5.94s/it]
92%|█████████▏| 11020/11952 [3:06:53<1:32:07, 5.93s/it]
{'loss': 0.4414, 'learning_rate': 3.172488852502187e-07, 'epoch': 0.92}
+
92%|█████████▏| 11020/11952 [3:06:53<1:32:07, 5.93s/it]
92%|█████████▏| 11021/11952 [3:06:59<1:32:25, 5.96s/it]
{'loss': 0.4593, 'learning_rate': 3.1657207191176043e-07, 'epoch': 0.92}
+
92%|█████████▏| 11021/11952 [3:06:59<1:32:25, 5.96s/it]
92%|█████████▏| 11022/11952 [3:07:05<1:33:21, 6.02s/it]
{'loss': 0.4616, 'learning_rate': 3.1589596968397027e-07, 'epoch': 0.92}
+
92%|█████████▏| 11022/11952 [3:07:05<1:33:21, 6.02s/it]
92%|█████████▏| 11023/11952 [3:07:11<1:31:55, 5.94s/it]
{'loss': 0.4688, 'learning_rate': 3.15220578616503e-07, 'epoch': 0.92}
+
92%|█████████▏| 11023/11952 [3:07:11<1:31:55, 5.94s/it]
92%|█████████▏| 11024/11952 [3:07:17<1:31:38, 5.93s/it]
{'loss': 0.4583, 'learning_rate': 3.1454589875895445e-07, 'epoch': 0.92}
+
92%|█████████▏| 11024/11952 [3:07:17<1:31:38, 5.93s/it]
92%|█████████▏| 11025/11952 [3:07:23<1:31:33, 5.93s/it]
{'loss': 0.4662, 'learning_rate': 3.1387193016086945e-07, 'epoch': 0.92}
+
92%|█████████▏| 11025/11952 [3:07:23<1:31:33, 5.93s/it]
92%|█████████▏| 11026/11952 [3:07:29<1:31:24, 5.92s/it]
{'loss': 0.4629, 'learning_rate': 3.131986728717429e-07, 'epoch': 0.92}
+
92%|█████████▏| 11026/11952 [3:07:29<1:31:24, 5.92s/it]
92%|█████████▏| 11027/11952 [3:07:34<1:30:26, 5.87s/it]
{'loss': 0.4678, 'learning_rate': 3.1252612694101515e-07, 'epoch': 0.92}
+
92%|█████████▏| 11027/11952 [3:07:34<1:30:26, 5.87s/it]
92%|█████████▏| 11028/11952 [3:07:40<1:29:35, 5.82s/it]
{'loss': 0.4724, 'learning_rate': 3.1185429241807453e-07, 'epoch': 0.92}
+
92%|█████████▏| 11028/11952 [3:07:40<1:29:35, 5.82s/it]
92%|█████████▏| 11029/11952 [3:07:46<1:29:12, 5.80s/it]
{'loss': 0.4607, 'learning_rate': 3.1118316935226043e-07, 'epoch': 0.92}
+
92%|█████████▏| 11029/11952 [3:07:46<1:29:12, 5.80s/it]
92%|█████████▏| 11030/11952 [3:07:52<1:29:03, 5.80s/it]
{'loss': 0.4534, 'learning_rate': 3.105127577928546e-07, 'epoch': 0.92}
+
92%|█████████▏| 11030/11952 [3:07:52<1:29:03, 5.80s/it]
92%|█████████▏| 11031/11952 [3:07:57<1:29:30, 5.83s/it]
{'loss': 0.4537, 'learning_rate': 3.0984305778908875e-07, 'epoch': 0.92}
+
92%|█████████▏| 11031/11952 [3:07:57<1:29:30, 5.83s/it]
92%|█████████▏| 11032/11952 [3:08:03<1:30:08, 5.88s/it]
{'loss': 0.4804, 'learning_rate': 3.091740693901468e-07, 'epoch': 0.92}
+
92%|█████████▏| 11032/11952 [3:08:03<1:30:08, 5.88s/it]
92%|█████████▏| 11033/11952 [3:08:09<1:29:32, 5.85s/it]
{'loss': 0.4322, 'learning_rate': 3.085057926451529e-07, 'epoch': 0.92}
+
92%|█████████▏| 11033/11952 [3:08:09<1:29:32, 5.85s/it]
92%|█████████▏| 11034/11952 [3:08:17<1:40:29, 6.57s/it]
{'loss': 0.4564, 'learning_rate': 3.078382276031833e-07, 'epoch': 0.92}
+
92%|█████████▏| 11034/11952 [3:08:17<1:40:29, 6.57s/it]
92%|█████████▏| 11035/11952 [3:08:24<1:38:22, 6.44s/it]
{'loss': 0.4704, 'learning_rate': 3.071713743132609e-07, 'epoch': 0.92}
+
92%|█████████▏| 11035/11952 [3:08:24<1:38:22, 6.44s/it]
92%|█████████▏| 11036/11952 [3:08:30<1:36:10, 6.30s/it]
{'loss': 0.4677, 'learning_rate': 3.0650523282435896e-07, 'epoch': 0.92}
+
92%|█████████▏| 11036/11952 [3:08:30<1:36:10, 6.30s/it]
92%|█████████▏| 11037/11952 [3:08:36<1:35:24, 6.26s/it]
{'loss': 0.467, 'learning_rate': 3.0583980318539377e-07, 'epoch': 0.92}
+
92%|█████████▏| 11037/11952 [3:08:36<1:35:24, 6.26s/it]
92%|█████████▏| 11038/11952 [3:08:41<1:32:27, 6.07s/it]
{'loss': 0.452, 'learning_rate': 3.051750854452329e-07, 'epoch': 0.92}
+
92%|█████████▏| 11038/11952 [3:08:41<1:32:27, 6.07s/it]
92%|█████████▏| 11039/11952 [3:08:47<1:31:46, 6.03s/it]
{'loss': 0.4757, 'learning_rate': 3.0451107965268956e-07, 'epoch': 0.92}
+
92%|█████████▏| 11039/11952 [3:08:47<1:31:46, 6.03s/it]
92%|█████████▏| 11040/11952 [3:08:53<1:31:23, 6.01s/it]
{'loss': 0.4601, 'learning_rate': 3.0384778585652477e-07, 'epoch': 0.92}
+
92%|█████████▏| 11040/11952 [3:08:53<1:31:23, 6.01s/it]
92%|█████████▏| 11041/11952 [3:09:02<1:44:58, 6.91s/it]
{'loss': 0.4614, 'learning_rate': 3.031852041054506e-07, 'epoch': 0.92}
+
92%|█████████▏| 11041/11952 [3:09:02<1:44:58, 6.91s/it]
92%|█████████▏| 11042/11952 [3:09:08<1:40:50, 6.65s/it]
{'loss': 0.4768, 'learning_rate': 3.0252333444812263e-07, 'epoch': 0.92}
+
92%|█████████▏| 11042/11952 [3:09:08<1:40:50, 6.65s/it]
92%|█████████▏| 11043/11952 [3:09:15<1:39:22, 6.56s/it]
{'loss': 0.4619, 'learning_rate': 3.0186217693314643e-07, 'epoch': 0.92}
+
92%|█████████▏| 11043/11952 [3:09:15<1:39:22, 6.56s/it]
92%|█████████▏| 11044/11952 [3:09:23<1:46:34, 7.04s/it]
{'loss': 0.4598, 'learning_rate': 3.012017316090743e-07, 'epoch': 0.92}
+
92%|█████████▏| 11044/11952 [3:09:23<1:46:34, 7.04s/it]
92%|█████████▏| 11045/11952 [3:09:29<1:40:28, 6.65s/it]
{'loss': 0.4628, 'learning_rate': 3.0054199852440626e-07, 'epoch': 0.92}
+
92%|█████████▏| 11045/11952 [3:09:29<1:40:28, 6.65s/it]
92%|█████████▏| 11046/11952 [3:09:37<1:48:23, 7.18s/it]
{'loss': 0.4393, 'learning_rate': 2.9988297772759136e-07, 'epoch': 0.92}
+
92%|█████████▏| 11046/11952 [3:09:37<1:48:23, 7.18s/it]
92%|█████████▏| 11047/11952 [3:09:46<1:56:28, 7.72s/it]
{'loss': 0.475, 'learning_rate': 2.992246692670242e-07, 'epoch': 0.92}
+
92%|█████████▏| 11047/11952 [3:09:46<1:56:28, 7.72s/it]
92%|█████████▏| 11048/11952 [3:09:52<1:48:25, 7.20s/it]
{'loss': 0.4703, 'learning_rate': 2.985670731910495e-07, 'epoch': 0.92}
+
92%|█████████▏| 11048/11952 [3:09:52<1:48:25, 7.20s/it]
92%|█████████▏| 11049/11952 [3:10:01<1:55:59, 7.71s/it]
{'loss': 0.4442, 'learning_rate': 2.9791018954795636e-07, 'epoch': 0.92}
+
92%|█████████▏| 11049/11952 [3:10:01<1:55:59, 7.71s/it]2 AutoResumeHook: Checking whether to suspend...
+03 AutoResumeHook: Checking whether to suspend...7
+5 4AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+6 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
92%|█████████▏| 11050/11952 [3:10:06<1:46:30, 7.09s/it]
{'loss': 0.4694, 'learning_rate': 2.972540183859862e-07, 'epoch': 0.92}
+
92%|█████████▏| 11050/11952 [3:10:06<1:46:30, 7.09s/it]
92%|█████████▏| 11051/11952 [3:10:13<1:42:10, 6.80s/it]
{'loss': 0.4698, 'learning_rate': 2.9659855975332274e-07, 'epoch': 0.92}
+
92%|█████████▏| 11051/11952 [3:10:13<1:42:10, 6.80s/it]
92%|█████████▏| 11052/11952 [3:10:19<1:38:11, 6.55s/it]
{'loss': 0.4357, 'learning_rate': 2.959438136981019e-07, 'epoch': 0.92}
+
92%|█████████▏| 11052/11952 [3:10:19<1:38:11, 6.55s/it]
92%|█████████▏| 11053/11952 [3:10:25<1:35:40, 6.39s/it]
{'loss': 0.4585, 'learning_rate': 2.9528978026840625e-07, 'epoch': 0.92}
+
92%|█████████▏| 11053/11952 [3:10:25<1:35:40, 6.39s/it]
92%|█████████▏| 11054/11952 [3:10:30<1:32:47, 6.20s/it]
{'loss': 0.4864, 'learning_rate': 2.9463645951226415e-07, 'epoch': 0.92}
+
92%|█████████▏| 11054/11952 [3:10:30<1:32:47, 6.20s/it]
92%|█████████▏| 11055/11952 [3:10:36<1:31:18, 6.11s/it]
{'loss': 0.4584, 'learning_rate': 2.939838514776527e-07, 'epoch': 0.92}
+
92%|█████████▏| 11055/11952 [3:10:36<1:31:18, 6.11s/it]
93%|█████████▎| 11056/11952 [3:10:42<1:29:34, 6.00s/it]
{'loss': 0.4561, 'learning_rate': 2.933319562124959e-07, 'epoch': 0.92}
+
93%|█████████▎| 11056/11952 [3:10:42<1:29:34, 6.00s/it]
93%|█████████▎| 11057/11952 [3:10:48<1:28:32, 5.94s/it]
{'loss': 0.4795, 'learning_rate': 2.926807737646675e-07, 'epoch': 0.93}
+
93%|█████████▎| 11057/11952 [3:10:48<1:28:32, 5.94s/it]
93%|█████████▎| 11058/11952 [3:10:54<1:29:23, 6.00s/it]
{'loss': 0.4472, 'learning_rate': 2.920303041819872e-07, 'epoch': 0.93}
+
93%|█████████▎| 11058/11952 [3:10:54<1:29:23, 6.00s/it]
93%|█████████▎| 11059/11952 [3:10:59<1:27:19, 5.87s/it]
{'loss': 0.461, 'learning_rate': 2.9138054751222447e-07, 'epoch': 0.93}
+
93%|█████████▎| 11059/11952 [3:10:59<1:27:19, 5.87s/it]
93%|█████████▎| 11060/11952 [3:11:05<1:26:23, 5.81s/it]
{'loss': 0.4699, 'learning_rate': 2.907315038030911e-07, 'epoch': 0.93}
+
93%|█████████▎| 11060/11952 [3:11:05<1:26:23, 5.81s/it]
93%|█████████▎| 11061/11952 [3:11:11<1:26:55, 5.85s/it]
{'loss': 0.4574, 'learning_rate': 2.900831731022524e-07, 'epoch': 0.93}
+
93%|█████████▎| 11061/11952 [3:11:11<1:26:55, 5.85s/it]
93%|█████████▎| 11062/11952 [3:11:18<1:29:56, 6.06s/it]
{'loss': 0.4534, 'learning_rate': 2.894355554573203e-07, 'epoch': 0.93}
+
93%|█████████▎| 11062/11952 [3:11:18<1:29:56, 6.06s/it]
93%|█████████▎| 11063/11952 [3:11:23<1:28:41, 5.99s/it]
{'loss': 0.4645, 'learning_rate': 2.8878865091584993e-07, 'epoch': 0.93}
+
93%|█████████▎| 11063/11952 [3:11:23<1:28:41, 5.99s/it]
93%|█████████▎| 11064/11952 [3:11:29<1:28:38, 5.99s/it]
{'loss': 0.4718, 'learning_rate': 2.881424595253501e-07, 'epoch': 0.93}
+
93%|█████████▎| 11064/11952 [3:11:29<1:28:38, 5.99s/it]
93%|█████████▎| 11065/11952 [3:11:35<1:28:35, 5.99s/it]
{'loss': 0.4806, 'learning_rate': 2.8749698133327396e-07, 'epoch': 0.93}
+
93%|█████████▎| 11065/11952 [3:11:35<1:28:35, 5.99s/it]
93%|█████████▎| 11066/11952 [3:11:41<1:28:21, 5.98s/it]
{'loss': 0.4608, 'learning_rate': 2.868522163870213e-07, 'epoch': 0.93}
+
93%|█████████▎| 11066/11952 [3:11:41<1:28:21, 5.98s/it]
93%|█████████▎| 11067/11952 [3:11:47<1:27:24, 5.93s/it]
{'loss': 0.4613, 'learning_rate': 2.8620816473394206e-07, 'epoch': 0.93}
+
93%|█████████▎| 11067/11952 [3:11:47<1:27:24, 5.93s/it]
93%|█████████▎| 11068/11952 [3:11:53<1:28:20, 6.00s/it]
{'loss': 0.4636, 'learning_rate': 2.855648264213329e-07, 'epoch': 0.93}
+
93%|█████████▎| 11068/11952 [3:11:53<1:28:20, 6.00s/it]
93%|█████████▎| 11069/11952 [3:11:59<1:26:22, 5.87s/it]
{'loss': 0.4611, 'learning_rate': 2.84922201496437e-07, 'epoch': 0.93}
+
93%|█████████▎| 11069/11952 [3:11:59<1:26:22, 5.87s/it]
93%|█████████▎| 11070/11952 [3:12:05<1:26:12, 5.86s/it]
{'loss': 0.4624, 'learning_rate': 2.8428029000644676e-07, 'epoch': 0.93}
+
93%|█████████▎| 11070/11952 [3:12:05<1:26:12, 5.86s/it]
93%|█████████▎| 11071/11952 [3:12:11<1:26:20, 5.88s/it]
{'loss': 0.4557, 'learning_rate': 2.83639091998501e-07, 'epoch': 0.93}
+
93%|█████████▎| 11071/11952 [3:12:11<1:26:20, 5.88s/it]
93%|█████████▎| 11072/11952 [3:12:16<1:25:36, 5.84s/it]
{'loss': 0.4618, 'learning_rate': 2.8299860751968664e-07, 'epoch': 0.93}
+
93%|█████████▎| 11072/11952 [3:12:16<1:25:36, 5.84s/it]
93%|█████████▎| 11073/11952 [3:12:23<1:27:03, 5.94s/it]
{'loss': 0.4716, 'learning_rate': 2.823588366170393e-07, 'epoch': 0.93}
+
93%|█████████▎| 11073/11952 [3:12:23<1:27:03, 5.94s/it]
93%|█████████▎| 11074/11952 [3:12:29<1:27:22, 5.97s/it]
{'loss': 0.4572, 'learning_rate': 2.8171977933754036e-07, 'epoch': 0.93}
+
93%|█████████▎| 11074/11952 [3:12:29<1:27:22, 5.97s/it]
93%|█████████▎| 11075/11952 [3:12:35<1:27:21, 5.98s/it]
{'loss': 0.4798, 'learning_rate': 2.810814357281189e-07, 'epoch': 0.93}
+
93%|█████████▎| 11075/11952 [3:12:35<1:27:21, 5.98s/it]
93%|█████████▎| 11076/11952 [3:12:41<1:27:52, 6.02s/it]
{'loss': 0.4614, 'learning_rate': 2.804438058356529e-07, 'epoch': 0.93}
+
93%|█████████▎| 11076/11952 [3:12:41<1:27:52, 6.02s/it]
93%|█████████▎| 11077/11952 [3:12:46<1:26:18, 5.92s/it]
{'loss': 0.4506, 'learning_rate': 2.798068897069672e-07, 'epoch': 0.93}
+
93%|█████████▎| 11077/11952 [3:12:46<1:26:18, 5.92s/it]
93%|█████████▎| 11078/11952 [3:12:52<1:25:46, 5.89s/it]
{'loss': 0.4792, 'learning_rate': 2.791706873888345e-07, 'epoch': 0.93}
+
93%|█████████▎| 11078/11952 [3:12:52<1:25:46, 5.89s/it]
93%|█████████▎| 11079/11952 [3:12:58<1:25:26, 5.87s/it]
{'loss': 0.463, 'learning_rate': 2.78535198927975e-07, 'epoch': 0.93}
+
93%|█████████▎| 11079/11952 [3:12:58<1:25:26, 5.87s/it]
93%|█████████▎| 11080/11952 [3:13:04<1:25:05, 5.86s/it]
{'loss': 0.4493, 'learning_rate': 2.779004243710548e-07, 'epoch': 0.93}
+
93%|█████████▎| 11080/11952 [3:13:04<1:25:05, 5.86s/it]
93%|█████████▎| 11081/11952 [3:13:10<1:24:38, 5.83s/it]
{'loss': 0.4583, 'learning_rate': 2.7726636376468995e-07, 'epoch': 0.93}
+
93%|█████████▎| 11081/11952 [3:13:10<1:24:38, 5.83s/it]
93%|█████████▎| 11082/11952 [3:13:15<1:24:09, 5.80s/it]
{'loss': 0.4744, 'learning_rate': 2.766330171554443e-07, 'epoch': 0.93}
+
93%|█████████▎| 11082/11952 [3:13:15<1:24:09, 5.80s/it]
93%|█████████▎| 11083/11952 [3:13:21<1:23:52, 5.79s/it]
{'loss': 0.4577, 'learning_rate': 2.7600038458982626e-07, 'epoch': 0.93}
+
93%|█████████▎| 11083/11952 [3:13:21<1:23:52, 5.79s/it]
93%|█████████▎| 11084/11952 [3:13:27<1:23:54, 5.80s/it]
{'loss': 0.4498, 'learning_rate': 2.7536846611429524e-07, 'epoch': 0.93}
+
93%|█████████▎| 11084/11952 [3:13:27<1:23:54, 5.80s/it]
93%|█████████▎| 11085/11952 [3:13:33<1:25:29, 5.92s/it]
{'loss': 0.466, 'learning_rate': 2.747372617752575e-07, 'epoch': 0.93}
+
93%|█████████▎| 11085/11952 [3:13:33<1:25:29, 5.92s/it]
93%|█████████▎| 11086/11952 [3:13:39<1:24:49, 5.88s/it]
{'loss': 0.4466, 'learning_rate': 2.741067716190637e-07, 'epoch': 0.93}
+
93%|█████████▎| 11086/11952 [3:13:39<1:24:49, 5.88s/it]
93%|█████████▎| 11087/11952 [3:13:45<1:25:40, 5.94s/it]
{'loss': 0.4521, 'learning_rate': 2.734769956920169e-07, 'epoch': 0.93}
+
93%|█████████▎| 11087/11952 [3:13:45<1:25:40, 5.94s/it]
93%|█████████▎| 11088/11952 [3:13:51<1:24:21, 5.86s/it]
{'loss': 0.4548, 'learning_rate': 2.728479340403634e-07, 'epoch': 0.93}
+
93%|█████████▎| 11088/11952 [3:13:51<1:24:21, 5.86s/it]
93%|█████████▎| 11089/11952 [3:13:57<1:23:50, 5.83s/it]
{'loss': 0.464, 'learning_rate': 2.7221958671029834e-07, 'epoch': 0.93}
+
93%|█████████▎| 11089/11952 [3:13:57<1:23:50, 5.83s/it]
93%|█████████▎| 11090/11952 [3:14:02<1:24:00, 5.85s/it]
{'loss': 0.463, 'learning_rate': 2.715919537479661e-07, 'epoch': 0.93}
+
93%|█████████▎| 11090/11952 [3:14:02<1:24:00, 5.85s/it]
93%|█████████▎| 11091/11952 [3:14:08<1:24:09, 5.86s/it]
{'loss': 0.4979, 'learning_rate': 2.709650351994575e-07, 'epoch': 0.93}
+
93%|█████████▎| 11091/11952 [3:14:08<1:24:09, 5.86s/it]
93%|█████████▎| 11092/11952 [3:14:14<1:24:51, 5.92s/it]
{'loss': 0.46, 'learning_rate': 2.7033883111081014e-07, 'epoch': 0.93}
+
93%|█████████▎| 11092/11952 [3:14:14<1:24:51, 5.92s/it]
93%|█████████▎| 11093/11952 [3:14:20<1:24:11, 5.88s/it]
{'loss': 0.4618, 'learning_rate': 2.6971334152801063e-07, 'epoch': 0.93}
+
93%|█████████▎| 11093/11952 [3:14:20<1:24:11, 5.88s/it]
93%|█████████▎| 11094/11952 [3:14:26<1:22:54, 5.80s/it]
{'loss': 0.4493, 'learning_rate': 2.690885664969933e-07, 'epoch': 0.93}
+
93%|█████████▎| 11094/11952 [3:14:26<1:22:54, 5.80s/it]
93%|█████████▎| 11095/11952 [3:14:32<1:23:15, 5.83s/it]
{'loss': 0.4691, 'learning_rate': 2.6846450606363705e-07, 'epoch': 0.93}
+
93%|█████████▎| 11095/11952 [3:14:32<1:23:15, 5.83s/it]
93%|█████████▎| 11096/11952 [3:14:37<1:22:27, 5.78s/it]
{'loss': 0.4505, 'learning_rate': 2.678411602737707e-07, 'epoch': 0.93}
+
93%|█████████▎| 11096/11952 [3:14:37<1:22:27, 5.78s/it]
93%|█████████▎| 11097/11952 [3:14:43<1:22:36, 5.80s/it]
{'loss': 0.4586, 'learning_rate': 2.6721852917316995e-07, 'epoch': 0.93}
+
93%|█████████▎| 11097/11952 [3:14:43<1:22:36, 5.80s/it]
93%|█████████▎| 11098/11952 [3:14:50<1:25:29, 6.01s/it]
{'loss': 0.4665, 'learning_rate': 2.665966128075592e-07, 'epoch': 0.93}
+
93%|█████████▎| 11098/11952 [3:14:50<1:25:29, 6.01s/it]
93%|█████████▎| 11099/11952 [3:14:56<1:26:34, 6.09s/it]
{'loss': 0.4521, 'learning_rate': 2.659754112226087e-07, 'epoch': 0.93}
+
93%|█████████▎| 11099/11952 [3:14:56<1:26:34, 6.09s/it]5 AutoResumeHook: Checking whether to suspend...
+02 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
93%|█████████▎| 11100/11952 [3:15:02<1:25:34, 6.03s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4666, 'learning_rate': 2.653549244639375e-07, 'epoch': 0.93}
+
93%|█████████▎| 11100/11952 [3:15:02<1:25:34, 6.03s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11100/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11100/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11100/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
93%|█████████▎| 11101/11952 [3:15:32<3:07:19, 13.21s/it]
{'loss': 0.456, 'learning_rate': 2.6473515257711136e-07, 'epoch': 0.93}
+
93%|█████████▎| 11101/11952 [3:15:32<3:07:19, 13.21s/it]
93%|█████████▎| 11102/11952 [3:15:38<2:36:08, 11.02s/it]
{'loss': 0.4674, 'learning_rate': 2.6411609560764273e-07, 'epoch': 0.93}
+
93%|█████████▎| 11102/11952 [3:15:38<2:36:08, 11.02s/it]
93%|█████████▎| 11103/11952 [3:15:43<2:13:27, 9.43s/it]
{'loss': 0.4626, 'learning_rate': 2.6349775360099306e-07, 'epoch': 0.93}
+
93%|█████████▎| 11103/11952 [3:15:43<2:13:27, 9.43s/it]
93%|█████████▎| 11104/11952 [3:15:49<1:58:30, 8.39s/it]
{'loss': 0.4403, 'learning_rate': 2.628801266025727e-07, 'epoch': 0.93}
+
93%|█████████▎| 11104/11952 [3:15:49<1:58:30, 8.39s/it]
93%|█████████▎| 11105/11952 [3:15:55<1:47:22, 7.61s/it]
{'loss': 0.4732, 'learning_rate': 2.622632146577364e-07, 'epoch': 0.93}
+
93%|█████████▎| 11105/11952 [3:15:55<1:47:22, 7.61s/it]
93%|█████████▎| 11106/11952 [3:16:01<1:39:42, 7.07s/it]
{'loss': 0.4657, 'learning_rate': 2.616470178117858e-07, 'epoch': 0.93}
+
93%|█████████▎| 11106/11952 [3:16:01<1:39:42, 7.07s/it]
93%|█████████▎| 11107/11952 [3:16:07<1:33:32, 6.64s/it]
{'loss': 0.4599, 'learning_rate': 2.6103153610997464e-07, 'epoch': 0.93}
+
93%|█████████▎| 11107/11952 [3:16:07<1:33:32, 6.64s/it]
93%|█████████▎| 11108/11952 [3:16:12<1:29:06, 6.33s/it]
{'loss': 0.4552, 'learning_rate': 2.604167695975002e-07, 'epoch': 0.93}
+
93%|█████████▎| 11108/11952 [3:16:12<1:29:06, 6.33s/it]
93%|█████████▎| 11109/11952 [3:16:18<1:26:51, 6.18s/it]
{'loss': 0.4677, 'learning_rate': 2.5980271831950734e-07, 'epoch': 0.93}
+
93%|█████████▎| 11109/11952 [3:16:18<1:26:51, 6.18s/it]
93%|█████████▎| 11110/11952 [3:16:24<1:25:04, 6.06s/it]
{'loss': 0.4628, 'learning_rate': 2.5918938232109004e-07, 'epoch': 0.93}
+
93%|█████████▎| 11110/11952 [3:16:24<1:25:04, 6.06s/it]
93%|█████████▎| 11111/11952 [3:16:30<1:24:01, 5.99s/it]
{'loss': 0.4507, 'learning_rate': 2.5857676164729006e-07, 'epoch': 0.93}
+
93%|█████████▎| 11111/11952 [3:16:30<1:24:01, 5.99s/it]
93%|█████████▎| 11112/11952 [3:16:36<1:23:33, 5.97s/it]
{'loss': 0.4524, 'learning_rate': 2.5796485634309477e-07, 'epoch': 0.93}
+
93%|█████████▎| 11112/11952 [3:16:36<1:23:33, 5.97s/it]
93%|█████████▎| 11113/11952 [3:16:41<1:22:42, 5.91s/it]
{'loss': 0.4644, 'learning_rate': 2.573536664534404e-07, 'epoch': 0.93}
+
93%|█████████▎| 11113/11952 [3:16:41<1:22:42, 5.91s/it]
93%|█████████▎| 11114/11952 [3:16:47<1:21:10, 5.81s/it]
{'loss': 0.4485, 'learning_rate': 2.5674319202320997e-07, 'epoch': 0.93}
+
93%|█████████▎| 11114/11952 [3:16:47<1:21:10, 5.81s/it]
93%|█████████▎| 11115/11952 [3:16:53<1:22:50, 5.94s/it]
{'loss': 0.4583, 'learning_rate': 2.5613343309723426e-07, 'epoch': 0.93}
+
93%|█████████▎| 11115/11952 [3:16:53<1:22:50, 5.94s/it]
93%|█████████▎| 11116/11952 [3:16:59<1:22:54, 5.95s/it]
{'loss': 0.4837, 'learning_rate': 2.555243897202919e-07, 'epoch': 0.93}
+
93%|█████████▎| 11116/11952 [3:16:59<1:22:54, 5.95s/it]
93%|█████████▎| 11117/11952 [3:17:05<1:22:29, 5.93s/it]
{'loss': 0.4759, 'learning_rate': 2.549160619371072e-07, 'epoch': 0.93}
+
93%|█████████▎| 11117/11952 [3:17:05<1:22:29, 5.93s/it]
93%|█████████▎| 11118/11952 [3:17:11<1:22:29, 5.94s/it]
{'loss': 0.4621, 'learning_rate': 2.5430844979235426e-07, 'epoch': 0.93}
+
93%|█████████▎| 11118/11952 [3:17:11<1:22:29, 5.94s/it]
93%|█████████▎| 11119/11952 [3:17:17<1:21:57, 5.90s/it]
{'loss': 0.4752, 'learning_rate': 2.5370155333065416e-07, 'epoch': 0.93}
+
93%|█████████▎| 11119/11952 [3:17:17<1:21:57, 5.90s/it]
93%|█████████▎| 11120/11952 [3:17:23<1:21:37, 5.89s/it]
{'loss': 0.4624, 'learning_rate': 2.5309537259657346e-07, 'epoch': 0.93}
+
93%|█████████▎| 11120/11952 [3:17:23<1:21:37, 5.89s/it]
93%|█████████▎| 11121/11952 [3:17:28<1:21:10, 5.86s/it]
{'loss': 0.4575, 'learning_rate': 2.524899076346288e-07, 'epoch': 0.93}
+
93%|█████████▎| 11121/11952 [3:17:28<1:21:10, 5.86s/it]
93%|█████████▎| 11122/11952 [3:17:34<1:21:34, 5.90s/it]
{'loss': 0.4817, 'learning_rate': 2.518851584892812e-07, 'epoch': 0.93}
+
93%|█████████▎| 11122/11952 [3:17:34<1:21:34, 5.90s/it]
93%|█████████▎| 11123/11952 [3:17:40<1:21:00, 5.86s/it]
{'loss': 0.4768, 'learning_rate': 2.5128112520494297e-07, 'epoch': 0.93}
+
93%|█████████▎| 11123/11952 [3:17:40<1:21:00, 5.86s/it]
93%|█████████▎| 11124/11952 [3:17:46<1:20:07, 5.81s/it]
{'loss': 0.4499, 'learning_rate': 2.5067780782596973e-07, 'epoch': 0.93}
+
93%|█████████▎| 11124/11952 [3:17:46<1:20:07, 5.81s/it]
93%|█████████▎| 11125/11952 [3:17:52<1:20:04, 5.81s/it]
{'loss': 0.4508, 'learning_rate': 2.500752063966694e-07, 'epoch': 0.93}
+
93%|█████████▎| 11125/11952 [3:17:52<1:20:04, 5.81s/it]
93%|█████████▎| 11126/11952 [3:17:58<1:20:26, 5.84s/it]
{'loss': 0.4726, 'learning_rate': 2.494733209612921e-07, 'epoch': 0.93}
+
93%|█████████▎| 11126/11952 [3:17:58<1:20:26, 5.84s/it]
93%|█████████▎| 11127/11952 [3:18:04<1:20:42, 5.87s/it]
{'loss': 0.4577, 'learning_rate': 2.488721515640391e-07, 'epoch': 0.93}
+
93%|█████████▎| 11127/11952 [3:18:04<1:20:42, 5.87s/it]
93%|█████████▎| 11128/11952 [3:18:10<1:22:11, 5.99s/it]
{'loss': 0.449, 'learning_rate': 2.482716982490574e-07, 'epoch': 0.93}
+
93%|█████████▎| 11128/11952 [3:18:10<1:22:11, 5.99s/it]
93%|█████████▎| 11129/11952 [3:18:16<1:22:17, 6.00s/it]
{'loss': 0.4783, 'learning_rate': 2.476719610604417e-07, 'epoch': 0.93}
+
93%|█████████▎| 11129/11952 [3:18:16<1:22:17, 6.00s/it]
93%|█████████▎| 11130/11952 [3:18:22<1:20:44, 5.89s/it]
{'loss': 0.483, 'learning_rate': 2.4707294004223335e-07, 'epoch': 0.93}
+
93%|█████████▎| 11130/11952 [3:18:22<1:20:44, 5.89s/it]
93%|█████████▎| 11131/11952 [3:18:28<1:21:26, 5.95s/it]
{'loss': 0.4561, 'learning_rate': 2.464746352384229e-07, 'epoch': 0.93}
+
93%|█████████▎| 11131/11952 [3:18:28<1:21:26, 5.95s/it]
93%|█████████▎| 11132/11952 [3:18:33<1:20:29, 5.89s/it]
{'loss': 0.4791, 'learning_rate': 2.4587704669294834e-07, 'epoch': 0.93}
+
93%|█████████▎| 11132/11952 [3:18:33<1:20:29, 5.89s/it]
93%|█████████▎| 11133/11952 [3:18:39<1:20:00, 5.86s/it]
{'loss': 0.4602, 'learning_rate': 2.452801744496913e-07, 'epoch': 0.93}
+
93%|█████████▎| 11133/11952 [3:18:39<1:20:00, 5.86s/it]
93%|█████████▎| 11134/11952 [3:18:45<1:21:22, 5.97s/it]
{'loss': 0.4529, 'learning_rate': 2.446840185524868e-07, 'epoch': 0.93}
+
93%|█████████▎| 11134/11952 [3:18:45<1:21:22, 5.97s/it]
93%|█████████▎| 11135/11952 [3:18:51<1:19:52, 5.87s/it]
{'loss': 0.4832, 'learning_rate': 2.4408857904511196e-07, 'epoch': 0.93}
+
93%|█████████▎| 11135/11952 [3:18:51<1:19:52, 5.87s/it]
93%|█████████▎| 11136/11952 [3:18:57<1:19:12, 5.82s/it]
{'loss': 0.4787, 'learning_rate': 2.4349385597129403e-07, 'epoch': 0.93}
+
93%|█████████▎| 11136/11952 [3:18:57<1:19:12, 5.82s/it]
93%|█████████▎| 11137/11952 [3:19:03<1:19:06, 5.82s/it]
{'loss': 0.4726, 'learning_rate': 2.428998493747081e-07, 'epoch': 0.93}
+
93%|█████████▎| 11137/11952 [3:19:03<1:19:06, 5.82s/it]
93%|█████████▎| 11138/11952 [3:19:09<1:20:11, 5.91s/it]
{'loss': 0.4646, 'learning_rate': 2.4230655929897263e-07, 'epoch': 0.93}
+
93%|█████████▎| 11138/11952 [3:19:09<1:20:11, 5.91s/it]
93%|█████████▎| 11139/11952 [3:19:15<1:20:09, 5.92s/it]
{'loss': 0.4458, 'learning_rate': 2.417139857876583e-07, 'epoch': 0.93}
+
93%|█████████▎| 11139/11952 [3:19:15<1:20:09, 5.92s/it]
93%|█████████▎| 11140/11952 [3:19:20<1:19:49, 5.90s/it]
{'loss': 0.4363, 'learning_rate': 2.4112212888428246e-07, 'epoch': 0.93}
+
93%|█████████▎| 11140/11952 [3:19:20<1:19:49, 5.90s/it]
93%|█████████▎| 11141/11952 [3:19:27<1:21:10, 6.01s/it]
{'loss': 0.4711, 'learning_rate': 2.4053098863230706e-07, 'epoch': 0.93}
+
93%|█████████▎| 11141/11952 [3:19:27<1:21:10, 6.01s/it]
93%|█████████▎| 11142/11952 [3:19:33<1:20:45, 5.98s/it]
{'loss': 0.4633, 'learning_rate': 2.3994056507514183e-07, 'epoch': 0.93}
+
93%|█████████▎| 11142/11952 [3:19:33<1:20:45, 5.98s/it]
93%|█████████▎| 11143/11952 [3:19:39<1:21:27, 6.04s/it]
{'loss': 0.4565, 'learning_rate': 2.3935085825614655e-07, 'epoch': 0.93}
+
93%|█████████▎| 11143/11952 [3:19:39<1:21:27, 6.04s/it]
93%|█████████▎| 11144/11952 [3:19:45<1:21:25, 6.05s/it]
{'loss': 0.4608, 'learning_rate': 2.387618682186277e-07, 'epoch': 0.93}
+
93%|█████████▎| 11144/11952 [3:19:45<1:21:25, 6.05s/it]
93%|█████████▎| 11145/11952 [3:19:51<1:20:41, 6.00s/it]
{'loss': 0.4632, 'learning_rate': 2.3817359500583615e-07, 'epoch': 0.93}
+
93%|█████████▎| 11145/11952 [3:19:51<1:20:41, 6.00s/it]
93%|█████████▎| 11146/11952 [3:19:57<1:20:33, 6.00s/it]
{'loss': 0.4617, 'learning_rate': 2.3758603866097406e-07, 'epoch': 0.93}
+
93%|█████████▎| 11146/11952 [3:19:57<1:20:33, 6.00s/it]
93%|█████████▎| 11147/11952 [3:20:03<1:20:01, 5.96s/it]
{'loss': 0.4715, 'learning_rate': 2.3699919922718805e-07, 'epoch': 0.93}
+
93%|█████████▎| 11147/11952 [3:20:03<1:20:01, 5.96s/it]
93%|█████████▎| 11148/11952 [3:20:09<1:19:36, 5.94s/it]
{'loss': 0.4526, 'learning_rate': 2.3641307674757362e-07, 'epoch': 0.93}
+
93%|█████████▎| 11148/11952 [3:20:09<1:19:36, 5.94s/it]
93%|█████████▎| 11149/11952 [3:20:14<1:19:21, 5.93s/it]
{'loss': 0.4631, 'learning_rate': 2.3582767126517302e-07, 'epoch': 0.93}
+
93%|█████████▎| 11149/11952 [3:20:14<1:19:21, 5.93s/it]5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+
93%|█████████▎| 11150/11952 [3:20:20<1:19:01, 5.91s/it]2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4627, 'learning_rate': 2.352429828229763e-07, 'epoch': 0.93}
+
93%|█████████▎| 11150/11952 [3:20:20<1:19:01, 5.91s/it]
93%|█████████▎| 11151/11952 [3:20:26<1:17:54, 5.84s/it]
{'loss': 0.4579, 'learning_rate': 2.3465901146391912e-07, 'epoch': 0.93}
+
93%|█████████▎| 11151/11952 [3:20:26<1:17:54, 5.84s/it]
93%|█████████▎| 11152/11952 [3:20:32<1:17:16, 5.80s/it]
{'loss': 0.4531, 'learning_rate': 2.3407575723088827e-07, 'epoch': 0.93}
+
93%|█████████▎| 11152/11952 [3:20:32<1:17:16, 5.80s/it]
93%|█████████▎| 11153/11952 [3:20:37<1:17:01, 5.78s/it]
{'loss': 0.4655, 'learning_rate': 2.3349322016671394e-07, 'epoch': 0.93}
+
93%|█████████▎| 11153/11952 [3:20:37<1:17:01, 5.78s/it]
93%|█████████▎| 11154/11952 [3:20:43<1:16:16, 5.74s/it]
{'loss': 0.4745, 'learning_rate': 2.3291140031417525e-07, 'epoch': 0.93}
+
93%|█████████▎| 11154/11952 [3:20:43<1:16:16, 5.74s/it]
93%|█████████▎| 11155/11952 [3:20:49<1:16:08, 5.73s/it]
{'loss': 0.4893, 'learning_rate': 2.3233029771599913e-07, 'epoch': 0.93}
+
93%|█████████▎| 11155/11952 [3:20:49<1:16:08, 5.73s/it]
93%|█████████▎| 11156/11952 [3:20:55<1:16:03, 5.73s/it]
{'loss': 0.4505, 'learning_rate': 2.3174991241485923e-07, 'epoch': 0.93}
+
93%|█████████▎| 11156/11952 [3:20:55<1:16:03, 5.73s/it]
93%|█████████▎| 11157/11952 [3:21:01<1:17:46, 5.87s/it]
{'loss': 0.4682, 'learning_rate': 2.31170244453377e-07, 'epoch': 0.93}
+
93%|█████████▎| 11157/11952 [3:21:01<1:17:46, 5.87s/it]
93%|█████████▎| 11158/11952 [3:21:06<1:16:56, 5.81s/it]
{'loss': 0.4609, 'learning_rate': 2.305912938741184e-07, 'epoch': 0.93}
+
93%|█████████▎| 11158/11952 [3:21:06<1:16:56, 5.81s/it]
93%|█████████▎| 11159/11952 [3:21:12<1:16:11, 5.77s/it]
{'loss': 0.4606, 'learning_rate': 2.3001306071960384e-07, 'epoch': 0.93}
+
93%|█████████▎| 11159/11952 [3:21:12<1:16:11, 5.77s/it]
93%|█████████▎| 11160/11952 [3:21:18<1:16:54, 5.83s/it]
{'loss': 0.4565, 'learning_rate': 2.294355450322916e-07, 'epoch': 0.93}
+
93%|█████████▎| 11160/11952 [3:21:18<1:16:54, 5.83s/it]
93%|█████████▎| 11161/11952 [3:21:24<1:16:04, 5.77s/it]
{'loss': 0.4542, 'learning_rate': 2.2885874685459553e-07, 'epoch': 0.93}
+
93%|█████████▎| 11161/11952 [3:21:24<1:16:04, 5.77s/it]
93%|█████████▎| 11162/11952 [3:21:30<1:17:19, 5.87s/it]
{'loss': 0.4691, 'learning_rate': 2.2828266622887173e-07, 'epoch': 0.93}
+
93%|█████████▎| 11162/11952 [3:21:30<1:17:19, 5.87s/it]
93%|█████████▎| 11163/11952 [3:21:36<1:17:33, 5.90s/it]
{'loss': 0.4622, 'learning_rate': 2.2770730319742528e-07, 'epoch': 0.93}
+
93%|█████████▎| 11163/11952 [3:21:36<1:17:33, 5.90s/it]
93%|█████████▎| 11164/11952 [3:21:42<1:17:30, 5.90s/it]
{'loss': 0.4703, 'learning_rate': 2.271326578025068e-07, 'epoch': 0.93}
+
93%|█████████▎| 11164/11952 [3:21:42<1:17:30, 5.90s/it]
93%|█████████▎| 11165/11952 [3:21:48<1:17:30, 5.91s/it]
{'loss': 0.4572, 'learning_rate': 2.2655873008631812e-07, 'epoch': 0.93}
+
93%|█████████▎| 11165/11952 [3:21:48<1:17:30, 5.91s/it]
93%|█████████▎| 11166/11952 [3:21:54<1:18:01, 5.96s/it]
{'loss': 0.4871, 'learning_rate': 2.259855200910066e-07, 'epoch': 0.93}
+
93%|█████████▎| 11166/11952 [3:21:54<1:18:01, 5.96s/it]
93%|█████████▎| 11167/11952 [3:21:59<1:17:10, 5.90s/it]
{'loss': 0.4661, 'learning_rate': 2.2541302785866525e-07, 'epoch': 0.93}
+
93%|█████████▎| 11167/11952 [3:21:59<1:17:10, 5.90s/it]
93%|█████████▎| 11168/11952 [3:22:05<1:17:56, 5.96s/it]
{'loss': 0.4621, 'learning_rate': 2.248412534313349e-07, 'epoch': 0.93}
+
93%|█████████▎| 11168/11952 [3:22:05<1:17:56, 5.96s/it]
93%|█████████▎| 11169/11952 [3:22:11<1:17:29, 5.94s/it]
{'loss': 0.4768, 'learning_rate': 2.2427019685100527e-07, 'epoch': 0.93}
+
93%|█████████▎| 11169/11952 [3:22:11<1:17:29, 5.94s/it]
93%|█████████▎| 11170/11952 [3:22:17<1:17:15, 5.93s/it]
{'loss': 0.4552, 'learning_rate': 2.236998581596128e-07, 'epoch': 0.93}
+
93%|█████████▎| 11170/11952 [3:22:17<1:17:15, 5.93s/it]
93%|█████████▎| 11171/11952 [3:22:23<1:16:17, 5.86s/it]
{'loss': 0.4535, 'learning_rate': 2.231302373990385e-07, 'epoch': 0.93}
+
93%|█████████▎| 11171/11952 [3:22:23<1:16:17, 5.86s/it]
93%|█████████▎| 11172/11952 [3:22:29<1:16:02, 5.85s/it]
{'loss': 0.4639, 'learning_rate': 2.225613346111155e-07, 'epoch': 0.93}
+
93%|█████████▎| 11172/11952 [3:22:29<1:16:02, 5.85s/it]
93%|█████████▎| 11173/11952 [3:22:35<1:15:48, 5.84s/it]
{'loss': 0.4708, 'learning_rate': 2.2199314983762043e-07, 'epoch': 0.93}
+
93%|█████████▎| 11173/11952 [3:22:35<1:15:48, 5.84s/it]
93%|█████████▎| 11174/11952 [3:22:41<1:17:15, 5.96s/it]
{'loss': 0.4768, 'learning_rate': 2.2142568312027879e-07, 'epoch': 0.93}
+
93%|█████████▎| 11174/11952 [3:22:41<1:17:15, 5.96s/it]
93%|█████████▎| 11175/11952 [3:22:47<1:17:09, 5.96s/it]
{'loss': 0.4697, 'learning_rate': 2.2085893450076167e-07, 'epoch': 0.93}
+
93%|█████████▎| 11175/11952 [3:22:47<1:17:09, 5.96s/it]
94%|█████████▎| 11176/11952 [3:22:53<1:16:49, 5.94s/it]
{'loss': 0.4648, 'learning_rate': 2.2029290402069137e-07, 'epoch': 0.94}
+
94%|█████████▎| 11176/11952 [3:22:53<1:16:49, 5.94s/it]
94%|█████████▎| 11177/11952 [3:22:59<1:18:11, 6.05s/it]
{'loss': 0.4732, 'learning_rate': 2.1972759172163239e-07, 'epoch': 0.94}
+
94%|█████████▎| 11177/11952 [3:22:59<1:18:11, 6.05s/it]
94%|█████████▎| 11178/11952 [3:23:05<1:16:18, 5.92s/it]
{'loss': 0.4662, 'learning_rate': 2.191629976451004e-07, 'epoch': 0.94}
+
94%|█████████▎| 11178/11952 [3:23:05<1:16:18, 5.92s/it]
94%|█████████▎| 11179/11952 [3:23:10<1:16:00, 5.90s/it]
{'loss': 0.458, 'learning_rate': 2.185991218325556e-07, 'epoch': 0.94}
+
94%|█████████▎| 11179/11952 [3:23:10<1:16:00, 5.90s/it]
94%|█████████▎| 11180/11952 [3:23:16<1:16:05, 5.91s/it]
{'loss': 0.4644, 'learning_rate': 2.1803596432540818e-07, 'epoch': 0.94}
+
94%|█████████▎| 11180/11952 [3:23:16<1:16:05, 5.91s/it]
94%|█████████▎| 11181/11952 [3:23:22<1:15:14, 5.86s/it]
{'loss': 0.4514, 'learning_rate': 2.1747352516501396e-07, 'epoch': 0.94}
+
94%|█████████▎| 11181/11952 [3:23:22<1:15:14, 5.86s/it]
94%|█████████▎| 11182/11952 [3:23:28<1:14:10, 5.78s/it]
{'loss': 0.477, 'learning_rate': 2.1691180439267434e-07, 'epoch': 0.94}
+
94%|█████████▎| 11182/11952 [3:23:28<1:14:10, 5.78s/it]
94%|█████████▎| 11183/11952 [3:23:34<1:15:31, 5.89s/it]
{'loss': 0.4799, 'learning_rate': 2.1635080204964187e-07, 'epoch': 0.94}
+
94%|█████████▎| 11183/11952 [3:23:34<1:15:31, 5.89s/it]
94%|█████████▎| 11184/11952 [3:23:40<1:15:23, 5.89s/it]
{'loss': 0.4699, 'learning_rate': 2.157905181771114e-07, 'epoch': 0.94}
+
94%|█████████▎| 11184/11952 [3:23:40<1:15:23, 5.89s/it]
94%|█████████▎| 11185/11952 [3:23:45<1:14:18, 5.81s/it]
{'loss': 0.4609, 'learning_rate': 2.1523095281623109e-07, 'epoch': 0.94}
+
94%|█████████▎| 11185/11952 [3:23:45<1:14:18, 5.81s/it]
94%|█████████▎| 11186/11952 [3:23:52<1:15:20, 5.90s/it]
{'loss': 0.446, 'learning_rate': 2.146721060080914e-07, 'epoch': 0.94}
+
94%|█████████▎| 11186/11952 [3:23:52<1:15:20, 5.90s/it]
94%|█████████▎| 11187/11952 [3:23:58<1:16:12, 5.98s/it]
{'loss': 0.4774, 'learning_rate': 2.141139777937318e-07, 'epoch': 0.94}
+
94%|█████████▎| 11187/11952 [3:23:58<1:16:12, 5.98s/it]
94%|█████████▎| 11188/11952 [3:24:04<1:16:07, 5.98s/it]
{'loss': 0.4701, 'learning_rate': 2.1355656821413938e-07, 'epoch': 0.94}
+
94%|█████████▎| 11188/11952 [3:24:04<1:16:07, 5.98s/it]
94%|█████████▎| 11189/11952 [3:24:10<1:15:35, 5.94s/it]
{'loss': 0.457, 'learning_rate': 2.1299987731024818e-07, 'epoch': 0.94}
+
94%|█████████▎| 11189/11952 [3:24:10<1:15:35, 5.94s/it]
94%|█████████▎| 11190/11952 [3:24:15<1:15:21, 5.93s/it]
{'loss': 0.4449, 'learning_rate': 2.1244390512293878e-07, 'epoch': 0.94}
+
94%|█████████▎| 11190/11952 [3:24:15<1:15:21, 5.93s/it]
94%|█████████▎| 11191/11952 [3:24:21<1:15:06, 5.92s/it]
{'loss': 0.4626, 'learning_rate': 2.1188865169303852e-07, 'epoch': 0.94}
+
94%|█████████▎| 11191/11952 [3:24:21<1:15:06, 5.92s/it]
94%|█████████▎| 11192/11952 [3:24:27<1:14:00, 5.84s/it]
{'loss': 0.4547, 'learning_rate': 2.1133411706132368e-07, 'epoch': 0.94}
+
94%|█████████▎| 11192/11952 [3:24:27<1:14:00, 5.84s/it]
94%|█████████▎| 11193/11952 [3:24:33<1:13:29, 5.81s/it]
{'loss': 0.4508, 'learning_rate': 2.1078030126851833e-07, 'epoch': 0.94}
+
94%|█████████▎| 11193/11952 [3:24:33<1:13:29, 5.81s/it]
94%|█████████▎| 11194/11952 [3:24:39<1:13:18, 5.80s/it]
{'loss': 0.4558, 'learning_rate': 2.1022720435529109e-07, 'epoch': 0.94}
+
94%|█████████▎| 11194/11952 [3:24:39<1:13:18, 5.80s/it]
94%|█████████▎| 11195/11952 [3:24:45<1:14:43, 5.92s/it]
{'loss': 0.4591, 'learning_rate': 2.0967482636225723e-07, 'epoch': 0.94}
+
94%|█████████▎| 11195/11952 [3:24:45<1:14:43, 5.92s/it]
94%|█████████▎| 11196/11952 [3:24:51<1:14:18, 5.90s/it]
{'loss': 0.4874, 'learning_rate': 2.0912316732998538e-07, 'epoch': 0.94}
+
94%|█████████▎| 11196/11952 [3:24:51<1:14:18, 5.90s/it]
94%|█████████▎| 11197/11952 [3:24:56<1:13:51, 5.87s/it]
{'loss': 0.4589, 'learning_rate': 2.0857222729898429e-07, 'epoch': 0.94}
+
94%|█████████▎| 11197/11952 [3:24:56<1:13:51, 5.87s/it]
94%|█████████▎| 11198/11952 [3:25:02<1:13:07, 5.82s/it]
{'loss': 0.4498, 'learning_rate': 2.0802200630971382e-07, 'epoch': 0.94}
+
94%|█████████▎| 11198/11952 [3:25:02<1:13:07, 5.82s/it]
94%|█████████▎| 11199/11952 [3:25:08<1:12:37, 5.79s/it]
{'loss': 0.4682, 'learning_rate': 2.0747250440257715e-07, 'epoch': 0.94}
+
94%|█████████▎| 11199/11952 [3:25:08<1:12:37, 5.79s/it]5 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
94%|█████████▎| 11200/11952 [3:25:13<1:12:17, 5.77s/it]1 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4665, 'learning_rate': 2.0692372161793094e-07, 'epoch': 0.94}
+
94%|█████████▎| 11200/11952 [3:25:13<1:12:17, 5.77s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11200/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11200/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11200/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
94%|█████████▎| 11201/11952 [3:25:43<2:43:11, 13.04s/it]
{'loss': 0.4639, 'learning_rate': 2.0637565799607517e-07, 'epoch': 0.94}
+
94%|█████████▎| 11201/11952 [3:25:43<2:43:11, 13.04s/it]
94%|█████████▎| 11202/11952 [3:25:49<2:16:26, 10.92s/it]
{'loss': 0.4561, 'learning_rate': 2.0582831357725542e-07, 'epoch': 0.94}
+
94%|█████████▎| 11202/11952 [3:25:49<2:16:26, 10.92s/it]
94%|█████████▎| 11203/11952 [3:25:55<1:57:14, 9.39s/it]
{'loss': 0.4466, 'learning_rate': 2.052816884016673e-07, 'epoch': 0.94}
+
94%|█████████▎| 11203/11952 [3:25:55<1:57:14, 9.39s/it]
94%|█████████▎| 11204/11952 [3:26:01<1:43:33, 8.31s/it]
{'loss': 0.4515, 'learning_rate': 2.0473578250945315e-07, 'epoch': 0.94}
+
94%|█████████▎| 11204/11952 [3:26:01<1:43:33, 8.31s/it]
94%|█████████▍| 11205/11952 [3:26:07<1:34:47, 7.61s/it]
{'loss': 0.4653, 'learning_rate': 2.0419059594069977e-07, 'epoch': 0.94}
+
94%|█████████▍| 11205/11952 [3:26:07<1:34:47, 7.61s/it]
94%|█████████▍| 11206/11952 [3:26:13<1:29:40, 7.21s/it]
{'loss': 0.4583, 'learning_rate': 2.0364612873544632e-07, 'epoch': 0.94}
+
94%|█████████▍| 11206/11952 [3:26:13<1:29:40, 7.21s/it]
94%|█████████▍| 11207/11952 [3:26:19<1:24:34, 6.81s/it]
{'loss': 0.4565, 'learning_rate': 2.0310238093367517e-07, 'epoch': 0.94}
+
94%|█████████▍| 11207/11952 [3:26:19<1:24:34, 6.81s/it]
94%|█████████▍| 11208/11952 [3:26:25<1:20:41, 6.51s/it]
{'loss': 0.4796, 'learning_rate': 2.0255935257531668e-07, 'epoch': 0.94}
+
94%|█████████▍| 11208/11952 [3:26:25<1:20:41, 6.51s/it]
94%|█████████▍| 11209/11952 [3:26:31<1:18:07, 6.31s/it]
{'loss': 0.4641, 'learning_rate': 2.0201704370024889e-07, 'epoch': 0.94}
+
94%|█████████▍| 11209/11952 [3:26:31<1:18:07, 6.31s/it]
94%|█████████▍| 11210/11952 [3:26:37<1:16:24, 6.18s/it]
{'loss': 0.4512, 'learning_rate': 2.0147545434829664e-07, 'epoch': 0.94}
+
94%|█████████▍| 11210/11952 [3:26:37<1:16:24, 6.18s/it]
94%|█████████▍| 11211/11952 [3:26:43<1:16:16, 6.18s/it]
{'loss': 0.4543, 'learning_rate': 2.0093458455923253e-07, 'epoch': 0.94}
+
94%|█████████▍| 11211/11952 [3:26:43<1:16:16, 6.18s/it]
94%|█████████▍| 11212/11952 [3:26:49<1:14:42, 6.06s/it]
{'loss': 0.4575, 'learning_rate': 2.0039443437277483e-07, 'epoch': 0.94}
+
94%|█████████▍| 11212/11952 [3:26:49<1:14:42, 6.06s/it]
94%|█████████▍| 11213/11952 [3:26:54<1:13:17, 5.95s/it]
{'loss': 0.4808, 'learning_rate': 1.9985500382858846e-07, 'epoch': 0.94}
+
94%|█████████▍| 11213/11952 [3:26:54<1:13:17, 5.95s/it]
94%|█████████▍| 11214/11952 [3:27:00<1:12:46, 5.92s/it]
{'loss': 0.4879, 'learning_rate': 1.9931629296629062e-07, 'epoch': 0.94}
+
94%|█████████▍| 11214/11952 [3:27:00<1:12:46, 5.92s/it]
94%|█████████▍| 11215/11952 [3:27:06<1:11:51, 5.85s/it]
{'loss': 0.4643, 'learning_rate': 1.9877830182543966e-07, 'epoch': 0.94}
+
94%|█████████▍| 11215/11952 [3:27:06<1:11:51, 5.85s/it]
94%|█████████▍| 11216/11952 [3:27:12<1:12:35, 5.92s/it]
{'loss': 0.4918, 'learning_rate': 1.982410304455429e-07, 'epoch': 0.94}
+
94%|█████████▍| 11216/11952 [3:27:12<1:12:35, 5.92s/it]
94%|█████████▍| 11217/11952 [3:27:18<1:12:07, 5.89s/it]
{'loss': 0.4732, 'learning_rate': 1.977044788660576e-07, 'epoch': 0.94}
+
94%|█████████▍| 11217/11952 [3:27:18<1:12:07, 5.89s/it]
94%|█████████▍| 11218/11952 [3:27:24<1:12:32, 5.93s/it]
{'loss': 0.458, 'learning_rate': 1.9716864712638452e-07, 'epoch': 0.94}
+
94%|█████████▍| 11218/11952 [3:27:24<1:12:32, 5.93s/it]
94%|█████████▍| 11219/11952 [3:27:30<1:11:36, 5.86s/it]
{'loss': 0.4465, 'learning_rate': 1.9663353526587104e-07, 'epoch': 0.94}
+
94%|█████████▍| 11219/11952 [3:27:30<1:11:36, 5.86s/it]
94%|█████████▍| 11220/11952 [3:27:35<1:10:28, 5.78s/it]
{'loss': 0.467, 'learning_rate': 1.9609914332381797e-07, 'epoch': 0.94}
+
94%|█████████▍| 11220/11952 [3:27:35<1:10:28, 5.78s/it]
94%|█████████▍| 11221/11952 [3:27:41<1:11:15, 5.85s/it]
{'loss': 0.471, 'learning_rate': 1.9556547133946503e-07, 'epoch': 0.94}
+
94%|█████████▍| 11221/11952 [3:27:41<1:11:15, 5.85s/it]
94%|█████████▍| 11222/11952 [3:27:47<1:10:56, 5.83s/it]
{'loss': 0.4334, 'learning_rate': 1.9503251935200418e-07, 'epoch': 0.94}
+
94%|█████████▍| 11222/11952 [3:27:47<1:10:56, 5.83s/it]
94%|█████████▍| 11223/11952 [3:27:53<1:10:12, 5.78s/it]
{'loss': 0.4527, 'learning_rate': 1.9450028740057415e-07, 'epoch': 0.94}
+
94%|█████████▍| 11223/11952 [3:27:53<1:10:12, 5.78s/it]
94%|█████████▍| 11224/11952 [3:27:58<1:10:28, 5.81s/it]
{'loss': 0.4616, 'learning_rate': 1.9396877552425808e-07, 'epoch': 0.94}
+
94%|█████████▍| 11224/11952 [3:27:58<1:10:28, 5.81s/it]
94%|█████████▍| 11225/11952 [3:28:04<1:10:11, 5.79s/it]
{'loss': 0.4508, 'learning_rate': 1.9343798376208812e-07, 'epoch': 0.94}
+
94%|█████████▍| 11225/11952 [3:28:04<1:10:11, 5.79s/it]
94%|█████████▍| 11226/11952 [3:28:10<1:10:12, 5.80s/it]
{'loss': 0.4742, 'learning_rate': 1.9290791215304527e-07, 'epoch': 0.94}
+
94%|█████████▍| 11226/11952 [3:28:10<1:10:12, 5.80s/it]
94%|█████████▍| 11227/11952 [3:28:16<1:10:26, 5.83s/it]
{'loss': 0.4621, 'learning_rate': 1.92378560736054e-07, 'epoch': 0.94}
+
94%|█████████▍| 11227/11952 [3:28:16<1:10:26, 5.83s/it]
94%|█████████▍| 11228/11952 [3:28:22<1:10:06, 5.81s/it]
{'loss': 0.4577, 'learning_rate': 1.918499295499887e-07, 'epoch': 0.94}
+
94%|█████████▍| 11228/11952 [3:28:22<1:10:06, 5.81s/it]
94%|█████████▍| 11229/11952 [3:28:28<1:10:41, 5.87s/it]
{'loss': 0.4754, 'learning_rate': 1.913220186336684e-07, 'epoch': 0.94}
+
94%|█████████▍| 11229/11952 [3:28:28<1:10:41, 5.87s/it]
94%|█████████▍| 11230/11952 [3:28:34<1:10:36, 5.87s/it]
{'loss': 0.4778, 'learning_rate': 1.9079482802586314e-07, 'epoch': 0.94}
+
94%|█████████▍| 11230/11952 [3:28:34<1:10:36, 5.87s/it]
94%|█████████▍| 11231/11952 [3:28:39<1:10:22, 5.86s/it]
{'loss': 0.443, 'learning_rate': 1.9026835776528529e-07, 'epoch': 0.94}
+
94%|█████████▍| 11231/11952 [3:28:39<1:10:22, 5.86s/it]
94%|█████████▍| 11232/11952 [3:28:45<1:10:27, 5.87s/it]
{'loss': 0.4614, 'learning_rate': 1.897426078905984e-07, 'epoch': 0.94}
+
94%|█████████▍| 11232/11952 [3:28:45<1:10:27, 5.87s/it]
94%|█████████▍| 11233/11952 [3:28:51<1:10:47, 5.91s/it]
{'loss': 0.4567, 'learning_rate': 1.8921757844040821e-07, 'epoch': 0.94}
+
94%|█████████▍| 11233/11952 [3:28:51<1:10:47, 5.91s/it]
94%|█████████▍| 11234/11952 [3:28:57<1:10:43, 5.91s/it]
{'loss': 0.4597, 'learning_rate': 1.8869326945327505e-07, 'epoch': 0.94}
+
94%|█████████▍| 11234/11952 [3:28:57<1:10:43, 5.91s/it]
94%|█████████▍| 11235/11952 [3:29:03<1:10:29, 5.90s/it]
{'loss': 0.4536, 'learning_rate': 1.8816968096769917e-07, 'epoch': 0.94}
+
94%|█████████▍| 11235/11952 [3:29:03<1:10:29, 5.90s/it]
94%|█████████▍| 11236/11952 [3:29:09<1:10:26, 5.90s/it]
{'loss': 0.4508, 'learning_rate': 1.8764681302213096e-07, 'epoch': 0.94}
+
94%|█████████▍| 11236/11952 [3:29:09<1:10:26, 5.90s/it]
94%|█████████▍| 11237/11952 [3:29:15<1:11:08, 5.97s/it]
{'loss': 0.4729, 'learning_rate': 1.8712466565496966e-07, 'epoch': 0.94}
+
94%|█████████▍| 11237/11952 [3:29:15<1:11:08, 5.97s/it]
94%|█████████▍| 11238/11952 [3:29:21<1:11:11, 5.98s/it]
{'loss': 0.4623, 'learning_rate': 1.866032389045569e-07, 'epoch': 0.94}
+
94%|█████████▍| 11238/11952 [3:29:21<1:11:11, 5.98s/it]
94%|█████████▍| 11239/11952 [3:29:27<1:09:49, 5.88s/it]
{'loss': 0.4619, 'learning_rate': 1.860825328091853e-07, 'epoch': 0.94}
+
94%|█████████▍| 11239/11952 [3:29:27<1:09:49, 5.88s/it]
94%|█████████▍| 11240/11952 [3:29:33<1:09:35, 5.87s/it]
{'loss': 0.4518, 'learning_rate': 1.8556254740709322e-07, 'epoch': 0.94}
+
94%|█████████▍| 11240/11952 [3:29:33<1:09:35, 5.87s/it]
94%|█████████▍| 11241/11952 [3:29:39<1:09:38, 5.88s/it]
{'loss': 0.4522, 'learning_rate': 1.8504328273646676e-07, 'epoch': 0.94}
+
94%|█████████▍| 11241/11952 [3:29:39<1:09:38, 5.88s/it]
94%|█████████▍| 11242/11952 [3:29:44<1:09:51, 5.90s/it]
{'loss': 0.4689, 'learning_rate': 1.8452473883543876e-07, 'epoch': 0.94}
+
94%|█████████▍| 11242/11952 [3:29:44<1:09:51, 5.90s/it]
94%|█████████▍| 11243/11952 [3:29:51<1:10:21, 5.95s/it]
{'loss': 0.4826, 'learning_rate': 1.8400691574208763e-07, 'epoch': 0.94}
+
94%|█████████▍| 11243/11952 [3:29:51<1:10:21, 5.95s/it]
94%|█████████▍| 11244/11952 [3:29:57<1:10:46, 6.00s/it]
{'loss': 0.4514, 'learning_rate': 1.8348981349444073e-07, 'epoch': 0.94}
+
94%|█████████▍| 11244/11952 [3:29:57<1:10:46, 6.00s/it]
94%|█████████▍| 11245/11952 [3:30:03<1:10:21, 5.97s/it]
{'loss': 0.4614, 'learning_rate': 1.8297343213047215e-07, 'epoch': 0.94}
+
94%|█████████▍| 11245/11952 [3:30:03<1:10:21, 5.97s/it]
94%|█████████▍| 11246/11952 [3:30:08<1:09:38, 5.92s/it]
{'loss': 0.4789, 'learning_rate': 1.8245777168810264e-07, 'epoch': 0.94}
+
94%|█████████▍| 11246/11952 [3:30:08<1:09:38, 5.92s/it]
94%|█████████▍| 11247/11952 [3:30:14<1:09:37, 5.93s/it]
{'loss': 0.4497, 'learning_rate': 1.8194283220519972e-07, 'epoch': 0.94}
+
94%|█████████▍| 11247/11952 [3:30:14<1:09:37, 5.93s/it]
94%|█████████▍| 11248/11952 [3:30:20<1:09:16, 5.90s/it]
{'loss': 0.4716, 'learning_rate': 1.8142861371957866e-07, 'epoch': 0.94}
+
94%|█████████▍| 11248/11952 [3:30:20<1:09:16, 5.90s/it]
94%|█████████▍| 11249/11952 [3:30:26<1:08:26, 5.84s/it]
{'loss': 0.4514, 'learning_rate': 1.809151162690026e-07, 'epoch': 0.94}
+
94%|█████████▍| 11249/11952 [3:30:26<1:08:26, 5.84s/it]5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...3 AutoResumeHook: Checking whether to suspend...
+
+2 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
94%|█████████▍| 11250/11952 [3:30:32<1:08:17, 5.84s/it]
{'loss': 0.4515, 'learning_rate': 1.8040233989117915e-07, 'epoch': 0.94}
+
94%|█████████▍| 11250/11952 [3:30:32<1:08:17, 5.84s/it]
94%|█████████▍| 11251/11952 [3:30:38<1:09:07, 5.92s/it]
{'loss': 0.4727, 'learning_rate': 1.79890284623766e-07, 'epoch': 0.94}
+
94%|█████████▍| 11251/11952 [3:30:38<1:09:07, 5.92s/it]
94%|█████████▍| 11252/11952 [3:30:44<1:08:21, 5.86s/it]
{'loss': 0.4491, 'learning_rate': 1.7937895050436528e-07, 'epoch': 0.94}
+
94%|█████████▍| 11252/11952 [3:30:44<1:08:21, 5.86s/it]
94%|█████████▍| 11253/11952 [3:30:49<1:07:27, 5.79s/it]
{'loss': 0.4514, 'learning_rate': 1.7886833757052692e-07, 'epoch': 0.94}
+
94%|█████████▍| 11253/11952 [3:30:49<1:07:27, 5.79s/it]
94%|█████████▍| 11254/11952 [3:30:55<1:07:07, 5.77s/it]
{'loss': 0.4681, 'learning_rate': 1.783584458597476e-07, 'epoch': 0.94}
+
94%|█████████▍| 11254/11952 [3:30:55<1:07:07, 5.77s/it]
94%|█████████▍| 11255/11952 [3:31:01<1:07:38, 5.82s/it]
{'loss': 0.4641, 'learning_rate': 1.7784927540947406e-07, 'epoch': 0.94}
+
94%|█████████▍| 11255/11952 [3:31:01<1:07:38, 5.82s/it]
94%|█████████▍| 11256/11952 [3:31:07<1:07:09, 5.79s/it]
{'loss': 0.4511, 'learning_rate': 1.7734082625709637e-07, 'epoch': 0.94}
+
94%|█████████▍| 11256/11952 [3:31:07<1:07:09, 5.79s/it]
94%|█████████▍| 11257/11952 [3:31:12<1:07:29, 5.83s/it]
{'loss': 0.4866, 'learning_rate': 1.7683309843995245e-07, 'epoch': 0.94}
+
94%|█████████▍| 11257/11952 [3:31:12<1:07:29, 5.83s/it]
94%|█████████▍| 11258/11952 [3:31:18<1:07:28, 5.83s/it]
{'loss': 0.4605, 'learning_rate': 1.76326091995328e-07, 'epoch': 0.94}
+
94%|█████████▍| 11258/11952 [3:31:18<1:07:28, 5.83s/it]
94%|█████████▍| 11259/11952 [3:31:24<1:07:53, 5.88s/it]
{'loss': 0.4512, 'learning_rate': 1.7581980696045665e-07, 'epoch': 0.94}
+
94%|█████████▍| 11259/11952 [3:31:24<1:07:53, 5.88s/it]
94%|█████████▍| 11260/11952 [3:31:30<1:08:52, 5.97s/it]
{'loss': 0.4494, 'learning_rate': 1.7531424337251523e-07, 'epoch': 0.94}
+
94%|█████████▍| 11260/11952 [3:31:30<1:08:52, 5.97s/it]
94%|█████████▍| 11261/11952 [3:31:36<1:08:08, 5.92s/it]
{'loss': 0.4466, 'learning_rate': 1.74809401268633e-07, 'epoch': 0.94}
+
94%|█████████▍| 11261/11952 [3:31:36<1:08:08, 5.92s/it]
94%|█████████▍| 11262/11952 [3:31:42<1:07:44, 5.89s/it]
{'loss': 0.4511, 'learning_rate': 1.7430528068588136e-07, 'epoch': 0.94}
+
94%|█████████▍| 11262/11952 [3:31:42<1:07:44, 5.89s/it]
94%|█████████▍| 11263/11952 [3:31:48<1:07:35, 5.89s/it]
{'loss': 0.4694, 'learning_rate': 1.73801881661283e-07, 'epoch': 0.94}
+
94%|█████████▍| 11263/11952 [3:31:48<1:07:35, 5.89s/it]
94%|█████████▍| 11264/11952 [3:31:54<1:07:02, 5.85s/it]
{'loss': 0.4656, 'learning_rate': 1.732992042318038e-07, 'epoch': 0.94}
+
94%|█████████▍| 11264/11952 [3:31:54<1:07:02, 5.85s/it]
94%|█████████▍| 11265/11952 [3:32:00<1:07:15, 5.87s/it]
{'loss': 0.4696, 'learning_rate': 1.7279724843435874e-07, 'epoch': 0.94}
+
94%|█████████▍| 11265/11952 [3:32:00<1:07:15, 5.87s/it]
94%|█████████▍| 11266/11952 [3:32:06<1:07:47, 5.93s/it]
{'loss': 0.4668, 'learning_rate': 1.7229601430580832e-07, 'epoch': 0.94}
+
94%|█████████▍| 11266/11952 [3:32:06<1:07:47, 5.93s/it]
94%|█████████▍| 11267/11952 [3:32:12<1:08:10, 5.97s/it]
{'loss': 0.4587, 'learning_rate': 1.7179550188296313e-07, 'epoch': 0.94}
+
94%|█████████▍| 11267/11952 [3:32:12<1:08:10, 5.97s/it]
94%|█████████▍| 11268/11952 [3:32:17<1:06:37, 5.84s/it]
{'loss': 0.4508, 'learning_rate': 1.7129571120257705e-07, 'epoch': 0.94}
+
94%|█████████▍| 11268/11952 [3:32:17<1:06:37, 5.84s/it]
94%|█████████▍| 11269/11952 [3:32:23<1:07:01, 5.89s/it]
{'loss': 0.4877, 'learning_rate': 1.7079664230135406e-07, 'epoch': 0.94}
+
94%|█████████▍| 11269/11952 [3:32:23<1:07:01, 5.89s/it]
94%|█████████▍| 11270/11952 [3:32:29<1:06:08, 5.82s/it]
{'loss': 0.4431, 'learning_rate': 1.7029829521594265e-07, 'epoch': 0.94}
+
94%|█████████▍| 11270/11952 [3:32:29<1:06:08, 5.82s/it]
94%|█████████▍| 11271/11952 [3:32:35<1:06:06, 5.83s/it]
{'loss': 0.4604, 'learning_rate': 1.698006699829402e-07, 'epoch': 0.94}
+
94%|█████████▍| 11271/11952 [3:32:35<1:06:06, 5.83s/it]
94%|█████████▍| 11272/11952 [3:32:40<1:05:15, 5.76s/it]
{'loss': 0.4764, 'learning_rate': 1.693037666388886e-07, 'epoch': 0.94}
+
94%|█████████▍| 11272/11952 [3:32:40<1:05:15, 5.76s/it]
94%|█████████▍| 11273/11952 [3:32:46<1:05:09, 5.76s/it]
{'loss': 0.449, 'learning_rate': 1.6880758522028083e-07, 'epoch': 0.94}
+
94%|█████████▍| 11273/11952 [3:32:46<1:05:09, 5.76s/it]
94%|█████████▍| 11274/11952 [3:32:52<1:06:44, 5.91s/it]
{'loss': 0.4654, 'learning_rate': 1.6831212576355116e-07, 'epoch': 0.94}
+
94%|█████████▍| 11274/11952 [3:32:52<1:06:44, 5.91s/it]
94%|█████████▍| 11275/11952 [3:32:59<1:07:21, 5.97s/it]
{'loss': 0.4697, 'learning_rate': 1.6781738830508708e-07, 'epoch': 0.94}
+
94%|█████████▍| 11275/11952 [3:32:59<1:07:21, 5.97s/it]
94%|█████████▍| 11276/11952 [3:33:04<1:06:54, 5.94s/it]
{'loss': 0.4456, 'learning_rate': 1.6732337288121848e-07, 'epoch': 0.94}
+
94%|█████████▍| 11276/11952 [3:33:04<1:06:54, 5.94s/it]
94%|█████████▍| 11277/11952 [3:33:10<1:06:51, 5.94s/it]
{'loss': 0.4683, 'learning_rate': 1.6683007952822405e-07, 'epoch': 0.94}
+
94%|█████████▍| 11277/11952 [3:33:10<1:06:51, 5.94s/it]
94%|█████████▍| 11278/11952 [3:33:17<1:07:41, 6.03s/it]
{'loss': 0.4491, 'learning_rate': 1.663375082823293e-07, 'epoch': 0.94}
+
94%|█████████▍| 11278/11952 [3:33:17<1:07:41, 6.03s/it]
94%|█████████▍| 11279/11952 [3:33:22<1:07:04, 5.98s/it]
{'loss': 0.4488, 'learning_rate': 1.658456591797075e-07, 'epoch': 0.94}
+
94%|█████████▍| 11279/11952 [3:33:22<1:07:04, 5.98s/it]
94%|█████████▍| 11280/11952 [3:33:28<1:06:47, 5.96s/it]
{'loss': 0.4635, 'learning_rate': 1.6535453225647645e-07, 'epoch': 0.94}
+
94%|█████████▍| 11280/11952 [3:33:28<1:06:47, 5.96s/it]
94%|█████████▍| 11281/11952 [3:33:35<1:07:50, 6.07s/it]
{'loss': 0.4656, 'learning_rate': 1.6486412754870286e-07, 'epoch': 0.94}
+
94%|█████████▍| 11281/11952 [3:33:35<1:07:50, 6.07s/it]
94%|█████████▍| 11282/11952 [3:33:41<1:07:41, 6.06s/it]
{'loss': 0.489, 'learning_rate': 1.643744450924012e-07, 'epoch': 0.94}
+
94%|█████████▍| 11282/11952 [3:33:41<1:07:41, 6.06s/it]
94%|█████████▍| 11283/11952 [3:33:47<1:08:43, 6.16s/it]
{'loss': 0.4561, 'learning_rate': 1.638854849235305e-07, 'epoch': 0.94}
+
94%|█████████▍| 11283/11952 [3:33:47<1:08:43, 6.16s/it]
94%|█████████▍| 11284/11952 [3:33:53<1:07:45, 6.09s/it]
{'loss': 0.458, 'learning_rate': 1.6339724707799875e-07, 'epoch': 0.94}
+
94%|█████████▍| 11284/11952 [3:33:53<1:07:45, 6.09s/it]
94%|█████████▍| 11285/11952 [3:33:59<1:06:58, 6.03s/it]
{'loss': 0.4563, 'learning_rate': 1.6290973159165945e-07, 'epoch': 0.94}
+
94%|█████████▍| 11285/11952 [3:33:59<1:06:58, 6.03s/it]
94%|█████████▍| 11286/11952 [3:34:05<1:05:30, 5.90s/it]
{'loss': 0.4512, 'learning_rate': 1.62422938500314e-07, 'epoch': 0.94}
+
94%|█████████▍| 11286/11952 [3:34:05<1:05:30, 5.90s/it]
94%|█████████▍| 11287/11952 [3:34:10<1:04:49, 5.85s/it]
{'loss': 0.4662, 'learning_rate': 1.619368678397093e-07, 'epoch': 0.94}
+
94%|█████████▍| 11287/11952 [3:34:10<1:04:49, 5.85s/it]
94%|█████████▍| 11288/11952 [3:34:16<1:05:07, 5.89s/it]
{'loss': 0.4656, 'learning_rate': 1.614515196455424e-07, 'epoch': 0.94}
+
94%|█████████▍| 11288/11952 [3:34:16<1:05:07, 5.89s/it]
94%|█████████▍| 11289/11952 [3:34:22<1:05:05, 5.89s/it]
{'loss': 0.4872, 'learning_rate': 1.6096689395345366e-07, 'epoch': 0.94}
+
94%|█████████▍| 11289/11952 [3:34:22<1:05:05, 5.89s/it]
94%|█████████▍| 11290/11952 [3:34:28<1:04:51, 5.88s/it]
{'loss': 0.4777, 'learning_rate': 1.604829907990335e-07, 'epoch': 0.94}
+
94%|█████████▍| 11290/11952 [3:34:28<1:04:51, 5.88s/it]
94%|█████████▍| 11291/11952 [3:34:34<1:05:23, 5.94s/it]
{'loss': 0.4589, 'learning_rate': 1.5999981021781685e-07, 'epoch': 0.94}
+
94%|█████████▍| 11291/11952 [3:34:34<1:05:23, 5.94s/it]
94%|█████████▍| 11292/11952 [3:34:40<1:05:38, 5.97s/it]
{'loss': 0.4641, 'learning_rate': 1.595173522452864e-07, 'epoch': 0.94}
+
94%|█████████▍| 11292/11952 [3:34:40<1:05:38, 5.97s/it]
94%|█████████▍| 11293/11952 [3:34:46<1:05:13, 5.94s/it]
{'loss': 0.4715, 'learning_rate': 1.5903561691687164e-07, 'epoch': 0.94}
+
94%|█████████▍| 11293/11952 [3:34:46<1:05:13, 5.94s/it]
94%|█████████▍| 11294/11952 [3:34:52<1:04:39, 5.90s/it]
{'loss': 0.446, 'learning_rate': 1.5855460426794865e-07, 'epoch': 0.94}
+
94%|█████████▍| 11294/11952 [3:34:52<1:04:39, 5.90s/it]
95%|█████████▍| 11295/11952 [3:34:57<1:03:56, 5.84s/it]
{'loss': 0.4725, 'learning_rate': 1.5807431433384368e-07, 'epoch': 0.94}
+
95%|█████████▍| 11295/11952 [3:34:57<1:03:56, 5.84s/it]
95%|█████████▍| 11296/11952 [3:35:03<1:03:27, 5.80s/it]
{'loss': 0.4727, 'learning_rate': 1.5759474714982405e-07, 'epoch': 0.95}
+
95%|█████████▍| 11296/11952 [3:35:03<1:03:27, 5.80s/it]
95%|█████████▍| 11297/11952 [3:35:10<1:05:41, 6.02s/it]
{'loss': 0.4476, 'learning_rate': 1.5711590275110933e-07, 'epoch': 0.95}
+
95%|█████████▍| 11297/11952 [3:35:10<1:05:41, 6.02s/it]
95%|█████████▍| 11298/11952 [3:35:15<1:04:49, 5.95s/it]
{'loss': 0.4618, 'learning_rate': 1.5663778117286254e-07, 'epoch': 0.95}
+
95%|█████████▍| 11298/11952 [3:35:15<1:04:49, 5.95s/it]
95%|█████████▍| 11299/11952 [3:35:22<1:05:29, 6.02s/it]
{'loss': 0.4643, 'learning_rate': 1.561603824501956e-07, 'epoch': 0.95}
+
95%|█████████▍| 11299/11952 [3:35:22<1:05:29, 6.02s/it]2 AutoResumeHook: Checking whether to suspend...
+3 5AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
95%|█████████▍| 11300/11952 [3:35:28<1:04:52, 5.97s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4793, 'learning_rate': 1.5568370661816713e-07, 'epoch': 0.95}
+
95%|█████████▍| 11300/11952 [3:35:28<1:04:52, 5.97s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11300/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11300/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11300/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
95%|█████████▍| 11301/11952 [3:35:58<2:23:07, 13.19s/it]
{'loss': 0.4569, 'learning_rate': 1.552077537117802e-07, 'epoch': 0.95}
+
95%|█████████▍| 11301/11952 [3:35:58<2:23:07, 13.19s/it]
95%|█████████▍| 11302/11952 [3:36:04<2:00:15, 11.10s/it]
{'loss': 0.4629, 'learning_rate': 1.5473252376598913e-07, 'epoch': 0.95}
+
95%|█████████▍| 11302/11952 [3:36:04<2:00:15, 11.10s/it]
95%|█████████▍| 11303/11952 [3:36:10<1:43:16, 9.55s/it]
{'loss': 0.4617, 'learning_rate': 1.5425801681569263e-07, 'epoch': 0.95}
+
95%|█████████▍| 11303/11952 [3:36:10<1:43:16, 9.55s/it]
95%|█████████▍| 11304/11952 [3:36:16<1:31:02, 8.43s/it]
{'loss': 0.4613, 'learning_rate': 1.5378423289573508e-07, 'epoch': 0.95}
+
95%|█████████▍| 11304/11952 [3:36:16<1:31:02, 8.43s/it]
95%|█████████▍| 11305/11952 [3:36:21<1:22:29, 7.65s/it]
{'loss': 0.45, 'learning_rate': 1.5331117204091085e-07, 'epoch': 0.95}
+
95%|█████████▍| 11305/11952 [3:36:21<1:22:29, 7.65s/it]
95%|█████████▍| 11306/11952 [3:36:27<1:16:56, 7.15s/it]
{'loss': 0.4758, 'learning_rate': 1.528388342859577e-07, 'epoch': 0.95}
+
95%|█████████▍| 11306/11952 [3:36:27<1:16:56, 7.15s/it]
95%|█████████▍| 11307/11952 [3:36:33<1:13:07, 6.80s/it]
{'loss': 0.4927, 'learning_rate': 1.5236721966556456e-07, 'epoch': 0.95}
+
95%|█████████▍| 11307/11952 [3:36:33<1:13:07, 6.80s/it]
95%|█████████▍| 11308/11952 [3:36:39<1:09:48, 6.50s/it]
{'loss': 0.4616, 'learning_rate': 1.518963282143615e-07, 'epoch': 0.95}
+
95%|█████████▍| 11308/11952 [3:36:39<1:09:48, 6.50s/it]
95%|█████████▍| 11309/11952 [3:36:45<1:08:20, 6.38s/it]
{'loss': 0.4713, 'learning_rate': 1.5142615996693087e-07, 'epoch': 0.95}
+
95%|█████████▍| 11309/11952 [3:36:45<1:08:20, 6.38s/it]
95%|█████████▍| 11310/11952 [3:36:51<1:07:07, 6.27s/it]
{'loss': 0.4613, 'learning_rate': 1.5095671495780062e-07, 'epoch': 0.95}
+
95%|█████████▍| 11310/11952 [3:36:51<1:07:07, 6.27s/it]
95%|█████████▍| 11311/11952 [3:36:57<1:05:33, 6.14s/it]
{'loss': 0.4549, 'learning_rate': 1.5048799322144426e-07, 'epoch': 0.95}
+
95%|█████████▍| 11311/11952 [3:36:57<1:05:33, 6.14s/it]
95%|█████████▍| 11312/11952 [3:37:03<1:05:32, 6.14s/it]
{'loss': 0.459, 'learning_rate': 1.5001999479228203e-07, 'epoch': 0.95}
+
95%|█████████▍| 11312/11952 [3:37:03<1:05:32, 6.14s/it]
95%|█████████▍| 11313/11952 [3:37:09<1:04:15, 6.03s/it]
{'loss': 0.4595, 'learning_rate': 1.49552719704682e-07, 'epoch': 0.95}
+
95%|█████████▍| 11313/11952 [3:37:09<1:04:15, 6.03s/it]
95%|█████████▍| 11314/11952 [3:37:15<1:02:52, 5.91s/it]
{'loss': 0.4503, 'learning_rate': 1.4908616799296006e-07, 'epoch': 0.95}
+
95%|█████████▍| 11314/11952 [3:37:15<1:02:52, 5.91s/it]
95%|█████████▍| 11315/11952 [3:37:20<1:01:39, 5.81s/it]
{'loss': 0.4753, 'learning_rate': 1.4862033969137545e-07, 'epoch': 0.95}
+
95%|█████████▍| 11315/11952 [3:37:20<1:01:39, 5.81s/it]
95%|█████████▍| 11316/11952 [3:37:27<1:03:37, 6.00s/it]
{'loss': 0.4399, 'learning_rate': 1.4815523483413864e-07, 'epoch': 0.95}
+
95%|█████████▍| 11316/11952 [3:37:27<1:03:37, 6.00s/it]
95%|█████████▍| 11317/11952 [3:37:33<1:03:59, 6.05s/it]
{'loss': 0.4847, 'learning_rate': 1.4769085345540556e-07, 'epoch': 0.95}
+
95%|█████████▍| 11317/11952 [3:37:33<1:03:59, 6.05s/it]
95%|█████████▍| 11318/11952 [3:37:39<1:03:23, 6.00s/it]
{'loss': 0.4602, 'learning_rate': 1.472271955892768e-07, 'epoch': 0.95}
+
95%|█████████▍| 11318/11952 [3:37:39<1:03:23, 6.00s/it]
95%|█████████▍| 11319/11952 [3:37:44<1:02:29, 5.92s/it]
{'loss': 0.4709, 'learning_rate': 1.4676426126980058e-07, 'epoch': 0.95}
+
95%|█████████▍| 11319/11952 [3:37:44<1:02:29, 5.92s/it]
95%|█████████▍| 11320/11952 [3:37:50<1:02:33, 5.94s/it]
{'loss': 0.4564, 'learning_rate': 1.4630205053097645e-07, 'epoch': 0.95}
+
95%|█████████▍| 11320/11952 [3:37:50<1:02:33, 5.94s/it]
95%|█████████▍| 11321/11952 [3:37:56<1:02:23, 5.93s/it]
{'loss': 0.4561, 'learning_rate': 1.4584056340674392e-07, 'epoch': 0.95}
+
95%|█████████▍| 11321/11952 [3:37:56<1:02:23, 5.93s/it]
95%|█████████▍| 11322/11952 [3:38:02<1:02:39, 5.97s/it]
{'loss': 0.4634, 'learning_rate': 1.4537979993099361e-07, 'epoch': 0.95}
+
95%|█████████▍| 11322/11952 [3:38:02<1:02:39, 5.97s/it]
95%|█████████▍| 11323/11952 [3:38:08<1:02:15, 5.94s/it]
{'loss': 0.462, 'learning_rate': 1.4491976013756292e-07, 'epoch': 0.95}
+
95%|█████████▍| 11323/11952 [3:38:08<1:02:15, 5.94s/it]
95%|█████████▍| 11324/11952 [3:38:14<1:01:13, 5.85s/it]
{'loss': 0.4504, 'learning_rate': 1.4446044406023485e-07, 'epoch': 0.95}
+
95%|█████████▍| 11324/11952 [3:38:14<1:01:13, 5.85s/it]
95%|█████████▍| 11325/11952 [3:38:20<1:00:53, 5.83s/it]
{'loss': 0.4507, 'learning_rate': 1.4400185173274018e-07, 'epoch': 0.95}
+
95%|█████████▍| 11325/11952 [3:38:20<1:00:53, 5.83s/it]
95%|█████████▍| 11326/11952 [3:38:25<1:00:46, 5.83s/it]
{'loss': 0.4674, 'learning_rate': 1.4354398318875417e-07, 'epoch': 0.95}
+
95%|█████████▍| 11326/11952 [3:38:25<1:00:46, 5.83s/it]
95%|█████████▍| 11327/11952 [3:38:31<1:00:37, 5.82s/it]
{'loss': 0.4756, 'learning_rate': 1.430868384619022e-07, 'epoch': 0.95}
+
95%|█████████▍| 11327/11952 [3:38:31<1:00:37, 5.82s/it]
95%|█████████▍| 11328/11952 [3:38:37<1:00:39, 5.83s/it]
{'loss': 0.4396, 'learning_rate': 1.4263041758575402e-07, 'epoch': 0.95}
+
95%|█████████▍| 11328/11952 [3:38:37<1:00:39, 5.83s/it]
95%|█████████▍| 11329/11952 [3:38:43<1:01:49, 5.95s/it]
{'loss': 0.464, 'learning_rate': 1.4217472059382952e-07, 'epoch': 0.95}
+
95%|█████████▍| 11329/11952 [3:38:43<1:01:49, 5.95s/it]
95%|█████████▍| 11330/11952 [3:38:49<1:01:03, 5.89s/it]
{'loss': 0.4678, 'learning_rate': 1.4171974751959082e-07, 'epoch': 0.95}
+
95%|█████████▍| 11330/11952 [3:38:49<1:01:03, 5.89s/it]
95%|█████████▍| 11331/11952 [3:38:55<1:00:41, 5.86s/it]
{'loss': 0.4847, 'learning_rate': 1.4126549839645009e-07, 'epoch': 0.95}
+
95%|█████████▍| 11331/11952 [3:38:55<1:00:41, 5.86s/it]
95%|█████████▍| 11332/11952 [3:39:01<59:55, 5.80s/it]
{'loss': 0.4553, 'learning_rate': 1.408119732577662e-07, 'epoch': 0.95}
+
95%|█████████▍| 11332/11952 [3:39:01<59:55, 5.80s/it]
95%|█████████▍| 11333/11952 [3:39:07<1:00:18, 5.85s/it]
{'loss': 0.4686, 'learning_rate': 1.4035917213684358e-07, 'epoch': 0.95}
+
95%|█████████▍| 11333/11952 [3:39:07<1:00:18, 5.85s/it]
95%|█████████▍| 11334/11952 [3:39:12<59:48, 5.81s/it]
{'loss': 0.4596, 'learning_rate': 1.3990709506693457e-07, 'epoch': 0.95}
+
95%|█████████▍| 11334/11952 [3:39:12<59:48, 5.81s/it]
95%|█████████▍| 11335/11952 [3:39:18<59:24, 5.78s/it]
{'loss': 0.443, 'learning_rate': 1.394557420812359e-07, 'epoch': 0.95}
+
95%|█████████▍| 11335/11952 [3:39:18<59:24, 5.78s/it]
95%|█████████▍| 11336/11952 [3:39:24<59:18, 5.78s/it]
{'loss': 0.4613, 'learning_rate': 1.3900511321289557e-07, 'epoch': 0.95}
+
95%|█████████▍| 11336/11952 [3:39:24<59:18, 5.78s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (4901 > 4096). Running this sequence through the model will result in indexing errors
+
95%|█████████▍| 11337/11952 [3:39:30<59:31, 5.81s/it]
{'loss': 0.4579, 'learning_rate': 1.385552084950037e-07, 'epoch': 0.95}
+
95%|█████████▍| 11337/11952 [3:39:30<59:31, 5.81s/it]
95%|█████████▍| 11338/11952 [3:39:35<59:20, 5.80s/it]
{'loss': 0.4549, 'learning_rate': 1.381060279606017e-07, 'epoch': 0.95}
+
95%|█████████▍| 11338/11952 [3:39:35<59:20, 5.80s/it]
95%|█████████▍| 11339/11952 [3:39:41<59:04, 5.78s/it]
{'loss': 0.4551, 'learning_rate': 1.3765757164267313e-07, 'epoch': 0.95}
+
95%|█████████▍| 11339/11952 [3:39:41<59:04, 5.78s/it]
95%|█████████▍| 11340/11952 [3:39:47<1:00:01, 5.88s/it]
{'loss': 0.4749, 'learning_rate': 1.3720983957415278e-07, 'epoch': 0.95}
+
95%|█████████▍| 11340/11952 [3:39:47<1:00:01, 5.88s/it]
95%|█████████▍| 11341/11952 [3:39:53<59:05, 5.80s/it]
{'loss': 0.4428, 'learning_rate': 1.3676283178791882e-07, 'epoch': 0.95}
+
95%|█████████▍| 11341/11952 [3:39:53<59:05, 5.80s/it]
95%|█████████▍| 11342/11952 [3:39:59<59:22, 5.84s/it]
{'loss': 0.4797, 'learning_rate': 1.363165483167983e-07, 'epoch': 0.95}
+
95%|█████████▍| 11342/11952 [3:39:59<59:22, 5.84s/it]
95%|█████████▍| 11343/11952 [3:40:05<1:00:42, 5.98s/it]
{'loss': 0.4681, 'learning_rate': 1.35870989193565e-07, 'epoch': 0.95}
+
95%|█████████▍| 11343/11952 [3:40:05<1:00:42, 5.98s/it]
95%|█████████▍| 11344/11952 [3:40:11<1:00:48, 6.00s/it]
{'loss': 0.4495, 'learning_rate': 1.3542615445093722e-07, 'epoch': 0.95}
+
95%|█████████▍| 11344/11952 [3:40:11<1:00:48, 6.00s/it]
95%|█████████▍| 11345/11952 [3:40:17<1:00:04, 5.94s/it]
{'loss': 0.4612, 'learning_rate': 1.3498204412158434e-07, 'epoch': 0.95}
+
95%|█████████▍| 11345/11952 [3:40:17<1:00:04, 5.94s/it]
95%|█████████▍| 11346/11952 [3:40:23<59:51, 5.93s/it]
{'loss': 0.4608, 'learning_rate': 1.3453865823811696e-07, 'epoch': 0.95}
+
95%|█████████▍| 11346/11952 [3:40:23<59:51, 5.93s/it]
95%|█████████▍| 11347/11952 [3:40:29<59:45, 5.93s/it]
{'loss': 0.4477, 'learning_rate': 1.3409599683309793e-07, 'epoch': 0.95}
+
95%|█████████▍| 11347/11952 [3:40:29<59:45, 5.93s/it]
95%|█████████▍| 11348/11952 [3:40:35<59:27, 5.91s/it]
{'loss': 0.4679, 'learning_rate': 1.3365405993903347e-07, 'epoch': 0.95}
+
95%|█████████▍| 11348/11952 [3:40:35<59:27, 5.91s/it]
95%|█████████▍| 11349/11952 [3:40:40<59:03, 5.88s/it]
{'loss': 0.4465, 'learning_rate': 1.332128475883765e-07, 'epoch': 0.95}
+
95%|█████████▍| 11349/11952 [3:40:40<59:03, 5.88s/it]0 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
95%|█████████▍| 11350/11952 [3:40:47<59:46, 5.96s/it]5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4629, 'learning_rate': 1.3277235981352887e-07, 'epoch': 0.95}
+
95%|█████████▍| 11350/11952 [3:40:47<59:46, 5.96s/it]
95%|█████████▍| 11351/11952 [3:40:52<58:29, 5.84s/it]
{'loss': 0.4655, 'learning_rate': 1.3233259664683916e-07, 'epoch': 0.95}
+
95%|█████████▍| 11351/11952 [3:40:52<58:29, 5.84s/it]
95%|█████████▍| 11352/11952 [3:40:58<57:49, 5.78s/it]
{'loss': 0.4558, 'learning_rate': 1.3189355812060157e-07, 'epoch': 0.95}
+
95%|█████████▍| 11352/11952 [3:40:58<57:49, 5.78s/it]
95%|█████████▍| 11353/11952 [3:41:04<58:48, 5.89s/it]
{'loss': 0.4475, 'learning_rate': 1.314552442670558e-07, 'epoch': 0.95}
+
95%|█████████▍| 11353/11952 [3:41:04<58:48, 5.89s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
95%|█████████▍| 11354/11952 [3:41:10<59:26, 5.96s/it]
{'loss': 0.4415, 'learning_rate': 1.310176551183906e-07, 'epoch': 0.95}
+
95%|█████████▍| 11354/11952 [3:41:10<59:26, 5.96s/it]
95%|█████████▌| 11355/11952 [3:41:16<58:23, 5.87s/it]
{'loss': 0.4641, 'learning_rate': 1.3058079070674023e-07, 'epoch': 0.95}
+
95%|█████████▌| 11355/11952 [3:41:16<58:23, 5.87s/it]
95%|█████████▌| 11356/11952 [3:41:22<59:16, 5.97s/it]
{'loss': 0.4601, 'learning_rate': 1.3014465106418573e-07, 'epoch': 0.95}
+
95%|█████████▌| 11356/11952 [3:41:22<59:16, 5.97s/it]
95%|█████████▌| 11357/11952 [3:41:28<1:00:08, 6.06s/it]
{'loss': 0.4457, 'learning_rate': 1.297092362227581e-07, 'epoch': 0.95}
+
95%|█████████▌| 11357/11952 [3:41:28<1:00:08, 6.06s/it]
95%|█████████▌| 11358/11952 [3:41:34<1:00:28, 6.11s/it]
{'loss': 0.4609, 'learning_rate': 1.2927454621442959e-07, 'epoch': 0.95}
+
95%|█████████▌| 11358/11952 [3:41:34<1:00:28, 6.11s/it]
95%|█████████▌| 11359/11952 [3:41:40<59:13, 5.99s/it]
{'loss': 0.4725, 'learning_rate': 1.2884058107112353e-07, 'epoch': 0.95}
+
95%|█████████▌| 11359/11952 [3:41:40<59:13, 5.99s/it]
95%|█████████▌| 11360/11952 [3:41:46<59:10, 6.00s/it]
{'loss': 0.455, 'learning_rate': 1.2840734082470662e-07, 'epoch': 0.95}
+
95%|█████████▌| 11360/11952 [3:41:46<59:10, 6.00s/it]
95%|█████████▌| 11361/11952 [3:41:52<58:38, 5.95s/it]
{'loss': 0.453, 'learning_rate': 1.279748255069968e-07, 'epoch': 0.95}
+
95%|█████████▌| 11361/11952 [3:41:52<58:38, 5.95s/it]
95%|█████████▌| 11362/11952 [3:41:58<58:44, 5.97s/it]
{'loss': 0.4684, 'learning_rate': 1.275430351497542e-07, 'epoch': 0.95}
+
95%|█████████▌| 11362/11952 [3:41:58<58:44, 5.97s/it]
95%|█████████▌| 11363/11952 [3:42:04<58:10, 5.93s/it]
{'loss': 0.4651, 'learning_rate': 1.27111969784689e-07, 'epoch': 0.95}
+
95%|█████████▌| 11363/11952 [3:42:04<58:10, 5.93s/it]
95%|█████████▌| 11364/11952 [3:42:10<57:34, 5.87s/it]
{'loss': 0.4371, 'learning_rate': 1.2668162944345587e-07, 'epoch': 0.95}
+
95%|█████████▌| 11364/11952 [3:42:10<57:34, 5.87s/it]
95%|█████████▌| 11365/11952 [3:42:16<57:37, 5.89s/it]
{'loss': 0.4689, 'learning_rate': 1.262520141576584e-07, 'epoch': 0.95}
+
95%|█████████▌| 11365/11952 [3:42:16<57:37, 5.89s/it]
95%|█████████▌| 11366/11952 [3:42:22<58:05, 5.95s/it]
{'loss': 0.4626, 'learning_rate': 1.2582312395884476e-07, 'epoch': 0.95}
+
95%|█████████▌| 11366/11952 [3:42:22<58:05, 5.95s/it]
95%|█████████▌| 11367/11952 [3:42:28<57:51, 5.93s/it]
{'loss': 0.4517, 'learning_rate': 1.2539495887851083e-07, 'epoch': 0.95}
+
95%|█████████▌| 11367/11952 [3:42:28<57:51, 5.93s/it]
95%|█████████▌| 11368/11952 [3:42:33<57:00, 5.86s/it]
{'loss': 0.4605, 'learning_rate': 1.2496751894810032e-07, 'epoch': 0.95}
+
95%|█████████▌| 11368/11952 [3:42:33<57:00, 5.86s/it]
95%|█████████▌| 11369/11952 [3:42:39<56:56, 5.86s/it]
{'loss': 0.4645, 'learning_rate': 1.245408041990004e-07, 'epoch': 0.95}
+
95%|█████████▌| 11369/11952 [3:42:39<56:56, 5.86s/it]
95%|█████████▌| 11370/11952 [3:42:45<56:33, 5.83s/it]
{'loss': 0.4477, 'learning_rate': 1.2411481466254926e-07, 'epoch': 0.95}
+
95%|█████████▌| 11370/11952 [3:42:45<56:33, 5.83s/it]
95%|█████████▌| 11371/11952 [3:42:51<57:47, 5.97s/it]
{'loss': 0.4739, 'learning_rate': 1.2368955037002973e-07, 'epoch': 0.95}
+
95%|█████████▌| 11371/11952 [3:42:51<57:47, 5.97s/it]
95%|█████████▌| 11372/11952 [3:42:57<57:39, 5.96s/it]
{'loss': 0.4712, 'learning_rate': 1.232650113526701e-07, 'epoch': 0.95}
+
95%|█████████▌| 11372/11952 [3:42:57<57:39, 5.96s/it]
95%|█████████▌| 11373/11952 [3:43:03<58:20, 6.05s/it]
{'loss': 0.4649, 'learning_rate': 1.228411976416488e-07, 'epoch': 0.95}
+
95%|█████████▌| 11373/11952 [3:43:03<58:20, 6.05s/it]
95%|█████████▌| 11374/11952 [3:43:09<57:10, 5.94s/it]
{'loss': 0.4477, 'learning_rate': 1.2241810926808762e-07, 'epoch': 0.95}
+
95%|█████████▌| 11374/11952 [3:43:09<57:10, 5.94s/it]
95%|█████████▌| 11375/11952 [3:43:15<56:45, 5.90s/it]
{'loss': 0.4506, 'learning_rate': 1.219957462630561e-07, 'epoch': 0.95}
+
95%|█████████▌| 11375/11952 [3:43:15<56:45, 5.90s/it]
95%|█████████▌| 11376/11952 [3:43:21<56:57, 5.93s/it]
{'loss': 0.4762, 'learning_rate': 1.2157410865757057e-07, 'epoch': 0.95}
+
95%|█████████▌| 11376/11952 [3:43:21<56:57, 5.93s/it]
95%|█████████▌| 11377/11952 [3:43:27<56:20, 5.88s/it]
{'loss': 0.4677, 'learning_rate': 1.2115319648259516e-07, 'epoch': 0.95}
+
95%|█████████▌| 11377/11952 [3:43:27<56:20, 5.88s/it]
95%|█████████▌| 11378/11952 [3:43:32<55:37, 5.81s/it]
{'loss': 0.4585, 'learning_rate': 1.2073300976904067e-07, 'epoch': 0.95}
+
95%|█████████▌| 11378/11952 [3:43:32<55:37, 5.81s/it]
95%|█████████▌| 11379/11952 [3:43:38<56:09, 5.88s/it]
{'loss': 0.4589, 'learning_rate': 1.2031354854776356e-07, 'epoch': 0.95}
+
95%|█████████▌| 11379/11952 [3:43:38<56:09, 5.88s/it]
95%|█████████▌| 11380/11952 [3:43:44<55:49, 5.86s/it]
{'loss': 0.4742, 'learning_rate': 1.198948128495647e-07, 'epoch': 0.95}
+
95%|█████████▌| 11380/11952 [3:43:44<55:49, 5.86s/it]
95%|█████████▌| 11381/11952 [3:43:50<56:27, 5.93s/it]
{'loss': 0.4694, 'learning_rate': 1.1947680270519733e-07, 'epoch': 0.95}
+
95%|█████████▌| 11381/11952 [3:43:50<56:27, 5.93s/it]
95%|█████████▌| 11382/11952 [3:43:56<55:46, 5.87s/it]
{'loss': 0.4748, 'learning_rate': 1.19059518145358e-07, 'epoch': 0.95}
+
95%|█████████▌| 11382/11952 [3:43:56<55:46, 5.87s/it]
95%|█████████▌| 11383/11952 [3:44:02<55:21, 5.84s/it]
{'loss': 0.4683, 'learning_rate': 1.186429592006888e-07, 'epoch': 0.95}
+
95%|█████████▌| 11383/11952 [3:44:02<55:21, 5.84s/it]
95%|█████████▌| 11384/11952 [3:44:07<54:58, 5.81s/it]
{'loss': 0.4732, 'learning_rate': 1.1822712590178197e-07, 'epoch': 0.95}
+
95%|█████████▌| 11384/11952 [3:44:07<54:58, 5.81s/it]
95%|█████████▌| 11385/11952 [3:44:13<54:43, 5.79s/it]
{'loss': 0.4454, 'learning_rate': 1.178120182791731e-07, 'epoch': 0.95}
+
95%|█████████▌| 11385/11952 [3:44:13<54:43, 5.79s/it]
95%|█████████▌| 11386/11952 [3:44:19<54:50, 5.81s/it]
{'loss': 0.4684, 'learning_rate': 1.1739763636334667e-07, 'epoch': 0.95}
+
95%|█████████▌| 11386/11952 [3:44:19<54:50, 5.81s/it]
95%|█████████▌| 11387/11952 [3:44:25<56:17, 5.98s/it]
{'loss': 0.4555, 'learning_rate': 1.1698398018473278e-07, 'epoch': 0.95}
+
95%|█████████▌| 11387/11952 [3:44:25<56:17, 5.98s/it]
95%|█████████▌| 11388/11952 [3:44:32<56:35, 6.02s/it]
{'loss': 0.4729, 'learning_rate': 1.1657104977370937e-07, 'epoch': 0.95}
+
95%|█████████▌| 11388/11952 [3:44:32<56:35, 6.02s/it]
95%|█████████▌| 11389/11952 [3:44:37<55:32, 5.92s/it]
{'loss': 0.4459, 'learning_rate': 1.1615884516059883e-07, 'epoch': 0.95}
+
95%|█████████▌| 11389/11952 [3:44:37<55:32, 5.92s/it]
95%|█████████▌| 11390/11952 [3:44:43<54:58, 5.87s/it]
{'loss': 0.462, 'learning_rate': 1.1574736637567252e-07, 'epoch': 0.95}
+
95%|█████████▌| 11390/11952 [3:44:43<54:58, 5.87s/it]
95%|█████████▌| 11391/11952 [3:44:49<56:11, 6.01s/it]
{'loss': 0.4428, 'learning_rate': 1.1533661344914848e-07, 'epoch': 0.95}
+
95%|█████████▌| 11391/11952 [3:44:49<56:11, 6.01s/it]
95%|█████████▌| 11392/11952 [3:44:55<55:22, 5.93s/it]
{'loss': 0.4663, 'learning_rate': 1.1492658641119037e-07, 'epoch': 0.95}
+
95%|█████████▌| 11392/11952 [3:44:55<55:22, 5.93s/it]
95%|█████████▌| 11393/11952 [3:45:01<54:29, 5.85s/it]
{'loss': 0.4739, 'learning_rate': 1.1451728529190852e-07, 'epoch': 0.95}
+
95%|█████████▌| 11393/11952 [3:45:01<54:29, 5.85s/it]
95%|█████████▌| 11394/11952 [3:45:07<55:06, 5.93s/it]
{'loss': 0.4518, 'learning_rate': 1.1410871012136116e-07, 'epoch': 0.95}
+
95%|█████████▌| 11394/11952 [3:45:07<55:06, 5.93s/it]
95%|█████████▌| 11395/11952 [3:45:12<54:21, 5.86s/it]
{'loss': 0.4517, 'learning_rate': 1.137008609295509e-07, 'epoch': 0.95}
+
95%|█████████▌| 11395/11952 [3:45:12<54:21, 5.86s/it]
95%|█████████▌| 11396/11952 [3:45:18<54:15, 5.86s/it]
{'loss': 0.4603, 'learning_rate': 1.1329373774642938e-07, 'epoch': 0.95}
+
95%|█████████▌| 11396/11952 [3:45:18<54:15, 5.86s/it]
95%|█████████▌| 11397/11952 [3:45:24<54:05, 5.85s/it]
{'loss': 0.4487, 'learning_rate': 1.1288734060189267e-07, 'epoch': 0.95}
+
95%|█████████▌| 11397/11952 [3:45:24<54:05, 5.85s/it]
95%|█████████▌| 11398/11952 [3:45:30<54:36, 5.91s/it]
{'loss': 0.4477, 'learning_rate': 1.1248166952578799e-07, 'epoch': 0.95}
+
95%|█████████▌| 11398/11952 [3:45:30<54:36, 5.91s/it]
95%|█████████▌| 11399/11952 [3:45:36<54:02, 5.86s/it]
{'loss': 0.4674, 'learning_rate': 1.1207672454790264e-07, 'epoch': 0.95}
+
95%|█████████▌| 11399/11952 [3:45:36<54:02, 5.86s/it]5 AutoResumeHook: Checking whether to suspend...
+72 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
95%|█████████▌| 11400/11952 [3:45:42<53:38, 5.83s/it]3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4888, 'learning_rate': 1.1167250569797728e-07, 'epoch': 0.95}
+
95%|█████████▌| 11400/11952 [3:45:42<53:38, 5.83s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11400/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11400/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11400/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
95%|█████████▌| 11401/11952 [3:46:13<2:04:48, 13.59s/it]
{'loss': 0.4248, 'learning_rate': 1.112690130056926e-07, 'epoch': 0.95}
+
95%|█████████▌| 11401/11952 [3:46:13<2:04:48, 13.59s/it]
95%|█████████▌| 11402/11952 [3:46:19<1:43:02, 11.24s/it]
{'loss': 0.4714, 'learning_rate': 1.1086624650068267e-07, 'epoch': 0.95}
+
95%|█████████▌| 11402/11952 [3:46:19<1:43:02, 11.24s/it]
95%|█████████▌| 11403/11952 [3:46:25<1:27:46, 9.59s/it]
{'loss': 0.4564, 'learning_rate': 1.1046420621252275e-07, 'epoch': 0.95}
+
95%|█████████▌| 11403/11952 [3:46:25<1:27:46, 9.59s/it]
95%|█████████▌| 11404/11952 [3:46:31<1:16:55, 8.42s/it]
{'loss': 0.4568, 'learning_rate': 1.1006289217073806e-07, 'epoch': 0.95}
+
95%|█████████▌| 11404/11952 [3:46:31<1:16:55, 8.42s/it]
95%|█████████▌| 11405/11952 [3:46:36<1:09:13, 7.59s/it]
{'loss': 0.4453, 'learning_rate': 1.0966230440479953e-07, 'epoch': 0.95}
+
95%|█████████▌| 11405/11952 [3:46:36<1:09:13, 7.59s/it]
95%|█████████▌| 11406/11952 [3:46:42<1:04:28, 7.09s/it]
{'loss': 0.4599, 'learning_rate': 1.0926244294412359e-07, 'epoch': 0.95}
+
95%|█████████▌| 11406/11952 [3:46:42<1:04:28, 7.09s/it]
95%|█████████▌| 11407/11952 [3:46:48<1:01:59, 6.82s/it]
{'loss': 0.4831, 'learning_rate': 1.0886330781807674e-07, 'epoch': 0.95}
+
95%|█████████▌| 11407/11952 [3:46:48<1:01:59, 6.82s/it]
95%|█████████▌| 11408/11952 [3:46:54<59:09, 6.53s/it]
{'loss': 0.459, 'learning_rate': 1.0846489905596669e-07, 'epoch': 0.95}
+
95%|█████████▌| 11408/11952 [3:46:54<59:09, 6.53s/it]
95%|█████████▌| 11409/11952 [3:47:00<57:37, 6.37s/it]
{'loss': 0.4722, 'learning_rate': 1.0806721668705333e-07, 'epoch': 0.95}
+
95%|█████████▌| 11409/11952 [3:47:00<57:37, 6.37s/it]
95%|█████████▌| 11410/11952 [3:47:06<56:05, 6.21s/it]
{'loss': 0.4564, 'learning_rate': 1.0767026074053888e-07, 'epoch': 0.95}
+
95%|█████████▌| 11410/11952 [3:47:06<56:05, 6.21s/it]
95%|█████████▌| 11411/11952 [3:47:12<54:33, 6.05s/it]
{'loss': 0.473, 'learning_rate': 1.0727403124557667e-07, 'epoch': 0.95}
+
95%|█████████▌| 11411/11952 [3:47:12<54:33, 6.05s/it]
95%|█████████▌| 11412/11952 [3:47:18<54:18, 6.03s/it]
{'loss': 0.4533, 'learning_rate': 1.0687852823126122e-07, 'epoch': 0.95}
+
95%|█████████▌| 11412/11952 [3:47:18<54:18, 6.03s/it]
95%|█████████▌| 11413/11952 [3:47:24<53:43, 5.98s/it]
{'loss': 0.466, 'learning_rate': 1.0648375172663927e-07, 'epoch': 0.95}
+
95%|█████████▌| 11413/11952 [3:47:24<53:43, 5.98s/it]
95%|█████████▌| 11414/11952 [3:47:29<53:09, 5.93s/it]
{'loss': 0.4882, 'learning_rate': 1.0608970176069987e-07, 'epoch': 0.95}
+
95%|█████████▌| 11414/11952 [3:47:29<53:09, 5.93s/it]
96%|█████████▌| 11415/11952 [3:47:35<52:35, 5.88s/it]
{'loss': 0.4757, 'learning_rate': 1.05696378362381e-07, 'epoch': 0.96}
+
96%|█████████▌| 11415/11952 [3:47:35<52:35, 5.88s/it]
96%|█████████▌| 11416/11952 [3:47:41<52:29, 5.88s/it]
{'loss': 0.4573, 'learning_rate': 1.053037815605662e-07, 'epoch': 0.96}
+
96%|█████████▌| 11416/11952 [3:47:41<52:29, 5.88s/it]
96%|█████████▌| 11417/11952 [3:47:47<51:47, 5.81s/it]
{'loss': 0.4652, 'learning_rate': 1.0491191138408685e-07, 'epoch': 0.96}
+
96%|█████████▌| 11417/11952 [3:47:47<51:47, 5.81s/it]
96%|█████████▌| 11418/11952 [3:47:53<51:56, 5.84s/it]
{'loss': 0.4586, 'learning_rate': 1.0452076786171994e-07, 'epoch': 0.96}
+
96%|█████████▌| 11418/11952 [3:47:53<51:56, 5.84s/it]
96%|█████████▌| 11419/11952 [3:47:59<52:05, 5.86s/it]
{'loss': 0.4461, 'learning_rate': 1.0413035102219027e-07, 'epoch': 0.96}
+
96%|█████████▌| 11419/11952 [3:47:59<52:05, 5.86s/it]
96%|█████████▌| 11420/11952 [3:48:05<52:42, 5.95s/it]
{'loss': 0.4575, 'learning_rate': 1.0374066089416602e-07, 'epoch': 0.96}
+
96%|█████████▌| 11420/11952 [3:48:05<52:42, 5.95s/it]
96%|█████████▌| 11421/11952 [3:48:11<52:52, 5.97s/it]
{'loss': 0.4532, 'learning_rate': 1.033516975062676e-07, 'epoch': 0.96}
+
96%|█████████▌| 11421/11952 [3:48:11<52:52, 5.97s/it]
96%|█████████▌| 11422/11952 [3:48:17<52:39, 5.96s/it]
{'loss': 0.4417, 'learning_rate': 1.0296346088705555e-07, 'epoch': 0.96}
+
96%|█████████▌| 11422/11952 [3:48:17<52:39, 5.96s/it]
96%|█████████▌| 11423/11952 [3:48:22<51:59, 5.90s/it]
{'loss': 0.4606, 'learning_rate': 1.025759510650437e-07, 'epoch': 0.96}
+
96%|█████████▌| 11423/11952 [3:48:22<51:59, 5.90s/it]
96%|█████████▌| 11424/11952 [3:48:29<52:47, 6.00s/it]
{'loss': 0.469, 'learning_rate': 1.0218916806868594e-07, 'epoch': 0.96}
+
96%|█████████▌| 11424/11952 [3:48:29<52:47, 6.00s/it]
96%|█████████▌| 11425/11952 [3:48:35<52:34, 5.99s/it]
{'loss': 0.4542, 'learning_rate': 1.0180311192638848e-07, 'epoch': 0.96}
+
96%|█████████▌| 11425/11952 [3:48:35<52:34, 5.99s/it]
96%|█████████▌| 11426/11952 [3:48:40<51:45, 5.90s/it]
{'loss': 0.4661, 'learning_rate': 1.0141778266650082e-07, 'epoch': 0.96}
+
96%|█████████▌| 11426/11952 [3:48:40<51:45, 5.90s/it]
96%|█████████▌| 11427/11952 [3:48:46<51:31, 5.89s/it]
{'loss': 0.4652, 'learning_rate': 1.0103318031732035e-07, 'epoch': 0.96}
+
96%|█████████▌| 11427/11952 [3:48:46<51:31, 5.89s/it]
96%|█████████▌| 11428/11952 [3:48:52<52:00, 5.96s/it]
{'loss': 0.4853, 'learning_rate': 1.006493049070889e-07, 'epoch': 0.96}
+
96%|█████████▌| 11428/11952 [3:48:52<52:00, 5.96s/it]
96%|█████████▌| 11429/11952 [3:48:58<52:41, 6.05s/it]
{'loss': 0.4559, 'learning_rate': 1.002661564639995e-07, 'epoch': 0.96}
+
96%|█████████▌| 11429/11952 [3:48:59<52:41, 6.05s/it]
96%|█████████▌| 11430/11952 [3:49:04<51:58, 5.98s/it]
{'loss': 0.4535, 'learning_rate': 9.988373501618631e-08, 'epoch': 0.96}
+
96%|█████████▌| 11430/11952 [3:49:04<51:58, 5.98s/it]
96%|█████████▌| 11431/11952 [3:49:10<51:59, 5.99s/it]
{'loss': 0.4537, 'learning_rate': 9.950204059173462e-08, 'epoch': 0.96}
+
96%|█████████▌| 11431/11952 [3:49:10<51:59, 5.99s/it]
96%|█████████▌| 11432/11952 [3:49:17<52:34, 6.07s/it]
{'loss': 0.462, 'learning_rate': 9.912107321867315e-08, 'epoch': 0.96}
+
96%|█████████▌| 11432/11952 [3:49:17<52:34, 6.07s/it]
96%|█████████▌| 11433/11952 [3:49:22<51:37, 5.97s/it]
{'loss': 0.4469, 'learning_rate': 9.87408329249795e-08, 'epoch': 0.96}
+
96%|█████████▌| 11433/11952 [3:49:22<51:37, 5.97s/it]
96%|█████████▌| 11434/11952 [3:49:28<51:18, 5.94s/it]
{'loss': 0.4602, 'learning_rate': 9.836131973857687e-08, 'epoch': 0.96}
+
96%|█████████▌| 11434/11952 [3:49:28<51:18, 5.94s/it]
96%|█████████▌| 11435/11952 [3:49:34<51:42, 6.00s/it]
{'loss': 0.4734, 'learning_rate': 9.798253368733523e-08, 'epoch': 0.96}
+
96%|█████████▌| 11435/11952 [3:49:34<51:42, 6.00s/it]
96%|█████████▌| 11436/11952 [3:49:40<50:57, 5.92s/it]
{'loss': 0.4662, 'learning_rate': 9.76044747990701e-08, 'epoch': 0.96}
+
96%|█████████▌| 11436/11952 [3:49:40<50:57, 5.92s/it]
96%|█████████▌| 11437/11952 [3:49:46<50:34, 5.89s/it]
{'loss': 0.4702, 'learning_rate': 9.722714310154591e-08, 'epoch': 0.96}
+
96%|█████████▌| 11437/11952 [3:49:46<50:34, 5.89s/it]
96%|█████████▌| 11438/11952 [3:49:52<50:28, 5.89s/it]
{'loss': 0.4542, 'learning_rate': 9.685053862247051e-08, 'epoch': 0.96}
+
96%|█████████▌| 11438/11952 [3:49:52<50:28, 5.89s/it]
96%|█████████▌| 11439/11952 [3:49:58<50:22, 5.89s/it]
{'loss': 0.4661, 'learning_rate': 9.647466138950178e-08, 'epoch': 0.96}
+
96%|█████████▌| 11439/11952 [3:49:58<50:22, 5.89s/it]
96%|█████████▌| 11440/11952 [3:50:04<50:50, 5.96s/it]
{'loss': 0.4739, 'learning_rate': 9.60995114302421e-08, 'epoch': 0.96}
+
96%|█████████▌| 11440/11952 [3:50:04<50:50, 5.96s/it]
96%|█████████▌| 11441/11952 [3:50:10<51:17, 6.02s/it]
{'loss': 0.4406, 'learning_rate': 9.572508877224163e-08, 'epoch': 0.96}
+
96%|█████████▌| 11441/11952 [3:50:10<51:17, 6.02s/it]
96%|█████████▌| 11442/11952 [3:50:16<50:24, 5.93s/it]
{'loss': 0.4697, 'learning_rate': 9.535139344299393e-08, 'epoch': 0.96}
+
96%|█████████▌| 11442/11952 [3:50:16<50:24, 5.93s/it]
96%|█████████▌| 11443/11952 [3:50:21<49:59, 5.89s/it]
{'loss': 0.4764, 'learning_rate': 9.497842546994485e-08, 'epoch': 0.96}
+
96%|█████████▌| 11443/11952 [3:50:21<49:59, 5.89s/it]
96%|█████████▌| 11444/11952 [3:50:27<49:12, 5.81s/it]
{'loss': 0.4497, 'learning_rate': 9.460618488048024e-08, 'epoch': 0.96}
+
96%|█████████▌| 11444/11952 [3:50:27<49:12, 5.81s/it]
96%|█████████▌| 11445/11952 [3:50:33<50:20, 5.96s/it]
{'loss': 0.4531, 'learning_rate': 9.423467170193933e-08, 'epoch': 0.96}
+
96%|█████████▌| 11445/11952 [3:50:33<50:20, 5.96s/it]
96%|█████████▌| 11446/11952 [3:50:39<49:27, 5.86s/it]
{'loss': 0.4582, 'learning_rate': 9.386388596160367e-08, 'epoch': 0.96}
+
96%|█████████▌| 11446/11952 [3:50:39<49:27, 5.86s/it]
96%|█████████▌| 11447/11952 [3:50:45<49:37, 5.90s/it]
{'loss': 0.4613, 'learning_rate': 9.349382768670034e-08, 'epoch': 0.96}
+
96%|█████████▌| 11447/11952 [3:50:45<49:37, 5.90s/it]
96%|█████████▌| 11448/11952 [3:50:51<49:00, 5.83s/it]
{'loss': 0.4622, 'learning_rate': 9.31244969044065e-08, 'epoch': 0.96}
+
96%|█████████▌| 11448/11952 [3:50:51<49:00, 5.83s/it]
96%|█████████▌| 11449/11952 [3:50:57<49:03, 5.85s/it]
{'loss': 0.4951, 'learning_rate': 9.275589364184379e-08, 'epoch': 0.96}
+
96%|█████████▌| 11449/11952 [3:50:57<49:03, 5.85s/it]5 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+04 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+
96%|█████████▌| 11450/11952 [3:51:03<49:15, 5.89s/it]1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4514, 'learning_rate': 9.238801792608054e-08, 'epoch': 0.96}
+
96%|█████████▌| 11450/11952 [3:51:03<49:15, 5.89s/it]
96%|█████████▌| 11451/11952 [3:51:09<49:23, 5.92s/it]
{'loss': 0.4673, 'learning_rate': 9.202086978413294e-08, 'epoch': 0.96}
+
96%|█████████▌| 11451/11952 [3:51:09<49:23, 5.92s/it]
96%|█████████▌| 11452/11952 [3:51:15<49:32, 5.94s/it]
{'loss': 0.4674, 'learning_rate': 9.165444924296163e-08, 'epoch': 0.96}
+
96%|█████████▌| 11452/11952 [3:51:15<49:32, 5.94s/it]
96%|█████████▌| 11453/11952 [3:51:20<49:02, 5.90s/it]
{'loss': 0.462, 'learning_rate': 9.12887563294751e-08, 'epoch': 0.96}
+
96%|█████████▌| 11453/11952 [3:51:20<49:02, 5.90s/it]
96%|█████████▌| 11454/11952 [3:51:26<48:35, 5.85s/it]
{'loss': 0.4548, 'learning_rate': 9.092379107053074e-08, 'epoch': 0.96}
+
96%|█████████▌| 11454/11952 [3:51:26<48:35, 5.85s/it]
96%|█████████▌| 11455/11952 [3:51:32<49:18, 5.95s/it]
{'loss': 0.4618, 'learning_rate': 9.055955349292711e-08, 'epoch': 0.96}
+
96%|█████████▌| 11455/11952 [3:51:32<49:18, 5.95s/it]
96%|█████████▌| 11456/11952 [3:51:38<49:26, 5.98s/it]
{'loss': 0.4822, 'learning_rate': 9.019604362341394e-08, 'epoch': 0.96}
+
96%|█████████▌| 11456/11952 [3:51:38<49:26, 5.98s/it]
96%|█████████▌| 11457/11952 [3:51:45<49:49, 6.04s/it]
{'loss': 0.4545, 'learning_rate': 8.983326148868432e-08, 'epoch': 0.96}
+
96%|█████████▌| 11457/11952 [3:51:45<49:49, 6.04s/it]
96%|█████████▌| 11458/11952 [3:51:50<49:23, 6.00s/it]
{'loss': 0.4525, 'learning_rate': 8.947120711538138e-08, 'epoch': 0.96}
+
96%|█████████▌| 11458/11952 [3:51:50<49:23, 6.00s/it]
96%|█████████▌| 11459/11952 [3:51:56<49:15, 5.99s/it]
{'loss': 0.462, 'learning_rate': 8.910988053009162e-08, 'epoch': 0.96}
+
96%|█████████▌| 11459/11952 [3:51:56<49:15, 5.99s/it]
96%|█████████▌| 11460/11952 [3:52:02<48:03, 5.86s/it]
{'loss': 0.4336, 'learning_rate': 8.874928175934938e-08, 'epoch': 0.96}
+
96%|█████████▌| 11460/11952 [3:52:02<48:03, 5.86s/it]
96%|█████████▌| 11461/11952 [3:52:08<47:52, 5.85s/it]
{'loss': 0.4565, 'learning_rate': 8.838941082963681e-08, 'epoch': 0.96}
+
96%|█████████▌| 11461/11952 [3:52:08<47:52, 5.85s/it]
96%|█████████▌| 11462/11952 [3:52:14<47:47, 5.85s/it]
{'loss': 0.4647, 'learning_rate': 8.803026776738055e-08, 'epoch': 0.96}
+
96%|█████████▌| 11462/11952 [3:52:14<47:47, 5.85s/it]
96%|█████████▌| 11463/11952 [3:52:19<47:25, 5.82s/it]
{'loss': 0.4468, 'learning_rate': 8.767185259895284e-08, 'epoch': 0.96}
+
96%|█████████▌| 11463/11952 [3:52:19<47:25, 5.82s/it]
96%|█████████▌| 11464/11952 [3:52:26<48:09, 5.92s/it]
{'loss': 0.4473, 'learning_rate': 8.731416535067705e-08, 'epoch': 0.96}
+
96%|█████████▌| 11464/11952 [3:52:26<48:09, 5.92s/it]
96%|█████████▌| 11465/11952 [3:52:31<47:16, 5.83s/it]
{'loss': 0.4576, 'learning_rate': 8.695720604881886e-08, 'epoch': 0.96}
+
96%|█████████▌| 11465/11952 [3:52:31<47:16, 5.83s/it]
96%|█████████▌| 11466/11952 [3:52:37<47:42, 5.89s/it]
{'loss': 0.4786, 'learning_rate': 8.660097471959173e-08, 'epoch': 0.96}
+
96%|█████████▌| 11466/11952 [3:52:37<47:42, 5.89s/it]
96%|█████████▌| 11467/11952 [3:52:44<48:48, 6.04s/it]
{'loss': 0.4623, 'learning_rate': 8.624547138915696e-08, 'epoch': 0.96}
+
96%|█████████▌| 11467/11952 [3:52:44<48:48, 6.04s/it]
96%|█████████▌| 11468/11952 [3:52:50<48:33, 6.02s/it]
{'loss': 0.4606, 'learning_rate': 8.589069608361922e-08, 'epoch': 0.96}
+
96%|█████████▌| 11468/11952 [3:52:50<48:33, 6.02s/it]
96%|█████████▌| 11469/11952 [3:52:55<47:51, 5.95s/it]
{'loss': 0.4581, 'learning_rate': 8.553664882903323e-08, 'epoch': 0.96}
+
96%|█████████▌| 11469/11952 [3:52:55<47:51, 5.95s/it]
96%|█████████▌| 11470/11952 [3:53:01<47:38, 5.93s/it]
{'loss': 0.4398, 'learning_rate': 8.518332965139931e-08, 'epoch': 0.96}
+
96%|█████████▌| 11470/11952 [3:53:01<47:38, 5.93s/it]
96%|█████████▌| 11471/11952 [3:53:08<48:34, 6.06s/it]
{'loss': 0.4641, 'learning_rate': 8.483073857666224e-08, 'epoch': 0.96}
+
96%|█████████▌| 11471/11952 [3:53:08<48:34, 6.06s/it]
96%|█████████▌| 11472/11952 [3:53:13<48:00, 6.00s/it]
{'loss': 0.4707, 'learning_rate': 8.447887563071466e-08, 'epoch': 0.96}
+
96%|█████████▌| 11472/11952 [3:53:13<48:00, 6.00s/it]
96%|█████████▌| 11473/11952 [3:53:20<48:17, 6.05s/it]
{'loss': 0.4626, 'learning_rate': 8.4127740839397e-08, 'epoch': 0.96}
+
96%|█████████▌| 11473/11952 [3:53:20<48:17, 6.05s/it]
96%|█████████▌| 11474/11952 [3:53:26<47:59, 6.02s/it]
{'loss': 0.4563, 'learning_rate': 8.377733422849532e-08, 'epoch': 0.96}
+
96%|█████████▌| 11474/11952 [3:53:26<47:59, 6.02s/it]
96%|█████████▌| 11475/11952 [3:53:31<47:01, 5.92s/it]
{'loss': 0.4642, 'learning_rate': 8.342765582374124e-08, 'epoch': 0.96}
+
96%|█████████▌| 11475/11952 [3:53:31<47:01, 5.92s/it]
96%|█████████▌| 11476/11952 [3:53:37<46:16, 5.83s/it]
{'loss': 0.4385, 'learning_rate': 8.307870565081422e-08, 'epoch': 0.96}
+
96%|█████████▌| 11476/11952 [3:53:37<46:16, 5.83s/it]
96%|█████████▌| 11477/11952 [3:53:43<46:24, 5.86s/it]
{'loss': 0.4736, 'learning_rate': 8.273048373533932e-08, 'epoch': 0.96}
+
96%|█████████▌| 11477/11952 [3:53:43<46:24, 5.86s/it]
96%|█████████▌| 11478/11952 [3:53:49<46:37, 5.90s/it]
{'loss': 0.45, 'learning_rate': 8.23829901028883e-08, 'epoch': 0.96}
+
96%|█████████▌| 11478/11952 [3:53:49<46:37, 5.90s/it]
96%|█████████▌| 11479/11952 [3:53:55<46:26, 5.89s/it]
{'loss': 0.4565, 'learning_rate': 8.203622477898077e-08, 'epoch': 0.96}
+
96%|█████████▌| 11479/11952 [3:53:55<46:26, 5.89s/it]
96%|█████████▌| 11480/11952 [3:54:00<46:11, 5.87s/it]
{'loss': 0.4609, 'learning_rate': 8.169018778908078e-08, 'epoch': 0.96}
+
96%|█████████▌| 11480/11952 [3:54:00<46:11, 5.87s/it]
96%|█████████▌| 11481/11952 [3:54:06<46:08, 5.88s/it]
{'loss': 0.4565, 'learning_rate': 8.134487915860024e-08, 'epoch': 0.96}
+
96%|█████████▌| 11481/11952 [3:54:06<46:08, 5.88s/it]
96%|█████████▌| 11482/11952 [3:54:12<46:28, 5.93s/it]
{'loss': 0.4625, 'learning_rate': 8.100029891289662e-08, 'epoch': 0.96}
+
96%|█████████▌| 11482/11952 [3:54:12<46:28, 5.93s/it]
96%|█████████▌| 11483/11952 [3:54:18<46:11, 5.91s/it]
{'loss': 0.4632, 'learning_rate': 8.065644707727415e-08, 'epoch': 0.96}
+
96%|█████████▌| 11483/11952 [3:54:18<46:11, 5.91s/it]
96%|█████████▌| 11484/11952 [3:54:24<45:33, 5.84s/it]
{'loss': 0.4644, 'learning_rate': 8.031332367698486e-08, 'epoch': 0.96}
+
96%|█████████▌| 11484/11952 [3:54:24<45:33, 5.84s/it]
96%|█████████▌| 11485/11952 [3:54:30<45:26, 5.84s/it]
{'loss': 0.4493, 'learning_rate': 7.997092873722633e-08, 'epoch': 0.96}
+
96%|█████████▌| 11485/11952 [3:54:30<45:26, 5.84s/it]
96%|█████████▌| 11486/11952 [3:54:36<45:36, 5.87s/it]
{'loss': 0.4484, 'learning_rate': 7.962926228314293e-08, 'epoch': 0.96}
+
96%|█████████▌| 11486/11952 [3:54:36<45:36, 5.87s/it]
96%|█████████▌| 11487/11952 [3:54:41<44:43, 5.77s/it]
{'loss': 0.4623, 'learning_rate': 7.928832433982348e-08, 'epoch': 0.96}
+
96%|█████████▌| 11487/11952 [3:54:41<44:43, 5.77s/it]
96%|█████████▌| 11488/11952 [3:54:47<44:41, 5.78s/it]
{'loss': 0.4518, 'learning_rate': 7.89481149323068e-08, 'epoch': 0.96}
+
96%|█████████▌| 11488/11952 [3:54:47<44:41, 5.78s/it]
96%|█████████▌| 11489/11952 [3:54:53<44:12, 5.73s/it]
{'loss': 0.4552, 'learning_rate': 7.860863408557629e-08, 'epoch': 0.96}
+
96%|█████████▌| 11489/11952 [3:54:53<44:12, 5.73s/it]
96%|█████████▌| 11490/11952 [3:54:58<44:08, 5.73s/it]
{'loss': 0.4685, 'learning_rate': 7.826988182456086e-08, 'epoch': 0.96}
+
96%|█████████▌| 11490/11952 [3:54:58<44:08, 5.73s/it]
96%|█████████▌| 11491/11952 [3:55:04<43:49, 5.70s/it]
{'loss': 0.4479, 'learning_rate': 7.793185817413728e-08, 'epoch': 0.96}
+
96%|█████████▌| 11491/11952 [3:55:04<43:49, 5.70s/it]
96%|█████████▌| 11492/11952 [3:55:10<44:00, 5.74s/it]
{'loss': 0.478, 'learning_rate': 7.759456315912905e-08, 'epoch': 0.96}
+
96%|█████████▌| 11492/11952 [3:55:10<44:00, 5.74s/it]
96%|█████████▌| 11493/11952 [3:55:16<44:44, 5.85s/it]
{'loss': 0.4773, 'learning_rate': 7.725799680430634e-08, 'epoch': 0.96}
+
96%|█████████▌| 11493/11952 [3:55:16<44:44, 5.85s/it]
96%|█████████▌| 11494/11952 [3:55:22<44:03, 5.77s/it]
{'loss': 0.4452, 'learning_rate': 7.692215913438383e-08, 'epoch': 0.96}
+
96%|█████████▌| 11494/11952 [3:55:22<44:03, 5.77s/it]
96%|█████████▌| 11495/11952 [3:55:28<44:49, 5.89s/it]
{'loss': 0.4524, 'learning_rate': 7.658705017402623e-08, 'epoch': 0.96}
+
96%|█████████▌| 11495/11952 [3:55:28<44:49, 5.89s/it]
96%|█████████▌| 11496/11952 [3:55:34<44:38, 5.87s/it]
{'loss': 0.4712, 'learning_rate': 7.625266994784053e-08, 'epoch': 0.96}
+
96%|█████████▌| 11496/11952 [3:55:34<44:38, 5.87s/it]
96%|█████████▌| 11497/11952 [3:55:39<44:36, 5.88s/it]
{'loss': 0.4557, 'learning_rate': 7.591901848038263e-08, 'epoch': 0.96}
+
96%|█████████▌| 11497/11952 [3:55:40<44:36, 5.88s/it]
96%|█████████▌| 11498/11952 [3:55:46<44:54, 5.94s/it]
{'loss': 0.4618, 'learning_rate': 7.558609579615406e-08, 'epoch': 0.96}
+
96%|█████████▌| 11498/11952 [3:55:46<44:54, 5.94s/it]
96%|█████████▌| 11499/11952 [3:55:51<44:16, 5.87s/it]
{'loss': 0.4687, 'learning_rate': 7.525390191960413e-08, 'epoch': 0.96}
+
96%|█████████▌| 11499/11952 [3:55:51<44:16, 5.87s/it]7 AutoResumeHook: Checking whether to suspend...
+25 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+0
+ AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+
96%|█████████▌| 11500/11952 [3:55:57<44:22, 5.89s/it]3 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4418, 'learning_rate': 7.49224368751278e-08, 'epoch': 0.96}
+
96%|█████████▌| 11500/11952 [3:55:57<44:22, 5.89s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11500/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11500/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11500/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
96%|█████████▌| 11501/11952 [3:56:27<1:38:34, 13.11s/it]
{'loss': 0.4609, 'learning_rate': 7.459170068706555e-08, 'epoch': 0.96}
+
96%|█████████▌| 11501/11952 [3:56:27<1:38:34, 13.11s/it]
96%|█████████▌| 11502/11952 [3:56:33<1:21:44, 10.90s/it]
{'loss': 0.4725, 'learning_rate': 7.42616933797069e-08, 'epoch': 0.96}
+
96%|█████████▌| 11502/11952 [3:56:33<1:21:44, 10.90s/it]
96%|█████████▌| 11503/11952 [3:56:39<1:10:54, 9.48s/it]
{'loss': 0.4742, 'learning_rate': 7.393241497728465e-08, 'epoch': 0.96}
+
96%|█████████▌| 11503/11952 [3:56:39<1:10:54, 9.48s/it]
96%|█████████▋| 11504/11952 [3:56:45<1:02:36, 8.39s/it]
{'loss': 0.479, 'learning_rate': 7.360386550398058e-08, 'epoch': 0.96}
+
96%|█████████▋| 11504/11952 [3:56:45<1:02:36, 8.39s/it]
96%|█████████▋| 11505/11952 [3:56:51<56:36, 7.60s/it]
{'loss': 0.4734, 'learning_rate': 7.327604498392094e-08, 'epoch': 0.96}
+
96%|█████████▋| 11505/11952 [3:56:51<56:36, 7.60s/it]
96%|█████████▋| 11506/11952 [3:56:56<52:08, 7.01s/it]
{'loss': 0.4444, 'learning_rate': 7.294895344118091e-08, 'epoch': 0.96}
+
96%|█████████▋| 11506/11952 [3:56:56<52:08, 7.01s/it]
96%|█████████▋| 11507/11952 [3:57:02<49:43, 6.70s/it]
{'loss': 0.4477, 'learning_rate': 7.262259089977907e-08, 'epoch': 0.96}
+
96%|█████████▋| 11507/11952 [3:57:02<49:43, 6.70s/it]
96%|█████████▋| 11508/11952 [3:57:08<47:59, 6.48s/it]
{'loss': 0.493, 'learning_rate': 7.229695738368403e-08, 'epoch': 0.96}
+
96%|█████████▋| 11508/11952 [3:57:08<47:59, 6.48s/it]
96%|█████████▋| 11509/11952 [3:57:14<46:13, 6.26s/it]
{'loss': 0.4547, 'learning_rate': 7.197205291680887e-08, 'epoch': 0.96}
+
96%|█████████▋| 11509/11952 [3:57:14<46:13, 6.26s/it]
96%|█████████▋| 11510/11952 [3:57:20<45:21, 6.16s/it]
{'loss': 0.4579, 'learning_rate': 7.164787752301117e-08, 'epoch': 0.96}
+
96%|█████████▋| 11510/11952 [3:57:20<45:21, 6.16s/it]
96%|█████████▋| 11511/11952 [3:57:26<45:00, 6.12s/it]
{'loss': 0.477, 'learning_rate': 7.132443122609856e-08, 'epoch': 0.96}
+
96%|█████████▋| 11511/11952 [3:57:26<45:00, 6.12s/it]
96%|█████████▋| 11512/11952 [3:57:32<44:19, 6.04s/it]
{'loss': 0.4626, 'learning_rate': 7.100171404982315e-08, 'epoch': 0.96}
+
96%|█████████▋| 11512/11952 [3:57:32<44:19, 6.04s/it]
96%|█████████▋| 11513/11952 [3:57:38<43:29, 5.94s/it]
{'loss': 0.4527, 'learning_rate': 7.067972601788376e-08, 'epoch': 0.96}
+
96%|█████████▋| 11513/11952 [3:57:38<43:29, 5.94s/it]srun: Job step aborted: Waiting up to 122 seconds for job step to finish.
+Jun 11 04:45:04.377618 2168900 slurmstepd 0x155550a06700: error: *** STEP 8846993.0 ON batch-block1-0082 CANCELLED AT 2025-06-11T04:45:04 DUE TO TIME LIMIT ***
+srun: error: batch-block1-0082: task 0: Terminated
+srun: Terminating StepId=8846993.0
+srun: job 8851917 queued and waiting for resources
+srun: job 8857770 queued and waiting for resources
+srun: job 8857770 has been allocated resources
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+MASTER_ADDR=batch-block7-00972
+JobID: 8857770 | Full list: batch-block7-00972
+NETWORK=Efficient-Large-Model/VILA1.5-3b
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
+*****************************************
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:07,290] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 14:27:08,465] [INFO] [comm.py:625:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 14:27:08,465] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 14:27:08,465] [INFO] [comm.py:594:init_distributed] cdb=None
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+You are attempting to use Flash Attention 2.0 with a model not initialized on GPU. Make sure to move the model to GPU after initializing it on CPU with `model.to('cuda')`.
+[2025-06-11 14:27:17,421] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 2.70B parameters
+
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 0%| | 0/2 [00:00, ?it/s]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.52s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.59s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.59s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.59s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.59s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.59s/it]
Loading checkpoint shards: 50%|█████ | 1/2 [00:04<00:04, 4.59s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.13s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:04<00:00, 2.49s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.14s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.50s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.14s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.14s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.14s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.14s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
+
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.14s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:05<00:00, 2.51s/it]
+
Loading checkpoint shards: 50%|█████ | 1/2 [00:06<00:06, 6.85s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:07<00:00, 3.40s/it]
Loading checkpoint shards: 100%|██████████| 2/2 [00:07<00:00, 3.92s/it]
+[2025-06-11 14:27:25,533] [WARNING] [partition_parameters.py:836:_post_init_method] param `probe` in SiglipMultiheadAttentionPoolingHead not on GPU so was not broadcasted from rank 0
+[2025-06-11 14:27:25,534] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.13B parameters
+[2025-06-11 14:27:27,310] [INFO] [partition_parameters.py:453:__exit__] finished initializing model with 3.15B parameters
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+[dist-0-of-8] LlavaLlamaModel(
+ (llm): LlamaForCausalLM(
+ (model): LlamaModel(
+ (embed_tokens): Embedding(32000, 2560, padding_idx=0)
+ (layers): ModuleList(
+ (0-31): 32 x LlamaDecoderLayer(
+ (self_attn): LlamaFlashAttention2(
+ (q_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (k_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (v_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (o_proj): Linear(in_features=2560, out_features=2560, bias=False)
+ (rotary_emb): LlamaRotaryEmbedding()
+ )
+ (mlp): LlamaMLP(
+ (gate_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (up_proj): Linear(in_features=2560, out_features=6912, bias=False)
+ (down_proj): Linear(in_features=6912, out_features=2560, bias=False)
+ (act_fn): SiLU()
+ )
+ (input_layernorm): LlamaRMSNorm()
+ (post_attention_layernorm): LlamaRMSNorm()
+ )
+ )
+ (norm): LlamaRMSNorm()
+ )
+ (lm_head): Linear(in_features=2560, out_features=32000, bias=False)
+ )
+ (vision_tower): SiglipVisionTower(
+ (vision_tower): SiglipVisionModel(
+ (vision_model): SiglipVisionTransformer(
+ (embeddings): SiglipVisionEmbeddings(
+ (patch_embedding): Conv2d(3, 1152, kernel_size=(14, 14), stride=(14, 14), padding=valid)
+ (position_embedding): Embedding(729, 1152)
+ )
+ (encoder): SiglipEncoder(
+ (layers): ModuleList(
+ (0-26): 27 x SiglipEncoderLayer(
+ (self_attn): SiglipAttention(
+ (k_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (v_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (q_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ (out_proj): Linear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layer_norm1): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ (layer_norm2): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ )
+ )
+ )
+ (post_layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (head): SiglipMultiheadAttentionPoolingHead(
+ (attention): MultiheadAttention(
+ (out_proj): NonDynamicallyQuantizableLinear(in_features=1152, out_features=1152, bias=True)
+ )
+ (layernorm): LayerNorm((1152,), eps=1e-06, elementwise_affine=True)
+ (mlp): SiglipMLP(
+ (activation_fn): PytorchGELUTanh()
+ (fc1): Linear(in_features=1152, out_features=4304, bias=True)
+ (fc2): Linear(in_features=4304, out_features=1152, bias=True)
+ )
+ )
+ )
+ )
+ )
+ (mm_projector): MultimodalProjector(
+ (layers): Sequential(
+ (0): DownSampleBlock()
+ (1): LayerNorm((4608,), eps=1e-05, elementwise_affine=True)
+ (2): Linear(in_features=4608, out_features=2560, bias=True)
+ (3): GELU(approximate='none')
+ (4): Linear(in_features=2560, out_features=2560, bias=True)
+ )
+ )
+)
+WARNING:root:You are setting tunable parameters for the model. Previous args include 'freeze_backbone' and 'tune_mm_mlp_adapter' are deprecated.
+ Notice: default value of tune_xxx is False, which means you would not tune this part.
+[dist-0-of-8] Tunable parameters:
+language model True
+[dist-0-of-8] vision tower True
+[dist-0-of-8] mm projector True
+[Dataset-INFO]: Loading from ['robopoint_1432k', 'sim_path_mask_subtraj', 'oxe_processed_path_mask_subtraj']
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8364481925964355
+length of dataloader:length of dataloader: 2390523905 30599643059964
+
+[GPU memory] before trainer[GPU memory] before trainer 0.82564496994018550.8060321807861328
+
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+Formatting inputs...Skip in lazy mode
+WARNING:root:Pay attention, split eval is not built...
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8271098136901855
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8273234367370605
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8274149894714355
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8332133293151855
+length of dataloader: 23905 3059964
+[GPU memory] before trainer 0.8259501457214355
+Parameter Offload: Total persistent parameters: 593856 in 349 params
+wandb: Using wandb-core as the SDK backend. Please refer to https://wandb.me/wandb-core for more information.
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.18.7
+wandb: Run data is saved locally in /lustre/fs12/portfolios/nvr/projects/nvr_srl_simpler/users/mmemmel/projects/vila/VILA/wandb/run-20250611_142850-nh1vjmt9
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run vila_3b_path_mask
+wandb: ⭐️ View project at https://wandb.ai/memmelma/VILA
+wandb: 🚀 View run at https://wandb.ai/memmelma/VILA/runs/nh1vjmt9
+
0%| | 0/11952 [00:00, ?it/s]Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+Could not estimate the number of tokens of the input, floating-point operations will not be computed
+
96%|█████████▌| 11501/11952 [00:23<00:00, 490.03it/s]
{'loss': 0.4609, 'learning_rate': 7.459170068706555e-08, 'epoch': 0.96}
+
96%|█████████▌| 11501/11952 [00:23<00:00, 490.03it/s]
{'loss': 0.4724, 'learning_rate': 7.42616933797069e-08, 'epoch': 0.96}
+
96%|█████████▌| 11502/11952 [00:29<00:00, 490.03it/s]
96%|█████████▌| 11502/11952 [00:34<00:00, 490.03it/s]
96%|█████████▌| 11503/11952 [00:35<00:01, 287.47it/s]
{'loss': 0.4743, 'learning_rate': 7.393241497728465e-08, 'epoch': 0.96}
+
96%|█████████▌| 11503/11952 [00:35<00:01, 287.47it/s]
96%|█████████▋| 11504/11952 [00:40<00:02, 222.08it/s]
{'loss': 0.4792, 'learning_rate': 7.360386550398058e-08, 'epoch': 0.96}
+
96%|█████████▋| 11504/11952 [00:40<00:02, 222.08it/s]
96%|█████████▋| 11505/11952 [00:46<00:02, 168.54it/s]
{'loss': 0.4734, 'learning_rate': 7.327604498392094e-08, 'epoch': 0.96}
+
96%|█████████▋| 11505/11952 [00:46<00:02, 168.54it/s]
96%|█████████▋| 11506/11952 [00:52<00:03, 125.84it/s]
{'loss': 0.4442, 'learning_rate': 7.294895344118091e-08, 'epoch': 0.96}
+
96%|█████████▋| 11506/11952 [00:52<00:03, 125.84it/s]
96%|█████████▋| 11507/11952 [00:57<00:04, 91.04it/s]
{'loss': 0.4476, 'learning_rate': 7.262259089977907e-08, 'epoch': 0.96}
+
96%|█████████▋| 11507/11952 [00:57<00:04, 91.04it/s]
96%|█████████▋| 11508/11952 [01:03<00:06, 65.44it/s]
{'loss': 0.493, 'learning_rate': 7.229695738368403e-08, 'epoch': 0.96}
+
96%|█████████▋| 11508/11952 [01:03<00:06, 65.44it/s]
96%|█████████▋| 11509/11952 [01:09<00:09, 47.09it/s]
{'loss': 0.4545, 'learning_rate': 7.197205291680887e-08, 'epoch': 0.96}
+
96%|█████████▋| 11509/11952 [01:09<00:09, 47.09it/s]
96%|█████████▋| 11510/11952 [01:15<00:13, 33.42it/s]
{'loss': 0.4578, 'learning_rate': 7.164787752301117e-08, 'epoch': 0.96}
+
96%|█████████▋| 11510/11952 [01:15<00:13, 33.42it/s]
96%|█████████▋| 11511/11952 [01:21<00:18, 23.40it/s]
{'loss': 0.4767, 'learning_rate': 7.132443122609856e-08, 'epoch': 0.96}
+
96%|█████████▋| 11511/11952 [01:21<00:18, 23.40it/s]
96%|█████████▋| 11512/11952 [01:27<00:26, 16.64it/s]
{'loss': 0.4626, 'learning_rate': 7.100171404982315e-08, 'epoch': 0.96}
+
96%|█████████▋| 11512/11952 [01:27<00:26, 16.64it/s]
96%|█████████▋| 11513/11952 [01:32<00:37, 11.86it/s]
{'loss': 0.4525, 'learning_rate': 7.067972601788376e-08, 'epoch': 0.96}
+
96%|█████████▋| 11513/11952 [01:32<00:37, 11.86it/s]
96%|█████████▋| 11514/11952 [01:38<00:51, 8.47it/s]
{'loss': 0.4466, 'learning_rate': 7.035846715392591e-08, 'epoch': 0.96}
+
96%|█████████▋| 11514/11952 [01:38<00:51, 8.47it/s]
96%|█████████▋| 11515/11952 [01:43<01:12, 6.04it/s]
{'loss': 0.4565, 'learning_rate': 7.003793748154186e-08, 'epoch': 0.96}
+
96%|█████████▋| 11515/11952 [01:43<01:12, 6.04it/s]
96%|█████████▋| 11516/11952 [01:49<01:41, 4.29it/s]
{'loss': 0.4513, 'learning_rate': 6.971813702427055e-08, 'epoch': 0.96}
+
96%|█████████▋| 11516/11952 [01:49<01:41, 4.29it/s]
96%|█████████▋| 11517/11952 [01:55<02:23, 3.04it/s]
{'loss': 0.4462, 'learning_rate': 6.939906580559542e-08, 'epoch': 0.96}
+
96%|█████████▋| 11517/11952 [01:55<02:23, 3.04it/s]
96%|█████████▋| 11518/11952 [02:01<03:20, 2.17it/s]
{'loss': 0.4708, 'learning_rate': 6.908072384894881e-08, 'epoch': 0.96}
+
96%|█████████▋| 11518/11952 [02:01<03:20, 2.17it/s]
96%|█████████▋| 11519/11952 [02:06<04:34, 1.58it/s]
{'loss': 0.4715, 'learning_rate': 6.876311117770762e-08, 'epoch': 0.96}
+
96%|█████████▋| 11519/11952 [02:06<04:34, 1.58it/s]
96%|█████████▋| 11520/11952 [02:12<06:23, 1.13it/s]
{'loss': 0.4652, 'learning_rate': 6.844622781519649e-08, 'epoch': 0.96}
+
96%|█████████▋| 11520/11952 [02:12<06:23, 1.13it/s]
96%|█████████▋| 11521/11952 [02:18<08:31, 1.19s/it]
{'loss': 0.4617, 'learning_rate': 6.813007378468684e-08, 'epoch': 0.96}
+
96%|█████████▋| 11521/11952 [02:18<08:31, 1.19s/it]
96%|█████████▋| 11522/11952 [02:24<11:10, 1.56s/it]
{'loss': 0.4697, 'learning_rate': 6.78146491093945e-08, 'epoch': 0.96}
+
96%|█████████▋| 11522/11952 [02:24<11:10, 1.56s/it]
96%|█████████▋| 11523/11952 [02:30<14:15, 1.99s/it]
{'loss': 0.4436, 'learning_rate': 6.74999538124832e-08, 'epoch': 0.96}
+
96%|█████████▋| 11523/11952 [02:30<14:15, 1.99s/it]
96%|█████████▋| 11524/11952 [02:36<17:37, 2.47s/it]
{'loss': 0.4746, 'learning_rate': 6.718598791706221e-08, 'epoch': 0.96}
+
96%|█████████▋| 11524/11952 [02:36<17:37, 2.47s/it]
96%|█████████▋| 11525/11952 [02:41<21:02, 2.96s/it]
{'loss': 0.4787, 'learning_rate': 6.687275144618865e-08, 'epoch': 0.96}
+
96%|█████████▋| 11525/11952 [02:41<21:02, 2.96s/it]
96%|█████████▋| 11526/11952 [02:47<24:28, 3.45s/it]
{'loss': 0.4546, 'learning_rate': 6.656024442286524e-08, 'epoch': 0.96}
+
96%|█████████▋| 11526/11952 [02:47<24:28, 3.45s/it]
96%|█████████▋| 11527/11952 [02:53<28:01, 3.96s/it]
{'loss': 0.4944, 'learning_rate': 6.62484668700425e-08, 'epoch': 0.96}
+
96%|█████████▋| 11527/11952 [02:53<28:01, 3.96s/it]
96%|█████████▋| 11528/11952 [02:59<30:47, 4.36s/it]
{'loss': 0.4772, 'learning_rate': 6.593741881061321e-08, 'epoch': 0.96}
+
96%|█████████▋| 11528/11952 [02:59<30:47, 4.36s/it]
96%|█████████▋| 11529/11952 [03:05<34:17, 4.86s/it]
{'loss': 0.4597, 'learning_rate': 6.562710026742248e-08, 'epoch': 0.96}
+
96%|█████████▋| 11529/11952 [03:05<34:17, 4.86s/it]
96%|█████████▋| 11530/11952 [03:11<35:27, 5.04s/it]
{'loss': 0.462, 'learning_rate': 6.531751126325647e-08, 'epoch': 0.96}
+
96%|█████████▋| 11530/11952 [03:11<35:27, 5.04s/it]
96%|█████████▋| 11531/11952 [03:16<36:42, 5.23s/it]
{'loss': 0.4656, 'learning_rate': 6.500865182085148e-08, 'epoch': 0.96}
+
96%|█████████▋| 11531/11952 [03:16<36:42, 5.23s/it]
96%|█████████▋| 11532/11952 [03:22<37:40, 5.38s/it]
{'loss': 0.4457, 'learning_rate': 6.470052196288712e-08, 'epoch': 0.96}
+
96%|█████████▋| 11532/11952 [03:22<37:40, 5.38s/it]
96%|█████████▋| 11533/11952 [03:28<38:51, 5.56s/it]
{'loss': 0.462, 'learning_rate': 6.439312171199308e-08, 'epoch': 0.96}
+
96%|█████████▋| 11533/11952 [03:28<38:51, 5.56s/it]
97%|█████████▋| 11534/11952 [03:34<39:25, 5.66s/it]
{'loss': 0.4589, 'learning_rate': 6.408645109074352e-08, 'epoch': 0.96}
+
97%|█████████▋| 11534/11952 [03:34<39:25, 5.66s/it]
97%|█████████▋| 11535/11952 [03:40<39:49, 5.73s/it]
{'loss': 0.4681, 'learning_rate': 6.37805101216571e-08, 'epoch': 0.97}
+
97%|█████████▋| 11535/11952 [03:40<39:49, 5.73s/it]
97%|█████████▋| 11536/11952 [03:46<39:35, 5.71s/it]
{'loss': 0.4498, 'learning_rate': 6.34752988272036e-08, 'epoch': 0.97}
+
97%|█████████▋| 11536/11952 [03:46<39:35, 5.71s/it]
97%|█████████▋| 11537/11952 [03:51<39:31, 5.71s/it]
{'loss': 0.4609, 'learning_rate': 6.317081722979402e-08, 'epoch': 0.97}
+
97%|█████████▋| 11537/11952 [03:51<39:31, 5.71s/it]
97%|█████████▋| 11538/11952 [03:57<39:21, 5.70s/it]
{'loss': 0.4832, 'learning_rate': 6.286706535179044e-08, 'epoch': 0.97}
+
97%|█████████▋| 11538/11952 [03:57<39:21, 5.70s/it]
97%|█████████▋| 11539/11952 [04:03<39:16, 5.71s/it]
{'loss': 0.4635, 'learning_rate': 6.256404321549725e-08, 'epoch': 0.97}
+
97%|█████████▋| 11539/11952 [04:03<39:16, 5.71s/it]
97%|█████████▋| 11540/11952 [04:08<39:05, 5.69s/it]
{'loss': 0.4608, 'learning_rate': 6.226175084316666e-08, 'epoch': 0.97}
+
97%|█████████▋| 11540/11952 [04:08<39:05, 5.69s/it]
97%|█████████▋| 11541/11952 [04:14<39:00, 5.69s/it]
{'loss': 0.4557, 'learning_rate': 6.19601882570009e-08, 'epoch': 0.97}
+
97%|█████████▋| 11541/11952 [04:14<39:00, 5.69s/it]
97%|█████████▋| 11542/11952 [04:20<38:55, 5.70s/it]
{'loss': 0.458, 'learning_rate': 6.165935547914225e-08, 'epoch': 0.97}
+
97%|█████████▋| 11542/11952 [04:20<38:55, 5.70s/it]
97%|█████████▋| 11543/11952 [04:25<38:57, 5.71s/it]
{'loss': 0.4766, 'learning_rate': 6.135925253168417e-08, 'epoch': 0.97}
+
97%|█████████▋| 11543/11952 [04:25<38:57, 5.71s/it]
97%|█████████▋| 11544/11952 [04:31<39:11, 5.76s/it]
{'loss': 0.455, 'learning_rate': 6.105987943666459e-08, 'epoch': 0.97}
+
97%|█████████▋| 11544/11952 [04:31<39:11, 5.76s/it]
97%|█████████▋| 11545/11952 [04:37<39:12, 5.78s/it]
{'loss': 0.4563, 'learning_rate': 6.07612362160681e-08, 'epoch': 0.97}
+
97%|█████████▋| 11545/11952 [04:37<39:12, 5.78s/it]
97%|█████████▋| 11546/11952 [04:43<39:38, 5.86s/it]
{'loss': 0.4636, 'learning_rate': 6.046332289182722e-08, 'epoch': 0.97}
+
97%|█████████▋| 11546/11952 [04:43<39:38, 5.86s/it]
97%|█████████▋| 11547/11952 [04:49<39:05, 5.79s/it]
{'loss': 0.4598, 'learning_rate': 6.016613948581662e-08, 'epoch': 0.97}
+
97%|█████████▋| 11547/11952 [04:49<39:05, 5.79s/it]
97%|█████████▋| 11548/11952 [04:55<39:22, 5.85s/it]
{'loss': 0.4772, 'learning_rate': 5.98696860198622e-08, 'epoch': 0.97}
+
97%|█████████▋| 11548/11952 [04:55<39:22, 5.85s/it]
97%|█████████▋| 11549/11952 [05:01<39:50, 5.93s/it]
{'loss': 0.4755, 'learning_rate': 5.957396251573433e-08, 'epoch': 0.97}
+
97%|█████████▋| 11549/11952 [05:01<39:50, 5.93s/it]6 AutoResumeHook: Checking whether to suspend...
