Training in progress, step 200

config.json

@@ -0,0 +1,61 @@
+{
+  "_name_or_path": "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct",
+  "architectures": [
+    "DeepseekV2ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "auto_map": {
+    "AutoConfig": "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct--configuration_deepseek.DeepseekV2Config",
+    "AutoModel": "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct--modeling_deepseek.DeepseekV2Model",
+    "AutoModelForCausalLM": "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct--modeling_deepseek.DeepseekV2ForCausalLM"
+  },
+  "aux_loss_alpha": 0.001,
+  "bos_token_id": 100000,
+  "eos_token_id": 100001,
+  "ep_size": 1,
+  "first_k_dense_replace": 1,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 10944,
+  "kv_lora_rank": 512,
+  "max_position_embeddings": 163840,
+  "model_type": "deepseek_v2",
+  "moe_intermediate_size": 1408,
+  "moe_layer_freq": 1,
+  "n_group": 1,
+  "n_routed_experts": 64,
+  "n_shared_experts": 2,
+  "norm_topk_prob": false,
+  "num_attention_heads": 16,
+  "num_experts_per_tok": 6,
+  "num_hidden_layers": 27,
+  "num_key_value_heads": 16,
+  "pretraining_tp": 1,
+  "q_lora_rank": null,
+  "qk_nope_head_dim": 128,
+  "qk_rope_head_dim": 64,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": {
+    "beta_fast": 32,
+    "beta_slow": 1,
+    "factor": 40,
+    "mscale": 0.707,
+    "mscale_all_dim": 0.707,
+    "original_max_position_embeddings": 4096,
+    "type": "yarn"
+  },
+  "rope_theta": 10000,
+  "routed_scaling_factor": 1.0,
+  "scoring_func": "softmax",
+  "seq_aux": true,
+  "tie_word_embeddings": false,
+  "topk_group": 1,
+  "topk_method": "greedy",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.49.0",
+  "use_cache": false,
+  "v_head_dim": 128,
+  "vocab_size": 102400
+}

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<｜begin▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<｜end▁of▁sentence｜>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<｜end▁of▁sentence｜>"
+}

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "add_prefix_space": null,
+  "added_tokens_decoder": {
+    "100000": {
+      "content": "<｜begin▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100001": {
+      "content": "<｜end▁of▁sentence｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100002": {
+      "content": "<｜fim▁hole｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100003": {
+      "content": "<｜fim▁begin｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100004": {
+      "content": "<｜fim▁end｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100005": {
+      "content": "<｜completion｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100006": {
+      "content": "<｜User｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100007": {
+      "content": "<｜Assistant｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "100008": {
+      "content": "<|EOT|>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100009": {
+      "content": "<｜tool▁calls▁begin｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
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+      "content": "<｜tool▁calls▁end｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
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+    "100011": {
+      "content": "<｜tool▁call▁begin｜>",
+      "lstrip": false,
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+      "single_word": false,
+      "special": false
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+    "100012": {
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+      "lstrip": false,
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+    "100013": {
+      "content": "<｜tool▁outputs▁begin｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
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+      "rstrip": false,
+      "single_word": false,
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+      "content": "<｜tool▁output▁begin｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
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+    "100016": {
+      "content": "<｜tool▁output▁end｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
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+    "100017": {
+      "content": "<｜tool▁sep｜>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "bos_token": "<｜begin▁of▁sentence｜>",
+  "chat_template": "{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{{ bos_token }}{% for message in messages %}{% if message['role'] == 'user' %}{{ 'User: ' + message['content'] + '\n\n' }}{% elif message['role'] == 'assistant' %}{{ 'Assistant: ' + message['content'] + eos_token }}{% elif message['role'] == 'system' %}{{ message['content'] + '\n\n' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ 'Assistant:' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<｜end▁of▁sentence｜>",
+  "extra_special_tokens": {},
+  "legacy": true,
+  "model_max_length": 16384,
+  "pad_token": "<｜end▁of▁sentence｜>",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizerFast",
+  "unk_token": null,
+  "use_default_system_prompt": false
+}

training.log

@@ -0,0 +1,245 @@
+
+
+[rank1]: Traceback (most recent call last):
+[rank1]:   File "/ocean/projects/cis240137p/hhe4/deepseek/open-r1/src/open_r1/sft.py", line 234, in <module>
+[rank1]:     main(script_args, training_args, model_args)
+[rank1]:   File "/ocean/projects/cis240137p/hhe4/deepseek/open-r1/src/open_r1/sft.py", line 188, in main
+[rank1]:     train_result = trainer.train(resume_from_checkpoint=checkpoint)
+[rank1]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 2232, in train
+[rank1]:     return inner_training_loop(
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 2548, in _inner_training_loop
+[rank1]:     tr_loss_step = self.training_step(model, inputs, num_items_in_batch)
