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[2025-11-06 16:11:41,516] [DEBUG] [axolotl.utils.config.log_gpu_memory_usage:127] [PID:837642] baseline 0.000GB ()
[2025-11-06 16:11:41,516] [INFO] [axolotl.cli.config.load_cfg:248] [PID:837642] config:
{
"activation_offloading": false,
"axolotl_config_path": "3b-qat-nvfp4.yaml",
"base_model": "meta-llama/Llama-3.2-3B",
"base_model_config": "meta-llama/Llama-3.2-3B",
"batch_size": 64,
"bf16": true,
"capabilities": {
"bf16": true,
"compute_capability": "sm_90",
"fp8": false,
"n_gpu": 1,
"n_node": 1
},
"context_parallel_size": 1,
"cosine_constant_lr_ratio": 0.0,
"cosine_min_lr_ratio": 1.0,
"dataloader_num_workers": 1,
"dataloader_pin_memory": true,
"dataloader_prefetch_factor": 256,
"dataset_prepared_path": "./outputs/dataset_prepared",
"dataset_processes": 128,
"datasets": [
{
"message_property_mappings": {
"content": "content",
"role": "role"
},
"path": "yahma/alpaca-cleaned",
"split": "train[:95%]",
"trust_remote_code": false,
"type": "alpaca"
}
],
"ddp": false,
"device": "cuda:0",
"dion_rank_fraction": 1.0,
"dion_rank_multiple_of": 1,
"env_capabilities": {
"torch_version": "2.8.0"
},
"eval_batch_size": 64,
"eval_causal_lm_metrics": [
"sacrebleu",
"comet",
"ter",
"chrf"
],
"eval_max_new_tokens": 128,
"eval_table_size": 0,
"evals_per_epoch": 1,
"experimental_skip_move_to_device": true,
"flash_attention": true,
"fp16": false,
"gradient_accumulation_steps": 1,
"gradient_checkpointing": true,
"gradient_checkpointing_kwargs": {
"use_reentrant": true
},
"hub_model_id": "AlexHung29629/3b-qat-nvfp4",
"include_tkps": true,
"is_llama_derived_model": true,
"learning_rate": 2e-05,
"liger_fused_linear_cross_entropy": true,
"liger_glu_activation": true,
"liger_layer_norm": true,
"liger_rms_norm": true,
"liger_rope": true,
"lisa_layers_attribute": "model.layers",
"load_best_model_at_end": false,
"load_in_4bit": false,
"load_in_8bit": false,
"local_rank": 0,
"logging_steps": 1,
"lora_dropout": 0.0,
"loraplus_lr_embedding": 1e-06,
"lr_scheduler": "cosine",
"mean_resizing_embeddings": false,
"micro_batch_size": 64,
"model_config_type": "llama",
"num_epochs": 1.0,
"optimizer": "adamw_torch_fused",
"output_dir": "./outputs/qat_out/",
"plugins": [
"axolotl.integrations.liger.LigerPlugin"
],
"pretrain_multipack_attn": true,
"profiler_steps_start": 0,
"qat": {
"activation_dtype": "TorchAOQuantDType.nvfp4",
"group_size": 16,
"quantize_embedding": false,
"weight_dtype": "TorchAOQuantDType.nvfp4"
},
"qlora_sharded_model_loading": false,
"ray_num_workers": 1,
"resources_per_worker": {
"GPU": 1
},
"sample_packing_bin_size": 200,
"sample_packing_group_size": 100000,
"save_first_step": true,
"save_only_model": true,
"save_safetensors": true,
"saves_per_epoch": 1,
"sequence_len": 8192,
"shuffle_before_merging_datasets": false,
"shuffle_merged_datasets": true,
"skip_prepare_dataset": false,
"special_tokens": {
"pad_token": "<|finetune_right_pad_id|>"
},
"streaming_multipack_buffer_size": 10000,
"strict": false,
"tensor_parallel_size": 1,
"tiled_mlp_use_original_mlp": true,
"tokenizer_config": "meta-llama/Llama-3.2-3B",
"tokenizer_save_jinja_files": true,
"torch_dtype": "torch.bfloat16",
"train_on_inputs": false,
"trl": {
"log_completions": false,
"mask_truncated_completions": false,
"ref_model_mixup_alpha": 0.9,
"ref_model_sync_steps": 64,
"scale_rewards": true,
"sync_ref_model": false,
"use_vllm": false,
