开始时间: Thu Oct 30 16:52:09 CST 2025
节点列表: SH-IDCA1404-10-140-54-103
总进程数: 8
当前任务ID: 6166705
INFO:    User not listed in /etc/subuid, trying root-mapped namespace
INFO:    No user namespaces available, using only the fakeroot command
WARNING: nv files may not be bound with --writable
WARNING: Skipping mount /etc/localtime [binds]: /etc/localtime doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-debugdump [files]: /usr/bin/nvidia-debugdump doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-persistenced [files]: /usr/bin/nvidia-persistenced doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-cuda-mps-control [files]: /usr/bin/nvidia-cuda-mps-control doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-cuda-mps-server [files]: /usr/bin/nvidia-cuda-mps-server doesn't exist in container
[INFO|2025-10-30 08:52:28] llamafactory.launcher:143 >> Initializing 8 distributed tasks at: 127.0.0.1:17821
W1030 08:52:32.065000 34577 site-packages/torch/distributed/run.py:792] 
W1030 08:52:32.065000 34577 site-packages/torch/distributed/run.py:792] *****************************************
W1030 08:52:32.065000 34577 site-packages/torch/distributed/run.py:792] 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. 
W1030 08:52:32.065000 34577 site-packages/torch/distributed/run.py:792] *****************************************
[2025-10-30 08:52:50,890] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 08:52:50,896] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 08:52:50,902] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 08:52:50,902] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 08:52:50,903] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 08:52:51,005] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 08:52:51,037] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 08:52:51,048] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
[2025-10-30 08:53:01,018] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 08:53:01,018] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 08:53:01,018] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 08:53:01,018] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 08:53:01,018] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 08:53:01,022] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 08:53:01,022] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 08:53:01,023] [INFO] [comm.py:700:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
[2025-10-30 08:53:01,024] [INFO] [comm.py:669:init_distributed] cdb=None
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 0, world size: 8, device: cuda:0, distributed training: True, compute dtype: torch.bfloat16
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:01,653 >> loading file vocab.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:01,654 >> loading file merges.txt
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:01,655 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:01,655 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:01,656 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:01,657 >> loading file tokenizer_config.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:01,657 >> loading file chat_template.jinja
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 1, world size: 8, device: cuda:1, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 3, world size: 8, device: cuda:3, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 2, world size: 8, device: cuda:2, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 5, world size: 8, device: cuda:5, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 7, world size: 8, device: cuda:7, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 6, world size: 8, device: cuda:6, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 08:53:01] llamafactory.hparams.parser:423 >> Process rank: 4, world size: 8, device: cuda:4, distributed training: True, compute dtype: torch.bfloat16
[INFO|tokenization_utils_base.py:2364] 2025-10-30 08:53:02,035 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[INFO|image_processing_base.py:381] 2025-10-30 08:53:02,047 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|image_processing_base.py:381] 2025-10-30 08:53:02,071 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|image_processing_base.py:428] 2025-10-30 08:53:02,100 >> Image processor Qwen2VLImageProcessorFast {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "disable_grouping": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_pad": null,
  "do_rescale": true,
  "do_resize": true,
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessorFast",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_tensors": null,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

[INFO|video_processing_utils.py:724] 2025-10-30 08:53:02,111 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|video_processing_utils.py:770] 2025-10-30 08:53:02,115 >> Video processor Qwen2VLVideoProcessor {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "do_sample_frames": false,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "fps": null,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_frames": 768,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_frames": 4,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "num_frames": null,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_metadata": false,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2,
  "video_metadata": null,
  "video_processor_type": "Qwen2VLVideoProcessor"
}

[INFO|feature_extraction_utils.py:556] 2025-10-30 08:53:02,140 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|feature_extraction_utils.py:597] 2025-10-30 08:53:02,142 >> Feature extractor WhisperFeatureExtractor {
  "chunk_length": 300,
  "dither": 0.0,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "return_attention_mask": true,
  "sampling_rate": 16000,
  "temporal_patch_size": 2
}

[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:02,160 >> loading file vocab.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:02,161 >> loading file merges.txt
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:02,161 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:02,162 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:02,162 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:02,163 >> loading file tokenizer_config.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 08:53:02,163 >> loading file chat_template.jinja
[INFO|tokenization_utils_base.py:2364] 2025-10-30 08:53:02,573 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[INFO|processing_utils.py:1114] 2025-10-30 08:53:02,584 >> loading configuration file None
[INFO|processing_utils.py:1199] 2025-10-30 08:53:03,085 >> Processor Qwen2_5OmniProcessor:
- image_processor: Qwen2VLImageProcessorFast {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "disable_grouping": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_pad": null,
  "do_rescale": true,
  "do_resize": true,
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessorFast",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_tensors": null,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- video_processor: Qwen2VLVideoProcessor {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "do_sample_frames": false,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "fps": null,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_frames": 768,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_frames": 4,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "num_frames": null,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_metadata": false,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2,
  "video_metadata": null,
  "video_processor_type": "Qwen2VLVideoProcessor"
}

- feature_extractor: WhisperFeatureExtractor {
  "chunk_length": 300,
  "dither": 0.0,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "return_attention_mask": true,
  "sampling_rate": 16000,
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='ckpts/Qwen2.5-Omni-3B', vocab_size=151643, model_max_length=32768, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|AUDIO|>', '<|audio_bos|>', '<|audio_eos|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_bos|>', '<|vision_eos|>', '<|vision_pad|>', '<|IMAGE|>', '<|VIDEO|>'], 'image_token': '<|IMAGE|>', 'audio_token': '<|AUDIO|>', 'video_token': '<|VIDEO|>', 'vision_bos_token': '<|vision_bos|>', 'vision_eos_token': '<|vision_eos|>', 'audio_bos_token': '<|audio_bos|>', 'audio_eos_token': '<|audio_eos|>'}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|AUDIO|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|audio_bos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|audio_eos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_bos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_eos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|IMAGE|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|VIDEO|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5OmniProcessor"
}

[INFO|2025-10-30 08:53:03] llamafactory.data.loader:143 >> Loading dataset VG-LLM-train/scan2cap_train_32frames.json...
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
[rank1]:[W1030 08:53:03.860595539 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 1]  using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank2]:[W1030 08:53:03.869556364 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 2]  using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank3]:[W1030 08:53:03.890519641 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 3]  using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank5]:[W1030 08:53:03.942323833 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 5]  using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank7]:[W1030 08:53:03.956763971 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 7]  using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank6]:[W1030 08:53:03.957994944 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 6]  using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank4]:[W1030 08:53:03.011468971 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 4]  using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank0]:[W1030 08:53:04.289560694 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 0]  using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
training example:
input_ids:
[151644, 8948, 198, 2610, 525, 264, 10950, 17847, 13, 151645, 198, 151644, 872, 198, 151652, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 151655, 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Carefully watch the video and describe the object located at [3.45, 0.9, -1.37] in detail.<|im_end|>
<|im_start|>assistant
A white cabinet in the corner of the room. in the direction from the door and from the inside . it will be on the left, there is a small brown table on the left side of the cabinet and a smaller table on the right side of the cabinet<|im_end|>

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labels:
A white cabinet in the corner of the room. in the direction from the door and from the inside . it will be on the left, there is a small brown table on the left side of the cabinet and a smaller table on the right side of the cabinet<|im_end|>

[INFO|configuration_utils.py:763] 2025-10-30 08:53:13,755 >> loading configuration file ckpts/Qwen2.5-Omni-3B/config.json
[WARNING|modeling_rope_utils.py:557] 2025-10-30 08:53:13,761 >> Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
[INFO|configuration_qwen2_5_omni.py:1059] 2025-10-30 08:53:13,766 >> thinker_config is None. Initializing thinker model with default values
[INFO|configuration_qwen2_5_omni.py:1063] 2025-10-30 08:53:13,766 >> talker_config is None. Initializing talker model with default values
[INFO|configuration_qwen2_5_omni.py:1067] 2025-10-30 08:53:13,767 >> token2wav_config is None. Initializing token2wav model with default values
[INFO|configuration_utils.py:839] 2025-10-30 08:53:13,774 >> Model config Qwen2_5OmniConfig {
  "architectures": [
    "Qwen2_5OmniForConditionalGeneration"
  ],
  "dtype": "bfloat16",
  "enable_audio_output": true,
  "enable_talker": true,
  "model_type": "qwen2_5_omni",
  "talker_config": {
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    "_name_or_path": "Qwen2.5-Omni-3B/talker",
    "architectures": [
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    "attention_dropout": 0.0,
    "audio_end_token_id": 151648,
    "audio_start_token_id": 151647,
    "audio_token_index": 151646,
    "dtype": "bfloat16",
    "embedding_size": 2048,
    "head_dim": 64,
    "hidden_act": "silu",
    "hidden_size": 896,
    "image_token_index": 151655,
    "init_std": 0.02,
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    "intermediate_size": 4864,
    "layer_types": [
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      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
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      "full_attention",
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      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention"
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    "max_position_embeddings": 32768,
    "max_window_layers": 28,
    "model_type": "qwen2_5_omni_talker",
    "num_attention_heads": 14,
    "num_hidden_layers": 24,
    "num_key_value_heads": 2,
    "position_id_per_seconds": 25,
    "rms_norm_eps": 1e-06,
    "rope_scaling": {
      "mrope_section": [
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        16,
        0
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      "rope_type": "default",
      "type": "default"
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    "rope_theta": 1000000.0,
    "seconds_per_chunk": 2,
    "sliding_window": null,
    "spatial_merge_size": 2,
    "tts_codec_end_token_id": 8294,
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    "tts_text_end_token_id": 151861,
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    "use_cache": true,
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  "thinker_config": {
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    "_name_or_path": "Qwen2.5-Omni-3B/thinker",
    "architectures": [
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      "activation_dropout": 0.0,
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    "text_config": {
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      "layer_types": [
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      "block_size": 24,
      "bos_token_id": null,
      "chunk_size_feed_forward": 0,
      "cross_attention_hidden_size": null,
      "decoder_start_token_id": null,
      "depth": 22,
      "dim": 1024,
      "diversity_penalty": 0.0,
      "do_sample": false,
      "dropout": 0.1,
      "dtype": "float32",
      "early_stopping": false,
      "emb_dim": 512,
      "enc_attention_channels": 64,
      "enc_channels": [
        256,
        256,
        256,
        256,
        768
      ],
      "enc_dilations": [
        1,
        2,
        3,
        4,
        1
      ],
      "enc_dim": 128,
      "enc_emb_dim": 192,
      "enc_global_context": true,
      "enc_kernel_sizes": [
        5,
        3,
        3,
        3,
        1
      ],
      "enc_lin_neurons": 192,
      "enc_res2net_scale": 2,
      "enc_se_channels": 64,
      "encoder_no_repeat_ngram_size": 0,
      "eos_token_id": null,
      "exponential_decay_length_penalty": null,
      "ff_mult": 2,
      "finetuning_task": null,
      "forced_bos_token_id": null,
      "forced_eos_token_id": null,
      "head_dim": 64,
      "heads": 16,
      "hidden_size": 1024,
      "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,
      "look_ahead_layers": [
        10
      ],
      "look_backward_layers": [
        0,
        20
      ],
      "max_length": 20,
      "max_position_embeddings": 32768,
      "mel_dim": 80,
      "min_length": 0,
      "model_type": "qwen2_5_omni_dit",
      "no_repeat_ngram_size": 0,
      "num_attention_heads": 16,
      "num_beam_groups": 1,
      "num_beams": 1,
      "num_embeds": 8193,
      "num_hidden_layers": 22,
      "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,
      "repeats": 2,
      "repetition_penalty": 1.0,
      "return_dict": true,
      "return_dict_in_generate": false,
      "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": true,
      "tokenizer_class": null,
      "top_k": 50,
      "top_p": 1.0,
      "torchscript": false,
      "typical_p": 1.0,
      "use_bfloat16": false
    },
    "model_type": "qwen2_5_omni_token2wav"
  },
  "transformers_version": "4.57.1"
}

[INFO|2025-10-30 08:53:13] llamafactory.model.model_utils.kv_cache:143 >> KV cache is disabled during training.
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
[WARNING|logging.py:328] 2025-10-30 08:53:20,456 >> `torch_dtype` is deprecated! Use `dtype` instead!
[INFO|modeling_utils.py:1169] 2025-10-30 08:53:20,461 >> loading weights file ckpts/Qwen2.5-Omni-3B/model.safetensors.index.json
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
[INFO|modeling_utils.py:2341] 2025-10-30 08:53:20,473 >> Instantiating Qwen2_5OmniForConditionalGeneration model under default dtype torch.bfloat16.
[INFO|configuration_utils.py:986] 2025-10-30 08:53:20,480 >> Generate config GenerationConfig {
  "use_cache": false
}

[INFO|configuration_utils.py:986] 2025-10-30 08:53:20,481 >> Generate config GenerationConfig {
  "bos_token_id": 151644,
  "eos_token_id": 151645,
  "pad_token_id": 151643
}

[INFO|configuration_utils.py:986] 2025-10-30 08:53:20,608 >> Generate config GenerationConfig {}

[INFO|modeling_utils.py:2341] 2025-10-30 08:53:20,622 >> Instantiating Qwen2_5OmniToken2WavDiTModel model under default dtype torch.float32.

