module:cuda/12.1/12.1.1 is provided for EXPERIMENTAL use
You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thouroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565
/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/convert_slow_tokenizer.py:473: UserWarning: The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option which is not implemented in the fast tokenizers. In practice this means that the fast version of the tokenizer can produce unknown tokens whereas the sentencepiece version would have converted these unknown tokens into a sequence of byte tokens matching the original piece of text.
  warnings.warn(

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Detected kernel version 4.18.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
wandb: Currently logged in as: shion46. Use `wandb login --relogin` to force relogin
wandb: - Waiting for wandb.init()...
wandb: \ Waiting for wandb.init()...
wandb: wandb version 0.16.3 is available!  To upgrade, please run:
wandb:  $ pip install wandb --upgrade
wandb: Tracking run with wandb version 0.16.2
wandb: Run data is saved locally in /home/ace14459tv/Shion_onon/Flan_T5/wandb/run-20240224_072910-np2744rt
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run chromatic-wonton-107
wandb: ⭐️ View project at https://wandb.ai/shion46/huggingface
wandb: 🚀 View run at https://wandb.ai/shion46/huggingface/runs/np2744rt
✅ 1 epochは 559 step です。

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  1%|          | 559/55900 [00:36<58:43, 15.71it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'loss': 23.2546, 'learning_rate': 5e-06, 'epoch': 1.0}


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  2%|▏         | 1118/55900 [01:16<57:48, 15.79it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.9237436652183533, 'eval_accuracy': 22.34, 'eval_runtime': 3.4822, 'eval_samples_per_second': 321.347, 'eval_steps_per_second': 20.102, 'epoch': 1.0}
{'loss': 0.8446, 'learning_rate': 1e-05, 'epoch': 2.0}


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  3%|▎         | 1677/55900 [01:55<56:53, 15.88it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.8114852905273438, 'eval_accuracy': 20.02, 'eval_runtime': 3.4474, 'eval_samples_per_second': 324.59, 'eval_steps_per_second': 20.305, 'epoch': 2.0}
{'loss': 0.8219, 'learning_rate': 1.5e-05, 'epoch': 3.0}


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  4%|▍         | 2236/55900 [02:34<54:36, 16.38it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.8069278597831726, 'eval_accuracy': 20.11, 'eval_runtime': 3.421, 'eval_samples_per_second': 327.094, 'eval_steps_per_second': 20.462, 'epoch': 3.0}
{'loss': 0.8191, 'learning_rate': 2e-05, 'epoch': 4.0}


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  5%|▌         | 2795/55900 [03:13<53:32, 16.53it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.8081911206245422, 'eval_accuracy': 21.45, 'eval_runtime': 3.4275, 'eval_samples_per_second': 326.473, 'eval_steps_per_second': 20.423, 'epoch': 4.0}
{'loss': 0.8151, 'learning_rate': 2.5e-05, 'epoch': 5.0}


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  6%|▌         | 3354/55900 [03:52<56:38, 15.46it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.8085305094718933, 'eval_accuracy': 19.57, 'eval_runtime': 3.3955, 'eval_samples_per_second': 329.557, 'eval_steps_per_second': 20.616, 'epoch': 5.0}
{'loss': 0.8052, 'learning_rate': 3e-05, 'epoch': 6.0}


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  7%|▋         | 3913/55900 [04:32<52:57, 16.36it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.7593018412590027, 'eval_accuracy': 33.33, 'eval_runtime': 3.395, 'eval_samples_per_second': 329.599, 'eval_steps_per_second': 20.618, 'epoch': 6.0}
{'loss': 0.7417, 'learning_rate': 3.5e-05, 'epoch': 7.0}


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  8%|▊         | 4472/55900 [05:11<52:18, 16.38it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.6957784295082092, 'eval_accuracy': 44.15, 'eval_runtime': 3.4589, 'eval_samples_per_second': 323.513, 'eval_steps_per_second': 20.238, 'epoch': 7.0}
{'loss': 0.6736, 'learning_rate': 4e-05, 'epoch': 8.0}