"vllm_server_host": "0.0.0.0",
"vllm_server_port": 8000
},
"use_ray": false,
"val_set_size": 0.0,
"vllm": {
"device": "auto",
"dtype": "auto",
"gpu_memory_utilization": 0.9,
"host": "0.0.0.0",
"port": 8000
},
"warmup_ratio": 0.1,
"weight_decay": 0.0,
"world_size": 1
}
[2025-11-06 16:11:46,489] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:278] [PID:837642] EOS: 128001 / <|end_of_text|>
[2025-11-06 16:11:46,489] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:279] [PID:837642] BOS: 128000 / <|begin_of_text|>
[2025-11-06 16:11:46,489] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:280] [PID:837642] PAD: 128004 / <|finetune_right_pad_id|>
[2025-11-06 16:11:46,489] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:837642] UNK: None / None
[2025-11-06 16:11:46,489] [INFO] [axolotl.loaders.tokenizer.load_tokenizer:295] [PID:837642] No Chat template selected. Consider adding a chat template for easier inference.
[2025-11-06 16:11:46,492] [INFO] [axolotl.utils.data.shared.load_preprocessed_dataset:476] [PID:837642] Unable to find prepared dataset in outputs/dataset_prepared/9bc662aed65b76546b2d635b3957a343
[2025-11-06 16:11:46,492] [INFO] [axolotl.utils.data.sft._load_raw_datasets:320] [PID:837642] Loading raw datasets...
[2025-11-06 16:11:46,492] [WARNING] [axolotl.utils.data.sft._load_raw_datasets:322] [PID:837642] Processing datasets during training can lead to VRAM instability. Please pre-process your dataset using `axolotl preprocess path/to/config.yml`.
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[2025-11-06 16:12:08,982] [INFO] [axolotl.utils.data.wrappers.get_dataset_wrapper:87] [PID:837642] Loading dataset: yahma/alpaca-cleaned with base_type: alpaca and prompt_style: None
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[2025-11-06 16:12:28,393] [INFO] [axolotl.utils.data.utils.handle_long_seq_in_dataset:218] [PID:837642] min_input_len: 33
[2025-11-06 16:12:28,393] [INFO] [axolotl.utils.data.utils.handle_long_seq_in_dataset:220] [PID:837642] max_input_len: 1051
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[2025-11-06 16:12:34,233] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:404] [PID:837642] total_num_tokens: 9_208_425
[2025-11-06 16:12:34,425] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:422] [PID:837642] `total_supervised_tokens: 6_847_432`
[2025-11-06 16:12:34,425] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:520] [PID:837642] total_num_steps: 769
[2025-11-06 16:12:34,425] [INFO] [axolotl.utils.data.sft._prepare_standard_dataset:121] [PID:837642] Maximum number of steps set at 769
[2025-11-06 16:12:34,441] [DEBUG] [axolotl.train.setup_model_and_tokenizer:70] [PID:837642] Loading tokenizer... meta-llama/Llama-3.2-3B
[2025-11-06 16:12:35,271] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:278] [PID:837642] EOS: 128001 / <|end_of_text|>
[2025-11-06 16:12:35,271] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:279] [PID:837642] BOS: 128000 / <|begin_of_text|>
[2025-11-06 16:12:35,271] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:280] [PID:837642] PAD: 128004 / <|finetune_right_pad_id|>
[2025-11-06 16:12:35,271] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:837642] UNK: None / None
[2025-11-06 16:12:35,271] [INFO] [axolotl.loaders.tokenizer.load_tokenizer:295] [PID:837642] No Chat template selected. Consider adding a chat template for easier inference.