+[rank1]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 3698, in training_step
+[rank1]:     loss = self.compute_loss(model, inputs, num_items_in_batch=num_items_in_batch)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/trl/trainer/sft_trainer.py", line 469, in compute_loss
+[rank1]:     (loss, outputs) = super().compute_loss(
+[rank1]:                       ^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 3759, in compute_loss
+[rank1]:     outputs = model(**inputs)
+[rank1]:               ^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+[rank1]:     return self._call_impl(*args, **kwargs)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
+[rank1]:     return forward_call(*args, **kwargs)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/deepspeed/utils/nvtx.py", line 18, in wrapped_fn
+[rank1]:     ret_val = func(*args, **kwargs)
+[rank1]:               ^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 1899, in forward
+[rank1]:     loss = self.module(*inputs, **kwargs)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+[rank1]:     return self._call_impl(*args, **kwargs)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1844, in _call_impl
+[rank1]:     return inner()
+[rank1]:            ^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in inner
+[rank1]:     result = forward_call(*args, **kwargs)
+[rank1]:              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/ocean/projects/cis240137p/hhe4/hf_cache/modules/transformers_modules/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct/e434a23f91ba5b4923cf6c9d9a238eb4a08e3a11/modeling_deepseek.py", line 1702, in forward
+[rank1]:     loss = loss_fct(shift_logits, shift_labels)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+[rank1]:     return self._call_impl(*args, **kwargs)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
+[rank1]:     return forward_call(*args, **kwargs)
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/loss.py", line 1293, in forward
+[rank1]:     return F.cross_entropy(
+[rank1]:            ^^^^^^^^^^^^^^^^
+[rank1]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/functional.py", line 3479, in cross_entropy
+[rank1]:     return torch._C._nn.cross_entropy_loss(
+[rank1]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank1]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.24 GiB. GPU 1 has a total capacity of 79.21 GiB of which 604.75 MiB is free. Including non-PyTorch memory, this process has 78.61 GiB memory in use. Of the allocated memory 73.91 GiB is allocated by PyTorch, and 3.09 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
+king train dataset:   2%|▏         | 2000/93733 [00:38<20:32, 74.46 examples/s]
+Detected kernel version 4.18.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
+2025-04-12 00:20:30 - INFO - __main__ - *** Train ***
+2025-04-12 00:20:30 - INFO - __main__ - DeepseekV2ForCausalLM(
+  (model): DeepseekV2Model(
+    (embed_tokens): Embedding(102400, 2048)
+    (layers): ModuleList(
+      (0): DeepseekV2DecoderLayer(
+        (self_attn): DeepseekV2FlashAttention2(
+          (q_proj): Linear(in_features=2048, out_features=3072, bias=False)
+          (kv_a_proj_with_mqa): Linear(in_features=2048, out_features=576, bias=False)
+          (kv_a_layernorm): DeepseekV2RMSNorm()
+          (kv_b_proj): Linear(in_features=512, out_features=4096, bias=False)
+          (o_proj): Linear(in_features=2048, out_features=2048, bias=False)
+          (rotary_emb): DeepseekV2YarnRotaryEmbedding()
+        )
+        (mlp): DeepseekV2MLP(
+          (gate_proj): Linear(in_features=2048, out_features=10944, bias=False)
+          (up_proj): Linear(in_features=2048, out_features=10944, bias=False)
+          (down_proj): Linear(in_features=10944, out_features=2048, bias=False)
+          (act_fn): SiLU()
+        )
+        (input_layernorm): DeepseekV2RMSNorm()
+        (post_attention_layernorm): DeepseekV2RMSNorm()
+      )
+      (1-26): 26 x DeepseekV2DecoderLayer(
+        (self_attn): DeepseekV2FlashAttention2(
+          (q_proj): Linear(in_features=2048, out_features=3072, bias=False)
+          (kv_a_proj_with_mqa): Linear(in_features=2048, out_features=576, bias=False)
+          (kv_a_layernorm): DeepseekV2RMSNorm()
+          (kv_b_proj): Linear(in_features=512, out_features=4096, bias=False)
+          (o_proj): Linear(in_features=2048, out_features=2048, bias=False)
+          (rotary_emb): DeepseekV2YarnRotaryEmbedding()
+        )
+        (mlp): DeepseekV2MoE(
+          (experts): ModuleList(
+            (0-63): 64 x DeepseekV2MLP(
+              (gate_proj): Linear(in_features=2048, out_features=1408, bias=False)
+              (up_proj): Linear(in_features=2048, out_features=1408, bias=False)
+              (down_proj): Linear(in_features=1408, out_features=2048, bias=False)
+              (act_fn): SiLU()
+            )
+          )
+          (gate): MoEGate()
+          (shared_experts): DeepseekV2MLP(
+            (gate_proj): Linear(in_features=2048, out_features=2816, bias=False)
+            (up_proj): Linear(in_features=2048, out_features=2816, bias=False)
+            (down_proj): Linear(in_features=2816, out_features=2048, bias=False)
+            (act_fn): SiLU()
+          )
+        )
+        (input_layernorm): DeepseekV2RMSNorm()
+        (post_attention_layernorm): DeepseekV2RMSNorm()
+      )
+    )
+    (norm): DeepseekV2RMSNorm()
+  )
+  (lm_head): Linear(in_features=2048, out_features=102400, bias=False)
+)
+Parameter Offload: Total persistent parameters: 126464 in 82 params
+wandb: WARNING The `run_name` is currently set to the same value as `TrainingArguments.output_dir`. If this was not intended, please specify a different run name by setting the `TrainingArguments.run_name` parameter.