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  9%|▉         | 5031/55900 [05:51<51:34, 16.44it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.6910514831542969, 'eval_accuracy': 45.76, 'eval_runtime': 3.4524, 'eval_samples_per_second': 324.118, 'eval_steps_per_second': 20.275, 'epoch': 8.0}
{'loss': 0.6209, 'learning_rate': 4.5e-05, 'epoch': 9.0}


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 10%|█         | 5590/55900 [06:30<51:46, 16.19it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.6926281452178955, 'eval_accuracy': 47.18, 'eval_runtime': 3.5044, 'eval_samples_per_second': 319.311, 'eval_steps_per_second': 19.975, 'epoch': 9.0}
{'loss': 0.5662, 'learning_rate': 5e-05, 'epoch': 10.0}


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 11%|█         | 6149/55900 [07:09<50:26, 16.44it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.679427981376648, 'eval_accuracy': 47.54, 'eval_runtime': 3.4109, 'eval_samples_per_second': 328.066, 'eval_steps_per_second': 20.522, 'epoch': 10.0}
{'loss': 0.507, 'learning_rate': 4.9444444444444446e-05, 'epoch': 11.0}


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  warnings.warn(
{'eval_loss': 0.7567007541656494, 'eval_accuracy': 47.9, 'eval_runtime': 3.3995, 'eval_samples_per_second': 329.163, 'eval_steps_per_second': 20.591, 'epoch': 11.0}
{'loss': 0.4515, 'learning_rate': 4.888888888888889e-05, 'epoch': 12.0}


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 13%|█▎        | 7267/55900 [08:28<49:41, 16.31it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.7335996627807617, 'eval_accuracy': 48.35, 'eval_runtime': 3.4256, 'eval_samples_per_second': 326.662, 'eval_steps_per_second': 20.435, 'epoch': 12.0}
{'loss': 0.4, 'learning_rate': 4.8333333333333334e-05, 'epoch': 13.0}


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  warnings.warn(
{'eval_loss': 0.8925325870513916, 'eval_accuracy': 47.36, 'eval_runtime': 3.3794, 'eval_samples_per_second': 331.126, 'eval_steps_per_second': 20.714, 'epoch': 13.0}
{'loss': 0.3489, 'learning_rate': 4.7777777777777784e-05, 'epoch': 14.0}


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 15%|█▌        | 8385/55900 [09:46<48:11, 16.43it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.9061934351921082, 'eval_accuracy': 47.36, 'eval_runtime': 3.3945, 'eval_samples_per_second': 329.649, 'eval_steps_per_second': 20.621, 'epoch': 14.0}
{'loss': 0.3045, 'learning_rate': 4.722222222222222e-05, 'epoch': 15.0}


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 16%|█▌        | 8944/55900 [10:26<47:47, 16.37it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 0.9434159398078918, 'eval_accuracy': 46.47, 'eval_runtime': 3.7623, 'eval_samples_per_second': 297.424, 'eval_steps_per_second': 18.606, 'epoch': 15.0}
{'loss': 0.264, 'learning_rate': 4.666666666666667e-05, 'epoch': 16.0}


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100%|██████████| 70/70 [00:03<00:00, 20.68it/s]

                                               
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 17%|█▋        | 9503/55900 [11:05<48:50, 15.83it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.1538761854171753, 'eval_accuracy': 47.27, 'eval_runtime': 3.4967, 'eval_samples_per_second': 320.019, 'eval_steps_per_second': 20.019, 'epoch': 16.0}
{'loss': 0.2286, 'learning_rate': 4.6111111111111115e-05, 'epoch': 17.0}


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 18%|█▊        | 10062/55900 [11:44<46:58, 16.26it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.1152620315551758, 'eval_accuracy': 47.54, 'eval_runtime': 3.4312, 'eval_samples_per_second': 326.129, 'eval_steps_per_second': 20.401, 'epoch': 17.0}
{'loss': 0.1984, 'learning_rate': 4.555555555555556e-05, 'epoch': 18.0}