[2025-11-06 16:12:35,271] [DEBUG] [axolotl.train.setup_model_and_tokenizer:79] [PID:837642] Loading model
[2025-11-06 16:12:35,502] [DEBUG] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_evaluation_loop:87] [PID:837642] Patched Trainer.evaluation_loop with nanmean loss calculation
[2025-11-06 16:12:35,503] [DEBUG] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_maybe_log_save_evaluate:138] [PID:837642] Patched Trainer._maybe_log_save_evaluate with nanmean loss calculation
[2025-11-06 16:12:35,531] [INFO] [axolotl.integrations.liger.plugin.pre_model_load:71] [PID:837642] Applying LIGER to llama with kwargs: {'rope': True, 'cross_entropy': None, 'fused_linear_cross_entropy': True, 'rms_norm': True, 'swiglu': True}
Loading checkpoint shards: 0%| | 0/2 [00:00<?, ?it/s]
Loading checkpoint shards: 100%|██████████| 2/2 [00:00<00:00, 86.01it/s]
[2025-11-06 16:15:46,317] [INFO] [axolotl.loaders.model._configure_embedding_dtypes:345] [PID:837642] Converting modules to torch.bfloat16
[2025-11-06 16:15:59,472] [DEBUG] [axolotl.loaders.model.log_gpu_memory_usage:127] [PID:837642] Memory usage after model load 0.000GB ()
[2025-11-06 16:16:00,600] [WARNING] [accelerate.utils.other.check_os_kernel:512] [PID:837642] 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.
[2025-11-06 16:16:07,189] [INFO] [axolotl.train.save_initial_configs:412] [PID:837642] Pre-saving tokenizer to ./outputs/qat_out/...
[2025-11-06 16:16:07,288] [INFO] [axolotl.train.save_initial_configs:417] [PID:837642] Pre-saving model config to ./outputs/qat_out/...
[2025-11-06 16:16:07,290] [INFO] [axolotl.train.execute_training:203] [PID:837642] Starting trainer...
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{'loss': 1.1473, 'grad_norm': 4.625, 'learning_rate': 0.0, 'memory/max_active (GiB)': 34.78, 'memory/max_allocated (GiB)': 34.78, 'memory/device_reserved (GiB)': 41.06, 'tokens_per_second_per_gpu': 879.01, 'epoch': 0.0}
0%| | 1/769 [00:10<2:09:18, 10.10s/it][2025-11-06 16:16:17,683] [INFO] [axolotl.core.trainers.base._save:671] [PID:837642] Saving model checkpoint to ./outputs/qat_out/checkpoint-1
0%| | 2/769 [00:28<3:13:22, 15.13s/it]
{'loss': 1.1048, 'grad_norm': 4.34375, 'learning_rate': 2.6315789473684213e-07, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 55.05, 'tokens_per_second_per_gpu': 1653.05, 'epoch': 0.0}
0%| | 2/769 [00:28<3:13:22, 15.13s/it]
0%| | 3/769 [00:35<2:23:03, 11.21s/it]
{'loss': 1.1442, 'grad_norm': 4.6875, 'learning_rate': 5.263157894736843e-07, 'memory/max_active (GiB)': 49.73, 'memory/max_allocated (GiB)': 49.73, 'memory/device_reserved (GiB)': 76.38, 'tokens_per_second_per_gpu': 1475.08, 'epoch': 0.0}
0%| | 3/769 [00:35<2:23:03, 11.21s/it]
1%| | 4/769 [00:40<1:55:11, 9.03s/it]