+wandb: Using wandb-core as the SDK backend.  Please refer to https://wandb.me/wandb-core for more information.
+wandb: Currently logged in as: hector_ (hector_-carnegie-mellon-university) to https://api.wandb.ai. Use `wandb login --relogin` to force relogin
+wandb: Tracking run with wandb version 0.19.8
+wandb: Run data is saved locally in /ocean/projects/cis240137p/hhe4/deepseek/open-r1/wandb/run-20250412_002043-nwpje7dw
+wandb: Run `wandb offline` to turn off syncing.
+wandb: Syncing run data/DeepSeek-Coder-V2-Lite-Instruct
+wandb: ⭐️ View project at https://wandb.ai/hector_-carnegie-mellon-university/huggingface
+wandb: 🚀 View run at https://wandb.ai/hector_-carnegie-mellon-university/huggingface/runs/nwpje7dw
+
  0%|          | 0/54042 [00:00<?, ?it/s]Traceback (most recent call last):
+  File "/ocean/projects/cis240137p/hhe4/deepseek/open-r1/src/open_r1/sft.py", line 234, in <module>
+    main(script_args, training_args, model_args)
+  File "/ocean/projects/cis240137p/hhe4/deepseek/open-r1/src/open_r1/sft.py", line 188, in main
+    train_result = trainer.train(resume_from_checkpoint=checkpoint)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 2232, in train
+    return inner_training_loop(
+           ^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 2548, in _inner_training_loop
+    tr_loss_step = self.training_step(model, inputs, num_items_in_batch)
+                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 3698, in training_step
+    loss = self.compute_loss(model, inputs, num_items_in_batch=num_items_in_batch)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/trl/trainer/sft_trainer.py", line 469, in compute_loss
+    (loss, outputs) = super().compute_loss(
+                      ^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 3759, in compute_loss
+    outputs = model(**inputs)
+              ^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/deepspeed/utils/nvtx.py", line 18, in wrapped_fn
+    ret_val = func(*args, **kwargs)
+              ^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 1899, in forward
+    loss = self.module(*inputs, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1844, in _call_impl
+    return inner()
+           ^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in inner
+    result = forward_call(*args, **kwargs)
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/ocean/projects/cis240137p/hhe4/hf_cache/modules/transformers_modules/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct/e434a23f91ba5b4923cf6c9d9a238eb4a08e3a11/modeling_deepseek.py", line 1702, in forward
+    loss = loss_fct(shift_logits, shift_labels)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+    return self._call_impl(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
+    return forward_call(*args, **kwargs)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/loss.py", line 1293, in forward
+    return F.cross_entropy(
+           ^^^^^^^^^^^^^^^^
+  File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/functional.py", line 3479, in cross_entropy
+    return torch._C._nn.cross_entropy_loss(
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.24 GiB. GPU 0 has a total capacity of 79.21 GiB of which 604.75 MiB is free. Including non-PyTorch memory, this process has 78.61 GiB memory in use. Of the allocated memory 73.91 GiB is allocated by PyTorch, and 3.09 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
+[rank0]: Traceback (most recent call last):
+[rank0]:   File "/ocean/projects/cis240137p/hhe4/deepseek/open-r1/src/open_r1/sft.py", line 234, in <module>
+[rank0]:     main(script_args, training_args, model_args)
+[rank0]:   File "/ocean/projects/cis240137p/hhe4/deepseek/open-r1/src/open_r1/sft.py", line 188, in main
+[rank0]:     train_result = trainer.train(resume_from_checkpoint=checkpoint)
+[rank0]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 2232, in train
+[rank0]:     return inner_training_loop(
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 2548, in _inner_training_loop
+[rank0]:     tr_loss_step = self.training_step(model, inputs, num_items_in_batch)