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 19%|█▉        | 10621/55900 [12:23<46:39, 16.17it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.1677929162979126, 'eval_accuracy': 48.35, 'eval_runtime': 3.4509, 'eval_samples_per_second': 324.266, 'eval_steps_per_second': 20.285, 'epoch': 18.0}
{'loss': 0.1765, 'learning_rate': 4.5e-05, 'epoch': 19.0}


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 20%|██        | 11180/55900 [13:02<46:32, 16.02it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.2945542335510254, 'eval_accuracy': 49.06, 'eval_runtime': 3.4452, 'eval_samples_per_second': 324.798, 'eval_steps_per_second': 20.318, 'epoch': 19.0}
{'loss': 0.1455, 'learning_rate': 4.4444444444444447e-05, 'epoch': 20.0}


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 21%|██        | 11739/55900 [13:41<44:43, 16.45it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.5462062358856201, 'eval_accuracy': 48.35, 'eval_runtime': 3.4189, 'eval_samples_per_second': 327.301, 'eval_steps_per_second': 20.475, 'epoch': 20.0}
{'loss': 0.1294, 'learning_rate': 4.388888888888889e-05, 'epoch': 21.0}


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 22%|██▏       | 12298/55900 [14:20<44:07, 16.47it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.442876935005188, 'eval_accuracy': 48.53, 'eval_runtime': 3.405, 'eval_samples_per_second': 328.633, 'eval_steps_per_second': 20.558, 'epoch': 21.0}
{'loss': 0.1142, 'learning_rate': 4.3333333333333334e-05, 'epoch': 22.0}


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  warnings.warn(
{'eval_loss': 1.8048895597457886, 'eval_accuracy': 48.53, 'eval_runtime': 3.5562, 'eval_samples_per_second': 314.659, 'eval_steps_per_second': 19.684, 'epoch': 22.0}
{'loss': 0.1029, 'learning_rate': 4.277777777777778e-05, 'epoch': 23.0}


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  warnings.warn(
{'eval_loss': 1.6746342182159424, 'eval_accuracy': 48.7, 'eval_runtime': 3.5149, 'eval_samples_per_second': 318.354, 'eval_steps_per_second': 19.915, 'epoch': 23.0}
{'loss': 0.0939, 'learning_rate': 4.222222222222222e-05, 'epoch': 24.0}


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 25%|██▌       | 13975/55900 [16:18<42:36, 16.40it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.0644052028656006, 'eval_accuracy': 48.79, 'eval_runtime': 3.4971, 'eval_samples_per_second': 319.975, 'eval_steps_per_second': 20.016, 'epoch': 24.0}
{'loss': 0.082, 'learning_rate': 4.166666666666667e-05, 'epoch': 25.0}


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 26%|██▌       | 14534/55900 [16:58<42:25, 16.25it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.8599143028259277, 'eval_accuracy': 47.54, 'eval_runtime': 3.4354, 'eval_samples_per_second': 325.722, 'eval_steps_per_second': 20.376, 'epoch': 25.0}
{'loss': 0.071, 'learning_rate': 4.111111111111111e-05, 'epoch': 26.0}


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 27%|██▋       | 15093/55900 [17:38<41:38, 16.33it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.8586091995239258, 'eval_accuracy': 48.61, 'eval_runtime': 3.4659, 'eval_samples_per_second': 322.856, 'eval_steps_per_second': 20.197, 'epoch': 26.0}
{'loss': 0.065, 'learning_rate': 4.055555555555556e-05, 'epoch': 27.0}


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 28%|██▊       | 15652/55900 [18:17<40:41, 16.49it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.1572799682617188, 'eval_accuracy': 48.61, 'eval_runtime': 3.42, 'eval_samples_per_second': 327.197, 'eval_steps_per_second': 20.468, 'epoch': 27.0}
{'loss': 0.0643, 'learning_rate': 4e-05, 'epoch': 28.0}