+71 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
97%|█████████▋| 11550/11952 [05:07<39:20, 5.87s/it]
{'loss': 0.4486, 'learning_rate': 5.9278968995150066e-08, 'epoch': 0.97}
+
97%|█████████▋| 11550/11952 [05:07<39:20, 5.87s/it]
97%|█████████▋| 11551/11952 [05:13<39:30, 5.91s/it]
{'loss': 0.4531, 'learning_rate': 5.898470547977098e-08, 'epoch': 0.97}
+
97%|█████████▋| 11551/11952 [05:13<39:30, 5.91s/it]
97%|█████████▋| 11552/11952 [05:19<39:12, 5.88s/it]
{'loss': 0.4647, 'learning_rate': 5.8691171991207554e-08, 'epoch': 0.97}
+
97%|█████████▋| 11552/11952 [05:19<39:12, 5.88s/it]
97%|█████████▋| 11553/11952 [05:24<39:03, 5.87s/it]
{'loss': 0.4795, 'learning_rate': 5.8398368551014774e-08, 'epoch': 0.97}
+
97%|█████████▋| 11553/11952 [05:24<39:03, 5.87s/it]
97%|█████████▋| 11554/11952 [05:30<39:03, 5.89s/it]
{'loss': 0.4659, 'learning_rate': 5.810629518069655e-08, 'epoch': 0.97}
+
97%|█████████▋| 11554/11952 [05:30<39:03, 5.89s/it]
97%|█████████▋| 11555/11952 [05:36<38:47, 5.86s/it]
{'loss': 0.4633, 'learning_rate': 5.781495190170017e-08, 'epoch': 0.97}
+
97%|█████████▋| 11555/11952 [05:36<38:47, 5.86s/it]
97%|█████████▋| 11556/11952 [05:42<38:43, 5.87s/it]
{'loss': 0.4726, 'learning_rate': 5.7524338735420734e-08, 'epoch': 0.97}
+
97%|█████████▋| 11556/11952 [05:42<38:43, 5.87s/it]
97%|█████████▋| 11557/11952 [05:48<38:26, 5.84s/it]
{'loss': 0.4533, 'learning_rate': 5.7234455703200073e-08, 'epoch': 0.97}
+
97%|█████████▋| 11557/11952 [05:48<38:26, 5.84s/it]
97%|█████████▋| 11558/11952 [05:54<38:47, 5.91s/it]
{'loss': 0.4576, 'learning_rate': 5.69453028263256e-08, 'epoch': 0.97}
+
97%|█████████▋| 11558/11952 [05:54<38:47, 5.91s/it]
97%|█████████▋| 11559/11952 [06:00<39:02, 5.96s/it]
{'loss': 0.5139, 'learning_rate': 5.6656880126032544e-08, 'epoch': 0.97}
+
97%|█████████▋| 11559/11952 [06:00<39:02, 5.96s/it]
97%|█████████▋| 11560/11952 [06:06<38:33, 5.90s/it]
{'loss': 0.4825, 'learning_rate': 5.636918762350063e-08, 'epoch': 0.97}
+
97%|█████████▋| 11560/11952 [06:06<38:33, 5.90s/it]
97%|█████████▋| 11561/11952 [06:12<38:47, 5.95s/it]
{'loss': 0.4501, 'learning_rate': 5.60822253398563e-08, 'epoch': 0.97}
+
97%|█████████▋| 11561/11952 [06:12<38:47, 5.95s/it]
97%|█████████▋| 11562/11952 [06:18<38:26, 5.91s/it]
{'loss': 0.4619, 'learning_rate': 5.57959932961738e-08, 'epoch': 0.97}
+
97%|█████████▋| 11562/11952 [06:18<38:26, 5.91s/it]
97%|█████████▋| 11563/11952 [06:23<38:05, 5.87s/it]
{'loss': 0.4715, 'learning_rate': 5.551049151347299e-08, 'epoch': 0.97}
+
97%|█████████▋| 11563/11952 [06:23<38:05, 5.87s/it]
97%|█████████▋| 11564/11952 [06:29<38:05, 5.89s/it]
{'loss': 0.4353, 'learning_rate': 5.522572001271931e-08, 'epoch': 0.97}
+
97%|█████████▋| 11564/11952 [06:29<38:05, 5.89s/it]
97%|█████████▋| 11565/11952 [06:35<37:36, 5.83s/it]
{'loss': 0.4583, 'learning_rate': 5.494167881482493e-08, 'epoch': 0.97}
+
97%|█████████▋| 11565/11952 [06:35<37:36, 5.83s/it]
97%|█████████▋| 11566/11952 [06:41<37:27, 5.82s/it]
{'loss': 0.4748, 'learning_rate': 5.4658367940648716e-08, 'epoch': 0.97}
+
97%|█████████▋| 11566/11952 [06:41<37:27, 5.82s/it]
97%|█████████▋| 11567/11952 [06:47<37:13, 5.80s/it]
{'loss': 0.4489, 'learning_rate': 5.437578741099625e-08, 'epoch': 0.97}
+
97%|█████████▋| 11567/11952 [06:47<37:13, 5.80s/it]
97%|█████████▋| 11568/11952 [06:52<36:45, 5.74s/it]
{'loss': 0.4516, 'learning_rate': 5.409393724661982e-08, 'epoch': 0.97}
+
97%|█████████▋| 11568/11952 [06:52<36:45, 5.74s/it]
97%|█████████▋| 11569/11952 [06:58<36:43, 5.75s/it]
{'loss': 0.4539, 'learning_rate': 5.381281746821621e-08, 'epoch': 0.97}
+
97%|█████████▋| 11569/11952 [06:58<36:43, 5.75s/it]
97%|█████████▋| 11570/11952 [07:04<36:45, 5.77s/it]
{'loss': 0.4893, 'learning_rate': 5.353242809643e-08, 'epoch': 0.97}
+
97%|█████████▋| 11570/11952 [07:04<36:45, 5.77s/it]
97%|█████████▋| 11571/11952 [07:09<36:19, 5.72s/it]
{'loss': 0.4578, 'learning_rate': 5.3252769151851404e-08, 'epoch': 0.97}
+
97%|█████████▋| 11571/11952 [07:09<36:19, 5.72s/it]
97%|█████████▋| 11572/11952 [07:15<36:26, 5.75s/it]
{'loss': 0.4645, 'learning_rate': 5.297384065501843e-08, 'epoch': 0.97}
+
97%|█████████▋| 11572/11952 [07:15<36:26, 5.75s/it]
97%|█████████▋| 11573/11952 [07:21<36:06, 5.72s/it]
{'loss': 0.45, 'learning_rate': 5.269564262641358e-08, 'epoch': 0.97}
+
97%|█████████▋| 11573/11952 [07:21<36:06, 5.72s/it]
97%|█████████▋| 11574/11952 [07:27<36:27, 5.79s/it]
{'loss': 0.4595, 'learning_rate': 5.241817508646607e-08, 'epoch': 0.97}
+
97%|█████████▋| 11574/11952 [07:27<36:27, 5.79s/it]
97%|█████████▋| 11575/11952 [07:33<37:16, 5.93s/it]
{'loss': 0.4711, 'learning_rate': 5.214143805555294e-08, 'epoch': 0.97}
+
97%|█████████▋| 11575/11952 [07:33<37:16, 5.93s/it]
97%|█████████▋| 11576/11952 [07:39<36:29, 5.82s/it]
{'loss': 0.4387, 'learning_rate': 5.1865431553996814e-08, 'epoch': 0.97}
+
97%|█████████▋| 11576/11952 [07:39<36:29, 5.82s/it]
97%|█████████▋| 11577/11952 [07:44<36:32, 5.85s/it]
{'loss': 0.4737, 'learning_rate': 5.159015560206593e-08, 'epoch': 0.97}
+
97%|█████████▋| 11577/11952 [07:44<36:32, 5.85s/it]
97%|█████████▋| 11578/11952 [07:50<36:11, 5.81s/it]
{'loss': 0.4596, 'learning_rate': 5.131561021997522e-08, 'epoch': 0.97}
+
97%|█████████▋| 11578/11952 [07:50<36:11, 5.81s/it]
97%|█████████▋| 11579/11952 [07:57<37:08, 5.97s/it]
{'loss': 0.4678, 'learning_rate': 5.104179542788634e-08, 'epoch': 0.97}
+
97%|█████████▋| 11579/11952 [07:57<37:08, 5.97s/it]
97%|█████████▋| 11580/11952 [08:02<36:27, 5.88s/it]
{'loss': 0.458, 'learning_rate': 5.0768711245907654e-08, 'epoch': 0.97}
+
97%|█████████▋| 11580/11952 [08:02<36:27, 5.88s/it]
97%|█████████▋| 11581/11952 [08:08<36:56, 5.97s/it]
{'loss': 0.4588, 'learning_rate': 5.049635769409311e-08, 'epoch': 0.97}
+
97%|█████████▋| 11581/11952 [08:08<36:56, 5.97s/it]
97%|█████████▋| 11582/11952 [08:14<36:26, 5.91s/it]
{'loss': 0.4621, 'learning_rate': 5.022473479244228e-08, 'epoch': 0.97}
+
97%|█████████▋| 11582/11952 [08:14<36:26, 5.91s/it]
97%|█████████▋| 11583/11952 [08:20<35:58, 5.85s/it]
{'loss': 0.4776, 'learning_rate': 4.995384256090252e-08, 'epoch': 0.97}
+
97%|█████████▋| 11583/11952 [08:20<35:58, 5.85s/it]
97%|█████████▋| 11584/11952 [08:26<35:37, 5.81s/it]
{'loss': 0.5035, 'learning_rate': 4.9683681019367935e-08, 'epoch': 0.97}
+
97%|█████████▋| 11584/11952 [08:26<35:37, 5.81s/it]
97%|█████████▋| 11585/11952 [08:31<35:29, 5.80s/it]
{'loss': 0.4653, 'learning_rate': 4.941425018767709e-08, 'epoch': 0.97}
+
97%|█████████▋| 11585/11952 [08:31<35:29, 5.80s/it]
97%|█████████▋| 11586/11952 [08:37<35:26, 5.81s/it]
{'loss': 0.4472, 'learning_rate': 4.914555008561528e-08, 'epoch': 0.97}
+
97%|█████████▋| 11586/11952 [08:37<35:26, 5.81s/it]
97%|█████████▋| 11587/11952 [08:43<34:52, 5.73s/it]
{'loss': 0.4582, 'learning_rate': 4.8877580732916706e-08, 'epoch': 0.97}
+
97%|█████████▋| 11587/11952 [08:43<34:52, 5.73s/it]
97%|█████████▋| 11588/11952 [08:48<34:38, 5.71s/it]
{'loss': 0.4557, 'learning_rate': 4.861034214925786e-08, 'epoch': 0.97}
+
97%|█████████▋| 11588/11952 [08:48<34:38, 5.71s/it]
97%|█████████▋| 11589/11952 [08:54<34:29, 5.70s/it]
{'loss': 0.4401, 'learning_rate': 4.834383435426526e-08, 'epoch': 0.97}
+
97%|█████████▋| 11589/11952 [08:54<34:29, 5.70s/it]
97%|█████████▋| 11590/11952 [09:00<34:38, 5.74s/it]
{'loss': 0.4679, 'learning_rate': 4.807805736750881e-08, 'epoch': 0.97}
+
97%|█████████▋| 11590/11952 [09:00<34:38, 5.74s/it]
97%|█████████▋| 11591/11952 [09:06<34:18, 5.70s/it]
{'loss': 0.4689, 'learning_rate': 4.7813011208507344e-08, 'epoch': 0.97}
+
97%|█████████▋| 11591/11952 [09:06<34:18, 5.70s/it]
97%|█████████▋| 11592/11952 [09:11<34:14, 5.71s/it]
{'loss': 0.4587, 'learning_rate': 4.754869589672306e-08, 'epoch': 0.97}
+
97%|█████████▋| 11592/11952 [09:11<34:14, 5.71s/it]
97%|█████████▋| 11593/11952 [09:17<34:16, 5.73s/it]
{'loss': 0.4385, 'learning_rate': 4.728511145156822e-08, 'epoch': 0.97}
+
97%|█████████▋| 11593/11952 [09:17<34:16, 5.73s/it]
97%|█████████▋| 11594/11952 [09:23<33:51, 5.68s/it]
{'loss': 0.4664, 'learning_rate': 4.702225789239734e-08, 'epoch': 0.97}
+
97%|█████████▋| 11594/11952 [09:23<33:51, 5.68s/it]
97%|█████████▋| 11595/11952 [09:28<33:49, 5.68s/it]
{'loss': 0.4549, 'learning_rate': 4.676013523851497e-08, 'epoch': 0.97}
+
97%|█████████▋| 11595/11952 [09:28<33:49, 5.68s/it]
97%|█████████▋| 11596/11952 [09:34<34:12, 5.76s/it]
{'loss': 0.4589, 'learning_rate': 4.6498743509170165e-08, 'epoch': 0.97}
+
97%|█████████▋| 11596/11952 [09:34<34:12, 5.76s/it]
97%|█████████▋| 11597/11952 [09:40<34:02, 5.75s/it]
{'loss': 0.479, 'learning_rate': 4.6238082723557566e-08, 'epoch': 0.97}
+
97%|█████████▋| 11597/11952 [09:40<34:02, 5.75s/it]
97%|█████████▋| 11598/11952 [09:45<33:24, 5.66s/it]
{'loss': 0.4623, 'learning_rate': 4.597815290081853e-08, 'epoch': 0.97}
+
97%|█████████▋| 11598/11952 [09:45<33:24, 5.66s/it]
97%|█████████▋| 11599/11952 [09:51<34:01, 5.78s/it]
{'loss': 0.4538, 'learning_rate': 4.571895406004334e-08, 'epoch': 0.97}
+
97%|█████████▋| 11599/11952 [09:51<34:01, 5.78s/it]2 AutoResumeHook: Checking whether to suspend...
+31 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+70 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
97%|█████████▋| 11600/11952 [09:57<34:00, 5.80s/it]
{'loss': 0.4619, 'learning_rate': 4.546048622026455e-08, 'epoch': 0.97}
+
97%|█████████▋| 11600/11952 [09:57<34:00, 5.80s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11600/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11600/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11600/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
97%|█████████▋| 11601/11952 [10:32<1:23:56, 14.35s/it]
{'loss': 0.4445, 'learning_rate': 4.520274940046254e-08, 'epoch': 0.97}
+
97%|█████████▋| 11601/11952 [10:32<1:23:56, 14.35s/it]
97%|█████████▋| 11602/11952 [10:37<1:08:38, 11.77s/it]
{'loss': 0.4731, 'learning_rate': 4.494574361956661e-08, 'epoch': 0.97}
+
97%|█████████▋| 11602/11952 [10:37<1:08:38, 11.77s/it]
97%|█████████▋| 11603/11952 [10:43<57:45, 9.93s/it]
{'loss': 0.4714, 'learning_rate': 4.4689468896449426e-08, 'epoch': 0.97}
+
97%|█████████▋| 11603/11952 [10:43<57:45, 9.93s/it]
97%|█████████▋| 11604/11952 [10:49<50:22, 8.68s/it]
{'loss': 0.4801, 'learning_rate': 4.44339252499304e-08, 'epoch': 0.97}
+
97%|█████████▋| 11604/11952 [10:49<50:22, 8.68s/it]
97%|█████████▋| 11605/11952 [10:55<45:06, 7.80s/it]
{'loss': 0.4417, 'learning_rate': 4.4179112698774505e-08, 'epoch': 0.97}
+
97%|█████████▋| 11605/11952 [10:55<45:06, 7.80s/it]
97%|█████████▋| 11606/11952 [11:00<41:28, 7.19s/it]
{'loss': 0.4605, 'learning_rate': 4.392503126169678e-08, 'epoch': 0.97}
+
97%|█████████▋| 11606/11952 [11:00<41:28, 7.19s/it]
97%|█████████▋| 11607/11952 [11:06<39:04, 6.80s/it]
{'loss': 0.4555, 'learning_rate': 4.3671680957352304e-08, 'epoch': 0.97}
+
97%|█████████▋| 11607/11952 [11:06<39:04, 6.80s/it]
97%|█████████▋| 11608/11952 [11:12<37:11, 6.49s/it]
{'loss': 0.4503, 'learning_rate': 4.341906180434952e-08, 'epoch': 0.97}
+
97%|█████████▋| 11608/11952 [11:12<37:11, 6.49s/it]
97%|█████████▋| 11609/11952 [11:18<35:54, 6.28s/it]
{'loss': 0.4642, 'learning_rate': 4.3167173821238026e-08, 'epoch': 0.97}
+
97%|█████████▋| 11609/11952 [11:18<35:54, 6.28s/it]
97%|█████████▋| 11610/11952 [11:23<34:22, 6.03s/it]
{'loss': 0.4799, 'learning_rate': 4.291601702651527e-08, 'epoch': 0.97}
+
97%|█████████▋| 11610/11952 [11:23<34:22, 6.03s/it]
97%|█████████▋| 11611/11952 [11:29<33:18, 5.86s/it]
{'loss': 0.4446, 'learning_rate': 4.2665591438626474e-08, 'epoch': 0.97}
+
97%|█████████▋| 11611/11952 [11:29<33:18, 5.86s/it]
97%|█████████▋| 11612/11952 [11:34<32:58, 5.82s/it]
{'loss': 0.4713, 'learning_rate': 4.241589707596028e-08, 'epoch': 0.97}
+
97%|█████████▋| 11612/11952 [11:34<32:58, 5.82s/it]
97%|█████████▋| 11613/11952 [11:40<32:43, 5.79s/it]
{'loss': 0.4628, 'learning_rate': 4.216693395685423e-08, 'epoch': 0.97}
+
97%|█████████▋| 11613/11952 [11:40<32:43, 5.79s/it]
97%|█████████▋| 11614/11952 [11:46<32:18, 5.74s/it]
{'loss': 0.4603, 'learning_rate': 4.191870209959037e-08, 'epoch': 0.97}
+
97%|█████████▋| 11614/11952 [11:46<32:18, 5.74s/it]
97%|█████████▋| 11615/11952 [11:52<32:25, 5.77s/it]
{'loss': 0.4876, 'learning_rate': 4.167120152239856e-08, 'epoch': 0.97}
+
97%|█████████▋| 11615/11952 [11:52<32:25, 5.77s/it]
97%|█████████▋| 11616/11952 [11:57<31:55, 5.70s/it]
{'loss': 0.4624, 'learning_rate': 4.142443224345427e-08, 'epoch': 0.97}
+
97%|█████████▋| 11616/11952 [11:57<31:55, 5.70s/it]
97%|█████████▋| 11617/11952 [12:03<32:31, 5.83s/it]
{'loss': 0.4711, 'learning_rate': 4.1178394280878554e-08, 'epoch': 0.97}
+
97%|█████████▋| 11617/11952 [12:03<32:31, 5.83s/it]
97%|█████████▋| 11618/11952 [12:09<31:59, 5.75s/it]
{'loss': 0.4748, 'learning_rate': 4.093308765273918e-08, 'epoch': 0.97}
+
97%|█████████▋| 11618/11952 [12:09<31:59, 5.75s/it]
97%|█████████▋| 11619/11952 [12:14<31:31, 5.68s/it]
{'loss': 0.4544, 'learning_rate': 4.068851237705174e-08, 'epoch': 0.97}
+
97%|█████████▋| 11619/11952 [12:14<31:31, 5.68s/it]
97%|█████████▋| 11620/11952 [12:20<31:12, 5.64s/it]
{'loss': 0.4416, 'learning_rate': 4.044466847177519e-08, 'epoch': 0.97}
+
97%|█████████▋| 11620/11952 [12:20<31:12, 5.64s/it]
97%|█████████▋| 11621/11952 [12:26<31:18, 5.68s/it]
{'loss': 0.4559, 'learning_rate': 4.0201555954818563e-08, 'epoch': 0.97}
+
97%|█████████▋| 11621/11952 [12:26<31:18, 5.68s/it]
97%|█████████▋| 11622/11952 [12:31<31:27, 5.72s/it]
{'loss': 0.4686, 'learning_rate': 3.9959174844032e-08, 'epoch': 0.97}
+
97%|█████████▋| 11622/11952 [12:31<31:27, 5.72s/it]
97%|█████████▋| 11623/11952 [12:37<31:30, 5.75s/it]
{'loss': 0.4665, 'learning_rate': 3.971752515721794e-08, 'epoch': 0.97}
+
97%|█████████▋| 11623/11952 [12:37<31:30, 5.75s/it]
97%|█████████▋| 11624/11952 [12:43<31:40, 5.79s/it]
{'loss': 0.4777, 'learning_rate': 3.9476606912121073e-08, 'epoch': 0.97}
+
97%|█████████▋| 11624/11952 [12:43<31:40, 5.79s/it]
97%|█████████▋| 11625/11952 [12:49<31:02, 5.70s/it]
{'loss': 0.469, 'learning_rate': 3.9236420126432806e-08, 'epoch': 0.97}
+
97%|█████████▋| 11625/11952 [12:49<31:02, 5.70s/it]
97%|█████████▋| 11626/11952 [12:55<31:19, 5.77s/it]
{'loss': 0.4729, 'learning_rate': 3.899696481779236e-08, 'epoch': 0.97}
+
97%|█████████▋| 11626/11952 [12:55<31:19, 5.77s/it]
97%|█████████▋| 11627/11952 [13:01<31:58, 5.90s/it]
{'loss': 0.4659, 'learning_rate': 3.8758241003782336e-08, 'epoch': 0.97}
+
97%|█████████▋| 11627/11952 [13:01<31:58, 5.90s/it]
97%|█████████▋| 11628/11952 [13:06<31:29, 5.83s/it]
{'loss': 0.4463, 'learning_rate': 3.852024870193649e-08, 'epoch': 0.97}
+
97%|█████████▋| 11628/11952 [13:06<31:29, 5.83s/it]
97%|█████████▋| 11629/11952 [13:12<31:46, 5.90s/it]
{'loss': 0.4729, 'learning_rate': 3.8282987929730844e-08, 'epoch': 0.97}
+
97%|█████████▋| 11629/11952 [13:12<31:46, 5.90s/it]
97%|█████████▋| 11630/11952 [13:18<31:39, 5.90s/it]
{'loss': 0.4636, 'learning_rate': 3.804645870458812e-08, 'epoch': 0.97}
+
97%|█████████▋| 11630/11952 [13:18<31:39, 5.90s/it]
97%|█████████▋| 11631/11952 [13:24<31:37, 5.91s/it]
{'loss': 0.4568, 'learning_rate': 3.781066104387887e-08, 'epoch': 0.97}
+
97%|█████████▋| 11631/11952 [13:24<31:37, 5.91s/it]
97%|█████████▋| 11632/11952 [13:30<31:23, 5.89s/it]
{'loss': 0.457, 'learning_rate': 3.757559496491925e-08, 'epoch': 0.97}
+
97%|█████████▋| 11632/11952 [13:30<31:23, 5.89s/it]
97%|█████████▋| 11633/11952 [13:36<31:09, 5.86s/it]
{'loss': 0.4333, 'learning_rate': 3.7341260484969885e-08, 'epoch': 0.97}
+
97%|█████████▋| 11633/11952 [13:36<31:09, 5.86s/it]
97%|█████████▋| 11634/11952 [13:42<30:52, 5.82s/it]
{'loss': 0.4622, 'learning_rate': 3.710765762124147e-08, 'epoch': 0.97}
+
97%|█████████▋| 11634/11952 [13:42<30:52, 5.82s/it]
97%|█████████▋| 11635/11952 [13:48<30:56, 5.86s/it]
{'loss': 0.4611, 'learning_rate': 3.687478639088804e-08, 'epoch': 0.97}
+
97%|█████████▋| 11635/11952 [13:48<30:56, 5.86s/it]
97%|█████████▋| 11636/11952 [13:53<30:26, 5.78s/it]
{'loss': 0.4524, 'learning_rate': 3.6642646811010375e-08, 'epoch': 0.97}
+
97%|█████████▋| 11636/11952 [13:53<30:26, 5.78s/it]
97%|█████████▋| 11637/11952 [13:59<30:12, 5.75s/it]
{'loss': 0.4486, 'learning_rate': 3.6411238898655943e-08, 'epoch': 0.97}
+
97%|█████████▋| 11637/11952 [13:59<30:12, 5.75s/it]
97%|█████████▋| 11638/11952 [14:05<30:24, 5.81s/it]
{'loss': 0.4561, 'learning_rate': 3.618056267081782e-08, 'epoch': 0.97}
+
97%|█████████▋| 11638/11952 [14:05<30:24, 5.81s/it]
97%|█████████▋| 11639/11952 [14:11<30:03, 5.76s/it]
{'loss': 0.465, 'learning_rate': 3.59506181444369e-08, 'epoch': 0.97}
+
97%|█████████▋| 11639/11952 [14:11<30:03, 5.76s/it]
97%|█████████▋| 11640/11952 [14:16<30:12, 5.81s/it]
{'loss': 0.4843, 'learning_rate': 3.5721405336398565e-08, 'epoch': 0.97}
+
97%|█████████▋| 11640/11952 [14:16<30:12, 5.81s/it]
97%|█████████▋| 11641/11952 [14:22<29:51, 5.76s/it]
{'loss': 0.458, 'learning_rate': 3.5492924263537124e-08, 'epoch': 0.97}
+
97%|█████████▋| 11641/11952 [14:22<29:51, 5.76s/it]
97%|█████████▋| 11642/11952 [14:28<29:40, 5.74s/it]
{'loss': 0.4535, 'learning_rate': 3.526517494262804e-08, 'epoch': 0.97}
+
97%|█████████▋| 11642/11952 [14:28<29:40, 5.74s/it]
97%|█████████▋| 11643/11952 [14:34<29:47, 5.79s/it]
{'loss': 0.4647, 'learning_rate': 3.5038157390399067e-08, 'epoch': 0.97}
+
97%|█████████▋| 11643/11952 [14:34<29:47, 5.79s/it]
97%|█████████▋| 11644/11952 [14:39<29:42, 5.79s/it]
{'loss': 0.4704, 'learning_rate': 3.481187162352018e-08, 'epoch': 0.97}
+
97%|█████████▋| 11644/11952 [14:39<29:42, 5.79s/it]
97%|█████████▋| 11645/11952 [14:45<29:35, 5.78s/it]
{'loss': 0.4537, 'learning_rate': 3.4586317658609205e-08, 'epoch': 0.97}
+
97%|█████████▋| 11645/11952 [14:45<29:35, 5.78s/it]
97%|█████████▋| 11646/11952 [14:51<29:35, 5.80s/it]
{'loss': 0.4813, 'learning_rate': 3.436149551223067e-08, 'epoch': 0.97}
+
97%|█████████▋| 11646/11952 [14:51<29:35, 5.80s/it]
97%|█████████▋| 11647/11952 [14:57<29:43, 5.85s/it]
{'loss': 0.4698, 'learning_rate': 3.413740520089248e-08, 'epoch': 0.97}
+
97%|█████████▋| 11647/11952 [14:57<29:43, 5.85s/it]
97%|█████████▋| 11648/11952 [15:03<29:59, 5.92s/it]
{'loss': 0.4612, 'learning_rate': 3.3914046741052585e-08, 'epoch': 0.97}
+
97%|█████████▋| 11648/11952 [15:03<29:59, 5.92s/it]
97%|█████████▋| 11649/11952 [15:09<30:01, 5.95s/it]
{'loss': 0.4437, 'learning_rate': 3.369142014911231e-08, 'epoch': 0.97}
+
97%|█████████▋| 11649/11952 [15:09<30:01, 5.95s/it]3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
97%|█████████▋| 11650/11952 [15:15<29:35, 5.88s/it]
{'loss': 0.4877, 'learning_rate': 3.34695254414219e-08, 'epoch': 0.97}
+
97%|█████████▋| 11650/11952 [15:15<29:35, 5.88s/it]
97%|█████████▋| 11651/11952 [15:20<29:04, 5.80s/it]
{'loss': 0.4612, 'learning_rate': 3.3248362634275e-08, 'epoch': 0.97}
+
97%|█████████▋| 11651/11952 [15:20<29:04, 5.80s/it]
97%|█████████▋| 11652/11952 [15:26<29:05, 5.82s/it]
{'loss': 0.4605, 'learning_rate': 3.302793174391417e-08, 'epoch': 0.97}
+
97%|█████████▋| 11652/11952 [15:26<29:05, 5.82s/it]
97%|█████████▋| 11653/11952 [15:32<28:53, 5.80s/it]
{'loss': 0.466, 'learning_rate': 3.280823278652645e-08, 'epoch': 0.97}
+
97%|█████████▋| 11653/11952 [15:32<28:53, 5.80s/it]
98%|█████████▊| 11654/11952 [15:38<28:34, 5.75s/it]
{'loss': 0.4523, 'learning_rate': 3.2589265778244505e-08, 'epoch': 0.98}
+
98%|█████████▊| 11654/11952 [15:38<28:34, 5.75s/it]
98%|█████████▊| 11655/11952 [15:44<28:44, 5.81s/it]
{'loss': 0.4371, 'learning_rate': 3.237103073514991e-08, 'epoch': 0.98}
+
98%|█████████▊| 11655/11952 [15:44<28:44, 5.81s/it]
98%|█████████▊| 11656/11952 [15:49<28:21, 5.75s/it]
{'loss': 0.4783, 'learning_rate': 3.215352767326873e-08, 'epoch': 0.98}
+
98%|█████████▊| 11656/11952 [15:49<28:21, 5.75s/it]
98%|█████████▊| 11657/11952 [15:55<28:16, 5.75s/it]
{'loss': 0.4543, 'learning_rate': 3.193675660857265e-08, 'epoch': 0.98}
+
98%|█████████▊| 11657/11952 [15:55<28:16, 5.75s/it]
98%|█████████▊| 11658/11952 [16:01<28:25, 5.80s/it]
{'loss': 0.471, 'learning_rate': 3.172071755698114e-08, 'epoch': 0.98}
+
98%|█████████▊| 11658/11952 [16:01<28:25, 5.80s/it]
98%|█████████▊| 11659/11952 [16:07<28:07, 5.76s/it]
{'loss': 0.4686, 'learning_rate': 3.150541053435818e-08, 'epoch': 0.98}
+
98%|█████████▊| 11659/11952 [16:07<28:07, 5.76s/it]
98%|█████████▊| 11660/11952 [16:13<28:23, 5.83s/it]
{'loss': 0.4683, 'learning_rate': 3.129083555651668e-08, 'epoch': 0.98}
+
98%|█████████▊| 11660/11952 [16:13<28:23, 5.83s/it]
98%|█████████▊| 11661/11952 [16:19<28:26, 5.87s/it]
{'loss': 0.452, 'learning_rate': 3.1076992639211824e-08, 'epoch': 0.98}
+
98%|█████████▊| 11661/11952 [16:19<28:26, 5.87s/it]
98%|█████████▊| 11662/11952 [16:24<28:02, 5.80s/it]
{'loss': 0.4614, 'learning_rate': 3.086388179814992e-08, 'epoch': 0.98}
+
98%|█████████▊| 11662/11952 [16:24<28:02, 5.80s/it]
98%|█████████▊| 11663/11952 [16:30<28:20, 5.88s/it]
{'loss': 0.469, 'learning_rate': 3.065150304897957e-08, 'epoch': 0.98}
+
98%|█████████▊| 11663/11952 [16:30<28:20, 5.88s/it]
98%|█████████▊| 11664/11952 [16:36<28:16, 5.89s/it]
{'loss': 0.4555, 'learning_rate': 3.043985640729718e-08, 'epoch': 0.98}
+
98%|█████████▊| 11664/11952 [16:36<28:16, 5.89s/it]
98%|█████████▊| 11665/11952 [16:42<27:52, 5.83s/it]
{'loss': 0.4715, 'learning_rate': 3.022894188864589e-08, 'epoch': 0.98}
+
98%|█████████▊| 11665/11952 [16:42<27:52, 5.83s/it]
98%|█████████▊| 11666/11952 [16:48<27:35, 5.79s/it]
{'loss': 0.4541, 'learning_rate': 3.0018759508513297e-08, 'epoch': 0.98}
+
98%|█████████▊| 11666/11952 [16:48<27:35, 5.79s/it]
98%|█████████▊| 11667/11952 [16:54<27:50, 5.86s/it]
{'loss': 0.4638, 'learning_rate': 2.980930928233372e-08, 'epoch': 0.98}
+
98%|█████████▊| 11667/11952 [16:54<27:50, 5.86s/it]
98%|█████████▊| 11668/11952 [16:59<27:14, 5.76s/it]
{'loss': 0.4959, 'learning_rate': 2.9600591225490415e-08, 'epoch': 0.98}
+
98%|█████████▊| 11668/11952 [16:59<27:14, 5.76s/it]
98%|█████████▊| 11669/11952 [17:05<27:40, 5.87s/it]
{'loss': 0.4738, 'learning_rate': 2.93926053533089e-08, 'epoch': 0.98}
+
98%|█████████▊| 11669/11952 [17:05<27:40, 5.87s/it]
98%|█████████▊| 11670/11952 [17:11<27:26, 5.84s/it]
{'loss': 0.4592, 'learning_rate': 2.918535168106473e-08, 'epoch': 0.98}
+
98%|█████████▊| 11670/11952 [17:11<27:26, 5.84s/it]
98%|█████████▊| 11671/11952 [17:16<26:51, 5.74s/it]
{'loss': 0.468, 'learning_rate': 2.897883022397574e-08, 'epoch': 0.98}
+
98%|█████████▊| 11671/11952 [17:16<26:51, 5.74s/it]
98%|█████████▊| 11672/11952 [17:22<26:41, 5.72s/it]
{'loss': 0.4645, 'learning_rate': 2.8773040997208678e-08, 'epoch': 0.98}
+
98%|█████████▊| 11672/11952 [17:22<26:41, 5.72s/it]
98%|█████████▊| 11673/11952 [17:28<26:41, 5.74s/it]
{'loss': 0.4617, 'learning_rate': 2.8567984015877014e-08, 'epoch': 0.98}
+
98%|█████████▊| 11673/11952 [17:28<26:41, 5.74s/it]
98%|█████████▊| 11674/11952 [17:34<26:54, 5.81s/it]
{'loss': 0.4605, 'learning_rate': 2.8363659295037592e-08, 'epoch': 0.98}
+
98%|█████████▊| 11674/11952 [17:34<26:54, 5.81s/it]
98%|█████████▊| 11675/11952 [17:40<26:51, 5.82s/it]
{'loss': 0.4509, 'learning_rate': 2.8160066849696187e-08, 'epoch': 0.98}
+
98%|█████████▊| 11675/11952 [17:40<26:51, 5.82s/it]
98%|█████████▊| 11676/11952 [17:46<26:56, 5.86s/it]
{'loss': 0.4641, 'learning_rate': 2.7957206694803064e-08, 'epoch': 0.98}
+
98%|█████████▊| 11676/11952 [17:46<26:56, 5.86s/it]
98%|█████████▊| 11677/11952 [17:52<26:44, 5.84s/it]
{'loss': 0.4295, 'learning_rate': 2.77550788452563e-08, 'epoch': 0.98}
+
98%|█████████▊| 11677/11952 [17:52<26:44, 5.84s/it]
98%|█████████▊| 11678/11952 [17:58<26:53, 5.89s/it]
{'loss': 0.4568, 'learning_rate': 2.755368331589847e-08, 'epoch': 0.98}
+
98%|█████████▊| 11678/11952 [17:58<26:53, 5.89s/it]
98%|█████████▊| 11679/11952 [18:04<27:07, 5.96s/it]
{'loss': 0.4661, 'learning_rate': 2.7353020121518857e-08, 'epoch': 0.98}
+
98%|█████████▊| 11679/11952 [18:04<27:07, 5.96s/it]
98%|█████████▊| 11680/11952 [18:09<26:50, 5.92s/it]
{'loss': 0.4596, 'learning_rate': 2.715308927685567e-08, 'epoch': 0.98}
+
98%|█████████▊| 11680/11952 [18:09<26:50, 5.92s/it]
98%|█████████▊| 11681/11952 [18:15<26:23, 5.84s/it]
{'loss': 0.4582, 'learning_rate': 2.6953890796588276e-08, 'epoch': 0.98}
+
98%|█████████▊| 11681/11952 [18:15<26:23, 5.84s/it]
98%|█████████▊| 11682/11952 [18:21<26:16, 5.84s/it]
{'loss': 0.4804, 'learning_rate': 2.67554246953472e-08, 'epoch': 0.98}
+
98%|█████████▊| 11682/11952 [18:21<26:16, 5.84s/it]
98%|█████████▊| 11683/11952 [18:27<26:19, 5.87s/it]
{'loss': 0.439, 'learning_rate': 2.655769098770522e-08, 'epoch': 0.98}
+
98%|█████████▊| 11683/11952 [18:27<26:19, 5.87s/it]
98%|█████████▊| 11684/11952 [18:33<26:03, 5.83s/it]
{'loss': 0.4728, 'learning_rate': 2.636068968818295e-08, 'epoch': 0.98}
+
98%|█████████▊| 11684/11952 [18:33<26:03, 5.83s/it]
98%|█████████▊| 11685/11952 [18:39<26:39, 5.99s/it]
{'loss': 0.465, 'learning_rate': 2.6164420811249925e-08, 'epoch': 0.98}
+
98%|█████████▊| 11685/11952 [18:39<26:39, 5.99s/it]
98%|█████████▊| 11686/11952 [18:45<26:04, 5.88s/it]
{'loss': 0.4494, 'learning_rate': 2.5968884371315728e-08, 'epoch': 0.98}
+
98%|█████████▊| 11686/11952 [18:45<26:04, 5.88s/it]
98%|█████████▊| 11687/11952 [18:51<26:02, 5.90s/it]
{'loss': 0.4401, 'learning_rate': 2.5774080382743317e-08, 'epoch': 0.98}
+
98%|█████████▊| 11687/11952 [18:51<26:02, 5.90s/it]
98%|█████████▊| 11688/11952 [18:57<26:00, 5.91s/it]
{'loss': 0.4924, 'learning_rate': 2.5580008859835692e-08, 'epoch': 0.98}
+
98%|█████████▊| 11688/11952 [18:57<26:00, 5.91s/it]
98%|█████████▊| 11689/11952 [19:02<25:49, 5.89s/it]
{'loss': 0.4549, 'learning_rate': 2.538666981684479e-08, 'epoch': 0.98}
+
98%|█████████▊| 11689/11952 [19:02<25:49, 5.89s/it]
98%|█████████▊| 11690/11952 [19:08<25:41, 5.88s/it]
{'loss': 0.4631, 'learning_rate': 2.5194063267970358e-08, 'epoch': 0.98}
+
98%|█████████▊| 11690/11952 [19:08<25:41, 5.88s/it]
98%|█████████▊| 11691/11952 [19:14<25:31, 5.87s/it]
{'loss': 0.4868, 'learning_rate': 2.5002189227354425e-08, 'epoch': 0.98}
+
98%|█████████▊| 11691/11952 [19:14<25:31, 5.87s/it]
98%|█████████▊| 11692/11952 [19:20<25:07, 5.80s/it]
{'loss': 0.4634, 'learning_rate': 2.481104770908904e-08, 'epoch': 0.98}
+
98%|█████████▊| 11692/11952 [19:20<25:07, 5.80s/it]
98%|█████████▊| 11693/11952 [19:25<24:49, 5.75s/it]
{'loss': 0.4397, 'learning_rate': 2.4620638727210766e-08, 'epoch': 0.98}
+
98%|█████████▊| 11693/11952 [19:25<24:49, 5.75s/it]
98%|█████████▊| 11694/11952 [19:31<24:35, 5.72s/it]
{'loss': 0.4728, 'learning_rate': 2.4430962295701743e-08, 'epoch': 0.98}
+
98%|█████████▊| 11694/11952 [19:31<24:35, 5.72s/it]
98%|█████████▊| 11695/11952 [19:37<24:41, 5.77s/it]
{'loss': 0.4633, 'learning_rate': 2.4242018428491944e-08, 'epoch': 0.98}
+
98%|█████████▊| 11695/11952 [19:37<24:41, 5.77s/it]
98%|█████████▊| 11696/11952 [19:43<24:56, 5.85s/it]
{'loss': 0.4515, 'learning_rate': 2.405380713945582e-08, 'epoch': 0.98}
+
98%|█████████▊| 11696/11952 [19:43<24:56, 5.85s/it]
98%|█████████▊| 11697/11952 [19:49<24:55, 5.87s/it]
{'loss': 0.4745, 'learning_rate': 2.3866328442414545e-08, 'epoch': 0.98}
+
98%|█████████▊| 11697/11952 [19:49<24:55, 5.87s/it]
98%|█████████▊| 11698/11952 [19:55<24:51, 5.87s/it]
{'loss': 0.4766, 'learning_rate': 2.3679582351137098e-08, 'epoch': 0.98}
+
98%|█████████▊| 11698/11952 [19:55<24:51, 5.87s/it]
98%|█████████▊| 11699/11952 [20:01<24:41, 5.86s/it]
{'loss': 0.4631, 'learning_rate': 2.349356887933585e-08, 'epoch': 0.98}
+
98%|█████████▊| 11699/11952 [20:01<24:41, 5.86s/it]3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+06 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
98%|█████████▊| 11700/11952 [20:06<24:38, 5.87s/it]
{'loss': 0.4695, 'learning_rate': 2.330828804067098e-08, 'epoch': 0.98}
+
98%|█████████▊| 11700/11952 [20:06<24:38, 5.87s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11700/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11700/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11700/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
98%|█████████▊| 11701/11952 [20:37<56:10, 13.43s/it]
{'loss': 0.4665, 'learning_rate': 2.3123739848749382e-08, 'epoch': 0.98}
+
98%|█████████▊| 11701/11952 [20:37<56:10, 13.43s/it]
98%|█████████▊| 11702/11952 [20:43<46:07, 11.07s/it]
{'loss': 0.46, 'learning_rate': 2.2939924317124663e-08, 'epoch': 0.98}
+
98%|█████████▊| 11702/11952 [20:43<46:07, 11.07s/it]
98%|█████████▊| 11703/11952 [20:49<39:15, 9.46s/it]
{'loss': 0.4722, 'learning_rate': 2.275684145929269e-08, 'epoch': 0.98}
+
98%|█████████▊| 11703/11952 [20:49<39:15, 9.46s/it]
98%|█████████▊| 11704/11952 [20:54<34:13, 8.28s/it]
{'loss': 0.4655, 'learning_rate': 2.2574491288700485e-08, 'epoch': 0.98}
+
98%|█████████▊| 11704/11952 [20:54<34:13, 8.28s/it]
98%|█████████▊| 11705/11952 [21:00<31:03, 7.54s/it]
{'loss': 0.4503, 'learning_rate': 2.2392873818738447e-08, 'epoch': 0.98}
+
98%|█████████▊| 11705/11952 [21:00<31:03, 7.54s/it]
98%|█████████▊| 11706/11952 [21:06<28:31, 6.96s/it]
{'loss': 0.4614, 'learning_rate': 2.2211989062743688e-08, 'epoch': 0.98}
+
98%|█████████▊| 11706/11952 [21:06<28:31, 6.96s/it]
98%|█████████▊| 11707/11952 [21:12<27:09, 6.65s/it]
{'loss': 0.4405, 'learning_rate': 2.2031837034000024e-08, 'epoch': 0.98}
+
98%|█████████▊| 11707/11952 [21:12<27:09, 6.65s/it]
98%|█████████▊| 11708/11952 [21:17<26:01, 6.40s/it]
{'loss': 0.4648, 'learning_rate': 2.1852417745735764e-08, 'epoch': 0.98}
+
98%|█████████▊| 11708/11952 [21:17<26:01, 6.40s/it]
98%|█████████▊| 11709/11952 [21:23<24:55, 6.16s/it]
{'loss': 0.4791, 'learning_rate': 2.1673731211129255e-08, 'epoch': 0.98}
+
98%|█████████▊| 11709/11952 [21:23<24:55, 6.16s/it]
98%|█████████▊| 11710/11952 [21:29<24:28, 6.07s/it]
{'loss': 0.467, 'learning_rate': 2.1495777443300005e-08, 'epoch': 0.98}
+
98%|█████████▊| 11710/11952 [21:29<24:28, 6.07s/it]
98%|█████████▊| 11711/11952 [21:35<24:06, 6.00s/it]
{'loss': 0.4428, 'learning_rate': 2.131855645531644e-08, 'epoch': 0.98}
+
98%|█████████▊| 11711/11952 [21:35<24:06, 6.00s/it]
98%|█████████▊| 11712/11952 [21:40<23:30, 5.88s/it]
{'loss': 0.4568, 'learning_rate': 2.1142068260194827e-08, 'epoch': 0.98}
+
98%|█████████▊| 11712/11952 [21:40<23:30, 5.88s/it]
98%|█████████▊| 11713/11952 [21:46<22:59, 5.77s/it]
{'loss': 0.4525, 'learning_rate': 2.0966312870893678e-08, 'epoch': 0.98}
+
98%|█████████▊| 11713/11952 [21:46<22:59, 5.77s/it]
98%|█████████▊| 11714/11952 [21:52<22:53, 5.77s/it]
{'loss': 0.4744, 'learning_rate': 2.0791290300321564e-08, 'epoch': 0.98}
+
98%|█████████▊| 11714/11952 [21:52<22:53, 5.77s/it]
98%|█████████▊| 11715/11952 [21:58<22:56, 5.81s/it]
{'loss': 0.4685, 'learning_rate': 2.0617000561329315e-08, 'epoch': 0.98}
+
98%|█████████▊| 11715/11952 [21:58<22:56, 5.81s/it]
98%|█████████▊| 11716/11952 [22:03<22:54, 5.83s/it]
{'loss': 0.4811, 'learning_rate': 2.04434436667178e-08, 'epoch': 0.98}
+
98%|█████████▊| 11716/11952 [22:03<22:54, 5.83s/it]
98%|█████████▊| 11717/11952 [22:09<22:32, 5.76s/it]
{'loss': 0.4609, 'learning_rate': 2.027061962923127e-08, 'epoch': 0.98}
+
98%|█████████▊| 11717/11952 [22:09<22:32, 5.76s/it]
98%|█████████▊| 11718/11952 [22:15<22:28, 5.76s/it]
{'loss': 0.4709, 'learning_rate': 2.0098528461562906e-08, 'epoch': 0.98}
+
98%|█████████▊| 11718/11952 [22:15<22:28, 5.76s/it]
98%|█████████▊| 11719/11952 [22:20<22:18, 5.74s/it]
{'loss': 0.4597, 'learning_rate': 1.9927170176348155e-08, 'epoch': 0.98}
+
98%|█████████▊| 11719/11952 [22:20<22:18, 5.74s/it]
98%|█████████▊| 11720/11952 [22:26<22:04, 5.71s/it]
{'loss': 0.4651, 'learning_rate': 1.9756544786171393e-08, 'epoch': 0.98}
+
98%|█████████▊| 11720/11952 [22:26<22:04, 5.71s/it]
98%|█████████▊| 11721/11952 [22:32<21:51, 5.68s/it]
{'loss': 0.4463, 'learning_rate': 1.9586652303562603e-08, 'epoch': 0.98}
+
98%|█████████▊| 11721/11952 [22:32<21:51, 5.68s/it]
98%|█████████▊| 11722/11952 [22:38<22:08, 5.78s/it]
{'loss': 0.4751, 'learning_rate': 1.941749274099958e-08, 'epoch': 0.98}
+
98%|█████████▊| 11722/11952 [22:38<22:08, 5.78s/it]
98%|█████████▊| 11723/11952 [22:43<21:47, 5.71s/it]
{'loss': 0.4505, 'learning_rate': 1.924906611090349e-08, 'epoch': 0.98}
+
98%|█████████▊| 11723/11952 [22:43<21:47, 5.71s/it]
98%|█████████▊| 11724/11952 [22:49<21:47, 5.73s/it]
{'loss': 0.4564, 'learning_rate': 1.9081372425642232e-08, 'epoch': 0.98}
+
98%|█████████▊| 11724/11952 [22:49<21:47, 5.73s/it]
98%|█████████▊| 11725/11952 [22:55<21:38, 5.72s/it]
{'loss': 0.4579, 'learning_rate': 1.8914411697531498e-08, 'epoch': 0.98}
+
98%|█████████▊| 11725/11952 [22:55<21:38, 5.72s/it]
98%|█████████▊| 11726/11952 [23:01<21:45, 5.78s/it]
{'loss': 0.4747, 'learning_rate': 1.8748183938832597e-08, 'epoch': 0.98}
+
98%|█████████▊| 11726/11952 [23:01<21:45, 5.78s/it]
98%|█████████▊| 11727/11952 [23:07<22:00, 5.87s/it]
{'loss': 0.4637, 'learning_rate': 1.8582689161751323e-08, 'epoch': 0.98}
+
98%|█████████▊| 11727/11952 [23:07<22:00, 5.87s/it]
98%|█████████▊| 11728/11952 [23:13<22:02, 5.90s/it]
{'loss': 0.4701, 'learning_rate': 1.841792737844128e-08, 'epoch': 0.98}
+
98%|█████████▊| 11728/11952 [23:13<22:02, 5.90s/it]
98%|█████████▊| 11729/11952 [23:19<21:53, 5.89s/it]
{'loss': 0.4685, 'learning_rate': 1.8253898601002794e-08, 'epoch': 0.98}
+
98%|█████████▊| 11729/11952 [23:19<21:53, 5.89s/it]
98%|█████████▊| 11730/11952 [23:24<21:42, 5.87s/it]
{'loss': 0.4487, 'learning_rate': 1.8090602841479566e-08, 'epoch': 0.98}
+
98%|█████████▊| 11730/11952 [23:24<21:42, 5.87s/it]
98%|█████████▊| 11731/11952 [23:30<21:42, 5.90s/it]
{'loss': 0.4494, 'learning_rate': 1.792804011186533e-08, 'epoch': 0.98}
+
98%|█████████▊| 11731/11952 [23:30<21:42, 5.90s/it]
98%|█████████▊| 11732/11952 [23:36<21:16, 5.80s/it]
{'loss': 0.4415, 'learning_rate': 1.7766210424097207e-08, 'epoch': 0.98}
+
98%|█████████▊| 11732/11952 [23:36<21:16, 5.80s/it]
98%|█████████▊| 11733/11952 [23:42<21:10, 5.80s/it]
{'loss': 0.4635, 'learning_rate': 1.7605113790059024e-08, 'epoch': 0.98}
+
98%|█████████▊| 11733/11952 [23:42<21:10, 5.80s/it]
98%|█████████▊| 11734/11952 [23:48<21:18, 5.87s/it]
{'loss': 0.459, 'learning_rate': 1.744475022158243e-08, 'epoch': 0.98}
+
98%|█████████▊| 11734/11952 [23:48<21:18, 5.87s/it]
98%|█████████▊| 11735/11952 [23:53<21:03, 5.82s/it]
{'loss': 0.4558, 'learning_rate': 1.7285119730442446e-08, 'epoch': 0.98}
+
98%|█████████▊| 11735/11952 [23:53<21:03, 5.82s/it]
98%|█████████▊| 11736/11952 [23:59<20:53, 5.80s/it]
{'loss': 0.4716, 'learning_rate': 1.712622232836192e-08, 'epoch': 0.98}
+
98%|█████████▊| 11736/11952 [23:59<20:53, 5.80s/it]
98%|█████████▊| 11737/11952 [24:05<21:02, 5.87s/it]
{'loss': 0.4586, 'learning_rate': 1.6968058027009292e-08, 'epoch': 0.98}
+
98%|█████████▊| 11737/11952 [24:05<21:02, 5.87s/it]
98%|█████████▊| 11738/11952 [24:11<21:07, 5.92s/it]
{'loss': 0.4835, 'learning_rate': 1.6810626837999722e-08, 'epoch': 0.98}
+
98%|█████████▊| 11738/11952 [24:11<21:07, 5.92s/it]
98%|█████████▊| 11739/11952 [24:17<20:44, 5.84s/it]
{'loss': 0.4461, 'learning_rate': 1.6653928772895067e-08, 'epoch': 0.98}
+
98%|█████████▊| 11739/11952 [24:17<20:44, 5.84s/it]
98%|█████████▊| 11740/11952 [24:22<20:14, 5.73s/it]
{'loss': 0.4419, 'learning_rate': 1.649796384320168e-08, 'epoch': 0.98}
+
98%|█████████▊| 11740/11952 [24:22<20:14, 5.73s/it]
98%|█████████▊| 11741/11952 [24:28<20:03, 5.70s/it]
{'loss': 0.4625, 'learning_rate': 1.6342732060373733e-08, 'epoch': 0.98}
+
98%|█████████▊| 11741/11952 [24:28<20:03, 5.70s/it]
98%|█████████▊| 11742/11952 [24:34<20:16, 5.79s/it]
{'loss': 0.4593, 'learning_rate': 1.6188233435809887e-08, 'epoch': 0.98}
+
98%|█████████▊| 11742/11952 [24:34<20:16, 5.79s/it]
98%|█████████▊| 11743/11952 [24:40<20:01, 5.75s/it]
{'loss': 0.4429, 'learning_rate': 1.6034467980857727e-08, 'epoch': 0.98}
+
98%|█████████▊| 11743/11952 [24:40<20:01, 5.75s/it]
98%|█████████▊| 11744/11952 [24:45<19:39, 5.67s/it]
{'loss': 0.4512, 'learning_rate': 1.5881435706806002e-08, 'epoch': 0.98}
+
98%|█████████▊| 11744/11952 [24:45<19:39, 5.67s/it]
98%|█████████▊| 11745/11952 [24:51<19:30, 5.66s/it]
{'loss': 0.4645, 'learning_rate': 1.5729136624895723e-08, 'epoch': 0.98}
+
98%|█████████▊| 11745/11952 [24:51<19:30, 5.66s/it]
98%|█████████▊| 11746/11952 [24:56<19:27, 5.67s/it]
{'loss': 0.4584, 'learning_rate': 1.5577570746309057e-08, 'epoch': 0.98}
+
98%|█████████▊| 11746/11952 [24:56<19:27, 5.67s/it]
98%|█████████▊| 11747/11952 [25:02<19:21, 5.66s/it]
{'loss': 0.4629, 'learning_rate': 1.5426738082178206e-08, 'epoch': 0.98}
+
98%|█████████▊| 11747/11952 [25:02<19:21, 5.66s/it]
98%|█████████▊| 11748/11952 [25:08<19:19, 5.68s/it]
{'loss': 0.4594, 'learning_rate': 1.5276638643578756e-08, 'epoch': 0.98}
+
98%|█████████▊| 11748/11952 [25:08<19:19, 5.68s/it]
98%|█████████▊| 11749/11952 [25:13<19:06, 5.65s/it]
{'loss': 0.4414, 'learning_rate': 1.5127272441533004e-08, 'epoch': 0.98}
+
98%|█████████▊| 11749/11952 [25:13<19:06, 5.65s/it]4 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+3 1AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
98%|█████████▊| 11750/11952 [25:19<19:15, 5.72s/it]
{'loss': 0.4754, 'learning_rate': 1.497863948700995e-08, 'epoch': 0.98}
+
98%|█████████▊| 11750/11952 [25:19<19:15, 5.72s/it]
98%|█████████▊| 11751/11952 [25:25<19:10, 5.73s/it]
{'loss': 0.4389, 'learning_rate': 1.4830739790925308e-08, 'epoch': 0.98}
+
98%|█████████▊| 11751/11952 [25:25<19:10, 5.73s/it]
98%|█████████▊| 11752/11952 [25:31<19:28, 5.84s/it]
{'loss': 0.4845, 'learning_rate': 1.4683573364138171e-08, 'epoch': 0.98}
+
98%|█████████▊| 11752/11952 [25:31<19:28, 5.84s/it]
98%|█████████▊| 11753/11952 [25:37<19:28, 5.87s/it]
{'loss': 0.4612, 'learning_rate': 1.4537140217458778e-08, 'epoch': 0.98}
+
98%|█████████▊| 11753/11952 [25:37<19:28, 5.87s/it]
98%|█████████▊| 11754/11952 [25:43<19:01, 5.77s/it]
{'loss': 0.4562, 'learning_rate': 1.439144036163964e-08, 'epoch': 0.98}
+
98%|█████████▊| 11754/11952 [25:43<19:01, 5.77s/it]
98%|█████████▊| 11755/11952 [25:48<18:52, 5.75s/it]
{'loss': 0.4516, 'learning_rate': 1.4246473807378869e-08, 'epoch': 0.98}
+
98%|█████████▊| 11755/11952 [25:48<18:52, 5.75s/it]
98%|█████████▊| 11756/11952 [25:54<18:50, 5.77s/it]
{'loss': 0.4753, 'learning_rate': 1.41022405653235e-08, 'epoch': 0.98}
+
98%|█████████▊| 11756/11952 [25:54<18:50, 5.77s/it]
98%|█████████▊| 11757/11952 [26:00<18:41, 5.75s/it]
{'loss': 0.4545, 'learning_rate': 1.395874064606506e-08, 'epoch': 0.98}
+
98%|█████████▊| 11757/11952 [26:00<18:41, 5.75s/it]
98%|█████████▊| 11758/11952 [26:06<18:33, 5.74s/it]
{'loss': 0.4614, 'learning_rate': 1.381597406014179e-08, 'epoch': 0.98}
+
98%|█████████▊| 11758/11952 [26:06<18:33, 5.74s/it]
98%|█████████▊| 11759/11952 [26:11<18:24, 5.72s/it]
{'loss': 0.4941, 'learning_rate': 1.3673940818037523e-08, 'epoch': 0.98}
+
98%|█████████▊| 11759/11952 [26:11<18:24, 5.72s/it]
98%|█████████▊| 11760/11952 [26:17<18:23, 5.75s/it]
{'loss': 0.4754, 'learning_rate': 1.3532640930182806e-08, 'epoch': 0.98}
+
98%|█████████▊| 11760/11952 [26:17<18:23, 5.75s/it]
98%|█████████▊| 11761/11952 [26:23<18:28, 5.80s/it]
{'loss': 0.4795, 'learning_rate': 1.339207440695378e-08, 'epoch': 0.98}
+
98%|█████████▊| 11761/11952 [26:23<18:28, 5.80s/it]
98%|█████████▊| 11762/11952 [26:29<18:49, 5.95s/it]
{'loss': 0.4604, 'learning_rate': 1.3252241258673305e-08, 'epoch': 0.98}
+
98%|█████████▊| 11762/11952 [26:29<18:49, 5.95s/it]
98%|█████████▊| 11763/11952 [26:35<18:37, 5.91s/it]
{'loss': 0.4656, 'learning_rate': 1.3113141495610937e-08, 'epoch': 0.98}
+
98%|█████████▊| 11763/11952 [26:35<18:37, 5.91s/it]
98%|█████████▊| 11764/11952 [26:41<18:13, 5.82s/it]
{'loss': 0.4797, 'learning_rate': 1.2974775127980732e-08, 'epoch': 0.98}
+
98%|█████████▊| 11764/11952 [26:41<18:13, 5.82s/it]
98%|█████████▊| 11765/11952 [26:46<17:54, 5.74s/it]
{'loss': 0.4449, 'learning_rate': 1.283714216594345e-08, 'epoch': 0.98}
+
98%|█████████▊| 11765/11952 [26:46<17:54, 5.74s/it]
98%|█████████▊| 11766/11952 [26:52<17:57, 5.79s/it]
{'loss': 0.4625, 'learning_rate': 1.2700242619606562e-08, 'epoch': 0.98}
+
98%|█████████▊| 11766/11952 [26:52<17:57, 5.79s/it]
98%|█████████▊| 11767/11952 [26:58<17:54, 5.81s/it]
{'loss': 0.4635, 'learning_rate': 1.2564076499024247e-08, 'epoch': 0.98}
+
98%|█████████▊| 11767/11952 [26:58<17:54, 5.81s/it]
98%|█████████▊| 11768/11952 [27:04<17:44, 5.78s/it]
{'loss': 0.4668, 'learning_rate': 1.2428643814195174e-08, 'epoch': 0.98}
+
98%|█████████▊| 11768/11952 [27:04<17:44, 5.78s/it]
98%|█████████▊| 11769/11952 [27:10<17:46, 5.83s/it]
{'loss': 0.4709, 'learning_rate': 1.229394457506472e-08, 'epoch': 0.98}
+
98%|█████████▊| 11769/11952 [27:10<17:46, 5.83s/it]
98%|█████████▊| 11770/11952 [27:16<17:39, 5.82s/it]
{'loss': 0.4454, 'learning_rate': 1.2159978791524973e-08, 'epoch': 0.98}
+
98%|█████████▊| 11770/11952 [27:16<17:39, 5.82s/it]
98%|█████████▊| 11771/11952 [27:21<17:32, 5.81s/it]
{'loss': 0.474, 'learning_rate': 1.202674647341362e-08, 'epoch': 0.98}
+
98%|█████████▊| 11771/11952 [27:21<17:32, 5.81s/it]
98%|█████████▊| 11772/11952 [27:27<17:21, 5.79s/it]
{'loss': 0.4544, 'learning_rate': 1.1894247630516165e-08, 'epoch': 0.98}
+
98%|█████████▊| 11772/11952 [27:27<17:21, 5.79s/it]
99%|█████████▊| 11773/11952 [27:33<17:01, 5.71s/it]
{'loss': 0.4765, 'learning_rate': 1.1762482272560382e-08, 'epoch': 0.98}
+
99%|█████████▊| 11773/11952 [27:33<17:01, 5.71s/it]
99%|█████████▊| 11774/11952 [27:39<17:15, 5.82s/it]
{'loss': 0.4647, 'learning_rate': 1.1631450409224088e-08, 'epoch': 0.99}
+
99%|█████████▊| 11774/11952 [27:39<17:15, 5.82s/it]
99%|█████████▊| 11775/11952 [27:44<17:06, 5.80s/it]
{'loss': 0.4871, 'learning_rate': 1.1501152050128472e-08, 'epoch': 0.99}
+
99%|█████████▊| 11775/11952 [27:44<17:06, 5.80s/it]
99%|█████████▊| 11776/11952 [27:50<16:48, 5.73s/it]
{'loss': 0.4494, 'learning_rate': 1.1371587204843659e-08, 'epoch': 0.99}
+
99%|█████████▊| 11776/11952 [27:50<16:48, 5.73s/it]
99%|█████████▊| 11777/11952 [27:56<16:52, 5.78s/it]
{'loss': 0.4947, 'learning_rate': 1.124275588288426e-08, 'epoch': 0.99}
+
99%|█████████▊| 11777/11952 [27:56<16:52, 5.78s/it]
99%|█████████▊| 11778/11952 [28:02<16:45, 5.78s/it]
{'loss': 0.4682, 'learning_rate': 1.1114658093709373e-08, 'epoch': 0.99}
+
99%|█████████▊| 11778/11952 [28:02<16:45, 5.78s/it]
99%|█████████▊| 11779/11952 [28:08<16:45, 5.81s/it]
{'loss': 0.4486, 'learning_rate': 1.0987293846728141e-08, 'epoch': 0.99}
+
99%|█████████▊| 11779/11952 [28:08<16:45, 5.81s/it]
99%|█████████▊| 11780/11952 [28:13<16:38, 5.81s/it]
{'loss': 0.4312, 'learning_rate': 1.0860663151291973e-08, 'epoch': 0.99}
+
99%|█████████▊| 11780/11952 [28:13<16:38, 5.81s/it]
99%|█████████▊| 11781/11952 [28:19<16:28, 5.78s/it]
{'loss': 0.4613, 'learning_rate': 1.0734766016700093e-08, 'epoch': 0.99}
+
99%|█████████▊| 11781/11952 [28:19<16:28, 5.78s/it]
99%|█████████▊| 11782/11952 [28:25<16:28, 5.81s/it]
{'loss': 0.4764, 'learning_rate': 1.0609602452199553e-08, 'epoch': 0.99}
+
99%|█████████▊| 11782/11952 [28:25<16:28, 5.81s/it]
99%|█████████▊| 11783/11952 [28:31<16:27, 5.85s/it]
{'loss': 0.4795, 'learning_rate': 1.0485172466980776e-08, 'epoch': 0.99}
+
99%|█████████▊| 11783/11952 [28:31<16:27, 5.85s/it]
99%|█████████▊| 11784/11952 [28:37<16:26, 5.87s/it]
{'loss': 0.4585, 'learning_rate': 1.0361476070180899e-08, 'epoch': 0.99}
+
99%|█████████▊| 11784/11952 [28:37<16:26, 5.87s/it]
99%|█████████▊| 11785/11952 [28:43<16:22, 5.88s/it]
{'loss': 0.459, 'learning_rate': 1.0238513270884876e-08, 'epoch': 0.99}
+
99%|█████████▊| 11785/11952 [28:43<16:22, 5.88s/it]
99%|█████████▊| 11786/11952 [28:48<16:09, 5.84s/it]
{'loss': 0.4561, 'learning_rate': 1.0116284078121042e-08, 'epoch': 0.99}
+
99%|█████████▊| 11786/11952 [28:48<16:09, 5.84s/it]
99%|█████████▊| 11787/11952 [28:54<16:06, 5.86s/it]
{'loss': 0.4608, 'learning_rate': 9.994788500866659e-09, 'epoch': 0.99}
+
99%|█████████▊| 11787/11952 [28:54<16:06, 5.86s/it]
99%|█████████▊| 11788/11952 [29:00<16:03, 5.88s/it]
{'loss': 0.4812, 'learning_rate': 9.87402654804348e-09, 'epoch': 0.99}
+
99%|█████████▊| 11788/11952 [29:00<16:03, 5.88s/it]
99%|█████████▊| 11789/11952 [29:06<16:06, 5.93s/it]
{'loss': 0.4629, 'learning_rate': 9.753998228519967e-09, 'epoch': 0.99}
+
99%|█████████▊| 11789/11952 [29:06<16:06, 5.93s/it]
99%|█████████▊| 11790/11952 [29:12<15:59, 5.92s/it]
{'loss': 0.4569, 'learning_rate': 9.634703551110181e-09, 'epoch': 0.99}
+
99%|█████████▊| 11790/11952 [29:12<15:59, 5.92s/it]
99%|█████████▊| 11791/11952 [29:18<15:49, 5.90s/it]
{'loss': 0.4736, 'learning_rate': 9.516142524574889e-09, 'epoch': 0.99}
+
99%|█████████▊| 11791/11952 [29:18<15:49, 5.90s/it]
99%|█████████▊| 11792/11952 [29:24<15:34, 5.84s/it]
{'loss': 0.4595, 'learning_rate': 9.398315157619354e-09, 'epoch': 0.99}
+
99%|█████████▊| 11792/11952 [29:24<15:34, 5.84s/it]
99%|█████████▊| 11793/11952 [29:29<15:15, 5.76s/it]
{'loss': 0.456, 'learning_rate': 9.281221458898871e-09, 'epoch': 0.99}
+
99%|█████████▊| 11793/11952 [29:29<15:15, 5.76s/it]
99%|█████████▊| 11794/11952 [29:35<14:54, 5.66s/it]
{'loss': 0.4692, 'learning_rate': 9.164861437009897e-09, 'epoch': 0.99}
+
99%|█████████▊| 11794/11952 [29:35<14:54, 5.66s/it]
99%|█████████▊| 11795/11952 [29:40<14:42, 5.62s/it]
{'loss': 0.4546, 'learning_rate': 9.049235100500042e-09, 'epoch': 0.99}
+
99%|█████████▊| 11795/11952 [29:40<14:42, 5.62s/it]
99%|█████████▊| 11796/11952 [29:46<14:34, 5.60s/it]
{'loss': 0.4422, 'learning_rate': 8.93434245785696e-09, 'epoch': 0.99}
+
99%|█████████▊| 11796/11952 [29:46<14:34, 5.60s/it]
99%|█████████▊| 11797/11952 [29:51<14:26, 5.59s/it]
{'loss': 0.4557, 'learning_rate': 8.820183517521675e-09, 'epoch': 0.99}
+
99%|█████████▊| 11797/11952 [29:51<14:26, 5.59s/it]
99%|█████████▊| 11798/11952 [29:57<14:28, 5.64s/it]
{'loss': 0.4557, 'learning_rate': 8.706758287874151e-09, 'epoch': 0.99}
+
99%|█████████▊| 11798/11952 [29:57<14:28, 5.64s/it]
99%|█████████▊| 11799/11952 [30:03<14:30, 5.69s/it]
{'loss': 0.4656, 'learning_rate': 8.594066777246613e-09, 'epoch': 0.99}
+
99%|█████████▊| 11799/11952 [30:03<14:30, 5.69s/it]6 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+07 AutoResumeHook: Checking whether to suspend...
+ AutoResumeHook: Checking whether to suspend...
+
99%|█████████▊| 11800/11952 [30:09<14:33, 5.75s/it]
{'loss': 0.501, 'learning_rate': 8.482108993912441e-09, 'epoch': 0.99}
+
99%|█████████▊| 11800/11952 [30:09<14:33, 5.75s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11800/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11800/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11800/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
99%|█████████▊| 11801/11952 [30:39<32:34, 12.94s/it]
{'loss': 0.4627, 'learning_rate': 8.370884946095059e-09, 'epoch': 0.99}
+
99%|█████████▊| 11801/11952 [30:39<32:34, 12.94s/it]
99%|█████████▊| 11802/11952 [30:44<26:59, 10.80s/it]
{'loss': 0.4597, 'learning_rate': 8.260394641961267e-09, 'epoch': 0.99}
+
99%|█████████▊| 11802/11952 [30:44<26:59, 10.80s/it]
99%|█████████▉| 11803/11952 [30:50<23:06, 9.31s/it]
{'loss': 0.4844, 'learning_rate': 8.150638089624574e-09, 'epoch': 0.99}
+
99%|█████████▉| 11803/11952 [30:50<23:06, 9.31s/it]
99%|█████████▉| 11804/11952 [30:56<20:30, 8.32s/it]
{'loss': 0.4403, 'learning_rate': 8.04161529714631e-09, 'epoch': 0.99}
+
99%|█████████▉| 11804/11952 [30:56<20:30, 8.32s/it]
99%|█████████▉| 11805/11952 [31:02<18:27, 7.53s/it]
{'loss': 0.4704, 'learning_rate': 7.933326272532294e-09, 'epoch': 0.99}
+
99%|█████████▉| 11805/11952 [31:02<18:27, 7.53s/it]
99%|█████████▉| 11806/11952 [31:08<17:06, 7.03s/it]
{'loss': 0.4568, 'learning_rate': 7.825771023735051e-09, 'epoch': 0.99}
+
99%|█████████▉| 11806/11952 [31:08<17:06, 7.03s/it]
99%|█████████▉| 11807/11952 [31:14<16:12, 6.70s/it]
{'loss': 0.4704, 'learning_rate': 7.7189495586516e-09, 'epoch': 0.99}
+
99%|█████████▉| 11807/11952 [31:14<16:12, 6.70s/it]
99%|█████████▉| 11808/11952 [31:19<15:18, 6.38s/it]
{'loss': 0.4585, 'learning_rate': 7.612861885128997e-09, 'epoch': 0.99}
+
99%|█████████▉| 11808/11952 [31:19<15:18, 6.38s/it]
99%|█████████▉| 11809/11952 [31:25<14:39, 6.15s/it]
{'loss': 0.4507, 'learning_rate': 7.507508010955455e-09, 'epoch': 0.99}
+
99%|█████████▉| 11809/11952 [31:25<14:39, 6.15s/it]
99%|█████████▉| 11810/11952 [31:31<14:34, 6.15s/it]
{'loss': 0.4675, 'learning_rate': 7.40288794386812e-09, 'epoch': 0.99}
+
99%|█████████▉| 11810/11952 [31:31<14:34, 6.15s/it]
99%|█████████▉| 11811/11952 [31:37<14:31, 6.18s/it]
{'loss': 0.4525, 'learning_rate': 7.299001691550844e-09, 'epoch': 0.99}
+
99%|█████████▉| 11811/11952 [31:37<14:31, 6.18s/it]
99%|█████████▉| 11812/11952 [31:43<14:08, 6.06s/it]
{'loss': 0.4645, 'learning_rate': 7.195849261631971e-09, 'epoch': 0.99}
+
99%|█████████▉| 11812/11952 [31:43<14:08, 6.06s/it]
99%|█████████▉| 11813/11952 [31:49<13:54, 6.00s/it]
{'loss': 0.4757, 'learning_rate': 7.093430661686551e-09, 'epoch': 0.99}
+
99%|█████████▉| 11813/11952 [31:49<13:54, 6.00s/it]
99%|█████████▉| 11814/11952 [31:55<13:38, 5.93s/it]
{'loss': 0.4585, 'learning_rate': 6.991745899236346e-09, 'epoch': 0.99}
+
99%|█████████▉| 11814/11952 [31:55<13:38, 5.93s/it]
99%|█████████▉| 11815/11952 [32:01<13:24, 5.87s/it]
{'loss': 0.4569, 'learning_rate': 6.890794981748717e-09, 'epoch': 0.99}
+
99%|█████████▉| 11815/11952 [32:01<13:24, 5.87s/it]
99%|█████████▉| 11816/11952 [32:06<13:18, 5.87s/it]
{'loss': 0.4858, 'learning_rate': 6.79057791663551e-09, 'epoch': 0.99}
+
99%|█████████▉| 11816/11952 [32:06<13:18, 5.87s/it]
99%|█████████▉| 11817/11952 [32:12<13:12, 5.87s/it]
{'loss': 0.4416, 'learning_rate': 6.691094711258617e-09, 'epoch': 0.99}
+
99%|█████████▉| 11817/11952 [32:12<13:12, 5.87s/it]
99%|█████████▉| 11818/11952 [32:18<13:10, 5.90s/it]
{'loss': 0.4474, 'learning_rate': 6.5923453729221935e-09, 'epoch': 0.99}
+
99%|█████████▉| 11818/11952 [32:18<13:10, 5.90s/it]
99%|█████████▉| 11819/11952 [32:24<12:54, 5.82s/it]
{'loss': 0.4492, 'learning_rate': 6.4943299088771065e-09, 'epoch': 0.99}
+
99%|█████████▉| 11819/11952 [32:24<12:54, 5.82s/it]
99%|█████████▉| 11820/11952 [32:30<12:47, 5.82s/it]
{'loss': 0.4803, 'learning_rate': 6.397048326323152e-09, 'epoch': 0.99}
+
99%|█████████▉| 11820/11952 [32:30<12:47, 5.82s/it]
99%|█████████▉| 11821/11952 [32:35<12:38, 5.79s/it]
{'loss': 0.458, 'learning_rate': 6.300500632403505e-09, 'epoch': 0.99}
+
99%|█████████▉| 11821/11952 [32:35<12:38, 5.79s/it]
99%|█████████▉| 11822/11952 [32:41<12:29, 5.77s/it]
{'loss': 0.4613, 'learning_rate': 6.204686834208051e-09, 'epoch': 0.99}
+
99%|█████████▉| 11822/11952 [32:41<12:29, 5.77s/it]
99%|█████████▉| 11823/11952 [32:47<12:25, 5.78s/it]
{'loss': 0.4649, 'learning_rate': 6.1096069387733825e-09, 'epoch': 0.99}
+
99%|█████████▉| 11823/11952 [32:47<12:25, 5.78s/it]
99%|█████████▉| 11824/11952 [32:53<12:25, 5.83s/it]
{'loss': 0.4637, 'learning_rate': 6.015260953080582e-09, 'epoch': 0.99}
+
99%|█████████▉| 11824/11952 [32:53<12:25, 5.83s/it]
99%|█████████▉| 11825/11952 [32:59<12:25, 5.87s/it]
{'loss': 0.4679, 'learning_rate': 5.921648884059661e-09, 'epoch': 0.99}
+
99%|█████████▉| 11825/11952 [32:59<12:25, 5.87s/it]
99%|█████████▉| 11826/11952 [33:05<12:13, 5.82s/it]
{'loss': 0.4586, 'learning_rate': 5.828770738584011e-09, 'epoch': 0.99}
+
99%|█████████▉| 11826/11952 [33:05<12:13, 5.82s/it]
99%|█████████▉| 11827/11952 [33:10<12:07, 5.82s/it]
{'loss': 0.4494, 'learning_rate': 5.736626523474842e-09, 'epoch': 0.99}
+
99%|█████████▉| 11827/11952 [33:10<12:07, 5.82s/it]
99%|█████████▉| 11828/11952 [33:16<11:56, 5.78s/it]
{'loss': 0.446, 'learning_rate': 5.645216245497853e-09, 'epoch': 0.99}
+
99%|█████████▉| 11828/11952 [33:16<11:56, 5.78s/it]
99%|█████████▉| 11829/11952 [33:22<11:47, 5.75s/it]
{'loss': 0.4763, 'learning_rate': 5.554539911367673e-09, 'epoch': 0.99}
+
99%|█████████▉| 11829/11952 [33:22<11:47, 5.75s/it]
99%|█████████▉| 11830/11952 [33:27<11:34, 5.69s/it]
{'loss': 0.4616, 'learning_rate': 5.4645975277412004e-09, 'epoch': 0.99}
+
99%|█████████▉| 11830/11952 [33:27<11:34, 5.69s/it]
99%|█████████▉| 11831/11952 [33:33<11:30, 5.70s/it]
{'loss': 0.4542, 'learning_rate': 5.37538910122426e-09, 'epoch': 0.99}
+
99%|█████████▉| 11831/11952 [33:33<11:30, 5.70s/it]
99%|█████████▉| 11832/11952 [33:39<11:32, 5.77s/it]
{'loss': 0.4753, 'learning_rate': 5.2869146383682794e-09, 'epoch': 0.99}
+
99%|█████████▉| 11832/11952 [33:39<11:32, 5.77s/it]
99%|█████████▉| 11833/11952 [33:45<11:35, 5.84s/it]
{'loss': 0.488, 'learning_rate': 5.199174145670283e-09, 'epoch': 0.99}
+
99%|█████████▉| 11833/11952 [33:45<11:35, 5.84s/it]
99%|█████████▉| 11834/11952 [33:51<11:25, 5.81s/it]
{'loss': 0.4638, 'learning_rate': 5.112167629572895e-09, 'epoch': 0.99}
+
99%|█████████▉| 11834/11952 [33:51<11:25, 5.81s/it]
99%|█████████▉| 11835/11952 [33:57<11:27, 5.87s/it]
{'loss': 0.479, 'learning_rate': 5.02589509646656e-09, 'epoch': 0.99}
+
99%|█████████▉| 11835/11952 [33:57<11:27, 5.87s/it]
99%|█████████▉| 11836/11952 [34:03<11:19, 5.86s/it]
{'loss': 0.4608, 'learning_rate': 4.94035655268621e-09, 'epoch': 0.99}
+
99%|█████████▉| 11836/11952 [34:03<11:19, 5.86s/it]
99%|█████████▉| 11837/11952 [34:08<11:16, 5.88s/it]
{'loss': 0.4786, 'learning_rate': 4.855552004513486e-09, 'epoch': 0.99}
+
99%|█████████▉| 11837/11952 [34:08<11:16, 5.88s/it]
99%|█████████▉| 11838/11952 [34:14<11:03, 5.82s/it]
{'loss': 0.4579, 'learning_rate': 4.7714814581756305e-09, 'epoch': 0.99}
+
99%|█████████▉| 11838/11952 [34:14<11:03, 5.82s/it]
99%|█████████▉| 11839/11952 [34:20<10:56, 5.81s/it]
{'loss': 0.4622, 'learning_rate': 4.6881449198477035e-09, 'epoch': 0.99}
+
99%|█████████▉| 11839/11952 [34:20<10:56, 5.81s/it]
99%|█████████▉| 11840/11952 [34:26<10:51, 5.82s/it]
{'loss': 0.4534, 'learning_rate': 4.605542395648144e-09, 'epoch': 0.99}
+
99%|█████████▉| 11840/11952 [34:26<10:51, 5.82s/it]
99%|█████████▉| 11841/11952 [34:31<10:43, 5.80s/it]
{'loss': 0.469, 'learning_rate': 4.52367389164432e-09, 'epoch': 0.99}
+
99%|█████████▉| 11841/11952 [34:31<10:43, 5.80s/it]
99%|█████████▉| 11842/11952 [34:37<10:41, 5.83s/it]
{'loss': 0.4853, 'learning_rate': 4.44253941384698e-09, 'epoch': 0.99}
+
99%|█████████▉| 11842/11952 [34:37<10:41, 5.83s/it]
99%|█████████▉| 11843/11952 [34:43<10:33, 5.81s/it]
{'loss': 0.4447, 'learning_rate': 4.362138968214691e-09, 'epoch': 0.99}
+
99%|█████████▉| 11843/11952 [34:43<10:33, 5.81s/it]
99%|█████████▉| 11844/11952 [34:49<10:21, 5.75s/it]
{'loss': 0.4573, 'learning_rate': 4.282472560651618e-09, 'epoch': 0.99}
+
99%|█████████▉| 11844/11952 [34:49<10:21, 5.75s/it]
99%|█████████▉| 11845/11952 [34:55<10:19, 5.79s/it]
{'loss': 0.461, 'learning_rate': 4.203540197009748e-09, 'epoch': 0.99}
+
99%|█████████▉| 11845/11952 [34:55<10:19, 5.79s/it]
99%|█████████▉| 11846/11952 [35:00<10:06, 5.72s/it]
{'loss': 0.4492, 'learning_rate': 4.125341883083334e-09, 'epoch': 0.99}
+
99%|█████████▉| 11846/11952 [35:00<10:06, 5.72s/it]
99%|█████████▉| 11847/11952 [35:06<10:08, 5.79s/it]
{'loss': 0.4663, 'learning_rate': 4.047877624615559e-09, 'epoch': 0.99}
+
99%|█████████▉| 11847/11952 [35:06<10:08, 5.79s/it]
99%|█████████▉| 11848/11952 [35:12<09:57, 5.75s/it]
{'loss': 0.455, 'learning_rate': 3.971147427296318e-09, 'epoch': 0.99}
+
99%|█████████▉| 11848/11952 [35:12<09:57, 5.75s/it]
99%|█████████▉| 11849/11952 [35:17<09:48, 5.72s/it]
{'loss': 0.4424, 'learning_rate': 3.895151296758881e-09, 'epoch': 0.99}
+
99%|█████████▉| 11849/11952 [35:17<09:48, 5.72s/it]34 AutoResumeHook: Checking whether to suspend...AutoResumeHook: Checking whether to suspend...
+
+6 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+5 2AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
99%|█████████▉| 11850/11952 [35:24<09:54, 5.82s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4672, 'learning_rate': 3.81988923858434e-09, 'epoch': 0.99}
+
99%|█████████▉| 11850/11952 [35:24<09:54, 5.82s/it]
99%|█████████▉| 11851/11952 [35:29<09:47, 5.82s/it]
{'loss': 0.4656, 'learning_rate': 3.745361258300495e-09, 'epoch': 0.99}
+
99%|█████████▉| 11851/11952 [35:29<09:47, 5.82s/it]
99%|█████████▉| 11852/11952 [35:36<09:51, 5.92s/it]
{'loss': 0.4624, 'learning_rate': 3.6715673613796353e-09, 'epoch': 0.99}
+
99%|█████████▉| 11852/11952 [35:36<09:51, 5.92s/it]
99%|█████████▉| 11853/11952 [35:41<09:39, 5.85s/it]
{'loss': 0.4421, 'learning_rate': 3.59850755324076e-09, 'epoch': 0.99}
+
99%|█████████▉| 11853/11952 [35:41<09:39, 5.85s/it]
99%|█████████▉| 11854/11952 [35:47<09:25, 5.77s/it]
{'loss': 0.4816, 'learning_rate': 3.5261818392484657e-09, 'epoch': 0.99}
+
99%|█████████▉| 11854/11952 [35:47<09:25, 5.77s/it]
99%|█████████▉| 11855/11952 [35:53<09:19, 5.76s/it]
{'loss': 0.4464, 'learning_rate': 3.454590224716281e-09, 'epoch': 0.99}
+
99%|█████████▉| 11855/11952 [35:53<09:19, 5.76s/it]
99%|█████████▉| 11856/11952 [35:58<09:09, 5.73s/it]
{'loss': 0.45, 'learning_rate': 3.383732714900001e-09, 'epoch': 0.99}
+
99%|█████████▉| 11856/11952 [35:58<09:09, 5.73s/it]
99%|█████████▉| 11857/11952 [36:04<08:58, 5.67s/it]
{'loss': 0.4448, 'learning_rate': 3.313609315003241e-09, 'epoch': 0.99}
+
99%|█████████▉| 11857/11952 [36:04<08:58, 5.67s/it]
99%|█████████▉| 11858/11952 [36:09<08:54, 5.69s/it]
{'loss': 0.4695, 'learning_rate': 3.244220030175216e-09, 'epoch': 0.99}
+
99%|█████████▉| 11858/11952 [36:09<08:54, 5.69s/it]
99%|█████████▉| 11859/11952 [36:15<08:46, 5.66s/it]
{'loss': 0.4581, 'learning_rate': 3.175564865512959e-09, 'epoch': 0.99}
+
99%|█████████▉| 11859/11952 [36:15<08:46, 5.66s/it]
99%|█████████▉| 11860/11952 [36:21<08:49, 5.75s/it]
{'loss': 0.4873, 'learning_rate': 3.107643826055773e-09, 'epoch': 0.99}
+
99%|█████████▉| 11860/11952 [36:21<08:49, 5.75s/it]
99%|█████████▉| 11861/11952 [36:27<08:42, 5.74s/it]
{'loss': 0.4794, 'learning_rate': 3.04045691679411e-09, 'epoch': 0.99}
+
99%|█████████▉| 11861/11952 [36:27<08:42, 5.74s/it]
99%|█████████▉| 11862/11952 [36:33<08:40, 5.78s/it]
{'loss': 0.4446, 'learning_rate': 2.9740041426606915e-09, 'epoch': 0.99}
+
99%|█████████▉| 11862/11952 [36:33<08:40, 5.78s/it]
99%|█████████▉| 11863/11952 [36:39<08:44, 5.90s/it]
{'loss': 0.4744, 'learning_rate': 2.908285508536057e-09, 'epoch': 0.99}
+
99%|█████████▉| 11863/11952 [36:39<08:44, 5.90s/it]
99%|█████████▉| 11864/11952 [36:44<08:30, 5.81s/it]
{'loss': 0.442, 'learning_rate': 2.843301019245237e-09, 'epoch': 0.99}
+
99%|█████████▉| 11864/11952 [36:44<08:30, 5.81s/it]
99%|█████████▉| 11865/11952 [36:50<08:26, 5.82s/it]
{'loss': 0.46, 'learning_rate': 2.7790506795610793e-09, 'epoch': 0.99}
+
99%|█████████▉| 11865/11952 [36:50<08:26, 5.82s/it]
99%|█████████▉| 11866/11952 [36:56<08:19, 5.81s/it]
{'loss': 0.4449, 'learning_rate': 2.7155344942020324e-09, 'epoch': 0.99}
+
99%|█████████▉| 11866/11952 [36:56<08:19, 5.81s/it]
99%|█████████▉| 11867/11952 [37:02<08:13, 5.80s/it]
{'loss': 0.4606, 'learning_rate': 2.6527524678321424e-09, 'epoch': 0.99}
+
99%|█████████▉| 11867/11952 [37:02<08:13, 5.80s/it]
99%|█████████▉| 11868/11952 [37:08<08:16, 5.91s/it]
{'loss': 0.4512, 'learning_rate': 2.5907046050632767e-09, 'epoch': 0.99}
+
99%|█████████▉| 11868/11952 [37:08<08:16, 5.91s/it]
99%|█████████▉| 11869/11952 [37:14<08:13, 5.95s/it]
{'loss': 0.467, 'learning_rate': 2.5293909104495696e-09, 'epoch': 0.99}
+
99%|█████████▉| 11869/11952 [37:14<08:13, 5.95s/it]
99%|█████████▉| 11870/11952 [37:20<08:04, 5.91s/it]
{'loss': 0.4508, 'learning_rate': 2.4688113884940855e-09, 'epoch': 0.99}
+
99%|█████████▉| 11870/11952 [37:20<08:04, 5.91s/it]
99%|█████████▉| 11871/11952 [37:26<07:54, 5.86s/it]
{'loss': 0.4537, 'learning_rate': 2.4089660436477093e-09, 'epoch': 0.99}
+
99%|█████████▉| 11871/11952 [37:26<07:54, 5.86s/it]
99%|█████████▉| 11872/11952 [37:31<07:42, 5.79s/it]
{'loss': 0.4676, 'learning_rate': 2.3498548803024825e-09, 'epoch': 0.99}
+
99%|█████████▉| 11872/11952 [37:31<07:42, 5.79s/it]
99%|█████████▉| 11873/11952 [37:37<07:38, 5.81s/it]
{'loss': 0.472, 'learning_rate': 2.2914779028015976e-09, 'epoch': 0.99}
+
99%|█████████▉| 11873/11952 [37:37<07:38, 5.81s/it]
99%|█████████▉| 11874/11952 [37:43<07:33, 5.81s/it]
{'loss': 0.4748, 'learning_rate': 2.233835115430516e-09, 'epoch': 0.99}
+
99%|█████████▉| 11874/11952 [37:43<07:33, 5.81s/it]
99%|█████████▉| 11875/11952 [37:48<07:19, 5.71s/it]
{'loss': 0.4612, 'learning_rate': 2.1769265224225176e-09, 'epoch': 0.99}
+
99%|█████████▉| 11875/11952 [37:48<07:19, 5.71s/it]
99%|█████████▉| 11876/11952 [37:54<07:14, 5.72s/it]
{'loss': 0.4694, 'learning_rate': 2.1207521279575925e-09, 'epoch': 0.99}
+
99%|█████████▉| 11876/11952 [37:54<07:14, 5.72s/it]
99%|█████████▉| 11877/11952 [38:00<07:05, 5.68s/it]
{'loss': 0.4486, 'learning_rate': 2.065311936160219e-09, 'epoch': 0.99}
+
99%|█████████▉| 11877/11952 [38:00<07:05, 5.68s/it]
99%|█████████▉| 11878/11952 [38:05<07:03, 5.73s/it]
{'loss': 0.4707, 'learning_rate': 2.0106059511015853e-09, 'epoch': 0.99}
+
99%|█████████▉| 11878/11952 [38:05<07:03, 5.73s/it]
99%|█████████▉| 11879/11952 [38:12<07:06, 5.84s/it]
{'loss': 0.4409, 'learning_rate': 1.9566341767984774e-09, 'epoch': 0.99}
+
99%|█████████▉| 11879/11952 [38:12<07:06, 5.84s/it]
99%|█████████▉| 11880/11952 [38:17<06:58, 5.81s/it]
{'loss': 0.4728, 'learning_rate': 1.903396617216613e-09, 'epoch': 0.99}
+
99%|█████████▉| 11880/11952 [38:17<06:58, 5.81s/it]
99%|█████████▉| 11881/11952 [38:23<06:58, 5.89s/it]
{'loss': 0.4348, 'learning_rate': 1.8508932762628662e-09, 'epoch': 0.99}
+
99%|█████████▉| 11881/11952 [38:23<06:58, 5.89s/it]
99%|█████████▉| 11882/11952 [38:29<06:43, 5.77s/it]
{'loss': 0.4634, 'learning_rate': 1.7991241577952624e-09, 'epoch': 0.99}
+
99%|█████████▉| 11882/11952 [38:29<06:43, 5.77s/it]
99%|█████████▉| 11883/11952 [38:35<06:35, 5.73s/it]
{'loss': 0.4532, 'learning_rate': 1.7480892656129845e-09, 'epoch': 0.99}
+
99%|█████████▉| 11883/11952 [38:35<06:35, 5.73s/it]
99%|█████████▉| 11884/11952 [38:40<06:33, 5.79s/it]
{'loss': 0.4515, 'learning_rate': 1.697788603466366e-09, 'epoch': 0.99}
+
99%|█████████▉| 11884/11952 [38:40<06:33, 5.79s/it]
99%|█████████▉| 11885/11952 [38:46<06:31, 5.84s/it]
{'loss': 0.4701, 'learning_rate': 1.6482221750468984e-09, 'epoch': 0.99}
+
99%|█████████▉| 11885/11952 [38:46<06:31, 5.84s/it]
99%|█████████▉| 11886/11952 [38:52<06:27, 5.88s/it]
{'loss': 0.4458, 'learning_rate': 1.5993899839972239e-09, 'epoch': 0.99}
+
99%|█████████▉| 11886/11952 [38:52<06:27, 5.88s/it]
99%|█████████▉| 11887/11952 [38:58<06:19, 5.84s/it]
{'loss': 0.4809, 'learning_rate': 1.5512920339011416e-09, 'epoch': 0.99}
+
99%|█████████▉| 11887/11952 [38:58<06:19, 5.84s/it]
99%|█████████▉| 11888/11952 [39:04<06:08, 5.75s/it]
{'loss': 0.4552, 'learning_rate': 1.503928328291382e-09, 'epoch': 0.99}
+
99%|█████████▉| 11888/11952 [39:04<06:08, 5.75s/it]
99%|█████████▉| 11889/11952 [39:09<06:03, 5.77s/it]
{'loss': 0.4768, 'learning_rate': 1.4572988706462732e-09, 'epoch': 0.99}
+
99%|█████████▉| 11889/11952 [39:09<06:03, 5.77s/it]
99%|█████████▉| 11890/11952 [39:16<06:02, 5.85s/it]
{'loss': 0.4614, 'learning_rate': 1.4114036643897434e-09, 'epoch': 0.99}
+
99%|█████████▉| 11890/11952 [39:16<06:02, 5.85s/it]
99%|█████████▉| 11891/11952 [39:21<05:57, 5.85s/it]
{'loss': 0.4842, 'learning_rate': 1.3662427128924294e-09, 'epoch': 0.99}
+
99%|█████████▉| 11891/11952 [39:21<05:57, 5.85s/it]
99%|█████████▉| 11892/11952 [39:27<05:46, 5.78s/it]
{'loss': 0.4597, 'learning_rate': 1.3218160194716778e-09, 'epoch': 0.99}
+
99%|█████████▉| 11892/11952 [39:27<05:46, 5.78s/it]
100%|█████████▉| 11893/11952 [39:33<05:45, 5.85s/it]
{'loss': 0.456, 'learning_rate': 1.2781235873882136e-09, 'epoch': 1.0}
+
100%|█████████▉| 11893/11952 [39:33<05:45, 5.85s/it]
100%|█████████▉| 11894/11952 [39:39<05:34, 5.78s/it]
{'loss': 0.4666, 'learning_rate': 1.2351654198528018e-09, 'epoch': 1.0}
+
100%|█████████▉| 11894/11952 [39:39<05:34, 5.78s/it]
100%|█████████▉| 11895/11952 [39:45<05:35, 5.88s/it]
{'loss': 0.4657, 'learning_rate': 1.1929415200173656e-09, 'epoch': 1.0}
+
100%|█████████▉| 11895/11952 [39:45<05:35, 5.88s/it]
100%|█████████▉| 11896/11952 [39:51<05:28, 5.87s/it]
{'loss': 0.4713, 'learning_rate': 1.151451890984978e-09, 'epoch': 1.0}
+
100%|█████████▉| 11896/11952 [39:51<05:28, 5.87s/it]
100%|█████████▉| 11897/11952 [39:56<05:20, 5.84s/it]
{'loss': 0.4443, 'learning_rate': 1.1106965358009814e-09, 'epoch': 1.0}
+
100%|█████████▉| 11897/11952 [39:56<05:20, 5.84s/it]
100%|█████████▉| 11898/11952 [40:02<05:14, 5.82s/it]
{'loss': 0.4491, 'learning_rate': 1.0706754574596468e-09, 'epoch': 1.0}
+
100%|█████████▉| 11898/11952 [40:02<05:14, 5.82s/it]
100%|█████████▉| 11899/11952 [40:08<05:07, 5.79s/it]
{'loss': 0.4913, 'learning_rate': 1.0313886588986244e-09, 'epoch': 1.0}
+
100%|█████████▉| 11899/11952 [40:08<05:07, 5.79s/it]4 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+37 AutoResumeHook: Checking whether to suspend...
+AutoResumeHook: Checking whether to suspend...
+1 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+
100%|█████████▉| 11900/11952 [40:14<05:02, 5.82s/it]
{'loss': 0.4457, 'learning_rate': 9.928361430044941e-10, 'epoch': 1.0}
+
100%|█████████▉| 11900/11952 [40:14<05:02, 5.82s/it]saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/tmp-checkpoint-11900/mm_projector
+/lustre/fs12/portfolios/nvr/users/mmemmel/miniforge3/envs/vila/lib/python3.10/site-packages/torch/nn/modules/module.py:1802: UserWarning: Positional args are being deprecated, use kwargs instead. Refer to https://pytorch.org/docs/master/generated/torch.nn.Module.html#torch.nn.Module.state_dict for details.
+ warnings.warn(
+
100%|█████████▉| 11901/11952 [40:44<11:16, 13.26s/it]
{'loss': 0.4564, 'learning_rate': 9.550179126072146e-10, 'epoch': 1.0}
+
100%|█████████▉| 11901/11952 [40:44<11:16, 13.26s/it]
100%|█████████▉| 11902/11952 [40:51<09:16, 11.14s/it]
{'loss': 0.4475, 'learning_rate': 9.179339704834533e-10, 'epoch': 1.0}
+
100%|█████████▉| 11902/11952 [40:51<09:16, 11.14s/it]
100%|█████████▉| 11903/11952 [40:56<07:46, 9.52s/it]
{'loss': 0.4701, 'learning_rate': 8.815843193576979e-10, 'epoch': 1.0}
+
100%|█████████▉| 11903/11952 [40:56<07:46, 9.52s/it]
100%|█████████▉| 11904/11952 [41:02<06:41, 8.37s/it]
{'loss': 0.4604, 'learning_rate': 8.459689618989241e-10, 'epoch': 1.0}
+
100%|█████████▉| 11904/11952 [41:02<06:41, 8.37s/it]
100%|█████████▉| 11905/11952 [41:08<05:58, 7.62s/it]
{'loss': 0.4639, 'learning_rate': 8.110879007228178e-10, 'epoch': 1.0}
+
100%|█████████▉| 11905/11952 [41:08<05:58, 7.62s/it]Token indices sequence length is longer than the specified maximum sequence length for this model (4214 > 4096). Running this sequence through the model will result in indexing errors
+
100%|█████████▉| 11906/11952 [41:14<05:23, 7.04s/it]
{'loss': 0.4658, 'learning_rate': 7.769411383906633e-10, 'epoch': 1.0}
+
100%|█████████▉| 11906/11952 [41:14<05:23, 7.04s/it]
100%|█████████▉| 11907/11952 [41:19<04:59, 6.65s/it]
{'loss': 0.4539, 'learning_rate': 7.435286774104545e-10, 'epoch': 1.0}
+
100%|█████████▉| 11907/11952 [41:19<04:59, 6.65s/it]
100%|█████████▉| 11908/11952 [41:25<04:40, 6.36s/it]
{'loss': 0.4592, 'learning_rate': 7.108505202346739e-10, 'epoch': 1.0}
+
100%|█████████▉| 11908/11952 [41:25<04:40, 6.36s/it]
100%|█████████▉| 11909/11952 [41:31<04:24, 6.16s/it]
{'loss': 0.442, 'learning_rate': 6.789066692636237e-10, 'epoch': 1.0}
+
100%|█████████▉| 11909/11952 [41:31<04:24, 6.16s/it]
100%|█████████▉| 11910/11952 [41:36<04:11, 5.99s/it]
{'loss': 0.4526, 'learning_rate': 6.476971268443156e-10, 'epoch': 1.0}
+
100%|█████████▉| 11910/11952 [41:36<04:11, 5.99s/it]
100%|█████████▉| 11911/11952 [41:42<04:06, 6.02s/it]
{'loss': 0.4614, 'learning_rate': 6.172218952671394e-10, 'epoch': 1.0}
+
100%|█████████▉| 11911/11952 [41:42<04:06, 6.02s/it]
100%|█████████▉| 11912/11952 [41:48<04:01, 6.03s/it]
{'loss': 0.449, 'learning_rate': 5.874809767703049e-10, 'epoch': 1.0}
+
100%|█████████▉| 11912/11952 [41:48<04:01, 6.03s/it]
100%|█████████▉| 11913/11952 [41:54<03:49, 5.89s/it]
{'loss': 0.4503, 'learning_rate': 5.58474373538731e-10, 'epoch': 1.0}
+
100%|█████████▉| 11913/11952 [41:54<03:49, 5.89s/it]
100%|█████████▉| 11914/11952 [42:00<03:40, 5.80s/it]
{'loss': 0.4608, 'learning_rate': 5.302020877018255e-10, 'epoch': 1.0}
+
100%|█████████▉| 11914/11952 [42:00<03:40, 5.80s/it]
100%|█████████▉| 11915/11952 [42:05<03:31, 5.71s/it]
{'loss': 0.4489, 'learning_rate': 5.026641213357054e-10, 'epoch': 1.0}
+
100%|█████████▉| 11915/11952 [42:05<03:31, 5.71s/it]
100%|█████████▉| 11916/11952 [42:11<03:24, 5.69s/it]
{'loss': 0.4484, 'learning_rate': 4.758604764631969e-10, 'epoch': 1.0}
+
100%|█████████▉| 11916/11952 [42:11<03:24, 5.69s/it]
100%|█████████▉| 11917/11952 [42:16<03:18, 5.67s/it]
{'loss': 0.4652, 'learning_rate': 4.4979115505272566e-10, 'epoch': 1.0}
+
100%|█████████▉| 11917/11952 [42:16<03:18, 5.67s/it]
100%|█████████▉| 11918/11952 [42:22<03:14, 5.73s/it]
{'loss': 0.4656, 'learning_rate': 4.2445615901831607e-10, 'epoch': 1.0}
+
100%|█████████▉| 11918/11952 [42:22<03:14, 5.73s/it]
100%|█████████▉| 11919/11952 [42:28<03:11, 5.80s/it]
{'loss': 0.4683, 'learning_rate': 3.998554902195917e-10, 'epoch': 1.0}
+
100%|█████████▉| 11919/11952 [42:28<03:11, 5.80s/it]
100%|█████████▉| 11920/11952 [42:34<03:04, 5.77s/it]
{'loss': 0.4503, 'learning_rate': 3.7598915046510587e-10, 'epoch': 1.0}
+
100%|█████████▉| 11920/11952 [42:34<03:04, 5.77s/it]
100%|█████████▉| 11921/11952 [42:40<02:59, 5.78s/it]
{'loss': 0.489, 'learning_rate': 3.528571415056803e-10, 'epoch': 1.0}
+
100%|█████████▉| 11921/11952 [42:40<02:59, 5.78s/it]
100%|█████████▉| 11922/11952 [42:45<02:52, 5.74s/it]
{'loss': 0.4592, 'learning_rate': 3.304594650410664e-10, 'epoch': 1.0}
+
100%|█████████▉| 11922/11952 [42:45<02:52, 5.74s/it]/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/VILA/llava/model/llava_arch.py:397: UserWarning: Inputs truncated!
+ warnings.warn("Inputs truncated!")
+
100%|█████████▉| 11923/11952 [42:51<02:48, 5.80s/it]
{'loss': 0.4751, 'learning_rate': 3.0879612271550454e-10, 'epoch': 1.0}
+
100%|█████████▉| 11923/11952 [42:51<02:48, 5.80s/it]
100%|█████████▉| 11924/11952 [42:57<02:41, 5.78s/it]
{'loss': 0.466, 'learning_rate': 2.878671161199442e-10, 'epoch': 1.0}
+
100%|█████████▉| 11924/11952 [42:57<02:41, 5.78s/it]
100%|█████████▉| 11925/11952 [43:03<02:34, 5.74s/it]
{'loss': 0.45, 'learning_rate': 2.676724467920444e-10, 'epoch': 1.0}
+
100%|█████████▉| 11925/11952 [43:03<02:34, 5.74s/it]
100%|█████████▉| 11926/11952 [43:09<02:30, 5.80s/it]
{'loss': 0.4598, 'learning_rate': 2.482121162139528e-10, 'epoch': 1.0}
+
100%|█████████▉| 11926/11952 [43:09<02:30, 5.80s/it]
100%|█████████▉| 11927/11952 [43:15<02:27, 5.89s/it]
{'loss': 0.505, 'learning_rate': 2.2948612581452646e-10, 'epoch': 1.0}
+
100%|█████████▉| 11927/11952 [43:15<02:27, 5.89s/it]
100%|█████████▉| 11928/11952 [43:21<02:22, 5.94s/it]
{'loss': 0.4551, 'learning_rate': 2.114944769704419e-10, 'epoch': 1.0}
+
100%|█████████▉| 11928/11952 [43:21<02:22, 5.94s/it]
100%|█████████▉| 11929/11952 [43:26<02:14, 5.86s/it]
{'loss': 0.4501, 'learning_rate': 1.9423717100175432e-10, 'epoch': 1.0}
+
100%|█████████▉| 11929/11952 [43:26<02:14, 5.86s/it]
100%|█████████▉| 11930/11952 [43:32<02:08, 5.86s/it]
{'loss': 0.4932, 'learning_rate': 1.777142091752282e-10, 'epoch': 1.0}
+
100%|█████████▉| 11930/11952 [43:32<02:08, 5.86s/it]
100%|█████████▉| 11931/11952 [43:38<02:01, 5.79s/it]
{'loss': 0.455, 'learning_rate': 1.619255927054475e-10, 'epoch': 1.0}
+
100%|█████████▉| 11931/11952 [43:38<02:01, 5.79s/it]
100%|█████████▉| 11932/11952 [43:43<01:54, 5.74s/it]
{'loss': 0.4599, 'learning_rate': 1.468713227514851e-10, 'epoch': 1.0}
+
100%|█████████▉| 11932/11952 [43:43<01:54, 5.74s/it]
100%|█████████▉| 11933/11952 [43:49<01:49, 5.76s/it]
{'loss': 0.4578, 'learning_rate': 1.3255140041912306e-10, 'epoch': 1.0}
+
100%|█████████▉| 11933/11952 [43:49<01:49, 5.76s/it]
100%|█████████▉| 11934/11952 [43:55<01:44, 5.81s/it]
{'loss': 0.4442, 'learning_rate': 1.1896582675974266e-10, 'epoch': 1.0}
+
100%|█████████▉| 11934/11952 [43:55<01:44, 5.81s/it]
100%|█████████▉| 11935/11952 [44:01<01:40, 5.89s/it]
{'loss': 0.464, 'learning_rate': 1.0611460277032415e-10, 'epoch': 1.0}
+
100%|█████████▉| 11935/11952 [44:01<01:40, 5.89s/it]
100%|█████████▉| 11936/11952 [44:07<01:33, 5.86s/it]
{'loss': 0.4523, 'learning_rate': 9.399772939455709e-11, 'epoch': 1.0}
+
100%|█████████▉| 11936/11952 [44:07<01:33, 5.86s/it]
100%|█████████▉| 11937/11952 [44:13<01:27, 5.83s/it]
{'loss': 0.4593, 'learning_rate': 8.261520752395059e-11, 'epoch': 1.0}
+
100%|█████████▉| 11937/11952 [44:13<01:27, 5.83s/it]
100%|█████████▉| 11938/11952 [44:19<01:21, 5.81s/it]
{'loss': 0.4764, 'learning_rate': 7.19670379922821e-11, 'epoch': 1.0}
+
100%|█████████▉| 11938/11952 [44:19<01:21, 5.81s/it]
100%|█████████▉| 11939/11952 [44:24<01:15, 5.82s/it]
{'loss': 0.4706, 'learning_rate': 6.205322158336913e-11, 'epoch': 1.0}
+
100%|█████████▉| 11939/11952 [44:24<01:15, 5.82s/it]
100%|█████████▉| 11940/11952 [44:30<01:10, 5.84s/it]
{'loss': 0.4774, 'learning_rate': 5.287375902440772e-11, 'epoch': 1.0}
+
100%|█████████▉| 11940/11952 [44:30<01:10, 5.84s/it]
100%|█████████▉| 11941/11952 [44:36<01:03, 5.73s/it]
{'loss': 0.4738, 'learning_rate': 4.442865098930327e-11, 'epoch': 1.0}
+
100%|█████████▉| 11941/11952 [44:36<01:03, 5.73s/it]
100%|█████████▉| 11942/11952 [44:41<00:57, 5.72s/it]
{'loss': 0.4651, 'learning_rate': 3.671789809867043e-11, 'epoch': 1.0}
+
100%|█████████▉| 11942/11952 [44:41<00:57, 5.72s/it]
100%|█████████▉| 11943/11952 [44:48<00:52, 5.82s/it]
{'loss': 0.474, 'learning_rate': 2.974150091761274e-11, 'epoch': 1.0}
+
100%|█████████▉| 11943/11952 [44:48<00:52, 5.82s/it]
100%|█████████▉| 11944/11952 [44:53<00:46, 5.84s/it]
{'loss': 0.4763, 'learning_rate': 2.349945996016345e-11, 'epoch': 1.0}
+
100%|█████████▉| 11944/11952 [44:53<00:46, 5.84s/it]
100%|█████████▉| 11945/11952 [44:59<00:40, 5.81s/it]
{'loss': 0.457, 'learning_rate': 1.7991775683734448e-11, 'epoch': 1.0}
+
100%|█████████▉| 11945/11952 [44:59<00:40, 5.81s/it]
100%|█████████▉| 11946/11952 [45:05<00:34, 5.76s/it]
{'loss': 0.466, 'learning_rate': 1.3218448492446912e-11, 'epoch': 1.0}
+
100%|█████████▉| 11946/11952 [45:05<00:34, 5.76s/it]
100%|█████████▉| 11947/11952 [45:10<00:28, 5.71s/it]
{'loss': 0.45, 'learning_rate': 9.179478738241542e-12, 'epoch': 1.0}
+
100%|█████████▉| 11947/11952 [45:10<00:28, 5.71s/it]
100%|█████████▉| 11948/11952 [45:16<00:22, 5.66s/it]
{'loss': 0.4781, 'learning_rate': 5.874866715327443e-12, 'epoch': 1.0}
+
100%|█████████▉| 11948/11952 [45:16<00:22, 5.66s/it]
100%|█████████▉| 11949/11952 [45:22<00:17, 5.73s/it]
{'loss': 0.4753, 'learning_rate': 3.3046126690639002e-12, 'epoch': 1.0}
+
100%|█████████▉| 11949/11952 [45:22<00:17, 5.73s/it]4 AutoResumeHook: Checking whether to suspend...
+3 AutoResumeHook: Checking whether to suspend...
+2 AutoResumeHook: Checking whether to suspend...
+5 AutoResumeHook: Checking whether to suspend...
+6 AutoResumeHook: Checking whether to suspend...
+0 AutoResumeHook: Checking whether to suspend...
+7 AutoResumeHook: Checking whether to suspend...
+
100%|█████████▉| 11950/11952 [45:28<00:11, 5.72s/it]1 AutoResumeHook: Checking whether to suspend...
+
{'loss': 0.4425, 'learning_rate': 1.4687167870786056e-12, 'epoch': 1.0}
+
100%|█████████▉| 11950/11952 [45:28<00:11, 5.72s/it]
100%|█████████▉| 11951/11952 [45:33<00:05, 5.77s/it]
{'loss': 0.4705, 'learning_rate': 3.6717920370854533e-13, 'epoch': 1.0}
+
100%|█████████▉| 11951/11952 [45:33<00:05, 5.77s/it]
100%|██████████| 11952/11952 [45:40<00:00, 5.88s/it]
{'loss': 0.4708, 'learning_rate': 0.0, 'epoch': 1.0}
+
100%|██████████| 11952/11952 [45:40<00:00, 5.88s/it]
{'train_runtime': 2743.4428, 'train_samples_per_second': 1115.374, 'train_steps_per_second': 4.357, 'train_loss': 0.017490314920663514, 'epoch': 1.0}
+
100%|██████████| 11952/11952 [45:41<00:00, 5.88s/it]
100%|██████████| 11952/11952 [45:41<00:00, 4.36it/s]
+saving llm to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/llm
+saving vision_tower to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/vision_tower
+saving mm_projector to /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/mm_projector
+[1;34mwandb[0m: 🚀 View run [33mvila_3b_path_mask[0m at: [34mhttps://wandb.ai/memmelma/VILA/runs/nh1vjmt9[0m
+[1;34mwandb[0m: Find logs at: [1;35m../../../../../../../../fs12/portfolios/nvr/projects/nvr_srl_simpler/users/mmemmel/projects/vila/VILA/wandb/run-20250611_142850-nh1vjmt9/logs[0m
+srun: job 8858209 queued and waiting for resources
+srun: job 8858209 has been allocated resources
+wandb: Currently logged in as: memmelma. Use `wandb login --relogin` to force relogin
+MASTER_ADDR=batch-block5-00334
+JobID: 8858209 | Full list: batch-block5-00334
+NETWORK=Efficient-Large-Model/VILA1.5-3b
+WARNING:torch.distributed.run:
+*****************************************
+Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
+*****************************************
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+Did not find AutoResume SDK!