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[INFO|configuration_utils.py:939] 2025-10-30 08:53:38,684 >> loading configuration file ckpts/Qwen2.5-Omni-3B/generation_config.json
[INFO|configuration_utils.py:986] 2025-10-30 08:53:38,684 >> Generate config GenerationConfig {}

[INFO|dynamic_module_utils.py:423] 2025-10-30 08:53:38,692 >> Could not locate the custom_generate/generate.py inside ckpts/Qwen2.5-Omni-3B.
[INFO|modeling_qwen2_5_omni.py:3727] 2025-10-30 08:53:38,742 >> Speaker ['Ethan', 'Chelsie'] loaded
[INFO|2025-10-30 08:53:38] llamafactory.model.model_utils.checkpointing:143 >> Gradient checkpointing enabled.
[INFO|2025-10-30 08:53:38] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference.
[INFO|2025-10-30 08:53:38] llamafactory.model.adapter:143 >> Upcasting trainable params to float32.
[INFO|2025-10-30 08:53:38] llamafactory.model.adapter:143 >> Fine-tuning method: Full
[INFO|2025-10-30 08:53:38] llamafactory.model.model_utils.visual:143 >> Set vision model not trainable: ['visual.patch_embed', 'visual.blocks', 'audio_tower'].
[INFO|2025-10-30 08:53:38] llamafactory.model.model_utils.visual:143 >> Set multi model projector not trainable: visual.merger.
[INFO|2025-10-30 08:53:38] llamafactory.model.loader:143 >> trainable params: 3,397,103,616 || all params: 4,703,464,448 || trainable%: 72.2256
Detected kernel version 3.10.0, 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.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
[INFO|trainer.py:749] 2025-10-30 08:53:39,084 >> Using auto half precision backend
[WARNING|trainer.py:982] 2025-10-30 08:53:39,087 >> The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
Gradient accumulation steps mismatch: GradientAccumulationPlugin has 1, DeepSpeed config has 4. Using DeepSpeed's value.
[2025-10-30 08:53:39,423] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed info: version=0.16.9, git-hash=unknown, git-branch=unknown
[2025-10-30 08:53:39,424] [INFO] [config.py:735:__init__] Config mesh_device None world_size = 8
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
[2025-10-30 08:53:42,220] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False
[2025-10-30 08:53:42,226] [INFO] [logging.py:107:log_dist] [Rank 0] Using client Optimizer as basic optimizer
[2025-10-30 08:53:42,227] [INFO] [logging.py:107:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer
[2025-10-30 08:53:42,263] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed Basic Optimizer = AdamW
[2025-10-30 08:53:42,264] [INFO] [utils.py:59:is_zero_supported_optimizer] Checking ZeRO support for optimizer=AdamW type=<class 'torch.optim.adamw.AdamW'>
[2025-10-30 08:53:42,264] [INFO] [logging.py:107:log_dist] [Rank 0] Creating torch.bfloat16 ZeRO stage 2 optimizer
[2025-10-30 08:53:42,265] [INFO] [stage_1_and_2.py:150:__init__] Reduce bucket size 500000000
[2025-10-30 08:53:42,265] [INFO] [stage_1_and_2.py:151:__init__] Allgather bucket size 500000000
[2025-10-30 08:53:42,265] [INFO] [stage_1_and_2.py:152:__init__] CPU Offload: False
[2025-10-30 08:53:42,266] [INFO] [stage_1_and_2.py:153:__init__] Round robin gradient partitioning: True
[2025-10-30 08:53:57,182] [INFO] [utils.py:781:see_memory_usage] Before initializing optimizer states
[2025-10-30 08:53:57,183] [INFO] [utils.py:782:see_memory_usage] MA 10.35 GB         Max_MA 10.35 GB         CA 10.38 GB         Max_CA 10 GB 
[2025-10-30 08:53:57,184] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory:  used = 82.78 GB, percent = 8.2%
[2025-10-30 08:53:57,435] [INFO] [utils.py:781:see_memory_usage] After initializing optimizer states
[2025-10-30 08:53:57,437] [INFO] [utils.py:782:see_memory_usage] MA 10.35 GB         Max_MA 11.93 GB         CA 11.96 GB         Max_CA 12 GB 
[2025-10-30 08:53:58,301] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory:  used = 84.63 GB, percent = 8.4%
[2025-10-30 08:53:58,302] [INFO] [stage_1_and_2.py:557:__init__] optimizer state initialized
[2025-10-30 08:53:58,599] [INFO] [utils.py:781:see_memory_usage] After initializing ZeRO optimizer
[2025-10-30 08:53:58,600] [INFO] [utils.py:782:see_memory_usage] MA 10.35 GB         Max_MA 10.35 GB         CA 11.96 GB         Max_CA 12 GB 
[2025-10-30 08:53:58,602] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory:  used = 92.19 GB, percent = 9.2%
[2025-10-30 08:53:58,605] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed Final Optimizer = DeepSpeedZeroOptimizer
[2025-10-30 08:53:58,605] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed using configured LR scheduler = None
[2025-10-30 08:53:58,606] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed LR Scheduler = None
[2025-10-30 08:53:58,606] [INFO] [logging.py:107:log_dist] [Rank 0] step=0, skipped=0, lr=[0.0, 0.0], mom=[(0.9, 0.999), (0.9, 0.999)]
[2025-10-30 08:53:58,611] [INFO] [config.py:1003:print] DeepSpeedEngine configuration:
[2025-10-30 08:53:58,612] [INFO] [config.py:1007:print]   activation_checkpointing_config  {
    "partition_activations": false, 
    "contiguous_memory_optimization": false, 
    "cpu_checkpointing": false, 
    "number_checkpoints": null, 
    "synchronize_checkpoint_boundary": false, 
    "profile": false
}
[2025-10-30 08:53:58,612] [INFO] [config.py:1007:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'intra_op_parallelism': 1, 'single_submit': False, 'overlap_events': True, 'use_gds': False}
[2025-10-30 08:53:58,613] [INFO] [config.py:1007:print]   amp_enabled .................. False
[2025-10-30 08:53:58,614] [INFO] [config.py:1007:print]   amp_params ................... False
[2025-10-30 08:53:58,615] [INFO] [config.py:1007:print]   autotuning_config ............ {
    "enabled": false, 
    "start_step": null, 
    "end_step": null, 
    "metric_path": null, 
    "arg_mappings": null, 
    "metric": "throughput", 
    "model_info": null, 
    "results_dir": "autotuning_results", 
    "exps_dir": "autotuning_exps", 
    "overwrite": true, 
    "fast": true, 
    "start_profile_step": 3, 
    "end_profile_step": 5, 
    "tuner_type": "gridsearch", 
    "tuner_early_stopping": 5, 
    "tuner_num_trials": 50, 
    "model_info_path": null, 
    "mp_size": 1, 
    "max_train_batch_size": null, 
    "min_train_batch_size": 1, 
    "max_train_micro_batch_size_per_gpu": 1.024000e+03, 
    "min_train_micro_batch_size_per_gpu": 1, 
    "num_tuning_micro_batch_sizes": 3
}
[2025-10-30 08:53:58,615] [INFO] [config.py:1007:print]   bfloat16_enabled ............. True
[2025-10-30 08:53:58,616] [INFO] [config.py:1007:print]   bfloat16_immediate_grad_update  True
[2025-10-30 08:53:58,616] [INFO] [config.py:1007:print]   checkpoint_parallel_write_pipeline  False
[2025-10-30 08:53:58,616] [INFO] [config.py:1007:print]   checkpoint_tag_validation_enabled  True
[2025-10-30 08:53:58,617] [INFO] [config.py:1007:print]   checkpoint_tag_validation_fail  False
[2025-10-30 08:53:58,617] [INFO] [config.py:1007:print]   comms_config ................. <deepspeed.comm.config.DeepSpeedCommsConfig object at 0x7f2401368510>
[2025-10-30 08:53:58,618] [INFO] [config.py:1007:print]   communication_data_type ...... None
[2025-10-30 08:53:58,618] [INFO] [config.py:1007:print]   compile_config ............... deepcompile=False free_activation=False offload_activation=False offload_opt_states=False double_buffer=True symmetric_memory=False debug_log=False offload_parameters=False sync_before_reduce=False sync_after_reduce=False sync_before_allgather=False sync_after_allgather=False
[2025-10-30 08:53:58,619] [INFO] [config.py:1007:print]   compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}}
[2025-10-30 08:53:58,619] [INFO] [config.py:1007:print]   curriculum_enabled_legacy .... False
[2025-10-30 08:53:58,620] [INFO] [config.py:1007:print]   curriculum_params_legacy ..... False
[2025-10-30 08:53:58,621] [INFO] [config.py:1007:print]   data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'pin_memory': False, 'curriculum_learning': {'enabled': False}, 'dynamic_batching': {'enabled': False, 'lr_scaling_method': 'linear', 'min_batch_size': 1, 'max_batch_size': None, 'sequence_picking_order': 'dataloader', 'verbose': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}}
[2025-10-30 08:53:58,621] [INFO] [config.py:1007:print]   data_efficiency_enabled ...... False
[2025-10-30 08:53:58,621] [INFO] [config.py:1007:print]   dataloader_drop_last ......... False
[2025-10-30 08:53:58,622] [INFO] [config.py:1007:print]   disable_allgather ............ False
[2025-10-30 08:53:58,622] [INFO] [config.py:1007:print]   dump_state ................... False
[2025-10-30 08:53:58,623] [INFO] [config.py:1007:print]   dynamic_loss_scale_args ...... None
[2025-10-30 08:53:58,623] [INFO] [config.py:1007:print]   eigenvalue_enabled ........... False
[2025-10-30 08:53:58,624] [INFO] [config.py:1007:print]   eigenvalue_gas_boundary_resolution  1
[2025-10-30 08:53:58,624] [INFO] [config.py:1007:print]   eigenvalue_layer_name ........ bert.encoder.layer
[2025-10-30 08:53:58,624] [INFO] [config.py:1007:print]   eigenvalue_layer_num ......... 0
[2025-10-30 08:53:58,625] [INFO] [config.py:1007:print]   eigenvalue_max_iter .......... 100
[2025-10-30 08:53:58,625] [INFO] [config.py:1007:print]   eigenvalue_stability ......... 1e-06
[2025-10-30 08:53:58,628] [INFO] [config.py:1007:print]   eigenvalue_tol ............... 0.01
[2025-10-30 08:53:58,628] [INFO] [config.py:1007:print]   eigenvalue_verbose ........... False
[2025-10-30 08:53:58,629] [INFO] [config.py:1007:print]   elasticity_enabled ........... False
[2025-10-30 08:53:58,629] [INFO] [config.py:1007:print]   flops_profiler_config ........ {
    "enabled": false, 
    "recompute_fwd_factor": 0.0, 
    "profile_step": 1, 
    "module_depth": -1, 
    "top_modules": 1, 
    "detailed": true, 
    "output_file": null
}
[2025-10-30 08:53:58,630] [INFO] [config.py:1007:print]   fp16_auto_cast ............... None
[2025-10-30 08:53:58,630] [INFO] [config.py:1007:print]   fp16_enabled ................. False
[2025-10-30 08:53:58,631] [INFO] [config.py:1007:print]   fp16_master_weights_and_gradients  False
[2025-10-30 08:53:58,631] [INFO] [config.py:1007:print]   global_rank .................. 0
[2025-10-30 08:53:58,631] [INFO] [config.py:1007:print]   grad_accum_dtype ............. None
[2025-10-30 08:53:58,632] [INFO] [config.py:1007:print]   gradient_accumulation_steps .. 4
[2025-10-30 08:53:58,632] [INFO] [config.py:1007:print]   gradient_clipping ............ 1.0
[2025-10-30 08:53:58,633] [INFO] [config.py:1007:print]   gradient_predivide_factor .... 1.0
[2025-10-30 08:53:58,633] [INFO] [config.py:1007:print]   graph_harvesting ............. False
[2025-10-30 08:53:58,633] [INFO] [config.py:1007:print]   hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8
[2025-10-30 08:53:58,634] [INFO] [config.py:1007:print]   initial_dynamic_scale ........ 1
[2025-10-30 08:53:58,634] [INFO] [config.py:1007:print]   load_universal_checkpoint .... False
[2025-10-30 08:53:58,635] [INFO] [config.py:1007:print]   loss_scale ................... 1.0
[2025-10-30 08:53:58,635] [INFO] [config.py:1007:print]   memory_breakdown ............. False
[2025-10-30 08:53:58,636] [INFO] [config.py:1007:print]   mics_hierarchial_params_gather  False
[2025-10-30 08:53:58,636] [INFO] [config.py:1007:print]   mics_shard_size .............. -1
[2025-10-30 08:53:58,637] [INFO] [config.py:1007:print]   monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') comet=CometConfig(enabled=False, samples_log_interval=100, project=None, workspace=None, api_key=None, experiment_name=None, experiment_key=None, online=None, mode=None) wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName')
[2025-10-30 08:53:58,637] [INFO] [config.py:1007:print]   nebula_config ................ {
    "enabled": false, 
    "persistent_storage_path": null, 
    "persistent_time_interval": 100, 
    "num_of_version_in_retention": 2, 
    "enable_nebula_load": true, 
    "load_path": null
}
[2025-10-30 08:53:58,637] [INFO] [config.py:1007:print]   optimizer_legacy_fusion ...... False
[2025-10-30 08:53:58,638] [INFO] [config.py:1007:print]   optimizer_name ............... None
[2025-10-30 08:53:58,638] [INFO] [config.py:1007:print]   optimizer_params ............. None
[2025-10-30 08:53:58,639] [INFO] [config.py:1007:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': True, 'grad_partitioned': True}
[2025-10-30 08:53:58,639] [INFO] [config.py:1007:print]   pld_enabled .................. False
[2025-10-30 08:53:58,639] [INFO] [config.py:1007:print]   pld_params ................... False
[2025-10-30 08:53:58,640] [INFO] [config.py:1007:print]   prescale_gradients ........... False
[2025-10-30 08:53:58,640] [INFO] [config.py:1007:print]   scheduler_name ............... None
[2025-10-30 08:53:58,641] [INFO] [config.py:1007:print]   scheduler_params ............. None
[2025-10-30 08:53:58,641] [INFO] [config.py:1007:print]   seq_parallel_communication_data_type  torch.float32
[2025-10-30 08:53:58,641] [INFO] [config.py:1007:print]   sparse_attention ............. None
[2025-10-30 08:53:58,642] [INFO] [config.py:1007:print]   sparse_gradients_enabled ..... False
[2025-10-30 08:53:58,642] [INFO] [config.py:1007:print]   steps_per_print .............. inf
[2025-10-30 08:53:58,643] [INFO] [config.py:1007:print]   tensor_parallel_config ....... dtype=torch.float16 autotp_size=0 tp_overlap_comm=False tensor_parallel=TPConfig(tp_size=1, tp_grain_size=1, mpu=None, tp_group=None) injection_policy_tuple=None keep_module_on_host=False replace_with_kernel_inject=False
[2025-10-30 08:53:58,643] [INFO] [config.py:1007:print]   timers_config ................ enabled=True synchronized=True
[2025-10-30 08:53:58,644] [INFO] [config.py:1007:print]   train_batch_size ............. 32
[2025-10-30 08:53:58,683] [INFO] [config.py:1007:print]   train_micro_batch_size_per_gpu  1
[2025-10-30 08:53:58,684] [INFO] [config.py:1007:print]   use_data_before_expert_parallel_  False
[2025-10-30 08:53:58,684] [INFO] [config.py:1007:print]   use_node_local_storage ....... False
[2025-10-30 08:53:58,685] [INFO] [config.py:1007:print]   wall_clock_breakdown ......... False
[2025-10-30 08:53:58,685] [INFO] [config.py:1007:print]   weight_quantization_config ... None
[2025-10-30 08:53:58,685] [INFO] [config.py:1007:print]   world_size ................... 8
[2025-10-30 08:53:58,686] [INFO] [config.py:1007:print]   zero_allow_untested_optimizer  True
[2025-10-30 08:53:58,686] [INFO] [config.py:1007:print]   zero_config .................. stage=2 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=500000000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=500000000 overlap_comm=False load_from_fp32_weights=True elastic_checkpoint=False offload_param=None offload_optimizer=None sub_group_size=1000000000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50000000 param_persistence_threshold=100000 model_persistence_threshold=9223372036854775807 max_live_parameters=1000000000 max_reuse_distance=1000000000 gather_16bit_weights_on_model_save=False module_granularity_threshold=0 use_all_reduce_for_fetch_params=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=True zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False zeropp_loco_param=None mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True log_trace_cache_warnings=False
[2025-10-30 08:53:58,687] [INFO] [config.py:1007:print]   zero_enabled ................. True
[2025-10-30 08:53:58,687] [INFO] [config.py:1007:print]   zero_force_ds_cpu_optimizer .. True
[2025-10-30 08:53:58,688] [INFO] [config.py:1007:print]   zero_optimization_stage ...... 2
[2025-10-30 08:53:58,688] [INFO] [config.py:993:print_user_config]   json = {
    "train_batch_size": 32, 
    "train_micro_batch_size_per_gpu": 1, 
    "gradient_accumulation_steps": 4, 
    "gradient_clipping": 1.0, 
    "zero_allow_untested_optimizer": true, 
    "fp16": {
        "enabled": false, 
        "loss_scale": 0, 
        "loss_scale_window": 1000, 
        "initial_scale_power": 16, 
        "hysteresis": 2, 
        "min_loss_scale": 1
    }, 
    "bf16": {
        "enabled": true
    }, 
    "zero_optimization": {
        "stage": 2, 
        "allgather_partitions": true, 
        "allgather_bucket_size": 5.000000e+08, 
        "overlap_comm": false, 
        "reduce_scatter": true, 
        "reduce_bucket_size": 5.000000e+08, 
        "contiguous_gradients": true, 
        "round_robin_gradients": true
    }, 
    "steps_per_print": inf
}
[INFO|trainer.py:2519] 2025-10-30 08:53:58,692 >> ***** Running training *****
[INFO|trainer.py:2520] 2025-10-30 08:53:58,693 >>   Num examples = 36,665
[INFO|trainer.py:2521] 2025-10-30 08:53:58,693 >>   Num Epochs = 1
[INFO|trainer.py:2522] 2025-10-30 08:53:58,694 >>   Instantaneous batch size per device = 1
[INFO|trainer.py:2525] 2025-10-30 08:53:58,694 >>   Total train batch size (w. parallel, distributed & accumulation) = 32
[INFO|trainer.py:2526] 2025-10-30 08:53:58,695 >>   Gradient Accumulation steps = 4
[INFO|trainer.py:2527] 2025-10-30 08:53:58,695 >>   Total optimization steps = 1,146
[INFO|trainer.py:2528] 2025-10-30 08:53:58,701 >>   Number of trainable parameters = 3,397,103,616

  0%|          | 0/1146 [00:00<?, ?it/s]`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
[WARNING|logging.py:328] 2025-10-30 08:54:39,798 >> `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...