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 29%|██▉       | 16211/55900 [18:56<40:11, 16.46it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.0109527111053467, 'eval_accuracy': 49.06, 'eval_runtime': 3.4138, 'eval_samples_per_second': 327.786, 'eval_steps_per_second': 20.505, 'epoch': 28.0}
{'loss': 0.0593, 'learning_rate': 3.944444444444445e-05, 'epoch': 29.0}


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 30%|███       | 16770/55900 [19:35<40:03, 16.28it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.088613510131836, 'eval_accuracy': 48.35, 'eval_runtime': 3.4301, 'eval_samples_per_second': 326.23, 'eval_steps_per_second': 20.408, 'epoch': 29.0}
{'loss': 0.058, 'learning_rate': 3.888888888888889e-05, 'epoch': 30.0}


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 31%|███       | 17329/55900 [20:15<39:36, 16.23it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.043304443359375, 'eval_accuracy': 49.24, 'eval_runtime': 3.4371, 'eval_samples_per_second': 325.567, 'eval_steps_per_second': 20.366, 'epoch': 30.0}
{'loss': 0.0518, 'learning_rate': 3.8333333333333334e-05, 'epoch': 31.0}


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 32%|███▏      | 17888/55900 [20:55<38:54, 16.28it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 1.9199258089065552, 'eval_accuracy': 48.79, 'eval_runtime': 3.4836, 'eval_samples_per_second': 321.215, 'eval_steps_per_second': 20.094, 'epoch': 31.0}
{'loss': 0.0489, 'learning_rate': 3.777777777777778e-05, 'epoch': 32.0}


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  warnings.warn(
{'eval_loss': 2.154787063598633, 'eval_accuracy': 49.15, 'eval_runtime': 3.6682, 'eval_samples_per_second': 305.058, 'eval_steps_per_second': 19.083, 'epoch': 32.0}
{'loss': 0.0408, 'learning_rate': 3.722222222222222e-05, 'epoch': 33.0}


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  warnings.warn(
{'eval_loss': 2.1978137493133545, 'eval_accuracy': 49.96, 'eval_runtime': 3.4137, 'eval_samples_per_second': 327.794, 'eval_steps_per_second': 20.505, 'epoch': 33.0}
{'loss': 0.0417, 'learning_rate': 3.6666666666666666e-05, 'epoch': 34.0}


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  warnings.warn(
{'eval_loss': 2.1676082611083984, 'eval_accuracy': 49.15, 'eval_runtime': 3.4458, 'eval_samples_per_second': 324.746, 'eval_steps_per_second': 20.315, 'epoch': 34.0}
{'loss': 0.0335, 'learning_rate': 3.611111111111111e-05, 'epoch': 35.0}


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 36%|███▌      | 20124/55900 [23:33<36:36, 16.29it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.4490537643432617, 'eval_accuracy': 49.51, 'eval_runtime': 3.5276, 'eval_samples_per_second': 317.21, 'eval_steps_per_second': 19.843, 'epoch': 35.0}
{'loss': 0.0357, 'learning_rate': 3.555555555555556e-05, 'epoch': 36.0}


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  warnings.warn(
{'eval_loss': 2.0498857498168945, 'eval_accuracy': 48.61, 'eval_runtime': 3.4191, 'eval_samples_per_second': 327.276, 'eval_steps_per_second': 20.473, 'epoch': 36.0}
{'loss': 0.0346, 'learning_rate': 3.5e-05, 'epoch': 37.0}


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  warnings.warn(
{'eval_loss': 2.2967424392700195, 'eval_accuracy': 48.61, 'eval_runtime': 3.4627, 'eval_samples_per_second': 323.156, 'eval_steps_per_second': 20.215, 'epoch': 37.0}
{'loss': 0.0341, 'learning_rate': 3.444444444444445e-05, 'epoch': 38.0}