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:52,669] [INFO] [real_accelerator.py:110:get_accelerator] Setting ds_accelerator to cuda (auto detect)
+[2025-06-11 15:17:55,260] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,260] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,259] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,260] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,260] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,260] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 15:17:55,260] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 15:17:55,260] [INFO] [comm.py:625:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+[2025-06-11 15:17:55,260] [WARNING] [comm.py:152:init_deepspeed_backend] NCCL backend in DeepSpeed not yet implemented
+[2025-06-11 15:17:55,260] [INFO] [comm.py:594:init_distributed] cdb=None
+Models has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp training
+Models has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp trainingModels has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp training
+
+Models has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp training
+Models has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp training
+Models has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp training
+Models has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp training
+Models has been ready under /lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask. Skipp training
diff --git a/trainer_state.json b/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..f2bef9b30825b13ed30b44195dbf26400157d28f
--- /dev/null
+++ b/trainer_state.json
@@ -0,0 +1,71742 @@
+{
+ "best_metric": null,
+ "best_model_checkpoint": null,
+ "epoch": 0.9999581677473331,
+ "eval_steps": 500,
+ "global_step": 11952,
+ "is_hyper_param_search": false,
+ "is_local_process_zero": true,
+ "is_world_process_zero": true,
+ "log_history": [
+ {
+ "epoch": 0.0,
+ "learning_rate": 5.571030640668524e-08,
+ "loss": 0.8031,
+ "step": 1
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.1142061281337048e-07,
+ "loss": 0.8071,
+ "step": 2
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.6713091922005573e-07,
+ "loss": 0.7913,
+ "step": 3
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.2284122562674096e-07,
+ "loss": 0.8033,
+ "step": 4
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.785515320334262e-07,
+ "loss": 0.805,
+ "step": 5
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.3426183844011146e-07,
+ "loss": 0.8159,
+ "step": 6
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.899721448467967e-07,
+ "loss": 0.8095,
+ "step": 7
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 4.456824512534819e-07,
+ "loss": 0.7973,
+ "step": 8
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 5.013927576601672e-07,
+ "loss": 0.7913,
+ "step": 9
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 5.571030640668524e-07,
+ "loss": 0.8118,
+ "step": 10
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 6.128133704735377e-07,
+ "loss": 0.7926,
+ "step": 11
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 6.685236768802229e-07,
+ "loss": 0.7805,
+ "step": 12
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 7.242339832869082e-07,
+ "loss": 0.7913,
+ "step": 13
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 7.799442896935934e-07,
+ "loss": 0.7994,
+ "step": 14
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 8.356545961002786e-07,
+ "loss": 0.7979,
+ "step": 15
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 8.913649025069638e-07,
+ "loss": 0.7736,
+ "step": 16
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 9.470752089136491e-07,
+ "loss": 0.7817,
+ "step": 17
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.0027855153203343e-06,
+ "loss": 0.7678,
+ "step": 18
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.0584958217270195e-06,
+ "loss": 0.7265,
+ "step": 19
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.1142061281337048e-06,
+ "loss": 0.7331,
+ "step": 20
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.16991643454039e-06,
+ "loss": 0.7349,
+ "step": 21
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.2256267409470754e-06,
+ "loss": 0.7219,
+ "step": 22
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.2813370473537607e-06,
+ "loss": 0.7335,
+ "step": 23
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.3370473537604459e-06,
+ "loss": 0.7127,
+ "step": 24
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.392757660167131e-06,
+ "loss": 0.7235,
+ "step": 25
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.4484679665738164e-06,
+ "loss": 0.6903,
+ "step": 26
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.5041782729805015e-06,
+ "loss": 0.6748,
+ "step": 27
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.5598885793871869e-06,
+ "loss": 0.6899,
+ "step": 28
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.615598885793872e-06,
+ "loss": 0.6611,
+ "step": 29
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.6713091922005572e-06,
+ "loss": 0.6656,
+ "step": 30
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.7270194986072425e-06,
+ "loss": 0.6954,
+ "step": 31
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.7827298050139277e-06,
+ "loss": 0.683,
+ "step": 32
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.838440111420613e-06,
+ "loss": 0.6812,
+ "step": 33
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.8941504178272982e-06,
+ "loss": 0.6796,
+ "step": 34
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 1.9498607242339835e-06,
+ "loss": 0.6593,
+ "step": 35
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.0055710306406687e-06,
+ "loss": 0.6622,
+ "step": 36
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.061281337047354e-06,
+ "loss": 0.6774,
+ "step": 37
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.116991643454039e-06,
+ "loss": 0.6606,
+ "step": 38
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.1727019498607245e-06,
+ "loss": 0.658,
+ "step": 39
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.2284122562674097e-06,
+ "loss": 0.6551,
+ "step": 40
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.284122562674095e-06,
+ "loss": 0.621,
+ "step": 41
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.33983286908078e-06,
+ "loss": 0.6396,
+ "step": 42
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.395543175487465e-06,
+ "loss": 0.6604,
+ "step": 43
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.4512534818941507e-06,
+ "loss": 0.6269,
+ "step": 44
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.506963788300836e-06,
+ "loss": 0.6314,
+ "step": 45
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.5626740947075214e-06,
+ "loss": 0.623,
+ "step": 46
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.618384401114206e-06,
+ "loss": 0.6306,
+ "step": 47
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.6740947075208917e-06,
+ "loss": 0.6014,
+ "step": 48
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.729805013927577e-06,
+ "loss": 0.6312,
+ "step": 49
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.785515320334262e-06,
+ "loss": 0.617,
+ "step": 50
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.841225626740947e-06,
+ "loss": 0.6195,
+ "step": 51
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.8969359331476327e-06,
+ "loss": 0.6213,
+ "step": 52
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 2.9526462395543174e-06,
+ "loss": 0.6236,
+ "step": 53
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.008356545961003e-06,
+ "loss": 0.6158,
+ "step": 54
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.064066852367688e-06,
+ "loss": 0.5968,
+ "step": 55
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.1197771587743737e-06,
+ "loss": 0.6257,
+ "step": 56
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.1754874651810585e-06,
+ "loss": 0.6096,
+ "step": 57
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.231197771587744e-06,
+ "loss": 0.6253,
+ "step": 58
+ },
+ {
+ "epoch": 0.0,
+ "learning_rate": 3.286908077994429e-06,
+ "loss": 0.6213,
+ "step": 59
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.3426183844011143e-06,
+ "loss": 0.6041,
+ "step": 60
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.3983286908077995e-06,
+ "loss": 0.6098,
+ "step": 61
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.454038997214485e-06,
+ "loss": 0.614,
+ "step": 62
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.5097493036211698e-06,
+ "loss": 0.6163,
+ "step": 63
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.5654596100278553e-06,
+ "loss": 0.6006,
+ "step": 64
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.6211699164345405e-06,
+ "loss": 0.5992,
+ "step": 65
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.676880222841226e-06,
+ "loss": 0.6079,
+ "step": 66
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.7325905292479116e-06,
+ "loss": 0.607,
+ "step": 67
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.7883008356545963e-06,
+ "loss": 0.6128,
+ "step": 68
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.844011142061282e-06,
+ "loss": 0.6046,
+ "step": 69
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.899721448467967e-06,
+ "loss": 0.5908,
+ "step": 70
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 3.955431754874652e-06,
+ "loss": 0.6016,
+ "step": 71
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.011142061281337e-06,
+ "loss": 0.615,
+ "step": 72
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.0668523676880225e-06,
+ "loss": 0.6117,
+ "step": 73
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.122562674094708e-06,
+ "loss": 0.5916,
+ "step": 74
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.178272980501394e-06,
+ "loss": 0.6005,
+ "step": 75
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.233983286908078e-06,
+ "loss": 0.5826,
+ "step": 76
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.289693593314764e-06,
+ "loss": 0.6087,
+ "step": 77
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.345403899721449e-06,
+ "loss": 0.5953,
+ "step": 78
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.401114206128134e-06,
+ "loss": 0.581,
+ "step": 79
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.456824512534819e-06,
+ "loss": 0.5961,
+ "step": 80
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.5125348189415045e-06,
+ "loss": 0.5837,
+ "step": 81
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.56824512534819e-06,
+ "loss": 0.5881,
+ "step": 82
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.623955431754875e-06,
+ "loss": 0.6076,
+ "step": 83
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.67966573816156e-06,
+ "loss": 0.5977,
+ "step": 84
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.735376044568246e-06,
+ "loss": 0.6113,
+ "step": 85
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.79108635097493e-06,
+ "loss": 0.5748,
+ "step": 86
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.846796657381616e-06,
+ "loss": 0.6021,
+ "step": 87
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.902506963788301e-06,
+ "loss": 0.5738,
+ "step": 88
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 4.9582172701949865e-06,
+ "loss": 0.5804,
+ "step": 89
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.013927576601672e-06,
+ "loss": 0.5796,
+ "step": 90
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.069637883008357e-06,
+ "loss": 0.591,
+ "step": 91
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.125348189415043e-06,
+ "loss": 0.5811,
+ "step": 92
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.181058495821727e-06,
+ "loss": 0.5667,
+ "step": 93
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.236768802228412e-06,
+ "loss": 0.6095,
+ "step": 94
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.292479108635098e-06,
+ "loss": 0.5935,
+ "step": 95
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.3481894150417834e-06,
+ "loss": 0.57,
+ "step": 96
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.403899721448468e-06,
+ "loss": 0.5865,
+ "step": 97
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.459610027855154e-06,
+ "loss": 0.6119,
+ "step": 98
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.515320334261839e-06,
+ "loss": 0.6189,
+ "step": 99
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.571030640668524e-06,
+ "loss": 0.6001,
+ "step": 100
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.62674094707521e-06,
+ "loss": 0.5787,
+ "step": 101
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.682451253481894e-06,
+ "loss": 0.5809,
+ "step": 102
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.7381615598885795e-06,
+ "loss": 0.5708,
+ "step": 103
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.7938718662952654e-06,
+ "loss": 0.6033,
+ "step": 104
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.849582172701951e-06,
+ "loss": 0.5802,
+ "step": 105
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.905292479108635e-06,
+ "loss": 0.587,
+ "step": 106
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 5.961002785515321e-06,
+ "loss": 0.5665,
+ "step": 107
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.016713091922006e-06,
+ "loss": 0.5883,
+ "step": 108
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.072423398328692e-06,
+ "loss": 0.5707,
+ "step": 109
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.128133704735376e-06,
+ "loss": 0.5862,
+ "step": 110
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.1838440111420615e-06,
+ "loss": 0.5918,
+ "step": 111
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.2395543175487475e-06,
+ "loss": 0.564,
+ "step": 112
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.295264623955433e-06,
+ "loss": 0.571,
+ "step": 113
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.350974930362117e-06,
+ "loss": 0.5589,
+ "step": 114
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.406685236768803e-06,
+ "loss": 0.5875,
+ "step": 115
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.462395543175488e-06,
+ "loss": 0.5771,
+ "step": 116
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.518105849582173e-06,
+ "loss": 0.5563,
+ "step": 117
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.573816155988858e-06,
+ "loss": 0.5947,
+ "step": 118
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.6295264623955435e-06,
+ "loss": 0.5625,
+ "step": 119
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.685236768802229e-06,
+ "loss": 0.5658,
+ "step": 120
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.740947075208915e-06,
+ "loss": 0.5672,
+ "step": 121
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.796657381615599e-06,
+ "loss": 0.5932,
+ "step": 122
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.852367688022284e-06,
+ "loss": 0.5779,
+ "step": 123
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.90807799442897e-06,
+ "loss": 0.5683,
+ "step": 124
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 6.963788300835655e-06,
+ "loss": 0.565,
+ "step": 125
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.0194986072423395e-06,
+ "loss": 0.5455,
+ "step": 126
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.0752089136490255e-06,
+ "loss": 0.5816,
+ "step": 127
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.130919220055711e-06,
+ "loss": 0.5675,
+ "step": 128
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.186629526462397e-06,
+ "loss": 0.575,
+ "step": 129
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.242339832869081e-06,
+ "loss": 0.5656,
+ "step": 130
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.298050139275766e-06,
+ "loss": 0.5686,
+ "step": 131
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.353760445682452e-06,
+ "loss": 0.5917,
+ "step": 132
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.409470752089137e-06,
+ "loss": 0.5935,
+ "step": 133
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.465181058495823e-06,
+ "loss": 0.5816,
+ "step": 134
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.5208913649025075e-06,
+ "loss": 0.5658,
+ "step": 135
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.576601671309193e-06,
+ "loss": 0.5707,
+ "step": 136
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.632311977715879e-06,
+ "loss": 0.5605,
+ "step": 137
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.688022284122564e-06,
+ "loss": 0.5882,
+ "step": 138
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.743732590529249e-06,
+ "loss": 0.5645,
+ "step": 139
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.799442896935934e-06,
+ "loss": 0.5875,
+ "step": 140
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.85515320334262e-06,
+ "loss": 0.5554,
+ "step": 141
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.910863509749304e-06,
+ "loss": 0.5579,
+ "step": 142
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 7.96657381615599e-06,
+ "loss": 0.5873,
+ "step": 143
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.022284122562675e-06,
+ "loss": 0.5785,
+ "step": 144
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.07799442896936e-06,
+ "loss": 0.5596,
+ "step": 145
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.133704735376045e-06,
+ "loss": 0.5765,
+ "step": 146
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.18941504178273e-06,
+ "loss": 0.5682,
+ "step": 147
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.245125348189415e-06,
+ "loss": 0.5593,
+ "step": 148
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.3008356545961e-06,
+ "loss": 0.5568,
+ "step": 149
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.356545961002787e-06,
+ "loss": 0.5685,
+ "step": 150
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.41225626740947e-06,
+ "loss": 0.5681,
+ "step": 151
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.467966573816156e-06,
+ "loss": 0.5858,
+ "step": 152
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.523676880222843e-06,
+ "loss": 0.5611,
+ "step": 153
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.579387186629528e-06,
+ "loss": 0.5584,
+ "step": 154
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.635097493036211e-06,
+ "loss": 0.5517,
+ "step": 155
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.690807799442898e-06,
+ "loss": 0.56,
+ "step": 156
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.746518105849583e-06,
+ "loss": 0.5673,
+ "step": 157
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.802228412256268e-06,
+ "loss": 0.5571,
+ "step": 158
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.857938718662954e-06,
+ "loss": 0.5716,
+ "step": 159
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.913649025069639e-06,
+ "loss": 0.5634,
+ "step": 160
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 8.969359331476324e-06,
+ "loss": 0.5602,
+ "step": 161
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.025069637883009e-06,
+ "loss": 0.5444,
+ "step": 162
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.080779944289694e-06,
+ "loss": 0.5793,
+ "step": 163
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.13649025069638e-06,
+ "loss": 0.5443,
+ "step": 164
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.192200557103064e-06,
+ "loss": 0.5449,
+ "step": 165
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.24791086350975e-06,
+ "loss": 0.5599,
+ "step": 166
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.303621169916436e-06,
+ "loss": 0.5362,
+ "step": 167
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.35933147632312e-06,
+ "loss": 0.5649,
+ "step": 168
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.415041782729805e-06,
+ "loss": 0.5734,
+ "step": 169
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.470752089136492e-06,
+ "loss": 0.5595,
+ "step": 170
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.526462395543177e-06,
+ "loss": 0.5483,
+ "step": 171
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.58217270194986e-06,
+ "loss": 0.5569,
+ "step": 172
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.637883008356547e-06,
+ "loss": 0.5591,
+ "step": 173
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.693593314763233e-06,
+ "loss": 0.5639,
+ "step": 174
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.749303621169918e-06,
+ "loss": 0.5504,
+ "step": 175
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.805013927576603e-06,
+ "loss": 0.5627,
+ "step": 176
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.860724233983288e-06,
+ "loss": 0.5587,
+ "step": 177
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.916434540389973e-06,
+ "loss": 0.5603,
+ "step": 178
+ },
+ {
+ "epoch": 0.01,
+ "learning_rate": 9.972144846796658e-06,
+ "loss": 0.5558,
+ "step": 179
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0027855153203343e-05,
+ "loss": 0.5519,
+ "step": 180
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.008356545961003e-05,
+ "loss": 0.5488,
+ "step": 181
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0139275766016714e-05,
+ "loss": 0.5417,
+ "step": 182
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0194986072423399e-05,
+ "loss": 0.5537,
+ "step": 183
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0250696378830086e-05,
+ "loss": 0.5349,
+ "step": 184
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0306406685236769e-05,
+ "loss": 0.5355,
+ "step": 185
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0362116991643454e-05,
+ "loss": 0.5492,
+ "step": 186
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0417827298050141e-05,
+ "loss": 0.5627,
+ "step": 187
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0473537604456825e-05,
+ "loss": 0.5576,
+ "step": 188
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0529247910863511e-05,
+ "loss": 0.5411,
+ "step": 189
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0584958217270197e-05,
+ "loss": 0.5494,
+ "step": 190
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.064066852367688e-05,
+ "loss": 0.5574,
+ "step": 191
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0696378830083567e-05,
+ "loss": 0.5522,
+ "step": 192
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0752089136490252e-05,
+ "loss": 0.546,
+ "step": 193
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0807799442896935e-05,
+ "loss": 0.5454,
+ "step": 194
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0863509749303622e-05,
+ "loss": 0.5463,
+ "step": 195
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0919220055710307e-05,
+ "loss": 0.5607,
+ "step": 196
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.0974930362116993e-05,
+ "loss": 0.5493,
+ "step": 197
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1030640668523678e-05,
+ "loss": 0.5301,
+ "step": 198
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1086350974930363e-05,
+ "loss": 0.5335,
+ "step": 199
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1142061281337048e-05,
+ "loss": 0.5532,
+ "step": 200
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1197771587743733e-05,
+ "loss": 0.5332,
+ "step": 201
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.125348189415042e-05,
+ "loss": 0.5719,
+ "step": 202
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1309192200557103e-05,
+ "loss": 0.5222,
+ "step": 203
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1364902506963789e-05,
+ "loss": 0.5481,
+ "step": 204
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1420612813370475e-05,
+ "loss": 0.5465,
+ "step": 205
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1476323119777159e-05,
+ "loss": 0.552,
+ "step": 206
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1532033426183844e-05,
+ "loss": 0.5473,
+ "step": 207
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1587743732590531e-05,
+ "loss": 0.5439,
+ "step": 208
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1643454038997214e-05,
+ "loss": 0.5462,
+ "step": 209
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1699164345403901e-05,
+ "loss": 0.5401,
+ "step": 210
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1754874651810586e-05,
+ "loss": 0.5498,
+ "step": 211
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.181058495821727e-05,
+ "loss": 0.5567,
+ "step": 212
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1866295264623957e-05,
+ "loss": 0.5436,
+ "step": 213
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1922005571030642e-05,
+ "loss": 0.5484,
+ "step": 214
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.1977715877437325e-05,
+ "loss": 0.5411,
+ "step": 215
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2033426183844012e-05,
+ "loss": 0.5581,
+ "step": 216
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2089136490250697e-05,
+ "loss": 0.5441,
+ "step": 217
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2144846796657384e-05,
+ "loss": 0.5574,
+ "step": 218
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2200557103064068e-05,
+ "loss": 0.5588,
+ "step": 219
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2256267409470753e-05,
+ "loss": 0.5554,
+ "step": 220
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.231197771587744e-05,
+ "loss": 0.5342,
+ "step": 221
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2367688022284123e-05,
+ "loss": 0.568,
+ "step": 222
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2423398328690808e-05,
+ "loss": 0.5387,
+ "step": 223
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2479108635097495e-05,
+ "loss": 0.5469,
+ "step": 224
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2534818941504178e-05,
+ "loss": 0.5312,
+ "step": 225
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2590529247910865e-05,
+ "loss": 0.5462,
+ "step": 226
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.264623955431755e-05,
+ "loss": 0.5595,
+ "step": 227
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2701949860724234e-05,
+ "loss": 0.5355,
+ "step": 228
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.275766016713092e-05,
+ "loss": 0.548,
+ "step": 229
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2813370473537606e-05,
+ "loss": 0.547,
+ "step": 230
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2869080779944293e-05,
+ "loss": 0.5309,
+ "step": 231
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2924791086350976e-05,
+ "loss": 0.557,
+ "step": 232
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.2980501392757661e-05,
+ "loss": 0.5592,
+ "step": 233
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3036211699164346e-05,
+ "loss": 0.5326,
+ "step": 234
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3091922005571032e-05,
+ "loss": 0.5262,
+ "step": 235
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3147632311977717e-05,
+ "loss": 0.5443,
+ "step": 236
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3203342618384402e-05,
+ "loss": 0.541,
+ "step": 237
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3259052924791087e-05,
+ "loss": 0.5411,
+ "step": 238
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3314763231197774e-05,
+ "loss": 0.5406,
+ "step": 239
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3370473537604457e-05,
+ "loss": 0.5488,
+ "step": 240
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3426183844011142e-05,
+ "loss": 0.5626,
+ "step": 241
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.348189415041783e-05,
+ "loss": 0.5479,
+ "step": 242
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3537604456824513e-05,
+ "loss": 0.5583,
+ "step": 243
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3593314763231198e-05,
+ "loss": 0.5572,
+ "step": 244
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3649025069637885e-05,
+ "loss": 0.5438,
+ "step": 245
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3704735376044568e-05,
+ "loss": 0.5382,
+ "step": 246
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3760445682451255e-05,
+ "loss": 0.5321,
+ "step": 247
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.381615598885794e-05,
+ "loss": 0.5513,
+ "step": 248
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3871866295264624e-05,
+ "loss": 0.546,
+ "step": 249
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.392757660167131e-05,
+ "loss": 0.5539,
+ "step": 250
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.3983286908077996e-05,
+ "loss": 0.5551,
+ "step": 251
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4038997214484679e-05,
+ "loss": 0.5484,
+ "step": 252
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4094707520891366e-05,
+ "loss": 0.5445,
+ "step": 253
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4150417827298051e-05,
+ "loss": 0.5497,
+ "step": 254
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4206128133704738e-05,
+ "loss": 0.5279,
+ "step": 255
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4261838440111421e-05,
+ "loss": 0.5312,
+ "step": 256
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4317548746518106e-05,
+ "loss": 0.5578,
+ "step": 257
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4373259052924793e-05,
+ "loss": 0.549,
+ "step": 258
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4428969359331477e-05,
+ "loss": 0.5359,
+ "step": 259
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4484679665738162e-05,
+ "loss": 0.5571,
+ "step": 260
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4540389972144849e-05,
+ "loss": 0.5211,
+ "step": 261
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4596100278551532e-05,
+ "loss": 0.5446,
+ "step": 262
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4651810584958219e-05,
+ "loss": 0.533,
+ "step": 263
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4707520891364904e-05,
+ "loss": 0.548,
+ "step": 264
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4763231197771588e-05,
+ "loss": 0.546,
+ "step": 265
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4818941504178274e-05,
+ "loss": 0.5171,
+ "step": 266
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.487465181058496e-05,
+ "loss": 0.5478,
+ "step": 267
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.4930362116991646e-05,
+ "loss": 0.5389,
+ "step": 268
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.498607242339833e-05,
+ "loss": 0.5388,
+ "step": 269
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5041782729805015e-05,
+ "loss": 0.5412,
+ "step": 270
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5097493036211702e-05,
+ "loss": 0.5354,
+ "step": 271
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5153203342618385e-05,
+ "loss": 0.5453,
+ "step": 272
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.520891364902507e-05,
+ "loss": 0.5322,
+ "step": 273
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5264623955431757e-05,
+ "loss": 0.5533,
+ "step": 274
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5320334261838443e-05,
+ "loss": 0.5358,
+ "step": 275
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5376044568245128e-05,
+ "loss": 0.5376,
+ "step": 276
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5431754874651813e-05,
+ "loss": 0.5359,
+ "step": 277
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5487465181058498e-05,
+ "loss": 0.5518,
+ "step": 278
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5543175487465183e-05,
+ "loss": 0.5365,
+ "step": 279
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5598885793871868e-05,
+ "loss": 0.5345,
+ "step": 280
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5654596100278553e-05,
+ "loss": 0.5424,
+ "step": 281
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.571030640668524e-05,
+ "loss": 0.5337,
+ "step": 282
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5766016713091924e-05,
+ "loss": 0.5202,
+ "step": 283
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.582172701949861e-05,
+ "loss": 0.5293,
+ "step": 284
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5877437325905294e-05,
+ "loss": 0.549,
+ "step": 285
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.593314763231198e-05,
+ "loss": 0.5346,
+ "step": 286
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.5988857938718664e-05,
+ "loss": 0.5482,
+ "step": 287
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.604456824512535e-05,
+ "loss": 0.5549,
+ "step": 288
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6100278551532035e-05,
+ "loss": 0.5293,
+ "step": 289
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.615598885793872e-05,
+ "loss": 0.5656,
+ "step": 290
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6211699164345405e-05,
+ "loss": 0.5305,
+ "step": 291
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.626740947075209e-05,
+ "loss": 0.5557,
+ "step": 292
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6323119777158775e-05,
+ "loss": 0.5374,
+ "step": 293
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.637883008356546e-05,
+ "loss": 0.5183,
+ "step": 294
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.6434540389972145e-05,
+ "loss": 0.5629,
+ "step": 295
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.649025069637883e-05,
+ "loss": 0.5362,
+ "step": 296
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.654596100278552e-05,
+ "loss": 0.532,
+ "step": 297
+ },
+ {
+ "epoch": 0.02,
+ "learning_rate": 1.66016713091922e-05,
+ "loss": 0.5322,
+ "step": 298
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6657381615598886e-05,
+ "loss": 0.528,
+ "step": 299
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6713091922005575e-05,
+ "loss": 0.5609,
+ "step": 300
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6768802228412256e-05,
+ "loss": 0.5438,
+ "step": 301
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.682451253481894e-05,
+ "loss": 0.5241,
+ "step": 302
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.688022284122563e-05,
+ "loss": 0.5318,
+ "step": 303
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6935933147632312e-05,
+ "loss": 0.539,
+ "step": 304
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.6991643454039e-05,
+ "loss": 0.5516,
+ "step": 305
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7047353760445685e-05,
+ "loss": 0.5418,
+ "step": 306
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7103064066852367e-05,
+ "loss": 0.5453,
+ "step": 307
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7158774373259056e-05,
+ "loss": 0.5144,
+ "step": 308
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.721448467966574e-05,
+ "loss": 0.5553,
+ "step": 309
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7270194986072423e-05,
+ "loss": 0.5618,
+ "step": 310
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.732590529247911e-05,
+ "loss": 0.525,
+ "step": 311
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7381615598885796e-05,
+ "loss": 0.5315,
+ "step": 312
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.743732590529248e-05,
+ "loss": 0.5413,
+ "step": 313
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7493036211699167e-05,
+ "loss": 0.549,
+ "step": 314
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7548746518105852e-05,
+ "loss": 0.5299,
+ "step": 315
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7604456824512537e-05,
+ "loss": 0.5693,
+ "step": 316
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7660167130919222e-05,
+ "loss": 0.5535,
+ "step": 317
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7715877437325907e-05,
+ "loss": 0.5383,
+ "step": 318
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7771587743732592e-05,
+ "loss": 0.5564,
+ "step": 319
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7827298050139278e-05,
+ "loss": 0.5521,
+ "step": 320
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7883008356545963e-05,
+ "loss": 0.5272,
+ "step": 321
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7938718662952648e-05,
+ "loss": 0.5204,
+ "step": 322
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.7994428969359333e-05,
+ "loss": 0.5537,
+ "step": 323
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8050139275766018e-05,
+ "loss": 0.5412,
+ "step": 324
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8105849582172703e-05,
+ "loss": 0.5343,
+ "step": 325
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.816155988857939e-05,
+ "loss": 0.5388,
+ "step": 326
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8217270194986074e-05,
+ "loss": 0.5325,
+ "step": 327
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.827298050139276e-05,
+ "loss": 0.525,
+ "step": 328
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8328690807799444e-05,
+ "loss": 0.5467,
+ "step": 329
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.838440111420613e-05,
+ "loss": 0.5329,
+ "step": 330
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8440111420612814e-05,
+ "loss": 0.5338,
+ "step": 331
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.84958217270195e-05,
+ "loss": 0.5236,
+ "step": 332
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8551532033426184e-05,
+ "loss": 0.5235,
+ "step": 333
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8607242339832873e-05,
+ "loss": 0.5295,
+ "step": 334
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8662952646239555e-05,
+ "loss": 0.5306,
+ "step": 335
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.871866295264624e-05,
+ "loss": 0.5102,
+ "step": 336
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.877437325905293e-05,
+ "loss": 0.5463,
+ "step": 337
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.883008356545961e-05,
+ "loss": 0.5163,
+ "step": 338
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8885793871866295e-05,
+ "loss": 0.5452,
+ "step": 339
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8941504178272984e-05,
+ "loss": 0.547,
+ "step": 340
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.8997214484679666e-05,
+ "loss": 0.5442,
+ "step": 341
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9052924791086354e-05,
+ "loss": 0.5389,
+ "step": 342
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.910863509749304e-05,
+ "loss": 0.5253,
+ "step": 343
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.916434540389972e-05,
+ "loss": 0.5252,
+ "step": 344
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.922005571030641e-05,
+ "loss": 0.5388,
+ "step": 345
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9275766016713095e-05,
+ "loss": 0.5336,
+ "step": 346
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9331476323119776e-05,
+ "loss": 0.5342,
+ "step": 347
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9387186629526465e-05,
+ "loss": 0.5227,
+ "step": 348
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.944289693593315e-05,
+ "loss": 0.5062,
+ "step": 349
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9498607242339835e-05,
+ "loss": 0.5286,
+ "step": 350
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.955431754874652e-05,
+ "loss": 0.5326,
+ "step": 351
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9610027855153206e-05,
+ "loss": 0.5219,
+ "step": 352
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.966573816155989e-05,
+ "loss": 0.5258,
+ "step": 353
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9721448467966576e-05,
+ "loss": 0.5307,
+ "step": 354
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.977715877437326e-05,
+ "loss": 0.5314,
+ "step": 355
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9832869080779946e-05,
+ "loss": 0.5438,
+ "step": 356
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.988857938718663e-05,
+ "loss": 0.5321,
+ "step": 357
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9944289693593316e-05,
+ "loss": 0.5139,
+ "step": 358
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 2e-05,
+ "loss": 0.5207,
+ "step": 359
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99999996328208e-05,
+ "loss": 0.5364,
+ "step": 360
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999998531283215e-05,
+ "loss": 0.54,
+ "step": 361
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999996695387335e-05,
+ "loss": 0.5216,
+ "step": 362
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999994125133287e-05,
+ "loss": 0.5454,
+ "step": 363
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999990820521264e-05,
+ "loss": 0.5464,
+ "step": 364
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999998678155151e-05,
+ "loss": 0.5201,
+ "step": 365
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999998200822432e-05,
+ "loss": 0.541,
+ "step": 366
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999976500540042e-05,
+ "loss": 0.5372,
+ "step": 367
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999970258499083e-05,
+ "loss": 0.5408,
+ "step": 368
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99999632821019e-05,
+ "loss": 0.5416,
+ "step": 369
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999955571349014e-05,
+ "loss": 0.5459,
+ "step": 370
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999947126240977e-05,
+ "loss": 0.5258,
+ "step": 371
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999937946778418e-05,
+ "loss": 0.5256,
+ "step": 372
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999992803296201e-05,
+ "loss": 0.5362,
+ "step": 373
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999917384792477e-05,
+ "loss": 0.5381,
+ "step": 374
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999906002270605e-05,
+ "loss": 0.536,
+ "step": 375
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999989388539723e-05,
+ "loss": 0.5304,
+ "step": 376
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999881034173242e-05,
+ "loss": 0.5351,
+ "step": 377
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999986744859958e-05,
+ "loss": 0.5387,
+ "step": 378
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999985312867725e-05,
+ "loss": 0.5333,
+ "step": 379
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999838074407296e-05,
+ "loss": 0.5152,
+ "step": 380
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999822285790825e-05,
+ "loss": 0.516,
+ "step": 381
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999805762829e-05,
+ "loss": 0.539,
+ "step": 382
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999978850552303e-05,
+ "loss": 0.5299,
+ "step": 383
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999770513874187e-05,
+ "loss": 0.5556,
+ "step": 384
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999751787883787e-05,
+ "loss": 0.5509,
+ "step": 385
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999973232755321e-05,
+ "loss": 0.5262,
+ "step": 386
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999971213288388e-05,
+ "loss": 0.5146,
+ "step": 387
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999691203877286e-05,
+ "loss": 0.5112,
+ "step": 388
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999966954053496e-05,
+ "loss": 0.544,
+ "step": 389
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999647142858496e-05,
+ "loss": 0.519,
+ "step": 390
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999624010849536e-05,
+ "loss": 0.5349,
+ "step": 391
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999960014450978e-05,
+ "loss": 0.5184,
+ "step": 392
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999575543840982e-05,
+ "loss": 0.5374,
+ "step": 393
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999955020884495e-05,
+ "loss": 0.5205,
+ "step": 394
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999524139523538e-05,
+ "loss": 0.5536,
+ "step": 395
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999497335878666e-05,
+ "loss": 0.5277,
+ "step": 396
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99994697979123e-05,
+ "loss": 0.5181,
+ "step": 397
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999441525626464e-05,
+ "loss": 0.5173,
+ "step": 398
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999412519023233e-05,
+ "loss": 0.5443,
+ "step": 399
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999382778104734e-05,
+ "loss": 0.5279,
+ "step": 400
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999935230287316e-05,
+ "loss": 0.5472,
+ "step": 401
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999321093330736e-05,
+ "loss": 0.5348,
+ "step": 402
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999289149479767e-05,
+ "loss": 0.5534,
+ "step": 403
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999256471322593e-05,
+ "loss": 0.5447,
+ "step": 404
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999223058861613e-05,
+ "loss": 0.5312,
+ "step": 405
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999188912099278e-05,
+ "loss": 0.5267,
+ "step": 406
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99991540310381e-05,
+ "loss": 0.5221,
+ "step": 407
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999118415680642e-05,
+ "loss": 0.5456,
+ "step": 408
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.999908206602952e-05,
+ "loss": 0.5202,
+ "step": 409
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999044982087394e-05,
+ "loss": 0.5202,
+ "step": 410
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9999007163856998e-05,
+ "loss": 0.5302,
+ "step": 411
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998968611341102e-05,
+ "loss": 0.5081,
+ "step": 412
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998929324542543e-05,
+ "loss": 0.5599,
+ "step": 413
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.99988893034642e-05,
+ "loss": 0.5327,
+ "step": 414
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998848548109017e-05,
+ "loss": 0.5236,
+ "step": 415
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998807058479986e-05,
+ "loss": 0.5366,
+ "step": 416
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998764834580147e-05,
+ "loss": 0.5525,
+ "step": 417
+ },
+ {
+ "epoch": 0.03,
+ "learning_rate": 1.9998721876412613e-05,
+ "loss": 0.5199,
+ "step": 418
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998678183980532e-05,
+ "loss": 0.518,
+ "step": 419
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999863375728711e-05,
+ "loss": 0.5472,
+ "step": 420
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998588596335612e-05,
+ "loss": 0.5363,
+ "step": 421
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998542701129357e-05,
+ "loss": 0.5383,
+ "step": 422
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999849607167171e-05,
+ "loss": 0.5367,
+ "step": 423
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99984487079661e-05,
+ "loss": 0.5358,
+ "step": 424
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998400610016003e-05,
+ "loss": 0.5414,
+ "step": 425
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998351777824956e-05,
+ "loss": 0.5361,
+ "step": 426
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998302211396537e-05,
+ "loss": 0.5266,
+ "step": 427
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999825191073439e-05,
+ "loss": 0.5149,
+ "step": 428
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998200875842206e-05,
+ "loss": 0.5253,
+ "step": 429
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998149106723737e-05,
+ "loss": 0.5362,
+ "step": 430
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998096603382785e-05,
+ "loss": 0.5377,
+ "step": 431
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9998043365823205e-05,
+ "loss": 0.5397,
+ "step": 432
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99979893940489e-05,
+ "loss": 0.5267,
+ "step": 433
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999793468806384e-05,
+ "loss": 0.5379,
+ "step": 434
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997879247872042e-05,
+ "loss": 0.5283,
+ "step": 435
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997823073477577e-05,
+ "loss": 0.5098,
+ "step": 436
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997766164884572e-05,
+ "loss": 0.5102,
+ "step": 437
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997708522097202e-05,
+ "loss": 0.5374,
+ "step": 438
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997650145119702e-05,
+ "loss": 0.5158,
+ "step": 439
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997591033956353e-05,
+ "loss": 0.5019,
+ "step": 440
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997531188611507e-05,
+ "loss": 0.5368,
+ "step": 441
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999747060908955e-05,
+ "loss": 0.5247,
+ "step": 442
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997409295394938e-05,
+ "loss": 0.5346,
+ "step": 443
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999734724753217e-05,
+ "loss": 0.5386,
+ "step": 444
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99972844655058e-05,
+ "loss": 0.5305,
+ "step": 445
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999722094932044e-05,
+ "loss": 0.5347,
+ "step": 446
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997156698980755e-05,
+ "loss": 0.5309,
+ "step": 447
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9997091714491465e-05,
+ "loss": 0.5383,
+ "step": 448
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999702599585734e-05,
+ "loss": 0.524,
+ "step": 449
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996959543083207e-05,
+ "loss": 0.5387,
+ "step": 450
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996892356173946e-05,
+ "loss": 0.5336,
+ "step": 451
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996824435134486e-05,
+ "loss": 0.5338,
+ "step": 452
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996755779969827e-05,
+ "loss": 0.5231,
+ "step": 453
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996686390685e-05,
+ "loss": 0.5371,
+ "step": 454
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996616267285104e-05,
+ "loss": 0.5467,
+ "step": 455
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996545409775286e-05,
+ "loss": 0.5239,
+ "step": 456
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996473818160752e-05,
+ "loss": 0.5296,
+ "step": 457
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999640149244676e-05,
+ "loss": 0.5514,
+ "step": 458
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996328432638622e-05,
+ "loss": 0.5196,
+ "step": 459
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996254638741702e-05,
+ "loss": 0.5297,
+ "step": 460
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999618011076142e-05,
+ "loss": 0.5309,
+ "step": 461
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996104848703243e-05,
+ "loss": 0.5313,
+ "step": 462
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9996028852572705e-05,
+ "loss": 0.5292,
+ "step": 463
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995952122375385e-05,
+ "loss": 0.5368,
+ "step": 464
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995874658116917e-05,
+ "loss": 0.5373,
+ "step": 465
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999579645980299e-05,
+ "loss": 0.5392,
+ "step": 466
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995717527439348e-05,
+ "loss": 0.5315,
+ "step": 467
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995637861031786e-05,
+ "loss": 0.5325,
+ "step": 468
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995557460586153e-05,
+ "loss": 0.5468,
+ "step": 469
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995476326108355e-05,
+ "loss": 0.5525,
+ "step": 470
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995394457604354e-05,
+ "loss": 0.5133,
+ "step": 471
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995311855080155e-05,
+ "loss": 0.5228,
+ "step": 472
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995228518541828e-05,
+ "loss": 0.5394,
+ "step": 473
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999514444799549e-05,
+ "loss": 0.5449,
+ "step": 474
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9995059643447313e-05,
+ "loss": 0.5181,
+ "step": 475
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994974104903536e-05,
+ "loss": 0.533,
+ "step": 476
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999488783237043e-05,
+ "loss": 0.5344,
+ "step": 477
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999480082585433e-05,
+ "loss": 0.5248,
+ "step": 478
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999471308536163e-05,
+ "loss": 0.5394,
+ "step": 479
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994624610898778e-05,
+ "loss": 0.5263,
+ "step": 480
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999453540247226e-05,
+ "loss": 0.5065,
+ "step": 481
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994445460088635e-05,
+ "loss": 0.5423,
+ "step": 482
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994354783754504e-05,
+ "loss": 0.5219,
+ "step": 483
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994263373476526e-05,
+ "loss": 0.5298,
+ "step": 484
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9994171229261417e-05,
+ "loss": 0.5212,
+ "step": 485
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999407835111594e-05,
+ "loss": 0.5283,
+ "step": 486
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999398473904692e-05,
+ "loss": 0.5377,
+ "step": 487
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999389039306123e-05,
+ "loss": 0.536,
+ "step": 488
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993795313165795e-05,
+ "loss": 0.5229,
+ "step": 489
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99936994993676e-05,
+ "loss": 0.5259,
+ "step": 490
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999360295167368e-05,
+ "loss": 0.5236,
+ "step": 491
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993505670091123e-05,
+ "loss": 0.5245,
+ "step": 492
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999340765462708e-05,
+ "loss": 0.5348,
+ "step": 493
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993308905288745e-05,
+ "loss": 0.5415,
+ "step": 494
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993209422083367e-05,
+ "loss": 0.5391,
+ "step": 495
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999310920501825e-05,
+ "loss": 0.5202,
+ "step": 496
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9993008254100765e-05,
+ "loss": 0.5172,
+ "step": 497
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992906569338314e-05,
+ "loss": 0.534,
+ "step": 498
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999280415073837e-05,
+ "loss": 0.5294,
+ "step": 499
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992700998308453e-05,
+ "loss": 0.5486,
+ "step": 500
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992597112056134e-05,
+ "loss": 0.5134,
+ "step": 501
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992492491989045e-05,
+ "loss": 0.5241,
+ "step": 502
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999238713811487e-05,
+ "loss": 0.528,
+ "step": 503
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999228105044135e-05,
+ "loss": 0.5463,
+ "step": 504
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9992174228976265e-05,
+ "loss": 0.5119,
+ "step": 505
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999206667372747e-05,
+ "loss": 0.5352,
+ "step": 506
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991958384702855e-05,
+ "loss": 0.5365,
+ "step": 507
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999184936191038e-05,
+ "loss": 0.5205,
+ "step": 508
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991739605358042e-05,
+ "loss": 0.5034,
+ "step": 509
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991629115053908e-05,
+ "loss": 0.5319,
+ "step": 510
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999151789100609e-05,
+ "loss": 0.5195,
+ "step": 511
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991405933222758e-05,
+ "loss": 0.5319,
+ "step": 512
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991293241712128e-05,
+ "loss": 0.5359,
+ "step": 513
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999117981648248e-05,
+ "loss": 0.5251,
+ "step": 514
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9991065657542146e-05,
+ "loss": 0.5134,
+ "step": 515
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990950764899502e-05,
+ "loss": 0.5365,
+ "step": 516
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999083513856299e-05,
+ "loss": 0.5388,
+ "step": 517
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99907187785411e-05,
+ "loss": 0.5144,
+ "step": 518
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990601684842385e-05,
+ "loss": 0.5203,
+ "step": 519
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990483857475428e-05,
+ "loss": 0.5384,
+ "step": 520
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990365296448892e-05,
+ "loss": 0.5309,
+ "step": 521
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.999024600177148e-05,
+ "loss": 0.5405,
+ "step": 522
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990125973451956e-05,
+ "loss": 0.5271,
+ "step": 523
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9990005211499137e-05,
+ "loss": 0.5266,
+ "step": 524
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998988371592188e-05,
+ "loss": 0.521,
+ "step": 525
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998976148672912e-05,
+ "loss": 0.5432,
+ "step": 526
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998963852392982e-05,
+ "loss": 0.5378,
+ "step": 527
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.998951482753302e-05,
+ "loss": 0.5218,
+ "step": 528
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99893903975478e-05,
+ "loss": 0.5309,
+ "step": 529
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.99892652339833e-05,
+ "loss": 0.5238,
+ "step": 530
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9989139336848708e-05,
+ "loss": 0.5364,
+ "step": 531
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9989012706153273e-05,
+ "loss": 0.5396,
+ "step": 532
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988885341906292e-05,
+ "loss": 0.5236,
+ "step": 533
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988757244117118e-05,
+ "loss": 0.5107,
+ "step": 534
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988628412795158e-05,
+ "loss": 0.5068,
+ "step": 535
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988498847949872e-05,
+ "loss": 0.5272,
+ "step": 536
+ },
+ {
+ "epoch": 0.04,
+ "learning_rate": 1.9988368549590778e-05,
+ "loss": 0.5193,
+ "step": 537
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998823751772744e-05,
+ "loss": 0.5314,
+ "step": 538
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9988105752369487e-05,
+ "loss": 0.524,
+ "step": 539
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998797325352659e-05,
+ "loss": 0.51,
+ "step": 540
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987840021208477e-05,
+ "loss": 0.5412,
+ "step": 541
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987706055424935e-05,
+ "loss": 0.5195,
+ "step": 542
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987571356185807e-05,
+ "loss": 0.5251,
+ "step": 543
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987435923500978e-05,
+ "loss": 0.5078,
+ "step": 544
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9987299757380393e-05,
+ "loss": 0.5461,
+ "step": 545
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998716285783406e-05,
+ "loss": 0.5278,
+ "step": 546
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998702522487202e-05,
+ "loss": 0.5154,
+ "step": 547
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998688685850439e-05,
+ "loss": 0.5246,
+ "step": 548
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998674775874133e-05,
+ "loss": 0.5102,
+ "step": 549
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9986607925593046e-05,
+ "loss": 0.5195,
+ "step": 550
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998646735906982e-05,
+ "loss": 0.5231,
+ "step": 551
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9986326059181965e-05,
+ "loss": 0.5364,
+ "step": 552
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998618402593986e-05,
+ "loss": 0.5223,
+ "step": 553
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9986041259353937e-05,
+ "loss": 0.5358,
+ "step": 554
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985897759434677e-05,
+ "loss": 0.5318,
+ "step": 555
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998575352619262e-05,
+ "loss": 0.5339,
+ "step": 556
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985608559638364e-05,
+ "loss": 0.5275,
+ "step": 557
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985462859782544e-05,
+ "loss": 0.5343,
+ "step": 558
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985316426635863e-05,
+ "loss": 0.5217,
+ "step": 559
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9985169260209075e-05,
+ "loss": 0.5284,
+ "step": 560
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998502136051299e-05,
+ "loss": 0.5254,
+ "step": 561
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984872727558468e-05,
+ "loss": 0.5316,
+ "step": 562
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998472336135642e-05,
+ "loss": 0.525,
+ "step": 563
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984573261917825e-05,
+ "loss": 0.5241,
+ "step": 564
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998442242925369e-05,
+ "loss": 0.5233,
+ "step": 565
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984270863375105e-05,
+ "loss": 0.5282,
+ "step": 566
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9984118564293197e-05,
+ "loss": 0.5263,
+ "step": 567
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983965532019142e-05,
+ "loss": 0.5201,
+ "step": 568
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998381176656419e-05,
+ "loss": 0.5317,
+ "step": 569
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983657267939627e-05,
+ "loss": 0.5263,
+ "step": 570
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.99835020361568e-05,
+ "loss": 0.5158,
+ "step": 571
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983346071227107e-05,
+ "loss": 0.5344,
+ "step": 572
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983189373162003e-05,
+ "loss": 0.5306,
+ "step": 573
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9983031941972994e-05,
+ "loss": 0.5402,
+ "step": 574
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998287377767164e-05,
+ "loss": 0.5339,
+ "step": 575
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982714880269557e-05,
+ "loss": 0.5216,
+ "step": 576
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998255524977842e-05,
+ "loss": 0.5053,
+ "step": 577
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982394886209943e-05,
+ "loss": 0.5199,
+ "step": 578
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982233789575904e-05,
+ "loss": 0.5293,
+ "step": 579
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9982071959888138e-05,
+ "loss": 0.5093,
+ "step": 580
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998190939715852e-05,
+ "loss": 0.5355,
+ "step": 581
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9981746101399e-05,
+ "loss": 0.5191,
+ "step": 582
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998158207262156e-05,
+ "loss": 0.5267,
+ "step": 583
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998141731083825e-05,
+ "loss": 0.5117,
+ "step": 584
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9981251816061168e-05,
+ "loss": 0.5119,
+ "step": 585
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9981085588302468e-05,
+ "loss": 0.518,
+ "step": 586
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998091862757436e-05,
+ "loss": 0.5203,
+ "step": 587
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9980750933889098e-05,
+ "loss": 0.5326,
+ "step": 588
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9980582507259e-05,
+ "loss": 0.5318,
+ "step": 589
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998041334769644e-05,
+ "loss": 0.5275,
+ "step": 590
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.998024345521383e-05,
+ "loss": 0.5346,
+ "step": 591
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9980072829823656e-05,
+ "loss": 0.5313,
+ "step": 592
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9979901471538442e-05,
+ "loss": 0.5433,
+ "step": 593
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997972938037077e-05,
+ "loss": 0.5223,
+ "step": 594
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9979556556333283e-05,
+ "loss": 0.5244,
+ "step": 595
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9979382999438672e-05,
+ "loss": 0.5391,
+ "step": 596
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997920870969968e-05,
+ "loss": 0.5366,
+ "step": 597
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997903368712911e-05,
+ "loss": 0.518,
+ "step": 598
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978857931739805e-05,
+ "loss": 0.5125,
+ "step": 599
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978681443544687e-05,
+ "loss": 0.5062,
+ "step": 600
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978504222556704e-05,
+ "loss": 0.51,
+ "step": 601
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978326268788873e-05,
+ "loss": 0.5224,
+ "step": 602
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9978147582254266e-05,
+ "loss": 0.5183,
+ "step": 603
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977968162966e-05,
+ "loss": 0.529,
+ "step": 604
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997778801093726e-05,
+ "loss": 0.5163,
+ "step": 605
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977607126181264e-05,
+ "loss": 0.508,
+ "step": 606
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977425508711303e-05,
+ "loss": 0.5383,
+ "step": 607
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997724315854071e-05,
+ "loss": 0.5161,
+ "step": 608
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9977060075682878e-05,
+ "loss": 0.5294,
+ "step": 609
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997687626015125e-05,
+ "loss": 0.5113,
+ "step": 610
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997669171195933e-05,
+ "loss": 0.525,
+ "step": 611
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9976506431120665e-05,
+ "loss": 0.5313,
+ "step": 612
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9976320417648868e-05,
+ "loss": 0.5248,
+ "step": 613
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9976133671557587e-05,
+ "loss": 0.537,
+ "step": 614
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9975946192860544e-05,
+ "loss": 0.5232,
+ "step": 615
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9975757981571512e-05,
+ "loss": 0.5132,
+ "step": 616
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.99755690377043e-05,
+ "loss": 0.531,
+ "step": 617
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997537936127279e-05,
+ "loss": 0.532,
+ "step": 618
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9975188952290915e-05,
+ "loss": 0.5399,
+ "step": 619
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997499781077265e-05,
+ "loss": 0.5195,
+ "step": 620
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997480593673203e-05,
+ "loss": 0.5213,
+ "step": 621
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9974613330183156e-05,
+ "loss": 0.5198,
+ "step": 622
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997441999114017e-05,
+ "loss": 0.5242,
+ "step": 623
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9974225919617258e-05,
+ "loss": 0.5376,
+ "step": 624
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9974031115628688e-05,
+ "loss": 0.521,
+ "step": 625
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973835579188753e-05,
+ "loss": 0.5179,
+ "step": 626
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997363931031182e-05,
+ "loss": 0.5341,
+ "step": 627
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973442309012296e-05,
+ "loss": 0.4995,
+ "step": 628
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973244575304657e-05,
+ "loss": 0.5421,
+ "step": 629
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9973046109203414e-05,
+ "loss": 0.5164,
+ "step": 630
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972846910723146e-05,
+ "loss": 0.5236,
+ "step": 631
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972646979878483e-05,
+ "loss": 0.5341,
+ "step": 632
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972446316684106e-05,
+ "loss": 0.5337,
+ "step": 633
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972244921154746e-05,
+ "loss": 0.5226,
+ "step": 634
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9972042793305196e-05,
+ "loss": 0.5177,
+ "step": 635
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971839933150307e-05,
+ "loss": 0.5229,
+ "step": 636
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997163634070496e-05,
+ "loss": 0.513,
+ "step": 637
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971432015984126e-05,
+ "loss": 0.5055,
+ "step": 638
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971226959002796e-05,
+ "loss": 0.4982,
+ "step": 639
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9971021169776024e-05,
+ "loss": 0.5206,
+ "step": 640
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9970814648318937e-05,
+ "loss": 0.4946,
+ "step": 641
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997060739464669e-05,
+ "loss": 0.5367,
+ "step": 642
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997039940877451e-05,
+ "loss": 0.5368,
+ "step": 643
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.997019069071767e-05,
+ "loss": 0.5131,
+ "step": 644
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996998124049149e-05,
+ "loss": 0.5253,
+ "step": 645
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9969771058111357e-05,
+ "loss": 0.5273,
+ "step": 646
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9969560143592705e-05,
+ "loss": 0.5247,
+ "step": 647
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996934849695102e-05,
+ "loss": 0.5292,
+ "step": 648
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9969136118201852e-05,
+ "loss": 0.5262,
+ "step": 649
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9968923007360788e-05,
+ "loss": 0.5031,
+ "step": 650
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9968709164443483e-05,
+ "loss": 0.523,
+ "step": 651
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9968494589465645e-05,
+ "loss": 0.5326,
+ "step": 652
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996827928244302e-05,
+ "loss": 0.4976,
+ "step": 653
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996806324339143e-05,
+ "loss": 0.5387,
+ "step": 654
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996784647232673e-05,
+ "loss": 0.5141,
+ "step": 655
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.996762896926485e-05,
+ "loss": 0.5372,
+ "step": 656
+ },
+ {
+ "epoch": 0.05,
+ "learning_rate": 1.9967410734221757e-05,
+ "loss": 0.5209,
+ "step": 657
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9967191767213475e-05,
+ "loss": 0.5474,
+ "step": 658
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9966972068256087e-05,
+ "loss": 0.5331,
+ "step": 659
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9966751637365726e-05,
+ "loss": 0.513,
+ "step": 660
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996653047455858e-05,
+ "loss": 0.5238,
+ "step": 661
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996630857985089e-05,
+ "loss": 0.5155,
+ "step": 662
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996608595325895e-05,
+ "loss": 0.5119,
+ "step": 663
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996586259479911e-05,
+ "loss": 0.5187,
+ "step": 664
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9965638504487773e-05,
+ "loss": 0.5293,
+ "step": 665
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9965413682341393e-05,
+ "loss": 0.5285,
+ "step": 666
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996518812837648e-05,
+ "loss": 0.5239,
+ "step": 667
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964961842609602e-05,
+ "loss": 0.524,
+ "step": 668
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964734825057374e-05,
+ "loss": 0.5324,
+ "step": 669
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964507075736463e-05,
+ "loss": 0.5108,
+ "step": 670
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99642785946636e-05,
+ "loss": 0.5108,
+ "step": 671
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9964049381855566e-05,
+ "loss": 0.5037,
+ "step": 672
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963819437329184e-05,
+ "loss": 0.5381,
+ "step": 673
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963588761101347e-05,
+ "loss": 0.5213,
+ "step": 674
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963357353188993e-05,
+ "loss": 0.5213,
+ "step": 675
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9963125213609113e-05,
+ "loss": 0.5493,
+ "step": 676
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996289234237876e-05,
+ "loss": 0.5336,
+ "step": 677
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996265873951503e-05,
+ "loss": 0.5166,
+ "step": 678
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996242440503508e-05,
+ "loss": 0.5261,
+ "step": 679
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9962189338956124e-05,
+ "loss": 0.516,
+ "step": 680
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9961953541295413e-05,
+ "loss": 0.5128,
+ "step": 681
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9961717012070273e-05,
+ "loss": 0.5057,
+ "step": 682
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9961479751298066e-05,
+ "loss": 0.514,
+ "step": 683
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996124175899622e-05,
+ "loss": 0.5306,
+ "step": 684
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996100303518221e-05,
+ "loss": 0.5231,
+ "step": 685
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9960763579873568e-05,
+ "loss": 0.5202,
+ "step": 686
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.996052339308788e-05,
+ "loss": 0.5057,
+ "step": 687
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9960282474842784e-05,
+ "loss": 0.5059,
+ "step": 688
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9960040825155968e-05,
+ "loss": 0.5282,
+ "step": 689
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9959798444045184e-05,
+ "loss": 0.5417,
+ "step": 690
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9959555331528226e-05,
+ "loss": 0.5122,
+ "step": 691
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995931148762295e-05,
+ "loss": 0.5125,
+ "step": 692
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9959066912347262e-05,
+ "loss": 0.5131,
+ "step": 693
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958821605719122e-05,
+ "loss": 0.5258,
+ "step": 694
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958575567756546e-05,
+ "loss": 0.5234,
+ "step": 695
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958328798477602e-05,
+ "loss": 0.5072,
+ "step": 696
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9958081297900413e-05,
+ "loss": 0.5149,
+ "step": 697
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995783306604315e-05,
+ "loss": 0.5273,
+ "step": 698
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995758410292404e-05,
+ "loss": 0.5115,
+ "step": 699
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9957334408561374e-05,
+ "loss": 0.5219,
+ "step": 700
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9957083982973488e-05,
+ "loss": 0.5097,
+ "step": 701
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956832826178765e-05,
+ "loss": 0.5104,
+ "step": 702
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956580938195654e-05,
+ "loss": 0.5237,
+ "step": 703
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956328319042648e-05,
+ "loss": 0.519,
+ "step": 704
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9956074968738306e-05,
+ "loss": 0.5404,
+ "step": 705
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9955820887301227e-05,
+ "loss": 0.5104,
+ "step": 706
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995556607475007e-05,
+ "loss": 0.5055,
+ "step": 707
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9955310531103552e-05,
+ "loss": 0.5312,
+ "step": 708
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9955054256380436e-05,
+ "loss": 0.5138,
+ "step": 709
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995479725059954e-05,
+ "loss": 0.5236,
+ "step": 710
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9954539513779737e-05,
+ "loss": 0.5212,
+ "step": 711
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9954281045939958e-05,
+ "loss": 0.5143,
+ "step": 712
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995402184709918e-05,
+ "loss": 0.5225,
+ "step": 713
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9953761917276443e-05,
+ "loss": 0.5255,
+ "step": 714
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.995350125649083e-05,
+ "loss": 0.5169,
+ "step": 715
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9953239864761486e-05,
+ "loss": 0.5122,
+ "step": 716
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952977742107606e-05,
+ "loss": 0.5222,
+ "step": 717
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952714888548432e-05,
+ "loss": 0.5347,
+ "step": 718
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952451304103278e-05,
+ "loss": 0.5194,
+ "step": 719
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9952186988791494e-05,
+ "loss": 0.5115,
+ "step": 720
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951921942632493e-05,
+ "loss": 0.521,
+ "step": 721
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951656165645736e-05,
+ "loss": 0.5169,
+ "step": 722
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951389657850744e-05,
+ "loss": 0.5083,
+ "step": 723
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9951122419267085e-05,
+ "loss": 0.5222,
+ "step": 724
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9950854449914384e-05,
+ "loss": 0.5328,
+ "step": 725
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9950585749812326e-05,
+ "loss": 0.502,
+ "step": 726
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9950316318980632e-05,
+ "loss": 0.5185,
+ "step": 727
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99500461574391e-05,
+ "loss": 0.528,
+ "step": 728
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994977526520756e-05,
+ "loss": 0.5134,
+ "step": 729
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9949503642305908e-05,
+ "loss": 0.5163,
+ "step": 730
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9949231288754094e-05,
+ "loss": 0.5277,
+ "step": 731
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948958204572114e-05,
+ "loss": 0.5142,
+ "step": 732
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948684389780026e-05,
+ "loss": 0.5133,
+ "step": 733
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948409844397934e-05,
+ "loss": 0.5184,
+ "step": 734
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9948134568446006e-05,
+ "loss": 0.4933,
+ "step": 735
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994785856194445e-05,
+ "loss": 0.5337,
+ "step": 736
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9947581824913536e-05,
+ "loss": 0.5312,
+ "step": 737
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994730435737359e-05,
+ "loss": 0.5064,
+ "step": 738
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9947026159344985e-05,
+ "loss": 0.5289,
+ "step": 739
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9946747230848152e-05,
+ "loss": 0.5196,
+ "step": 740
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994646757190357e-05,
+ "loss": 0.5098,
+ "step": 741
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9946187182531785e-05,
+ "loss": 0.5362,
+ "step": 742
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945906062753383e-05,
+ "loss": 0.5438,
+ "step": 743
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945624212589007e-05,
+ "loss": 0.5376,
+ "step": 744
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945341632059356e-05,
+ "loss": 0.508,
+ "step": 745
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9945058321185175e-05,
+ "loss": 0.5277,
+ "step": 746
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994477427998728e-05,
+ "loss": 0.528,
+ "step": 747
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9944489508486528e-05,
+ "loss": 0.515,
+ "step": 748
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9944204006703828e-05,
+ "loss": 0.5223,
+ "step": 749
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9943917774660145e-05,
+ "loss": 0.5251,
+ "step": 750
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99436308123765e-05,
+ "loss": 0.51,
+ "step": 751
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9943343119873966e-05,
+ "loss": 0.5188,
+ "step": 752
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9943054697173676e-05,
+ "loss": 0.5078,
+ "step": 753
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99427655442968e-05,
+ "loss": 0.505,
+ "step": 754
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994247566126458e-05,
+ "loss": 0.5079,
+ "step": 755
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99421850480983e-05,
+ "loss": 0.521,
+ "step": 756
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9941893704819307e-05,
+ "loss": 0.5151,
+ "step": 757
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9941601631448986e-05,
+ "loss": 0.5118,
+ "step": 758
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9941308828008794e-05,
+ "loss": 0.5173,
+ "step": 759
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994101529452023e-05,
+ "loss": 0.5219,
+ "step": 760
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9940721031004853e-05,
+ "loss": 0.5182,
+ "step": 761
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9940426037484268e-05,
+ "loss": 0.5159,
+ "step": 762
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.994013031398014e-05,
+ "loss": 0.5232,
+ "step": 763
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9939833860514187e-05,
+ "loss": 0.5113,
+ "step": 764
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9939536677108176e-05,
+ "loss": 0.5284,
+ "step": 765
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993923876378393e-05,
+ "loss": 0.5181,
+ "step": 766
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993894012056334e-05,
+ "loss": 0.5263,
+ "step": 767
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993864074746832e-05,
+ "loss": 0.508,
+ "step": 768
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993834064452086e-05,
+ "loss": 0.5173,
+ "step": 769
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9938039811743e-05,
+ "loss": 0.5273,
+ "step": 770
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9937738249156836e-05,
+ "loss": 0.5169,
+ "step": 771
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9937435956784506e-05,
+ "loss": 0.5033,
+ "step": 772
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9937132934648213e-05,
+ "loss": 0.4927,
+ "step": 773
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.993682918277021e-05,
+ "loss": 0.5177,
+ "step": 774
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.99365247011728e-05,
+ "loss": 0.51,
+ "step": 775
+ },
+ {
+ "epoch": 0.06,
+ "learning_rate": 1.9936219489878343e-05,
+ "loss": 0.5046,
+ "step": 776
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9935913548909258e-05,
+ "loss": 0.5577,
+ "step": 777
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9935606878288008e-05,
+ "loss": 0.5247,
+ "step": 778
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9935299478037114e-05,
+ "loss": 0.5033,
+ "step": 779
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993499134817915e-05,
+ "loss": 0.5286,
+ "step": 780
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9934682488736745e-05,
+ "loss": 0.5342,
+ "step": 781
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993437289973258e-05,
+ "loss": 0.5145,
+ "step": 782
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993406258118939e-05,
+ "loss": 0.5139,
+ "step": 783
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993375153312996e-05,
+ "loss": 0.5159,
+ "step": 784
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9933439755577134e-05,
+ "loss": 0.506,
+ "step": 785
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9933127248553813e-05,
+ "loss": 0.5219,
+ "step": 786
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993281401208294e-05,
+ "loss": 0.5383,
+ "step": 787
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993250004618752e-05,
+ "loss": 0.5096,
+ "step": 788
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9932185350890606e-05,
+ "loss": 0.5199,
+ "step": 789
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9931869926215315e-05,
+ "loss": 0.5117,
+ "step": 790
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9931553772184805e-05,
+ "loss": 0.5312,
+ "step": 791
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9931236888822295e-05,
+ "loss": 0.5135,
+ "step": 792
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993091927615105e-05,
+ "loss": 0.5282,
+ "step": 793
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9930600934194405e-05,
+ "loss": 0.5438,
+ "step": 794
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.993028186297573e-05,
+ "loss": 0.5087,
+ "step": 795
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9929962062518458e-05,
+ "loss": 0.5244,
+ "step": 796
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9929641532846074e-05,
+ "loss": 0.5054,
+ "step": 797
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992932027398212e-05,
+ "loss": 0.5353,
+ "step": 798
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992899828595018e-05,
+ "loss": 0.5065,
+ "step": 799
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9928675568773906e-05,
+ "loss": 0.5293,
+ "step": 800
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992835212247699e-05,
+ "loss": 0.5097,
+ "step": 801
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9928027947083195e-05,
+ "loss": 0.5242,
+ "step": 802
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992770304261632e-05,
+ "loss": 0.5199,
+ "step": 803
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9927377409100222e-05,
+ "loss": 0.5333,
+ "step": 804
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992705104655882e-05,
+ "loss": 0.5338,
+ "step": 805
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992672395501608e-05,
+ "loss": 0.5206,
+ "step": 806
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992639613449602e-05,
+ "loss": 0.5262,
+ "step": 807
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9926067585022718e-05,
+ "loss": 0.5317,
+ "step": 808
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9925738306620294e-05,
+ "loss": 0.5414,
+ "step": 809
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9925408299312935e-05,
+ "loss": 0.5112,
+ "step": 810
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992507756312487e-05,
+ "loss": 0.5168,
+ "step": 811
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99247460980804e-05,
+ "loss": 0.5242,
+ "step": 812
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9924413904203847e-05,
+ "loss": 0.51,
+ "step": 813
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992408098151962e-05,
+ "loss": 0.5168,
+ "step": 814
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992374733005216e-05,
+ "loss": 0.5223,
+ "step": 815
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9923412949825975e-05,
+ "loss": 0.5066,
+ "step": 816
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9923077840865615e-05,
+ "loss": 0.5063,
+ "step": 817
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9922742003195696e-05,
+ "loss": 0.5171,
+ "step": 818
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9922405436840872e-05,
+ "loss": 0.5278,
+ "step": 819
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9922068141825864e-05,
+ "loss": 0.5183,
+ "step": 820
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9921730118175443e-05,
+ "loss": 0.5055,
+ "step": 821
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9921391365914426e-05,
+ "loss": 0.5416,
+ "step": 822
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9921051885067695e-05,
+ "loss": 0.5098,
+ "step": 823
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9920711675660178e-05,
+ "loss": 0.543,
+ "step": 824
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.992037073771686e-05,
+ "loss": 0.5269,
+ "step": 825
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9920029071262778e-05,
+ "loss": 0.4967,
+ "step": 826
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9919686676323015e-05,
+ "loss": 0.5036,
+ "step": 827
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9919343552922727e-05,
+ "loss": 0.518,
+ "step": 828
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9918999701087104e-05,
+ "loss": 0.5273,
+ "step": 829
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9918655120841403e-05,
+ "loss": 0.5271,
+ "step": 830
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991830981221092e-05,
+ "loss": 0.5263,
+ "step": 831
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991796377522102e-05,
+ "loss": 0.5187,
+ "step": 832
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9917617009897113e-05,
+ "loss": 0.5042,
+ "step": 833
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9917269516264662e-05,
+ "loss": 0.5248,
+ "step": 834
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9916921294349187e-05,
+ "loss": 0.4992,
+ "step": 835
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9916572344176258e-05,
+ "loss": 0.5347,
+ "step": 836
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9916222665771506e-05,
+ "loss": 0.5343,
+ "step": 837
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9915872259160603e-05,
+ "loss": 0.511,
+ "step": 838
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991552112436929e-05,
+ "loss": 0.5374,
+ "step": 839
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991516926142334e-05,
+ "loss": 0.5074,
+ "step": 840
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99148166703486e-05,
+ "loss": 0.5287,
+ "step": 841
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991446335117097e-05,
+ "loss": 0.5089,
+ "step": 842
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991410930391638e-05,
+ "loss": 0.5148,
+ "step": 843
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9913754528610846e-05,
+ "loss": 0.5282,
+ "step": 844
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991339902528041e-05,
+ "loss": 0.5093,
+ "step": 845
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9913042793951184e-05,
+ "loss": 0.5292,
+ "step": 846
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9912685834649324e-05,
+ "loss": 0.5164,
+ "step": 847
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991232814740105e-05,
+ "loss": 0.5011,
+ "step": 848
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991196973223262e-05,
+ "loss": 0.5238,
+ "step": 849
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9911610589170363e-05,
+ "loss": 0.5173,
+ "step": 850
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9911250718240653e-05,
+ "loss": 0.5082,
+ "step": 851
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991089011946991e-05,
+ "loss": 0.5063,
+ "step": 852
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.991052879288462e-05,
+ "loss": 0.5203,
+ "step": 853
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9910166738511315e-05,
+ "loss": 0.5008,
+ "step": 854
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9909803956376588e-05,
+ "loss": 0.5135,
+ "step": 855
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9909440446507074e-05,
+ "loss": 0.5087,
+ "step": 856
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990907620892947e-05,
+ "loss": 0.5175,
+ "step": 857
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9908711243670526e-05,
+ "loss": 0.5173,
+ "step": 858
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990834555075704e-05,
+ "loss": 0.5081,
+ "step": 859
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9907979130215868e-05,
+ "loss": 0.517,
+ "step": 860
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990761198207392e-05,
+ "loss": 0.5276,
+ "step": 861
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9907244106358158e-05,
+ "loss": 0.5121,
+ "step": 862
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9906875503095594e-05,
+ "loss": 0.5236,
+ "step": 863
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99065061723133e-05,
+ "loss": 0.524,
+ "step": 864
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9906136114038398e-05,
+ "loss": 0.5112,
+ "step": 865
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990576532829806e-05,
+ "loss": 0.5318,
+ "step": 866
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990539381511952e-05,
+ "loss": 0.5188,
+ "step": 867
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9905021574530055e-05,
+ "loss": 0.5064,
+ "step": 868
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9904648606557007e-05,
+ "loss": 0.528,
+ "step": 869
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9904274911227762e-05,
+ "loss": 0.5179,
+ "step": 870
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990390048856976e-05,
+ "loss": 0.5177,
+ "step": 871
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.99035253386105e-05,
+ "loss": 0.516,
+ "step": 872
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9903149461377532e-05,
+ "loss": 0.525,
+ "step": 873
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9902772856898457e-05,
+ "loss": 0.5407,
+ "step": 874
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9902395525200933e-05,
+ "loss": 0.5232,
+ "step": 875
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9902017466312668e-05,
+ "loss": 0.5302,
+ "step": 876
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9901638680261426e-05,
+ "loss": 0.5218,
+ "step": 877
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9901259167075023e-05,
+ "loss": 0.5213,
+ "step": 878
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9900878926781327e-05,
+ "loss": 0.5346,
+ "step": 879
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.990049795940827e-05,
+ "loss": 0.5155,
+ "step": 880
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9900116264983815e-05,
+ "loss": 0.523,
+ "step": 881
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9899733843536e-05,
+ "loss": 0.5037,
+ "step": 882
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9899350695092914e-05,
+ "loss": 0.516,
+ "step": 883
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.989896681968268e-05,
+ "loss": 0.5274,
+ "step": 884
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.98985822173335e-05,
+ "loss": 0.5063,
+ "step": 885
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9898196888073612e-05,
+ "loss": 0.507,
+ "step": 886
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9897810831931314e-05,
+ "loss": 0.5332,
+ "step": 887
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.989742404893496e-05,
+ "loss": 0.5391,
+ "step": 888
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9897036539112945e-05,
+ "loss": 0.5041,
+ "step": 889
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9896648302493734e-05,
+ "loss": 0.5138,
+ "step": 890
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9896259339105835e-05,
+ "loss": 0.5398,
+ "step": 891
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9895869648977812e-05,
+ "loss": 0.516,
+ "step": 892
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9895479232138282e-05,
+ "loss": 0.5177,
+ "step": 893
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9895088088615915e-05,
+ "loss": 0.4917,
+ "step": 894
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.9894696218439436e-05,
+ "loss": 0.526,
+ "step": 895
+ },
+ {
+ "epoch": 0.07,
+ "learning_rate": 1.989430362163762e-05,
+ "loss": 0.5205,
+ "step": 896
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98939102982393e-05,
+ "loss": 0.5188,
+ "step": 897
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9893516248273362e-05,
+ "loss": 0.5392,
+ "step": 898
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.989312147176874e-05,
+ "loss": 0.5131,
+ "step": 899
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9892725968754426e-05,
+ "loss": 0.5156,
+ "step": 900
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9892329739259462e-05,
+ "loss": 0.4967,
+ "step": 901
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9891932783312948e-05,
+ "loss": 0.5241,
+ "step": 902
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9891535100944033e-05,
+ "loss": 0.5174,
+ "step": 903
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9891136692181926e-05,
+ "loss": 0.5355,
+ "step": 904
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.989073755705588e-05,
+ "loss": 0.5073,
+ "step": 905
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9890337695595202e-05,
+ "loss": 0.518,
+ "step": 906
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988993710782926e-05,
+ "loss": 0.5088,
+ "step": 907
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988953579378748e-05,
+ "loss": 0.5005,
+ "step": 908
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988913375349932e-05,
+ "loss": 0.5177,
+ "step": 909
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988873098699431e-05,
+ "loss": 0.5096,
+ "step": 910
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9888327494302025e-05,
+ "loss": 0.5153,
+ "step": 911
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98879232754521e-05,
+ "loss": 0.5335,
+ "step": 912
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9887518330474216e-05,
+ "loss": 0.5308,
+ "step": 913
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9887112659398108e-05,
+ "loss": 0.5303,
+ "step": 914
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9886706262253574e-05,
+ "loss": 0.5258,
+ "step": 915
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988629913907045e-05,
+ "loss": 0.5278,
+ "step": 916
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988589128987864e-05,
+ "loss": 0.5097,
+ "step": 917
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9885482714708093e-05,
+ "loss": 0.5024,
+ "step": 918
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988507341358881e-05,
+ "loss": 0.5346,
+ "step": 919
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9884663386550853e-05,
+ "loss": 0.5104,
+ "step": 920
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.988425263362433e-05,
+ "loss": 0.5202,
+ "step": 921
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98838411548394e-05,
+ "loss": 0.5188,
+ "step": 922
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9883428950226294e-05,
+ "loss": 0.5121,
+ "step": 923
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9883016019815268e-05,
+ "loss": 0.5089,
+ "step": 924
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9882602363636656e-05,
+ "loss": 0.5172,
+ "step": 925
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9882187981720827e-05,
+ "loss": 0.52,
+ "step": 926
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9881772874098218e-05,
+ "loss": 0.5118,
+ "step": 927
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9881357040799312e-05,
+ "loss": 0.531,
+ "step": 928
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9880940481854646e-05,
+ "loss": 0.5273,
+ "step": 929
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9880523197294804e-05,
+ "loss": 0.5082,
+ "step": 930
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9880105187150435e-05,
+ "loss": 0.5142,
+ "step": 931
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987968645145224e-05,
+ "loss": 0.5217,
+ "step": 932
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987926699023096e-05,
+ "loss": 0.504,
+ "step": 933
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9878846803517408e-05,
+ "loss": 0.5272,
+ "step": 934
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987842589134243e-05,
+ "loss": 0.5336,
+ "step": 935
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9878004253736945e-05,
+ "loss": 0.5198,
+ "step": 936
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9877581890731915e-05,
+ "loss": 0.5233,
+ "step": 937
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987715880235835e-05,
+ "loss": 0.5315,
+ "step": 938
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9876734988647334e-05,
+ "loss": 0.5072,
+ "step": 939
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9876310449629973e-05,
+ "loss": 0.5278,
+ "step": 940
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9875885185337453e-05,
+ "loss": 0.5219,
+ "step": 941
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9875459195801e-05,
+ "loss": 0.5161,
+ "step": 942
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98750324810519e-05,
+ "loss": 0.5227,
+ "step": 943
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987460504112149e-05,
+ "loss": 0.5114,
+ "step": 944
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9874176876041157e-05,
+ "loss": 0.5262,
+ "step": 945
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9873747985842343e-05,
+ "loss": 0.508,
+ "step": 946
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9873318370556546e-05,
+ "loss": 0.5422,
+ "step": 947
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9872888030215313e-05,
+ "loss": 0.5087,
+ "step": 948
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9872456964850246e-05,
+ "loss": 0.5138,
+ "step": 949
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9872025174493003e-05,
+ "loss": 0.5138,
+ "step": 950
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9871592659175296e-05,
+ "loss": 0.5301,
+ "step": 951
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987115941892888e-05,
+ "loss": 0.4924,
+ "step": 952
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.987072545378557e-05,
+ "loss": 0.5321,
+ "step": 953
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9870290763777243e-05,
+ "loss": 0.5333,
+ "step": 954
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9869855348935817e-05,
+ "loss": 0.5032,
+ "step": 955
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986941920929326e-05,
+ "loss": 0.5294,
+ "step": 956
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986898234488161e-05,
+ "loss": 0.5085,
+ "step": 957
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9868544755732948e-05,
+ "loss": 0.4924,
+ "step": 958
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9868106441879403e-05,
+ "loss": 0.496,
+ "step": 959
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9867667403353162e-05,
+ "loss": 0.5076,
+ "step": 960
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9867227640186474e-05,
+ "loss": 0.5201,
+ "step": 961
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9866787152411624e-05,
+ "loss": 0.5204,
+ "step": 962
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986634594006097e-05,
+ "loss": 0.5269,
+ "step": 963
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9865904003166904e-05,
+ "loss": 0.5226,
+ "step": 964
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9865461341761885e-05,
+ "loss": 0.5212,
+ "step": 965
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986501795587842e-05,
+ "loss": 0.5216,
+ "step": 966
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9864573845549063e-05,
+ "loss": 0.5174,
+ "step": 967
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9864129010806437e-05,
+ "loss": 0.5356,
+ "step": 968
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9863683451683204e-05,
+ "loss": 0.4997,
+ "step": 969
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9863237168212084e-05,
+ "loss": 0.5137,
+ "step": 970
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.986279016042585e-05,
+ "loss": 0.5368,
+ "step": 971
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9862342428357327e-05,
+ "loss": 0.5209,
+ "step": 972
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9861893972039402e-05,
+ "loss": 0.5135,
+ "step": 973
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9861444791504997e-05,
+ "loss": 0.517,
+ "step": 974
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9860994886787106e-05,
+ "loss": 0.5308,
+ "step": 975
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9860544257918765e-05,
+ "loss": 0.5223,
+ "step": 976
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9860092904933065e-05,
+ "loss": 0.5231,
+ "step": 977
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9859640827863157e-05,
+ "loss": 0.5187,
+ "step": 978
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9859188026742235e-05,
+ "loss": 0.524,
+ "step": 979
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9858734501603553e-05,
+ "loss": 0.5258,
+ "step": 980
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985828025248041e-05,
+ "loss": 0.5138,
+ "step": 981
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985782527940617e-05,
+ "loss": 0.5222,
+ "step": 982
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9857369582414246e-05,
+ "loss": 0.5048,
+ "step": 983
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98569131615381e-05,
+ "loss": 0.498,
+ "step": 984
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985645601681125e-05,
+ "loss": 0.5268,
+ "step": 985
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9855998148267265e-05,
+ "loss": 0.5111,
+ "step": 986
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9855539555939768e-05,
+ "loss": 0.5131,
+ "step": 987
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985508023986244e-05,
+ "loss": 0.5085,
+ "step": 988
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985462020006901e-05,
+ "loss": 0.4973,
+ "step": 989
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9854159436593258e-05,
+ "loss": 0.5084,
+ "step": 990
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9853697949469027e-05,
+ "loss": 0.499,
+ "step": 991
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98532357387302e-05,
+ "loss": 0.5203,
+ "step": 992
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9852772804410728e-05,
+ "loss": 0.4915,
+ "step": 993
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.98523091465446e-05,
+ "loss": 0.5183,
+ "step": 994
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9851844765165863e-05,
+ "loss": 0.505,
+ "step": 995
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9851379660308624e-05,
+ "loss": 0.5046,
+ "step": 996
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9850913832007042e-05,
+ "loss": 0.515,
+ "step": 997
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.985044728029532e-05,
+ "loss": 0.503,
+ "step": 998
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984998000520772e-05,
+ "loss": 0.5179,
+ "step": 999
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9849512006778557e-05,
+ "loss": 0.5145,
+ "step": 1000
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9849043285042203e-05,
+ "loss": 0.5222,
+ "step": 1001
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9848573840033068e-05,
+ "loss": 0.4923,
+ "step": 1002
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984810367178564e-05,
+ "loss": 0.5156,
+ "step": 1003
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984763278033444e-05,
+ "loss": 0.5181,
+ "step": 1004
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9847161165714043e-05,
+ "loss": 0.5291,
+ "step": 1005
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984668882795909e-05,
+ "loss": 0.5196,
+ "step": 1006
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9846215767104266e-05,
+ "loss": 0.5165,
+ "step": 1007
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984574198318431e-05,
+ "loss": 0.5066,
+ "step": 1008
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9845267476234013e-05,
+ "loss": 0.5345,
+ "step": 1009
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984479224628822e-05,
+ "loss": 0.5275,
+ "step": 1010
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9844316293381834e-05,
+ "loss": 0.5111,
+ "step": 1011
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9843839617549805e-05,
+ "loss": 0.4976,
+ "step": 1012
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.984336221882714e-05,
+ "loss": 0.5251,
+ "step": 1013
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9842884097248892e-05,
+ "loss": 0.5083,
+ "step": 1014
+ },
+ {
+ "epoch": 0.08,
+ "learning_rate": 1.9842405252850175e-05,
+ "loss": 0.5086,
+ "step": 1015
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.984192568566616e-05,
+ "loss": 0.535,
+ "step": 1016
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9841445395732054e-05,
+ "loss": 0.5005,
+ "step": 1017
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.984096438308313e-05,
+ "loss": 0.5042,
+ "step": 1018
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9840482647754716e-05,
+ "loss": 0.5152,
+ "step": 1019
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9840000189782184e-05,
+ "loss": 0.5217,
+ "step": 1020
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983951700920097e-05,
+ "loss": 0.5063,
+ "step": 1021
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9839033106046548e-05,
+ "loss": 0.5153,
+ "step": 1022
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983854848035446e-05,
+ "loss": 0.5272,
+ "step": 1023
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9838063132160292e-05,
+ "loss": 0.5123,
+ "step": 1024
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983757706149969e-05,
+ "loss": 0.5136,
+ "step": 1025
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9837090268408342e-05,
+ "loss": 0.5199,
+ "step": 1026
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9836602752922004e-05,
+ "loss": 0.5092,
+ "step": 1027
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9836114515076473e-05,
+ "loss": 0.5272,
+ "step": 1028
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98356255549076e-05,
+ "loss": 0.5041,
+ "step": 1029
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98351358724513e-05,
+ "loss": 0.529,
+ "step": 1030
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9834645467743524e-05,
+ "loss": 0.5032,
+ "step": 1031
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9834154340820296e-05,
+ "loss": 0.5256,
+ "step": 1032
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983366249171767e-05,
+ "loss": 0.5248,
+ "step": 1033
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9833169920471778e-05,
+ "loss": 0.5205,
+ "step": 1034
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9832676627118784e-05,
+ "loss": 0.5149,
+ "step": 1035
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9832182611694916e-05,
+ "loss": 0.5022,
+ "step": 1036
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.983168787423645e-05,
+ "loss": 0.5143,
+ "step": 1037
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9831192414779724e-05,
+ "loss": 0.5363,
+ "step": 1038
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9830696233361113e-05,
+ "loss": 0.4941,
+ "step": 1039
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9830199330017063e-05,
+ "loss": 0.5166,
+ "step": 1040
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982970170478406e-05,
+ "loss": 0.5323,
+ "step": 1041
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9829203357698647e-05,
+ "loss": 0.5265,
+ "step": 1042
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9828704288797425e-05,
+ "loss": 0.5111,
+ "step": 1043
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982820449811704e-05,
+ "loss": 0.5161,
+ "step": 1044
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9827703985694194e-05,
+ "loss": 0.5233,
+ "step": 1045
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9827202751565644e-05,
+ "loss": 0.5273,
+ "step": 1046
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9826700795768197e-05,
+ "loss": 0.5168,
+ "step": 1047
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982619811833872e-05,
+ "loss": 0.504,
+ "step": 1048
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982569471931412e-05,
+ "loss": 0.5216,
+ "step": 1049
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982519059873137e-05,
+ "loss": 0.5331,
+ "step": 1050
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9824685756627487e-05,
+ "loss": 0.5473,
+ "step": 1051
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9824180193039545e-05,
+ "loss": 0.5213,
+ "step": 1052
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9823673908004673e-05,
+ "loss": 0.5104,
+ "step": 1053
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.982316690156005e-05,
+ "loss": 0.5322,
+ "step": 1054
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9822659173742904e-05,
+ "loss": 0.52,
+ "step": 1055
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9822150724590528e-05,
+ "loss": 0.5226,
+ "step": 1056
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9821641554140252e-05,
+ "loss": 0.4941,
+ "step": 1057
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9821131662429476e-05,
+ "loss": 0.5173,
+ "step": 1058
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9820621049495637e-05,
+ "loss": 0.5042,
+ "step": 1059
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9820109715376236e-05,
+ "loss": 0.5264,
+ "step": 1060
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9819597660108823e-05,
+ "loss": 0.5155,
+ "step": 1061
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9819084883731e-05,
+ "loss": 0.5059,
+ "step": 1062
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9818571386280422e-05,
+ "loss": 0.5237,
+ "step": 1063
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9818057167794803e-05,
+ "loss": 0.5203,
+ "step": 1064
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98175422283119e-05,
+ "loss": 0.5128,
+ "step": 1065
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9817026567869527e-05,
+ "loss": 0.5125,
+ "step": 1066
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9816510186505562e-05,
+ "loss": 0.5056,
+ "step": 1067
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9815993084257913e-05,
+ "loss": 0.5249,
+ "step": 1068
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9815475261164563e-05,
+ "loss": 0.5111,
+ "step": 1069
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9814956717263534e-05,
+ "loss": 0.5204,
+ "step": 1070
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9814437452592908e-05,
+ "loss": 0.5045,
+ "step": 1071
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9813917467190817e-05,
+ "loss": 0.4943,
+ "step": 1072
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9813396761095446e-05,
+ "loss": 0.5294,
+ "step": 1073
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9812875334345032e-05,
+ "loss": 0.5243,
+ "step": 1074
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.981235318697787e-05,
+ "loss": 0.508,
+ "step": 1075
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.98118303190323e-05,
+ "loss": 0.5013,
+ "step": 1076
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9811306730546728e-05,
+ "loss": 0.494,
+ "step": 1077
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9810782421559595e-05,
+ "loss": 0.5325,
+ "step": 1078
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9810257392109405e-05,
+ "loss": 0.5255,
+ "step": 1079
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9809731642234715e-05,
+ "loss": 0.5053,
+ "step": 1080
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9809205171974136e-05,
+ "loss": 0.5062,
+ "step": 1081
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9808677981366334e-05,
+ "loss": 0.5201,
+ "step": 1082
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9808150070450015e-05,
+ "loss": 0.4957,
+ "step": 1083
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980762143926395e-05,
+ "loss": 0.5247,
+ "step": 1084
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9807092087846956e-05,
+ "loss": 0.5265,
+ "step": 1085
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9806562016237913e-05,
+ "loss": 0.528,
+ "step": 1086
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9806031224475743e-05,
+ "loss": 0.5301,
+ "step": 1087
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9805499712599426e-05,
+ "loss": 0.5281,
+ "step": 1088
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9804967480647996e-05,
+ "loss": 0.5024,
+ "step": 1089
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9804434528660536e-05,
+ "loss": 0.5087,
+ "step": 1090
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9803900856676182e-05,
+ "loss": 0.5004,
+ "step": 1091
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980336646473413e-05,
+ "loss": 0.5165,
+ "step": 1092
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980283135287362e-05,
+ "loss": 0.4901,
+ "step": 1093
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9802295521133942e-05,
+ "loss": 0.5026,
+ "step": 1094
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980175896955446e-05,
+ "loss": 0.5191,
+ "step": 1095
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9801221698174564e-05,
+ "loss": 0.5122,
+ "step": 1096
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.980068370703371e-05,
+ "loss": 0.5061,
+ "step": 1097
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9800144996171415e-05,
+ "loss": 0.5216,
+ "step": 1098
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.979960556562723e-05,
+ "loss": 0.5257,
+ "step": 1099
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.979906541544077e-05,
+ "loss": 0.5028,
+ "step": 1100
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9798524545651705e-05,
+ "loss": 0.5225,
+ "step": 1101
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9797982956299754e-05,
+ "loss": 0.5049,
+ "step": 1102
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9797440647424687e-05,
+ "loss": 0.5348,
+ "step": 1103
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9796897619066327e-05,
+ "loss": 0.5152,
+ "step": 1104
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9796353871264555e-05,
+ "loss": 0.5002,
+ "step": 1105
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.97958094040593e-05,
+ "loss": 0.5106,
+ "step": 1106
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9795264217490547e-05,
+ "loss": 0.5306,
+ "step": 1107
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9794718311598337e-05,
+ "loss": 0.5149,
+ "step": 1108
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9794171686422746e-05,
+ "loss": 0.4985,
+ "step": 1109
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9793624342003927e-05,
+ "loss": 0.526,
+ "step": 1110
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.979307627838207e-05,
+ "loss": 0.5112,
+ "step": 1111
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9792527495597423e-05,
+ "loss": 0.5188,
+ "step": 1112
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9791977993690292e-05,
+ "loss": 0.5096,
+ "step": 1113
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9791427772701017e-05,
+ "loss": 0.5175,
+ "step": 1114
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9790876832670018e-05,
+ "loss": 0.5098,
+ "step": 1115
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9790325173637744e-05,
+ "loss": 0.5037,
+ "step": 1116
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9789772795644714e-05,
+ "loss": 0.5231,
+ "step": 1117
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9789219698731484e-05,
+ "loss": 0.5139,
+ "step": 1118
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9788665882938677e-05,
+ "loss": 0.5106,
+ "step": 1119
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9788111348306963e-05,
+ "loss": 0.522,
+ "step": 1120
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978755609487706e-05,
+ "loss": 0.4982,
+ "step": 1121
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9787000122689753e-05,
+ "loss": 0.5091,
+ "step": 1122
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978644343178586e-05,
+ "loss": 0.5313,
+ "step": 1123
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978588602220627e-05,
+ "loss": 0.5007,
+ "step": 1124
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978532789399191e-05,
+ "loss": 0.5144,
+ "step": 1125
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978476904718377e-05,
+ "loss": 0.5293,
+ "step": 1126
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9784209481822892e-05,
+ "loss": 0.5137,
+ "step": 1127
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9783649197950362e-05,
+ "loss": 0.4985,
+ "step": 1128
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978308819560733e-05,
+ "loss": 0.5455,
+ "step": 1129
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9782526474834988e-05,
+ "loss": 0.4913,
+ "step": 1130
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978196403567459e-05,
+ "loss": 0.5198,
+ "step": 1131
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.9781400878167446e-05,
+ "loss": 0.5024,
+ "step": 1132
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.97808370023549e-05,
+ "loss": 0.5142,
+ "step": 1133
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.978027240827837e-05,
+ "loss": 0.5143,
+ "step": 1134
+ },
+ {
+ "epoch": 0.09,
+ "learning_rate": 1.977970709597931e-05,
+ "loss": 0.5094,
+ "step": 1135
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977914106549924e-05,
+ "loss": 0.5372,
+ "step": 1136
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9778574316879724e-05,
+ "loss": 0.5168,
+ "step": 1137
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9778006850162384e-05,
+ "loss": 0.4953,
+ "step": 1138
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9777438665388885e-05,
+ "loss": 0.5212,
+ "step": 1139
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9776869762600963e-05,
+ "loss": 0.5067,
+ "step": 1140
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977630014184039e-05,
+ "loss": 0.5148,
+ "step": 1141
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9775729803148994e-05,
+ "loss": 0.5136,
+ "step": 1142
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9775158746568665e-05,
+ "loss": 0.508,
+ "step": 1143
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9774586972141337e-05,
+ "loss": 0.5262,
+ "step": 1144
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9774014479908996e-05,
+ "loss": 0.5161,
+ "step": 1145
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977344126991368e-05,
+ "loss": 0.5174,
+ "step": 1146
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9772867342197494e-05,
+ "loss": 0.5228,
+ "step": 1147
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977229269680258e-05,
+ "loss": 0.5263,
+ "step": 1148
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9771717333771133e-05,
+ "loss": 0.4995,
+ "step": 1149
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9771141253145405e-05,
+ "loss": 0.5082,
+ "step": 1150
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.977056445496771e-05,
+ "loss": 0.5178,
+ "step": 1151
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.97699869392804e-05,
+ "loss": 0.5053,
+ "step": 1152
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9769408706125882e-05,
+ "loss": 0.5052,
+ "step": 1153
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9768829755546625e-05,
+ "loss": 0.5217,
+ "step": 1154
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9768250087585143e-05,
+ "loss": 0.5274,
+ "step": 1155
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9767669702284e-05,
+ "loss": 0.5186,
+ "step": 1156
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9767088599685828e-05,
+ "loss": 0.5069,
+ "step": 1157
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9766506779833288e-05,
+ "loss": 0.523,
+ "step": 1158
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.976592424276911e-05,
+ "loss": 0.4902,
+ "step": 1159
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.976534098853608e-05,
+ "loss": 0.5006,
+ "step": 1160
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9764757017177025e-05,
+ "loss": 0.5004,
+ "step": 1161
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9764172328734828e-05,
+ "loss": 0.5145,
+ "step": 1162
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9763586923252428e-05,
+ "loss": 0.493,
+ "step": 1163
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9763000800772812e-05,
+ "loss": 0.5021,
+ "step": 1164
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9762413961339025e-05,
+ "loss": 0.5073,
+ "step": 1165
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9761826404994166e-05,
+ "loss": 0.5356,
+ "step": 1166
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9761238131781373e-05,
+ "loss": 0.523,
+ "step": 1167
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9760649141743855e-05,
+ "loss": 0.513,
+ "step": 1168
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9760059434924857e-05,
+ "loss": 0.5363,
+ "step": 1169
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9759469011367695e-05,
+ "loss": 0.5097,
+ "step": 1170
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975887787111572e-05,
+ "loss": 0.5259,
+ "step": 1171
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975828601421234e-05,
+ "loss": 0.5167,
+ "step": 1172
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975769344070103e-05,
+ "loss": 0.4906,
+ "step": 1173
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9757100150625295e-05,
+ "loss": 0.525,
+ "step": 1174
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975650614402871e-05,
+ "loss": 0.5207,
+ "step": 1175
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975591142095489e-05,
+ "loss": 0.5033,
+ "step": 1176
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9755315981447513e-05,
+ "loss": 0.5178,
+ "step": 1177
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975471982555031e-05,
+ "loss": 0.4966,
+ "step": 1178
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9754122953307052e-05,
+ "loss": 0.524,
+ "step": 1179
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9753525364761577e-05,
+ "loss": 0.5143,
+ "step": 1180
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975292705995777e-05,
+ "loss": 0.5026,
+ "step": 1181
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9752328038939562e-05,
+ "loss": 0.5305,
+ "step": 1182
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9751728301750943e-05,
+ "loss": 0.5092,
+ "step": 1183
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975112784843596e-05,
+ "loss": 0.5055,
+ "step": 1184
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.975052667903871e-05,
+ "loss": 0.5055,
+ "step": 1185
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9749924793603333e-05,
+ "loss": 0.5254,
+ "step": 1186
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974932219217403e-05,
+ "loss": 0.4859,
+ "step": 1187
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9748718874795057e-05,
+ "loss": 0.524,
+ "step": 1188
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9748114841510723e-05,
+ "loss": 0.5059,
+ "step": 1189
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9747510092365373e-05,
+ "loss": 0.4723,
+ "step": 1190
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974690462740343e-05,
+ "loss": 0.4963,
+ "step": 1191
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974629844666935e-05,
+ "loss": 0.522,
+ "step": 1192
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9745691550207647e-05,
+ "loss": 0.5129,
+ "step": 1193
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9745083938062896e-05,
+ "loss": 0.5143,
+ "step": 1194
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974447561027971e-05,
+ "loss": 0.51,
+ "step": 1195
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9743866566902766e-05,
+ "loss": 0.4938,
+ "step": 1196
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.974325680797679e-05,
+ "loss": 0.5115,
+ "step": 1197
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9742646333546564e-05,
+ "loss": 0.5036,
+ "step": 1198
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9742035143656907e-05,
+ "loss": 0.5087,
+ "step": 1199
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9741423238352713e-05,
+ "loss": 0.5302,
+ "step": 1200
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9740810617678912e-05,
+ "loss": 0.5194,
+ "step": 1201
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9740197281680495e-05,
+ "loss": 0.5209,
+ "step": 1202
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9739583230402503e-05,
+ "loss": 0.5251,
+ "step": 1203
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9738968463890026e-05,
+ "loss": 0.4995,
+ "step": 1204
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9738352982188217e-05,
+ "loss": 0.5176,
+ "step": 1205
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9737736785342265e-05,
+ "loss": 0.4993,
+ "step": 1206
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9737119873397427e-05,
+ "loss": 0.5252,
+ "step": 1207
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9736502246399006e-05,
+ "loss": 0.5087,
+ "step": 1208
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.973588390439236e-05,
+ "loss": 0.5036,
+ "step": 1209
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9735264847422893e-05,
+ "loss": 0.5247,
+ "step": 1210
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9734645075536063e-05,
+ "loss": 0.5141,
+ "step": 1211
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9734024588777393e-05,
+ "loss": 0.5,
+ "step": 1212
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9733403387192443e-05,
+ "loss": 0.5339,
+ "step": 1213
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.973278147082683e-05,
+ "loss": 0.5397,
+ "step": 1214
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9732158839726233e-05,
+ "loss": 0.5121,
+ "step": 1215
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9731535493936365e-05,
+ "loss": 0.5215,
+ "step": 1216
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9730911433503007e-05,
+ "loss": 0.5149,
+ "step": 1217
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.973028665847199e-05,
+ "loss": 0.4978,
+ "step": 1218
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9729661168889193e-05,
+ "loss": 0.5068,
+ "step": 1219
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9729034964800546e-05,
+ "loss": 0.5087,
+ "step": 1220
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9728408046252035e-05,
+ "loss": 0.5171,
+ "step": 1221
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9727780413289706e-05,
+ "loss": 0.4988,
+ "step": 1222
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.972715206595964e-05,
+ "loss": 0.5109,
+ "step": 1223
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9726523004307987e-05,
+ "loss": 0.5163,
+ "step": 1224
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9725893228380938e-05,
+ "loss": 0.5143,
+ "step": 1225
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9725262738224743e-05,
+ "loss": 0.4988,
+ "step": 1226
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9724631533885706e-05,
+ "loss": 0.5187,
+ "step": 1227
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9723999615410175e-05,
+ "loss": 0.4917,
+ "step": 1228
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9723366982844555e-05,
+ "loss": 0.5087,
+ "step": 1229
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.972273363623531e-05,
+ "loss": 0.5089,
+ "step": 1230
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9722099575628947e-05,
+ "loss": 0.5231,
+ "step": 1231
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9721464801072027e-05,
+ "loss": 0.526,
+ "step": 1232
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.972082931261117e-05,
+ "loss": 0.5141,
+ "step": 1233
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9720193110293033e-05,
+ "loss": 0.5202,
+ "step": 1234
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971955619416435e-05,
+ "loss": 0.5147,
+ "step": 1235
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9718918564271883e-05,
+ "loss": 0.5051,
+ "step": 1236
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9718280220662463e-05,
+ "loss": 0.5223,
+ "step": 1237
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9717641163382963e-05,
+ "loss": 0.4992,
+ "step": 1238
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9717001392480316e-05,
+ "loss": 0.5245,
+ "step": 1239
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9716360908001498e-05,
+ "loss": 0.5031,
+ "step": 1240
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9715719709993557e-05,
+ "loss": 0.525,
+ "step": 1241
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9715077798503564e-05,
+ "loss": 0.5027,
+ "step": 1242
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971443517357867e-05,
+ "loss": 0.5122,
+ "step": 1243
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971379183526606e-05,
+ "loss": 0.5119,
+ "step": 1244
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971314778361298e-05,
+ "loss": 0.5363,
+ "step": 1245
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9712503018666725e-05,
+ "loss": 0.508,
+ "step": 1246
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9711857540474653e-05,
+ "loss": 0.5225,
+ "step": 1247
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.971121134908415e-05,
+ "loss": 0.4993,
+ "step": 1248
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9710564444542683e-05,
+ "loss": 0.5271,
+ "step": 1249
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9709916826897747e-05,
+ "loss": 0.502,
+ "step": 1250
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9709268496196912e-05,
+ "loss": 0.519,
+ "step": 1251
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9708619452487777e-05,
+ "loss": 0.5257,
+ "step": 1252
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9707969695818013e-05,
+ "loss": 0.5047,
+ "step": 1253
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9707319226235337e-05,
+ "loss": 0.5178,
+ "step": 1254
+ },
+ {
+ "epoch": 0.1,
+ "learning_rate": 1.9706668043787505e-05,
+ "loss": 0.5169,
+ "step": 1255
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.970601614852235e-05,
+ "loss": 0.5234,
+ "step": 1256
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9705363540487737e-05,
+ "loss": 0.5084,
+ "step": 1257
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9704710219731594e-05,
+ "loss": 0.5308,
+ "step": 1258
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9704056186301898e-05,
+ "loss": 0.4999,
+ "step": 1259
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.970340144024668e-05,
+ "loss": 0.5197,
+ "step": 1260
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9702745981614018e-05,
+ "loss": 0.5139,
+ "step": 1261
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9702089810452046e-05,
+ "loss": 0.513,
+ "step": 1262
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9701432926808955e-05,
+ "loss": 0.5229,
+ "step": 1263
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9700775330732977e-05,
+ "loss": 0.5081,
+ "step": 1264
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.970011702227241e-05,
+ "loss": 0.5058,
+ "step": 1265
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9699458001475594e-05,
+ "loss": 0.5179,
+ "step": 1266
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9698798268390927e-05,
+ "loss": 0.521,
+ "step": 1267
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9698137823066856e-05,
+ "loss": 0.5244,
+ "step": 1268
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969747666555188e-05,
+ "loss": 0.5232,
+ "step": 1269
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969681479589455e-05,
+ "loss": 0.4983,
+ "step": 1270
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9696152214143476e-05,
+ "loss": 0.4996,
+ "step": 1271
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9695488920347313e-05,
+ "loss": 0.5006,
+ "step": 1272
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969482491455477e-05,
+ "loss": 0.5173,
+ "step": 1273
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969416019681461e-05,
+ "loss": 0.5322,
+ "step": 1274
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9693494767175644e-05,
+ "loss": 0.5,
+ "step": 1275
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969282862568674e-05,
+ "loss": 0.5144,
+ "step": 1276
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969216177239682e-05,
+ "loss": 0.5095,
+ "step": 1277
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.969149420735485e-05,
+ "loss": 0.4908,
+ "step": 1278
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9690825930609857e-05,
+ "loss": 0.5235,
+ "step": 1279
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9690156942210912e-05,
+ "loss": 0.5159,
+ "step": 1280
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968948724220715e-05,
+ "loss": 0.5012,
+ "step": 1281
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9688816830647743e-05,
+ "loss": 0.5233,
+ "step": 1282
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9688145707581927e-05,
+ "loss": 0.5285,
+ "step": 1283
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9687473873058987e-05,
+ "loss": 0.4938,
+ "step": 1284
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9686801327128256e-05,
+ "loss": 0.5234,
+ "step": 1285
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968612806983913e-05,
+ "loss": 0.5155,
+ "step": 1286
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9685454101241048e-05,
+ "loss": 0.5218,
+ "step": 1287
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9684779421383496e-05,
+ "loss": 0.5122,
+ "step": 1288
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968410403031603e-05,
+ "loss": 0.5191,
+ "step": 1289
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9683427928088243e-05,
+ "loss": 0.5145,
+ "step": 1290
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9682751114749783e-05,
+ "loss": 0.4944,
+ "step": 1291
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968207359035036e-05,
+ "loss": 0.5042,
+ "step": 1292
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9681395354939714e-05,
+ "loss": 0.5227,
+ "step": 1293
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9680716408567667e-05,
+ "loss": 0.4942,
+ "step": 1294
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.968003675128407e-05,
+ "loss": 0.5026,
+ "step": 1295
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.967935638313884e-05,
+ "loss": 0.5096,
+ "step": 1296
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9678675304181932e-05,
+ "loss": 0.5114,
+ "step": 1297
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9677993514463368e-05,
+ "loss": 0.5041,
+ "step": 1298
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9677311014033217e-05,
+ "loss": 0.5283,
+ "step": 1299
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.967662780294159e-05,
+ "loss": 0.524,
+ "step": 1300
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9675943881238672e-05,
+ "loss": 0.5259,
+ "step": 1301
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9675259248974675e-05,
+ "loss": 0.5022,
+ "step": 1302
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.967457390619988e-05,
+ "loss": 0.5028,
+ "step": 1303
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9673887852964623e-05,
+ "loss": 0.5134,
+ "step": 1304
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9673201089319275e-05,
+ "loss": 0.5189,
+ "step": 1305
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9672513615314278e-05,
+ "loss": 0.507,
+ "step": 1306
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9671825431000107e-05,
+ "loss": 0.5226,
+ "step": 1307
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9671136536427308e-05,
+ "loss": 0.5185,
+ "step": 1308
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9670446931646463e-05,
+ "loss": 0.5154,
+ "step": 1309
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966975661670822e-05,
+ "loss": 0.5179,
+ "step": 1310
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966906559166327e-05,
+ "loss": 0.541,
+ "step": 1311
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966837385656236e-05,
+ "loss": 0.5082,
+ "step": 1312
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9667681411456286e-05,
+ "loss": 0.4997,
+ "step": 1313
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.96669882563959e-05,
+ "loss": 0.5202,
+ "step": 1314
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9666294391432108e-05,
+ "loss": 0.5297,
+ "step": 1315
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966559981661586e-05,
+ "loss": 0.5074,
+ "step": 1316
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9664904531998165e-05,
+ "loss": 0.4969,
+ "step": 1317
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9664208537630073e-05,
+ "loss": 0.5015,
+ "step": 1318
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966351183356271e-05,
+ "loss": 0.5037,
+ "step": 1319
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9662814419847228e-05,
+ "loss": 0.4986,
+ "step": 1320
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966211629653485e-05,
+ "loss": 0.5048,
+ "step": 1321
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9661417463676834e-05,
+ "loss": 0.5106,
+ "step": 1322
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.966071792132451e-05,
+ "loss": 0.5144,
+ "step": 1323
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9660017669529236e-05,
+ "loss": 0.5227,
+ "step": 1324
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965931670834245e-05,
+ "loss": 0.5105,
+ "step": 1325
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965861503781562e-05,
+ "loss": 0.4987,
+ "step": 1326
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9657912658000272e-05,
+ "loss": 0.5063,
+ "step": 1327
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965720956894799e-05,
+ "loss": 0.5112,
+ "step": 1328
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9656505770710404e-05,
+ "loss": 0.5036,
+ "step": 1329
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9655801263339198e-05,
+ "loss": 0.4904,
+ "step": 1330
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965509604688611e-05,
+ "loss": 0.5203,
+ "step": 1331
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9654390121402927e-05,
+ "loss": 0.5097,
+ "step": 1332
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965368348694149e-05,
+ "loss": 0.5146,
+ "step": 1333
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965297614355369e-05,
+ "loss": 0.4991,
+ "step": 1334
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.965226809129147e-05,
+ "loss": 0.5255,
+ "step": 1335
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9651559330206827e-05,
+ "loss": 0.5182,
+ "step": 1336
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9650849860351818e-05,
+ "loss": 0.5092,
+ "step": 1337
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9650139681778527e-05,
+ "loss": 0.537,
+ "step": 1338
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9649428794539122e-05,
+ "loss": 0.5066,
+ "step": 1339
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9648717198685798e-05,
+ "loss": 0.5199,
+ "step": 1340
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9648004894270816e-05,
+ "loss": 0.4998,
+ "step": 1341
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9647291881346485e-05,
+ "loss": 0.5155,
+ "step": 1342
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9646578159965163e-05,
+ "loss": 0.5068,
+ "step": 1343
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9645863730179263e-05,
+ "loss": 0.4993,
+ "step": 1344
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.964514859204125e-05,
+ "loss": 0.5225,
+ "step": 1345
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9644432745603644e-05,
+ "loss": 0.5065,
+ "step": 1346
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9643716190919014e-05,
+ "loss": 0.5013,
+ "step": 1347
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9642998928039976e-05,
+ "loss": 0.499,
+ "step": 1348
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.96422809570192e-05,
+ "loss": 0.515,
+ "step": 1349
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9641562277909424e-05,
+ "loss": 0.5082,
+ "step": 1350
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9640842890763413e-05,
+ "loss": 0.5162,
+ "step": 1351
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9640122795633997e-05,
+ "loss": 0.4928,
+ "step": 1352
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9639401992574065e-05,
+ "loss": 0.4976,
+ "step": 1353
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9638680481636535e-05,
+ "loss": 0.5015,
+ "step": 1354
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9637958262874404e-05,
+ "loss": 0.4962,
+ "step": 1355
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.963723533634071e-05,
+ "loss": 0.5228,
+ "step": 1356
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9636511702088535e-05,
+ "loss": 0.5255,
+ "step": 1357
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.963578736017102e-05,
+ "loss": 0.5213,
+ "step": 1358
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.963506231064136e-05,
+ "loss": 0.5361,
+ "step": 1359
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9634336553552803e-05,
+ "loss": 0.5014,
+ "step": 1360
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9633610088958638e-05,
+ "loss": 0.5107,
+ "step": 1361
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9632882916912217e-05,
+ "loss": 0.501,
+ "step": 1362
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9632155037466942e-05,
+ "loss": 0.513,
+ "step": 1363
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9631426450676264e-05,
+ "loss": 0.4982,
+ "step": 1364
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9630697156593688e-05,
+ "loss": 0.5127,
+ "step": 1365
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.962996715527277e-05,
+ "loss": 0.488,
+ "step": 1366
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9629236446767118e-05,
+ "loss": 0.5273,
+ "step": 1367
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.962850503113039e-05,
+ "loss": 0.506,
+ "step": 1368
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9627772908416302e-05,
+ "loss": 0.4915,
+ "step": 1369
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9627040078678617e-05,
+ "loss": 0.506,
+ "step": 1370
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9626306541971153e-05,
+ "loss": 0.5139,
+ "step": 1371
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.962557229834777e-05,
+ "loss": 0.4852,
+ "step": 1372
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9624837347862398e-05,
+ "loss": 0.532,
+ "step": 1373
+ },
+ {
+ "epoch": 0.11,
+ "learning_rate": 1.9624101690569e-05,
+ "loss": 0.5052,
+ "step": 1374
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9623365326521603e-05,
+ "loss": 0.5007,
+ "step": 1375
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9622628255774288e-05,
+ "loss": 0.4933,
+ "step": 1376
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9621890478381175e-05,
+ "loss": 0.5235,
+ "step": 1377
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9621151994396443e-05,
+ "loss": 0.5125,
+ "step": 1378
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.962041280387433e-05,
+ "loss": 0.5039,
+ "step": 1379
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9619672906869114e-05,
+ "loss": 0.5263,
+ "step": 1380
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961893230343513e-05,
+ "loss": 0.5178,
+ "step": 1381
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9618190993626768e-05,
+ "loss": 0.5091,
+ "step": 1382
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961744897749846e-05,
+ "loss": 0.5201,
+ "step": 1383
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9616706255104705e-05,
+ "loss": 0.5166,
+ "step": 1384
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9615962826500038e-05,
+ "loss": 0.5028,
+ "step": 1385
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961521869173906e-05,
+ "loss": 0.5015,
+ "step": 1386
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9614473850876413e-05,
+ "loss": 0.507,
+ "step": 1387
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9613728303966794e-05,
+ "loss": 0.513,
+ "step": 1388
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.961298205106496e-05,
+ "loss": 0.5002,
+ "step": 1389
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9612235092225704e-05,
+ "loss": 0.5226,
+ "step": 1390
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9611487427503883e-05,
+ "loss": 0.4932,
+ "step": 1391
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9610739056954406e-05,
+ "loss": 0.5077,
+ "step": 1392
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9609989980632222e-05,
+ "loss": 0.5023,
+ "step": 1393
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9609240198592344e-05,
+ "loss": 0.52,
+ "step": 1394
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9608489710889837e-05,
+ "loss": 0.488,
+ "step": 1395
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9607738517579807e-05,
+ "loss": 0.4979,
+ "step": 1396
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9606986618717428e-05,
+ "loss": 0.5187,
+ "step": 1397
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9606234014357905e-05,
+ "loss": 0.5141,
+ "step": 1398
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9605480704556516e-05,
+ "loss": 0.5124,
+ "step": 1399
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960472668936857e-05,
+ "loss": 0.4959,
+ "step": 1400
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960397196884945e-05,
+ "loss": 0.495,
+ "step": 1401
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960321654305457e-05,
+ "loss": 0.514,
+ "step": 1402
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9602460412039416e-05,
+ "loss": 0.5115,
+ "step": 1403
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9601703575859504e-05,
+ "loss": 0.527,
+ "step": 1404
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960094603457042e-05,
+ "loss": 0.5074,
+ "step": 1405
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.960018778822779e-05,
+ "loss": 0.51,
+ "step": 1406
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9599428836887302e-05,
+ "loss": 0.5231,
+ "step": 1407
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9598669180604685e-05,
+ "loss": 0.5108,
+ "step": 1408
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959790881943573e-05,
+ "loss": 0.5175,
+ "step": 1409
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959714775343627e-05,
+ "loss": 0.4948,
+ "step": 1410
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9596385982662197e-05,
+ "loss": 0.5196,
+ "step": 1411
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959562350716945e-05,
+ "loss": 0.4951,
+ "step": 1412
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959486032701403e-05,
+ "loss": 0.5001,
+ "step": 1413
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959409644225197e-05,
+ "loss": 0.5112,
+ "step": 1414
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.959333185293937e-05,
+ "loss": 0.5144,
+ "step": 1415
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9592566559132384e-05,
+ "loss": 0.5077,
+ "step": 1416
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9591800560887207e-05,
+ "loss": 0.5186,
+ "step": 1417
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9591033858260094e-05,
+ "loss": 0.5239,
+ "step": 1418
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9590266451307348e-05,
+ "loss": 0.5225,
+ "step": 1419
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.958949834008532e-05,
+ "loss": 0.5016,
+ "step": 1420
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.958872952465042e-05,
+ "loss": 0.4952,
+ "step": 1421
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9587960005059104e-05,
+ "loss": 0.4957,
+ "step": 1422
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9587189781367888e-05,
+ "loss": 0.5117,
+ "step": 1423
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.958641885363333e-05,
+ "loss": 0.5254,
+ "step": 1424
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9585647221912044e-05,
+ "loss": 0.5041,
+ "step": 1425
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9584874886260695e-05,
+ "loss": 0.4954,
+ "step": 1426
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9584101846736002e-05,
+ "loss": 0.5099,
+ "step": 1427
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9583328103394733e-05,
+ "loss": 0.5261,
+ "step": 1428
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9582553656293707e-05,
+ "loss": 0.4948,
+ "step": 1429
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9581778505489797e-05,
+ "loss": 0.5298,
+ "step": 1430
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9581002651039928e-05,
+ "loss": 0.5066,
+ "step": 1431
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9580226093001077e-05,
+ "loss": 0.5078,
+ "step": 1432
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9579448831430264e-05,
+ "loss": 0.5214,
+ "step": 1433
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9578670866384574e-05,
+ "loss": 0.5257,
+ "step": 1434
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9577892197921136e-05,
+ "loss": 0.5086,
+ "step": 1435
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9577112826097134e-05,
+ "loss": 0.5219,
+ "step": 1436
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.95763327509698e-05,
+ "loss": 0.509,
+ "step": 1437
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9575551972596422e-05,
+ "loss": 0.5082,
+ "step": 1438
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9574770491034333e-05,
+ "loss": 0.5165,
+ "step": 1439
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9573988306340924e-05,
+ "loss": 0.5104,
+ "step": 1440
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9573205418573634e-05,
+ "loss": 0.5131,
+ "step": 1441
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9572421827789954e-05,
+ "loss": 0.5001,
+ "step": 1442
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.957163753404743e-05,
+ "loss": 0.5068,
+ "step": 1443
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.957085253740366e-05,
+ "loss": 0.5094,
+ "step": 1444
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9570066837916285e-05,
+ "loss": 0.504,
+ "step": 1445
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956928043564301e-05,
+ "loss": 0.5258,
+ "step": 1446
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956849333064158e-05,
+ "loss": 0.5101,
+ "step": 1447
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9567705522969796e-05,
+ "loss": 0.5094,
+ "step": 1448
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9566917012685515e-05,
+ "loss": 0.5293,
+ "step": 1449
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9566127799846642e-05,
+ "loss": 0.515,
+ "step": 1450
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9565337884511128e-05,
+ "loss": 0.4926,
+ "step": 1451
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956454726673699e-05,
+ "loss": 0.5152,
+ "step": 1452
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9563755946582277e-05,
+ "loss": 0.5183,
+ "step": 1453
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.956296392410511e-05,
+ "loss": 0.5313,
+ "step": 1454
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9562171199363646e-05,
+ "loss": 0.4952,
+ "step": 1455
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9561377772416103e-05,
+ "loss": 0.5244,
+ "step": 1456
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9560583643320745e-05,
+ "loss": 0.5044,
+ "step": 1457
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.955978881213589e-05,
+ "loss": 0.5245,
+ "step": 1458
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9558993278919904e-05,
+ "loss": 0.5117,
+ "step": 1459
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9558197043731214e-05,
+ "loss": 0.4932,
+ "step": 1460
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9557400106628285e-05,
+ "loss": 0.4863,
+ "step": 1461
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9556602467669645e-05,
+ "loss": 0.5167,
+ "step": 1462
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9555804126913868e-05,
+ "loss": 0.5063,
+ "step": 1463
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9555005084419585e-05,
+ "loss": 0.5097,
+ "step": 1464
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9554205340245468e-05,
+ "loss": 0.5213,
+ "step": 1465
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.955340489445025e-05,
+ "loss": 0.4985,
+ "step": 1466
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9552603747092714e-05,
+ "loss": 0.5026,
+ "step": 1467
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9551801898231692e-05,
+ "loss": 0.506,
+ "step": 1468
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9550999347926064e-05,
+ "loss": 0.5001,
+ "step": 1469
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.955019609623477e-05,
+ "loss": 0.5154,
+ "step": 1470
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.95493921432168e-05,
+ "loss": 0.5028,
+ "step": 1471
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9548587488931187e-05,
+ "loss": 0.5032,
+ "step": 1472
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9547782133437024e-05,
+ "loss": 0.508,
+ "step": 1473
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9546976076793456e-05,
+ "loss": 0.5321,
+ "step": 1474
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954616931905967e-05,
+ "loss": 0.4916,
+ "step": 1475
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954536186029492e-05,
+ "loss": 0.4889,
+ "step": 1476
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954455370055849e-05,
+ "loss": 0.5233,
+ "step": 1477
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9543744839909743e-05,
+ "loss": 0.4962,
+ "step": 1478
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9542935278408066e-05,
+ "loss": 0.4988,
+ "step": 1479
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9542125016112913e-05,
+ "loss": 0.5181,
+ "step": 1480
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.954131405308379e-05,
+ "loss": 0.5045,
+ "step": 1481
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9540502389380245e-05,
+ "loss": 0.5008,
+ "step": 1482
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.953969002506189e-05,
+ "loss": 0.522,
+ "step": 1483
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9538876960188378e-05,
+ "loss": 0.5198,
+ "step": 1484
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9538063194819418e-05,
+ "loss": 0.5029,
+ "step": 1485
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9537248729014767e-05,
+ "loss": 0.5282,
+ "step": 1486
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9536433562834235e-05,
+ "loss": 0.5243,
+ "step": 1487
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.953561769633769e-05,
+ "loss": 0.5025,
+ "step": 1488
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9534801129585044e-05,
+ "loss": 0.5192,
+ "step": 1489
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.953398386263626e-05,
+ "loss": 0.4863,
+ "step": 1490
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9533165895551356e-05,
+ "loss": 0.5097,
+ "step": 1491
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.95323472283904e-05,
+ "loss": 0.5092,
+ "step": 1492
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9531527861213514e-05,
+ "loss": 0.5021,
+ "step": 1493
+ },
+ {
+ "epoch": 0.12,
+ "learning_rate": 1.9530707794080864e-05,
+ "loss": 0.5236,
+ "step": 1494
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9529887027052676e-05,
+ "loss": 0.5116,
+ "step": 1495
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952906556018922e-05,
+ "loss": 0.5081,
+ "step": 1496
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9528243393550825e-05,
+ "loss": 0.4812,
+ "step": 1497
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9527420527197867e-05,
+ "loss": 0.5272,
+ "step": 1498
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9526596961190772e-05,
+ "loss": 0.4959,
+ "step": 1499
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952577269559002e-05,
+ "loss": 0.5129,
+ "step": 1500
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952494773045614e-05,
+ "loss": 0.5061,
+ "step": 1501
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9524122065849722e-05,
+ "loss": 0.5036,
+ "step": 1502
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9523295701831388e-05,
+ "loss": 0.5044,
+ "step": 1503
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.952246863846183e-05,
+ "loss": 0.516,
+ "step": 1504
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9521640875801783e-05,
+ "loss": 0.5064,
+ "step": 1505
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9520812413912032e-05,
+ "loss": 0.5003,
+ "step": 1506
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9519983252853415e-05,
+ "loss": 0.5019,
+ "step": 1507
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9519153392686828e-05,
+ "loss": 0.5233,
+ "step": 1508
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.951832283347321e-05,
+ "loss": 0.516,
+ "step": 1509
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9517491575273552e-05,
+ "loss": 0.5068,
+ "step": 1510
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9516659618148897e-05,
+ "loss": 0.5093,
+ "step": 1511
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9515826962160342e-05,
+ "loss": 0.5433,
+ "step": 1512
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9514993607369037e-05,
+ "loss": 0.4968,
+ "step": 1513
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9514159553836177e-05,
+ "loss": 0.5295,
+ "step": 1514
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.951332480162301e-05,
+ "loss": 0.5024,
+ "step": 1515
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9512489350790838e-05,
+ "loss": 0.4909,
+ "step": 1516
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9511653201401012e-05,
+ "loss": 0.5222,
+ "step": 1517
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.951081635351494e-05,
+ "loss": 0.538,
+ "step": 1518
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9509978807194075e-05,
+ "loss": 0.5152,
+ "step": 1519
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.950914056249992e-05,
+ "loss": 0.5195,
+ "step": 1520
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9508301619494033e-05,
+ "loss": 0.496,
+ "step": 1521
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.950746197823802e-05,
+ "loss": 0.5049,
+ "step": 1522
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9506621638793548e-05,
+ "loss": 0.4945,
+ "step": 1523
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9505780601222323e-05,
+ "loss": 0.5202,
+ "step": 1524
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9504938865586107e-05,
+ "loss": 0.523,
+ "step": 1525
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9504096431946716e-05,
+ "loss": 0.522,
+ "step": 1526
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9503253300366013e-05,
+ "loss": 0.49,
+ "step": 1527
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9502409470905913e-05,
+ "loss": 0.5066,
+ "step": 1528
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.950156494362839e-05,
+ "loss": 0.4991,
+ "step": 1529
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9500719718595454e-05,
+ "loss": 0.4954,
+ "step": 1530
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9499873795869178e-05,
+ "loss": 0.5012,
+ "step": 1531
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9499027175511682e-05,
+ "loss": 0.4998,
+ "step": 1532
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9498179857585143e-05,
+ "loss": 0.5168,
+ "step": 1533
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.949733184215178e-05,
+ "loss": 0.5179,
+ "step": 1534
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9496483129273866e-05,
+ "loss": 0.5061,
+ "step": 1535
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9495633719013733e-05,
+ "loss": 0.527,
+ "step": 1536
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9494783611433754e-05,
+ "loss": 0.506,
+ "step": 1537
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9493932806596357e-05,
+ "loss": 0.5057,
+ "step": 1538
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9493081304564025e-05,
+ "loss": 0.5144,
+ "step": 1539
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9492229105399287e-05,
+ "loss": 0.518,
+ "step": 1540
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9491376209164726e-05,
+ "loss": 0.526,
+ "step": 1541
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.949052261592297e-05,
+ "loss": 0.5012,
+ "step": 1542
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948966832573671e-05,
+ "loss": 0.5005,
+ "step": 1543
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9488813338668676e-05,
+ "loss": 0.5124,
+ "step": 1544
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948795765478166e-05,
+ "loss": 0.5017,
+ "step": 1545
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9487101274138494e-05,
+ "loss": 0.5069,
+ "step": 1546
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9486244196802075e-05,
+ "loss": 0.4965,
+ "step": 1547
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9485386422835334e-05,
+ "loss": 0.5156,
+ "step": 1548
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948452795230127e-05,
+ "loss": 0.5098,
+ "step": 1549
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948366878526292e-05,
+ "loss": 0.5146,
+ "step": 1550
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948280892178338e-05,
+ "loss": 0.4822,
+ "step": 1551
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9481948361925796e-05,
+ "loss": 0.52,
+ "step": 1552
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9481087105753364e-05,
+ "loss": 0.5043,
+ "step": 1553
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.948022515332933e-05,
+ "loss": 0.4827,
+ "step": 1554
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9479362504716987e-05,
+ "loss": 0.5335,
+ "step": 1555
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9478499159979693e-05,
+ "loss": 0.5135,
+ "step": 1556
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9477635119180843e-05,
+ "loss": 0.5032,
+ "step": 1557
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947677038238389e-05,
+ "loss": 0.5122,
+ "step": 1558
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947590494965234e-05,
+ "loss": 0.5083,
+ "step": 1559
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9475038821049744e-05,
+ "loss": 0.5332,
+ "step": 1560
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9474171996639702e-05,
+ "loss": 0.4818,
+ "step": 1561
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947330447648588e-05,
+ "loss": 0.5206,
+ "step": 1562
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9472436260651976e-05,
+ "loss": 0.5059,
+ "step": 1563
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.947156734920175e-05,
+ "loss": 0.5188,
+ "step": 1564
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9470697742199018e-05,
+ "loss": 0.5141,
+ "step": 1565
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9469827439707632e-05,
+ "loss": 0.505,
+ "step": 1566
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946895644179151e-05,
+ "loss": 0.5005,
+ "step": 1567
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946808474851461e-05,
+ "loss": 0.5152,
+ "step": 1568
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9467212359940944e-05,
+ "loss": 0.5156,
+ "step": 1569
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9466339276134584e-05,
+ "loss": 0.5007,
+ "step": 1570
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946546549715964e-05,
+ "loss": 0.514,
+ "step": 1571
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9464591023080274e-05,
+ "loss": 0.5101,
+ "step": 1572
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9463715853960714e-05,
+ "loss": 0.5019,
+ "step": 1573
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9462839989865226e-05,
+ "loss": 0.5165,
+ "step": 1574
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9461963430858125e-05,
+ "loss": 0.5078,
+ "step": 1575
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9461086177003788e-05,
+ "loss": 0.5235,
+ "step": 1576
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.946020822836663e-05,
+ "loss": 0.4954,
+ "step": 1577
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945932958501113e-05,
+ "loss": 0.5357,
+ "step": 1578
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945845024700181e-05,
+ "loss": 0.4957,
+ "step": 1579
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9457570214403242e-05,
+ "loss": 0.5249,
+ "step": 1580
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9456689487280056e-05,
+ "loss": 0.5397,
+ "step": 1581
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9455808065696925e-05,
+ "loss": 0.5026,
+ "step": 1582
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9454925949718583e-05,
+ "loss": 0.4986,
+ "step": 1583
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9454043139409803e-05,
+ "loss": 0.5172,
+ "step": 1584
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945315963483542e-05,
+ "loss": 0.5243,
+ "step": 1585
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945227543606031e-05,
+ "loss": 0.4918,
+ "step": 1586
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945139054314941e-05,
+ "loss": 0.5084,
+ "step": 1587
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.945050495616769e-05,
+ "loss": 0.5445,
+ "step": 1588
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9449618675180205e-05,
+ "loss": 0.5013,
+ "step": 1589
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9448731700252025e-05,
+ "loss": 0.5026,
+ "step": 1590
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9447844031448288e-05,
+ "loss": 0.5368,
+ "step": 1591
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.944695566883418e-05,
+ "loss": 0.5089,
+ "step": 1592
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9446066612474942e-05,
+ "loss": 0.4996,
+ "step": 1593
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9445176862435864e-05,
+ "loss": 0.5315,
+ "step": 1594
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.944428641878228e-05,
+ "loss": 0.4945,
+ "step": 1595
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9443395281579583e-05,
+ "loss": 0.5109,
+ "step": 1596
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9442503450893216e-05,
+ "loss": 0.4996,
+ "step": 1597
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.944161092678867e-05,
+ "loss": 0.4923,
+ "step": 1598
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9440717709331484e-05,
+ "loss": 0.5056,
+ "step": 1599
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943982379858726e-05,
+ "loss": 0.5007,
+ "step": 1600
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943892919462164e-05,
+ "loss": 0.498,
+ "step": 1601
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943803389750032e-05,
+ "loss": 0.5099,
+ "step": 1602
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943713790728904e-05,
+ "loss": 0.5205,
+ "step": 1603
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.943624122405361e-05,
+ "loss": 0.5158,
+ "step": 1604
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9435343847859873e-05,
+ "loss": 0.5149,
+ "step": 1605
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9434445778773724e-05,
+ "loss": 0.5091,
+ "step": 1606
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9433547016861124e-05,
+ "loss": 0.5026,
+ "step": 1607
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9432647562188062e-05,
+ "loss": 0.502,
+ "step": 1608
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9431747414820597e-05,
+ "loss": 0.4999,
+ "step": 1609
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9430846574824835e-05,
+ "loss": 0.5014,
+ "step": 1610
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9429945042266925e-05,
+ "loss": 0.4999,
+ "step": 1611
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9429042817213072e-05,
+ "loss": 0.5387,
+ "step": 1612
+ },
+ {
+ "epoch": 0.13,
+ "learning_rate": 1.9428139899729538e-05,
+ "loss": 0.5215,
+ "step": 1613
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9427236289882618e-05,
+ "loss": 0.49,
+ "step": 1614
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9426331987738678e-05,
+ "loss": 0.5053,
+ "step": 1615
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9425426993364126e-05,
+ "loss": 0.5108,
+ "step": 1616
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9424521306825414e-05,
+ "loss": 0.5044,
+ "step": 1617
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.942361492818906e-05,
+ "loss": 0.5024,
+ "step": 1618
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.942270785752162e-05,
+ "loss": 0.5122,
+ "step": 1619
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.942180009488971e-05,
+ "loss": 0.4883,
+ "step": 1620
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9420891640359986e-05,
+ "loss": 0.5229,
+ "step": 1621
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9419982493999164e-05,
+ "loss": 0.5099,
+ "step": 1622
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941907265587401e-05,
+ "loss": 0.506,
+ "step": 1623
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941816212605134e-05,
+ "loss": 0.5054,
+ "step": 1624
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9417250904598012e-05,
+ "loss": 0.5049,
+ "step": 1625
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941633899158095e-05,
+ "loss": 0.4866,
+ "step": 1626
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9415426387067113e-05,
+ "loss": 0.5025,
+ "step": 1627
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9414513091123527e-05,
+ "loss": 0.4994,
+ "step": 1628
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.941359910381726e-05,
+ "loss": 0.4944,
+ "step": 1629
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9412684425215426e-05,
+ "loss": 0.4999,
+ "step": 1630
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.94117690553852e-05,
+ "loss": 0.5114,
+ "step": 1631
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.94108529943938e-05,
+ "loss": 0.5099,
+ "step": 1632
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9409936242308496e-05,
+ "loss": 0.4935,
+ "step": 1633
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9409018799196615e-05,
+ "loss": 0.5183,
+ "step": 1634
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940810066512553e-05,
+ "loss": 0.5118,
+ "step": 1635
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9407181840162664e-05,
+ "loss": 0.4947,
+ "step": 1636
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940626232437549e-05,
+ "loss": 0.4854,
+ "step": 1637
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9405342117831533e-05,
+ "loss": 0.5058,
+ "step": 1638
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940442122059837e-05,
+ "loss": 0.5044,
+ "step": 1639
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940349963274363e-05,
+ "loss": 0.5109,
+ "step": 1640
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.940257735433499e-05,
+ "loss": 0.5157,
+ "step": 1641
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9401654385440176e-05,
+ "loss": 0.5039,
+ "step": 1642
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9400730726126967e-05,
+ "loss": 0.5233,
+ "step": 1643
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9399806376463197e-05,
+ "loss": 0.5069,
+ "step": 1644
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9398881336516743e-05,
+ "loss": 0.4975,
+ "step": 1645
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9397955606355535e-05,
+ "loss": 0.4895,
+ "step": 1646
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939702918604756e-05,
+ "loss": 0.5138,
+ "step": 1647
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939610207566084e-05,
+ "loss": 0.5043,
+ "step": 1648
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9395174275263474e-05,
+ "loss": 0.5129,
+ "step": 1649
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939424578492358e-05,
+ "loss": 0.5204,
+ "step": 1650
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939331660470935e-05,
+ "loss": 0.5179,
+ "step": 1651
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.939238673468902e-05,
+ "loss": 0.4908,
+ "step": 1652
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9391456174930872e-05,
+ "loss": 0.5208,
+ "step": 1653
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9390524925503244e-05,
+ "loss": 0.5036,
+ "step": 1654
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938959298647453e-05,
+ "loss": 0.5021,
+ "step": 1655
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9388660357913155e-05,
+ "loss": 0.4836,
+ "step": 1656
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9387727039887613e-05,
+ "loss": 0.5131,
+ "step": 1657
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9386793032466447e-05,
+ "loss": 0.4923,
+ "step": 1658
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938585833571824e-05,
+ "loss": 0.4989,
+ "step": 1659
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938492294971164e-05,
+ "loss": 0.4997,
+ "step": 1660
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938398687451533e-05,
+ "loss": 0.5122,
+ "step": 1661
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938305011019806e-05,
+ "loss": 0.5224,
+ "step": 1662
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938211265682861e-05,
+ "loss": 0.5035,
+ "step": 1663
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938117451447583e-05,
+ "loss": 0.4923,
+ "step": 1664
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.938023568320862e-05,
+ "loss": 0.4831,
+ "step": 1665
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.937929616309591e-05,
+ "loss": 0.5233,
+ "step": 1666
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9378355954206706e-05,
+ "loss": 0.4931,
+ "step": 1667
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9377415056610044e-05,
+ "loss": 0.5169,
+ "step": 1668
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9376473470375027e-05,
+ "loss": 0.5293,
+ "step": 1669
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9375531195570793e-05,
+ "loss": 0.4901,
+ "step": 1670
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.937458823226655e-05,
+ "loss": 0.494,
+ "step": 1671
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9373644580531538e-05,
+ "loss": 0.4901,
+ "step": 1672
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9372700240435054e-05,
+ "loss": 0.4935,
+ "step": 1673
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9371755212046448e-05,
+ "loss": 0.5092,
+ "step": 1674
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.937080949543512e-05,
+ "loss": 0.5221,
+ "step": 1675
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9369863090670518e-05,
+ "loss": 0.5167,
+ "step": 1676
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9368915997822143e-05,
+ "loss": 0.4965,
+ "step": 1677
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936796821695955e-05,
+ "loss": 0.5117,
+ "step": 1678
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9367019748152328e-05,
+ "loss": 0.4949,
+ "step": 1679
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936607059147014e-05,
+ "loss": 0.4979,
+ "step": 1680
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9365120746982683e-05,
+ "loss": 0.5053,
+ "step": 1681
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936417021475971e-05,
+ "loss": 0.5028,
+ "step": 1682
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9363218994871026e-05,
+ "loss": 0.4857,
+ "step": 1683
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9362267087386487e-05,
+ "loss": 0.5216,
+ "step": 1684
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.936131449237599e-05,
+ "loss": 0.5015,
+ "step": 1685
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9360361209909494e-05,
+ "loss": 0.513,
+ "step": 1686
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9359407240057003e-05,
+ "loss": 0.4847,
+ "step": 1687
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9358452582888575e-05,
+ "loss": 0.5185,
+ "step": 1688
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.935749723847431e-05,
+ "loss": 0.4861,
+ "step": 1689
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.935654120688437e-05,
+ "loss": 0.5161,
+ "step": 1690
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9355584488188965e-05,
+ "loss": 0.4871,
+ "step": 1691
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9354627082458342e-05,
+ "loss": 0.525,
+ "step": 1692
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9353668989762817e-05,
+ "loss": 0.504,
+ "step": 1693
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.935271021017275e-05,
+ "loss": 0.4978,
+ "step": 1694
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9351750743758543e-05,
+ "loss": 0.5007,
+ "step": 1695
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9350790590590657e-05,
+ "loss": 0.5096,
+ "step": 1696
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.93498297507396e-05,
+ "loss": 0.5025,
+ "step": 1697
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9348868224275943e-05,
+ "loss": 0.5048,
+ "step": 1698
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9347906011270283e-05,
+ "loss": 0.5047,
+ "step": 1699
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9346943111793286e-05,
+ "loss": 0.512,
+ "step": 1700
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.934597952591567e-05,
+ "loss": 0.5133,
+ "step": 1701
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.934501525370818e-05,
+ "loss": 0.4905,
+ "step": 1702
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9344050295241648e-05,
+ "loss": 0.4937,
+ "step": 1703
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9343084650586922e-05,
+ "loss": 0.5147,
+ "step": 1704
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9342118319814923e-05,
+ "loss": 0.4967,
+ "step": 1705
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.934115130299661e-05,
+ "loss": 0.5341,
+ "step": 1706
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9340183600202998e-05,
+ "loss": 0.4955,
+ "step": 1707
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.933921521150515e-05,
+ "loss": 0.4864,
+ "step": 1708
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9338246136974182e-05,
+ "loss": 0.5248,
+ "step": 1709
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9337276376681264e-05,
+ "loss": 0.5103,
+ "step": 1710
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.93363059306976e-05,
+ "loss": 0.5182,
+ "step": 1711
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.933533479909446e-05,
+ "loss": 0.5186,
+ "step": 1712
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9334362981943163e-05,
+ "loss": 0.5112,
+ "step": 1713
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9333390479315074e-05,
+ "loss": 0.4874,
+ "step": 1714
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9332417291281608e-05,
+ "loss": 0.4948,
+ "step": 1715
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9331443417914232e-05,
+ "loss": 0.5153,
+ "step": 1716
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9330468859284462e-05,
+ "loss": 0.5004,
+ "step": 1717
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932949361546387e-05,
+ "loss": 0.4919,
+ "step": 1718
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9328517686524073e-05,
+ "loss": 0.5057,
+ "step": 1719
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9327541072536733e-05,
+ "loss": 0.5056,
+ "step": 1720
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9326563773573576e-05,
+ "loss": 0.4943,
+ "step": 1721
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9325585789706366e-05,
+ "loss": 0.5114,
+ "step": 1722
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932460712100692e-05,
+ "loss": 0.4955,
+ "step": 1723
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9323627767547118e-05,
+ "loss": 0.4962,
+ "step": 1724
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932264772939887e-05,
+ "loss": 0.5037,
+ "step": 1725
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9321667006634146e-05,
+ "loss": 0.5101,
+ "step": 1726
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.932068559932497e-05,
+ "loss": 0.5041,
+ "step": 1727
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9319703507543415e-05,
+ "loss": 0.4974,
+ "step": 1728
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9318720731361593e-05,
+ "loss": 0.5173,
+ "step": 1729
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.931773727085168e-05,
+ "loss": 0.5043,
+ "step": 1730
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9316753126085902e-05,
+ "loss": 0.5068,
+ "step": 1731
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9315768297136523e-05,
+ "loss": 0.5033,
+ "step": 1732
+ },
+ {
+ "epoch": 0.14,
+ "learning_rate": 1.9314782784075866e-05,
+ "loss": 0.5153,
+ "step": 1733
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9313796586976306e-05,
+ "loss": 0.5235,
+ "step": 1734
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9312809705910266e-05,
+ "loss": 0.4886,
+ "step": 1735
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9311822140950213e-05,
+ "loss": 0.493,
+ "step": 1736
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.931083389216867e-05,
+ "loss": 0.5066,
+ "step": 1737
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930984495963822e-05,
+ "loss": 0.4965,
+ "step": 1738
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930885534343147e-05,
+ "loss": 0.497,
+ "step": 1739
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930786504362111e-05,
+ "loss": 0.4967,
+ "step": 1740
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930687406027985e-05,
+ "loss": 0.4892,
+ "step": 1741
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930588239348047e-05,
+ "loss": 0.5099,
+ "step": 1742
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9304890043295796e-05,
+ "loss": 0.5118,
+ "step": 1743
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.93038970097987e-05,
+ "loss": 0.504,
+ "step": 1744
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.93029032930621e-05,
+ "loss": 0.5056,
+ "step": 1745
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930190889315898e-05,
+ "loss": 0.499,
+ "step": 1746
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.930091381016236e-05,
+ "loss": 0.5259,
+ "step": 1747
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9299918044145315e-05,
+ "loss": 0.5033,
+ "step": 1748
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9298921595180968e-05,
+ "loss": 0.5005,
+ "step": 1749
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9297924463342495e-05,
+ "loss": 0.518,
+ "step": 1750
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.929692664870313e-05,
+ "loss": 0.5143,
+ "step": 1751
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9295928151336134e-05,
+ "loss": 0.5061,
+ "step": 1752
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9294928971314843e-05,
+ "loss": 0.5013,
+ "step": 1753
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9293929108712624e-05,
+ "loss": 0.5112,
+ "step": 1754
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9292928563602912e-05,
+ "loss": 0.4963,
+ "step": 1755
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9291927336059175e-05,
+ "loss": 0.5058,
+ "step": 1756
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9290925426154948e-05,
+ "loss": 0.4977,
+ "step": 1757
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9289922833963798e-05,
+ "loss": 0.5122,
+ "step": 1758
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9288919559559353e-05,
+ "loss": 0.5096,
+ "step": 1759
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.928791560301529e-05,
+ "loss": 0.5032,
+ "step": 1760
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9286910964405345e-05,
+ "loss": 0.4987,
+ "step": 1761
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9285905643803277e-05,
+ "loss": 0.5022,
+ "step": 1762
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9284899641282925e-05,
+ "loss": 0.4889,
+ "step": 1763
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.928389295691816e-05,
+ "loss": 0.5117,
+ "step": 1764
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9282885590782916e-05,
+ "loss": 0.5068,
+ "step": 1765
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.928187754295116e-05,
+ "loss": 0.5271,
+ "step": 1766
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9280868813496927e-05,
+ "loss": 0.497,
+ "step": 1767
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9279859402494288e-05,
+ "loss": 0.5223,
+ "step": 1768
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9278849310017372e-05,
+ "loss": 0.5151,
+ "step": 1769
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9277838536140357e-05,
+ "loss": 0.5233,
+ "step": 1770
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.927682708093747e-05,
+ "loss": 0.4949,
+ "step": 1771
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9275814944482988e-05,
+ "loss": 0.5211,
+ "step": 1772
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9274802126851237e-05,
+ "loss": 0.4977,
+ "step": 1773
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9273788628116593e-05,
+ "loss": 0.5169,
+ "step": 1774
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9272774448353484e-05,
+ "loss": 0.5062,
+ "step": 1775
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.927175958763639e-05,
+ "loss": 0.4999,
+ "step": 1776
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9270744046039834e-05,
+ "loss": 0.5578,
+ "step": 1777
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92697278236384e-05,
+ "loss": 0.5188,
+ "step": 1778
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9268710920506707e-05,
+ "loss": 0.5076,
+ "step": 1779
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926769333671943e-05,
+ "loss": 0.4947,
+ "step": 1780
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926667507235131e-05,
+ "loss": 0.5049,
+ "step": 1781
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9265656127477114e-05,
+ "loss": 0.5118,
+ "step": 1782
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926463650217167e-05,
+ "loss": 0.489,
+ "step": 1783
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9263616196509855e-05,
+ "loss": 0.5062,
+ "step": 1784
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9262595210566598e-05,
+ "loss": 0.5238,
+ "step": 1785
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9261573544416872e-05,
+ "loss": 0.4939,
+ "step": 1786
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.926055119813571e-05,
+ "loss": 0.491,
+ "step": 1787
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9259528171798184e-05,
+ "loss": 0.4932,
+ "step": 1788
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925850446547942e-05,
+ "loss": 0.5256,
+ "step": 1789
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92574800792546e-05,
+ "loss": 0.5049,
+ "step": 1790
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925645501319895e-05,
+ "loss": 0.4982,
+ "step": 1791
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925542926738774e-05,
+ "loss": 0.5154,
+ "step": 1792
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92544028418963e-05,
+ "loss": 0.5136,
+ "step": 1793
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9253375736800014e-05,
+ "loss": 0.4918,
+ "step": 1794
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9252347952174294e-05,
+ "loss": 0.5009,
+ "step": 1795
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.925131948809463e-05,
+ "loss": 0.5235,
+ "step": 1796
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9250290344636537e-05,
+ "loss": 0.5012,
+ "step": 1797
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.92492605218756e-05,
+ "loss": 0.4942,
+ "step": 1798
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9248230019887438e-05,
+ "loss": 0.5102,
+ "step": 1799
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.924719883874773e-05,
+ "loss": 0.4946,
+ "step": 1800
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9246166978532203e-05,
+ "loss": 0.5077,
+ "step": 1801
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.924513443931663e-05,
+ "loss": 0.5084,
+ "step": 1802
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9244101221176834e-05,
+ "loss": 0.4944,
+ "step": 1803
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9243067324188696e-05,
+ "loss": 0.5069,
+ "step": 1804
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9242032748428138e-05,
+ "loss": 0.4945,
+ "step": 1805
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.924099749397114e-05,
+ "loss": 0.507,
+ "step": 1806
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9239961560893717e-05,
+ "loss": 0.5152,
+ "step": 1807
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.923892494927195e-05,
+ "loss": 0.4897,
+ "step": 1808
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9237887659181963e-05,
+ "loss": 0.4968,
+ "step": 1809
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9236849690699924e-05,
+ "loss": 0.5118,
+ "step": 1810
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.923581104390207e-05,
+ "loss": 0.5128,
+ "step": 1811
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9234771718864667e-05,
+ "loss": 0.4928,
+ "step": 1812
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9233731715664036e-05,
+ "loss": 0.5075,
+ "step": 1813
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9232691034376556e-05,
+ "loss": 0.5109,
+ "step": 1814
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9231649675078647e-05,
+ "loss": 0.4918,
+ "step": 1815
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9230607637846785e-05,
+ "loss": 0.5056,
+ "step": 1816
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9229564922757487e-05,
+ "loss": 0.4999,
+ "step": 1817
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9228521529887333e-05,
+ "loss": 0.5066,
+ "step": 1818
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9227477459312942e-05,
+ "loss": 0.4944,
+ "step": 1819
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9226432711110983e-05,
+ "loss": 0.5145,
+ "step": 1820
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.922538728535819e-05,
+ "loss": 0.5033,
+ "step": 1821
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.922434118213132e-05,
+ "loss": 0.5292,
+ "step": 1822
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9223294401507196e-05,
+ "loss": 0.5067,
+ "step": 1823
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9222246943562702e-05,
+ "loss": 0.5016,
+ "step": 1824
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9221198808374746e-05,
+ "loss": 0.4928,
+ "step": 1825
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9220149996020306e-05,
+ "loss": 0.5077,
+ "step": 1826
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9219100506576396e-05,
+ "loss": 0.4962,
+ "step": 1827
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9218050340120095e-05,
+ "loss": 0.5081,
+ "step": 1828
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9216999496728513e-05,
+ "loss": 0.5203,
+ "step": 1829
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9215947976478825e-05,
+ "loss": 0.511,
+ "step": 1830
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9214895779448254e-05,
+ "loss": 0.5018,
+ "step": 1831
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.921384290571406e-05,
+ "loss": 0.4929,
+ "step": 1832
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9212789355353567e-05,
+ "loss": 0.4992,
+ "step": 1833
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.921173512844414e-05,
+ "loss": 0.5106,
+ "step": 1834
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9210680225063204e-05,
+ "loss": 0.4934,
+ "step": 1835
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9209624645288224e-05,
+ "loss": 0.5013,
+ "step": 1836
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9208568389196715e-05,
+ "loss": 0.4948,
+ "step": 1837
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920751145686624e-05,
+ "loss": 0.4963,
+ "step": 1838
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9206453848374425e-05,
+ "loss": 0.499,
+ "step": 1839
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920539556379893e-05,
+ "loss": 0.4947,
+ "step": 1840
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920433660321747e-05,
+ "loss": 0.5145,
+ "step": 1841
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.920327696670782e-05,
+ "loss": 0.4967,
+ "step": 1842
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9202216654347786e-05,
+ "loss": 0.52,
+ "step": 1843
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9201155666215237e-05,
+ "loss": 0.5103,
+ "step": 1844
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9200094002388084e-05,
+ "loss": 0.5124,
+ "step": 1845
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9199031662944294e-05,
+ "loss": 0.5054,
+ "step": 1846
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.919796864796188e-05,
+ "loss": 0.4923,
+ "step": 1847
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.919690495751891e-05,
+ "loss": 0.5264,
+ "step": 1848
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9195840591693486e-05,
+ "loss": 0.4979,
+ "step": 1849
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.919477555056378e-05,
+ "loss": 0.5072,
+ "step": 1850
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9193709834208005e-05,
+ "loss": 0.5136,
+ "step": 1851
+ },
+ {
+ "epoch": 0.15,
+ "learning_rate": 1.9192643442704413e-05,
+ "loss": 0.5028,
+ "step": 1852
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9191576376131328e-05,
+ "loss": 0.52,
+ "step": 1853
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91905086345671e-05,
+ "loss": 0.5033,
+ "step": 1854
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9189440218090146e-05,
+ "loss": 0.5088,
+ "step": 1855
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9188371126778923e-05,
+ "loss": 0.5009,
+ "step": 1856
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9187301360711943e-05,
+ "loss": 0.5068,
+ "step": 1857
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9186230919967764e-05,
+ "loss": 0.4997,
+ "step": 1858
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9185159804624994e-05,
+ "loss": 0.5098,
+ "step": 1859
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9184088014762292e-05,
+ "loss": 0.4964,
+ "step": 1860
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9183015550458367e-05,
+ "loss": 0.5084,
+ "step": 1861
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.918194241179197e-05,
+ "loss": 0.5049,
+ "step": 1862
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9180868598841916e-05,
+ "loss": 0.4998,
+ "step": 1863
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9179794111687063e-05,
+ "loss": 0.5073,
+ "step": 1864
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9178718950406304e-05,
+ "loss": 0.5088,
+ "step": 1865
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.917764311507861e-05,
+ "loss": 0.4973,
+ "step": 1866
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9176566605782974e-05,
+ "loss": 0.5177,
+ "step": 1867
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9175489422598455e-05,
+ "loss": 0.5072,
+ "step": 1868
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9174411565604157e-05,
+ "loss": 0.5095,
+ "step": 1869
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.917333303487923e-05,
+ "loss": 0.4966,
+ "step": 1870
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9172253830502883e-05,
+ "loss": 0.5067,
+ "step": 1871
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9171173952554367e-05,
+ "loss": 0.5058,
+ "step": 1872
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.917009340111298e-05,
+ "loss": 0.5126,
+ "step": 1873
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.916901217625807e-05,
+ "loss": 0.5041,
+ "step": 1874
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.916793027806905e-05,
+ "loss": 0.4989,
+ "step": 1875
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9166847706625357e-05,
+ "loss": 0.5211,
+ "step": 1876
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91657644620065e-05,
+ "loss": 0.499,
+ "step": 1877
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9164680544292023e-05,
+ "loss": 0.4914,
+ "step": 1878
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9163595953561523e-05,
+ "loss": 0.5074,
+ "step": 1879
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9162510689894653e-05,
+ "loss": 0.534,
+ "step": 1880
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.916142475337111e-05,
+ "loss": 0.5084,
+ "step": 1881
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9160338144070635e-05,
+ "loss": 0.5069,
+ "step": 1882
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9159250862073028e-05,
+ "loss": 0.5611,
+ "step": 1883
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9158162907458135e-05,
+ "loss": 0.4864,
+ "step": 1884
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9157074280305847e-05,
+ "loss": 0.5034,
+ "step": 1885
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9155984980696112e-05,
+ "loss": 0.5303,
+ "step": 1886
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9154895008708923e-05,
+ "loss": 0.4934,
+ "step": 1887
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9153804364424325e-05,
+ "loss": 0.4889,
+ "step": 1888
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9152713047922406e-05,
+ "loss": 0.5199,
+ "step": 1889
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9151621059283306e-05,
+ "loss": 0.5035,
+ "step": 1890
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9150528398587226e-05,
+ "loss": 0.5213,
+ "step": 1891
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9149435065914395e-05,
+ "loss": 0.4933,
+ "step": 1892
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9148341061345114e-05,
+ "loss": 0.4935,
+ "step": 1893
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9147246384959715e-05,
+ "loss": 0.5199,
+ "step": 1894
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9146151036838583e-05,
+ "loss": 0.5242,
+ "step": 1895
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9145055017062165e-05,
+ "loss": 0.4793,
+ "step": 1896
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.914395832571094e-05,
+ "loss": 0.5142,
+ "step": 1897
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.914286096286545e-05,
+ "loss": 0.4923,
+ "step": 1898
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9141762928606282e-05,
+ "loss": 0.4866,
+ "step": 1899
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9140664223014064e-05,
+ "loss": 0.4988,
+ "step": 1900
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9139564846169486e-05,
+ "loss": 0.4838,
+ "step": 1901
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913846479815328e-05,
+ "loss": 0.5151,
+ "step": 1902
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913736407904623e-05,
+ "loss": 0.493,
+ "step": 1903
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9136262688929167e-05,
+ "loss": 0.4959,
+ "step": 1904
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913516062788297e-05,
+ "loss": 0.5162,
+ "step": 1905
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9134057895988574e-05,
+ "loss": 0.4908,
+ "step": 1906
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913295449332696e-05,
+ "loss": 0.5083,
+ "step": 1907
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913185041997915e-05,
+ "loss": 0.5152,
+ "step": 1908
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.913074567602623e-05,
+ "loss": 0.5059,
+ "step": 1909
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9129640261549324e-05,
+ "loss": 0.509,
+ "step": 1910
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9128534176629613e-05,
+ "loss": 0.5031,
+ "step": 1911
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9127427421348316e-05,
+ "loss": 0.5084,
+ "step": 1912
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9126319995786717e-05,
+ "loss": 0.5322,
+ "step": 1913
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.912521190002614e-05,
+ "loss": 0.5027,
+ "step": 1914
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9124103134147945e-05,
+ "loss": 0.505,
+ "step": 1915
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9122993698233576e-05,
+ "loss": 0.5083,
+ "step": 1916
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9121883592364486e-05,
+ "loss": 0.5209,
+ "step": 1917
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9120772816622213e-05,
+ "loss": 0.509,
+ "step": 1918
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9119661371088318e-05,
+ "loss": 0.5019,
+ "step": 1919
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9118549255844425e-05,
+ "loss": 0.4998,
+ "step": 1920
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91174364709722e-05,
+ "loss": 0.4973,
+ "step": 1921
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9116323016553363e-05,
+ "loss": 0.5233,
+ "step": 1922
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.911520889266968e-05,
+ "loss": 0.492,
+ "step": 1923
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.911409409940297e-05,
+ "loss": 0.5242,
+ "step": 1924
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91129786368351e-05,
+ "loss": 0.5041,
+ "step": 1925
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.911186250504798e-05,
+ "loss": 0.5142,
+ "step": 1926
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9110745704123577e-05,
+ "loss": 0.5063,
+ "step": 1927
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9109628234143905e-05,
+ "loss": 0.497,
+ "step": 1928
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9108510095191025e-05,
+ "loss": 0.4973,
+ "step": 1929
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.910739128734705e-05,
+ "loss": 0.4926,
+ "step": 1930
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9106271810694137e-05,
+ "loss": 0.5205,
+ "step": 1931
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9105151665314497e-05,
+ "loss": 0.4997,
+ "step": 1932
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9104030851290393e-05,
+ "loss": 0.5069,
+ "step": 1933
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.910290936870413e-05,
+ "loss": 0.5012,
+ "step": 1934
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.910178721763806e-05,
+ "loss": 0.5198,
+ "step": 1935
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.91006643981746e-05,
+ "loss": 0.5206,
+ "step": 1936
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9099540910396194e-05,
+ "loss": 0.4984,
+ "step": 1937
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9098416754385355e-05,
+ "loss": 0.5317,
+ "step": 1938
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909729193022463e-05,
+ "loss": 0.4949,
+ "step": 1939
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9096166437996626e-05,
+ "loss": 0.4801,
+ "step": 1940
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9095040277783993e-05,
+ "loss": 0.5191,
+ "step": 1941
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909391344966943e-05,
+ "loss": 0.5103,
+ "step": 1942
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909278595373569e-05,
+ "loss": 0.4988,
+ "step": 1943
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9091657790065565e-05,
+ "loss": 0.49,
+ "step": 1944
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.909052895874191e-05,
+ "loss": 0.528,
+ "step": 1945
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9089399459847615e-05,
+ "loss": 0.4989,
+ "step": 1946
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9088269293465634e-05,
+ "loss": 0.4941,
+ "step": 1947
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9087138459678956e-05,
+ "loss": 0.5119,
+ "step": 1948
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.908600695857062e-05,
+ "loss": 0.5093,
+ "step": 1949
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9084874790223735e-05,
+ "loss": 0.5122,
+ "step": 1950
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9083741954721423e-05,
+ "loss": 0.4985,
+ "step": 1951
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.908260845214689e-05,
+ "loss": 0.5291,
+ "step": 1952
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9081474282583367e-05,
+ "loss": 0.5037,
+ "step": 1953
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9080339446114148e-05,
+ "loss": 0.4901,
+ "step": 1954
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.907920394282256e-05,
+ "loss": 0.4888,
+ "step": 1955
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9078067772792006e-05,
+ "loss": 0.4985,
+ "step": 1956
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.907693093610591e-05,
+ "loss": 0.5106,
+ "step": 1957
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9075793432847763e-05,
+ "loss": 0.5031,
+ "step": 1958
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.907465526310109e-05,
+ "loss": 0.5117,
+ "step": 1959
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9073516426949485e-05,
+ "loss": 0.5219,
+ "step": 1960
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9072376924476568e-05,
+ "loss": 0.5064,
+ "step": 1961
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9071236755766028e-05,
+ "loss": 0.5332,
+ "step": 1962
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9070095920901588e-05,
+ "loss": 0.5191,
+ "step": 1963
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.906895441996703e-05,
+ "loss": 0.5143,
+ "step": 1964
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.906781225304618e-05,
+ "loss": 0.491,
+ "step": 1965
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9066669420222915e-05,
+ "loss": 0.5089,
+ "step": 1966
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9065525921581158e-05,
+ "loss": 0.5046,
+ "step": 1967
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9064381757204884e-05,
+ "loss": 0.501,
+ "step": 1968
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9063236927178116e-05,
+ "loss": 0.5061,
+ "step": 1969
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9062091431584924e-05,
+ "loss": 0.5049,
+ "step": 1970
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.9060945270509427e-05,
+ "loss": 0.4905,
+ "step": 1971
+ },
+ {
+ "epoch": 0.16,
+ "learning_rate": 1.90597984440358e-05,
+ "loss": 0.4926,
+ "step": 1972
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9058650952248257e-05,
+ "loss": 0.4932,
+ "step": 1973
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9057502795231066e-05,
+ "loss": 0.5016,
+ "step": 1974
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9056353973068544e-05,
+ "loss": 0.4863,
+ "step": 1975
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.905520448584505e-05,
+ "loss": 0.5144,
+ "step": 1976
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9054054333645006e-05,
+ "loss": 0.4898,
+ "step": 1977
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.905290351655287e-05,
+ "loss": 0.4975,
+ "step": 1978
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9051752034653153e-05,
+ "loss": 0.526,
+ "step": 1979
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9050599888030413e-05,
+ "loss": 0.5172,
+ "step": 1980
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9049447076769265e-05,
+ "loss": 0.4884,
+ "step": 1981
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904829360095436e-05,
+ "loss": 0.5012,
+ "step": 1982
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904713946067041e-05,
+ "loss": 0.5017,
+ "step": 1983
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904598465600217e-05,
+ "loss": 0.5158,
+ "step": 1984
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904482918703444e-05,
+ "loss": 0.5017,
+ "step": 1985
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9043673053852073e-05,
+ "loss": 0.496,
+ "step": 1986
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9042516256539974e-05,
+ "loss": 0.5146,
+ "step": 1987
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.904135879518309e-05,
+ "loss": 0.497,
+ "step": 1988
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9040200669866426e-05,
+ "loss": 0.5092,
+ "step": 1989
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903904188067502e-05,
+ "loss": 0.4902,
+ "step": 1990
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903788242769398e-05,
+ "loss": 0.5079,
+ "step": 1991
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9036722311008442e-05,
+ "loss": 0.5132,
+ "step": 1992
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9035561530703605e-05,
+ "loss": 0.5149,
+ "step": 1993
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903440008686471e-05,
+ "loss": 0.4911,
+ "step": 1994
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9033237979577053e-05,
+ "loss": 0.5114,
+ "step": 1995
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9032075208925967e-05,
+ "loss": 0.5084,
+ "step": 1996