  0%|          | 1/1146 [01:35<30:13:10, 95.01s/it]
                                                   
{'loss': 3.0487, 'grad_norm': 87.8638687133789, 'learning_rate': 0.0, 'epoch': 0.0}

  0%|          | 1/1146 [01:35<30:13:10, 95.01s/it]slurmstepd: error: *** JOB 6166705 ON SH-IDCA1404-10-140-54-103 CANCELLED AT 2025-10-30T16:56:15 DUE TO PREEMPTION ***
W1030 08:56:15.850000 34577 site-packages/torch/distributed/elastic/agent/server/api.py:719] Received 15 death signal, shutting down workers
W1030 08:56:15.855000 34577 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 34897 closing signal SIGTERM
W1030 08:56:15.857000 34577 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 34898 closing signal SIGTERM
W1030 08:56:15.860000 34577 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 34899 closing signal SIGTERM
W1030 08:56:15.868000 34577 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 34900 closing signal SIGTERM
[rank6]:[E1030 09:06:19.441673575 ProcessGroupNCCL.cpp:629] [Rank 6] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600000 milliseconds before timing out.
[rank6]:[E1030 09:06:19.446485889 ProcessGroupNCCL.cpp:2168] [PG ID 1 PG GUID 1 Rank 6]  failure detected by watchdog at work sequence id: 1496 PG status: last enqueued work: 1497, last completed work: 1495
[rank6]:[E1030 09:06:19.446936890 ProcessGroupNCCL.cpp:667] Stack trace of the failed collective not found, potentially because FlightRecorder is disabled. You can enable it by setting TORCH_NCCL_TRACE_BUFFER_SIZE to a non-zero value.
[rank7]:[E1030 09:06:19.474911406 ProcessGroupNCCL.cpp:629] [Rank 7] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
[rank7]:[E1030 09:06:19.475669433 ProcessGroupNCCL.cpp:2168] [PG ID 1 PG GUID 1 Rank 7]  failure detected by watchdog at work sequence id: 1496 PG status: last enqueued work: 1497, last completed work: 1495
[rank7]:[E1030 09:06:19.476087152 ProcessGroupNCCL.cpp:667] Stack trace of the failed collective not found, potentially because FlightRecorder is disabled. You can enable it by setting TORCH_NCCL_TRACE_BUFFER_SIZE to a non-zero value.
[rank4]:[E1030 09:06:19.502729978 ProcessGroupNCCL.cpp:629] [Rank 4] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
[rank4]:[E1030 09:06:19.503488543 ProcessGroupNCCL.cpp:2168] [PG ID 1 PG GUID 1 Rank 4]  failure detected by watchdog at work sequence id: 1496 PG status: last enqueued work: 1497, last completed work: 1495
[rank4]:[E1030 09:06:19.503915934 ProcessGroupNCCL.cpp:667] Stack trace of the failed collective not found, potentially because FlightRecorder is disabled. You can enable it by setting TORCH_NCCL_TRACE_BUFFER_SIZE to a non-zero value.
[rank5]:[E1030 09:06:19.571427633 ProcessGroupNCCL.cpp:629] [Rank 5] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
[rank5]:[E1030 09:06:19.572371042 ProcessGroupNCCL.cpp:2168] [PG ID 1 PG GUID 1 Rank 5]  failure detected by watchdog at work sequence id: 1496 PG status: last enqueued work: 1497, last completed work: 1495
[rank5]:[E1030 09:06:19.572756747 ProcessGroupNCCL.cpp:667] Stack trace of the failed collective not found, potentially because FlightRecorder is disabled. You can enable it by setting TORCH_NCCL_TRACE_BUFFER_SIZE to a non-zero value.
[rank5]:[E1030 09:06:26.801971631 ProcessGroupNCCL.cpp:681] [Rank 5] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank5]:[E1030 09:06:26.802483863 ProcessGroupNCCL.cpp:695] [Rank 5] To avoid data inconsistency, we are taking the entire process down.
[rank5]:[E1030 09:06:26.804517750 ProcessGroupNCCL.cpp:1895] [PG ID 1 PG GUID 1 Rank 5] Process group watchdog thread terminated with exception: [Rank 5] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f01cc36c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7f017a61bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7f017a61d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f017a61e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f01cc7ee5c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f01cd06bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7f01cd0fca04 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 5] Process group watchdog thread terminated with exception: [Rank 5] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600089 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f01cc36c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7f017a61bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7f017a61d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f017a61e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f01cc7ee5c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f01cd06bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7f01cd0fca04 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1901 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f01cc36c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe5c6fc (0x7f017a2796fc in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f01cc7ee5c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f01cd06bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: clone + 0x44 (0x7f01cd0fca04 in /lib/x86_64-linux-gnu/libc.so.6)
libfakeroot: read: socket is closed

[rank6]:[E1030 09:06:26.841602945 ProcessGroupNCCL.cpp:681] [Rank 6] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank6]:[E1030 09:06:26.842090785 ProcessGroupNCCL.cpp:695] [Rank 6] To avoid data inconsistency, we are taking the entire process down.
libfakeroot: read: socket is closed
[rank6]:[E1030 09:06:26.844315360 ProcessGroupNCCL.cpp:1895] [PG ID 1 PG GUID 1 Rank 6] Process group watchdog thread terminated with exception: [Rank 6] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600000 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fc38156c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7fc32fc1bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7fc32fc1d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fc32fc1e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fc3819e95c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fc38246bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7fc3824fca04 in /lib/x86_64-linux-gnu/libc.so.6)

[rank7]:[E1030 09:06:26.844519283 ProcessGroupNCCL.cpp:681] [Rank 7] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
terminate called after throwing an instance of 'c10::DistBackendError'
[rank7]:[E1030 09:06:26.845005959 ProcessGroupNCCL.cpp:695] [Rank 7] To avoid data inconsistency, we are taking the entire process down.
libfakeroot: read: socket is closed
  what():  [PG ID 1 PG GUID 1 Rank 6] Process group watchdog thread terminated with exception: [Rank 6] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600000 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fc38156c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7fc32fc1bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7fc32fc1d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fc32fc1e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fc3819e95c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fc38246bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7fc3824fca04 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1901 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fc38156c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe5c6fc (0x7fc32f8796fc in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7fc3819e95c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7fc38246bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: clone + 0x44 (0x7fc3824fca04 in /lib/x86_64-linux-gnu/libc.so.6)

[rank7]:[E1030 09:06:26.848189847 ProcessGroupNCCL.cpp:1895] [PG ID 1 PG GUID 1 Rank 7] Process group watchdog thread terminated with exception: [Rank 7] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f53a3d6c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7f535201bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7f535201d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f535201e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f53a42895c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f53a4a6bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7f53a4afca04 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 7] Process group watchdog thread terminated with exception: [Rank 7] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600077 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f53a3d6c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7f535201bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7f535201d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7f535201e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7f53a42895c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7f53a4a6bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7f53a4afca04 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1901 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7f53a3d6c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe5c6fc (0x7f5351c796fc in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7f53a42895c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7f53a4a6bac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: clone + 0x44 (0x7f53a4afca04 in /lib/x86_64-linux-gnu/libc.so.6)

[rank4]:[E1030 09:06:26.861455991 ProcessGroupNCCL.cpp:681] [Rank 4] Some NCCL operations have failed or timed out. Due to the asynchronous nature of CUDA kernels, subsequent GPU operations might run on corrupted/incomplete data.
[rank4]:[E1030 09:06:26.861903237 ProcessGroupNCCL.cpp:695] [Rank 4] To avoid data inconsistency, we are taking the entire process down.
libfakeroot: read: socket is closed
[rank4]:[E1030 09:06:26.863899423 ProcessGroupNCCL.cpp:1895] [PG ID 1 PG GUID 1 Rank 4] Process group watchdog thread terminated with exception: [Rank 4] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fd6cdb6c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7fd67c21bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7fd67c21d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fd67c21e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fd6ce2fd5c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fd6ceb84ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7fd6cec15a04 in /lib/x86_64-linux-gnu/libc.so.6)

terminate called after throwing an instance of 'c10::DistBackendError'
  what():  [PG ID 1 PG GUID 1 Rank 4] Process group watchdog thread terminated with exception: [Rank 4] Watchdog caught collective operation timeout: WorkNCCL(SeqNum=1496, OpType=ALLREDUCE, NumelIn=487865344, NumelOut=487865344, Timeout(ms)=600000) ran for 600094 milliseconds before timing out.
Exception raised from checkTimeout at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:632 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fd6cdb6c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: c10d::ProcessGroupNCCL::WorkNCCL::checkTimeout(std::optional<std::chrono::duration<long, std::ratio<1l, 1000l> > >) + 0x2b4 (0x7fd67c21bc74 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: c10d::ProcessGroupNCCL::watchdogHandler() + 0x890 (0x7fd67c21d7d0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #3: c10d::ProcessGroupNCCL::ncclCommWatchdog() + 0x14d (0x7fd67c21e6ed in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #4: <unknown function> + 0x145c0 (0x7fd6ce2fd5c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #5: <unknown function> + 0x94ac3 (0x7fd6ceb84ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #6: clone + 0x44 (0x7fd6cec15a04 in /lib/x86_64-linux-gnu/libc.so.6)

Exception raised from ncclCommWatchdog at /pytorch/torch/csrc/distributed/c10d/ProcessGroupNCCL.cpp:1901 (most recent call first):
frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7fd6cdb6c1b6 in /opt/conda/lib/python3.11/site-packages/torch/lib/libc10.so)
frame #1: <unknown function> + 0xe5c6fc (0x7fd67be796fc in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch_cuda.so)
frame #2: <unknown function> + 0x145c0 (0x7fd6ce2fd5c0 in /opt/conda/lib/python3.11/site-packages/torch/lib/libtorch.so)
frame #3: <unknown function> + 0x94ac3 (0x7fd6ceb84ac3 in /lib/x86_64-linux-gnu/libc.so.6)
frame #4: clone + 0x44 (0x7fd6cec15a04 in /lib/x86_64-linux-gnu/libc.so.6)

libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
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libfakeroot: write: Broken pipe
libfakeroot: write: Broken pipe
开始时间: Thu Oct 30 23:14:07 CST 2025
节点列表: SH-IDCA1404-10-140-54-74
总进程数: 8
当前任务ID: 6166705
INFO:    User not listed in /etc/subuid, trying root-mapped namespace
INFO:    No user namespaces available, using only the fakeroot command
WARNING: nv files may not be bound with --writable
WARNING: Skipping mount /etc/localtime [binds]: /etc/localtime doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-debugdump [files]: /usr/bin/nvidia-debugdump doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-persistenced [files]: /usr/bin/nvidia-persistenced doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-cuda-mps-control [files]: /usr/bin/nvidia-cuda-mps-control doesn't exist in container
WARNING: Skipping mount /usr/bin/nvidia-cuda-mps-server [files]: /usr/bin/nvidia-cuda-mps-server doesn't exist in container
[INFO|2025-10-30 15:14:28] llamafactory.launcher:143 >> Initializing 8 distributed tasks at: 127.0.0.1:17821
W1030 15:14:32.428000 108934 site-packages/torch/distributed/run.py:792] 
W1030 15:14:32.428000 108934 site-packages/torch/distributed/run.py:792] *****************************************
W1030 15:14:32.428000 108934 site-packages/torch/distributed/run.py:792] 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. 
W1030 15:14:32.428000 108934 site-packages/torch/distributed/run.py:792] *****************************************
[2025-10-30 15:14:53,079] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 15:14:53,079] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 15:14:53,079] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 15:14:53,079] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 15:14:53,080] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 15:14:53,080] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 15:14:53,080] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2025-10-30 15:14:53,081] [INFO] [real_accelerator.py:254:get_accelerator] Setting ds_accelerator to cuda (auto detect)
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
/opt/conda/lib/python3.11/site-packages/jieba/_compat.py:18: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  import pkg_resources
[2025-10-30 15:15:03,303] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 15:15:03,303] [INFO] [comm.py:669:init_distributed] cdb=None
[INFO|2025-10-30 15:15:03] llamafactory.hparams.parser:423 >> Process rank: 3, world size: 8, device: cuda:3, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 15:15:03] llamafactory.hparams.parser:423 >> Process rank: 1, world size: 8, device: cuda:1, distributed training: True, compute dtype: torch.bfloat16
[2025-10-30 15:15:03,664] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 15:15:03,664] [INFO] [comm.py:700:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
[2025-10-30 15:15:03,733] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 15:15:03,734] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 15:15:03,812] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 15:15:03,816] [INFO] [comm.py:669:init_distributed] cdb=None
[2025-10-30 15:15:03,817] [INFO] [comm.py:669:init_distributed] cdb=None
[INFO|2025-10-30 15:15:03] llamafactory.hparams.parser:423 >> Process rank: 0, world size: 8, device: cuda:0, distributed training: True, compute dtype: torch.bfloat16
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,030 >> loading file vocab.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,030 >> loading file merges.txt
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,031 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,031 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,032 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,032 >> loading file tokenizer_config.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,033 >> loading file chat_template.jinja
[INFO|2025-10-30 15:15:04] llamafactory.hparams.parser:423 >> Process rank: 2, world size: 8, device: cuda:2, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 15:15:04] llamafactory.hparams.parser:423 >> Process rank: 4, world size: 8, device: cuda:4, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 15:15:04] llamafactory.hparams.parser:423 >> Process rank: 5, world size: 8, device: cuda:5, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 15:15:04] llamafactory.hparams.parser:423 >> Process rank: 6, world size: 8, device: cuda:6, distributed training: True, compute dtype: torch.bfloat16
[INFO|2025-10-30 15:15:04] llamafactory.hparams.parser:423 >> Process rank: 7, world size: 8, device: cuda:7, distributed training: True, compute dtype: torch.bfloat16
[INFO|tokenization_utils_base.py:2364] 2025-10-30 15:15:04,427 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[INFO|image_processing_base.py:381] 2025-10-30 15:15:04,438 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|image_processing_base.py:381] 2025-10-30 15:15:04,461 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|image_processing_base.py:428] 2025-10-30 15:15:04,491 >> Image processor Qwen2VLImageProcessorFast {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "disable_grouping": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_pad": null,
  "do_rescale": true,
  "do_resize": true,
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessorFast",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_tensors": null,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