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 39%|███▉      | 21801/55900 [25:31<34:38, 16.41it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.215726852416992, 'eval_accuracy': 49.69, 'eval_runtime': 3.4476, 'eval_samples_per_second': 324.574, 'eval_steps_per_second': 20.304, 'epoch': 38.0}
{'loss': 0.0305, 'learning_rate': 3.388888888888889e-05, 'epoch': 39.0}


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  warnings.warn(
{'eval_loss': 2.505403757095337, 'eval_accuracy': 50.31, 'eval_runtime': 3.4517, 'eval_samples_per_second': 324.188, 'eval_steps_per_second': 20.28, 'epoch': 39.0}
{'loss': 0.0301, 'learning_rate': 3.3333333333333335e-05, 'epoch': 40.0}


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 41%|████      | 22919/55900 [26:50<34:26, 15.96it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.2375857830047607, 'eval_accuracy': 50.76, 'eval_runtime': 3.4996, 'eval_samples_per_second': 319.747, 'eval_steps_per_second': 20.002, 'epoch': 40.0}
{'loss': 0.0323, 'learning_rate': 3.277777777777778e-05, 'epoch': 41.0}


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 42%|████▏     | 23478/55900 [27:29<33:15, 16.24it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.16780424118042, 'eval_accuracy': 48.88, 'eval_runtime': 3.4408, 'eval_samples_per_second': 325.214, 'eval_steps_per_second': 20.344, 'epoch': 41.0}
{'loss': 0.0238, 'learning_rate': 3.222222222222223e-05, 'epoch': 42.0}


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 43%|████▎     | 24037/55900 [28:09<32:23, 16.40it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.5068981647491455, 'eval_accuracy': 49.15, 'eval_runtime': 3.3831, 'eval_samples_per_second': 330.761, 'eval_steps_per_second': 20.691, 'epoch': 42.0}
{'loss': 0.0238, 'learning_rate': 3.1666666666666666e-05, 'epoch': 43.0}


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  warnings.warn(
{'eval_loss': 2.32020902633667, 'eval_accuracy': 48.61, 'eval_runtime': 3.3887, 'eval_samples_per_second': 330.211, 'eval_steps_per_second': 20.657, 'epoch': 43.0}
{'loss': 0.0238, 'learning_rate': 3.111111111111111e-05, 'epoch': 44.0}


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 45%|████▌     | 25155/55900 [29:27<32:05, 15.97it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.38089656829834, 'eval_accuracy': 48.97, 'eval_runtime': 3.416, 'eval_samples_per_second': 327.572, 'eval_steps_per_second': 20.492, 'epoch': 44.0}
{'loss': 0.02, 'learning_rate': 3.055555555555556e-05, 'epoch': 45.0}


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  warnings.warn(
{'eval_loss': 2.4949185848236084, 'eval_accuracy': 49.06, 'eval_runtime': 3.4425, 'eval_samples_per_second': 325.058, 'eval_steps_per_second': 20.334, 'epoch': 45.0}
{'loss': 0.0214, 'learning_rate': 3e-05, 'epoch': 46.0}


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 47%|████▋     | 26273/55900 [30:45<29:47, 16.58it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.557819128036499, 'eval_accuracy': 49.42, 'eval_runtime': 3.3946, 'eval_samples_per_second': 329.645, 'eval_steps_per_second': 20.621, 'epoch': 46.0}
{'loss': 0.0206, 'learning_rate': 2.9444444444444448e-05, 'epoch': 47.0}


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  warnings.warn(
{'eval_loss': 2.5700979232788086, 'eval_accuracy': 49.78, 'eval_runtime': 3.8979, 'eval_samples_per_second': 287.076, 'eval_steps_per_second': 17.958, 'epoch': 47.0}
{'loss': 0.022, 'learning_rate': 2.8888888888888888e-05, 'epoch': 48.0}