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.903091177499685e-05,
+ "loss": 0.4958,
+ "step": 1997
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9029747677875132e-05,
+ "loss": 0.5,
+ "step": 1998
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.90285829176463e-05,
+ "loss": 0.5156,
+ "step": 1999
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9027417494395896e-05,
+ "loss": 0.501,
+ "step": 2000
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9026251408209494e-05,
+ "loss": 0.4945,
+ "step": 2001
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9025084659172733e-05,
+ "loss": 0.4951,
+ "step": 2002
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9023917247371292e-05,
+ "loss": 0.4994,
+ "step": 2003
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9022749172890904e-05,
+ "loss": 0.5328,
+ "step": 2004
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9021580435817343e-05,
+ "loss": 0.5034,
+ "step": 2005
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.902041103623644e-05,
+ "loss": 0.5178,
+ "step": 2006
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.901924097423407e-05,
+ "loss": 0.4987,
+ "step": 2007
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.901807024989615e-05,
+ "loss": 0.4948,
+ "step": 2008
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9016898863308667e-05,
+ "loss": 0.4785,
+ "step": 2009
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9015726814557632e-05,
+ "loss": 0.496,
+ "step": 2010
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9014554103729125e-05,
+ "loss": 0.5314,
+ "step": 2011
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9013380730909255e-05,
+ "loss": 0.503,
+ "step": 2012
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.901220669618419e-05,
+ "loss": 0.5094,
+ "step": 2013
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9011031999640152e-05,
+ "loss": 0.5112,
+ "step": 2014
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9009856641363406e-05,
+ "loss": 0.5092,
+ "step": 2015
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9008680621440262e-05,
+ "loss": 0.5008,
+ "step": 2016
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9007503939957085e-05,
+ "loss": 0.503,
+ "step": 2017
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.900632659700028e-05,
+ "loss": 0.5023,
+ "step": 2018
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9005148592656312e-05,
+ "loss": 0.4859,
+ "step": 2019
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9003969927011683e-05,
+ "loss": 0.4745,
+ "step": 2020
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.900279060015296e-05,
+ "loss": 0.5014,
+ "step": 2021
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9001610612166735e-05,
+ "loss": 0.4822,
+ "step": 2022
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.9000429963139668e-05,
+ "loss": 0.4995,
+ "step": 2023
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8999248653158463e-05,
+ "loss": 0.5026,
+ "step": 2024
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8998066682309864e-05,
+ "loss": 0.5068,
+ "step": 2025
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8996884050680675e-05,
+ "loss": 0.5157,
+ "step": 2026
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8995700758357744e-05,
+ "loss": 0.4847,
+ "step": 2027
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.899451680542796e-05,
+ "loss": 0.4887,
+ "step": 2028
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8993332191978277e-05,
+ "loss": 0.5107,
+ "step": 2029
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8992146918095684e-05,
+ "loss": 0.5014,
+ "step": 2030
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8990960983867222e-05,
+ "loss": 0.5074,
+ "step": 2031
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.898977438937998e-05,
+ "loss": 0.5281,
+ "step": 2032
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8988587134721103e-05,
+ "loss": 0.4978,
+ "step": 2033
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8987399219977768e-05,
+ "loss": 0.5055,
+ "step": 2034
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8986210645237216e-05,
+ "loss": 0.5146,
+ "step": 2035
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8985021410586732e-05,
+ "loss": 0.5041,
+ "step": 2036
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8983831516113645e-05,
+ "loss": 0.5209,
+ "step": 2037
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.898264096190534e-05,
+ "loss": 0.4876,
+ "step": 2038
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8981449748049248e-05,
+ "loss": 0.5127,
+ "step": 2039
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8980257874632836e-05,
+ "loss": 0.5006,
+ "step": 2040
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8979065341743642e-05,
+ "loss": 0.4796,
+ "step": 2041
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8977872149469236e-05,
+ "loss": 0.4946,
+ "step": 2042
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.897667829789724e-05,
+ "loss": 0.5015,
+ "step": 2043
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8975483787115326e-05,
+ "loss": 0.4806,
+ "step": 2044
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8974288617211217e-05,
+ "loss": 0.5259,
+ "step": 2045
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8973092788272677e-05,
+ "loss": 0.5037,
+ "step": 2046
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8971896300387525e-05,
+ "loss": 0.506,
+ "step": 2047
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8970699153643623e-05,
+ "loss": 0.5138,
+ "step": 2048
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.896950134812889e-05,
+ "loss": 0.5103,
+ "step": 2049
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8968302883931283e-05,
+ "loss": 0.4973,
+ "step": 2050
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8967103761138817e-05,
+ "loss": 0.524,
+ "step": 2051
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8965903979839547e-05,
+ "loss": 0.5037,
+ "step": 2052
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8964703540121577e-05,
+ "loss": 0.4964,
+ "step": 2053
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8963502442073073e-05,
+ "loss": 0.499,
+ "step": 2054
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8962300685782224e-05,
+ "loss": 0.507,
+ "step": 2055
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8961098271337296e-05,
+ "loss": 0.5196,
+ "step": 2056
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8959895198826582e-05,
+ "loss": 0.489,
+ "step": 2057
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.895869146833843e-05,
+ "loss": 0.5034,
+ "step": 2058
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8957487079961235e-05,
+ "loss": 0.5135,
+ "step": 2059
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.895628203378345e-05,
+ "loss": 0.4917,
+ "step": 2060
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8955076329893565e-05,
+ "loss": 0.503,
+ "step": 2061
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8953869968380117e-05,
+ "loss": 0.53,
+ "step": 2062
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8952662949331707e-05,
+ "loss": 0.4998,
+ "step": 2063
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8951455272836963e-05,
+ "loss": 0.4908,
+ "step": 2064
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8950246938984573e-05,
+ "loss": 0.5131,
+ "step": 2065
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.894903794786328e-05,
+ "loss": 0.5325,
+ "step": 2066
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.894782829956186e-05,
+ "loss": 0.5071,
+ "step": 2067
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8946617994169146e-05,
+ "loss": 0.5157,
+ "step": 2068
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8945407031774018e-05,
+ "loss": 0.4963,
+ "step": 2069
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8944195412465404e-05,
+ "loss": 0.5301,
+ "step": 2070
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8942983136332282e-05,
+ "loss": 0.5193,
+ "step": 2071
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8941770203463674e-05,
+ "loss": 0.4954,
+ "step": 2072
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8940556613948656e-05,
+ "loss": 0.5124,
+ "step": 2073
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8939342367876345e-05,
+ "loss": 0.51,
+ "step": 2074
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.893812746533591e-05,
+ "loss": 0.4831,
+ "step": 2075
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8936911906416572e-05,
+ "loss": 0.4994,
+ "step": 2076
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8935695691207598e-05,
+ "loss": 0.5263,
+ "step": 2077
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8934478819798296e-05,
+ "loss": 0.4893,
+ "step": 2078
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8933261292278033e-05,
+ "loss": 0.5132,
+ "step": 2079
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8932043108736217e-05,
+ "loss": 0.5076,
+ "step": 2080
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.89308242692623e-05,
+ "loss": 0.527,
+ "step": 2081
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.89296047739458e-05,
+ "loss": 0.5058,
+ "step": 2082
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.892838462287627e-05,
+ "loss": 0.5095,
+ "step": 2083
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8927163816143302e-05,
+ "loss": 0.4916,
+ "step": 2084
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8925942353836558e-05,
+ "loss": 0.4806,
+ "step": 2085
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.892472023604573e-05,
+ "loss": 0.5076,
+ "step": 2086
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8923497462860572e-05,
+ "loss": 0.5209,
+ "step": 2087
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8922274034370875e-05,
+ "loss": 0.4888,
+ "step": 2088
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.8921049950666484e-05,
+ "loss": 0.5002,
+ "step": 2089
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.891982521183729e-05,
+ "loss": 0.5068,
+ "step": 2090
+ },
+ {
+ "epoch": 0.17,
+ "learning_rate": 1.891859981797323e-05,
+ "loss": 0.4904,
+ "step": 2091
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.89173737691643e-05,
+ "loss": 0.5147,
+ "step": 2092
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8916147065500524e-05,
+ "loss": 0.489,
+ "step": 2093
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8914919707071997e-05,
+ "loss": 0.5265,
+ "step": 2094
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8913691693968846e-05,
+ "loss": 0.4928,
+ "step": 2095
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.891246302628125e-05,
+ "loss": 0.5037,
+ "step": 2096
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.891123370409944e-05,
+ "loss": 0.5027,
+ "step": 2097
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8910003727513697e-05,
+ "loss": 0.496,
+ "step": 2098
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8908773096614333e-05,
+ "loss": 0.4993,
+ "step": 2099
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8907541811491726e-05,
+ "loss": 0.4809,
+ "step": 2100
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.89063098722363e-05,
+ "loss": 0.4981,
+ "step": 2101
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8905077278938524e-05,
+ "loss": 0.5007,
+ "step": 2102
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.890384403168891e-05,
+ "loss": 0.5164,
+ "step": 2103
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.890261013057802e-05,
+ "loss": 0.5046,
+ "step": 2104
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8901375575696476e-05,
+ "loss": 0.5137,
+ "step": 2105
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.890014036713493e-05,
+ "loss": 0.5103,
+ "step": 2106
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8898904504984096e-05,
+ "loss": 0.5071,
+ "step": 2107
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8897667989334726e-05,
+ "loss": 0.5271,
+ "step": 2108
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889643082027763e-05,
+ "loss": 0.5044,
+ "step": 2109
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8895192997903657e-05,
+ "loss": 0.4989,
+ "step": 2110
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8893954522303707e-05,
+ "loss": 0.5072,
+ "step": 2111
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889271539356873e-05,
+ "loss": 0.4782,
+ "step": 2112
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889147561178972e-05,
+ "loss": 0.4853,
+ "step": 2113
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.889023517705773e-05,
+ "loss": 0.5108,
+ "step": 2114
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888899408946384e-05,
+ "loss": 0.5195,
+ "step": 2115
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.88877523490992e-05,
+ "loss": 0.4972,
+ "step": 2116
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888650995605499e-05,
+ "loss": 0.4881,
+ "step": 2117
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8885266910422454e-05,
+ "loss": 0.4766,
+ "step": 2118
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888402321229287e-05,
+ "loss": 0.4896,
+ "step": 2119
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8882778861757573e-05,
+ "loss": 0.5269,
+ "step": 2120
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8881533858907945e-05,
+ "loss": 0.5108,
+ "step": 2121
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.888028820383541e-05,
+ "loss": 0.5037,
+ "step": 2122
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8879041896631448e-05,
+ "loss": 0.4973,
+ "step": 2123
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8877794937387576e-05,
+ "loss": 0.5348,
+ "step": 2124
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8876547326195373e-05,
+ "loss": 0.5247,
+ "step": 2125
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.887529906314645e-05,
+ "loss": 0.5148,
+ "step": 2126
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8874050148332484e-05,
+ "loss": 0.5,
+ "step": 2127
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.887280058184518e-05,
+ "loss": 0.4996,
+ "step": 2128
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8871550363776308e-05,
+ "loss": 0.5084,
+ "step": 2129
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8870299494217675e-05,
+ "loss": 0.5191,
+ "step": 2130
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8869047973261148e-05,
+ "loss": 0.5196,
+ "step": 2131
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8867795800998623e-05,
+ "loss": 0.5111,
+ "step": 2132
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8866542977522057e-05,
+ "loss": 0.4926,
+ "step": 2133
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8865289502923455e-05,
+ "loss": 0.5095,
+ "step": 2134
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8864035377294865e-05,
+ "loss": 0.5105,
+ "step": 2135
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8862780600728384e-05,
+ "loss": 0.507,
+ "step": 2136
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.886152517331616e-05,
+ "loss": 0.486,
+ "step": 2137
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8860269095150387e-05,
+ "loss": 0.5058,
+ "step": 2138
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.88590123663233e-05,
+ "loss": 0.4886,
+ "step": 2139
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8857754986927196e-05,
+ "loss": 0.5001,
+ "step": 2140
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8856496957054406e-05,
+ "loss": 0.5071,
+ "step": 2141
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8855238276797315e-05,
+ "loss": 0.5145,
+ "step": 2142
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.885397894624836e-05,
+ "loss": 0.5025,
+ "step": 2143
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8852718965500018e-05,
+ "loss": 0.4977,
+ "step": 2144
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8851458334644814e-05,
+ "loss": 0.4879,
+ "step": 2145
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8850197053775326e-05,
+ "loss": 0.499,
+ "step": 2146
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8848935122984177e-05,
+ "loss": 0.4959,
+ "step": 2147
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884767254236404e-05,
+ "loss": 0.4981,
+ "step": 2148
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884640931200763e-05,
+ "loss": 0.5005,
+ "step": 2149
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8845145432007715e-05,
+ "loss": 0.4988,
+ "step": 2150
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884388090245711e-05,
+ "loss": 0.4929,
+ "step": 2151
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8842615723448678e-05,
+ "loss": 0.5127,
+ "step": 2152
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.884134989507532e-05,
+ "loss": 0.5139,
+ "step": 2153
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8840083417430003e-05,
+ "loss": 0.4953,
+ "step": 2154
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8838816290605732e-05,
+ "loss": 0.5164,
+ "step": 2155
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883754851469555e-05,
+ "loss": 0.5008,
+ "step": 2156
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883628008979257e-05,
+ "loss": 0.4822,
+ "step": 2157
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8835011015989927e-05,
+ "loss": 0.5138,
+ "step": 2158
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8833741293380826e-05,
+ "loss": 0.5049,
+ "step": 2159
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883247092205851e-05,
+ "loss": 0.5085,
+ "step": 2160
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.883119990211626e-05,
+ "loss": 0.4884,
+ "step": 2161
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8829928233647422e-05,
+ "loss": 0.5028,
+ "step": 2162
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8828655916745383e-05,
+ "loss": 0.5221,
+ "step": 2163
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8827382951503575e-05,
+ "loss": 0.5228,
+ "step": 2164
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8826109338015478e-05,
+ "loss": 0.5035,
+ "step": 2165
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8824835076374622e-05,
+ "loss": 0.4917,
+ "step": 2166
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.882356016667458e-05,
+ "loss": 0.5087,
+ "step": 2167
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8822284609008985e-05,
+ "loss": 0.4921,
+ "step": 2168
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8821008403471497e-05,
+ "loss": 0.5027,
+ "step": 2169
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8819731550155845e-05,
+ "loss": 0.5117,
+ "step": 2170
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8818454049155792e-05,
+ "loss": 0.4992,
+ "step": 2171
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.881717590056515e-05,
+ "loss": 0.4923,
+ "step": 2172
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8815897104477786e-05,
+ "loss": 0.4898,
+ "step": 2173
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8814617660987603e-05,
+ "loss": 0.523,
+ "step": 2174
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.881333757018857e-05,
+ "loss": 0.5144,
+ "step": 2175
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8812056832174673e-05,
+ "loss": 0.4931,
+ "step": 2176
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.881077544703998e-05,
+ "loss": 0.4996,
+ "step": 2177
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8809493414878585e-05,
+ "loss": 0.4943,
+ "step": 2178
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.880821073578463e-05,
+ "loss": 0.4915,
+ "step": 2179
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8806927409852323e-05,
+ "loss": 0.5129,
+ "step": 2180
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8805643437175892e-05,
+ "loss": 0.4973,
+ "step": 2181
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8804358817849634e-05,
+ "loss": 0.4808,
+ "step": 2182
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8803073551967884e-05,
+ "loss": 0.5014,
+ "step": 2183
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8801787639625025e-05,
+ "loss": 0.5324,
+ "step": 2184
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8800501080915496e-05,
+ "loss": 0.4964,
+ "step": 2185
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.879921387593377e-05,
+ "loss": 0.5127,
+ "step": 2186
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8797926024774375e-05,
+ "loss": 0.5176,
+ "step": 2187
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8796637527531883e-05,
+ "loss": 0.5158,
+ "step": 2188
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8795348384300922e-05,
+ "loss": 0.5075,
+ "step": 2189
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.879405859517616e-05,
+ "loss": 0.4952,
+ "step": 2190
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8792768160252308e-05,
+ "loss": 0.5071,
+ "step": 2191
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8791477079624138e-05,
+ "loss": 0.5143,
+ "step": 2192
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8790185353386453e-05,
+ "loss": 0.4903,
+ "step": 2193
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.878889298163412e-05,
+ "loss": 0.5099,
+ "step": 2194
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8787599964462044e-05,
+ "loss": 0.5002,
+ "step": 2195
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8786306301965175e-05,
+ "loss": 0.4997,
+ "step": 2196
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8785011994238516e-05,
+ "loss": 0.5037,
+ "step": 2197
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8783717041377113e-05,
+ "loss": 0.5111,
+ "step": 2198
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8782421443476072e-05,
+ "loss": 0.4795,
+ "step": 2199
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.878112520063052e-05,
+ "loss": 0.4958,
+ "step": 2200
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8779828312935664e-05,
+ "loss": 0.5096,
+ "step": 2201
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.877853078048673e-05,
+ "loss": 0.5011,
+ "step": 2202
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8777232603379012e-05,
+ "loss": 0.5011,
+ "step": 2203
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8775933781707836e-05,
+ "loss": 0.4967,
+ "step": 2204
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8774634315568583e-05,
+ "loss": 0.5074,
+ "step": 2205
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8773334205056687e-05,
+ "loss": 0.4919,
+ "step": 2206
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8772033450267617e-05,
+ "loss": 0.5044,
+ "step": 2207
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8770732051296895e-05,
+ "loss": 0.5007,
+ "step": 2208
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.876943000824009e-05,
+ "loss": 0.5067,
+ "step": 2209
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8768127321192825e-05,
+ "loss": 0.4923,
+ "step": 2210
+ },
+ {
+ "epoch": 0.18,
+ "learning_rate": 1.8766823990250756e-05,
+ "loss": 0.4937,
+ "step": 2211
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8765520015509597e-05,
+ "loss": 0.5473,
+ "step": 2212
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8764215397065105e-05,
+ "loss": 0.5043,
+ "step": 2213
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8762910135013088e-05,
+ "loss": 0.4941,
+ "step": 2214
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8761604229449402e-05,
+ "loss": 0.5032,
+ "step": 2215
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8760297680469938e-05,
+ "loss": 0.4992,
+ "step": 2216
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875899048817065e-05,
+ "loss": 0.4925,
+ "step": 2217
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8757682652647538e-05,
+ "loss": 0.5178,
+ "step": 2218
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875637417399663e-05,
+ "loss": 0.5141,
+ "step": 2219
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875506505231403e-05,
+ "loss": 0.4848,
+ "step": 2220
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8753755287695866e-05,
+ "loss": 0.4989,
+ "step": 2221
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875244488023832e-05,
+ "loss": 0.4951,
+ "step": 2222
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.875113383003763e-05,
+ "loss": 0.4867,
+ "step": 2223
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8749822137190065e-05,
+ "loss": 0.4955,
+ "step": 2224
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8748509801791962e-05,
+ "loss": 0.514,
+ "step": 2225
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.874719682393968e-05,
+ "loss": 0.4934,
+ "step": 2226
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8745883203729648e-05,
+ "loss": 0.504,
+ "step": 2227
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8744568941258335e-05,
+ "loss": 0.5041,
+ "step": 2228
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8743254036622243e-05,
+ "loss": 0.4908,
+ "step": 2229
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.874193848991795e-05,
+ "loss": 0.5062,
+ "step": 2230
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8740622301242045e-05,
+ "loss": 0.5084,
+ "step": 2231
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8739305470691197e-05,
+ "loss": 0.4935,
+ "step": 2232
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8737987998362106e-05,
+ "loss": 0.4952,
+ "step": 2233
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8736669884351523e-05,
+ "loss": 0.5139,
+ "step": 2234
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8735351128756238e-05,
+ "loss": 0.4954,
+ "step": 2235
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8734031731673096e-05,
+ "loss": 0.5215,
+ "step": 2236
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8732711693199e-05,
+ "loss": 0.5039,
+ "step": 2237
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.873139101343087e-05,
+ "loss": 0.5171,
+ "step": 2238
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8730069692465708e-05,
+ "loss": 0.4796,
+ "step": 2239
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8728747730400533e-05,
+ "loss": 0.5093,
+ "step": 2240
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.872742512733243e-05,
+ "loss": 0.5096,
+ "step": 2241
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8726101883358534e-05,
+ "loss": 0.4824,
+ "step": 2242
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8724777998576006e-05,
+ "loss": 0.5057,
+ "step": 2243
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.872345347308207e-05,
+ "loss": 0.5089,
+ "step": 2244
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.872212830697399e-05,
+ "loss": 0.501,
+ "step": 2245
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8720802500349095e-05,
+ "loss": 0.5236,
+ "step": 2246
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.871947605330473e-05,
+ "loss": 0.5291,
+ "step": 2247
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8718148965938312e-05,
+ "loss": 0.5228,
+ "step": 2248
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8716821238347296e-05,
+ "loss": 0.4989,
+ "step": 2249
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8715492870629183e-05,
+ "loss": 0.4978,
+ "step": 2250
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8714163862881527e-05,
+ "loss": 0.4955,
+ "step": 2251
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8712834215201918e-05,
+ "loss": 0.5113,
+ "step": 2252
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8711503927688007e-05,
+ "loss": 0.5227,
+ "step": 2253
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.871017300043748e-05,
+ "loss": 0.5006,
+ "step": 2254
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8708841433548076e-05,
+ "loss": 0.5215,
+ "step": 2255
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8707509227117578e-05,
+ "loss": 0.5261,
+ "step": 2256
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8706176381243822e-05,
+ "loss": 0.5057,
+ "step": 2257
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8704842896024685e-05,
+ "loss": 0.4915,
+ "step": 2258
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8703508771558093e-05,
+ "loss": 0.4977,
+ "step": 2259
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8702174007942012e-05,
+ "loss": 0.4921,
+ "step": 2260
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.870083860527447e-05,
+ "loss": 0.4881,
+ "step": 2261
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.869950256365353e-05,
+ "loss": 0.5051,
+ "step": 2262
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8698165883177308e-05,
+ "loss": 0.5007,
+ "step": 2263
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8696828563943962e-05,
+ "loss": 0.5076,
+ "step": 2264
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8695490606051694e-05,
+ "loss": 0.4853,
+ "step": 2265
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8694152009598767e-05,
+ "loss": 0.5068,
+ "step": 2266
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8692812774683477e-05,
+ "loss": 0.4871,
+ "step": 2267
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8691472901404174e-05,
+ "loss": 0.4977,
+ "step": 2268
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8690132389859254e-05,
+ "loss": 0.4994,
+ "step": 2269
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.868879124014715e-05,
+ "loss": 0.4928,
+ "step": 2270
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8687449452366362e-05,
+ "loss": 0.5154,
+ "step": 2271
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8686107026615418e-05,
+ "loss": 0.5094,
+ "step": 2272
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8684763962992903e-05,
+ "loss": 0.4799,
+ "step": 2273
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8683420261597445e-05,
+ "loss": 0.5091,
+ "step": 2274
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8682075922527717e-05,
+ "loss": 0.5067,
+ "step": 2275
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.868073094588245e-05,
+ "loss": 0.5016,
+ "step": 2276
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8679385331760405e-05,
+ "loss": 0.5159,
+ "step": 2277
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8678039080260403e-05,
+ "loss": 0.5221,
+ "step": 2278
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8676692191481303e-05,
+ "loss": 0.4992,
+ "step": 2279
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.867534466552202e-05,
+ "loss": 0.5096,
+ "step": 2280
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8673996502481507e-05,
+ "loss": 0.5064,
+ "step": 2281
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.867264770245877e-05,
+ "loss": 0.4879,
+ "step": 2282
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8671298265552855e-05,
+ "loss": 0.5101,
+ "step": 2283
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8669948191862866e-05,
+ "loss": 0.5155,
+ "step": 2284
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.866859748148794e-05,
+ "loss": 0.5111,
+ "step": 2285
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.866724613452727e-05,
+ "loss": 0.4805,
+ "step": 2286
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8665894151080097e-05,
+ "loss": 0.5088,
+ "step": 2287
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8664541531245698e-05,
+ "loss": 0.5163,
+ "step": 2288
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.866318827512341e-05,
+ "loss": 0.5177,
+ "step": 2289
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8661834382812608e-05,
+ "loss": 0.4867,
+ "step": 2290
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8660479854412713e-05,
+ "loss": 0.5183,
+ "step": 2291
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8659124690023205e-05,
+ "loss": 0.4917,
+ "step": 2292
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.865776888974359e-05,
+ "loss": 0.5098,
+ "step": 2293
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.865641245367344e-05,
+ "loss": 0.4977,
+ "step": 2294
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8655055381912367e-05,
+ "loss": 0.5151,
+ "step": 2295
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8653697674560023e-05,
+ "loss": 0.524,
+ "step": 2296
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8652339331716114e-05,
+ "loss": 0.4991,
+ "step": 2297
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8650980353480395e-05,
+ "loss": 0.5015,
+ "step": 2298
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8649620739952658e-05,
+ "loss": 0.5034,
+ "step": 2299
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8648260491232753e-05,
+ "loss": 0.4985,
+ "step": 2300
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8646899607420567e-05,
+ "loss": 0.4961,
+ "step": 2301
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8645538088616038e-05,
+ "loss": 0.5044,
+ "step": 2302
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8644175934919156e-05,
+ "loss": 0.5092,
+ "step": 2303
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8642813146429943e-05,
+ "loss": 0.5069,
+ "step": 2304
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8641449723248482e-05,
+ "loss": 0.5064,
+ "step": 2305
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8640085665474898e-05,
+ "loss": 0.5085,
+ "step": 2306
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8638720973209353e-05,
+ "loss": 0.5056,
+ "step": 2307
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.863735564655208e-05,
+ "loss": 0.4973,
+ "step": 2308
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8635989685603327e-05,
+ "loss": 0.5089,
+ "step": 2309
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8634623090463413e-05,
+ "loss": 0.4941,
+ "step": 2310
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8633255861232692e-05,
+ "loss": 0.4903,
+ "step": 2311
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.863188799801157e-05,
+ "loss": 0.5029,
+ "step": 2312
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8630519500900495e-05,
+ "loss": 0.4915,
+ "step": 2313
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8629150369999967e-05,
+ "loss": 0.4913,
+ "step": 2314
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8627780605410528e-05,
+ "loss": 0.5075,
+ "step": 2315
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8626410207232762e-05,
+ "loss": 0.4993,
+ "step": 2316
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8625039175567316e-05,
+ "loss": 0.5164,
+ "step": 2317
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8623667510514867e-05,
+ "loss": 0.4919,
+ "step": 2318
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8622295212176142e-05,
+ "loss": 0.5125,
+ "step": 2319
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.862092228065192e-05,
+ "loss": 0.5005,
+ "step": 2320
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.861954871604302e-05,
+ "loss": 0.4824,
+ "step": 2321
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8618174518450317e-05,
+ "loss": 0.4943,
+ "step": 2322
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8616799687974724e-05,
+ "loss": 0.5029,
+ "step": 2323
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.86154242247172e-05,
+ "loss": 0.4923,
+ "step": 2324
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8614048128778755e-05,
+ "loss": 0.5028,
+ "step": 2325
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8612671400260445e-05,
+ "loss": 0.4956,
+ "step": 2326
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.861129403926337e-05,
+ "loss": 0.5067,
+ "step": 2327
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.8609916045888677e-05,
+ "loss": 0.4775,
+ "step": 2328
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.860853742023756e-05,
+ "loss": 0.4859,
+ "step": 2329
+ },
+ {
+ "epoch": 0.19,
+ "learning_rate": 1.860715816241126e-05,
+ "loss": 0.5,
+ "step": 2330
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.860577827251107e-05,
+ "loss": 0.5103,
+ "step": 2331
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8604397750638314e-05,
+ "loss": 0.5085,
+ "step": 2332
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8603016596894375e-05,
+ "loss": 0.4992,
+ "step": 2333
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.860163481138068e-05,
+ "loss": 0.5093,
+ "step": 2334
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8600252394198702e-05,
+ "loss": 0.5172,
+ "step": 2335
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8598869345449957e-05,
+ "loss": 0.4971,
+ "step": 2336
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8597485665236016e-05,
+ "loss": 0.5007,
+ "step": 2337
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8596101353658488e-05,
+ "loss": 0.4957,
+ "step": 2338
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8594716410819027e-05,
+ "loss": 0.4941,
+ "step": 2339
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8593330836819342e-05,
+ "loss": 0.4833,
+ "step": 2340
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8591944631761185e-05,
+ "loss": 0.4959,
+ "step": 2341
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.859055779574635e-05,
+ "loss": 0.5065,
+ "step": 2342
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.858917032887668e-05,
+ "loss": 0.5085,
+ "step": 2343
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8587782231254065e-05,
+ "loss": 0.5195,
+ "step": 2344
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8586393502980442e-05,
+ "loss": 0.5003,
+ "step": 2345
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8585004144157798e-05,
+ "loss": 0.4933,
+ "step": 2346
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8583614154888154e-05,
+ "loss": 0.5186,
+ "step": 2347
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8582223535273587e-05,
+ "loss": 0.4988,
+ "step": 2348
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8580832285416223e-05,
+ "loss": 0.5032,
+ "step": 2349
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8579440405418222e-05,
+ "loss": 0.5109,
+ "step": 2350
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.857804789538181e-05,
+ "loss": 0.503,
+ "step": 2351
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8576654755409233e-05,
+ "loss": 0.5101,
+ "step": 2352
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8575260985602806e-05,
+ "loss": 0.5242,
+ "step": 2353
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8573866586064877e-05,
+ "loss": 0.5165,
+ "step": 2354
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.857247155689785e-05,
+ "loss": 0.5158,
+ "step": 2355
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8571075898204167e-05,
+ "loss": 0.4967,
+ "step": 2356
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.856967961008632e-05,
+ "loss": 0.5094,
+ "step": 2357
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8568282692646844e-05,
+ "loss": 0.4908,
+ "step": 2358
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8566885145988326e-05,
+ "loss": 0.48,
+ "step": 2359
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8565486970213397e-05,
+ "loss": 0.5177,
+ "step": 2360
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8564088165424733e-05,
+ "loss": 0.496,
+ "step": 2361
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8562688731725053e-05,
+ "loss": 0.5195,
+ "step": 2362
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8561288669217125e-05,
+ "loss": 0.4852,
+ "step": 2363
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8559887978003766e-05,
+ "loss": 0.4954,
+ "step": 2364
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8558486658187843e-05,
+ "loss": 0.5074,
+ "step": 2365
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8557084709872253e-05,
+ "loss": 0.4885,
+ "step": 2366
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8555682133159952e-05,
+ "loss": 0.4868,
+ "step": 2367
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8554278928153942e-05,
+ "loss": 0.5194,
+ "step": 2368
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.855287509495727e-05,
+ "loss": 0.4986,
+ "step": 2369
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8551470633673023e-05,
+ "loss": 0.5032,
+ "step": 2370
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.855006554440434e-05,
+ "loss": 0.5006,
+ "step": 2371
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8548659827254408e-05,
+ "loss": 0.5124,
+ "step": 2372
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8547253482326458e-05,
+ "loss": 0.4894,
+ "step": 2373
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8545846509723757e-05,
+ "loss": 0.5089,
+ "step": 2374
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8544438909549636e-05,
+ "loss": 0.4991,
+ "step": 2375
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.854303068190746e-05,
+ "loss": 0.5044,
+ "step": 2376
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.854162182690064e-05,
+ "loss": 0.5011,
+ "step": 2377
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8540212344632646e-05,
+ "loss": 0.4879,
+ "step": 2378
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8538802235206977e-05,
+ "loss": 0.5249,
+ "step": 2379
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8537391498727187e-05,
+ "loss": 0.489,
+ "step": 2380
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8535980135296876e-05,
+ "loss": 0.5214,
+ "step": 2381
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8534568145019687e-05,
+ "loss": 0.5325,
+ "step": 2382
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.853315552799931e-05,
+ "loss": 0.5143,
+ "step": 2383
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8531742284339486e-05,
+ "loss": 0.5069,
+ "step": 2384
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.853032841414399e-05,
+ "loss": 0.4942,
+ "step": 2385
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852891391751666e-05,
+ "loss": 0.4831,
+ "step": 2386
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8527498794561367e-05,
+ "loss": 0.4999,
+ "step": 2387
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8526083045382025e-05,
+ "loss": 0.4998,
+ "step": 2388
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852466667008261e-05,
+ "loss": 0.5075,
+ "step": 2389
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8523249668767135e-05,
+ "loss": 0.5047,
+ "step": 2390
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852183204153965e-05,
+ "loss": 0.5177,
+ "step": 2391
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.852041378850427e-05,
+ "loss": 0.486,
+ "step": 2392
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.851899490976514e-05,
+ "loss": 0.4809,
+ "step": 2393
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.851757540542645e-05,
+ "loss": 0.5098,
+ "step": 2394
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8516155275592457e-05,
+ "loss": 0.4916,
+ "step": 2395
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8514734520367438e-05,
+ "loss": 0.5143,
+ "step": 2396
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8513313139855734e-05,
+ "loss": 0.4984,
+ "step": 2397
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8511891134161718e-05,
+ "loss": 0.4834,
+ "step": 2398
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8510468503389825e-05,
+ "loss": 0.4972,
+ "step": 2399
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8509045247644524e-05,
+ "loss": 0.4988,
+ "step": 2400
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8507621367030326e-05,
+ "loss": 0.5079,
+ "step": 2401
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8506196861651802e-05,
+ "loss": 0.514,
+ "step": 2402
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8504771731613568e-05,
+ "loss": 0.4905,
+ "step": 2403
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8503345977020262e-05,
+ "loss": 0.5006,
+ "step": 2404
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8501919597976602e-05,
+ "loss": 0.4949,
+ "step": 2405
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.850049259458733e-05,
+ "loss": 0.5129,
+ "step": 2406
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8499064966957233e-05,
+ "loss": 0.498,
+ "step": 2407
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8497636715191153e-05,
+ "loss": 0.499,
+ "step": 2408
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8496207839393984e-05,
+ "loss": 0.4932,
+ "step": 2409
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.849477833967065e-05,
+ "loss": 0.5081,
+ "step": 2410
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.849334821612612e-05,
+ "loss": 0.497,
+ "step": 2411
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8491917468865426e-05,
+ "loss": 0.5113,
+ "step": 2412
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8490486097993635e-05,
+ "loss": 0.5037,
+ "step": 2413
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.848905410361586e-05,
+ "loss": 0.4858,
+ "step": 2414
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.848762148583726e-05,
+ "loss": 0.4957,
+ "step": 2415
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8486188244763038e-05,
+ "loss": 0.5217,
+ "step": 2416
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8484754380498452e-05,
+ "loss": 0.496,
+ "step": 2417
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8483319893148794e-05,
+ "loss": 0.4957,
+ "step": 2418
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.848188478281941e-05,
+ "loss": 0.4935,
+ "step": 2419
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8480449049615684e-05,
+ "loss": 0.4964,
+ "step": 2420
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.847901269364305e-05,
+ "loss": 0.4948,
+ "step": 2421
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.847757571500699e-05,
+ "loss": 0.4968,
+ "step": 2422
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8476138113813037e-05,
+ "loss": 0.5153,
+ "step": 2423
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8474699890166753e-05,
+ "loss": 0.513,
+ "step": 2424
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8473261044173756e-05,
+ "loss": 0.5264,
+ "step": 2425
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8471821575939713e-05,
+ "loss": 0.4933,
+ "step": 2426
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8470381485570327e-05,
+ "loss": 0.5192,
+ "step": 2427
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8468940773171357e-05,
+ "loss": 0.4959,
+ "step": 2428
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8467499438848606e-05,
+ "loss": 0.5083,
+ "step": 2429
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.846605748270791e-05,
+ "loss": 0.5058,
+ "step": 2430
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8464614904855168e-05,
+ "loss": 0.5126,
+ "step": 2431
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8463171705396313e-05,
+ "loss": 0.5123,
+ "step": 2432
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.846172788443733e-05,
+ "loss": 0.4949,
+ "step": 2433
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8460283442084246e-05,
+ "loss": 0.497,
+ "step": 2434
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8458838378443134e-05,
+ "loss": 0.5059,
+ "step": 2435
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8457392693620114e-05,
+ "loss": 0.5048,
+ "step": 2436
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8455946387721356e-05,
+ "loss": 0.518,
+ "step": 2437
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.845449946085306e-05,
+ "loss": 0.5013,
+ "step": 2438
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8453051913121494e-05,
+ "loss": 0.4975,
+ "step": 2439
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8451603744632952e-05,
+ "loss": 0.504,
+ "step": 2440
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.845015495549378e-05,
+ "loss": 0.5083,
+ "step": 2441
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.844870554581038e-05,
+ "loss": 0.5114,
+ "step": 2442
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8447255515689185e-05,
+ "loss": 0.4908,
+ "step": 2443
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.844580486523668e-05,
+ "loss": 0.4994,
+ "step": 2444
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8444353594559392e-05,
+ "loss": 0.5013,
+ "step": 2445
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.84429017037639e-05,
+ "loss": 0.5016,
+ "step": 2446
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8441449192956823e-05,
+ "loss": 0.5037,
+ "step": 2447
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8439996062244828e-05,
+ "loss": 0.4919,
+ "step": 2448
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.843854231173463e-05,
+ "loss": 0.4875,
+ "step": 2449
+ },
+ {
+ "epoch": 0.2,
+ "learning_rate": 1.8437087941532982e-05,
+ "loss": 0.4861,
+ "step": 2450
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8435632951746685e-05,
+ "loss": 0.5123,
+ "step": 2451
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8434177342482594e-05,
+ "loss": 0.4923,
+ "step": 2452
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8432721113847596e-05,
+ "loss": 0.5275,
+ "step": 2453
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8431264265948636e-05,
+ "loss": 0.529,
+ "step": 2454
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8429806798892694e-05,
+ "loss": 0.5048,
+ "step": 2455
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8428348712786803e-05,
+ "loss": 0.485,
+ "step": 2456
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.842689000773804e-05,
+ "loss": 0.5057,
+ "step": 2457
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8425430683853527e-05,
+ "loss": 0.5013,
+ "step": 2458
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8423970741240426e-05,
+ "loss": 0.4978,
+ "step": 2459
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.842251018000595e-05,
+ "loss": 0.4971,
+ "step": 2460
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8421049000257362e-05,
+ "loss": 0.5246,
+ "step": 2461
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.841958720210196e-05,
+ "loss": 0.4989,
+ "step": 2462
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8418124785647092e-05,
+ "loss": 0.5098,
+ "step": 2463
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8416661751000156e-05,
+ "loss": 0.5075,
+ "step": 2464
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.841519809826859e-05,
+ "loss": 0.4991,
+ "step": 2465
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8413733827559873e-05,
+ "loss": 0.4971,
+ "step": 2466
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.841226893898154e-05,
+ "loss": 0.5031,
+ "step": 2467
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8410803432641165e-05,
+ "loss": 0.4909,
+ "step": 2468
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840933730864637e-05,
+ "loss": 0.5077,
+ "step": 2469
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840787056710482e-05,
+ "loss": 0.5273,
+ "step": 2470
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8406403208124227e-05,
+ "loss": 0.5063,
+ "step": 2471
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8404935231812348e-05,
+ "loss": 0.5041,
+ "step": 2472
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8403466638276983e-05,
+ "loss": 0.493,
+ "step": 2473
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840199742762598e-05,
+ "loss": 0.4928,
+ "step": 2474
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.840052759996723e-05,
+ "loss": 0.506,
+ "step": 2475
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.839905715540868e-05,
+ "loss": 0.503,
+ "step": 2476
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8397586094058303e-05,
+ "loss": 0.4865,
+ "step": 2477
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.839611441602413e-05,
+ "loss": 0.4936,
+ "step": 2478
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8394642121414238e-05,
+ "loss": 0.501,
+ "step": 2479
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8393169210336747e-05,
+ "loss": 0.4826,
+ "step": 2480
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8391695682899814e-05,
+ "loss": 0.5122,
+ "step": 2481
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.839022153921166e-05,
+ "loss": 0.5038,
+ "step": 2482
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8388746779380532e-05,
+ "loss": 0.4954,
+ "step": 2483
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.838727140351473e-05,
+ "loss": 0.5098,
+ "step": 2484
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.83857954117226e-05,
+ "loss": 0.4984,
+ "step": 2485
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8384318804112533e-05,
+ "loss": 0.5117,
+ "step": 2486
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.838284158079297e-05,
+ "loss": 0.4905,
+ "step": 2487
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8381363741872386e-05,
+ "loss": 0.4969,
+ "step": 2488
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8379885287459315e-05,
+ "loss": 0.5055,
+ "step": 2489
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8378406217662314e-05,
+ "loss": 0.4903,
+ "step": 2490
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8376926532590012e-05,
+ "loss": 0.4854,
+ "step": 2491
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.837544623235107e-05,
+ "loss": 0.5033,
+ "step": 2492
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8373965317054195e-05,
+ "loss": 0.5127,
+ "step": 2493
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8372483786808133e-05,
+ "loss": 0.488,
+ "step": 2494
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8371001641721685e-05,
+ "loss": 0.4882,
+ "step": 2495
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8369518881903698e-05,
+ "loss": 0.5022,
+ "step": 2496
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8368035507463053e-05,
+ "loss": 0.4967,
+ "step": 2497
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8366551518508685e-05,
+ "loss": 0.4857,
+ "step": 2498
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8365066915149573e-05,
+ "loss": 0.4862,
+ "step": 2499
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8363581697494738e-05,
+ "loss": 0.4842,
+ "step": 2500
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8362095865653257e-05,
+ "loss": 0.4985,
+ "step": 2501
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8360609419734227e-05,
+ "loss": 0.5008,
+ "step": 2502
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.835912235984682e-05,
+ "loss": 0.5087,
+ "step": 2503
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8357634686100236e-05,
+ "loss": 0.4947,
+ "step": 2504
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.835614639860372e-05,
+ "loss": 0.4921,
+ "step": 2505
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.835465749746657e-05,
+ "loss": 0.4997,
+ "step": 2506
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8353167982798124e-05,
+ "loss": 0.5113,
+ "step": 2507
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8351677854707763e-05,
+ "loss": 0.4809,
+ "step": 2508
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8350187113304918e-05,
+ "loss": 0.5035,
+ "step": 2509
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8348695758699065e-05,
+ "loss": 0.5228,
+ "step": 2510
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8347203790999716e-05,
+ "loss": 0.5196,
+ "step": 2511
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.834571121031644e-05,
+ "loss": 0.4999,
+ "step": 2512
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8344218016758847e-05,
+ "loss": 0.5013,
+ "step": 2513
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.834272421043659e-05,
+ "loss": 0.5062,
+ "step": 2514
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8341229791459365e-05,
+ "loss": 0.5037,
+ "step": 2515
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833973475993692e-05,
+ "loss": 0.5002,
+ "step": 2516
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8338239115979038e-05,
+ "loss": 0.501,
+ "step": 2517
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833674285969556e-05,
+ "loss": 0.4984,
+ "step": 2518
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833524599119636e-05,
+ "loss": 0.4887,
+ "step": 2519
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8333748510591364e-05,
+ "loss": 0.5059,
+ "step": 2520
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.833225041799054e-05,
+ "loss": 0.5056,
+ "step": 2521
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8330751713503902e-05,
+ "loss": 0.494,
+ "step": 2522
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8329252397241504e-05,
+ "loss": 0.497,
+ "step": 2523
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.832775246931346e-05,
+ "loss": 0.5149,
+ "step": 2524
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.832625192982991e-05,
+ "loss": 0.4997,
+ "step": 2525
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8324750778901047e-05,
+ "loss": 0.5015,
+ "step": 2526
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8323249016637118e-05,
+ "loss": 0.5,
+ "step": 2527
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8321746643148394e-05,
+ "loss": 0.5136,
+ "step": 2528
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8320243658545215e-05,
+ "loss": 0.5003,
+ "step": 2529
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8318740062937944e-05,
+ "loss": 0.482,
+ "step": 2530
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8317235856437006e-05,
+ "loss": 0.476,
+ "step": 2531
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.831573103915286e-05,
+ "loss": 0.4906,
+ "step": 2532
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8314225611196013e-05,
+ "loss": 0.5128,
+ "step": 2533
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8312719572677018e-05,
+ "loss": 0.5126,
+ "step": 2534
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8311212923706473e-05,
+ "loss": 0.5084,
+ "step": 2535
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8309705664395024e-05,
+ "loss": 0.5062,
+ "step": 2536
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.830819779485335e-05,
+ "loss": 0.4906,
+ "step": 2537
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8306689315192187e-05,
+ "loss": 0.5119,
+ "step": 2538
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8305180225522306e-05,
+ "loss": 0.4949,
+ "step": 2539
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.830367052595454e-05,
+ "loss": 0.4931,
+ "step": 2540
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8302160216599745e-05,
+ "loss": 0.5127,
+ "step": 2541
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8300649297568837e-05,
+ "loss": 0.488,
+ "step": 2542
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8299137768972766e-05,
+ "loss": 0.5083,
+ "step": 2543
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829762563092254e-05,
+ "loss": 0.4948,
+ "step": 2544
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8296112883529197e-05,
+ "loss": 0.5074,
+ "step": 2545
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829459952690383e-05,
+ "loss": 0.5196,
+ "step": 2546
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8293085561157578e-05,
+ "loss": 0.4939,
+ "step": 2547
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829157098640161e-05,
+ "loss": 0.4937,
+ "step": 2548
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.829005580274716e-05,
+ "loss": 0.4949,
+ "step": 2549
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.828854001030549e-05,
+ "loss": 0.4918,
+ "step": 2550
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.828702360918792e-05,
+ "loss": 0.5065,
+ "step": 2551
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8285506599505803e-05,
+ "loss": 0.4884,
+ "step": 2552
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8283988981370543e-05,
+ "loss": 0.5058,
+ "step": 2553
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8282470754893585e-05,
+ "loss": 0.5247,
+ "step": 2554
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.828095192018643e-05,
+ "loss": 0.5005,
+ "step": 2555
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.82794324773606e-05,
+ "loss": 0.4886,
+ "step": 2556
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8277912426527696e-05,
+ "loss": 0.5016,
+ "step": 2557
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8276391767799326e-05,
+ "loss": 0.4991,
+ "step": 2558
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8274870501287174e-05,
+ "loss": 0.5007,
+ "step": 2559
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8273348627102948e-05,
+ "loss": 0.4941,
+ "step": 2560
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.827182614535841e-05,
+ "loss": 0.4995,
+ "step": 2561
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8270303056165364e-05,
+ "loss": 0.4974,
+ "step": 2562
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.826877935963566e-05,
+ "loss": 0.5034,
+ "step": 2563
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8267255055881197e-05,
+ "loss": 0.4848,
+ "step": 2564
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8265730145013903e-05,
+ "loss": 0.5114,
+ "step": 2565
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.826420462714577e-05,
+ "loss": 0.5084,
+ "step": 2566
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8262678502388824e-05,
+ "loss": 0.5176,
+ "step": 2567
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8261151770855134e-05,
+ "loss": 0.4974,
+ "step": 2568
+ },
+ {
+ "epoch": 0.21,
+ "learning_rate": 1.8259624432656816e-05,
+ "loss": 0.5196,
+ "step": 2569
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.825809648790604e-05,
+ "loss": 0.4914,
+ "step": 2570
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8256567936715e-05,
+ "loss": 0.4887,
+ "step": 2571
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8255038779195957e-05,
+ "loss": 0.513,
+ "step": 2572
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.82535090154612e-05,
+ "loss": 0.4801,
+ "step": 2573
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.825197864562307e-05,
+ "loss": 0.4912,
+ "step": 2574
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.825044766979395e-05,
+ "loss": 0.5092,
+ "step": 2575
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8248916088086268e-05,
+ "loss": 0.5197,
+ "step": 2576
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.82473839006125e-05,
+ "loss": 0.4776,
+ "step": 2577
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.824585110748516e-05,
+ "loss": 0.4789,
+ "step": 2578
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8244317708816815e-05,
+ "loss": 0.5079,
+ "step": 2579
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8242783704720066e-05,
+ "loss": 0.5039,
+ "step": 2580
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8241249095307566e-05,
+ "loss": 0.4892,
+ "step": 2581
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823971388069201e-05,
+ "loss": 0.4991,
+ "step": 2582
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823817806098614e-05,
+ "loss": 0.4969,
+ "step": 2583
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8236641636302737e-05,
+ "loss": 0.4987,
+ "step": 2584
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823510460675463e-05,
+ "loss": 0.49,
+ "step": 2585
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8233566972454696e-05,
+ "loss": 0.4967,
+ "step": 2586
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.823202873351585e-05,
+ "loss": 0.4846,
+ "step": 2587
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8230489890051048e-05,
+ "loss": 0.5066,
+ "step": 2588
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8228950442173304e-05,
+ "loss": 0.513,
+ "step": 2589
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8227410389995668e-05,
+ "loss": 0.4966,
+ "step": 2590
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8225869733631234e-05,
+ "loss": 0.5062,
+ "step": 2591
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8224328473193137e-05,
+ "loss": 0.488,
+ "step": 2592
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.822278660879457e-05,
+ "loss": 0.4971,
+ "step": 2593
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.822124414054875e-05,
+ "loss": 0.5029,
+ "step": 2594
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8219701068568957e-05,
+ "loss": 0.4926,
+ "step": 2595
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8218157392968505e-05,
+ "loss": 0.4797,
+ "step": 2596
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.821661311386076e-05,
+ "loss": 0.5108,
+ "step": 2597
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8215068231359118e-05,
+ "loss": 0.5117,
+ "step": 2598
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.821352274557704e-05,
+ "loss": 0.4963,
+ "step": 2599
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8211976656628007e-05,
+ "loss": 0.5159,
+ "step": 2600
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.821042996462557e-05,
+ "loss": 0.4822,
+ "step": 2601
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8208882669683305e-05,
+ "loss": 0.4933,
+ "step": 2602
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.820733477191484e-05,
+ "loss": 0.4897,
+ "step": 2603
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8205786271433845e-05,
+ "loss": 0.4959,
+ "step": 2604
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8204237168354038e-05,
+ "loss": 0.5009,
+ "step": 2605
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8202687462789175e-05,
+ "loss": 0.4853,
+ "step": 2606
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8201137154853065e-05,
+ "loss": 0.523,
+ "step": 2607
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8199586244659554e-05,
+ "loss": 0.512,
+ "step": 2608
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8198034732322532e-05,
+ "loss": 0.4876,
+ "step": 2609
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8196482617955938e-05,
+ "loss": 0.5184,
+ "step": 2610
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8194929901673752e-05,
+ "loss": 0.536,
+ "step": 2611
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.819337658359e-05,
+ "loss": 0.4823,
+ "step": 2612
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.819182266381875e-05,
+ "loss": 0.504,
+ "step": 2613
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8190268142474113e-05,
+ "loss": 0.5123,
+ "step": 2614
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8188713019670253e-05,
+ "loss": 0.4874,
+ "step": 2615
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8187157295521366e-05,
+ "loss": 0.4956,
+ "step": 2616
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8185600970141703e-05,
+ "loss": 0.5148,
+ "step": 2617
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.818404404364555e-05,
+ "loss": 0.4907,
+ "step": 2618
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.818248651614724e-05,
+ "loss": 0.4943,
+ "step": 2619
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8180928387761157e-05,
+ "loss": 0.5055,
+ "step": 2620
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.817936965860172e-05,
+ "loss": 0.4992,
+ "step": 2621
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8177810328783395e-05,
+ "loss": 0.5033,
+ "step": 2622
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8176250398420694e-05,
+ "loss": 0.4799,
+ "step": 2623
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.817468986762817e-05,
+ "loss": 0.4893,
+ "step": 2624
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8173128736520427e-05,
+ "loss": 0.5092,
+ "step": 2625
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.81715670052121e-05,
+ "loss": 0.4862,
+ "step": 2626
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8170004673817882e-05,
+ "loss": 0.5004,
+ "step": 2627
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8168441742452502e-05,
+ "loss": 0.4948,
+ "step": 2628
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8166878211230736e-05,
+ "loss": 0.5071,
+ "step": 2629
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8165314080267406e-05,
+ "loss": 0.5127,
+ "step": 2630
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8163749349677363e-05,
+ "loss": 0.5117,
+ "step": 2631
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8162184019575534e-05,
+ "loss": 0.5178,
+ "step": 2632
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.816061809007685e-05,
+ "loss": 0.5083,
+ "step": 2633
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8159051561296323e-05,
+ "loss": 0.5078,
+ "step": 2634
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.815748443334898e-05,
+ "loss": 0.5072,
+ "step": 2635
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8155916706349913e-05,
+ "loss": 0.4987,
+ "step": 2636
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8154348380414245e-05,
+ "loss": 0.5096,
+ "step": 2637
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.815277945565715e-05,
+ "loss": 0.5288,
+ "step": 2638
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8151209932193844e-05,
+ "loss": 0.4849,
+ "step": 2639
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.814963981013958e-05,
+ "loss": 0.4918,
+ "step": 2640
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8148069089609667e-05,
+ "loss": 0.4967,
+ "step": 2641
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8146497770719448e-05,
+ "loss": 0.5129,
+ "step": 2642
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8144925853584315e-05,
+ "loss": 0.4814,
+ "step": 2643
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8143353338319712e-05,
+ "loss": 0.5177,
+ "step": 2644
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8141780225041104e-05,
+ "loss": 0.5168,
+ "step": 2645
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8140206513864026e-05,
+ "loss": 0.5167,
+ "step": 2646
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8138632204904033e-05,
+ "loss": 0.4849,
+ "step": 2647
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8137057298276745e-05,
+ "loss": 0.4971,
+ "step": 2648
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8135481794097814e-05,
+ "loss": 0.5189,
+ "step": 2649
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.813390569248294e-05,
+ "loss": 0.4916,
+ "step": 2650
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.813232899354786e-05,
+ "loss": 0.5015,
+ "step": 2651
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8130751697408364e-05,
+ "loss": 0.499,
+ "step": 2652
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8129173804180285e-05,
+ "loss": 0.4776,
+ "step": 2653
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.812759531397949e-05,
+ "loss": 0.4923,
+ "step": 2654
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8126016226921898e-05,
+ "loss": 0.5178,
+ "step": 2655
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.812443654312348e-05,
+ "loss": 0.4954,
+ "step": 2656
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8122856262700227e-05,
+ "loss": 0.5286,
+ "step": 2657
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.81212753857682e-05,
+ "loss": 0.5092,
+ "step": 2658
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8119693912443487e-05,
+ "loss": 0.5141,
+ "step": 2659
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8118111842842227e-05,
+ "loss": 0.5079,
+ "step": 2660
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8116529177080594e-05,
+ "loss": 0.4833,
+ "step": 2661
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8114945915274826e-05,
+ "loss": 0.5262,
+ "step": 2662
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8113362057541175e-05,
+ "loss": 0.5065,
+ "step": 2663
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.811177760399596e-05,
+ "loss": 0.492,
+ "step": 2664
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.811019255475554e-05,
+ "loss": 0.4939,
+ "step": 2665
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8108606909936312e-05,
+ "loss": 0.4864,
+ "step": 2666
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.810702066965472e-05,
+ "loss": 0.4914,
+ "step": 2667
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.810543383402725e-05,
+ "loss": 0.5023,
+ "step": 2668
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8103846403170427e-05,
+ "loss": 0.4967,
+ "step": 2669
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8102258377200837e-05,
+ "loss": 0.4998,
+ "step": 2670
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8100669756235087e-05,
+ "loss": 0.5019,
+ "step": 2671
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8099080540389845e-05,
+ "loss": 0.5198,
+ "step": 2672
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8097490729781815e-05,
+ "loss": 0.5041,
+ "step": 2673
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8095900324527745e-05,
+ "loss": 0.4983,
+ "step": 2674
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8094309324744428e-05,
+ "loss": 0.4895,
+ "step": 2675
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8092717730548702e-05,
+ "loss": 0.5035,
+ "step": 2676
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8091125542057442e-05,
+ "loss": 0.51,
+ "step": 2677
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8089532759387586e-05,
+ "loss": 0.4928,
+ "step": 2678
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8087939382656082e-05,
+ "loss": 0.4932,
+ "step": 2679
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8086345411979952e-05,
+ "loss": 0.5225,
+ "step": 2680
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.808475084747625e-05,
+ "loss": 0.4933,
+ "step": 2681
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.808315568926207e-05,
+ "loss": 0.5014,
+ "step": 2682
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.808155993745456e-05,
+ "loss": 0.4988,
+ "step": 2683
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8079963592170903e-05,
+ "loss": 0.4932,
+ "step": 2684
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.807836665352832e-05,
+ "loss": 0.4945,
+ "step": 2685
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8076769121644097e-05,
+ "loss": 0.4966,
+ "step": 2686
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8075170996635538e-05,
+ "loss": 0.516,
+ "step": 2687
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8073572278620015e-05,
+ "loss": 0.5308,
+ "step": 2688
+ },
+ {
+ "epoch": 0.22,
+ "learning_rate": 1.8071972967714918e-05,
+ "loss": 0.4975,
+ "step": 2689
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8070373064037702e-05,
+ "loss": 0.5108,
+ "step": 2690
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8068772567705858e-05,
+ "loss": 0.4995,
+ "step": 2691
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8067171478836916e-05,
+ "loss": 0.4989,
+ "step": 2692
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8065569797548453e-05,
+ "loss": 0.4833,
+ "step": 2693
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8063967523958093e-05,
+ "loss": 0.4976,
+ "step": 2694
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80623646581835e-05,
+ "loss": 0.5101,
+ "step": 2695
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8060761200342376e-05,
+ "loss": 0.5045,
+ "step": 2696
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8059157150552477e-05,
+ "loss": 0.4985,
+ "step": 2697
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80575525089316e-05,
+ "loss": 0.4916,
+ "step": 2698
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.805594727559758e-05,
+ "loss": 0.4951,
+ "step": 2699
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80543414506683e-05,
+ "loss": 0.5025,
+ "step": 2700
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8052735034261683e-05,
+ "loss": 0.5244,
+ "step": 2701
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8051128026495703e-05,
+ "loss": 0.4934,
+ "step": 2702
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8049520427488362e-05,
+ "loss": 0.5106,
+ "step": 2703
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8047912237357724e-05,
+ "loss": 0.5032,
+ "step": 2704
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8046303456221885e-05,
+ "loss": 0.4925,
+ "step": 2705
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8044694084198985e-05,
+ "loss": 0.4961,
+ "step": 2706
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8043084121407214e-05,
+ "loss": 0.4993,
+ "step": 2707
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80414735679648e-05,
+ "loss": 0.5052,
+ "step": 2708
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8039862423990012e-05,
+ "loss": 0.5097,
+ "step": 2709
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803825068960117e-05,
+ "loss": 0.5066,
+ "step": 2710
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803663836491663e-05,
+ "loss": 0.5189,
+ "step": 2711
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8035025450054796e-05,
+ "loss": 0.4867,
+ "step": 2712
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803341194513411e-05,
+ "loss": 0.4937,
+ "step": 2713
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.803179785027307e-05,
+ "loss": 0.512,
+ "step": 2714
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8030183165590197e-05,
+ "loss": 0.4938,
+ "step": 2715
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8028567891204074e-05,
+ "loss": 0.4957,
+ "step": 2716
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.802695202723332e-05,
+ "loss": 0.4973,
+ "step": 2717
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8025335573796596e-05,
+ "loss": 0.5068,
+ "step": 2718
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8023718531012602e-05,
+ "loss": 0.4977,
+ "step": 2719
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.80221008990001e-05,
+ "loss": 0.4864,
+ "step": 2720
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8020482677877868e-05,
+ "loss": 0.5293,
+ "step": 2721
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.801886386776475e-05,
+ "loss": 0.4882,
+ "step": 2722
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8017244468779625e-05,
+ "loss": 0.4978,
+ "step": 2723
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8015624481041408e-05,
+ "loss": 0.4887,
+ "step": 2724
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8014003904669073e-05,
+ "loss": 0.4994,
+ "step": 2725
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8012382739781623e-05,
+ "loss": 0.498,
+ "step": 2726
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.801076098649811e-05,
+ "loss": 0.5084,
+ "step": 2727
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8009138644937626e-05,
+ "loss": 0.5097,
+ "step": 2728
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8007515715219317e-05,
+ "loss": 0.5071,
+ "step": 2729
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8005892197462355e-05,
+ "loss": 0.5053,
+ "step": 2730
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8004268091785973e-05,
+ "loss": 0.4957,
+ "step": 2731
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.8002643398309434e-05,
+ "loss": 0.4895,
+ "step": 2732
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.800101811715205e-05,
+ "loss": 0.4991,
+ "step": 2733
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.799939224843317e-05,
+ "loss": 0.4882,
+ "step": 2734
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7997765792272203e-05,
+ "loss": 0.4993,
+ "step": 2735
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7996138748788573e-05,
+ "loss": 0.4852,
+ "step": 2736
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.799451111810178e-05,
+ "loss": 0.5067,
+ "step": 2737
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7992882900331336e-05,
+ "loss": 0.5039,
+ "step": 2738
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.799125409559682e-05,
+ "loss": 0.4889,
+ "step": 2739
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7989624704017838e-05,
+ "loss": 0.4925,
+ "step": 2740
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.798799472571405e-05,
+ "loss": 0.4827,
+ "step": 2741
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7986364160805156e-05,
+ "loss": 0.4894,
+ "step": 2742
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7984733009410896e-05,
+ "loss": 0.5013,
+ "step": 2743
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7983101271651052e-05,
+ "loss": 0.4842,
+ "step": 2744
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.798146894764546e-05,
+ "loss": 0.5058,
+ "step": 2745
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7979836037513977e-05,
+ "loss": 0.5045,
+ "step": 2746
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7978202541376533e-05,
+ "loss": 0.4997,
+ "step": 2747
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7976568459353078e-05,
+ "loss": 0.5177,
+ "step": 2748
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.797493379156361e-05,
+ "loss": 0.4966,
+ "step": 2749
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7973298538128174e-05,
+ "loss": 0.4932,
+ "step": 2750
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.797166269916686e-05,
+ "loss": 0.4896,
+ "step": 2751
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.797002627479979e-05,
+ "loss": 0.4984,
+ "step": 2752
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7968389265147142e-05,
+ "loss": 0.5047,
+ "step": 2753
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.796675167032913e-05,
+ "loss": 0.4992,
+ "step": 2754
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7965113490466013e-05,
+ "loss": 0.4927,
+ "step": 2755
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.796347472567809e-05,
+ "loss": 0.4969,
+ "step": 2756
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7961835376085702e-05,
+ "loss": 0.497,
+ "step": 2757
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7960195441809242e-05,
+ "loss": 0.4832,
+ "step": 2758
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.795855492296914e-05,
+ "loss": 0.5121,
+ "step": 2759
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7956913819685865e-05,
+ "loss": 0.5147,
+ "step": 2760
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7955272132079935e-05,
+ "loss": 0.4937,
+ "step": 2761
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7953629860271906e-05,
+ "loss": 0.5006,
+ "step": 2762
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7951987004382384e-05,
+ "loss": 0.4956,
+ "step": 2763
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.795034356453201e-05,
+ "loss": 0.5006,
+ "step": 2764
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.794869954084147e-05,
+ "loss": 0.51,
+ "step": 2765
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.79470549334315e-05,
+ "loss": 0.4736,
+ "step": 2766
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.794540974242287e-05,
+ "loss": 0.5055,
+ "step": 2767
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7943763967936395e-05,
+ "loss": 0.5209,
+ "step": 2768
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7942117610092938e-05,
+ "loss": 0.493,
+ "step": 2769
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.794047066901339e-05,
+ "loss": 0.4909,
+ "step": 2770
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7938823144818712e-05,
+ "loss": 0.5175,
+ "step": 2771
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7937175037629876e-05,
+ "loss": 0.4814,
+ "step": 2772
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793552634756792e-05,
+ "loss": 0.5145,
+ "step": 2773
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793387707475392e-05,
+ "loss": 0.5087,
+ "step": 2774
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793222721930898e-05,
+ "loss": 0.504,
+ "step": 2775
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.793057678135427e-05,
+ "loss": 0.4912,
+ "step": 2776
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7928925761010984e-05,
+ "loss": 0.5088,
+ "step": 2777
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.792727415840037e-05,
+ "loss": 0.484,
+ "step": 2778
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7925621973643713e-05,
+ "loss": 0.5029,
+ "step": 2779
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7923969206862347e-05,
+ "loss": 0.5131,
+ "step": 2780
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7922315858177638e-05,
+ "loss": 0.4955,
+ "step": 2781
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7920661927711002e-05,
+ "loss": 0.5075,
+ "step": 2782
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7919007415583903e-05,
+ "loss": 0.469,
+ "step": 2783
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7917352321917834e-05,
+ "loss": 0.5087,
+ "step": 2784
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7915696646834343e-05,
+ "loss": 0.4729,
+ "step": 2785
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7914040390455014e-05,
+ "loss": 0.4914,
+ "step": 2786
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7912383552901473e-05,
+ "loss": 0.5058,
+ "step": 2787
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7910726134295396e-05,
+ "loss": 0.4916,
+ "step": 2788
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7909068134758497e-05,
+ "loss": 0.5064,
+ "step": 2789
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7907409554412526e-05,
+ "loss": 0.501,
+ "step": 2790
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.790575039337929e-05,
+ "loss": 0.5054,
+ "step": 2791
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7904090651780624e-05,
+ "loss": 0.4934,
+ "step": 2792
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.790243032973842e-05,
+ "loss": 0.5042,
+ "step": 2793
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.79007694273746e-05,
+ "loss": 0.4681,
+ "step": 2794
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7899107944811133e-05,
+ "loss": 0.5011,
+ "step": 2795
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7897445882170038e-05,
+ "loss": 0.5067,
+ "step": 2796
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.789578323957336e-05,
+ "loss": 0.5044,
+ "step": 2797
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7894120017143205e-05,
+ "loss": 0.5046,
+ "step": 2798
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.789245621500171e-05,
+ "loss": 0.4989,
+ "step": 2799
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7890791833271058e-05,
+ "loss": 0.4721,
+ "step": 2800
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7889126872073473e-05,
+ "loss": 0.5095,
+ "step": 2801
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7887461331531224e-05,
+ "loss": 0.496,
+ "step": 2802
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.788579521176662e-05,
+ "loss": 0.4881,
+ "step": 2803
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7884128512902018e-05,
+ "loss": 0.5057,
+ "step": 2804
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.788246123505981e-05,
+ "loss": 0.5034,
+ "step": 2805
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.7880793378362432e-05,
+ "loss": 0.4997,
+ "step": 2806
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.787912494293237e-05,
+ "loss": 0.4959,
+ "step": 2807
+ },
+ {
+ "epoch": 0.23,
+ "learning_rate": 1.787745592889214e-05,
+ "loss": 0.4812,
+ "step": 2808
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7875786336364316e-05,
+ "loss": 0.5047,
+ "step": 2809
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.78741161654715e-05,
+ "loss": 0.4924,
+ "step": 2810
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7872445416336343e-05,
+ "loss": 0.5078,
+ "step": 2811
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7870774089081537e-05,
+ "loss": 0.4883,
+ "step": 2812
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.786910218382982e-05,
+ "loss": 0.5038,
+ "step": 2813
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7867429700703967e-05,
+ "loss": 0.5137,
+ "step": 2814
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7865756639826805e-05,
+ "loss": 0.5147,
+ "step": 2815
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.786408300132119e-05,
+ "loss": 0.4802,
+ "step": 2816
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7862408785310025e-05,
+ "loss": 0.5072,
+ "step": 2817
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7860733991916263e-05,
+ "loss": 0.5101,
+ "step": 2818
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7859058621262893e-05,
+ "loss": 0.4928,
+ "step": 2819
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7857382673472946e-05,
+ "loss": 0.499,
+ "step": 2820
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7855706148669494e-05,
+ "loss": 0.5024,
+ "step": 2821
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.785402904697566e-05,
+ "loss": 0.4932,
+ "step": 2822
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7852351368514597e-05,
+ "loss": 0.5075,
+ "step": 2823
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7850673113409514e-05,
+ "loss": 0.499,
+ "step": 2824
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7848994281783648e-05,
+ "loss": 0.5007,
+ "step": 2825
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.784731487376029e-05,
+ "loss": 0.5201,
+ "step": 2826
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7845634889462763e-05,
+ "loss": 0.4836,
+ "step": 2827
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.784395432901445e-05,
+ "loss": 0.5021,
+ "step": 2828
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.784227319253875e-05,
+ "loss": 0.5008,
+ "step": 2829
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7840591480159127e-05,
+ "loss": 0.5007,
+ "step": 2830
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7838909191999077e-05,
+ "loss": 0.4969,
+ "step": 2831
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.783722632818214e-05,
+ "loss": 0.4959,
+ "step": 2832
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.78355428888319e-05,
+ "loss": 0.5112,
+ "step": 2833
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.783385887407198e-05,
+ "loss": 0.5032,
+ "step": 2834
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.783217428402605e-05,
+ "loss": 0.5036,
+ "step": 2835
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7830489118817812e-05,
+ "loss": 0.5104,
+ "step": 2836
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7828803378571028e-05,
+ "loss": 0.4815,
+ "step": 2837
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7827117063409483e-05,
+ "loss": 0.4726,
+ "step": 2838
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.782543017345702e-05,
+ "loss": 0.4989,
+ "step": 2839
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.782374270883751e-05,
+ "loss": 0.4892,
+ "step": 2840
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7822054669674878e-05,
+ "loss": 0.4928,
+ "step": 2841
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7820366056093083e-05,
+ "loss": 0.4805,
+ "step": 2842
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7818676868216137e-05,
+ "loss": 0.4995,
+ "step": 2843
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.781698710616808e-05,
+ "loss": 0.4744,
+ "step": 2844
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7815296770073002e-05,
+ "loss": 0.4918,
+ "step": 2845
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7813605860055034e-05,
+ "loss": 0.5363,
+ "step": 2846
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7811914376238354e-05,
+ "loss": 0.4904,
+ "step": 2847
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7810222318747173e-05,
+ "loss": 0.4744,
+ "step": 2848
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780852968770575e-05,
+ "loss": 0.4957,
+ "step": 2849
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7806836483238387e-05,
+ "loss": 0.521,
+ "step": 2850
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780514270546942e-05,
+ "loss": 0.4905,
+ "step": 2851
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780344835452324e-05,
+ "loss": 0.494,
+ "step": 2852
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.780175343052427e-05,
+ "loss": 0.4928,
+ "step": 2853
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7800057933596975e-05,
+ "loss": 0.4872,
+ "step": 2854
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.779836186386587e-05,
+ "loss": 0.4856,
+ "step": 2855
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7796665221455503e-05,
+ "loss": 0.5121,
+ "step": 2856
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7794968006490475e-05,
+ "loss": 0.4866,
+ "step": 2857
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7793270219095418e-05,
+ "loss": 0.498,
+ "step": 2858
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.779157185939501e-05,
+ "loss": 0.4983,
+ "step": 2859
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.778987292751397e-05,
+ "loss": 0.501,
+ "step": 2860
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7788173423577063e-05,
+ "loss": 0.5019,
+ "step": 2861
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7786473347709094e-05,
+ "loss": 0.5126,
+ "step": 2862
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.778477270003491e-05,
+ "loss": 0.5096,
+ "step": 2863
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7783071480679397e-05,
+ "loss": 0.506,
+ "step": 2864
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7781369689767488e-05,
+ "loss": 0.4847,
+ "step": 2865
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7779667327424152e-05,
+ "loss": 0.5061,
+ "step": 2866
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.777796439377441e-05,
+ "loss": 0.5108,
+ "step": 2867
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.777626088894331e-05,
+ "loss": 0.486,
+ "step": 2868
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7774556813055956e-05,
+ "loss": 0.4891,
+ "step": 2869
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7772852166237483e-05,
+ "loss": 0.5196,
+ "step": 2870
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7771146948613078e-05,
+ "loss": 0.507,
+ "step": 2871
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7769441160307967e-05,
+ "loss": 0.5085,
+ "step": 2872
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.776773480144741e-05,
+ "loss": 0.4863,
+ "step": 2873
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.776602787215672e-05,
+ "loss": 0.4874,
+ "step": 2874
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7764320372561238e-05,
+ "loss": 0.5047,
+ "step": 2875
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7762612302786372e-05,
+ "loss": 0.495,
+ "step": 2876
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.776090366295754e-05,
+ "loss": 0.5146,
+ "step": 2877
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.775919445320022e-05,
+ "loss": 0.4959,
+ "step": 2878
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7757484673639936e-05,
+ "loss": 0.4918,
+ "step": 2879
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7755774324402244e-05,
+ "loss": 0.4994,
+ "step": 2880
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7754063405612744e-05,
+ "loss": 0.4843,
+ "step": 2881
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7752351917397078e-05,
+ "loss": 0.5114,
+ "step": 2882
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.775063985988093e-05,
+ "loss": 0.4892,
+ "step": 2883
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.774892723319003e-05,
+ "loss": 0.5053,
+ "step": 2884
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7747214037450146e-05,
+ "loss": 0.4994,
+ "step": 2885
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7745500272787084e-05,
+ "loss": 0.4916,
+ "step": 2886
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7743785939326697e-05,
+ "loss": 0.5066,
+ "step": 2887
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7742071037194882e-05,
+ "loss": 0.484,
+ "step": 2888
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7740355566517567e-05,
+ "loss": 0.5008,
+ "step": 2889
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7738639527420738e-05,
+ "loss": 0.4982,
+ "step": 2890
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.773692292003041e-05,
+ "loss": 0.4913,
+ "step": 2891
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7735205744472642e-05,
+ "loss": 0.5338,
+ "step": 2892
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7733488000873538e-05,
+ "loss": 0.5042,
+ "step": 2893
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.773176968935924e-05,
+ "loss": 0.4934,
+ "step": 2894
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7730050810055935e-05,
+ "loss": 0.499,
+ "step": 2895
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.772833136308985e-05,
+ "loss": 0.5032,
+ "step": 2896
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7726611348587255e-05,
+ "loss": 0.5151,
+ "step": 2897
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7724890766674457e-05,
+ "loss": 0.4901,
+ "step": 2898
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7723169617477815e-05,
+ "loss": 0.5074,
+ "step": 2899
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.772144790112372e-05,
+ "loss": 0.4803,
+ "step": 2900
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7719725617738605e-05,
+ "loss": 0.4699,
+ "step": 2901
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.771800276744895e-05,
+ "loss": 0.5076,
+ "step": 2902
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.771627935038127e-05,
+ "loss": 0.4943,
+ "step": 2903
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7714555366662133e-05,
+ "loss": 0.4933,
+ "step": 2904
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7712830816418137e-05,
+ "loss": 0.5069,
+ "step": 2905
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7711105699775925e-05,
+ "loss": 0.4909,
+ "step": 2906
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7709380016862182e-05,
+ "loss": 0.4913,
+ "step": 2907
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7707653767803638e-05,
+ "loss": 0.4997,
+ "step": 2908
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.770592695272706e-05,
+ "loss": 0.4943,
+ "step": 2909
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7704199571759257e-05,
+ "loss": 0.5002,
+ "step": 2910
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.770247162502708e-05,
+ "loss": 0.4869,
+ "step": 2911
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7700743112657427e-05,
+ "loss": 0.504,
+ "step": 2912
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7699014034777227e-05,
+ "loss": 0.4923,
+ "step": 2913
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7697284391513462e-05,
+ "loss": 0.5013,
+ "step": 2914
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7695554182993145e-05,
+ "loss": 0.5073,
+ "step": 2915
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7693823409343335e-05,
+ "loss": 0.4885,
+ "step": 2916
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.769209207069114e-05,
+ "loss": 0.5021,
+ "step": 2917
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7690360167163693e-05,
+ "loss": 0.4975,
+ "step": 2918
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.768862769888818e-05,
+ "loss": 0.5013,
+ "step": 2919
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7686894665991837e-05,
+ "loss": 0.5013,
+ "step": 2920
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7685161068601915e-05,
+ "loss": 0.4903,
+ "step": 2921
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.768342690684573e-05,
+ "loss": 0.4874,
+ "step": 2922
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.768169218085063e-05,
+ "loss": 0.5023,
+ "step": 2923
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7679956890744008e-05,
+ "loss": 0.4943,
+ "step": 2924
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7678221036653295e-05,
+ "loss": 0.505,
+ "step": 2925
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7676484618705966e-05,
+ "loss": 0.4858,
+ "step": 2926
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7674747637029533e-05,
+ "loss": 0.4885,
+ "step": 2927
+ },
+ {
+ "epoch": 0.24,
+ "learning_rate": 1.7673010091751557e-05,
+ "loss": 0.4894,
+ "step": 2928
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7671271982999637e-05,
+ "loss": 0.4983,
+ "step": 2929
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7669533310901405e-05,
+ "loss": 0.4914,
+ "step": 2930
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.766779407558455e-05,
+ "loss": 0.5021,
+ "step": 2931
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7666054277176788e-05,
+ "loss": 0.4882,
+ "step": 2932
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7664313915805885e-05,
+ "loss": 0.4862,
+ "step": 2933
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7662572991599648e-05,
+ "loss": 0.5032,
+ "step": 2934
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7660831504685923e-05,
+ "loss": 0.4968,
+ "step": 2935
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7659089455192594e-05,
+ "loss": 0.4915,
+ "step": 2936
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7657346843247595e-05,
+ "loss": 0.5019,
+ "step": 2937
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.765560366897889e-05,
+ "loss": 0.4972,
+ "step": 2938
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7653859932514494e-05,
+ "loss": 0.4978,
+ "step": 2939
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.765211563398246e-05,
+ "loss": 0.5023,
+ "step": 2940
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7650370773510885e-05,
+ "loss": 0.5064,
+ "step": 2941
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7648625351227894e-05,
+ "loss": 0.481,
+ "step": 2942
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7646879367261673e-05,
+ "loss": 0.4964,
+ "step": 2943
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7645132821740437e-05,
+ "loss": 0.4971,
+ "step": 2944
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7643385714792446e-05,
+ "loss": 0.4873,
+ "step": 2945
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7641638046546e-05,
+ "loss": 0.4941,
+ "step": 2946
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7639889817129435e-05,
+ "loss": 0.4745,
+ "step": 2947
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.763814102667114e-05,
+ "loss": 0.4895,
+ "step": 2948
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7636391675299546e-05,
+ "loss": 0.5155,
+ "step": 2949
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.76346417631431e-05,
+ "loss": 0.4832,
+ "step": 2950
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.763289129033032e-05,
+ "loss": 0.4912,
+ "step": 2951
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7631140256989753e-05,
+ "loss": 0.5079,
+ "step": 2952
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.762938866324998e-05,
+ "loss": 0.4972,
+ "step": 2953
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7627636509239646e-05,
+ "loss": 0.4955,
+ "step": 2954
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7625883795087405e-05,
+ "loss": 0.4958,
+ "step": 2955
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.762413052092198e-05,
+ "loss": 0.4923,
+ "step": 2956
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7622376686872122e-05,
+ "loss": 0.4913,
+ "step": 2957
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.762062229306662e-05,
+ "loss": 0.51,
+ "step": 2958
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7618867339634314e-05,
+ "loss": 0.4916,
+ "step": 2959
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7617111826704083e-05,
+ "loss": 0.5067,
+ "step": 2960
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.761535575440484e-05,
+ "loss": 0.517,
+ "step": 2961
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7613599122865545e-05,
+ "loss": 0.4977,
+ "step": 2962
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.76118419322152e-05,
+ "loss": 0.5007,
+ "step": 2963
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.761008418258284e-05,
+ "loss": 0.4947,
+ "step": 2964
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7608325874097548e-05,
+ "loss": 0.5109,
+ "step": 2965
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7606567006888453e-05,
+ "loss": 0.4925,
+ "step": 2966
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7604807581084714e-05,
+ "loss": 0.4935,
+ "step": 2967
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7603047596815538e-05,
+ "loss": 0.4883,
+ "step": 2968
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.760128705421017e-05,
+ "loss": 0.5063,
+ "step": 2969
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7599525953397898e-05,
+ "loss": 0.4865,
+ "step": 2970
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7597764294508048e-05,
+ "loss": 0.5095,
+ "step": 2971
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7596002077669988e-05,
+ "loss": 0.4756,
+ "step": 2972
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.759423930301313e-05,
+ "loss": 0.4943,
+ "step": 2973
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7592475970666926e-05,
+ "loss": 0.5059,
+ "step": 2974
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7590712080760865e-05,
+ "loss": 0.493,
+ "step": 2975
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7588947633424478e-05,
+ "loss": 0.4919,
+ "step": 2976
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7587182628787343e-05,
+ "loss": 0.492,
+ "step": 2977
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.758541706697908e-05,
+ "loss": 0.5072,
+ "step": 2978
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.758365094812933e-05,
+ "loss": 0.4911,
+ "step": 2979
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.75818842723678e-05,
+ "loss": 0.4993,
+ "step": 2980
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7580117039824224e-05,
+ "loss": 0.5072,
+ "step": 2981
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.757834925062838e-05,
+ "loss": 0.4968,
+ "step": 2982
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7576580904910088e-05,
+ "loss": 0.4873,
+ "step": 2983
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.757481200279921e-05,
+ "loss": 0.5004,
+ "step": 2984
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7573042544425644e-05,
+ "loss": 0.5078,
+ "step": 2985
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.757127252991933e-05,
+ "loss": 0.486,
+ "step": 2986
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7569501959410253e-05,
+ "loss": 0.5065,
+ "step": 2987
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7567730833028436e-05,
+ "loss": 0.5147,
+ "step": 2988
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7565959150903943e-05,
+ "loss": 0.4804,
+ "step": 2989
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.756418691316688e-05,
+ "loss": 0.4937,
+ "step": 2990
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7562414119947392e-05,
+ "loss": 0.4972,
+ "step": 2991
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7560640771375668e-05,
+ "loss": 0.4794,
+ "step": 2992
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.755886686758193e-05,
+ "loss": 0.5034,
+ "step": 2993
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7557092408696446e-05,
+ "loss": 0.5085,
+ "step": 2994
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7555317394849532e-05,
+ "loss": 0.4924,
+ "step": 2995
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7553541826171535e-05,
+ "loss": 0.5068,
+ "step": 2996
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.755176570279284e-05,
+ "loss": 0.4977,
+ "step": 2997
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7549989024843883e-05,
+ "loss": 0.4948,
+ "step": 2998
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7548211792455134e-05,
+ "loss": 0.5113,
+ "step": 2999
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.754643400575711e-05,
+ "loss": 0.4921,
+ "step": 3000
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7544655664880357e-05,
+ "loss": 0.4879,
+ "step": 3001
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7542876769955475e-05,
+ "loss": 0.5032,
+ "step": 3002
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7541097321113093e-05,
+ "loss": 0.4926,
+ "step": 3003
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7539317318483893e-05,
+ "loss": 0.4976,
+ "step": 3004
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7537536762198584e-05,
+ "loss": 0.4868,
+ "step": 3005
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.753575565238793e-05,
+ "loss": 0.5015,
+ "step": 3006
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.753397398918272e-05,
+ "loss": 0.4932,
+ "step": 3007
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.75321917727138e-05,
+ "loss": 0.5025,
+ "step": 3008
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7530409003112042e-05,
+ "loss": 0.5077,
+ "step": 3009
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7528625680508372e-05,
+ "loss": 0.5092,
+ "step": 3010
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7526841805033742e-05,
+ "loss": 0.483,
+ "step": 3011
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.752505737681916e-05,
+ "loss": 0.4801,
+ "step": 3012
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7523272395995657e-05,
+ "loss": 0.5236,
+ "step": 3013
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.752148686269433e-05,
+ "loss": 0.4854,
+ "step": 3014
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7519700777046285e-05,
+ "loss": 0.4899,
+ "step": 3015
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7517914139182694e-05,
+ "loss": 0.4946,
+ "step": 3016
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.751612694923476e-05,
+ "loss": 0.4829,
+ "step": 3017
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.751433920733372e-05,
+ "loss": 0.4841,
+ "step": 3018
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7512550913610867e-05,
+ "loss": 0.5057,
+ "step": 3019
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.751076206819752e-05,
+ "loss": 0.4959,
+ "step": 3020
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.750897267122505e-05,
+ "loss": 0.5034,
+ "step": 3021
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7507182722824854e-05,
+ "loss": 0.4933,
+ "step": 3022
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7505392223128385e-05,
+ "loss": 0.5029,
+ "step": 3023
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.750360117226713e-05,
+ "loss": 0.5082,
+ "step": 3024
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7501809570372614e-05,
+ "loss": 0.4933,
+ "step": 3025
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7500017417576406e-05,
+ "loss": 0.4984,
+ "step": 3026
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7498224714010113e-05,
+ "loss": 0.5161,
+ "step": 3027
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7496431459805387e-05,
+ "loss": 0.5026,
+ "step": 3028
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.749463765509391e-05,
+ "loss": 0.5023,
+ "step": 3029
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.749284330000742e-05,
+ "loss": 0.5051,
+ "step": 3030
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7491048394677682e-05,
+ "loss": 0.503,
+ "step": 3031
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7489252939236506e-05,
+ "loss": 0.5008,
+ "step": 3032
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7487456933815746e-05,
+ "loss": 0.507,
+ "step": 3033
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7485660378547293e-05,
+ "loss": 0.5189,
+ "step": 3034
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7483863273563072e-05,
+ "loss": 0.4798,
+ "step": 3035
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7482065618995063e-05,
+ "loss": 0.4859,
+ "step": 3036
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7480267414975274e-05,
+ "loss": 0.5047,
+ "step": 3037
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7478468661635763e-05,
+ "loss": 0.4966,
+ "step": 3038
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7476669359108614e-05,
+ "loss": 0.4787,
+ "step": 3039
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7474869507525967e-05,
+ "loss": 0.4912,
+ "step": 3040
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7473069107019993e-05,
+ "loss": 0.4911,
+ "step": 3041
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7471268157722907e-05,
+ "loss": 0.4955,
+ "step": 3042
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7469466659766963e-05,
+ "loss": 0.4862,
+ "step": 3043
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7467664613284455e-05,
+ "loss": 0.5016,
+ "step": 3044
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.7465862018407718e-05,
+ "loss": 0.5008,
+ "step": 3045
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.746405887526913e-05,
+ "loss": 0.5055,
+ "step": 3046
+ },
+ {
+ "epoch": 0.25,
+ "learning_rate": 1.74622551840011e-05,
+ "loss": 0.4982,
+ "step": 3047
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7460450944736087e-05,
+ "loss": 0.5026,
+ "step": 3048
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7458646157606585e-05,
+ "loss": 0.4959,
+ "step": 3049
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.745684082274514e-05,
+ "loss": 0.4894,
+ "step": 3050
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7455034940284313e-05,
+ "loss": 0.4976,
+ "step": 3051
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.745322851035673e-05,
+ "loss": 0.4959,
+ "step": 3052
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7451421533095047e-05,
+ "loss": 0.4848,
+ "step": 3053
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.744961400863196e-05,
+ "loss": 0.5046,
+ "step": 3054
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7447805937100203e-05,
+ "loss": 0.4826,
+ "step": 3055
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7445997318632555e-05,
+ "loss": 0.4998,
+ "step": 3056
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7444188153361836e-05,
+ "loss": 0.4941,
+ "step": 3057
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.74423784414209e-05,
+ "loss": 0.4904,
+ "step": 3058
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.744056818294265e-05,
+ "loss": 0.4982,
+ "step": 3059
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.743875737806002e-05,
+ "loss": 0.4896,
+ "step": 3060
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7436946026905986e-05,
+ "loss": 0.5043,
+ "step": 3061
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.743513412961357e-05,
+ "loss": 0.4901,
+ "step": 3062
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7433321686315824e-05,
+ "loss": 0.4888,
+ "step": 3063
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7431508697145855e-05,
+ "loss": 0.498,
+ "step": 3064
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7429695162236798e-05,
+ "loss": 0.5043,
+ "step": 3065
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7427881081721828e-05,
+ "loss": 0.4807,
+ "step": 3066
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7426066455734167e-05,
+ "loss": 0.483,
+ "step": 3067
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7424251284407075e-05,
+ "loss": 0.5025,
+ "step": 3068
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7422435567873846e-05,
+ "loss": 0.5057,
+ "step": 3069
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.742061930626782e-05,
+ "loss": 0.4982,
+ "step": 3070
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7418802499722377e-05,
+ "loss": 0.5053,
+ "step": 3071
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7416985148370938e-05,
+ "loss": 0.5214,
+ "step": 3072
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.741516725234696e-05,
+ "loss": 0.4795,
+ "step": 3073
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7413348811783938e-05,
+ "loss": 0.4918,
+ "step": 3074
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7411529826815416e-05,
+ "loss": 0.4958,
+ "step": 3075
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.740971029757497e-05,
+ "loss": 0.502,
+ "step": 3076
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7407890224196217e-05,
+ "loss": 0.4911,
+ "step": 3077
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7406069606812822e-05,
+ "loss": 0.503,
+ "step": 3078
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7404248445558476e-05,
+ "loss": 0.4926,
+ "step": 3079
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7402426740566922e-05,
+ "loss": 0.4967,
+ "step": 3080
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7400604491971937e-05,
+ "loss": 0.4957,
+ "step": 3081
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7398781699907337e-05,
+ "loss": 0.4982,
+ "step": 3082
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7396958364506983e-05,
+ "loss": 0.4722,
+ "step": 3083
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7395134485904775e-05,
+ "loss": 0.4908,
+ "step": 3084
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.739331006423465e-05,
+ "loss": 0.5098,
+ "step": 3085
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7391485099630584e-05,
+ "loss": 0.4836,
+ "step": 3086
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7389659592226597e-05,
+ "loss": 0.5039,
+ "step": 3087
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7387833542156743e-05,
+ "loss": 0.4989,
+ "step": 3088
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7386006949555124e-05,
+ "loss": 0.4883,
+ "step": 3089
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7384179814555872e-05,
+ "loss": 0.4955,
+ "step": 3090
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7382352137293172e-05,
+ "loss": 0.5069,
+ "step": 3091
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7380523917901233e-05,
+ "loss": 0.4878,
+ "step": 3092
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7378695156514318e-05,
+ "loss": 0.4928,
+ "step": 3093
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7376865853266717e-05,
+ "loss": 0.5107,
+ "step": 3094
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7375036008292775e-05,
+ "loss": 0.4845,
+ "step": 3095
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7373205621726864e-05,
+ "loss": 0.5126,
+ "step": 3096
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7371374693703395e-05,
+ "loss": 0.4847,
+ "step": 3097
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.736954322435683e-05,
+ "loss": 0.5076,
+ "step": 3098
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7367711213821663e-05,
+ "loss": 0.4967,
+ "step": 3099
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.736587866223243e-05,
+ "loss": 0.508,
+ "step": 3100
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7364045569723706e-05,
+ "loss": 0.4877,
+ "step": 3101
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7362211936430103e-05,
+ "loss": 0.4913,
+ "step": 3102
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7360377762486277e-05,
+ "loss": 0.5046,
+ "step": 3103
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7358543048026925e-05,
+ "loss": 0.5047,
+ "step": 3104
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7356707793186777e-05,
+ "loss": 0.4684,
+ "step": 3105
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7354871998100605e-05,
+ "loss": 0.5183,
+ "step": 3106
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7353035662903225e-05,
+ "loss": 0.4857,
+ "step": 3107
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.735119878772949e-05,
+ "loss": 0.4787,
+ "step": 3108
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7349361372714294e-05,
+ "loss": 0.4873,
+ "step": 3109
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7347523417992564e-05,
+ "loss": 0.4822,
+ "step": 3110
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7345684923699277e-05,
+ "loss": 0.4815,
+ "step": 3111
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.734384588996944e-05,
+ "loss": 0.5008,
+ "step": 3112
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.734200631693811e-05,
+ "loss": 0.5086,
+ "step": 3113
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7340166204740373e-05,
+ "loss": 0.4907,
+ "step": 3114
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7338325553511357e-05,
+ "loss": 0.4919,
+ "step": 3115
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7336484363386237e-05,
+ "loss": 0.5166,
+ "step": 3116
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7334642634500217e-05,
+ "loss": 0.4958,
+ "step": 3117
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7332800366988552e-05,
+ "loss": 0.4995,
+ "step": 3118
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.733095756098653e-05,
+ "loss": 0.5063,
+ "step": 3119
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.732911421662947e-05,
+ "loss": 0.4965,
+ "step": 3120
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.732727033405275e-05,
+ "loss": 0.5028,
+ "step": 3121
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7325425913391772e-05,
+ "loss": 0.484,
+ "step": 3122
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7323580954781986e-05,
+ "loss": 0.516,
+ "step": 3123
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7321735458358872e-05,
+ "loss": 0.4818,
+ "step": 3124
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.731988942425796e-05,
+ "loss": 0.4944,
+ "step": 3125
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7318042852614817e-05,
+ "loss": 0.5021,
+ "step": 3126
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7316195743565045e-05,
+ "loss": 0.5114,
+ "step": 3127
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7314348097244288e-05,
+ "loss": 0.5076,
+ "step": 3128
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7312499913788225e-05,
+ "loss": 0.503,
+ "step": 3129
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7310651193332586e-05,
+ "loss": 0.4836,
+ "step": 3130
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.730880193601313e-05,
+ "loss": 0.4987,
+ "step": 3131
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7306952141965664e-05,
+ "loss": 0.4865,
+ "step": 3132
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7305101811326017e-05,
+ "loss": 0.4911,
+ "step": 3133
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7303250944230084e-05,
+ "loss": 0.5219,
+ "step": 3134
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7301399540813773e-05,
+ "loss": 0.4941,
+ "step": 3135
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.729954760121305e-05,
+ "loss": 0.4856,
+ "step": 3136
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7297695125563915e-05,
+ "loss": 0.496,
+ "step": 3137
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.72958421140024e-05,
+ "loss": 0.4944,
+ "step": 3138
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7293988566664586e-05,
+ "loss": 0.4983,
+ "step": 3139
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7292134483686594e-05,
+ "loss": 0.4886,
+ "step": 3140
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7290279865204567e-05,
+ "loss": 0.498,
+ "step": 3141
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.728842471135472e-05,
+ "loss": 0.4731,
+ "step": 3142
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.728656902227327e-05,
+ "loss": 0.5268,
+ "step": 3143
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.72847127980965e-05,
+ "loss": 0.5159,
+ "step": 3144
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7282856038960724e-05,
+ "loss": 0.5017,
+ "step": 3145
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7280998745002286e-05,
+ "loss": 0.4799,
+ "step": 3146
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7279140916357588e-05,
+ "loss": 0.4828,
+ "step": 3147
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.727728255316306e-05,
+ "loss": 0.5081,
+ "step": 3148
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7275423655555163e-05,
+ "loss": 0.4772,
+ "step": 3149
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7273564223670422e-05,
+ "loss": 0.5074,
+ "step": 3150
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.727170425764537e-05,
+ "loss": 0.4899,
+ "step": 3151
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7269843757616605e-05,
+ "loss": 0.4881,
+ "step": 3152
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7267982723720755e-05,
+ "loss": 0.4807,
+ "step": 3153
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.726612115609448e-05,
+ "loss": 0.5115,
+ "step": 3154
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7264259054874492e-05,
+ "loss": 0.5049,
+ "step": 3155
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.726239642019753e-05,
+ "loss": 0.496,
+ "step": 3156
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7260533252200383e-05,
+ "loss": 0.4848,
+ "step": 3157
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7258669551019872e-05,
+ "loss": 0.5023,
+ "step": 3158
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.725680531679286e-05,
+ "loss": 0.5088,
+ "step": 3159
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.725494054965625e-05,
+ "loss": 0.5108,
+ "step": 3160
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7253075249746984e-05,
+ "loss": 0.4842,
+ "step": 3161
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7251209417202036e-05,
+ "loss": 0.4926,
+ "step": 3162
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724934305215843e-05,
+ "loss": 0.5006,
+ "step": 3163
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.7247476154753222e-05,
+ "loss": 0.4902,
+ "step": 3164
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724560872512351e-05,
+ "loss": 0.5061,
+ "step": 3165
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724374076340643e-05,
+ "loss": 0.4807,
+ "step": 3166
+ },
+ {
+ "epoch": 0.26,
+ "learning_rate": 1.724187226973916e-05,
+ "loss": 0.4988,
+ "step": 3167
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7240003244258904e-05,
+ "loss": 0.4889,
+ "step": 3168
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.723813368710293e-05,
+ "loss": 0.488,
+ "step": 3169
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.723626359840852e-05,
+ "loss": 0.5014,
+ "step": 3170
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7234392978313012e-05,
+ "loss": 0.4979,
+ "step": 3171
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7232521826953773e-05,
+ "loss": 0.4916,
+ "step": 3172
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7230650144468212e-05,
+ "loss": 0.5112,
+ "step": 3173
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7228777930993784e-05,
+ "loss": 0.477,
+ "step": 3174
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7226905186667965e-05,
+ "loss": 0.5136,
+ "step": 3175
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.722503191162829e-05,
+ "loss": 0.5031,
+ "step": 3176
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7223158106012326e-05,
+ "loss": 0.4908,
+ "step": 3177
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.722128376995767e-05,
+ "loss": 0.4848,
+ "step": 3178
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.721940890360197e-05,
+ "loss": 0.4897,
+ "step": 3179
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7217533507082907e-05,
+ "loss": 0.489,
+ "step": 3180
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.721565758053821e-05,
+ "loss": 0.5087,
+ "step": 3181
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7213781124105623e-05,
+ "loss": 0.5086,
+ "step": 3182
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7211904137922962e-05,
+ "loss": 0.4942,
+ "step": 3183
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.721002662212805e-05,
+ "loss": 0.4779,
+ "step": 3184
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.720814857685878e-05,
+ "loss": 0.4938,
+ "step": 3185
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7206270002253056e-05,
+ "loss": 0.4867,
+ "step": 3186
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7204390898448837e-05,
+ "loss": 0.4784,
+ "step": 3187
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.720251126558411e-05,
+ "loss": 0.4861,
+ "step": 3188
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.720063110379692e-05,
+ "loss": 0.5038,
+ "step": 3189
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7198750413225327e-05,
+ "loss": 0.5021,
+ "step": 3190
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7196869194007448e-05,
+ "loss": 0.4814,
+ "step": 3191
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.719498744628143e-05,
+ "loss": 0.4862,
+ "step": 3192
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.719310517018546e-05,
+ "loss": 0.5017,
+ "step": 3193
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7191222365857764e-05,
+ "loss": 0.4901,
+ "step": 3194
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7189339033436607e-05,
+ "loss": 0.4953,
+ "step": 3195
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7187455173060294e-05,
+ "loss": 0.5086,
+ "step": 3196
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7185570784867168e-05,
+ "loss": 0.4942,
+ "step": 3197
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7183685868995616e-05,
+ "loss": 0.5027,
+ "step": 3198
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.718180042558405e-05,
+ "loss": 0.4924,
+ "step": 3199
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.717991445477093e-05,
+ "loss": 0.517,
+ "step": 3200
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7178027956694753e-05,
+ "loss": 0.4834,
+ "step": 3201
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7176140931494064e-05,
+ "loss": 0.4947,
+ "step": 3202
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.717425337930743e-05,
+ "loss": 0.5267,
+ "step": 3203
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7172365300273467e-05,
+ "loss": 0.5019,
+ "step": 3204
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7170476694530834e-05,
+ "loss": 0.4692,
+ "step": 3205
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.716858756221821e-05,
+ "loss": 0.4858,
+ "step": 3206
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7166697903474335e-05,
+ "loss": 0.5162,
+ "step": 3207
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.716480771843798e-05,
+ "loss": 0.493,
+ "step": 3208
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7162917007247937e-05,
+ "loss": 0.4835,
+ "step": 3209
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7161025770043065e-05,
+ "loss": 0.5061,
+ "step": 3210
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7159134006962248e-05,
+ "loss": 0.4877,
+ "step": 3211
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7157241718144404e-05,
+ "loss": 0.4893,
+ "step": 3212
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7155348903728497e-05,
+ "loss": 0.4832,
+ "step": 3213
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.715345556385353e-05,
+ "loss": 0.4912,
+ "step": 3214
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.715156169865854e-05,
+ "loss": 0.4865,
+ "step": 3215
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7149667308282604e-05,
+ "loss": 0.4766,
+ "step": 3216
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.714777239286484e-05,
+ "loss": 0.5137,
+ "step": 3217
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7145876952544395e-05,
+ "loss": 0.4717,
+ "step": 3218
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7143980987460475e-05,
+ "loss": 0.5099,
+ "step": 3219
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7142084497752304e-05,
+ "loss": 0.5271,
+ "step": 3220
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.714018748355915e-05,
+ "loss": 0.4995,
+ "step": 3221
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.713828994502033e-05,
+ "loss": 0.522,
+ "step": 3222
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7136391882275186e-05,
+ "loss": 0.4746,
+ "step": 3223
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7134493295463104e-05,
+ "loss": 0.4952,
+ "step": 3224
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.713259418472351e-05,
+ "loss": 0.4802,
+ "step": 3225
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.713069455019586e-05,
+ "loss": 0.4934,
+ "step": 3226
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.712879439201967e-05,
+ "loss": 0.5037,
+ "step": 3227
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7126893710334465e-05,
+ "loss": 0.497,
+ "step": 3228
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7124992505279833e-05,
+ "loss": 0.4945,
+ "step": 3229
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.712309077699538e-05,
+ "loss": 0.4899,
+ "step": 3230
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.712118852562077e-05,
+ "loss": 0.5034,
+ "step": 3231
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.71192857512957e-05,
+ "loss": 0.4879,
+ "step": 3232
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7117382454159887e-05,
+ "loss": 0.4883,
+ "step": 3233
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7115478634353117e-05,
+ "loss": 0.4988,
+ "step": 3234
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7113574292015185e-05,
+ "loss": 0.4861,
+ "step": 3235
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.711166942728595e-05,
+ "loss": 0.5031,
+ "step": 3236
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.710976404030529e-05,
+ "loss": 0.4695,
+ "step": 3237
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.710785813121313e-05,
+ "loss": 0.4973,
+ "step": 3238
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7105951700149433e-05,
+ "loss": 0.5143,
+ "step": 3239
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7104044747254202e-05,
+ "loss": 0.4813,
+ "step": 3240
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7102137272667466e-05,
+ "loss": 0.513,
+ "step": 3241
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7100229276529314e-05,
+ "loss": 0.4643,
+ "step": 3242
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7098320758979854e-05,
+ "loss": 0.492,
+ "step": 3243
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7096411720159244e-05,
+ "loss": 0.4903,
+ "step": 3244
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7094502160207672e-05,
+ "loss": 0.5142,
+ "step": 3245
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7092592079265368e-05,
+ "loss": 0.4952,
+ "step": 3246
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7090681477472605e-05,
+ "loss": 0.491,
+ "step": 3247
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7088770354969685e-05,
+ "loss": 0.5151,
+ "step": 3248
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.708685871189695e-05,
+ "loss": 0.503,
+ "step": 3249
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7084946548394797e-05,
+ "loss": 0.5048,
+ "step": 3250
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7083033864603632e-05,
+ "loss": 0.4966,
+ "step": 3251
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7081120660663923e-05,
+ "loss": 0.5089,
+ "step": 3252
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7079206936716163e-05,
+ "loss": 0.4987,
+ "step": 3253
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.707729269290089e-05,
+ "loss": 0.4891,
+ "step": 3254
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.707537792935868e-05,
+ "loss": 0.4912,
+ "step": 3255
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7073462646230144e-05,
+ "loss": 0.4958,
+ "step": 3256
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7071546843655932e-05,
+ "loss": 0.4796,
+ "step": 3257
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.706963052177673e-05,
+ "loss": 0.494,
+ "step": 3258
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.706771368073327e-05,
+ "loss": 0.5072,
+ "step": 3259
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7065796320666312e-05,
+ "loss": 0.5034,
+ "step": 3260
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7063878441716665e-05,
+ "loss": 0.5014,
+ "step": 3261
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7061960044025162e-05,
+ "loss": 0.509,
+ "step": 3262
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.706004112773269e-05,
+ "loss": 0.504,
+ "step": 3263
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7058121692980157e-05,
+ "loss": 0.494,
+ "step": 3264
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7056201739908528e-05,
+ "loss": 0.494,
+ "step": 3265
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.705428126865879e-05,
+ "loss": 0.4973,
+ "step": 3266
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7052360279371978e-05,
+ "loss": 0.4877,
+ "step": 3267
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.705043877218916e-05,
+ "loss": 0.4844,
+ "step": 3268
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7048516747251444e-05,
+ "loss": 0.5011,
+ "step": 3269
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.704659420469997e-05,
+ "loss": 0.4979,
+ "step": 3270
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7044671144675935e-05,
+ "loss": 0.4596,
+ "step": 3271
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7042747567320548e-05,
+ "loss": 0.5083,
+ "step": 3272
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.704082347277507e-05,
+ "loss": 0.4956,
+ "step": 3273
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7038898861180805e-05,
+ "loss": 0.481,
+ "step": 3274
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7036973732679084e-05,
+ "loss": 0.507,
+ "step": 3275
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7035048087411283e-05,
+ "loss": 0.4831,
+ "step": 3276
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.703312192551881e-05,
+ "loss": 0.4758,
+ "step": 3277
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.703119524714311e-05,
+ "loss": 0.503,
+ "step": 3278
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.702926805242568e-05,
+ "loss": 0.508,
+ "step": 3279
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7027340341508043e-05,
+ "loss": 0.5148,
+ "step": 3280
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.702541211453176e-05,
+ "loss": 0.469,
+ "step": 3281
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.702348337163843e-05,
+ "loss": 0.4877,
+ "step": 3282
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7021554112969696e-05,
+ "loss": 0.5001,
+ "step": 3283
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.701962433866723e-05,
+ "loss": 0.4817,
+ "step": 3284
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7017694048872756e-05,
+ "loss": 0.5152,
+ "step": 3285
+ },
+ {
+ "epoch": 0.27,
+ "learning_rate": 1.7015763243728014e-05,
+ "loss": 0.5012,
+ "step": 3286
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.70138319233748e-05,
+ "loss": 0.4863,
+ "step": 3287
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7011900087954945e-05,
+ "loss": 0.4832,
+ "step": 3288
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7009967737610312e-05,
+ "loss": 0.5042,
+ "step": 3289
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.70080348724828e-05,
+ "loss": 0.5057,
+ "step": 3290
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7006101492714362e-05,
+ "loss": 0.5154,
+ "step": 3291
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7004167598446967e-05,
+ "loss": 0.4931,
+ "step": 3292
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.700223318982264e-05,
+ "loss": 0.5065,
+ "step": 3293
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.7000298266983428e-05,
+ "loss": 0.4968,
+ "step": 3294
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.699836283007143e-05,
+ "loss": 0.4878,
+ "step": 3295
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6996426879228775e-05,
+ "loss": 0.4811,
+ "step": 3296
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6994490414597627e-05,
+ "loss": 0.5043,
+ "step": 3297
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6992553436320195e-05,
+ "loss": 0.4804,
+ "step": 3298
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6990615944538725e-05,
+ "loss": 0.481,
+ "step": 3299
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6988677939395496e-05,
+ "loss": 0.4824,
+ "step": 3300
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.698673942103283e-05,
+ "loss": 0.4943,
+ "step": 3301
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6984800389593076e-05,
+ "loss": 0.4982,
+ "step": 3302
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6982860845218637e-05,
+ "loss": 0.4838,
+ "step": 3303
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.698092078805194e-05,
+ "loss": 0.5223,
+ "step": 3304
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6978980218235454e-05,
+ "loss": 0.4791,
+ "step": 3305
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.697703913591169e-05,
+ "loss": 0.4881,
+ "step": 3306
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6975097541223195e-05,
+ "loss": 0.4824,
+ "step": 3307
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6973155434312544e-05,
+ "loss": 0.4667,
+ "step": 3308
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6971212815322365e-05,
+ "loss": 0.509,
+ "step": 3309
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.696926968439531e-05,
+ "loss": 0.5058,
+ "step": 3310
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6967326041674076e-05,
+ "loss": 0.5017,
+ "step": 3311
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.69653818873014e-05,
+ "loss": 0.4986,
+ "step": 3312
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6963437221420046e-05,
+ "loss": 0.5003,
+ "step": 3313
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6961492044172824e-05,
+ "loss": 0.4991,
+ "step": 3314
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6959546355702584e-05,
+ "loss": 0.495,
+ "step": 3315
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6957600156152206e-05,
+ "loss": 0.4848,
+ "step": 3316
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6955653445664612e-05,
+ "loss": 0.4958,
+ "step": 3317
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.695370622438276e-05,
+ "loss": 0.4899,
+ "step": 3318
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6951758492449646e-05,
+ "loss": 0.4963,
+ "step": 3319
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6949810250008302e-05,
+ "loss": 0.4902,
+ "step": 3320
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.69478614972018e-05,
+ "loss": 0.4889,
+ "step": 3321
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.694591223417325e-05,
+ "loss": 0.4899,
+ "step": 3322
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.694396246106579e-05,
+ "loss": 0.4928,
+ "step": 3323
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6942012178022613e-05,
+ "loss": 0.5079,
+ "step": 3324
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6940061385186936e-05,
+ "loss": 0.48,
+ "step": 3325
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6938110082702014e-05,
+ "loss": 0.4855,
+ "step": 3326
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6936158270711148e-05,
+ "loss": 0.4925,
+ "step": 3327
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6934205949357666e-05,
+ "loss": 0.4942,
+ "step": 3328
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.693225311878494e-05,
+ "loss": 0.507,
+ "step": 3329
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6930299779136382e-05,
+ "loss": 0.4764,
+ "step": 3330
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6928345930555432e-05,
+ "loss": 0.49,
+ "step": 3331
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6926391573185576e-05,
+ "loss": 0.4877,
+ "step": 3332
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.692443670717033e-05,
+ "loss": 0.491,
+ "step": 3333
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6922481332653248e-05,
+ "loss": 0.4942,
+ "step": 3334
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6920525449777937e-05,
+ "loss": 0.4978,
+ "step": 3335
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.691856905868802e-05,
+ "loss": 0.4789,
+ "step": 3336
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6916612159527166e-05,
+ "loss": 0.4907,
+ "step": 3337
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6914654752439083e-05,
+ "loss": 0.5074,
+ "step": 3338
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.691269683756752e-05,
+ "loss": 0.4883,
+ "step": 3339
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6910738415056245e-05,
+ "loss": 0.4935,
+ "step": 3340
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6908779485049093e-05,
+ "loss": 0.5326,
+ "step": 3341
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6906820047689907e-05,
+ "loss": 0.5007,
+ "step": 3342
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6904860103122587e-05,
+ "loss": 0.473,
+ "step": 3343
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6902899651491056e-05,
+ "loss": 0.4961,
+ "step": 3344
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.690093869293929e-05,
+ "loss": 0.4919,
+ "step": 3345
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6898977227611288e-05,
+ "loss": 0.5026,
+ "step": 3346
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6897015255651093e-05,
+ "loss": 0.5022,
+ "step": 3347
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6895052777202784e-05,
+ "loss": 0.4966,
+ "step": 3348
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.689308979241048e-05,
+ "loss": 0.511,
+ "step": 3349
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6891126301418334e-05,
+ "loss": 0.4936,
+ "step": 3350
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.688916230437053e-05,
+ "loss": 0.4949,
+ "step": 3351
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.68871978014113e-05,
+ "loss": 0.504,
+ "step": 3352
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6885232792684914e-05,
+ "loss": 0.4937,
+ "step": 3353
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6883267278335668e-05,
+ "loss": 0.5026,
+ "step": 3354
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.68813012585079e-05,
+ "loss": 0.4734,
+ "step": 3355
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.687933473334599e-05,
+ "loss": 0.4808,
+ "step": 3356
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6877367702994353e-05,
+ "loss": 0.4932,
+ "step": 3357
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6875400167597433e-05,
+ "loss": 0.5041,
+ "step": 3358
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6873432127299725e-05,
+ "loss": 0.4932,
+ "step": 3359
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6871463582245753e-05,
+ "loss": 0.4834,
+ "step": 3360
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6869494532580072e-05,
+ "loss": 0.499,
+ "step": 3361
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6867524978447286e-05,
+ "loss": 0.4741,
+ "step": 3362
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6865554919992026e-05,
+ "loss": 0.5121,
+ "step": 3363
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6863584357358974e-05,
+ "loss": 0.5057,
+ "step": 3364
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.686161329069283e-05,
+ "loss": 0.4854,
+ "step": 3365
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685964172013835e-05,
+ "loss": 0.4994,
+ "step": 3366
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685766964584031e-05,
+ "loss": 0.4862,
+ "step": 3367
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685569706794354e-05,
+ "loss": 0.4974,
+ "step": 3368
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6853723986592885e-05,
+ "loss": 0.5175,
+ "step": 3369
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.685175040193325e-05,
+ "loss": 0.5038,
+ "step": 3370
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6849776314109568e-05,
+ "loss": 0.5083,
+ "step": 3371
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6847801723266798e-05,
+ "loss": 0.5001,
+ "step": 3372
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6845826629549952e-05,
+ "loss": 0.5107,
+ "step": 3373
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6843851033104076e-05,
+ "loss": 0.5127,
+ "step": 3374
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6841874934074244e-05,
+ "loss": 0.491,
+ "step": 3375
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6839898332605575e-05,
+ "loss": 0.495,
+ "step": 3376
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.683792122884322e-05,
+ "loss": 0.4971,
+ "step": 3377
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6835943622932377e-05,
+ "loss": 0.5114,
+ "step": 3378
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6833965515018257e-05,
+ "loss": 0.4907,
+ "step": 3379
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.683198690524614e-05,
+ "loss": 0.519,
+ "step": 3380
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6830007793761323e-05,
+ "loss": 0.4936,
+ "step": 3381
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.682802818070914e-05,
+ "loss": 0.4878,
+ "step": 3382
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6826048066234967e-05,
+ "loss": 0.4965,
+ "step": 3383
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6824067450484214e-05,
+ "loss": 0.5071,
+ "step": 3384
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.682208633360233e-05,
+ "loss": 0.4647,
+ "step": 3385
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6820104715734803e-05,
+ "loss": 0.484,
+ "step": 3386
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6818122597027152e-05,
+ "loss": 0.4863,
+ "step": 3387
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.681613997762494e-05,
+ "loss": 0.4965,
+ "step": 3388
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6814156857673753e-05,
+ "loss": 0.4948,
+ "step": 3389
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6812173237319232e-05,
+ "loss": 0.4834,
+ "step": 3390
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6810189116707042e-05,
+ "loss": 0.5055,
+ "step": 3391
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6808204495982887e-05,
+ "loss": 0.5029,
+ "step": 3392
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6806219375292513e-05,
+ "loss": 0.495,
+ "step": 3393
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.68042337547817e-05,
+ "loss": 0.4815,
+ "step": 3394
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6802247634596256e-05,
+ "loss": 0.4937,
+ "step": 3395
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.680026101488204e-05,
+ "loss": 0.5125,
+ "step": 3396
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.679827389578494e-05,
+ "loss": 0.4883,
+ "step": 3397
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6796286277450882e-05,
+ "loss": 0.503,
+ "step": 3398
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6794298160025822e-05,
+ "loss": 0.4779,
+ "step": 3399
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6792309543655774e-05,
+ "loss": 0.4657,
+ "step": 3400
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6790320428486757e-05,
+ "loss": 0.5017,
+ "step": 3401
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6788330814664856e-05,
+ "loss": 0.4918,
+ "step": 3402
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.678634070233617e-05,
+ "loss": 0.4799,
+ "step": 3403
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6784350091646852e-05,
+ "loss": 0.4953,
+ "step": 3404
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6782358982743084e-05,
+ "loss": 0.5107,
+ "step": 3405
+ },
+ {
+ "epoch": 0.28,
+ "learning_rate": 1.6780367375771075e-05,
+ "loss": 0.4833,
+ "step": 3406
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6778375270877095e-05,
+ "loss": 0.493,
+ "step": 3407
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6776382668207424e-05,
+ "loss": 0.4983,
+ "step": 3408
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6774389567908394e-05,
+ "loss": 0.482,
+ "step": 3409
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.677239597012638e-05,
+ "loss": 0.502,
+ "step": 3410
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6770401875007766e-05,
+ "loss": 0.5169,
+ "step": 3411
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6768407282699e-05,
+ "loss": 0.4878,
+ "step": 3412
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6766412193346555e-05,
+ "loss": 0.5064,
+ "step": 3413
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6764416607096942e-05,
+ "loss": 0.5101,
+ "step": 3414
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6762420524096712e-05,
+ "loss": 0.5111,
+ "step": 3415
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6760423944492442e-05,
+ "loss": 0.4933,
+ "step": 3416
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6758426868430758e-05,
+ "loss": 0.4991,
+ "step": 3417
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6756429296058314e-05,
+ "loss": 0.5079,
+ "step": 3418
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6754431227521806e-05,
+ "loss": 0.4799,
+ "step": 3419
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6752432662967958e-05,
+ "loss": 0.4992,
+ "step": 3420
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6750433602543546e-05,
+ "loss": 0.5113,
+ "step": 3421
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.674843404639537e-05,
+ "loss": 0.4779,
+ "step": 3422
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6746433994670258e-05,
+ "loss": 0.509,
+ "step": 3423
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6744433447515098e-05,
+ "loss": 0.4972,
+ "step": 3424
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.67424324050768e-05,
+ "loss": 0.4903,
+ "step": 3425
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6740430867502307e-05,
+ "loss": 0.4894,
+ "step": 3426
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6738428834938606e-05,
+ "loss": 0.4954,
+ "step": 3427
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6736426307532722e-05,
+ "loss": 0.4985,
+ "step": 3428
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6734423285431705e-05,
+ "loss": 0.4952,
+ "step": 3429
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6732419768782656e-05,
+ "loss": 0.5189,
+ "step": 3430
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6730415757732702e-05,
+ "loss": 0.4859,
+ "step": 3431
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6728411252429006e-05,
+ "loss": 0.5037,
+ "step": 3432
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.672640625301877e-05,
+ "loss": 0.4977,
+ "step": 3433
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6724400759649243e-05,
+ "loss": 0.4831,
+ "step": 3434
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.672239477246769e-05,
+ "loss": 0.4928,
+ "step": 3435
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6720388291621423e-05,
+ "loss": 0.4899,
+ "step": 3436
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6718381317257793e-05,
+ "loss": 0.4841,
+ "step": 3437
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6716373849524187e-05,
+ "loss": 0.5012,
+ "step": 3438
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.671436588856802e-05,
+ "loss": 0.5064,
+ "step": 3439
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6712357434536747e-05,
+ "loss": 0.4881,
+ "step": 3440
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6710348487577863e-05,
+ "loss": 0.4914,
+ "step": 3441
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6708339047838897e-05,
+ "loss": 0.4985,
+ "step": 3442
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6706329115467412e-05,
+ "loss": 0.4928,
+ "step": 3443
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.670431869061101e-05,
+ "loss": 0.4741,
+ "step": 3444
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6702307773417334e-05,
+ "loss": 0.4799,
+ "step": 3445
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6700296364034048e-05,
+ "loss": 0.5049,
+ "step": 3446
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6698284462608866e-05,
+ "loss": 0.5034,
+ "step": 3447
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6696272069289533e-05,
+ "loss": 0.4924,
+ "step": 3448
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6694259184223833e-05,
+ "loss": 0.5037,
+ "step": 3449
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6692245807559578e-05,
+ "loss": 0.4939,
+ "step": 3450
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.669023193944463e-05,
+ "loss": 0.4952,
+ "step": 3451
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668821758002688e-05,
+ "loss": 0.4887,
+ "step": 3452
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668620272945424e-05,
+ "loss": 0.5063,
+ "step": 3453
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6684187387874686e-05,
+ "loss": 0.4739,
+ "step": 3454
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668217155543621e-05,
+ "loss": 0.5013,
+ "step": 3455
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.668015523228685e-05,
+ "loss": 0.4862,
+ "step": 3456
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6678138418574673e-05,
+ "loss": 0.4973,
+ "step": 3457
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6676121114447784e-05,
+ "loss": 0.4797,
+ "step": 3458
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6674103320054335e-05,
+ "loss": 0.5063,
+ "step": 3459
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6672085035542497e-05,
+ "loss": 0.4745,
+ "step": 3460
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.667006626106048e-05,
+ "loss": 0.4841,
+ "step": 3461
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6668046996756544e-05,
+ "loss": 0.4975,
+ "step": 3462
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6666027242778972e-05,
+ "loss": 0.5235,
+ "step": 3463
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.666400699927608e-05,
+ "loss": 0.4883,
+ "step": 3464
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6661986266396235e-05,
+ "loss": 0.5063,
+ "step": 3465
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6659965044287826e-05,
+ "loss": 0.4858,
+ "step": 3466
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6657943333099287e-05,
+ "loss": 0.4754,
+ "step": 3467
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6655921132979082e-05,
+ "loss": 0.4743,
+ "step": 3468
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6653898444075713e-05,
+ "loss": 0.4887,
+ "step": 3469
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6651875266537718e-05,
+ "loss": 0.4948,
+ "step": 3470
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.664985160051367e-05,
+ "loss": 0.4873,
+ "step": 3471
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6647827446152183e-05,
+ "loss": 0.486,
+ "step": 3472
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6645802803601893e-05,
+ "loss": 0.4984,
+ "step": 3473
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.664377767301149e-05,
+ "loss": 0.5056,
+ "step": 3474
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.664175205452969e-05,
+ "loss": 0.4926,
+ "step": 3475
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.663972594830524e-05,
+ "loss": 0.5159,
+ "step": 3476
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6637699354486936e-05,
+ "loss": 0.5252,
+ "step": 3477
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6635672273223597e-05,
+ "loss": 0.4872,
+ "step": 3478
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.663364470466409e-05,
+ "loss": 0.4877,
+ "step": 3479
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6631616648957303e-05,
+ "loss": 0.4879,
+ "step": 3480
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6629588106252173e-05,
+ "loss": 0.4756,
+ "step": 3481
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6627559076697672e-05,
+ "loss": 0.5409,
+ "step": 3482
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6625529560442793e-05,
+ "loss": 0.5017,
+ "step": 3483
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6623499557636584e-05,
+ "loss": 0.4925,
+ "step": 3484
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6621469068428114e-05,
+ "loss": 0.4936,
+ "step": 3485
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.66194380929665e-05,
+ "loss": 0.5126,
+ "step": 3486
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6617406631400884e-05,
+ "loss": 0.4967,
+ "step": 3487
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6615374683880445e-05,
+ "loss": 0.4864,
+ "step": 3488
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6613342250554406e-05,
+ "loss": 0.4922,
+ "step": 3489
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6611309331572022e-05,
+ "loss": 0.4962,
+ "step": 3490
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6609275927082577e-05,
+ "loss": 0.4899,
+ "step": 3491
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.66072420372354e-05,
+ "loss": 0.4947,
+ "step": 3492
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.660520766217985e-05,
+ "loss": 0.5001,
+ "step": 3493
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6603172802065317e-05,
+ "loss": 0.5018,
+ "step": 3494
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6601137457041242e-05,
+ "loss": 0.5025,
+ "step": 3495
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6599101627257087e-05,
+ "loss": 0.4887,
+ "step": 3496
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6597065312862358e-05,
+ "loss": 0.4875,
+ "step": 3497
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.659502851400659e-05,
+ "loss": 0.5023,
+ "step": 3498
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6592991230839355e-05,
+ "loss": 0.4966,
+ "step": 3499
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.659095346351027e-05,
+ "loss": 0.5032,
+ "step": 3500
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6588915212168977e-05,
+ "loss": 0.4823,
+ "step": 3501
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.658687647696516e-05,
+ "loss": 0.5014,
+ "step": 3502
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.658483725804853e-05,
+ "loss": 0.4557,
+ "step": 3503
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6582797555568834e-05,
+ "loss": 0.5108,
+ "step": 3504
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.658075736967587e-05,
+ "loss": 0.5026,
+ "step": 3505
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6578716700519454e-05,
+ "loss": 0.5017,
+ "step": 3506
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.657667554824945e-05,
+ "loss": 0.4901,
+ "step": 3507
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6574633913015742e-05,
+ "loss": 0.4907,
+ "step": 3508
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.657259179496827e-05,
+ "loss": 0.4864,
+ "step": 3509
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6570549194256995e-05,
+ "loss": 0.495,
+ "step": 3510
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6568506111031913e-05,
+ "loss": 0.5021,
+ "step": 3511
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6566462545443066e-05,
+ "loss": 0.5074,
+ "step": 3512
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.656441849764052e-05,
+ "loss": 0.4989,
+ "step": 3513
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6562373967774382e-05,
+ "loss": 0.509,
+ "step": 3514
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6560328955994796e-05,
+ "loss": 0.5201,
+ "step": 3515
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.655828346245194e-05,
+ "loss": 0.5027,
+ "step": 3516
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.655623748729602e-05,
+ "loss": 0.4831,
+ "step": 3517
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.655419103067729e-05,
+ "loss": 0.5112,
+ "step": 3518
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6552144092746032e-05,
+ "loss": 0.4874,
+ "step": 3519
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6550096673652565e-05,
+ "loss": 0.4991,
+ "step": 3520
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.654804877354724e-05,
+ "loss": 0.4899,
+ "step": 3521
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.654600039258045e-05,
+ "loss": 0.5151,
+ "step": 3522
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6543951530902618e-05,
+ "loss": 0.5163,
+ "step": 3523
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6541902188664206e-05,
+ "loss": 0.4763,
+ "step": 3524
+ },
+ {
+ "epoch": 0.29,
+ "learning_rate": 1.6539852366015702e-05,
+ "loss": 0.5012,
+ "step": 3525
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6537802063107646e-05,
+ "loss": 0.4732,
+ "step": 3526
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6535751280090598e-05,
+ "loss": 0.51,
+ "step": 3527
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6533700017115162e-05,
+ "loss": 0.5077,
+ "step": 3528
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.653164827433197e-05,
+ "loss": 0.5029,
+ "step": 3529
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6529596051891696e-05,
+ "loss": 0.4791,
+ "step": 3530
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6527543349945047e-05,
+ "loss": 0.5035,
+ "step": 3531
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6525490168642765e-05,
+ "loss": 0.4892,
+ "step": 3532
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6523436508135624e-05,
+ "loss": 0.4915,
+ "step": 3533
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6521382368574442e-05,
+ "loss": 0.4816,
+ "step": 3534
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.651932775011006e-05,
+ "loss": 0.481,
+ "step": 3535
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6517272652893367e-05,
+ "loss": 0.4885,
+ "step": 3536
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6515217077075276e-05,
+ "loss": 0.506,
+ "step": 3537
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.651316102280674e-05,
+ "loss": 0.4849,
+ "step": 3538
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6511104490238753e-05,
+ "loss": 0.5038,
+ "step": 3539
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6509047479522332e-05,
+ "loss": 0.5172,
+ "step": 3540
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.650698999080854e-05,
+ "loss": 0.4906,
+ "step": 3541
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6504932024248462e-05,
+ "loss": 0.4895,
+ "step": 3542
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6502873579993238e-05,
+ "loss": 0.4769,
+ "step": 3543
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6500814658194024e-05,
+ "loss": 0.5035,
+ "step": 3544
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.649875525900202e-05,
+ "loss": 0.5003,
+ "step": 3545
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.649669538256846e-05,
+ "loss": 0.4854,
+ "step": 3546
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6494635029044613e-05,
+ "loss": 0.4941,
+ "step": 3547
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.649257419858178e-05,
+ "loss": 0.4851,
+ "step": 3548
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6490512891331304e-05,
+ "loss": 0.4964,
+ "step": 3549
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6488451107444556e-05,
+ "loss": 0.5009,
+ "step": 3550
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.648638884707295e-05,
+ "loss": 0.496,
+ "step": 3551
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6484326110367924e-05,
+ "loss": 0.5007,
+ "step": 3552
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.648226289748096e-05,
+ "loss": 0.5075,
+ "step": 3553
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.648019920856357e-05,
+ "loss": 0.4816,
+ "step": 3554
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6478135043767303e-05,
+ "loss": 0.5059,
+ "step": 3555
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.647607040324374e-05,
+ "loss": 0.4913,
+ "step": 3556
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6474005287144507e-05,
+ "loss": 0.4945,
+ "step": 3557
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.647193969562125e-05,
+ "loss": 0.4799,
+ "step": 3558
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6469873628825665e-05,
+ "loss": 0.5039,
+ "step": 3559
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6467807086909468e-05,
+ "loss": 0.4956,
+ "step": 3560
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.646574007002442e-05,
+ "loss": 0.5098,
+ "step": 3561
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6463672578322315e-05,
+ "loss": 0.4929,
+ "step": 3562
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.646160461195498e-05,
+ "loss": 0.4958,
+ "step": 3563
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6459536171074278e-05,
+ "loss": 0.4969,
+ "step": 3564
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6457467255832108e-05,
+ "loss": 0.5093,
+ "step": 3565
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.64553978663804e-05,
+ "loss": 0.4717,
+ "step": 3566
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.645332800287112e-05,
+ "loss": 0.498,
+ "step": 3567
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.645125766545628e-05,
+ "loss": 0.5006,
+ "step": 3568
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6449186854287903e-05,
+ "loss": 0.5093,
+ "step": 3569
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.644711556951807e-05,
+ "loss": 0.5111,
+ "step": 3570
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6445043811298887e-05,
+ "loss": 0.5057,
+ "step": 3571
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.644297157978249e-05,
+ "loss": 0.4916,
+ "step": 3572
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.644089887512106e-05,
+ "loss": 0.4835,
+ "step": 3573
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6438825697466808e-05,
+ "loss": 0.4892,
+ "step": 3574
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6436752046971975e-05,
+ "loss": 0.4817,
+ "step": 3575
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6434677923788848e-05,
+ "loss": 0.483,
+ "step": 3576
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6432603328069732e-05,
+ "loss": 0.5143,
+ "step": 3577
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.643052825996699e-05,
+ "loss": 0.507,
+ "step": 3578
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6428452719632994e-05,
+ "loss": 0.4962,
+ "step": 3579
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.642637670722017e-05,
+ "loss": 0.5072,
+ "step": 3580
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.642430022288097e-05,
+ "loss": 0.4931,
+ "step": 3581
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6422223266767883e-05,
+ "loss": 0.4838,
+ "step": 3582
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.642014583903343e-05,
+ "loss": 0.5034,
+ "step": 3583
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.641806793983017e-05,
+ "loss": 0.5004,
+ "step": 3584
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6415989569310698e-05,
+ "loss": 0.4913,
+ "step": 3585
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6413910727627637e-05,
+ "loss": 0.4919,
+ "step": 3586
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6411831414933647e-05,
+ "loss": 0.5063,
+ "step": 3587
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6409751631381428e-05,
+ "loss": 0.481,
+ "step": 3588
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.640767137712371e-05,
+ "loss": 0.5164,
+ "step": 3589
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6405590652313256e-05,
+ "loss": 0.4764,
+ "step": 3590
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.640350945710287e-05,
+ "loss": 0.4895,
+ "step": 3591
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.640142779164538e-05,
+ "loss": 0.5138,
+ "step": 3592
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6399345656093663e-05,
+ "loss": 0.476,
+ "step": 3593
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6397263050600615e-05,
+ "loss": 0.4773,
+ "step": 3594
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6395179975319178e-05,
+ "loss": 0.5097,
+ "step": 3595
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6393096430402323e-05,
+ "loss": 0.5019,
+ "step": 3596
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6391012416003053e-05,
+ "loss": 0.4923,
+ "step": 3597
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.638892793227442e-05,
+ "loss": 0.4851,
+ "step": 3598
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6386842979369487e-05,
+ "loss": 0.4981,
+ "step": 3599
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6384757557441373e-05,
+ "loss": 0.5019,
+ "step": 3600
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6382671666643223e-05,
+ "loss": 0.492,
+ "step": 3601
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.638058530712821e-05,
+ "loss": 0.4817,
+ "step": 3602
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6378498479049553e-05,
+ "loss": 0.5039,
+ "step": 3603
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6376411182560498e-05,
+ "loss": 0.5044,
+ "step": 3604
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6374323417814325e-05,
+ "loss": 0.5089,
+ "step": 3605
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6372235184964357e-05,
+ "loss": 0.4915,
+ "step": 3606
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6370146484163935e-05,
+ "loss": 0.4752,
+ "step": 3607
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6368057315566454e-05,
+ "loss": 0.5043,
+ "step": 3608
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.636596767932533e-05,
+ "loss": 0.5013,
+ "step": 3609
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.636387757559402e-05,
+ "loss": 0.482,
+ "step": 3610
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6361787004526006e-05,
+ "loss": 0.524,
+ "step": 3611
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.635969596627482e-05,
+ "loss": 0.5078,
+ "step": 3612
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.635760446099401e-05,
+ "loss": 0.4964,
+ "step": 3613
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6355512488837173e-05,
+ "loss": 0.4827,
+ "step": 3614
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6353420049957932e-05,
+ "loss": 0.4924,
+ "step": 3615
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6351327144509954e-05,
+ "loss": 0.5235,
+ "step": 3616
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6349233772646923e-05,
+ "loss": 0.4919,
+ "step": 3617
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6347139934522572e-05,
+ "loss": 0.5046,
+ "step": 3618
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6345045630290664e-05,
+ "loss": 0.5007,
+ "step": 3619
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6342950860105e-05,
+ "loss": 0.4592,
+ "step": 3620
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.63408556241194e-05,
+ "loss": 0.4886,
+ "step": 3621
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.633875992248774e-05,
+ "loss": 0.4956,
+ "step": 3622
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.633666375536392e-05,
+ "loss": 0.4919,
+ "step": 3623
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6334567122901862e-05,
+ "loss": 0.5073,
+ "step": 3624
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.633247002525555e-05,
+ "loss": 0.5198,
+ "step": 3625
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6330372462578972e-05,
+ "loss": 0.481,
+ "step": 3626
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6328274435026174e-05,
+ "loss": 0.4838,
+ "step": 3627
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6326175942751222e-05,
+ "loss": 0.4937,
+ "step": 3628
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.632407698590822e-05,
+ "loss": 0.4734,
+ "step": 3629
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6321977564651313e-05,
+ "loss": 0.4866,
+ "step": 3630
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6319877679134662e-05,
+ "loss": 0.5065,
+ "step": 3631
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6317777329512485e-05,
+ "loss": 0.4771,
+ "step": 3632
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6315676515939015e-05,
+ "loss": 0.4991,
+ "step": 3633
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6313575238568535e-05,
+ "loss": 0.494,
+ "step": 3634
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6311473497555343e-05,
+ "loss": 0.4731,
+ "step": 3635
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6309371293053793e-05,
+ "loss": 0.5089,
+ "step": 3636
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.630726862521826e-05,
+ "loss": 0.4857,
+ "step": 3637
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6305165494203147e-05,
+ "loss": 0.4843,
+ "step": 3638
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6303061900162912e-05,
+ "loss": 0.5002,
+ "step": 3639
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6300957843252027e-05,
+ "loss": 0.4996,
+ "step": 3640
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6298853323625003e-05,
+ "loss": 0.4843,
+ "step": 3641
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6296748341436386e-05,
+ "loss": 0.491,
+ "step": 3642
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6294642896840768e-05,
+ "loss": 0.4923,
+ "step": 3643
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6292536989992754e-05,
+ "loss": 0.4955,
+ "step": 3644
+ },
+ {
+ "epoch": 0.3,
+ "learning_rate": 1.6290430621046994e-05,
+ "loss": 0.4928,
+ "step": 3645
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6288323790158175e-05,
+ "loss": 0.4971,
+ "step": 3646
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6286216497481014e-05,
+ "loss": 0.488,
+ "step": 3647
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6284108743170256e-05,
+ "loss": 0.493,
+ "step": 3648
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.628200052738069e-05,
+ "loss": 0.4973,
+ "step": 3649
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6279891850267134e-05,
+ "loss": 0.4951,
+ "step": 3650
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6277782711984446e-05,
+ "loss": 0.4991,
+ "step": 3651
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.62756731126875e-05,
+ "loss": 0.4884,
+ "step": 3652
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6273563052531227e-05,
+ "loss": 0.4774,
+ "step": 3653
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6271452531670577e-05,
+ "loss": 0.4959,
+ "step": 3654
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6269341550260537e-05,
+ "loss": 0.4922,
+ "step": 3655
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6267230108456126e-05,
+ "loss": 0.5079,
+ "step": 3656
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6265118206412412e-05,
+ "loss": 0.482,
+ "step": 3657
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6263005844284468e-05,
+ "loss": 0.4812,
+ "step": 3658
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6260893022227425e-05,
+ "loss": 0.521,
+ "step": 3659
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6258779740396443e-05,
+ "loss": 0.4847,
+ "step": 3660
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6256665998946708e-05,
+ "loss": 0.499,
+ "step": 3661
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6254551798033444e-05,
+ "loss": 0.4978,
+ "step": 3662
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6252437137811913e-05,
+ "loss": 0.4887,
+ "step": 3663
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.62503220184374e-05,
+ "loss": 0.4927,
+ "step": 3664
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.624820644006524e-05,
+ "loss": 0.4999,
+ "step": 3665
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6246090402850783e-05,
+ "loss": 0.5203,
+ "step": 3666
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6243973906949434e-05,
+ "loss": 0.4929,
+ "step": 3667
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6241856952516604e-05,
+ "loss": 0.4796,
+ "step": 3668
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.623973953970776e-05,
+ "loss": 0.4937,
+ "step": 3669
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6237621668678406e-05,
+ "loss": 0.4927,
+ "step": 3670
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6235503339584052e-05,
+ "loss": 0.4964,
+ "step": 3671
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6233384552580272e-05,
+ "loss": 0.4833,
+ "step": 3672
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6231265307822658e-05,
+ "loss": 0.4704,
+ "step": 3673
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.622914560546684e-05,
+ "loss": 0.5002,
+ "step": 3674
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6227025445668473e-05,
+ "loss": 0.4905,
+ "step": 3675
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.622490482858326e-05,
+ "loss": 0.4894,
+ "step": 3676
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6222783754366926e-05,
+ "loss": 0.4877,
+ "step": 3677
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6220662223175233e-05,
+ "loss": 0.4793,
+ "step": 3678
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6218540235163983e-05,
+ "loss": 0.4839,
+ "step": 3679
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6216417790489005e-05,
+ "loss": 0.4906,
+ "step": 3680
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6214294889306158e-05,
+ "loss": 0.4857,
+ "step": 3681
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.621217153177134e-05,
+ "loss": 0.4932,
+ "step": 3682
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.621004771804049e-05,
+ "loss": 0.4943,
+ "step": 3683
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.620792344826956e-05,
+ "loss": 0.517,
+ "step": 3684
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6205798722614552e-05,
+ "loss": 0.4828,
+ "step": 3685
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6203673541231497e-05,
+ "loss": 0.473,
+ "step": 3686
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6201547904276463e-05,
+ "loss": 0.4931,
+ "step": 3687
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6199421811905542e-05,
+ "loss": 0.508,
+ "step": 3688
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.619729526427487e-05,
+ "loss": 0.4883,
+ "step": 3689
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6195168261540612e-05,
+ "loss": 0.4819,
+ "step": 3690
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6193040803858965e-05,
+ "loss": 0.5097,
+ "step": 3691
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6190912891386154e-05,
+ "loss": 0.5071,
+ "step": 3692
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6188784524278455e-05,
+ "loss": 0.4829,
+ "step": 3693
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6186655702692162e-05,
+ "loss": 0.4916,
+ "step": 3694
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6184526426783607e-05,
+ "loss": 0.5002,
+ "step": 3695
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.618239669670915e-05,
+ "loss": 0.4863,
+ "step": 3696
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.61802665126252e-05,
+ "loss": 0.5061,
+ "step": 3697
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6178135874688183e-05,
+ "loss": 0.4785,
+ "step": 3698
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6176004783054556e-05,
+ "loss": 0.5046,
+ "step": 3699
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6173873237880832e-05,
+ "loss": 0.5005,
+ "step": 3700
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6171741239323537e-05,
+ "loss": 0.4856,
+ "step": 3701
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6169608787539234e-05,
+ "loss": 0.5233,
+ "step": 3702
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6167475882684522e-05,
+ "loss": 0.4767,
+ "step": 3703
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6165342524916035e-05,
+ "loss": 0.5088,
+ "step": 3704
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6163208714390437e-05,
+ "loss": 0.5114,
+ "step": 3705
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6161074451264425e-05,
+ "loss": 0.503,
+ "step": 3706
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.615893973569473e-05,
+ "loss": 0.4942,
+ "step": 3707
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.615680456783812e-05,
+ "loss": 0.4998,
+ "step": 3708
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.615466894785139e-05,
+ "loss": 0.5169,
+ "step": 3709
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6152532875891372e-05,
+ "loss": 0.4753,
+ "step": 3710
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6150396352114926e-05,
+ "loss": 0.481,
+ "step": 3711
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6148259376678957e-05,
+ "loss": 0.4966,
+ "step": 3712
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6146121949740393e-05,
+ "loss": 0.5167,
+ "step": 3713
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6143984071456197e-05,
+ "loss": 0.4961,
+ "step": 3714
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.614184574198336e-05,
+ "loss": 0.5012,
+ "step": 3715
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.613970696147892e-05,
+ "loss": 0.4894,
+ "step": 3716
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.613756773009994e-05,
+ "loss": 0.4937,
+ "step": 3717
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6135428048003513e-05,
+ "loss": 0.4853,
+ "step": 3718
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6133287915346772e-05,
+ "loss": 0.5156,
+ "step": 3719
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6131147332286872e-05,
+ "loss": 0.4906,
+ "step": 3720
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6129006298981015e-05,
+ "loss": 0.4942,
+ "step": 3721
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6126864815586427e-05,
+ "loss": 0.5072,
+ "step": 3722
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6124722882260372e-05,
+ "loss": 0.5006,
+ "step": 3723
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6122580499160144e-05,
+ "loss": 0.4895,
+ "step": 3724
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6120437666443067e-05,
+ "loss": 0.5041,
+ "step": 3725
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6118294384266506e-05,
+ "loss": 0.4864,
+ "step": 3726
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6116150652787852e-05,
+ "loss": 0.4983,
+ "step": 3727
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6114006472164535e-05,
+ "loss": 0.5044,
+ "step": 3728
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6111861842554014e-05,
+ "loss": 0.4779,
+ "step": 3729
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6109716764113778e-05,
+ "loss": 0.4895,
+ "step": 3730
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6107571237001356e-05,
+ "loss": 0.4795,
+ "step": 3731
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6105425261374305e-05,
+ "loss": 0.4991,
+ "step": 3732
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6103278837390218e-05,
+ "loss": 0.4792,
+ "step": 3733
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6101131965206714e-05,
+ "loss": 0.4891,
+ "step": 3734
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6098984644981463e-05,
+ "loss": 0.5137,
+ "step": 3735
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6096836876872143e-05,
+ "loss": 0.5098,
+ "step": 3736
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6094688661036483e-05,
+ "loss": 0.5053,
+ "step": 3737
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6092539997632236e-05,
+ "loss": 0.4915,
+ "step": 3738
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.609039088681719e-05,
+ "loss": 0.4916,
+ "step": 3739
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6088241328749172e-05,
+ "loss": 0.484,
+ "step": 3740
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6086091323586034e-05,
+ "loss": 0.5012,
+ "step": 3741
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6083940871485663e-05,
+ "loss": 0.4669,
+ "step": 3742
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.608178997260598e-05,
+ "loss": 0.4923,
+ "step": 3743
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6079638627104937e-05,
+ "loss": 0.4927,
+ "step": 3744
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6077486835140518e-05,
+ "loss": 0.4755,
+ "step": 3745
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6075334596870746e-05,
+ "loss": 0.4855,
+ "step": 3746
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.607318191245367e-05,
+ "loss": 0.4979,
+ "step": 3747
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.607102878204738e-05,
+ "loss": 0.4754,
+ "step": 3748
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6068875205809978e-05,
+ "loss": 0.5086,
+ "step": 3749
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.606672118389963e-05,
+ "loss": 0.5113,
+ "step": 3750
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6064566716474506e-05,
+ "loss": 0.5014,
+ "step": 3751
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.606241180369283e-05,
+ "loss": 0.4899,
+ "step": 3752
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.606025644571285e-05,
+ "loss": 0.5102,
+ "step": 3753
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6058100642692837e-05,
+ "loss": 0.4875,
+ "step": 3754
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6055944394791113e-05,
+ "loss": 0.5025,
+ "step": 3755
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.605378770216602e-05,
+ "loss": 0.4748,
+ "step": 3756
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.605163056497594e-05,
+ "loss": 0.4893,
+ "step": 3757
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6049472983379285e-05,
+ "loss": 0.4999,
+ "step": 3758
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6047314957534487e-05,
+ "loss": 0.5149,
+ "step": 3759
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.604515648760004e-05,
+ "loss": 0.4722,
+ "step": 3760
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6042997573734437e-05,
+ "loss": 0.5037,
+ "step": 3761
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6040838216096233e-05,
+ "loss": 0.4684,
+ "step": 3762
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6038678414843994e-05,
+ "loss": 0.5232,
+ "step": 3763
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.6036518170136326e-05,
+ "loss": 0.4807,
+ "step": 3764
+ },
+ {
+ "epoch": 0.31,
+ "learning_rate": 1.603435748213187e-05,
+ "loss": 0.4972,
+ "step": 3765
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6032196350989306e-05,
+ "loss": 0.4843,
+ "step": 3766
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.603003477686733e-05,
+ "loss": 0.4668,
+ "step": 3767
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6027872759924678e-05,
+ "loss": 0.4949,
+ "step": 3768
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6025710300320124e-05,
+ "loss": 0.4948,
+ "step": 3769
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6023547398212467e-05,
+ "loss": 0.4746,
+ "step": 3770
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6021384053760546e-05,
+ "loss": 0.476,
+ "step": 3771
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6019220267123223e-05,
+ "loss": 0.4951,
+ "step": 3772
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.60170560384594e-05,
+ "loss": 0.4662,
+ "step": 3773
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.601489136792801e-05,
+ "loss": 0.4972,
+ "step": 3774
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6012726255688013e-05,
+ "loss": 0.4956,
+ "step": 3775
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6010560701898405e-05,
+ "loss": 0.4779,
+ "step": 3776
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6008394706718224e-05,
+ "loss": 0.5058,
+ "step": 3777
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6006228270306526e-05,
+ "loss": 0.5015,
+ "step": 3778
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6004061392822407e-05,
+ "loss": 0.4791,
+ "step": 3779
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.6001894074424987e-05,
+ "loss": 0.4736,
+ "step": 3780
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5999726315273435e-05,
+ "loss": 0.4803,
+ "step": 3781
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.599755811552693e-05,
+ "loss": 0.5038,
+ "step": 3782
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5995389475344715e-05,
+ "loss": 0.4888,
+ "step": 3783
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5993220394886024e-05,
+ "loss": 0.4943,
+ "step": 3784
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5991050874310156e-05,
+ "loss": 0.5088,
+ "step": 3785
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5988880913776434e-05,
+ "loss": 0.4833,
+ "step": 3786
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5986710513444205e-05,
+ "loss": 0.499,
+ "step": 3787
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5984539673472856e-05,
+ "loss": 0.4909,
+ "step": 3788
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5982368394021804e-05,
+ "loss": 0.4929,
+ "step": 3789
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5980196675250504e-05,
+ "loss": 0.4894,
+ "step": 3790
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5978024517318428e-05,
+ "loss": 0.4776,
+ "step": 3791
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5975851920385103e-05,
+ "loss": 0.4832,
+ "step": 3792
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5973678884610062e-05,
+ "loss": 0.4832,
+ "step": 3793
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.597150541015289e-05,
+ "loss": 0.4827,
+ "step": 3794
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5969331497173203e-05,
+ "loss": 0.4805,
+ "step": 3795
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5967157145830638e-05,
+ "loss": 0.4961,
+ "step": 3796
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.596498235628487e-05,
+ "loss": 0.5165,
+ "step": 3797
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5962807128695606e-05,
+ "loss": 0.4927,
+ "step": 3798
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5960631463222592e-05,
+ "loss": 0.5033,
+ "step": 3799
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.595845536002559e-05,
+ "loss": 0.4744,
+ "step": 3800
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5956278819264417e-05,
+ "loss": 0.4675,
+ "step": 3801
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5954101841098895e-05,
+ "loss": 0.4773,
+ "step": 3802
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.59519244256889e-05,
+ "loss": 0.4848,
+ "step": 3803
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5949746573194334e-05,
+ "loss": 0.4883,
+ "step": 3804
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5947568283775125e-05,
+ "loss": 0.4869,
+ "step": 3805
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5945389557591237e-05,
+ "loss": 0.4972,
+ "step": 3806
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.594321039480267e-05,
+ "loss": 0.4711,
+ "step": 3807
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5941030795569452e-05,
+ "loss": 0.4634,
+ "step": 3808
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5938850760051643e-05,
+ "loss": 0.4964,
+ "step": 3809
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5936670288409335e-05,
+ "loss": 0.4977,
+ "step": 3810
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5934489380802653e-05,
+ "loss": 0.5042,
+ "step": 3811
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5932308037391756e-05,
+ "loss": 0.493,
+ "step": 3812
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.593012625833683e-05,
+ "loss": 0.4989,
+ "step": 3813
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.59279440437981e-05,
+ "loss": 0.4855,
+ "step": 3814
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.592576139393581e-05,
+ "loss": 0.483,
+ "step": 3815
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5923578308910254e-05,
+ "loss": 0.4849,
+ "step": 3816
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.592139478888174e-05,
+ "loss": 0.483,
+ "step": 3817
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5919210834010628e-05,
+ "loss": 0.511,
+ "step": 3818
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5917026444457288e-05,
+ "loss": 0.4953,
+ "step": 3819
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.591484162038214e-05,
+ "loss": 0.4849,
+ "step": 3820
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5912656361945626e-05,
+ "loss": 0.4783,
+ "step": 3821
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5910470669308217e-05,
+ "loss": 0.4872,
+ "step": 3822
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5908284542630425e-05,
+ "loss": 0.5001,
+ "step": 3823
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5906097982072793e-05,
+ "loss": 0.4711,
+ "step": 3824
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.590391098779589e-05,
+ "loss": 0.468,
+ "step": 3825
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5901723559960322e-05,
+ "loss": 0.5036,
+ "step": 3826
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5899535698726723e-05,
+ "loss": 0.483,
+ "step": 3827
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5897347404255757e-05,
+ "loss": 0.4843,
+ "step": 3828
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.589515867670813e-05,
+ "loss": 0.4897,
+ "step": 3829
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.589296951624457e-05,
+ "loss": 0.4886,
+ "step": 3830
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5890779923025832e-05,
+ "loss": 0.4777,
+ "step": 3831
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5888589897212726e-05,
+ "loss": 0.495,
+ "step": 3832
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5886399438966068e-05,
+ "loss": 0.4896,
+ "step": 3833
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5884208548446716e-05,
+ "loss": 0.4846,
+ "step": 3834
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5882017225815566e-05,
+ "loss": 0.4673,
+ "step": 3835
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5879825471233538e-05,
+ "loss": 0.4854,
+ "step": 3836
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5877633284861577e-05,
+ "loss": 0.4916,
+ "step": 3837
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.587544066686068e-05,
+ "loss": 0.4774,
+ "step": 3838
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5873247617391854e-05,
+ "loss": 0.4825,
+ "step": 3839
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5871054136616154e-05,
+ "loss": 0.4933,
+ "step": 3840
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5868860224694656e-05,
+ "loss": 0.5059,
+ "step": 3841
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.586666588178848e-05,
+ "loss": 0.4819,
+ "step": 3842
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5864471108058755e-05,
+ "loss": 0.4753,
+ "step": 3843
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.586227590366667e-05,
+ "loss": 0.5028,
+ "step": 3844
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.586008026877342e-05,
+ "loss": 0.5122,
+ "step": 3845
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.585788420354025e-05,
+ "loss": 0.5066,
+ "step": 3846
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5855687708128433e-05,
+ "loss": 0.4991,
+ "step": 3847
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5853490782699266e-05,
+ "loss": 0.4953,
+ "step": 3848
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5851293427414075e-05,
+ "loss": 0.4834,
+ "step": 3849
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.584909564243424e-05,
+ "loss": 0.49,
+ "step": 3850
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5846897427921147e-05,
+ "loss": 0.4989,
+ "step": 3851
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.584469878403623e-05,
+ "loss": 0.481,
+ "step": 3852
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5842499710940936e-05,
+ "loss": 0.5093,
+ "step": 3853
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5840300208796767e-05,
+ "loss": 0.4943,
+ "step": 3854
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5838100277765244e-05,
+ "loss": 0.4794,
+ "step": 3855
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5835899918007917e-05,
+ "loss": 0.4951,
+ "step": 3856
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5833699129686376e-05,
+ "loss": 0.4958,
+ "step": 3857
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5831497912962235e-05,
+ "loss": 0.5049,
+ "step": 3858
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5829296267997142e-05,
+ "loss": 0.4801,
+ "step": 3859
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.582709419495277e-05,
+ "loss": 0.4781,
+ "step": 3860
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5824891693990845e-05,
+ "loss": 0.5053,
+ "step": 3861
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.58226887652731e-05,
+ "loss": 0.5095,
+ "step": 3862
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.582048540896131e-05,
+ "loss": 0.5,
+ "step": 3863
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.581828162521728e-05,
+ "loss": 0.4818,
+ "step": 3864
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5816077414202848e-05,
+ "loss": 0.4957,
+ "step": 3865
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5813872776079882e-05,
+ "loss": 0.477,
+ "step": 3866
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.581166771101028e-05,
+ "loss": 0.4875,
+ "step": 3867
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5809462219155976e-05,
+ "loss": 0.4905,
+ "step": 3868
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.580725630067893e-05,
+ "loss": 0.4993,
+ "step": 3869
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5805049955741135e-05,
+ "loss": 0.486,
+ "step": 3870
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5802843184504614e-05,
+ "loss": 0.4895,
+ "step": 3871
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5800635987131426e-05,
+ "loss": 0.5033,
+ "step": 3872
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.579842836378366e-05,
+ "loss": 0.4842,
+ "step": 3873
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.579622031462343e-05,
+ "loss": 0.479,
+ "step": 3874
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5794011839812888e-05,
+ "loss": 0.5077,
+ "step": 3875
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.579180293951422e-05,
+ "loss": 0.4942,
+ "step": 3876
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5789593613889632e-05,
+ "loss": 0.4722,
+ "step": 3877
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5787383863101366e-05,
+ "loss": 0.48,
+ "step": 3878
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5785173687311704e-05,
+ "loss": 0.4909,
+ "step": 3879
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5782963086682946e-05,
+ "loss": 0.4962,
+ "step": 3880
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5780752061377436e-05,
+ "loss": 0.502,
+ "step": 3881
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5778540611557538e-05,
+ "loss": 0.4961,
+ "step": 3882
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.577632873738565e-05,
+ "loss": 0.506,
+ "step": 3883
+ },
+ {
+ "epoch": 0.32,
+ "learning_rate": 1.5774116439024206e-05,
+ "loss": 0.4868,
+ "step": 3884
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5771903716635666e-05,
+ "loss": 0.4888,
+ "step": 3885
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.576969057038253e-05,
+ "loss": 0.5003,
+ "step": 3886
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5767477000427306e-05,
+ "loss": 0.4854,
+ "step": 3887
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.576526300693257e-05,
+ "loss": 0.4996,
+ "step": 3888
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5763048590060894e-05,
+ "loss": 0.4976,
+ "step": 3889
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5760833749974898e-05,
+ "loss": 0.4881,
+ "step": 3890
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5758618486837232e-05,
+ "loss": 0.494,
+ "step": 3891
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5756402800810582e-05,
+ "loss": 0.4804,
+ "step": 3892
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.575418669205765e-05,
+ "loss": 0.4861,
+ "step": 3893
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.575197016074118e-05,
+ "loss": 0.4914,
+ "step": 3894
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5749753207023944e-05,
+ "loss": 0.4872,
+ "step": 3895
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574753583106875e-05,
+ "loss": 0.489,
+ "step": 3896
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574531803303843e-05,
+ "loss": 0.4924,
+ "step": 3897
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574309981309585e-05,
+ "loss": 0.4816,
+ "step": 3898
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.574088117140391e-05,
+ "loss": 0.4639,
+ "step": 3899
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.573866210812553e-05,
+ "loss": 0.4816,
+ "step": 3900
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5736442623423675e-05,
+ "loss": 0.4962,
+ "step": 3901
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5734222717461338e-05,
+ "loss": 0.4772,
+ "step": 3902
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5732002390401527e-05,
+ "loss": 0.5055,
+ "step": 3903
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5729781642407305e-05,
+ "loss": 0.5134,
+ "step": 3904
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5727560473641755e-05,
+ "loss": 0.4845,
+ "step": 3905
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.572533888426798e-05,
+ "loss": 0.4959,
+ "step": 3906
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5723116874449136e-05,
+ "loss": 0.5198,
+ "step": 3907
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5720894444348393e-05,
+ "loss": 0.4905,
+ "step": 3908
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5718671594128957e-05,
+ "loss": 0.4815,
+ "step": 3909
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.571644832395406e-05,
+ "loss": 0.5216,
+ "step": 3910
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5714224633986978e-05,
+ "loss": 0.4948,
+ "step": 3911
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5712000524391004e-05,
+ "loss": 0.4868,
+ "step": 3912
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5709775995329475e-05,
+ "loss": 0.488,
+ "step": 3913
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.570755104696574e-05,
+ "loss": 0.4918,
+ "step": 3914
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5705325679463198e-05,
+ "loss": 0.4765,
+ "step": 3915
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5703099892985267e-05,
+ "loss": 0.501,
+ "step": 3916
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5700873687695405e-05,
+ "loss": 0.4919,
+ "step": 3917
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5698647063757086e-05,
+ "loss": 0.4837,
+ "step": 3918
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5696420021333828e-05,
+ "loss": 0.4798,
+ "step": 3919
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5694192560589184e-05,
+ "loss": 0.4893,
+ "step": 3920
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5691964681686715e-05,
+ "loss": 0.4969,
+ "step": 3921
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5689736384790038e-05,
+ "loss": 0.4692,
+ "step": 3922
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5687507670062788e-05,
+ "loss": 0.4862,
+ "step": 3923
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5685278537668627e-05,
+ "loss": 0.4888,
+ "step": 3924
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.568304898777126e-05,
+ "loss": 0.518,
+ "step": 3925
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.568081902053441e-05,
+ "loss": 0.4963,
+ "step": 3926
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.567858863612184e-05,
+ "loss": 0.4802,
+ "step": 3927
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5676357834697342e-05,
+ "loss": 0.5066,
+ "step": 3928
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5674126616424735e-05,
+ "loss": 0.495,
+ "step": 3929
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5671894981467866e-05,
+ "loss": 0.4616,
+ "step": 3930
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5669662929990622e-05,
+ "loss": 0.4896,
+ "step": 3931
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5667430462156918e-05,
+ "loss": 0.4981,
+ "step": 3932
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.566519757813069e-05,
+ "loss": 0.4783,
+ "step": 3933
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5662964278075913e-05,
+ "loss": 0.5017,
+ "step": 3934
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5660730562156596e-05,
+ "loss": 0.4876,
+ "step": 3935
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5658496430536772e-05,
+ "loss": 0.4888,
+ "step": 3936
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5656261883380504e-05,
+ "loss": 0.484,
+ "step": 3937
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.565402692085189e-05,
+ "loss": 0.5082,
+ "step": 3938
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5651791543115056e-05,
+ "loss": 0.4958,
+ "step": 3939
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.564955575033416e-05,
+ "loss": 0.4958,
+ "step": 3940
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5647319542673386e-05,
+ "loss": 0.5015,
+ "step": 3941
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.564508292029695e-05,
+ "loss": 0.4872,
+ "step": 3942
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5642845883369114e-05,
+ "loss": 0.471,
+ "step": 3943
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.564060843205414e-05,
+ "loss": 0.484,
+ "step": 3944
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5638370566516344e-05,
+ "loss": 0.4949,
+ "step": 3945
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5636132286920066e-05,
+ "loss": 0.4749,
+ "step": 3946
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5633893593429677e-05,
+ "loss": 0.4953,
+ "step": 3947
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5631654486209572e-05,
+ "loss": 0.513,
+ "step": 3948
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5629414965424187e-05,
+ "loss": 0.4946,
+ "step": 3949
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5627175031237986e-05,
+ "loss": 0.4743,
+ "step": 3950
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.562493468381545e-05,
+ "loss": 0.4942,
+ "step": 3951
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5622693923321105e-05,
+ "loss": 0.5027,
+ "step": 3952
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.562045274991951e-05,
+ "loss": 0.5063,
+ "step": 3953
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5618211163775242e-05,
+ "loss": 0.5087,
+ "step": 3954
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.561596916505291e-05,
+ "loss": 0.4906,
+ "step": 3955
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5613726753917166e-05,
+ "loss": 0.4729,
+ "step": 3956
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5611483930532677e-05,
+ "loss": 0.4925,
+ "step": 3957
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5609240695064146e-05,
+ "loss": 0.4867,
+ "step": 3958
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.560699704767631e-05,
+ "loss": 0.4978,
+ "step": 3959
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5604752988533933e-05,
+ "loss": 0.4827,
+ "step": 3960
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.560250851780181e-05,
+ "loss": 0.4758,
+ "step": 3961
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.560026363564476e-05,
+ "loss": 0.5156,
+ "step": 3962
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5598018342227645e-05,
+ "loss": 0.4874,
+ "step": 3963
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5595772637715345e-05,
+ "loss": 0.4942,
+ "step": 3964
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5593526522272774e-05,
+ "loss": 0.4825,
+ "step": 3965
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5591279996064884e-05,
+ "loss": 0.4938,
+ "step": 3966
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.558903305925665e-05,
+ "loss": 0.5092,
+ "step": 3967
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5586785712013073e-05,
+ "loss": 0.4806,
+ "step": 3968
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5584537954499186e-05,
+ "loss": 0.5001,
+ "step": 3969
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5582289786880064e-05,
+ "loss": 0.4897,
+ "step": 3970
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5580041209320797e-05,
+ "loss": 0.4813,
+ "step": 3971
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5577792221986512e-05,
+ "loss": 0.4873,
+ "step": 3972
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5575542825042368e-05,
+ "loss": 0.4936,
+ "step": 3973
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.557329301865355e-05,
+ "loss": 0.4823,
+ "step": 3974
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.557104280298527e-05,
+ "loss": 0.4738,
+ "step": 3975
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.556879217820278e-05,
+ "loss": 0.4857,
+ "step": 3976
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5566541144471355e-05,
+ "loss": 0.4782,
+ "step": 3977
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.55642897019563e-05,
+ "loss": 0.5053,
+ "step": 3978
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5562037850822954e-05,
+ "loss": 0.4842,
+ "step": 3979
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5559785591236683e-05,
+ "loss": 0.4971,
+ "step": 3980
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5557532923362883e-05,
+ "loss": 0.4861,
+ "step": 3981
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.555527984736698e-05,
+ "loss": 0.4977,
+ "step": 3982
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.555302636341443e-05,
+ "loss": 0.5032,
+ "step": 3983
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5550772471670724e-05,
+ "loss": 0.4829,
+ "step": 3984
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5548518172301373e-05,
+ "loss": 0.5062,
+ "step": 3985
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5546263465471926e-05,
+ "loss": 0.4957,
+ "step": 3986
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.554400835134796e-05,
+ "loss": 0.4942,
+ "step": 3987
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.554175283009508e-05,
+ "loss": 0.4794,
+ "step": 3988
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5539496901878915e-05,
+ "loss": 0.4872,
+ "step": 3989
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5537240566865145e-05,
+ "loss": 0.4901,
+ "step": 3990
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.553498382521946e-05,
+ "loss": 0.4855,
+ "step": 3991
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5532726677107583e-05,
+ "loss": 0.4874,
+ "step": 3992
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.553046912269527e-05,
+ "loss": 0.4815,
+ "step": 3993
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5528211162148305e-05,
+ "loss": 0.5012,
+ "step": 3994
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.552595279563251e-05,
+ "loss": 0.4831,
+ "step": 3995
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5523694023313723e-05,