[INFO|video_processing_utils.py:724] 2025-10-30 15:15:04,502 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|video_processing_utils.py:770] 2025-10-30 15:15:04,505 >> Video processor Qwen2VLVideoProcessor {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "do_sample_frames": false,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "fps": null,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_frames": 768,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_frames": 4,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "num_frames": null,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_metadata": false,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2,
  "video_metadata": null,
  "video_processor_type": "Qwen2VLVideoProcessor"
}

[INFO|feature_extraction_utils.py:556] 2025-10-30 15:15:04,532 >> loading configuration file ckpts/Qwen2.5-Omni-3B/preprocessor_config.json
[INFO|feature_extraction_utils.py:597] 2025-10-30 15:15:04,533 >> Feature extractor WhisperFeatureExtractor {
  "chunk_length": 300,
  "dither": 0.0,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "return_attention_mask": true,
  "sampling_rate": 16000,
  "temporal_patch_size": 2
}

[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,553 >> loading file vocab.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,554 >> loading file merges.txt
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,555 >> loading file tokenizer.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,555 >> loading file added_tokens.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,556 >> loading file special_tokens_map.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,556 >> loading file tokenizer_config.json
[INFO|tokenization_utils_base.py:2093] 2025-10-30 15:15:04,557 >> loading file chat_template.jinja
[INFO|tokenization_utils_base.py:2364] 2025-10-30 15:15:04,975 >> Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
[INFO|processing_utils.py:1114] 2025-10-30 15:15:04,987 >> loading configuration file None
[rank1]:[W1030 15:15:05.889855935 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 1]  using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank3]:[W1030 15:15:05.071328430 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 3]  using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[INFO|processing_utils.py:1199] 2025-10-30 15:15:05,507 >> Processor Qwen2_5OmniProcessor:
- image_processor: Qwen2VLImageProcessorFast {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "disable_grouping": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_pad": null,
  "do_rescale": true,
  "do_resize": true,
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessorFast",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_tensors": null,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2
}

- video_processor: Qwen2VLVideoProcessor {
  "chunk_length": 300,
  "crop_size": null,
  "data_format": "channels_first",
  "default_to_square": true,
  "device": null,
  "dither": 0.0,
  "do_center_crop": null,
  "do_convert_rgb": true,
  "do_normalize": true,
  "do_rescale": true,
  "do_resize": true,
  "do_sample_frames": false,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "fps": null,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "input_data_format": null,
  "max_frames": 768,
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_frames": 4,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "num_frames": null,
  "pad_size": null,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "resample": 3,
  "rescale_factor": 0.00392156862745098,
  "return_attention_mask": true,
  "return_metadata": false,
  "sampling_rate": 16000,
  "size": {
    "longest_edge": 12845056,
    "shortest_edge": 3136
  },
  "temporal_patch_size": 2,
  "video_metadata": null,
  "video_processor_type": "Qwen2VLVideoProcessor"
}

- feature_extractor: WhisperFeatureExtractor {
  "chunk_length": 300,
  "dither": 0.0,
  "feature_extractor_type": "WhisperFeatureExtractor",
  "feature_size": 128,
  "hop_length": 160,
  "image_mean": [
    0.48145466,
    0.4578275,
    0.40821073
  ],
  "image_processor_type": "Qwen2VLImageProcessor",
  "image_std": [
    0.26862954,
    0.26130258,
    0.27577711
  ],
  "max_pixels": 12845056,
  "merge_size": 2,
  "min_pixels": 3136,
  "n_fft": 400,
  "n_samples": 4800000,
  "nb_max_frames": 30000,
  "padding_side": "right",
  "padding_value": 0.0,
  "patch_size": 14,
  "processor_class": "Qwen2_5OmniProcessor",
  "return_attention_mask": true,
  "sampling_rate": 16000,
  "temporal_patch_size": 2
}

- tokenizer: Qwen2TokenizerFast(name_or_path='ckpts/Qwen2.5-Omni-3B', vocab_size=151643, model_max_length=32768, is_fast=True, padding_side='right', truncation_side='right', special_tokens={'eos_token': '<|im_end|>', 'pad_token': '<|endoftext|>', 'additional_special_tokens': ['<|im_start|>', '<|im_end|>', '<|AUDIO|>', '<|audio_bos|>', '<|audio_eos|>', '<|box_end|>', '<|quad_start|>', '<|quad_end|>', '<|vision_bos|>', '<|vision_eos|>', '<|vision_pad|>', '<|IMAGE|>', '<|VIDEO|>'], 'image_token': '<|IMAGE|>', 'audio_token': '<|AUDIO|>', 'video_token': '<|VIDEO|>', 'vision_bos_token': '<|vision_bos|>', 'vision_eos_token': '<|vision_eos|>', 'audio_bos_token': '<|audio_bos|>', 'audio_eos_token': '<|audio_eos|>'}, clean_up_tokenization_spaces=False, added_tokens_decoder={
	151643: AddedToken("<|endoftext|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151644: AddedToken("<|im_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151645: AddedToken("<|im_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151646: AddedToken("<|AUDIO|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151647: AddedToken("<|audio_bos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151648: AddedToken("<|audio_eos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151649: AddedToken("<|box_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151650: AddedToken("<|quad_start|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151651: AddedToken("<|quad_end|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151652: AddedToken("<|vision_bos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151653: AddedToken("<|vision_eos|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151654: AddedToken("<|vision_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151655: AddedToken("<|IMAGE|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151656: AddedToken("<|VIDEO|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=True),
	151657: AddedToken("<tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151658: AddedToken("</tool_call>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151659: AddedToken("<|fim_prefix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151660: AddedToken("<|fim_middle|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151661: AddedToken("<|fim_suffix|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151662: AddedToken("<|fim_pad|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151663: AddedToken("<|repo_name|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
	151664: AddedToken("<|file_sep|>", rstrip=False, lstrip=False, single_word=False, normalized=False, special=False),
}
)

{
  "processor_class": "Qwen2_5OmniProcessor"
}

[INFO|2025-10-30 15:15:05] llamafactory.data.loader:143 >> Loading dataset VG-LLM-train/scan2cap_train_32frames.json...
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
[rank2]:[W1030 15:15:05.464608985 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 2]  using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank7]:[W1030 15:15:05.487410056 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 7]  using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank6]:[W1030 15:15:05.512429539 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 6]  using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank4]:[W1030 15:15:05.522631444 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 4]  using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank5]:[W1030 15:15:05.557031449 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 5]  using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
[rank0]:[W1030 15:15:06.635697602 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 0]  using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
`trust_remote_code` is not supported anymore.
Please check that the Hugging Face dataset 'json' isn't based on a loading script and remove `trust_remote_code`.
If the dataset is based on a loading script, please ask the dataset author to remove it and convert it to a standard format like Parquet.
training example:
input_ids:
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inputs:
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
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Carefully watch the video and describe the object located at [3.45, 0.9, -1.37] in detail.<|im_end|>
<|im_start|>assistant
A white cabinet in the corner of the room. in the direction from the door and from the inside . it will be on the left, there is a small brown table on the left side of the cabinet and a smaller table on the right side of the cabinet<|im_end|>

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labels:
A white cabinet in the corner of the room. in the direction from the door and from the inside . it will be on the left, there is a small brown table on the left side of the cabinet and a smaller table on the right side of the cabinet<|im_end|>

[INFO|configuration_utils.py:763] 2025-10-30 15:15:15,884 >> loading configuration file ckpts/Qwen2.5-Omni-3B/config.json
[WARNING|modeling_rope_utils.py:557] 2025-10-30 15:15:15,889 >> Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
[INFO|configuration_qwen2_5_omni.py:1059] 2025-10-30 15:15:15,892 >> thinker_config is None. Initializing thinker model with default values
[INFO|configuration_qwen2_5_omni.py:1063] 2025-10-30 15:15:15,893 >> talker_config is None. Initializing talker model with default values
[INFO|configuration_qwen2_5_omni.py:1067] 2025-10-30 15:15:15,893 >> token2wav_config is None. Initializing token2wav model with default values
[INFO|configuration_utils.py:839] 2025-10-30 15:15:15,898 >> Model config Qwen2_5OmniConfig {
  "architectures": [
    "Qwen2_5OmniForConditionalGeneration"
  ],
  "dtype": "bfloat16",
  "enable_audio_output": true,
  "enable_talker": true,
  "model_type": "qwen2_5_omni",
  "talker_config": {
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    "_name_or_path": "Qwen2.5-Omni-3B/talker",
    "architectures": [
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    "attention_dropout": 0.0,
    "audio_end_token_id": 151648,
    "audio_start_token_id": 151647,
    "audio_token_index": 151646,
    "dtype": "bfloat16",
    "embedding_size": 2048,
    "head_dim": 64,
    "hidden_act": "silu",
    "hidden_size": 896,
    "image_token_index": 151655,
    "init_std": 0.02,
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    "intermediate_size": 4864,
    "layer_types": [
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      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
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      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention",
      "full_attention"
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    "max_position_embeddings": 32768,
    "max_window_layers": 28,
    "model_type": "qwen2_5_omni_talker",
    "num_attention_heads": 14,
    "num_hidden_layers": 24,
    "num_key_value_heads": 2,
    "position_id_per_seconds": 25,
    "rms_norm_eps": 1e-06,
    "rope_scaling": {
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        16,
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      "rope_type": "default",
      "type": "default"
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    "rope_theta": 1000000.0,
    "seconds_per_chunk": 2,
    "sliding_window": null,
    "spatial_merge_size": 2,
    "tts_codec_end_token_id": 8294,
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  "thinker_config": {
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      "activation_dropout": 0.0,
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      "block_size": 24,
      "bos_token_id": null,
      "chunk_size_feed_forward": 0,
      "cross_attention_hidden_size": null,
      "decoder_start_token_id": null,
      "depth": 22,
      "dim": 1024,
      "diversity_penalty": 0.0,
      "do_sample": false,
      "dropout": 0.1,
      "dtype": "float32",
      "early_stopping": false,
      "emb_dim": 512,
      "enc_attention_channels": 64,
      "enc_channels": [
        256,
        256,
        256,
        256,
        768
      ],
      "enc_dilations": [
        1,
        2,
        3,
        4,
        1
      ],
      "enc_dim": 128,
      "enc_emb_dim": 192,
      "enc_global_context": true,
      "enc_kernel_sizes": [
        5,
        3,
        3,
        3,
        1
      ],
      "enc_lin_neurons": 192,
      "enc_res2net_scale": 2,
      "enc_se_channels": 64,
      "encoder_no_repeat_ngram_size": 0,
      "eos_token_id": null,
      "exponential_decay_length_penalty": null,
      "ff_mult": 2,
      "finetuning_task": null,
      "forced_bos_token_id": null,
      "forced_eos_token_id": null,
      "head_dim": 64,
      "heads": 16,
      "hidden_size": 1024,
      "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,
      "look_ahead_layers": [
        10
      ],
      "look_backward_layers": [
        0,
        20
      ],
      "max_length": 20,
      "max_position_embeddings": 32768,
      "mel_dim": 80,
      "min_length": 0,
      "model_type": "qwen2_5_omni_dit",
      "no_repeat_ngram_size": 0,
      "num_attention_heads": 16,
      "num_beam_groups": 1,
      "num_beams": 1,
      "num_embeds": 8193,
      "num_hidden_layers": 22,
      "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,
      "repeats": 2,
      "repetition_penalty": 1.0,
      "return_dict": true,
      "return_dict_in_generate": false,
      "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": true,
      "tokenizer_class": null,
      "top_k": 50,
      "top_p": 1.0,
      "torchscript": false,
      "typical_p": 1.0,
      "use_bfloat16": false
    },
    "model_type": "qwen2_5_omni_token2wav"
  },
  "transformers_version": "4.57.1"
}

[INFO|2025-10-30 15:15:15] llamafactory.model.model_utils.kv_cache:143 >> KV cache is disabled during training.
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
Unrecognized keys in `rope_scaling` for 'rope_type'='default': {'mrope_section'}
[WARNING|logging.py:328] 2025-10-30 15:15:17,747 >> `torch_dtype` is deprecated! Use `dtype` instead!
[INFO|modeling_utils.py:1169] 2025-10-30 15:15:17,751 >> loading weights file ckpts/Qwen2.5-Omni-3B/model.safetensors.index.json
[INFO|modeling_utils.py:2341] 2025-10-30 15:15:17,756 >> Instantiating Qwen2_5OmniForConditionalGeneration model under default dtype torch.bfloat16.
[INFO|configuration_utils.py:986] 2025-10-30 15:15:17,761 >> Generate config GenerationConfig {
  "use_cache": false
}

[INFO|configuration_utils.py:986] 2025-10-30 15:15:17,762 >> Generate config GenerationConfig {
  "bos_token_id": 151644,
  "eos_token_id": 151645,
  "pad_token_id": 151643
}

`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!
[INFO|configuration_utils.py:986] 2025-10-30 15:15:17,837 >> Generate config GenerationConfig {}

[INFO|modeling_utils.py:2341] 2025-10-30 15:15:17,851 >> Instantiating Qwen2_5OmniToken2WavDiTModel model under default dtype torch.float32.
`torch_dtype` is deprecated! Use `dtype` instead!
`torch_dtype` is deprecated! Use `dtype` instead!