+[rank0]:                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 3698, in training_step
+[rank0]:     loss = self.compute_loss(model, inputs, num_items_in_batch=num_items_in_batch)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/trl/trainer/sft_trainer.py", line 469, in compute_loss
+[rank0]:     (loss, outputs) = super().compute_loss(
+[rank0]:                       ^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/transformers/trainer.py", line 3759, in compute_loss
+[rank0]:     outputs = model(**inputs)
+[rank0]:               ^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+[rank0]:     return self._call_impl(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
+[rank0]:     return forward_call(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/deepspeed/utils/nvtx.py", line 18, in wrapped_fn
+[rank0]:     ret_val = func(*args, **kwargs)
+[rank0]:               ^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/deepspeed/runtime/engine.py", line 1899, in forward
+[rank0]:     loss = self.module(*inputs, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+[rank0]:     return self._call_impl(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1844, in _call_impl
+[rank0]:     return inner()
+[rank0]:            ^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1790, in inner
+[rank0]:     result = forward_call(*args, **kwargs)
+[rank0]:              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/ocean/projects/cis240137p/hhe4/hf_cache/modules/transformers_modules/deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct/e434a23f91ba5b4923cf6c9d9a238eb4a08e3a11/modeling_deepseek.py", line 1702, in forward
+[rank0]:     loss = loss_fct(shift_logits, shift_labels)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
+[rank0]:     return self._call_impl(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
+[rank0]:     return forward_call(*args, **kwargs)
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/modules/loss.py", line 1293, in forward
+[rank0]:     return F.cross_entropy(
+[rank0]:            ^^^^^^^^^^^^^^^^
+[rank0]:   File "/jet/home/hhe4/deepseek/open-r1/openr1/lib/python3.11/site-packages/torch/nn/functional.py", line 3479, in cross_entropy
+[rank0]:     return torch._C._nn.cross_entropy_loss(
+[rank0]:            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+[rank0]: torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 6.24 GiB. GPU 0 has a total capacity of 79.21 GiB of which 604.75 MiB is free. Including non-PyTorch memory, this process has 78.61 GiB memory in use. Of the allocated memory 73.91 GiB is allocated by PyTorch, and 3.09 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

training_args.bin

@@ -0,0 +1,3 @@
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+oid sha256:784c8ddede97b768ac7df72d26cc44295ab6c84ab394fde376d273efc9af5e4c
+size 7544

training_backup.log

@@ -0,0 +1,525 @@
+2025-03-31 16:45:54 - INFO - __main__ - Model parameters ModelConfig(model_name_or_path='deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct', model_revision='main', torch_dtype='bfloat16', trust_remote_code=False, attn_implementation='flash_attention_2', use_peft=False, lora_r=16, lora_alpha=32, lora_dropout=0.05, lora_target_modules=None, lora_modules_to_save=None, lora_task_type='CAUSAL_LM', use_rslora=False, load_in_8bit=False, load_in_4bit=False, bnb_4bit_quant_type='nf4', use_bnb_nested_quant=False)
+2025-03-31 16:45:54 - INFO - __main__ - Script parameters ScriptArguments(dataset_name='open-r1/OpenR1-Math-220k', dataset_config=None, dataset_train_split='train', dataset_test_split='test', gradient_checkpointing_use_reentrant=False, ignore_bias_buffers=False)
+2025-03-31 16:45:54 - INFO - __main__ - Training parameters SFTConfig(
+_n_gpu=1,
+accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False},
+adafactor=False,
+adam_beta1=0.9,
+adam_beta2=0.999,
+adam_epsilon=1e-08,
+auto_find_batch_size=False,
+average_tokens_across_devices=False,
+batch_eval_metrics=False,
+benchmarks=[],
+bf16=True,
+bf16_full_eval=False,