{'loss': 1.1473, 'grad_norm': 3.671875, 'learning_rate': 7.894736842105263e-07, 'memory/max_active (GiB)': 46.8, 'memory/max_allocated (GiB)': 46.8, 'memory/device_reserved (GiB)': 76.38, 'tokens_per_second_per_gpu': 2080.31, 'epoch': 0.01}
1%| | 4/769 [00:41<1:55:11, 9.03s/it]
1%| | 5/769 [00:46<1:39:41, 7.83s/it]
{'loss': 1.1704, 'grad_norm': 4.15625, 'learning_rate': 1.0526315789473685e-06, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 76.38, 'tokens_per_second_per_gpu': 1673.31, 'epoch': 0.01}
1%| | 5/769 [00:46<1:39:41, 7.83s/it]
1%| | 6/769 [00:51<1:28:32, 6.96s/it]
{'loss': 1.1557, 'grad_norm': 4.09375, 'learning_rate': 1.3157894736842106e-06, 'memory/max_active (GiB)': 43.82, 'memory/max_allocated (GiB)': 43.82, 'memory/device_reserved (GiB)': 78.38, 'tokens_per_second_per_gpu': 1894.62, 'epoch': 0.01}
1%| | 6/769 [00:51<1:28:32, 6.96s/it]
1%| | 7/769 [00:57<1:20:49, 6.36s/it]
{'loss': 1.1819, 'grad_norm': 5.21875, 'learning_rate': 1.5789473684210526e-06, 'memory/max_active (GiB)': 43.82, 'memory/max_allocated (GiB)': 43.82, 'memory/device_reserved (GiB)': 77.51, 'tokens_per_second_per_gpu': 1854.54, 'epoch': 0.01}
1%| | 7/769 [00:57<1:20:49, 6.36s/it]
1%| | 8/769 [01:02<1:18:07, 6.16s/it]
{'loss': 1.1807, 'grad_norm': 4.125, 'learning_rate': 1.8421052631578948e-06, 'memory/max_active (GiB)': 46.78, 'memory/max_allocated (GiB)': 46.78, 'memory/device_reserved (GiB)': 78.38, 'tokens_per_second_per_gpu': 1751.39, 'epoch': 0.01}
1%| | 8/769 [01:02<1:18:07, 6.16s/it]
1%| | 9/769 [01:08<1:16:07, 6.01s/it]
{'loss': 1.1324, 'grad_norm': 4.40625, 'learning_rate': 2.105263157894737e-06, 'memory/max_active (GiB)': 46.75, 'memory/max_allocated (GiB)': 46.75, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1412.84, 'epoch': 0.01}
1%| | 9/769 [01:08<1:16:07, 6.01s/it]
1%|▏ | 10/769 [01:13<1:12:34, 5.74s/it]
{'loss': 1.1556, 'grad_norm': 3.78125, 'learning_rate': 2.368421052631579e-06, 'memory/max_active (GiB)': 43.82, 'memory/max_allocated (GiB)': 43.82, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1849.28, 'epoch': 0.01}
1%|▏ | 10/769 [01:13<1:12:34, 5.74s/it]
1%|▏ | 11/769 [01:19<1:12:17, 5.72s/it]
{'loss': 1.1855, 'grad_norm': 3.859375, 'learning_rate': 2.631578947368421e-06, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1624.94, 'epoch': 0.01}
1%|▏ | 11/769 [01:19<1:12:17, 5.72s/it]
2%|▏ | 12/769 [01:24<1:12:03, 5.71s/it]
{'loss': 1.1024, 'grad_norm': 4.09375, 'learning_rate': 2.8947368421052634e-06, 'memory/max_active (GiB)': 46.75, 'memory/max_allocated (GiB)': 46.75, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1463.62, 'epoch': 0.02}
2%|▏ | 12/769 [01:25<1:12:03, 5.71s/it]
2%|▏ | 13/769 [01:29<1:08:10, 5.41s/it]
{'loss': 1.1591, 'grad_norm': 3.765625, 'learning_rate': 3.157894736842105e-06, 'memory/max_active (GiB)': 41.5, 'memory/max_allocated (GiB)': 41.5, 'memory/device_reserved (GiB)': 78.38, 'tokens_per_second_per_gpu': 1910.89, 'epoch': 0.02}