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[INFO|configuration_utils.py:939] 2025-10-30 15:15:35,808 >> loading configuration file ckpts/Qwen2.5-Omni-3B/generation_config.json
[INFO|configuration_utils.py:986] 2025-10-30 15:15:35,809 >> Generate config GenerationConfig {}

[INFO|dynamic_module_utils.py:423] 2025-10-30 15:15:35,816 >> Could not locate the custom_generate/generate.py inside ckpts/Qwen2.5-Omni-3B.
[INFO|modeling_qwen2_5_omni.py:3727] 2025-10-30 15:15:35,865 >> Speaker ['Ethan', 'Chelsie'] loaded
[INFO|2025-10-30 15:15:35] llamafactory.model.model_utils.checkpointing:143 >> Gradient checkpointing enabled.
[INFO|2025-10-30 15:15:35] llamafactory.model.model_utils.attention:143 >> Using torch SDPA for faster training and inference.
[INFO|2025-10-30 15:15:35] llamafactory.model.adapter:143 >> Upcasting trainable params to float32.
[INFO|2025-10-30 15:15:35] llamafactory.model.adapter:143 >> Fine-tuning method: Full
[INFO|2025-10-30 15:15:35] llamafactory.model.model_utils.visual:143 >> Set vision model not trainable: ['visual.patch_embed', 'visual.blocks', 'audio_tower'].
[INFO|2025-10-30 15:15:35] llamafactory.model.model_utils.visual:143 >> Set multi model projector not trainable: visual.merger.
[INFO|2025-10-30 15:15:36] llamafactory.model.loader:143 >> trainable params: 3,397,103,616 || all params: 4,703,464,448 || trainable%: 72.2256
Detected kernel version 3.10.0, 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.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
[INFO|trainer.py:749] 2025-10-30 15:15:36,275 >> Using auto half precision backend
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
[WARNING|trainer.py:982] 2025-10-30 15:15:36,278 >> The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.
Gradient accumulation steps mismatch: GradientAccumulationPlugin has 1, DeepSpeed config has 4. Using DeepSpeed's value.
[2025-10-30 15:15:36,641] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed info: version=0.16.9, git-hash=unknown, git-branch=unknown
[2025-10-30 15:15:36,641] [INFO] [config.py:735:__init__] Config mesh_device None world_size = 8
[2025-10-30 15:15:38,615] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed Flops Profiler Enabled: False
[2025-10-30 15:15:38,619] [INFO] [logging.py:107:log_dist] [Rank 0] Using client Optimizer as basic optimizer
[2025-10-30 15:15:38,620] [INFO] [logging.py:107:log_dist] [Rank 0] Removing param_group that has no 'params' in the basic Optimizer
[2025-10-30 15:15:38,656] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed Basic Optimizer = AdamW
[2025-10-30 15:15:38,657] [INFO] [utils.py:59:is_zero_supported_optimizer] Checking ZeRO support for optimizer=AdamW type=<class 'torch.optim.adamw.AdamW'>
[2025-10-30 15:15:38,657] [INFO] [logging.py:107:log_dist] [Rank 0] Creating torch.bfloat16 ZeRO stage 2 optimizer
[2025-10-30 15:15:38,658] [INFO] [stage_1_and_2.py:150:__init__] Reduce bucket size 500000000
[2025-10-30 15:15:38,658] [INFO] [stage_1_and_2.py:151:__init__] Allgather bucket size 500000000
[2025-10-30 15:15:38,659] [INFO] [stage_1_and_2.py:152:__init__] CPU Offload: False
[2025-10-30 15:15:38,659] [INFO] [stage_1_and_2.py:153:__init__] Round robin gradient partitioning: True
[2025-10-30 15:15:53,799] [INFO] [utils.py:781:see_memory_usage] Before initializing optimizer states
[2025-10-30 15:15:53,801] [INFO] [utils.py:782:see_memory_usage] MA 10.35 GB         Max_MA 10.35 GB         CA 10.38 GB         Max_CA 10 GB 
[2025-10-30 15:15:53,805] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory:  used = 133.7 GB, percent = 13.3%
[2025-10-30 15:15:54,384] [INFO] [utils.py:781:see_memory_usage] After initializing optimizer states
[2025-10-30 15:15:54,386] [INFO] [utils.py:782:see_memory_usage] MA 10.35 GB         Max_MA 11.93 GB         CA 11.96 GB         Max_CA 12 GB 
[2025-10-30 15:15:54,388] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory:  used = 137.65 GB, percent = 13.7%
[2025-10-30 15:15:54,389] [INFO] [stage_1_and_2.py:557:__init__] optimizer state initialized
[2025-10-30 15:15:54,852] [INFO] [utils.py:781:see_memory_usage] After initializing ZeRO optimizer
[2025-10-30 15:15:54,854] [INFO] [utils.py:782:see_memory_usage] MA 10.35 GB         Max_MA 10.35 GB         CA 11.96 GB         Max_CA 12 GB 
[2025-10-30 15:15:54,855] [INFO] [utils.py:789:see_memory_usage] CPU Virtual Memory:  used = 137.39 GB, percent = 13.6%
[2025-10-30 15:15:54,860] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed Final Optimizer = DeepSpeedZeroOptimizer
[2025-10-30 15:15:54,860] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed using configured LR scheduler = None
[2025-10-30 15:15:54,861] [INFO] [logging.py:107:log_dist] [Rank 0] DeepSpeed LR Scheduler = None
[2025-10-30 15:15:54,861] [INFO] [logging.py:107:log_dist] [Rank 0] step=0, skipped=0, lr=[0.0, 0.0], mom=[(0.9, 0.999), (0.9, 0.999)]
[2025-10-30 15:15:54,865] [INFO] [config.py:1003:print] DeepSpeedEngine configuration:
[2025-10-30 15:15:54,866] [INFO] [config.py:1007:print]   activation_checkpointing_config  {
    "partition_activations": false, 
    "contiguous_memory_optimization": false, 
    "cpu_checkpointing": false, 
    "number_checkpoints": null, 
    "synchronize_checkpoint_boundary": false, 
    "profile": false
}
[2025-10-30 15:15:54,867] [INFO] [config.py:1007:print]   aio_config ................... {'block_size': 1048576, 'queue_depth': 8, 'intra_op_parallelism': 1, 'single_submit': False, 'overlap_events': True, 'use_gds': False}
[2025-10-30 15:15:54,867] [INFO] [config.py:1007:print]   amp_enabled .................. False
[2025-10-30 15:15:54,868] [INFO] [config.py:1007:print]   amp_params ................... False
[2025-10-30 15:15:54,869] [INFO] [config.py:1007:print]   autotuning_config ............ {
    "enabled": false, 
    "start_step": null, 
    "end_step": null, 
    "metric_path": null, 
    "arg_mappings": null, 
    "metric": "throughput", 
    "model_info": null, 
    "results_dir": "autotuning_results", 
    "exps_dir": "autotuning_exps", 
    "overwrite": true, 
    "fast": true, 
    "start_profile_step": 3, 
    "end_profile_step": 5, 
    "tuner_type": "gridsearch", 
    "tuner_early_stopping": 5, 
    "tuner_num_trials": 50, 
    "model_info_path": null, 
    "mp_size": 1, 
    "max_train_batch_size": null, 
    "min_train_batch_size": 1, 
    "max_train_micro_batch_size_per_gpu": 1.024000e+03, 
    "min_train_micro_batch_size_per_gpu": 1, 
    "num_tuning_micro_batch_sizes": 3
}
[2025-10-30 15:15:54,869] [INFO] [config.py:1007:print]   bfloat16_enabled ............. True
[2025-10-30 15:15:54,870] [INFO] [config.py:1007:print]   bfloat16_immediate_grad_update  True
[2025-10-30 15:15:54,870] [INFO] [config.py:1007:print]   checkpoint_parallel_write_pipeline  False
[2025-10-30 15:15:54,870] [INFO] [config.py:1007:print]   checkpoint_tag_validation_enabled  True
[2025-10-30 15:15:54,872] [INFO] [config.py:1007:print]   checkpoint_tag_validation_fail  False
[2025-10-30 15:15:54,873] [INFO] [config.py:1007:print]   comms_config ................. <deepspeed.comm.config.DeepSpeedCommsConfig object at 0x7f6aff82c890>
[2025-10-30 15:15:54,875] [INFO] [config.py:1007:print]   communication_data_type ...... None
[2025-10-30 15:15:54,876] [INFO] [config.py:1007:print]   compile_config ............... deepcompile=False free_activation=False offload_activation=False offload_opt_states=False double_buffer=True symmetric_memory=False debug_log=False offload_parameters=False sync_before_reduce=False sync_after_reduce=False sync_before_allgather=False sync_after_allgather=False
[2025-10-30 15:15:54,876] [INFO] [config.py:1007:print]   compression_config ........... {'weight_quantization': {'shared_parameters': {'enabled': False, 'quantizer_kernel': False, 'schedule_offset': 0, 'quantize_groups': 1, 'quantize_verbose': False, 'quantization_type': 'symmetric', 'quantize_weight_in_forward': False, 'rounding': 'nearest', 'fp16_mixed_quantize': False, 'quantize_change_ratio': 0.001}, 'different_groups': {}}, 'activation_quantization': {'shared_parameters': {'enabled': False, 'quantization_type': 'symmetric', 'range_calibration': 'dynamic', 'schedule_offset': 1000}, 'different_groups': {}}, 'sparse_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'row_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'head_pruning': {'shared_parameters': {'enabled': False, 'method': 'topk', 'schedule_offset': 1000}, 'different_groups': {}}, 'channel_pruning': {'shared_parameters': {'enabled': False, 'method': 'l1', 'schedule_offset': 1000}, 'different_groups': {}}, 'layer_reduction': {'enabled': False}}
[2025-10-30 15:15:54,877] [INFO] [config.py:1007:print]   curriculum_enabled_legacy .... False
[2025-10-30 15:15:54,877] [INFO] [config.py:1007:print]   curriculum_params_legacy ..... False
[2025-10-30 15:15:54,877] [INFO] [config.py:1007:print]   data_efficiency_config ....... {'enabled': False, 'seed': 1234, 'data_sampling': {'enabled': False, 'num_epochs': 1000, 'num_workers': 0, 'pin_memory': False, 'curriculum_learning': {'enabled': False}, 'dynamic_batching': {'enabled': False, 'lr_scaling_method': 'linear', 'min_batch_size': 1, 'max_batch_size': None, 'sequence_picking_order': 'dataloader', 'verbose': False}}, 'data_routing': {'enabled': False, 'random_ltd': {'enabled': False, 'layer_token_lr_schedule': {'enabled': False}}}}
[2025-10-30 15:15:54,878] [INFO] [config.py:1007:print]   data_efficiency_enabled ...... False
[2025-10-30 15:15:54,878] [INFO] [config.py:1007:print]   dataloader_drop_last ......... False
[2025-10-30 15:15:54,879] [INFO] [config.py:1007:print]   disable_allgather ............ False
[2025-10-30 15:15:54,879] [INFO] [config.py:1007:print]   dump_state ................... False
[2025-10-30 15:15:54,880] [INFO] [config.py:1007:print]   dynamic_loss_scale_args ...... None
[2025-10-30 15:15:54,882] [INFO] [config.py:1007:print]   eigenvalue_enabled ........... False
[2025-10-30 15:15:54,883] [INFO] [config.py:1007:print]   eigenvalue_gas_boundary_resolution  1
[2025-10-30 15:15:54,883] [INFO] [config.py:1007:print]   eigenvalue_layer_name ........ bert.encoder.layer
[2025-10-30 15:15:54,883] [INFO] [config.py:1007:print]   eigenvalue_layer_num ......... 0
[2025-10-30 15:15:54,884] [INFO] [config.py:1007:print]   eigenvalue_max_iter .......... 100
[2025-10-30 15:15:54,884] [INFO] [config.py:1007:print]   eigenvalue_stability ......... 1e-06
[2025-10-30 15:15:54,885] [INFO] [config.py:1007:print]   eigenvalue_tol ............... 0.01
[2025-10-30 15:15:54,885] [INFO] [config.py:1007:print]   eigenvalue_verbose ........... False
[2025-10-30 15:15:54,886] [INFO] [config.py:1007:print]   elasticity_enabled ........... False
[2025-10-30 15:15:54,886] [INFO] [config.py:1007:print]   flops_profiler_config ........ {
    "enabled": false, 
    "recompute_fwd_factor": 0.0, 
    "profile_step": 1, 
    "module_depth": -1, 
    "top_modules": 1, 
    "detailed": true, 
    "output_file": null
}
[2025-10-30 15:15:54,886] [INFO] [config.py:1007:print]   fp16_auto_cast ............... None
[2025-10-30 15:15:54,887] [INFO] [config.py:1007:print]   fp16_enabled ................. False
[2025-10-30 15:15:54,887] [INFO] [config.py:1007:print]   fp16_master_weights_and_gradients  False
[2025-10-30 15:15:54,888] [INFO] [config.py:1007:print]   global_rank .................. 0
[2025-10-30 15:15:54,888] [INFO] [config.py:1007:print]   grad_accum_dtype ............. None
[2025-10-30 15:15:54,889] [INFO] [config.py:1007:print]   gradient_accumulation_steps .. 4
[2025-10-30 15:15:54,889] [INFO] [config.py:1007:print]   gradient_clipping ............ 1.0
[2025-10-30 15:15:54,889] [INFO] [config.py:1007:print]   gradient_predivide_factor .... 1.0
[2025-10-30 15:15:54,890] [INFO] [config.py:1007:print]   graph_harvesting ............. False
[2025-10-30 15:15:54,891] [INFO] [config.py:1007:print]   hybrid_engine ................ enabled=False max_out_tokens=512 inference_tp_size=1 release_inference_cache=False pin_parameters=True tp_gather_partition_size=8
[2025-10-30 15:15:54,891] [INFO] [config.py:1007:print]   initial_dynamic_scale ........ 1
[2025-10-30 15:15:54,892] [INFO] [config.py:1007:print]   load_universal_checkpoint .... False
[2025-10-30 15:15:54,892] [INFO] [config.py:1007:print]   loss_scale ................... 1.0
[2025-10-30 15:15:54,893] [INFO] [config.py:1007:print]   memory_breakdown ............. False
[2025-10-30 15:15:54,893] [INFO] [config.py:1007:print]   mics_hierarchial_params_gather  False
[2025-10-30 15:15:54,894] [INFO] [config.py:1007:print]   mics_shard_size .............. -1
[2025-10-30 15:15:54,894] [INFO] [config.py:1007:print]   monitor_config ............... tensorboard=TensorBoardConfig(enabled=False, output_path='', job_name='DeepSpeedJobName') comet=CometConfig(enabled=False, samples_log_interval=100, project=None, workspace=None, api_key=None, experiment_name=None, experiment_key=None, online=None, mode=None) wandb=WandbConfig(enabled=False, group=None, team=None, project='deepspeed') csv_monitor=CSVConfig(enabled=False, output_path='', job_name='DeepSpeedJobName')
[2025-10-30 15:15:54,895] [INFO] [config.py:1007:print]   nebula_config ................ {
    "enabled": false, 
    "persistent_storage_path": null, 
    "persistent_time_interval": 100, 
    "num_of_version_in_retention": 2, 
    "enable_nebula_load": true, 
    "load_path": null
}
[2025-10-30 15:15:54,895] [INFO] [config.py:1007:print]   optimizer_legacy_fusion ...... False
[2025-10-30 15:15:54,895] [INFO] [config.py:1007:print]   optimizer_name ............... None
[2025-10-30 15:15:54,896] [INFO] [config.py:1007:print]   optimizer_params ............. None
[2025-10-30 15:15:54,896] [INFO] [config.py:1007:print]   pipeline ..................... {'stages': 'auto', 'partition': 'best', 'seed_layers': False, 'activation_checkpoint_interval': 0, 'pipe_partitioned': True, 'grad_partitioned': True}
[2025-10-30 15:15:54,897] [INFO] [config.py:1007:print]   pld_enabled .................. False
[2025-10-30 15:15:54,897] [INFO] [config.py:1007:print]   pld_params ................... False
[2025-10-30 15:15:54,898] [INFO] [config.py:1007:print]   prescale_gradients ........... False
[2025-10-30 15:15:54,898] [INFO] [config.py:1007:print]   scheduler_name ............... None
[2025-10-30 15:15:54,898] [INFO] [config.py:1007:print]   scheduler_params ............. None
[2025-10-30 15:15:54,900] [INFO] [config.py:1007:print]   seq_parallel_communication_data_type  torch.float32
[2025-10-30 15:15:54,900] [INFO] [config.py:1007:print]   sparse_attention ............. None
[2025-10-30 15:15:54,901] [INFO] [config.py:1007:print]   sparse_gradients_enabled ..... False
[2025-10-30 15:15:54,902] [INFO] [config.py:1007:print]   steps_per_print .............. inf
[2025-10-30 15:15:54,902] [INFO] [config.py:1007:print]   tensor_parallel_config ....... dtype=torch.float16 autotp_size=0 tp_overlap_comm=False tensor_parallel=TPConfig(tp_size=1, tp_grain_size=1, mpu=None, tp_group=None) injection_policy_tuple=None keep_module_on_host=False replace_with_kernel_inject=False
[2025-10-30 15:15:54,903] [INFO] [config.py:1007:print]   timers_config ................ enabled=True synchronized=True
[2025-10-30 15:15:54,903] [INFO] [config.py:1007:print]   train_batch_size ............. 32
[2025-10-30 15:15:54,903] [INFO] [config.py:1007:print]   train_micro_batch_size_per_gpu  1
[2025-10-30 15:15:54,904] [INFO] [config.py:1007:print]   use_data_before_expert_parallel_  False
[2025-10-30 15:15:54,904] [INFO] [config.py:1007:print]   use_node_local_storage ....... False
[2025-10-30 15:15:54,905] [INFO] [config.py:1007:print]   wall_clock_breakdown ......... False
[2025-10-30 15:15:54,905] [INFO] [config.py:1007:print]   weight_quantization_config ... None
[2025-10-30 15:15:54,906] [INFO] [config.py:1007:print]   world_size ................... 8
[2025-10-30 15:15:54,907] [INFO] [config.py:1007:print]   zero_allow_untested_optimizer  True
[2025-10-30 15:15:54,907] [INFO] [config.py:1007:print]   zero_config .................. stage=2 contiguous_gradients=True reduce_scatter=True reduce_bucket_size=500000000 use_multi_rank_bucket_allreduce=True allgather_partitions=True allgather_bucket_size=500000000 overlap_comm=False load_from_fp32_weights=True elastic_checkpoint=False offload_param=None offload_optimizer=None sub_group_size=1000000000 cpu_offload_param=None cpu_offload_use_pin_memory=None cpu_offload=None prefetch_bucket_size=50000000 param_persistence_threshold=100000 model_persistence_threshold=9223372036854775807 max_live_parameters=1000000000 max_reuse_distance=1000000000 gather_16bit_weights_on_model_save=False module_granularity_threshold=0 use_all_reduce_for_fetch_params=False stage3_gather_fp16_weights_on_model_save=False ignore_unused_parameters=True legacy_stage1=False round_robin_gradients=True zero_hpz_partition_size=1 zero_quantized_weights=False zero_quantized_nontrainable_weights=False zero_quantized_gradients=False zeropp_loco_param=None mics_shard_size=-1 mics_hierarchical_params_gather=False memory_efficient_linear=True pipeline_loading_checkpoint=False override_module_apply=True log_trace_cache_warnings=False
[2025-10-30 15:15:54,908] [INFO] [config.py:1007:print]   zero_enabled ................. True
[2025-10-30 15:15:54,908] [INFO] [config.py:1007:print]   zero_force_ds_cpu_optimizer .. True
[2025-10-30 15:15:54,909] [INFO] [config.py:1007:print]   zero_optimization_stage ...... 2
[2025-10-30 15:15:54,910] [INFO] [config.py:993:print_user_config]   json = {
    "train_batch_size": 32, 
    "train_micro_batch_size_per_gpu": 1, 
    "gradient_accumulation_steps": 4, 
    "gradient_clipping": 1.0, 
    "zero_allow_untested_optimizer": true, 
    "fp16": {
        "enabled": false, 
        "loss_scale": 0, 
        "loss_scale_window": 1000, 
        "initial_scale_power": 16, 
        "hysteresis": 2, 
        "min_loss_scale": 1
    }, 
    "bf16": {
        "enabled": true
    }, 
    "zero_optimization": {
        "stage": 2, 
        "allgather_partitions": true, 
        "allgather_bucket_size": 5.000000e+08, 
        "overlap_comm": false, 
        "reduce_scatter": true, 
        "reduce_bucket_size": 5.000000e+08, 
        "contiguous_gradients": true, 
        "round_robin_gradients": true
    }, 
    "steps_per_print": inf
}
[INFO|trainer.py:2519] 2025-10-30 15:15:54,915 >> ***** Running training *****
[INFO|trainer.py:2520] 2025-10-30 15:15:54,916 >>   Num examples = 36,665
[INFO|trainer.py:2521] 2025-10-30 15:15:54,916 >>   Num Epochs = 1
[INFO|trainer.py:2522] 2025-10-30 15:15:54,917 >>   Instantaneous batch size per device = 1
[INFO|trainer.py:2525] 2025-10-30 15:15:54,917 >>   Total train batch size (w. parallel, distributed & accumulation) = 32
[INFO|trainer.py:2526] 2025-10-30 15:15:54,958 >>   Gradient Accumulation steps = 4
[INFO|trainer.py:2527] 2025-10-30 15:15:54,959 >>   Total optimization steps = 1,146
[INFO|trainer.py:2528] 2025-10-30 15:15:54,964 >>   Number of trainable parameters = 3,397,103,616