+callbacks=[],
+chars_per_token=<CHARS_PER_TOKEN>,
+chat_template=None,
+data_seed=None,
+dataloader_drop_last=False,
+dataloader_num_workers=0,
+dataloader_persistent_workers=False,
+dataloader_pin_memory=True,
+dataloader_prefetch_factor=None,
+dataset_batch_size=None,
+dataset_kwargs=None,
+dataset_num_proc=None,
+dataset_text_field=text,
+ddp_backend=None,
+ddp_broadcast_buffers=None,
+ddp_bucket_cap_mb=None,
+ddp_find_unused_parameters=None,
+ddp_timeout=1800,
+debug=[],
+deepspeed=None,
+disable_tqdm=False,
+dispatch_batches=None,
+do_eval=True,
+do_predict=False,
+do_train=False,
+eval_accumulation_steps=None,
+eval_delay=0,
+eval_do_concat_batches=True,
+eval_on_start=False,
+eval_packing=None,
+eval_steps=None,
+eval_strategy=IntervalStrategy.NO,
+eval_use_gather_object=False,
+evaluation_strategy=None,
+fp16=False,
+fp16_backend=auto,
+fp16_full_eval=False,
+fp16_opt_level=O1,
+fsdp=[],
+fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False},
+fsdp_min_num_params=0,
+fsdp_transformer_layer_cls_to_wrap=None,
+full_determinism=False,
+gradient_accumulation_steps=1,
+gradient_checkpointing=True,
+gradient_checkpointing_kwargs={'use_reentrant': False},
+greater_is_better=None,
+group_by_length=False,
+half_precision_backend=auto,
+hub_always_push=False,
+hub_model_id=Deepseek-Coder-V2-Lite-13B-Instruct-Open-R1-Distill,
+hub_model_revision=main,
+hub_private_repo=None,
+hub_strategy=HubStrategy.EVERY_SAVE,
+hub_token=<HUB_TOKEN>,
+ignore_data_skip=False,
+include_for_metrics=[],
+include_inputs_for_metrics=False,
+include_num_input_tokens_seen=False,
+include_tokens_per_second=False,
+jit_mode_eval=False,
+label_names=None,
+label_smoothing_factor=0.0,
+learning_rate=5e-05,
+length_column_name=length,
+load_best_model_at_end=False,
+local_rank=0,
+log_level=info,
+log_level_replica=warning,
+log_on_each_node=True,
+logging_dir=data/DeepSeek-Coder-V2-Lite-Instruct/runs/Mar31_16-45-54_w002.ib.bridges2.psc.edu,
+logging_first_step=False,
+logging_nan_inf_filter=True,
+logging_steps=1,
+logging_strategy=IntervalStrategy.STEPS,
+lr_scheduler_kwargs={'min_lr_rate': 0.1},
+lr_scheduler_type=SchedulerType.COSINE_WITH_MIN_LR,
+max_grad_norm=1.0,
+max_length=32768,
+max_seq_length=None,
+max_steps=-1,
+metric_for_best_model=None,
+model_init_kwargs=None,
+mp_parameters=,
+neftune_noise_alpha=None,
+no_cuda=False,
+num_of_sequences=None,
+num_train_epochs=5,
+optim=OptimizerNames.ADAMW_TORCH,
+optim_args=None,
+optim_target_modules=None,
+output_dir=data/DeepSeek-Coder-V2-Lite-Instruct,
+overwrite_hub_revision=False,
+overwrite_output_dir=True,
+packing=True,
+past_index=-1,
+per_device_eval_batch_size=16,
+per_device_train_batch_size=16,
+prediction_loss_only=False,
+push_to_hub=True,
+push_to_hub_model_id=None,
+push_to_hub_organization=None,
+push_to_hub_revision=False,
+push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
+ray_scope=last,
+remove_unused_columns=True,
+report_to=['wandb'],
+restore_callback_states_from_checkpoint=False,
+resume_from_checkpoint=None,
+run_name=data/DeepSeek-Coder-V2-Lite-Instruct,
+save_on_each_node=False,
+save_only_model=False,
+save_safetensors=True,
+save_steps=200,
+save_strategy=SaveStrategy.STEPS,
+save_total_limit=1,
+seed=42,
+skip_memory_metrics=True,
+split_batches=None,
+system_prompt=None,
+tf32=None,
+torch_compile=False,
+torch_compile_backend=None,
+torch_compile_mode=None,
+torch_empty_cache_steps=None,
+torchdynamo=None,
+tpu_metrics_debug=False,
+tpu_num_cores=None,
+use_cpu=False,
+use_ipex=False,
+use_legacy_prediction_loop=False,
+use_liger=True,
+use_liger_kernel=False,
+use_mps_device=False,
+wandb_entity=None,
+wandb_project=None,
+warmup_ratio=0.1,
+warmup_steps=0,
+weight_decay=0.0,
+)
+2025-03-31 16:45:57 - INFO - __main__ - *** Initializing model kwargs ***
+2025-03-31 16:48:46 - INFO - __main__ - Model parameters ModelConfig(model_name_or_path='deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct', model_revision='main', torch_dtype='bfloat16', trust_remote_code=True, attn_implementation='flash_attention_2', use_peft=False, lora_r=16, lora_alpha=32, lora_dropout=0.05, lora_target_modules=None, lora_modules_to_save=None, lora_task_type='CAUSAL_LM', use_rslora=False, load_in_8bit=False, load_in_4bit=False, bnb_4bit_quant_type='nf4', use_bnb_nested_quant=False)