+ "loss": 0.487,
+ "step": 3996
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5521434845357824e-05,
+ "loss": 0.4729,
+ "step": 3997
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5519175261930716e-05,
+ "loss": 0.4859,
+ "step": 3998
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.551691527319833e-05,
+ "loss": 0.4979,
+ "step": 3999
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.551465487932663e-05,
+ "loss": 0.4947,
+ "step": 4000
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.551239408048162e-05,
+ "loss": 0.48,
+ "step": 4001
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5510132876829313e-05,
+ "loss": 0.4818,
+ "step": 4002
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.5507871268535765e-05,
+ "loss": 0.4845,
+ "step": 4003
+ },
+ {
+ "epoch": 0.33,
+ "learning_rate": 1.550560925576706e-05,
+ "loss": 0.5188,
+ "step": 4004
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5503346838689314e-05,
+ "loss": 0.479,
+ "step": 4005
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5501084017468665e-05,
+ "loss": 0.5038,
+ "step": 4006
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5498820792271284e-05,
+ "loss": 0.5002,
+ "step": 4007
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.549655716326338e-05,
+ "loss": 0.5109,
+ "step": 4008
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5494293130611175e-05,
+ "loss": 0.4899,
+ "step": 4009
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5492028694480938e-05,
+ "loss": 0.4973,
+ "step": 4010
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5489763855038954e-05,
+ "loss": 0.4873,
+ "step": 4011
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.548749861245155e-05,
+ "loss": 0.4707,
+ "step": 4012
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.548523296688507e-05,
+ "loss": 0.48,
+ "step": 4013
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5482966918505897e-05,
+ "loss": 0.4909,
+ "step": 4014
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5480700467480437e-05,
+ "loss": 0.496,
+ "step": 4015
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.547843361397513e-05,
+ "loss": 0.4784,
+ "step": 4016
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5476166358156446e-05,
+ "loss": 0.49,
+ "step": 4017
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5473898700190884e-05,
+ "loss": 0.5039,
+ "step": 4018
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5471630640244966e-05,
+ "loss": 0.4724,
+ "step": 4019
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5469362178485252e-05,
+ "loss": 0.481,
+ "step": 4020
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.546709331507833e-05,
+ "loss": 0.5026,
+ "step": 4021
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5464824050190816e-05,
+ "loss": 0.4854,
+ "step": 4022
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5462554383989347e-05,
+ "loss": 0.5195,
+ "step": 4023
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.546028431664061e-05,
+ "loss": 0.4913,
+ "step": 4024
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5458013848311305e-05,
+ "loss": 0.4944,
+ "step": 4025
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.545574297916816e-05,
+ "loss": 0.4911,
+ "step": 4026
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5453471709377945e-05,
+ "loss": 0.4948,
+ "step": 4027
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.545120003910745e-05,
+ "loss": 0.4996,
+ "step": 4028
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.54489279685235e-05,
+ "loss": 0.4778,
+ "step": 4029
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.544665549779294e-05,
+ "loss": 0.4836,
+ "step": 4030
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5444382627082657e-05,
+ "loss": 0.4674,
+ "step": 4031
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5442109356559556e-05,
+ "loss": 0.4828,
+ "step": 4032
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543983568639058e-05,
+ "loss": 0.4952,
+ "step": 4033
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5437561616742703e-05,
+ "loss": 0.4733,
+ "step": 4034
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543528714778291e-05,
+ "loss": 0.4976,
+ "step": 4035
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543301227967824e-05,
+ "loss": 0.4952,
+ "step": 4036
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.543073701259574e-05,
+ "loss": 0.496,
+ "step": 4037
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.542846134670251e-05,
+ "loss": 0.4901,
+ "step": 4038
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5426185282165652e-05,
+ "loss": 0.5044,
+ "step": 4039
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5423908819152317e-05,
+ "loss": 0.4779,
+ "step": 4040
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.542163195782968e-05,
+ "loss": 0.5076,
+ "step": 4041
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5419354698364944e-05,
+ "loss": 0.4836,
+ "step": 4042
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5417077040925334e-05,
+ "loss": 0.4994,
+ "step": 4043
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.541479898567812e-05,
+ "loss": 0.5221,
+ "step": 4044
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.541252053279059e-05,
+ "loss": 0.4938,
+ "step": 4045
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.541024168243007e-05,
+ "loss": 0.4794,
+ "step": 4046
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5407962434763897e-05,
+ "loss": 0.4798,
+ "step": 4047
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5405682789959455e-05,
+ "loss": 0.4878,
+ "step": 4048
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5403402748184156e-05,
+ "loss": 0.5025,
+ "step": 4049
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5401122309605437e-05,
+ "loss": 0.4778,
+ "step": 4050
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5398841474390754e-05,
+ "loss": 0.4801,
+ "step": 4051
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5396560242707613e-05,
+ "loss": 0.4845,
+ "step": 4052
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5394278614723535e-05,
+ "loss": 0.4736,
+ "step": 4053
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5391996590606066e-05,
+ "loss": 0.5036,
+ "step": 4054
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.53897141705228e-05,
+ "loss": 0.5004,
+ "step": 4055
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.538743135464134e-05,
+ "loss": 0.4898,
+ "step": 4056
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5385148143129328e-05,
+ "loss": 0.4723,
+ "step": 4057
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5382864536154437e-05,
+ "loss": 0.5157,
+ "step": 4058
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5380580533884364e-05,
+ "loss": 0.4803,
+ "step": 4059
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5378296136486837e-05,
+ "loss": 0.5016,
+ "step": 4060
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5376011344129608e-05,
+ "loss": 0.5045,
+ "step": 4061
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.537372615698047e-05,
+ "loss": 0.4805,
+ "step": 4062
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5371440575207233e-05,
+ "loss": 0.5004,
+ "step": 4063
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.536915459897774e-05,
+ "loss": 0.4941,
+ "step": 4064
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5366868228459866e-05,
+ "loss": 0.4623,
+ "step": 4065
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.536458146382151e-05,
+ "loss": 0.4911,
+ "step": 4066
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.536229430523061e-05,
+ "loss": 0.4749,
+ "step": 4067
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5360006752855113e-05,
+ "loss": 0.4797,
+ "step": 4068
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.535771880686302e-05,
+ "loss": 0.4853,
+ "step": 4069
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5355430467422343e-05,
+ "loss": 0.4968,
+ "step": 4070
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.535314173470112e-05,
+ "loss": 0.4907,
+ "step": 4071
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5350852608867436e-05,
+ "loss": 0.4847,
+ "step": 4072
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5348563090089394e-05,
+ "loss": 0.5151,
+ "step": 4073
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5346273178535126e-05,
+ "loss": 0.4775,
+ "step": 4074
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.534398287437279e-05,
+ "loss": 0.4907,
+ "step": 4075
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5341692177770583e-05,
+ "loss": 0.466,
+ "step": 4076
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5339401088896715e-05,
+ "loss": 0.5019,
+ "step": 4077
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.533710960791944e-05,
+ "loss": 0.4801,
+ "step": 4078
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5334817735007037e-05,
+ "loss": 0.4967,
+ "step": 4079
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.533252547032781e-05,
+ "loss": 0.4966,
+ "step": 4080
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.533023281405009e-05,
+ "loss": 0.5023,
+ "step": 4081
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5327939766342237e-05,
+ "loss": 0.5038,
+ "step": 4082
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5325646327372658e-05,
+ "loss": 0.4999,
+ "step": 4083
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.532335249730976e-05,
+ "loss": 0.4819,
+ "step": 4084
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5321058276321988e-05,
+ "loss": 0.4924,
+ "step": 4085
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5318763664577838e-05,
+ "loss": 0.4895,
+ "step": 4086
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5316468662245805e-05,
+ "loss": 0.4882,
+ "step": 4087
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.531417326949442e-05,
+ "loss": 0.4849,
+ "step": 4088
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5311877486492264e-05,
+ "loss": 0.4824,
+ "step": 4089
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5309581313407914e-05,
+ "loss": 0.483,
+ "step": 4090
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5307284750409993e-05,
+ "loss": 0.4939,
+ "step": 4091
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.530498779766716e-05,
+ "loss": 0.5149,
+ "step": 4092
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5302690455348085e-05,
+ "loss": 0.4828,
+ "step": 4093
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.530039272362148e-05,
+ "loss": 0.4805,
+ "step": 4094
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5298094602656077e-05,
+ "loss": 0.4946,
+ "step": 4095
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5295796092620646e-05,
+ "loss": 0.4826,
+ "step": 4096
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5293497193683974e-05,
+ "loss": 0.5091,
+ "step": 4097
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5291197906014886e-05,
+ "loss": 0.4893,
+ "step": 4098
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5288898229782234e-05,
+ "loss": 0.4873,
+ "step": 4099
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5286598165154892e-05,
+ "loss": 0.4815,
+ "step": 4100
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5284297712301773e-05,
+ "loss": 0.4878,
+ "step": 4101
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5281996871391805e-05,
+ "loss": 0.4834,
+ "step": 4102
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5279695642593958e-05,
+ "loss": 0.4621,
+ "step": 4103
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.527739402607722e-05,
+ "loss": 0.4742,
+ "step": 4104
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.527509202201062e-05,
+ "loss": 0.4787,
+ "step": 4105
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5272789630563202e-05,
+ "loss": 0.495,
+ "step": 4106
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.527048685190404e-05,
+ "loss": 0.495,
+ "step": 4107
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5268183686202245e-05,
+ "loss": 0.51,
+ "step": 4108
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5265880133626956e-05,
+ "loss": 0.4721,
+ "step": 4109
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5263576194347334e-05,
+ "loss": 0.498,
+ "step": 4110
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5261271868532568e-05,
+ "loss": 0.5005,
+ "step": 4111
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5258967156351878e-05,
+ "loss": 0.4735,
+ "step": 4112
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.525666205797451e-05,
+ "loss": 0.4863,
+ "step": 4113
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5254356573569748e-05,
+ "loss": 0.4886,
+ "step": 4114
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5252050703306895e-05,
+ "loss": 0.4866,
+ "step": 4115
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5249744447355282e-05,
+ "loss": 0.5044,
+ "step": 4116
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5247437805884273e-05,
+ "loss": 0.4863,
+ "step": 4117
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5245130779063255e-05,
+ "loss": 0.5085,
+ "step": 4118
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.524282336706165e-05,
+ "loss": 0.4725,
+ "step": 4119
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5240515570048903e-05,
+ "loss": 0.4866,
+ "step": 4120
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5238207388194493e-05,
+ "loss": 0.485,
+ "step": 4121
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5235898821667916e-05,
+ "loss": 0.5004,
+ "step": 4122
+ },
+ {
+ "epoch": 0.34,
+ "learning_rate": 1.5233589870638708e-05,
+ "loss": 0.4852,
+ "step": 4123
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5231280535276426e-05,
+ "loss": 0.4778,
+ "step": 4124
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5228970815750666e-05,
+ "loss": 0.4932,
+ "step": 4125
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5226660712231032e-05,
+ "loss": 0.4973,
+ "step": 4126
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5224350224887179e-05,
+ "loss": 0.4899,
+ "step": 4127
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5222039353888774e-05,
+ "loss": 0.4763,
+ "step": 4128
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5219728099405516e-05,
+ "loss": 0.4994,
+ "step": 4129
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.521741646160714e-05,
+ "loss": 0.4798,
+ "step": 4130
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5215104440663399e-05,
+ "loss": 0.4698,
+ "step": 4131
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.521279203674408e-05,
+ "loss": 0.472,
+ "step": 4132
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5210479250018995e-05,
+ "loss": 0.4933,
+ "step": 4133
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5208166080657982e-05,
+ "loss": 0.4828,
+ "step": 4134
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.520585252883092e-05,
+ "loss": 0.497,
+ "step": 4135
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5203538594707699e-05,
+ "loss": 0.4824,
+ "step": 4136
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.520122427845825e-05,
+ "loss": 0.4743,
+ "step": 4137
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5198909580252517e-05,
+ "loss": 0.5035,
+ "step": 4138
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.519659450026049e-05,
+ "loss": 0.5019,
+ "step": 4139
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.519427903865218e-05,
+ "loss": 0.5058,
+ "step": 4140
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.519196319559762e-05,
+ "loss": 0.4959,
+ "step": 4141
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.518964697126688e-05,
+ "loss": 0.4922,
+ "step": 4142
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.518733036583005e-05,
+ "loss": 0.5021,
+ "step": 4143
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5185013379457254e-05,
+ "loss": 0.4927,
+ "step": 4144
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5182696012318641e-05,
+ "loss": 0.5034,
+ "step": 4145
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.518037826458439e-05,
+ "loss": 0.498,
+ "step": 4146
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5178060136424706e-05,
+ "loss": 0.5033,
+ "step": 4147
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5175741628009824e-05,
+ "loss": 0.4818,
+ "step": 4148
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5173422739510003e-05,
+ "loss": 0.5017,
+ "step": 4149
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5171103471095533e-05,
+ "loss": 0.4716,
+ "step": 4150
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5168783822936735e-05,
+ "loss": 0.4648,
+ "step": 4151
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.516646379520395e-05,
+ "loss": 0.4952,
+ "step": 4152
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5164143388067554e-05,
+ "loss": 0.4907,
+ "step": 4153
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5161822601697945e-05,
+ "loss": 0.4882,
+ "step": 4154
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5159501436265553e-05,
+ "loss": 0.4774,
+ "step": 4155
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5157179891940837e-05,
+ "loss": 0.4901,
+ "step": 4156
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5154857968894278e-05,
+ "loss": 0.4773,
+ "step": 4157
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5152535667296395e-05,
+ "loss": 0.4894,
+ "step": 4158
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5150212987317721e-05,
+ "loss": 0.4976,
+ "step": 4159
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5147889929128825e-05,
+ "loss": 0.4964,
+ "step": 4160
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5145566492900305e-05,
+ "loss": 0.4747,
+ "step": 4161
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5143242678802787e-05,
+ "loss": 0.4627,
+ "step": 4162
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5140918487006918e-05,
+ "loss": 0.483,
+ "step": 4163
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5138593917683374e-05,
+ "loss": 0.4939,
+ "step": 4164
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.513626897100287e-05,
+ "loss": 0.4938,
+ "step": 4165
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5133943647136131e-05,
+ "loss": 0.4925,
+ "step": 4166
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5131617946253928e-05,
+ "loss": 0.4871,
+ "step": 4167
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5129291868527052e-05,
+ "loss": 0.4939,
+ "step": 4168
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5126965414126309e-05,
+ "loss": 0.4752,
+ "step": 4169
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.512463858322255e-05,
+ "loss": 0.4781,
+ "step": 4170
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5122311375986649e-05,
+ "loss": 0.4782,
+ "step": 4171
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.511998379258951e-05,
+ "loss": 0.4739,
+ "step": 4172
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5117655833202052e-05,
+ "loss": 0.5065,
+ "step": 4173
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5115327497995238e-05,
+ "loss": 0.5288,
+ "step": 4174
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.511299878714005e-05,
+ "loss": 0.4939,
+ "step": 4175
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5110669700807496e-05,
+ "loss": 0.5027,
+ "step": 4176
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5108340239168614e-05,
+ "loss": 0.5097,
+ "step": 4177
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5106010402394477e-05,
+ "loss": 0.4741,
+ "step": 4178
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5103680190656169e-05,
+ "loss": 0.4856,
+ "step": 4179
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5101349604124816e-05,
+ "loss": 0.5238,
+ "step": 4180
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5099018642971568e-05,
+ "loss": 0.4797,
+ "step": 4181
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5096687307367601e-05,
+ "loss": 0.5027,
+ "step": 4182
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5094355597484111e-05,
+ "loss": 0.481,
+ "step": 4183
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.509202351349234e-05,
+ "loss": 0.5015,
+ "step": 4184
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.508969105556354e-05,
+ "loss": 0.4847,
+ "step": 4185
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5087358223869e-05,
+ "loss": 0.4803,
+ "step": 4186
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5085025018580029e-05,
+ "loss": 0.4904,
+ "step": 4187
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5082691439867973e-05,
+ "loss": 0.4654,
+ "step": 4188
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5080357487904198e-05,
+ "loss": 0.4828,
+ "step": 4189
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5078023162860099e-05,
+ "loss": 0.5049,
+ "step": 4190
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5075688464907099e-05,
+ "loss": 0.4923,
+ "step": 4191
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5073353394216652e-05,
+ "loss": 0.4693,
+ "step": 4192
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5071017950960234e-05,
+ "loss": 0.4917,
+ "step": 4193
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5068682135309347e-05,
+ "loss": 0.495,
+ "step": 4194
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5066345947435525e-05,
+ "loss": 0.4869,
+ "step": 4195
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5064009387510333e-05,
+ "loss": 0.4836,
+ "step": 4196
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5061672455705352e-05,
+ "loss": 0.4999,
+ "step": 4197
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.50593351521922e-05,
+ "loss": 0.5058,
+ "step": 4198
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.505699747714252e-05,
+ "loss": 0.4897,
+ "step": 4199
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5054659430727974e-05,
+ "loss": 0.4752,
+ "step": 4200
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5052321013120263e-05,
+ "loss": 0.4942,
+ "step": 4201
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5049982224491115e-05,
+ "loss": 0.4665,
+ "step": 4202
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5047643065012276e-05,
+ "loss": 0.497,
+ "step": 4203
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5045303534855524e-05,
+ "loss": 0.5008,
+ "step": 4204
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5042963634192667e-05,
+ "loss": 0.4908,
+ "step": 4205
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5040623363195535e-05,
+ "loss": 0.498,
+ "step": 4206
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5038282722035986e-05,
+ "loss": 0.4864,
+ "step": 4207
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5035941710885915e-05,
+ "loss": 0.5004,
+ "step": 4208
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5033600329917227e-05,
+ "loss": 0.5207,
+ "step": 4209
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5031258579301868e-05,
+ "loss": 0.4731,
+ "step": 4210
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5028916459211804e-05,
+ "loss": 0.4995,
+ "step": 4211
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5026573969819035e-05,
+ "loss": 0.4928,
+ "step": 4212
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.502423111129558e-05,
+ "loss": 0.4968,
+ "step": 4213
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5021887883813488e-05,
+ "loss": 0.4896,
+ "step": 4214
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.501954428754484e-05,
+ "loss": 0.4845,
+ "step": 4215
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5017200322661735e-05,
+ "loss": 0.4936,
+ "step": 4216
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5014855989336308e-05,
+ "loss": 0.4902,
+ "step": 4217
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5012511287740715e-05,
+ "loss": 0.4821,
+ "step": 4218
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5010166218047139e-05,
+ "loss": 0.4979,
+ "step": 4219
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.50078207804278e-05,
+ "loss": 0.4948,
+ "step": 4220
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5005474975054928e-05,
+ "loss": 0.4824,
+ "step": 4221
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.5003128802100792e-05,
+ "loss": 0.4921,
+ "step": 4222
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.500078226173769e-05,
+ "loss": 0.4964,
+ "step": 4223
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4998435354137937e-05,
+ "loss": 0.4867,
+ "step": 4224
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4996088079473884e-05,
+ "loss": 0.4999,
+ "step": 4225
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4993740437917898e-05,
+ "loss": 0.5114,
+ "step": 4226
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4991392429642389e-05,
+ "loss": 0.4886,
+ "step": 4227
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.498904405481978e-05,
+ "loss": 0.4818,
+ "step": 4228
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4986695313622525e-05,
+ "loss": 0.5041,
+ "step": 4229
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4984346206223108e-05,
+ "loss": 0.4954,
+ "step": 4230
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4981996732794038e-05,
+ "loss": 0.494,
+ "step": 4231
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4979646893507847e-05,
+ "loss": 0.4941,
+ "step": 4232
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4977296688537101e-05,
+ "loss": 0.4994,
+ "step": 4233
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4974946118054392e-05,
+ "loss": 0.4972,
+ "step": 4234
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4972595182232328e-05,
+ "loss": 0.4681,
+ "step": 4235
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4970243881243558e-05,
+ "loss": 0.4936,
+ "step": 4236
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4967892215260751e-05,
+ "loss": 0.4879,
+ "step": 4237
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.49655401844566e-05,
+ "loss": 0.4786,
+ "step": 4238
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4963187789003835e-05,
+ "loss": 0.4921,
+ "step": 4239
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.49608350290752e-05,
+ "loss": 0.4926,
+ "step": 4240
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4958481904843473e-05,
+ "loss": 0.4689,
+ "step": 4241
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4956128416481459e-05,
+ "loss": 0.478,
+ "step": 4242
+ },
+ {
+ "epoch": 0.35,
+ "learning_rate": 1.4953774564161991e-05,
+ "loss": 0.4967,
+ "step": 4243
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.495142034805792e-05,
+ "loss": 0.4759,
+ "step": 4244
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4949065768342136e-05,
+ "loss": 0.4725,
+ "step": 4245
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4946710825187545e-05,
+ "loss": 0.4913,
+ "step": 4246
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4944355518767086e-05,
+ "loss": 0.4778,
+ "step": 4247
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4941999849253723e-05,
+ "loss": 0.4754,
+ "step": 4248
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4939643816820449e-05,
+ "loss": 0.4989,
+ "step": 4249
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4937287421640277e-05,
+ "loss": 0.4903,
+ "step": 4250
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.493493066388625e-05,
+ "loss": 0.4936,
+ "step": 4251
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4932573543731441e-05,
+ "loss": 0.4945,
+ "step": 4252
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.493021606134895e-05,
+ "loss": 0.5001,
+ "step": 4253
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4927858216911897e-05,
+ "loss": 0.4595,
+ "step": 4254
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.492550001059343e-05,
+ "loss": 0.4922,
+ "step": 4255
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4923141442566732e-05,
+ "loss": 0.4985,
+ "step": 4256
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4920782513005003e-05,
+ "loss": 0.5076,
+ "step": 4257
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4918423222081473e-05,
+ "loss": 0.5075,
+ "step": 4258
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4916063569969398e-05,
+ "loss": 0.5165,
+ "step": 4259
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4913703556842066e-05,
+ "loss": 0.4758,
+ "step": 4260
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.491134318287278e-05,
+ "loss": 0.4828,
+ "step": 4261
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4908982448234875e-05,
+ "loss": 0.4891,
+ "step": 4262
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.490662135310172e-05,
+ "loss": 0.4657,
+ "step": 4263
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.49042598976467e-05,
+ "loss": 0.5058,
+ "step": 4264
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4901898082043232e-05,
+ "loss": 0.4888,
+ "step": 4265
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4899535906464757e-05,
+ "loss": 0.4943,
+ "step": 4266
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4897173371084743e-05,
+ "loss": 0.4916,
+ "step": 4267
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4894810476076688e-05,
+ "loss": 0.4967,
+ "step": 4268
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.489244722161411e-05,
+ "loss": 0.5103,
+ "step": 4269
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4890083607870559e-05,
+ "loss": 0.4885,
+ "step": 4270
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4887719635019605e-05,
+ "loss": 0.5045,
+ "step": 4271
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.488535530323485e-05,
+ "loss": 0.4692,
+ "step": 4272
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4882990612689918e-05,
+ "loss": 0.5159,
+ "step": 4273
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.488062556355847e-05,
+ "loss": 0.4899,
+ "step": 4274
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4878260156014182e-05,
+ "loss": 0.4831,
+ "step": 4275
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4875894390230757e-05,
+ "loss": 0.4664,
+ "step": 4276
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4873528266381927e-05,
+ "loss": 0.4861,
+ "step": 4277
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.487116178464145e-05,
+ "loss": 0.4937,
+ "step": 4278
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4868794945183113e-05,
+ "loss": 0.4788,
+ "step": 4279
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4866427748180729e-05,
+ "loss": 0.4746,
+ "step": 4280
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4864060193808133e-05,
+ "loss": 0.5078,
+ "step": 4281
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4861692282239181e-05,
+ "loss": 0.4726,
+ "step": 4282
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4859324013647773e-05,
+ "loss": 0.4855,
+ "step": 4283
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4856955388207821e-05,
+ "loss": 0.4965,
+ "step": 4284
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.485458640609327e-05,
+ "loss": 0.4585,
+ "step": 4285
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4852217067478082e-05,
+ "loss": 0.4939,
+ "step": 4286
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4849847372536252e-05,
+ "loss": 0.4907,
+ "step": 4287
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4847477321441806e-05,
+ "loss": 0.4992,
+ "step": 4288
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4845106914368786e-05,
+ "loss": 0.4741,
+ "step": 4289
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4842736151491268e-05,
+ "loss": 0.5102,
+ "step": 4290
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.484036503298335e-05,
+ "loss": 0.4947,
+ "step": 4291
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4837993559019157e-05,
+ "loss": 0.5033,
+ "step": 4292
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4835621729772838e-05,
+ "loss": 0.4976,
+ "step": 4293
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4833249545418572e-05,
+ "loss": 0.4881,
+ "step": 4294
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4830877006130561e-05,
+ "loss": 0.4842,
+ "step": 4295
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4828504112083038e-05,
+ "loss": 0.5006,
+ "step": 4296
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4826130863450257e-05,
+ "loss": 0.4883,
+ "step": 4297
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4823757260406498e-05,
+ "loss": 0.4763,
+ "step": 4298
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4821383303126067e-05,
+ "loss": 0.4734,
+ "step": 4299
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.48190089917833e-05,
+ "loss": 0.5042,
+ "step": 4300
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4816634326552561e-05,
+ "loss": 0.4874,
+ "step": 4301
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.481425930760823e-05,
+ "loss": 0.4944,
+ "step": 4302
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4811883935124716e-05,
+ "loss": 0.512,
+ "step": 4303
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.480950820927646e-05,
+ "loss": 0.5002,
+ "step": 4304
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.480713213023793e-05,
+ "loss": 0.4948,
+ "step": 4305
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4804755698183606e-05,
+ "loss": 0.4853,
+ "step": 4306
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4802378913288009e-05,
+ "loss": 0.4656,
+ "step": 4307
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4800001775725684e-05,
+ "loss": 0.4808,
+ "step": 4308
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4797624285671187e-05,
+ "loss": 0.4804,
+ "step": 4309
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4795246443299119e-05,
+ "loss": 0.4866,
+ "step": 4310
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4792868248784098e-05,
+ "loss": 0.5026,
+ "step": 4311
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4790489702300768e-05,
+ "loss": 0.4892,
+ "step": 4312
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4788110804023798e-05,
+ "loss": 0.4854,
+ "step": 4313
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4785731554127885e-05,
+ "loss": 0.4904,
+ "step": 4314
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4783351952787754e-05,
+ "loss": 0.4885,
+ "step": 4315
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4780972000178151e-05,
+ "loss": 0.4908,
+ "step": 4316
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.477859169647385e-05,
+ "loss": 0.4939,
+ "step": 4317
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4776211041849651e-05,
+ "loss": 0.4988,
+ "step": 4318
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4773830036480377e-05,
+ "loss": 0.4819,
+ "step": 4319
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4771448680540881e-05,
+ "loss": 0.4991,
+ "step": 4320
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4769066974206041e-05,
+ "loss": 0.4881,
+ "step": 4321
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.476668491765076e-05,
+ "loss": 0.511,
+ "step": 4322
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4764302511049962e-05,
+ "loss": 0.4744,
+ "step": 4323
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4761919754578603e-05,
+ "loss": 0.4949,
+ "step": 4324
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4759536648411668e-05,
+ "loss": 0.4802,
+ "step": 4325
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4757153192724154e-05,
+ "loss": 0.4845,
+ "step": 4326
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4754769387691096e-05,
+ "loss": 0.4661,
+ "step": 4327
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4752385233487554e-05,
+ "loss": 0.4855,
+ "step": 4328
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4750000730288605e-05,
+ "loss": 0.465,
+ "step": 4329
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4747615878269358e-05,
+ "loss": 0.4894,
+ "step": 4330
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.474523067760495e-05,
+ "loss": 0.5,
+ "step": 4331
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4742845128470538e-05,
+ "loss": 0.5042,
+ "step": 4332
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4740459231041306e-05,
+ "loss": 0.4949,
+ "step": 4333
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4738072985492462e-05,
+ "loss": 0.505,
+ "step": 4334
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4735686391999249e-05,
+ "loss": 0.4786,
+ "step": 4335
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4733299450736925e-05,
+ "loss": 0.482,
+ "step": 4336
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4730912161880772e-05,
+ "loss": 0.4861,
+ "step": 4337
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4728524525606111e-05,
+ "loss": 0.4779,
+ "step": 4338
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4726136542088277e-05,
+ "loss": 0.4865,
+ "step": 4339
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4723748211502628e-05,
+ "loss": 0.4938,
+ "step": 4340
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4721359534024562e-05,
+ "loss": 0.4721,
+ "step": 4341
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4718970509829489e-05,
+ "loss": 0.4929,
+ "step": 4342
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4716581139092851e-05,
+ "loss": 0.5027,
+ "step": 4343
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.471419142199011e-05,
+ "loss": 0.4993,
+ "step": 4344
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4711801358696755e-05,
+ "loss": 0.4877,
+ "step": 4345
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4709410949388311e-05,
+ "loss": 0.491,
+ "step": 4346
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4707020194240313e-05,
+ "loss": 0.5074,
+ "step": 4347
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4704629093428331e-05,
+ "loss": 0.5038,
+ "step": 4348
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4702237647127957e-05,
+ "loss": 0.4815,
+ "step": 4349
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4699845855514807e-05,
+ "loss": 0.5135,
+ "step": 4350
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4697453718764525e-05,
+ "loss": 0.4867,
+ "step": 4351
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4695061237052781e-05,
+ "loss": 0.5028,
+ "step": 4352
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4692668410555269e-05,
+ "loss": 0.5103,
+ "step": 4353
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4690275239447704e-05,
+ "loss": 0.486,
+ "step": 4354
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4687881723905834e-05,
+ "loss": 0.4773,
+ "step": 4355
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4685487864105431e-05,
+ "loss": 0.486,
+ "step": 4356
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4683093660222288e-05,
+ "loss": 0.502,
+ "step": 4357
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4680699112432223e-05,
+ "loss": 0.5118,
+ "step": 4358
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4678304220911086e-05,
+ "loss": 0.475,
+ "step": 4359
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4675908985834744e-05,
+ "loss": 0.4904,
+ "step": 4360
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4673513407379095e-05,
+ "loss": 0.494,
+ "step": 4361
+ },
+ {
+ "epoch": 0.36,
+ "learning_rate": 1.4671117485720058e-05,
+ "loss": 0.4699,
+ "step": 4362
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4668721221033586e-05,
+ "loss": 0.4813,
+ "step": 4363
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4666324613495641e-05,
+ "loss": 0.5052,
+ "step": 4364
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4663927663282228e-05,
+ "loss": 0.5067,
+ "step": 4365
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4661530370569366e-05,
+ "loss": 0.4903,
+ "step": 4366
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4659132735533104e-05,
+ "loss": 0.4757,
+ "step": 4367
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4656734758349509e-05,
+ "loss": 0.4849,
+ "step": 4368
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4654336439194686e-05,
+ "loss": 0.5033,
+ "step": 4369
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4651937778244748e-05,
+ "loss": 0.4794,
+ "step": 4370
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.464953877567585e-05,
+ "loss": 0.4982,
+ "step": 4371
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4647139431664167e-05,
+ "loss": 0.4785,
+ "step": 4372
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4644739746385894e-05,
+ "loss": 0.4746,
+ "step": 4373
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4642339720017249e-05,
+ "loss": 0.4791,
+ "step": 4374
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4639939352734484e-05,
+ "loss": 0.482,
+ "step": 4375
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4637538644713873e-05,
+ "loss": 0.4858,
+ "step": 4376
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4635137596131715e-05,
+ "loss": 0.4855,
+ "step": 4377
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4632736207164326e-05,
+ "loss": 0.4978,
+ "step": 4378
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4630334477988064e-05,
+ "loss": 0.4673,
+ "step": 4379
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4627932408779295e-05,
+ "loss": 0.4958,
+ "step": 4380
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4625529999714416e-05,
+ "loss": 0.5042,
+ "step": 4381
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4623127250969858e-05,
+ "loss": 0.4891,
+ "step": 4382
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4620724162722062e-05,
+ "loss": 0.5032,
+ "step": 4383
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4618320735147501e-05,
+ "loss": 0.4884,
+ "step": 4384
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4615916968422674e-05,
+ "loss": 0.4967,
+ "step": 4385
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4613512862724103e-05,
+ "loss": 0.4824,
+ "step": 4386
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4611108418228342e-05,
+ "loss": 0.4766,
+ "step": 4387
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.460870363511195e-05,
+ "loss": 0.4905,
+ "step": 4388
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.460629851355154e-05,
+ "loss": 0.4821,
+ "step": 4389
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.460389305372372e-05,
+ "loss": 0.4958,
+ "step": 4390
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4601487255805146e-05,
+ "loss": 0.4676,
+ "step": 4391
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4599081119972486e-05,
+ "loss": 0.501,
+ "step": 4392
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.459667464640244e-05,
+ "loss": 0.4787,
+ "step": 4393
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4594267835271725e-05,
+ "loss": 0.5029,
+ "step": 4394
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4591860686757089e-05,
+ "loss": 0.5047,
+ "step": 4395
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4589453201035302e-05,
+ "loss": 0.5009,
+ "step": 4396
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4587045378283162e-05,
+ "loss": 0.4818,
+ "step": 4397
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4584637218677488e-05,
+ "loss": 0.4601,
+ "step": 4398
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4582228722395128e-05,
+ "loss": 0.504,
+ "step": 4399
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4579819889612949e-05,
+ "loss": 0.4719,
+ "step": 4400
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4577410720507842e-05,
+ "loss": 0.5031,
+ "step": 4401
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4575001215256735e-05,
+ "loss": 0.4812,
+ "step": 4402
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4572591374036567e-05,
+ "loss": 0.4906,
+ "step": 4403
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4570181197024307e-05,
+ "loss": 0.4945,
+ "step": 4404
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4567770684396947e-05,
+ "loss": 0.4849,
+ "step": 4405
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.456535983633151e-05,
+ "loss": 0.4788,
+ "step": 4406
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4562948653005032e-05,
+ "loss": 0.4917,
+ "step": 4407
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4560537134594586e-05,
+ "loss": 0.4728,
+ "step": 4408
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.455812528127726e-05,
+ "loss": 0.4997,
+ "step": 4409
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4555713093230173e-05,
+ "loss": 0.493,
+ "step": 4410
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4553300570630464e-05,
+ "loss": 0.4758,
+ "step": 4411
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4550887713655297e-05,
+ "loss": 0.4887,
+ "step": 4412
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.454847452248187e-05,
+ "loss": 0.4892,
+ "step": 4413
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4546060997287392e-05,
+ "loss": 0.4678,
+ "step": 4414
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.45436471382491e-05,
+ "loss": 0.5012,
+ "step": 4415
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4541232945544263e-05,
+ "loss": 0.5001,
+ "step": 4416
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4538818419350164e-05,
+ "loss": 0.4674,
+ "step": 4417
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4536403559844123e-05,
+ "loss": 0.5016,
+ "step": 4418
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.453398836720347e-05,
+ "loss": 0.4768,
+ "step": 4419
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.453157284160557e-05,
+ "loss": 0.4941,
+ "step": 4420
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.452915698322781e-05,
+ "loss": 0.4916,
+ "step": 4421
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4526740792247597e-05,
+ "loss": 0.4901,
+ "step": 4422
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4524324268842369e-05,
+ "loss": 0.4863,
+ "step": 4423
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4521907413189587e-05,
+ "loss": 0.4917,
+ "step": 4424
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4519490225466733e-05,
+ "loss": 0.4962,
+ "step": 4425
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4517072705851312e-05,
+ "loss": 0.485,
+ "step": 4426
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.451465485452086e-05,
+ "loss": 0.4956,
+ "step": 4427
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4512236671652932e-05,
+ "loss": 0.4826,
+ "step": 4428
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4509818157425112e-05,
+ "loss": 0.4832,
+ "step": 4429
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4507399312015005e-05,
+ "loss": 0.4936,
+ "step": 4430
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4504980135600242e-05,
+ "loss": 0.4902,
+ "step": 4431
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4502560628358473e-05,
+ "loss": 0.4943,
+ "step": 4432
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4500140790467377e-05,
+ "loss": 0.4822,
+ "step": 4433
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.449772062210466e-05,
+ "loss": 0.4996,
+ "step": 4434
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.449530012344805e-05,
+ "loss": 0.5047,
+ "step": 4435
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4492879294675297e-05,
+ "loss": 0.4677,
+ "step": 4436
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4490458135964173e-05,
+ "loss": 0.4872,
+ "step": 4437
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4488036647492482e-05,
+ "loss": 0.4731,
+ "step": 4438
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4485614829438046e-05,
+ "loss": 0.4759,
+ "step": 4439
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4483192681978715e-05,
+ "loss": 0.4946,
+ "step": 4440
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4480770205292363e-05,
+ "loss": 0.4783,
+ "step": 4441
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4478347399556878e-05,
+ "loss": 0.4796,
+ "step": 4442
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.447592426495019e-05,
+ "loss": 0.495,
+ "step": 4443
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4473500801650243e-05,
+ "loss": 0.4885,
+ "step": 4444
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4471077009835001e-05,
+ "loss": 0.4771,
+ "step": 4445
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.446865288968246e-05,
+ "loss": 0.4934,
+ "step": 4446
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4466228441370638e-05,
+ "loss": 0.5003,
+ "step": 4447
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4463803665077573e-05,
+ "loss": 0.4921,
+ "step": 4448
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4461378560981335e-05,
+ "loss": 0.4844,
+ "step": 4449
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4458953129260014e-05,
+ "loss": 0.484,
+ "step": 4450
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4456527370091722e-05,
+ "loss": 0.477,
+ "step": 4451
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4454101283654594e-05,
+ "loss": 0.4759,
+ "step": 4452
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.445167487012679e-05,
+ "loss": 0.4673,
+ "step": 4453
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4449248129686504e-05,
+ "loss": 0.4975,
+ "step": 4454
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4446821062511942e-05,
+ "loss": 0.5007,
+ "step": 4455
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4444393668781334e-05,
+ "loss": 0.5061,
+ "step": 4456
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4441965948672943e-05,
+ "loss": 0.4783,
+ "step": 4457
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4439537902365047e-05,
+ "loss": 0.5025,
+ "step": 4458
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4437109530035951e-05,
+ "loss": 0.4762,
+ "step": 4459
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.443468083186399e-05,
+ "loss": 0.503,
+ "step": 4460
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.443225180802751e-05,
+ "loss": 0.4933,
+ "step": 4461
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4429822458704896e-05,
+ "loss": 0.4887,
+ "step": 4462
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4427392784074545e-05,
+ "loss": 0.4973,
+ "step": 4463
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.442496278431488e-05,
+ "loss": 0.5274,
+ "step": 4464
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4422532459604357e-05,
+ "loss": 0.4956,
+ "step": 4465
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.442010181012144e-05,
+ "loss": 0.4856,
+ "step": 4466
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4417670836044635e-05,
+ "loss": 0.5036,
+ "step": 4467
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4415239537552457e-05,
+ "loss": 0.5218,
+ "step": 4468
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4412807914823452e-05,
+ "loss": 0.4733,
+ "step": 4469
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4410375968036185e-05,
+ "loss": 0.4742,
+ "step": 4470
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4407943697369255e-05,
+ "loss": 0.4971,
+ "step": 4471
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4405511103001274e-05,
+ "loss": 0.4941,
+ "step": 4472
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.440307818511088e-05,
+ "loss": 0.4734,
+ "step": 4473
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4400644943876736e-05,
+ "loss": 0.494,
+ "step": 4474
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4398211379477534e-05,
+ "loss": 0.5102,
+ "step": 4475
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.439577749209198e-05,
+ "loss": 0.4926,
+ "step": 4476
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.439334328189881e-05,
+ "loss": 0.4995,
+ "step": 4477
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4390908749076787e-05,
+ "loss": 0.5003,
+ "step": 4478
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4388473893804683e-05,
+ "loss": 0.5023,
+ "step": 4479
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.438603871626131e-05,
+ "loss": 0.4786,
+ "step": 4480
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4383603216625499e-05,
+ "loss": 0.4957,
+ "step": 4481
+ },
+ {
+ "epoch": 0.37,
+ "learning_rate": 1.4381167395076101e-05,
+ "loss": 0.5121,
+ "step": 4482
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4378731251791989e-05,
+ "loss": 0.4638,
+ "step": 4483
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4376294786952067e-05,
+ "loss": 0.4954,
+ "step": 4484
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4373858000735262e-05,
+ "loss": 0.4954,
+ "step": 4485
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4371420893320515e-05,
+ "loss": 0.4881,
+ "step": 4486
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4368983464886799e-05,
+ "loss": 0.5036,
+ "step": 4487
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4366545715613112e-05,
+ "loss": 0.4723,
+ "step": 4488
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4364107645678465e-05,
+ "loss": 0.4846,
+ "step": 4489
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4361669255261905e-05,
+ "loss": 0.4819,
+ "step": 4490
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.43592305445425e-05,
+ "loss": 0.4875,
+ "step": 4491
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4356791513699334e-05,
+ "loss": 0.4895,
+ "step": 4492
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4354352162911522e-05,
+ "loss": 0.4762,
+ "step": 4493
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4351912492358196e-05,
+ "loss": 0.4905,
+ "step": 4494
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4349472502218515e-05,
+ "loss": 0.4592,
+ "step": 4495
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4347032192671668e-05,
+ "loss": 0.4966,
+ "step": 4496
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4344591563896857e-05,
+ "loss": 0.4847,
+ "step": 4497
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4342150616073312e-05,
+ "loss": 0.4795,
+ "step": 4498
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4339709349380285e-05,
+ "loss": 0.5128,
+ "step": 4499
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4337267763997054e-05,
+ "loss": 0.4757,
+ "step": 4500
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4334825860102917e-05,
+ "loss": 0.4912,
+ "step": 4501
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4332383637877203e-05,
+ "loss": 0.4773,
+ "step": 4502
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.432994109749925e-05,
+ "loss": 0.4955,
+ "step": 4503
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4327498239148434e-05,
+ "loss": 0.4786,
+ "step": 4504
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4325055063004145e-05,
+ "loss": 0.4953,
+ "step": 4505
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4322611569245806e-05,
+ "loss": 0.4892,
+ "step": 4506
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4320167758052848e-05,
+ "loss": 0.4917,
+ "step": 4507
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4317723629604743e-05,
+ "loss": 0.4832,
+ "step": 4508
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.431527918408097e-05,
+ "loss": 0.4878,
+ "step": 4509
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4312834421661044e-05,
+ "loss": 0.4948,
+ "step": 4510
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4310389342524494e-05,
+ "loss": 0.4869,
+ "step": 4511
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4307943946850883e-05,
+ "loss": 0.491,
+ "step": 4512
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4305498234819783e-05,
+ "loss": 0.4886,
+ "step": 4513
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4303052206610801e-05,
+ "loss": 0.4815,
+ "step": 4514
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4300605862403563e-05,
+ "loss": 0.4738,
+ "step": 4515
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4298159202377719e-05,
+ "loss": 0.5164,
+ "step": 4516
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4295712226712941e-05,
+ "loss": 0.4937,
+ "step": 4517
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4293264935588921e-05,
+ "loss": 0.4743,
+ "step": 4518
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4290817329185388e-05,
+ "loss": 0.4843,
+ "step": 4519
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.428836940768207e-05,
+ "loss": 0.4989,
+ "step": 4520
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4285921171258741e-05,
+ "loss": 0.4858,
+ "step": 4521
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4283472620095192e-05,
+ "loss": 0.477,
+ "step": 4522
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4281023754371226e-05,
+ "loss": 0.4741,
+ "step": 4523
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4278574574266681e-05,
+ "loss": 0.4952,
+ "step": 4524
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4276125079961417e-05,
+ "loss": 0.4953,
+ "step": 4525
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4273675271635313e-05,
+ "loss": 0.5021,
+ "step": 4526
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4271225149468272e-05,
+ "loss": 0.4825,
+ "step": 4527
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.426877471364022e-05,
+ "loss": 0.4693,
+ "step": 4528
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4266323964331112e-05,
+ "loss": 0.4788,
+ "step": 4529
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4263872901720914e-05,
+ "loss": 0.469,
+ "step": 4530
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4261421525989625e-05,
+ "loss": 0.4949,
+ "step": 4531
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4258969837317265e-05,
+ "loss": 0.4905,
+ "step": 4532
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4256517835883874e-05,
+ "loss": 0.488,
+ "step": 4533
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4254065521869519e-05,
+ "loss": 0.5049,
+ "step": 4534
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4251612895454282e-05,
+ "loss": 0.5057,
+ "step": 4535
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4249159956818279e-05,
+ "loss": 0.4912,
+ "step": 4536
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4246706706141646e-05,
+ "loss": 0.5032,
+ "step": 4537
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4244253143604531e-05,
+ "loss": 0.4765,
+ "step": 4538
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4241799269387122e-05,
+ "loss": 0.4854,
+ "step": 4539
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4239345083669615e-05,
+ "loss": 0.4815,
+ "step": 4540
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.423689058663224e-05,
+ "loss": 0.5124,
+ "step": 4541
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4234435778455242e-05,
+ "loss": 0.4851,
+ "step": 4542
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4231980659318891e-05,
+ "loss": 0.5049,
+ "step": 4543
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4229525229403486e-05,
+ "loss": 0.4756,
+ "step": 4544
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4227069488889338e-05,
+ "loss": 0.4865,
+ "step": 4545
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.422461343795679e-05,
+ "loss": 0.4887,
+ "step": 4546
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4222157076786201e-05,
+ "loss": 0.4804,
+ "step": 4547
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4219700405557958e-05,
+ "loss": 0.4999,
+ "step": 4548
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4217243424452466e-05,
+ "loss": 0.4974,
+ "step": 4549
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4214786133650162e-05,
+ "loss": 0.5029,
+ "step": 4550
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4212328533331493e-05,
+ "loss": 0.4983,
+ "step": 4551
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4209870623676934e-05,
+ "loss": 0.5079,
+ "step": 4552
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4207412404866992e-05,
+ "loss": 0.5062,
+ "step": 4553
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.420495387708218e-05,
+ "loss": 0.496,
+ "step": 4554
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4202495040503043e-05,
+ "loss": 0.5021,
+ "step": 4555
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4200035895310151e-05,
+ "loss": 0.492,
+ "step": 4556
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4197576441684096e-05,
+ "loss": 0.4871,
+ "step": 4557
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4195116679805483e-05,
+ "loss": 0.4845,
+ "step": 4558
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4192656609854949e-05,
+ "loss": 0.4746,
+ "step": 4559
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4190196232013154e-05,
+ "loss": 0.486,
+ "step": 4560
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4187735546460775e-05,
+ "loss": 0.4918,
+ "step": 4561
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4185274553378513e-05,
+ "loss": 0.5124,
+ "step": 4562
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.41828132529471e-05,
+ "loss": 0.4785,
+ "step": 4563
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4180351645347279e-05,
+ "loss": 0.4927,
+ "step": 4564
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.417788973075982e-05,
+ "loss": 0.5018,
+ "step": 4565
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4175427509365516e-05,
+ "loss": 0.4941,
+ "step": 4566
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.417296498134518e-05,
+ "loss": 0.4783,
+ "step": 4567
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4170502146879656e-05,
+ "loss": 0.5057,
+ "step": 4568
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4168039006149799e-05,
+ "loss": 0.5271,
+ "step": 4569
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4165575559336496e-05,
+ "loss": 0.4779,
+ "step": 4570
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4163111806620646e-05,
+ "loss": 0.4642,
+ "step": 4571
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.416064774818318e-05,
+ "loss": 0.5108,
+ "step": 4572
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4158183384205052e-05,
+ "loss": 0.4914,
+ "step": 4573
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4155718714867232e-05,
+ "loss": 0.4902,
+ "step": 4574
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4153253740350717e-05,
+ "loss": 0.4846,
+ "step": 4575
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4150788460836516e-05,
+ "loss": 0.4685,
+ "step": 4576
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4148322876505675e-05,
+ "loss": 0.4808,
+ "step": 4577
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4145856987539261e-05,
+ "loss": 0.4915,
+ "step": 4578
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.414339079411835e-05,
+ "loss": 0.4938,
+ "step": 4579
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4140924296424055e-05,
+ "loss": 0.4984,
+ "step": 4580
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4138457494637501e-05,
+ "loss": 0.4884,
+ "step": 4581
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4135990388939839e-05,
+ "loss": 0.4833,
+ "step": 4582
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4133522979512252e-05,
+ "loss": 0.4856,
+ "step": 4583
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4131055266535926e-05,
+ "loss": 0.4952,
+ "step": 4584
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4128587250192087e-05,
+ "loss": 0.5056,
+ "step": 4585
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.412611893066197e-05,
+ "loss": 0.4818,
+ "step": 4586
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4123650308126839e-05,
+ "loss": 0.4854,
+ "step": 4587
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4121181382767986e-05,
+ "loss": 0.4762,
+ "step": 4588
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4118712154766708e-05,
+ "loss": 0.4713,
+ "step": 4589
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4116242624304343e-05,
+ "loss": 0.4836,
+ "step": 4590
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.411377279156224e-05,
+ "loss": 0.4767,
+ "step": 4591
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4111302656721775e-05,
+ "loss": 0.4845,
+ "step": 4592
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.410883221996434e-05,
+ "loss": 0.4769,
+ "step": 4593
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.410636148147136e-05,
+ "loss": 0.4906,
+ "step": 4594
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4103890441424271e-05,
+ "loss": 0.4971,
+ "step": 4595
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4101419100004537e-05,
+ "loss": 0.481,
+ "step": 4596
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4098947457393641e-05,
+ "loss": 0.4774,
+ "step": 4597
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4096475513773097e-05,
+ "loss": 0.4893,
+ "step": 4598
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4094003269324428e-05,
+ "loss": 0.4874,
+ "step": 4599
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.4091530724229188e-05,
+ "loss": 0.5024,
+ "step": 4600
+ },
+ {
+ "epoch": 0.38,
+ "learning_rate": 1.408905787866895e-05,
+ "loss": 0.5141,
+ "step": 4601
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4086584732825306e-05,
+ "loss": 0.4768,
+ "step": 4602
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4084111286879878e-05,
+ "loss": 0.5029,
+ "step": 4603
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4081637541014306e-05,
+ "loss": 0.4939,
+ "step": 4604
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4079163495410248e-05,
+ "loss": 0.4798,
+ "step": 4605
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.407668915024939e-05,
+ "loss": 0.4618,
+ "step": 4606
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4074214505713437e-05,
+ "loss": 0.4803,
+ "step": 4607
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4071739561984115e-05,
+ "loss": 0.4847,
+ "step": 4608
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4069264319243178e-05,
+ "loss": 0.4754,
+ "step": 4609
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4066788777672393e-05,
+ "loss": 0.5171,
+ "step": 4610
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4064312937453556e-05,
+ "loss": 0.4757,
+ "step": 4611
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.406183679876848e-05,
+ "loss": 0.5263,
+ "step": 4612
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4059360361799004e-05,
+ "loss": 0.4928,
+ "step": 4613
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4056883626726989e-05,
+ "loss": 0.4916,
+ "step": 4614
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4054406593734316e-05,
+ "loss": 0.482,
+ "step": 4615
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4051929263002884e-05,
+ "loss": 0.4772,
+ "step": 4616
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.404945163471462e-05,
+ "loss": 0.4909,
+ "step": 4617
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4046973709051467e-05,
+ "loss": 0.4879,
+ "step": 4618
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4044495486195404e-05,
+ "loss": 0.492,
+ "step": 4619
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4042016966328411e-05,
+ "loss": 0.4755,
+ "step": 4620
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4039538149632508e-05,
+ "loss": 0.526,
+ "step": 4621
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4037059036289722e-05,
+ "loss": 0.4765,
+ "step": 4622
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4034579626482112e-05,
+ "loss": 0.4763,
+ "step": 4623
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4032099920391753e-05,
+ "loss": 0.4879,
+ "step": 4624
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.402961991820075e-05,
+ "loss": 0.4795,
+ "step": 4625
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4027139620091221e-05,
+ "loss": 0.4731,
+ "step": 4626
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4024659026245307e-05,
+ "loss": 0.4775,
+ "step": 4627
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4022178136845173e-05,
+ "loss": 0.5075,
+ "step": 4628
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4019696952073008e-05,
+ "loss": 0.4915,
+ "step": 4629
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4017215472111016e-05,
+ "loss": 0.4835,
+ "step": 4630
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.401473369714143e-05,
+ "loss": 0.4964,
+ "step": 4631
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.40122516273465e-05,
+ "loss": 0.4938,
+ "step": 4632
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4009769262908498e-05,
+ "loss": 0.4688,
+ "step": 4633
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.4007286604009717e-05,
+ "loss": 0.4844,
+ "step": 4634
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.400480365083248e-05,
+ "loss": 0.5028,
+ "step": 4635
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.400232040355912e-05,
+ "loss": 0.4694,
+ "step": 4636
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3999836862371992e-05,
+ "loss": 0.5068,
+ "step": 4637
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3997353027453484e-05,
+ "loss": 0.526,
+ "step": 4638
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3994868898985996e-05,
+ "loss": 0.5087,
+ "step": 4639
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.399238447715195e-05,
+ "loss": 0.4647,
+ "step": 4640
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3989899762133797e-05,
+ "loss": 0.5089,
+ "step": 4641
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3987414754114e-05,
+ "loss": 0.477,
+ "step": 4642
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3984929453275045e-05,
+ "loss": 0.4633,
+ "step": 4643
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3982443859799446e-05,
+ "loss": 0.4792,
+ "step": 4644
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3979957973869738e-05,
+ "loss": 0.508,
+ "step": 4645
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.397747179566847e-05,
+ "loss": 0.4722,
+ "step": 4646
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3974985325378215e-05,
+ "loss": 0.4924,
+ "step": 4647
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.397249856318157e-05,
+ "loss": 0.4871,
+ "step": 4648
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3970011509261155e-05,
+ "loss": 0.4978,
+ "step": 4649
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3967524163799606e-05,
+ "loss": 0.4922,
+ "step": 4650
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3965036526979586e-05,
+ "loss": 0.4957,
+ "step": 4651
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3962548598983774e-05,
+ "loss": 0.4908,
+ "step": 4652
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3960060379994875e-05,
+ "loss": 0.489,
+ "step": 4653
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.395757187019561e-05,
+ "loss": 0.4736,
+ "step": 4654
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3955083069768733e-05,
+ "loss": 0.4822,
+ "step": 4655
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3952593978897002e-05,
+ "loss": 0.4798,
+ "step": 4656
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3950104597763212e-05,
+ "loss": 0.4925,
+ "step": 4657
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3947614926550168e-05,
+ "loss": 0.4817,
+ "step": 4658
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3945124965440701e-05,
+ "loss": 0.4935,
+ "step": 4659
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3942634714617671e-05,
+ "loss": 0.5021,
+ "step": 4660
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3940144174263943e-05,
+ "loss": 0.492,
+ "step": 4661
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3937653344562417e-05,
+ "loss": 0.4698,
+ "step": 4662
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3935162225696006e-05,
+ "loss": 0.4974,
+ "step": 4663
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3932670817847647e-05,
+ "loss": 0.4825,
+ "step": 4664
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3930179121200303e-05,
+ "loss": 0.4825,
+ "step": 4665
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.392768713593695e-05,
+ "loss": 0.4866,
+ "step": 4666
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3925194862240589e-05,
+ "loss": 0.498,
+ "step": 4667
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3922702300294246e-05,
+ "loss": 0.4945,
+ "step": 4668
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3920209450280959e-05,
+ "loss": 0.4962,
+ "step": 4669
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3917716312383797e-05,
+ "loss": 0.4794,
+ "step": 4670
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3915222886785844e-05,
+ "loss": 0.4718,
+ "step": 4671
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3912729173670207e-05,
+ "loss": 0.485,
+ "step": 4672
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3910235173220015e-05,
+ "loss": 0.4924,
+ "step": 4673
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3907740885618415e-05,
+ "loss": 0.4844,
+ "step": 4674
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3905246311048575e-05,
+ "loss": 0.4807,
+ "step": 4675
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3902751449693693e-05,
+ "loss": 0.4933,
+ "step": 4676
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3900256301736976e-05,
+ "loss": 0.4699,
+ "step": 4677
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3897760867361657e-05,
+ "loss": 0.4775,
+ "step": 4678
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3895265146750994e-05,
+ "loss": 0.4956,
+ "step": 4679
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3892769140088259e-05,
+ "loss": 0.4707,
+ "step": 4680
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3890272847556747e-05,
+ "loss": 0.4774,
+ "step": 4681
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3887776269339783e-05,
+ "loss": 0.4832,
+ "step": 4682
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38852794056207e-05,
+ "loss": 0.4933,
+ "step": 4683
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3882782256582852e-05,
+ "loss": 0.4934,
+ "step": 4684
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.388028482240963e-05,
+ "loss": 0.4822,
+ "step": 4685
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3877787103284428e-05,
+ "loss": 0.4891,
+ "step": 4686
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3875289099390672e-05,
+ "loss": 0.4905,
+ "step": 4687
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38727908109118e-05,
+ "loss": 0.5032,
+ "step": 4688
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3870292238031283e-05,
+ "loss": 0.4791,
+ "step": 4689
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3867793380932597e-05,
+ "loss": 0.4809,
+ "step": 4690
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3865294239799254e-05,
+ "loss": 0.4697,
+ "step": 4691
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.386279481481478e-05,
+ "loss": 0.5101,
+ "step": 4692
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3860295106162722e-05,
+ "loss": 0.477,
+ "step": 4693
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3857795114026648e-05,
+ "loss": 0.4973,
+ "step": 4694
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3855294838590143e-05,
+ "loss": 0.4843,
+ "step": 4695
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3852794280036823e-05,
+ "loss": 0.4937,
+ "step": 4696
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3850293438550317e-05,
+ "loss": 0.481,
+ "step": 4697
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3847792314314272e-05,
+ "loss": 0.4813,
+ "step": 4698
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3845290907512367e-05,
+ "loss": 0.4771,
+ "step": 4699
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3842789218328289e-05,
+ "loss": 0.5068,
+ "step": 4700
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3840287246945759e-05,
+ "loss": 0.4914,
+ "step": 4701
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38377849935485e-05,
+ "loss": 0.4749,
+ "step": 4702
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3835282458320278e-05,
+ "loss": 0.4946,
+ "step": 4703
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3832779641444864e-05,
+ "loss": 0.4967,
+ "step": 4704
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3830276543106053e-05,
+ "loss": 0.4846,
+ "step": 4705
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3827773163487663e-05,
+ "loss": 0.4776,
+ "step": 4706
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3825269502773538e-05,
+ "loss": 0.505,
+ "step": 4707
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3822765561147529e-05,
+ "loss": 0.465,
+ "step": 4708
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3820261338793515e-05,
+ "loss": 0.4896,
+ "step": 4709
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3817756835895399e-05,
+ "loss": 0.5086,
+ "step": 4710
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.38152520526371e-05,
+ "loss": 0.5081,
+ "step": 4711
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3812746989202559e-05,
+ "loss": 0.4698,
+ "step": 4712
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3810241645775738e-05,
+ "loss": 0.497,
+ "step": 4713
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.380773602254062e-05,
+ "loss": 0.4849,
+ "step": 4714
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3805230119681203e-05,
+ "loss": 0.4766,
+ "step": 4715
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3802723937381512e-05,
+ "loss": 0.4944,
+ "step": 4716
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3800217475825597e-05,
+ "loss": 0.489,
+ "step": 4717
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3797710735197516e-05,
+ "loss": 0.4637,
+ "step": 4718
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.379520371568135e-05,
+ "loss": 0.482,
+ "step": 4719
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3792696417461213e-05,
+ "loss": 0.5144,
+ "step": 4720
+ },
+ {
+ "epoch": 0.39,
+ "learning_rate": 1.3790188840721223e-05,
+ "loss": 0.4927,
+ "step": 4721
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.378768098564553e-05,
+ "loss": 0.4736,
+ "step": 4722
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3785172852418303e-05,
+ "loss": 0.4891,
+ "step": 4723
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3782664441223724e-05,
+ "loss": 0.495,
+ "step": 4724
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3780155752246e-05,
+ "loss": 0.4943,
+ "step": 4725
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3777646785669357e-05,
+ "loss": 0.4907,
+ "step": 4726
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3775137541678052e-05,
+ "loss": 0.4822,
+ "step": 4727
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3772628020456346e-05,
+ "loss": 0.4896,
+ "step": 4728
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3770118222188529e-05,
+ "loss": 0.4812,
+ "step": 4729
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3767608147058913e-05,
+ "loss": 0.4859,
+ "step": 4730
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3765097795251822e-05,
+ "loss": 0.4721,
+ "step": 4731
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.376258716695161e-05,
+ "loss": 0.4959,
+ "step": 4732
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.376007626234265e-05,
+ "loss": 0.4818,
+ "step": 4733
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3757565081609327e-05,
+ "loss": 0.4732,
+ "step": 4734
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3755053624936055e-05,
+ "loss": 0.4902,
+ "step": 4735
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.375254189250726e-05,
+ "loss": 0.4942,
+ "step": 4736
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3750029884507394e-05,
+ "loss": 0.4723,
+ "step": 4737
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3747517601120934e-05,
+ "loss": 0.5007,
+ "step": 4738
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3745005042532369e-05,
+ "loss": 0.5025,
+ "step": 4739
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.374249220892621e-05,
+ "loss": 0.4768,
+ "step": 4740
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3739979100486986e-05,
+ "loss": 0.494,
+ "step": 4741
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3737465717399259e-05,
+ "loss": 0.5006,
+ "step": 4742
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3734952059847589e-05,
+ "loss": 0.4787,
+ "step": 4743
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3732438128016578e-05,
+ "loss": 0.486,
+ "step": 4744
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3729923922090836e-05,
+ "loss": 0.5041,
+ "step": 4745
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3727409442254994e-05,
+ "loss": 0.4867,
+ "step": 4746
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3724894688693704e-05,
+ "loss": 0.5076,
+ "step": 4747
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3722379661591643e-05,
+ "loss": 0.5011,
+ "step": 4748
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3719864361133502e-05,
+ "loss": 0.4931,
+ "step": 4749
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3717348787503993e-05,
+ "loss": 0.4803,
+ "step": 4750
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3714832940887854e-05,
+ "loss": 0.4869,
+ "step": 4751
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3712316821469831e-05,
+ "loss": 0.4963,
+ "step": 4752
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3709800429434702e-05,
+ "loss": 0.4769,
+ "step": 4753
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.370728376496726e-05,
+ "loss": 0.477,
+ "step": 4754
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3704766828252321e-05,
+ "loss": 0.5086,
+ "step": 4755
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3702249619474712e-05,
+ "loss": 0.4896,
+ "step": 4756
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.369973213881929e-05,
+ "loss": 0.4693,
+ "step": 4757
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3697214386470932e-05,
+ "loss": 0.4847,
+ "step": 4758
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3694696362614524e-05,
+ "loss": 0.4807,
+ "step": 4759
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3692178067434982e-05,
+ "loss": 0.4717,
+ "step": 4760
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3689659501117243e-05,
+ "loss": 0.4815,
+ "step": 4761
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3687140663846252e-05,
+ "loss": 0.4829,
+ "step": 4762
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3684621555806988e-05,
+ "loss": 0.4869,
+ "step": 4763
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3682102177184444e-05,
+ "loss": 0.4915,
+ "step": 4764
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3679582528163633e-05,
+ "loss": 0.4821,
+ "step": 4765
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3677062608929583e-05,
+ "loss": 0.4984,
+ "step": 4766
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3674542419667347e-05,
+ "loss": 0.4911,
+ "step": 4767
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3672021960562001e-05,
+ "loss": 0.4761,
+ "step": 4768
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3669501231798638e-05,
+ "loss": 0.4801,
+ "step": 4769
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3666980233562364e-05,
+ "loss": 0.5164,
+ "step": 4770
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3664458966038314e-05,
+ "loss": 0.4852,
+ "step": 4771
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.366193742941164e-05,
+ "loss": 0.4944,
+ "step": 4772
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.365941562386751e-05,
+ "loss": 0.4886,
+ "step": 4773
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3656893549591121e-05,
+ "loss": 0.4837,
+ "step": 4774
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3654371206767678e-05,
+ "loss": 0.4903,
+ "step": 4775
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3651848595582416e-05,
+ "loss": 0.4611,
+ "step": 4776
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3649325716220579e-05,
+ "loss": 0.4914,
+ "step": 4777
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.364680256886744e-05,
+ "loss": 0.4672,
+ "step": 4778
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.364427915370829e-05,
+ "loss": 0.4768,
+ "step": 4779
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3641755470928435e-05,
+ "loss": 0.4871,
+ "step": 4780
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3639231520713207e-05,
+ "loss": 0.4953,
+ "step": 4781
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3636707303247953e-05,
+ "loss": 0.4642,
+ "step": 4782
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.363418281871804e-05,
+ "loss": 0.5042,
+ "step": 4783
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3631658067308857e-05,
+ "loss": 0.485,
+ "step": 4784
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.362913304920581e-05,
+ "loss": 0.4988,
+ "step": 4785
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3626607764594329e-05,
+ "loss": 0.4921,
+ "step": 4786
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3624082213659854e-05,
+ "loss": 0.5012,
+ "step": 4787
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3621556396587856e-05,
+ "loss": 0.4926,
+ "step": 4788
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3619030313563821e-05,
+ "loss": 0.4879,
+ "step": 4789
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3616503964773252e-05,
+ "loss": 0.4911,
+ "step": 4790
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3613977350401675e-05,
+ "loss": 0.4665,
+ "step": 4791
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3611450470634631e-05,
+ "loss": 0.4938,
+ "step": 4792
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3608923325657686e-05,
+ "loss": 0.4847,
+ "step": 4793
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3606395915656423e-05,
+ "loss": 0.5109,
+ "step": 4794
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3603868240816445e-05,
+ "loss": 0.4765,
+ "step": 4795
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3601340301323371e-05,
+ "loss": 0.4859,
+ "step": 4796
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3598812097362846e-05,
+ "loss": 0.505,
+ "step": 4797
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3596283629120527e-05,
+ "loss": 0.5041,
+ "step": 4798
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3593754896782099e-05,
+ "loss": 0.4924,
+ "step": 4799
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.359122590053326e-05,
+ "loss": 0.467,
+ "step": 4800
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3588696640559725e-05,
+ "loss": 0.5029,
+ "step": 4801
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3586167117047238e-05,
+ "loss": 0.4932,
+ "step": 4802
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.358363733018155e-05,
+ "loss": 0.4759,
+ "step": 4803
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3581107280148443e-05,
+ "loss": 0.5209,
+ "step": 4804
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3578576967133712e-05,
+ "loss": 0.4676,
+ "step": 4805
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3576046391323176e-05,
+ "loss": 0.4666,
+ "step": 4806
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3573515552902663e-05,
+ "loss": 0.4912,
+ "step": 4807
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3570984452058035e-05,
+ "loss": 0.4882,
+ "step": 4808
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.356845308897516e-05,
+ "loss": 0.475,
+ "step": 4809
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3565921463839934e-05,
+ "loss": 0.4938,
+ "step": 4810
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3563389576838264e-05,
+ "loss": 0.4858,
+ "step": 4811
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3560857428156086e-05,
+ "loss": 0.4817,
+ "step": 4812
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.355832501797935e-05,
+ "loss": 0.5182,
+ "step": 4813
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3555792346494023e-05,
+ "loss": 0.5071,
+ "step": 4814
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.35532594138861e-05,
+ "loss": 0.486,
+ "step": 4815
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.355072622034158e-05,
+ "loss": 0.4677,
+ "step": 4816
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3548192766046499e-05,
+ "loss": 0.4871,
+ "step": 4817
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3545659051186897e-05,
+ "loss": 0.505,
+ "step": 4818
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3543125075948842e-05,
+ "loss": 0.4679,
+ "step": 4819
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.354059084051842e-05,
+ "loss": 0.518,
+ "step": 4820
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3538056345081729e-05,
+ "loss": 0.4902,
+ "step": 4821
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.35355215898249e-05,
+ "loss": 0.4813,
+ "step": 4822
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3532986574934071e-05,
+ "loss": 0.4975,
+ "step": 4823
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.35304513005954e-05,
+ "loss": 0.4795,
+ "step": 4824
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.352791576699507e-05,
+ "loss": 0.4782,
+ "step": 4825
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3525379974319282e-05,
+ "loss": 0.491,
+ "step": 4826
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.352284392275425e-05,
+ "loss": 0.4788,
+ "step": 4827
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3520307612486211e-05,
+ "loss": 0.4711,
+ "step": 4828
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3517771043701427e-05,
+ "loss": 0.4901,
+ "step": 4829
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3515234216586169e-05,
+ "loss": 0.4877,
+ "step": 4830
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3512697131326726e-05,
+ "loss": 0.4863,
+ "step": 4831
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.351015978810942e-05,
+ "loss": 0.4971,
+ "step": 4832
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3507622187120582e-05,
+ "loss": 0.4835,
+ "step": 4833
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3505084328546554e-05,
+ "loss": 0.4859,
+ "step": 4834
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3502546212573715e-05,
+ "loss": 0.4858,
+ "step": 4835
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.350000783938845e-05,
+ "loss": 0.4833,
+ "step": 4836
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3497469209177166e-05,
+ "loss": 0.4879,
+ "step": 4837
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.349493032212629e-05,
+ "loss": 0.4848,
+ "step": 4838
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3492391178422271e-05,
+ "loss": 0.4863,
+ "step": 4839
+ },
+ {
+ "epoch": 0.4,
+ "learning_rate": 1.3489851778251563e-05,
+ "loss": 0.48,
+ "step": 4840
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3487312121800661e-05,
+ "loss": 0.4777,
+ "step": 4841
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3484772209256061e-05,
+ "loss": 0.4783,
+ "step": 4842
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3482232040804286e-05,
+ "loss": 0.5042,
+ "step": 4843
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3479691616631869e-05,
+ "loss": 0.4642,
+ "step": 4844
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3477150936925374e-05,
+ "loss": 0.4839,
+ "step": 4845
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3474610001871379e-05,
+ "loss": 0.4922,
+ "step": 4846
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3472068811656477e-05,
+ "loss": 0.4956,
+ "step": 4847
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3469527366467281e-05,
+ "loss": 0.479,
+ "step": 4848
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3466985666490428e-05,
+ "loss": 0.502,
+ "step": 4849
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3464443711912566e-05,
+ "loss": 0.4734,
+ "step": 4850
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3461901502920371e-05,
+ "loss": 0.4976,
+ "step": 4851
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3459359039700525e-05,
+ "loss": 0.4828,
+ "step": 4852
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3456816322439742e-05,
+ "loss": 0.488,
+ "step": 4853
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3454273351324747e-05,
+ "loss": 0.4822,
+ "step": 4854
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.345173012654228e-05,
+ "loss": 0.4855,
+ "step": 4855
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3449186648279114e-05,
+ "loss": 0.4978,
+ "step": 4856
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3446642916722027e-05,
+ "loss": 0.4827,
+ "step": 4857
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3444098932057818e-05,
+ "loss": 0.5126,
+ "step": 4858
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3441554694473307e-05,
+ "loss": 0.4707,
+ "step": 4859
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3439010204155334e-05,
+ "loss": 0.5114,
+ "step": 4860
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3436465461290757e-05,
+ "loss": 0.5015,
+ "step": 4861
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.343392046606645e-05,
+ "loss": 0.4831,
+ "step": 4862
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3431375218669307e-05,
+ "loss": 0.4898,
+ "step": 4863
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.342882971928624e-05,
+ "loss": 0.4893,
+ "step": 4864
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3426283968104178e-05,
+ "loss": 0.4799,
+ "step": 4865
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3423737965310073e-05,
+ "loss": 0.4845,
+ "step": 4866
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3421191711090895e-05,
+ "loss": 0.4986,
+ "step": 4867
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3418645205633625e-05,
+ "loss": 0.4814,
+ "step": 4868
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.341609844912527e-05,
+ "loss": 0.4772,
+ "step": 4869
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3413551441752855e-05,
+ "loss": 0.4904,
+ "step": 4870
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.341100418370342e-05,
+ "loss": 0.4926,
+ "step": 4871
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3408456675164023e-05,
+ "loss": 0.4714,
+ "step": 4872
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3405908916321748e-05,
+ "loss": 0.471,
+ "step": 4873
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3403360907363687e-05,
+ "loss": 0.5065,
+ "step": 4874
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3400812648476956e-05,
+ "loss": 0.4832,
+ "step": 4875
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3398264139848687e-05,
+ "loss": 0.4877,
+ "step": 4876
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3395715381666038e-05,
+ "loss": 0.4762,
+ "step": 4877
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3393166374116175e-05,
+ "loss": 0.4868,
+ "step": 4878
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3390617117386285e-05,
+ "loss": 0.4823,
+ "step": 4879
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3388067611663578e-05,
+ "loss": 0.4737,
+ "step": 4880
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3385517857135274e-05,
+ "loss": 0.4901,
+ "step": 4881
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3382967853988623e-05,
+ "loss": 0.4653,
+ "step": 4882
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3380417602410884e-05,
+ "loss": 0.4864,
+ "step": 4883
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3377867102589336e-05,
+ "loss": 0.4931,
+ "step": 4884
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3375316354711277e-05,
+ "loss": 0.4761,
+ "step": 4885
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3372765358964024e-05,
+ "loss": 0.489,
+ "step": 4886
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3370214115534912e-05,
+ "loss": 0.4897,
+ "step": 4887
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3367662624611293e-05,
+ "loss": 0.4856,
+ "step": 4888
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3365110886380537e-05,
+ "loss": 0.5125,
+ "step": 4889
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3362558901030035e-05,
+ "loss": 0.4959,
+ "step": 4890
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3360006668747195e-05,
+ "loss": 0.4597,
+ "step": 4891
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3357454189719437e-05,
+ "loss": 0.5056,
+ "step": 4892
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3354901464134208e-05,
+ "loss": 0.4856,
+ "step": 4893
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3352348492178972e-05,
+ "loss": 0.4788,
+ "step": 4894
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3349795274041208e-05,
+ "loss": 0.4858,
+ "step": 4895
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3347241809908408e-05,
+ "loss": 0.4982,
+ "step": 4896
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3344688099968092e-05,
+ "loss": 0.4558,
+ "step": 4897
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3342134144407796e-05,
+ "loss": 0.482,
+ "step": 4898
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3339579943415069e-05,
+ "loss": 0.5045,
+ "step": 4899
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.333702549717748e-05,
+ "loss": 0.4684,
+ "step": 4900
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3334470805882615e-05,
+ "loss": 0.4804,
+ "step": 4901
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3331915869718088e-05,
+ "loss": 0.4914,
+ "step": 4902
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3329360688871518e-05,
+ "loss": 0.4885,
+ "step": 4903
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3326805263530545e-05,
+ "loss": 0.4959,
+ "step": 4904
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3324249593882832e-05,
+ "loss": 0.4996,
+ "step": 4905
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3321693680116054e-05,
+ "loss": 0.4728,
+ "step": 4906
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3319137522417908e-05,
+ "loss": 0.4861,
+ "step": 4907
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3316581120976109e-05,
+ "loss": 0.4854,
+ "step": 4908
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3314024475978388e-05,
+ "loss": 0.4933,
+ "step": 4909
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.331146758761249e-05,
+ "loss": 0.4676,
+ "step": 4910
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3308910456066191e-05,
+ "loss": 0.4983,
+ "step": 4911
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3306353081527265e-05,
+ "loss": 0.5059,
+ "step": 4912
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3303795464183522e-05,
+ "loss": 0.4859,
+ "step": 4913
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3301237604222786e-05,
+ "loss": 0.5003,
+ "step": 4914
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.329867950183289e-05,
+ "loss": 0.4709,
+ "step": 4915
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3296121157201689e-05,
+ "loss": 0.5096,
+ "step": 4916
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.329356257051706e-05,
+ "loss": 0.4888,
+ "step": 4917
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3291003741966898e-05,
+ "loss": 0.4876,
+ "step": 4918
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3288444671739106e-05,
+ "loss": 0.4887,
+ "step": 4919
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3285885360021615e-05,
+ "loss": 0.4732,
+ "step": 4920
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3283325807002374e-05,
+ "loss": 0.4874,
+ "step": 4921
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3280766012869338e-05,
+ "loss": 0.4845,
+ "step": 4922
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3278205977810492e-05,
+ "loss": 0.4866,
+ "step": 4923
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3275645702013836e-05,
+ "loss": 0.4692,
+ "step": 4924
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3273085185667385e-05,
+ "loss": 0.4743,
+ "step": 4925
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.327052442895917e-05,
+ "loss": 0.4811,
+ "step": 4926
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3267963432077242e-05,
+ "loss": 0.4902,
+ "step": 4927
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3265402195209675e-05,
+ "loss": 0.475,
+ "step": 4928
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3262840718544552e-05,
+ "loss": 0.4967,
+ "step": 4929
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3260279002269977e-05,
+ "loss": 0.4948,
+ "step": 4930
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3257717046574074e-05,
+ "loss": 0.467,
+ "step": 4931
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.325515485164498e-05,
+ "loss": 0.4723,
+ "step": 4932
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3252592417670856e-05,
+ "loss": 0.4997,
+ "step": 4933
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3250029744839867e-05,
+ "loss": 0.4764,
+ "step": 4934
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3247466833340216e-05,
+ "loss": 0.492,
+ "step": 4935
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.324490368336011e-05,
+ "loss": 0.4627,
+ "step": 4936
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.324234029508777e-05,
+ "loss": 0.484,
+ "step": 4937
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3239776668711444e-05,
+ "loss": 0.4789,
+ "step": 4938
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3237212804419398e-05,
+ "loss": 0.4715,
+ "step": 4939
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3234648702399903e-05,
+ "loss": 0.4995,
+ "step": 4940
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3232084362841267e-05,
+ "loss": 0.4747,
+ "step": 4941
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3229519785931795e-05,
+ "loss": 0.4898,
+ "step": 4942
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3226954971859827e-05,
+ "loss": 0.5059,
+ "step": 4943
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3224389920813703e-05,
+ "loss": 0.4816,
+ "step": 4944
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3221824632981797e-05,
+ "loss": 0.474,
+ "step": 4945
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3219259108552488e-05,
+ "loss": 0.4707,
+ "step": 4946
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3216693347714183e-05,
+ "loss": 0.4751,
+ "step": 4947
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3214127350655294e-05,
+ "loss": 0.4763,
+ "step": 4948
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3211561117564267e-05,
+ "loss": 0.517,
+ "step": 4949
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3208994648629546e-05,
+ "loss": 0.4788,
+ "step": 4950
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3206427944039604e-05,
+ "loss": 0.4886,
+ "step": 4951
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3203861003982933e-05,
+ "loss": 0.4797,
+ "step": 4952
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3201293828648032e-05,
+ "loss": 0.4796,
+ "step": 4953
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3198726418223428e-05,
+ "loss": 0.4591,
+ "step": 4954
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3196158772897663e-05,
+ "loss": 0.4763,
+ "step": 4955
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3193590892859291e-05,
+ "loss": 0.4906,
+ "step": 4956
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3191022778296887e-05,
+ "loss": 0.492,
+ "step": 4957
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.318845442939904e-05,
+ "loss": 0.4808,
+ "step": 4958
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3185885846354365e-05,
+ "loss": 0.495,
+ "step": 4959
+ },
+ {
+ "epoch": 0.41,
+ "learning_rate": 1.3183317029351483e-05,
+ "loss": 0.4769,
+ "step": 4960
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3180747978579039e-05,
+ "loss": 0.4781,
+ "step": 4961
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3178178694225695e-05,
+ "loss": 0.4663,
+ "step": 4962
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3175609176480122e-05,
+ "loss": 0.4681,
+ "step": 4963
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.317303942553102e-05,
+ "loss": 0.4945,
+ "step": 4964
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3170469441567104e-05,
+ "loss": 0.47,
+ "step": 4965
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3167899224777098e-05,
+ "loss": 0.4708,
+ "step": 4966
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.316532877534975e-05,
+ "loss": 0.5071,
+ "step": 4967
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.316275809347382e-05,
+ "loss": 0.4788,
+ "step": 4968
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.316018717933809e-05,
+ "loss": 0.4694,
+ "step": 4969
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3157616033131361e-05,
+ "loss": 0.4749,
+ "step": 4970
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.315504465504244e-05,
+ "loss": 0.4792,
+ "step": 4971
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3152473045260168e-05,
+ "loss": 0.4936,
+ "step": 4972
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3149901203973383e-05,
+ "loss": 0.5079,
+ "step": 4973
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3147329131370956e-05,
+ "loss": 0.4884,
+ "step": 4974
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3144756827641769e-05,
+ "loss": 0.4967,
+ "step": 4975
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3142184292974723e-05,
+ "loss": 0.48,
+ "step": 4976
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3139611527558729e-05,
+ "loss": 0.502,
+ "step": 4977
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3137038531582721e-05,
+ "loss": 0.4875,
+ "step": 4978
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3134465305235653e-05,
+ "loss": 0.4827,
+ "step": 4979
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3131891848706492e-05,
+ "loss": 0.479,
+ "step": 4980
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3129318162184216e-05,
+ "loss": 0.4702,
+ "step": 4981
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3126744245857835e-05,
+ "loss": 0.4727,
+ "step": 4982
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.312417009991636e-05,
+ "loss": 0.4882,
+ "step": 4983
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3121595724548825e-05,
+ "loss": 0.4865,
+ "step": 4984
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3119021119944287e-05,
+ "loss": 0.4924,
+ "step": 4985
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3116446286291811e-05,
+ "loss": 0.499,
+ "step": 4986
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3113871223780481e-05,
+ "loss": 0.4787,
+ "step": 4987
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3111295932599396e-05,
+ "loss": 0.478,
+ "step": 4988
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3108720412937681e-05,
+ "loss": 0.4822,
+ "step": 4989
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3106144664984473e-05,
+ "loss": 0.4804,
+ "step": 4990
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3103568688928917e-05,
+ "loss": 0.4707,
+ "step": 4991
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3100992484960185e-05,
+ "loss": 0.4968,
+ "step": 4992
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3098416053267463e-05,
+ "loss": 0.4693,
+ "step": 4993
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3095839394039953e-05,
+ "loss": 0.4758,
+ "step": 4994
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3093262507466873e-05,
+ "loss": 0.5018,
+ "step": 4995
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3090685393737464e-05,
+ "loss": 0.4784,
+ "step": 4996
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3088108053040974e-05,
+ "loss": 0.4755,
+ "step": 4997
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.308553048556667e-05,
+ "loss": 0.4867,
+ "step": 4998
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3082952691503843e-05,
+ "loss": 0.4803,
+ "step": 4999
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3080374671041793e-05,
+ "loss": 0.4798,
+ "step": 5000
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3077796424369842e-05,
+ "loss": 0.4852,
+ "step": 5001
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.307521795167732e-05,
+ "loss": 0.4841,
+ "step": 5002
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3072639253153583e-05,
+ "loss": 0.5082,
+ "step": 5003
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3070060328988e-05,
+ "loss": 0.4823,
+ "step": 5004
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3067481179369951e-05,
+ "loss": 0.4915,
+ "step": 5005
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.306490180448885e-05,
+ "loss": 0.5137,
+ "step": 5006
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3062322204534105e-05,
+ "loss": 0.509,
+ "step": 5007
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3059742379695158e-05,
+ "loss": 0.4846,
+ "step": 5008
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3057162330161453e-05,
+ "loss": 0.4945,
+ "step": 5009
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.305458205612246e-05,
+ "loss": 0.4883,
+ "step": 5010
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3052001557767671e-05,
+ "loss": 0.4953,
+ "step": 5011
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.304942083528658e-05,
+ "loss": 0.5003,
+ "step": 5012
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3046839888868706e-05,
+ "loss": 0.4656,
+ "step": 5013
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3044258718703581e-05,
+ "loss": 0.492,
+ "step": 5014
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.304167732498076e-05,
+ "loss": 0.4865,
+ "step": 5015
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3039095707889808e-05,
+ "loss": 0.486,
+ "step": 5016
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3036513867620309e-05,
+ "loss": 0.4977,
+ "step": 5017
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.303393180436186e-05,
+ "loss": 0.4894,
+ "step": 5018
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3031349518304078e-05,
+ "loss": 0.4717,
+ "step": 5019
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3028767009636593e-05,
+ "loss": 0.5052,
+ "step": 5020
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3026184278549062e-05,
+ "loss": 0.4768,
+ "step": 5021
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.302360132523114e-05,
+ "loss": 0.4759,
+ "step": 5022
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3021018149872516e-05,
+ "loss": 0.4861,
+ "step": 5023
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3018434752662882e-05,
+ "loss": 0.5004,
+ "step": 5024
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3015851133791955e-05,
+ "loss": 0.4867,
+ "step": 5025
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3013267293449463e-05,
+ "loss": 0.4708,
+ "step": 5026
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3010683231825158e-05,
+ "loss": 0.4981,
+ "step": 5027
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.30080989491088e-05,
+ "loss": 0.4881,
+ "step": 5028
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.300551444549016e-05,
+ "loss": 0.4787,
+ "step": 5029
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3002929721159043e-05,
+ "loss": 0.504,
+ "step": 5030
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.3000344776305258e-05,
+ "loss": 0.511,
+ "step": 5031
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2997759611118634e-05,
+ "loss": 0.4751,
+ "step": 5032
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2995174225789008e-05,
+ "loss": 0.5148,
+ "step": 5033
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2992588620506251e-05,
+ "loss": 0.5013,
+ "step": 5034
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2990002795460228e-05,
+ "loss": 0.4959,
+ "step": 5035
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2987416750840836e-05,
+ "loss": 0.4788,
+ "step": 5036
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2984830486837985e-05,
+ "loss": 0.4932,
+ "step": 5037
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2982244003641599e-05,
+ "loss": 0.487,
+ "step": 5038
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2979657301441615e-05,
+ "loss": 0.4873,
+ "step": 5039
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2977070380427993e-05,
+ "loss": 0.4762,
+ "step": 5040
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2974483240790705e-05,
+ "loss": 0.4804,
+ "step": 5041
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2971895882719741e-05,
+ "loss": 0.4935,
+ "step": 5042
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2969308306405102e-05,
+ "loss": 0.4742,
+ "step": 5043
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2966720512036813e-05,
+ "loss": 0.5088,
+ "step": 5044
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2964132499804907e-05,
+ "loss": 0.4828,
+ "step": 5045
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.296154426989944e-05,
+ "loss": 0.4859,
+ "step": 5046
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2958955822510482e-05,
+ "loss": 0.4948,
+ "step": 5047
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2956367157828113e-05,
+ "loss": 0.4609,
+ "step": 5048
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.295377827604244e-05,
+ "loss": 0.5,
+ "step": 5049
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.295118917734357e-05,
+ "loss": 0.4859,
+ "step": 5050
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2948599861921644e-05,
+ "loss": 0.4748,
+ "step": 5051
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2946010329966811e-05,
+ "loss": 0.4679,
+ "step": 5052
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2943420581669231e-05,
+ "loss": 0.4995,
+ "step": 5053
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2940830617219087e-05,
+ "loss": 0.5,
+ "step": 5054
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2938240436806575e-05,
+ "loss": 0.4732,
+ "step": 5055
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2935650040621901e-05,
+ "loss": 0.4839,
+ "step": 5056
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2933059428855303e-05,
+ "loss": 0.4713,
+ "step": 5057
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2930468601697022e-05,
+ "loss": 0.4795,
+ "step": 5058
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2927877559337311e-05,
+ "loss": 0.4778,
+ "step": 5059
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2925286301966451e-05,
+ "loss": 0.4813,
+ "step": 5060
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2922694829774733e-05,
+ "loss": 0.5003,
+ "step": 5061
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2920103142952465e-05,
+ "loss": 0.4835,
+ "step": 5062
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2917511241689963e-05,
+ "loss": 0.4714,
+ "step": 5063
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2914919126177576e-05,
+ "loss": 0.5055,
+ "step": 5064
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.291232679660565e-05,
+ "loss": 0.4942,
+ "step": 5065
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2909734253164557e-05,
+ "loss": 0.4614,
+ "step": 5066
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2907141496044679e-05,
+ "loss": 0.4689,
+ "step": 5067
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2904548525436429e-05,
+ "loss": 0.4843,
+ "step": 5068
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2901955341530213e-05,
+ "loss": 0.472,
+ "step": 5069
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2899361944516464e-05,
+ "loss": 0.489,
+ "step": 5070
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2896768334585635e-05,
+ "loss": 0.5033,
+ "step": 5071
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2894174511928189e-05,
+ "loss": 0.4797,
+ "step": 5072
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2891580476734602e-05,
+ "loss": 0.4992,
+ "step": 5073
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2888986229195375e-05,
+ "loss": 0.4896,
+ "step": 5074
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2886391769501016e-05,
+ "loss": 0.4872,
+ "step": 5075
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2883797097842048e-05,
+ "loss": 0.4663,
+ "step": 5076
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2881202214409016e-05,
+ "loss": 0.4954,
+ "step": 5077
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2878607119392479e-05,
+ "loss": 0.5041,
+ "step": 5078
+ },
+ {
+ "epoch": 0.42,
+ "learning_rate": 1.2876011812983009e-05,
+ "loss": 0.4777,
+ "step": 5079
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.287341629537119e-05,
+ "loss": 0.5026,
+ "step": 5080
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2870820566747633e-05,
+ "loss": 0.471,
+ "step": 5081
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2868224627302952e-05,
+ "loss": 0.4873,
+ "step": 5082
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2865628477227787e-05,
+ "loss": 0.488,
+ "step": 5083
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2863032116712781e-05,
+ "loss": 0.4907,
+ "step": 5084
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2860435545948609e-05,
+ "loss": 0.4816,
+ "step": 5085
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2857838765125945e-05,
+ "loss": 0.4917,
+ "step": 5086
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.285524177443549e-05,
+ "loss": 0.4916,
+ "step": 5087
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2852644574067955e-05,
+ "loss": 0.4771,
+ "step": 5088
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.285004716421407e-05,
+ "loss": 0.4911,
+ "step": 5089
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2847449545064572e-05,
+ "loss": 0.4913,
+ "step": 5090
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2844851716810225e-05,
+ "loss": 0.4803,
+ "step": 5091
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2842253679641799e-05,
+ "loss": 0.4891,
+ "step": 5092
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2839655433750084e-05,
+ "loss": 0.4777,
+ "step": 5093
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2837056979325886e-05,
+ "loss": 0.4791,
+ "step": 5094
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2834458316560023e-05,
+ "loss": 0.4653,
+ "step": 5095
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2831859445643333e-05,
+ "loss": 0.4935,
+ "step": 5096
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.282926036676666e-05,
+ "loss": 0.5006,
+ "step": 5097
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2826661080120877e-05,
+ "loss": 0.463,
+ "step": 5098
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.282406158589686e-05,
+ "loss": 0.4902,
+ "step": 5099
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2821461884285506e-05,
+ "loss": 0.4759,
+ "step": 5100
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2818861975477728e-05,
+ "loss": 0.4796,
+ "step": 5101
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2816261859664448e-05,
+ "loss": 0.4833,
+ "step": 5102
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2813661537036613e-05,
+ "loss": 0.4863,
+ "step": 5103
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2811061007785175e-05,
+ "loss": 0.4719,
+ "step": 5104
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2808460272101113e-05,
+ "loss": 0.4843,
+ "step": 5105
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.280585933017541e-05,
+ "loss": 0.4763,
+ "step": 5106
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2803258182199064e-05,
+ "loss": 0.4812,
+ "step": 5107
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2800656828363098e-05,
+ "loss": 0.4878,
+ "step": 5108
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2798055268858544e-05,
+ "loss": 0.4949,
+ "step": 5109
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2795453503876449e-05,
+ "loss": 0.5089,
+ "step": 5110
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2792851533607875e-05,
+ "loss": 0.482,
+ "step": 5111
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2790249358243902e-05,
+ "loss": 0.5057,
+ "step": 5112
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2787646977975623e-05,
+ "loss": 0.5177,
+ "step": 5113
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2785044392994142e-05,
+ "loss": 0.461,
+ "step": 5114
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2782441603490585e-05,
+ "loss": 0.479,
+ "step": 5115
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.277983860965609e-05,
+ "loss": 0.5029,
+ "step": 5116
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.277723541168181e-05,
+ "loss": 0.475,
+ "step": 5117
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2774632009758911e-05,
+ "loss": 0.4754,
+ "step": 5118
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2772028404078581e-05,
+ "loss": 0.483,
+ "step": 5119
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2769424594832014e-05,
+ "loss": 0.4806,
+ "step": 5120
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2766820582210421e-05,
+ "loss": 0.4651,
+ "step": 5121
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2764216366405036e-05,
+ "loss": 0.4875,
+ "step": 5122
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2761611947607095e-05,
+ "loss": 0.4948,
+ "step": 5123
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2759007326007862e-05,
+ "loss": 0.4835,
+ "step": 5124
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2756402501798606e-05,
+ "loss": 0.4828,
+ "step": 5125
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2753797475170613e-05,
+ "loss": 0.4781,
+ "step": 5126
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.275119224631519e-05,
+ "loss": 0.4875,
+ "step": 5127
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2748586815423646e-05,
+ "loss": 0.4688,
+ "step": 5128
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2745981182687323e-05,
+ "loss": 0.479,
+ "step": 5129
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2743375348297567e-05,
+ "loss": 0.4941,
+ "step": 5130
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.274076931244573e-05,
+ "loss": 0.5048,
+ "step": 5131
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2738163075323198e-05,
+ "loss": 0.4627,
+ "step": 5132
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2735556637121356e-05,
+ "loss": 0.4784,
+ "step": 5133
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2732949998031612e-05,
+ "loss": 0.4883,
+ "step": 5134
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2730343158245389e-05,
+ "loss": 0.4992,
+ "step": 5135
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2727736117954122e-05,
+ "loss": 0.4715,
+ "step": 5136
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.272512887734926e-05,
+ "loss": 0.4769,
+ "step": 5137
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2722521436622263e-05,
+ "loss": 0.5004,
+ "step": 5138
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2719913795964618e-05,
+ "loss": 0.4909,
+ "step": 5139
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.271730595556782e-05,
+ "loss": 0.4747,
+ "step": 5140
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2714697915623374e-05,
+ "loss": 0.4969,
+ "step": 5141
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2712089676322803e-05,
+ "loss": 0.479,
+ "step": 5142
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2709481237857643e-05,
+ "loss": 0.4771,
+ "step": 5143
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2706872600419456e-05,
+ "loss": 0.5098,
+ "step": 5144
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2704263764199803e-05,
+ "loss": 0.4819,
+ "step": 5145
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2701654729390264e-05,
+ "loss": 0.4838,
+ "step": 5146
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2699045496182442e-05,
+ "loss": 0.4829,
+ "step": 5147
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2696436064767943e-05,
+ "loss": 0.4952,
+ "step": 5148
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2693826435338394e-05,
+ "loss": 0.4854,
+ "step": 5149
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.269121660808544e-05,
+ "loss": 0.483,
+ "step": 5150
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2688606583200728e-05,
+ "loss": 0.4843,
+ "step": 5151
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2685996360875933e-05,
+ "loss": 0.4863,
+ "step": 5152
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2683385941302737e-05,
+ "loss": 0.4922,
+ "step": 5153
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2680775324672839e-05,
+ "loss": 0.4687,
+ "step": 5154
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2678164511177948e-05,
+ "loss": 0.494,
+ "step": 5155
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.26755535010098e-05,
+ "loss": 0.4872,
+ "step": 5156
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.267294229436013e-05,
+ "loss": 0.4892,
+ "step": 5157
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2670330891420694e-05,
+ "loss": 0.4867,
+ "step": 5158
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.266771929238326e-05,
+ "loss": 0.4676,
+ "step": 5159
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2665107497439623e-05,
+ "loss": 0.4976,
+ "step": 5160
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2662495506781575e-05,
+ "loss": 0.4855,
+ "step": 5161
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.265988332060093e-05,
+ "loss": 0.4878,
+ "step": 5162
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.265727093908952e-05,
+ "loss": 0.4841,
+ "step": 5163
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.265465836243918e-05,
+ "loss": 0.4876,
+ "step": 5164
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2652045590841774e-05,
+ "loss": 0.4905,
+ "step": 5165
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2649432624489171e-05,
+ "loss": 0.4761,
+ "step": 5166
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2646819463573257e-05,
+ "loss": 0.4716,
+ "step": 5167
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.264420610828593e-05,
+ "loss": 0.4791,
+ "step": 5168
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2641592558819102e-05,
+ "loss": 0.4844,
+ "step": 5169
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2638978815364705e-05,
+ "loss": 0.4864,
+ "step": 5170
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2636364878114682e-05,
+ "loss": 0.4723,
+ "step": 5171
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2633750747260985e-05,
+ "loss": 0.4821,
+ "step": 5172
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.263113642299559e-05,
+ "loss": 0.4819,
+ "step": 5173
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2628521905510476e-05,
+ "loss": 0.4784,
+ "step": 5174
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2625907194997652e-05,
+ "loss": 0.4812,
+ "step": 5175
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2623292291649119e-05,
+ "loss": 0.4735,
+ "step": 5176
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2620677195656916e-05,
+ "loss": 0.4846,
+ "step": 5177
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.261806190721308e-05,
+ "loss": 0.5012,
+ "step": 5178
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2615446426509663e-05,
+ "loss": 0.5073,
+ "step": 5179
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.261283075373874e-05,
+ "loss": 0.4963,
+ "step": 5180
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2610214889092399e-05,
+ "loss": 0.4903,
+ "step": 5181
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2607598832762728e-05,
+ "loss": 0.485,
+ "step": 5182
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2604982584941846e-05,
+ "loss": 0.4773,
+ "step": 5183
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2602366145821879e-05,
+ "loss": 0.4819,
+ "step": 5184
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2599749515594964e-05,
+ "loss": 0.4781,
+ "step": 5185
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2597132694453258e-05,
+ "loss": 0.4648,
+ "step": 5186
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.259451568258893e-05,
+ "loss": 0.4819,
+ "step": 5187
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2591898480194165e-05,
+ "loss": 0.5044,
+ "step": 5188
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2589281087461152e-05,
+ "loss": 0.4943,
+ "step": 5189
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2586663504582104e-05,
+ "loss": 0.4827,
+ "step": 5190
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.258404573174925e-05,
+ "loss": 0.4828,
+ "step": 5191
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2581427769154826e-05,
+ "loss": 0.4685,
+ "step": 5192
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2578809616991081e-05,
+ "loss": 0.4819,
+ "step": 5193
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2576191275450287e-05,
+ "loss": 0.4996,
+ "step": 5194
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2573572744724718e-05,
+ "loss": 0.4831,
+ "step": 5195
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2570954025006672e-05,
+ "loss": 0.499,
+ "step": 5196
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2568335116488457e-05,
+ "loss": 0.4894,
+ "step": 5197
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2565716019362393e-05,
+ "loss": 0.4802,
+ "step": 5198
+ },
+ {
+ "epoch": 0.43,
+ "learning_rate": 1.2563096733820816e-05,
+ "loss": 0.479,
+ "step": 5199
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2560477260056072e-05,
+ "loss": 0.4739,
+ "step": 5200
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2557857598260532e-05,
+ "loss": 0.4864,
+ "step": 5201
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.255523774862657e-05,
+ "loss": 0.4791,
+ "step": 5202
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2552617711346572e-05,
+ "loss": 0.4939,
+ "step": 5203
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.254999748661295e-05,
+ "loss": 0.4796,
+ "step": 5204
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2547377074618114e-05,
+ "loss": 0.4678,
+ "step": 5205
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2544756475554505e-05,
+ "loss": 0.4995,
+ "step": 5206
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2542135689614565e-05,
+ "loss": 0.483,
+ "step": 5207
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2539514716990753e-05,
+ "loss": 0.4679,
+ "step": 5208
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2536893557875543e-05,
+ "loss": 0.4865,
+ "step": 5209
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.253427221246142e-05,
+ "loss": 0.4795,
+ "step": 5210
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2531650680940888e-05,
+ "loss": 0.4777,
+ "step": 5211
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.252902896350646e-05,
+ "loss": 0.4953,
+ "step": 5212
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.252640706035066e-05,
+ "loss": 0.5058,
+ "step": 5213
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2523784971666039e-05,
+ "loss": 0.4991,
+ "step": 5214
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2521162697645144e-05,
+ "loss": 0.4984,
+ "step": 5215
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.251854023848055e-05,
+ "loss": 0.4979,
+ "step": 5216
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.251591759436483e-05,
+ "loss": 0.4866,
+ "step": 5217
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2513294765490593e-05,
+ "loss": 0.4815,
+ "step": 5218
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2510671752050441e-05,
+ "loss": 0.4922,
+ "step": 5219
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2508048554236996e-05,
+ "loss": 0.4619,
+ "step": 5220
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2505425172242895e-05,
+ "loss": 0.4701,
+ "step": 5221
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2502801606260792e-05,
+ "loss": 0.4784,
+ "step": 5222
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2500177856483351e-05,
+ "loss": 0.4772,
+ "step": 5223
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2497553923103247e-05,
+ "loss": 0.4912,
+ "step": 5224
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.249492980631317e-05,
+ "loss": 0.4981,
+ "step": 5225
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2492305506305824e-05,
+ "loss": 0.4649,
+ "step": 5226
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2489681023273927e-05,
+ "loss": 0.4915,
+ "step": 5227
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2487056357410215e-05,
+ "loss": 0.4691,
+ "step": 5228
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2484431508907429e-05,
+ "loss": 0.4756,
+ "step": 5229
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2481806477958323e-05,
+ "loss": 0.4938,
+ "step": 5230
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.247918126475567e-05,
+ "loss": 0.4832,
+ "step": 5231
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2476555869492262e-05,
+ "loss": 0.4856,
+ "step": 5232
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2473930292360889e-05,
+ "loss": 0.4804,
+ "step": 5233
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2471304533554364e-05,
+ "loss": 0.5037,
+ "step": 5234
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2468678593265518e-05,
+ "loss": 0.4744,
+ "step": 5235
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2466052471687178e-05,
+ "loss": 0.4723,
+ "step": 5236
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2463426169012204e-05,
+ "loss": 0.4755,
+ "step": 5237
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2460799685433457e-05,
+ "loss": 0.4816,
+ "step": 5238
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.245817302114382e-05,
+ "loss": 0.4794,
+ "step": 5239
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2455546176336177e-05,
+ "loss": 0.4817,
+ "step": 5240
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2452919151203439e-05,
+ "loss": 0.5024,
+ "step": 5241
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.245029194593852e-05,
+ "loss": 0.4645,
+ "step": 5242
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2447664560734352e-05,
+ "loss": 0.4934,
+ "step": 5243
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2445036995783876e-05,
+ "loss": 0.4699,
+ "step": 5244
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2442409251280058e-05,
+ "loss": 0.4868,
+ "step": 5245
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2439781327415858e-05,
+ "loss": 0.4947,
+ "step": 5246
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2437153224384269e-05,
+ "loss": 0.4851,
+ "step": 5247
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2434524942378283e-05,
+ "loss": 0.5058,
+ "step": 5248
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2431896481590912e-05,
+ "loss": 0.4728,
+ "step": 5249
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2429267842215181e-05,
+ "loss": 0.4873,
+ "step": 5250
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2426639024444118e-05,
+ "loss": 0.4701,
+ "step": 5251
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2424010028470779e-05,
+ "loss": 0.4963,
+ "step": 5252
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.242138085448823e-05,
+ "loss": 0.501,
+ "step": 5253
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2418751502689537e-05,
+ "loss": 0.4718,
+ "step": 5254
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.24161219732678e-05,
+ "loss": 0.5091,
+ "step": 5255
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.241349226641611e-05,
+ "loss": 0.493,
+ "step": 5256
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2410862382327587e-05,
+ "loss": 0.4905,
+ "step": 5257
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.240823232119536e-05,
+ "loss": 0.4691,
+ "step": 5258
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2405602083212567e-05,
+ "loss": 0.4941,
+ "step": 5259
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2402971668572364e-05,
+ "loss": 0.4871,
+ "step": 5260
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2400341077467912e-05,
+ "loss": 0.4755,
+ "step": 5261
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2397710310092396e-05,
+ "loss": 0.4886,
+ "step": 5262
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2395079366639011e-05,
+ "loss": 0.5008,
+ "step": 5263
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2392448247300959e-05,
+ "loss": 0.4723,
+ "step": 5264
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2389816952271456e-05,
+ "loss": 0.4819,
+ "step": 5265
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.238718548174374e-05,
+ "loss": 0.4801,
+ "step": 5266
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2384553835911049e-05,
+ "loss": 0.5106,
+ "step": 5267
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2381922014966641e-05,
+ "loss": 0.5061,
+ "step": 5268
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.237929001910379e-05,
+ "loss": 0.4961,
+ "step": 5269
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2376657848515774e-05,
+ "loss": 0.4996,
+ "step": 5270
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.237402550339589e-05,
+ "loss": 0.4873,
+ "step": 5271
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2371392983937449e-05,
+ "loss": 0.4964,
+ "step": 5272
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2368760290333771e-05,
+ "loss": 0.493,
+ "step": 5273
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2366127422778192e-05,
+ "loss": 0.4932,
+ "step": 5274
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2363494381464052e-05,
+ "loss": 0.4952,
+ "step": 5275
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2360861166584717e-05,
+ "loss": 0.4878,
+ "step": 5276
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2358227778333556e-05,
+ "loss": 0.4842,
+ "step": 5277
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2355594216903956e-05,
+ "loss": 0.4739,
+ "step": 5278
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2352960482489317e-05,
+ "loss": 0.4898,
+ "step": 5279
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2350326575283047e-05,
+ "loss": 0.45,
+ "step": 5280
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2347692495478565e-05,
+ "loss": 0.4845,
+ "step": 5281
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2345058243269314e-05,
+ "loss": 0.4905,
+ "step": 5282
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.234242381884874e-05,
+ "loss": 0.4936,
+ "step": 5283
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2339789222410301e-05,
+ "loss": 0.4803,
+ "step": 5284
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2337154454147476e-05,
+ "loss": 0.4985,
+ "step": 5285
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2334519514253747e-05,
+ "loss": 0.4824,
+ "step": 5286
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2331884402922613e-05,
+ "loss": 0.4794,
+ "step": 5287
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2329249120347591e-05,
+ "loss": 0.4644,
+ "step": 5288
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.23266136667222e-05,
+ "loss": 0.4718,
+ "step": 5289
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2323978042239982e-05,
+ "loss": 0.4865,
+ "step": 5290
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.232134224709448e-05,
+ "loss": 0.4865,
+ "step": 5291
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2318706281479256e-05,
+ "loss": 0.4886,
+ "step": 5292
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2316070145587888e-05,
+ "loss": 0.4689,
+ "step": 5293
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2313433839613964e-05,
+ "loss": 0.4984,
+ "step": 5294
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2310797363751078e-05,
+ "loss": 0.497,
+ "step": 5295
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.230816071819285e-05,
+ "loss": 0.4869,
+ "step": 5296
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2305523903132897e-05,
+ "loss": 0.5057,
+ "step": 5297
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2302886918764856e-05,
+ "loss": 0.4959,
+ "step": 5298
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.230024976528238e-05,
+ "loss": 0.4867,
+ "step": 5299
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2297612442879129e-05,
+ "loss": 0.4817,
+ "step": 5300
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2294974951748775e-05,
+ "loss": 0.4834,
+ "step": 5301
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2292337292085006e-05,
+ "loss": 0.4934,
+ "step": 5302
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2289699464081521e-05,
+ "loss": 0.4969,
+ "step": 5303
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2287061467932033e-05,
+ "loss": 0.4713,
+ "step": 5304
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.228442330383026e-05,
+ "loss": 0.4615,
+ "step": 5305
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2281784971969944e-05,
+ "loss": 0.4634,
+ "step": 5306
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.227914647254483e-05,
+ "loss": 0.4882,
+ "step": 5307
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2276507805748676e-05,
+ "loss": 0.4769,
+ "step": 5308
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.227386897177526e-05,
+ "loss": 0.4874,
+ "step": 5309
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2271229970818366e-05,
+ "loss": 0.504,
+ "step": 5310
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2268590803071787e-05,
+ "loss": 0.4827,
+ "step": 5311
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2265951468729336e-05,
+ "loss": 0.4654,
+ "step": 5312
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2263311967984834e-05,
+ "loss": 0.5182,
+ "step": 5313
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2260672301032116e-05,
+ "loss": 0.4757,
+ "step": 5314
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2258032468065024e-05,
+ "loss": 0.4899,
+ "step": 5315
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2255392469277421e-05,
+ "loss": 0.4886,
+ "step": 5316
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2252752304863178e-05,
+ "loss": 0.4833,
+ "step": 5317
+ },
+ {
+ "epoch": 0.44,
+ "learning_rate": 1.2250111975016173e-05,
+ "loss": 0.4766,
+ "step": 5318
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2247471479930303e-05,
+ "loss": 0.4942,
+ "step": 5319
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2244830819799478e-05,
+ "loss": 0.4695,
+ "step": 5320
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2242189994817614e-05,
+ "loss": 0.4811,
+ "step": 5321
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2239549005178642e-05,
+ "loss": 0.4927,
+ "step": 5322
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2236907851076505e-05,
+ "loss": 0.4838,
+ "step": 5323
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2234266532705161e-05,
+ "loss": 0.4872,
+ "step": 5324
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2231625050258576e-05,
+ "loss": 0.492,
+ "step": 5325
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2228983403930727e-05,
+ "loss": 0.4847,
+ "step": 5326
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2226341593915612e-05,
+ "loss": 0.4641,
+ "step": 5327
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2223699620407227e-05,
+ "loss": 0.5174,
+ "step": 5328
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.222105748359959e-05,
+ "loss": 0.4728,
+ "step": 5329
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2218415183686732e-05,
+ "loss": 0.4889,
+ "step": 5330
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2215772720862691e-05,
+ "loss": 0.5182,
+ "step": 5331
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2213130095321517e-05,
+ "loss": 0.4757,
+ "step": 5332
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.221048730725727e-05,
+ "loss": 0.4729,
+ "step": 5333
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2207844356864031e-05,
+ "loss": 0.4839,
+ "step": 5334
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2205201244335889e-05,
+ "loss": 0.4946,
+ "step": 5335
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2202557969866934e-05,
+ "loss": 0.4686,
+ "step": 5336
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2199914533651289e-05,
+ "loss": 0.4722,
+ "step": 5337
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2197270935883068e-05,
+ "loss": 0.4708,
+ "step": 5338
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2194627176756408e-05,
+ "loss": 0.5,
+ "step": 5339
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2191983256465455e-05,
+ "loss": 0.463,
+ "step": 5340
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2189339175204373e-05,
+ "loss": 0.4606,
+ "step": 5341
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2186694933167326e-05,
+ "loss": 0.5079,
+ "step": 5342
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2184050530548496e-05,
+ "loss": 0.4716,
+ "step": 5343
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2181405967542082e-05,
+ "loss": 0.4788,
+ "step": 5344
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2178761244342286e-05,
+ "loss": 0.488,
+ "step": 5345
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2176116361143326e-05,
+ "loss": 0.4836,
+ "step": 5346
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2173471318139431e-05,
+ "loss": 0.4844,
+ "step": 5347
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2170826115524845e-05,
+ "loss": 0.4895,
+ "step": 5348
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2168180753493817e-05,
+ "loss": 0.4887,
+ "step": 5349
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2165535232240611e-05,
+ "loss": 0.4839,
+ "step": 5350
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2162889551959506e-05,
+ "loss": 0.4759,
+ "step": 5351
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.216024371284479e-05,
+ "loss": 0.4753,
+ "step": 5352
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.215759771509076e-05,
+ "loss": 0.4875,
+ "step": 5353
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2154951558891728e-05,
+ "loss": 0.4858,
+ "step": 5354
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2152305244442014e-05,
+ "loss": 0.4829,
+ "step": 5355
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2149658771935955e-05,
+ "loss": 0.4784,
+ "step": 5356
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.21470121415679e-05,
+ "loss": 0.4715,
+ "step": 5357
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2144365353532204e-05,
+ "loss": 0.4761,
+ "step": 5358
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2141718408023233e-05,
+ "loss": 0.4941,
+ "step": 5359
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2139071305235368e-05,
+ "loss": 0.4754,
+ "step": 5360
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2136424045363007e-05,
+ "loss": 0.4846,
+ "step": 5361
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2133776628600552e-05,
+ "loss": 0.4779,
+ "step": 5362
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2131129055142411e-05,
+ "loss": 0.481,
+ "step": 5363
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2128481325183022e-05,
+ "loss": 0.4914,
+ "step": 5364
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2125833438916812e-05,
+ "loss": 0.4922,
+ "step": 5365
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2123185396538242e-05,
+ "loss": 0.4835,
+ "step": 5366
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2120537198241763e-05,
+ "loss": 0.4769,
+ "step": 5367
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2117888844221852e-05,
+ "loss": 0.4646,
+ "step": 5368
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2115240334672997e-05,
+ "loss": 0.4822,
+ "step": 5369
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2112591669789685e-05,
+ "loss": 0.4844,
+ "step": 5370
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2109942849766432e-05,
+ "loss": 0.4739,
+ "step": 5371
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.210729387479775e-05,
+ "loss": 0.4888,
+ "step": 5372
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.210464474507817e-05,
+ "loss": 0.496,
+ "step": 5373
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2101995460802235e-05,
+ "loss": 0.4643,
+ "step": 5374
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2099346022164496e-05,
+ "loss": 0.4959,
+ "step": 5375
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2096696429359518e-05,
+ "loss": 0.4997,
+ "step": 5376
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2094046682581872e-05,
+ "loss": 0.5001,
+ "step": 5377
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.209139678202615e-05,
+ "loss": 0.4878,
+ "step": 5378
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2088746727886949e-05,
+ "loss": 0.4932,
+ "step": 5379
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2086096520358872e-05,
+ "loss": 0.4941,
+ "step": 5380
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2083446159636543e-05,
+ "loss": 0.4906,
+ "step": 5381
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2080795645914595e-05,
+ "loss": 0.4808,
+ "step": 5382
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2078144979387674e-05,
+ "loss": 0.5055,
+ "step": 5383
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2075494160250423e-05,
+ "loss": 0.4768,
+ "step": 5384
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2072843188697516e-05,
+ "loss": 0.4818,
+ "step": 5385
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2070192064923627e-05,
+ "loss": 0.4919,
+ "step": 5386
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2067540789123441e-05,
+ "loss": 0.4866,
+ "step": 5387
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2064889361491663e-05,
+ "loss": 0.4826,
+ "step": 5388
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2062237782222996e-05,
+ "loss": 0.4683,
+ "step": 5389
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2059586051512164e-05,
+ "loss": 0.4713,
+ "step": 5390
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.20569341695539e-05,
+ "loss": 0.4872,
+ "step": 5391
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2054282136542946e-05,
+ "loss": 0.5091,
+ "step": 5392
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2051629952674055e-05,
+ "loss": 0.4817,
+ "step": 5393
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2048977618141995e-05,
+ "loss": 0.5097,
+ "step": 5394
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2046325133141542e-05,
+ "loss": 0.4779,
+ "step": 5395
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2043672497867479e-05,
+ "loss": 0.4591,
+ "step": 5396
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2041019712514607e-05,
+ "loss": 0.4957,
+ "step": 5397
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2038366777277743e-05,
+ "loss": 0.475,
+ "step": 5398
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2035713692351698e-05,
+ "loss": 0.483,
+ "step": 5399
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2033060457931308e-05,
+ "loss": 0.4841,
+ "step": 5400
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.203040707421141e-05,
+ "loss": 0.4775,
+ "step": 5401
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2027753541386865e-05,
+ "loss": 0.466,
+ "step": 5402
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2025099859652532e-05,
+ "loss": 0.4859,
+ "step": 5403
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.202244602920329e-05,
+ "loss": 0.4848,
+ "step": 5404
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2019792050234022e-05,
+ "loss": 0.4779,
+ "step": 5405
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2017137922939629e-05,
+ "loss": 0.4719,
+ "step": 5406
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2014483647515014e-05,
+ "loss": 0.4811,
+ "step": 5407
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2011829224155101e-05,
+ "loss": 0.4836,
+ "step": 5408
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2009174653054815e-05,
+ "loss": 0.4754,
+ "step": 5409
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.2006519934409105e-05,
+ "loss": 0.4843,
+ "step": 5410
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.200386506841291e-05,
+ "loss": 0.4793,
+ "step": 5411
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.20012100552612e-05,
+ "loss": 0.4602,
+ "step": 5412
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1998554895148953e-05,
+ "loss": 0.4766,
+ "step": 5413
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.199589958827114e-05,
+ "loss": 0.4675,
+ "step": 5414
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1993244134822767e-05,
+ "loss": 0.4753,
+ "step": 5415
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1990588534998834e-05,
+ "loss": 0.4726,
+ "step": 5416
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1987932788994362e-05,
+ "loss": 0.4837,
+ "step": 5417
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1985276897004367e-05,
+ "loss": 0.475,
+ "step": 5418
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1982620859223902e-05,
+ "loss": 0.4957,
+ "step": 5419
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1979964675848004e-05,
+ "loss": 0.5041,
+ "step": 5420
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1977308347071735e-05,
+ "loss": 0.4591,
+ "step": 5421
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1974651873090163e-05,
+ "loss": 0.4675,
+ "step": 5422
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1971995254098374e-05,
+ "loss": 0.4879,
+ "step": 5423
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1969338490291455e-05,
+ "loss": 0.464,
+ "step": 5424
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1966681581864507e-05,
+ "loss": 0.4879,
+ "step": 5425
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1964024529012648e-05,
+ "loss": 0.5053,
+ "step": 5426
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.196136733193099e-05,
+ "loss": 0.5042,
+ "step": 5427
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1958709990814677e-05,
+ "loss": 0.4944,
+ "step": 5428
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1956052505858851e-05,
+ "loss": 0.4783,
+ "step": 5429
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1953394877258662e-05,
+ "loss": 0.5042,
+ "step": 5430
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1950737105209278e-05,
+ "loss": 0.4801,
+ "step": 5431
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1948079189905872e-05,
+ "loss": 0.502,
+ "step": 5432
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1945421131543639e-05,
+ "loss": 0.4985,
+ "step": 5433
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1942762930317768e-05,
+ "loss": 0.4746,
+ "step": 5434
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1940104586423465e-05,
+ "loss": 0.4948,
+ "step": 5435
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1937446100055954e-05,
+ "loss": 0.4836,
+ "step": 5436
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1934787471410457e-05,
+ "loss": 0.4663,
+ "step": 5437
+ },
+ {
+ "epoch": 0.45,
+ "learning_rate": 1.1932128700682216e-05,
+ "loss": 0.5137,
+ "step": 5438
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1929469788066481e-05,
+ "loss": 0.4803,
+ "step": 5439
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1926810733758511e-05,
+ "loss": 0.4849,
+ "step": 5440
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1924151537953574e-05,
+ "loss": 0.4916,
+ "step": 5441
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1921492200846949e-05,
+ "loss": 0.4784,
+ "step": 5442
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.191883272263393e-05,
+ "loss": 0.4805,
+ "step": 5443
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1916173103509819e-05,
+ "loss": 0.4756,
+ "step": 5444
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.191351334366992e-05,
+ "loss": 0.5125,
+ "step": 5445
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1910853443309566e-05,
+ "loss": 0.4804,
+ "step": 5446
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.190819340262408e-05,
+ "loss": 0.4834,
+ "step": 5447
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1905533221808805e-05,
+ "loss": 0.4813,
+ "step": 5448
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1902872901059102e-05,
+ "loss": 0.501,
+ "step": 5449
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1900212440570324e-05,
+ "loss": 0.4523,
+ "step": 5450
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1897551840537848e-05,
+ "loss": 0.4583,
+ "step": 5451
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1894891101157058e-05,
+ "loss": 0.4717,
+ "step": 5452
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1892230222623345e-05,
+ "loss": 0.4813,
+ "step": 5453
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1889569205132119e-05,
+ "loss": 0.495,
+ "step": 5454
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1886908048878785e-05,
+ "loss": 0.4842,
+ "step": 5455
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1884246754058775e-05,
+ "loss": 0.4882,
+ "step": 5456
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1881585320867521e-05,
+ "loss": 0.4802,
+ "step": 5457
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1878923749500466e-05,
+ "loss": 0.4653,
+ "step": 5458
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1876262040153064e-05,
+ "loss": 0.4861,
+ "step": 5459
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1873600193020786e-05,
+ "loss": 0.4977,
+ "step": 5460
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.18709382082991e-05,
+ "loss": 0.4697,
+ "step": 5461
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1868276086183494e-05,
+ "loss": 0.4973,
+ "step": 5462
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1865613826869463e-05,
+ "loss": 0.5125,
+ "step": 5463
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1862951430552514e-05,
+ "loss": 0.4998,
+ "step": 5464
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1860288897428158e-05,
+ "loss": 0.4609,
+ "step": 5465
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1857626227691924e-05,
+ "loss": 0.47,
+ "step": 5466
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1854963421539348e-05,
+ "loss": 0.4728,
+ "step": 5467
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.185230047916597e-05,
+ "loss": 0.4885,
+ "step": 5468
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1849637400767351e-05,
+ "loss": 0.49,
+ "step": 5469
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1846974186539055e-05,
+ "loss": 0.5007,
+ "step": 5470
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1844310836676658e-05,
+ "loss": 0.4694,
+ "step": 5471
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.184164735137574e-05,
+ "loss": 0.4736,
+ "step": 5472
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1838983730831904e-05,
+ "loss": 0.5052,
+ "step": 5473
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1836319975240751e-05,
+ "loss": 0.4826,
+ "step": 5474
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1833656084797898e-05,
+ "loss": 0.4675,
+ "step": 5475
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1830992059698967e-05,
+ "loss": 0.4842,
+ "step": 5476
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1828327900139596e-05,
+ "loss": 0.4937,
+ "step": 5477
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1825663606315425e-05,
+ "loss": 0.4691,
+ "step": 5478
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1822999178422114e-05,
+ "loss": 0.4715,
+ "step": 5479
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.182033461665533e-05,
+ "loss": 0.4987,
+ "step": 5480
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.181766992121074e-05,
+ "loss": 0.4855,
+ "step": 5481
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1815005092284033e-05,
+ "loss": 0.4915,
+ "step": 5482
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.18123401300709e-05,
+ "loss": 0.469,
+ "step": 5483
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1809675034767043e-05,
+ "loss": 0.4964,
+ "step": 5484
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1807009806568181e-05,
+ "loss": 0.4829,
+ "step": 5485
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1804344445670034e-05,
+ "loss": 0.4707,
+ "step": 5486
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1801678952268338e-05,
+ "loss": 0.4788,
+ "step": 5487
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.179901332655883e-05,
+ "loss": 0.4759,
+ "step": 5488
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1796347568737268e-05,
+ "loss": 0.4847,
+ "step": 5489
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1793681678999412e-05,
+ "loss": 0.4786,
+ "step": 5490
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1791015657541037e-05,
+ "loss": 0.4953,
+ "step": 5491
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1788349504557917e-05,
+ "loss": 0.4832,
+ "step": 5492
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1785683220245849e-05,
+ "loss": 0.4776,
+ "step": 5493
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1783016804800631e-05,
+ "loss": 0.4789,
+ "step": 5494
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1780350258418078e-05,
+ "loss": 0.4819,
+ "step": 5495
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1777683581294003e-05,
+ "loss": 0.4795,
+ "step": 5496
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1775016773624246e-05,
+ "loss": 0.4736,
+ "step": 5497
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1772349835604638e-05,
+ "loss": 0.5113,
+ "step": 5498
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1769682767431026e-05,
+ "loss": 0.4702,
+ "step": 5499
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1767015569299274e-05,
+ "loss": 0.4802,
+ "step": 5500
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1764348241405249e-05,
+ "loss": 0.4804,
+ "step": 5501
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1761680783944829e-05,
+ "loss": 0.4852,
+ "step": 5502
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1759013197113895e-05,
+ "loss": 0.4836,
+ "step": 5503
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.175634548110835e-05,
+ "loss": 0.4939,
+ "step": 5504
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1753677636124101e-05,
+ "loss": 0.5088,
+ "step": 5505
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1751009662357059e-05,
+ "loss": 0.471,
+ "step": 5506
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1748341560003149e-05,
+ "loss": 0.489,
+ "step": 5507
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.174567332925831e-05,
+ "loss": 0.4822,
+ "step": 5508
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.174300497031848e-05,
+ "loss": 0.4794,
+ "step": 5509
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1740336483379613e-05,
+ "loss": 0.4821,
+ "step": 5510
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1737667868637674e-05,
+ "loss": 0.4755,
+ "step": 5511
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1734999126288637e-05,
+ "loss": 0.4849,
+ "step": 5512
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1732330256528477e-05,
+ "loss": 0.4922,
+ "step": 5513
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1729661259553193e-05,
+ "loss": 0.4849,
+ "step": 5514
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1726992135558776e-05,
+ "loss": 0.4955,
+ "step": 5515
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1724322884741242e-05,
+ "loss": 0.4834,
+ "step": 5516
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1721653507296604e-05,
+ "loss": 0.5012,
+ "step": 5517
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1718984003420899e-05,
+ "loss": 0.4802,
+ "step": 5518
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1716314373310154e-05,
+ "loss": 0.4789,
+ "step": 5519
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.171364461716042e-05,
+ "loss": 0.4883,
+ "step": 5520
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1710974735167755e-05,
+ "loss": 0.4702,
+ "step": 5521
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1708304727528223e-05,
+ "loss": 0.4768,
+ "step": 5522
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1705634594437893e-05,
+ "loss": 0.4884,
+ "step": 5523
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1702964336092857e-05,
+ "loss": 0.4935,
+ "step": 5524
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.17002939526892e-05,
+ "loss": 0.4804,
+ "step": 5525
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.169762344442303e-05,
+ "loss": 0.4896,
+ "step": 5526
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1694952811490451e-05,
+ "loss": 0.4846,
+ "step": 5527
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1692282054087594e-05,
+ "loss": 0.4812,
+ "step": 5528
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1689611172410577e-05,
+ "loss": 0.5226,
+ "step": 5529
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1686940166655543e-05,
+ "loss": 0.4731,
+ "step": 5530
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1684269037018641e-05,
+ "loss": 0.475,
+ "step": 5531
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1681597783696027e-05,
+ "loss": 0.5193,
+ "step": 5532
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1678926406883866e-05,
+ "loss": 0.4724,
+ "step": 5533
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1676254906778331e-05,
+ "loss": 0.4698,
+ "step": 5534
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1673583283575607e-05,
+ "loss": 0.4757,
+ "step": 5535
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1670911537471889e-05,
+ "loss": 0.48,
+ "step": 5536
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1668239668663377e-05,
+ "loss": 0.4737,
+ "step": 5537
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1665567677346285e-05,
+ "loss": 0.4547,
+ "step": 5538
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.166289556371683e-05,
+ "loss": 0.4934,
+ "step": 5539
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1660223327971239e-05,
+ "loss": 0.4754,
+ "step": 5540
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1657550970305752e-05,
+ "loss": 0.473,
+ "step": 5541
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1654878490916617e-05,
+ "loss": 0.4748,
+ "step": 5542
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.165220589000009e-05,
+ "loss": 0.486,
+ "step": 5543
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1649533167752434e-05,
+ "loss": 0.4595,
+ "step": 5544
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.164686032436992e-05,
+ "loss": 0.4842,
+ "step": 5545
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1644187360048838e-05,
+ "loss": 0.4897,
+ "step": 5546
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.164151427498547e-05,
+ "loss": 0.4752,
+ "step": 5547
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1638841069376125e-05,
+ "loss": 0.4937,
+ "step": 5548
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1636167743417111e-05,
+ "loss": 0.4841,
+ "step": 5549
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1633494297304738e-05,
+ "loss": 0.4826,
+ "step": 5550
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.163082073123534e-05,
+ "loss": 0.4777,
+ "step": 5551
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1628147045405248e-05,
+ "loss": 0.4806,
+ "step": 5552
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1625473240010814e-05,
+ "loss": 0.4643,
+ "step": 5553
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1622799315248382e-05,
+ "loss": 0.5037,
+ "step": 5554
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1620125271314322e-05,
+ "loss": 0.4654,
+ "step": 5555
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1617451108404996e-05,
+ "loss": 0.4785,
+ "step": 5556
+ },
+ {
+ "epoch": 0.46,
+ "learning_rate": 1.1614776826716791e-05,
+ "loss": 0.4712,
+ "step": 5557
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.161210242644609e-05,
+ "loss": 0.4797,
+ "step": 5558
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1609427907789294e-05,
+ "loss": 0.4672,
+ "step": 5559
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.160675327094281e-05,
+ "loss": 0.5135,
+ "step": 5560
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.160407851610304e-05,
+ "loss": 0.5052,
+ "step": 5561
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1601403643466422e-05,
+ "loss": 0.4833,
+ "step": 5562
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.159872865322938e-05,
+ "loss": 0.5247,
+ "step": 5563
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1596053545588355e-05,
+ "loss": 0.5032,
+ "step": 5564
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1593378320739796e-05,
+ "loss": 0.4918,
+ "step": 5565
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1590702978880159e-05,
+ "loss": 0.4745,
+ "step": 5566
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1588027520205915e-05,
+ "loss": 0.4933,
+ "step": 5567
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1585351944913532e-05,
+ "loss": 0.4832,
+ "step": 5568
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1582676253199498e-05,
+ "loss": 0.4923,
+ "step": 5569
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1580000445260305e-05,
+ "loss": 0.4878,
+ "step": 5570
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1577324521292445e-05,
+ "loss": 0.4873,
+ "step": 5571
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1574648481492434e-05,
+ "loss": 0.4808,
+ "step": 5572
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1571972326056794e-05,
+ "loss": 0.4868,
+ "step": 5573
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.156929605518204e-05,
+ "loss": 0.49,
+ "step": 5574
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1566619669064709e-05,
+ "loss": 0.468,
+ "step": 5575
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1563943167901348e-05,
+ "loss": 0.4702,
+ "step": 5576
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1561266551888505e-05,
+ "loss": 0.4777,
+ "step": 5577
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1558589821222742e-05,
+ "loss": 0.4819,
+ "step": 5578
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1555912976100623e-05,
+ "loss": 0.4927,
+ "step": 5579
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.155323601671873e-05,
+ "loss": 0.4894,
+ "step": 5580
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.155055894327364e-05,
+ "loss": 0.4895,
+ "step": 5581
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1547881755961952e-05,
+ "loss": 0.4753,
+ "step": 5582
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1545204454980268e-05,
+ "loss": 0.483,
+ "step": 5583
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1542527040525192e-05,
+ "loss": 0.4889,
+ "step": 5584
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1539849512793348e-05,
+ "loss": 0.4702,
+ "step": 5585
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1537171871981363e-05,
+ "loss": 0.4892,
+ "step": 5586
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1534494118285865e-05,
+ "loss": 0.4854,
+ "step": 5587
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1531816251903503e-05,
+ "loss": 0.4915,
+ "step": 5588
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1529138273030927e-05,
+ "loss": 0.4627,
+ "step": 5589
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1526460181864799e-05,
+ "loss": 0.4904,
+ "step": 5590
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.152378197860178e-05,
+ "loss": 0.5022,
+ "step": 5591
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1521103663438551e-05,
+ "loss": 0.4974,
+ "step": 5592
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1518425236571797e-05,
+ "loss": 0.48,
+ "step": 5593
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1515746698198211e-05,
+ "loss": 0.4676,
+ "step": 5594
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1513068048514489e-05,
+ "loss": 0.4756,
+ "step": 5595
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1510389287717345e-05,
+ "loss": 0.4957,
+ "step": 5596
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.150771041600349e-05,
+ "loss": 0.4611,
+ "step": 5597
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1505031433569658e-05,
+ "loss": 0.4657,
+ "step": 5598
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1502352340612576e-05,
+ "loss": 0.4936,
+ "step": 5599
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1499673137328986e-05,
+ "loss": 0.4698,
+ "step": 5600
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1496993823915639e-05,
+ "loss": 0.4816,
+ "step": 5601
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1494314400569288e-05,
+ "loss": 0.4927,
+ "step": 5602
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1491634867486707e-05,
+ "loss": 0.4541,
+ "step": 5603
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1488955224864667e-05,
+ "loss": 0.48,
+ "step": 5604
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1486275472899943e-05,
+ "loss": 0.4936,
+ "step": 5605
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1483595611789336e-05,
+ "loss": 0.4853,
+ "step": 5606
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1480915641729633e-05,
+ "loss": 0.4817,
+ "step": 5607
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.147823556291765e-05,
+ "loss": 0.4931,
+ "step": 5608
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1475555375550191e-05,
+ "loss": 0.4849,
+ "step": 5609
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1472875079824087e-05,
+ "loss": 0.4649,
+ "step": 5610
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1470194675936159e-05,
+ "loss": 0.4762,
+ "step": 5611
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1467514164083252e-05,
+ "loss": 0.4908,
+ "step": 5612
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1464833544462203e-05,
+ "loss": 0.4826,
+ "step": 5613
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1462152817269879e-05,
+ "loss": 0.4964,
+ "step": 5614
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.145947198270313e-05,
+ "loss": 0.4881,
+ "step": 5615
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1456791040958828e-05,
+ "loss": 0.4719,
+ "step": 5616
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1454109992233851e-05,
+ "loss": 0.4977,
+ "step": 5617
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1451428836725087e-05,
+ "loss": 0.4921,
+ "step": 5618
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1448747574629424e-05,
+ "loss": 0.476,
+ "step": 5619
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1446066206143766e-05,
+ "loss": 0.4831,
+ "step": 5620
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1443384731465021e-05,
+ "loss": 0.4824,
+ "step": 5621
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1440703150790102e-05,
+ "loss": 0.4794,
+ "step": 5622
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1438021464315939e-05,
+ "loss": 0.4919,
+ "step": 5623
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.143533967223946e-05,
+ "loss": 0.4893,
+ "step": 5624
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1432657774757607e-05,
+ "loss": 0.4674,
+ "step": 5625
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1429975772067322e-05,
+ "loss": 0.4806,
+ "step": 5626
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1427293664365568e-05,
+ "loss": 0.5062,
+ "step": 5627
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1424611451849301e-05,
+ "loss": 0.4882,
+ "step": 5628
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1421929134715492e-05,
+ "loss": 0.4883,
+ "step": 5629
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1419246713161128e-05,
+ "loss": 0.4493,
+ "step": 5630
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1416564187383185e-05,
+ "loss": 0.4925,
+ "step": 5631
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1413881557578662e-05,
+ "loss": 0.4814,
+ "step": 5632
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1411198823944553e-05,
+ "loss": 0.4868,
+ "step": 5633
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1408515986677877e-05,
+ "loss": 0.4744,
+ "step": 5634
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1405833045975644e-05,
+ "loss": 0.4786,
+ "step": 5635
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.140315000203488e-05,
+ "loss": 0.4724,
+ "step": 5636
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1400466855052617e-05,
+ "loss": 0.4885,
+ "step": 5637
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.139778360522589e-05,
+ "loss": 0.4876,
+ "step": 5638
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.139510025275175e-05,
+ "loss": 0.4921,
+ "step": 5639
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.139241679782725e-05,
+ "loss": 0.5004,
+ "step": 5640
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1389733240649454e-05,
+ "loss": 0.4859,
+ "step": 5641
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1387049581415428e-05,
+ "loss": 0.4938,
+ "step": 5642
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.138436582032225e-05,
+ "loss": 0.4681,
+ "step": 5643
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1381681957567e-05,
+ "loss": 0.4845,
+ "step": 5644
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1378997993346782e-05,
+ "loss": 0.4733,
+ "step": 5645
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.137631392785868e-05,
+ "loss": 0.4937,
+ "step": 5646
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1373629761299811e-05,
+ "loss": 0.4775,
+ "step": 5647
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1370945493867284e-05,
+ "loss": 0.471,
+ "step": 5648
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1368261125758224e-05,
+ "loss": 0.4901,
+ "step": 5649
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1365576657169754e-05,
+ "loss": 0.4707,
+ "step": 5650
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.136289208829902e-05,
+ "loss": 0.4803,
+ "step": 5651
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1360207419343157e-05,
+ "loss": 0.4749,
+ "step": 5652
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1357522650499317e-05,
+ "loss": 0.4835,
+ "step": 5653
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.135483778196466e-05,
+ "loss": 0.4921,
+ "step": 5654
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1352152813936354e-05,
+ "loss": 0.4825,
+ "step": 5655
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1349467746611569e-05,
+ "loss": 0.4778,
+ "step": 5656
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1346782580187486e-05,
+ "loss": 0.4877,
+ "step": 5657
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1344097314861292e-05,
+ "loss": 0.5045,
+ "step": 5658
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1341411950830179e-05,
+ "loss": 0.4885,
+ "step": 5659
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1338726488291351e-05,
+ "loss": 0.4939,
+ "step": 5660
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1336040927442023e-05,
+ "loss": 0.4826,
+ "step": 5661
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1333355268479403e-05,
+ "loss": 0.4694,
+ "step": 5662
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1330669511600716e-05,
+ "loss": 0.467,
+ "step": 5663
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1327983657003197e-05,
+ "loss": 0.5067,
+ "step": 5664
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1325297704884081e-05,
+ "loss": 0.4779,
+ "step": 5665
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.132261165544062e-05,
+ "loss": 0.4802,
+ "step": 5666
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.131992550887005e-05,
+ "loss": 0.4811,
+ "step": 5667
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1317239265369648e-05,
+ "loss": 0.5074,
+ "step": 5668
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.131455292513667e-05,
+ "loss": 0.4494,
+ "step": 5669
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1311866488368392e-05,
+ "loss": 0.4755,
+ "step": 5670
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1309179955262097e-05,
+ "loss": 0.5055,
+ "step": 5671
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1306493326015074e-05,
+ "loss": 0.4714,
+ "step": 5672
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1303806600824613e-05,
+ "loss": 0.4855,
+ "step": 5673
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1301119779888015e-05,
+ "loss": 0.4815,
+ "step": 5674
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1298432863402595e-05,
+ "loss": 0.4807,
+ "step": 5675
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1295745851565667e-05,
+ "loss": 0.4727,
+ "step": 5676
+ },
+ {
+ "epoch": 0.47,
+ "learning_rate": 1.1293058744574552e-05,
+ "loss": 0.4793,
+ "step": 5677
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.129037154262658e-05,
+ "loss": 0.4741,
+ "step": 5678
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.128768424591909e-05,
+ "loss": 0.4584,
+ "step": 5679
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1284996854649424e-05,
+ "loss": 0.4911,
+ "step": 5680
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1282309369014937e-05,
+ "loss": 0.4811,
+ "step": 5681
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.127962178921298e-05,
+ "loss": 0.4769,
+ "step": 5682
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1276934115440924e-05,
+ "loss": 0.4743,
+ "step": 5683
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1274246347896136e-05,
+ "loss": 0.48,
+ "step": 5684
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1271558486775995e-05,
+ "loss": 0.4874,
+ "step": 5685
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1268870532277889e-05,
+ "loss": 0.463,
+ "step": 5686
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1266182484599209e-05,
+ "loss": 0.4752,
+ "step": 5687
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1263494343937354e-05,
+ "loss": 0.4682,
+ "step": 5688
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1260806110489726e-05,
+ "loss": 0.4947,
+ "step": 5689
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1258117784453746e-05,
+ "loss": 0.4735,
+ "step": 5690
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1255429366026826e-05,
+ "loss": 0.4578,
+ "step": 5691
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1252740855406397e-05,
+ "loss": 0.4827,
+ "step": 5692
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1250052252789891e-05,
+ "loss": 0.4848,
+ "step": 5693
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1247363558374745e-05,
+ "loss": 0.4687,
+ "step": 5694
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1244674772358406e-05,
+ "loss": 0.473,
+ "step": 5695
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.124198589493833e-05,
+ "loss": 0.4834,
+ "step": 5696
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1239296926311975e-05,
+ "loss": 0.4675,
+ "step": 5697
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.123660786667681e-05,
+ "loss": 0.4829,
+ "step": 5698
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1233918716230308e-05,
+ "loss": 0.4824,
+ "step": 5699
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1231229475169945e-05,
+ "loss": 0.4713,
+ "step": 5700
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1228540143693209e-05,
+ "loss": 0.4831,
+ "step": 5701
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.12258507219976e-05,
+ "loss": 0.4796,
+ "step": 5702
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.122316121028061e-05,
+ "loss": 0.4962,
+ "step": 5703
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1220471608739748e-05,
+ "loss": 0.4918,
+ "step": 5704
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1217781917572524e-05,
+ "loss": 0.4789,
+ "step": 5705
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1215092136976466e-05,
+ "loss": 0.5123,
+ "step": 5706
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1212402267149094e-05,
+ "loss": 0.478,
+ "step": 5707
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1209712308287941e-05,
+ "loss": 0.4826,
+ "step": 5708
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.120702226059055e-05,
+ "loss": 0.4965,
+ "step": 5709
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1204332124254463e-05,
+ "loss": 0.469,
+ "step": 5710
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1201641899477231e-05,
+ "loss": 0.4617,
+ "step": 5711
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.119895158645642e-05,
+ "loss": 0.4843,
+ "step": 5712
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1196261185389593e-05,
+ "loss": 0.4833,
+ "step": 5713
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1193570696474317e-05,
+ "loss": 0.4829,
+ "step": 5714
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1190880119908175e-05,
+ "loss": 0.4845,
+ "step": 5715
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1188189455888747e-05,
+ "loss": 0.4692,
+ "step": 5716
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1185498704613632e-05,
+ "loss": 0.4786,
+ "step": 5717
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1182807866280419e-05,
+ "loss": 0.4714,
+ "step": 5718
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1180116941086719e-05,
+ "loss": 0.4922,
+ "step": 5719
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1177425929230137e-05,
+ "loss": 0.4893,
+ "step": 5720
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.117473483090829e-05,
+ "loss": 0.476,
+ "step": 5721
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1172043646318809e-05,
+ "loss": 0.4827,
+ "step": 5722
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1169352375659314e-05,
+ "loss": 0.4936,
+ "step": 5723
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1166661019127447e-05,
+ "loss": 0.4858,
+ "step": 5724
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1163969576920846e-05,
+ "loss": 0.4639,
+ "step": 5725
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1161278049237157e-05,
+ "loss": 0.5047,
+ "step": 5726
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1158586436274042e-05,
+ "loss": 0.4743,
+ "step": 5727
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1155894738229156e-05,
+ "loss": 0.485,
+ "step": 5728
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.115320295530017e-05,
+ "loss": 0.4729,
+ "step": 5729
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1150511087684757e-05,
+ "loss": 0.4761,
+ "step": 5730
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1147819135580588e-05,
+ "loss": 0.4886,
+ "step": 5731
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1145127099185363e-05,
+ "loss": 0.4789,
+ "step": 5732
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1142434978696763e-05,
+ "loss": 0.495,
+ "step": 5733
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1139742774312495e-05,
+ "loss": 0.4717,
+ "step": 5734
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1137050486230251e-05,
+ "loss": 0.495,
+ "step": 5735
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1134358114647752e-05,
+ "loss": 0.4825,
+ "step": 5736
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1131665659762712e-05,
+ "loss": 0.476,
+ "step": 5737
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.112897312177285e-05,
+ "loss": 0.4794,
+ "step": 5738
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.11262805008759e-05,
+ "loss": 0.4632,
+ "step": 5739
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1123587797269596e-05,
+ "loss": 0.5031,
+ "step": 5740
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1120895011151675e-05,
+ "loss": 0.4687,
+ "step": 5741
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1118202142719887e-05,
+ "loss": 0.5017,
+ "step": 5742
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1115509192171988e-05,
+ "loss": 0.4941,
+ "step": 5743
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.111281615970573e-05,
+ "loss": 0.4736,
+ "step": 5744
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1110123045518882e-05,
+ "loss": 0.4698,
+ "step": 5745
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1107429849809215e-05,
+ "loss": 0.491,
+ "step": 5746
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1104736572774506e-05,
+ "loss": 0.4839,
+ "step": 5747
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1102043214612539e-05,
+ "loss": 0.4779,
+ "step": 5748
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1099349775521103e-05,
+ "loss": 0.4833,
+ "step": 5749
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1096656255697991e-05,
+ "loss": 0.4852,
+ "step": 5750
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1093962655341002e-05,
+ "loss": 0.4684,
+ "step": 5751
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1091268974647947e-05,
+ "loss": 0.4879,
+ "step": 5752
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.108857521381664e-05,
+ "loss": 0.4902,
+ "step": 5753
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1085881373044895e-05,
+ "loss": 0.4738,
+ "step": 5754
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1083187452530539e-05,
+ "loss": 0.4899,
+ "step": 5755
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1080493452471403e-05,
+ "loss": 0.4831,
+ "step": 5756
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1077799373065321e-05,
+ "loss": 0.4738,
+ "step": 5757
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1075105214510135e-05,
+ "loss": 0.4864,
+ "step": 5758
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1072410977003693e-05,
+ "loss": 0.4776,
+ "step": 5759
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1069716660743852e-05,
+ "loss": 0.4847,
+ "step": 5760
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1067022265928472e-05,
+ "loss": 0.482,
+ "step": 5761
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1064327792755405e-05,
+ "loss": 0.4857,
+ "step": 5762
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1061633241422538e-05,
+ "loss": 0.4833,
+ "step": 5763
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1058938612127744e-05,
+ "loss": 0.4706,
+ "step": 5764
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1056243905068899e-05,
+ "loss": 0.481,
+ "step": 5765
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1053549120443893e-05,
+ "loss": 0.4646,
+ "step": 5766
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1050854258450623e-05,
+ "loss": 0.4928,
+ "step": 5767
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.104815931928699e-05,
+ "loss": 0.4864,
+ "step": 5768
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1045464303150892e-05,
+ "loss": 0.4873,
+ "step": 5769
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1042769210240248e-05,
+ "loss": 0.4881,
+ "step": 5770
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1040074040752971e-05,
+ "loss": 0.4759,
+ "step": 5771
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1037378794886977e-05,
+ "loss": 0.4723,
+ "step": 5772
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1034683472840201e-05,
+ "loss": 0.468,
+ "step": 5773
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1031988074810578e-05,
+ "loss": 0.4803,
+ "step": 5774
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1029292600996042e-05,
+ "loss": 0.5059,
+ "step": 5775
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1026597051594534e-05,
+ "loss": 0.4792,
+ "step": 5776
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.102390142680401e-05,
+ "loss": 0.4762,
+ "step": 5777
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1021205726822429e-05,
+ "loss": 0.4988,
+ "step": 5778
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1018509951847743e-05,
+ "loss": 0.4742,
+ "step": 5779
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1015814102077921e-05,
+ "loss": 0.4762,
+ "step": 5780
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1013118177710942e-05,
+ "loss": 0.4947,
+ "step": 5781
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1010422178944772e-05,
+ "loss": 0.4727,
+ "step": 5782
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.10077261059774e-05,
+ "loss": 0.4662,
+ "step": 5783
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1005029959006818e-05,
+ "loss": 0.4927,
+ "step": 5784
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.1002333738231016e-05,
+ "loss": 0.4872,
+ "step": 5785
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.099963744384799e-05,
+ "loss": 0.4899,
+ "step": 5786
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0996941076055751e-05,
+ "loss": 0.4824,
+ "step": 5787
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0994244635052304e-05,
+ "loss": 0.4645,
+ "step": 5788
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0991548121035664e-05,
+ "loss": 0.4843,
+ "step": 5789
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.098885153420386e-05,
+ "loss": 0.4767,
+ "step": 5790
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.098615487475491e-05,
+ "loss": 0.4897,
+ "step": 5791
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0983458142886848e-05,
+ "loss": 0.4754,
+ "step": 5792
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0980761338797707e-05,
+ "loss": 0.4671,
+ "step": 5793
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0978064462685536e-05,
+ "loss": 0.4932,
+ "step": 5794
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0975367514748378e-05,
+ "loss": 0.4822,
+ "step": 5795
+ },
+ {
+ "epoch": 0.48,
+ "learning_rate": 1.0972670495184286e-05,
+ "loss": 0.5096,
+ "step": 5796
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0969973404191322e-05,
+ "loss": 0.5035,
+ "step": 5797
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.096727624196754e-05,
+ "loss": 0.4778,
+ "step": 5798
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0964579008711018e-05,
+ "loss": 0.4801,
+ "step": 5799
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0961881704619823e-05,
+ "loss": 0.4845,
+ "step": 5800
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.095918432989204e-05,
+ "loss": 0.4793,
+ "step": 5801
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0956486884725748e-05,
+ "loss": 0.4717,
+ "step": 5802
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0953789369319031e-05,
+ "loss": 0.4756,
+ "step": 5803
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0951091783869998e-05,
+ "loss": 0.485,
+ "step": 5804
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0948394128576739e-05,
+ "loss": 0.496,
+ "step": 5805
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.094569640363736e-05,
+ "loss": 0.4963,
+ "step": 5806
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0942998609249968e-05,
+ "loss": 0.4884,
+ "step": 5807
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0940300745612679e-05,
+ "loss": 0.4687,
+ "step": 5808
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0937602812923617e-05,
+ "loss": 0.4779,
+ "step": 5809
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0934904811380904e-05,
+ "loss": 0.4892,
+ "step": 5810
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0932206741182672e-05,
+ "loss": 0.4831,
+ "step": 5811
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0929508602527052e-05,
+ "loss": 0.4711,
+ "step": 5812
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0926810395612187e-05,
+ "loss": 0.4934,
+ "step": 5813
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0924112120636222e-05,
+ "loss": 0.48,
+ "step": 5814
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0921413777797305e-05,
+ "loss": 0.4744,
+ "step": 5815
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0918715367293595e-05,
+ "loss": 0.4796,
+ "step": 5816
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0916016889323246e-05,
+ "loss": 0.4669,
+ "step": 5817
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0913318344084428e-05,
+ "loss": 0.4656,
+ "step": 5818
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0910619731775311e-05,
+ "loss": 0.4658,
+ "step": 5819
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0907921052594066e-05,
+ "loss": 0.4817,
+ "step": 5820
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0905222306738879e-05,
+ "loss": 0.4862,
+ "step": 5821
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0902523494407928e-05,
+ "loss": 0.4828,
+ "step": 5822
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0899824615799406e-05,
+ "loss": 0.4725,
+ "step": 5823
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0897125671111507e-05,
+ "loss": 0.4827,
+ "step": 5824
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.089442666054243e-05,
+ "loss": 0.4902,
+ "step": 5825
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0891727584290381e-05,
+ "loss": 0.465,
+ "step": 5826
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0889028442553565e-05,
+ "loss": 0.4795,
+ "step": 5827
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.08863292355302e-05,
+ "loss": 0.4693,
+ "step": 5828
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0883629963418501e-05,
+ "loss": 0.4781,
+ "step": 5829
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.088093062641669e-05,
+ "loss": 0.5004,
+ "step": 5830
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0878231224723001e-05,
+ "loss": 0.4815,
+ "step": 5831
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0875531758535668e-05,
+ "loss": 0.4879,
+ "step": 5832
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0872832228052919e-05,
+ "loss": 0.4919,
+ "step": 5833
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0870132633472999e-05,
+ "loss": 0.5049,
+ "step": 5834
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0867432974994162e-05,
+ "loss": 0.4874,
+ "step": 5835
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0864733252814654e-05,
+ "loss": 0.4906,
+ "step": 5836
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0862033467132732e-05,
+ "loss": 0.4875,
+ "step": 5837
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0859333618146659e-05,
+ "loss": 0.4617,
+ "step": 5838
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0856633706054698e-05,
+ "loss": 0.4761,
+ "step": 5839
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0853933731055122e-05,
+ "loss": 0.4735,
+ "step": 5840
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0851233693346204e-05,
+ "loss": 0.4843,
+ "step": 5841
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0848533593126225e-05,
+ "loss": 0.4845,
+ "step": 5842
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0845833430593467e-05,
+ "loss": 0.4731,
+ "step": 5843
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0843133205946218e-05,
+ "loss": 0.4897,
+ "step": 5844
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0840432919382774e-05,
+ "loss": 0.501,
+ "step": 5845
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0837732571101437e-05,
+ "loss": 0.4934,
+ "step": 5846
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0835032161300499e-05,
+ "loss": 0.4878,
+ "step": 5847
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0832331690178274e-05,
+ "loss": 0.4885,
+ "step": 5848
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0829631157933071e-05,
+ "loss": 0.4741,
+ "step": 5849
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0826930564763207e-05,
+ "loss": 0.5027,
+ "step": 5850
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0824229910867002e-05,
+ "loss": 0.4769,
+ "step": 5851
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0821529196442782e-05,
+ "loss": 0.4863,
+ "step": 5852
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0818828421688873e-05,
+ "loss": 0.4707,
+ "step": 5853
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.081612758680361e-05,
+ "loss": 0.4718,
+ "step": 5854
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0813426691985331e-05,
+ "loss": 0.469,
+ "step": 5855
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0810725737432381e-05,
+ "loss": 0.4993,
+ "step": 5856
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0808024723343104e-05,
+ "loss": 0.4695,
+ "step": 5857
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0805323649915854e-05,
+ "loss": 0.4555,
+ "step": 5858
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0802622517348982e-05,
+ "loss": 0.4673,
+ "step": 5859
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0799921325840851e-05,
+ "loss": 0.4788,
+ "step": 5860
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0797220075589825e-05,
+ "loss": 0.4518,
+ "step": 5861
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0794518766794272e-05,
+ "loss": 0.4822,
+ "step": 5862
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.079181739965257e-05,
+ "loss": 0.4787,
+ "step": 5863
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0789115974363086e-05,
+ "loss": 0.4897,
+ "step": 5864
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0786414491124208e-05,
+ "loss": 0.4997,
+ "step": 5865
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0783712950134324e-05,
+ "loss": 0.4807,
+ "step": 5866
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0781011351591819e-05,
+ "loss": 0.4609,
+ "step": 5867
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0778309695695088e-05,
+ "loss": 0.4857,
+ "step": 5868
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.077560798264253e-05,
+ "loss": 0.4819,
+ "step": 5869
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0772906212632547e-05,
+ "loss": 0.4784,
+ "step": 5870
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0770204385863547e-05,
+ "loss": 0.4976,
+ "step": 5871
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0767502502533945e-05,
+ "loss": 0.473,
+ "step": 5872
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0764800562842149e-05,
+ "loss": 0.4696,
+ "step": 5873
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0762098566986578e-05,
+ "loss": 0.4932,
+ "step": 5874
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0759396515165657e-05,
+ "loss": 0.4942,
+ "step": 5875
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.075669440757782e-05,
+ "loss": 0.4632,
+ "step": 5876
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.075399224442149e-05,
+ "loss": 0.477,
+ "step": 5877
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0751290025895104e-05,
+ "loss": 0.49,
+ "step": 5878
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0748587752197106e-05,
+ "loss": 0.4698,
+ "step": 5879
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0745885423525934e-05,
+ "loss": 0.4739,
+ "step": 5880
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0743183040080043e-05,
+ "loss": 0.4757,
+ "step": 5881
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0740480602057877e-05,
+ "loss": 0.4677,
+ "step": 5882
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0737778109657899e-05,
+ "loss": 0.4867,
+ "step": 5883
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0735075563078565e-05,
+ "loss": 0.4678,
+ "step": 5884
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0732372962518337e-05,
+ "loss": 0.4661,
+ "step": 5885
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0729670308175683e-05,
+ "loss": 0.4743,
+ "step": 5886
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.072696760024908e-05,
+ "loss": 0.4877,
+ "step": 5887
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0724264838936998e-05,
+ "loss": 0.4869,
+ "step": 5888
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0721562024437919e-05,
+ "loss": 0.4722,
+ "step": 5889
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0718859156950329e-05,
+ "loss": 0.4959,
+ "step": 5890
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.071615623667271e-05,
+ "loss": 0.4653,
+ "step": 5891
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0713453263803553e-05,
+ "loss": 0.4606,
+ "step": 5892
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.071075023854136e-05,
+ "loss": 0.49,
+ "step": 5893
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0708047161084626e-05,
+ "loss": 0.4895,
+ "step": 5894
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.070534403163185e-05,
+ "loss": 0.4806,
+ "step": 5895
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0702640850381542e-05,
+ "loss": 0.4713,
+ "step": 5896
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0699937617532216e-05,
+ "loss": 0.4832,
+ "step": 5897
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0697234333282382e-05,
+ "loss": 0.4784,
+ "step": 5898
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0694530997830556e-05,
+ "loss": 0.4696,
+ "step": 5899
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0691827611375268e-05,
+ "loss": 0.5059,
+ "step": 5900
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.068912417411503e-05,
+ "loss": 0.4705,
+ "step": 5901
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0686420686248382e-05,
+ "loss": 0.4696,
+ "step": 5902
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0683717147973856e-05,
+ "loss": 0.4935,
+ "step": 5903
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0681013559489985e-05,
+ "loss": 0.4837,
+ "step": 5904
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.067830992099531e-05,
+ "loss": 0.4748,
+ "step": 5905
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0675606232688377e-05,
+ "loss": 0.4827,
+ "step": 5906
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0672902494767731e-05,
+ "loss": 0.5115,
+ "step": 5907
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0670198707431927e-05,
+ "loss": 0.4813,
+ "step": 5908
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0667494870879513e-05,
+ "loss": 0.4771,
+ "step": 5909
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0664790985309058e-05,
+ "loss": 0.5049,
+ "step": 5910
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0662087050919111e-05,
+ "loss": 0.4861,
+ "step": 5911
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.065938306790825e-05,
+ "loss": 0.4752,
+ "step": 5912
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0656679036475038e-05,
+ "loss": 0.4789,
+ "step": 5913
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.065397495681805e-05,
+ "loss": 0.4715,
+ "step": 5914
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.065127082913586e-05,
+ "loss": 0.4669,
+ "step": 5915
+ },
+ {
+ "epoch": 0.49,
+ "learning_rate": 1.0648566653627048e-05,
+ "loss": 0.4878,
+ "step": 5916
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.06458624304902e-05,
+ "loss": 0.4657,
+ "step": 5917
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0643158159923902e-05,
+ "loss": 0.4867,
+ "step": 5918
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0640453842126742e-05,
+ "loss": 0.4842,
+ "step": 5919
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0637749477297317e-05,
+ "loss": 0.4846,
+ "step": 5920
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.063504506563422e-05,
+ "loss": 0.4753,
+ "step": 5921
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0632340607336056e-05,
+ "loss": 0.4803,
+ "step": 5922
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.062963610260143e-05,
+ "loss": 0.4649,
+ "step": 5923
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0626931551628948e-05,
+ "loss": 0.5102,
+ "step": 5924
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0624226954617221e-05,
+ "loss": 0.4758,
+ "step": 5925
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0621522311764857e-05,
+ "loss": 0.4701,
+ "step": 5926
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0618817623270484e-05,
+ "loss": 0.4919,
+ "step": 5927
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.061611288933272e-05,
+ "loss": 0.5002,
+ "step": 5928
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0613408110150185e-05,
+ "loss": 0.4994,
+ "step": 5929
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.061070328592151e-05,
+ "loss": 0.4734,
+ "step": 5930
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0607998416845329e-05,
+ "loss": 0.4737,
+ "step": 5931
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0605293503120268e-05,
+ "loss": 0.4695,
+ "step": 5932
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0602588544944972e-05,
+ "loss": 0.4705,
+ "step": 5933
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.059988354251808e-05,
+ "loss": 0.4683,
+ "step": 5934
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.059717849603824e-05,
+ "loss": 0.4895,
+ "step": 5935
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0594473405704088e-05,
+ "loss": 0.4732,
+ "step": 5936
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0591768271714285e-05,
+ "loss": 0.4844,
+ "step": 5937
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.058906309426748e-05,
+ "loss": 0.4746,
+ "step": 5938
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0586357873562332e-05,
+ "loss": 0.4765,
+ "step": 5939
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0583652609797501e-05,
+ "loss": 0.4753,
+ "step": 5940
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0580947303171651e-05,
+ "loss": 0.4755,
+ "step": 5941
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0578241953883445e-05,
+ "loss": 0.4855,
+ "step": 5942
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0575536562131556e-05,
+ "loss": 0.4863,
+ "step": 5943
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0572831128114658e-05,
+ "loss": 0.4672,
+ "step": 5944
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0570125652031425e-05,
+ "loss": 0.4928,
+ "step": 5945
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0567420134080531e-05,
+ "loss": 0.4896,
+ "step": 5946
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0564714574460664e-05,
+ "loss": 0.4839,
+ "step": 5947
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0562008973370508e-05,
+ "loss": 0.4808,
+ "step": 5948
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0559303331008752e-05,
+ "loss": 0.4783,
+ "step": 5949
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0556597647574083e-05,
+ "loss": 0.4887,
+ "step": 5950
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.05538919232652e-05,
+ "loss": 0.4867,
+ "step": 5951
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0551186158280795e-05,
+ "loss": 0.5122,
+ "step": 5952
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0548480352819573e-05,
+ "loss": 0.4623,
+ "step": 5953
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0545774507080237e-05,
+ "loss": 0.4677,
+ "step": 5954
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.054306862126149e-05,
+ "loss": 0.4772,
+ "step": 5955
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0540362695562043e-05,
+ "loss": 0.4747,
+ "step": 5956
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0537656730180606e-05,
+ "loss": 0.4751,
+ "step": 5957
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0534950725315893e-05,
+ "loss": 0.4904,
+ "step": 5958
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0532244681166628e-05,
+ "loss": 0.4845,
+ "step": 5959
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0529538597931524e-05,
+ "loss": 0.4788,
+ "step": 5960
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.052683247580931e-05,
+ "loss": 0.4771,
+ "step": 5961
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0524126314998711e-05,
+ "loss": 0.4895,
+ "step": 5962
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0521420115698448e-05,
+ "loss": 0.4743,
+ "step": 5963
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0518713878107268e-05,
+ "loss": 0.4543,
+ "step": 5964
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0516007602423896e-05,
+ "loss": 0.4893,
+ "step": 5965
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0513301288847076e-05,
+ "loss": 0.4831,
+ "step": 5966
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0510594937575537e-05,
+ "loss": 0.4739,
+ "step": 5967
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0507888548808034e-05,
+ "loss": 0.4901,
+ "step": 5968
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0505182122743309e-05,
+ "loss": 0.4903,
+ "step": 5969
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0502475659580107e-05,
+ "loss": 0.4827,
+ "step": 5970
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0499769159517186e-05,
+ "loss": 0.4875,
+ "step": 5971
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0497062622753296e-05,
+ "loss": 0.4978,
+ "step": 5972
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.049435604948719e-05,
+ "loss": 0.4832,
+ "step": 5973
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0491649439917636e-05,
+ "loss": 0.4586,
+ "step": 5974
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0488942794243393e-05,
+ "loss": 0.4639,
+ "step": 5975
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0486236112663224e-05,
+ "loss": 0.4936,
+ "step": 5976
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0483529395375896e-05,
+ "loss": 0.4603,
+ "step": 5977
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0480822642580178e-05,
+ "loss": 0.4836,
+ "step": 5978
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0478115854474848e-05,
+ "loss": 0.5113,
+ "step": 5979
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0475409031258678e-05,
+ "loss": 0.4747,
+ "step": 5980
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0472702173130447e-05,
+ "loss": 0.4841,
+ "step": 5981
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0469995280288936e-05,
+ "loss": 0.4726,
+ "step": 5982
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0467288352932923e-05,
+ "loss": 0.47,
+ "step": 5983
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0464581391261198e-05,
+ "loss": 0.4819,
+ "step": 5984
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0461874395472549e-05,
+ "loss": 0.4767,
+ "step": 5985
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0459167365765765e-05,
+ "loss": 0.4681,
+ "step": 5986
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0456460302339636e-05,
+ "loss": 0.4776,
+ "step": 5987
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0453753205392967e-05,
+ "loss": 0.4719,
+ "step": 5988
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0451046075124544e-05,
+ "loss": 0.4728,
+ "step": 5989
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0448338911733178e-05,
+ "loss": 0.4883,
+ "step": 5990
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0445631715417666e-05,
+ "loss": 0.5035,
+ "step": 5991
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0442924486376813e-05,
+ "loss": 0.4744,
+ "step": 5992
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0440217224809427e-05,
+ "loss": 0.498,
+ "step": 5993
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.043750993091432e-05,
+ "loss": 0.4707,
+ "step": 5994