  0%|          | 0/1146 [00:00<?, ?it/s]`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
[WARNING|logging.py:328] 2025-10-30 15:16:13,359 >> `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...
`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...

  0%|          | 1/1146 [00:42<13:33:56, 42.65s/it]
                                                   
{'loss': 3.0487, 'grad_norm': 87.76886749267578, 'learning_rate': 0.0, 'epoch': 0.0}

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  0%|          | 2/1146 [01:09<10:32:39, 33.18s/it]
                                                   
{'loss': 3.0326, 'grad_norm': 90.83219146728516, 'learning_rate': 8.695652173913044e-08, 'epoch': 0.0}

  0%|          | 2/1146 [01:09<10:32:39, 33.18s/it]
  0%|          | 3/1146 [01:35<9:32:49, 30.07s/it] 
                                                  
{'loss': 3.0519, 'grad_norm': 88.12660217285156, 'learning_rate': 1.7391304347826088e-07, 'epoch': 0.0}

  0%|          | 3/1146 [01:35<9:32:49, 30.07s/it]
  0%|          | 4/1146 [02:01<9:01:48, 28.47s/it]
                                                  
{'loss': 3.1672, 'grad_norm': 89.76210021972656, 'learning_rate': 2.608695652173913e-07, 'epoch': 0.0}

  0%|          | 4/1146 [02:01<9:01:48, 28.47s/it]
  0%|          | 5/1146 [02:26<8:40:13, 27.36s/it]
                                                  
{'loss': 3.0186, 'grad_norm': 87.10993194580078, 'learning_rate': 3.4782608695652175e-07, 'epoch': 0.0}

  0%|          | 5/1146 [02:26<8:40:13, 27.36s/it]
  1%|          | 6/1146 [02:53<8:32:05, 26.95s/it]
                                                  
{'loss': 3.071, 'grad_norm': 82.0281982421875, 'learning_rate': 4.347826086956522e-07, 'epoch': 0.01}

  1%|          | 6/1146 [02:53<8:32:05, 26.95s/it]
  1%|          | 7/1146 [03:18<8:23:45, 26.54s/it]
                                                  
{'loss': 2.9104, 'grad_norm': 79.63187408447266, 'learning_rate': 5.217391304347826e-07, 'epoch': 0.01}

  1%|          | 7/1146 [03:18<8:23:45, 26.54s/it]
  1%|          | 8/1146 [03:44<8:16:32, 26.18s/it]
                                                  
{'loss': 3.1575, 'grad_norm': 87.73326873779297, 'learning_rate': 6.086956521739131e-07, 'epoch': 0.01}

  1%|          | 8/1146 [03:44<8:16:32, 26.18s/it]
  1%|          | 9/1146 [04:10<8:14:51, 26.11s/it]
                                                  
{'loss': 2.7869, 'grad_norm': 64.2441177368164, 'learning_rate': 6.956521739130435e-07, 'epoch': 0.01}

  1%|          | 9/1146 [04:10<8:14:51, 26.11s/it]
  1%|          | 10/1146 [04:36<8:15:48, 26.19s/it]
                                                   
{'loss': 3.0605, 'grad_norm': 70.00951385498047, 'learning_rate': 7.82608695652174e-07, 'epoch': 0.01}

  1%|          | 10/1146 [04:36<8:15:48, 26.19s/it]
  1%|          | 11/1146 [05:02<8:12:54, 26.06s/it]
                                                   
{'loss': 2.7621, 'grad_norm': 48.61689376831055, 'learning_rate': 8.695652173913044e-07, 'epoch': 0.01}

  1%|          | 11/1146 [05:02<8:12:54, 26.06s/it]
  1%|          | 12/1146 [05:28<8:10:40, 25.96s/it]
                                                   
{'loss': 2.8721, 'grad_norm': 45.11052322387695, 'learning_rate': 9.565217391304349e-07, 'epoch': 0.01}

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  1%|          | 13/1146 [05:54<8:12:34, 26.09s/it]
                                                   
{'loss': 2.5862, 'grad_norm': 45.611995697021484, 'learning_rate': 1.0434782608695653e-06, 'epoch': 0.01}

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  1%|          | 14/1146 [06:20<8:10:59, 26.02s/it]
                                                   
{'loss': 2.8375, 'grad_norm': 42.117408752441406, 'learning_rate': 1.1304347826086956e-06, 'epoch': 0.01}

  1%|          | 14/1146 [06:20<8:10:59, 26.02s/it]
  1%|▏         | 15/1146 [06:45<8:08:10, 25.90s/it]
                                                   
{'loss': 2.3659, 'grad_norm': 34.61255645751953, 'learning_rate': 1.2173913043478262e-06, 'epoch': 0.01}

  1%|▏         | 15/1146 [06:45<8:08:10, 25.90s/it]
  1%|▏         | 16/1146 [07:11<8:06:37, 25.84s/it]
                                                   
{'loss': 2.1771, 'grad_norm': 30.530881881713867, 'learning_rate': 1.3043478260869566e-06, 'epoch': 0.01}

  1%|▏         | 16/1146 [07:11<8:06:37, 25.84s/it]
  1%|▏         | 17/1146 [07:37<8:07:37, 25.91s/it]
                                                   
{'loss': 2.363, 'grad_norm': 29.775405883789062, 'learning_rate': 1.391304347826087e-06, 'epoch': 0.01}

  1%|▏         | 17/1146 [07:37<8:07:37, 25.91s/it]
  2%|▏         | 18/1146 [08:03<8:07:14, 25.92s/it]
                                                   
{'loss': 2.1899, 'grad_norm': 30.224348068237305, 'learning_rate': 1.4782608695652176e-06, 'epoch': 0.02}

  2%|▏         | 18/1146 [08:03<8:07:14, 25.92s/it]
  2%|▏         | 19/1146 [08:29<8:03:55, 25.76s/it]
                                                   
{'loss': 2.3346, 'grad_norm': 24.932607650756836, 'learning_rate': 1.565217391304348e-06, 'epoch': 0.02}

  2%|▏         | 19/1146 [08:29<8:03:55, 25.76s/it]
  2%|▏         | 20/1146 [08:55<8:07:00, 25.95s/it]
                                                   
{'loss': 2.2013, 'grad_norm': 22.714818954467773, 'learning_rate': 1.6521739130434784e-06, 'epoch': 0.02}

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  2%|▏         | 21/1146 [09:21<8:07:53, 26.02s/it]
                                                   
{'loss': 2.21, 'grad_norm': 27.887670516967773, 'learning_rate': 1.7391304347826088e-06, 'epoch': 0.02}

  2%|▏         | 21/1146 [09:21<8:07:53, 26.02s/it]
  2%|▏         | 22/1146 [09:47<8:05:49, 25.93s/it]
                                                   
{'loss': 2.0947, 'grad_norm': 28.15935707092285, 'learning_rate': 1.8260869565217394e-06, 'epoch': 0.02}

  2%|▏         | 22/1146 [09:47<8:05:49, 25.93s/it]
  2%|▏         | 23/1146 [10:13<8:06:18, 25.98s/it]
                                                   
{'loss': 1.9774, 'grad_norm': 21.274784088134766, 'learning_rate': 1.9130434782608697e-06, 'epoch': 0.02}

  2%|▏         | 23/1146 [10:13<8:06:18, 25.98s/it]
  2%|▏         | 24/1146 [10:39<8:05:48, 25.98s/it]
                                                   
{'loss': 2.0239, 'grad_norm': 19.53569793701172, 'learning_rate': 2.0000000000000003e-06, 'epoch': 0.02}

  2%|▏         | 24/1146 [10:39<8:05:48, 25.98s/it]
  2%|▏         | 25/1146 [11:05<8:05:31, 25.99s/it]
                                                   
{'loss': 2.1537, 'grad_norm': 16.339805603027344, 'learning_rate': 2.0869565217391305e-06, 'epoch': 0.02}

  2%|▏         | 25/1146 [11:05<8:05:31, 25.99s/it]
  2%|▏         | 26/1146 [11:31<8:02:58, 25.87s/it]
                                                   
{'loss': 1.9562, 'grad_norm': 16.08367156982422, 'learning_rate': 2.173913043478261e-06, 'epoch': 0.02}

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  2%|▏         | 27/1146 [11:56<8:01:22, 25.81s/it]
                                                   
{'loss': 2.0472, 'grad_norm': 15.255630493164062, 'learning_rate': 2.2608695652173913e-06, 'epoch': 0.02}

  2%|▏         | 27/1146 [11:56<8:01:22, 25.81s/it]
  2%|▏         | 28/1146 [12:23<8:03:53, 25.97s/it]
                                                   
{'loss': 1.9548, 'grad_norm': 11.413243293762207, 'learning_rate': 2.347826086956522e-06, 'epoch': 0.02}

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  3%|▎         | 29/1146 [12:48<8:03:14, 25.96s/it]
                                                   
{'loss': 1.9132, 'grad_norm': 10.853246688842773, 'learning_rate': 2.4347826086956525e-06, 'epoch': 0.03}

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  3%|▎         | 30/1146 [13:14<7:59:40, 25.79s/it]
                                                   