+2025-03-31 16:48:46 - INFO - __main__ - Script parameters ScriptArguments(dataset_name='open-r1/OpenR1-Math-220k', dataset_config=None, dataset_train_split='train', dataset_test_split='test', gradient_checkpointing_use_reentrant=False, ignore_bias_buffers=False)
+2025-03-31 16:48:46 - INFO - __main__ - Training parameters SFTConfig(
+_n_gpu=1,
+accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False},
+adafactor=False,
+adam_beta1=0.9,
+adam_beta2=0.999,
+adam_epsilon=1e-08,
+auto_find_batch_size=False,
+average_tokens_across_devices=False,
+batch_eval_metrics=False,
+benchmarks=[],
+bf16=True,
+bf16_full_eval=False,
+callbacks=[],
+chars_per_token=<CHARS_PER_TOKEN>,
+chat_template=None,
+data_seed=None,
+dataloader_drop_last=False,
+dataloader_num_workers=0,
+dataloader_persistent_workers=False,
+dataloader_pin_memory=True,
+dataloader_prefetch_factor=None,
+dataset_batch_size=None,
+dataset_kwargs=None,
+dataset_num_proc=None,
+dataset_text_field=text,
+ddp_backend=None,
+ddp_broadcast_buffers=None,
+ddp_bucket_cap_mb=None,
+ddp_find_unused_parameters=None,
+ddp_timeout=1800,
+debug=[],
+deepspeed=None,
+disable_tqdm=False,
+dispatch_batches=None,
+do_eval=True,
+do_predict=False,
+do_train=False,
+eval_accumulation_steps=None,
+eval_delay=0,
+eval_do_concat_batches=True,
+eval_on_start=False,
+eval_packing=None,
+eval_steps=None,
+eval_strategy=IntervalStrategy.NO,
+eval_use_gather_object=False,
+evaluation_strategy=None,
+fp16=False,
+fp16_backend=auto,
+fp16_full_eval=False,
+fp16_opt_level=O1,
+fsdp=[],
+fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False},
+fsdp_min_num_params=0,
+fsdp_transformer_layer_cls_to_wrap=None,
+full_determinism=False,
+gradient_accumulation_steps=1,
+gradient_checkpointing=True,
+gradient_checkpointing_kwargs={'use_reentrant': False},
+greater_is_better=None,
+group_by_length=False,
+half_precision_backend=auto,
+hub_always_push=False,
+hub_model_id=Deepseek-Coder-V2-Lite-13B-Instruct-Open-R1-Distill,
+hub_model_revision=main,
+hub_private_repo=None,
+hub_strategy=HubStrategy.EVERY_SAVE,
+hub_token=<HUB_TOKEN>,
+ignore_data_skip=False,
+include_for_metrics=[],
+include_inputs_for_metrics=False,
+include_num_input_tokens_seen=False,
+include_tokens_per_second=False,
+jit_mode_eval=False,
+label_names=None,
+label_smoothing_factor=0.0,
+learning_rate=5e-05,
+length_column_name=length,
+load_best_model_at_end=False,
+local_rank=0,
+log_level=info,
+log_level_replica=warning,
+log_on_each_node=True,
+logging_dir=data/DeepSeek-Coder-V2-Lite-Instruct/runs/Mar31_16-48-46_w002.ib.bridges2.psc.edu,
+logging_first_step=False,
+logging_nan_inf_filter=True,
+logging_steps=1,
+logging_strategy=IntervalStrategy.STEPS,
+lr_scheduler_kwargs={'min_lr_rate': 0.1},
+lr_scheduler_type=SchedulerType.COSINE_WITH_MIN_LR,
+max_grad_norm=1.0,
+max_length=32768,
+max_seq_length=None,
+max_steps=-1,
+metric_for_best_model=None,
+model_init_kwargs=None,
+mp_parameters=,
+neftune_noise_alpha=None,
+no_cuda=False,
+num_of_sequences=None,
+num_train_epochs=5,
+optim=OptimizerNames.ADAMW_TORCH,
+optim_args=None,
+optim_target_modules=None,
+output_dir=data/DeepSeek-Coder-V2-Lite-Instruct,
+overwrite_hub_revision=False,
+overwrite_output_dir=True,
+packing=True,
+past_index=-1,
+per_device_eval_batch_size=16,
+per_device_train_batch_size=16,
+prediction_loss_only=False,
+push_to_hub=True,
+push_to_hub_model_id=None,
+push_to_hub_organization=None,
+push_to_hub_revision=False,
+push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
+ray_scope=last,
+remove_unused_columns=True,
+report_to=['wandb'],
+restore_callback_states_from_checkpoint=False,
+resume_from_checkpoint=None,
+run_name=data/DeepSeek-Coder-V2-Lite-Instruct,
+save_on_each_node=False,
+save_only_model=False,
+save_safetensors=True,
+save_steps=200,
+save_strategy=SaveStrategy.STEPS,
+save_total_limit=1,
+seed=42,
+skip_memory_metrics=True,
+split_batches=None,