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0434802604890306e-05,
+ "loss": 0.4854,
+ "step": 5995
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0432095246936195e-05,
+ "loss": 0.4768,
+ "step": 5996
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0429387857250806e-05,
+ "loss": 0.4729,
+ "step": 5997
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.042668043603296e-05,
+ "loss": 0.483,
+ "step": 5998
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0423972983481477e-05,
+ "loss": 0.4757,
+ "step": 5999
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0421265499795181e-05,
+ "loss": 0.4865,
+ "step": 6000
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0418557985172899e-05,
+ "loss": 0.4946,
+ "step": 6001
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0415850439813462e-05,
+ "loss": 0.4533,
+ "step": 6002
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0413142863915695e-05,
+ "loss": 0.4847,
+ "step": 6003
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0410435257678433e-05,
+ "loss": 0.4828,
+ "step": 6004
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0407727621300516e-05,
+ "loss": 0.4671,
+ "step": 6005
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0405019954980779e-05,
+ "loss": 0.4716,
+ "step": 6006
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0402312258918061e-05,
+ "loss": 0.4786,
+ "step": 6007
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.03996045333112e-05,
+ "loss": 0.4873,
+ "step": 6008
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0396896778359047e-05,
+ "loss": 0.479,
+ "step": 6009
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0394188994260445e-05,
+ "loss": 0.463,
+ "step": 6010
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0391481181214244e-05,
+ "loss": 0.4551,
+ "step": 6011
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0388773339419294e-05,
+ "loss": 0.4634,
+ "step": 6012
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0386065469074447e-05,
+ "loss": 0.4834,
+ "step": 6013
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0383357570378553e-05,
+ "loss": 0.4901,
+ "step": 6014
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0380649643530476e-05,
+ "loss": 0.4779,
+ "step": 6015
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0377941688729074e-05,
+ "loss": 0.4925,
+ "step": 6016
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0375233706173207e-05,
+ "loss": 0.4912,
+ "step": 6017
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0372525696061735e-05,
+ "loss": 0.4781,
+ "step": 6018
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0369817658593524e-05,
+ "loss": 0.4854,
+ "step": 6019
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0367109593967445e-05,
+ "loss": 0.4858,
+ "step": 6020
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0364401502382364e-05,
+ "loss": 0.4811,
+ "step": 6021
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0361693384037154e-05,
+ "loss": 0.4865,
+ "step": 6022
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0358985239130685e-05,
+ "loss": 0.4867,
+ "step": 6023
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.035627706786183e-05,
+ "loss": 0.4796,
+ "step": 6024
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.035356887042947e-05,
+ "loss": 0.486,
+ "step": 6025
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0350860647032488e-05,
+ "loss": 0.4733,
+ "step": 6026
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0348152397869757e-05,
+ "loss": 0.4706,
+ "step": 6027
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0345444123140159e-05,
+ "loss": 0.4709,
+ "step": 6028
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0342735823042585e-05,
+ "loss": 0.4718,
+ "step": 6029
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0340027497775915e-05,
+ "loss": 0.476,
+ "step": 6030
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0337319147539042e-05,
+ "loss": 0.4838,
+ "step": 6031
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0334610772530851e-05,
+ "loss": 0.4914,
+ "step": 6032
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.033190237295024e-05,
+ "loss": 0.4516,
+ "step": 6033
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0329193948996097e-05,
+ "loss": 0.4834,
+ "step": 6034
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0326485500867316e-05,
+ "loss": 0.4735,
+ "step": 6035
+ },
+ {
+ "epoch": 0.5,
+ "learning_rate": 1.0323777028762804e-05,
+ "loss": 0.4786,
+ "step": 6036
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0321068532881454e-05,
+ "loss": 0.4708,
+ "step": 6037
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0318360013422162e-05,
+ "loss": 0.5103,
+ "step": 6038
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0315651470583836e-05,
+ "loss": 0.5011,
+ "step": 6039
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0312942904565379e-05,
+ "loss": 0.4685,
+ "step": 6040
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0310234315565699e-05,
+ "loss": 0.4897,
+ "step": 6041
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0307525703783698e-05,
+ "loss": 0.489,
+ "step": 6042
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0304817069418292e-05,
+ "loss": 0.4754,
+ "step": 6043
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0302108412668387e-05,
+ "loss": 0.4889,
+ "step": 6044
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0299399733732893e-05,
+ "loss": 0.4967,
+ "step": 6045
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.029669103281073e-05,
+ "loss": 0.4701,
+ "step": 6046
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0293982310100814e-05,
+ "loss": 0.4751,
+ "step": 6047
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0291273565802058e-05,
+ "loss": 0.4912,
+ "step": 6048
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0288564800113383e-05,
+ "loss": 0.4817,
+ "step": 6049
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0285856013233708e-05,
+ "loss": 0.4599,
+ "step": 6050
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0283147205361959e-05,
+ "loss": 0.4964,
+ "step": 6051
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0280438376697056e-05,
+ "loss": 0.4632,
+ "step": 6052
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0277729527437924e-05,
+ "loss": 0.463,
+ "step": 6053
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0275020657783492e-05,
+ "loss": 0.493,
+ "step": 6054
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0272311767932686e-05,
+ "loss": 0.4833,
+ "step": 6055
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0269602858084435e-05,
+ "loss": 0.4912,
+ "step": 6056
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0266893928437673e-05,
+ "loss": 0.481,
+ "step": 6057
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0264184979191331e-05,
+ "loss": 0.4745,
+ "step": 6058
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0261476010544345e-05,
+ "loss": 0.4958,
+ "step": 6059
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0258767022695645e-05,
+ "loss": 0.491,
+ "step": 6060
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0256058015844173e-05,
+ "loss": 0.4881,
+ "step": 6061
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0253348990188863e-05,
+ "loss": 0.4736,
+ "step": 6062
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.025063994592866e-05,
+ "loss": 0.4744,
+ "step": 6063
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.02479308832625e-05,
+ "loss": 0.4759,
+ "step": 6064
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0245221802389328e-05,
+ "loss": 0.4655,
+ "step": 6065
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0242512703508085e-05,
+ "loss": 0.4912,
+ "step": 6066
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.023980358681772e-05,
+ "loss": 0.4852,
+ "step": 6067
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0237094452517178e-05,
+ "loss": 0.4838,
+ "step": 6068
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0234385300805403e-05,
+ "loss": 0.4851,
+ "step": 6069
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0231676131881348e-05,
+ "loss": 0.4732,
+ "step": 6070
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.022896694594396e-05,
+ "loss": 0.4902,
+ "step": 6071
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.022625774319219e-05,
+ "loss": 0.4603,
+ "step": 6072
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0223548523824996e-05,
+ "loss": 0.4785,
+ "step": 6073
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0220839288041328e-05,
+ "loss": 0.4651,
+ "step": 6074
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.021813003604014e-05,
+ "loss": 0.4707,
+ "step": 6075
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0215420768020388e-05,
+ "loss": 0.5073,
+ "step": 6076
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0212711484181034e-05,
+ "loss": 0.4872,
+ "step": 6077
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0210002184721033e-05,
+ "loss": 0.4836,
+ "step": 6078
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0207292869839343e-05,
+ "loss": 0.46,
+ "step": 6079
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.020458353973493e-05,
+ "loss": 0.4641,
+ "step": 6080
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0201874194606748e-05,
+ "loss": 0.4703,
+ "step": 6081
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.019916483465377e-05,
+ "loss": 0.4775,
+ "step": 6082
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.019645546007495e-05,
+ "loss": 0.4857,
+ "step": 6083
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0193746071069262e-05,
+ "loss": 0.4703,
+ "step": 6084
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0191036667835668e-05,
+ "loss": 0.4713,
+ "step": 6085
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0188327250573133e-05,
+ "loss": 0.4823,
+ "step": 6086
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0185617819480628e-05,
+ "loss": 0.4943,
+ "step": 6087
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0182908374757126e-05,
+ "loss": 0.4849,
+ "step": 6088
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0180198916601592e-05,
+ "loss": 0.4815,
+ "step": 6089
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0177489445212998e-05,
+ "loss": 0.486,
+ "step": 6090
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0174779960790318e-05,
+ "loss": 0.4575,
+ "step": 6091
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0172070463532524e-05,
+ "loss": 0.4709,
+ "step": 6092
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.016936095363859e-05,
+ "loss": 0.4649,
+ "step": 6093
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0166651431307494e-05,
+ "loss": 0.4872,
+ "step": 6094
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0163941896738213e-05,
+ "loss": 0.4819,
+ "step": 6095
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0161232350129715e-05,
+ "loss": 0.4658,
+ "step": 6096
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0158522791680985e-05,
+ "loss": 0.4744,
+ "step": 6097
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0155813221591004e-05,
+ "loss": 0.4849,
+ "step": 6098
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0153103640058745e-05,
+ "loss": 0.4775,
+ "step": 6099
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0150394047283192e-05,
+ "loss": 0.4644,
+ "step": 6100
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0147684443463328e-05,
+ "loss": 0.4933,
+ "step": 6101
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0144974828798131e-05,
+ "loss": 0.4612,
+ "step": 6102
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0142265203486583e-05,
+ "loss": 0.4857,
+ "step": 6103
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0139555567727674e-05,
+ "loss": 0.4879,
+ "step": 6104
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0136845921720385e-05,
+ "loss": 0.4769,
+ "step": 6105
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0134136265663698e-05,
+ "loss": 0.4763,
+ "step": 6106
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.01314265997566e-05,
+ "loss": 0.4778,
+ "step": 6107
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0128716924198083e-05,
+ "loss": 0.4715,
+ "step": 6108
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.012600723918713e-05,
+ "loss": 0.468,
+ "step": 6109
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0123297544922728e-05,
+ "loss": 0.5026,
+ "step": 6110
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0120587841603868e-05,
+ "loss": 0.4965,
+ "step": 6111
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.011787812942954e-05,
+ "loss": 0.4759,
+ "step": 6112
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0115168408598728e-05,
+ "loss": 0.4755,
+ "step": 6113
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.011245867931043e-05,
+ "loss": 0.4671,
+ "step": 6114
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0109748941763635e-05,
+ "loss": 0.4646,
+ "step": 6115
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0107039196157335e-05,
+ "loss": 0.4868,
+ "step": 6116
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.010432944269052e-05,
+ "loss": 0.4626,
+ "step": 6117
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0101619681562183e-05,
+ "loss": 0.4982,
+ "step": 6118
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0098909912971322e-05,
+ "loss": 0.4729,
+ "step": 6119
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0096200137116924e-05,
+ "loss": 0.4953,
+ "step": 6120
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0093490354197994e-05,
+ "loss": 0.4823,
+ "step": 6121
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0090780564413518e-05,
+ "loss": 0.4974,
+ "step": 6122
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0088070767962497e-05,
+ "loss": 0.4955,
+ "step": 6123
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0085360965043923e-05,
+ "loss": 0.4789,
+ "step": 6124
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0082651155856795e-05,
+ "loss": 0.4786,
+ "step": 6125
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.007994134060011e-05,
+ "loss": 0.4877,
+ "step": 6126
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0077231519472866e-05,
+ "loss": 0.4656,
+ "step": 6127
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.007452169267406e-05,
+ "loss": 0.4981,
+ "step": 6128
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0071811860402692e-05,
+ "loss": 0.5001,
+ "step": 6129
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0069102022857757e-05,
+ "loss": 0.4817,
+ "step": 6130
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0066392180238258e-05,
+ "loss": 0.4879,
+ "step": 6131
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0063682332743196e-05,
+ "loss": 0.4897,
+ "step": 6132
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0060972480571565e-05,
+ "loss": 0.4781,
+ "step": 6133
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0058262623922368e-05,
+ "loss": 0.4542,
+ "step": 6134
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.005555276299461e-05,
+ "loss": 0.4887,
+ "step": 6135
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0052842897987288e-05,
+ "loss": 0.4949,
+ "step": 6136
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0050133029099401e-05,
+ "loss": 0.4703,
+ "step": 6137
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0047423156529952e-05,
+ "loss": 0.4776,
+ "step": 6138
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0044713280477946e-05,
+ "loss": 0.4973,
+ "step": 6139
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0042003401142383e-05,
+ "loss": 0.4845,
+ "step": 6140
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0039293518722262e-05,
+ "loss": 0.4794,
+ "step": 6141
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0036583633416593e-05,
+ "loss": 0.4974,
+ "step": 6142
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0033873745424369e-05,
+ "loss": 0.4832,
+ "step": 6143
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.00311638549446e-05,
+ "loss": 0.4864,
+ "step": 6144
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0028453962176287e-05,
+ "loss": 0.4641,
+ "step": 6145
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0025744067318435e-05,
+ "loss": 0.4801,
+ "step": 6146
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0023034170570044e-05,
+ "loss": 0.4759,
+ "step": 6147
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0020324272130117e-05,
+ "loss": 0.4816,
+ "step": 6148
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0017614372197667e-05,
+ "loss": 0.4867,
+ "step": 6149
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0014904470971686e-05,
+ "loss": 0.4779,
+ "step": 6150
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0012194568651184e-05,
+ "loss": 0.4897,
+ "step": 6151
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0009484665435163e-05,
+ "loss": 0.4805,
+ "step": 6152
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0006774761522626e-05,
+ "loss": 0.4745,
+ "step": 6153
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.000406485711258e-05,
+ "loss": 0.4776,
+ "step": 6154
+ },
+ {
+ "epoch": 0.51,
+ "learning_rate": 1.0001354952404027e-05,
+ "loss": 0.4708,
+ "step": 6155
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.998645047595975e-06,
+ "loss": 0.4719,
+ "step": 6156
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.995935142887424e-06,
+ "loss": 0.4778,
+ "step": 6157
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.993225238477377e-06,
+ "loss": 0.479,
+ "step": 6158
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.99051533456484e-06,
+ "loss": 0.4616,
+ "step": 6159
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.987805431348818e-06,
+ "loss": 0.4924,
+ "step": 6160
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.985095529028317e-06,
+ "loss": 0.4886,
+ "step": 6161
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.982385627802338e-06,
+ "loss": 0.473,
+ "step": 6162
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.979675727869884e-06,
+ "loss": 0.5046,
+ "step": 6163
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.976965829429958e-06,
+ "loss": 0.4845,
+ "step": 6164
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.97425593268157e-06,
+ "loss": 0.4805,
+ "step": 6165
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.971546037823713e-06,
+ "loss": 0.4887,
+ "step": 6166
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.968836145055402e-06,
+ "loss": 0.4882,
+ "step": 6167
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.966126254575634e-06,
+ "loss": 0.4744,
+ "step": 6168
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.963416366583412e-06,
+ "loss": 0.4752,
+ "step": 6169
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.960706481277742e-06,
+ "loss": 0.4858,
+ "step": 6170
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.957996598857622e-06,
+ "loss": 0.4589,
+ "step": 6171
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.955286719522059e-06,
+ "loss": 0.4713,
+ "step": 6172
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.952576843470048e-06,
+ "loss": 0.5407,
+ "step": 6173
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.949866970900602e-06,
+ "loss": 0.4929,
+ "step": 6174
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.947157102012716e-06,
+ "loss": 0.4734,
+ "step": 6175
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.944447237005392e-06,
+ "loss": 0.4758,
+ "step": 6176
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.941737376077634e-06,
+ "loss": 0.4628,
+ "step": 6177
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.93902751942844e-06,
+ "loss": 0.4739,
+ "step": 6178
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.93631766725681e-06,
+ "loss": 0.4739,
+ "step": 6179
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.93360781976174e-06,
+ "loss": 0.488,
+ "step": 6180
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.930897977142245e-06,
+ "loss": 0.484,
+ "step": 6181
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.928188139597313e-06,
+ "loss": 0.4858,
+ "step": 6182
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.925478307325944e-06,
+ "loss": 0.4791,
+ "step": 6183
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.922768480527138e-06,
+ "loss": 0.4836,
+ "step": 6184
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.920058659399895e-06,
+ "loss": 0.471,
+ "step": 6185
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.91734884414321e-06,
+ "loss": 0.4773,
+ "step": 6186
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.914639034956079e-06,
+ "loss": 0.4778,
+ "step": 6187
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.911929232037507e-06,
+ "loss": 0.4983,
+ "step": 6188
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.909219435586485e-06,
+ "loss": 0.4768,
+ "step": 6189
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.906509645802009e-06,
+ "loss": 0.4848,
+ "step": 6190
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.903799862883077e-06,
+ "loss": 0.4802,
+ "step": 6191
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.901090087028685e-06,
+ "loss": 0.4775,
+ "step": 6192
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.898380318437822e-06,
+ "loss": 0.4846,
+ "step": 6193
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.895670557309484e-06,
+ "loss": 0.4832,
+ "step": 6194
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.892960803842668e-06,
+ "loss": 0.4866,
+ "step": 6195
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.890251058236368e-06,
+ "loss": 0.4776,
+ "step": 6196
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.887541320689573e-06,
+ "loss": 0.4772,
+ "step": 6197
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.884831591401276e-06,
+ "loss": 0.5,
+ "step": 6198
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.882121870570465e-06,
+ "loss": 0.4832,
+ "step": 6199
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.879412158396134e-06,
+ "loss": 0.4802,
+ "step": 6200
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.876702455077272e-06,
+ "loss": 0.4718,
+ "step": 6201
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.873992760812871e-06,
+ "loss": 0.4742,
+ "step": 6202
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.87128307580192e-06,
+ "loss": 0.4717,
+ "step": 6203
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.868573400243402e-06,
+ "loss": 0.4813,
+ "step": 6204
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.865863734336305e-06,
+ "loss": 0.4895,
+ "step": 6205
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.86315407827962e-06,
+ "loss": 0.4889,
+ "step": 6206
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.860444432272328e-06,
+ "loss": 0.4873,
+ "step": 6207
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.857734796513417e-06,
+ "loss": 0.4915,
+ "step": 6208
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.855025171201874e-06,
+ "loss": 0.4696,
+ "step": 6209
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.852315556536674e-06,
+ "loss": 0.4605,
+ "step": 6210
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.84960595271681e-06,
+ "loss": 0.4808,
+ "step": 6211
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.846896359941258e-06,
+ "loss": 0.4867,
+ "step": 6212
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.844186778409002e-06,
+ "loss": 0.4805,
+ "step": 6213
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.841477208319015e-06,
+ "loss": 0.4754,
+ "step": 6214
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.838767649870287e-06,
+ "loss": 0.4691,
+ "step": 6215
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.83605810326179e-06,
+ "loss": 0.4701,
+ "step": 6216
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.833348568692507e-06,
+ "loss": 0.4799,
+ "step": 6217
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.830639046361412e-06,
+ "loss": 0.4803,
+ "step": 6218
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.82792953646748e-06,
+ "loss": 0.4602,
+ "step": 6219
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.825220039209687e-06,
+ "loss": 0.4757,
+ "step": 6220
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.822510554787004e-06,
+ "loss": 0.4817,
+ "step": 6221
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.819801083398411e-06,
+ "loss": 0.4772,
+ "step": 6222
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.817091625242879e-06,
+ "loss": 0.4876,
+ "step": 6223
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.814382180519375e-06,
+ "loss": 0.4803,
+ "step": 6224
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.81167274942687e-06,
+ "loss": 0.4761,
+ "step": 6225
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.808963332164337e-06,
+ "loss": 0.4727,
+ "step": 6226
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.806253928930743e-06,
+ "loss": 0.468,
+ "step": 6227
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.80354453992505e-06,
+ "loss": 0.4583,
+ "step": 6228
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.800835165346234e-06,
+ "loss": 0.4972,
+ "step": 6229
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.798125805393255e-06,
+ "loss": 0.4874,
+ "step": 6230
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.795416460265074e-06,
+ "loss": 0.4627,
+ "step": 6231
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.79270713016066e-06,
+ "loss": 0.5072,
+ "step": 6232
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.789997815278973e-06,
+ "loss": 0.4845,
+ "step": 6233
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.787288515818968e-06,
+ "loss": 0.4799,
+ "step": 6234
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.784579231979612e-06,
+ "loss": 0.47,
+ "step": 6235
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.781869963959861e-06,
+ "loss": 0.4865,
+ "step": 6236
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.779160711958673e-06,
+ "loss": 0.4727,
+ "step": 6237
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.776451476175006e-06,
+ "loss": 0.4904,
+ "step": 6238
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.773742256807812e-06,
+ "loss": 0.4865,
+ "step": 6239
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.771033054056044e-06,
+ "loss": 0.4669,
+ "step": 6240
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.768323868118656e-06,
+ "loss": 0.4877,
+ "step": 6241
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.765614699194598e-06,
+ "loss": 0.469,
+ "step": 6242
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.762905547482825e-06,
+ "loss": 0.473,
+ "step": 6243
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.760196413182283e-06,
+ "loss": 0.4738,
+ "step": 6244
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.757487296491918e-06,
+ "loss": 0.4813,
+ "step": 6245
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.754778197610674e-06,
+ "loss": 0.4992,
+ "step": 6246
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.752069116737504e-06,
+ "loss": 0.4679,
+ "step": 6247
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.74936005407134e-06,
+ "loss": 0.456,
+ "step": 6248
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.746651009811137e-06,
+ "loss": 0.4749,
+ "step": 6249
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.74394198415583e-06,
+ "loss": 0.4758,
+ "step": 6250
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.741232977304356e-06,
+ "loss": 0.4719,
+ "step": 6251
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.738523989455659e-06,
+ "loss": 0.4639,
+ "step": 6252
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.735815020808672e-06,
+ "loss": 0.4738,
+ "step": 6253
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.733106071562332e-06,
+ "loss": 0.4639,
+ "step": 6254
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.730397141915567e-06,
+ "loss": 0.4905,
+ "step": 6255
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.727688232067318e-06,
+ "loss": 0.4697,
+ "step": 6256
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.72497934221651e-06,
+ "loss": 0.4867,
+ "step": 6257
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.722270472562078e-06,
+ "loss": 0.4721,
+ "step": 6258
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.71956162330295e-06,
+ "loss": 0.4716,
+ "step": 6259
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.716852794638046e-06,
+ "loss": 0.4712,
+ "step": 6260
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.714143986766294e-06,
+ "loss": 0.4798,
+ "step": 6261
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.711435199886618e-06,
+ "loss": 0.4679,
+ "step": 6262
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.708726434197944e-06,
+ "loss": 0.4605,
+ "step": 6263
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.706017689899189e-06,
+ "loss": 0.4812,
+ "step": 6264
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.703308967189273e-06,
+ "loss": 0.4768,
+ "step": 6265
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.700600266267109e-06,
+ "loss": 0.4735,
+ "step": 6266
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.697891587331618e-06,
+ "loss": 0.4862,
+ "step": 6267
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.695182930581715e-06,
+ "loss": 0.4751,
+ "step": 6268
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.692474296216303e-06,
+ "loss": 0.4512,
+ "step": 6269
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.689765684434305e-06,
+ "loss": 0.4947,
+ "step": 6270
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.687057095434624e-06,
+ "loss": 0.4816,
+ "step": 6271
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.684348529416166e-06,
+ "loss": 0.4744,
+ "step": 6272
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.681639986577841e-06,
+ "loss": 0.4612,
+ "step": 6273
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.678931467118553e-06,
+ "loss": 0.4734,
+ "step": 6274
+ },
+ {
+ "epoch": 0.52,
+ "learning_rate": 9.676222971237197e-06,
+ "loss": 0.4665,
+ "step": 6275
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.673514499132683e-06,
+ "loss": 0.4761,
+ "step": 6276
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.670806051003906e-06,
+ "loss": 0.4849,
+ "step": 6277
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.668097627049765e-06,
+ "loss": 0.479,
+ "step": 6278
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.665389227469152e-06,
+ "loss": 0.471,
+ "step": 6279
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.662680852460963e-06,
+ "loss": 0.4824,
+ "step": 6280
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.659972502224089e-06,
+ "loss": 0.4746,
+ "step": 6281
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.657264176957419e-06,
+ "loss": 0.4834,
+ "step": 6282
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.654555876859841e-06,
+ "loss": 0.4928,
+ "step": 6283
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.651847602130247e-06,
+ "loss": 0.4866,
+ "step": 6284
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.649139352967515e-06,
+ "loss": 0.4769,
+ "step": 6285
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.646431129570531e-06,
+ "loss": 0.4794,
+ "step": 6286
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.643722932138172e-06,
+ "loss": 0.4776,
+ "step": 6287
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.64101476086932e-06,
+ "loss": 0.4743,
+ "step": 6288
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.638306615962847e-06,
+ "loss": 0.4793,
+ "step": 6289
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.635598497617636e-06,
+ "loss": 0.4823,
+ "step": 6290
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.632890406032556e-06,
+ "loss": 0.467,
+ "step": 6291
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.630182341406477e-06,
+ "loss": 0.4598,
+ "step": 6292
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.627474303938267e-06,
+ "loss": 0.4697,
+ "step": 6293
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.624766293826798e-06,
+ "loss": 0.4777,
+ "step": 6294
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.62205831127093e-06,
+ "loss": 0.4762,
+ "step": 6295
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.619350356469524e-06,
+ "loss": 0.4949,
+ "step": 6296
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.616642429621449e-06,
+ "loss": 0.4867,
+ "step": 6297
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.613934530925556e-06,
+ "loss": 0.4907,
+ "step": 6298
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.611226660580709e-06,
+ "loss": 0.4929,
+ "step": 6299
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.60851881878576e-06,
+ "loss": 0.4616,
+ "step": 6300
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.605811005739558e-06,
+ "loss": 0.4869,
+ "step": 6301
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.603103221640956e-06,
+ "loss": 0.4846,
+ "step": 6302
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.600395466688801e-06,
+ "loss": 0.4695,
+ "step": 6303
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.597687741081942e-06,
+ "loss": 0.4904,
+ "step": 6304
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.594980045019224e-06,
+ "loss": 0.4837,
+ "step": 6305
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.592272378699486e-06,
+ "loss": 0.4682,
+ "step": 6306
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.589564742321569e-06,
+ "loss": 0.4882,
+ "step": 6307
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.586857136084309e-06,
+ "loss": 0.483,
+ "step": 6308
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.58414956018654e-06,
+ "loss": 0.4886,
+ "step": 6309
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.581442014827101e-06,
+ "loss": 0.491,
+ "step": 6310
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.57873450020482e-06,
+ "loss": 0.4758,
+ "step": 6311
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.576027016518527e-06,
+ "loss": 0.4617,
+ "step": 6312
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.573319563967043e-06,
+ "loss": 0.4783,
+ "step": 6313
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.570612142749196e-06,
+ "loss": 0.4769,
+ "step": 6314
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.56790475306381e-06,
+ "loss": 0.4733,
+ "step": 6315
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.565197395109694e-06,
+ "loss": 0.4816,
+ "step": 6316
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.56249006908568e-06,
+ "loss": 0.4784,
+ "step": 6317
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.559782775190574e-06,
+ "loss": 0.4769,
+ "step": 6318
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.55707551362319e-06,
+ "loss": 0.4679,
+ "step": 6319
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.554368284582339e-06,
+ "loss": 0.4917,
+ "step": 6320
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.551661088266825e-06,
+ "loss": 0.4883,
+ "step": 6321
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.548953924875459e-06,
+ "loss": 0.4608,
+ "step": 6322
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.546246794607037e-06,
+ "loss": 0.4799,
+ "step": 6323
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.543539697660363e-06,
+ "loss": 0.4842,
+ "step": 6324
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.540832634234238e-06,
+ "loss": 0.4864,
+ "step": 6325
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.538125604527455e-06,
+ "loss": 0.4847,
+ "step": 6326
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.535418608738808e-06,
+ "loss": 0.5013,
+ "step": 6327
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.53271164706708e-06,
+ "loss": 0.4738,
+ "step": 6328
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.53000471971107e-06,
+ "loss": 0.4796,
+ "step": 6329
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.527297826869553e-06,
+ "loss": 0.4594,
+ "step": 6330
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.524590968741324e-06,
+ "loss": 0.4737,
+ "step": 6331
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.521884145525153e-06,
+ "loss": 0.4757,
+ "step": 6332
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.519177357419824e-06,
+ "loss": 0.5014,
+ "step": 6333
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.516470604624109e-06,
+ "loss": 0.4906,
+ "step": 6334
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.513763887336781e-06,
+ "loss": 0.4728,
+ "step": 6335
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.511057205756614e-06,
+ "loss": 0.4792,
+ "step": 6336
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.508350560082364e-06,
+ "loss": 0.4579,
+ "step": 6337
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.505643950512811e-06,
+ "loss": 0.4688,
+ "step": 6338
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.502937377246707e-06,
+ "loss": 0.489,
+ "step": 6339
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.500230840482817e-06,
+ "loss": 0.4965,
+ "step": 6340
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.497524340419896e-06,
+ "loss": 0.4631,
+ "step": 6341
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.494817877256696e-06,
+ "loss": 0.4601,
+ "step": 6342
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.49211145119197e-06,
+ "loss": 0.4815,
+ "step": 6343
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.489405062424464e-06,
+ "loss": 0.4815,
+ "step": 6344
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.486698711152928e-06,
+ "loss": 0.489,
+ "step": 6345
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.483992397576106e-06,
+ "loss": 0.4806,
+ "step": 6346
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.481286121892734e-06,
+ "loss": 0.4701,
+ "step": 6347
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.478579884301554e-06,
+ "loss": 0.4687,
+ "step": 6348
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.475873685001295e-06,
+ "loss": 0.4647,
+ "step": 6349
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.473167524190692e-06,
+ "loss": 0.4665,
+ "step": 6350
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.470461402068478e-06,
+ "loss": 0.4681,
+ "step": 6351
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.467755318833376e-06,
+ "loss": 0.482,
+ "step": 6352
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.46504927468411e-06,
+ "loss": 0.4852,
+ "step": 6353
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.462343269819398e-06,
+ "loss": 0.4887,
+ "step": 6354
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.459637304437962e-06,
+ "loss": 0.4993,
+ "step": 6355
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.456931378738515e-06,
+ "loss": 0.4926,
+ "step": 6356
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.454225492919765e-06,
+ "loss": 0.4916,
+ "step": 6357
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.451519647180427e-06,
+ "loss": 0.4718,
+ "step": 6358
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.448813841719207e-06,
+ "loss": 0.4794,
+ "step": 6359
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.446108076734803e-06,
+ "loss": 0.461,
+ "step": 6360
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.44340235242592e-06,
+ "loss": 0.486,
+ "step": 6361
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.440696668991253e-06,
+ "loss": 0.467,
+ "step": 6362
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.437991026629497e-06,
+ "loss": 0.4657,
+ "step": 6363
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.435285425539337e-06,
+ "loss": 0.4854,
+ "step": 6364
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.43257986591947e-06,
+ "loss": 0.4839,
+ "step": 6365
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.42987434796858e-06,
+ "loss": 0.4686,
+ "step": 6366
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.427168871885345e-06,
+ "loss": 0.4639,
+ "step": 6367
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.424463437868445e-06,
+ "loss": 0.4912,
+ "step": 6368
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.421758046116557e-06,
+ "loss": 0.4673,
+ "step": 6369
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.419052696828352e-06,
+ "loss": 0.4861,
+ "step": 6370
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.416347390202499e-06,
+ "loss": 0.4816,
+ "step": 6371
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.41364212643767e-06,
+ "loss": 0.4647,
+ "step": 6372
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.410936905732522e-06,
+ "loss": 0.4781,
+ "step": 6373
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.40823172828572e-06,
+ "loss": 0.4912,
+ "step": 6374
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.405526594295915e-06,
+ "loss": 0.4641,
+ "step": 6375
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.402821503961766e-06,
+ "loss": 0.4802,
+ "step": 6376
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.400116457481924e-06,
+ "loss": 0.4938,
+ "step": 6377
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.397411455055028e-06,
+ "loss": 0.4878,
+ "step": 6378
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.394706496879733e-06,
+ "loss": 0.4762,
+ "step": 6379
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.392001583154675e-06,
+ "loss": 0.4799,
+ "step": 6380
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.389296714078493e-06,
+ "loss": 0.4966,
+ "step": 6381
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.386591889849819e-06,
+ "loss": 0.4841,
+ "step": 6382
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.383887110667285e-06,
+ "loss": 0.5037,
+ "step": 6383
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.381182376729516e-06,
+ "loss": 0.4769,
+ "step": 6384
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.378477688235144e-06,
+ "loss": 0.4716,
+ "step": 6385
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.375773045382782e-06,
+ "loss": 0.4908,
+ "step": 6386
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.373068448371054e-06,
+ "loss": 0.4506,
+ "step": 6387
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.370363897398573e-06,
+ "loss": 0.4837,
+ "step": 6388
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.367659392663947e-06,
+ "loss": 0.4797,
+ "step": 6389
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.364954934365783e-06,
+ "loss": 0.4906,
+ "step": 6390
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.362250522702685e-06,
+ "loss": 0.4653,
+ "step": 6391
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.35954615787326e-06,
+ "loss": 0.4811,
+ "step": 6392
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.356841840076102e-06,
+ "loss": 0.4746,
+ "step": 6393
+ },
+ {
+ "epoch": 0.53,
+ "learning_rate": 9.354137569509804e-06,
+ "loss": 0.4864,
+ "step": 6394
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.351433346372955e-06,
+ "loss": 0.4882,
+ "step": 6395
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.348729170864145e-06,
+ "loss": 0.4855,
+ "step": 6396
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.346025043181955e-06,
+ "loss": 0.4606,
+ "step": 6397
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.343320963524964e-06,
+ "loss": 0.482,
+ "step": 6398
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.340616932091752e-06,
+ "loss": 0.4876,
+ "step": 6399
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.33791294908089e-06,
+ "loss": 0.4936,
+ "step": 6400
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.335209014690946e-06,
+ "loss": 0.495,
+ "step": 6401
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.332505129120489e-06,
+ "loss": 0.4882,
+ "step": 6402
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.32980129256808e-06,
+ "loss": 0.4871,
+ "step": 6403
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.327097505232274e-06,
+ "loss": 0.4526,
+ "step": 6404
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.324393767311625e-06,
+ "loss": 0.4816,
+ "step": 6405
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.321690079004691e-06,
+ "loss": 0.4765,
+ "step": 6406
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.318986440510018e-06,
+ "loss": 0.4737,
+ "step": 6407
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.316282852026147e-06,
+ "loss": 0.4784,
+ "step": 6408
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.313579313751621e-06,
+ "loss": 0.4744,
+ "step": 6409
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.310875825884972e-06,
+ "loss": 0.4675,
+ "step": 6410
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.308172388624739e-06,
+ "loss": 0.465,
+ "step": 6411
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.305469002169442e-06,
+ "loss": 0.477,
+ "step": 6412
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.30276566671762e-06,
+ "loss": 0.4649,
+ "step": 6413
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.300062382467785e-06,
+ "loss": 0.4649,
+ "step": 6414
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.29735914961846e-06,
+ "loss": 0.468,
+ "step": 6415
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.294655968368153e-06,
+ "loss": 0.4863,
+ "step": 6416
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.291952838915379e-06,
+ "loss": 0.4815,
+ "step": 6417
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.289249761458643e-06,
+ "loss": 0.4916,
+ "step": 6418
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.286546736196447e-06,
+ "loss": 0.4722,
+ "step": 6419
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.283843763327293e-06,
+ "loss": 0.5097,
+ "step": 6420
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.281140843049674e-06,
+ "loss": 0.4785,
+ "step": 6421
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.278437975562083e-06,
+ "loss": 0.4712,
+ "step": 6422
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.275735161063006e-06,
+ "loss": 0.4693,
+ "step": 6423
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.273032399750925e-06,
+ "loss": 0.4631,
+ "step": 6424
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.270329691824318e-06,
+ "loss": 0.4736,
+ "step": 6425
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.267627037481667e-06,
+ "loss": 0.4763,
+ "step": 6426
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.264924436921438e-06,
+ "loss": 0.475,
+ "step": 6427
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.262221890342104e-06,
+ "loss": 0.5036,
+ "step": 6428
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.259519397942125e-06,
+ "loss": 0.4682,
+ "step": 6429
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.256816959919962e-06,
+ "loss": 0.4808,
+ "step": 6430
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.254114576474068e-06,
+ "loss": 0.4676,
+ "step": 6431
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.251412247802896e-06,
+ "loss": 0.4549,
+ "step": 6432
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.248709974104897e-06,
+ "loss": 0.4904,
+ "step": 6433
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.246007755578514e-06,
+ "loss": 0.4909,
+ "step": 6434
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.243305592422184e-06,
+ "loss": 0.479,
+ "step": 6435
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.240603484834347e-06,
+ "loss": 0.4879,
+ "step": 6436
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.237901433013427e-06,
+ "loss": 0.4899,
+ "step": 6437
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.235199437157858e-06,
+ "loss": 0.4525,
+ "step": 6438
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.232497497466057e-06,
+ "loss": 0.4823,
+ "step": 6439
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.229795614136452e-06,
+ "loss": 0.4723,
+ "step": 6440
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.227093787367454e-06,
+ "loss": 0.4649,
+ "step": 6441
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.224392017357471e-06,
+ "loss": 0.4885,
+ "step": 6442
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.221690304304915e-06,
+ "loss": 0.4626,
+ "step": 6443
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.218988648408187e-06,
+ "loss": 0.4568,
+ "step": 6444
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.216287049865681e-06,
+ "loss": 0.4942,
+ "step": 6445
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.213585508875792e-06,
+ "loss": 0.5012,
+ "step": 6446
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.210884025636916e-06,
+ "loss": 0.4838,
+ "step": 6447
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.208182600347432e-06,
+ "loss": 0.4744,
+ "step": 6448
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.20548123320573e-06,
+ "loss": 0.4823,
+ "step": 6449
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.20277992441018e-06,
+ "loss": 0.4897,
+ "step": 6450
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.200078674159154e-06,
+ "loss": 0.4671,
+ "step": 6451
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.197377482651023e-06,
+ "loss": 0.4986,
+ "step": 6452
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.194676350084148e-06,
+ "loss": 0.4702,
+ "step": 6453
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.191975276656898e-06,
+ "loss": 0.4758,
+ "step": 6454
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.189274262567622e-06,
+ "loss": 0.4712,
+ "step": 6455
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.186573308014672e-06,
+ "loss": 0.4757,
+ "step": 6456
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.183872413196392e-06,
+ "loss": 0.4419,
+ "step": 6457
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.181171578311132e-06,
+ "loss": 0.483,
+ "step": 6458
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.17847080355722e-06,
+ "loss": 0.4725,
+ "step": 6459
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.175770089133e-06,
+ "loss": 0.4854,
+ "step": 6460
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.173069435236796e-06,
+ "loss": 0.5029,
+ "step": 6461
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.170368842066932e-06,
+ "loss": 0.4741,
+ "step": 6462
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.167668309821729e-06,
+ "loss": 0.4736,
+ "step": 6463
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.164967838699504e-06,
+ "loss": 0.5017,
+ "step": 6464
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.162267428898568e-06,
+ "loss": 0.4903,
+ "step": 6465
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.159567080617226e-06,
+ "loss": 0.4764,
+ "step": 6466
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.156866794053783e-06,
+ "loss": 0.4889,
+ "step": 6467
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.154166569406537e-06,
+ "loss": 0.4664,
+ "step": 6468
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.15146640687378e-06,
+ "loss": 0.494,
+ "step": 6469
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.148766306653801e-06,
+ "loss": 0.4731,
+ "step": 6470
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.146066268944883e-06,
+ "loss": 0.4908,
+ "step": 6471
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.143366293945305e-06,
+ "loss": 0.4881,
+ "step": 6472
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.140666381853343e-06,
+ "loss": 0.4623,
+ "step": 6473
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.137966532867268e-06,
+ "loss": 0.4839,
+ "step": 6474
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.135266747185348e-06,
+ "loss": 0.484,
+ "step": 6475
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.132567025005842e-06,
+ "loss": 0.4819,
+ "step": 6476
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.129867366527004e-06,
+ "loss": 0.4728,
+ "step": 6477
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.127167771947086e-06,
+ "loss": 0.4608,
+ "step": 6478
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.12446824146434e-06,
+ "loss": 0.4677,
+ "step": 6479
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.121768775276997e-06,
+ "loss": 0.4838,
+ "step": 6480
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.11906937358331e-06,
+ "loss": 0.4658,
+ "step": 6481
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.116370036581504e-06,
+ "loss": 0.4829,
+ "step": 6482
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.113670764469803e-06,
+ "loss": 0.4701,
+ "step": 6483
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.110971557446437e-06,
+ "loss": 0.4751,
+ "step": 6484
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.108272415709624e-06,
+ "loss": 0.4502,
+ "step": 6485
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.105573339457574e-06,
+ "loss": 0.4784,
+ "step": 6486
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.102874328888493e-06,
+ "loss": 0.4574,
+ "step": 6487
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.100175384200595e-06,
+ "loss": 0.4764,
+ "step": 6488
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.097476505592074e-06,
+ "loss": 0.4746,
+ "step": 6489
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.094777693261124e-06,
+ "loss": 0.4867,
+ "step": 6490
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.092078947405937e-06,
+ "loss": 0.4723,
+ "step": 6491
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.089380268224694e-06,
+ "loss": 0.4829,
+ "step": 6492
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.086681655915574e-06,
+ "loss": 0.4703,
+ "step": 6493
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.083983110676755e-06,
+ "loss": 0.4804,
+ "step": 6494
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.081284632706408e-06,
+ "loss": 0.4808,
+ "step": 6495
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.078586222202698e-06,
+ "loss": 0.4923,
+ "step": 6496
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.075887879363783e-06,
+ "loss": 0.4779,
+ "step": 6497
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.073189604387815e-06,
+ "loss": 0.4824,
+ "step": 6498
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.07049139747295e-06,
+ "loss": 0.4912,
+ "step": 6499
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.06779325881733e-06,
+ "loss": 0.477,
+ "step": 6500
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.065095188619096e-06,
+ "loss": 0.4758,
+ "step": 6501
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.062397187076384e-06,
+ "loss": 0.467,
+ "step": 6502
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.059699254387323e-06,
+ "loss": 0.4954,
+ "step": 6503
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.057001390750035e-06,
+ "loss": 0.4689,
+ "step": 6504
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.054303596362646e-06,
+ "loss": 0.4764,
+ "step": 6505
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.051605871423266e-06,
+ "loss": 0.4866,
+ "step": 6506
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.048908216130002e-06,
+ "loss": 0.4834,
+ "step": 6507
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.046210630680968e-06,
+ "loss": 0.4618,
+ "step": 6508
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.043513115274257e-06,
+ "loss": 0.4803,
+ "step": 6509
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.040815670107964e-06,
+ "loss": 0.4672,
+ "step": 6510
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.038118295380179e-06,
+ "loss": 0.4937,
+ "step": 6511
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.035420991288987e-06,
+ "loss": 0.4753,
+ "step": 6512
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.032723758032462e-06,
+ "loss": 0.4871,
+ "step": 6513
+ },
+ {
+ "epoch": 0.54,
+ "learning_rate": 9.030026595808682e-06,
+ "loss": 0.4761,
+ "step": 6514
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.027329504815714e-06,
+ "loss": 0.509,
+ "step": 6515
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.024632485251624e-06,
+ "loss": 0.4935,
+ "step": 6516
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.021935537314467e-06,
+ "loss": 0.4866,
+ "step": 6517
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.019238661202296e-06,
+ "loss": 0.4957,
+ "step": 6518
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.016541857113157e-06,
+ "loss": 0.4776,
+ "step": 6519
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.013845125245095e-06,
+ "loss": 0.4852,
+ "step": 6520
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.01114846579614e-06,
+ "loss": 0.4643,
+ "step": 6521
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.008451878964336e-06,
+ "loss": 0.4801,
+ "step": 6522
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.005755364947699e-06,
+ "loss": 0.4683,
+ "step": 6523
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.00305892394425e-06,
+ "loss": 0.4803,
+ "step": 6524
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 9.000362556152013e-06,
+ "loss": 0.4789,
+ "step": 6525
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.997666261768989e-06,
+ "loss": 0.4686,
+ "step": 6526
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.994970040993187e-06,
+ "loss": 0.5007,
+ "step": 6527
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.9922738940226e-06,
+ "loss": 0.4736,
+ "step": 6528
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.989577821055231e-06,
+ "loss": 0.4812,
+ "step": 6529
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.986881822289062e-06,
+ "loss": 0.49,
+ "step": 6530
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.98418589792208e-06,
+ "loss": 0.4833,
+ "step": 6531
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.98149004815226e-06,
+ "loss": 0.4741,
+ "step": 6532
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.978794273177576e-06,
+ "loss": 0.4823,
+ "step": 6533
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.97609857319599e-06,
+ "loss": 0.4539,
+ "step": 6534
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.973402948405466e-06,
+ "loss": 0.4686,
+ "step": 6535
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.970707399003961e-06,
+ "loss": 0.4727,
+ "step": 6536
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.968011925189426e-06,
+ "loss": 0.4807,
+ "step": 6537
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.9653165271598e-06,
+ "loss": 0.4661,
+ "step": 6538
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.962621205113025e-06,
+ "loss": 0.4563,
+ "step": 6539
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.959925959247036e-06,
+ "loss": 0.4915,
+ "step": 6540
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.957230789759752e-06,
+ "loss": 0.4776,
+ "step": 6541
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.954535696849108e-06,
+ "loss": 0.4824,
+ "step": 6542
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.951840680713013e-06,
+ "loss": 0.4858,
+ "step": 6543
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.949145741549378e-06,
+ "loss": 0.4641,
+ "step": 6544
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.946450879556108e-06,
+ "loss": 0.4672,
+ "step": 6545
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.943756094931106e-06,
+ "loss": 0.4964,
+ "step": 6546
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.941061387872263e-06,
+ "loss": 0.4896,
+ "step": 6547
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.938366758577462e-06,
+ "loss": 0.4759,
+ "step": 6548
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.935672207244596e-06,
+ "loss": 0.4772,
+ "step": 6549
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.932977734071533e-06,
+ "loss": 0.4732,
+ "step": 6550
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.93028333925615e-06,
+ "loss": 0.4791,
+ "step": 6551
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.927589022996308e-06,
+ "loss": 0.4696,
+ "step": 6552
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.92489478548987e-06,
+ "loss": 0.4734,
+ "step": 6553
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.922200626934682e-06,
+ "loss": 0.4917,
+ "step": 6554
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.919506547528599e-06,
+ "loss": 0.4855,
+ "step": 6555
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.916812547469461e-06,
+ "loss": 0.4893,
+ "step": 6556
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.914118626955106e-06,
+ "loss": 0.4473,
+ "step": 6557
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.911424786183362e-06,
+ "loss": 0.4829,
+ "step": 6558
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.908731025352055e-06,
+ "loss": 0.4882,
+ "step": 6559
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.906037344659e-06,
+ "loss": 0.4827,
+ "step": 6560
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.903343744302016e-06,
+ "loss": 0.469,
+ "step": 6561
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.900650224478899e-06,
+ "loss": 0.4783,
+ "step": 6562
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.897956785387463e-06,
+ "loss": 0.4845,
+ "step": 6563
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.895263427225497e-06,
+ "loss": 0.4707,
+ "step": 6564
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.89257015019079e-06,
+ "loss": 0.4974,
+ "step": 6565
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.889876954481122e-06,
+ "loss": 0.4709,
+ "step": 6566
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.887183840294274e-06,
+ "loss": 0.4527,
+ "step": 6567
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.88449080782802e-06,
+ "loss": 0.4861,
+ "step": 6568
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.881797857280113e-06,
+ "loss": 0.4684,
+ "step": 6569
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.879104988848326e-06,
+ "loss": 0.4724,
+ "step": 6570
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.876412202730405e-06,
+ "loss": 0.4827,
+ "step": 6571
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.873719499124101e-06,
+ "loss": 0.4686,
+ "step": 6572
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.871026878227151e-06,
+ "loss": 0.4915,
+ "step": 6573
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.868334340237293e-06,
+ "loss": 0.4946,
+ "step": 6574
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.86564188535225e-06,
+ "loss": 0.4845,
+ "step": 6575
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.86294951376975e-06,
+ "loss": 0.4632,
+ "step": 6576
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.86025722568751e-06,
+ "loss": 0.4733,
+ "step": 6577
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.857565021303238e-06,
+ "loss": 0.4629,
+ "step": 6578
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.85487290081464e-06,
+ "loss": 0.4984,
+ "step": 6579
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.852180864419413e-06,
+ "loss": 0.4787,
+ "step": 6580
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.84948891231525e-06,
+ "loss": 0.4913,
+ "step": 6581
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.846797044699831e-06,
+ "loss": 0.4955,
+ "step": 6582
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.844105261770844e-06,
+ "loss": 0.478,
+ "step": 6583
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.84141356372596e-06,
+ "loss": 0.4816,
+ "step": 6584
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.838721950762845e-06,
+ "loss": 0.4711,
+ "step": 6585
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.836030423079157e-06,
+ "loss": 0.4757,
+ "step": 6586
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.833338980872558e-06,
+ "loss": 0.4635,
+ "step": 6587
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.830647624340689e-06,
+ "loss": 0.4623,
+ "step": 6588
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.827956353681191e-06,
+ "loss": 0.4898,
+ "step": 6589
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.82526516909171e-06,
+ "loss": 0.4753,
+ "step": 6590
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.822574070769867e-06,
+ "loss": 0.4799,
+ "step": 6591
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.819883058913285e-06,
+ "loss": 0.4814,
+ "step": 6592
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.817192133719583e-06,
+ "loss": 0.5005,
+ "step": 6593
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.814501295386373e-06,
+ "loss": 0.4939,
+ "step": 6594
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.811810544111258e-06,
+ "loss": 0.4781,
+ "step": 6595
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.809119880091829e-06,
+ "loss": 0.4704,
+ "step": 6596
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.806429303525685e-06,
+ "loss": 0.4791,
+ "step": 6597
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.803738814610409e-06,
+ "loss": 0.4631,
+ "step": 6598
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.801048413543581e-06,
+ "loss": 0.4904,
+ "step": 6599
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.79835810052277e-06,
+ "loss": 0.4783,
+ "step": 6600
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.79566787574554e-06,
+ "loss": 0.4744,
+ "step": 6601
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.792977739409455e-06,
+ "loss": 0.4782,
+ "step": 6602
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.790287691712059e-06,
+ "loss": 0.478,
+ "step": 6603
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.78759773285091e-06,
+ "loss": 0.4799,
+ "step": 6604
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.784907863023537e-06,
+ "loss": 0.4553,
+ "step": 6605
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.782218082427478e-06,
+ "loss": 0.4705,
+ "step": 6606
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.779528391260257e-06,
+ "loss": 0.4689,
+ "step": 6607
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.776838789719396e-06,
+ "loss": 0.4538,
+ "step": 6608
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.774149278002402e-06,
+ "loss": 0.4857,
+ "step": 6609
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.771459856306791e-06,
+ "loss": 0.4831,
+ "step": 6610
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.768770524830058e-06,
+ "loss": 0.4744,
+ "step": 6611
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.766081283769695e-06,
+ "loss": 0.4704,
+ "step": 6612
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.763392133323192e-06,
+ "loss": 0.476,
+ "step": 6613
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.760703073688027e-06,
+ "loss": 0.4742,
+ "step": 6614
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.758014105061674e-06,
+ "loss": 0.469,
+ "step": 6615
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.755325227641596e-06,
+ "loss": 0.4838,
+ "step": 6616
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.752636441625259e-06,
+ "loss": 0.4951,
+ "step": 6617
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.749947747210112e-06,
+ "loss": 0.4718,
+ "step": 6618
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.747259144593604e-06,
+ "loss": 0.4653,
+ "step": 6619
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.744570633973177e-06,
+ "loss": 0.472,
+ "step": 6620
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.741882215546259e-06,
+ "loss": 0.4854,
+ "step": 6621
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.739193889510276e-06,
+ "loss": 0.4681,
+ "step": 6622
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.736505656062648e-06,
+ "loss": 0.4679,
+ "step": 6623
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.733817515400793e-06,
+ "loss": 0.4907,
+ "step": 6624
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.731129467722113e-06,
+ "loss": 0.4657,
+ "step": 6625
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.728441513224008e-06,
+ "loss": 0.4657,
+ "step": 6626
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.725753652103868e-06,
+ "loss": 0.4826,
+ "step": 6627
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.72306588455908e-06,
+ "loss": 0.4653,
+ "step": 6628
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.720378210787024e-06,
+ "loss": 0.4729,
+ "step": 6629
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.717690630985065e-06,
+ "loss": 0.4685,
+ "step": 6630
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.715003145350576e-06,
+ "loss": 0.4579,
+ "step": 6631
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.712315754080913e-06,
+ "loss": 0.4743,
+ "step": 6632
+ },
+ {
+ "epoch": 0.55,
+ "learning_rate": 8.709628457373421e-06,
+ "loss": 0.4584,
+ "step": 6633
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.706941255425452e-06,
+ "loss": 0.4803,
+ "step": 6634
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.704254148434338e-06,
+ "loss": 0.4585,
+ "step": 6635
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.70156713659741e-06,
+ "loss": 0.4726,
+ "step": 6636
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.698880220111987e-06,
+ "loss": 0.4588,
+ "step": 6637
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.69619339917539e-06,
+ "loss": 0.4938,
+ "step": 6638
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.69350667398493e-06,
+ "loss": 0.4575,
+ "step": 6639
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.690820044737905e-06,
+ "loss": 0.4914,
+ "step": 6640
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.688133511631611e-06,
+ "loss": 0.4948,
+ "step": 6641
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.685447074863333e-06,
+ "loss": 0.4842,
+ "step": 6642
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.682760734630357e-06,
+ "loss": 0.4749,
+ "step": 6643
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.68007449112995e-06,
+ "loss": 0.4753,
+ "step": 6644
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.677388344559386e-06,
+ "loss": 0.4793,
+ "step": 6645
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.67470229511592e-06,
+ "loss": 0.4646,
+ "step": 6646
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.672016342996805e-06,
+ "loss": 0.4625,
+ "step": 6647
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.669330488399286e-06,
+ "loss": 0.4775,
+ "step": 6648
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.6666447315206e-06,
+ "loss": 0.4756,
+ "step": 6649
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.663959072557979e-06,
+ "loss": 0.4676,
+ "step": 6650
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.66127351170865e-06,
+ "loss": 0.4726,
+ "step": 6651
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.658588049169825e-06,
+ "loss": 0.4714,
+ "step": 6652
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.655902685138712e-06,
+ "loss": 0.4803,
+ "step": 6653
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.653217419812517e-06,
+ "loss": 0.4892,
+ "step": 6654
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.650532253388435e-06,
+ "loss": 0.4818,
+ "step": 6655
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.64784718606365e-06,
+ "loss": 0.4835,
+ "step": 6656
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.64516221803534e-06,
+ "loss": 0.4779,
+ "step": 6657
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.642477349500686e-06,
+ "loss": 0.4493,
+ "step": 6658
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.639792580656845e-06,
+ "loss": 0.486,
+ "step": 6659
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.637107911700984e-06,
+ "loss": 0.4814,
+ "step": 6660
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.634423342830247e-06,
+ "loss": 0.4684,
+ "step": 6661
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.631738874241781e-06,
+ "loss": 0.4948,
+ "step": 6662
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.629054506132719e-06,
+ "loss": 0.4751,
+ "step": 6663
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.62637023870019e-06,
+ "loss": 0.4949,
+ "step": 6664
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.623686072141322e-06,
+ "loss": 0.4846,
+ "step": 6665
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.621002006653223e-06,
+ "loss": 0.5014,
+ "step": 6666
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.618318042433001e-06,
+ "loss": 0.4761,
+ "step": 6667
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.615634179677754e-06,
+ "loss": 0.455,
+ "step": 6668
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.612950418584575e-06,
+ "loss": 0.4812,
+ "step": 6669
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.610266759350551e-06,
+ "loss": 0.445,
+ "step": 6670
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.60758320217275e-06,
+ "loss": 0.4593,
+ "step": 6671
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.604899747248251e-06,
+ "loss": 0.48,
+ "step": 6672
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.602216394774114e-06,
+ "loss": 0.485,
+ "step": 6673
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.599533144947386e-06,
+ "loss": 0.4597,
+ "step": 6674
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.596849997965122e-06,
+ "loss": 0.4916,
+ "step": 6675
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.594166954024359e-06,
+ "loss": 0.4836,
+ "step": 6676
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.591484013322128e-06,
+ "loss": 0.4712,
+ "step": 6677
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.588801176055447e-06,
+ "loss": 0.4779,
+ "step": 6678
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.586118442421341e-06,
+ "loss": 0.4899,
+ "step": 6679
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.583435812616817e-06,
+ "loss": 0.4701,
+ "step": 6680
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.580753286838875e-06,
+ "loss": 0.4788,
+ "step": 6681
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.57807086528451e-06,
+ "loss": 0.4701,
+ "step": 6682
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.575388548150702e-06,
+ "loss": 0.4718,
+ "step": 6683
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.572706335634437e-06,
+ "loss": 0.4727,
+ "step": 6684
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.570024227932678e-06,
+ "loss": 0.4729,
+ "step": 6685
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.567342225242397e-06,
+ "loss": 0.4713,
+ "step": 6686
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.564660327760543e-06,
+ "loss": 0.4734,
+ "step": 6687
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.561978535684065e-06,
+ "loss": 0.4841,
+ "step": 6688
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.5592968492099e-06,
+ "loss": 0.4794,
+ "step": 6689
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.556615268534984e-06,
+ "loss": 0.4915,
+ "step": 6690
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.553933793856234e-06,
+ "loss": 0.4734,
+ "step": 6691
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.551252425370577e-06,
+ "loss": 0.4661,
+ "step": 6692
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.548571163274915e-06,
+ "loss": 0.4723,
+ "step": 6693
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.54589000776615e-06,
+ "loss": 0.4812,
+ "step": 6694
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.543208959041174e-06,
+ "loss": 0.4868,
+ "step": 6695
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.540528017296876e-06,
+ "loss": 0.4789,
+ "step": 6696
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.537847182730126e-06,
+ "loss": 0.4894,
+ "step": 6697
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.535166455537795e-06,
+ "loss": 0.4734,
+ "step": 6698
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.532485835916754e-06,
+ "loss": 0.4674,
+ "step": 6699
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.529805324063843e-06,
+ "loss": 0.4828,
+ "step": 6700
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.527124920175918e-06,
+ "loss": 0.4801,
+ "step": 6701
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.524444624449812e-06,
+ "loss": 0.4383,
+ "step": 6702
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.521764437082355e-06,
+ "loss": 0.4693,
+ "step": 6703
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.519084358270368e-06,
+ "loss": 0.4689,
+ "step": 6704
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.516404388210668e-06,
+ "loss": 0.4543,
+ "step": 6705
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.513724527100055e-06,
+ "loss": 0.4868,
+ "step": 6706
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.511044775135336e-06,
+ "loss": 0.4848,
+ "step": 6707
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.508365132513296e-06,
+ "loss": 0.4832,
+ "step": 6708
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.505685599430715e-06,
+ "loss": 0.4872,
+ "step": 6709
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.503006176084366e-06,
+ "loss": 0.4848,
+ "step": 6710
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.50032686267102e-06,
+ "loss": 0.4751,
+ "step": 6711
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.497647659387426e-06,
+ "loss": 0.4748,
+ "step": 6712
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.494968566430346e-06,
+ "loss": 0.4774,
+ "step": 6713
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.492289583996511e-06,
+ "loss": 0.4901,
+ "step": 6714
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.489610712282658e-06,
+ "loss": 0.477,
+ "step": 6715
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.486931951485515e-06,
+ "loss": 0.4673,
+ "step": 6716
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.484253301801794e-06,
+ "loss": 0.4684,
+ "step": 6717
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.481574763428208e-06,
+ "loss": 0.4901,
+ "step": 6718
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.47889633656145e-06,
+ "loss": 0.4841,
+ "step": 6719
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.476218021398224e-06,
+ "loss": 0.4742,
+ "step": 6720
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.473539818135205e-06,
+ "loss": 0.473,
+ "step": 6721
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.470861726969075e-06,
+ "loss": 0.4822,
+ "step": 6722
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.4681837480965e-06,
+ "loss": 0.4779,
+ "step": 6723
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.46550588171414e-06,
+ "loss": 0.4748,
+ "step": 6724
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.462828128018642e-06,
+ "loss": 0.4784,
+ "step": 6725
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.460150487206652e-06,
+ "loss": 0.4835,
+ "step": 6726
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.45747295947481e-06,
+ "loss": 0.4796,
+ "step": 6727
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.454795545019737e-06,
+ "loss": 0.4778,
+ "step": 6728
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.452118244038052e-06,
+ "loss": 0.4831,
+ "step": 6729
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.449441056726364e-06,
+ "loss": 0.4749,
+ "step": 6730
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.446763983281276e-06,
+ "loss": 0.4853,
+ "step": 6731
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.444087023899377e-06,
+ "loss": 0.491,
+ "step": 6732
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.44141017877726e-06,
+ "loss": 0.4564,
+ "step": 6733
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.438733448111496e-06,
+ "loss": 0.4818,
+ "step": 6734
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.436056832098655e-06,
+ "loss": 0.4734,
+ "step": 6735
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.433380330935293e-06,
+ "loss": 0.4585,
+ "step": 6736
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.430703944817967e-06,
+ "loss": 0.4646,
+ "step": 6737
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.428027673943213e-06,
+ "loss": 0.4824,
+ "step": 6738
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.425351518507565e-06,
+ "loss": 0.4706,
+ "step": 6739
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.422675478707556e-06,
+ "loss": 0.4733,
+ "step": 6740
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.4199995547397e-06,
+ "loss": 0.5001,
+ "step": 6741
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.417323746800504e-06,
+ "loss": 0.4803,
+ "step": 6742
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.414648055086471e-06,
+ "loss": 0.4705,
+ "step": 6743
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.41197247979409e-06,
+ "loss": 0.4768,
+ "step": 6744
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.409297021119843e-06,
+ "loss": 0.4859,
+ "step": 6745
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.406621679260206e-06,
+ "loss": 0.4715,
+ "step": 6746
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.403946454411645e-06,
+ "loss": 0.462,
+ "step": 6747
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.401271346770622e-06,
+ "loss": 0.4751,
+ "step": 6748
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.398596356533581e-06,
+ "loss": 0.4768,
+ "step": 6749
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.395921483896963e-06,
+ "loss": 0.471,
+ "step": 6750
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.393246729057196e-06,
+ "loss": 0.5009,
+ "step": 6751
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.39057209221071e-06,
+ "loss": 0.4724,
+ "step": 6752
+ },
+ {
+ "epoch": 0.56,
+ "learning_rate": 8.38789757355391e-06,
+ "loss": 0.471,
+ "step": 6753
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.38522317328321e-06,
+ "loss": 0.4789,
+ "step": 6754
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.382548891595006e-06,
+ "loss": 0.4581,
+ "step": 6755
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.379874728685681e-06,
+ "loss": 0.4895,
+ "step": 6756
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.37720068475162e-06,
+ "loss": 0.4833,
+ "step": 6757
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.37452675998919e-06,
+ "loss": 0.4793,
+ "step": 6758
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.371852954594755e-06,
+ "loss": 0.4747,
+ "step": 6759
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.369179268764662e-06,
+ "loss": 0.4749,
+ "step": 6760
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.366505702695264e-06,
+ "loss": 0.4625,
+ "step": 6761
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.363832256582892e-06,
+ "loss": 0.4828,
+ "step": 6762
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.361158930623877e-06,
+ "loss": 0.4782,
+ "step": 6763
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.358485725014531e-06,
+ "loss": 0.4788,
+ "step": 6764
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.355812639951168e-06,
+ "loss": 0.4712,
+ "step": 6765
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.35313967563008e-06,
+ "loss": 0.4894,
+ "step": 6766
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.350466832247568e-06,
+ "loss": 0.4702,
+ "step": 6767
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.347794109999912e-06,
+ "loss": 0.4668,
+ "step": 6768
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.345121509083384e-06,
+ "loss": 0.4578,
+ "step": 6769
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.34244902969425e-06,
+ "loss": 0.4826,
+ "step": 6770
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.339776672028765e-06,
+ "loss": 0.4897,
+ "step": 6771
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.337104436283176e-06,
+ "loss": 0.4767,
+ "step": 6772
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.334432322653717e-06,
+ "loss": 0.5019,
+ "step": 6773
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.331760331336622e-06,
+ "loss": 0.4777,
+ "step": 6774
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.329088462528113e-06,
+ "loss": 0.4643,
+ "step": 6775
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.326416716424396e-06,
+ "loss": 0.4687,
+ "step": 6776
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.323745093221672e-06,
+ "loss": 0.4902,
+ "step": 6777
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.32107359311614e-06,
+ "loss": 0.4804,
+ "step": 6778
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.318402216303978e-06,
+ "loss": 0.4833,
+ "step": 6779
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.31573096298136e-06,
+ "loss": 0.4916,
+ "step": 6780
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.313059833344459e-06,
+ "loss": 0.4769,
+ "step": 6781
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.310388827589424e-06,
+ "loss": 0.4853,
+ "step": 6782
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.30771794591241e-06,
+ "loss": 0.4967,
+ "step": 6783
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.30504718850955e-06,
+ "loss": 0.4618,
+ "step": 6784
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.302376555576974e-06,
+ "loss": 0.4827,
+ "step": 6785
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.299706047310803e-06,
+ "loss": 0.458,
+ "step": 6786
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.297035663907146e-06,
+ "loss": 0.4838,
+ "step": 6787
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.294365405562107e-06,
+ "loss": 0.4725,
+ "step": 6788
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.29169527247178e-06,
+ "loss": 0.4844,
+ "step": 6789
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.289025264832247e-06,
+ "loss": 0.479,
+ "step": 6790
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.286355382839584e-06,
+ "loss": 0.4811,
+ "step": 6791
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.283685626689851e-06,
+ "loss": 0.4781,
+ "step": 6792
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.281015996579106e-06,
+ "loss": 0.4775,
+ "step": 6793
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.278346492703394e-06,
+ "loss": 0.4994,
+ "step": 6794
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.275677115258761e-06,
+ "loss": 0.4812,
+ "step": 6795
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.273007864441227e-06,
+ "loss": 0.4621,
+ "step": 6796
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.27033874044681e-06,
+ "loss": 0.4713,
+ "step": 6797
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.267669743471525e-06,
+ "loss": 0.4923,
+ "step": 6798
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.265000873711368e-06,
+ "loss": 0.4829,
+ "step": 6799
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.262332131362326e-06,
+ "loss": 0.4658,
+ "step": 6800
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.259663516620389e-06,
+ "loss": 0.5034,
+ "step": 6801
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.256995029681526e-06,
+ "loss": 0.4598,
+ "step": 6802
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.254326670741694e-06,
+ "loss": 0.4704,
+ "step": 6803
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.251658439996854e-06,
+ "loss": 0.4928,
+ "step": 6804
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.248990337642946e-06,
+ "loss": 0.4666,
+ "step": 6805
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.246322363875904e-06,
+ "loss": 0.4721,
+ "step": 6806
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.24365451889165e-06,
+ "loss": 0.474,
+ "step": 6807
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.240986802886105e-06,
+ "loss": 0.4743,
+ "step": 6808
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.238319216055175e-06,
+ "loss": 0.4705,
+ "step": 6809
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.235651758594753e-06,
+ "loss": 0.4877,
+ "step": 6810
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.23298443070073e-06,
+ "loss": 0.4727,
+ "step": 6811
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.230317232568977e-06,
+ "loss": 0.4659,
+ "step": 6812
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.227650164395369e-06,
+ "loss": 0.4665,
+ "step": 6813
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.224983226375756e-06,
+ "loss": 0.461,
+ "step": 6814
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.222316418705995e-06,
+ "loss": 0.4809,
+ "step": 6815
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.219649741581925e-06,
+ "loss": 0.4596,
+ "step": 6816
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.216983195199372e-06,
+ "loss": 0.4577,
+ "step": 6817
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.214316779754154e-06,
+ "loss": 0.4787,
+ "step": 6818
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.211650495442088e-06,
+ "loss": 0.4803,
+ "step": 6819
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.20898434245897e-06,
+ "loss": 0.4821,
+ "step": 6820
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.206318321000588e-06,
+ "loss": 0.4678,
+ "step": 6821
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.203652431262733e-06,
+ "loss": 0.501,
+ "step": 6822
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.200986673441173e-06,
+ "loss": 0.4752,
+ "step": 6823
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.198321047731665e-06,
+ "loss": 0.4762,
+ "step": 6824
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.195655554329969e-06,
+ "loss": 0.4846,
+ "step": 6825
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.192990193431824e-06,
+ "loss": 0.4847,
+ "step": 6826
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.19032496523296e-06,
+ "loss": 0.4782,
+ "step": 6827
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.187659869929104e-06,
+ "loss": 0.4777,
+ "step": 6828
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.184994907715969e-06,
+ "loss": 0.4826,
+ "step": 6829
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.182330078789262e-06,
+ "loss": 0.4972,
+ "step": 6830
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.179665383344674e-06,
+ "loss": 0.4655,
+ "step": 6831
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.177000821577888e-06,
+ "loss": 0.4884,
+ "step": 6832
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.174336393684577e-06,
+ "loss": 0.4607,
+ "step": 6833
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.17167209986041e-06,
+ "loss": 0.4567,
+ "step": 6834
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.169007940301034e-06,
+ "loss": 0.4858,
+ "step": 6835
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.166343915202106e-06,
+ "loss": 0.473,
+ "step": 6836
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.163680024759252e-06,
+ "loss": 0.4651,
+ "step": 6837
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.161016269168101e-06,
+ "loss": 0.4667,
+ "step": 6838
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.158352648624263e-06,
+ "loss": 0.5024,
+ "step": 6839
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.155689163323348e-06,
+ "loss": 0.478,
+ "step": 6840
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.153025813460947e-06,
+ "loss": 0.4516,
+ "step": 6841
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.15036259923265e-06,
+ "loss": 0.478,
+ "step": 6842
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.147699520834033e-06,
+ "loss": 0.4709,
+ "step": 6843
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.145036578460656e-06,
+ "loss": 0.4604,
+ "step": 6844
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.142373772308078e-06,
+ "loss": 0.4652,
+ "step": 6845
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.139711102571846e-06,
+ "loss": 0.4943,
+ "step": 6846
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.137048569447492e-06,
+ "loss": 0.4631,
+ "step": 6847
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.134386173130539e-06,
+ "loss": 0.4891,
+ "step": 6848
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.131723913816508e-06,
+ "loss": 0.4725,
+ "step": 6849
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.129061791700903e-06,
+ "loss": 0.4699,
+ "step": 6850
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.126399806979217e-06,
+ "loss": 0.4892,
+ "step": 6851
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.123737959846937e-06,
+ "loss": 0.4647,
+ "step": 6852
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.121076250499539e-06,
+ "loss": 0.4725,
+ "step": 6853
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.118414679132484e-06,
+ "loss": 0.4585,
+ "step": 6854
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.115753245941225e-06,
+ "loss": 0.481,
+ "step": 6855
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.113091951121215e-06,
+ "loss": 0.4593,
+ "step": 6856
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.110430794867884e-06,
+ "loss": 0.4727,
+ "step": 6857
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.107769777376657e-06,
+ "loss": 0.4692,
+ "step": 6858
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.105108898842946e-06,
+ "loss": 0.4705,
+ "step": 6859
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.102448159462155e-06,
+ "loss": 0.4907,
+ "step": 6860
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.099787559429682e-06,
+ "loss": 0.4831,
+ "step": 6861
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.0971270989409e-06,
+ "loss": 0.4815,
+ "step": 6862
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.094466778191194e-06,
+ "loss": 0.4879,
+ "step": 6863
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.091806597375925e-06,
+ "loss": 0.4851,
+ "step": 6864
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.089146556690437e-06,
+ "loss": 0.4682,
+ "step": 6865
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.086486656330082e-06,
+ "loss": 0.4849,
+ "step": 6866
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.083826896490186e-06,
+ "loss": 0.4875,
+ "step": 6867
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.081167277366076e-06,
+ "loss": 0.4755,
+ "step": 6868
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.078507799153053e-06,
+ "loss": 0.4663,
+ "step": 6869
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.07584846204643e-06,
+ "loss": 0.4806,
+ "step": 6870
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.073189266241492e-06,
+ "loss": 0.4771,
+ "step": 6871
+ },
+ {
+ "epoch": 0.57,
+ "learning_rate": 8.070530211933522e-06,
+ "loss": 0.4727,
+ "step": 6872
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.067871299317786e-06,
+ "loss": 0.4623,
+ "step": 6873
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.065212528589545e-06,
+ "loss": 0.5038,
+ "step": 6874
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.062553899944049e-06,
+ "loss": 0.4703,
+ "step": 6875
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.059895413576535e-06,
+ "loss": 0.4934,
+ "step": 6876
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.057237069682235e-06,
+ "loss": 0.4898,
+ "step": 6877
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.054578868456364e-06,
+ "loss": 0.4677,
+ "step": 6878
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.05192081009413e-06,
+ "loss": 0.5034,
+ "step": 6879
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.049262894790725e-06,
+ "loss": 0.4796,
+ "step": 6880
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.046605122741343e-06,
+ "loss": 0.4751,
+ "step": 6881
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.04394749414115e-06,
+ "loss": 0.4621,
+ "step": 6882
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.041290009185325e-06,
+ "loss": 0.4772,
+ "step": 6883
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.038632668069011e-06,
+ "loss": 0.471,
+ "step": 6884
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.035975470987357e-06,
+ "loss": 0.4558,
+ "step": 6885
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.033318418135494e-06,
+ "loss": 0.4728,
+ "step": 6886
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.03066150970855e-06,
+ "loss": 0.4667,
+ "step": 6887
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.02800474590163e-06,
+ "loss": 0.4804,
+ "step": 6888
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.025348126909837e-06,
+ "loss": 0.4809,
+ "step": 6889
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.02269165292827e-06,
+ "loss": 0.4799,
+ "step": 6890
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.020035324152e-06,
+ "loss": 0.456,
+ "step": 6891
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.017379140776103e-06,
+ "loss": 0.4874,
+ "step": 6892
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.014723102995635e-06,
+ "loss": 0.4772,
+ "step": 6893
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.012067211005645e-06,
+ "loss": 0.4651,
+ "step": 6894
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.00941146500117e-06,
+ "loss": 0.4828,
+ "step": 6895
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.006755865177233e-06,
+ "loss": 0.4682,
+ "step": 6896
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.00410041172886e-06,
+ "loss": 0.4852,
+ "step": 6897
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 8.001445104851052e-06,
+ "loss": 0.4691,
+ "step": 6898
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.998789944738801e-06,
+ "loss": 0.4742,
+ "step": 6899
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.996134931587092e-06,
+ "loss": 0.4673,
+ "step": 6900
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.993480065590902e-06,
+ "loss": 0.502,
+ "step": 6901
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.990825346945188e-06,
+ "loss": 0.4744,
+ "step": 6902
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.9881707758449e-06,
+ "loss": 0.4806,
+ "step": 6903
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.985516352484987e-06,
+ "loss": 0.4837,
+ "step": 6904
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.982862077060376e-06,
+ "loss": 0.4685,
+ "step": 6905
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.98020794976598e-06,
+ "loss": 0.466,
+ "step": 6906
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.977553970796713e-06,
+ "loss": 0.4756,
+ "step": 6907
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.974900140347473e-06,
+ "loss": 0.472,
+ "step": 6908
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.97224645861314e-06,
+ "loss": 0.4496,
+ "step": 6909
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.969592925788592e-06,
+ "loss": 0.4872,
+ "step": 6910
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.966939542068694e-06,
+ "loss": 0.4819,
+ "step": 6911
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.964286307648305e-06,
+ "loss": 0.4716,
+ "step": 6912
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.96163322272226e-06,
+ "loss": 0.4722,
+ "step": 6913
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.958980287485394e-06,
+ "loss": 0.4683,
+ "step": 6914
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.956327502132523e-06,
+ "loss": 0.4634,
+ "step": 6915
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.953674866858462e-06,
+ "loss": 0.4692,
+ "step": 6916
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.951022381858005e-06,
+ "loss": 0.4735,
+ "step": 6917
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.948370047325946e-06,
+ "loss": 0.4642,
+ "step": 6918
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.945717863457057e-06,
+ "loss": 0.4884,
+ "step": 6919
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.943065830446104e-06,
+ "loss": 0.4975,
+ "step": 6920
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.940413948487838e-06,
+ "loss": 0.5001,
+ "step": 6921
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.937762217777007e-06,
+ "loss": 0.4835,
+ "step": 6922
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.935110638508339e-06,
+ "loss": 0.4903,
+ "step": 6923
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.93245921087656e-06,
+ "loss": 0.4688,
+ "step": 6924
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.929807935076376e-06,
+ "loss": 0.4764,
+ "step": 6925
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.927156811302486e-06,
+ "loss": 0.4792,
+ "step": 6926
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.92450583974958e-06,
+ "loss": 0.4833,
+ "step": 6927
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.921855020612333e-06,
+ "loss": 0.4812,
+ "step": 6928
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.919204354085408e-06,
+ "loss": 0.4649,
+ "step": 6929
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.916553840363458e-06,
+ "loss": 0.4554,
+ "step": 6930
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.913903479641131e-06,
+ "loss": 0.4636,
+ "step": 6931
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.911253272113056e-06,
+ "loss": 0.5109,
+ "step": 6932
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.908603217973853e-06,
+ "loss": 0.4811,
+ "step": 6933
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.905953317418131e-06,
+ "loss": 0.4753,
+ "step": 6934
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.903303570640488e-06,
+ "loss": 0.4691,
+ "step": 6935
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.900653977835507e-06,
+ "loss": 0.4661,
+ "step": 6936
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.898004539197766e-06,
+ "loss": 0.4696,
+ "step": 6937
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.89535525492183e-06,
+ "loss": 0.4606,
+ "step": 6938
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.892706125202254e-06,
+ "loss": 0.4798,
+ "step": 6939
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.890057150233572e-06,
+ "loss": 0.4586,
+ "step": 6940
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.887408330210316e-06,
+ "loss": 0.4835,
+ "step": 6941
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.884759665327008e-06,
+ "loss": 0.4821,
+ "step": 6942
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.882111155778152e-06,
+ "loss": 0.4927,
+ "step": 6943
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.879462801758239e-06,
+ "loss": 0.4873,
+ "step": 6944
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.876814603461763e-06,
+ "loss": 0.4801,
+ "step": 6945
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.87416656108319e-06,
+ "loss": 0.476,
+ "step": 6946
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.871518674816982e-06,
+ "loss": 0.464,
+ "step": 6947
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.86887094485759e-06,
+ "loss": 0.4831,
+ "step": 6948
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.866223371399453e-06,
+ "loss": 0.4791,
+ "step": 6949
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.863575954636993e-06,
+ "loss": 0.4936,
+ "step": 6950
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.860928694764632e-06,
+ "loss": 0.4846,
+ "step": 6951
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.858281591976768e-06,
+ "loss": 0.4687,
+ "step": 6952
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.8556346464678e-06,
+ "loss": 0.4587,
+ "step": 6953
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.852987858432104e-06,
+ "loss": 0.4825,
+ "step": 6954
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.850341228064048e-06,
+ "loss": 0.4723,
+ "step": 6955
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.84769475555799e-06,
+ "loss": 0.4522,
+ "step": 6956
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.845048441108276e-06,
+ "loss": 0.484,
+ "step": 6957
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.842402284909242e-06,
+ "loss": 0.4794,
+ "step": 6958
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.839756287155213e-06,
+ "loss": 0.4794,
+ "step": 6959
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.837110448040495e-06,
+ "loss": 0.4825,
+ "step": 6960
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.834464767759392e-06,
+ "loss": 0.4612,
+ "step": 6961
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.831819246506187e-06,
+ "loss": 0.4708,
+ "step": 6962
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.829173884475158e-06,
+ "loss": 0.4607,
+ "step": 6963
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.826528681860567e-06,
+ "loss": 0.4605,
+ "step": 6964
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.823883638856675e-06,
+ "loss": 0.4779,
+ "step": 6965
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.821238755657716e-06,
+ "loss": 0.4447,
+ "step": 6966
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.818594032457922e-06,
+ "loss": 0.4876,
+ "step": 6967
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.815949469451506e-06,
+ "loss": 0.4654,
+ "step": 6968
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.813305066832679e-06,
+ "loss": 0.4654,
+ "step": 6969
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.810660824795632e-06,
+ "loss": 0.4729,
+ "step": 6970
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.808016743534546e-06,
+ "loss": 0.4886,
+ "step": 6971
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.805372823243595e-06,
+ "loss": 0.4669,
+ "step": 6972
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.802729064116933e-06,
+ "loss": 0.4781,
+ "step": 6973
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.800085466348715e-06,
+ "loss": 0.485,
+ "step": 6974
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.797442030133067e-06,
+ "loss": 0.4754,
+ "step": 6975
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.794798755664116e-06,
+ "loss": 0.4706,
+ "step": 6976
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.79215564313597e-06,
+ "loss": 0.476,
+ "step": 6977
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.789512692742731e-06,
+ "loss": 0.4709,
+ "step": 6978
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.786869904678486e-06,
+ "loss": 0.481,
+ "step": 6979
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.784227279137314e-06,
+ "loss": 0.4754,
+ "step": 6980
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.781584816313271e-06,
+ "loss": 0.4683,
+ "step": 6981
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.778942516400413e-06,
+ "loss": 0.4823,
+ "step": 6982
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.776300379592778e-06,
+ "loss": 0.4723,
+ "step": 6983
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.773658406084395e-06,
+ "loss": 0.4722,
+ "step": 6984
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.771016596069273e-06,
+ "loss": 0.478,
+ "step": 6985
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.768374949741427e-06,
+ "loss": 0.474,
+ "step": 6986
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.765733467294842e-06,
+ "loss": 0.4582,
+ "step": 6987
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.763092148923496e-06,
+ "loss": 0.4778,
+ "step": 6988
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.760450994821363e-06,
+ "loss": 0.4914,
+ "step": 6989
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.757810005182391e-06,
+ "loss": 0.4729,
+ "step": 6990
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.755169180200524e-06,
+ "loss": 0.4858,
+ "step": 6991
+ },
+ {
+ "epoch": 0.58,
+ "learning_rate": 7.752528520069697e-06,
+ "loss": 0.4731,
+ "step": 6992
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.74988802498383e-06,
+ "loss": 0.4915,
+ "step": 6993
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.747247695136825e-06,
+ "loss": 0.4868,
+ "step": 6994
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.74460753072258e-06,
+ "loss": 0.484,
+ "step": 6995
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.74196753193498e-06,
+ "loss": 0.4831,
+ "step": 6996
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.739327698967891e-06,
+ "loss": 0.4833,
+ "step": 6997
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.736688032015168e-06,
+ "loss": 0.4727,
+ "step": 6998
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.734048531270664e-06,
+ "loss": 0.4703,
+ "step": 6999
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.731409196928214e-06,
+ "loss": 0.438,
+ "step": 7000
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.728770029181638e-06,
+ "loss": 0.4715,
+ "step": 7001
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.726131028224742e-06,
+ "loss": 0.4702,
+ "step": 7002
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.723492194251326e-06,
+ "loss": 0.4689,
+ "step": 7003
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.720853527455174e-06,
+ "loss": 0.4701,
+ "step": 7004
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.718215028030056e-06,
+ "loss": 0.475,
+ "step": 7005
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.71557669616974e-06,
+ "loss": 0.4504,
+ "step": 7006
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.71293853206797e-06,
+ "loss": 0.4582,
+ "step": 7007
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.710300535918482e-06,
+ "loss": 0.4723,
+ "step": 7008
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.707662707914997e-06,
+ "loss": 0.4739,
+ "step": 7009
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.705025048251228e-06,
+ "loss": 0.4664,
+ "step": 7010
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.702387557120876e-06,
+ "loss": 0.4789,
+ "step": 7011
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.699750234717622e-06,
+ "loss": 0.4828,
+ "step": 7012
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.697113081235147e-06,
+ "loss": 0.4587,
+ "step": 7013
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.694476096867105e-06,
+ "loss": 0.4863,
+ "step": 7014
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.691839281807153e-06,
+ "loss": 0.4657,
+ "step": 7015
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.689202636248923e-06,
+ "loss": 0.4932,
+ "step": 7016
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.68656616038604e-06,
+ "loss": 0.4581,
+ "step": 7017
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.683929854412114e-06,
+ "loss": 0.4734,
+ "step": 7018
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.681293718520746e-06,
+ "loss": 0.4629,
+ "step": 7019
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.678657752905522e-06,
+ "loss": 0.4578,
+ "step": 7020
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.676021957760023e-06,
+ "loss": 0.4507,
+ "step": 7021
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.673386333277802e-06,
+ "loss": 0.4571,
+ "step": 7022
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.670750879652414e-06,
+ "loss": 0.4914,
+ "step": 7023
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.668115597077388e-06,
+ "loss": 0.4869,
+ "step": 7024
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.665480485746255e-06,
+ "loss": 0.4831,
+ "step": 7025
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.662845545852526e-06,
+ "loss": 0.4795,
+ "step": 7026
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.6602107775897e-06,
+ "loss": 0.4938,
+ "step": 7027
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.657576181151266e-06,
+ "loss": 0.4709,
+ "step": 7028
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.654941756730687e-06,
+ "loss": 0.4714,
+ "step": 7029
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.652307504521437e-06,
+ "loss": 0.4525,
+ "step": 7030
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.649673424716958e-06,
+ "loss": 0.4659,
+ "step": 7031
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.647039517510685e-06,
+ "loss": 0.4626,
+ "step": 7032
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.644405783096044e-06,
+ "loss": 0.4977,
+ "step": 7033
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.641772221666446e-06,
+ "loss": 0.4793,
+ "step": 7034
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.639138833415285e-06,
+ "loss": 0.4711,
+ "step": 7035
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.636505618535953e-06,
+ "loss": 0.4851,
+ "step": 7036
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.633872577221815e-06,
+ "loss": 0.4648,
+ "step": 7037
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.631239709666234e-06,
+ "loss": 0.4492,
+ "step": 7038
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.628607016062553e-06,
+ "loss": 0.4862,
+ "step": 7039
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.625974496604109e-06,
+ "loss": 0.4618,
+ "step": 7040
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.623342151484229e-06,
+ "loss": 0.457,
+ "step": 7041
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.620709980896215e-06,
+ "loss": 0.4916,
+ "step": 7042
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.618077985033363e-06,
+ "loss": 0.5061,
+ "step": 7043
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.6154461640889555e-06,
+ "loss": 0.4657,
+ "step": 7044
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.612814518256265e-06,
+ "loss": 0.4678,
+ "step": 7045
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.610183047728543e-06,
+ "loss": 0.4981,
+ "step": 7046
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.607551752699043e-06,
+ "loss": 0.4745,
+ "step": 7047
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.604920633360991e-06,
+ "loss": 0.4684,
+ "step": 7048
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.6022896899076045e-06,
+ "loss": 0.4702,
+ "step": 7049
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.59965892253209e-06,
+ "loss": 0.4809,
+ "step": 7050
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.597028331427643e-06,
+ "loss": 0.4865,
+ "step": 7051
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.594397916787439e-06,
+ "loss": 0.4956,
+ "step": 7052
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.591767678804642e-06,
+ "loss": 0.4843,
+ "step": 7053
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.589137617672415e-06,
+ "loss": 0.4779,
+ "step": 7054
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.586507733583892e-06,
+ "loss": 0.4786,
+ "step": 7055
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.583878026732204e-06,
+ "loss": 0.4609,
+ "step": 7056
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.581248497310465e-06,
+ "loss": 0.4686,
+ "step": 7057
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5786191455117765e-06,
+ "loss": 0.479,
+ "step": 7058
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.575989971529223e-06,
+ "loss": 0.4769,
+ "step": 7059
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.573360975555885e-06,
+ "loss": 0.4699,
+ "step": 7060
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.570732157784823e-06,
+ "loss": 0.5061,
+ "step": 7061
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.56810351840909e-06,
+ "loss": 0.4889,
+ "step": 7062
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.56547505762172e-06,
+ "loss": 0.4664,
+ "step": 7063
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.562846775615734e-06,
+ "loss": 0.4808,
+ "step": 7064
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.560218672584143e-06,
+ "loss": 0.487,
+ "step": 7065
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.557590748719943e-06,
+ "loss": 0.4975,
+ "step": 7066
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5549630042161236e-06,
+ "loss": 0.4613,
+ "step": 7067
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.552335439265652e-06,
+ "loss": 0.4905,
+ "step": 7068
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.549708054061484e-06,
+ "loss": 0.4649,
+ "step": 7069
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.547080848796564e-06,
+ "loss": 0.5153,
+ "step": 7070
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.544453823663825e-06,
+ "loss": 0.4835,
+ "step": 7071
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.541826978856185e-06,
+ "loss": 0.4816,
+ "step": 7072
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.539200314566543e-06,
+ "loss": 0.465,
+ "step": 7073
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.536573830987798e-06,
+ "loss": 0.4549,
+ "step": 7074
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.533947528312825e-06,
+ "loss": 0.4682,
+ "step": 7075
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.531321406734486e-06,
+ "loss": 0.456,
+ "step": 7076
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.528695466445638e-06,
+ "loss": 0.4794,
+ "step": 7077
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.526069707639115e-06,
+ "loss": 0.461,
+ "step": 7078
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.523444130507743e-06,
+ "loss": 0.4683,
+ "step": 7079
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.52081873524433e-06,
+ "loss": 0.471,
+ "step": 7080
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.518193522041679e-06,
+ "loss": 0.4773,
+ "step": 7081
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5155684910925754e-06,
+ "loss": 0.472,
+ "step": 7082
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.5129436425897876e-06,
+ "loss": 0.4755,
+ "step": 7083
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.510318976726074e-06,
+ "loss": 0.4634,
+ "step": 7084
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.507694493694179e-06,
+ "loss": 0.476,
+ "step": 7085
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.505070193686835e-06,
+ "loss": 0.4749,
+ "step": 7086
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.502446076896754e-06,
+ "loss": 0.4622,
+ "step": 7087
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.4998221435166504e-06,
+ "loss": 0.4815,
+ "step": 7088
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.497198393739209e-06,
+ "loss": 0.4569,
+ "step": 7089
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.494574827757107e-06,
+ "loss": 0.4719,
+ "step": 7090
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.4919514457630085e-06,
+ "loss": 0.4518,
+ "step": 7091
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.489328247949565e-06,
+ "loss": 0.4851,
+ "step": 7092
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.486705234509412e-06,
+ "loss": 0.4957,
+ "step": 7093
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.484082405635169e-06,
+ "loss": 0.4889,
+ "step": 7094
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.481459761519454e-06,
+ "loss": 0.4776,
+ "step": 7095
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.478837302354859e-06,
+ "loss": 0.4728,
+ "step": 7096
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.476215028333964e-06,
+ "loss": 0.4643,
+ "step": 7097
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.473592939649341e-06,
+ "loss": 0.468,
+ "step": 7098
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.470971036493546e-06,
+ "loss": 0.4845,
+ "step": 7099
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.468349319059114e-06,
+ "loss": 0.4818,
+ "step": 7100
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.465727787538584e-06,
+ "loss": 0.4749,
+ "step": 7101
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.463106442124459e-06,
+ "loss": 0.477,
+ "step": 7102
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.46048528300925e-06,
+ "loss": 0.4793,
+ "step": 7103
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.457864310385439e-06,
+ "loss": 0.4767,
+ "step": 7104
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.455243524445499e-06,
+ "loss": 0.474,
+ "step": 7105
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.452622925381887e-06,
+ "loss": 0.4725,
+ "step": 7106
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.450002513387053e-06,
+ "loss": 0.4833,
+ "step": 7107
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.4473822886534285e-06,
+ "loss": 0.4849,
+ "step": 7108
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.444762251373433e-06,
+ "loss": 0.498,
+ "step": 7109
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.442142401739469e-06,
+ "loss": 0.4671,
+ "step": 7110
+ },
+ {
+ "epoch": 0.59,
+ "learning_rate": 7.439522739943929e-06,
+ "loss": 0.4719,
+ "step": 7111
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.436903266179187e-06,
+ "loss": 0.4683,
+ "step": 7112
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.434283980637611e-06,
+ "loss": 0.4745,
+ "step": 7113
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4316648835115445e-06,
+ "loss": 0.4699,
+ "step": 7114
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4290459749933296e-06,
+ "loss": 0.4847,
+ "step": 7115
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.426427255275284e-06,
+ "loss": 0.5188,
+ "step": 7116
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.423808724549715e-06,
+ "loss": 0.483,
+ "step": 7117
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.421190383008921e-06,
+ "loss": 0.4699,
+ "step": 7118
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.418572230845178e-06,
+ "loss": 0.4695,
+ "step": 7119
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4159542682507535e-06,
+ "loss": 0.4848,
+ "step": 7120
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.413336495417896e-06,
+ "loss": 0.4621,
+ "step": 7121
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.410718912538853e-06,
+ "loss": 0.464,
+ "step": 7122
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.40810151980584e-06,
+ "loss": 0.4818,
+ "step": 7123
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.405484317411071e-06,
+ "loss": 0.4593,
+ "step": 7124
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.4028673055467456e-06,
+ "loss": 0.4669,
+ "step": 7125
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.400250484405041e-06,
+ "loss": 0.4662,
+ "step": 7126
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.397633854178125e-06,
+ "loss": 0.4847,
+ "step": 7127
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.395017415058154e-06,
+ "loss": 0.4946,
+ "step": 7128
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3924011672372745e-06,
+ "loss": 0.4734,
+ "step": 7129
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3897851109076055e-06,
+ "loss": 0.4795,
+ "step": 7130
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.387169246261262e-06,
+ "loss": 0.4637,
+ "step": 7131
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3845535734903385e-06,
+ "loss": 0.4562,
+ "step": 7132
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.381938092786926e-06,
+ "loss": 0.4704,
+ "step": 7133
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.37932280434309e-06,
+ "loss": 0.5288,
+ "step": 7134
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.376707708350881e-06,
+ "loss": 0.4919,
+ "step": 7135
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.374092805002353e-06,
+ "loss": 0.476,
+ "step": 7136
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.371478094489526e-06,
+ "loss": 0.4844,
+ "step": 7137
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.368863577004415e-06,
+ "loss": 0.4514,
+ "step": 7138
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3662492527390195e-06,
+ "loss": 0.4578,
+ "step": 7139
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.363635121885324e-06,
+ "loss": 0.4904,
+ "step": 7140
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.361021184635296e-06,
+ "loss": 0.4677,
+ "step": 7141
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.358407441180901e-06,
+ "loss": 0.4727,
+ "step": 7142
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.355793891714073e-06,
+ "loss": 0.4931,
+ "step": 7143
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.353180536426746e-06,
+ "loss": 0.4635,
+ "step": 7144
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.350567375510831e-06,
+ "loss": 0.4627,
+ "step": 7145
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.347954409158229e-06,
+ "loss": 0.4851,
+ "step": 7146
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.345341637560822e-06,
+ "loss": 0.4668,
+ "step": 7147
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3427290609104825e-06,
+ "loss": 0.4759,
+ "step": 7148
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.34011667939907e-06,
+ "loss": 0.4839,
+ "step": 7149
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.337504493218427e-06,
+ "loss": 0.4695,
+ "step": 7150
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.33489250256038e-06,
+ "loss": 0.4707,
+ "step": 7151
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.332280707616742e-06,
+ "loss": 0.4862,
+ "step": 7152
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.329669108579312e-06,
+ "loss": 0.4982,
+ "step": 7153
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.3270577056398765e-06,
+ "loss": 0.4853,
+ "step": 7154
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.324446498990202e-06,
+ "loss": 0.46,
+ "step": 7155
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.321835488822052e-06,
+ "loss": 0.489,
+ "step": 7156
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.319224675327165e-06,
+ "loss": 0.4728,
+ "step": 7157
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.316614058697264e-06,
+ "loss": 0.4661,
+ "step": 7158
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.31400363912407e-06,
+ "loss": 0.4589,
+ "step": 7159
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.311393416799275e-06,
+ "loss": 0.477,
+ "step": 7160
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.308783391914566e-06,
+ "loss": 0.4748,
+ "step": 7161
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.306173564661606e-06,
+ "loss": 0.4859,
+ "step": 7162
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.303563935232059e-06,
+ "loss": 0.4681,
+ "step": 7163
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.30095450381756e-06,
+ "loss": 0.4732,
+ "step": 7164
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.298345270609738e-06,
+ "loss": 0.4953,
+ "step": 7165
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.295736235800202e-06,
+ "loss": 0.4648,
+ "step": 7166
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.293127399580548e-06,
+ "loss": 0.4667,
+ "step": 7167
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.290518762142359e-06,
+ "loss": 0.4753,
+ "step": 7168
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.287910323677199e-06,
+ "loss": 0.4855,
+ "step": 7169
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.285302084376629e-06,
+ "loss": 0.4779,
+ "step": 7170
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.282694044432182e-06,
+ "loss": 0.4729,
+ "step": 7171
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2800862040353834e-06,
+ "loss": 0.4795,
+ "step": 7172
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.277478563377738e-06,
+ "loss": 0.4546,
+ "step": 7173
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.274871122650746e-06,
+ "loss": 0.4783,
+ "step": 7174
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.272263882045884e-06,
+ "loss": 0.484,
+ "step": 7175
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.269656841754612e-06,
+ "loss": 0.4802,
+ "step": 7176
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2670500019683895e-06,
+ "loss": 0.4704,
+ "step": 7177
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.264443362878648e-06,
+ "loss": 0.4744,
+ "step": 7178
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.261836924676806e-06,
+ "loss": 0.4763,
+ "step": 7179
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.259230687554273e-06,
+ "loss": 0.4847,
+ "step": 7180
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.25662465170244e-06,
+ "loss": 0.4645,
+ "step": 7181
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.254018817312676e-06,
+ "loss": 0.4808,
+ "step": 7182
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2514131845763535e-06,
+ "loss": 0.4698,
+ "step": 7183
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.248807753684812e-06,
+ "loss": 0.4562,
+ "step": 7184
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.246202524829389e-06,
+ "loss": 0.4745,
+ "step": 7185
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.243597498201398e-06,
+ "loss": 0.474,
+ "step": 7186
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.240992673992142e-06,
+ "loss": 0.4557,
+ "step": 7187
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.238388052392906e-06,
+ "loss": 0.4624,
+ "step": 7188
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.235783633594966e-06,
+ "loss": 0.4785,
+ "step": 7189
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2331794177895785e-06,
+ "loss": 0.4791,
+ "step": 7190
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.230575405167989e-06,
+ "loss": 0.4867,
+ "step": 7191
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2279715959214216e-06,
+ "loss": 0.473,
+ "step": 7192
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2253679902410914e-06,
+ "loss": 0.4794,
+ "step": 7193
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2227645883181926e-06,
+ "loss": 0.4752,
+ "step": 7194
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.220161390343914e-06,
+ "loss": 0.4562,
+ "step": 7195
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.217558396509416e-06,
+ "loss": 0.4697,
+ "step": 7196
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.214955607005861e-06,
+ "loss": 0.479,
+ "step": 7197
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.212353022024381e-06,
+ "loss": 0.4691,
+ "step": 7198
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.209750641756099e-06,
+ "loss": 0.5009,
+ "step": 7199
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2071484663921265e-06,
+ "loss": 0.4813,
+ "step": 7200
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2045464961235545e-06,
+ "loss": 0.4723,
+ "step": 7201
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.2019447311414615e-06,
+ "loss": 0.4889,
+ "step": 7202
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.199343171636903e-06,
+ "loss": 0.4896,
+ "step": 7203
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1967418178009396e-06,
+ "loss": 0.4664,
+ "step": 7204
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1941406698245945e-06,
+ "loss": 0.465,
+ "step": 7205
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1915397278988895e-06,
+ "loss": 0.4895,
+ "step": 7206
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.188938992214827e-06,
+ "loss": 0.4543,
+ "step": 7207
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.186338462963392e-06,
+ "loss": 0.4568,
+ "step": 7208
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.183738140335556e-06,
+ "loss": 0.4777,
+ "step": 7209
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.181138024522274e-06,
+ "loss": 0.4731,
+ "step": 7210
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1785381157144954e-06,
+ "loss": 0.4658,
+ "step": 7211
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.175938414103143e-06,
+ "loss": 0.4924,
+ "step": 7212
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.173338919879127e-06,
+ "loss": 0.4749,
+ "step": 7213
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.170739633233341e-06,
+ "loss": 0.46,
+ "step": 7214
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.168140554356671e-06,
+ "loss": 0.486,
+ "step": 7215
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.165541683439976e-06,
+ "loss": 0.4737,
+ "step": 7216
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.162943020674116e-06,
+ "loss": 0.4437,
+ "step": 7217
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.160344566249918e-06,
+ "loss": 0.4727,
+ "step": 7218
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1577463203582056e-06,
+ "loss": 0.4749,
+ "step": 7219
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.155148283189779e-06,
+ "loss": 0.4594,
+ "step": 7220
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.152550454935432e-06,
+ "loss": 0.4536,
+ "step": 7221
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.149952835785936e-06,
+ "loss": 0.4791,
+ "step": 7222
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.147355425932045e-06,
+ "loss": 0.4786,
+ "step": 7223
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.144758225564511e-06,
+ "loss": 0.4874,
+ "step": 7224
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1421612348740564e-06,
+ "loss": 0.4724,
+ "step": 7225
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.139564454051393e-06,
+ "loss": 0.4492,
+ "step": 7226
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.1369678832872205e-06,
+ "loss": 0.4765,
+ "step": 7227
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.134371522772218e-06,
+ "loss": 0.4604,
+ "step": 7228
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.131775372697051e-06,
+ "loss": 0.4776,
+ "step": 7229
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.129179433252369e-06,
+ "loss": 0.4757,
+ "step": 7230
+ },
+ {
+ "epoch": 0.6,
+ "learning_rate": 7.126583704628811e-06,
+ "loss": 0.4783,
+ "step": 7231
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.123988187016994e-06,
+ "loss": 0.4575,
+ "step": 7232
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.121392880607524e-06,
+ "loss": 0.4542,
+ "step": 7233
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.118797785590987e-06,
+ "loss": 0.4811,
+ "step": 7234
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.116202902157955e-06,
+ "loss": 0.4668,
+ "step": 7235
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.113608230498989e-06,
+ "loss": 0.4617,
+ "step": 7236
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.1110137708046245e-06,
+ "loss": 0.4798,
+ "step": 7237
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.108419523265398e-06,
+ "loss": 0.4776,
+ "step": 7238
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.105825488071814e-06,
+ "loss": 0.4692,
+ "step": 7239
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.1032316654143685e-06,
+ "loss": 0.5049,
+ "step": 7240
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.100638055483539e-06,
+ "loss": 0.497,
+ "step": 7241
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.098044658469794e-06,
+ "loss": 0.4646,
+ "step": 7242
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.095451474563577e-06,
+ "loss": 0.4768,
+ "step": 7243
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0928585039553196e-06,
+ "loss": 0.4877,
+ "step": 7244
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.090265746835448e-06,
+ "loss": 0.4736,
+ "step": 7245
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.087673203394353e-06,
+ "loss": 0.4889,
+ "step": 7246
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.085080873822427e-06,
+ "loss": 0.4775,
+ "step": 7247
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.082488758310039e-06,
+ "loss": 0.4754,
+ "step": 7248
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.079896857047541e-06,
+ "loss": 0.4945,
+ "step": 7249
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.07730517022527e-06,
+ "loss": 0.4771,
+ "step": 7250
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.074713698033551e-06,
+ "loss": 0.4622,
+ "step": 7251
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0721224406626895e-06,
+ "loss": 0.4601,
+ "step": 7252
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.069531398302982e-06,
+ "loss": 0.4758,
+ "step": 7253
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0669405711447e-06,
+ "loss": 0.4787,
+ "step": 7254
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.064349959378102e-06,
+ "loss": 0.4817,
+ "step": 7255
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.061759563193431e-06,
+ "loss": 0.4727,
+ "step": 7256
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.059169382780914e-06,
+ "loss": 0.4839,
+ "step": 7257
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.05657941833077e-06,
+ "loss": 0.4819,
+ "step": 7258
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.053989670033191e-06,
+ "loss": 0.4709,
+ "step": 7259
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.051400138078357e-06,
+ "loss": 0.5036,
+ "step": 7260
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.048810822656431e-06,
+ "loss": 0.4635,
+ "step": 7261
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.046221723957566e-06,
+ "loss": 0.4943,
+ "step": 7262
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.043632842171891e-06,
+ "loss": 0.466,
+ "step": 7263
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.04104417748952e-06,
+ "loss": 0.487,
+ "step": 7264
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.038455730100562e-06,
+ "loss": 0.5054,
+ "step": 7265
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.035867500195095e-06,
+ "loss": 0.4723,
+ "step": 7266
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.033279487963189e-06,
+ "loss": 0.4646,
+ "step": 7267
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.030691693594901e-06,
+ "loss": 0.49,
+ "step": 7268
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.028104117280265e-06,
+ "loss": 0.4855,
+ "step": 7269
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.0255167592092995e-06,
+ "loss": 0.4694,
+ "step": 7270
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.022929619572009e-06,
+ "loss": 0.4606,
+ "step": 7271
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.020342698558387e-06,
+ "loss": 0.4617,
+ "step": 7272
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.017755996358404e-06,
+ "loss": 0.4771,
+ "step": 7273
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.015169513162018e-06,
+ "loss": 0.4914,
+ "step": 7274
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.012583249159167e-06,
+ "loss": 0.4829,
+ "step": 7275
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.009997204539775e-06,
+ "loss": 0.488,
+ "step": 7276
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.007411379493755e-06,
+ "loss": 0.4732,
+ "step": 7277
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.004825774210992e-06,
+ "loss": 0.4704,
+ "step": 7278
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 7.002240388881369e-06,
+ "loss": 0.4658,
+ "step": 7279
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.999655223694743e-06,
+ "loss": 0.4793,
+ "step": 7280
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.997070278840961e-06,
+ "loss": 0.4676,
+ "step": 7281
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.994485554509842e-06,
+ "loss": 0.4818,
+ "step": 7282
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9919010508912075e-06,
+ "loss": 0.4762,
+ "step": 7283
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.989316768174848e-06,
+ "loss": 0.4686,
+ "step": 7284
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.986732706550536e-06,
+ "loss": 0.4748,
+ "step": 7285
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.984148866208047e-06,
+ "loss": 0.4721,
+ "step": 7286
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.98156524733712e-06,
+ "loss": 0.48,
+ "step": 7287
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.978981850127487e-06,
+ "loss": 0.4841,
+ "step": 7288
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.976398674768863e-06,
+ "loss": 0.4418,
+ "step": 7289
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.973815721450942e-06,
+ "loss": 0.4861,
+ "step": 7290
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.971232990363406e-06,
+ "loss": 0.4719,
+ "step": 7291
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.968650481695926e-06,
+ "loss": 0.4704,
+ "step": 7292
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.966068195638143e-06,
+ "loss": 0.4914,
+ "step": 7293
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.963486132379694e-06,
+ "loss": 0.4566,
+ "step": 7294
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.960904292110194e-06,
+ "loss": 0.4767,
+ "step": 7295
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.958322675019243e-06,
+ "loss": 0.4918,
+ "step": 7296
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.955741281296421e-06,
+ "loss": 0.4656,
+ "step": 7297
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.953160111131295e-06,
+ "loss": 0.4493,
+ "step": 7298
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.950579164713422e-06,
+ "loss": 0.4678,
+ "step": 7299
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.947998442232332e-06,
+ "loss": 0.4811,
+ "step": 7300
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.945417943877541e-06,
+ "loss": 0.4744,
+ "step": 7301
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.942837669838552e-06,
+ "loss": 0.4583,
+ "step": 7302
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9402576203048474e-06,
+ "loss": 0.498,
+ "step": 7303
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.937677795465898e-06,
+ "loss": 0.4433,
+ "step": 7304
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.935098195511151e-06,
+ "loss": 0.4787,
+ "step": 7305
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.932518820630048e-06,
+ "loss": 0.4839,
+ "step": 7306
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.929939671012005e-06,
+ "loss": 0.4922,
+ "step": 7307
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9273607468464185e-06,
+ "loss": 0.451,
+ "step": 7308
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.924782048322683e-06,
+ "loss": 0.4665,
+ "step": 7309
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.922203575630164e-06,
+ "loss": 0.4927,
+ "step": 7310
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9196253289582104e-06,
+ "loss": 0.4512,
+ "step": 7311
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.917047308496159e-06,
+ "loss": 0.4649,
+ "step": 7312
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.914469514433331e-06,
+ "loss": 0.4551,
+ "step": 7313
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9118919469590285e-06,
+ "loss": 0.4659,
+ "step": 7314
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.9093146062625395e-06,
+ "loss": 0.4642,
+ "step": 7315
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.906737492533129e-06,
+ "loss": 0.4668,
+ "step": 7316
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.904160605960051e-06,
+ "loss": 0.4703,
+ "step": 7317
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.901583946732542e-06,
+ "loss": 0.4792,
+ "step": 7318
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.899007515039817e-06,
+ "loss": 0.4782,
+ "step": 7319
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.896431311071086e-06,
+ "loss": 0.4555,
+ "step": 7320
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.893855335015532e-06,
+ "loss": 0.4866,
+ "step": 7321
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.891279587062321e-06,
+ "loss": 0.4725,
+ "step": 7322
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.888704067400605e-06,
+ "loss": 0.4588,
+ "step": 7323
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.886128776219525e-06,
+ "loss": 0.4671,
+ "step": 7324
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8835537137081955e-06,
+ "loss": 0.4611,
+ "step": 7325
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.880978880055716e-06,
+ "loss": 0.4666,
+ "step": 7326
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.878404275451176e-06,
+ "loss": 0.473,
+ "step": 7327
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.875829900083642e-06,
+ "loss": 0.4906,
+ "step": 7328
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.873255754142167e-06,
+ "loss": 0.4585,
+ "step": 7329
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.870681837815784e-06,
+ "loss": 0.4581,
+ "step": 7330
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.868108151293513e-06,
+ "loss": 0.4791,
+ "step": 7331
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.865534694764348e-06,
+ "loss": 0.4673,
+ "step": 7332
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.86296146841728e-06,
+ "loss": 0.4584,
+ "step": 7333
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.860388472441274e-06,
+ "loss": 0.4574,
+ "step": 7334
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8578157070252815e-06,
+ "loss": 0.4765,
+ "step": 7335
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8552431723582335e-06,
+ "loss": 0.4709,
+ "step": 7336
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.852670868629048e-06,
+ "loss": 0.4589,
+ "step": 7337
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.85009879602662e-06,
+ "loss": 0.4735,
+ "step": 7338
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8475269547398335e-06,
+ "loss": 0.4506,
+ "step": 7339
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.844955344957559e-06,
+ "loss": 0.488,
+ "step": 7340
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.842383966868642e-06,
+ "loss": 0.4864,
+ "step": 7341
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.839812820661912e-06,
+ "loss": 0.4675,
+ "step": 7342
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.837241906526182e-06,
+ "loss": 0.4823,
+ "step": 7343
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.834671224650254e-06,
+ "loss": 0.4612,
+ "step": 7344
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.832100775222906e-06,
+ "loss": 0.478,
+ "step": 7345
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.829530558432898e-06,
+ "loss": 0.4456,
+ "step": 7346
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.8269605744689805e-06,
+ "loss": 0.4765,
+ "step": 7347
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.824390823519882e-06,
+ "loss": 0.481,
+ "step": 7348
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.82182130577431e-06,
+ "loss": 0.4775,
+ "step": 7349
+ },
+ {
+ "epoch": 0.61,
+ "learning_rate": 6.819252021420966e-06,
+ "loss": 0.4842,
+ "step": 7350
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.816682970648522e-06,
+ "loss": 0.4671,
+ "step": 7351
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.814114153645641e-06,
+ "loss": 0.4894,
+ "step": 7352
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.811545570600961e-06,
+ "loss": 0.4694,
+ "step": 7353
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.808977221703115e-06,
+ "loss": 0.4797,
+ "step": 7354
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.8064091071407115e-06,
+ "loss": 0.4816,
+ "step": 7355
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.803841227102339e-06,
+ "loss": 0.4575,
+ "step": 7356
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.801273581776575e-06,
+ "loss": 0.4852,
+ "step": 7357
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.798706171351971e-06,
+ "loss": 0.4799,
+ "step": 7358
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.796138996017073e-06,
+ "loss": 0.4692,
+ "step": 7359
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.793572055960398e-06,
+ "loss": 0.4631,
+ "step": 7360
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.791005351370458e-06,
+ "loss": 0.47,
+ "step": 7361
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.788438882435737e-06,
+ "loss": 0.4797,
+ "step": 7362
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7858726493447084e-06,
+ "loss": 0.4582,
+ "step": 7363
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.78330665228582e-06,
+ "loss": 0.4842,
+ "step": 7364
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.780740891447515e-06,
+ "loss": 0.4711,
+ "step": 7365
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.778175367018205e-06,
+ "loss": 0.4705,
+ "step": 7366
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.775610079186299e-06,
+ "loss": 0.4719,
+ "step": 7367
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.773045028140177e-06,
+ "loss": 0.474,
+ "step": 7368
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.770480214068207e-06,
+ "loss": 0.4711,
+ "step": 7369
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.767915637158735e-06,
+ "loss": 0.4732,
+ "step": 7370
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.765351297600098e-06,
+ "loss": 0.5037,
+ "step": 7371
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.762787195580609e-06,
+ "loss": 0.4625,
+ "step": 7372
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.760223331288558e-06,
+ "loss": 0.4838,
+ "step": 7373
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.757659704912234e-06,
+ "loss": 0.4613,
+ "step": 7374
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.755096316639894e-06,
+ "loss": 0.4719,
+ "step": 7375
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.752533166659786e-06,
+ "loss": 0.4777,
+ "step": 7376
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.749970255160134e-06,
+ "loss": 0.4718,
+ "step": 7377
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.747407582329151e-06,
+ "loss": 0.4682,
+ "step": 7378
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.744845148355023e-06,
+ "loss": 0.4711,
+ "step": 7379
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.742282953425928e-06,
+ "loss": 0.4649,
+ "step": 7380
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.739720997730024e-06,
+ "loss": 0.4666,
+ "step": 7381
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.73715928145545e-06,
+ "loss": 0.4793,
+ "step": 7382
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.734597804790328e-06,
+ "loss": 0.4825,
+ "step": 7383
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.732036567922761e-06,
+ "loss": 0.4683,
+ "step": 7384
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.729475571040835e-06,
+ "loss": 0.4744,
+ "step": 7385
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.726914814332621e-06,
+ "loss": 0.4606,
+ "step": 7386
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.724354297986164e-06,
+ "loss": 0.4713,
+ "step": 7387
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7217940221895095e-06,
+ "loss": 0.5145,
+ "step": 7388
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7192339871306655e-06,
+ "loss": 0.4723,
+ "step": 7389
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7166741929976295e-06,
+ "loss": 0.4768,
+ "step": 7390
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.7141146399783875e-06,
+ "loss": 0.4662,
+ "step": 7391
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.711555328260899e-06,
+ "loss": 0.4682,
+ "step": 7392
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.708996258033109e-06,
+ "loss": 0.4747,
+ "step": 7393
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.706437429482942e-06,
+ "loss": 0.4901,
+ "step": 7394
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.703878842798315e-06,
+ "loss": 0.4792,
+ "step": 7395
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.701320498167115e-06,
+ "loss": 0.4451,
+ "step": 7396
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.6987623957772165e-06,
+ "loss": 0.4769,
+ "step": 7397
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.696204535816479e-06,
+ "loss": 0.4691,
+ "step": 7398
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.693646918472739e-06,
+ "loss": 0.4577,
+ "step": 7399
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.691089543933815e-06,
+ "loss": 0.4784,
+ "step": 7400
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.68853241238751e-06,
+ "loss": 0.4884,
+ "step": 7401
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.685975524021615e-06,
+ "loss": 0.4705,
+ "step": 7402
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.683418879023893e-06,
+ "loss": 0.4748,
+ "step": 7403
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.6808624775820954e-06,
+ "loss": 0.49,
+ "step": 7404
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.678306319883948e-06,
+ "loss": 0.456,
+ "step": 7405
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.675750406117172e-06,
+ "loss": 0.447,
+ "step": 7406
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.673194736469455e-06,
+ "loss": 0.4794,
+ "step": 7407
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.670639311128484e-06,
+ "loss": 0.4712,
+ "step": 7408
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.668084130281913e-06,
+ "loss": 0.4512,
+ "step": 7409
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.665529194117386e-06,
+ "loss": 0.4734,
+ "step": 7410
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.662974502822524e-06,
+ "loss": 0.4735,
+ "step": 7411
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.660420056584935e-06,
+ "loss": 0.4767,
+ "step": 7412
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.65786585559221e-06,
+ "loss": 0.4643,
+ "step": 7413
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.655311900031909e-06,
+ "loss": 0.4899,
+ "step": 7414
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.652758190091595e-06,
+ "loss": 0.4542,
+ "step": 7415
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.650204725958795e-06,
+ "loss": 0.4742,
+ "step": 7416
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.647651507821029e-06,
+ "loss": 0.4802,
+ "step": 7417
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.645098535865793e-06,
+ "loss": 0.4728,
+ "step": 7418
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.642545810280567e-06,
+ "loss": 0.4773,
+ "step": 7419
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.63999333125281e-06,
+ "loss": 0.4743,
+ "step": 7420
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.637441098969967e-06,
+ "loss": 0.4709,
+ "step": 7421
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.634889113619463e-06,
+ "loss": 0.4619,
+ "step": 7422
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.632337375388709e-06,
+ "loss": 0.4638,
+ "step": 7423
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.629785884465091e-06,
+ "loss": 0.4739,
+ "step": 7424
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.62723464103598e-06,
+ "loss": 0.4845,
+ "step": 7425
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.624683645288726e-06,
+ "loss": 0.46,
+ "step": 7426
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.622132897410668e-06,
+ "loss": 0.4822,
+ "step": 7427
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.619582397589117e-06,
+ "loss": 0.4872,
+ "step": 7428
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.617032146011377e-06,
+ "loss": 0.4577,
+ "step": 7429
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.614482142864728e-06,
+ "loss": 0.4661,
+ "step": 7430
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.611932388336425e-06,
+ "loss": 0.4734,
+ "step": 7431
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.609382882613717e-06,
+ "loss": 0.5089,
+ "step": 7432
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.606833625883829e-06,
+ "loss": 0.4623,
+ "step": 7433
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.604284618333967e-06,
+ "loss": 0.4694,
+ "step": 7434
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.601735860151313e-06,
+ "loss": 0.4794,
+ "step": 7435
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.599187351523046e-06,
+ "loss": 0.4663,
+ "step": 7436
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.596639092636315e-06,
+ "loss": 0.4743,
+ "step": 7437
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.594091083678256e-06,
+ "loss": 0.4755,
+ "step": 7438
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.5915433248359795e-06,
+ "loss": 0.4826,
+ "step": 7439
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.588995816296585e-06,
+ "loss": 0.4959,
+ "step": 7440
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.586448558247147e-06,
+ "loss": 0.4803,
+ "step": 7441
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.58390155087473e-06,
+ "loss": 0.4815,
+ "step": 7442
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.581354794366377e-06,
+ "loss": 0.4684,
+ "step": 7443
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.578808288909109e-06,
+ "loss": 0.4681,
+ "step": 7444
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.576262034689929e-06,
+ "loss": 0.4779,
+ "step": 7445
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.573716031895825e-06,
+ "loss": 0.4647,
+ "step": 7446
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.571170280713765e-06,
+ "loss": 0.4679,
+ "step": 7447
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.568624781330694e-06,
+ "loss": 0.472,
+ "step": 7448
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.566079533933551e-06,
+ "loss": 0.4853,
+ "step": 7449
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.563534538709244e-06,
+ "loss": 0.4819,
+ "step": 7450
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.560989795844668e-06,
+ "loss": 0.4661,
+ "step": 7451
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.558445305526695e-06,
+ "loss": 0.4871,
+ "step": 7452
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.555901067942188e-06,
+ "loss": 0.4697,
+ "step": 7453
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.553357083277979e-06,
+ "loss": 0.4684,
+ "step": 7454
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.550813351720888e-06,
+ "loss": 0.448,
+ "step": 7455
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.54826987345772e-06,
+ "loss": 0.4641,
+ "step": 7456
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.545726648675255e-06,
+ "loss": 0.4725,
+ "step": 7457
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.54318367756026e-06,
+ "loss": 0.4737,
+ "step": 7458
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.540640960299477e-06,
+ "loss": 0.4911,
+ "step": 7459
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.538098497079634e-06,
+ "loss": 0.4779,
+ "step": 7460
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.5355562880874345e-06,
+ "loss": 0.4593,
+ "step": 7461
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.533014333509573e-06,
+ "loss": 0.4589,
+ "step": 7462
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.530472633532718e-06,
+ "loss": 0.485,
+ "step": 7463
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.527931188343525e-06,
+ "loss": 0.5078,
+ "step": 7464
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.525389998128624e-06,
+ "loss": 0.4716,
+ "step": 7465
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.522849063074628e-06,
+ "loss": 0.4613,
+ "step": 7466
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.520308383368134e-06,
+ "loss": 0.4736,
+ "step": 7467
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.51776795919572e-06,
+ "loss": 0.4775,
+ "step": 7468
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.515227790743939e-06,
+ "loss": 0.4675,
+ "step": 7469
+ },
+ {
+ "epoch": 0.62,
+ "learning_rate": 6.51268787819934e-06,
+ "loss": 0.5053,
+ "step": 7470
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.510148221748438e-06,
+ "loss": 0.4562,
+ "step": 7471
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.507608821577733e-06,
+ "loss": 0.4942,
+ "step": 7472
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.505069677873712e-06,
+ "loss": 0.4833,
+ "step": 7473
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.502530790822838e-06,
+ "loss": 0.4595,
+ "step": 7474
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.499992160611556e-06,
+ "loss": 0.4807,
+ "step": 7475
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4974537874262865e-06,
+ "loss": 0.4696,
+ "step": 7476
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.494915671453448e-06,
+ "loss": 0.4573,
+ "step": 7477
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.492377812879422e-06,
+ "loss": 0.4639,
+ "step": 7478
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.489840211890581e-06,
+ "loss": 0.4548,
+ "step": 7479
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4873028686732755e-06,
+ "loss": 0.4844,
+ "step": 7480
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.484765783413838e-06,
+ "loss": 0.4707,
+ "step": 7481
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.482228956298575e-06,
+ "loss": 0.4791,
+ "step": 7482
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.479692387513788e-06,
+ "loss": 0.4717,
+ "step": 7483
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.477156077245752e-06,
+ "loss": 0.4769,
+ "step": 7484
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.474620025680722e-06,
+ "loss": 0.487,
+ "step": 7485
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.472084233004934e-06,
+ "loss": 0.4828,
+ "step": 7486
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.469548699404603e-06,
+ "loss": 0.4782,
+ "step": 7487
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.467013425065935e-06,
+ "loss": 0.4786,
+ "step": 7488
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.464478410175101e-06,
+ "loss": 0.4812,
+ "step": 7489
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.461943654918271e-06,
+ "loss": 0.4729,
+ "step": 7490
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.459409159481584e-06,
+ "loss": 0.4727,
+ "step": 7491
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.456874924051162e-06,
+ "loss": 0.4939,
+ "step": 7492
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.454340948813105e-06,
+ "loss": 0.4628,
+ "step": 7493
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.451807233953504e-06,
+ "loss": 0.4971,
+ "step": 7494
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4492737796584225e-06,
+ "loss": 0.4719,
+ "step": 7495
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.446740586113902e-06,
+ "loss": 0.4494,
+ "step": 7496
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.4442076535059774e-06,
+ "loss": 0.4809,
+ "step": 7497
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.441674982020654e-06,
+ "loss": 0.4808,
+ "step": 7498
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.439142571843915e-06,
+ "loss": 0.4673,
+ "step": 7499
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.43661042316174e-06,
+ "loss": 0.4685,
+ "step": 7500
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.434078536160072e-06,
+ "loss": 0.4587,
+ "step": 7501
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.431546911024844e-06,
+ "loss": 0.4609,
+ "step": 7502
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.429015547941968e-06,
+ "loss": 0.4694,
+ "step": 7503
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.426484447097336e-06,
+ "loss": 0.4861,
+ "step": 7504
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.423953608676827e-06,
+ "loss": 0.4696,
+ "step": 7505
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.42142303286629e-06,
+ "loss": 0.483,
+ "step": 7506
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.418892719851561e-06,
+ "loss": 0.4773,
+ "step": 7507
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.416362669818454e-06,
+ "loss": 0.4661,
+ "step": 7508
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.413832882952769e-06,
+ "loss": 0.4772,
+ "step": 7509
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.411303359440277e-06,
+ "loss": 0.4728,
+ "step": 7510
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.408774099466744e-06,
+ "loss": 0.4697,
+ "step": 7511
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.406245103217903e-06,
+ "loss": 0.4669,
+ "step": 7512
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.403716370879476e-06,
+ "loss": 0.4848,
+ "step": 7513
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.401187902637157e-06,
+ "loss": 0.4847,
+ "step": 7514
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.398659698676632e-06,
+ "loss": 0.4871,
+ "step": 7515
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.396131759183557e-06,
+ "loss": 0.4799,
+ "step": 7516
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.393604084343579e-06,
+ "loss": 0.4634,
+ "step": 7517
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.391076674342316e-06,
+ "loss": 0.4661,
+ "step": 7518
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.388549529365371e-06,
+ "loss": 0.4611,
+ "step": 7519
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3860226495983295e-06,
+ "loss": 0.4653,
+ "step": 7520
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.383496035226752e-06,
+ "loss": 0.4802,
+ "step": 7521
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.380969686436183e-06,
+ "loss": 0.4697,
+ "step": 7522
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.378443603412145e-06,
+ "loss": 0.47,
+ "step": 7523
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.375917786340149e-06,
+ "loss": 0.4656,
+ "step": 7524
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.373392235405674e-06,
+ "loss": 0.4674,
+ "step": 7525
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3708669507941925e-06,
+ "loss": 0.454,
+ "step": 7526
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.368341932691146e-06,
+ "loss": 0.4648,
+ "step": 7527
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.365817181281965e-06,
+ "loss": 0.4764,
+ "step": 7528
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.36329269675205e-06,
+ "loss": 0.4925,
+ "step": 7529
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.360768479286793e-06,
+ "loss": 0.4803,
+ "step": 7530
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.358244529071565e-06,
+ "loss": 0.4688,
+ "step": 7531
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.355720846291713e-06,
+ "loss": 0.4638,
+ "step": 7532
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3531974311325625e-06,
+ "loss": 0.4732,
+ "step": 7533
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.350674283779424e-06,
+ "loss": 0.4725,
+ "step": 7534
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.348151404417589e-06,
+ "loss": 0.46,
+ "step": 7535
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3456287932323255e-06,
+ "loss": 0.4699,
+ "step": 7536
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.34310645040888e-06,
+ "loss": 0.464,
+ "step": 7537
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.34058437613249e-06,
+ "loss": 0.4604,
+ "step": 7538
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.338062570588363e-06,
+ "loss": 0.4868,
+ "step": 7539
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.335541033961687e-06,
+ "loss": 0.4638,
+ "step": 7540
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.33301976643764e-06,
+ "loss": 0.4742,
+ "step": 7541
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.330498768201367e-06,
+ "loss": 0.4737,
+ "step": 7542
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.327978039438003e-06,
+ "loss": 0.476,
+ "step": 7543
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.325457580332655e-06,
+ "loss": 0.4563,
+ "step": 7544
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3229373910704205e-06,
+ "loss": 0.4869,
+ "step": 7545
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.3204174718363705e-06,
+ "loss": 0.4795,
+ "step": 7546
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.317897822815559e-06,
+ "loss": 0.4641,
+ "step": 7547
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.315378444193014e-06,
+ "loss": 0.4707,
+ "step": 7548
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.31285933615375e-06,
+ "loss": 0.4488,
+ "step": 7549
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.310340498882763e-06,
+ "loss": 0.4658,
+ "step": 7550
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.30782193256502e-06,
+ "loss": 0.4589,
+ "step": 7551
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.305303637385478e-06,
+ "loss": 0.4657,
+ "step": 7552
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.302785613529072e-06,
+ "loss": 0.4786,
+ "step": 7553
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.300267861180713e-06,
+ "loss": 0.4664,
+ "step": 7554
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.297750380525289e-06,
+ "loss": 0.4712,
+ "step": 7555
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.295233171747683e-06,
+ "loss": 0.4753,
+ "step": 7556
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.292716235032738e-06,
+ "loss": 0.4655,
+ "step": 7557
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.290199570565298e-06,
+ "loss": 0.4664,
+ "step": 7558
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.287683178530172e-06,
+ "loss": 0.4774,
+ "step": 7559
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.285167059112149e-06,
+ "loss": 0.482,
+ "step": 7560
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.282651212496009e-06,
+ "loss": 0.4864,
+ "step": 7561
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.280135638866502e-06,
+ "loss": 0.4768,
+ "step": 7562
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.277620338408362e-06,
+ "loss": 0.4789,
+ "step": 7563
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.275105311306298e-06,
+ "loss": 0.4865,
+ "step": 7564
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.272590557745011e-06,
+ "loss": 0.4426,
+ "step": 7565
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.270076077909166e-06,
+ "loss": 0.4658,
+ "step": 7566
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.267561871983424e-06,
+ "loss": 0.4645,
+ "step": 7567
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.265047940152413e-06,
+ "loss": 0.4599,
+ "step": 7568
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.262534282600747e-06,
+ "loss": 0.4751,
+ "step": 7569
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2600208995130156e-06,
+ "loss": 0.4681,
+ "step": 7570
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.257507791073792e-06,
+ "loss": 0.4576,
+ "step": 7571
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.254994957467633e-06,
+ "loss": 0.4755,
+ "step": 7572
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.252482398879068e-06,
+ "loss": 0.4781,
+ "step": 7573
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.249970115492609e-06,
+ "loss": 0.4545,
+ "step": 7574
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.247458107492745e-06,
+ "loss": 0.4745,
+ "step": 7575
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.244946375063951e-06,
+ "loss": 0.4892,
+ "step": 7576
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.242434918390678e-06,
+ "loss": 0.4818,
+ "step": 7577
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.239923737657351e-06,
+ "loss": 0.4687,
+ "step": 7578
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.237412833048389e-06,
+ "loss": 0.4732,
+ "step": 7579
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2349022047481784e-06,
+ "loss": 0.4699,
+ "step": 7580
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2323918529410895e-06,
+ "loss": 0.4839,
+ "step": 7581
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2298817778114725e-06,
+ "loss": 0.4702,
+ "step": 7582
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.227371979543658e-06,
+ "loss": 0.4687,
+ "step": 7583
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.224862458321954e-06,
+ "loss": 0.5033,
+ "step": 7584
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.222353214330643e-06,
+ "loss": 0.4622,
+ "step": 7585
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2198442477540036e-06,
+ "loss": 0.4653,
+ "step": 7586
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.2173355587762805e-06,
+ "loss": 0.4618,
+ "step": 7587
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.214827147581701e-06,
+ "loss": 0.4721,
+ "step": 7588
+ },
+ {
+ "epoch": 0.63,
+ "learning_rate": 6.212319014354472e-06,
+ "loss": 0.4822,
+ "step": 7589
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.209811159278778e-06,
+ "loss": 0.4573,
+ "step": 7590
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.207303582538789e-06,
+ "loss": 0.4765,
+ "step": 7591
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.2047962843186495e-06,
+ "loss": 0.4657,
+ "step": 7592
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.202289264802488e-06,
+ "loss": 0.4607,
+ "step": 7593
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.199782524174406e-06,
+ "loss": 0.4389,
+ "step": 7594
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.197276062618489e-06,
+ "loss": 0.4819,
+ "step": 7595
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.194769880318801e-06,
+ "loss": 0.4754,
+ "step": 7596
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.192263977459385e-06,
+ "loss": 0.4634,
+ "step": 7597
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.189758354224262e-06,
+ "loss": 0.4707,
+ "step": 7598
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.187253010797443e-06,
+ "loss": 0.4694,
+ "step": 7599
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1847479473629035e-06,
+ "loss": 0.4673,
+ "step": 7600
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1822431641046045e-06,
+ "loss": 0.4739,
+ "step": 7601
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1797386612064895e-06,
+ "loss": 0.4772,
+ "step": 7602
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.177234438852477e-06,
+ "loss": 0.4582,
+ "step": 7603
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.174730497226467e-06,
+ "loss": 0.4811,
+ "step": 7604
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.172226836512336e-06,
+ "loss": 0.4807,
+ "step": 7605
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.16972345689395e-06,
+ "loss": 0.4766,
+ "step": 7606
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.167220358555138e-06,
+ "loss": 0.4655,
+ "step": 7607
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.164717541679724e-06,
+ "loss": 0.4603,
+ "step": 7608
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.162215006451502e-06,
+ "loss": 0.4671,
+ "step": 7609
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.159712753054248e-06,
+ "loss": 0.4648,
+ "step": 7610
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.157210781671713e-06,
+ "loss": 0.4749,
+ "step": 7611
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.154709092487633e-06,
+ "loss": 0.4573,
+ "step": 7612
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.152207685685727e-06,
+ "loss": 0.4714,
+ "step": 7613
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1497065614496866e-06,
+ "loss": 0.4892,
+ "step": 7614
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.147205719963181e-06,
+ "loss": 0.4641,
+ "step": 7615
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.144705161409858e-06,
+ "loss": 0.4658,
+ "step": 7616
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.142204885973358e-06,
+ "loss": 0.4738,
+ "step": 7617
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1397048938372825e-06,
+ "loss": 0.4532,
+ "step": 7618
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.13720518518522e-06,
+ "loss": 0.481,
+ "step": 7619
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.134705760200747e-06,
+ "loss": 0.4683,
+ "step": 7620
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.132206619067407e-06,
+ "loss": 0.4594,
+ "step": 7621
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1297077619687216e-06,
+ "loss": 0.4808,
+ "step": 7622
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.127209189088204e-06,
+ "loss": 0.4638,
+ "step": 7623
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1247109006093345e-06,
+ "loss": 0.4768,
+ "step": 7624
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.122212896715577e-06,
+ "loss": 0.4717,
+ "step": 7625
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.119715177590373e-06,
+ "loss": 0.4688,
+ "step": 7626
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1172177434171495e-06,
+ "loss": 0.4736,
+ "step": 7627
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.114720594379304e-06,
+ "loss": 0.5022,
+ "step": 7628
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.112223730660221e-06,
+ "loss": 0.4698,
+ "step": 7629
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.109727152443254e-06,
+ "loss": 0.4825,
+ "step": 7630
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.1072308599117445e-06,
+ "loss": 0.4657,
+ "step": 7631
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.104734853249009e-06,
+ "loss": 0.4716,
+ "step": 7632
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.102239132638343e-06,
+ "loss": 0.4828,
+ "step": 7633
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.099743698263028e-06,
+ "loss": 0.4588,
+ "step": 7634
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.097248550306311e-06,
+ "loss": 0.4679,
+ "step": 7635
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.094753688951428e-06,
+ "loss": 0.4711,
+ "step": 7636
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.092259114381589e-06,
+ "loss": 0.4754,
+ "step": 7637
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.089764826779989e-06,
+ "loss": 0.4503,
+ "step": 7638
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.087270826329793e-06,
+ "loss": 0.4527,
+ "step": 7639
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.084777113214156e-06,
+ "loss": 0.4627,
+ "step": 7640
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.082283687616204e-06,
+ "loss": 0.4812,
+ "step": 7641
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.079790549719044e-06,
+ "loss": 0.4899,
+ "step": 7642
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.077297699705758e-06,
+ "loss": 0.4577,
+ "step": 7643
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.074805137759414e-06,
+ "loss": 0.4823,
+ "step": 7644
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.072312864063054e-06,
+ "loss": 0.4605,
+ "step": 7645
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0698208787996995e-06,
+ "loss": 0.4674,
+ "step": 7646
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.067329182152355e-06,
+ "loss": 0.4326,
+ "step": 7647
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.064837774303997e-06,
+ "loss": 0.4767,
+ "step": 7648
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0623466554375864e-06,
+ "loss": 0.4843,
+ "step": 7649
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.059855825736061e-06,
+ "loss": 0.4827,
+ "step": 7650
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.057365285382333e-06,
+ "loss": 0.4549,
+ "step": 7651
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0548750345593e-06,
+ "loss": 0.4818,
+ "step": 7652
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.052385073449833e-06,
+ "loss": 0.4602,
+ "step": 7653
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.049895402236789e-06,
+ "loss": 0.4846,
+ "step": 7654
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.047406021103e-06,
+ "loss": 0.4772,
+ "step": 7655
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.04491693023127e-06,
+ "loss": 0.4602,
+ "step": 7656
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.042428129804392e-06,
+ "loss": 0.4973,
+ "step": 7657
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0399396200051285e-06,
+ "loss": 0.4907,
+ "step": 7658
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0374514010162296e-06,
+ "loss": 0.4616,
+ "step": 7659
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.034963473020417e-06,
+ "loss": 0.4955,
+ "step": 7660
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0324758362003956e-06,
+ "loss": 0.4642,
+ "step": 7661
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.029988490738849e-06,
+ "loss": 0.4725,
+ "step": 7662
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.027501436818433e-06,
+ "loss": 0.4769,
+ "step": 7663
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0250146746217895e-06,
+ "loss": 0.4685,
+ "step": 7664
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.022528204331534e-06,
+ "loss": 0.4556,
+ "step": 7665
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.020042026130262e-06,
+ "loss": 0.4587,
+ "step": 7666
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.017556140200553e-06,
+ "loss": 0.4977,
+ "step": 7667
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.015070546724957e-06,
+ "loss": 0.4682,
+ "step": 7668
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.012585245886004e-06,
+ "loss": 0.4524,
+ "step": 7669
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.0101002378662066e-06,
+ "loss": 0.4828,
+ "step": 7670
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.007615522848053e-06,
+ "loss": 0.4578,
+ "step": 7671
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.00513110101401e-06,
+ "loss": 0.4576,
+ "step": 7672
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.002646972546517e-06,
+ "loss": 0.4703,
+ "step": 7673
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 6.000163137628009e-06,
+ "loss": 0.4826,
+ "step": 7674
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.997679596440884e-06,
+ "loss": 0.4883,
+ "step": 7675
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.995196349167523e-06,
+ "loss": 0.4739,
+ "step": 7676
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.992713395990285e-06,
+ "loss": 0.485,
+ "step": 7677
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.990230737091505e-06,
+ "loss": 0.4745,
+ "step": 7678
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.987748372653504e-06,
+ "loss": 0.4834,
+ "step": 7679
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9852663028585704e-06,
+ "loss": 0.466,
+ "step": 7680
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.982784527888985e-06,
+ "loss": 0.4647,
+ "step": 7681
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.980303047926996e-06,
+ "loss": 0.476,
+ "step": 7682
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.977821863154832e-06,
+ "loss": 0.4727,
+ "step": 7683
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.975340973754697e-06,
+ "loss": 0.463,
+ "step": 7684
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.972860379908784e-06,
+ "loss": 0.474,
+ "step": 7685
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.970380081799254e-06,
+ "loss": 0.4732,
+ "step": 7686
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.967900079608247e-06,
+ "loss": 0.4832,
+ "step": 7687
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.965420373517892e-06,
+ "loss": 0.4749,
+ "step": 7688
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.96294096371028e-06,
+ "loss": 0.4943,
+ "step": 7689
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.960461850367496e-06,
+ "loss": 0.4747,
+ "step": 7690
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9579830336715905e-06,
+ "loss": 0.4638,
+ "step": 7691
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9555045138046e-06,
+ "loss": 0.4821,
+ "step": 7692
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.953026290948534e-06,
+ "loss": 0.4843,
+ "step": 7693
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.950548365285383e-06,
+ "loss": 0.4715,
+ "step": 7694
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.948070736997118e-06,
+ "loss": 0.4683,
+ "step": 7695
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9455934062656874e-06,
+ "loss": 0.4626,
+ "step": 7696
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.943116373273012e-06,
+ "loss": 0.4571,
+ "step": 7697
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.940639638200998e-06,
+ "loss": 0.48,
+ "step": 7698
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.938163201231523e-06,
+ "loss": 0.4771,
+ "step": 7699
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.935687062546449e-06,
+ "loss": 0.4547,
+ "step": 7700
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.933211222327608e-06,
+ "loss": 0.4689,
+ "step": 7701
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.930735680756825e-06,
+ "loss": 0.4698,
+ "step": 7702
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.928260438015887e-06,
+ "loss": 0.4458,
+ "step": 7703
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.925785494286566e-06,
+ "loss": 0.4599,
+ "step": 7704
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.923310849750614e-06,
+ "loss": 0.4897,
+ "step": 7705
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.920836504589756e-06,
+ "loss": 0.4731,
+ "step": 7706
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.9183624589856956e-06,
+ "loss": 0.4675,
+ "step": 7707
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.915888713120124e-06,
+ "loss": 0.4822,
+ "step": 7708
+ },
+ {
+ "epoch": 0.64,
+ "learning_rate": 5.913415267174696e-06,
+ "loss": 0.4777,
+ "step": 7709
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.910942121331054e-06,
+ "loss": 0.4775,
+ "step": 7710
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.908469275770815e-06,
+ "loss": 0.4773,
+ "step": 7711
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.905996730675575e-06,
+ "loss": 0.4766,
+ "step": 7712
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.903524486226907e-06,
+ "loss": 0.4699,
+ "step": 7713
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.901052542606358e-06,
+ "loss": 0.4748,
+ "step": 7714
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.898580899995463e-06,
+ "loss": 0.4859,
+ "step": 7715
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.896109558575731e-06,
+ "loss": 0.4632,
+ "step": 7716
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.893638518528643e-06,
+ "loss": 0.4726,
+ "step": 7717
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.891167780035663e-06,
+ "loss": 0.4775,
+ "step": 7718
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.888697343278229e-06,
+ "loss": 0.4747,
+ "step": 7719
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.886227208437763e-06,
+ "loss": 0.4684,
+ "step": 7720
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8837573756956575e-06,
+ "loss": 0.4646,
+ "step": 7721
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.881287845233292e-06,
+ "loss": 0.4675,
+ "step": 7722
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.878818617232018e-06,
+ "loss": 0.4882,
+ "step": 7723
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.876349691873162e-06,
+ "loss": 0.4614,
+ "step": 7724
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.873881069338032e-06,
+ "loss": 0.4633,
+ "step": 7725
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.871412749807917e-06,
+ "loss": 0.4684,
+ "step": 7726
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.868944733464077e-06,
+ "loss": 0.4677,
+ "step": 7727
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.866477020487748e-06,
+ "loss": 0.4895,
+ "step": 7728
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.86400961106016e-06,
+ "loss": 0.4697,
+ "step": 7729
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8615425053625005e-06,
+ "loss": 0.4953,
+ "step": 7730
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.859075703575949e-06,
+ "loss": 0.464,
+ "step": 7731
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.856609205881654e-06,
+ "loss": 0.4749,
+ "step": 7732
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.854143012460745e-06,
+ "loss": 0.4698,
+ "step": 7733
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.851677123494326e-06,
+ "loss": 0.4582,
+ "step": 7734
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.849211539163486e-06,
+ "loss": 0.4782,
+ "step": 7735
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.846746259649288e-06,
+ "loss": 0.4867,
+ "step": 7736
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.844281285132769e-06,
+ "loss": 0.4811,
+ "step": 7737
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.841816615794948e-06,
+ "loss": 0.4702,
+ "step": 7738
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.839352251816821e-06,
+ "loss": 0.4787,
+ "step": 7739
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.836888193379359e-06,
+ "loss": 0.4668,
+ "step": 7740
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.834424440663512e-06,
+ "loss": 0.4868,
+ "step": 7741
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.831960993850203e-06,
+ "loss": 0.4854,
+ "step": 7742
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.829497853120345e-06,
+ "loss": 0.4697,
+ "step": 7743
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.827035018654821e-06,
+ "loss": 0.4569,
+ "step": 7744
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.824572490634488e-06,
+ "loss": 0.464,
+ "step": 7745
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.822110269240184e-06,
+ "loss": 0.5041,
+ "step": 7746
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.819648354652725e-06,
+ "loss": 0.4528,
+ "step": 7747
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8171867470529e-06,
+ "loss": 0.4847,
+ "step": 7748
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.8147254466214865e-06,
+ "loss": 0.4592,
+ "step": 7749
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.812264453539228e-06,
+ "loss": 0.4716,
+ "step": 7750
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.809803767986851e-06,
+ "loss": 0.473,
+ "step": 7751
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.807343390145055e-06,
+ "loss": 0.4787,
+ "step": 7752
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.80488332019452e-06,
+ "loss": 0.4637,
+ "step": 7753
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.802423558315908e-06,
+ "loss": 0.4845,
+ "step": 7754
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.799964104689847e-06,
+ "loss": 0.4641,
+ "step": 7755
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.797504959496957e-06,
+ "loss": 0.4473,
+ "step": 7756
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.795046122917823e-06,
+ "loss": 0.4654,
+ "step": 7757
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.792587595133012e-06,
+ "loss": 0.4761,
+ "step": 7758
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.790129376323068e-06,
+ "loss": 0.4757,
+ "step": 7759
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.787671466668513e-06,
+ "loss": 0.4667,
+ "step": 7760
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.785213866349844e-06,
+ "loss": 0.5057,
+ "step": 7761
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.782756575547535e-06,
+ "loss": 0.4902,
+ "step": 7762
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.780299594442047e-06,
+ "loss": 0.4814,
+ "step": 7763
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.777842923213801e-06,
+ "loss": 0.4806,
+ "step": 7764
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.775386562043212e-06,
+ "loss": 0.4772,
+ "step": 7765
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7729305111106645e-06,
+ "loss": 0.4515,
+ "step": 7766
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.770474770596518e-06,
+ "loss": 0.4629,
+ "step": 7767
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.768019340681113e-06,
+ "loss": 0.4687,
+ "step": 7768
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.765564221544759e-06,
+ "loss": 0.458,
+ "step": 7769
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.763109413367762e-06,
+ "loss": 0.4801,
+ "step": 7770
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.760654916330388e-06,
+ "loss": 0.5006,
+ "step": 7771
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.758200730612883e-06,
+ "loss": 0.4343,
+ "step": 7772
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.75574685639547e-06,
+ "loss": 0.4685,
+ "step": 7773
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7532932938583575e-06,
+ "loss": 0.4836,
+ "step": 7774
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.750840043181722e-06,
+ "loss": 0.4585,
+ "step": 7775
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7483871045457185e-06,
+ "loss": 0.4923,
+ "step": 7776
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.745934478130484e-06,
+ "loss": 0.4916,
+ "step": 7777
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7434821641161285e-06,
+ "loss": 0.4803,
+ "step": 7778
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.74103016268274e-06,
+ "loss": 0.4627,
+ "step": 7779
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.738578474010379e-06,
+ "loss": 0.4538,
+ "step": 7780
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.736127098279092e-06,
+ "loss": 0.4798,
+ "step": 7781
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.733676035668891e-06,
+ "loss": 0.4515,
+ "step": 7782
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.731225286359781e-06,
+ "loss": 0.4924,
+ "step": 7783
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.728774850531733e-06,
+ "loss": 0.468,
+ "step": 7784
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.726324728364688e-06,
+ "loss": 0.4704,
+ "step": 7785
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.723874920038586e-06,
+ "loss": 0.4524,
+ "step": 7786
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.721425425733322e-06,
+ "loss": 0.4711,
+ "step": 7787
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.718976245628779e-06,
+ "loss": 0.4704,
+ "step": 7788
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.7165273799048105e-06,
+ "loss": 0.475,
+ "step": 7789
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.71407882874126e-06,
+ "loss": 0.4684,
+ "step": 7790
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.711630592317933e-06,
+ "loss": 0.4576,
+ "step": 7791
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.709182670814619e-06,
+ "loss": 0.4713,
+ "step": 7792
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.706735064411082e-06,
+ "loss": 0.4866,
+ "step": 7793
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.704287773287061e-06,
+ "loss": 0.4498,
+ "step": 7794
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.701840797622284e-06,
+ "loss": 0.4883,
+ "step": 7795
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.699394137596437e-06,
+ "loss": 0.4998,
+ "step": 7796
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6969477933892e-06,
+ "loss": 0.4451,
+ "step": 7797
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.69450176518022e-06,
+ "loss": 0.4563,
+ "step": 7798
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.692056053149122e-06,
+ "loss": 0.4794,
+ "step": 7799
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.68961065747551e-06,
+ "loss": 0.4454,
+ "step": 7800
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.687165578338962e-06,
+ "loss": 0.4627,
+ "step": 7801
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.684720815919036e-06,
+ "loss": 0.4788,
+ "step": 7802
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.682276370395261e-06,
+ "loss": 0.4744,
+ "step": 7803
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.679832241947154e-06,
+ "loss": 0.4643,
+ "step": 7804
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.677388430754196e-06,
+ "loss": 0.4488,
+ "step": 7805
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.674944936995854e-06,
+ "loss": 0.4716,
+ "step": 7806
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.672501760851568e-06,
+ "loss": 0.4773,
+ "step": 7807
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6700589025007535e-06,
+ "loss": 0.4811,
+ "step": 7808
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.667616362122803e-06,
+ "loss": 0.491,
+ "step": 7809
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.665174139897083e-06,
+ "loss": 0.4657,
+ "step": 7810
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.662732236002949e-06,
+ "loss": 0.4906,
+ "step": 7811
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.660290650619719e-06,
+ "loss": 0.481,
+ "step": 7812
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.657849383926693e-06,
+ "loss": 0.4664,
+ "step": 7813
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.655408436103149e-06,
+ "loss": 0.4844,
+ "step": 7814
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.652967807328334e-06,
+ "loss": 0.4665,
+ "step": 7815
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6505274977814875e-06,
+ "loss": 0.4795,
+ "step": 7816
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.648087507641806e-06,
+ "loss": 0.4739,
+ "step": 7817
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6456478370884815e-06,
+ "loss": 0.508,
+ "step": 7818
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.643208486300669e-06,
+ "loss": 0.4686,
+ "step": 7819
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.640769455457502e-06,
+ "loss": 0.4812,
+ "step": 7820
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.6383307447380965e-06,
+ "loss": 0.4453,
+ "step": 7821
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.635892354321539e-06,
+ "loss": 0.4728,
+ "step": 7822
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.633454284386893e-06,
+ "loss": 0.4947,
+ "step": 7823
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.631016535113204e-06,
+ "loss": 0.4628,
+ "step": 7824
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.628579106679491e-06,
+ "loss": 0.4684,
+ "step": 7825
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.62614199926474e-06,
+ "loss": 0.4589,
+ "step": 7826
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.623705213047933e-06,
+ "loss": 0.483,
+ "step": 7827
+ },
+ {
+ "epoch": 0.65,
+ "learning_rate": 5.621268748208013e-06,
+ "loss": 0.4802,
+ "step": 7828
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.618832604923904e-06,
+ "loss": 0.4595,
+ "step": 7829
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.616396783374501e-06,
+ "loss": 0.4818,
+ "step": 7830
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.613961283738692e-06,
+ "loss": 0.4592,
+ "step": 7831
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.61152610619532e-06,
+ "loss": 0.4717,
+ "step": 7832
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.60909125092322e-06,
+ "loss": 0.4754,
+ "step": 7833
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.606656718101193e-06,
+ "loss": 0.4837,
+ "step": 7834
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.604222507908021e-06,
+ "loss": 0.4693,
+ "step": 7835
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.60178862052247e-06,
+ "loss": 0.4601,
+ "step": 7836
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.599355056123263e-06,
+ "loss": 0.5122,
+ "step": 7837
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.596921814889122e-06,
+ "loss": 0.4721,
+ "step": 7838
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.594488896998729e-06,
+ "loss": 0.481,
+ "step": 7839
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.592056302630748e-06,
+ "loss": 0.4778,
+ "step": 7840
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.589624031963816e-06,
+ "loss": 0.4752,
+ "step": 7841
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.5871920851765535e-06,
+ "loss": 0.4595,
+ "step": 7842
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.584760462447548e-06,
+ "loss": 0.4692,
+ "step": 7843
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.582329163955367e-06,
+ "loss": 0.47,
+ "step": 7844
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.579898189878561e-06,
+ "loss": 0.4761,
+ "step": 7845
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.577467540395645e-06,
+ "loss": 0.473,
+ "step": 7846
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.575037215685119e-06,
+ "loss": 0.4554,
+ "step": 7847
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.572607215925458e-06,
+ "loss": 0.4822,
+ "step": 7848
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.570177541295107e-06,
+ "loss": 0.4727,
+ "step": 7849
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.567748191972493e-06,
+ "loss": 0.4875,
+ "step": 7850
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.565319168136012e-06,
+ "loss": 0.4617,
+ "step": 7851
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.56289046996405e-06,
+ "loss": 0.4695,
+ "step": 7852
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.5604620976349575e-06,
+ "loss": 0.4883,
+ "step": 7853
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.558034051327061e-06,
+ "loss": 0.4778,
+ "step": 7854
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.55560633121867e-06,
+ "loss": 0.4758,
+ "step": 7855
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.553178937488061e-06,
+ "loss": 0.4683,
+ "step": 7856
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.550751870313494e-06,
+ "loss": 0.4598,
+ "step": 7857
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.548325129873209e-06,
+ "loss": 0.5035,
+ "step": 7858
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.545898716345408e-06,
+ "loss": 0.4741,
+ "step": 7859
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.543472629908282e-06,
+ "loss": 0.4689,
+ "step": 7860
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.541046870739987e-06,
+ "loss": 0.4767,
+ "step": 7861
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.538621439018666e-06,
+ "loss": 0.4579,
+ "step": 7862
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.53619633492243e-06,
+ "loss": 0.4773,
+ "step": 7863
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.533771558629365e-06,
+ "loss": 0.4711,
+ "step": 7864
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.531347110317544e-06,
+ "loss": 0.482,
+ "step": 7865
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.528922990165004e-06,
+ "loss": 0.443,
+ "step": 7866
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.52649919834976e-06,
+ "loss": 0.4557,
+ "step": 7867
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.524075735049812e-06,
+ "loss": 0.4646,
+ "step": 7868
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.521652600443124e-06,
+ "loss": 0.4632,
+ "step": 7869
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.519229794707643e-06,
+ "loss": 0.4557,
+ "step": 7870
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.516807318021286e-06,
+ "loss": 0.475,
+ "step": 7871
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.514385170561956e-06,
+ "loss": 0.4735,
+ "step": 7872
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.511963352507521e-06,
+ "loss": 0.4566,
+ "step": 7873
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.50954186403583e-06,
+ "loss": 0.4755,
+ "step": 7874
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.507120705324709e-06,
+ "loss": 0.4943,
+ "step": 7875
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.504699876551951e-06,
+ "loss": 0.4656,
+ "step": 7876
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.502279377895341e-06,
+ "loss": 0.4863,
+ "step": 7877
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.499859209532622e-06,
+ "loss": 0.4729,
+ "step": 7878
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.497439371641528e-06,
+ "loss": 0.4802,
+ "step": 7879
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.495019864399761e-06,
+ "loss": 0.4667,
+ "step": 7880
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.492600687984997e-06,
+ "loss": 0.4724,
+ "step": 7881
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.490181842574891e-06,
+ "loss": 0.4769,
+ "step": 7882
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.487763328347071e-06,
+ "loss": 0.4641,
+ "step": 7883
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.485345145479147e-06,
+ "loss": 0.485,
+ "step": 7884
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.482927294148691e-06,
+ "loss": 0.4727,
+ "step": 7885
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.480509774533271e-06,
+ "loss": 0.4835,
+ "step": 7886
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.478092586810413e-06,
+ "loss": 0.4731,
+ "step": 7887
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.47567573115763e-06,
+ "loss": 0.4807,
+ "step": 7888
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.473259207752404e-06,
+ "loss": 0.4883,
+ "step": 7889
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.470843016772194e-06,
+ "loss": 0.4636,
+ "step": 7890
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.468427158394434e-06,
+ "loss": 0.4616,
+ "step": 7891
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.466011632796531e-06,
+ "loss": 0.4808,
+ "step": 7892
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.463596440155878e-06,
+ "loss": 0.4907,
+ "step": 7893
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.461181580649837e-06,
+ "loss": 0.4812,
+ "step": 7894
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4587670544557404e-06,
+ "loss": 0.4711,
+ "step": 7895
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.456352861750904e-06,
+ "loss": 0.4735,
+ "step": 7896
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.453939002712611e-06,
+ "loss": 0.4667,
+ "step": 7897
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.451525477518133e-06,
+ "loss": 0.4629,
+ "step": 7898
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4491122863447e-06,
+ "loss": 0.4739,
+ "step": 7899
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.446699429369538e-06,
+ "loss": 0.4901,
+ "step": 7900
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.444286906769831e-06,
+ "loss": 0.4603,
+ "step": 7901
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.441874718722744e-06,
+ "loss": 0.474,
+ "step": 7902
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.439462865405419e-06,
+ "loss": 0.4659,
+ "step": 7903
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.437051346994973e-06,
+ "loss": 0.4519,
+ "step": 7904
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.434640163668494e-06,
+ "loss": 0.4696,
+ "step": 7905
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.432229315603054e-06,
+ "loss": 0.5035,
+ "step": 7906
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.429818802975697e-06,
+ "loss": 0.4653,
+ "step": 7907
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.427408625963434e-06,
+ "loss": 0.473,
+ "step": 7908
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.424998784743266e-06,
+ "loss": 0.5055,
+ "step": 7909
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4225892794921585e-06,
+ "loss": 0.4932,
+ "step": 7910
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.420180110387056e-06,
+ "loss": 0.4689,
+ "step": 7911
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.417771277604873e-06,
+ "loss": 0.4671,
+ "step": 7912
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4153627813225114e-06,
+ "loss": 0.4679,
+ "step": 7913
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.412954621716839e-06,
+ "loss": 0.4852,
+ "step": 7914
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.410546798964701e-06,
+ "loss": 0.4746,
+ "step": 7915
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.408139313242916e-06,
+ "loss": 0.4582,
+ "step": 7916
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.405732164728276e-06,
+ "loss": 0.4603,
+ "step": 7917
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.4033253535975635e-06,
+ "loss": 0.4852,
+ "step": 7918
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.400918880027513e-06,
+ "loss": 0.4561,
+ "step": 7919
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.398512744194854e-06,
+ "loss": 0.4665,
+ "step": 7920
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3961069462762804e-06,
+ "loss": 0.4571,
+ "step": 7921
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3937014864484635e-06,
+ "loss": 0.4624,
+ "step": 7922
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.39129636488805e-06,
+ "loss": 0.4613,
+ "step": 7923
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.388891581771664e-06,
+ "loss": 0.4828,
+ "step": 7924
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3864871372759e-06,
+ "loss": 0.4632,
+ "step": 7925
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.384083031577327e-06,
+ "loss": 0.4565,
+ "step": 7926
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.381679264852503e-06,
+ "loss": 0.4787,
+ "step": 7927
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.379275837277944e-06,
+ "loss": 0.4624,
+ "step": 7928
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3768727490301445e-06,
+ "loss": 0.4692,
+ "step": 7929
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.374470000285584e-06,
+ "loss": 0.454,
+ "step": 7930
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3720675912207085e-06,
+ "loss": 0.4773,
+ "step": 7931
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.369665522011938e-06,
+ "loss": 0.4697,
+ "step": 7932
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.367263792835673e-06,
+ "loss": 0.4758,
+ "step": 7933
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3648624038682886e-06,
+ "loss": 0.4822,
+ "step": 7934
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.362461355286129e-06,
+ "loss": 0.4614,
+ "step": 7935
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.360060647265519e-06,
+ "loss": 0.4877,
+ "step": 7936
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.357660279982757e-06,
+ "loss": 0.4527,
+ "step": 7937
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.35526025361411e-06,
+ "loss": 0.4733,
+ "step": 7938
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.352860568335835e-06,
+ "loss": 0.4525,
+ "step": 7939
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3504612243241474e-06,
+ "loss": 0.4608,
+ "step": 7940
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3480622217552524e-06,
+ "loss": 0.4853,
+ "step": 7941
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.3456635608053186e-06,
+ "loss": 0.4678,
+ "step": 7942
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.343265241650495e-06,
+ "loss": 0.4678,
+ "step": 7943
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.340867264466902e-06,
+ "loss": 0.471,
+ "step": 7944
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.338469629430638e-06,
+ "loss": 0.4485,
+ "step": 7945
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.336072336717773e-06,
+ "loss": 0.4902,
+ "step": 7946
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.333675386504361e-06,
+ "loss": 0.47,
+ "step": 7947
+ },
+ {
+ "epoch": 0.66,
+ "learning_rate": 5.33127877896642e-06,
+ "loss": 0.4581,
+ "step": 7948
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.328882514279942e-06,
+ "loss": 0.4655,
+ "step": 7949
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3264865926209076e-06,
+ "loss": 0.4873,
+ "step": 7950
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.324091014165259e-06,
+ "loss": 0.4545,
+ "step": 7951
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3216957790889176e-06,
+ "loss": 0.4819,
+ "step": 7952
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.319300887567777e-06,
+ "loss": 0.4598,
+ "step": 7953
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.316906339777714e-06,
+ "loss": 0.4577,
+ "step": 7954
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.31451213589457e-06,
+ "loss": 0.4706,
+ "step": 7955
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.312118276094167e-06,
+ "loss": 0.4746,
+ "step": 7956
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3097247605522996e-06,
+ "loss": 0.4613,
+ "step": 7957
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.307331589444737e-06,
+ "loss": 0.469,
+ "step": 7958
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.304938762947221e-06,
+ "loss": 0.4634,
+ "step": 7959
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.3025462812354744e-06,
+ "loss": 0.4984,
+ "step": 7960
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.300154144485194e-06,
+ "loss": 0.4598,
+ "step": 7961
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.297762352872044e-06,
+ "loss": 0.448,
+ "step": 7962
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2953709065716704e-06,
+ "loss": 0.4654,
+ "step": 7963
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.292979805759689e-06,
+ "loss": 0.4789,
+ "step": 7964
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.290589050611692e-06,
+ "loss": 0.4614,
+ "step": 7965
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.288198641303248e-06,
+ "loss": 0.4794,
+ "step": 7966
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.285808578009894e-06,
+ "loss": 0.454,
+ "step": 7967
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.283418860907155e-06,
+ "loss": 0.4548,
+ "step": 7968
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.281029490170515e-06,
+ "loss": 0.469,
+ "step": 7969
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2786404659754375e-06,
+ "loss": 0.4638,
+ "step": 7970
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.276251788497373e-06,
+ "loss": 0.4919,
+ "step": 7971
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.273863457911728e-06,
+ "loss": 0.4731,
+ "step": 7972
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.271475474393889e-06,
+ "loss": 0.4618,
+ "step": 7973
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.269087838119229e-06,
+ "loss": 0.4624,
+ "step": 7974
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.266700549263079e-06,
+ "loss": 0.4752,
+ "step": 7975
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.264313608000755e-06,
+ "loss": 0.4623,
+ "step": 7976
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.261927014507542e-06,
+ "loss": 0.4629,
+ "step": 7977
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2595407689587006e-06,
+ "loss": 0.457,
+ "step": 7978
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2571548715294664e-06,
+ "loss": 0.4797,
+ "step": 7979
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.254769322395053e-06,
+ "loss": 0.474,
+ "step": 7980
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2523841217306415e-06,
+ "loss": 0.456,
+ "step": 7981
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.249999269711396e-06,
+ "loss": 0.454,
+ "step": 7982
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.247614766512449e-06,
+ "loss": 0.4753,
+ "step": 7983
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.245230612308906e-06,
+ "loss": 0.4781,
+ "step": 7984
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.24284680727585e-06,
+ "loss": 0.4845,
+ "step": 7985
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.240463351588339e-06,
+ "loss": 0.4856,
+ "step": 7986
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.238080245421397e-06,
+ "loss": 0.4736,
+ "step": 7987
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.235697488950041e-06,
+ "loss": 0.4765,
+ "step": 7988
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.233315082349245e-06,
+ "loss": 0.4583,
+ "step": 7989
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2309330257939596e-06,
+ "loss": 0.467,
+ "step": 7990
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.22855131945912e-06,
+ "loss": 0.4896,
+ "step": 7991
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.226169963519625e-06,
+ "loss": 0.4487,
+ "step": 7992
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.223788958150353e-06,
+ "loss": 0.4804,
+ "step": 7993
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.221408303526151e-06,
+ "loss": 0.4854,
+ "step": 7994