{'loss': 1.7923, 'grad_norm': 10.025012016296387, 'learning_rate': 2.5217391304347826e-06, 'epoch': 0.03}

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  3%|▎         | 31/1146 [13:40<8:01:44, 25.92s/it]
                                                   
{'loss': 1.9748, 'grad_norm': 9.974859237670898, 'learning_rate': 2.6086956521739132e-06, 'epoch': 0.03}

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  3%|▎         | 32/1146 [14:06<8:02:35, 25.99s/it]
                                                   
{'loss': 1.8219, 'grad_norm': 9.28125286102295, 'learning_rate': 2.695652173913044e-06, 'epoch': 0.03}

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  3%|▎         | 33/1146 [14:32<8:00:23, 25.90s/it]
                                                   
{'loss': 1.7107, 'grad_norm': 9.1905517578125, 'learning_rate': 2.782608695652174e-06, 'epoch': 0.03}

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  3%|▎         | 34/1146 [14:58<7:58:50, 25.84s/it]
                                                   
{'loss': 1.9069, 'grad_norm': 9.644187927246094, 'learning_rate': 2.8695652173913046e-06, 'epoch': 0.03}

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{'loss': 1.8349, 'grad_norm': 9.01826286315918, 'learning_rate': 2.956521739130435e-06, 'epoch': 0.03}

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{'loss': 1.7864, 'grad_norm': 8.209209442138672, 'learning_rate': 3.043478260869566e-06, 'epoch': 0.03}

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{'loss': 1.7647, 'grad_norm': 9.072196006774902, 'learning_rate': 3.130434782608696e-06, 'epoch': 0.03}

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{'loss': 1.7154, 'grad_norm': 8.333982467651367, 'learning_rate': 3.217391304347826e-06, 'epoch': 0.03}

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  3%|▎         | 39/1146 [17:08<8:00:11, 26.03s/it]
                                                   
{'loss': 1.6767, 'grad_norm': 8.417268753051758, 'learning_rate': 3.3043478260869567e-06, 'epoch': 0.03}

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  3%|▎         | 40/1146 [17:34<7:59:14, 26.00s/it]
                                                   
{'loss': 1.6288, 'grad_norm': 7.973165988922119, 'learning_rate': 3.391304347826087e-06, 'epoch': 0.03}

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  4%|▎         | 41/1146 [18:00<7:58:16, 25.97s/it]
                                                   
{'loss': 1.7383, 'grad_norm': 8.1939697265625, 'learning_rate': 3.4782608695652175e-06, 'epoch': 0.04}

  4%|▎         | 41/1146 [18:00<7:58:16, 25.97s/it]
  4%|▎         | 42/1146 [18:26<7:58:51, 26.03s/it]
                                                   
{'loss': 1.5928, 'grad_norm': 7.046876907348633, 'learning_rate': 3.565217391304348e-06, 'epoch': 0.04}

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{'loss': 1.5296, 'grad_norm': 8.747233390808105, 'learning_rate': 3.6521739130434787e-06, 'epoch': 0.04}

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{'loss': 1.7142, 'grad_norm': 9.229941368103027, 'learning_rate': 3.739130434782609e-06, 'epoch': 0.04}

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{'loss': 1.5957, 'grad_norm': 9.32880973815918, 'learning_rate': 3.8260869565217395e-06, 'epoch': 0.04}

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{'loss': 1.6838, 'grad_norm': 9.274460792541504, 'learning_rate': 3.91304347826087e-06, 'epoch': 0.04}

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{'loss': 1.6791, 'grad_norm': 7.56842041015625, 'learning_rate': 4.000000000000001e-06, 'epoch': 0.04}

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{'loss': 1.6972, 'grad_norm': 7.578010082244873, 'learning_rate': 4.086956521739131e-06, 'epoch': 0.04}

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{'loss': 1.7066, 'grad_norm': 8.215082168579102, 'learning_rate': 4.173913043478261e-06, 'epoch': 0.04}

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{'loss': 1.6844, 'grad_norm': 8.56248950958252, 'learning_rate': 4.260869565217392e-06, 'epoch': 0.04}

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{'loss': 1.674, 'grad_norm': 7.7441630363464355, 'learning_rate': 4.347826086956522e-06, 'epoch': 0.04}

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{'loss': 1.5812, 'grad_norm': 6.880199432373047, 'learning_rate': 4.434782608695653e-06, 'epoch': 0.05}

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{'loss': 1.6189, 'grad_norm': 8.119424819946289, 'learning_rate': 4.5217391304347826e-06, 'epoch': 0.05}

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{'loss': 1.6514, 'grad_norm': 7.647992134094238, 'learning_rate': 4.608695652173913e-06, 'epoch': 0.05}

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{'loss': 1.7178, 'grad_norm': 7.559144496917725, 'learning_rate': 4.695652173913044e-06, 'epoch': 0.05}

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{'loss': 1.6316, 'grad_norm': 7.983002185821533, 'learning_rate': 4.782608695652174e-06, 'epoch': 0.05}

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{'loss': 1.6004, 'grad_norm': 7.838183879852295, 'learning_rate': 4.869565217391305e-06, 'epoch': 0.05}

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{'loss': 1.6005, 'grad_norm': 7.958566665649414, 'learning_rate': 4.9565217391304355e-06, 'epoch': 0.05}

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{'loss': 1.5939, 'grad_norm': 7.580433368682861, 'learning_rate': 5.043478260869565e-06, 'epoch': 0.05}

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{'loss': 1.5855, 'grad_norm': 7.627135753631592, 'learning_rate': 5.130434782608697e-06, 'epoch': 0.05}

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{'loss': 1.4677, 'grad_norm': 7.756627082824707, 'learning_rate': 5.2173913043478265e-06, 'epoch': 0.05}

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{'loss': 1.6484, 'grad_norm': 7.601851940155029, 'learning_rate': 5.304347826086957e-06, 'epoch': 0.05}

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{'loss': 1.6054, 'grad_norm': 8.443552017211914, 'learning_rate': 5.391304347826088e-06, 'epoch': 0.05}

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{'loss': 1.5319, 'grad_norm': 7.365474700927734, 'learning_rate': 5.478260869565217e-06, 'epoch': 0.06}

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{'loss': 1.7043, 'grad_norm': 7.83988618850708, 'learning_rate': 5.565217391304348e-06, 'epoch': 0.06}

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{'loss': 1.5675, 'grad_norm': 8.728271484375, 'learning_rate': 5.652173913043479e-06, 'epoch': 0.06}

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{'loss': 1.5635, 'grad_norm': 9.661201477050781, 'learning_rate': 5.739130434782609e-06, 'epoch': 0.06}

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{'loss': 1.6598, 'grad_norm': 7.576848983764648, 'learning_rate': 5.826086956521739e-06, 'epoch': 0.06}

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{'loss': 1.4972, 'grad_norm': 7.561553955078125, 'learning_rate': 5.91304347826087e-06, 'epoch': 0.06}

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{'loss': 1.5503, 'grad_norm': 7.2475481033325195, 'learning_rate': 6e-06, 'epoch': 0.06}

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{'loss': 1.5118, 'grad_norm': 7.334590911865234, 'learning_rate': 6.086956521739132e-06, 'epoch': 0.06}

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{'loss': 1.7376, 'grad_norm': 7.769559383392334, 'learning_rate': 6.173913043478261e-06, 'epoch': 0.06}

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{'loss': 1.5012, 'grad_norm': 8.886149406433105, 'learning_rate': 6.260869565217392e-06, 'epoch': 0.06}

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{'loss': 1.6229, 'grad_norm': 8.739788055419922, 'learning_rate': 6.3478260869565225e-06, 'epoch': 0.06}

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{'loss': 1.5219, 'grad_norm': 7.732006549835205, 'learning_rate': 6.434782608695652e-06, 'epoch': 0.07}

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{'loss': 1.5189, 'grad_norm': 7.980958461761475, 'learning_rate': 6.521739130434783e-06, 'epoch': 0.07}

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{'loss': 1.6637, 'grad_norm': 8.607786178588867, 'learning_rate': 6.6086956521739135e-06, 'epoch': 0.07}

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{'loss': 1.4446, 'grad_norm': 7.533051490783691, 'learning_rate': 6.695652173913044e-06, 'epoch': 0.07}

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{'loss': 1.5881, 'grad_norm': 8.322000503540039, 'learning_rate': 6.782608695652174e-06, 'epoch': 0.07}

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{'loss': 1.6445, 'grad_norm': 8.121260643005371, 'learning_rate': 6.869565217391305e-06, 'epoch': 0.07}

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{'loss': 1.4647, 'grad_norm': 7.419255256652832, 'learning_rate': 6.956521739130435e-06, 'epoch': 0.07}

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{'loss': 1.4868, 'grad_norm': 7.407382965087891, 'learning_rate': 7.0434782608695665e-06, 'epoch': 0.07}

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{'loss': 1.4281, 'grad_norm': 6.782423973083496, 'learning_rate': 7.130434782608696e-06, 'epoch': 0.07}

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{'loss': 1.61, 'grad_norm': 7.840005397796631, 'learning_rate': 7.217391304347827e-06, 'epoch': 0.07}

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{'loss': 1.5992, 'grad_norm': 7.948174476623535, 'learning_rate': 7.304347826086957e-06, 'epoch': 0.07}

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{'loss': 1.4928, 'grad_norm': 7.3349690437316895, 'learning_rate': 7.391304347826087e-06, 'epoch': 0.08}

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{'loss': 1.3838, 'grad_norm': 7.508388519287109, 'learning_rate': 7.478260869565218e-06, 'epoch': 0.08}

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{'loss': 1.6189, 'grad_norm': 8.336546897888184, 'learning_rate': 7.565217391304348e-06, 'epoch': 0.08}

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{'loss': 1.5103, 'grad_norm': 7.23030424118042, 'learning_rate': 7.652173913043479e-06, 'epoch': 0.08}

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{'loss': 1.4938, 'grad_norm': 8.73573112487793, 'learning_rate': 7.739130434782609e-06, 'epoch': 0.08}

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{'loss': 1.4857, 'grad_norm': 8.127388954162598, 'learning_rate': 7.82608695652174e-06, 'epoch': 0.08}

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{'loss': 1.4163, 'grad_norm': 8.067717552185059, 'learning_rate': 7.91304347826087e-06, 'epoch': 0.08}

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{'loss': 1.5575, 'grad_norm': 7.603127956390381, 'learning_rate': 8.000000000000001e-06, 'epoch': 0.08}

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{'loss': 1.4107, 'grad_norm': 7.017223358154297, 'learning_rate': 8.086956521739131e-06, 'epoch': 0.08}

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{'loss': 1.4045, 'grad_norm': 9.13593578338623, 'learning_rate': 8.173913043478263e-06, 'epoch': 0.08}

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{'loss': 1.5849, 'grad_norm': 7.945863246917725, 'learning_rate': 8.260869565217392e-06, 'epoch': 0.08}

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{'loss': 1.4617, 'grad_norm': 7.594067096710205, 'learning_rate': 8.347826086956522e-06, 'epoch': 0.08}

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{'loss': 1.5239, 'grad_norm': 6.76491641998291, 'learning_rate': 8.434782608695653e-06, 'epoch': 0.09}

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{'loss': 1.4965, 'grad_norm': 7.117091655731201, 'learning_rate': 8.521739130434783e-06, 'epoch': 0.09}

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{'loss': 1.4963, 'grad_norm': 6.76460599899292, 'learning_rate': 8.608695652173915e-06, 'epoch': 0.09}

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{'loss': 1.591, 'grad_norm': 7.103768825531006, 'learning_rate': 8.695652173913044e-06, 'epoch': 0.09}

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{'loss': 1.5225, 'grad_norm': 6.976682662963867, 'learning_rate': 8.782608695652174e-06, 'epoch': 0.09}

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{'loss': 1.4342, 'grad_norm': 7.857356548309326, 'learning_rate': 8.869565217391306e-06, 'epoch': 0.09}

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{'loss': 1.637, 'grad_norm': 8.63404655456543, 'learning_rate': 8.956521739130435e-06, 'epoch': 0.09}

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{'loss': 1.5661, 'grad_norm': 8.394899368286133, 'learning_rate': 9.043478260869565e-06, 'epoch': 0.09}

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{'loss': 1.5251, 'grad_norm': 7.850900173187256, 'learning_rate': 9.130434782608697e-06, 'epoch': 0.09}

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{'loss': 1.6145, 'grad_norm': 7.331704616546631, 'learning_rate': 9.217391304347826e-06, 'epoch': 0.09}

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{'loss': 1.4797, 'grad_norm': 7.412929058074951, 'learning_rate': 9.304347826086956e-06, 'epoch': 0.09}

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{'loss': 1.4754, 'grad_norm': 7.101129531860352, 'learning_rate': 9.391304347826087e-06, 'epoch': 0.1}

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{'loss': 1.51, 'grad_norm': 8.072187423706055, 'learning_rate': 9.478260869565217e-06, 'epoch': 0.1}

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{'loss': 1.3325, 'grad_norm': 7.228797912597656, 'learning_rate': 9.565217391304349e-06, 'epoch': 0.1}

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{'loss': 1.4118, 'grad_norm': 8.14680290222168, 'learning_rate': 9.652173913043478e-06, 'epoch': 0.1}

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{'loss': 1.395, 'grad_norm': 7.451870441436768, 'learning_rate': 9.73913043478261e-06, 'epoch': 0.1}

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{'loss': 1.5646, 'grad_norm': 8.038395881652832, 'learning_rate': 9.82608695652174e-06, 'epoch': 0.1}

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{'loss': 1.404, 'grad_norm': 7.315112113952637, 'learning_rate': 9.913043478260871e-06, 'epoch': 0.1}

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{'loss': 1.2967, 'grad_norm': 7.279412746429443, 'learning_rate': 1e-05, 'epoch': 0.1}

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{'loss': 1.5054, 'grad_norm': 7.1510772705078125, 'learning_rate': 9.999976787490876e-06, 'epoch': 0.1}

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{'loss': 1.7506, 'grad_norm': 8.988655090332031, 'learning_rate': 9.999907150179033e-06, 'epoch': 0.1}

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{'loss': 1.5574, 'grad_norm': 9.282151222229004, 'learning_rate': 9.99979108871105e-06, 'epoch': 0.1}

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{'loss': 1.5641, 'grad_norm': 8.615939140319824, 'learning_rate': 9.999628604164562e-06, 'epoch': 0.1}

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{'loss': 1.628, 'grad_norm': 7.523653984069824, 'learning_rate': 9.999419698048236e-06, 'epoch': 0.11}

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{'loss': 1.4213, 'grad_norm': 8.108613967895508, 'learning_rate': 9.999164372301769e-06, 'epoch': 0.11}

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{'loss': 1.5076, 'grad_norm': 7.515083312988281, 'learning_rate': 9.998862629295858e-06, 'epoch': 0.11}

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{'loss': 1.3078, 'grad_norm': 7.974615097045898, 'learning_rate': 9.998514471832193e-06, 'epoch': 0.11}

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{'loss': 1.4977, 'grad_norm': 8.17342758178711, 'learning_rate': 9.99811990314341e-06, 'epoch': 0.11}