2%|▏ | 13/769 [01:29<1:08:10, 5.41s/it]
2%|▏ | 14/769 [01:35<1:09:08, 5.49s/it]
{'loss': 1.0844, 'grad_norm': 3.484375, 'learning_rate': 3.421052631578948e-06, 'memory/max_active (GiB)': 46.76, 'memory/max_allocated (GiB)': 46.76, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1588.42, 'epoch': 0.02}
2%|▏ | 14/769 [01:35<1:09:08, 5.49s/it]
2%|▏ | 15/769 [01:39<1:05:28, 5.21s/it]
{'loss': 1.2444, 'grad_norm': 3.984375, 'learning_rate': 3.6842105263157896e-06, 'memory/max_active (GiB)': 41.46, 'memory/max_allocated (GiB)': 41.46, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1568.51, 'epoch': 0.02}
2%|▏ | 15/769 [01:39<1:05:28, 5.21s/it]
2%|▏ | 16/769 [01:45<1:07:09, 5.35s/it]
{'loss': 1.1609, 'grad_norm': 3.578125, 'learning_rate': 3.947368421052632e-06, 'memory/max_active (GiB)': 46.74, 'memory/max_allocated (GiB)': 46.74, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1338.16, 'epoch': 0.02}
2%|▏ | 16/769 [01:45<1:07:09, 5.35s/it]
2%|▏ | 17/769 [01:51<1:08:21, 5.45s/it]
{'loss': 1.099, 'grad_norm': 3.125, 'learning_rate': 4.210526315789474e-06, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1704.75, 'epoch': 0.02}
2%|▏ | 17/769 [01:51<1:08:21, 5.45s/it]
2%|▏ | 18/769 [01:57<1:09:09, 5.53s/it]
{'loss': 1.0828, 'grad_norm': 3.046875, 'learning_rate': 4.473684210526316e-06, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.88, 'tokens_per_second_per_gpu': 1664.81, 'epoch': 0.02}
2%|▏ | 18/769 [01:57<1:09:09, 5.53s/it]
2%|▏ | 19/769 [02:02<1:07:39, 5.41s/it]
{'loss': 1.2319, 'grad_norm': 3.4375, 'learning_rate': 4.736842105263158e-06, 'memory/max_active (GiB)': 43.8, 'memory/max_allocated (GiB)': 43.8, 'memory/device_reserved (GiB)': 78.38, 'tokens_per_second_per_gpu': 1602.68, 'epoch': 0.02}
2%|▏ | 19/769 [02:02<1:07:39, 5.41s/it]
3%|▎ | 20/769 [02:07<1:08:44, 5.51s/it]
{'loss': 1.0638, 'grad_norm': 2.953125, 'learning_rate': 5e-06, 'memory/max_active (GiB)': 46.78, 'memory/max_allocated (GiB)': 46.78, 'memory/device_reserved (GiB)': 78.13, 'tokens_per_second_per_gpu': 1755.41, 'epoch': 0.03}
3%|▎ | 20/769 [02:07<1:08:44, 5.51s/it]
3%|▎ | 21/769 [02:13<1:09:22, 5.56s/it]
{'loss': 1.2072, 'grad_norm': 2.859375, 'learning_rate': 5.263157894736842e-06, 'memory/max_active (GiB)': 46.78, 'memory/max_allocated (GiB)': 46.78, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1833.74, 'epoch': 0.03}
3%|▎ | 21/769 [02:13<1:09:22, 5.56s/it]
3%|▎ | 22/769 [02:18<1:07:37, 5.43s/it]
{'loss': 1.2006, 'grad_norm': 3.109375, 'learning_rate': 5.526315789473685e-06, 'memory/max_active (GiB)': 43.79, 'memory/max_allocated (GiB)': 43.79, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1567.66, 'epoch': 0.03}
3%|▎ | 22/769 [02:18<1:07:37, 5.43s/it]