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.219027999821851e-06,
+ "loss": 0.4575,
+ "step": 7995
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2166480472122475e-06,
+ "loss": 0.4674,
+ "step": 7996
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.214268445872117e-06,
+ "loss": 0.4684,
+ "step": 7997
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.211889195976207e-06,
+ "loss": 0.4653,
+ "step": 7998
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.209510297699239e-06,
+ "loss": 0.4578,
+ "step": 7999
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.2071317512159055e-06,
+ "loss": 0.4672,
+ "step": 8000
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.204753556700881e-06,
+ "loss": 0.4591,
+ "step": 8001
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.202375714328814e-06,
+ "loss": 0.4749,
+ "step": 8002
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.199998224274321e-06,
+ "loss": 0.483,
+ "step": 8003
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.197621086711993e-06,
+ "loss": 0.4896,
+ "step": 8004
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.195244301816398e-06,
+ "loss": 0.4701,
+ "step": 8005
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.192867869762076e-06,
+ "loss": 0.4645,
+ "step": 8006
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1904917907235395e-06,
+ "loss": 0.4561,
+ "step": 8007
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.188116064875286e-06,
+ "loss": 0.4791,
+ "step": 8008
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.185740692391774e-06,
+ "loss": 0.4797,
+ "step": 8009
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.183365673447442e-06,
+ "loss": 0.4743,
+ "step": 8010
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.180991008216698e-06,
+ "loss": 0.4652,
+ "step": 8011
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.178616696873935e-06,
+ "loss": 0.4932,
+ "step": 8012
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1762427395935065e-06,
+ "loss": 0.4888,
+ "step": 8013
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.173869136549744e-06,
+ "loss": 0.48,
+ "step": 8014
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.171495887916962e-06,
+ "loss": 0.465,
+ "step": 8015
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1691229938694396e-06,
+ "loss": 0.4495,
+ "step": 8016
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.166750454581432e-06,
+ "loss": 0.4761,
+ "step": 8017
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.164378270227167e-06,
+ "loss": 0.4633,
+ "step": 8018
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.162006440980849e-06,
+ "loss": 0.4559,
+ "step": 8019
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.159634967016653e-06,
+ "loss": 0.4589,
+ "step": 8020
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.157263848508735e-06,
+ "loss": 0.4933,
+ "step": 8021
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.154893085631213e-06,
+ "loss": 0.4685,
+ "step": 8022
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.152522678558195e-06,
+ "loss": 0.4722,
+ "step": 8023
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.150152627463749e-06,
+ "loss": 0.473,
+ "step": 8024
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1477829325219235e-06,
+ "loss": 0.4841,
+ "step": 8025
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1454135939067365e-06,
+ "loss": 0.4842,
+ "step": 8026
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.143044611792183e-06,
+ "loss": 0.4715,
+ "step": 8027
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.140675986352228e-06,
+ "loss": 0.4933,
+ "step": 8028
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.13830771776082e-06,
+ "loss": 0.4563,
+ "step": 8029
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.135939806191874e-06,
+ "loss": 0.4535,
+ "step": 8030
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.133572251819272e-06,
+ "loss": 0.4683,
+ "step": 8031
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.131205054816888e-06,
+ "loss": 0.4829,
+ "step": 8032
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.128838215358553e-06,
+ "loss": 0.4593,
+ "step": 8033
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.126471733618079e-06,
+ "loss": 0.4618,
+ "step": 8034
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.124105609769246e-06,
+ "loss": 0.4798,
+ "step": 8035
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.12173984398582e-06,
+ "loss": 0.4731,
+ "step": 8036
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.119374436441531e-06,
+ "loss": 0.4838,
+ "step": 8037
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.117009387310083e-06,
+ "loss": 0.4896,
+ "step": 8038
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.114644696765157e-06,
+ "loss": 0.4656,
+ "step": 8039
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.112280364980402e-06,
+ "loss": 0.4628,
+ "step": 8040
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.109916392129446e-06,
+ "loss": 0.469,
+ "step": 8041
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1075527783858934e-06,
+ "loss": 0.4615,
+ "step": 8042
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.105189523923312e-06,
+ "loss": 0.4725,
+ "step": 8043
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.1028266289152565e-06,
+ "loss": 0.4601,
+ "step": 8044
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.100464093535244e-06,
+ "loss": 0.4656,
+ "step": 8045
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.098101917956771e-06,
+ "loss": 0.4931,
+ "step": 8046
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0957401023533036e-06,
+ "loss": 0.4619,
+ "step": 8047
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.093378646898282e-06,
+ "loss": 0.4562,
+ "step": 8048
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.091017551765127e-06,
+ "loss": 0.4753,
+ "step": 8049
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0886568171272265e-06,
+ "loss": 0.475,
+ "step": 8050
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.08629644315794e-06,
+ "loss": 0.453,
+ "step": 8051
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0839364300306016e-06,
+ "loss": 0.4629,
+ "step": 8052
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.081576777918529e-06,
+ "loss": 0.4749,
+ "step": 8053
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.079217486994999e-06,
+ "loss": 0.4747,
+ "step": 8054
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0768585574332675e-06,
+ "loss": 0.4711,
+ "step": 8055
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.074499989406569e-06,
+ "loss": 0.4655,
+ "step": 8056
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.072141783088107e-06,
+ "loss": 0.4468,
+ "step": 8057
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.069783938651054e-06,
+ "loss": 0.45,
+ "step": 8058
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.067426456268563e-06,
+ "loss": 0.4939,
+ "step": 8059
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.065069336113756e-06,
+ "loss": 0.4619,
+ "step": 8060
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.062712578359728e-06,
+ "loss": 0.4636,
+ "step": 8061
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.060356183179556e-06,
+ "loss": 0.4795,
+ "step": 8062
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.058000150746276e-06,
+ "loss": 0.471,
+ "step": 8063
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.055644481232914e-06,
+ "loss": 0.4677,
+ "step": 8064
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.0532891748124565e-06,
+ "loss": 0.4624,
+ "step": 8065
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.050934231657867e-06,
+ "loss": 0.4759,
+ "step": 8066
+ },
+ {
+ "epoch": 0.67,
+ "learning_rate": 5.048579651942083e-06,
+ "loss": 0.4778,
+ "step": 8067
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.046225435838015e-06,
+ "loss": 0.4734,
+ "step": 8068
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.043871583518542e-06,
+ "loss": 0.4746,
+ "step": 8069
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.04151809515653e-06,
+ "loss": 0.4566,
+ "step": 8070
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.039164970924805e-06,
+ "loss": 0.4637,
+ "step": 8071
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.0368122109961716e-06,
+ "loss": 0.453,
+ "step": 8072
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.034459815543401e-06,
+ "loss": 0.4528,
+ "step": 8073
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.032107784739253e-06,
+ "loss": 0.4723,
+ "step": 8074
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.029756118756446e-06,
+ "loss": 0.4791,
+ "step": 8075
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.027404817767672e-06,
+ "loss": 0.4692,
+ "step": 8076
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.025053881945612e-06,
+ "loss": 0.4452,
+ "step": 8077
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.0227033114629e-06,
+ "loss": 0.4711,
+ "step": 8078
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.020353106492156e-06,
+ "loss": 0.4609,
+ "step": 8079
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.018003267205969e-06,
+ "loss": 0.4732,
+ "step": 8080
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.015653793776898e-06,
+ "loss": 0.4574,
+ "step": 8081
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.013304686377478e-06,
+ "loss": 0.4587,
+ "step": 8082
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.010955945180225e-06,
+ "loss": 0.4708,
+ "step": 8083
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.008607570357612e-06,
+ "loss": 0.4685,
+ "step": 8084
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.006259562082102e-06,
+ "loss": 0.4661,
+ "step": 8085
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.003911920526119e-06,
+ "loss": 0.4538,
+ "step": 8086
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 5.0015646458620645e-06,
+ "loss": 0.4543,
+ "step": 8087
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.999217738262313e-06,
+ "loss": 0.4777,
+ "step": 8088
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.996871197899207e-06,
+ "loss": 0.4714,
+ "step": 8089
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.994525024945075e-06,
+ "loss": 0.4666,
+ "step": 8090
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.992179219572204e-06,
+ "loss": 0.4673,
+ "step": 8091
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.989833781952864e-06,
+ "loss": 0.4602,
+ "step": 8092
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.987488712259288e-06,
+ "loss": 0.4727,
+ "step": 8093
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.985144010663695e-06,
+ "loss": 0.4598,
+ "step": 8094
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.982799677338268e-06,
+ "loss": 0.4775,
+ "step": 8095
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.980455712455161e-06,
+ "loss": 0.4617,
+ "step": 8096
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.978112116186512e-06,
+ "loss": 0.4769,
+ "step": 8097
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.975768888704422e-06,
+ "loss": 0.4757,
+ "step": 8098
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.973426030180968e-06,
+ "loss": 0.4748,
+ "step": 8099
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.971083540788199e-06,
+ "loss": 0.4697,
+ "step": 8100
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.968741420698137e-06,
+ "loss": 0.4743,
+ "step": 8101
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.966399670082779e-06,
+ "loss": 0.4653,
+ "step": 8102
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.964058289114089e-06,
+ "loss": 0.4759,
+ "step": 8103
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.961717277964012e-06,
+ "loss": 0.5013,
+ "step": 8104
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.959376636804467e-06,
+ "loss": 0.4803,
+ "step": 8105
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9570363658073366e-06,
+ "loss": 0.4712,
+ "step": 8106
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.954696465144479e-06,
+ "loss": 0.4678,
+ "step": 8107
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.952356934987728e-06,
+ "loss": 0.4561,
+ "step": 8108
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.95001777550889e-06,
+ "loss": 0.4624,
+ "step": 8109
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.947678986879737e-06,
+ "loss": 0.4786,
+ "step": 8110
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.945340569272029e-06,
+ "loss": 0.4465,
+ "step": 8111
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.943002522857487e-06,
+ "loss": 0.477,
+ "step": 8112
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.940664847807804e-06,
+ "loss": 0.4772,
+ "step": 8113
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9383275442946495e-06,
+ "loss": 0.4757,
+ "step": 8114
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.935990612489671e-06,
+ "loss": 0.4488,
+ "step": 8115
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.933654052564477e-06,
+ "loss": 0.4872,
+ "step": 8116
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.931317864690655e-06,
+ "loss": 0.4675,
+ "step": 8117
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.92898204903977e-06,
+ "loss": 0.4818,
+ "step": 8118
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.92664660578335e-06,
+ "loss": 0.4752,
+ "step": 8119
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.924311535092904e-06,
+ "loss": 0.4517,
+ "step": 8120
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9219768371399055e-06,
+ "loss": 0.4548,
+ "step": 8121
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.919642512095808e-06,
+ "loss": 0.454,
+ "step": 8122
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.917308560132029e-06,
+ "loss": 0.4802,
+ "step": 8123
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.914974981419974e-06,
+ "loss": 0.4431,
+ "step": 8124
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9126417761310005e-06,
+ "loss": 0.4663,
+ "step": 8125
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9103089444364605e-06,
+ "loss": 0.4542,
+ "step": 8126
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9079764865076615e-06,
+ "loss": 0.4589,
+ "step": 8127
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.90564440251589e-06,
+ "loss": 0.4767,
+ "step": 8128
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.903312692632405e-06,
+ "loss": 0.463,
+ "step": 8129
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.9009813570284326e-06,
+ "loss": 0.4729,
+ "step": 8130
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.898650395875185e-06,
+ "loss": 0.4562,
+ "step": 8131
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.896319809343834e-06,
+ "loss": 0.4701,
+ "step": 8132
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.893989597605528e-06,
+ "loss": 0.4578,
+ "step": 8133
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8916597608313855e-06,
+ "loss": 0.4918,
+ "step": 8134
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8893302991925075e-06,
+ "loss": 0.4608,
+ "step": 8135
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.887001212859954e-06,
+ "loss": 0.4662,
+ "step": 8136
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.884672502004762e-06,
+ "loss": 0.4747,
+ "step": 8137
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8823441667979475e-06,
+ "loss": 0.4636,
+ "step": 8138
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.880016207410493e-06,
+ "loss": 0.4709,
+ "step": 8139
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.877688624013353e-06,
+ "loss": 0.4848,
+ "step": 8140
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.875361416777453e-06,
+ "loss": 0.4728,
+ "step": 8141
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.873034585873697e-06,
+ "loss": 0.494,
+ "step": 8142
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.870708131472957e-06,
+ "loss": 0.4538,
+ "step": 8143
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.868382053746072e-06,
+ "loss": 0.4667,
+ "step": 8144
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.866056352863866e-06,
+ "loss": 0.4854,
+ "step": 8145
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8637310289971314e-06,
+ "loss": 0.4811,
+ "step": 8146
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.861406082316626e-06,
+ "loss": 0.471,
+ "step": 8147
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8590815129930865e-06,
+ "loss": 0.4748,
+ "step": 8148
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8567573211972175e-06,
+ "loss": 0.4685,
+ "step": 8149
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.854433507099698e-06,
+ "loss": 0.4846,
+ "step": 8150
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.852110070871175e-06,
+ "loss": 0.4754,
+ "step": 8151
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.849787012682282e-06,
+ "loss": 0.464,
+ "step": 8152
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8474643327036095e-06,
+ "loss": 0.4705,
+ "step": 8153
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.845142031105724e-06,
+ "loss": 0.4814,
+ "step": 8154
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8428201080591645e-06,
+ "loss": 0.4669,
+ "step": 8155
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.840498563734449e-06,
+ "loss": 0.4703,
+ "step": 8156
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.838177398302056e-06,
+ "loss": 0.4661,
+ "step": 8157
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8358566119324494e-06,
+ "loss": 0.4684,
+ "step": 8158
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.833536204796052e-06,
+ "loss": 0.4745,
+ "step": 8159
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.831216177063268e-06,
+ "loss": 0.4634,
+ "step": 8160
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.82889652890447e-06,
+ "loss": 0.4606,
+ "step": 8161
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8265772604900015e-06,
+ "loss": 0.4659,
+ "step": 8162
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.824258371990181e-06,
+ "loss": 0.4668,
+ "step": 8163
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.821939863575295e-06,
+ "loss": 0.4562,
+ "step": 8164
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.819621735415613e-06,
+ "loss": 0.4466,
+ "step": 8165
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.817303987681359e-06,
+ "loss": 0.4877,
+ "step": 8166
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.814986620542747e-06,
+ "loss": 0.4766,
+ "step": 8167
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.8126696341699515e-06,
+ "loss": 0.4601,
+ "step": 8168
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.810353028733123e-06,
+ "loss": 0.4765,
+ "step": 8169
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.808036804402383e-06,
+ "loss": 0.4913,
+ "step": 8170
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.80572096134782e-06,
+ "loss": 0.4553,
+ "step": 8171
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.803405499739511e-06,
+ "loss": 0.4824,
+ "step": 8172
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.801090419747486e-06,
+ "loss": 0.466,
+ "step": 8173
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.798775721541757e-06,
+ "loss": 0.4502,
+ "step": 8174
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.796461405292302e-06,
+ "loss": 0.453,
+ "step": 8175
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.794147471169082e-06,
+ "loss": 0.4768,
+ "step": 8176
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.7918339193420195e-06,
+ "loss": 0.4754,
+ "step": 8177
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.789520749981007e-06,
+ "loss": 0.4688,
+ "step": 8178
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.787207963255922e-06,
+ "loss": 0.4925,
+ "step": 8179
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.7848955593366035e-06,
+ "loss": 0.4751,
+ "step": 8180
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.782583538392863e-06,
+ "loss": 0.4647,
+ "step": 8181
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.7802719005944875e-06,
+ "loss": 0.4637,
+ "step": 8182
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.777960646111233e-06,
+ "loss": 0.4859,
+ "step": 8183
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.775649775112828e-06,
+ "loss": 0.4761,
+ "step": 8184
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.77333928776897e-06,
+ "loss": 0.4867,
+ "step": 8185
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.771029184249339e-06,
+ "loss": 0.4683,
+ "step": 8186
+ },
+ {
+ "epoch": 0.68,
+ "learning_rate": 4.768719464723572e-06,
+ "loss": 0.4825,
+ "step": 8187
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.766410129361294e-06,
+ "loss": 0.4661,
+ "step": 8188
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7641011783320866e-06,
+ "loss": 0.4592,
+ "step": 8189
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7617926118055125e-06,
+ "loss": 0.4794,
+ "step": 8190
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7594844299511e-06,
+ "loss": 0.4742,
+ "step": 8191
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.757176632938351e-06,
+ "loss": 0.4719,
+ "step": 8192
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.754869220936748e-06,
+ "loss": 0.4626,
+ "step": 8193
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.752562194115732e-06,
+ "loss": 0.4645,
+ "step": 8194
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.750255552644722e-06,
+ "loss": 0.4626,
+ "step": 8195
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7479492966931076e-06,
+ "loss": 0.4671,
+ "step": 8196
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.745643426430254e-06,
+ "loss": 0.4699,
+ "step": 8197
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.743337942025489e-06,
+ "loss": 0.4682,
+ "step": 8198
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.741032843648126e-06,
+ "loss": 0.4568,
+ "step": 8199
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.738728131467436e-06,
+ "loss": 0.4775,
+ "step": 8200
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.73642380565267e-06,
+ "loss": 0.4795,
+ "step": 8201
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.734119866373046e-06,
+ "loss": 0.4591,
+ "step": 8202
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.731816313797757e-06,
+ "loss": 0.4689,
+ "step": 8203
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7295131480959655e-06,
+ "loss": 0.4534,
+ "step": 8204
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.727210369436803e-06,
+ "loss": 0.4792,
+ "step": 8205
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.724907977989384e-06,
+ "loss": 0.4638,
+ "step": 8206
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7226059739227796e-06,
+ "loss": 0.4603,
+ "step": 8207
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.720304357406044e-06,
+ "loss": 0.4847,
+ "step": 8208
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7180031286081975e-06,
+ "loss": 0.464,
+ "step": 8209
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.715702287698232e-06,
+ "loss": 0.4724,
+ "step": 8210
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.71340183484511e-06,
+ "loss": 0.4716,
+ "step": 8211
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.711101770217766e-06,
+ "loss": 0.471,
+ "step": 8212
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.708802093985113e-06,
+ "loss": 0.473,
+ "step": 8213
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.706502806316028e-06,
+ "loss": 0.4778,
+ "step": 8214
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.704203907379358e-06,
+ "loss": 0.4548,
+ "step": 8215
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.7019053973439265e-06,
+ "loss": 0.484,
+ "step": 8216
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6996072763785225e-06,
+ "loss": 0.473,
+ "step": 8217
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.697309544651918e-06,
+ "loss": 0.4642,
+ "step": 8218
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6950122023328415e-06,
+ "loss": 0.4716,
+ "step": 8219
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.692715249590007e-06,
+ "loss": 0.4708,
+ "step": 8220
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.69041868659209e-06,
+ "loss": 0.4752,
+ "step": 8221
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.68812251350774e-06,
+ "loss": 0.4551,
+ "step": 8222
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.685826730505581e-06,
+ "loss": 0.4794,
+ "step": 8223
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.683531337754201e-06,
+ "loss": 0.4568,
+ "step": 8224
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6812363354221675e-06,
+ "loss": 0.4637,
+ "step": 8225
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.678941723678012e-06,
+ "loss": 0.4712,
+ "step": 8226
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.676647502690248e-06,
+ "loss": 0.4848,
+ "step": 8227
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.674353672627345e-06,
+ "loss": 0.4672,
+ "step": 8228
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.672060233657762e-06,
+ "loss": 0.4781,
+ "step": 8229
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.669767185949915e-06,
+ "loss": 0.4555,
+ "step": 8230
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.667474529672196e-06,
+ "loss": 0.4874,
+ "step": 8231
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.665182264992966e-06,
+ "loss": 0.4607,
+ "step": 8232
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.66289039208056e-06,
+ "loss": 0.4571,
+ "step": 8233
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.660598911103288e-06,
+ "loss": 0.4561,
+ "step": 8234
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.658307822229423e-06,
+ "loss": 0.4632,
+ "step": 8235
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.656017125627214e-06,
+ "loss": 0.4754,
+ "step": 8236
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.653726821464876e-06,
+ "loss": 0.483,
+ "step": 8237
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.651436909910607e-06,
+ "loss": 0.4668,
+ "step": 8238
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.649147391132562e-06,
+ "loss": 0.4958,
+ "step": 8239
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.646858265298881e-06,
+ "loss": 0.4723,
+ "step": 8240
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.644569532577662e-06,
+ "loss": 0.4746,
+ "step": 8241
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6422811931369825e-06,
+ "loss": 0.4718,
+ "step": 8242
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.639993247144889e-06,
+ "loss": 0.4667,
+ "step": 8243
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.637705694769396e-06,
+ "loss": 0.4615,
+ "step": 8244
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.635418536178492e-06,
+ "loss": 0.4802,
+ "step": 8245
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.633131771540136e-06,
+ "loss": 0.471,
+ "step": 8246
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.630845401022264e-06,
+ "loss": 0.4659,
+ "step": 8247
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.628559424792769e-06,
+ "loss": 0.48,
+ "step": 8248
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.626273843019532e-06,
+ "loss": 0.4433,
+ "step": 8249
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.623988655870394e-06,
+ "loss": 0.4805,
+ "step": 8250
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.621703863513168e-06,
+ "loss": 0.4693,
+ "step": 8251
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.61941946611564e-06,
+ "loss": 0.4697,
+ "step": 8252
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.617135463845563e-06,
+ "loss": 0.4931,
+ "step": 8253
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.614851856870673e-06,
+ "loss": 0.4724,
+ "step": 8254
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.612568645358664e-06,
+ "loss": 0.4771,
+ "step": 8255
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.6102858294772055e-06,
+ "loss": 0.4438,
+ "step": 8256
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.608003409393939e-06,
+ "loss": 0.49,
+ "step": 8257
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.60572138527647e-06,
+ "loss": 0.4572,
+ "step": 8258
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.60343975729239e-06,
+ "loss": 0.4596,
+ "step": 8259
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.601158525609245e-06,
+ "loss": 0.4777,
+ "step": 8260
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.598877690394565e-06,
+ "loss": 0.4661,
+ "step": 8261
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.596597251815844e-06,
+ "loss": 0.458,
+ "step": 8262
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5943172100405455e-06,
+ "loss": 0.4684,
+ "step": 8263
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.592037565236108e-06,
+ "loss": 0.4587,
+ "step": 8264
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.589758317569938e-06,
+ "loss": 0.4612,
+ "step": 8265
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5874794672094135e-06,
+ "loss": 0.475,
+ "step": 8266
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.585201014321882e-06,
+ "loss": 0.4665,
+ "step": 8267
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.582922959074668e-06,
+ "loss": 0.4585,
+ "step": 8268
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5806453016350584e-06,
+ "loss": 0.4705,
+ "step": 8269
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5783680421703205e-06,
+ "loss": 0.4901,
+ "step": 8270
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.576091180847684e-06,
+ "loss": 0.4554,
+ "step": 8271
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.57381471783435e-06,
+ "loss": 0.4782,
+ "step": 8272
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.571538653297491e-06,
+ "loss": 0.4807,
+ "step": 8273
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5692629874042585e-06,
+ "loss": 0.4598,
+ "step": 8274
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.566987720321764e-06,
+ "loss": 0.4618,
+ "step": 8275
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.564712852217094e-06,
+ "loss": 0.47,
+ "step": 8276
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.562438383257304e-06,
+ "loss": 0.4723,
+ "step": 8277
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5601643136094195e-06,
+ "loss": 0.4548,
+ "step": 8278
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.557890643440445e-06,
+ "loss": 0.4667,
+ "step": 8279
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5556173729173434e-06,
+ "loss": 0.4726,
+ "step": 8280
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.55334450220706e-06,
+ "loss": 0.4704,
+ "step": 8281
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.551072031476504e-06,
+ "loss": 0.4842,
+ "step": 8282
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.548799960892552e-06,
+ "loss": 0.4802,
+ "step": 8283
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.546528290622058e-06,
+ "loss": 0.4843,
+ "step": 8284
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.544257020831843e-06,
+ "loss": 0.4921,
+ "step": 8285
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.541986151688702e-06,
+ "loss": 0.4769,
+ "step": 8286
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.539715683359391e-06,
+ "loss": 0.45,
+ "step": 8287
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.537445616010655e-06,
+ "loss": 0.4646,
+ "step": 8288
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.535175949809188e-06,
+ "loss": 0.4756,
+ "step": 8289
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.532906684921672e-06,
+ "loss": 0.4601,
+ "step": 8290
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.53063782151475e-06,
+ "loss": 0.486,
+ "step": 8291
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5283693597550384e-06,
+ "loss": 0.4705,
+ "step": 8292
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.526101299809122e-06,
+ "loss": 0.4619,
+ "step": 8293
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.523833641843554e-06,
+ "loss": 0.4683,
+ "step": 8294
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.521566386024871e-06,
+ "loss": 0.4627,
+ "step": 8295
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.519299532519566e-06,
+ "loss": 0.483,
+ "step": 8296
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.517033081494109e-06,
+ "loss": 0.4766,
+ "step": 8297
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.514767033114935e-06,
+ "loss": 0.4708,
+ "step": 8298
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.512501387548453e-06,
+ "loss": 0.4741,
+ "step": 8299
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.510236144961047e-06,
+ "loss": 0.4742,
+ "step": 8300
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.507971305519062e-06,
+ "loss": 0.4632,
+ "step": 8301
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.505706869388825e-06,
+ "loss": 0.468,
+ "step": 8302
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.503442836736624e-06,
+ "loss": 0.4569,
+ "step": 8303
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.5011792077287175e-06,
+ "loss": 0.4734,
+ "step": 8304
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.498915982531339e-06,
+ "loss": 0.4751,
+ "step": 8305
+ },
+ {
+ "epoch": 0.69,
+ "learning_rate": 4.49665316131069e-06,
+ "loss": 0.4773,
+ "step": 8306
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.494390744232943e-06,
+ "loss": 0.4506,
+ "step": 8307
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.492128731464237e-06,
+ "loss": 0.4594,
+ "step": 8308
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.489867123170692e-06,
+ "loss": 0.4719,
+ "step": 8309
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.487605919518382e-06,
+ "loss": 0.4808,
+ "step": 8310
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.485345120673369e-06,
+ "loss": 0.4713,
+ "step": 8311
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4830847268016745e-06,
+ "loss": 0.4824,
+ "step": 8312
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.480824738069291e-06,
+ "loss": 0.4813,
+ "step": 8313
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.478565154642178e-06,
+ "loss": 0.477,
+ "step": 8314
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.476305976686279e-06,
+ "loss": 0.4704,
+ "step": 8315
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.474047204367494e-06,
+ "loss": 0.4748,
+ "step": 8316
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4717888378516986e-06,
+ "loss": 0.454,
+ "step": 8317
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.469530877304737e-06,
+ "loss": 0.4577,
+ "step": 8318
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.467273322892421e-06,
+ "loss": 0.4852,
+ "step": 8319
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.465016174780544e-06,
+ "loss": 0.4551,
+ "step": 8320
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.462759433134855e-06,
+ "loss": 0.4726,
+ "step": 8321
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4605030981210824e-06,
+ "loss": 0.5028,
+ "step": 8322
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4582471699049245e-06,
+ "loss": 0.4718,
+ "step": 8323
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.455991648652044e-06,
+ "loss": 0.479,
+ "step": 8324
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.453736534528077e-06,
+ "loss": 0.4514,
+ "step": 8325
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.45148182769863e-06,
+ "loss": 0.467,
+ "step": 8326
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.449227528329281e-06,
+ "loss": 0.489,
+ "step": 8327
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.446973636585571e-06,
+ "loss": 0.4569,
+ "step": 8328
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.444720152633023e-06,
+ "loss": 0.4732,
+ "step": 8329
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.442467076637121e-06,
+ "loss": 0.4608,
+ "step": 8330
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.440214408763318e-06,
+ "loss": 0.4619,
+ "step": 8331
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.437962149177047e-06,
+ "loss": 0.469,
+ "step": 8332
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.435710298043703e-06,
+ "loss": 0.4816,
+ "step": 8333
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.43345885552865e-06,
+ "loss": 0.4489,
+ "step": 8334
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.431207821797222e-06,
+ "loss": 0.4529,
+ "step": 8335
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.428957197014732e-06,
+ "loss": 0.4827,
+ "step": 8336
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.426706981346456e-06,
+ "loss": 0.4554,
+ "step": 8337
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.424457174957637e-06,
+ "loss": 0.4698,
+ "step": 8338
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.422207778013493e-06,
+ "loss": 0.4708,
+ "step": 8339
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.419958790679205e-06,
+ "loss": 0.4747,
+ "step": 8340
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.4177102131199405e-06,
+ "loss": 0.4694,
+ "step": 8341
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.415462045500813e-06,
+ "loss": 0.4597,
+ "step": 8342
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.41321428798693e-06,
+ "loss": 0.4661,
+ "step": 8343
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.410966940743353e-06,
+ "loss": 0.4799,
+ "step": 8344
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.408720003935116e-06,
+ "loss": 0.4642,
+ "step": 8345
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.406473477727228e-06,
+ "loss": 0.4708,
+ "step": 8346
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.404227362284661e-06,
+ "loss": 0.4911,
+ "step": 8347
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.401981657772359e-06,
+ "loss": 0.4707,
+ "step": 8348
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.399736364355243e-06,
+ "loss": 0.4633,
+ "step": 8349
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.397491482198195e-06,
+ "loss": 0.4862,
+ "step": 8350
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.395247011466067e-06,
+ "loss": 0.461,
+ "step": 8351
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.393002952323691e-06,
+ "loss": 0.4619,
+ "step": 8352
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3907593049358555e-06,
+ "loss": 0.4857,
+ "step": 8353
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.388516069467327e-06,
+ "loss": 0.482,
+ "step": 8354
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.386273246082834e-06,
+ "loss": 0.4656,
+ "step": 8355
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.384030834947088e-06,
+ "loss": 0.4777,
+ "step": 8356
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.381788836224759e-06,
+ "loss": 0.4786,
+ "step": 8357
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.379547250080491e-06,
+ "loss": 0.4525,
+ "step": 8358
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.377306076678895e-06,
+ "loss": 0.4711,
+ "step": 8359
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.375065316184556e-06,
+ "loss": 0.4986,
+ "step": 8360
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.372824968762019e-06,
+ "loss": 0.4564,
+ "step": 8361
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.37058503457581e-06,
+ "loss": 0.4666,
+ "step": 8362
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.368345513790427e-06,
+ "loss": 0.4745,
+ "step": 8363
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.366106406570325e-06,
+ "loss": 0.5115,
+ "step": 8364
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.363867713079935e-06,
+ "loss": 0.4606,
+ "step": 8365
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.361629433483659e-06,
+ "loss": 0.4698,
+ "step": 8366
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3593915679458645e-06,
+ "loss": 0.4697,
+ "step": 8367
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3571541166308926e-06,
+ "loss": 0.4661,
+ "step": 8368
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.354917079703049e-06,
+ "loss": 0.4622,
+ "step": 8369
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.352680457326617e-06,
+ "loss": 0.4748,
+ "step": 8370
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.350444249665845e-06,
+ "loss": 0.4748,
+ "step": 8371
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.348208456884945e-06,
+ "loss": 0.4493,
+ "step": 8372
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.345973079148111e-06,
+ "loss": 0.486,
+ "step": 8373
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.343738116619499e-06,
+ "loss": 0.4661,
+ "step": 8374
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.3415035694632326e-06,
+ "loss": 0.4423,
+ "step": 8375
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.339269437843405e-06,
+ "loss": 0.4572,
+ "step": 8376
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.337035721924089e-06,
+ "loss": 0.4763,
+ "step": 8377
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.334802421869316e-06,
+ "loss": 0.4874,
+ "step": 8378
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.332569537843089e-06,
+ "loss": 0.4534,
+ "step": 8379
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.330337070009382e-06,
+ "loss": 0.4533,
+ "step": 8380
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.328105018532136e-06,
+ "loss": 0.461,
+ "step": 8381
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.32587338357527e-06,
+ "loss": 0.4669,
+ "step": 8382
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.323642165302658e-06,
+ "loss": 0.4619,
+ "step": 8383
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.321411363878159e-06,
+ "loss": 0.4544,
+ "step": 8384
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.319180979465592e-06,
+ "loss": 0.4866,
+ "step": 8385
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.316951012228744e-06,
+ "loss": 0.4647,
+ "step": 8386
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.314721462331376e-06,
+ "loss": 0.4605,
+ "step": 8387
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.312492329937218e-06,
+ "loss": 0.4656,
+ "step": 8388
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.310263615209963e-06,
+ "loss": 0.4996,
+ "step": 8389
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.308035318313286e-06,
+ "loss": 0.4711,
+ "step": 8390
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.305807439410822e-06,
+ "loss": 0.4672,
+ "step": 8391
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.30357997866617e-06,
+ "loss": 0.4885,
+ "step": 8392
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.301352936242916e-06,
+ "loss": 0.4748,
+ "step": 8393
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.2991263123046005e-06,
+ "loss": 0.4615,
+ "step": 8394
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.296900107014735e-06,
+ "loss": 0.4693,
+ "step": 8395
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.294674320536803e-06,
+ "loss": 0.4776,
+ "step": 8396
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.292448953034261e-06,
+ "loss": 0.4694,
+ "step": 8397
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.290224004670529e-06,
+ "loss": 0.4633,
+ "step": 8398
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.287999475608997e-06,
+ "loss": 0.4731,
+ "step": 8399
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.285775366013026e-06,
+ "loss": 0.4514,
+ "step": 8400
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.283551676045945e-06,
+ "loss": 0.4551,
+ "step": 8401
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.281328405871048e-06,
+ "loss": 0.4775,
+ "step": 8402
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.279105555651608e-06,
+ "loss": 0.4647,
+ "step": 8403
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.276883125550864e-06,
+ "loss": 0.47,
+ "step": 8404
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.27466111573202e-06,
+ "loss": 0.4737,
+ "step": 8405
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.272439526358249e-06,
+ "loss": 0.4676,
+ "step": 8406
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.270218357592696e-06,
+ "loss": 0.459,
+ "step": 8407
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.267997609598477e-06,
+ "loss": 0.4788,
+ "step": 8408
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.26577728253867e-06,
+ "loss": 0.4554,
+ "step": 8409
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.263557376576326e-06,
+ "loss": 0.4793,
+ "step": 8410
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.261337891874473e-06,
+ "loss": 0.4776,
+ "step": 8411
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.259118828596096e-06,
+ "loss": 0.4613,
+ "step": 8412
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.25690018690415e-06,
+ "loss": 0.4708,
+ "step": 8413
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.254681966961571e-06,
+ "loss": 0.4675,
+ "step": 8414
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.2524641689312526e-06,
+ "loss": 0.4669,
+ "step": 8415
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.250246792976058e-06,
+ "loss": 0.4417,
+ "step": 8416
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.248029839258821e-06,
+ "loss": 0.4719,
+ "step": 8417
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.245813307942354e-06,
+ "loss": 0.4622,
+ "step": 8418
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.243597199189422e-06,
+ "loss": 0.4852,
+ "step": 8419
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.241381513162769e-06,
+ "loss": 0.4809,
+ "step": 8420
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.239166250025106e-06,
+ "loss": 0.4711,
+ "step": 8421
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.236951409939109e-06,
+ "loss": 0.4572,
+ "step": 8422
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.234736993067434e-06,
+ "loss": 0.4833,
+ "step": 8423
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.2325229995726915e-06,
+ "loss": 0.4804,
+ "step": 8424
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.230309429617474e-06,
+ "loss": 0.456,
+ "step": 8425
+ },
+ {
+ "epoch": 0.7,
+ "learning_rate": 4.228096283364335e-06,
+ "loss": 0.4626,
+ "step": 8426
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.2258835609757965e-06,
+ "loss": 0.4777,
+ "step": 8427
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.223671262614354e-06,
+ "loss": 0.4482,
+ "step": 8428
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.221459388442467e-06,
+ "loss": 0.4631,
+ "step": 8429
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.219247938622566e-06,
+ "loss": 0.451,
+ "step": 8430
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.217036913317054e-06,
+ "loss": 0.4781,
+ "step": 8431
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.214826312688299e-06,
+ "loss": 0.4649,
+ "step": 8432
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.212616136898634e-06,
+ "loss": 0.4937,
+ "step": 8433
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.210406386110371e-06,
+ "loss": 0.4511,
+ "step": 8434
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.208197060485783e-06,
+ "loss": 0.4606,
+ "step": 8435
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.205988160187113e-06,
+ "loss": 0.4546,
+ "step": 8436
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.20377968537657e-06,
+ "loss": 0.4751,
+ "step": 8437
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.201571636216343e-06,
+ "loss": 0.4677,
+ "step": 8438
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.199364012868575e-06,
+ "loss": 0.4771,
+ "step": 8439
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.197156815495389e-06,
+ "loss": 0.4534,
+ "step": 8440
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.194950044258871e-06,
+ "loss": 0.4552,
+ "step": 8441
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.192743699321075e-06,
+ "loss": 0.4798,
+ "step": 8442
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.190537780844026e-06,
+ "loss": 0.4611,
+ "step": 8443
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.188332288989721e-06,
+ "loss": 0.4666,
+ "step": 8444
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.186127223920118e-06,
+ "loss": 0.4572,
+ "step": 8445
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.183922585797152e-06,
+ "loss": 0.4646,
+ "step": 8446
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.181718374782722e-06,
+ "loss": 0.4711,
+ "step": 8447
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.179514591038692e-06,
+ "loss": 0.4616,
+ "step": 8448
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.177311234726904e-06,
+ "loss": 0.473,
+ "step": 8449
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.175108306009159e-06,
+ "loss": 0.4671,
+ "step": 8450
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.172905805047229e-06,
+ "loss": 0.4892,
+ "step": 8451
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.170703732002864e-06,
+ "loss": 0.4654,
+ "step": 8452
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.168502087037771e-06,
+ "loss": 0.4498,
+ "step": 8453
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.166300870313625e-06,
+ "loss": 0.493,
+ "step": 8454
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.164100081992084e-06,
+ "loss": 0.4726,
+ "step": 8455
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.161899722234759e-06,
+ "loss": 0.4567,
+ "step": 8456
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.159699791203237e-06,
+ "loss": 0.4695,
+ "step": 8457
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.157500289059065e-06,
+ "loss": 0.4722,
+ "step": 8458
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.155301215963776e-06,
+ "loss": 0.4779,
+ "step": 8459
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.153102572078855e-06,
+ "loss": 0.4611,
+ "step": 8460
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.150904357565763e-06,
+ "loss": 0.4846,
+ "step": 8461
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.148706572585927e-06,
+ "loss": 0.4619,
+ "step": 8462
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.146509217300738e-06,
+ "loss": 0.4694,
+ "step": 8463
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.14431229187157e-06,
+ "loss": 0.4676,
+ "step": 8464
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.142115796459748e-06,
+ "loss": 0.4772,
+ "step": 8465
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.13991973122658e-06,
+ "loss": 0.4591,
+ "step": 8466
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.137724096333334e-06,
+ "loss": 0.4703,
+ "step": 8467
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.135528891941246e-06,
+ "loss": 0.4667,
+ "step": 8468
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.133334118211526e-06,
+ "loss": 0.4814,
+ "step": 8469
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.131139775305346e-06,
+ "loss": 0.463,
+ "step": 8470
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.128945863383846e-06,
+ "loss": 0.4672,
+ "step": 8471
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.126752382608147e-06,
+ "loss": 0.4525,
+ "step": 8472
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.124559333139324e-06,
+ "loss": 0.4729,
+ "step": 8473
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.122366715138426e-06,
+ "loss": 0.4727,
+ "step": 8474
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.1201745287664664e-06,
+ "loss": 0.4635,
+ "step": 8475
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.117982774184436e-06,
+ "loss": 0.4769,
+ "step": 8476
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.115791451553286e-06,
+ "loss": 0.4583,
+ "step": 8477
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.1136005610339335e-06,
+ "loss": 0.476,
+ "step": 8478
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.111410102787276e-06,
+ "loss": 0.4648,
+ "step": 8479
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.109220076974168e-06,
+ "loss": 0.4614,
+ "step": 8480
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.107030483755436e-06,
+ "loss": 0.482,
+ "step": 8481
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.104841323291876e-06,
+ "loss": 0.4816,
+ "step": 8482
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.102652595744248e-06,
+ "loss": 0.4644,
+ "step": 8483
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.100464301273282e-06,
+ "loss": 0.4676,
+ "step": 8484
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.098276440039681e-06,
+ "loss": 0.4865,
+ "step": 8485
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0960890122041095e-06,
+ "loss": 0.472,
+ "step": 8486
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.093902017927208e-06,
+ "loss": 0.4773,
+ "step": 8487
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.091715457369577e-06,
+ "loss": 0.4894,
+ "step": 8488
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.089529330691789e-06,
+ "loss": 0.4876,
+ "step": 8489
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.087343638054382e-06,
+ "loss": 0.4657,
+ "step": 8490
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.085158379617866e-06,
+ "loss": 0.4594,
+ "step": 8491
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.082973555542713e-06,
+ "loss": 0.4669,
+ "step": 8492
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.080789165989376e-06,
+ "loss": 0.484,
+ "step": 8493
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0786052111182625e-06,
+ "loss": 0.4446,
+ "step": 8494
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0764216910897496e-06,
+ "loss": 0.4834,
+ "step": 8495
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.074238606064194e-06,
+ "loss": 0.4814,
+ "step": 8496
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.072055956201907e-06,
+ "loss": 0.4433,
+ "step": 8497
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.069873741663171e-06,
+ "loss": 0.466,
+ "step": 8498
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.067691962608245e-06,
+ "loss": 0.4694,
+ "step": 8499
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0655106191973485e-06,
+ "loss": 0.4718,
+ "step": 8500
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.063329711590668e-06,
+ "loss": 0.4776,
+ "step": 8501
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.061149239948361e-06,
+ "loss": 0.4952,
+ "step": 8502
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.058969204430553e-06,
+ "loss": 0.4696,
+ "step": 8503
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.056789605197335e-06,
+ "loss": 0.4936,
+ "step": 8504
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.054610442408765e-06,
+ "loss": 0.4689,
+ "step": 8505
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.052431716224876e-06,
+ "loss": 0.4777,
+ "step": 8506
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.050253426805668e-06,
+ "loss": 0.4714,
+ "step": 8507
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.048075574311101e-06,
+ "loss": 0.4638,
+ "step": 8508
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.045898158901108e-06,
+ "loss": 0.4809,
+ "step": 8509
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.043721180735589e-06,
+ "loss": 0.4672,
+ "step": 8510
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.041544639974413e-06,
+ "loss": 0.4507,
+ "step": 8511
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.03936853677741e-06,
+ "loss": 0.4801,
+ "step": 8512
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.037192871304396e-06,
+ "loss": 0.4604,
+ "step": 8513
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.035017643715135e-06,
+ "loss": 0.462,
+ "step": 8514
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.032842854169368e-06,
+ "loss": 0.465,
+ "step": 8515
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.030668502826799e-06,
+ "loss": 0.4692,
+ "step": 8516
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.028494589847109e-06,
+ "loss": 0.4676,
+ "step": 8517
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.026321115389942e-06,
+ "loss": 0.475,
+ "step": 8518
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0241480796149e-06,
+ "loss": 0.4485,
+ "step": 8519
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.021975482681571e-06,
+ "loss": 0.4837,
+ "step": 8520
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0198033247494995e-06,
+ "loss": 0.4756,
+ "step": 8521
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.017631605978198e-06,
+ "loss": 0.4693,
+ "step": 8522
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.015460326527149e-06,
+ "loss": 0.4934,
+ "step": 8523
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.013289486555801e-06,
+ "loss": 0.4677,
+ "step": 8524
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.01111908622357e-06,
+ "loss": 0.4588,
+ "step": 8525
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.008949125689846e-06,
+ "loss": 0.4807,
+ "step": 8526
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0067796051139775e-06,
+ "loss": 0.4802,
+ "step": 8527
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.0046105246552895e-06,
+ "loss": 0.4561,
+ "step": 8528
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.002441884473069e-06,
+ "loss": 0.4578,
+ "step": 8529
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 4.000273684726569e-06,
+ "loss": 0.469,
+ "step": 8530
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.998105925575017e-06,
+ "loss": 0.4794,
+ "step": 8531
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.995938607177599e-06,
+ "loss": 0.4589,
+ "step": 8532
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.993771729693476e-06,
+ "loss": 0.4691,
+ "step": 8533
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.991605293281779e-06,
+ "loss": 0.4729,
+ "step": 8534
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.989439298101597e-06,
+ "loss": 0.477,
+ "step": 8535
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.9872737443119914e-06,
+ "loss": 0.4653,
+ "step": 8536
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.985108632071995e-06,
+ "loss": 0.4654,
+ "step": 8537
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.982943961540604e-06,
+ "loss": 0.4591,
+ "step": 8538
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.980779732876777e-06,
+ "loss": 0.4844,
+ "step": 8539
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.978615946239456e-06,
+ "loss": 0.4753,
+ "step": 8540
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.9764526017875326e-06,
+ "loss": 0.4698,
+ "step": 8541
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.974289699679879e-06,
+ "loss": 0.4496,
+ "step": 8542
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.972127240075325e-06,
+ "loss": 0.4753,
+ "step": 8543
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.969965223132675e-06,
+ "loss": 0.4723,
+ "step": 8544
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.967803649010698e-06,
+ "loss": 0.4615,
+ "step": 8545
+ },
+ {
+ "epoch": 0.71,
+ "learning_rate": 3.965642517868129e-06,
+ "loss": 0.4637,
+ "step": 8546
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.963481829863673e-06,
+ "loss": 0.4717,
+ "step": 8547
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9613215851560094e-06,
+ "loss": 0.4675,
+ "step": 8548
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.95916178390377e-06,
+ "loss": 0.4737,
+ "step": 8549
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.957002426265564e-06,
+ "loss": 0.4573,
+ "step": 8550
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.954843512399965e-06,
+ "loss": 0.477,
+ "step": 8551
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.952685042465515e-06,
+ "loss": 0.4955,
+ "step": 8552
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.950527016620719e-06,
+ "loss": 0.4608,
+ "step": 8553
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.948369435024061e-06,
+ "loss": 0.4601,
+ "step": 8554
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9462122978339815e-06,
+ "loss": 0.4654,
+ "step": 8555
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.944055605208891e-06,
+ "loss": 0.4643,
+ "step": 8556
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.941899357307164e-06,
+ "loss": 0.4667,
+ "step": 8557
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.939743554287154e-06,
+ "loss": 0.4756,
+ "step": 8558
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.937588196307172e-06,
+ "loss": 0.4816,
+ "step": 8559
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9354332835254935e-06,
+ "loss": 0.4623,
+ "step": 8560
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.933278816100373e-06,
+ "loss": 0.468,
+ "step": 8561
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9311247941900245e-06,
+ "loss": 0.4859,
+ "step": 8562
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9289712179526275e-06,
+ "loss": 0.4537,
+ "step": 8563
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.926818087546333e-06,
+ "loss": 0.4717,
+ "step": 8564
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.924665403129259e-06,
+ "loss": 0.4674,
+ "step": 8565
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9225131648594835e-06,
+ "loss": 0.4457,
+ "step": 8566
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.920361372895067e-06,
+ "loss": 0.4414,
+ "step": 8567
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.918210027394021e-06,
+ "loss": 0.4717,
+ "step": 8568
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9160591285143375e-06,
+ "loss": 0.462,
+ "step": 8569
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.9139086764139675e-06,
+ "loss": 0.4642,
+ "step": 8570
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.911758671250829e-06,
+ "loss": 0.4636,
+ "step": 8571
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.909609113182812e-06,
+ "loss": 0.462,
+ "step": 8572
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.907460002367766e-06,
+ "loss": 0.4626,
+ "step": 8573
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.90531133896352e-06,
+ "loss": 0.4717,
+ "step": 8574
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.90316312312786e-06,
+ "loss": 0.4724,
+ "step": 8575
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.901015355018541e-06,
+ "loss": 0.4667,
+ "step": 8576
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8988680347932836e-06,
+ "loss": 0.4813,
+ "step": 8577
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.896721162609785e-06,
+ "loss": 0.4612,
+ "step": 8578
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.894574738625699e-06,
+ "loss": 0.4741,
+ "step": 8579
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.892428762998644e-06,
+ "loss": 0.4814,
+ "step": 8580
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.890283235886223e-06,
+ "loss": 0.4944,
+ "step": 8581
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.888138157445989e-06,
+ "loss": 0.433,
+ "step": 8582
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.885993527835466e-06,
+ "loss": 0.4921,
+ "step": 8583
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.883849347212151e-06,
+ "loss": 0.4568,
+ "step": 8584
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8817056157334985e-06,
+ "loss": 0.4738,
+ "step": 8585
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.879562333556939e-06,
+ "loss": 0.4914,
+ "step": 8586
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.877419500839861e-06,
+ "loss": 0.4677,
+ "step": 8587
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.875277117739632e-06,
+ "loss": 0.4613,
+ "step": 8588
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.873135184413573e-06,
+ "loss": 0.4628,
+ "step": 8589
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.870993701018988e-06,
+ "loss": 0.4649,
+ "step": 8590
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.868852667713131e-06,
+ "loss": 0.4456,
+ "step": 8591
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8667120846532335e-06,
+ "loss": 0.4777,
+ "step": 8592
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.864571951996491e-06,
+ "loss": 0.476,
+ "step": 8593
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.862432269900062e-06,
+ "loss": 0.4743,
+ "step": 8594
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.860293038521082e-06,
+ "loss": 0.4484,
+ "step": 8595
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.858154258016643e-06,
+ "loss": 0.4882,
+ "step": 8596
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.856015928543811e-06,
+ "loss": 0.4718,
+ "step": 8597
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.85387805025961e-06,
+ "loss": 0.4623,
+ "step": 8598
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8517406233210445e-06,
+ "loss": 0.4816,
+ "step": 8599
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.849603647885076e-06,
+ "loss": 0.47,
+ "step": 8600
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.84746712410863e-06,
+ "loss": 0.4653,
+ "step": 8601
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.845331052148612e-06,
+ "loss": 0.4681,
+ "step": 8602
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.843195432161883e-06,
+ "loss": 0.4579,
+ "step": 8603
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.841060264305272e-06,
+ "loss": 0.4616,
+ "step": 8604
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.838925548735579e-06,
+ "loss": 0.4761,
+ "step": 8605
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.836791285609568e-06,
+ "loss": 0.4677,
+ "step": 8606
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.834657475083967e-06,
+ "loss": 0.4562,
+ "step": 8607
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.83252411731548e-06,
+ "loss": 0.492,
+ "step": 8608
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.830391212460767e-06,
+ "loss": 0.4816,
+ "step": 8609
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.828258760676464e-06,
+ "loss": 0.4645,
+ "step": 8610
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.826126762119169e-06,
+ "loss": 0.4629,
+ "step": 8611
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.823995216945445e-06,
+ "loss": 0.4651,
+ "step": 8612
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.821864125311824e-06,
+ "loss": 0.4499,
+ "step": 8613
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.819733487374801e-06,
+ "loss": 0.4697,
+ "step": 8614
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.81760330329085e-06,
+ "loss": 0.4748,
+ "step": 8615
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.815473573216397e-06,
+ "loss": 0.4666,
+ "step": 8616
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8133442973078415e-06,
+ "loss": 0.4688,
+ "step": 8617
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.811215475721548e-06,
+ "loss": 0.4636,
+ "step": 8618
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.809087108613846e-06,
+ "loss": 0.452,
+ "step": 8619
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.8069591961410402e-06,
+ "loss": 0.458,
+ "step": 8620
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.804831738459388e-06,
+ "loss": 0.4557,
+ "step": 8621
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.80270473572513e-06,
+ "loss": 0.483,
+ "step": 8622
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.800578188094459e-06,
+ "loss": 0.4682,
+ "step": 8623
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7984520957235403e-06,
+ "loss": 0.4645,
+ "step": 8624
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7963264587685067e-06,
+ "loss": 0.4688,
+ "step": 8625
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7942012773854532e-06,
+ "loss": 0.4634,
+ "step": 8626
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.792076551730447e-06,
+ "loss": 0.4708,
+ "step": 8627
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.789952281959515e-06,
+ "loss": 0.4622,
+ "step": 8628
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7878284682286615e-06,
+ "loss": 0.4641,
+ "step": 8629
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7857051106938425e-06,
+ "loss": 0.4655,
+ "step": 8630
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7835822095109966e-06,
+ "loss": 0.4844,
+ "step": 8631
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7814597648360176e-06,
+ "loss": 0.4661,
+ "step": 8632
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7793377768247685e-06,
+ "loss": 0.4646,
+ "step": 8633
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7772162456330796e-06,
+ "loss": 0.49,
+ "step": 8634
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.775095171416744e-06,
+ "loss": 0.4759,
+ "step": 8635
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.77297455433153e-06,
+ "loss": 0.4735,
+ "step": 8636
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7708543945331654e-06,
+ "loss": 0.4817,
+ "step": 8637
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.768734692177345e-06,
+ "loss": 0.449,
+ "step": 8638
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.766615447419727e-06,
+ "loss": 0.4656,
+ "step": 8639
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.764496660415948e-06,
+ "loss": 0.4704,
+ "step": 8640
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.762378331321599e-06,
+ "loss": 0.4846,
+ "step": 8641
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7602604602922365e-06,
+ "loss": 0.4714,
+ "step": 8642
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.758143047483398e-06,
+ "loss": 0.4686,
+ "step": 8643
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.756026093050571e-06,
+ "loss": 0.4748,
+ "step": 8644
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7539095971492177e-06,
+ "loss": 0.4507,
+ "step": 8645
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7517935599347634e-06,
+ "loss": 0.4642,
+ "step": 8646
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7496779815626026e-06,
+ "loss": 0.4805,
+ "step": 8647
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.74756286218809e-06,
+ "loss": 0.4671,
+ "step": 8648
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.745448201966558e-06,
+ "loss": 0.4739,
+ "step": 8649
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7433340010532926e-06,
+ "loss": 0.4768,
+ "step": 8650
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7412202596035586e-06,
+ "loss": 0.4509,
+ "step": 8651
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.739106977772575e-06,
+ "loss": 0.4845,
+ "step": 8652
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7369941557155354e-06,
+ "loss": 0.4621,
+ "step": 8653
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7348817935875947e-06,
+ "loss": 0.4534,
+ "step": 8654
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7327698915438725e-06,
+ "loss": 0.4751,
+ "step": 8655
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.730658449739466e-06,
+ "loss": 0.4679,
+ "step": 8656
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7285474683294274e-06,
+ "loss": 0.4685,
+ "step": 8657
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7264369474687767e-06,
+ "loss": 0.4646,
+ "step": 8658
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7243268873125038e-06,
+ "loss": 0.4867,
+ "step": 8659
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7222172880155585e-06,
+ "loss": 0.473,
+ "step": 8660
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.720108149732866e-06,
+ "loss": 0.4919,
+ "step": 8661
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.717999472619309e-06,
+ "loss": 0.4689,
+ "step": 8662
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7158912568297458e-06,
+ "loss": 0.482,
+ "step": 8663
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.7137835025189894e-06,
+ "loss": 0.4459,
+ "step": 8664
+ },
+ {
+ "epoch": 0.72,
+ "learning_rate": 3.711676209841828e-06,
+ "loss": 0.4706,
+ "step": 8665
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.7095693789530096e-06,
+ "loss": 0.4603,
+ "step": 8666
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.707463010007252e-06,
+ "loss": 0.4563,
+ "step": 8667
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.7053571031592393e-06,
+ "loss": 0.4674,
+ "step": 8668
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.703251658563615e-06,
+ "loss": 0.4673,
+ "step": 8669
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.7011466763750026e-06,
+ "loss": 0.4479,
+ "step": 8670
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6990421567479764e-06,
+ "loss": 0.465,
+ "step": 8671
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6969380998370896e-06,
+ "loss": 0.4908,
+ "step": 8672
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6948345057968525e-06,
+ "loss": 0.4905,
+ "step": 8673
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.692731374781744e-06,
+ "loss": 0.4654,
+ "step": 8674
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.69062870694621e-06,
+ "loss": 0.4858,
+ "step": 8675
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.688526502444657e-06,
+ "loss": 0.4783,
+ "step": 8676
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6864247614314696e-06,
+ "loss": 0.4673,
+ "step": 8677
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6843234840609877e-06,
+ "loss": 0.4805,
+ "step": 8678
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6822226704875208e-06,
+ "loss": 0.4687,
+ "step": 8679
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6801223208653392e-06,
+ "loss": 0.4843,
+ "step": 8680
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6780224353486916e-06,
+ "loss": 0.4707,
+ "step": 8681
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.675923014091781e-06,
+ "loss": 0.4632,
+ "step": 8682
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.673824057248778e-06,
+ "loss": 0.4782,
+ "step": 8683
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.671725564973827e-06,
+ "loss": 0.4764,
+ "step": 8684
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.669627537421029e-06,
+ "loss": 0.4581,
+ "step": 8685
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6675299747444536e-06,
+ "loss": 0.4726,
+ "step": 8686
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6654328770981396e-06,
+ "loss": 0.4647,
+ "step": 8687
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6633362446360865e-06,
+ "loss": 0.4703,
+ "step": 8688
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6612400775122603e-06,
+ "loss": 0.448,
+ "step": 8689
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.659144375880602e-06,
+ "loss": 0.4705,
+ "step": 8690
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6570491398950038e-06,
+ "loss": 0.4516,
+ "step": 8691
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.654954369709337e-06,
+ "loss": 0.449,
+ "step": 8692
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6528600654774306e-06,
+ "loss": 0.466,
+ "step": 8693
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.650766227353081e-06,
+ "loss": 0.464,
+ "step": 8694
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.648672855490052e-06,
+ "loss": 0.4556,
+ "step": 8695
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6465799500420673e-06,
+ "loss": 0.4629,
+ "step": 8696
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6444875111628287e-06,
+ "loss": 0.4737,
+ "step": 8697
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.642395539005993e-06,
+ "loss": 0.4636,
+ "step": 8698
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.640304033725185e-06,
+ "loss": 0.4655,
+ "step": 8699
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6382129954739975e-06,
+ "loss": 0.4755,
+ "step": 8700
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6361224244059823e-06,
+ "loss": 0.4662,
+ "step": 8701
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.634032320674672e-06,
+ "loss": 0.4579,
+ "step": 8702
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.631942684433546e-06,
+ "loss": 0.4519,
+ "step": 8703
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.629853515836065e-06,
+ "loss": 0.4656,
+ "step": 8704
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.627764815035647e-06,
+ "loss": 0.463,
+ "step": 8705
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6256765821856775e-06,
+ "loss": 0.4798,
+ "step": 8706
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6235888174395062e-06,
+ "loss": 0.4823,
+ "step": 8707
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.621501520950451e-06,
+ "loss": 0.4671,
+ "step": 8708
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6194146928717942e-06,
+ "loss": 0.4839,
+ "step": 8709
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.61732833335678e-06,
+ "loss": 0.4805,
+ "step": 8710
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6152424425586285e-06,
+ "loss": 0.4655,
+ "step": 8711
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.613157020630512e-06,
+ "loss": 0.4648,
+ "step": 8712
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.611072067725583e-06,
+ "loss": 0.4541,
+ "step": 8713
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.608987583996948e-06,
+ "loss": 0.4756,
+ "step": 8714
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.606903569597683e-06,
+ "loss": 0.4576,
+ "step": 8715
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.6048200246808273e-06,
+ "loss": 0.4836,
+ "step": 8716
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.602736949399388e-06,
+ "loss": 0.473,
+ "step": 8717
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.600654343906341e-06,
+ "loss": 0.4894,
+ "step": 8718
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5985722083546228e-06,
+ "loss": 0.4522,
+ "step": 8719
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5964905428971354e-06,
+ "loss": 0.473,
+ "step": 8720
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.594409347686746e-06,
+ "loss": 0.4861,
+ "step": 8721
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5923286228762934e-06,
+ "loss": 0.4682,
+ "step": 8722
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5902483686185764e-06,
+ "loss": 0.457,
+ "step": 8723
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.588168585066355e-06,
+ "loss": 0.4876,
+ "step": 8724
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5860892723723674e-06,
+ "loss": 0.4721,
+ "step": 8725
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5840104306893055e-06,
+ "loss": 0.4603,
+ "step": 8726
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5819320601698324e-06,
+ "loss": 0.4653,
+ "step": 8727
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.579854160966574e-06,
+ "loss": 0.4754,
+ "step": 8728
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5777767332321222e-06,
+ "loss": 0.4538,
+ "step": 8729
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5756997771190317e-06,
+ "loss": 0.4826,
+ "step": 8730
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.573623292779832e-06,
+ "loss": 0.4565,
+ "step": 8731
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5715472803670092e-06,
+ "loss": 0.4866,
+ "step": 8732
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5694717400330125e-06,
+ "loss": 0.4571,
+ "step": 8733
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5673966719302677e-06,
+ "loss": 0.4778,
+ "step": 8734
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.565322076211156e-06,
+ "loss": 0.4611,
+ "step": 8735
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5632479530280273e-06,
+ "loss": 0.4616,
+ "step": 8736
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5611743025331933e-06,
+ "loss": 0.4913,
+ "step": 8737
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.559101124878941e-06,
+ "loss": 0.46,
+ "step": 8738
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.557028420217512e-06,
+ "loss": 0.4664,
+ "step": 8739
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5549561887011186e-06,
+ "loss": 0.47,
+ "step": 8740
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.552884430481934e-06,
+ "loss": 0.4343,
+ "step": 8741
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5508131457120986e-06,
+ "loss": 0.4623,
+ "step": 8742
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5487423345437253e-06,
+ "loss": 0.4712,
+ "step": 8743
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.546671997128879e-06,
+ "loss": 0.4623,
+ "step": 8744
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5446021336196024e-06,
+ "loss": 0.4617,
+ "step": 8745
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5425327441678956e-06,
+ "loss": 0.4594,
+ "step": 8746
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5404638289257256e-06,
+ "loss": 0.4785,
+ "step": 8747
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.538395388045024e-06,
+ "loss": 0.4682,
+ "step": 8748
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.53632742167769e-06,
+ "loss": 0.4745,
+ "step": 8749
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5342599299755854e-06,
+ "loss": 0.4562,
+ "step": 8750
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.532192913090534e-06,
+ "loss": 0.4783,
+ "step": 8751
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5301263711743384e-06,
+ "loss": 0.4638,
+ "step": 8752
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.528060304378749e-06,
+ "loss": 0.4599,
+ "step": 8753
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.525994712855494e-06,
+ "loss": 0.4589,
+ "step": 8754
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5239295967562603e-06,
+ "loss": 0.4726,
+ "step": 8755
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5218649562327e-06,
+ "loss": 0.492,
+ "step": 8756
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.519800791436434e-06,
+ "loss": 0.45,
+ "step": 8757
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.517737102519041e-06,
+ "loss": 0.4591,
+ "step": 8758
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5156738896320773e-06,
+ "loss": 0.4785,
+ "step": 8759
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.513611152927052e-06,
+ "loss": 0.4613,
+ "step": 8760
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5115488925554453e-06,
+ "loss": 0.46,
+ "step": 8761
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5094871086686997e-06,
+ "loss": 0.46,
+ "step": 8762
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.507425801418223e-06,
+ "loss": 0.4892,
+ "step": 8763
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5053649709553893e-06,
+ "loss": 0.4579,
+ "step": 8764
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5033046174315422e-06,
+ "loss": 0.4607,
+ "step": 8765
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.5012447409979832e-06,
+ "loss": 0.4775,
+ "step": 8766
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4991853418059798e-06,
+ "loss": 0.4502,
+ "step": 8767
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4971264200067657e-06,
+ "loss": 0.4841,
+ "step": 8768
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4950679757515395e-06,
+ "loss": 0.4704,
+ "step": 8769
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4930100091914655e-06,
+ "loss": 0.4668,
+ "step": 8770
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4909525204776684e-06,
+ "loss": 0.4685,
+ "step": 8771
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4888955097612487e-06,
+ "loss": 0.4771,
+ "step": 8772
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4868389771932608e-06,
+ "loss": 0.4739,
+ "step": 8773
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4847829229247243e-06,
+ "loss": 0.4764,
+ "step": 8774
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.482727347106636e-06,
+ "loss": 0.4639,
+ "step": 8775
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4806722498899424e-06,
+ "loss": 0.4862,
+ "step": 8776
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4786176314255626e-06,
+ "loss": 0.4599,
+ "step": 8777
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4765634918643778e-06,
+ "loss": 0.4675,
+ "step": 8778
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.474509831357239e-06,
+ "loss": 0.4556,
+ "step": 8779
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.472456650054957e-06,
+ "loss": 0.4535,
+ "step": 8780
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4704039481083086e-06,
+ "loss": 0.4802,
+ "step": 8781
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4683517256680365e-06,
+ "loss": 0.4857,
+ "step": 8782
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.466299982884842e-06,
+ "loss": 0.4661,
+ "step": 8783
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.4642487199094042e-06,
+ "loss": 0.4644,
+ "step": 8784
+ },
+ {
+ "epoch": 0.73,
+ "learning_rate": 3.462197936892354e-06,
+ "loss": 0.4719,
+ "step": 8785
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4601476339842976e-06,
+ "loss": 0.4574,
+ "step": 8786
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4580978113357967e-06,
+ "loss": 0.4828,
+ "step": 8787
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4560484690973838e-06,
+ "loss": 0.4778,
+ "step": 8788
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4539996074195526e-06,
+ "loss": 0.4658,
+ "step": 8789
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4519512264527633e-06,
+ "loss": 0.4703,
+ "step": 8790
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.44990332634744e-06,
+ "loss": 0.4833,
+ "step": 8791
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.447855907253971e-06,
+ "loss": 0.464,
+ "step": 8792
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4458089693227127e-06,
+ "loss": 0.4666,
+ "step": 8793
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.443762512703981e-06,
+ "loss": 0.4895,
+ "step": 8794
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4417165375480644e-06,
+ "loss": 0.4448,
+ "step": 8795
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.439671044005206e-06,
+ "loss": 0.4548,
+ "step": 8796
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4376260322256207e-06,
+ "loss": 0.4647,
+ "step": 8797
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.435581502359484e-06,
+ "loss": 0.4641,
+ "step": 8798
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4335374545569355e-06,
+ "loss": 0.4555,
+ "step": 8799
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.431493888968087e-06,
+ "loss": 0.4594,
+ "step": 8800
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4294508057430077e-06,
+ "loss": 0.4741,
+ "step": 8801
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4274082050317324e-06,
+ "loss": 0.4444,
+ "step": 8802
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.425366086984261e-06,
+ "loss": 0.4935,
+ "step": 8803
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4233244517505535e-06,
+ "loss": 0.4806,
+ "step": 8804
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4212832994805445e-06,
+ "loss": 0.4512,
+ "step": 8805
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.419242630324131e-06,
+ "loss": 0.4563,
+ "step": 8806
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.417202444431167e-06,
+ "loss": 0.4666,
+ "step": 8807
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4151627419514753e-06,
+ "loss": 0.4755,
+ "step": 8808
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4131235230348434e-06,
+ "loss": 0.4383,
+ "step": 8809
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.411084787831024e-06,
+ "loss": 0.4517,
+ "step": 8810
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4090465364897317e-06,
+ "loss": 0.4664,
+ "step": 8811
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4070087691606446e-06,
+ "loss": 0.4844,
+ "step": 8812
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4049714859934144e-06,
+ "loss": 0.4634,
+ "step": 8813
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4029346871376477e-06,
+ "loss": 0.4492,
+ "step": 8814
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.4008983727429147e-06,
+ "loss": 0.4665,
+ "step": 8815
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.398862542958761e-06,
+ "loss": 0.4744,
+ "step": 8816
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3968271979346857e-06,
+ "loss": 0.4571,
+ "step": 8817
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3947923378201576e-06,
+ "loss": 0.4543,
+ "step": 8818
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3927579627646024e-06,
+ "loss": 0.4386,
+ "step": 8819
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.390724072917424e-06,
+ "loss": 0.4878,
+ "step": 8820
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3886906684279806e-06,
+ "loss": 0.4807,
+ "step": 8821
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3866577494455953e-06,
+ "loss": 0.485,
+ "step": 8822
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3846253161195584e-06,
+ "loss": 0.46,
+ "step": 8823
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3825933685991184e-06,
+ "loss": 0.4907,
+ "step": 8824
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3805619070335026e-06,
+ "loss": 0.4913,
+ "step": 8825
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.378530931571884e-06,
+ "loss": 0.4608,
+ "step": 8826
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3765004423634164e-06,
+ "loss": 0.4769,
+ "step": 8827
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.374470439557207e-06,
+ "loss": 0.4694,
+ "step": 8828
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.37244092330233e-06,
+ "loss": 0.4434,
+ "step": 8829
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.370411893747827e-06,
+ "loss": 0.4433,
+ "step": 8830
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.368383351042699e-06,
+ "loss": 0.4656,
+ "step": 8831
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.366355295335915e-06,
+ "loss": 0.4648,
+ "step": 8832
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.364327726776403e-06,
+ "loss": 0.4587,
+ "step": 8833
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.362300645513067e-06,
+ "loss": 0.4806,
+ "step": 8834
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3602740516947595e-06,
+ "loss": 0.4774,
+ "step": 8835
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.358247945470313e-06,
+ "loss": 0.4611,
+ "step": 8836
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.356222326988512e-06,
+ "loss": 0.4639,
+ "step": 8837
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.354197196398109e-06,
+ "loss": 0.4685,
+ "step": 8838
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.352172553847819e-06,
+ "loss": 0.4648,
+ "step": 8839
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3501483994863293e-06,
+ "loss": 0.4667,
+ "step": 8840
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3481247334622822e-06,
+ "loss": 0.4724,
+ "step": 8841
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.346101555924288e-06,
+ "loss": 0.4687,
+ "step": 8842
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.34407886702092e-06,
+ "loss": 0.4531,
+ "step": 8843
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.342056666900716e-06,
+ "loss": 0.4567,
+ "step": 8844
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3400349557121748e-06,
+ "loss": 0.4598,
+ "step": 8845
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.338013733603768e-06,
+ "loss": 0.489,
+ "step": 8846
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3359930007239204e-06,
+ "loss": 0.4647,
+ "step": 8847
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3339727572210323e-06,
+ "loss": 0.4698,
+ "step": 8848
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3319530032434588e-06,
+ "loss": 0.4671,
+ "step": 8849
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3299337389395225e-06,
+ "loss": 0.4578,
+ "step": 8850
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.327914964457509e-06,
+ "loss": 0.4684,
+ "step": 8851
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3258966799456705e-06,
+ "loss": 0.4679,
+ "step": 8852
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3238788855522164e-06,
+ "loss": 0.4732,
+ "step": 8853
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3218615814253306e-06,
+ "loss": 0.471,
+ "step": 8854
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.319844767713155e-06,
+ "loss": 0.4485,
+ "step": 8855
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.317828444563792e-06,
+ "loss": 0.4604,
+ "step": 8856
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3158126121253178e-06,
+ "loss": 0.4795,
+ "step": 8857
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3137972705457632e-06,
+ "loss": 0.4728,
+ "step": 8858
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3117824199731274e-06,
+ "loss": 0.4833,
+ "step": 8859
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3097680605553697e-06,
+ "loss": 0.4926,
+ "step": 8860
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.307754192440421e-06,
+ "loss": 0.4609,
+ "step": 8861
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3057408157761696e-06,
+ "loss": 0.4956,
+ "step": 8862
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3037279307104685e-06,
+ "loss": 0.4779,
+ "step": 8863
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.3017155373911382e-06,
+ "loss": 0.4621,
+ "step": 8864
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.299703635965953e-06,
+ "loss": 0.4677,
+ "step": 8865
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2976922265826695e-06,
+ "loss": 0.4607,
+ "step": 8866
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.295681309388987e-06,
+ "loss": 0.4671,
+ "step": 8867
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2936708845325882e-06,
+ "loss": 0.4555,
+ "step": 8868
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2916609521611052e-06,
+ "loss": 0.4641,
+ "step": 8869
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2896515124221395e-06,
+ "loss": 0.4775,
+ "step": 8870
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.287642565463257e-06,
+ "loss": 0.4471,
+ "step": 8871
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2856341114319856e-06,
+ "loss": 0.467,
+ "step": 8872
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.283626150475818e-06,
+ "loss": 0.4799,
+ "step": 8873
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.281618682742207e-06,
+ "loss": 0.4601,
+ "step": 8874
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2796117083785793e-06,
+ "loss": 0.4666,
+ "step": 8875
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2776052275323155e-06,
+ "loss": 0.461,
+ "step": 8876
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2755992403507595e-06,
+ "loss": 0.4508,
+ "step": 8877
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2735937469812308e-06,
+ "loss": 0.4643,
+ "step": 8878
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2715887475709994e-06,
+ "loss": 0.4558,
+ "step": 8879
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.269584242267301e-06,
+ "loss": 0.4459,
+ "step": 8880
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2675802312173468e-06,
+ "loss": 0.4652,
+ "step": 8881
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.265576714568296e-06,
+ "loss": 0.4812,
+ "step": 8882
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.263573692467282e-06,
+ "loss": 0.4507,
+ "step": 8883
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2615711650613978e-06,
+ "loss": 0.4705,
+ "step": 8884
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2595691324976987e-06,
+ "loss": 0.4785,
+ "step": 8885
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2575675949232044e-06,
+ "loss": 0.4464,
+ "step": 8886
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2555665524849056e-06,
+ "loss": 0.4793,
+ "step": 8887
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2535660053297426e-06,
+ "loss": 0.467,
+ "step": 8888
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2515659536046362e-06,
+ "loss": 0.4741,
+ "step": 8889
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.249566397456456e-06,
+ "loss": 0.456,
+ "step": 8890
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2475673370320437e-06,
+ "loss": 0.4789,
+ "step": 8891
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2455687724781993e-06,
+ "loss": 0.4689,
+ "step": 8892
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.243570703941692e-06,
+ "loss": 0.4554,
+ "step": 8893
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2415731315692456e-06,
+ "loss": 0.4697,
+ "step": 8894
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2395760555075616e-06,
+ "loss": 0.4546,
+ "step": 8895
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.237579475903294e-06,
+ "loss": 0.4439,
+ "step": 8896
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.235583392903059e-06,
+ "loss": 0.4737,
+ "step": 8897
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2335878066534464e-06,
+ "loss": 0.4907,
+ "step": 8898
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.231592717301003e-06,
+ "loss": 0.4479,
+ "step": 8899
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.229598124992238e-06,
+ "loss": 0.4761,
+ "step": 8900
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2276040298736246e-06,
+ "loss": 0.4905,
+ "step": 8901
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.225610432091604e-06,
+ "loss": 0.4728,
+ "step": 8902
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.223617331792578e-06,
+ "loss": 0.4552,
+ "step": 8903
+ },
+ {
+ "epoch": 0.74,
+ "learning_rate": 3.2216247291229087e-06,
+ "loss": 0.4697,
+ "step": 8904
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2196326242289266e-06,
+ "loss": 0.4414,
+ "step": 8905
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.217641017256923e-06,
+ "loss": 0.4574,
+ "step": 8906
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.21564990835315e-06,
+ "loss": 0.4696,
+ "step": 8907
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2136592976638293e-06,
+ "loss": 0.4626,
+ "step": 8908
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2116691853351455e-06,
+ "loss": 0.448,
+ "step": 8909
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2096795715132436e-06,
+ "loss": 0.4561,
+ "step": 8910
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2076904563442303e-06,
+ "loss": 0.4295,
+ "step": 8911
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2057018399741777e-06,
+ "loss": 0.4665,
+ "step": 8912
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2037137225491233e-06,
+ "loss": 0.4557,
+ "step": 8913
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.2017261042150625e-06,
+ "loss": 0.4629,
+ "step": 8914
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.199738985117963e-06,
+ "loss": 0.455,
+ "step": 8915
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.197752365403748e-06,
+ "loss": 0.4552,
+ "step": 8916
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.195766245218307e-06,
+ "loss": 0.469,
+ "step": 8917
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1937806247074875e-06,
+ "loss": 0.4608,
+ "step": 8918
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1917955040171146e-06,
+ "loss": 0.4603,
+ "step": 8919
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.189810883292961e-06,
+ "loss": 0.4671,
+ "step": 8920
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.187826762680768e-06,
+ "loss": 0.4597,
+ "step": 8921
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.185843142326247e-06,
+ "loss": 0.4783,
+ "step": 8922
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1838600223750625e-06,
+ "loss": 0.4879,
+ "step": 8923
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.181877402972848e-06,
+ "loss": 0.452,
+ "step": 8924
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1798952842651985e-06,
+ "loss": 0.4763,
+ "step": 8925
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.177913666397673e-06,
+ "loss": 0.4543,
+ "step": 8926
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.175932549515789e-06,
+ "loss": 0.4596,
+ "step": 8927
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.173951933765038e-06,
+ "loss": 0.4473,
+ "step": 8928
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.171971819290862e-06,
+ "loss": 0.4753,
+ "step": 8929
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.169992206238679e-06,
+ "loss": 0.4606,
+ "step": 8930
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.16801309475386e-06,
+ "loss": 0.4574,
+ "step": 8931
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.166034484981744e-06,
+ "loss": 0.4675,
+ "step": 8932
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1640563770676305e-06,
+ "loss": 0.473,
+ "step": 8933
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1620787711567823e-06,
+ "loss": 0.4408,
+ "step": 8934
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1601016673944262e-06,
+ "loss": 0.4406,
+ "step": 8935
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.158125065925758e-06,
+ "loss": 0.4783,
+ "step": 8936
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1561489668959268e-06,
+ "loss": 0.4705,
+ "step": 8937
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1541733704500464e-06,
+ "loss": 0.4587,
+ "step": 8938
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1521982767332038e-06,
+ "loss": 0.4524,
+ "step": 8939
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.150223685890437e-06,
+ "loss": 0.4647,
+ "step": 8940
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1482495980667516e-06,
+ "loss": 0.4681,
+ "step": 8941
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1462760134071145e-06,
+ "loss": 0.4533,
+ "step": 8942
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1443029320564642e-06,
+ "loss": 0.4697,
+ "step": 8943
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1423303541596904e-06,
+ "loss": 0.4745,
+ "step": 8944
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1403582798616527e-06,
+ "loss": 0.4818,
+ "step": 8945
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1383867093071717e-06,
+ "loss": 0.4557,
+ "step": 8946
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1364156426410307e-06,
+ "loss": 0.4594,
+ "step": 8947
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1344450800079753e-06,
+ "loss": 0.4624,
+ "step": 8948
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1324750215527157e-06,
+ "loss": 0.4538,
+ "step": 8949
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1305054674199297e-06,
+ "loss": 0.4745,
+ "step": 8950
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.12853641775425e-06,
+ "loss": 0.4548,
+ "step": 8951
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1265678727002758e-06,
+ "loss": 0.4664,
+ "step": 8952
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.124599832402567e-06,
+ "loss": 0.459,
+ "step": 8953
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.122632297005651e-06,
+ "loss": 0.4514,
+ "step": 8954
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1206652666540107e-06,
+ "loss": 0.5009,
+ "step": 8955
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1186987414921023e-06,
+ "loss": 0.451,
+ "step": 8956
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1167327216643374e-06,
+ "loss": 0.4915,
+ "step": 8957
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1147672073150916e-06,
+ "loss": 0.4549,
+ "step": 8958
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1128021985887004e-06,
+ "loss": 0.4543,
+ "step": 8959
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.110837695629473e-06,
+ "loss": 0.4726,
+ "step": 8960
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1088736985816716e-06,
+ "loss": 0.4673,
+ "step": 8961
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1069102075895207e-06,
+ "loss": 0.4575,
+ "step": 8962
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1049472227972157e-06,
+ "loss": 0.4507,
+ "step": 8963
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1029847443489093e-06,
+ "loss": 0.4733,
+ "step": 8964
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.1010227723887153e-06,
+ "loss": 0.4522,
+ "step": 8965
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0990613070607145e-06,
+ "loss": 0.4629,
+ "step": 8966
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0971003485089477e-06,
+ "loss": 0.4818,
+ "step": 8967
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.095139896877417e-06,
+ "loss": 0.4479,
+ "step": 8968
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.093179952310096e-06,
+ "loss": 0.4705,
+ "step": 8969
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.091220514950908e-06,
+ "loss": 0.4932,
+ "step": 8970
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0892615849437533e-06,
+ "loss": 0.4519,
+ "step": 8971
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0873031624324835e-06,
+ "loss": 0.4589,
+ "step": 8972
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.085345247560918e-06,
+ "loss": 0.4546,
+ "step": 8973
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0833878404728366e-06,
+ "loss": 0.4622,
+ "step": 8974
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.081430941311985e-06,
+ "loss": 0.4992,
+ "step": 8975
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0794745502220646e-06,
+ "loss": 0.4815,
+ "step": 8976
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.077518667346752e-06,
+ "loss": 0.4669,
+ "step": 8977
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.075563292829675e-06,
+ "loss": 0.4699,
+ "step": 8978
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0736084268144264e-06,
+ "loss": 0.4627,
+ "step": 8979
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0716540694445694e-06,
+ "loss": 0.4654,
+ "step": 8980
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0697002208636195e-06,
+ "loss": 0.4628,
+ "step": 8981
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0677468812150612e-06,
+ "loss": 0.4558,
+ "step": 8982
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0657940506423345e-06,
+ "loss": 0.4844,
+ "step": 8983
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0638417292888546e-06,
+ "loss": 0.4778,
+ "step": 8984
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0618899172979875e-06,
+ "loss": 0.4671,
+ "step": 8985
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0599386148130684e-06,
+ "loss": 0.4511,
+ "step": 8986
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0579878219773917e-06,
+ "loss": 0.4486,
+ "step": 8987
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0560375389342147e-06,
+ "loss": 0.4686,
+ "step": 8988
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0540877658267555e-06,
+ "loss": 0.4589,
+ "step": 8989
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0521385027982033e-06,
+ "loss": 0.4522,
+ "step": 8990
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.050189749991699e-06,
+ "loss": 0.4682,
+ "step": 8991
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0482415075503556e-06,
+ "loss": 0.4816,
+ "step": 8992
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0462937756172417e-06,
+ "loss": 0.4533,
+ "step": 8993
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0443465543353902e-06,
+ "loss": 0.4747,
+ "step": 8994
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0423998438477964e-06,
+ "loss": 0.4747,
+ "step": 8995
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0404536442974165e-06,
+ "loss": 0.4568,
+ "step": 8996
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0385079558271768e-06,
+ "loss": 0.4665,
+ "step": 8997
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.036562778579959e-06,
+ "loss": 0.4617,
+ "step": 8998
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0346181126986063e-06,
+ "loss": 0.4713,
+ "step": 8999
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0326739583259255e-06,
+ "loss": 0.4868,
+ "step": 9000
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.030730315604693e-06,
+ "loss": 0.4813,
+ "step": 9001
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0287871846776397e-06,
+ "loss": 0.4769,
+ "step": 9002
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0268445656874555e-06,
+ "loss": 0.4529,
+ "step": 9003
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0249024587768074e-06,
+ "loss": 0.4653,
+ "step": 9004
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.02296086408831e-06,
+ "loss": 0.4987,
+ "step": 9005
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0210197817645472e-06,
+ "loss": 0.445,
+ "step": 9006
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0190792119480638e-06,
+ "loss": 0.4692,
+ "step": 9007
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.017139154781368e-06,
+ "loss": 0.4617,
+ "step": 9008
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.015199610406925e-06,
+ "loss": 0.4727,
+ "step": 9009
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0132605789671744e-06,
+ "loss": 0.4471,
+ "step": 9010
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0113220606045035e-06,
+ "loss": 0.4654,
+ "step": 9011
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0093840554612753e-06,
+ "loss": 0.4895,
+ "step": 9012
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0074465636798056e-06,
+ "loss": 0.4657,
+ "step": 9013
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0055095854023764e-06,
+ "loss": 0.483,
+ "step": 9014
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.0035731207712305e-06,
+ "loss": 0.4526,
+ "step": 9015
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 3.001637169928575e-06,
+ "loss": 0.4655,
+ "step": 9016
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9997017330165736e-06,
+ "loss": 0.4689,
+ "step": 9017
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9977668101773636e-06,
+ "loss": 0.4669,
+ "step": 9018
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.995832401553035e-06,
+ "loss": 0.4726,
+ "step": 9019
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.993898507285643e-06,
+ "loss": 0.4629,
+ "step": 9020
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9919651275172e-06,
+ "loss": 0.4591,
+ "step": 9021
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.990032262389693e-06,
+ "loss": 0.4758,
+ "step": 9022
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9880999120450595e-06,
+ "loss": 0.4545,
+ "step": 9023
+ },
+ {
+ "epoch": 0.75,
+ "learning_rate": 2.9861680766252e-06,
+ "loss": 0.4509,
+ "step": 9024
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9842367562719887e-06,
+ "loss": 0.4604,
+ "step": 9025
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.982305951127249e-06,
+ "loss": 0.46,
+ "step": 9026
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9803756613327704e-06,
+ "loss": 0.4715,
+ "step": 9027
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.978445887030308e-06,
+ "loss": 0.4413,
+ "step": 9028
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.976516628361574e-06,
+ "loss": 0.4943,
+ "step": 9029
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.974587885468243e-06,
+ "loss": 0.4575,
+ "step": 9030
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9726596584919596e-06,
+ "loss": 0.4496,
+ "step": 9031
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.970731947574319e-06,
+ "loss": 0.4542,
+ "step": 9032
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.968804752856891e-06,
+ "loss": 0.4855,
+ "step": 9033
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9668780744811967e-06,
+ "loss": 0.4437,
+ "step": 9034
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9649519125887227e-06,
+ "loss": 0.4699,
+ "step": 9035
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.96302626732092e-06,
+ "loss": 0.4794,
+ "step": 9036
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9611011388191956e-06,
+ "loss": 0.4607,
+ "step": 9037
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9591765272249305e-06,
+ "loss": 0.472,
+ "step": 9038
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9572524326794562e-06,
+ "loss": 0.4636,
+ "step": 9039
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9553288553240698e-06,
+ "loss": 0.4749,
+ "step": 9040
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9534057953000283e-06,
+ "loss": 0.4753,
+ "step": 9041
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9514832527485593e-06,
+ "loss": 0.4424,
+ "step": 9042
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.949561227810843e-06,
+ "loss": 0.4706,
+ "step": 9043
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.947639720628023e-06,
+ "loss": 0.4448,
+ "step": 9044
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.945718731341212e-06,
+ "loss": 0.4846,
+ "step": 9045
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.943798260091475e-06,
+ "loss": 0.4563,
+ "step": 9046
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9418783070198455e-06,
+ "loss": 0.4693,
+ "step": 9047
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9399588722673165e-06,
+ "loss": 0.4424,
+ "step": 9048
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.938039955974843e-06,
+ "loss": 0.4605,
+ "step": 9049
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9361215582833425e-06,
+ "loss": 0.474,
+ "step": 9050
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9342036793336904e-06,
+ "loss": 0.4644,
+ "step": 9051
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9322863192667306e-06,
+ "loss": 0.4739,
+ "step": 9052
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9303694782232706e-06,
+ "loss": 0.451,
+ "step": 9053
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.928453156344071e-06,
+ "loss": 0.4632,
+ "step": 9054
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9265373537698595e-06,
+ "loss": 0.4599,
+ "step": 9055
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.924622070641323e-06,
+ "loss": 0.4581,
+ "step": 9056
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.922707307099113e-06,
+ "loss": 0.4745,
+ "step": 9057
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.920793063283839e-06,
+ "loss": 0.4713,
+ "step": 9058
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9188793393360813e-06,
+ "loss": 0.4605,
+ "step": 9059
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.916966135396372e-06,
+ "loss": 0.4687,
+ "step": 9060
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9150534516052085e-06,
+ "loss": 0.4748,
+ "step": 9061
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9131412881030487e-06,
+ "loss": 0.454,
+ "step": 9062
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.911229645030319e-06,
+ "loss": 0.4901,
+ "step": 9063
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.909318522527397e-06,
+ "loss": 0.4588,
+ "step": 9064
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9074079207346328e-06,
+ "loss": 0.4642,
+ "step": 9065
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.9054978397923306e-06,
+ "loss": 0.4733,
+ "step": 9066
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.903588279840759e-06,
+ "loss": 0.4799,
+ "step": 9067
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.901679241020149e-06,
+ "loss": 0.472,
+ "step": 9068
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8997707234706894e-06,
+ "loss": 0.4813,
+ "step": 9069
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8978627273325378e-06,
+ "loss": 0.4612,
+ "step": 9070
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8959552527458025e-06,
+ "loss": 0.4695,
+ "step": 9071
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8940482998505703e-06,
+ "loss": 0.4619,
+ "step": 9072
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.892141868786871e-06,
+ "loss": 0.452,
+ "step": 9073
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8902359596947127e-06,
+ "loss": 0.4722,
+ "step": 9074
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8883305727140533e-06,
+ "loss": 0.442,
+ "step": 9075
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8864257079848166e-06,
+ "loss": 0.4708,
+ "step": 9076
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8845213656468896e-06,
+ "loss": 0.4646,
+ "step": 9077
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.882617545840114e-06,
+ "loss": 0.4648,
+ "step": 9078
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8807142487043047e-06,
+ "loss": 0.4804,
+ "step": 9079
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8788114743792317e-06,
+ "loss": 0.46,
+ "step": 9080
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8769092230046236e-06,
+ "loss": 0.455,
+ "step": 9081
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.875007494720171e-06,
+ "loss": 0.4514,
+ "step": 9082
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8731062896655383e-06,
+ "loss": 0.4745,
+ "step": 9083
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.871205607980335e-06,
+ "loss": 0.4647,
+ "step": 9084
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8693054498041383e-06,
+ "loss": 0.4675,
+ "step": 9085
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.867405815276494e-06,
+ "loss": 0.4572,
+ "step": 9086
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.865506704536899e-06,
+ "loss": 0.4301,
+ "step": 9087
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8636081177248176e-06,
+ "loss": 0.4656,
+ "step": 9088
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.861710054979674e-06,
+ "loss": 0.4682,
+ "step": 9089
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.859812516440853e-06,
+ "loss": 0.4671,
+ "step": 9090
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8579155022477024e-06,
+ "loss": 0.4713,
+ "step": 9091
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.856019012539528e-06,
+ "loss": 0.4732,
+ "step": 9092
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8541230474556035e-06,
+ "loss": 0.4658,
+ "step": 9093
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.852227607135164e-06,
+ "loss": 0.4677,
+ "step": 9094
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.850332691717399e-06,
+ "loss": 0.4676,
+ "step": 9095
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8484383013414627e-06,
+ "loss": 0.4892,
+ "step": 9096
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.846544436146473e-06,
+ "loss": 0.4541,
+ "step": 9097
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8446510962715055e-06,
+ "loss": 0.464,
+ "step": 9098
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8427582818555976e-06,
+ "loss": 0.4755,
+ "step": 9099
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8408659930377556e-06,
+ "loss": 0.4582,
+ "step": 9100
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.838974229956938e-06,
+ "loss": 0.4648,
+ "step": 9101
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.837082992752067e-06,
+ "loss": 0.4542,
+ "step": 9102
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.835192281562027e-06,
+ "loss": 0.4401,
+ "step": 9103
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8333020965256666e-06,
+ "loss": 0.4844,
+ "step": 9104
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8314124377817888e-06,
+ "loss": 0.4815,
+ "step": 9105
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8295233054691685e-06,
+ "loss": 0.479,
+ "step": 9106
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8276346997265324e-06,
+ "loss": 0.4473,
+ "step": 9107
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8257466206925723e-06,
+ "loss": 0.4676,
+ "step": 9108
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.82385906850594e-06,
+ "loss": 0.4612,
+ "step": 9109
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.82197204330525e-06,
+ "loss": 0.4752,
+ "step": 9110
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.820085545229078e-06,
+ "loss": 0.4496,
+ "step": 9111
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8181995744159553e-06,
+ "loss": 0.4537,
+ "step": 9112
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8163141310043886e-06,
+ "loss": 0.4666,
+ "step": 9113
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.81442921513283e-06,
+ "loss": 0.4734,
+ "step": 9114
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.812544826939706e-06,
+ "loss": 0.4739,
+ "step": 9115
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8106609665633943e-06,
+ "loss": 0.4542,
+ "step": 9116
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.808777634142239e-06,
+ "loss": 0.4808,
+ "step": 9117
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8068948298145437e-06,
+ "loss": 0.4737,
+ "step": 9118
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.80501255371857e-06,
+ "loss": 0.453,
+ "step": 9119
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.803130805992552e-06,
+ "loss": 0.4852,
+ "step": 9120
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.8012495867746735e-06,
+ "loss": 0.4509,
+ "step": 9121
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.799368896203084e-06,
+ "loss": 0.447,
+ "step": 9122
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7974887344158897e-06,
+ "loss": 0.4753,
+ "step": 9123
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7956091015511676e-06,
+ "loss": 0.4621,
+ "step": 9124
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.793729997746948e-06,
+ "loss": 0.4722,
+ "step": 9125
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.791851423141222e-06,
+ "loss": 0.4903,
+ "step": 9126
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7899733778719483e-06,
+ "loss": 0.4797,
+ "step": 9127
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7880958620770415e-06,
+ "loss": 0.4619,
+ "step": 9128
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7862188758943788e-06,
+ "loss": 0.4626,
+ "step": 9129
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7843424194617964e-06,
+ "loss": 0.4839,
+ "step": 9130
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7824664929170953e-06,
+ "loss": 0.4832,
+ "step": 9131
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7805910963980343e-06,
+ "loss": 0.5038,
+ "step": 9132
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.778716230042333e-06,
+ "loss": 0.4822,
+ "step": 9133
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7768418939876794e-06,
+ "loss": 0.4542,
+ "step": 9134
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7749680883717102e-06,
+ "loss": 0.4602,
+ "step": 9135
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.773094813332037e-06,
+ "loss": 0.4747,
+ "step": 9136
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7712220690062208e-06,
+ "loss": 0.4595,
+ "step": 9137
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.769349855531789e-06,
+ "loss": 0.4627,
+ "step": 9138
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7674781730462273e-06,
+ "loss": 0.4563,
+ "step": 9139
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.765607021686989e-06,
+ "loss": 0.4852,
+ "step": 9140
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7637364015914803e-06,
+ "loss": 0.4463,
+ "step": 9141
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.7618663128970722e-06,
+ "loss": 0.4673,
+ "step": 9142
+ },
+ {
+ "epoch": 0.76,
+ "learning_rate": 2.759996755741098e-06,
+ "loss": 0.446,
+ "step": 9143
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7581277302608446e-06,
+ "loss": 0.4693,
+ "step": 9144
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7562592365935724e-06,
+ "loss": 0.4751,
+ "step": 9145
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.75439127487649e-06,
+ "loss": 0.4539,
+ "step": 9146
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7525238452467783e-06,
+ "loss": 0.4628,
+ "step": 9147
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7506569478415713e-06,
+ "loss": 0.4756,
+ "step": 9148
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7487905827979654e-06,
+ "loss": 0.4652,
+ "step": 9149
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7469247502530194e-06,
+ "loss": 0.4361,
+ "step": 9150
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.745059450343752e-06,
+ "loss": 0.4724,
+ "step": 9151
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7431946832071433e-06,
+ "loss": 0.4707,
+ "step": 9152
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7413304489801296e-06,
+ "loss": 0.4704,
+ "step": 9153
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7394667477996207e-06,
+ "loss": 0.4542,
+ "step": 9154
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.737603579802471e-06,
+ "loss": 0.4505,
+ "step": 9155
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7357409451255113e-06,
+ "loss": 0.458,
+ "step": 9156
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.733878843905523e-06,
+ "loss": 0.4673,
+ "step": 9157
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7320172762792497e-06,
+ "loss": 0.4914,
+ "step": 9158
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7301562423833985e-06,
+ "loss": 0.4658,
+ "step": 9159
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.728295742354631e-06,
+ "loss": 0.449,
+ "step": 9160
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7264357763295822e-06,
+ "loss": 0.4757,
+ "step": 9161
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7245763444448383e-06,
+ "loss": 0.4689,
+ "step": 9162
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7227174468369454e-06,
+ "loss": 0.4551,
+ "step": 9163
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.720859083642415e-06,
+ "loss": 0.4712,
+ "step": 9164
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7190012549977153e-06,
+ "loss": 0.4821,
+ "step": 9165
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7171439610392815e-06,
+ "loss": 0.4558,
+ "step": 9166
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7152872019035005e-06,
+ "loss": 0.4696,
+ "step": 9167
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7134309777267307e-06,
+ "loss": 0.4633,
+ "step": 9168
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.711575288645284e-06,
+ "loss": 0.4628,
+ "step": 9169
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7097201347954318e-06,
+ "loss": 0.466,
+ "step": 9170
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7078655163134117e-06,
+ "loss": 0.4747,
+ "step": 9171
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.706011433335417e-06,
+ "loss": 0.4617,
+ "step": 9172
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.704157885997605e-06,
+ "loss": 0.4672,
+ "step": 9173
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.702304874436089e-06,
+ "loss": 0.453,
+ "step": 9174
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.7004523987869526e-06,
+ "loss": 0.4688,
+ "step": 9175
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.698600459186228e-06,
+ "loss": 0.4595,
+ "step": 9176
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6967490557699196e-06,
+ "loss": 0.4421,
+ "step": 9177
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6948981886739846e-06,
+ "loss": 0.4677,
+ "step": 9178
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.693047858034342e-06,
+ "loss": 0.4797,
+ "step": 9179
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6911980639868696e-06,
+ "loss": 0.4518,
+ "step": 9180
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6893488066674154e-06,
+ "loss": 0.4681,
+ "step": 9181
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.687500086211777e-06,
+ "loss": 0.4684,
+ "step": 9182
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.685651902755717e-06,
+ "loss": 0.465,
+ "step": 9183
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6838042564349597e-06,
+ "loss": 0.4633,
+ "step": 9184
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6819571473851836e-06,
+ "loss": 0.4565,
+ "step": 9185
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6801105757420397e-06,
+ "loss": 0.4577,
+ "step": 9186
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6782645416411267e-06,
+ "loss": 0.4726,
+ "step": 9187
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.676419045218016e-06,
+ "loss": 0.4555,
+ "step": 9188
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.674574086608228e-06,
+ "loss": 0.4847,
+ "step": 9189
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.672729665947251e-06,
+ "loss": 0.4464,
+ "step": 9190
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6708857833705315e-06,
+ "loss": 0.4601,
+ "step": 9191
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.669042439013476e-06,
+ "loss": 0.4795,
+ "step": 9192
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6671996330114514e-06,
+ "loss": 0.4571,
+ "step": 9193
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6653573654997835e-06,
+ "loss": 0.4686,
+ "step": 9194
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6635156366137672e-06,
+ "loss": 0.4599,
+ "step": 9195
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6616744464886437e-06,
+ "loss": 0.4802,
+ "step": 9196
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.65983379525963e-06,
+ "loss": 0.4669,
+ "step": 9197
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6579936830618926e-06,
+ "loss": 0.4458,
+ "step": 9198
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.656154110030561e-06,
+ "loss": 0.466,
+ "step": 9199
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6543150763007265e-06,
+ "loss": 0.4608,
+ "step": 9200
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.652476582007436e-06,
+ "loss": 0.4676,
+ "step": 9201
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6506386272857086e-06,
+ "loss": 0.4696,
+ "step": 9202
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.648801212270512e-06,
+ "loss": 0.463,
+ "step": 9203
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.646964337096778e-06,
+ "loss": 0.4484,
+ "step": 9204
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6451280018993996e-06,
+ "loss": 0.4569,
+ "step": 9205
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.643292206813227e-06,
+ "loss": 0.4825,
+ "step": 9206
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6414569519730793e-06,
+ "loss": 0.4526,
+ "step": 9207
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6396222375137227e-06,
+ "loss": 0.4555,
+ "step": 9208
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6377880635698973e-06,
+ "loss": 0.4824,
+ "step": 9209
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.635954430276296e-06,
+ "loss": 0.4683,
+ "step": 9210
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.634121337767571e-06,
+ "loss": 0.4648,
+ "step": 9211
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6322887861783385e-06,
+ "loss": 0.4767,
+ "step": 9212
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.630456775643173e-06,
+ "loss": 0.4557,
+ "step": 9213
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6286253062966096e-06,
+ "loss": 0.4721,
+ "step": 9214
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6267943782731407e-06,
+ "loss": 0.4695,
+ "step": 9215
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.624963991707228e-06,
+ "loss": 0.4559,
+ "step": 9216
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6231341467332827e-06,
+ "loss": 0.477,
+ "step": 9217
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6213048434856846e-06,
+ "loss": 0.4626,
+ "step": 9218
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.61947608209877e-06,
+ "loss": 0.4592,
+ "step": 9219
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6176478627068324e-06,
+ "loss": 0.5004,
+ "step": 9220
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.615820185444128e-06,
+ "loss": 0.488,
+ "step": 9221
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6139930504448785e-06,
+ "loss": 0.4704,
+ "step": 9222
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6121664578432593e-06,
+ "loss": 0.4755,
+ "step": 9223
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6103404077734075e-06,
+ "loss": 0.4581,
+ "step": 9224
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.60851490036942e-06,
+ "loss": 0.4553,
+ "step": 9225
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.606689935765351e-06,
+ "loss": 0.4777,
+ "step": 9226
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.604865514095225e-06,
+ "loss": 0.4676,
+ "step": 9227
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6030416354930154e-06,
+ "loss": 0.4463,
+ "step": 9228
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.6012183000926638e-06,
+ "loss": 0.4546,
+ "step": 9229
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5993955080280663e-06,
+ "loss": 0.483,
+ "step": 9230
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5975732594330816e-06,
+ "loss": 0.4715,
+ "step": 9231
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.595751554441527e-06,
+ "loss": 0.4556,
+ "step": 9232
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5939303931871827e-06,
+ "loss": 0.4788,
+ "step": 9233
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.592109775803785e-06,
+ "loss": 0.4724,
+ "step": 9234
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.590289702425032e-06,
+ "loss": 0.4611,
+ "step": 9235
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5884701731845862e-06,
+ "loss": 0.4714,
+ "step": 9236
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5866511882160604e-06,
+ "loss": 0.4642,
+ "step": 9237
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.584832747653041e-06,
+ "loss": 0.4718,
+ "step": 9238
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.583014851629062e-06,
+ "loss": 0.4696,
+ "step": 9239
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5811975002776233e-06,
+ "loss": 0.4488,
+ "step": 9240
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.579380693732183e-06,
+ "loss": 0.4678,
+ "step": 9241
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.577564432126156e-06,
+ "loss": 0.4598,
+ "step": 9242
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5757487155929285e-06,
+ "loss": 0.482,
+ "step": 9243
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.573933544265835e-06,
+ "loss": 0.4572,
+ "step": 9244
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.572118918278176e-06,
+ "loss": 0.4634,
+ "step": 9245
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.570304837763208e-06,
+ "loss": 0.4784,
+ "step": 9246
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.568491302854147e-06,
+ "loss": 0.458,
+ "step": 9247
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5666783136841777e-06,
+ "loss": 0.4777,
+ "step": 9248
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.564865870386433e-06,
+ "loss": 0.4558,
+ "step": 9249
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5630539730940163e-06,
+ "loss": 0.4666,
+ "step": 9250
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5612426219399834e-06,
+ "loss": 0.4487,
+ "step": 9251
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5594318170573527e-06,
+ "loss": 0.4581,
+ "step": 9252
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5576215585791007e-06,
+ "loss": 0.4659,
+ "step": 9253
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5558118466381675e-06,
+ "loss": 0.4502,
+ "step": 9254
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5540026813674458e-06,
+ "loss": 0.4941,
+ "step": 9255
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5521940628998e-06,
+ "loss": 0.4728,
+ "step": 9256
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.550385991368044e-06,
+ "loss": 0.4579,
+ "step": 9257
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.548578466904953e-06,
+ "loss": 0.4819,
+ "step": 9258
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5467714896432704e-06,
+ "loss": 0.4623,
+ "step": 9259
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5449650597156884e-06,
+ "loss": 0.4512,
+ "step": 9260
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5431591772548647e-06,
+ "loss": 0.469,
+ "step": 9261
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5413538423934125e-06,
+ "loss": 0.4628,
+ "step": 9262
+ },
+ {
+ "epoch": 0.77,
+ "learning_rate": 2.5395490552639145e-06,
+ "loss": 0.4641,
+ "step": 9263
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5377448159989037e-06,
+ "loss": 0.458,
+ "step": 9264
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5359411247308753e-06,
+ "loss": 0.4823,
+ "step": 9265
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5341379815922853e-06,
+ "loss": 0.467,
+ "step": 9266
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5323353867155465e-06,
+ "loss": 0.4686,
+ "step": 9267
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.53053334023304e-06,
+ "loss": 0.4559,
+ "step": 9268
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5287318422770934e-06,
+ "loss": 0.4608,
+ "step": 9269
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5269308929800084e-06,
+ "loss": 0.4619,
+ "step": 9270
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.525130492474035e-06,
+ "loss": 0.4805,
+ "step": 9271
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.523330640891388e-06,
+ "loss": 0.4584,
+ "step": 9272
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5215313383642414e-06,
+ "loss": 0.4771,
+ "step": 9273
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.519732585024729e-06,
+ "loss": 0.4555,
+ "step": 9274
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5179343810049418e-06,
+ "loss": 0.466,
+ "step": 9275
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5161367264369296e-06,
+ "loss": 0.4694,
+ "step": 9276
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5143396214527127e-06,
+ "loss": 0.4603,
+ "step": 9277
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5125430661842587e-06,
+ "loss": 0.4644,
+ "step": 9278
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5107470607634956e-06,
+ "loss": 0.4647,
+ "step": 9279
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5089516053223216e-06,
+ "loss": 0.4704,
+ "step": 9280
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5071566999925833e-06,
+ "loss": 0.4869,
+ "step": 9281
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5053623449060927e-06,
+ "loss": 0.4826,
+ "step": 9282
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5035685401946163e-06,
+ "loss": 0.4694,
+ "step": 9283
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.5017752859898892e-06,
+ "loss": 0.4598,
+ "step": 9284
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.499982582423597e-06,
+ "loss": 0.4522,
+ "step": 9285
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4981904296273884e-06,
+ "loss": 0.4609,
+ "step": 9286
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4963988277328733e-06,
+ "loss": 0.4702,
+ "step": 9287
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.494607776871616e-06,
+ "loss": 0.4667,
+ "step": 9288
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.492817277175148e-06,
+ "loss": 0.4737,
+ "step": 9289
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.491027328774952e-06,
+ "loss": 0.4664,
+ "step": 9290
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4892379318024806e-06,
+ "loss": 0.4345,
+ "step": 9291
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4874490863891355e-06,
+ "loss": 0.4877,
+ "step": 9292
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.485660792666281e-06,
+ "loss": 0.4726,
+ "step": 9293
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4838730507652455e-06,
+ "loss": 0.4508,
+ "step": 9294
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.482085860817309e-06,
+ "loss": 0.4623,
+ "step": 9295
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.480299222953716e-06,
+ "loss": 0.4561,
+ "step": 9296
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.478513137305675e-06,
+ "loss": 0.4565,
+ "step": 9297
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4767276040043433e-06,
+ "loss": 0.4553,
+ "step": 9298
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4749426231808427e-06,
+ "loss": 0.4781,
+ "step": 9299
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4731581949662597e-06,
+ "loss": 0.4629,
+ "step": 9300
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4713743194916318e-06,
+ "loss": 0.4546,
+ "step": 9301
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4695909968879607e-06,
+ "loss": 0.466,
+ "step": 9302
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4678082272862025e-06,
+ "loss": 0.4552,
+ "step": 9303
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4660260108172816e-06,
+ "loss": 0.4513,
+ "step": 9304
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4642443476120746e-06,
+ "loss": 0.4539,
+ "step": 9305
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.462463237801419e-06,
+ "loss": 0.4682,
+ "step": 9306
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.460682681516112e-06,
+ "loss": 0.453,
+ "step": 9307
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4589026788869117e-06,
+ "loss": 0.4768,
+ "step": 9308
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4571232300445293e-06,
+ "loss": 0.4839,
+ "step": 9309
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4553443351196426e-06,
+ "loss": 0.4596,
+ "step": 9310
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.453565994242891e-06,
+ "loss": 0.4595,
+ "step": 9311
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4517882075448663e-06,
+ "loss": 0.4475,
+ "step": 9312
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4500109751561187e-06,
+ "loss": 0.4539,
+ "step": 9313
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4482342972071626e-06,
+ "loss": 0.4622,
+ "step": 9314
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.44645817382847e-06,
+ "loss": 0.4861,
+ "step": 9315
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.444682605150471e-06,
+ "loss": 0.4707,
+ "step": 9316
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.442907591303554e-06,
+ "loss": 0.479,
+ "step": 9317
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.441133132418073e-06,
+ "loss": 0.4697,
+ "step": 9318
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4393592286243363e-06,
+ "loss": 0.4657,
+ "step": 9319
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4375858800526077e-06,
+ "loss": 0.4666,
+ "step": 9320
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.43581308683312e-06,
+ "loss": 0.4637,
+ "step": 9321
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4340408490960575e-06,
+ "loss": 0.4706,
+ "step": 9322
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.432269166971567e-06,
+ "loss": 0.4753,
+ "step": 9323
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4304980405897483e-06,
+ "loss": 0.4751,
+ "step": 9324
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4287274700806727e-06,
+ "loss": 0.4541,
+ "step": 9325
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.42695745557436e-06,
+ "loss": 0.4487,
+ "step": 9326
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4251879972007943e-06,
+ "loss": 0.4575,
+ "step": 9327
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.423419095089915e-06,
+ "loss": 0.4677,
+ "step": 9328
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4216507493716213e-06,
+ "loss": 0.4627,
+ "step": 9329
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4198829601757787e-06,
+ "loss": 0.4684,
+ "step": 9330
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.418115727632201e-06,
+ "loss": 0.4892,
+ "step": 9331
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4163490518706713e-06,
+ "loss": 0.4636,
+ "step": 9332
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.414582933020924e-06,
+ "loss": 0.459,
+ "step": 9333
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.412817371212657e-06,
+ "loss": 0.4632,
+ "step": 9334
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4110523665755236e-06,
+ "loss": 0.4559,
+ "step": 9335
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4092879192391406e-06,
+ "loss": 0.4697,
+ "step": 9336
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.407524029333077e-06,
+ "loss": 0.4719,
+ "step": 9337
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.405760696986873e-06,
+ "loss": 0.4609,
+ "step": 9338
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.403997922330016e-06,
+ "loss": 0.4663,
+ "step": 9339
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4022357054919545e-06,
+ "loss": 0.4537,
+ "step": 9340
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.4004740466021047e-06,
+ "loss": 0.4711,
+ "step": 9341
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.398712945789832e-06,
+ "loss": 0.4591,
+ "step": 9342
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3969524031844638e-06,
+ "loss": 0.4759,
+ "step": 9343
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3951924189152854e-06,
+ "loss": 0.4557,
+ "step": 9344
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3934329931115474e-06,
+ "loss": 0.4759,
+ "step": 9345
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.391674125902452e-06,
+ "loss": 0.4565,
+ "step": 9346
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3899158174171644e-06,
+ "loss": 0.4823,
+ "step": 9347
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.388158067784806e-06,
+ "loss": 0.4724,
+ "step": 9348
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3864008771344595e-06,
+ "loss": 0.4682,
+ "step": 9349
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3846442455951612e-06,
+ "loss": 0.4776,
+ "step": 9350
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3828881732959163e-06,
+ "loss": 0.4587,
+ "step": 9351
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.381132660365684e-06,
+ "loss": 0.4814,
+ "step": 9352
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.37937770693338e-06,
+ "loss": 0.4737,
+ "step": 9353
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3776233131278805e-06,
+ "loss": 0.447,
+ "step": 9354
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3758694790780214e-06,
+ "loss": 0.4658,
+ "step": 9355
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3741162049125964e-06,
+ "loss": 0.4719,
+ "step": 9356
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.372363490760359e-06,
+ "loss": 0.4448,
+ "step": 9357
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3706113367500183e-06,
+ "loss": 0.4582,
+ "step": 9358
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.36885974301025e-06,
+ "loss": 0.4683,
+ "step": 9359
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.367108709669683e-06,
+ "loss": 0.4571,
+ "step": 9360
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3653582368569017e-06,
+ "loss": 0.4503,
+ "step": 9361
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3636083247004592e-06,
+ "loss": 0.4537,
+ "step": 9362
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3618589733288588e-06,
+ "loss": 0.4668,
+ "step": 9363
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3601101828705664e-06,
+ "loss": 0.4526,
+ "step": 9364
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.358361953454004e-06,
+ "loss": 0.478,
+ "step": 9365
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.356614285207557e-06,
+ "loss": 0.4649,
+ "step": 9366
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3548671782595655e-06,
+ "loss": 0.4418,
+ "step": 9367
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3531206327383305e-06,
+ "loss": 0.4629,
+ "step": 9368
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.35137464877211e-06,
+ "loss": 0.4576,
+ "step": 9369
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3496292264891194e-06,
+ "loss": 0.4573,
+ "step": 9370
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3478843660175423e-06,
+ "loss": 0.4696,
+ "step": 9371
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.346140067485506e-06,
+ "loss": 0.4837,
+ "step": 9372
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3443963310211105e-06,
+ "loss": 0.476,
+ "step": 9373
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.342653156752408e-06,
+ "loss": 0.4577,
+ "step": 9374
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3409105448074067e-06,
+ "loss": 0.4761,
+ "step": 9375
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.339168495314079e-06,
+ "loss": 0.4755,
+ "step": 9376
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3374270084003535e-06,
+ "loss": 0.4652,
+ "step": 9377
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3356860841941152e-06,
+ "loss": 0.4781,
+ "step": 9378
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.3339457228232142e-06,
+ "loss": 0.4703,
+ "step": 9379
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.332205924415455e-06,
+ "loss": 0.4699,
+ "step": 9380
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.330466689098596e-06,
+ "loss": 0.4769,
+ "step": 9381
+ },
+ {
+ "epoch": 0.78,
+ "learning_rate": 2.328728017000367e-06,
+ "loss": 0.47,
+ "step": 9382
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3269899082484447e-06,
+ "loss": 0.4821,
+ "step": 9383
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.325252362970469e-06,
+ "loss": 0.4785,
+ "step": 9384
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3235153812940357e-06,
+ "loss": 0.4489,
+ "step": 9385
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.321778963346707e-06,
+ "loss": 0.4619,
+ "step": 9386
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3200431092559948e-06,
+ "loss": 0.4659,
+ "step": 9387
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3183078191493734e-06,
+ "loss": 0.4701,
+ "step": 9388
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3165730931542753e-06,
+ "loss": 0.4658,
+ "step": 9389
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3148389313980912e-06,
+ "loss": 0.4866,
+ "step": 9390
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3131053340081675e-06,
+ "loss": 0.4773,
+ "step": 9391
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3113723011118196e-06,
+ "loss": 0.4558,
+ "step": 9392
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3096398328363078e-06,
+ "loss": 0.4641,
+ "step": 9393
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3079079293088623e-06,
+ "loss": 0.4733,
+ "step": 9394
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.3061765906566644e-06,
+ "loss": 0.4505,
+ "step": 9395
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.304445817006857e-06,
+ "loss": 0.4527,
+ "step": 9396
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.302715608486541e-06,
+ "loss": 0.4698,
+ "step": 9397
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.300985965222775e-06,
+ "loss": 0.4587,
+ "step": 9398
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2992568873425746e-06,
+ "loss": 0.4571,
+ "step": 9399
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2975283749729205e-06,
+ "loss": 0.4801,
+ "step": 9400
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2958004282407466e-06,
+ "loss": 0.464,
+ "step": 9401
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2940730472729423e-06,
+ "loss": 0.4576,
+ "step": 9402
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.292346232196364e-06,
+ "loss": 0.468,
+ "step": 9403
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2906199831378194e-06,
+ "loss": 0.4632,
+ "step": 9404
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.288894300224076e-06,
+ "loss": 0.4746,
+ "step": 9405
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2871691835818642e-06,
+ "loss": 0.4696,
+ "step": 9406
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.285444633337869e-06,
+ "loss": 0.4789,
+ "step": 9407
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2837206496187314e-06,
+ "loss": 0.4654,
+ "step": 9408
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.281997232551055e-06,
+ "loss": 0.4687,
+ "step": 9409
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2802743822614003e-06,
+ "loss": 0.4548,
+ "step": 9410
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2785520988762833e-06,
+ "loss": 0.4527,
+ "step": 9411
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.276830382522187e-06,
+ "loss": 0.4528,
+ "step": 9412
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.275109233325542e-06,
+ "loss": 0.4684,
+ "step": 9413
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2733886514127466e-06,
+ "loss": 0.4661,
+ "step": 9414
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2716686369101525e-06,
+ "loss": 0.4706,
+ "step": 9415
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2699491899440683e-06,
+ "loss": 0.4721,
+ "step": 9416
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2682303106407645e-06,
+ "loss": 0.4519,
+ "step": 9417
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2665119991264673e-06,
+ "loss": 0.4758,
+ "step": 9418
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2647942555273592e-06,
+ "loss": 0.4432,
+ "step": 9419
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2630770799695922e-06,
+ "loss": 0.4654,
+ "step": 9420
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2613604725792636e-06,
+ "loss": 0.4654,
+ "step": 9421
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.259644433482434e-06,
+ "loss": 0.4582,
+ "step": 9422
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2579289628051203e-06,
+ "loss": 0.4455,
+ "step": 9423
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.256214060673305e-06,
+ "loss": 0.4711,
+ "step": 9424
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2544997272129197e-06,
+ "loss": 0.4694,
+ "step": 9425
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.252785962549856e-06,
+ "loss": 0.4452,
+ "step": 9426
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2510727668099706e-06,
+ "loss": 0.4767,
+ "step": 9427
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2493601401190723e-06,
+ "loss": 0.4607,
+ "step": 9428
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.247648082602927e-06,
+ "loss": 0.4478,
+ "step": 9429
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2459365943872613e-06,
+ "loss": 0.4754,
+ "step": 9430
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.244225675597761e-06,
+ "loss": 0.4856,
+ "step": 9431
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.242515326360066e-06,
+ "loss": 0.4694,
+ "step": 9432
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2408055467997823e-06,
+ "loss": 0.4513,
+ "step": 9433
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2390963370424635e-06,
+ "loss": 0.4721,
+ "step": 9434
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.237387697213632e-06,
+ "loss": 0.4726,
+ "step": 9435
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2356796274387617e-06,
+ "loss": 0.4632,
+ "step": 9436
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2339721278432847e-06,
+ "loss": 0.4877,
+ "step": 9437
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2322651985525932e-06,
+ "loss": 0.4796,
+ "step": 9438
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2305588396920375e-06,
+ "loss": 0.4482,
+ "step": 9439
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.228853051386922e-06,
+ "loss": 0.4621,
+ "step": 9440
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.22714783376252e-06,
+ "loss": 0.4697,
+ "step": 9441
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2254431869440496e-06,
+ "loss": 0.4766,
+ "step": 9442
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.223739111056692e-06,
+ "loss": 0.4686,
+ "step": 9443
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.222035606225593e-06,
+ "loss": 0.46,
+ "step": 9444
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.220332672575849e-06,
+ "loss": 0.4642,
+ "step": 9445
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2186303102325125e-06,
+ "loss": 0.4591,
+ "step": 9446
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2169285193206038e-06,
+ "loss": 0.4726,
+ "step": 9447
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2152272999650916e-06,
+ "loss": 0.4684,
+ "step": 9448
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2135266522909073e-06,
+ "loss": 0.491,
+ "step": 9449
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2118265764229396e-06,
+ "loss": 0.4728,
+ "step": 9450
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2101270724860345e-06,
+ "loss": 0.4598,
+ "step": 9451
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2084281406049966e-06,
+ "loss": 0.4708,
+ "step": 9452
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2067297809045863e-06,
+ "loss": 0.4778,
+ "step": 9453
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.2050319935095254e-06,
+ "loss": 0.4637,
+ "step": 9454
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.203334778544497e-06,
+ "loss": 0.4553,
+ "step": 9455
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.201638136134132e-06,
+ "loss": 0.4488,
+ "step": 9456
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.199942066403028e-06,
+ "loss": 0.4643,
+ "step": 9457
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.198246569475735e-06,
+ "loss": 0.4453,
+ "step": 9458
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1965516454767645e-06,
+ "loss": 0.4703,
+ "step": 9459
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1948572945305813e-06,
+ "loss": 0.4579,
+ "step": 9460
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.193163516761617e-06,
+ "loss": 0.4486,
+ "step": 9461
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1914703122942525e-06,
+ "loss": 0.4719,
+ "step": 9462
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1897776812528317e-06,
+ "loss": 0.4651,
+ "step": 9463
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.188085623761649e-06,
+ "loss": 0.4757,
+ "step": 9464
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1863941399449685e-06,
+ "loss": 0.4875,
+ "step": 9465
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1847032299270032e-06,
+ "loss": 0.4704,
+ "step": 9466
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1830128938319238e-06,
+ "loss": 0.455,
+ "step": 9467
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1813231317838667e-06,
+ "loss": 0.4656,
+ "step": 9468
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.179633943906918e-06,
+ "loss": 0.454,
+ "step": 9469
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1779453303251262e-06,
+ "loss": 0.4647,
+ "step": 9470
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.176257291162495e-06,
+ "loss": 0.4512,
+ "step": 9471
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.174569826542986e-06,
+ "loss": 0.473,
+ "step": 9472
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.172882936590518e-06,
+ "loss": 0.4463,
+ "step": 9473
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1711966214289747e-06,
+ "loss": 0.4627,
+ "step": 9474
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1695108811821863e-06,
+ "loss": 0.4592,
+ "step": 9475
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1678257159739524e-06,
+ "loss": 0.4872,
+ "step": 9476
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1661411259280206e-06,
+ "loss": 0.4719,
+ "step": 9477
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1644571111681023e-06,
+ "loss": 0.4569,
+ "step": 9478
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1627736718178626e-06,
+ "loss": 0.4524,
+ "step": 9479
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.161090808000924e-06,
+ "loss": 0.4584,
+ "step": 9480
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1594085198408756e-06,
+ "loss": 0.4599,
+ "step": 9481
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1577268074612535e-06,
+ "loss": 0.4763,
+ "step": 9482
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.156045670985556e-06,
+ "loss": 0.4584,
+ "step": 9483
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1543651105372352e-06,
+ "loss": 0.4735,
+ "step": 9484
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.152685126239713e-06,
+ "loss": 0.4688,
+ "step": 9485
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1510057182163547e-06,
+ "loss": 0.4492,
+ "step": 9486
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1493268865904872e-06,
+ "loss": 0.4916,
+ "step": 9487
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1476486314854027e-06,
+ "loss": 0.4659,
+ "step": 9488
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1459709530243423e-06,
+ "loss": 0.4438,
+ "step": 9489
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.144293851330508e-06,
+ "loss": 0.4826,
+ "step": 9490
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1426173265270578e-06,
+ "loss": 0.4829,
+ "step": 9491
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1409413787371114e-06,
+ "loss": 0.4722,
+ "step": 9492
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.13926600808374e-06,
+ "loss": 0.4796,
+ "step": 9493
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1375912146899767e-06,
+ "loss": 0.4647,
+ "step": 9494
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.135916998678812e-06,
+ "loss": 0.4497,
+ "step": 9495
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.134243360173196e-06,
+ "loss": 0.4972,
+ "step": 9496
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1325702992960317e-06,
+ "loss": 0.4788,
+ "step": 9497
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.130897816170181e-06,
+ "loss": 0.4516,
+ "step": 9498
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1292259109184654e-06,
+ "loss": 0.4556,
+ "step": 9499
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1275545836636625e-06,
+ "loss": 0.4519,
+ "step": 9500
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.1258838345285027e-06,
+ "loss": 0.4905,
+ "step": 9501
+ },
+ {
+ "epoch": 0.79,
+ "learning_rate": 2.124213663635687e-06,
+ "loss": 0.4682,
+ "step": 9502
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1225440711078615e-06,
+ "loss": 0.4862,
+ "step": 9503
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.120875057067635e-06,
+ "loss": 0.4761,
+ "step": 9504
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1192066216375695e-06,
+ "loss": 0.4625,
+ "step": 9505
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1175387649401935e-06,
+ "loss": 0.4456,
+ "step": 9506
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1158714870979856e-06,
+ "loss": 0.4596,
+ "step": 9507
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.114204788233379e-06,
+ "loss": 0.4775,
+ "step": 9508
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1125386684687774e-06,
+ "loss": 0.4652,
+ "step": 9509
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.110873127926529e-06,
+ "loss": 0.4516,
+ "step": 9510
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1092081667289454e-06,
+ "loss": 0.4667,
+ "step": 9511
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1075437849982937e-06,
+ "loss": 0.4646,
+ "step": 9512
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.105879982856799e-06,
+ "loss": 0.473,
+ "step": 9513
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.1042167604266415e-06,
+ "loss": 0.4532,
+ "step": 9514
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.102554117829967e-06,
+ "loss": 0.4778,
+ "step": 9515
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.100892055188867e-06,
+ "loss": 0.4789,
+ "step": 9516
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0992305726254026e-06,
+ "loss": 0.4668,
+ "step": 9517
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0975696702615823e-06,
+ "loss": 0.483,
+ "step": 9518
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0959093482193783e-06,
+ "loss": 0.4624,
+ "step": 9519
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.094249606620715e-06,
+ "loss": 0.4581,
+ "step": 9520
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.092590445587476e-06,
+ "loss": 0.4768,
+ "step": 9521
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0909318652415078e-06,
+ "loss": 0.4691,
+ "step": 9522
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0892738657046065e-06,
+ "loss": 0.4657,
+ "step": 9523
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0876164470985305e-06,
+ "loss": 0.4549,
+ "step": 9524
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0859596095449886e-06,
+ "loss": 0.4605,
+ "step": 9525
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0843033531656596e-06,
+ "loss": 0.4536,
+ "step": 9526
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0826476780821683e-06,
+ "loss": 0.4656,
+ "step": 9527
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.080992584416097e-06,
+ "loss": 0.4637,
+ "step": 9528
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.079338072288997e-06,
+ "loss": 0.4756,
+ "step": 9529
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0776841418223635e-06,
+ "loss": 0.4659,
+ "step": 9530
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0760307931376555e-06,
+ "loss": 0.4654,
+ "step": 9531
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0743780263562884e-06,
+ "loss": 0.4624,
+ "step": 9532
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0727258415996334e-06,
+ "loss": 0.4591,
+ "step": 9533
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0710742389890205e-06,
+ "loss": 0.4664,
+ "step": 9534
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.069423218645734e-06,
+ "loss": 0.4513,
+ "step": 9535
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.067772780691023e-06,
+ "loss": 0.4584,
+ "step": 9536
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0661229252460835e-06,
+ "loss": 0.4804,
+ "step": 9537
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.064473652432081e-06,
+ "loss": 0.4685,
+ "step": 9538
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0628249623701255e-06,
+ "loss": 0.457,
+ "step": 9539
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.061176855181293e-06,
+ "loss": 0.4696,
+ "step": 9540
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0595293309866107e-06,
+ "loss": 0.4725,
+ "step": 9541
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0578823899070653e-06,
+ "loss": 0.4579,
+ "step": 9542
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0562360320636064e-06,
+ "loss": 0.4803,
+ "step": 9543
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0545902575771326e-06,
+ "loss": 0.4821,
+ "step": 9544
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0529450665685023e-06,
+ "loss": 0.4638,
+ "step": 9545
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0513004591585305e-06,
+ "loss": 0.4593,
+ "step": 9546
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.049656435467994e-06,
+ "loss": 0.473,
+ "step": 9547
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.04801299561762e-06,
+ "loss": 0.4585,
+ "step": 9548
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0463701397280953e-06,
+ "loss": 0.4658,
+ "step": 9549
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0447278679200676e-06,
+ "loss": 0.4673,
+ "step": 9550
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0430861803141377e-06,
+ "loss": 0.4683,
+ "step": 9551
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0414450770308638e-06,
+ "loss": 0.4636,
+ "step": 9552
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.03980455819076e-06,
+ "loss": 0.4777,
+ "step": 9553
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0381646239143017e-06,
+ "loss": 0.453,
+ "step": 9554
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0365252743219143e-06,
+ "loss": 0.4474,
+ "step": 9555
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.034886509533991e-06,
+ "loss": 0.4671,
+ "step": 9556
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0332483296708693e-06,
+ "loss": 0.4719,
+ "step": 9557
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.031610734852858e-06,
+ "loss": 0.4555,
+ "step": 9558
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.029973725200212e-06,
+ "loss": 0.4698,
+ "step": 9559
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.028337300833144e-06,
+ "loss": 0.4783,
+ "step": 9560
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0267014618718295e-06,
+ "loss": 0.4447,
+ "step": 9561
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0250662084363928e-06,
+ "loss": 0.4752,
+ "step": 9562
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.023431540646926e-06,
+ "loss": 0.4757,
+ "step": 9563
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.02179745862347e-06,
+ "loss": 0.4496,
+ "step": 9564
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0201639624860246e-06,
+ "loss": 0.4651,
+ "step": 9565
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0185310523545475e-06,
+ "loss": 0.4539,
+ "step": 9566
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0168987283489494e-06,
+ "loss": 0.4631,
+ "step": 9567
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0152669905891075e-06,
+ "loss": 0.4478,
+ "step": 9568
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.013635839194844e-06,
+ "loss": 0.4758,
+ "step": 9569
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0120052742859497e-06,
+ "loss": 0.4786,
+ "step": 9570
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.010375295982163e-06,
+ "loss": 0.4593,
+ "step": 9571
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0087459044031843e-06,
+ "loss": 0.466,
+ "step": 9572
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0071170996686674e-06,
+ "loss": 0.4639,
+ "step": 9573
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0054888818982254e-06,
+ "loss": 0.4788,
+ "step": 9574
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0038612512114285e-06,
+ "loss": 0.4549,
+ "step": 9575
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.0022342077278014e-06,
+ "loss": 0.454,
+ "step": 9576
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 2.00060775156683e-06,
+ "loss": 0.4759,
+ "step": 9577
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.998981882847951e-06,
+ "loss": 0.4794,
+ "step": 9578
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9973566016905666e-06,
+ "loss": 0.4785,
+ "step": 9579
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.995731908214028e-06,
+ "loss": 0.4464,
+ "step": 9580
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.994107802537646e-06,
+ "loss": 0.4696,
+ "step": 9581
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9924842847806867e-06,
+ "loss": 0.4567,
+ "step": 9582
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9908613550623746e-06,
+ "loss": 0.4601,
+ "step": 9583
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9892390135018945e-06,
+ "loss": 0.4741,
+ "step": 9584
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.987617260218382e-06,
+ "loss": 0.4543,
+ "step": 9585
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.985996095330931e-06,
+ "loss": 0.4632,
+ "step": 9586
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.984375518958592e-06,
+ "loss": 0.4491,
+ "step": 9587
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9827555312203785e-06,
+ "loss": 0.4767,
+ "step": 9588
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9811361322352517e-06,
+ "loss": 0.473,
+ "step": 9589
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9795173221221318e-06,
+ "loss": 0.4599,
+ "step": 9590
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9778991009999036e-06,
+ "loss": 0.482,
+ "step": 9591
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9762814689873987e-06,
+ "loss": 0.4809,
+ "step": 9592
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.974664426203409e-06,
+ "loss": 0.4695,
+ "step": 9593
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.973047972766684e-06,
+ "loss": 0.4676,
+ "step": 9594
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9714321087959296e-06,
+ "loss": 0.4593,
+ "step": 9595
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9698168344098056e-06,
+ "loss": 0.4615,
+ "step": 9596
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9682021497269357e-06,
+ "loss": 0.4768,
+ "step": 9597
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9665880548658888e-06,
+ "loss": 0.457,
+ "step": 9598
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9649745499452067e-06,
+ "loss": 0.4568,
+ "step": 9599
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9633616350833717e-06,
+ "loss": 0.4788,
+ "step": 9600
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.961749310398833e-06,
+ "loss": 0.4911,
+ "step": 9601
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9601375760099895e-06,
+ "loss": 0.4736,
+ "step": 9602
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9585264320352003e-06,
+ "loss": 0.464,
+ "step": 9603
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9569158785927867e-06,
+ "loss": 0.4649,
+ "step": 9604
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.955305915801016e-06,
+ "loss": 0.4484,
+ "step": 9605
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9536965437781186e-06,
+ "loss": 0.4635,
+ "step": 9606
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9520877626422794e-06,
+ "loss": 0.4572,
+ "step": 9607
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.95047957251164e-06,
+ "loss": 0.4729,
+ "step": 9608
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9488719735043018e-06,
+ "loss": 0.4615,
+ "step": 9609
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9472649657383157e-06,
+ "loss": 0.4654,
+ "step": 9610
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9456585493317004e-06,
+ "loss": 0.4707,
+ "step": 9611
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.94405272440242e-06,
+ "loss": 0.4773,
+ "step": 9612
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.942447491068401e-06,
+ "loss": 0.4667,
+ "step": 9613
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.940842849447524e-06,
+ "loss": 0.4603,
+ "step": 9614
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9392387996576277e-06,
+ "loss": 0.4447,
+ "step": 9615
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.937635341816506e-06,
+ "loss": 0.4665,
+ "step": 9616
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9360324760419093e-06,
+ "loss": 0.4667,
+ "step": 9617
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.934430202451549e-06,
+ "loss": 0.454,
+ "step": 9618
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9328285211630847e-06,
+ "loss": 0.4657,
+ "step": 9619
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9312274322941426e-06,
+ "loss": 0.4621,
+ "step": 9620
+ },
+ {
+ "epoch": 0.8,
+ "learning_rate": 1.9296269359622977e-06,
+ "loss": 0.457,
+ "step": 9621
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9280270322850836e-06,
+ "loss": 0.4572,
+ "step": 9622
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.92642772137999e-06,
+ "loss": 0.4614,
+ "step": 9623
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9248290033644614e-06,
+ "loss": 0.4545,
+ "step": 9624
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9232308783559064e-06,
+ "loss": 0.4749,
+ "step": 9625
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9216333464716817e-06,
+ "loss": 0.4872,
+ "step": 9626
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9200364078291032e-06,
+ "loss": 0.4565,
+ "step": 9627
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9184400625454413e-06,
+ "loss": 0.4787,
+ "step": 9628
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.916844310737931e-06,
+ "loss": 0.4553,
+ "step": 9629
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9152491525237504e-06,
+ "loss": 0.4542,
+ "step": 9630
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9136545880200484e-06,
+ "loss": 0.4756,
+ "step": 9631
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.912060617343919e-06,
+ "loss": 0.4579,
+ "step": 9632
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.910467240612419e-06,
+ "loss": 0.4656,
+ "step": 9633
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9088744579425567e-06,
+ "loss": 0.4556,
+ "step": 9634
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9072822694513016e-06,
+ "loss": 0.4717,
+ "step": 9635
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9056906752555759e-06,
+ "loss": 0.4633,
+ "step": 9636
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9040996754722574e-06,
+ "loss": 0.4566,
+ "step": 9637
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.902509270218189e-06,
+ "loss": 0.4552,
+ "step": 9638
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.9009194596101566e-06,
+ "loss": 0.4667,
+ "step": 9639
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8993302437649143e-06,
+ "loss": 0.4566,
+ "step": 9640
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8977416227991663e-06,
+ "loss": 0.4585,
+ "step": 9641
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.896153596829574e-06,
+ "loss": 0.4518,
+ "step": 9642
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8945661659727555e-06,
+ "loss": 0.4677,
+ "step": 9643
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8929793303452814e-06,
+ "loss": 0.4731,
+ "step": 9644
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.891393090063688e-06,
+ "loss": 0.4661,
+ "step": 9645
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8898074452444604e-06,
+ "loss": 0.4539,
+ "step": 9646
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8882223960040413e-06,
+ "loss": 0.4814,
+ "step": 9647
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8866379424588287e-06,
+ "loss": 0.4711,
+ "step": 9648
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8850540847251786e-06,
+ "loss": 0.4454,
+ "step": 9649
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8834708229194054e-06,
+ "loss": 0.4759,
+ "step": 9650
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8818881571577741e-06,
+ "loss": 0.4592,
+ "step": 9651
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8803060875565127e-06,
+ "loss": 0.4533,
+ "step": 9652
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8787246142318006e-06,
+ "loss": 0.484,
+ "step": 9653
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8771437372997736e-06,
+ "loss": 0.4713,
+ "step": 9654
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8755634568765246e-06,
+ "loss": 0.4474,
+ "step": 9655
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8739837730781029e-06,
+ "loss": 0.4372,
+ "step": 9656
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.872404686020516e-06,
+ "loss": 0.4562,
+ "step": 9657
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8708261958197193e-06,
+ "loss": 0.4659,
+ "step": 9658
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8692483025916387e-06,
+ "loss": 0.4809,
+ "step": 9659
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8676710064521409e-06,
+ "loss": 0.4592,
+ "step": 9660
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8660943075170634e-06,
+ "loss": 0.4448,
+ "step": 9661
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.864518205902187e-06,
+ "loss": 0.4631,
+ "step": 9662
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.862942701723257e-06,
+ "loss": 0.4671,
+ "step": 9663
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8613677950959697e-06,
+ "loss": 0.4527,
+ "step": 9664
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8597934861359779e-06,
+ "loss": 0.4446,
+ "step": 9665
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.858219774958897e-06,
+ "loss": 0.4743,
+ "step": 9666
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8566466616802914e-06,
+ "loss": 0.4744,
+ "step": 9667
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.855074146415685e-06,
+ "loss": 0.4457,
+ "step": 9668
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8535022292805539e-06,
+ "loss": 0.4582,
+ "step": 9669
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.851930910390337e-06,
+ "loss": 0.4666,
+ "step": 9670
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8503601898604207e-06,
+ "loss": 0.4709,
+ "step": 9671
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8487900678061588e-06,
+ "loss": 0.4568,
+ "step": 9672
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8472205443428504e-06,
+ "loss": 0.4638,
+ "step": 9673
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8456516195857543e-06,
+ "loss": 0.4657,
+ "step": 9674
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8440832936500875e-06,
+ "loss": 0.4578,
+ "step": 9675
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.842515566651021e-06,
+ "loss": 0.4629,
+ "step": 9676
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8409484387036813e-06,
+ "loss": 0.4413,
+ "step": 9677
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8393819099231503e-06,
+ "loss": 0.4732,
+ "step": 9678
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.837815980424471e-06,
+ "loss": 0.4708,
+ "step": 9679
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8362506503226374e-06,
+ "loss": 0.483,
+ "step": 9680
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8346859197325984e-06,
+ "loss": 0.4639,
+ "step": 9681
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8331217887692653e-06,
+ "loss": 0.4756,
+ "step": 9682
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8315582575475e-06,
+ "loss": 0.4638,
+ "step": 9683
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8299953261821202e-06,
+ "loss": 0.4641,
+ "step": 9684
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8284329947878999e-06,
+ "loss": 0.4882,
+ "step": 9685
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8268712634795749e-06,
+ "loss": 0.4464,
+ "step": 9686
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8253101323718303e-06,
+ "loss": 0.4501,
+ "step": 9687
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8237496015793077e-06,
+ "loss": 0.4642,
+ "step": 9688
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8221896712166075e-06,
+ "loss": 0.4618,
+ "step": 9689
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8206303413982806e-06,
+ "loss": 0.4548,
+ "step": 9690
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.819071612238843e-06,
+ "loss": 0.4565,
+ "step": 9691
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8175134838527575e-06,
+ "loss": 0.4589,
+ "step": 9692
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8159559563544504e-06,
+ "loss": 0.4569,
+ "step": 9693
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.814399029858298e-06,
+ "loss": 0.4753,
+ "step": 9694
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8128427044786345e-06,
+ "loss": 0.4571,
+ "step": 9695
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8112869803297494e-06,
+ "loss": 0.4539,
+ "step": 9696
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8097318575258894e-06,
+ "loss": 0.4814,
+ "step": 9697
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.808177336181256e-06,
+ "loss": 0.4669,
+ "step": 9698
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8066234164100038e-06,
+ "loss": 0.4593,
+ "step": 9699
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8050700983262526e-06,
+ "loss": 0.4782,
+ "step": 9700
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8035173820440643e-06,
+ "loss": 0.4736,
+ "step": 9701
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8019652676774703e-06,
+ "loss": 0.4838,
+ "step": 9702
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.8004137553404498e-06,
+ "loss": 0.4489,
+ "step": 9703
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.798862845146938e-06,
+ "loss": 0.4896,
+ "step": 9704
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.797312537210827e-06,
+ "loss": 0.4669,
+ "step": 9705
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.795762831645964e-06,
+ "loss": 0.4614,
+ "step": 9706
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7942137285661576e-06,
+ "loss": 0.4606,
+ "step": 9707
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7926652280851642e-06,
+ "loss": 0.4639,
+ "step": 9708
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7911173303166985e-06,
+ "loss": 0.4593,
+ "step": 9709
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.789570035374434e-06,
+ "loss": 0.4639,
+ "step": 9710
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7880233433719929e-06,
+ "loss": 0.4737,
+ "step": 9711
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7864772544229626e-06,
+ "loss": 0.4641,
+ "step": 9712
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7849317686408817e-06,
+ "loss": 0.4718,
+ "step": 9713
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7833868861392423e-06,
+ "loss": 0.4658,
+ "step": 9714
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7818426070314953e-06,
+ "loss": 0.4595,
+ "step": 9715
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7802989314310449e-06,
+ "loss": 0.4852,
+ "step": 9716
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7787558594512533e-06,
+ "loss": 0.4482,
+ "step": 9717
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7772133912054367e-06,
+ "loss": 0.4569,
+ "step": 9718
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7756715268068635e-06,
+ "loss": 0.4792,
+ "step": 9719
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7741302663687697e-06,
+ "loss": 0.4654,
+ "step": 9720
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7725896100043349e-06,
+ "loss": 0.4532,
+ "step": 9721
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7710495578266963e-06,
+ "loss": 0.4619,
+ "step": 9722
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7695101099489542e-06,
+ "loss": 0.4695,
+ "step": 9723
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7679712664841554e-06,
+ "loss": 0.465,
+ "step": 9724
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.766433027545308e-06,
+ "loss": 0.4712,
+ "step": 9725
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7648953932453706e-06,
+ "loss": 0.4926,
+ "step": 9726
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.763358363697265e-06,
+ "loss": 0.4681,
+ "step": 9727
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7618219390138635e-06,
+ "loss": 0.4721,
+ "step": 9728
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7602861193079922e-06,
+ "loss": 0.4555,
+ "step": 9729
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7587509046924378e-06,
+ "loss": 0.4666,
+ "step": 9730
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7572162952799366e-06,
+ "loss": 0.4645,
+ "step": 9731
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7556822911831882e-06,
+ "loss": 0.4613,
+ "step": 9732
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7541488925148397e-06,
+ "loss": 0.4739,
+ "step": 9733
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.752616099387502e-06,
+ "loss": 0.455,
+ "step": 9734
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7510839119137347e-06,
+ "loss": 0.4624,
+ "step": 9735
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7495523302060546e-06,
+ "loss": 0.4691,
+ "step": 9736
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7480213543769343e-06,
+ "loss": 0.4729,
+ "step": 9737
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7464909845388045e-06,
+ "loss": 0.4682,
+ "step": 9738
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7449612208040479e-06,
+ "loss": 0.4588,
+ "step": 9739
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.743432063285001e-06,
+ "loss": 0.464,
+ "step": 9740
+ },
+ {
+ "epoch": 0.81,
+ "learning_rate": 1.7419035120939642e-06,
+ "loss": 0.4633,
+ "step": 9741
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.740375567343182e-06,
+ "loss": 0.4697,
+ "step": 9742
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7388482291448684e-06,
+ "loss": 0.4564,
+ "step": 9743
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7373214976111786e-06,
+ "loss": 0.4541,
+ "step": 9744
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.735795372854231e-06,
+ "loss": 0.4673,
+ "step": 9745
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7342698549860958e-06,
+ "loss": 0.4842,
+ "step": 9746
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.732744944118805e-06,
+ "loss": 0.459,
+ "step": 9747
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7312206403643395e-06,
+ "loss": 0.4632,
+ "step": 9748
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7296969438346378e-06,
+ "loss": 0.4745,
+ "step": 9749
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7281738546415938e-06,
+ "loss": 0.4645,
+ "step": 9750
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.726651372897057e-06,
+ "loss": 0.4611,
+ "step": 9751
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7251294987128287e-06,
+ "loss": 0.4632,
+ "step": 9752
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.723608232200673e-06,
+ "loss": 0.4493,
+ "step": 9753
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7220875734723063e-06,
+ "loss": 0.4455,
+ "step": 9754
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.720567522639398e-06,
+ "loss": 0.4785,
+ "step": 9755
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7190480798135745e-06,
+ "loss": 0.4574,
+ "step": 9756
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7175292451064174e-06,
+ "loss": 0.4784,
+ "step": 9757
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.716011018629462e-06,
+ "loss": 0.4608,
+ "step": 9758
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7144934004942027e-06,
+ "loss": 0.4531,
+ "step": 9759
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7129763908120823e-06,
+ "loss": 0.4734,
+ "step": 9760
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7114599896945105e-06,
+ "loss": 0.4574,
+ "step": 9761
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.709944197252843e-06,
+ "loss": 0.4479,
+ "step": 9762
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7084290135983895e-06,
+ "loss": 0.4544,
+ "step": 9763
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7069144388424253e-06,
+ "loss": 0.4866,
+ "step": 9764
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7054004730961704e-06,
+ "loss": 0.4746,
+ "step": 9765
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7038871164708059e-06,
+ "loss": 0.4562,
+ "step": 9766
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7023743690774619e-06,
+ "loss": 0.4627,
+ "step": 9767
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.7008622310272349e-06,
+ "loss": 0.4512,
+ "step": 9768
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6993507024311661e-06,
+ "loss": 0.4584,
+ "step": 9769
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.697839783400258e-06,
+ "loss": 0.4578,
+ "step": 9770
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6963294740454638e-06,
+ "loss": 0.4818,
+ "step": 9771
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.694819774477694e-06,
+ "loss": 0.4753,
+ "step": 9772
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6933106848078174e-06,
+ "loss": 0.4678,
+ "step": 9773
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.691802205146652e-06,
+ "loss": 0.4589,
+ "step": 9774
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6902943356049796e-06,
+ "loss": 0.4672,
+ "step": 9775
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6887870762935276e-06,
+ "loss": 0.4603,
+ "step": 9776
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6872804273229838e-06,
+ "loss": 0.4586,
+ "step": 9777
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6857743888039902e-06,
+ "loss": 0.4551,
+ "step": 9778
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6842689608471451e-06,
+ "loss": 0.4649,
+ "step": 9779
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6827641435629983e-06,
+ "loss": 0.4798,
+ "step": 9780
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6812599370620574e-06,
+ "loss": 0.4601,
+ "step": 9781
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.679756341454788e-06,
+ "loss": 0.4397,
+ "step": 9782
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6782533568516047e-06,
+ "loss": 0.4517,
+ "step": 9783
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6767509833628847e-06,
+ "loss": 0.4718,
+ "step": 9784
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6752492210989523e-06,
+ "loss": 0.4713,
+ "step": 9785
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6737480701700936e-06,
+ "loss": 0.4593,
+ "step": 9786
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6722475306865415e-06,
+ "loss": 0.4871,
+ "step": 9787
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6707476027584956e-06,
+ "loss": 0.4819,
+ "step": 9788
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6692482864961024e-06,
+ "loss": 0.4736,
+ "step": 9789
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6677495820094635e-06,
+ "loss": 0.4608,
+ "step": 9790
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6662514894086402e-06,
+ "loss": 0.4389,
+ "step": 9791
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.664754008803644e-06,
+ "loss": 0.4748,
+ "step": 9792
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6632571403044429e-06,
+ "loss": 0.4592,
+ "step": 9793
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6617608840209642e-06,
+ "loss": 0.4609,
+ "step": 9794
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6602652400630825e-06,
+ "loss": 0.4567,
+ "step": 9795
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6587702085406366e-06,
+ "loss": 0.5012,
+ "step": 9796
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6572757895634117e-06,
+ "loss": 0.4571,
+ "step": 9797
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6557819832411537e-06,
+ "loss": 0.4843,
+ "step": 9798
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6542887896835614e-06,
+ "loss": 0.4747,
+ "step": 9799
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.652796209000287e-06,
+ "loss": 0.4576,
+ "step": 9800
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6513042413009383e-06,
+ "loss": 0.4586,
+ "step": 9801
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6498128866950835e-06,
+ "loss": 0.4844,
+ "step": 9802
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6483221452922394e-06,
+ "loss": 0.4594,
+ "step": 9803
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.646832017201877e-06,
+ "loss": 0.4692,
+ "step": 9804
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6453425025334302e-06,
+ "loss": 0.4718,
+ "step": 9805
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6438536013962814e-06,
+ "loss": 0.4611,
+ "step": 9806
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6423653138997675e-06,
+ "loss": 0.4661,
+ "step": 9807
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.64087764015318e-06,
+ "loss": 0.4553,
+ "step": 9808
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.639390580265774e-06,
+ "loss": 0.4626,
+ "step": 9809
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6379041343467484e-06,
+ "loss": 0.4576,
+ "step": 9810
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6364183025052626e-06,
+ "loss": 0.4766,
+ "step": 9811
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6349330848504308e-06,
+ "loss": 0.4571,
+ "step": 9812
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6334484814913165e-06,
+ "loss": 0.4734,
+ "step": 9813
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6319644925369504e-06,
+ "loss": 0.4534,
+ "step": 9814
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6304811180963032e-06,
+ "loss": 0.4627,
+ "step": 9815
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6289983582783142e-06,
+ "loss": 0.4361,
+ "step": 9816
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6275162131918688e-06,
+ "loss": 0.4706,
+ "step": 9817
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6260346829458084e-06,
+ "loss": 0.4615,
+ "step": 9818
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.624553767648931e-06,
+ "loss": 0.4508,
+ "step": 9819
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.623073467409988e-06,
+ "loss": 0.4657,
+ "step": 9820
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.621593782337686e-06,
+ "loss": 0.4634,
+ "step": 9821
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.62011471254069e-06,
+ "loss": 0.4603,
+ "step": 9822
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.618636258127615e-06,
+ "loss": 0.4654,
+ "step": 9823
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6171584192070322e-06,
+ "loss": 0.46,
+ "step": 9824
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6156811958874664e-06,
+ "loss": 0.478,
+ "step": 9825
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6142045882774027e-06,
+ "loss": 0.4481,
+ "step": 9826
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6127285964852758e-06,
+ "loss": 0.4746,
+ "step": 9827
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6112532206194719e-06,
+ "loss": 0.4595,
+ "step": 9828
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6097784607883427e-06,
+ "loss": 0.4624,
+ "step": 9829
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6083043171001856e-06,
+ "loss": 0.4669,
+ "step": 9830
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6068307896632562e-06,
+ "loss": 0.456,
+ "step": 9831
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6053578785857637e-06,
+ "loss": 0.4572,
+ "step": 9832
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6038855839758727e-06,
+ "loss": 0.4696,
+ "step": 9833
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6024139059417e-06,
+ "loss": 0.4707,
+ "step": 9834
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.6009428445913245e-06,
+ "loss": 0.4542,
+ "step": 9835
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5994724000327689e-06,
+ "loss": 0.4657,
+ "step": 9836
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5980025723740222e-06,
+ "loss": 0.4558,
+ "step": 9837
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5965333617230206e-06,
+ "loss": 0.4499,
+ "step": 9838
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5950647681876564e-06,
+ "loss": 0.4672,
+ "step": 9839
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5935967918757766e-06,
+ "loss": 0.4803,
+ "step": 9840
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5921294328951842e-06,
+ "loss": 0.4685,
+ "step": 9841
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5906626913536315e-06,
+ "loss": 0.4913,
+ "step": 9842
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5891965673588371e-06,
+ "loss": 0.4623,
+ "step": 9843
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5877310610184638e-06,
+ "loss": 0.467,
+ "step": 9844
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5862661724401296e-06,
+ "loss": 0.4534,
+ "step": 9845
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5848019017314143e-06,
+ "loss": 0.4589,
+ "step": 9846
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5833382489998461e-06,
+ "loss": 0.4532,
+ "step": 9847
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5818752143529092e-06,
+ "loss": 0.4563,
+ "step": 9848
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.580412797898041e-06,
+ "loss": 0.4748,
+ "step": 9849
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.578950999742639e-06,
+ "loss": 0.4534,
+ "step": 9850
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5774898199940503e-06,
+ "loss": 0.4749,
+ "step": 9851
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.576029258759577e-06,
+ "loss": 0.4571,
+ "step": 9852
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.574569316146477e-06,
+ "loss": 0.4619,
+ "step": 9853
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.573109992261963e-06,
+ "loss": 0.4568,
+ "step": 9854
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5716512872131983e-06,
+ "loss": 0.46,
+ "step": 9855
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5701932011073072e-06,
+ "loss": 0.464,
+ "step": 9856
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5687357340513676e-06,
+ "loss": 0.4505,
+ "step": 9857
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.567278886152407e-06,
+ "loss": 0.4821,
+ "step": 9858
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.5658226575174107e-06,
+ "loss": 0.4536,
+ "step": 9859
+ },
+ {
+ "epoch": 0.82,
+ "learning_rate": 1.564367048253318e-06,
+ "loss": 0.4568,
+ "step": 9860
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5629120584670233e-06,
+ "loss": 0.4723,
+ "step": 9861
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.561457688265372e-06,
+ "loss": 0.4438,
+ "step": 9862
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5600039377551713e-06,
+ "loss": 0.4778,
+ "step": 9863
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5585508070431777e-06,
+ "loss": 0.4595,
+ "step": 9864
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5570982962361014e-06,
+ "loss": 0.4779,
+ "step": 9865
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5556464054406084e-06,
+ "loss": 0.4676,
+ "step": 9866
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5541951347633222e-06,
+ "loss": 0.4708,
+ "step": 9867
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5527444843108164e-06,
+ "loss": 0.4505,
+ "step": 9868
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5512944541896192e-06,
+ "loss": 0.4521,
+ "step": 9869
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5498450445062185e-06,
+ "loss": 0.4528,
+ "step": 9870
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5483962553670507e-06,
+ "loss": 0.4653,
+ "step": 9871
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5469480868785092e-06,
+ "loss": 0.4514,
+ "step": 9872
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5455005391469414e-06,
+ "loss": 0.4529,
+ "step": 9873
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5440536122786487e-06,
+ "loss": 0.4503,
+ "step": 9874
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5426073063798853e-06,
+ "loss": 0.4638,
+ "step": 9875
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.541161621556867e-06,
+ "loss": 0.4875,
+ "step": 9876
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5397165579157547e-06,
+ "loss": 0.4691,
+ "step": 9877
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5382721155626701e-06,
+ "loss": 0.4669,
+ "step": 9878
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5368282946036884e-06,
+ "loss": 0.4839,
+ "step": 9879
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5353850951448346e-06,
+ "loss": 0.45,
+ "step": 9880
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.533942517292092e-06,
+ "loss": 0.4832,
+ "step": 9881
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5325005611513988e-06,
+ "loss": 0.4552,
+ "step": 9882
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5310592268286427e-06,
+ "loss": 0.4636,
+ "step": 9883
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5296185144296737e-06,
+ "loss": 0.4557,
+ "step": 9884
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5281784240602915e-06,
+ "loss": 0.4538,
+ "step": 9885
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5267389558262458e-06,
+ "loss": 0.4727,
+ "step": 9886
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.525300109833251e-06,
+ "loss": 0.468,
+ "step": 9887
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5238618861869657e-06,
+ "loss": 0.4555,
+ "step": 9888
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5224242849930104e-06,
+ "loss": 0.4554,
+ "step": 9889
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5209873063569514e-06,
+ "loss": 0.461,
+ "step": 9890
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5195509503843198e-06,
+ "loss": 0.4678,
+ "step": 9891
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5181152171805946e-06,
+ "loss": 0.4675,
+ "step": 9892
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5166801068512083e-06,
+ "loss": 0.4785,
+ "step": 9893
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5152456195015508e-06,
+ "loss": 0.4646,
+ "step": 9894
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5138117552369636e-06,
+ "loss": 0.4579,
+ "step": 9895
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5123785141627422e-06,
+ "loss": 0.4778,
+ "step": 9896
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5109458963841405e-06,
+ "loss": 0.4539,
+ "step": 9897
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5095139020063654e-06,
+ "loss": 0.4777,
+ "step": 9898
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5080825311345748e-06,
+ "loss": 0.4639,
+ "step": 9899
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5066517838738826e-06,
+ "loss": 0.4715,
+ "step": 9900
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5052216603293567e-06,
+ "loss": 0.4642,
+ "step": 9901
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5037921606060201e-06,
+ "loss": 0.4706,
+ "step": 9902
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5023632848088466e-06,
+ "loss": 0.4704,
+ "step": 9903
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.5009350330427707e-06,
+ "loss": 0.4681,
+ "step": 9904
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4995074054126758e-06,
+ "loss": 0.4892,
+ "step": 9905
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4980804020234018e-06,
+ "loss": 0.4726,
+ "step": 9906
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4966540229797377e-06,
+ "loss": 0.449,
+ "step": 9907
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.495228268386436e-06,
+ "loss": 0.4921,
+ "step": 9908
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4938031383481976e-06,
+ "loss": 0.4561,
+ "step": 9909
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4923786329696732e-06,
+ "loss": 0.4515,
+ "step": 9910
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.490954752355479e-06,
+ "loss": 0.4636,
+ "step": 9911
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4895314966101771e-06,
+ "loss": 0.4696,
+ "step": 9912
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4881088658382825e-06,
+ "loss": 0.46,
+ "step": 9913
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4866868601442708e-06,
+ "loss": 0.4571,
+ "step": 9914
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4852654796325649e-06,
+ "loss": 0.4791,
+ "step": 9915
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.483844724407546e-06,
+ "loss": 0.4548,
+ "step": 9916
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4824245945735504e-06,
+ "loss": 0.4757,
+ "step": 9917
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4810050902348637e-06,
+ "loss": 0.4646,
+ "step": 9918
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4795862114957316e-06,
+ "loss": 0.4581,
+ "step": 9919
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4781679584603502e-06,
+ "loss": 0.4629,
+ "step": 9920
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.476750331232868e-06,
+ "loss": 0.4577,
+ "step": 9921
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.475333329917391e-06,
+ "loss": 0.4527,
+ "step": 9922
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4739169546179765e-06,
+ "loss": 0.4807,
+ "step": 9923
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4725012054386378e-06,
+ "loss": 0.4923,
+ "step": 9924
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.471086082483343e-06,
+ "loss": 0.4598,
+ "step": 9925
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4696715858560117e-06,
+ "loss": 0.4665,
+ "step": 9926
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4682577156605172e-06,
+ "loss": 0.4629,
+ "step": 9927
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4668444720006925e-06,
+ "loss": 0.4601,
+ "step": 9928
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.465431854980317e-06,
+ "loss": 0.4491,
+ "step": 9929
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.464019864703128e-06,
+ "loss": 0.4712,
+ "step": 9930
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.462608501272814e-06,
+ "loss": 0.4774,
+ "step": 9931
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4611977647930253e-06,
+ "loss": 0.4513,
+ "step": 9932
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4597876553673563e-06,
+ "loss": 0.4563,
+ "step": 9933
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4583781730993608e-06,
+ "loss": 0.499,
+ "step": 9934
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4569693180925448e-06,
+ "loss": 0.4526,
+ "step": 9935
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4555610904503693e-06,
+ "loss": 0.4584,
+ "step": 9936
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4541534902762454e-06,
+ "loss": 0.4796,
+ "step": 9937
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4527465176735468e-06,
+ "loss": 0.4667,
+ "step": 9938
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4513401727455912e-06,
+ "loss": 0.4605,
+ "step": 9939
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4499344555956596e-06,
+ "loss": 0.4599,
+ "step": 9940
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4485293663269784e-06,
+ "loss": 0.4705,
+ "step": 9941
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4471249050427327e-06,
+ "loss": 0.4587,
+ "step": 9942
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.445721071846059e-06,
+ "loss": 0.4666,
+ "step": 9943
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4443178668400482e-06,
+ "loss": 0.4746,
+ "step": 9944
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.44291529012775e-06,
+ "loss": 0.4541,
+ "step": 9945
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4415133418121607e-06,
+ "loss": 0.4601,
+ "step": 9946
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.440112021996235e-06,
+ "loss": 0.4644,
+ "step": 9947
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.438711330782877e-06,
+ "loss": 0.4746,
+ "step": 9948
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4373112682749513e-06,
+ "loss": 0.453,
+ "step": 9949
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.435911834575271e-06,
+ "loss": 0.4469,
+ "step": 9950
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4345130297866028e-06,
+ "loss": 0.4831,
+ "step": 9951
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4331148540116736e-06,
+ "loss": 0.4721,
+ "step": 9952
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4317173073531577e-06,
+ "loss": 0.4719,
+ "step": 9953
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4303203899136841e-06,
+ "loss": 0.4573,
+ "step": 9954
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4289241017958366e-06,
+ "loss": 0.4556,
+ "step": 9955
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4275284431021541e-06,
+ "loss": 0.4715,
+ "step": 9956
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4261334139351269e-06,
+ "loss": 0.4622,
+ "step": 9957
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4247390143971972e-06,
+ "loss": 0.4679,
+ "step": 9958
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.423345244590768e-06,
+ "loss": 0.4744,
+ "step": 9959
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4219521046181928e-06,
+ "loss": 0.4441,
+ "step": 9960
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4205595945817773e-06,
+ "loss": 0.4609,
+ "step": 9961
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.41916771458378e-06,
+ "loss": 0.4812,
+ "step": 9962
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4177764647264148e-06,
+ "loss": 0.4526,
+ "step": 9963
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4163858451118506e-06,
+ "loss": 0.4531,
+ "step": 9964
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.414995855842205e-06,
+ "loss": 0.4603,
+ "step": 9965
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4136064970195595e-06,
+ "loss": 0.447,
+ "step": 9966
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4122177687459382e-06,
+ "loss": 0.4504,
+ "step": 9967
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4108296711233249e-06,
+ "loss": 0.461,
+ "step": 9968
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4094422042536538e-06,
+ "loss": 0.458,
+ "step": 9969
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4080553682388188e-06,
+ "loss": 0.4563,
+ "step": 9970
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4066691631806574e-06,
+ "loss": 0.4701,
+ "step": 9971
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4052835891809735e-06,
+ "loss": 0.4579,
+ "step": 9972
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.403898646341515e-06,
+ "loss": 0.4772,
+ "step": 9973
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4025143347639858e-06,
+ "loss": 0.467,
+ "step": 9974
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.4011306545500435e-06,
+ "loss": 0.4744,
+ "step": 9975
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3997476058013016e-06,
+ "loss": 0.4634,
+ "step": 9976
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.398365188619324e-06,
+ "loss": 0.4809,
+ "step": 9977
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3969834031056273e-06,
+ "loss": 0.4474,
+ "step": 9978
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3956022493616895e-06,
+ "loss": 0.4512,
+ "step": 9979
+ },
+ {
+ "epoch": 0.83,
+ "learning_rate": 1.3942217274889325e-06,
+ "loss": 0.4772,
+ "step": 9980
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3928418375887388e-06,
+ "loss": 0.4751,
+ "step": 9981
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3914625797624415e-06,
+ "loss": 0.4361,
+ "step": 9982
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3900839541113265e-06,
+ "loss": 0.4814,
+ "step": 9983
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3887059607366338e-06,
+ "loss": 0.4506,
+ "step": 9984
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3873285997395569e-06,
+ "loss": 0.4521,
+ "step": 9985
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3859518712212473e-06,
+ "loss": 0.4759,
+ "step": 9986
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3845757752828037e-06,
+ "loss": 0.4694,
+ "step": 9987
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3832003120252801e-06,
+ "loss": 0.4438,
+ "step": 9988
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3818254815496846e-06,
+ "loss": 0.4566,
+ "step": 9989
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3804512839569805e-06,
+ "loss": 0.4699,
+ "step": 9990
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3790777193480842e-06,
+ "loss": 0.4585,
+ "step": 9991
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3777047878238603e-06,
+ "loss": 0.4504,
+ "step": 9992
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3763324894851371e-06,
+ "loss": 0.4583,