+system_prompt=None,
+tf32=None,
+torch_compile=False,
+torch_compile_backend=None,
+torch_compile_mode=None,
+torch_empty_cache_steps=None,
+torchdynamo=None,
+tpu_metrics_debug=False,
+tpu_num_cores=None,
+use_cpu=False,
+use_ipex=False,
+use_legacy_prediction_loop=False,
+use_liger=True,
+use_liger_kernel=False,
+use_mps_device=False,
+wandb_entity=None,
+wandb_project=None,
+warmup_ratio=0.1,
+warmup_steps=0,
+weight_decay=0.0,
+)
+2025-03-31 16:48:48 - INFO - __main__ - *** Initializing model kwargs ***
+2025-03-31 16:54:35 - INFO - __main__ - Model parameters ModelConfig(model_name_or_path='deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct', model_revision='main', torch_dtype='bfloat16', trust_remote_code=True, attn_implementation='flash_attention_2', use_peft=False, lora_r=16, lora_alpha=32, lora_dropout=0.05, lora_target_modules=None, lora_modules_to_save=None, lora_task_type='CAUSAL_LM', use_rslora=False, load_in_8bit=False, load_in_4bit=False, bnb_4bit_quant_type='nf4', use_bnb_nested_quant=False)
+2025-03-31 16:54:35 - INFO - __main__ - Script parameters ScriptArguments(dataset_name='open-r1/OpenR1-Math-220k', dataset_config=None, dataset_train_split='train', dataset_test_split='test', gradient_checkpointing_use_reentrant=False, ignore_bias_buffers=False)
+2025-03-31 16:54:35 - INFO - __main__ - Training parameters SFTConfig(
+_n_gpu=1,
+accelerator_config={'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None, 'use_configured_state': False},
+adafactor=False,
+adam_beta1=0.9,
+adam_beta2=0.999,
+adam_epsilon=1e-08,
+auto_find_batch_size=False,
+average_tokens_across_devices=False,
+batch_eval_metrics=False,
+benchmarks=[],
+bf16=True,
+bf16_full_eval=False,
+callbacks=[],
+chars_per_token=<CHARS_PER_TOKEN>,
+chat_template=None,
+data_seed=None,
+dataloader_drop_last=False,
+dataloader_num_workers=0,
+dataloader_persistent_workers=False,
+dataloader_pin_memory=True,
+dataloader_prefetch_factor=None,
+dataset_batch_size=None,
+dataset_kwargs=None,
+dataset_num_proc=None,
+dataset_text_field=text,
+ddp_backend=None,
+ddp_broadcast_buffers=None,
+ddp_bucket_cap_mb=None,
+ddp_find_unused_parameters=None,
+ddp_timeout=1800,
+debug=[],
+deepspeed=None,
+disable_tqdm=False,
+dispatch_batches=None,
+do_eval=True,
+do_predict=False,
+do_train=False,
+eval_accumulation_steps=None,
+eval_delay=0,
+eval_do_concat_batches=True,
+eval_on_start=False,
+eval_packing=None,
+eval_steps=None,
+eval_strategy=IntervalStrategy.NO,
+eval_use_gather_object=False,
+evaluation_strategy=None,
+fp16=False,
+fp16_backend=auto,
+fp16_full_eval=False,
+fp16_opt_level=O1,
+fsdp=[],
+fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False},
+fsdp_min_num_params=0,
+fsdp_transformer_layer_cls_to_wrap=None,
+full_determinism=False,
+gradient_accumulation_steps=1,
+gradient_checkpointing=True,
+gradient_checkpointing_kwargs={'use_reentrant': False},
+greater_is_better=None,
+group_by_length=False,
+half_precision_backend=auto,
+hub_always_push=False,
+hub_model_id=Deepseek-Coder-V2-Lite-13B-Instruct-Open-R1-Distill,
+hub_model_revision=main,
+hub_private_repo=None,
+hub_strategy=HubStrategy.EVERY_SAVE,
+hub_token=<HUB_TOKEN>,
+ignore_data_skip=False,
+include_for_metrics=[],
+include_inputs_for_metrics=False,
+include_num_input_tokens_seen=False,
+include_tokens_per_second=False,
+jit_mode_eval=False,
+label_names=None,
+label_smoothing_factor=0.0,
+learning_rate=5e-05,
+length_column_name=length,
+load_best_model_at_end=False,
+local_rank=0,
+log_level=info,
+log_level_replica=warning,
+log_on_each_node=True,
+logging_dir=data/DeepSeek-Coder-V2-Lite-Instruct/runs/Mar31_16-54-34_w002.ib.bridges2.psc.edu,
+logging_first_step=False,
+logging_nan_inf_filter=True,
+logging_steps=1,
+logging_strategy=IntervalStrategy.STEPS,
+lr_scheduler_kwargs={'min_lr_rate': 0.1},
+lr_scheduler_type=SchedulerType.COSINE_WITH_MIN_LR,
+max_grad_norm=1.0,
+max_length=32768,
+max_seq_length=None,
+max_steps=-1,
+metric_for_best_model=None,
+model_init_kwargs=None,
+mp_parameters=,
+neftune_noise_alpha=None,
+no_cuda=False,
+num_of_sequences=None,