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{'loss': 1.5379, 'grad_norm': 7.13555908203125, 'learning_rate': 9.997678926893086e-06, 'epoch': 0.11}

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{'loss': 1.5686, 'grad_norm': 7.281565189361572, 'learning_rate': 9.997191547175688e-06, 'epoch': 0.11}

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{'loss': 1.5349, 'grad_norm': 8.045228004455566, 'learning_rate': 9.996657768516533e-06, 'epoch': 0.11}

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{'loss': 1.4394, 'grad_norm': 8.390572547912598, 'learning_rate': 9.996077595871764e-06, 'epoch': 0.11}

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{'loss': 1.5854, 'grad_norm': 7.571259021759033, 'learning_rate': 9.995451034628281e-06, 'epoch': 0.11}

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{'loss': 1.3885, 'grad_norm': 6.902918815612793, 'learning_rate': 9.994778090603712e-06, 'epoch': 0.11}

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{'loss': 1.5235, 'grad_norm': 7.737064838409424, 'learning_rate': 9.99405877004634e-06, 'epoch': 0.12}

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{'loss': 1.6202, 'grad_norm': 7.1436052322387695, 'learning_rate': 9.993293079635062e-06, 'epoch': 0.12}

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{'loss': 1.427, 'grad_norm': 7.01748514175415, 'learning_rate': 9.992481026479316e-06, 'epoch': 0.12}

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{'loss': 1.3473, 'grad_norm': 6.502024173736572, 'learning_rate': 9.991622618119018e-06, 'epoch': 0.12}

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{'loss': 1.6436, 'grad_norm': 7.014427185058594, 'learning_rate': 9.990717862524493e-06, 'epoch': 0.12}

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{'loss': 1.4814, 'grad_norm': 7.217776298522949, 'learning_rate': 9.9897667680964e-06, 'epoch': 0.12}

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{'loss': 1.4487, 'grad_norm': 6.510077476501465, 'learning_rate': 9.988769343665655e-06, 'epoch': 0.12}

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{'loss': 1.4256, 'grad_norm': 6.6083903312683105, 'learning_rate': 9.987725598493344e-06, 'epoch': 0.12}

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{'loss': 1.6843, 'grad_norm': 7.342029571533203, 'learning_rate': 9.986635542270648e-06, 'epoch': 0.12}

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{'loss': 1.5202, 'grad_norm': 7.984467506408691, 'learning_rate': 9.985499185118744e-06, 'epoch': 0.12}

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{'loss': 1.3633, 'grad_norm': 7.413086414337158, 'learning_rate': 9.98431653758871e-06, 'epoch': 0.12}

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{'loss': 1.4706, 'grad_norm': 6.910080432891846, 'learning_rate': 9.983087610661433e-06, 'epoch': 0.12}

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{'loss': 1.5699, 'grad_norm': 6.978632926940918, 'learning_rate': 9.981812415747505e-06, 'epoch': 0.13}

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{'loss': 1.6106, 'grad_norm': 7.076592445373535, 'learning_rate': 9.980490964687113e-06, 'epoch': 0.13}

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{'loss': 1.6189, 'grad_norm': 7.769218921661377, 'learning_rate': 9.979123269749938e-06, 'epoch': 0.13}

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{'loss': 1.4753, 'grad_norm': 7.524374961853027, 'learning_rate': 9.977709343635032e-06, 'epoch': 0.13}

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{'loss': 1.3667, 'grad_norm': 6.942412853240967, 'learning_rate': 9.976249199470703e-06, 'epoch': 0.13}

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{'loss': 1.1885, 'grad_norm': 7.769628047943115, 'learning_rate': 9.974742850814393e-06, 'epoch': 0.13}

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{'loss': 1.5321, 'grad_norm': 7.888459205627441, 'learning_rate': 9.973190311652558e-06, 'epoch': 0.13}

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{'loss': 1.5821, 'grad_norm': 7.321242332458496, 'learning_rate': 9.97159159640053e-06, 'epoch': 0.13}

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{'loss': 1.5288, 'grad_norm': 6.658504009246826, 'learning_rate': 9.969946719902384e-06, 'epoch': 0.13}

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{'loss': 1.4702, 'grad_norm': 6.7957844734191895, 'learning_rate': 9.968255697430804e-06, 'epoch': 0.13}

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{'loss': 1.3685, 'grad_norm': 7.221371173858643, 'learning_rate': 9.96651854468694e-06, 'epoch': 0.13}

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{'loss': 1.4824, 'grad_norm': 7.697729587554932, 'learning_rate': 9.964735277800264e-06, 'epoch': 0.14}

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{'loss': 1.3986, 'grad_norm': 7.712857246398926, 'learning_rate': 9.962905913328413e-06, 'epoch': 0.14}

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{'loss': 1.4301, 'grad_norm': 7.2948832511901855, 'learning_rate': 9.961030468257044e-06, 'epoch': 0.14}

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{'loss': 1.5928, 'grad_norm': 6.851278305053711, 'learning_rate': 9.959108959999673e-06, 'epoch': 0.14}

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{'loss': 1.3942, 'grad_norm': 6.815929412841797, 'learning_rate': 9.957141406397508e-06, 'epoch': 0.14}

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{'loss': 1.5101, 'grad_norm': 6.961345195770264, 'learning_rate': 9.95512782571929e-06, 'epoch': 0.14}

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{'loss': 1.5148, 'grad_norm': 8.002721786499023, 'learning_rate': 9.95306823666113e-06, 'epoch': 0.14}

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{'loss': 1.5693, 'grad_norm': 6.914393424987793, 'learning_rate': 9.950962658346312e-06, 'epoch': 0.14}

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{'loss': 1.5053, 'grad_norm': 7.146297931671143, 'learning_rate': 9.948811110325142e-06, 'epoch': 0.14}

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{'loss': 1.4912, 'grad_norm': 6.762185096740723, 'learning_rate': 9.946613612574752e-06, 'epoch': 0.14}

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{'loss': 1.3409, 'grad_norm': 6.475704669952393, 'learning_rate': 9.944370185498917e-06, 'epoch': 0.14}

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{'loss': 1.337, 'grad_norm': 6.876773834228516, 'learning_rate': 9.942080849927861e-06, 'epoch': 0.14}

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{'loss': 1.514, 'grad_norm': 6.558300971984863, 'learning_rate': 9.939745627118078e-06, 'epoch': 0.15}

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{'loss': 1.5351, 'grad_norm': 6.268004417419434, 'learning_rate': 9.93736453875212e-06, 'epoch': 0.15}

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{'loss': 1.3723, 'grad_norm': 6.931794166564941, 'learning_rate': 9.934937606938399e-06, 'epoch': 0.15}

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{'loss': 1.2641, 'grad_norm': 6.9745707511901855, 'learning_rate': 9.932464854210986e-06, 'epoch': 0.15}

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{'loss': 1.5312, 'grad_norm': 6.960727214813232, 'learning_rate': 9.9299463035294e-06, 'epoch': 0.15}

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{'loss': 1.4562, 'grad_norm': 7.690456867218018, 'learning_rate': 9.927381978278392e-06, 'epoch': 0.15}

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{'loss': 1.3515, 'grad_norm': 6.2744460105896, 'learning_rate': 9.924771902267733e-06, 'epoch': 0.15}

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{'loss': 1.4297, 'grad_norm': 7.233633518218994, 'learning_rate': 9.922116099731988e-06, 'epoch': 0.15}

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{'loss': 1.3519, 'grad_norm': 6.305213451385498, 'learning_rate': 9.919414595330292e-06, 'epoch': 0.15}

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{'loss': 1.3709, 'grad_norm': 7.579061031341553, 'learning_rate': 9.916667414146125e-06, 'epoch': 0.15}

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{'loss': 1.4857, 'grad_norm': 7.2118306159973145, 'learning_rate': 9.913874581687073e-06, 'epoch': 0.15}

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{'loss': 1.5281, 'grad_norm': 7.223677158355713, 'learning_rate': 9.911036123884597e-06, 'epoch': 0.16}

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100%|██████████| 1146/1146 [8:19:10<00:00, 27.47s/it][INFO|trainer.py:4309] 2025-10-30 23:35:11,159 >> Saving model checkpoint to saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146
[INFO|configuration_utils.py:491] 2025-10-30 23:35:11,210 >> Configuration saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/config.json
[INFO|configuration_utils.py:757] 2025-10-30 23:35:11,213 >> Configuration saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/generation_config.json
[INFO|modeling_utils.py:4189] 2025-10-30 23:35:31,602 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/model.safetensors.index.json.
[INFO|tokenization_utils_base.py:2421] 2025-10-30 23:35:31,606 >> chat template saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/chat_template.jinja
[INFO|tokenization_utils_base.py:2590] 2025-10-30 23:35:31,608 >> tokenizer config file saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/tokenizer_config.json
[INFO|tokenization_utils_base.py:2599] 2025-10-30 23:35:31,611 >> Special tokens file saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/special_tokens_map.json
[2025-10-30 23:35:32,440] [INFO] [logging.py:107:log_dist] [Rank 0] [Torch] Checkpoint global_step1146 is about to be saved!
[2025-10-30 23:35:33,729] [INFO] [logging.py:107:log_dist] [Rank 0] Saving model checkpoint: saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/global_step1146/mp_rank_00_model_states.pt
[2025-10-30 23:35:33,729] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/global_step1146/mp_rank_00_model_states.pt...
[2025-10-30 23:35:57,259] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/global_step1146/mp_rank_00_model_states.pt.
[2025-10-30 23:35:57,272] [INFO] [torch_checkpoint_engine.py:21:save] [Torch] Saving saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/global_step1146/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt...
[2025-10-30 23:36:09,736] [INFO] [torch_checkpoint_engine.py:23:save] [Torch] Saved saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/global_step1146/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt.
[2025-10-30 23:36:09,744] [INFO] [engine.py:3701:_save_zero_checkpoint] zero checkpoint saved saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/global_step1146/bf16_zero_pp_rank_0_mp_rank_00_optim_states.pt
[2025-10-30 23:36:09,745] [INFO] [torch_checkpoint_engine.py:33:commit] [Torch] Checkpoint global_step1146 is ready now!
[INFO|image_processing_base.py:253] 2025-10-30 23:36:10,560 >> Image processor saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/preprocessor_config.json
[INFO|video_processing_utils.py:600] 2025-10-30 23:36:10,563 >> Video processor saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/video_preprocessor_config.json
[INFO|feature_extraction_utils.py:434] 2025-10-30 23:36:10,566 >> Feature extractor saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/preprocessor_config.json
[INFO|tokenization_utils_base.py:2421] 2025-10-30 23:36:10,569 >> chat template saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/chat_template.jinja
[INFO|tokenization_utils_base.py:2590] 2025-10-30 23:36:10,571 >> tokenizer config file saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/tokenizer_config.json
[INFO|tokenization_utils_base.py:2599] 2025-10-30 23:36:10,573 >> Special tokens file saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/special_tokens_map.json
[INFO|processing_utils.py:814] 2025-10-30 23:36:10,723 >> chat template saved in saves/qwen2_omni-3b/full/sft_scan2cap/checkpoint-1146/chat_template.jinja
[INFO|trainer.py:2810] 2025-10-30 23:36:11,102 >> 

Training completed. Do not forget to share your model on huggingface.co/models =)



                                                     
{'train_runtime': 30016.139, 'train_samples_per_second': 1.222, 'train_steps_per_second': 0.038, 'train_loss': 1.3602013491211138, 'epoch': 1.0}

100%|██████████| 1146/1146 [8:20:16<00:00, 27.47s/it]
100%|██████████| 1146/1146 [8:20:16<00:00, 26.19s/it]
[INFO|image_processing_base.py:253] 2025-10-30 23:36:11,125 >> Image processor saved in saves/qwen2_omni-3b/full/sft_scan2cap/preprocessor_config.json
[INFO|video_processing_utils.py:600] 2025-10-30 23:36:11,127 >> Video processor saved in saves/qwen2_omni-3b/full/sft_scan2cap/video_preprocessor_config.json
[INFO|feature_extraction_utils.py:434] 2025-10-30 23:36:11,130 >> Feature extractor saved in saves/qwen2_omni-3b/full/sft_scan2cap/preprocessor_config.json
[INFO|tokenization_utils_base.py:2421] 2025-10-30 23:36:11,132 >> chat template saved in saves/qwen2_omni-3b/full/sft_scan2cap/chat_template.jinja
[INFO|tokenization_utils_base.py:2590] 2025-10-30 23:36:11,134 >> tokenizer config file saved in saves/qwen2_omni-3b/full/sft_scan2cap/tokenizer_config.json
[INFO|tokenization_utils_base.py:2599] 2025-10-30 23:36:11,136 >> Special tokens file saved in saves/qwen2_omni-3b/full/sft_scan2cap/special_tokens_map.json
[INFO|processing_utils.py:814] 2025-10-30 23:36:11,304 >> chat template saved in saves/qwen2_omni-3b/full/sft_scan2cap/chat_template.jinja
[INFO|trainer.py:4309] 2025-10-30 23:36:16,682 >> Saving model checkpoint to saves/qwen2_omni-3b/full/sft_scan2cap
[INFO|configuration_utils.py:491] 2025-10-30 23:36:16,692 >> Configuration saved in saves/qwen2_omni-3b/full/sft_scan2cap/config.json
[INFO|configuration_utils.py:757] 2025-10-30 23:36:16,695 >> Configuration saved in saves/qwen2_omni-3b/full/sft_scan2cap/generation_config.json
[INFO|modeling_utils.py:4189] 2025-10-30 23:36:34,185 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 2 checkpoint shards. You can find where each parameters has been saved in the index located at saves/qwen2_omni-3b/full/sft_scan2cap/model.safetensors.index.json.
[INFO|tokenization_utils_base.py:2421] 2025-10-30 23:36:34,190 >> chat template saved in saves/qwen2_omni-3b/full/sft_scan2cap/chat_template.jinja
[INFO|tokenization_utils_base.py:2590] 2025-10-30 23:36:34,192 >> tokenizer config file saved in saves/qwen2_omni-3b/full/sft_scan2cap/tokenizer_config.json
[INFO|tokenization_utils_base.py:2599] 2025-10-30 23:36:34,195 >> Special tokens file saved in saves/qwen2_omni-3b/full/sft_scan2cap/special_tokens_map.json
***** train metrics *****
  epoch                    =           1.0
  total_flos               = 11370250131GF
  train_loss               =        1.3602
  train_runtime            =    8:20:16.13
  train_samples_per_second =         1.222
  train_steps_per_second   =         0.038
Figure saved at: saves/qwen2_omni-3b/full/sft_scan2cap/training_loss.png
[WARNING|2025-10-30 23:36:35] llamafactory.extras.ploting:148 >> No metric eval_loss to plot.
[WARNING|2025-10-30 23:36:35] llamafactory.extras.ploting:148 >> No metric eval_accuracy to plot.
[INFO|modelcard.py:456] 2025-10-30 23:36:35,253 >> Dropping the following result as it does not have all the necessary fields:
{'task': {'name': 'Causal Language Modeling', 'type': 'text-generation'}}