3%|▎ | 23/769 [02:25<1:12:34, 5.84s/it]
{'loss': 1.0081, 'grad_norm': 2.625, 'learning_rate': 5.789473684210527e-06, 'memory/max_active (GiB)': 49.73, 'memory/max_allocated (GiB)': 49.73, 'memory/device_reserved (GiB)': 78.38, 'tokens_per_second_per_gpu': 1412.25, 'epoch': 0.03}
3%|▎ | 23/769 [02:25<1:12:34, 5.84s/it]
3%|▎ | 24/769 [02:31<1:12:04, 5.80s/it]
{'loss': 1.1437, 'grad_norm': 2.6875, 'learning_rate': 6.0526315789473685e-06, 'memory/max_active (GiB)': 46.78, 'memory/max_allocated (GiB)': 46.78, 'memory/device_reserved (GiB)': 78.26, 'tokens_per_second_per_gpu': 1749.27, 'epoch': 0.03}
3%|▎ | 24/769 [02:31<1:12:04, 5.80s/it]
3%|▎ | 25/769 [02:36<1:11:33, 5.77s/it]
{'loss': 1.0987, 'grad_norm': 2.765625, 'learning_rate': 6.31578947368421e-06, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1627.64, 'epoch': 0.03}
3%|▎ | 25/769 [02:36<1:11:33, 5.77s/it]
3%|▎ | 26/769 [02:42<1:09:06, 5.58s/it]
{'loss': 1.1046, 'grad_norm': 2.6875, 'learning_rate': 6.578947368421054e-06, 'memory/max_active (GiB)': 43.82, 'memory/max_allocated (GiB)': 43.82, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1967.95, 'epoch': 0.03}
3%|▎ | 26/769 [02:42<1:09:06, 5.58s/it]
4%|▎ | 27/769 [02:47<1:09:27, 5.62s/it]
{'loss': 1.1072, 'grad_norm': 2.8125, 'learning_rate': 6.842105263157896e-06, 'memory/max_active (GiB)': 46.76, 'memory/max_allocated (GiB)': 46.76, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1594.62, 'epoch': 0.04}
4%|▎ | 27/769 [02:47<1:09:27, 5.62s/it]
4%|▎ | 28/769 [02:52<1:05:29, 5.30s/it]
{'loss': 1.1974, 'grad_norm': 3.03125, 'learning_rate': 7.1052631578947375e-06, 'memory/max_active (GiB)': 41.47, 'memory/max_allocated (GiB)': 41.47, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1766.49, 'epoch': 0.04}
4%|▎ | 28/769 [02:52<1:05:29, 5.30s/it]
4%|▍ | 29/769 [02:58<1:06:52, 5.42s/it]
{'loss': 1.2164, 'grad_norm': 2.734375, 'learning_rate': 7.368421052631579e-06, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1593.41, 'epoch': 0.04}
4%|▍ | 29/769 [02:58<1:06:52, 5.42s/it]
4%|▍ | 30/769 [03:03<1:07:46, 5.50s/it]
{'loss': 1.1324, 'grad_norm': 2.65625, 'learning_rate': 7.631578947368423e-06, 'memory/max_active (GiB)': 46.76, 'memory/max_allocated (GiB)': 46.76, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1607.66, 'epoch': 0.04}
4%|▍ | 30/769 [03:03<1:07:46, 5.50s/it]
4%|▍ | 31/769 [03:09<1:08:21, 5.56s/it]
{'loss': 1.0693, 'grad_norm': 2.96875, 'learning_rate': 7.894736842105265e-06, 'memory/max_active (GiB)': 46.75, 'memory/max_allocated (GiB)': 46.75, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1454.28, 'epoch': 0.04}
4%|▍ | 31/769 [03:09<1:08:21, 5.56s/it]
4%|▍ | 32/769 [03:14<1:06:43, 5.43s/it]
{'loss': 1.0988, 'grad_norm': 2.65625, 'learning_rate': 8.157894736842106e-06, 'memory/max_active (GiB)': 43.82, 'memory/max_allocated (GiB)': 43.82, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1972.66, 'epoch': 0.04}