+num_train_epochs=5,
+optim=OptimizerNames.ADAMW_TORCH,
+optim_args=None,
+optim_target_modules=None,
+output_dir=data/DeepSeek-Coder-V2-Lite-Instruct,
+overwrite_hub_revision=False,
+overwrite_output_dir=True,
+packing=True,
+past_index=-1,
+per_device_eval_batch_size=16,
+per_device_train_batch_size=16,
+prediction_loss_only=False,
+push_to_hub=True,
+push_to_hub_model_id=None,
+push_to_hub_organization=None,
+push_to_hub_revision=False,
+push_to_hub_token=<PUSH_TO_HUB_TOKEN>,
+ray_scope=last,
+remove_unused_columns=True,
+report_to=['wandb'],
+restore_callback_states_from_checkpoint=False,
+resume_from_checkpoint=None,
+run_name=data/DeepSeek-Coder-V2-Lite-Instruct,
+save_on_each_node=False,
+save_only_model=False,
+save_safetensors=True,
+save_steps=200,
+save_strategy=SaveStrategy.STEPS,
+save_total_limit=1,
+seed=42,
+skip_memory_metrics=True,
+split_batches=None,
+system_prompt=None,
+tf32=None,
+torch_compile=False,
+torch_compile_backend=None,
+torch_compile_mode=None,
+torch_empty_cache_steps=None,
+torchdynamo=None,
+tpu_metrics_debug=False,
+tpu_num_cores=None,
+use_cpu=False,
+use_ipex=False,
+use_legacy_prediction_loop=False,
+use_liger=False,
+use_liger_kernel=False,
+use_mps_device=False,
+wandb_entity=None,
+wandb_project=None,
+warmup_ratio=0.1,
+warmup_steps=0,
+weight_decay=0.0,
+)
+2025-03-31 16:54:36 - INFO - __main__ - *** Initializing model kwargs ***
+2025-03-31 17:52:07 - INFO - __main__ - *** Train ***
+2025-03-31 17:52:07 - INFO - __main__ - DeepseekV2ForCausalLM(
+  (model): DeepseekV2Model(
+    (embed_tokens): Embedding(102400, 2048)
+    (layers): ModuleList(
+      (0): DeepseekV2DecoderLayer(
+        (self_attn): DeepseekV2FlashAttention2(
+          (q_proj): Linear(in_features=2048, out_features=3072, bias=False)
+          (kv_a_proj_with_mqa): Linear(in_features=2048, out_features=576, bias=False)
+          (kv_a_layernorm): DeepseekV2RMSNorm()
+          (kv_b_proj): Linear(in_features=512, out_features=4096, bias=False)
+          (o_proj): Linear(in_features=2048, out_features=2048, bias=False)
+          (rotary_emb): DeepseekV2YarnRotaryEmbedding()
+        )
+        (mlp): DeepseekV2MLP(
+          (gate_proj): Linear(in_features=2048, out_features=10944, bias=False)
+          (up_proj): Linear(in_features=2048, out_features=10944, bias=False)
+          (down_proj): Linear(in_features=10944, out_features=2048, bias=False)
+          (act_fn): SiLU()
+        )
+        (input_layernorm): DeepseekV2RMSNorm()
+        (post_attention_layernorm): DeepseekV2RMSNorm()
+      )
+      (1-26): 26 x DeepseekV2DecoderLayer(
+        (self_attn): DeepseekV2FlashAttention2(
+          (q_proj): Linear(in_features=2048, out_features=3072, bias=False)
+          (kv_a_proj_with_mqa): Linear(in_features=2048, out_features=576, bias=False)
+          (kv_a_layernorm): DeepseekV2RMSNorm()
+          (kv_b_proj): Linear(in_features=512, out_features=4096, bias=False)
+          (o_proj): Linear(in_features=2048, out_features=2048, bias=False)
+          (rotary_emb): DeepseekV2YarnRotaryEmbedding()
+        )
+        (mlp): DeepseekV2MoE(
+          (experts): ModuleList(
+            (0-63): 64 x DeepseekV2MLP(
+              (gate_proj): Linear(in_features=2048, out_features=1408, bias=False)
+              (up_proj): Linear(in_features=2048, out_features=1408, bias=False)
+              (down_proj): Linear(in_features=1408, out_features=2048, bias=False)
+              (act_fn): SiLU()
+            )
+          )
+          (gate): MoEGate()
+          (shared_experts): DeepseekV2MLP(
+            (gate_proj): Linear(in_features=2048, out_features=2816, bias=False)
+            (up_proj): Linear(in_features=2048, out_features=2816, bias=False)
+            (down_proj): Linear(in_features=2816, out_features=2048, bias=False)
+            (act_fn): SiLU()
+          )
+        )
+        (input_layernorm): DeepseekV2RMSNorm()
+        (post_attention_layernorm): DeepseekV2RMSNorm()
+      )
+    )
+    (norm): DeepseekV2RMSNorm()
+  )
+  (lm_head): Linear(in_features=2048, out_features=102400, bias=False)
+)