+ "step": 9993
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3749608244326862e-06,
+ "loss": 0.461,
+ "step": 9994
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.373589792767238e-06,
+ "loss": 0.4712,
+ "step": 9995
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.372219394589477e-06,
+ "loss": 0.4688,
+ "step": 9996
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3708496300000363e-06,
+ "loss": 0.479,
+ "step": 9997
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.369480499099508e-06,
+ "loss": 0.4624,
+ "step": 9998
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3681120019884331e-06,
+ "loss": 0.4708,
+ "step": 9999
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3667441387673098e-06,
+ "loss": 0.4821,
+ "step": 10000
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.36537690953659e-06,
+ "loss": 0.4553,
+ "step": 10001
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3640103143966765e-06,
+ "loss": 0.4771,
+ "step": 10002
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3626443534479262e-06,
+ "loss": 0.4618,
+ "step": 10003
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3612790267906484e-06,
+ "loss": 0.4534,
+ "step": 10004
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3599143345251075e-06,
+ "loss": 0.4711,
+ "step": 10005
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.35855027675152e-06,
+ "loss": 0.4506,
+ "step": 10006
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3571868535700595e-06,
+ "loss": 0.4574,
+ "step": 10007
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3558240650808473e-06,
+ "loss": 0.4485,
+ "step": 10008
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.354461911383963e-06,
+ "loss": 0.4536,
+ "step": 10009
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.353100392579434e-06,
+ "loss": 0.467,
+ "step": 10010
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.351739508767249e-06,
+ "loss": 0.4719,
+ "step": 10011
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3503792600473408e-06,
+ "loss": 0.4611,
+ "step": 10012
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.349019646519607e-06,
+ "loss": 0.4513,
+ "step": 10013
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3476606682838866e-06,
+ "loss": 0.4686,
+ "step": 10014
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3463023254399798e-06,
+ "loss": 0.4681,
+ "step": 10015
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3449446180876369e-06,
+ "loss": 0.4556,
+ "step": 10016
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3435875463265624e-06,
+ "loss": 0.4678,
+ "step": 10017
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3422311102564134e-06,
+ "loss": 0.4727,
+ "step": 10018
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.340875309976799e-06,
+ "loss": 0.4818,
+ "step": 10019
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3395201455872886e-06,
+ "loss": 0.4737,
+ "step": 10020
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3381656171873936e-06,
+ "loss": 0.4683,
+ "step": 10021
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.336811724876592e-06,
+ "loss": 0.4708,
+ "step": 10022
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3354584687543037e-06,
+ "loss": 0.4664,
+ "step": 10023
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3341058489199065e-06,
+ "loss": 0.4535,
+ "step": 10024
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3327538654727323e-06,
+ "loss": 0.4832,
+ "step": 10025
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3314025185120616e-06,
+ "loss": 0.4402,
+ "step": 10026
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3300518081371373e-06,
+ "loss": 0.4713,
+ "step": 10027
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3287017344471477e-06,
+ "loss": 0.4847,
+ "step": 10028
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3273522975412344e-06,
+ "loss": 0.485,
+ "step": 10029
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3260034975184955e-06,
+ "loss": 0.4526,
+ "step": 10030
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3246553344779834e-06,
+ "loss": 0.4636,
+ "step": 10031
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3233078085187002e-06,
+ "loss": 0.4618,
+ "step": 10032
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3219609197396e-06,
+ "loss": 0.4777,
+ "step": 10033
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3206146682395983e-06,
+ "loss": 0.4768,
+ "step": 10034
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3192690541175536e-06,
+ "loss": 0.469,
+ "step": 10035
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3179240774722845e-06,
+ "loss": 0.4677,
+ "step": 10036
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3165797384025602e-06,
+ "loss": 0.4521,
+ "step": 10037
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3152360370071016e-06,
+ "loss": 0.458,
+ "step": 10038
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3138929733845873e-06,
+ "loss": 0.4684,
+ "step": 10039
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3125505476336408e-06,
+ "loss": 0.4928,
+ "step": 10040
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.31120875985285e-06,
+ "loss": 0.4457,
+ "step": 10041
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3098676101407493e-06,
+ "loss": 0.4711,
+ "step": 10042
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3085270985958276e-06,
+ "loss": 0.4534,
+ "step": 10043
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.307187225316524e-06,
+ "loss": 0.4645,
+ "step": 10044
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3058479904012356e-06,
+ "loss": 0.4482,
+ "step": 10045
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3045093939483066e-06,
+ "loss": 0.4551,
+ "step": 10046
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.303171436056042e-06,
+ "loss": 0.4767,
+ "step": 10047
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3018341168226944e-06,
+ "loss": 0.4526,
+ "step": 10048
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.3004974363464717e-06,
+ "loss": 0.4568,
+ "step": 10049
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2991613947255321e-06,
+ "loss": 0.4566,
+ "step": 10050
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2978259920579895e-06,
+ "loss": 0.4475,
+ "step": 10051
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2964912284419119e-06,
+ "loss": 0.4601,
+ "step": 10052
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2951571039753163e-06,
+ "loss": 0.4661,
+ "step": 10053
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2938236187561782e-06,
+ "loss": 0.4581,
+ "step": 10054
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.292490772882422e-06,
+ "loss": 0.4995,
+ "step": 10055
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2911585664519267e-06,
+ "loss": 0.4664,
+ "step": 10056
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2898269995625234e-06,
+ "loss": 0.4653,
+ "step": 10057
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2884960723119978e-06,
+ "loss": 0.4812,
+ "step": 10058
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2871657847980856e-06,
+ "loss": 0.4597,
+ "step": 10059
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.285836137118477e-06,
+ "loss": 0.4648,
+ "step": 10060
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2845071293708188e-06,
+ "loss": 0.4471,
+ "step": 10061
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2831787616527058e-06,
+ "loss": 0.4796,
+ "step": 10062
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2818510340616896e-06,
+ "loss": 0.4558,
+ "step": 10063
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2805239466952723e-06,
+ "loss": 0.4706,
+ "step": 10064
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2791974996509094e-06,
+ "loss": 0.4646,
+ "step": 10065
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2778716930260105e-06,
+ "loss": 0.4734,
+ "step": 10066
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2765465269179334e-06,
+ "loss": 0.4534,
+ "step": 10067
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.275222001423998e-06,
+ "loss": 0.4768,
+ "step": 10068
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2738981166414688e-06,
+ "loss": 0.467,
+ "step": 10069
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2725748726675691e-06,
+ "loss": 0.4768,
+ "step": 10070
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2712522695994666e-06,
+ "loss": 0.4946,
+ "step": 10071
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.269930307534295e-06,
+ "loss": 0.4539,
+ "step": 10072
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.268608986569131e-06,
+ "loss": 0.4647,
+ "step": 10073
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2672883068010033e-06,
+ "loss": 0.4726,
+ "step": 10074
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2659682683269036e-06,
+ "loss": 0.4771,
+ "step": 10075
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2646488712437654e-06,
+ "loss": 0.4556,
+ "step": 10076
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2633301156484822e-06,
+ "loss": 0.4647,
+ "step": 10077
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2620120016378956e-06,
+ "loss": 0.4549,
+ "step": 10078
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2606945293088047e-06,
+ "loss": 0.4467,
+ "step": 10079
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2593776987579576e-06,
+ "loss": 0.4639,
+ "step": 10080
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2580615100820548e-06,
+ "loss": 0.4664,
+ "step": 10081
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2567459633777567e-06,
+ "loss": 0.4634,
+ "step": 10082
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2554310587416674e-06,
+ "loss": 0.4713,
+ "step": 10083
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2541167962703515e-06,
+ "loss": 0.4783,
+ "step": 10084
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.252803176060321e-06,
+ "loss": 0.4557,
+ "step": 10085
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.251490198208043e-06,
+ "loss": 0.4748,
+ "step": 10086
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2501778628099349e-06,
+ "loss": 0.4805,
+ "step": 10087
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2488661699623739e-06,
+ "loss": 0.4657,
+ "step": 10088
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.247555119761682e-06,
+ "loss": 0.4644,
+ "step": 10089
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2462447123041388e-06,
+ "loss": 0.464,
+ "step": 10090
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.244934947685974e-06,
+ "loss": 0.4735,
+ "step": 10091
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2436258260033696e-06,
+ "loss": 0.4721,
+ "step": 10092
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2423173473524653e-06,
+ "loss": 0.4823,
+ "step": 10093
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2410095118293475e-06,
+ "loss": 0.4499,
+ "step": 10094
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2397023195300618e-06,
+ "loss": 0.4769,
+ "step": 10095
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.238395770550601e-06,
+ "loss": 0.4584,
+ "step": 10096
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2370898649869122e-06,
+ "loss": 0.4785,
+ "step": 10097
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2357846029348975e-06,
+ "loss": 0.461,
+ "step": 10098
+ },
+ {
+ "epoch": 0.84,
+ "learning_rate": 1.2344799844904065e-06,
+ "loss": 0.4563,
+ "step": 10099
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2331760097492485e-06,
+ "loss": 0.4628,
+ "step": 10100
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2318726788071767e-06,
+ "loss": 0.4704,
+ "step": 10101
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.230569991759909e-06,
+ "loss": 0.473,
+ "step": 10102
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2292679487031045e-06,
+ "loss": 0.4632,
+ "step": 10103
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2279665497323835e-06,
+ "loss": 0.4495,
+ "step": 10104
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2266657949433135e-06,
+ "loss": 0.4662,
+ "step": 10105
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2253656844314155e-06,
+ "loss": 0.4628,
+ "step": 10106
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.224066218292167e-06,
+ "loss": 0.4859,
+ "step": 10107
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2227673966209896e-06,
+ "loss": 0.4671,
+ "step": 10108
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2214692195132705e-06,
+ "loss": 0.4454,
+ "step": 10109
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2201716870643388e-06,
+ "loss": 0.458,
+ "step": 10110
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2188747993694805e-06,
+ "loss": 0.452,
+ "step": 10111
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.217578556523934e-06,
+ "loss": 0.4621,
+ "step": 10112
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2162829586228874e-06,
+ "loss": 0.4471,
+ "step": 10113
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.214988005761487e-06,
+ "loss": 0.4653,
+ "step": 10114
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2136936980348267e-06,
+ "loss": 0.4649,
+ "step": 10115
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2124000355379583e-06,
+ "loss": 0.4577,
+ "step": 10116
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.21110701836588e-06,
+ "loss": 0.4553,
+ "step": 10117
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2098146466135475e-06,
+ "loss": 0.4912,
+ "step": 10118
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2085229203758663e-06,
+ "loss": 0.4616,
+ "step": 10119
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2072318397476945e-06,
+ "loss": 0.4577,
+ "step": 10120
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2059414048238437e-06,
+ "loss": 0.4583,
+ "step": 10121
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2046516156990796e-06,
+ "loss": 0.4592,
+ "step": 10122
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2033624724681191e-06,
+ "loss": 0.468,
+ "step": 10123
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2020739752256282e-06,
+ "loss": 0.4817,
+ "step": 10124
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.2007861240662334e-06,
+ "loss": 0.4542,
+ "step": 10125
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1994989190845075e-06,
+ "loss": 0.4465,
+ "step": 10126
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1982123603749762e-06,
+ "loss": 0.455,
+ "step": 10127
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1969264480321175e-06,
+ "loss": 0.465,
+ "step": 10128
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1956411821503688e-06,
+ "loss": 0.462,
+ "step": 10129
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1943565628241105e-06,
+ "loss": 0.4554,
+ "step": 10130
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1930725901476814e-06,
+ "loss": 0.4542,
+ "step": 10131
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1917892642153706e-06,
+ "loss": 0.469,
+ "step": 10132
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.190506585121418e-06,
+ "loss": 0.4819,
+ "step": 10133
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1892245529600222e-06,
+ "loss": 0.4757,
+ "step": 10134
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1879431678253261e-06,
+ "loss": 0.4704,
+ "step": 10135
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1866624298114338e-06,
+ "loss": 0.459,
+ "step": 10136
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1853823390123964e-06,
+ "loss": 0.4646,
+ "step": 10137
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1841028955222155e-06,
+ "loss": 0.4662,
+ "step": 10138
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1828240994348517e-06,
+ "loss": 0.4671,
+ "step": 10139
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1815459508442118e-06,
+ "loss": 0.4511,
+ "step": 10140
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1802684498441585e-06,
+ "loss": 0.4797,
+ "step": 10141
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1789915965285037e-06,
+ "loss": 0.4553,
+ "step": 10142
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.177715390991019e-06,
+ "loss": 0.4775,
+ "step": 10143
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1764398333254202e-06,
+ "loss": 0.4567,
+ "step": 10144
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1751649236253815e-06,
+ "loss": 0.4767,
+ "step": 10145
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1738906619845248e-06,
+ "loss": 0.4722,
+ "step": 10146
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1726170484964282e-06,
+ "loss": 0.4849,
+ "step": 10147
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1713440832546196e-06,
+ "loss": 0.4432,
+ "step": 10148
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1700717663525784e-06,
+ "loss": 0.4562,
+ "step": 10149
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1688000978837423e-06,
+ "loss": 0.478,
+ "step": 10150
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1675290779414949e-06,
+ "loss": 0.4653,
+ "step": 10151
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1662587066191755e-06,
+ "loss": 0.4584,
+ "step": 10152
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1649889840100737e-06,
+ "loss": 0.4666,
+ "step": 10153
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1637199102074326e-06,
+ "loss": 0.4629,
+ "step": 10154
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1624514853044488e-06,
+ "loss": 0.4594,
+ "step": 10155
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1611837093942691e-06,
+ "loss": 0.4912,
+ "step": 10156
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1599165825699955e-06,
+ "loss": 0.4794,
+ "step": 10157
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1586501049246801e-06,
+ "loss": 0.4589,
+ "step": 10158
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1573842765513266e-06,
+ "loss": 0.4812,
+ "step": 10159
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1561190975428926e-06,
+ "loss": 0.4629,
+ "step": 10160
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1548545679922885e-06,
+ "loss": 0.4512,
+ "step": 10161
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.153590687992372e-06,
+ "loss": 0.4553,
+ "step": 10162
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1523274576359633e-06,
+ "loss": 0.4647,
+ "step": 10163
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.151064877015825e-06,
+ "loss": 0.4667,
+ "step": 10164
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1498029462246752e-06,
+ "loss": 0.4664,
+ "step": 10165
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1485416653551884e-06,
+ "loss": 0.459,
+ "step": 10166
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1472810344999852e-06,
+ "loss": 0.4335,
+ "step": 10167
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1460210537516426e-06,
+ "loss": 0.4746,
+ "step": 10168
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1447617232026842e-06,
+ "loss": 0.4671,
+ "step": 10169
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1435030429455951e-06,
+ "loss": 0.4687,
+ "step": 10170
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1422450130728069e-06,
+ "loss": 0.4722,
+ "step": 10171
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1409876336767013e-06,
+ "loss": 0.4592,
+ "step": 10172
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1397309048496174e-06,
+ "loss": 0.4744,
+ "step": 10173
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1384748266838408e-06,
+ "loss": 0.4578,
+ "step": 10174
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1372193992716175e-06,
+ "loss": 0.467,
+ "step": 10175
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1359646227051357e-06,
+ "loss": 0.4537,
+ "step": 10176
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1347104970765466e-06,
+ "loss": 0.454,
+ "step": 10177
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.133457022477945e-06,
+ "loss": 0.475,
+ "step": 10178
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1322041990013798e-06,
+ "loss": 0.4638,
+ "step": 10179
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.130952026738855e-06,
+ "loss": 0.4609,
+ "step": 10180
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1297005057823251e-06,
+ "loss": 0.4676,
+ "step": 10181
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1284496362236952e-06,
+ "loss": 0.4789,
+ "step": 10182
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1271994181548217e-06,
+ "loss": 0.4718,
+ "step": 10183
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1259498516675204e-06,
+ "loss": 0.4717,
+ "step": 10184
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.12470093685355e-06,
+ "loss": 0.4607,
+ "step": 10185
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1234526738046303e-06,
+ "loss": 0.4358,
+ "step": 10186
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.122205062612426e-06,
+ "loss": 0.474,
+ "step": 10187
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1209581033685558e-06,
+ "loss": 0.4668,
+ "step": 10188
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1197117961645921e-06,
+ "loss": 0.4598,
+ "step": 10189
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.118466141092055e-06,
+ "loss": 0.4466,
+ "step": 10190
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1172211382424269e-06,
+ "loss": 0.4796,
+ "step": 10191
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1159767877071314e-06,
+ "loss": 0.461,
+ "step": 10192
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1147330895775498e-06,
+ "loss": 0.472,
+ "step": 10193
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1134900439450124e-06,
+ "loss": 0.4753,
+ "step": 10194
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.112247650900804e-06,
+ "loss": 0.449,
+ "step": 10195
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1110059105361616e-06,
+ "loss": 0.4559,
+ "step": 10196
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1097648229422719e-06,
+ "loss": 0.4649,
+ "step": 10197
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.108524388210278e-06,
+ "loss": 0.4535,
+ "step": 10198
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1072846064312715e-06,
+ "loss": 0.4645,
+ "step": 10199
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1060454776962947e-06,
+ "loss": 0.4628,
+ "step": 10200
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1048070020963453e-06,
+ "loss": 0.4658,
+ "step": 10201
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1035691797223724e-06,
+ "loss": 0.4706,
+ "step": 10202
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1023320106652735e-06,
+ "loss": 0.4566,
+ "step": 10203
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.1010954950159058e-06,
+ "loss": 0.4699,
+ "step": 10204
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0998596328650724e-06,
+ "loss": 0.4587,
+ "step": 10205
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.098624424303526e-06,
+ "loss": 0.4722,
+ "step": 10206
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0973898694219809e-06,
+ "loss": 0.4548,
+ "step": 10207
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0961559683110946e-06,
+ "loss": 0.4523,
+ "step": 10208
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0949227210614798e-06,
+ "loss": 0.4467,
+ "step": 10209
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0936901277637002e-06,
+ "loss": 0.4952,
+ "step": 10210
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0924581885082753e-06,
+ "loss": 0.4745,
+ "step": 10211
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0912269033856716e-06,
+ "loss": 0.45,
+ "step": 10212
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.089996272486309e-06,
+ "loss": 0.4564,
+ "step": 10213
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.088766295900562e-06,
+ "loss": 0.4536,
+ "step": 10214
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0875369737187502e-06,
+ "loss": 0.4627,
+ "step": 10215
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0863083060311563e-06,
+ "loss": 0.4539,
+ "step": 10216
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0850802929280034e-06,
+ "loss": 0.474,
+ "step": 10217
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0838529344994763e-06,
+ "loss": 0.4448,
+ "step": 10218
+ },
+ {
+ "epoch": 0.85,
+ "learning_rate": 1.0826262308357038e-06,
+ "loss": 0.4548,
+ "step": 10219
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0814001820267717e-06,
+ "loss": 0.4531,
+ "step": 10220
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0801747881627134e-06,
+ "loss": 0.4624,
+ "step": 10221
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0789500493335191e-06,
+ "loss": 0.4819,
+ "step": 10222
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0777259656291284e-06,
+ "loss": 0.4558,
+ "step": 10223
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.07650253713943e-06,
+ "loss": 0.4588,
+ "step": 10224
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0752797639542712e-06,
+ "loss": 0.4649,
+ "step": 10225
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0740576461634466e-06,
+ "loss": 0.4855,
+ "step": 10226
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0728361838567003e-06,
+ "loss": 0.4787,
+ "step": 10227
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0716153771237359e-06,
+ "loss": 0.4544,
+ "step": 10228
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0703952260542016e-06,
+ "loss": 0.4666,
+ "step": 10229
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0691757307377014e-06,
+ "loss": 0.4757,
+ "step": 10230
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0679568912637872e-06,
+ "loss": 0.4772,
+ "step": 10231
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0667387077219704e-06,
+ "loss": 0.4798,
+ "step": 10232
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0655211802017052e-06,
+ "loss": 0.4355,
+ "step": 10233
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0643043087924043e-06,
+ "loss": 0.4507,
+ "step": 10234
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0630880935834286e-06,
+ "loss": 0.4636,
+ "step": 10235
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0618725346640902e-06,
+ "loss": 0.4574,
+ "step": 10236
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0606576321236585e-06,
+ "loss": 0.473,
+ "step": 10237
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0594433860513452e-06,
+ "loss": 0.458,
+ "step": 10238
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0582297965363264e-06,
+ "loss": 0.4414,
+ "step": 10239
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0570168636677191e-06,
+ "loss": 0.4564,
+ "step": 10240
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.055804587534598e-06,
+ "loss": 0.4609,
+ "step": 10241
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0545929682259847e-06,
+ "loss": 0.4552,
+ "step": 10242
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0533820058308576e-06,
+ "loss": 0.487,
+ "step": 10243
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0521717004381427e-06,
+ "loss": 0.4707,
+ "step": 10244
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0509620521367225e-06,
+ "loss": 0.4729,
+ "step": 10245
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0497530610154283e-06,
+ "loss": 0.4663,
+ "step": 10246
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.04854472716304e-06,
+ "loss": 0.4829,
+ "step": 10247
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0473370506682968e-06,
+ "loss": 0.4565,
+ "step": 10248
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.046130031619883e-06,
+ "loss": 0.4666,
+ "step": 10249
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.044923670106439e-06,
+ "loss": 0.4489,
+ "step": 10250
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0437179662165508e-06,
+ "loss": 0.4793,
+ "step": 10251
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0425129200387662e-06,
+ "loss": 0.4564,
+ "step": 10252
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0413085316615745e-06,
+ "loss": 0.47,
+ "step": 10253
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0401048011734227e-06,
+ "loss": 0.4469,
+ "step": 10254
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0389017286627078e-06,
+ "loss": 0.4772,
+ "step": 10255
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0376993142177771e-06,
+ "loss": 0.475,
+ "step": 10256
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.036497557926931e-06,
+ "loss": 0.4524,
+ "step": 10257
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.035296459878421e-06,
+ "loss": 0.4645,
+ "step": 10258
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0340960201604544e-06,
+ "loss": 0.4579,
+ "step": 10259
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0328962388611841e-06,
+ "loss": 0.4659,
+ "step": 10260
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0316971160687172e-06,
+ "loss": 0.4552,
+ "step": 10261
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0304986518711124e-06,
+ "loss": 0.452,
+ "step": 10262
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.029300846356379e-06,
+ "loss": 0.4648,
+ "step": 10263
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0281036996124793e-06,
+ "loss": 0.4696,
+ "step": 10264
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.026907211727326e-06,
+ "loss": 0.4558,
+ "step": 10265
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0257113827887865e-06,
+ "loss": 0.4506,
+ "step": 10266
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0245162128846764e-06,
+ "loss": 0.4555,
+ "step": 10267
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.023321702102762e-06,
+ "loss": 0.4706,
+ "step": 10268
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0221278505307665e-06,
+ "loss": 0.4593,
+ "step": 10269
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0209346582563596e-06,
+ "loss": 0.4606,
+ "step": 10270
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0197421253671646e-06,
+ "loss": 0.458,
+ "step": 10271
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.018550251950755e-06,
+ "loss": 0.4643,
+ "step": 10272
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0173590380946596e-06,
+ "loss": 0.497,
+ "step": 10273
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.016168483886356e-06,
+ "loss": 0.4946,
+ "step": 10274
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0149785894132714e-06,
+ "loss": 0.4545,
+ "step": 10275
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0137893547627875e-06,
+ "loss": 0.4669,
+ "step": 10276
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0126007800222347e-06,
+ "loss": 0.4839,
+ "step": 10277
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0114128652789023e-06,
+ "loss": 0.4633,
+ "step": 10278
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0102256106200203e-06,
+ "loss": 0.4627,
+ "step": 10279
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0090390161327801e-06,
+ "loss": 0.4656,
+ "step": 10280
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0078530819043174e-06,
+ "loss": 0.4692,
+ "step": 10281
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.006667808021725e-06,
+ "loss": 0.4646,
+ "step": 10282
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0054831945720411e-06,
+ "loss": 0.4597,
+ "step": 10283
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0042992416422614e-06,
+ "loss": 0.4651,
+ "step": 10284
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.0031159493193277e-06,
+ "loss": 0.4696,
+ "step": 10285
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.001933317690139e-06,
+ "loss": 0.4727,
+ "step": 10286
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 1.000751346841542e-06,
+ "loss": 0.4629,
+ "step": 10287
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.995700368603333e-07,
+ "loss": 0.4629,
+ "step": 10288
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.983893878332674e-07,
+ "loss": 0.4644,
+ "step": 10289
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.972093998470444e-07,
+ "loss": 0.4686,
+ "step": 10290
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.960300729883177e-07,
+ "loss": 0.4609,
+ "step": 10291
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.9485140734369e-07,
+ "loss": 0.4454,
+ "step": 10292
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.936734029997218e-07,
+ "loss": 0.4597,
+ "step": 10293
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.92496060042919e-07,
+ "loss": 0.4802,
+ "step": 10294
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.913193785597396e-07,
+ "loss": 0.4629,
+ "step": 10295
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.90143358636596e-07,
+ "loss": 0.4501,
+ "step": 10296
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.88968000359849e-07,
+ "loss": 0.4537,
+ "step": 10297
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.877933038158105e-07,
+ "loss": 0.464,
+ "step": 10298
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.866192690907472e-07,
+ "loss": 0.4678,
+ "step": 10299
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.85445896270878e-07,
+ "loss": 0.4739,
+ "step": 10300
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.84273185442367e-07,
+ "loss": 0.4806,
+ "step": 10301
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.831011366913335e-07,
+ "loss": 0.4504,
+ "step": 10302
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.819297501038494e-07,
+ "loss": 0.4628,
+ "step": 10303
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.80759025765935e-07,
+ "loss": 0.4659,
+ "step": 10304
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.795889637635636e-07,
+ "loss": 0.4496,
+ "step": 10305
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.78419564182659e-07,
+ "loss": 0.4522,
+ "step": 10306
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.772508271090997e-07,
+ "loss": 0.4757,
+ "step": 10307
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.760827526287108e-07,
+ "loss": 0.4711,
+ "step": 10308
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.749153408272693e-07,
+ "loss": 0.4507,
+ "step": 10309
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.737485917905088e-07,
+ "loss": 0.4604,
+ "step": 10310
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.725825056041094e-07,
+ "loss": 0.4598,
+ "step": 10311
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.714170823537007e-07,
+ "loss": 0.471,
+ "step": 10312
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.702523221248706e-07,
+ "loss": 0.4624,
+ "step": 10313
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.69088225003152e-07,
+ "loss": 0.4548,
+ "step": 10314
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.679247910740331e-07,
+ "loss": 0.4672,
+ "step": 10315
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.667620204229488e-07,
+ "loss": 0.4596,
+ "step": 10316
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.6559991313529e-07,
+ "loss": 0.447,
+ "step": 10317
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.64438469296396e-07,
+ "loss": 0.4531,
+ "step": 10318
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.632776889915595e-07,
+ "loss": 0.4692,
+ "step": 10319
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.621175723060216e-07,
+ "loss": 0.4731,
+ "step": 10320
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.609581193249794e-07,
+ "loss": 0.4477,
+ "step": 10321
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.597993301335773e-07,
+ "loss": 0.48,
+ "step": 10322
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.586412048169114e-07,
+ "loss": 0.4617,
+ "step": 10323
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.574837434600293e-07,
+ "loss": 0.4565,
+ "step": 10324
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.563269461479307e-07,
+ "loss": 0.4485,
+ "step": 10325
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.551708129655635e-07,
+ "loss": 0.4653,
+ "step": 10326
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.54015343997834e-07,
+ "loss": 0.46,
+ "step": 10327
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.528605393295909e-07,
+ "loss": 0.4716,
+ "step": 10328
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.517063990456399e-07,
+ "loss": 0.4637,
+ "step": 10329
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.505529232307376e-07,
+ "loss": 0.4507,
+ "step": 10330
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.494001119695884e-07,
+ "loss": 0.4772,
+ "step": 10331
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.482479653468512e-07,
+ "loss": 0.4558,
+ "step": 10332
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.47096483447133e-07,
+ "loss": 0.4491,
+ "step": 10333
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.459456663549959e-07,
+ "loss": 0.4573,
+ "step": 10334
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.447955141549514e-07,
+ "loss": 0.4429,
+ "step": 10335
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.436460269314607e-07,
+ "loss": 0.4629,
+ "step": 10336
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.424972047689374e-07,
+ "loss": 0.4625,
+ "step": 10337
+ },
+ {
+ "epoch": 0.86,
+ "learning_rate": 9.413490477517462e-07,
+ "loss": 0.4684,
+ "step": 10338
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.402015559642019e-07,
+ "loss": 0.4807,
+ "step": 10339
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.390547294905739e-07,
+ "loss": 0.4669,
+ "step": 10340
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.379085684150779e-07,
+ "loss": 0.4493,
+ "step": 10341
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.367630728218868e-07,
+ "loss": 0.4639,
+ "step": 10342
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.356182427951188e-07,
+ "loss": 0.4678,
+ "step": 10343
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.344740784188445e-07,
+ "loss": 0.4619,
+ "step": 10344
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.333305797770887e-07,
+ "loss": 0.489,
+ "step": 10345
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.321877469538232e-07,
+ "loss": 0.4565,
+ "step": 10346
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.31045580032972e-07,
+ "loss": 0.4754,
+ "step": 10347
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.299040790984137e-07,
+ "loss": 0.4564,
+ "step": 10348
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.287632442339756e-07,
+ "loss": 0.472,
+ "step": 10349
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.276230755234328e-07,
+ "loss": 0.4752,
+ "step": 10350
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.264835730505184e-07,
+ "loss": 0.4529,
+ "step": 10351
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.25344736898911e-07,
+ "loss": 0.4372,
+ "step": 10352
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.242065671522393e-07,
+ "loss": 0.4867,
+ "step": 10353
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.230690638940898e-07,
+ "loss": 0.4552,
+ "step": 10354
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.219322272079955e-07,
+ "loss": 0.47,
+ "step": 10355
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.207960571774388e-07,
+ "loss": 0.459,
+ "step": 10356
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.196605538858571e-07,
+ "loss": 0.4625,
+ "step": 10357
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.185257174166362e-07,
+ "loss": 0.4528,
+ "step": 10358
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.173915478531148e-07,
+ "loss": 0.4446,
+ "step": 10359
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.162580452785775e-07,
+ "loss": 0.477,
+ "step": 10360
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.151252097762675e-07,
+ "loss": 0.4613,
+ "step": 10361
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.139930414293774e-07,
+ "loss": 0.4511,
+ "step": 10362
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.128615403210472e-07,
+ "loss": 0.4492,
+ "step": 10363
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.117307065343683e-07,
+ "loss": 0.4666,
+ "step": 10364
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.106005401523865e-07,
+ "loss": 0.4672,
+ "step": 10365
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.094710412580942e-07,
+ "loss": 0.4787,
+ "step": 10366
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.083422099344375e-07,
+ "loss": 0.4664,
+ "step": 10367
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.072140462643154e-07,
+ "loss": 0.4515,
+ "step": 10368
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.060865503305738e-07,
+ "loss": 0.4508,
+ "step": 10369
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.049597222160111e-07,
+ "loss": 0.4644,
+ "step": 10370
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.038335620033756e-07,
+ "loss": 0.4454,
+ "step": 10371
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.02708069775372e-07,
+ "loss": 0.4649,
+ "step": 10372
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.015832456146489e-07,
+ "loss": 0.4778,
+ "step": 10373
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 9.004590896038068e-07,
+ "loss": 0.4462,
+ "step": 10374
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.99335601825404e-07,
+ "loss": 0.4462,
+ "step": 10375
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.982127823619413e-07,
+ "loss": 0.4594,
+ "step": 10376
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.970906312958749e-07,
+ "loss": 0.4522,
+ "step": 10377
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.959691487096111e-07,
+ "loss": 0.482,
+ "step": 10378
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.948483346855064e-07,
+ "loss": 0.4502,
+ "step": 10379
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.937281893058658e-07,
+ "loss": 0.4623,
+ "step": 10380
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.926087126529548e-07,
+ "loss": 0.4559,
+ "step": 10381
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.914899048089765e-07,
+ "loss": 0.4734,
+ "step": 10382
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.903717658560961e-07,
+ "loss": 0.4638,
+ "step": 10383
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.892542958764238e-07,
+ "loss": 0.4368,
+ "step": 10384
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.881374949520216e-07,
+ "loss": 0.4844,
+ "step": 10385
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.870213631649038e-07,
+ "loss": 0.4673,
+ "step": 10386
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.859059005970305e-07,
+ "loss": 0.4555,
+ "step": 10387
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.847911073303206e-07,
+ "loss": 0.4701,
+ "step": 10388
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.836769834466397e-07,
+ "loss": 0.4677,
+ "step": 10389
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.825635290278034e-07,
+ "loss": 0.4631,
+ "step": 10390
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.814507441555775e-07,
+ "loss": 0.4691,
+ "step": 10391
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.803386289116833e-07,
+ "loss": 0.4743,
+ "step": 10392
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.792271833777888e-07,
+ "loss": 0.4724,
+ "step": 10393
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.78116407635512e-07,
+ "loss": 0.4461,
+ "step": 10394
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.770063017664276e-07,
+ "loss": 0.4705,
+ "step": 10395
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.75896865852055e-07,
+ "loss": 0.4547,
+ "step": 10396
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.747880999738667e-07,
+ "loss": 0.4837,
+ "step": 10397
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.736800042132853e-07,
+ "loss": 0.4696,
+ "step": 10398
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.725725786516858e-07,
+ "loss": 0.4605,
+ "step": 10399
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.714658233703921e-07,
+ "loss": 0.4868,
+ "step": 10400
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.703597384506779e-07,
+ "loss": 0.4542,
+ "step": 10401
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.692543239737706e-07,
+ "loss": 0.4542,
+ "step": 10402
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.681495800208517e-07,
+ "loss": 0.4587,
+ "step": 10403
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.670455066730444e-07,
+ "loss": 0.4659,
+ "step": 10404
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.65942104011428e-07,
+ "loss": 0.474,
+ "step": 10405
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.648393721170323e-07,
+ "loss": 0.4734,
+ "step": 10406
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.63737311070837e-07,
+ "loss": 0.4765,
+ "step": 10407
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.626359209537716e-07,
+ "loss": 0.4577,
+ "step": 10408
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.615352018467204e-07,
+ "loss": 0.4625,
+ "step": 10409
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.604351538305156e-07,
+ "loss": 0.4697,
+ "step": 10410
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.593357769859368e-07,
+ "loss": 0.4622,
+ "step": 10411
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.582370713937193e-07,
+ "loss": 0.4769,
+ "step": 10412
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.571390371345489e-07,
+ "loss": 0.4899,
+ "step": 10413
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.560416742890599e-07,
+ "loss": 0.4746,
+ "step": 10414
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.549449829378354e-07,
+ "loss": 0.4566,
+ "step": 10415
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.538489631614167e-07,
+ "loss": 0.4804,
+ "step": 10416
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.527536150402882e-07,
+ "loss": 0.4592,
+ "step": 10417
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.516589386548879e-07,
+ "loss": 0.4471,
+ "step": 10418
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.505649340856048e-07,
+ "loss": 0.4799,
+ "step": 10419
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.494716014127768e-07,
+ "loss": 0.4877,
+ "step": 10420
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.483789407166932e-07,
+ "loss": 0.4582,
+ "step": 10421
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.472869520775972e-07,
+ "loss": 0.4554,
+ "step": 10422
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.461956355756772e-07,
+ "loss": 0.4487,
+ "step": 10423
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.451049912910769e-07,
+ "loss": 0.4454,
+ "step": 10424
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.440150193038888e-07,
+ "loss": 0.4578,
+ "step": 10425
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.429257196941554e-07,
+ "loss": 0.4786,
+ "step": 10426
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.418370925418695e-07,
+ "loss": 0.4635,
+ "step": 10427
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.407491379269739e-07,
+ "loss": 0.4748,
+ "step": 10428
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.396618559293679e-07,
+ "loss": 0.4652,
+ "step": 10429
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.385752466288933e-07,
+ "loss": 0.4624,
+ "step": 10430
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.374893101053482e-07,
+ "loss": 0.4563,
+ "step": 10431
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.364040464384771e-07,
+ "loss": 0.4677,
+ "step": 10432
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.353194557079791e-07,
+ "loss": 0.4588,
+ "step": 10433
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.34235537993503e-07,
+ "loss": 0.4498,
+ "step": 10434
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.331522933746428e-07,
+ "loss": 0.4734,
+ "step": 10435
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.320697219309526e-07,
+ "loss": 0.4523,
+ "step": 10436
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.309878237419289e-07,
+ "loss": 0.4687,
+ "step": 10437
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.299065988870236e-07,
+ "loss": 0.4675,
+ "step": 10438
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.288260474456367e-07,
+ "loss": 0.4673,
+ "step": 10439
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.277461694971178e-07,
+ "loss": 0.4436,
+ "step": 10440
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.266669651207704e-07,
+ "loss": 0.4659,
+ "step": 10441
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.255884343958453e-07,
+ "loss": 0.4867,
+ "step": 10442
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.245105774015461e-07,
+ "loss": 0.4468,
+ "step": 10443
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.234333942170281e-07,
+ "loss": 0.4678,
+ "step": 10444
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.223568849213925e-07,
+ "loss": 0.4726,
+ "step": 10445
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.212810495936952e-07,
+ "loss": 0.4651,
+ "step": 10446
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.202058883129404e-07,
+ "loss": 0.474,
+ "step": 10447
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.191314011580842e-07,
+ "loss": 0.4809,
+ "step": 10448
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.180575882080288e-07,
+ "loss": 0.4541,
+ "step": 10449
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.169844495416368e-07,
+ "loss": 0.4656,
+ "step": 10450
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.159119852377106e-07,
+ "loss": 0.4456,
+ "step": 10451
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.148401953750096e-07,
+ "loss": 0.4625,
+ "step": 10452
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.137690800322384e-07,
+ "loss": 0.4638,
+ "step": 10453
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.126986392880587e-07,
+ "loss": 0.4811,
+ "step": 10454
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.116288732210787e-07,
+ "loss": 0.4776,
+ "step": 10455
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.105597819098554e-07,
+ "loss": 0.4533,
+ "step": 10456
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.094913654329018e-07,
+ "loss": 0.4689,
+ "step": 10457
+ },
+ {
+ "epoch": 0.87,
+ "learning_rate": 8.08423623868676e-07,
+ "loss": 0.4605,
+ "step": 10458
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.073565572955877e-07,
+ "loss": 0.4652,
+ "step": 10459
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.062901657919998e-07,
+ "loss": 0.4584,
+ "step": 10460
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.052244494362227e-07,
+ "loss": 0.4699,
+ "step": 10461
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.041594083065152e-07,
+ "loss": 0.4525,
+ "step": 10462
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.030950424810946e-07,
+ "loss": 0.476,
+ "step": 10463
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.020313520381206e-07,
+ "loss": 0.4795,
+ "step": 10464
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 8.009683370557075e-07,
+ "loss": 0.4751,
+ "step": 10465
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.999059976119183e-07,
+ "loss": 0.4427,
+ "step": 10466
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.988443337847673e-07,
+ "loss": 0.4616,
+ "step": 10467
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.977833456522166e-07,
+ "loss": 0.4687,
+ "step": 10468
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.967230332921816e-07,
+ "loss": 0.4731,
+ "step": 10469
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.956633967825289e-07,
+ "loss": 0.4715,
+ "step": 10470
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.946044362010718e-07,
+ "loss": 0.4532,
+ "step": 10471
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.935461516255782e-07,
+ "loss": 0.4768,
+ "step": 10472
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.924885431337604e-07,
+ "loss": 0.4527,
+ "step": 10473
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.914316108032882e-07,
+ "loss": 0.4693,
+ "step": 10474
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.903753547117788e-07,
+ "loss": 0.4768,
+ "step": 10475
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.893197749367943e-07,
+ "loss": 0.4678,
+ "step": 10476
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.882648715558583e-07,
+ "loss": 0.4589,
+ "step": 10477
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.872106446464345e-07,
+ "loss": 0.4649,
+ "step": 10478
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.861570942859431e-07,
+ "loss": 0.4652,
+ "step": 10479
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.851042205517512e-07,
+ "loss": 0.4853,
+ "step": 10480
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.840520235211768e-07,
+ "loss": 0.4503,
+ "step": 10481
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.830005032714905e-07,
+ "loss": 0.463,
+ "step": 10482
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.819496598799093e-07,
+ "loss": 0.4523,
+ "step": 10483
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.808994934236058e-07,
+ "loss": 0.4681,
+ "step": 10484
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.798500039796974e-07,
+ "loss": 0.4989,
+ "step": 10485
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.788011916252558e-07,
+ "loss": 0.4629,
+ "step": 10486
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.777530564373015e-07,
+ "loss": 0.4475,
+ "step": 10487
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.767055984928041e-07,
+ "loss": 0.4632,
+ "step": 10488
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.756588178686853e-07,
+ "loss": 0.4704,
+ "step": 10489
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.746127146418148e-07,
+ "loss": 0.4527,
+ "step": 10490
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.735672888890155e-07,
+ "loss": 0.4651,
+ "step": 10491
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.725225406870607e-07,
+ "loss": 0.4569,
+ "step": 10492
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.714784701126687e-07,
+ "loss": 0.464,
+ "step": 10493
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.704350772425129e-07,
+ "loss": 0.4621,
+ "step": 10494
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.693923621532184e-07,
+ "loss": 0.4683,
+ "step": 10495
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.683503249213554e-07,
+ "loss": 0.4905,
+ "step": 10496
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.673089656234456e-07,
+ "loss": 0.4562,
+ "step": 10497
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.662682843359648e-07,
+ "loss": 0.4489,
+ "step": 10498
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.652282811353362e-07,
+ "loss": 0.4638,
+ "step": 10499
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.641889560979321e-07,
+ "loss": 0.4682,
+ "step": 10500
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.631503093000758e-07,
+ "loss": 0.4702,
+ "step": 10501
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.621123408180419e-07,
+ "loss": 0.4686,
+ "step": 10502
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.61075050728054e-07,
+ "loss": 0.452,
+ "step": 10503
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.600384391062865e-07,
+ "loss": 0.4584,
+ "step": 10504
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.590025060288642e-07,
+ "loss": 0.4783,
+ "step": 10505
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.579672515718628e-07,
+ "loss": 0.4468,
+ "step": 10506
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.569326758113049e-07,
+ "loss": 0.4802,
+ "step": 10507
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.558987788231675e-07,
+ "loss": 0.4594,
+ "step": 10508
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.548655606833755e-07,
+ "loss": 0.4826,
+ "step": 10509
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.538330214678002e-07,
+ "loss": 0.4664,
+ "step": 10510
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.528011612522723e-07,
+ "loss": 0.4502,
+ "step": 10511
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.517699801125655e-07,
+ "loss": 0.45,
+ "step": 10512
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.507394781244038e-07,
+ "loss": 0.4798,
+ "step": 10513
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.497096553634653e-07,
+ "loss": 0.4694,
+ "step": 10514
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.48680511905373e-07,
+ "loss": 0.4539,
+ "step": 10515
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.476520478257065e-07,
+ "loss": 0.466,
+ "step": 10516
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.466242631999887e-07,
+ "loss": 0.4647,
+ "step": 10517
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.455971581036991e-07,
+ "loss": 0.4704,
+ "step": 10518
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.44570732612262e-07,
+ "loss": 0.4576,
+ "step": 10519
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.435449868010535e-07,
+ "loss": 0.4648,
+ "step": 10520
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.425199207454014e-07,
+ "loss": 0.4485,
+ "step": 10521
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.41495534520581e-07,
+ "loss": 0.4636,
+ "step": 10522
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.404718282018197e-07,
+ "loss": 0.4768,
+ "step": 10523
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.394488018642931e-07,
+ "loss": 0.4482,
+ "step": 10524
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.3842645558313e-07,
+ "loss": 0.4373,
+ "step": 10525
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.374047894334047e-07,
+ "loss": 0.4618,
+ "step": 10526
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.363838034901471e-07,
+ "loss": 0.4681,
+ "step": 10527
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.35363497828333e-07,
+ "loss": 0.4577,
+ "step": 10528
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.343438725228891e-07,
+ "loss": 0.4653,
+ "step": 10529
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.33324927648692e-07,
+ "loss": 0.4989,
+ "step": 10530
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.323066632805676e-07,
+ "loss": 0.4368,
+ "step": 10531
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.312890794932969e-07,
+ "loss": 0.4771,
+ "step": 10532
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.302721763616039e-07,
+ "loss": 0.4751,
+ "step": 10533
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.292559539601674e-07,
+ "loss": 0.4537,
+ "step": 10534
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.28240412363611e-07,
+ "loss": 0.4543,
+ "step": 10535
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.272255516465176e-07,
+ "loss": 0.4839,
+ "step": 10536
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.262113718834086e-07,
+ "loss": 0.4525,
+ "step": 10537
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.251978731487664e-07,
+ "loss": 0.4823,
+ "step": 10538
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.241850555170149e-07,
+ "loss": 0.4638,
+ "step": 10539
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.231729190625314e-07,
+ "loss": 0.4807,
+ "step": 10540
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.221614638596441e-07,
+ "loss": 0.4729,
+ "step": 10541
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.211506899826304e-07,
+ "loss": 0.4802,
+ "step": 10542
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.201405975057152e-07,
+ "loss": 0.4365,
+ "step": 10543
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.191311865030748e-07,
+ "loss": 0.4644,
+ "step": 10544
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.18122457048841e-07,
+ "loss": 0.4555,
+ "step": 10545
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.171144092170845e-07,
+ "loss": 0.4495,
+ "step": 10546
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.161070430818385e-07,
+ "loss": 0.4348,
+ "step": 10547
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.151003587170757e-07,
+ "loss": 0.4765,
+ "step": 10548
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.14094356196724e-07,
+ "loss": 0.4557,
+ "step": 10549
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.130890355946596e-07,
+ "loss": 0.4436,
+ "step": 10550
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.12084396984708e-07,
+ "loss": 0.4619,
+ "step": 10551
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.11080440440648e-07,
+ "loss": 0.4572,
+ "step": 10552
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.100771660362061e-07,
+ "loss": 0.464,
+ "step": 10553
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.090745738450566e-07,
+ "loss": 0.465,
+ "step": 10554
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.080726639408264e-07,
+ "loss": 0.4505,
+ "step": 10555
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.070714363970899e-07,
+ "loss": 0.458,
+ "step": 10556
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.060708912873771e-07,
+ "loss": 0.4661,
+ "step": 10557
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.050710286851603e-07,
+ "loss": 0.4561,
+ "step": 10558
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.040718486638676e-07,
+ "loss": 0.4619,
+ "step": 10559
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.030733512968735e-07,
+ "loss": 0.4623,
+ "step": 10560
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.020755366575038e-07,
+ "loss": 0.4636,
+ "step": 10561
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.010784048190344e-07,
+ "loss": 0.4576,
+ "step": 10562
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 7.000819558546901e-07,
+ "loss": 0.4482,
+ "step": 10563
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.990861898376444e-07,
+ "loss": 0.4662,
+ "step": 10564
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.980911068410224e-07,
+ "loss": 0.4577,
+ "step": 10565
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.97096706937902e-07,
+ "loss": 0.4521,
+ "step": 10566
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.961029902013039e-07,
+ "loss": 0.452,
+ "step": 10567
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.951099567042052e-07,
+ "loss": 0.4763,
+ "step": 10568
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.941176065195299e-07,
+ "loss": 0.4561,
+ "step": 10569
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.931259397201517e-07,
+ "loss": 0.4594,
+ "step": 10570
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.921349563788949e-07,
+ "loss": 0.4663,
+ "step": 10571
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.911446565685298e-07,
+ "loss": 0.4581,
+ "step": 10572
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.901550403617852e-07,
+ "loss": 0.4803,
+ "step": 10573
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.891661078313317e-07,
+ "loss": 0.4621,
+ "step": 10574
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.881778590497923e-07,
+ "loss": 0.4698,
+ "step": 10575
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.87190294089738e-07,
+ "loss": 0.4748,
+ "step": 10576
+ },
+ {
+ "epoch": 0.88,
+ "learning_rate": 6.86203413023696e-07,
+ "loss": 0.453,
+ "step": 10577
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.852172159241343e-07,
+ "loss": 0.4714,
+ "step": 10578
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.842317028634793e-07,
+ "loss": 0.4762,
+ "step": 10579
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.832468739141007e-07,
+ "loss": 0.4559,
+ "step": 10580
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.822627291483197e-07,
+ "loss": 0.4699,
+ "step": 10581
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.812792686384095e-07,
+ "loss": 0.4521,
+ "step": 10582
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.802964924565891e-07,
+ "loss": 0.4515,
+ "step": 10583
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.793144006750318e-07,
+ "loss": 0.4689,
+ "step": 10584
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.783329933658555e-07,
+ "loss": 0.4531,
+ "step": 10585
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.773522706011337e-07,
+ "loss": 0.4877,
+ "step": 10586
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.763722324528843e-07,
+ "loss": 0.4599,
+ "step": 10587
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.753928789930797e-07,
+ "loss": 0.469,
+ "step": 10588
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.74414210293638e-07,
+ "loss": 0.4548,
+ "step": 10589
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.734362264264283e-07,
+ "loss": 0.4717,
+ "step": 10590
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.724589274632698e-07,
+ "loss": 0.4463,
+ "step": 10591
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.714823134759307e-07,
+ "loss": 0.4454,
+ "step": 10592
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.705063845361315e-07,
+ "loss": 0.4723,
+ "step": 10593
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.695311407155391e-07,
+ "loss": 0.4621,
+ "step": 10594
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.68556582085772e-07,
+ "loss": 0.4683,
+ "step": 10595
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.675827087183961e-07,
+ "loss": 0.4772,
+ "step": 10596
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.666095206849288e-07,
+ "loss": 0.4646,
+ "step": 10597
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.656370180568395e-07,
+ "loss": 0.4574,
+ "step": 10598
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.646652009055409e-07,
+ "loss": 0.4854,
+ "step": 10599
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.63694069302403e-07,
+ "loss": 0.4795,
+ "step": 10600
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.627236233187407e-07,
+ "loss": 0.4678,
+ "step": 10601
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.61753863025818e-07,
+ "loss": 0.4546,
+ "step": 10602
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.607847884948515e-07,
+ "loss": 0.4514,
+ "step": 10603
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.598163997970053e-07,
+ "loss": 0.4607,
+ "step": 10604
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.588486970033936e-07,
+ "loss": 0.467,
+ "step": 10605
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.578816801850796e-07,
+ "loss": 0.461,
+ "step": 10606
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.569153494130798e-07,
+ "loss": 0.4654,
+ "step": 10607
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.55949704758354e-07,
+ "loss": 0.485,
+ "step": 10608
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.549847462918191e-07,
+ "loss": 0.4681,
+ "step": 10609
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.540204740843348e-07,
+ "loss": 0.4647,
+ "step": 10610
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.530568882067145e-07,
+ "loss": 0.4694,
+ "step": 10611
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.520939887297184e-07,
+ "loss": 0.4592,
+ "step": 10612
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.511317757240598e-07,
+ "loss": 0.4805,
+ "step": 10613
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.50170249260399e-07,
+ "loss": 0.4699,
+ "step": 10614
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.492094094093459e-07,
+ "loss": 0.4552,
+ "step": 10615
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.482492562414621e-07,
+ "loss": 0.4495,
+ "step": 10616
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.472897898272534e-07,
+ "loss": 0.4724,
+ "step": 10617
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.463310102371834e-07,
+ "loss": 0.4603,
+ "step": 10618
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.453729175416579e-07,
+ "loss": 0.4423,
+ "step": 10619
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.444155118110373e-07,
+ "loss": 0.4421,
+ "step": 10620
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.434587931156299e-07,
+ "loss": 0.4656,
+ "step": 10621
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.425027615256907e-07,
+ "loss": 0.4639,
+ "step": 10622
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.415474171114288e-07,
+ "loss": 0.4575,
+ "step": 10623
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.405927599429995e-07,
+ "loss": 0.4592,
+ "step": 10624
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.396387900905099e-07,
+ "loss": 0.4616,
+ "step": 10625
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.386855076240117e-07,
+ "loss": 0.4553,
+ "step": 10626
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.377329126135168e-07,
+ "loss": 0.4603,
+ "step": 10627
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.367810051289746e-07,
+ "loss": 0.4622,
+ "step": 10628
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.358297852402894e-07,
+ "loss": 0.4787,
+ "step": 10629
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.348792530173187e-07,
+ "loss": 0.4648,
+ "step": 10630
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.339294085298631e-07,
+ "loss": 0.4586,
+ "step": 10631
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.329802518476746e-07,
+ "loss": 0.464,
+ "step": 10632
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.320317830404554e-07,
+ "loss": 0.4964,
+ "step": 10633
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.310840021778586e-07,
+ "loss": 0.4679,
+ "step": 10634
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.30136909329484e-07,
+ "loss": 0.4348,
+ "step": 10635
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.291905045648839e-07,
+ "loss": 0.4809,
+ "step": 10636
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.282447879535558e-07,
+ "loss": 0.4575,
+ "step": 10637
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.272997595649499e-07,
+ "loss": 0.4739,
+ "step": 10638
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.263554194684662e-07,
+ "loss": 0.4522,
+ "step": 10639
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.254117677334514e-07,
+ "loss": 0.4417,
+ "step": 10640
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.244688044292058e-07,
+ "loss": 0.4564,
+ "step": 10641
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.23526529624976e-07,
+ "loss": 0.4505,
+ "step": 10642
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.225849433899578e-07,
+ "loss": 0.4596,
+ "step": 10643
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.216440457932981e-07,
+ "loss": 0.4338,
+ "step": 10644
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.207038369040918e-07,
+ "loss": 0.4676,
+ "step": 10645
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.197643167913847e-07,
+ "loss": 0.4753,
+ "step": 10646
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.188254855241693e-07,
+ "loss": 0.4584,
+ "step": 10647
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.178873431713928e-07,
+ "loss": 0.4765,
+ "step": 10648
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.169498898019443e-07,
+ "loss": 0.4592,
+ "step": 10649
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.160131254846702e-07,
+ "loss": 0.4643,
+ "step": 10650
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.150770502883618e-07,
+ "loss": 0.4684,
+ "step": 10651
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.141416642817599e-07,
+ "loss": 0.4886,
+ "step": 10652
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.13206967533555e-07,
+ "loss": 0.4641,
+ "step": 10653
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.122729601123878e-07,
+ "loss": 0.4639,
+ "step": 10654
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.113396420868489e-07,
+ "loss": 0.4511,
+ "step": 10655
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.104070135254758e-07,
+ "loss": 0.4748,
+ "step": 10656
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.09475074496757e-07,
+ "loss": 0.4607,
+ "step": 10657
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.085438250691311e-07,
+ "loss": 0.4689,
+ "step": 10658
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.076132653109834e-07,
+ "loss": 0.4497,
+ "step": 10659
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.066833952906515e-07,
+ "loss": 0.4615,
+ "step": 10660
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.057542150764218e-07,
+ "loss": 0.4654,
+ "step": 10661
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.048257247365297e-07,
+ "loss": 0.4703,
+ "step": 10662
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.038979243391597e-07,
+ "loss": 0.4581,
+ "step": 10663
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.029708139524438e-07,
+ "loss": 0.4653,
+ "step": 10664
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.020443936444664e-07,
+ "loss": 0.4835,
+ "step": 10665
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.0111866348326e-07,
+ "loss": 0.4538,
+ "step": 10666
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 6.001936235368044e-07,
+ "loss": 0.4771,
+ "step": 10667
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.992692738730332e-07,
+ "loss": 0.4604,
+ "step": 10668
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.983456145598266e-07,
+ "loss": 0.4592,
+ "step": 10669
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.974226456650123e-07,
+ "loss": 0.4773,
+ "step": 10670
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.965003672563719e-07,
+ "loss": 0.472,
+ "step": 10671
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.955787794016321e-07,
+ "loss": 0.4521,
+ "step": 10672
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.946578821684713e-07,
+ "loss": 0.4492,
+ "step": 10673
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.937376756245139e-07,
+ "loss": 0.4726,
+ "step": 10674
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.928181598373395e-07,
+ "loss": 0.4556,
+ "step": 10675
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.918993348744728e-07,
+ "loss": 0.4523,
+ "step": 10676
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.909812008033866e-07,
+ "loss": 0.461,
+ "step": 10677
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.900637576915069e-07,
+ "loss": 0.4729,
+ "step": 10678
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.891470056062043e-07,
+ "loss": 0.4656,
+ "step": 10679
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.882309446148038e-07,
+ "loss": 0.4639,
+ "step": 10680
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.87315574784576e-07,
+ "loss": 0.4651,
+ "step": 10681
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.864008961827428e-07,
+ "loss": 0.4665,
+ "step": 10682
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.854869088764737e-07,
+ "loss": 0.4629,
+ "step": 10683
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.845736129328883e-07,
+ "loss": 0.4569,
+ "step": 10684
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.836610084190541e-07,
+ "loss": 0.455,
+ "step": 10685
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.82749095401991e-07,
+ "loss": 0.4809,
+ "step": 10686
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.81837873948663e-07,
+ "loss": 0.4639,
+ "step": 10687
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.809273441259899e-07,
+ "loss": 0.4451,
+ "step": 10688
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.800175060008362e-07,
+ "loss": 0.4691,
+ "step": 10689
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.791083596400148e-07,
+ "loss": 0.467,
+ "step": 10690
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.781999051102927e-07,
+ "loss": 0.463,
+ "step": 10691
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.772921424783806e-07,
+ "loss": 0.4638,
+ "step": 10692
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.763850718109421e-07,
+ "loss": 0.475,
+ "step": 10693
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.754786931745859e-07,
+ "loss": 0.4652,
+ "step": 10694
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.745730066358779e-07,
+ "loss": 0.4622,
+ "step": 10695
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.736680122613237e-07,
+ "loss": 0.4608,
+ "step": 10696
+ },
+ {
+ "epoch": 0.89,
+ "learning_rate": 5.727637101173844e-07,
+ "loss": 0.4586,
+ "step": 10697
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.718601002704671e-07,
+ "loss": 0.442,
+ "step": 10698
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.709571827869287e-07,
+ "loss": 0.4706,
+ "step": 10699
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.70054957733076e-07,
+ "loss": 0.4871,
+ "step": 10700
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.691534251751652e-07,
+ "loss": 0.4701,
+ "step": 10701
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.682525851794019e-07,
+ "loss": 0.4756,
+ "step": 10702
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.673524378119388e-07,
+ "loss": 0.4662,
+ "step": 10703
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.664529831388799e-07,
+ "loss": 0.4683,
+ "step": 10704
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.655542212262766e-07,
+ "loss": 0.4452,
+ "step": 10705
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.646561521401317e-07,
+ "loss": 0.4809,
+ "step": 10706
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.637587759463925e-07,
+ "loss": 0.4604,
+ "step": 10707
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.628620927109607e-07,
+ "loss": 0.4794,
+ "step": 10708
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.619661024996848e-07,
+ "loss": 0.4603,
+ "step": 10709
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.610708053783642e-07,
+ "loss": 0.4669,
+ "step": 10710
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.60176201412741e-07,
+ "loss": 0.471,
+ "step": 10711
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.59282290668517e-07,
+ "loss": 0.4629,
+ "step": 10712
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.58389073211335e-07,
+ "loss": 0.4513,
+ "step": 10713
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.574965491067874e-07,
+ "loss": 0.5152,
+ "step": 10714
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.566047184204182e-07,
+ "loss": 0.4614,
+ "step": 10715
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.557135812177228e-07,
+ "loss": 0.4401,
+ "step": 10716
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.548231375641389e-07,
+ "loss": 0.4655,
+ "step": 10717
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.539333875250596e-07,
+ "loss": 0.4761,
+ "step": 10718
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.530443311658218e-07,
+ "loss": 0.4628,
+ "step": 10719
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.521559685517153e-07,
+ "loss": 0.4645,
+ "step": 10720
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.51268299747978e-07,
+ "loss": 0.4947,
+ "step": 10721
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.503813248197965e-07,
+ "loss": 0.4574,
+ "step": 10722
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.494950438323077e-07,
+ "loss": 0.4685,
+ "step": 10723
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.48609456850594e-07,
+ "loss": 0.4751,
+ "step": 10724
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.477245639396922e-07,
+ "loss": 0.4682,
+ "step": 10725
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.468403651645826e-07,
+ "loss": 0.4474,
+ "step": 10726
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.459568605901977e-07,
+ "loss": 0.4704,
+ "step": 10727
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.450740502814178e-07,
+ "loss": 0.4847,
+ "step": 10728
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.441919343030744e-07,
+ "loss": 0.4695,
+ "step": 10729
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.433105127199467e-07,
+ "loss": 0.4646,
+ "step": 10730
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.424297855967597e-07,
+ "loss": 0.4771,
+ "step": 10731
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.415497529981928e-07,
+ "loss": 0.4748,
+ "step": 10732
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.40670414988872e-07,
+ "loss": 0.4688,
+ "step": 10733
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.397917716333723e-07,
+ "loss": 0.4381,
+ "step": 10734
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.389138229962155e-07,
+ "loss": 0.4684,
+ "step": 10735
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.380365691418765e-07,
+ "loss": 0.4519,
+ "step": 10736
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.371600101347763e-07,
+ "loss": 0.4714,
+ "step": 10737
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.362841460392875e-07,
+ "loss": 0.4653,
+ "step": 10738
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.354089769197268e-07,
+ "loss": 0.4803,
+ "step": 10739
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.345345028403659e-07,
+ "loss": 0.4518,
+ "step": 10740
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.33660723865419e-07,
+ "loss": 0.4649,
+ "step": 10741
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.32787640059057e-07,
+ "loss": 0.461,
+ "step": 10742
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.31915251485392e-07,
+ "loss": 0.4962,
+ "step": 10743
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.310435582084917e-07,
+ "loss": 0.4649,
+ "step": 10744
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.301725602923691e-07,
+ "loss": 0.4624,
+ "step": 10745
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.293022578009843e-07,
+ "loss": 0.467,
+ "step": 10746
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.284326507982507e-07,
+ "loss": 0.4678,
+ "step": 10747
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.275637393480282e-07,
+ "loss": 0.4608,
+ "step": 10748
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.266955235141235e-07,
+ "loss": 0.4783,
+ "step": 10749
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.258280033602992e-07,
+ "loss": 0.4863,
+ "step": 10750
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.249611789502607e-07,
+ "loss": 0.4491,
+ "step": 10751
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.240950503476616e-07,
+ "loss": 0.4695,
+ "step": 10752
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.232296176161101e-07,
+ "loss": 0.4812,
+ "step": 10753
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.223648808191584e-07,
+ "loss": 0.4459,
+ "step": 10754
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.215008400203103e-07,
+ "loss": 0.4771,
+ "step": 10755
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.20637495283014e-07,
+ "loss": 0.4675,
+ "step": 10756
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.197748466706742e-07,
+ "loss": 0.4509,
+ "step": 10757
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.189128942466393e-07,
+ "loss": 0.4566,
+ "step": 10758
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.180516380742051e-07,
+ "loss": 0.4632,
+ "step": 10759
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.171910782166212e-07,
+ "loss": 0.4563,
+ "step": 10760
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.163312147370824e-07,
+ "loss": 0.4507,
+ "step": 10761
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.154720476987329e-07,
+ "loss": 0.4547,
+ "step": 10762
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.146135771646655e-07,
+ "loss": 0.4596,
+ "step": 10763
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.137558031979273e-07,
+ "loss": 0.4456,
+ "step": 10764
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.128987258615059e-07,
+ "loss": 0.4591,
+ "step": 10765
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.12042345218342e-07,
+ "loss": 0.4841,
+ "step": 10766
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.111866613313255e-07,
+ "loss": 0.4637,
+ "step": 10767
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.103316742632935e-07,
+ "loss": 0.4692,
+ "step": 10768
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.094773840770306e-07,
+ "loss": 0.4977,
+ "step": 10769
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.086237908352776e-07,
+ "loss": 0.4727,
+ "step": 10770
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.077708946007143e-07,
+ "loss": 0.4818,
+ "step": 10771
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.069186954359761e-07,
+ "loss": 0.4501,
+ "step": 10772
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.060671934036421e-07,
+ "loss": 0.4501,
+ "step": 10773
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.052163885662476e-07,
+ "loss": 0.4629,
+ "step": 10774
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.043662809862692e-07,
+ "loss": 0.4542,
+ "step": 10775
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.03516870726134e-07,
+ "loss": 0.4559,
+ "step": 10776
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.026681578482229e-07,
+ "loss": 0.4821,
+ "step": 10777
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.018201424148606e-07,
+ "loss": 0.4764,
+ "step": 10778
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.009728244883205e-07,
+ "loss": 0.4775,
+ "step": 10779
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 5.001262041308263e-07,
+ "loss": 0.4691,
+ "step": 10780
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.992802814045505e-07,
+ "loss": 0.4439,
+ "step": 10781
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.984350563716145e-07,
+ "loss": 0.4732,
+ "step": 10782
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.975905290940874e-07,
+ "loss": 0.4788,
+ "step": 10783
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.967466996339887e-07,
+ "loss": 0.471,
+ "step": 10784
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.959035680532854e-07,
+ "loss": 0.4454,
+ "step": 10785
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.950611344138945e-07,
+ "loss": 0.4511,
+ "step": 10786
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.9421939877768e-07,
+ "loss": 0.4767,
+ "step": 10787
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.933783612064546e-07,
+ "loss": 0.4464,
+ "step": 10788
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.925380217619813e-07,
+ "loss": 0.4537,
+ "step": 10789
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.916983805059705e-07,
+ "loss": 0.4717,
+ "step": 10790
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.90859437500083e-07,
+ "loss": 0.4549,
+ "step": 10791
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.900211928059284e-07,
+ "loss": 0.4547,
+ "step": 10792
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.891836464850596e-07,
+ "loss": 0.4571,
+ "step": 10793
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.883467985989876e-07,
+ "loss": 0.4762,
+ "step": 10794
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.875106492091642e-07,
+ "loss": 0.4692,
+ "step": 10795
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.866751983769935e-07,
+ "loss": 0.4702,
+ "step": 10796
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.858404461638266e-07,
+ "loss": 0.4569,
+ "step": 10797
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.850063926309657e-07,
+ "loss": 0.4488,
+ "step": 10798
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.841730378396592e-07,
+ "loss": 0.4586,
+ "step": 10799
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.833403818511062e-07,
+ "loss": 0.4559,
+ "step": 10800
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.825084247264522e-07,
+ "loss": 0.4566,
+ "step": 10801
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.816771665267939e-07,
+ "loss": 0.4449,
+ "step": 10802
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.808466073131735e-07,
+ "loss": 0.4585,
+ "step": 10803
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.800167471465844e-07,
+ "loss": 0.4537,
+ "step": 10804
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.791875860879703e-07,
+ "loss": 0.4585,
+ "step": 10805
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.783591241982199e-07,
+ "loss": 0.4525,
+ "step": 10806
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.775313615381716e-07,
+ "loss": 0.4708,
+ "step": 10807
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.767042981686143e-07,
+ "loss": 0.4424,
+ "step": 10808
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.758779341502817e-07,
+ "loss": 0.47,
+ "step": 10809
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.750522695438597e-07,
+ "loss": 0.453,
+ "step": 10810
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.742273044099821e-07,
+ "loss": 0.4558,
+ "step": 10811
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.7340303880923145e-07,
+ "loss": 0.4708,
+ "step": 10812
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.7257947280213713e-07,
+ "loss": 0.4453,
+ "step": 10813
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.7175660644917745e-07,
+ "loss": 0.4709,
+ "step": 10814
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.709344398107829e-07,
+ "loss": 0.4792,
+ "step": 10815
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.701129729473286e-07,
+ "loss": 0.4693,
+ "step": 10816
+ },
+ {
+ "epoch": 0.9,
+ "learning_rate": 4.6929220591913847e-07,
+ "loss": 0.4548,
+ "step": 10817
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6847213878648876e-07,
+ "loss": 0.4827,
+ "step": 10818
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6765277160960133e-07,
+ "loss": 0.4751,
+ "step": 10819
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6683410444864573e-07,
+ "loss": 0.4529,
+ "step": 10820
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6601613736374173e-07,
+ "loss": 0.4748,
+ "step": 10821
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6519887041495905e-07,
+ "loss": 0.4607,
+ "step": 10822
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6438230366231075e-07,
+ "loss": 0.4451,
+ "step": 10823
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6356643716576557e-07,
+ "loss": 0.4693,
+ "step": 10824
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.627512709852355e-07,
+ "loss": 0.4662,
+ "step": 10825
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.61936805180585e-07,
+ "loss": 0.4448,
+ "step": 10826
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.611230398116229e-07,
+ "loss": 0.47,
+ "step": 10827
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.6030997493811126e-07,
+ "loss": 0.4645,
+ "step": 10828
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.594976106197546e-07,
+ "loss": 0.435,
+ "step": 10829
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5868594691621304e-07,
+ "loss": 0.4691,
+ "step": 10830
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5787498388708774e-07,
+ "loss": 0.4661,
+ "step": 10831
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.570647215919366e-07,
+ "loss": 0.4651,
+ "step": 10832
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5625516009026095e-07,
+ "loss": 0.4573,
+ "step": 10833
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5544629944150876e-07,
+ "loss": 0.4668,
+ "step": 10834
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5463813970508364e-07,
+ "loss": 0.461,
+ "step": 10835
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5383068094033036e-07,
+ "loss": 0.4437,
+ "step": 10836
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.53023923206547e-07,
+ "loss": 0.4601,
+ "step": 10837
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5221786656297727e-07,
+ "loss": 0.4662,
+ "step": 10838
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.51412511068815e-07,
+ "loss": 0.4571,
+ "step": 10839
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.5060785678320397e-07,
+ "loss": 0.4747,
+ "step": 10840
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.498039037652313e-07,
+ "loss": 0.4635,
+ "step": 10841
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.490006520739387e-07,
+ "loss": 0.4445,
+ "step": 10842
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4819810176831235e-07,
+ "loss": 0.4579,
+ "step": 10843
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.473962529072873e-07,
+ "loss": 0.4499,
+ "step": 10844
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.465951055497497e-07,
+ "loss": 0.4692,
+ "step": 10845
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4579465975453264e-07,
+ "loss": 0.4776,
+ "step": 10846
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4499491558041673e-07,
+ "loss": 0.4795,
+ "step": 10847
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4419587308613285e-07,
+ "loss": 0.4559,
+ "step": 10848
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.433975323303574e-07,
+ "loss": 0.4781,
+ "step": 10849
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.42599893371719e-07,
+ "loss": 0.4636,
+ "step": 10850
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.418029562687898e-07,
+ "loss": 0.462,
+ "step": 10851
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4100672108009837e-07,
+ "loss": 0.4626,
+ "step": 10852
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.4021118786411465e-07,
+ "loss": 0.4657,
+ "step": 10853
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3941635667925866e-07,
+ "loss": 0.4566,
+ "step": 10854
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3862222758389806e-07,
+ "loss": 0.4768,
+ "step": 10855
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3782880063635403e-07,
+ "loss": 0.4521,
+ "step": 10856
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3703607589489105e-07,
+ "loss": 0.471,
+ "step": 10857
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.362440534177226e-07,
+ "loss": 0.4468,
+ "step": 10858
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3545273326301205e-07,
+ "loss": 0.4578,
+ "step": 10859
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3466211548887195e-07,
+ "loss": 0.4488,
+ "step": 10860
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.338722001533602e-07,
+ "loss": 0.4784,
+ "step": 10861
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3308298731448596e-07,
+ "loss": 0.4639,
+ "step": 10862
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.322944770302051e-07,
+ "loss": 0.4591,
+ "step": 10863
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.3150666935842243e-07,
+ "loss": 0.4511,
+ "step": 10864
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.307195643569917e-07,
+ "loss": 0.459,
+ "step": 10865
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.299331620837133e-07,
+ "loss": 0.4785,
+ "step": 10866
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.29147462596341e-07,
+ "loss": 0.4438,
+ "step": 10867
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.283624659525698e-07,
+ "loss": 0.465,
+ "step": 10868
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2757817221004803e-07,
+ "loss": 0.4592,
+ "step": 10869
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.267945814263708e-07,
+ "loss": 0.4657,
+ "step": 10870
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2601169365908077e-07,
+ "loss": 0.4765,
+ "step": 10871
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2522950896566994e-07,
+ "loss": 0.4664,
+ "step": 10872
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2444802740358114e-07,
+ "loss": 0.4634,
+ "step": 10873
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2366724903020076e-07,
+ "loss": 0.4695,
+ "step": 10874
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2288717390286614e-07,
+ "loss": 0.4691,
+ "step": 10875
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2210780207886383e-07,
+ "loss": 0.4936,
+ "step": 10876
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.2132913361542683e-07,
+ "loss": 0.4619,
+ "step": 10877
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.205511685697372e-07,
+ "loss": 0.4653,
+ "step": 10878
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1977390699892706e-07,
+ "loss": 0.4641,
+ "step": 10879
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1899734896007404e-07,
+ "loss": 0.4697,
+ "step": 10880
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1822149451020475e-07,
+ "loss": 0.4413,
+ "step": 10881
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1744634370629587e-07,
+ "loss": 0.4594,
+ "step": 10882
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.166718966052696e-07,
+ "loss": 0.4503,
+ "step": 10883
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.158981532640005e-07,
+ "loss": 0.4772,
+ "step": 10884
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1512511373930533e-07,
+ "loss": 0.4692,
+ "step": 10885
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.143527780879575e-07,
+ "loss": 0.4666,
+ "step": 10886
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1358114636667056e-07,
+ "loss": 0.4712,
+ "step": 10887
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.128102186321126e-07,
+ "loss": 0.4737,
+ "step": 10888
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1203999494089596e-07,
+ "loss": 0.45,
+ "step": 10889
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.112704753495822e-07,
+ "loss": 0.4695,
+ "step": 10890
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.1050165991468273e-07,
+ "loss": 0.4741,
+ "step": 10891
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.097335486926546e-07,
+ "loss": 0.4438,
+ "step": 10892
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.08966141739906e-07,
+ "loss": 0.4623,
+ "step": 10893
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.08199439112793e-07,
+ "loss": 0.4615,
+ "step": 10894
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0743344086761725e-07,
+ "loss": 0.4557,
+ "step": 10895
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.066681470606304e-07,
+ "loss": 0.482,
+ "step": 10896
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0590355774803416e-07,
+ "loss": 0.4708,
+ "step": 10897
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.051396729859758e-07,
+ "loss": 0.4756,
+ "step": 10898
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.043764928305505e-07,
+ "loss": 0.466,
+ "step": 10899
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.036140173378045e-07,
+ "loss": 0.4491,
+ "step": 10900
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.028522465637319e-07,
+ "loss": 0.4952,
+ "step": 10901
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0209118056427356e-07,
+ "loss": 0.4506,
+ "step": 10902
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.013308193953169e-07,
+ "loss": 0.4513,
+ "step": 10903
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 4.0057116311270073e-07,
+ "loss": 0.4536,
+ "step": 10904
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.998122117722125e-07,
+ "loss": 0.4479,
+ "step": 10905
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.990539654295833e-07,
+ "loss": 0.4539,
+ "step": 10906
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.982964241404974e-07,
+ "loss": 0.4578,
+ "step": 10907
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.975395879605881e-07,
+ "loss": 0.4572,
+ "step": 10908
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.96783456945431e-07,
+ "loss": 0.4333,
+ "step": 10909
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.960280311505538e-07,
+ "loss": 0.4491,
+ "step": 10910
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9527331063143215e-07,
+ "loss": 0.4693,
+ "step": 10911
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9451929544348956e-07,
+ "loss": 0.4599,
+ "step": 10912
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9376598564209614e-07,
+ "loss": 0.4722,
+ "step": 10913
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9301338128257536e-07,
+ "loss": 0.4704,
+ "step": 10914
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.922614824201931e-07,
+ "loss": 0.4599,
+ "step": 10915
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.915102891101652e-07,
+ "loss": 0.4563,
+ "step": 10916
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.9075980140765637e-07,
+ "loss": 0.4605,
+ "step": 10917
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.900100193677814e-07,
+ "loss": 0.4588,
+ "step": 10918
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.892609430455985e-07,
+ "loss": 0.4697,
+ "step": 10919
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.885125724961192e-07,
+ "loss": 0.4797,
+ "step": 10920
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.877649077742984e-07,
+ "loss": 0.4523,
+ "step": 10921
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8701794893504343e-07,
+ "loss": 0.4725,
+ "step": 10922
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.862716960332058e-07,
+ "loss": 0.4492,
+ "step": 10923
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8552614912358956e-07,
+ "loss": 0.435,
+ "step": 10924
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8478130826094307e-07,
+ "loss": 0.4606,
+ "step": 10925
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8403717349996263e-07,
+ "loss": 0.4684,
+ "step": 10926
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.832937448952978e-07,
+ "loss": 0.4579,
+ "step": 10927
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8255102250154054e-07,
+ "loss": 0.4772,
+ "step": 10928
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.81809006373236e-07,
+ "loss": 0.4719,
+ "step": 10929
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.8106769656487184e-07,
+ "loss": 0.4419,
+ "step": 10930
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.803270931308889e-07,
+ "loss": 0.4684,
+ "step": 10931
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.795871961256725e-07,
+ "loss": 0.4569,
+ "step": 10932
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.788480056035571e-07,
+ "loss": 0.4644,
+ "step": 10933
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.78109521618828e-07,
+ "loss": 0.4834,
+ "step": 10934
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.773717442257141e-07,
+ "loss": 0.4578,
+ "step": 10935
+ },
+ {
+ "epoch": 0.91,
+ "learning_rate": 3.7663467347839766e-07,
+ "loss": 0.4573,
+ "step": 10936
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7589830943100205e-07,
+ "loss": 0.4669,
+ "step": 10937
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7516265213760507e-07,
+ "loss": 0.4479,
+ "step": 10938
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7442770165223133e-07,
+ "loss": 0.4579,
+ "step": 10939
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7369345802885095e-07,
+ "loss": 0.4696,
+ "step": 10940
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7295992132138416e-07,
+ "loss": 0.4632,
+ "step": 10941
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.7222709158369895e-07,
+ "loss": 0.4405,
+ "step": 10942
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.714949688696123e-07,
+ "loss": 0.4644,
+ "step": 10943
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.707635532328857e-07,
+ "loss": 0.4782,
+ "step": 10944
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.700328447272339e-07,
+ "loss": 0.4324,
+ "step": 10945
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.693028434063151e-07,
+ "loss": 0.4569,
+ "step": 10946
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6857354932373857e-07,
+ "loss": 0.454,
+ "step": 10947
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6784496253305937e-07,
+ "loss": 0.4474,
+ "step": 10948
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.671170830877846e-07,
+ "loss": 0.4524,
+ "step": 10949
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.663899110413638e-07,
+ "loss": 0.4726,
+ "step": 10950
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6566344644719974e-07,
+ "loss": 0.4711,
+ "step": 10951
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.649376893586398e-07,
+ "loss": 0.441,
+ "step": 10952
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6421263982898023e-07,
+ "loss": 0.4742,
+ "step": 10953
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.634882979114662e-07,
+ "loss": 0.4701,
+ "step": 10954
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.627646636592919e-07,
+ "loss": 0.4461,
+ "step": 10955
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6204173712559464e-07,
+ "loss": 0.4677,
+ "step": 10956
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6131951836346544e-07,
+ "loss": 0.4643,
+ "step": 10957
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.6059800742593963e-07,
+ "loss": 0.4507,
+ "step": 10958
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5987720436600483e-07,
+ "loss": 0.4745,
+ "step": 10959
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5915710923658974e-07,
+ "loss": 0.4839,
+ "step": 10960
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.584377220905788e-07,
+ "loss": 0.458,
+ "step": 10961
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5771904298079864e-07,
+ "loss": 0.4535,
+ "step": 10962
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.57001071960027e-07,
+ "loss": 0.443,
+ "step": 10963
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.562838090809884e-07,
+ "loss": 0.4507,
+ "step": 10964
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.555672543963562e-07,
+ "loss": 0.4554,
+ "step": 10965
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.548514079587495e-07,
+ "loss": 0.4864,
+ "step": 10966
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.541362698207373e-07,
+ "loss": 0.4705,
+ "step": 10967
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5342184003483884e-07,
+ "loss": 0.451,
+ "step": 10968
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.527081186535164e-07,
+ "loss": 0.4559,
+ "step": 10969
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5199510572918484e-07,
+ "loss": 0.4681,
+ "step": 10970
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.5128280131420333e-07,
+ "loss": 0.4597,
+ "step": 10971
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.505712054608801e-07,
+ "loss": 0.4551,
+ "step": 10972
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4986031822147325e-07,
+ "loss": 0.4646,
+ "step": 10973
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4915013964818556e-07,
+ "loss": 0.4706,
+ "step": 10974
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4844066979317193e-07,
+ "loss": 0.4488,
+ "step": 10975
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.477319087085318e-07,
+ "loss": 0.4767,
+ "step": 10976
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.470238564463135e-07,
+ "loss": 0.4695,
+ "step": 10977
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4631651305851224e-07,
+ "loss": 0.4663,
+ "step": 10978
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4560987859707407e-07,
+ "loss": 0.455,
+ "step": 10979
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.44903953113892e-07,
+ "loss": 0.4549,
+ "step": 10980
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.4419873666080237e-07,
+ "loss": 0.4622,
+ "step": 10981
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.434942292895982e-07,
+ "loss": 0.4688,
+ "step": 10982
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.427904310520136e-07,
+ "loss": 0.4463,
+ "step": 10983
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.420873419997317e-07,
+ "loss": 0.4726,
+ "step": 10984
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.413849621843857e-07,
+ "loss": 0.4541,
+ "step": 10985
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.406832916575542e-07,
+ "loss": 0.4545,
+ "step": 10986
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3998233047076613e-07,
+ "loss": 0.449,
+ "step": 10987
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3928207867549467e-07,
+ "loss": 0.4896,
+ "step": 10988
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.385825363231665e-07,
+ "loss": 0.4583,
+ "step": 10989
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3788370346515274e-07,
+ "loss": 0.4388,
+ "step": 10990
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3718558015277237e-07,
+ "loss": 0.4818,
+ "step": 10991
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3648816643729207e-07,
+ "loss": 0.4601,
+ "step": 10992
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.357914623699265e-07,
+ "loss": 0.4561,
+ "step": 10993
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3509546800183923e-07,
+ "loss": 0.4834,
+ "step": 10994
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.344001833841426e-07,
+ "loss": 0.4675,
+ "step": 10995
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.337056085678936e-07,
+ "loss": 0.4454,
+ "step": 10996
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3301174360410026e-07,
+ "loss": 0.4625,
+ "step": 10997
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3231858854371634e-07,
+ "loss": 0.462,
+ "step": 10998
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3162614343764334e-07,
+ "loss": 0.4516,
+ "step": 10999
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.309344083367327e-07,
+ "loss": 0.4705,
+ "step": 11000
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.3024338329178285e-07,
+ "loss": 0.4631,
+ "step": 11001
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2955306835353863e-07,
+ "loss": 0.4625,
+ "step": 11002
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2886346357269614e-07,
+ "loss": 0.4815,
+ "step": 11003
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.28174568999895e-07,
+ "loss": 0.4582,
+ "step": 11004
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.274863846857257e-07,
+ "loss": 0.4654,
+ "step": 11005
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2679891068072566e-07,
+ "loss": 0.4465,
+ "step": 11006
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.26112147035379e-07,
+ "loss": 0.4808,
+ "step": 11007
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.254260938001186e-07,
+ "loss": 0.4494,
+ "step": 11008
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2474075102532756e-07,
+ "loss": 0.4643,
+ "step": 11009
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.240561187613323e-07,
+ "loss": 0.4687,
+ "step": 11010
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.233721970584114e-07,
+ "loss": 0.4417,
+ "step": 11011
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.226889859667881e-07,
+ "loss": 0.4668,
+ "step": 11012
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.220064855366345e-07,
+ "loss": 0.4714,
+ "step": 11013
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2132469581807046e-07,
+ "loss": 0.4715,
+ "step": 11014
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.2064361686116377e-07,
+ "loss": 0.4557,
+ "step": 11015
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.199632487159321e-07,
+ "loss": 0.4709,
+ "step": 11016
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1928359143233556e-07,
+ "loss": 0.4687,
+ "step": 11017
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1860464506028865e-07,
+ "loss": 0.4549,
+ "step": 11018
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1792640964964593e-07,
+ "loss": 0.4747,
+ "step": 11019
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.172488852502187e-07,
+ "loss": 0.4414,
+ "step": 11020
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1657207191176043e-07,
+ "loss": 0.4593,
+ "step": 11021
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1589596968397027e-07,
+ "loss": 0.4616,
+ "step": 11022
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.15220578616503e-07,
+ "loss": 0.4688,
+ "step": 11023
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1454589875895445e-07,
+ "loss": 0.4583,
+ "step": 11024
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1387193016086945e-07,
+ "loss": 0.4662,
+ "step": 11025
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.131986728717429e-07,
+ "loss": 0.4629,
+ "step": 11026
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1252612694101515e-07,
+ "loss": 0.4678,
+ "step": 11027
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1185429241807453e-07,
+ "loss": 0.4724,
+ "step": 11028
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.1118316935226043e-07,
+ "loss": 0.4607,
+ "step": 11029
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.105127577928546e-07,
+ "loss": 0.4534,
+ "step": 11030
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0984305778908875e-07,
+ "loss": 0.4537,
+ "step": 11031
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.091740693901468e-07,
+ "loss": 0.4804,
+ "step": 11032
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.085057926451529e-07,
+ "loss": 0.4322,
+ "step": 11033
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.078382276031833e-07,
+ "loss": 0.4564,
+ "step": 11034
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.071713743132609e-07,
+ "loss": 0.4704,
+ "step": 11035
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0650523282435896e-07,
+ "loss": 0.4677,
+ "step": 11036
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0583980318539377e-07,
+ "loss": 0.467,
+ "step": 11037
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.051750854452329e-07,
+ "loss": 0.452,
+ "step": 11038
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0451107965268956e-07,
+ "loss": 0.4757,
+ "step": 11039
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0384778585652477e-07,
+ "loss": 0.4601,
+ "step": 11040
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.031852041054506e-07,
+ "loss": 0.4614,
+ "step": 11041
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0252333444812263e-07,
+ "loss": 0.4768,
+ "step": 11042
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0186217693314643e-07,
+ "loss": 0.4619,
+ "step": 11043
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.012017316090743e-07,
+ "loss": 0.4598,
+ "step": 11044
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 3.0054199852440626e-07,
+ "loss": 0.4628,
+ "step": 11045
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9988297772759136e-07,
+ "loss": 0.4393,
+ "step": 11046
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.992246692670242e-07,
+ "loss": 0.475,
+ "step": 11047
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.985670731910495e-07,
+ "loss": 0.4703,
+ "step": 11048
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9791018954795636e-07,
+ "loss": 0.4442,
+ "step": 11049
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.972540183859862e-07,
+ "loss": 0.4694,
+ "step": 11050
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9659855975332274e-07,
+ "loss": 0.4698,
+ "step": 11051
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.959438136981019e-07,
+ "loss": 0.4357,
+ "step": 11052
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9528978026840625e-07,
+ "loss": 0.4585,
+ "step": 11053
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.9463645951226415e-07,
+ "loss": 0.4864,
+ "step": 11054
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.939838514776527e-07,
+ "loss": 0.4584,
+ "step": 11055
+ },
+ {
+ "epoch": 0.92,
+ "learning_rate": 2.933319562124959e-07,
+ "loss": 0.4561,
+ "step": 11056
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.926807737646675e-07,
+ "loss": 0.4795,
+ "step": 11057
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.920303041819872e-07,
+ "loss": 0.4472,
+ "step": 11058
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.9138054751222447e-07,
+ "loss": 0.461,
+ "step": 11059
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.907315038030911e-07,
+ "loss": 0.4699,
+ "step": 11060
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.900831731022524e-07,
+ "loss": 0.4574,
+ "step": 11061
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.894355554573203e-07,
+ "loss": 0.4534,
+ "step": 11062
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8878865091584993e-07,
+ "loss": 0.4645,
+ "step": 11063
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.881424595253501e-07,
+ "loss": 0.4718,
+ "step": 11064
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8749698133327396e-07,
+ "loss": 0.4806,
+ "step": 11065
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.868522163870213e-07,
+ "loss": 0.4608,
+ "step": 11066
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8620816473394206e-07,
+ "loss": 0.4613,
+ "step": 11067
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.855648264213329e-07,
+ "loss": 0.4636,
+ "step": 11068
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.84922201496437e-07,
+ "loss": 0.4611,
+ "step": 11069
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8428029000644676e-07,
+ "loss": 0.4624,
+ "step": 11070
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.83639091998501e-07,
+ "loss": 0.4557,
+ "step": 11071
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8299860751968664e-07,
+ "loss": 0.4618,
+ "step": 11072
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.823588366170393e-07,
+ "loss": 0.4716,
+ "step": 11073
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.8171977933754036e-07,
+ "loss": 0.4572,
+ "step": 11074
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.810814357281189e-07,
+ "loss": 0.4798,
+ "step": 11075
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.804438058356529e-07,
+ "loss": 0.4614,
+ "step": 11076
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.798068897069672e-07,
+ "loss": 0.4506,
+ "step": 11077
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.791706873888345e-07,
+ "loss": 0.4792,
+ "step": 11078
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.78535198927975e-07,
+ "loss": 0.463,
+ "step": 11079
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.779004243710548e-07,
+ "loss": 0.4493,
+ "step": 11080
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7726636376468995e-07,
+ "loss": 0.4583,
+ "step": 11081
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.766330171554443e-07,
+ "loss": 0.4744,
+ "step": 11082
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7600038458982626e-07,
+ "loss": 0.4577,
+ "step": 11083
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7536846611429524e-07,
+ "loss": 0.4498,
+ "step": 11084
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.747372617752575e-07,
+ "loss": 0.466,
+ "step": 11085
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.741067716190637e-07,
+ "loss": 0.4466,
+ "step": 11086
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.734769956920169e-07,
+ "loss": 0.4521,
+ "step": 11087
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.728479340403634e-07,
+ "loss": 0.4548,
+ "step": 11088
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7221958671029834e-07,
+ "loss": 0.464,
+ "step": 11089
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.715919537479661e-07,
+ "loss": 0.463,
+ "step": 11090
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.709650351994575e-07,
+ "loss": 0.4979,
+ "step": 11091
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.7033883111081014e-07,
+ "loss": 0.46,
+ "step": 11092
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6971334152801063e-07,
+ "loss": 0.4618,
+ "step": 11093
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.690885664969933e-07,
+ "loss": 0.4493,
+ "step": 11094
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6846450606363705e-07,
+ "loss": 0.4691,
+ "step": 11095
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.678411602737707e-07,
+ "loss": 0.4505,
+ "step": 11096
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6721852917316995e-07,
+ "loss": 0.4586,
+ "step": 11097
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.665966128075592e-07,
+ "loss": 0.4665,
+ "step": 11098
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.659754112226087e-07,
+ "loss": 0.4521,
+ "step": 11099
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.653549244639375e-07,
+ "loss": 0.4666,
+ "step": 11100
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6473515257711136e-07,
+ "loss": 0.456,
+ "step": 11101
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6411609560764273e-07,
+ "loss": 0.4674,
+ "step": 11102
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6349775360099306e-07,
+ "loss": 0.4626,
+ "step": 11103
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.628801266025727e-07,
+ "loss": 0.4403,
+ "step": 11104
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.622632146577364e-07,
+ "loss": 0.4732,
+ "step": 11105
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.616470178117858e-07,
+ "loss": 0.4657,
+ "step": 11106
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.6103153610997464e-07,
+ "loss": 0.4599,
+ "step": 11107
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.604167695975002e-07,
+ "loss": 0.4552,
+ "step": 11108
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5980271831950734e-07,
+ "loss": 0.4677,
+ "step": 11109
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5918938232109004e-07,
+ "loss": 0.4628,
+ "step": 11110
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5857676164729006e-07,
+ "loss": 0.4507,
+ "step": 11111
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5796485634309477e-07,
+ "loss": 0.4524,
+ "step": 11112
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.573536664534404e-07,
+ "loss": 0.4644,
+ "step": 11113
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5674319202320997e-07,
+ "loss": 0.4485,
+ "step": 11114
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5613343309723426e-07,
+ "loss": 0.4583,
+ "step": 11115
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.555243897202919e-07,
+ "loss": 0.4837,
+ "step": 11116
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.549160619371072e-07,
+ "loss": 0.4759,
+ "step": 11117
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5430844979235426e-07,
+ "loss": 0.4621,
+ "step": 11118
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5370155333065416e-07,
+ "loss": 0.4752,
+ "step": 11119
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5309537259657346e-07,
+ "loss": 0.4624,
+ "step": 11120
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.524899076346288e-07,
+ "loss": 0.4575,
+ "step": 11121
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.518851584892812e-07,
+ "loss": 0.4817,
+ "step": 11122
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5128112520494297e-07,
+ "loss": 0.4768,
+ "step": 11123
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.5067780782596973e-07,
+ "loss": 0.4499,
+ "step": 11124
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.500752063966694e-07,
+ "loss": 0.4508,
+ "step": 11125
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.494733209612921e-07,
+ "loss": 0.4726,
+ "step": 11126
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.488721515640391e-07,
+ "loss": 0.4577,
+ "step": 11127
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.482716982490574e-07,
+ "loss": 0.449,
+ "step": 11128
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.476719610604417e-07,
+ "loss": 0.4783,
+ "step": 11129
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4707294004223335e-07,
+ "loss": 0.483,
+ "step": 11130
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.464746352384229e-07,
+ "loss": 0.4561,
+ "step": 11131
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4587704669294834e-07,
+ "loss": 0.4791,
+ "step": 11132
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.452801744496913e-07,
+ "loss": 0.4602,
+ "step": 11133
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.446840185524868e-07,
+ "loss": 0.4529,
+ "step": 11134
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4408857904511196e-07,
+ "loss": 0.4832,
+ "step": 11135
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4349385597129403e-07,
+ "loss": 0.4787,
+ "step": 11136
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.428998493747081e-07,
+ "loss": 0.4726,
+ "step": 11137
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4230655929897263e-07,
+ "loss": 0.4646,
+ "step": 11138
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.417139857876583e-07,
+ "loss": 0.4458,
+ "step": 11139
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4112212888428246e-07,
+ "loss": 0.4363,
+ "step": 11140
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.4053098863230706e-07,
+ "loss": 0.4711,
+ "step": 11141
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3994056507514183e-07,
+ "loss": 0.4633,
+ "step": 11142
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3935085825614655e-07,
+ "loss": 0.4565,
+ "step": 11143
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.387618682186277e-07,
+ "loss": 0.4608,
+ "step": 11144
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3817359500583615e-07,
+ "loss": 0.4632,
+ "step": 11145
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3758603866097406e-07,
+ "loss": 0.4617,
+ "step": 11146
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3699919922718805e-07,
+ "loss": 0.4715,
+ "step": 11147
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3641307674757362e-07,
+ "loss": 0.4526,
+ "step": 11148
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3582767126517302e-07,
+ "loss": 0.4631,
+ "step": 11149
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.352429828229763e-07,
+ "loss": 0.4627,
+ "step": 11150
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3465901146391912e-07,
+ "loss": 0.4579,
+ "step": 11151
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3407575723088827e-07,
+ "loss": 0.4531,
+ "step": 11152
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3349322016671394e-07,
+ "loss": 0.4655,
+ "step": 11153
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3291140031417525e-07,
+ "loss": 0.4745,
+ "step": 11154
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3233029771599913e-07,
+ "loss": 0.4893,
+ "step": 11155
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3174991241485923e-07,
+ "loss": 0.4505,
+ "step": 11156
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.31170244453377e-07,
+ "loss": 0.4682,
+ "step": 11157
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.305912938741184e-07,
+ "loss": 0.4609,
+ "step": 11158
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.3001306071960384e-07,
+ "loss": 0.4606,
+ "step": 11159
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.294355450322916e-07,
+ "loss": 0.4565,
+ "step": 11160
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2885874685459553e-07,
+ "loss": 0.4542,
+ "step": 11161
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2828266622887173e-07,
+ "loss": 0.4691,
+ "step": 11162
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2770730319742528e-07,
+ "loss": 0.4622,
+ "step": 11163
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.271326578025068e-07,
+ "loss": 0.4703,
+ "step": 11164
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2655873008631812e-07,
+ "loss": 0.4572,
+ "step": 11165
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.259855200910066e-07,
+ "loss": 0.4871,
+ "step": 11166
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2541302785866525e-07,
+ "loss": 0.4661,
+ "step": 11167
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.248412534313349e-07,
+ "loss": 0.4621,
+ "step": 11168
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2427019685100527e-07,
+ "loss": 0.4768,
+ "step": 11169
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.236998581596128e-07,
+ "loss": 0.4552,
+ "step": 11170
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.231302373990385e-07,
+ "loss": 0.4535,
+ "step": 11171
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.225613346111155e-07,
+ "loss": 0.4639,
+ "step": 11172
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2199314983762043e-07,
+ "loss": 0.4708,
+ "step": 11173
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2142568312027879e-07,
+ "loss": 0.4768,
+ "step": 11174
+ },
+ {
+ "epoch": 0.93,
+ "learning_rate": 2.2085893450076167e-07,
+ "loss": 0.4697,
+ "step": 11175
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.2029290402069137e-07,
+ "loss": 0.4648,
+ "step": 11176
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1972759172163239e-07,
+ "loss": 0.4732,
+ "step": 11177
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.191629976451004e-07,
+ "loss": 0.4662,
+ "step": 11178
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.185991218325556e-07,
+ "loss": 0.458,
+ "step": 11179
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1803596432540818e-07,
+ "loss": 0.4644,
+ "step": 11180
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1747352516501396e-07,
+ "loss": 0.4514,
+ "step": 11181
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1691180439267434e-07,
+ "loss": 0.477,
+ "step": 11182
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1635080204964187e-07,
+ "loss": 0.4799,
+ "step": 11183
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.157905181771114e-07,
+ "loss": 0.4699,
+ "step": 11184
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1523095281623109e-07,
+ "loss": 0.4609,
+ "step": 11185
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.146721060080914e-07,
+ "loss": 0.446,
+ "step": 11186
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.141139777937318e-07,
+ "loss": 0.4774,
+ "step": 11187
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1355656821413938e-07,
+ "loss": 0.4701,
+ "step": 11188
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1299987731024818e-07,
+ "loss": 0.457,
+ "step": 11189
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1244390512293878e-07,
+ "loss": 0.4449,
+ "step": 11190
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1188865169303852e-07,
+ "loss": 0.4626,
+ "step": 11191
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1133411706132368e-07,
+ "loss": 0.4547,
+ "step": 11192
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1078030126851833e-07,
+ "loss": 0.4508,
+ "step": 11193
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.1022720435529109e-07,
+ "loss": 0.4558,
+ "step": 11194
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0967482636225723e-07,
+ "loss": 0.4591,
+ "step": 11195
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0912316732998538e-07,
+ "loss": 0.4874,
+ "step": 11196
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0857222729898429e-07,
+ "loss": 0.4589,
+ "step": 11197
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0802200630971382e-07,
+ "loss": 0.4498,
+ "step": 11198
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0747250440257715e-07,
+ "loss": 0.4682,
+ "step": 11199
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0692372161793094e-07,
+ "loss": 0.4665,
+ "step": 11200
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0637565799607517e-07,
+ "loss": 0.4639,
+ "step": 11201
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0582831357725542e-07,
+ "loss": 0.4561,
+ "step": 11202
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.052816884016673e-07,
+ "loss": 0.4466,
+ "step": 11203
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0473578250945315e-07,
+ "loss": 0.4515,
+ "step": 11204
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0419059594069977e-07,
+ "loss": 0.4653,
+ "step": 11205
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0364612873544632e-07,
+ "loss": 0.4583,
+ "step": 11206
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0310238093367517e-07,
+ "loss": 0.4565,
+ "step": 11207
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0255935257531668e-07,
+ "loss": 0.4796,
+ "step": 11208
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0201704370024889e-07,
+ "loss": 0.4641,
+ "step": 11209
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0147545434829664e-07,
+ "loss": 0.4512,
+ "step": 11210
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0093458455923253e-07,
+ "loss": 0.4543,
+ "step": 11211
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 2.0039443437277483e-07,
+ "loss": 0.4575,
+ "step": 11212
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9985500382858846e-07,
+ "loss": 0.4808,
+ "step": 11213
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9931629296629062e-07,
+ "loss": 0.4879,
+ "step": 11214
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9877830182543966e-07,
+ "loss": 0.4643,
+ "step": 11215
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.982410304455429e-07,
+ "loss": 0.4918,
+ "step": 11216
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.977044788660576e-07,
+ "loss": 0.4732,
+ "step": 11217
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9716864712638452e-07,
+ "loss": 0.458,
+ "step": 11218
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9663353526587104e-07,
+ "loss": 0.4465,
+ "step": 11219
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9609914332381797e-07,
+ "loss": 0.467,
+ "step": 11220
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9556547133946503e-07,
+ "loss": 0.471,
+ "step": 11221
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9503251935200418e-07,
+ "loss": 0.4334,
+ "step": 11222
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9450028740057415e-07,
+ "loss": 0.4527,
+ "step": 11223
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9396877552425808e-07,
+ "loss": 0.4616,
+ "step": 11224
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9343798376208812e-07,
+ "loss": 0.4508,
+ "step": 11225
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9290791215304527e-07,
+ "loss": 0.4742,
+ "step": 11226
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.92378560736054e-07,
+ "loss": 0.4621,
+ "step": 11227
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.918499295499887e-07,
+ "loss": 0.4577,
+ "step": 11228
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.913220186336684e-07,
+ "loss": 0.4754,
+ "step": 11229
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9079482802586314e-07,
+ "loss": 0.4778,
+ "step": 11230
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.9026835776528529e-07,
+ "loss": 0.443,
+ "step": 11231
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.897426078905984e-07,
+ "loss": 0.4614,
+ "step": 11232
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8921757844040821e-07,
+ "loss": 0.4567,
+ "step": 11233
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8869326945327505e-07,
+ "loss": 0.4597,
+ "step": 11234
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8816968096769917e-07,
+ "loss": 0.4536,
+ "step": 11235
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8764681302213096e-07,
+ "loss": 0.4508,
+ "step": 11236
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8712466565496966e-07,
+ "loss": 0.4729,
+ "step": 11237
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.866032389045569e-07,
+ "loss": 0.4623,
+ "step": 11238
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.860825328091853e-07,
+ "loss": 0.4619,
+ "step": 11239
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8556254740709322e-07,
+ "loss": 0.4518,
+ "step": 11240
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8504328273646676e-07,
+ "loss": 0.4522,
+ "step": 11241
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8452473883543876e-07,
+ "loss": 0.4689,
+ "step": 11242
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8400691574208763e-07,
+ "loss": 0.4826,
+ "step": 11243
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8348981349444073e-07,
+ "loss": 0.4514,
+ "step": 11244
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8297343213047215e-07,
+ "loss": 0.4614,
+ "step": 11245
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8245777168810264e-07,
+ "loss": 0.4789,
+ "step": 11246
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8194283220519972e-07,
+ "loss": 0.4497,
+ "step": 11247
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8142861371957866e-07,
+ "loss": 0.4716,
+ "step": 11248
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.809151162690026e-07,
+ "loss": 0.4514,
+ "step": 11249
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.8040233989117915e-07,
+ "loss": 0.4515,
+ "step": 11250
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.79890284623766e-07,
+ "loss": 0.4727,
+ "step": 11251
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7937895050436528e-07,
+ "loss": 0.4491,
+ "step": 11252
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7886833757052692e-07,
+ "loss": 0.4514,
+ "step": 11253
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.783584458597476e-07,
+ "loss": 0.4681,
+ "step": 11254
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7784927540947406e-07,
+ "loss": 0.4641,
+ "step": 11255
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7734082625709637e-07,
+ "loss": 0.4511,
+ "step": 11256
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7683309843995245e-07,
+ "loss": 0.4866,
+ "step": 11257
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.76326091995328e-07,
+ "loss": 0.4605,
+ "step": 11258
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7581980696045665e-07,
+ "loss": 0.4512,
+ "step": 11259
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7531424337251523e-07,
+ "loss": 0.4494,
+ "step": 11260
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.74809401268633e-07,
+ "loss": 0.4466,
+ "step": 11261
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7430528068588136e-07,
+ "loss": 0.4511,
+ "step": 11262
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.73801881661283e-07,
+ "loss": 0.4694,
+ "step": 11263
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.732992042318038e-07,
+ "loss": 0.4656,
+ "step": 11264
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7279724843435874e-07,
+ "loss": 0.4696,
+ "step": 11265
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7229601430580832e-07,
+ "loss": 0.4668,
+ "step": 11266
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7179550188296313e-07,
+ "loss": 0.4587,
+ "step": 11267
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7129571120257705e-07,
+ "loss": 0.4508,
+ "step": 11268
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7079664230135406e-07,
+ "loss": 0.4877,
+ "step": 11269
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.7029829521594265e-07,
+ "loss": 0.4431,
+ "step": 11270
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.698006699829402e-07,
+ "loss": 0.4604,
+ "step": 11271
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.693037666388886e-07,
+ "loss": 0.4764,
+ "step": 11272
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6880758522028083e-07,
+ "loss": 0.449,
+ "step": 11273
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6831212576355116e-07,
+ "loss": 0.4654,
+ "step": 11274
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6781738830508708e-07,
+ "loss": 0.4697,
+ "step": 11275
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6732337288121848e-07,
+ "loss": 0.4456,
+ "step": 11276
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6683007952822405e-07,
+ "loss": 0.4683,
+ "step": 11277
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.663375082823293e-07,
+ "loss": 0.4491,
+ "step": 11278
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.658456591797075e-07,
+ "loss": 0.4488,
+ "step": 11279
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6535453225647645e-07,
+ "loss": 0.4635,
+ "step": 11280
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6486412754870286e-07,
+ "loss": 0.4656,
+ "step": 11281
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.643744450924012e-07,
+ "loss": 0.489,
+ "step": 11282
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.638854849235305e-07,
+ "loss": 0.4561,
+ "step": 11283
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6339724707799875e-07,
+ "loss": 0.458,
+ "step": 11284
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6290973159165945e-07,
+ "loss": 0.4563,
+ "step": 11285
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.62422938500314e-07,
+ "loss": 0.4512,
+ "step": 11286
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.619368678397093e-07,
+ "loss": 0.4662,
+ "step": 11287
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.614515196455424e-07,
+ "loss": 0.4656,
+ "step": 11288
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.6096689395345366e-07,
+ "loss": 0.4872,
+ "step": 11289
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.604829907990335e-07,
+ "loss": 0.4777,
+ "step": 11290
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5999981021781685e-07,
+ "loss": 0.4589,
+ "step": 11291
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.595173522452864e-07,
+ "loss": 0.4641,
+ "step": 11292
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5903561691687164e-07,
+ "loss": 0.4715,
+ "step": 11293
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5855460426794865e-07,
+ "loss": 0.446,
+ "step": 11294
+ },
+ {
+ "epoch": 0.94,
+ "learning_rate": 1.5807431433384368e-07,
+ "loss": 0.4725,
+ "step": 11295
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5759474714982405e-07,
+ "loss": 0.4727,
+ "step": 11296
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5711590275110933e-07,
+ "loss": 0.4476,
+ "step": 11297
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5663778117286254e-07,
+ "loss": 0.4618,
+ "step": 11298
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.561603824501956e-07,
+ "loss": 0.4643,
+ "step": 11299
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5568370661816713e-07,
+ "loss": 0.4793,
+ "step": 11300
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.552077537117802e-07,
+ "loss": 0.4569,
+ "step": 11301
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5473252376598913e-07,
+ "loss": 0.4629,
+ "step": 11302
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5425801681569263e-07,
+ "loss": 0.4617,
+ "step": 11303
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5378423289573508e-07,
+ "loss": 0.4613,
+ "step": 11304
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5331117204091085e-07,
+ "loss": 0.45,
+ "step": 11305
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.528388342859577e-07,
+ "loss": 0.4758,
+ "step": 11306
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5236721966556456e-07,
+ "loss": 0.4927,
+ "step": 11307
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.518963282143615e-07,
+ "loss": 0.4616,
+ "step": 11308
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5142615996693087e-07,
+ "loss": 0.4713,
+ "step": 11309
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5095671495780062e-07,
+ "loss": 0.4613,
+ "step": 11310
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5048799322144426e-07,
+ "loss": 0.4549,
+ "step": 11311
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.5001999479228203e-07,
+ "loss": 0.459,
+ "step": 11312
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.49552719704682e-07,
+ "loss": 0.4595,
+ "step": 11313
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4908616799296006e-07,
+ "loss": 0.4503,
+ "step": 11314
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4862033969137545e-07,
+ "loss": 0.4753,
+ "step": 11315
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4815523483413864e-07,
+ "loss": 0.4399,
+ "step": 11316
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4769085345540556e-07,
+ "loss": 0.4847,
+ "step": 11317
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.472271955892768e-07,
+ "loss": 0.4602,
+ "step": 11318
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4676426126980058e-07,
+ "loss": 0.4709,
+ "step": 11319
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4630205053097645e-07,
+ "loss": 0.4564,
+ "step": 11320
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4584056340674392e-07,
+ "loss": 0.4561,
+ "step": 11321
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4537979993099361e-07,
+ "loss": 0.4634,
+ "step": 11322
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4491976013756292e-07,
+ "loss": 0.462,
+ "step": 11323
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4446044406023485e-07,
+ "loss": 0.4504,
+ "step": 11324
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4400185173274018e-07,
+ "loss": 0.4507,
+ "step": 11325
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4354398318875417e-07,
+ "loss": 0.4674,
+ "step": 11326
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.430868384619022e-07,
+ "loss": 0.4756,
+ "step": 11327
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4263041758575402e-07,
+ "loss": 0.4396,
+ "step": 11328
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4217472059382952e-07,
+ "loss": 0.464,
+ "step": 11329
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4171974751959082e-07,
+ "loss": 0.4678,
+ "step": 11330
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4126549839645009e-07,
+ "loss": 0.4847,
+ "step": 11331
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.408119732577662e-07,
+ "loss": 0.4553,
+ "step": 11332
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.4035917213684358e-07,
+ "loss": 0.4686,
+ "step": 11333
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3990709506693457e-07,
+ "loss": 0.4596,
+ "step": 11334
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.394557420812359e-07,
+ "loss": 0.443,
+ "step": 11335
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3900511321289557e-07,
+ "loss": 0.4613,
+ "step": 11336
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.385552084950037e-07,
+ "loss": 0.4579,
+ "step": 11337
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.381060279606017e-07,
+ "loss": 0.4549,
+ "step": 11338
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3765757164267313e-07,
+ "loss": 0.4551,
+ "step": 11339
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3720983957415278e-07,
+ "loss": 0.4749,
+ "step": 11340
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3676283178791882e-07,
+ "loss": 0.4428,
+ "step": 11341
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.363165483167983e-07,
+ "loss": 0.4797,
+ "step": 11342
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.35870989193565e-07,
+ "loss": 0.4681,
+ "step": 11343
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3542615445093722e-07,
+ "loss": 0.4495,
+ "step": 11344
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3498204412158434e-07,
+ "loss": 0.4612,
+ "step": 11345
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3453865823811696e-07,
+ "loss": 0.4608,
+ "step": 11346
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3409599683309793e-07,
+ "loss": 0.4477,
+ "step": 11347
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3365405993903347e-07,
+ "loss": 0.4679,
+ "step": 11348
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.332128475883765e-07,
+ "loss": 0.4465,
+ "step": 11349
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3277235981352887e-07,
+ "loss": 0.4629,
+ "step": 11350
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3233259664683916e-07,
+ "loss": 0.4655,
+ "step": 11351
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3189355812060157e-07,
+ "loss": 0.4558,
+ "step": 11352
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.314552442670558e-07,
+ "loss": 0.4475,
+ "step": 11353
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.310176551183906e-07,
+ "loss": 0.4415,
+ "step": 11354
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3058079070674023e-07,
+ "loss": 0.4641,
+ "step": 11355
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.3014465106418573e-07,
+ "loss": 0.4601,
+ "step": 11356
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.297092362227581e-07,
+ "loss": 0.4457,
+ "step": 11357
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2927454621442959e-07,
+ "loss": 0.4609,
+ "step": 11358
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2884058107112353e-07,
+ "loss": 0.4725,
+ "step": 11359
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2840734082470662e-07,
+ "loss": 0.455,
+ "step": 11360
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.279748255069968e-07,
+ "loss": 0.453,
+ "step": 11361
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.275430351497542e-07,
+ "loss": 0.4684,
+ "step": 11362
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.27111969784689e-07,
+ "loss": 0.4651,
+ "step": 11363
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2668162944345587e-07,
+ "loss": 0.4371,
+ "step": 11364
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.262520141576584e-07,
+ "loss": 0.4689,
+ "step": 11365
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2582312395884476e-07,
+ "loss": 0.4626,
+ "step": 11366
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2539495887851083e-07,
+ "loss": 0.4517,
+ "step": 11367
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2496751894810032e-07,
+ "loss": 0.4605,
+ "step": 11368
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.245408041990004e-07,
+ "loss": 0.4645,
+ "step": 11369
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2411481466254926e-07,
+ "loss": 0.4477,
+ "step": 11370
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2368955037002973e-07,
+ "loss": 0.4739,
+ "step": 11371
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.232650113526701e-07,
+ "loss": 0.4712,
+ "step": 11372
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.228411976416488e-07,
+ "loss": 0.4649,
+ "step": 11373
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2241810926808762e-07,
+ "loss": 0.4477,
+ "step": 11374
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.219957462630561e-07,
+ "loss": 0.4506,
+ "step": 11375
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2157410865757057e-07,
+ "loss": 0.4762,
+ "step": 11376
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2115319648259516e-07,
+ "loss": 0.4677,
+ "step": 11377
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2073300976904067e-07,
+ "loss": 0.4585,
+ "step": 11378
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.2031354854776356e-07,
+ "loss": 0.4589,
+ "step": 11379
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.198948128495647e-07,
+ "loss": 0.4742,
+ "step": 11380
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1947680270519733e-07,
+ "loss": 0.4694,
+ "step": 11381
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.19059518145358e-07,
+ "loss": 0.4748,
+ "step": 11382
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.186429592006888e-07,
+ "loss": 0.4683,
+ "step": 11383
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1822712590178197e-07,
+ "loss": 0.4732,
+ "step": 11384
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.178120182791731e-07,
+ "loss": 0.4454,
+ "step": 11385
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1739763636334667e-07,
+ "loss": 0.4684,
+ "step": 11386
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1698398018473278e-07,
+ "loss": 0.4555,
+ "step": 11387
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1657104977370937e-07,
+ "loss": 0.4729,
+ "step": 11388
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1615884516059883e-07,
+ "loss": 0.4459,
+ "step": 11389
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1574736637567252e-07,
+ "loss": 0.462,
+ "step": 11390
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1533661344914848e-07,
+ "loss": 0.4428,
+ "step": 11391
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1492658641119037e-07,
+ "loss": 0.4663,
+ "step": 11392
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1451728529190852e-07,
+ "loss": 0.4739,
+ "step": 11393
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1410871012136116e-07,
+ "loss": 0.4518,
+ "step": 11394
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.137008609295509e-07,
+ "loss": 0.4517,
+ "step": 11395
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1329373774642938e-07,
+ "loss": 0.4603,
+ "step": 11396
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1288734060189267e-07,
+ "loss": 0.4487,
+ "step": 11397
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1248166952578799e-07,
+ "loss": 0.4477,
+ "step": 11398
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1207672454790264e-07,
+ "loss": 0.4674,
+ "step": 11399
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1167250569797728e-07,
+ "loss": 0.4888,
+ "step": 11400
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.112690130056926e-07,
+ "loss": 0.4248,
+ "step": 11401
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1086624650068267e-07,
+ "loss": 0.4714,
+ "step": 11402
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1046420621252275e-07,
+ "loss": 0.4564,
+ "step": 11403
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.1006289217073806e-07,
+ "loss": 0.4568,
+ "step": 11404
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0966230440479953e-07,
+ "loss": 0.4453,
+ "step": 11405
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0926244294412359e-07,
+ "loss": 0.4599,
+ "step": 11406
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0886330781807674e-07,
+ "loss": 0.4831,
+ "step": 11407
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0846489905596669e-07,
+ "loss": 0.459,
+ "step": 11408
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0806721668705333e-07,
+ "loss": 0.4722,
+ "step": 11409
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0767026074053888e-07,
+ "loss": 0.4564,
+ "step": 11410
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0727403124557667e-07,
+ "loss": 0.473,
+ "step": 11411
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0687852823126122e-07,
+ "loss": 0.4533,
+ "step": 11412
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0648375172663927e-07,
+ "loss": 0.466,
+ "step": 11413
+ },
+ {
+ "epoch": 0.95,
+ "learning_rate": 1.0608970176069987e-07,
+ "loss": 0.4882,
+ "step": 11414
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.05696378362381e-07,
+ "loss": 0.4757,
+ "step": 11415
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.053037815605662e-07,
+ "loss": 0.4573,
+ "step": 11416
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0491191138408685e-07,
+ "loss": 0.4652,
+ "step": 11417
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0452076786171994e-07,
+ "loss": 0.4586,
+ "step": 11418
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0413035102219027e-07,
+ "loss": 0.4461,
+ "step": 11419
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0374066089416602e-07,
+ "loss": 0.4575,
+ "step": 11420
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.033516975062676e-07,
+ "loss": 0.4532,
+ "step": 11421
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0296346088705555e-07,
+ "loss": 0.4417,
+ "step": 11422
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.025759510650437e-07,
+ "loss": 0.4606,
+ "step": 11423
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0218916806868594e-07,
+ "loss": 0.469,
+ "step": 11424
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0180311192638848e-07,
+ "loss": 0.4542,
+ "step": 11425
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0141778266650082e-07,
+ "loss": 0.4661,
+ "step": 11426
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.0103318031732035e-07,
+ "loss": 0.4652,
+ "step": 11427
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.006493049070889e-07,
+ "loss": 0.4853,
+ "step": 11428
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 1.002661564639995e-07,
+ "loss": 0.4559,
+ "step": 11429
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.988373501618631e-08,
+ "loss": 0.4535,
+ "step": 11430
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.950204059173462e-08,
+ "loss": 0.4537,
+ "step": 11431
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.912107321867315e-08,
+ "loss": 0.462,
+ "step": 11432
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.87408329249795e-08,
+ "loss": 0.4469,
+ "step": 11433
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.836131973857687e-08,
+ "loss": 0.4602,
+ "step": 11434
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.798253368733523e-08,
+ "loss": 0.4734,
+ "step": 11435
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.76044747990701e-08,
+ "loss": 0.4662,
+ "step": 11436
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.722714310154591e-08,
+ "loss": 0.4702,
+ "step": 11437
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.685053862247051e-08,
+ "loss": 0.4542,
+ "step": 11438
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.647466138950178e-08,
+ "loss": 0.4661,
+ "step": 11439
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.60995114302421e-08,
+ "loss": 0.4739,
+ "step": 11440
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.572508877224163e-08,
+ "loss": 0.4406,
+ "step": 11441
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.535139344299393e-08,
+ "loss": 0.4697,
+ "step": 11442
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.497842546994485e-08,
+ "loss": 0.4764,
+ "step": 11443
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.460618488048024e-08,
+ "loss": 0.4497,
+ "step": 11444
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.423467170193933e-08,
+ "loss": 0.4531,
+ "step": 11445
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.386388596160367e-08,
+ "loss": 0.4582,
+ "step": 11446
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.349382768670034e-08,
+ "loss": 0.4613,
+ "step": 11447
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.31244969044065e-08,
+ "loss": 0.4622,
+ "step": 11448
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.275589364184379e-08,
+ "loss": 0.4951,
+ "step": 11449
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.238801792608054e-08,
+ "loss": 0.4514,
+ "step": 11450
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.202086978413294e-08,
+ "loss": 0.4673,
+ "step": 11451
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.165444924296163e-08,
+ "loss": 0.4674,
+ "step": 11452
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.12887563294751e-08,
+ "loss": 0.462,
+ "step": 11453
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.092379107053074e-08,
+ "loss": 0.4548,
+ "step": 11454
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.055955349292711e-08,
+ "loss": 0.4618,
+ "step": 11455
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 9.019604362341394e-08,
+ "loss": 0.4822,
+ "step": 11456
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.983326148868432e-08,
+ "loss": 0.4545,
+ "step": 11457
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.947120711538138e-08,
+ "loss": 0.4525,
+ "step": 11458
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.910988053009162e-08,
+ "loss": 0.462,
+ "step": 11459
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.874928175934938e-08,
+ "loss": 0.4336,
+ "step": 11460
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.838941082963681e-08,
+ "loss": 0.4565,
+ "step": 11461
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.803026776738055e-08,
+ "loss": 0.4647,
+ "step": 11462
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.767185259895284e-08,
+ "loss": 0.4468,
+ "step": 11463
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.731416535067705e-08,
+ "loss": 0.4473,
+ "step": 11464
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.695720604881886e-08,
+ "loss": 0.4576,
+ "step": 11465
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.660097471959173e-08,
+ "loss": 0.4786,
+ "step": 11466
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.624547138915696e-08,
+ "loss": 0.4623,
+ "step": 11467
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.589069608361922e-08,
+ "loss": 0.4606,
+ "step": 11468
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.553664882903323e-08,
+ "loss": 0.4581,
+ "step": 11469
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.518332965139931e-08,
+ "loss": 0.4398,
+ "step": 11470
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.483073857666224e-08,
+ "loss": 0.4641,
+ "step": 11471
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.447887563071466e-08,
+ "loss": 0.4707,
+ "step": 11472
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.4127740839397e-08,
+ "loss": 0.4626,
+ "step": 11473
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.377733422849532e-08,
+ "loss": 0.4563,
+ "step": 11474
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.342765582374124e-08,
+ "loss": 0.4642,
+ "step": 11475
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.307870565081422e-08,
+ "loss": 0.4385,
+ "step": 11476
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.273048373533932e-08,
+ "loss": 0.4736,
+ "step": 11477
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.23829901028883e-08,
+ "loss": 0.45,
+ "step": 11478
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.203622477898077e-08,
+ "loss": 0.4565,
+ "step": 11479
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.169018778908078e-08,
+ "loss": 0.4609,
+ "step": 11480
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.134487915860024e-08,
+ "loss": 0.4565,
+ "step": 11481
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.100029891289662e-08,
+ "loss": 0.4625,
+ "step": 11482
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.065644707727415e-08,
+ "loss": 0.4632,
+ "step": 11483
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 8.031332367698486e-08,
+ "loss": 0.4644,
+ "step": 11484
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.997092873722633e-08,
+ "loss": 0.4493,
+ "step": 11485
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.962926228314293e-08,
+ "loss": 0.4484,
+ "step": 11486
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.928832433982348e-08,
+ "loss": 0.4623,
+ "step": 11487
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.89481149323068e-08,
+ "loss": 0.4518,
+ "step": 11488
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.860863408557629e-08,
+ "loss": 0.4552,
+ "step": 11489
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.826988182456086e-08,
+ "loss": 0.4685,
+ "step": 11490
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.793185817413728e-08,
+ "loss": 0.4479,
+ "step": 11491
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.759456315912905e-08,
+ "loss": 0.478,
+ "step": 11492
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.725799680430634e-08,
+ "loss": 0.4773,
+ "step": 11493
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.692215913438383e-08,
+ "loss": 0.4452,
+ "step": 11494
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.658705017402623e-08,
+ "loss": 0.4524,
+ "step": 11495
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.625266994784053e-08,
+ "loss": 0.4712,
+ "step": 11496
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.591901848038263e-08,
+ "loss": 0.4557,
+ "step": 11497
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.558609579615406e-08,
+ "loss": 0.4618,
+ "step": 11498
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.525390191960413e-08,
+ "loss": 0.4687,
+ "step": 11499
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.49224368751278e-08,
+ "loss": 0.4418,
+ "step": 11500
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.459170068706555e-08,
+ "loss": 0.4609,
+ "step": 11501
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.42616933797069e-08,
+ "loss": 0.4724,
+ "step": 11502
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.393241497728465e-08,
+ "loss": 0.4743,
+ "step": 11503
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.360386550398058e-08,
+ "loss": 0.4792,
+ "step": 11504
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.327604498392094e-08,
+ "loss": 0.4734,
+ "step": 11505
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.294895344118091e-08,
+ "loss": 0.4442,
+ "step": 11506
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.262259089977907e-08,
+ "loss": 0.4476,
+ "step": 11507
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.229695738368403e-08,
+ "loss": 0.493,
+ "step": 11508
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.197205291680887e-08,
+ "loss": 0.4545,
+ "step": 11509
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.164787752301117e-08,
+ "loss": 0.4578,
+ "step": 11510
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.132443122609856e-08,
+ "loss": 0.4767,
+ "step": 11511
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.100171404982315e-08,
+ "loss": 0.4626,
+ "step": 11512
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.067972601788376e-08,
+ "loss": 0.4525,
+ "step": 11513
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.035846715392591e-08,
+ "loss": 0.4466,
+ "step": 11514
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 7.003793748154186e-08,
+ "loss": 0.4565,
+ "step": 11515
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.971813702427055e-08,
+ "loss": 0.4513,
+ "step": 11516
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.939906580559542e-08,
+ "loss": 0.4462,
+ "step": 11517
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.908072384894881e-08,
+ "loss": 0.4708,
+ "step": 11518
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.876311117770762e-08,
+ "loss": 0.4715,
+ "step": 11519
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.844622781519649e-08,
+ "loss": 0.4652,
+ "step": 11520
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.813007378468684e-08,
+ "loss": 0.4617,
+ "step": 11521
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.78146491093945e-08,
+ "loss": 0.4697,
+ "step": 11522
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.74999538124832e-08,
+ "loss": 0.4436,
+ "step": 11523
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.718598791706221e-08,
+ "loss": 0.4746,
+ "step": 11524
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.687275144618865e-08,
+ "loss": 0.4787,
+ "step": 11525
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.656024442286524e-08,
+ "loss": 0.4546,
+ "step": 11526
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.62484668700425e-08,
+ "loss": 0.4944,
+ "step": 11527
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.593741881061321e-08,
+ "loss": 0.4772,
+ "step": 11528
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.562710026742248e-08,
+ "loss": 0.4597,
+ "step": 11529
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.531751126325647e-08,
+ "loss": 0.462,
+ "step": 11530
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.500865182085148e-08,
+ "loss": 0.4656,
+ "step": 11531
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.470052196288712e-08,
+ "loss": 0.4457,
+ "step": 11532
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.439312171199308e-08,
+ "loss": 0.462,
+ "step": 11533
+ },
+ {
+ "epoch": 0.96,
+ "learning_rate": 6.408645109074352e-08,
+ "loss": 0.4589,
+ "step": 11534
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.37805101216571e-08,
+ "loss": 0.4681,
+ "step": 11535
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.34752988272036e-08,
+ "loss": 0.4498,
+ "step": 11536
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.317081722979402e-08,
+ "loss": 0.4609,
+ "step": 11537
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.286706535179044e-08,
+ "loss": 0.4832,
+ "step": 11538
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.256404321549725e-08,
+ "loss": 0.4635,
+ "step": 11539
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.226175084316666e-08,
+ "loss": 0.4608,
+ "step": 11540
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.19601882570009e-08,
+ "loss": 0.4557,
+ "step": 11541
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.165935547914225e-08,
+ "loss": 0.458,
+ "step": 11542
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.135925253168417e-08,
+ "loss": 0.4766,
+ "step": 11543
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.105987943666459e-08,
+ "loss": 0.455,
+ "step": 11544
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.07612362160681e-08,
+ "loss": 0.4563,
+ "step": 11545
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.046332289182722e-08,
+ "loss": 0.4636,
+ "step": 11546
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 6.016613948581662e-08,
+ "loss": 0.4598,
+ "step": 11547
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.98696860198622e-08,
+ "loss": 0.4772,
+ "step": 11548
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.957396251573433e-08,
+ "loss": 0.4755,
+ "step": 11549
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.9278968995150066e-08,
+ "loss": 0.4486,
+ "step": 11550
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.898470547977098e-08,
+ "loss": 0.4531,
+ "step": 11551
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.8691171991207554e-08,
+ "loss": 0.4647,
+ "step": 11552
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.8398368551014774e-08,
+ "loss": 0.4795,
+ "step": 11553
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.810629518069655e-08,
+ "loss": 0.4659,
+ "step": 11554
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.781495190170017e-08,
+ "loss": 0.4633,
+ "step": 11555
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.7524338735420734e-08,
+ "loss": 0.4726,
+ "step": 11556
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.7234455703200073e-08,
+ "loss": 0.4533,
+ "step": 11557
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.69453028263256e-08,
+ "loss": 0.4576,
+ "step": 11558
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.6656880126032544e-08,
+ "loss": 0.5139,
+ "step": 11559
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.636918762350063e-08,
+ "loss": 0.4825,
+ "step": 11560
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.60822253398563e-08,
+ "loss": 0.4501,
+ "step": 11561
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.57959932961738e-08,
+ "loss": 0.4619,
+ "step": 11562
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.551049151347299e-08,
+ "loss": 0.4715,
+ "step": 11563
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.522572001271931e-08,
+ "loss": 0.4353,
+ "step": 11564
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.494167881482493e-08,
+ "loss": 0.4583,
+ "step": 11565
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.4658367940648716e-08,
+ "loss": 0.4748,
+ "step": 11566
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.437578741099625e-08,
+ "loss": 0.4489,
+ "step": 11567
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.409393724661982e-08,
+ "loss": 0.4516,
+ "step": 11568
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.381281746821621e-08,
+ "loss": 0.4539,
+ "step": 11569
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.353242809643e-08,
+ "loss": 0.4893,
+ "step": 11570
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.3252769151851404e-08,
+ "loss": 0.4578,
+ "step": 11571
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.297384065501843e-08,
+ "loss": 0.4645,
+ "step": 11572
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.269564262641358e-08,
+ "loss": 0.45,
+ "step": 11573
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.241817508646607e-08,
+ "loss": 0.4595,
+ "step": 11574
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.214143805555294e-08,
+ "loss": 0.4711,
+ "step": 11575
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.1865431553996814e-08,
+ "loss": 0.4387,
+ "step": 11576
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.159015560206593e-08,
+ "loss": 0.4737,
+ "step": 11577
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.131561021997522e-08,
+ "loss": 0.4596,
+ "step": 11578
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.104179542788634e-08,
+ "loss": 0.4678,
+ "step": 11579
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.0768711245907654e-08,
+ "loss": 0.458,
+ "step": 11580
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.049635769409311e-08,
+ "loss": 0.4588,
+ "step": 11581
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 5.022473479244228e-08,
+ "loss": 0.4621,
+ "step": 11582
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.995384256090252e-08,
+ "loss": 0.4776,
+ "step": 11583
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.9683681019367935e-08,
+ "loss": 0.5035,
+ "step": 11584
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.941425018767709e-08,
+ "loss": 0.4653,
+ "step": 11585
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.914555008561528e-08,
+ "loss": 0.4472,
+ "step": 11586
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.8877580732916706e-08,
+ "loss": 0.4582,
+ "step": 11587
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.861034214925786e-08,
+ "loss": 0.4557,
+ "step": 11588
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.834383435426526e-08,
+ "loss": 0.4401,
+ "step": 11589
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.807805736750881e-08,
+ "loss": 0.4679,
+ "step": 11590
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.7813011208507344e-08,
+ "loss": 0.4689,
+ "step": 11591
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.754869589672306e-08,
+ "loss": 0.4587,
+ "step": 11592
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.728511145156822e-08,
+ "loss": 0.4385,
+ "step": 11593
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.702225789239734e-08,
+ "loss": 0.4664,
+ "step": 11594
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.676013523851497e-08,
+ "loss": 0.4549,
+ "step": 11595
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.6498743509170165e-08,
+ "loss": 0.4589,
+ "step": 11596
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.6238082723557566e-08,
+ "loss": 0.479,
+ "step": 11597
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.597815290081853e-08,
+ "loss": 0.4623,
+ "step": 11598
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.571895406004334e-08,
+ "loss": 0.4538,
+ "step": 11599
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.546048622026455e-08,
+ "loss": 0.4619,
+ "step": 11600
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.520274940046254e-08,
+ "loss": 0.4445,
+ "step": 11601
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.494574361956661e-08,
+ "loss": 0.4731,
+ "step": 11602
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.4689468896449426e-08,
+ "loss": 0.4714,
+ "step": 11603
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.44339252499304e-08,
+ "loss": 0.4801,
+ "step": 11604
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.4179112698774505e-08,
+ "loss": 0.4417,
+ "step": 11605
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.392503126169678e-08,
+ "loss": 0.4605,
+ "step": 11606
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.3671680957352304e-08,
+ "loss": 0.4555,
+ "step": 11607
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.341906180434952e-08,
+ "loss": 0.4503,
+ "step": 11608
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.3167173821238026e-08,
+ "loss": 0.4642,
+ "step": 11609
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.291601702651527e-08,
+ "loss": 0.4799,
+ "step": 11610
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.2665591438626474e-08,
+ "loss": 0.4446,
+ "step": 11611
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.241589707596028e-08,
+ "loss": 0.4713,
+ "step": 11612
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.216693395685423e-08,
+ "loss": 0.4628,
+ "step": 11613
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.191870209959037e-08,
+ "loss": 0.4603,
+ "step": 11614
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.167120152239856e-08,
+ "loss": 0.4876,
+ "step": 11615
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.142443224345427e-08,
+ "loss": 0.4624,
+ "step": 11616
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.1178394280878554e-08,
+ "loss": 0.4711,
+ "step": 11617
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.093308765273918e-08,
+ "loss": 0.4748,
+ "step": 11618
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.068851237705174e-08,
+ "loss": 0.4544,
+ "step": 11619
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.044466847177519e-08,
+ "loss": 0.4416,
+ "step": 11620
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 4.0201555954818563e-08,
+ "loss": 0.4559,
+ "step": 11621
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.9959174844032e-08,
+ "loss": 0.4686,
+ "step": 11622
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.971752515721794e-08,
+ "loss": 0.4665,
+ "step": 11623
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.9476606912121073e-08,
+ "loss": 0.4777,
+ "step": 11624
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.9236420126432806e-08,
+ "loss": 0.469,
+ "step": 11625
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.899696481779236e-08,
+ "loss": 0.4729,
+ "step": 11626
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.8758241003782336e-08,
+ "loss": 0.4659,
+ "step": 11627
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.852024870193649e-08,
+ "loss": 0.4463,
+ "step": 11628
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.8282987929730844e-08,
+ "loss": 0.4729,
+ "step": 11629
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.804645870458812e-08,
+ "loss": 0.4636,
+ "step": 11630
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.781066104387887e-08,
+ "loss": 0.4568,
+ "step": 11631
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.757559496491925e-08,
+ "loss": 0.457,
+ "step": 11632
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.7341260484969885e-08,
+ "loss": 0.4333,
+ "step": 11633
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.710765762124147e-08,
+ "loss": 0.4622,
+ "step": 11634
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.687478639088804e-08,
+ "loss": 0.4611,
+ "step": 11635
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.6642646811010375e-08,
+ "loss": 0.4524,
+ "step": 11636
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.6411238898655943e-08,
+ "loss": 0.4486,
+ "step": 11637
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.618056267081782e-08,
+ "loss": 0.4561,
+ "step": 11638
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.59506181444369e-08,
+ "loss": 0.465,
+ "step": 11639
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.5721405336398565e-08,
+ "loss": 0.4843,
+ "step": 11640
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.5492924263537124e-08,
+ "loss": 0.458,
+ "step": 11641
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.526517494262804e-08,
+ "loss": 0.4535,
+ "step": 11642
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.5038157390399067e-08,
+ "loss": 0.4647,
+ "step": 11643
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.481187162352018e-08,
+ "loss": 0.4704,
+ "step": 11644
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.4586317658609205e-08,
+ "loss": 0.4537,
+ "step": 11645
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.436149551223067e-08,
+ "loss": 0.4813,
+ "step": 11646
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.413740520089248e-08,
+ "loss": 0.4698,
+ "step": 11647
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.3914046741052585e-08,
+ "loss": 0.4612,
+ "step": 11648
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.369142014911231e-08,
+ "loss": 0.4437,
+ "step": 11649
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.34695254414219e-08,
+ "loss": 0.4877,
+ "step": 11650
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.3248362634275e-08,
+ "loss": 0.4612,
+ "step": 11651
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.302793174391417e-08,
+ "loss": 0.4605,
+ "step": 11652
+ },
+ {
+ "epoch": 0.97,
+ "learning_rate": 3.280823278652645e-08,
+ "loss": 0.466,
+ "step": 11653
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.2589265778244505e-08,
+ "loss": 0.4523,
+ "step": 11654
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.237103073514991e-08,
+ "loss": 0.4371,
+ "step": 11655
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.215352767326873e-08,
+ "loss": 0.4783,
+ "step": 11656
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.193675660857265e-08,
+ "loss": 0.4543,
+ "step": 11657
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.172071755698114e-08,
+ "loss": 0.471,
+ "step": 11658
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.150541053435818e-08,
+ "loss": 0.4686,
+ "step": 11659
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.129083555651668e-08,
+ "loss": 0.4683,
+ "step": 11660
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.1076992639211824e-08,
+ "loss": 0.452,
+ "step": 11661
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.086388179814992e-08,
+ "loss": 0.4614,
+ "step": 11662
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.065150304897957e-08,
+ "loss": 0.469,
+ "step": 11663
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.043985640729718e-08,
+ "loss": 0.4555,
+ "step": 11664
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.022894188864589e-08,
+ "loss": 0.4715,
+ "step": 11665
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 3.0018759508513297e-08,
+ "loss": 0.4541,
+ "step": 11666
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.980930928233372e-08,
+ "loss": 0.4638,
+ "step": 11667
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.9600591225490415e-08,
+ "loss": 0.4959,
+ "step": 11668
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.93926053533089e-08,
+ "loss": 0.4738,
+ "step": 11669
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.918535168106473e-08,
+ "loss": 0.4592,
+ "step": 11670
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.897883022397574e-08,
+ "loss": 0.468,
+ "step": 11671
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8773040997208678e-08,
+ "loss": 0.4645,
+ "step": 11672
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8567984015877014e-08,
+ "loss": 0.4617,
+ "step": 11673
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8363659295037592e-08,
+ "loss": 0.4605,
+ "step": 11674
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.8160066849696187e-08,
+ "loss": 0.4509,
+ "step": 11675
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.7957206694803064e-08,
+ "loss": 0.4641,
+ "step": 11676
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.77550788452563e-08,
+ "loss": 0.4295,
+ "step": 11677
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.755368331589847e-08,
+ "loss": 0.4568,
+ "step": 11678
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.7353020121518857e-08,
+ "loss": 0.4661,
+ "step": 11679
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.715308927685567e-08,
+ "loss": 0.4596,
+ "step": 11680
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.6953890796588276e-08,
+ "loss": 0.4582,
+ "step": 11681
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.67554246953472e-08,
+ "loss": 0.4804,
+ "step": 11682
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.655769098770522e-08,
+ "loss": 0.439,
+ "step": 11683
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.636068968818295e-08,
+ "loss": 0.4728,
+ "step": 11684
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.6164420811249925e-08,
+ "loss": 0.465,
+ "step": 11685
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5968884371315728e-08,
+ "loss": 0.4494,
+ "step": 11686
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5774080382743317e-08,
+ "loss": 0.4401,
+ "step": 11687
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5580008859835692e-08,
+ "loss": 0.4924,
+ "step": 11688
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.538666981684479e-08,
+ "loss": 0.4549,
+ "step": 11689
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5194063267970358e-08,
+ "loss": 0.4631,
+ "step": 11690
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.5002189227354425e-08,
+ "loss": 0.4868,
+ "step": 11691
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.481104770908904e-08,
+ "loss": 0.4634,
+ "step": 11692
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.4620638727210766e-08,
+ "loss": 0.4397,
+ "step": 11693
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.4430962295701743e-08,
+ "loss": 0.4728,
+ "step": 11694
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.4242018428491944e-08,
+ "loss": 0.4633,
+ "step": 11695
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.405380713945582e-08,
+ "loss": 0.4515,
+ "step": 11696
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.3866328442414545e-08,
+ "loss": 0.4745,
+ "step": 11697
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.3679582351137098e-08,
+ "loss": 0.4766,
+ "step": 11698
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.349356887933585e-08,
+ "loss": 0.4631,
+ "step": 11699
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.330828804067098e-08,
+ "loss": 0.4695,
+ "step": 11700
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.3123739848749382e-08,
+ "loss": 0.4665,
+ "step": 11701
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2939924317124663e-08,
+ "loss": 0.46,
+ "step": 11702
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.275684145929269e-08,
+ "loss": 0.4722,
+ "step": 11703
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2574491288700485e-08,
+ "loss": 0.4655,
+ "step": 11704
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2392873818738447e-08,
+ "loss": 0.4503,
+ "step": 11705
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2211989062743688e-08,
+ "loss": 0.4614,
+ "step": 11706
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.2031837034000024e-08,
+ "loss": 0.4405,
+ "step": 11707
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1852417745735764e-08,
+ "loss": 0.4648,
+ "step": 11708
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1673731211129255e-08,
+ "loss": 0.4791,
+ "step": 11709
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1495777443300005e-08,
+ "loss": 0.467,
+ "step": 11710
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.131855645531644e-08,
+ "loss": 0.4428,
+ "step": 11711
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.1142068260194827e-08,
+ "loss": 0.4568,
+ "step": 11712
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0966312870893678e-08,
+ "loss": 0.4525,
+ "step": 11713
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0791290300321564e-08,
+ "loss": 0.4744,
+ "step": 11714
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0617000561329315e-08,
+ "loss": 0.4685,
+ "step": 11715
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.04434436667178e-08,
+ "loss": 0.4811,
+ "step": 11716
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.027061962923127e-08,
+ "loss": 0.4609,
+ "step": 11717
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 2.0098528461562906e-08,
+ "loss": 0.4709,
+ "step": 11718
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9927170176348155e-08,
+ "loss": 0.4597,
+ "step": 11719
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9756544786171393e-08,
+ "loss": 0.4651,
+ "step": 11720
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9586652303562603e-08,
+ "loss": 0.4463,
+ "step": 11721
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.941749274099958e-08,
+ "loss": 0.4751,
+ "step": 11722
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.924906611090349e-08,
+ "loss": 0.4505,
+ "step": 11723
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.9081372425642232e-08,
+ "loss": 0.4564,
+ "step": 11724
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8914411697531498e-08,
+ "loss": 0.4579,
+ "step": 11725
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8748183938832597e-08,
+ "loss": 0.4747,
+ "step": 11726
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8582689161751323e-08,
+ "loss": 0.4637,
+ "step": 11727
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.841792737844128e-08,
+ "loss": 0.4701,
+ "step": 11728
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8253898601002794e-08,
+ "loss": 0.4685,
+ "step": 11729
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.8090602841479566e-08,
+ "loss": 0.4487,
+ "step": 11730
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.792804011186533e-08,
+ "loss": 0.4494,
+ "step": 11731
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.7766210424097207e-08,
+ "loss": 0.4415,
+ "step": 11732
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.7605113790059024e-08,
+ "loss": 0.4635,
+ "step": 11733
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.744475022158243e-08,
+ "loss": 0.459,
+ "step": 11734
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.7285119730442446e-08,
+ "loss": 0.4558,
+ "step": 11735
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.712622232836192e-08,
+ "loss": 0.4716,
+ "step": 11736
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6968058027009292e-08,
+ "loss": 0.4586,
+ "step": 11737
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6810626837999722e-08,
+ "loss": 0.4835,
+ "step": 11738
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6653928772895067e-08,
+ "loss": 0.4461,
+ "step": 11739
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.649796384320168e-08,
+ "loss": 0.4419,
+ "step": 11740
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6342732060373733e-08,
+ "loss": 0.4625,
+ "step": 11741
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6188233435809887e-08,
+ "loss": 0.4593,
+ "step": 11742
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.6034467980857727e-08,
+ "loss": 0.4429,
+ "step": 11743
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5881435706806002e-08,
+ "loss": 0.4512,
+ "step": 11744
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5729136624895723e-08,
+ "loss": 0.4645,
+ "step": 11745
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5577570746309057e-08,
+ "loss": 0.4584,
+ "step": 11746
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5426738082178206e-08,
+ "loss": 0.4629,
+ "step": 11747
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5276638643578756e-08,
+ "loss": 0.4594,
+ "step": 11748
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.5127272441533004e-08,
+ "loss": 0.4414,
+ "step": 11749
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.497863948700995e-08,
+ "loss": 0.4754,
+ "step": 11750
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4830739790925308e-08,
+ "loss": 0.4389,
+ "step": 11751
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4683573364138171e-08,
+ "loss": 0.4845,
+ "step": 11752
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4537140217458778e-08,
+ "loss": 0.4612,
+ "step": 11753
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.439144036163964e-08,
+ "loss": 0.4562,
+ "step": 11754
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.4246473807378869e-08,
+ "loss": 0.4516,
+ "step": 11755
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.41022405653235e-08,
+ "loss": 0.4753,
+ "step": 11756
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.395874064606506e-08,
+ "loss": 0.4545,
+ "step": 11757
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.381597406014179e-08,
+ "loss": 0.4614,
+ "step": 11758
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3673940818037523e-08,
+ "loss": 0.4941,
+ "step": 11759
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3532640930182806e-08,
+ "loss": 0.4754,
+ "step": 11760
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.339207440695378e-08,
+ "loss": 0.4795,
+ "step": 11761
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3252241258673305e-08,
+ "loss": 0.4604,
+ "step": 11762
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.3113141495610937e-08,
+ "loss": 0.4656,
+ "step": 11763
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2974775127980732e-08,
+ "loss": 0.4797,
+ "step": 11764
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.283714216594345e-08,
+ "loss": 0.4449,
+ "step": 11765
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2700242619606562e-08,
+ "loss": 0.4625,
+ "step": 11766
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2564076499024247e-08,
+ "loss": 0.4635,
+ "step": 11767
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2428643814195174e-08,
+ "loss": 0.4668,
+ "step": 11768
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.229394457506472e-08,
+ "loss": 0.4709,
+ "step": 11769
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.2159978791524973e-08,
+ "loss": 0.4454,
+ "step": 11770
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.202674647341362e-08,
+ "loss": 0.474,
+ "step": 11771
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.1894247630516165e-08,
+ "loss": 0.4544,
+ "step": 11772
+ },
+ {
+ "epoch": 0.98,
+ "learning_rate": 1.1762482272560382e-08,
+ "loss": 0.4765,
+ "step": 11773
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1631450409224088e-08,
+ "loss": 0.4647,
+ "step": 11774
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1501152050128472e-08,
+ "loss": 0.4871,
+ "step": 11775
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1371587204843659e-08,
+ "loss": 0.4494,
+ "step": 11776
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.124275588288426e-08,
+ "loss": 0.4947,
+ "step": 11777
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.1114658093709373e-08,
+ "loss": 0.4682,
+ "step": 11778
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0987293846728141e-08,
+ "loss": 0.4486,
+ "step": 11779
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0860663151291973e-08,
+ "loss": 0.4312,
+ "step": 11780
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0734766016700093e-08,
+ "loss": 0.4613,
+ "step": 11781
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0609602452199553e-08,
+ "loss": 0.4764,
+ "step": 11782
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0485172466980776e-08,
+ "loss": 0.4795,
+ "step": 11783
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0361476070180899e-08,
+ "loss": 0.4585,
+ "step": 11784
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0238513270884876e-08,
+ "loss": 0.459,
+ "step": 11785
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.0116284078121042e-08,
+ "loss": 0.4561,
+ "step": 11786
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.994788500866659e-09,
+ "loss": 0.4608,
+ "step": 11787
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.87402654804348e-09,
+ "loss": 0.4812,
+ "step": 11788
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.753998228519967e-09,
+ "loss": 0.4629,
+ "step": 11789
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.634703551110181e-09,
+ "loss": 0.4569,
+ "step": 11790
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.516142524574889e-09,
+ "loss": 0.4736,
+ "step": 11791
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.398315157619354e-09,
+ "loss": 0.4595,
+ "step": 11792
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.281221458898871e-09,
+ "loss": 0.456,
+ "step": 11793
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.164861437009897e-09,
+ "loss": 0.4692,
+ "step": 11794
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 9.049235100500042e-09,
+ "loss": 0.4546,
+ "step": 11795
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.93434245785696e-09,
+ "loss": 0.4422,
+ "step": 11796
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.820183517521675e-09,
+ "loss": 0.4557,
+ "step": 11797
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.706758287874151e-09,
+ "loss": 0.4557,
+ "step": 11798
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.594066777246613e-09,
+ "loss": 0.4656,
+ "step": 11799
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.482108993912441e-09,
+ "loss": 0.501,
+ "step": 11800
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.370884946095059e-09,
+ "loss": 0.4627,
+ "step": 11801
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.260394641961267e-09,
+ "loss": 0.4597,
+ "step": 11802
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.150638089624574e-09,
+ "loss": 0.4844,
+ "step": 11803
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 8.04161529714631e-09,
+ "loss": 0.4403,
+ "step": 11804
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.933326272532294e-09,
+ "loss": 0.4704,
+ "step": 11805
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.825771023735051e-09,
+ "loss": 0.4568,
+ "step": 11806
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.7189495586516e-09,
+ "loss": 0.4704,
+ "step": 11807
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.612861885128997e-09,
+ "loss": 0.4585,
+ "step": 11808
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.507508010955455e-09,
+ "loss": 0.4507,
+ "step": 11809
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.40288794386812e-09,
+ "loss": 0.4675,
+ "step": 11810
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.299001691550844e-09,
+ "loss": 0.4525,
+ "step": 11811
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.195849261631971e-09,
+ "loss": 0.4645,
+ "step": 11812
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 7.093430661686551e-09,
+ "loss": 0.4757,
+ "step": 11813
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.991745899236346e-09,
+ "loss": 0.4585,
+ "step": 11814
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.890794981748717e-09,
+ "loss": 0.4569,
+ "step": 11815
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.79057791663551e-09,
+ "loss": 0.4858,
+ "step": 11816
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.691094711258617e-09,
+ "loss": 0.4416,
+ "step": 11817
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.5923453729221935e-09,
+ "loss": 0.4474,
+ "step": 11818
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.4943299088771065e-09,
+ "loss": 0.4492,
+ "step": 11819
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.397048326323152e-09,
+ "loss": 0.4803,
+ "step": 11820
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.300500632403505e-09,
+ "loss": 0.458,
+ "step": 11821
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.204686834208051e-09,
+ "loss": 0.4613,
+ "step": 11822
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.1096069387733825e-09,
+ "loss": 0.4649,
+ "step": 11823
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 6.015260953080582e-09,
+ "loss": 0.4637,
+ "step": 11824
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.921648884059661e-09,
+ "loss": 0.4679,
+ "step": 11825
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.828770738584011e-09,
+ "loss": 0.4586,
+ "step": 11826
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.736626523474842e-09,
+ "loss": 0.4494,
+ "step": 11827
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.645216245497853e-09,
+ "loss": 0.446,
+ "step": 11828
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.554539911367673e-09,
+ "loss": 0.4763,
+ "step": 11829
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.4645975277412004e-09,
+ "loss": 0.4616,
+ "step": 11830
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.37538910122426e-09,
+ "loss": 0.4542,
+ "step": 11831
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.2869146383682794e-09,
+ "loss": 0.4753,
+ "step": 11832
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.199174145670283e-09,
+ "loss": 0.488,
+ "step": 11833
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.112167629572895e-09,
+ "loss": 0.4638,
+ "step": 11834
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 5.02589509646656e-09,
+ "loss": 0.479,
+ "step": 11835
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.94035655268621e-09,
+ "loss": 0.4608,
+ "step": 11836
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.855552004513486e-09,
+ "loss": 0.4786,
+ "step": 11837
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.7714814581756305e-09,
+ "loss": 0.4579,
+ "step": 11838
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.6881449198477035e-09,
+ "loss": 0.4622,
+ "step": 11839
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.605542395648144e-09,
+ "loss": 0.4534,
+ "step": 11840
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.52367389164432e-09,
+ "loss": 0.469,
+ "step": 11841
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.44253941384698e-09,
+ "loss": 0.4853,
+ "step": 11842
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.362138968214691e-09,
+ "loss": 0.4447,
+ "step": 11843
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.282472560651618e-09,
+ "loss": 0.4573,
+ "step": 11844
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.203540197009748e-09,
+ "loss": 0.461,
+ "step": 11845
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.125341883083334e-09,
+ "loss": 0.4492,
+ "step": 11846
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 4.047877624615559e-09,
+ "loss": 0.4663,
+ "step": 11847
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.971147427296318e-09,
+ "loss": 0.455,
+ "step": 11848
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.895151296758881e-09,
+ "loss": 0.4424,
+ "step": 11849
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.81988923858434e-09,
+ "loss": 0.4672,
+ "step": 11850
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.745361258300495e-09,
+ "loss": 0.4656,
+ "step": 11851
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.6715673613796353e-09,
+ "loss": 0.4624,
+ "step": 11852
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.59850755324076e-09,
+ "loss": 0.4421,
+ "step": 11853
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.5261818392484657e-09,
+ "loss": 0.4816,
+ "step": 11854
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.454590224716281e-09,
+ "loss": 0.4464,
+ "step": 11855
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.383732714900001e-09,
+ "loss": 0.45,
+ "step": 11856
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.313609315003241e-09,
+ "loss": 0.4448,
+ "step": 11857
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.244220030175216e-09,
+ "loss": 0.4695,
+ "step": 11858
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.175564865512959e-09,
+ "loss": 0.4581,
+ "step": 11859
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.107643826055773e-09,
+ "loss": 0.4873,
+ "step": 11860
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 3.04045691679411e-09,
+ "loss": 0.4794,
+ "step": 11861
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.9740041426606915e-09,
+ "loss": 0.4446,
+ "step": 11862
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.908285508536057e-09,
+ "loss": 0.4744,
+ "step": 11863
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.843301019245237e-09,
+ "loss": 0.442,
+ "step": 11864
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.7790506795610793e-09,
+ "loss": 0.46,
+ "step": 11865
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.7155344942020324e-09,
+ "loss": 0.4449,
+ "step": 11866
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.6527524678321424e-09,
+ "loss": 0.4606,
+ "step": 11867
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.5907046050632767e-09,
+ "loss": 0.4512,
+ "step": 11868
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.5293909104495696e-09,
+ "loss": 0.467,
+ "step": 11869
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.4688113884940855e-09,
+ "loss": 0.4508,
+ "step": 11870
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.4089660436477093e-09,
+ "loss": 0.4537,
+ "step": 11871
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.3498548803024825e-09,
+ "loss": 0.4676,
+ "step": 11872
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.2914779028015976e-09,
+ "loss": 0.472,
+ "step": 11873
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.233835115430516e-09,
+ "loss": 0.4748,
+ "step": 11874
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.1769265224225176e-09,
+ "loss": 0.4612,
+ "step": 11875
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.1207521279575925e-09,
+ "loss": 0.4694,
+ "step": 11876
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.065311936160219e-09,
+ "loss": 0.4486,
+ "step": 11877
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 2.0106059511015853e-09,
+ "loss": 0.4707,
+ "step": 11878
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.9566341767984774e-09,
+ "loss": 0.4409,
+ "step": 11879
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.903396617216613e-09,
+ "loss": 0.4728,
+ "step": 11880
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.8508932762628662e-09,
+ "loss": 0.4348,
+ "step": 11881
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.7991241577952624e-09,
+ "loss": 0.4634,
+ "step": 11882
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.7480892656129845e-09,
+ "loss": 0.4532,
+ "step": 11883
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.697788603466366e-09,
+ "loss": 0.4515,
+ "step": 11884
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.6482221750468984e-09,
+ "loss": 0.4701,
+ "step": 11885
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.5993899839972239e-09,
+ "loss": 0.4458,
+ "step": 11886
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.5512920339011416e-09,
+ "loss": 0.4809,
+ "step": 11887
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.503928328291382e-09,
+ "loss": 0.4552,
+ "step": 11888
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.4572988706462732e-09,
+ "loss": 0.4768,
+ "step": 11889
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.4114036643897434e-09,
+ "loss": 0.4614,
+ "step": 11890
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.3662427128924294e-09,
+ "loss": 0.4842,
+ "step": 11891
+ },
+ {
+ "epoch": 0.99,
+ "learning_rate": 1.3218160194716778e-09,
+ "loss": 0.4597,
+ "step": 11892
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.2781235873882136e-09,
+ "loss": 0.456,
+ "step": 11893
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.2351654198528018e-09,
+ "loss": 0.4666,
+ "step": 11894
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.1929415200173656e-09,
+ "loss": 0.4657,
+ "step": 11895
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.151451890984978e-09,
+ "loss": 0.4713,
+ "step": 11896
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.1106965358009814e-09,
+ "loss": 0.4443,
+ "step": 11897
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.0706754574596468e-09,
+ "loss": 0.4491,
+ "step": 11898
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.0313886588986244e-09,
+ "loss": 0.4913,
+ "step": 11899
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 9.928361430044941e-10,
+ "loss": 0.4457,
+ "step": 11900
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 9.550179126072146e-10,
+ "loss": 0.4564,
+ "step": 11901
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 9.179339704834533e-10,
+ "loss": 0.4475,
+ "step": 11902
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 8.815843193576979e-10,
+ "loss": 0.4701,
+ "step": 11903
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 8.459689618989241e-10,
+ "loss": 0.4604,
+ "step": 11904
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 8.110879007228178e-10,
+ "loss": 0.4639,
+ "step": 11905
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 7.769411383906633e-10,
+ "loss": 0.4658,
+ "step": 11906
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 7.435286774104545e-10,
+ "loss": 0.4539,
+ "step": 11907
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 7.108505202346739e-10,
+ "loss": 0.4592,
+ "step": 11908
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 6.789066692636237e-10,
+ "loss": 0.442,
+ "step": 11909
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 6.476971268443156e-10,
+ "loss": 0.4526,
+ "step": 11910
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 6.172218952671394e-10,
+ "loss": 0.4614,
+ "step": 11911
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 5.874809767703049e-10,
+ "loss": 0.449,
+ "step": 11912
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 5.58474373538731e-10,
+ "loss": 0.4503,
+ "step": 11913
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 5.302020877018255e-10,
+ "loss": 0.4608,
+ "step": 11914
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 5.026641213357054e-10,
+ "loss": 0.4489,
+ "step": 11915
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 4.758604764631969e-10,
+ "loss": 0.4484,
+ "step": 11916
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 4.4979115505272566e-10,
+ "loss": 0.4652,
+ "step": 11917
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 4.2445615901831607e-10,
+ "loss": 0.4656,
+ "step": 11918
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.998554902195917e-10,
+ "loss": 0.4683,
+ "step": 11919
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.7598915046510587e-10,
+ "loss": 0.4503,
+ "step": 11920
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.528571415056803e-10,
+ "loss": 0.489,
+ "step": 11921
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.304594650410664e-10,
+ "loss": 0.4592,
+ "step": 11922
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.0879612271550454e-10,
+ "loss": 0.4751,
+ "step": 11923
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 2.878671161199442e-10,
+ "loss": 0.466,
+ "step": 11924
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 2.676724467920444e-10,
+ "loss": 0.45,
+ "step": 11925
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 2.482121162139528e-10,
+ "loss": 0.4598,
+ "step": 11926
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 2.2948612581452646e-10,
+ "loss": 0.505,
+ "step": 11927
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 2.114944769704419e-10,
+ "loss": 0.4551,
+ "step": 11928
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.9423717100175432e-10,
+ "loss": 0.4501,
+ "step": 11929
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.777142091752282e-10,
+ "loss": 0.4932,
+ "step": 11930
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.619255927054475e-10,
+ "loss": 0.455,
+ "step": 11931
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.468713227514851e-10,
+ "loss": 0.4599,
+ "step": 11932
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.3255140041912306e-10,
+ "loss": 0.4578,
+ "step": 11933
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.1896582675974266e-10,
+ "loss": 0.4442,
+ "step": 11934
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.0611460277032415e-10,
+ "loss": 0.464,
+ "step": 11935
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 9.399772939455709e-11,
+ "loss": 0.4523,
+ "step": 11936
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 8.261520752395059e-11,
+ "loss": 0.4593,
+ "step": 11937
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 7.19670379922821e-11,
+ "loss": 0.4764,
+ "step": 11938
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 6.205322158336913e-11,
+ "loss": 0.4706,
+ "step": 11939
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 5.287375902440772e-11,
+ "loss": 0.4774,
+ "step": 11940
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 4.442865098930327e-11,
+ "loss": 0.4738,
+ "step": 11941
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.671789809867043e-11,
+ "loss": 0.4651,
+ "step": 11942
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 2.974150091761274e-11,
+ "loss": 0.474,
+ "step": 11943
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 2.349945996016345e-11,
+ "loss": 0.4763,
+ "step": 11944
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.7991775683734448e-11,
+ "loss": 0.457,
+ "step": 11945
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.3218448492446912e-11,
+ "loss": 0.466,
+ "step": 11946
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 9.179478738241542e-12,
+ "loss": 0.45,
+ "step": 11947
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 5.874866715327443e-12,
+ "loss": 0.4781,
+ "step": 11948
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.3046126690639002e-12,
+ "loss": 0.4753,
+ "step": 11949
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 1.4687167870786056e-12,
+ "loss": 0.4425,
+ "step": 11950
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 3.6717920370854533e-13,
+ "loss": 0.4705,
+ "step": 11951
+ },
+ {
+ "epoch": 1.0,
+ "learning_rate": 0.0,
+ "loss": 0.4708,
+ "step": 11952
+ },
+ {
+ "epoch": 1.0,
+ "step": 11952,
+ "total_flos": 0.0,
+ "train_loss": 0.017490314920663514,
+ "train_runtime": 2743.4428,
+ "train_samples_per_second": 1115.374,
+ "train_steps_per_second": 4.357
+ }
+ ],
+ "logging_steps": 1.0,
+ "max_steps": 11952,
+ "num_input_tokens_seen": 0,
+ "num_train_epochs": 1,
+ "save_steps": 100,
+ "total_flos": 0.0,
+ "train_batch_size": 16,
+ "trial_name": null,
+ "trial_params": null
+}
diff --git a/vision_tower/config.json b/vision_tower/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..d206ea4893c85cf612a9ca5e15094655e3a3a453
--- /dev/null
+++ b/vision_tower/config.json
@@ -0,0 +1,19 @@
+{
+ "_name_or_path": "/lustre/fs12/portfolios/nvr/users/mmemmel/projects/vila/checkpoints/finetuned/vila_3b_path_mask/vision_tower",
+ "architectures": [
+ "SiglipVisionModel"
+ ],
+ "attention_dropout": 0.0,
+ "hidden_act": "gelu_pytorch_tanh",
+ "hidden_size": 1152,
+ "image_size": 384,
+ "intermediate_size": 4304,
+ "layer_norm_eps": 1e-06,
+ "model_type": "siglip_vision_model",
+ "num_attention_heads": 16,
+ "num_channels": 3,
+ "num_hidden_layers": 27,
+ "patch_size": 14,
+ "torch_dtype": "bfloat16",
+ "transformers_version": "4.36.2"
+}
diff --git a/vision_tower/model.safetensors b/vision_tower/model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..b6c2935653809218cfd3df65ea542edc40ad4b72
--- /dev/null
+++ b/vision_tower/model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a21d59235b9ff110c123480bb55cb2893ebab59faf902cbc648113251d9d29e6
+size 856506120
diff --git a/vision_tower/preprocessor_config.json b/vision_tower/preprocessor_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..0f13134ed29056f82f3ab7e0246f0ab973e7ecf3
--- /dev/null
+++ b/vision_tower/preprocessor_config.json
@@ -0,0 +1,24 @@
+{
+ "do_convert_rgb": true,
+ "do_normalize": true,
+ "do_rescale": true,
+ "do_resize": true,
+ "image_mean": [
+ 0.5,
+ 0.5,
+ 0.5
+ ],
+ "image_processor_type": "SiglipImageProcessor",
+ "image_std": [
+ 0.5,
+ 0.5,
+ 0.5
+ ],
+ "processor_class": "SiglipProcessor",
+ "resample": 3,
+ "rescale_factor": 0.00392156862745098,
+ "size": {
+ "height": 384,
+ "width": 384
+ }
+}