4%|▍ | 32/769 [03:14<1:06:43, 5.43s/it]
4%|▍ | 33/769 [03:19<1:03:27, 5.17s/it]
{'loss': 1.074, 'grad_norm': 2.84375, 'learning_rate': 8.421052631578948e-06, 'memory/max_active (GiB)': 41.48, 'memory/max_allocated (GiB)': 41.48, 'memory/device_reserved (GiB)': 77.13, 'tokens_per_second_per_gpu': 1705.8, 'epoch': 0.04}
4%|▍ | 33/769 [03:19<1:03:27, 5.17s/it]
4%|▍ | 34/769 [03:24<1:03:14, 5.16s/it]
{'loss': 1.1673, 'grad_norm': 2.671875, 'learning_rate': 8.68421052631579e-06, 'memory/max_active (GiB)': 43.81, 'memory/max_allocated (GiB)': 43.81, 'memory/device_reserved (GiB)': 76.88, 'tokens_per_second_per_gpu': 1761.02, 'epoch': 0.04}
4%|▍ | 34/769 [03:24<1:03:14, 5.16s/it]
5%|▍ | 35/769 [03:29<1:02:59, 5.15s/it]
{'loss': 1.1655, 'grad_norm': 3.03125, 'learning_rate': 8.947368421052632e-06, 'memory/max_active (GiB)': 43.79, 'memory/max_allocated (GiB)': 43.79, 'memory/device_reserved (GiB)': 76.01, 'tokens_per_second_per_gpu': 1479.42, 'epoch': 0.05}
5%|▍ | 35/769 [03:29<1:02:59, 5.15s/it]
5%|▍ | 36/769 [03:35<1:04:53, 5.31s/it]
{'loss': 1.1483, 'grad_norm': 2.71875, 'learning_rate': 9.210526315789474e-06, 'memory/max_active (GiB)': 46.75, 'memory/max_allocated (GiB)': 46.75, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1466.59, 'epoch': 0.05}
5%|▍ | 36/769 [03:35<1:04:53, 5.31s/it]
5%|▍ | 37/769 [03:40<1:04:09, 5.26s/it]
{'loss': 1.159, 'grad_norm': 2.578125, 'learning_rate': 9.473684210526315e-06, 'memory/max_active (GiB)': 43.81, 'memory/max_allocated (GiB)': 43.81, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1806.68, 'epoch': 0.05}
5%|▍ | 37/769 [03:40<1:04:09, 5.26s/it]
5%|▍ | 38/769 [03:45<1:05:41, 5.39s/it]
{'loss': 1.1035, 'grad_norm': 2.625, 'learning_rate': 9.736842105263159e-06, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1689.12, 'epoch': 0.05}
5%|▍ | 38/769 [03:45<1:05:41, 5.39s/it]
5%|▌ | 39/769 [03:51<1:06:41, 5.48s/it]
{'loss': 1.0471, 'grad_norm': 2.609375, 'learning_rate': 1e-05, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1579.8, 'epoch': 0.05}
5%|▌ | 39/769 [03:51<1:06:41, 5.48s/it]
5%|▌ | 40/769 [03:56<1:05:20, 5.38s/it]
{'loss': 1.2091, 'grad_norm': 2.96875, 'learning_rate': 1.0263157894736844e-05, 'memory/max_active (GiB)': 43.8, 'memory/max_allocated (GiB)': 43.8, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1542.1, 'epoch': 0.05}
5%|▌ | 40/769 [03:56<1:05:20, 5.38s/it]
5%|▌ | 41/769 [04:02<1:06:25, 5.47s/it]
{'loss': 1.0722, 'grad_norm': 2.59375, 'learning_rate': 1.0526315789473684e-05, 'memory/max_active (GiB)': 46.77, 'memory/max_allocated (GiB)': 46.77, 'memory/device_reserved (GiB)': 77.38, 'tokens_per_second_per_gpu': 1585.53, 'epoch': 0.05}
5%|▌ | 41/769 [04:02<1:06:25, 5.47s/it] |