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 49%|████▉     | 27391/55900 [32:04<29:05, 16.34it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.6096274852752686, 'eval_accuracy': 47.99, 'eval_runtime': 3.5349, 'eval_samples_per_second': 316.56, 'eval_steps_per_second': 19.803, 'epoch': 48.0}
{'loss': 0.021, 'learning_rate': 2.8333333333333335e-05, 'epoch': 49.0}


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  warnings.warn(
{'eval_loss': 2.528146266937256, 'eval_accuracy': 48.26, 'eval_runtime': 3.7282, 'eval_samples_per_second': 300.147, 'eval_steps_per_second': 18.776, 'epoch': 49.0}
{'loss': 0.0212, 'learning_rate': 2.777777777777778e-05, 'epoch': 50.0}


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 51%|█████     | 28509/55900 [33:24<28:45, 15.88it/s]/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/generation/utils.py:1355: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.
  warnings.warn(
{'eval_loss': 2.5419249534606934, 'eval_accuracy': 48.53, 'eval_runtime': 3.4399, 'eval_samples_per_second': 325.3, 'eval_steps_per_second': 20.349, 'epoch': 50.0}
{'loss': 0.019, 'learning_rate': 2.7222222222222223e-05, 'epoch': 51.0}


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  warnings.warn(
{'eval_loss': 2.546407699584961, 'eval_accuracy': 49.06, 'eval_runtime': 3.5191, 'eval_samples_per_second': 317.978, 'eval_steps_per_second': 19.891, 'epoch': 51.0}
{'loss': 0.0169, 'learning_rate': 2.6666666666666667e-05, 'epoch': 52.0}


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  warnings.warn(
{'eval_loss': 2.6929850578308105, 'eval_accuracy': 49.42, 'eval_runtime': 3.4096, 'eval_samples_per_second': 328.193, 'eval_steps_per_second': 20.53, 'epoch': 52.0}
{'loss': 0.0143, 'learning_rate': 2.6111111111111114e-05, 'epoch': 53.0}


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  warnings.warn(
{'eval_loss': 2.7189438343048096, 'eval_accuracy': 49.15, 'eval_runtime': 3.412, 'eval_samples_per_second': 327.955, 'eval_steps_per_second': 20.516, 'epoch': 53.0}
{'loss': 0.0138, 'learning_rate': 2.5555555555555554e-05, 'epoch': 54.0}


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  warnings.warn(
{'eval_loss': 2.8362603187561035, 'eval_accuracy': 49.6, 'eval_runtime': 3.4043, 'eval_samples_per_second': 328.699, 'eval_steps_per_second': 20.562, 'epoch': 54.0}
{'loss': 0.0181, 'learning_rate': 2.5e-05, 'epoch': 55.0}


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  warnings.warn(
{'eval_loss': 2.595752239227295, 'eval_accuracy': 49.42, 'eval_runtime': 3.4015, 'eval_samples_per_second': 328.976, 'eval_steps_per_second': 20.579, 'epoch': 55.0}
{'loss': 0.0194, 'learning_rate': 2.4444444444444445e-05, 'epoch': 56.0}


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  warnings.warn(
{'eval_loss': 2.473750591278076, 'eval_accuracy': 48.88, 'eval_runtime': 3.512, 'eval_samples_per_second': 318.617, 'eval_steps_per_second': 19.931, 'epoch': 56.0}
{'loss': 0.0131, 'learning_rate': 2.3888888888888892e-05, 'epoch': 57.0}


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  warnings.warn(
{'eval_loss': 2.7509641647338867, 'eval_accuracy': 49.51, 'eval_runtime': 3.4113, 'eval_samples_per_second': 328.025, 'eval_steps_per_second': 20.52, 'epoch': 57.0}
{'loss': 0.012, 'learning_rate': 2.3333333333333336e-05, 'epoch': 58.0}


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  warnings.warn(
{'eval_loss': 3.103240489959717, 'eval_accuracy': 49.69, 'eval_runtime': 3.3917, 'eval_samples_per_second': 329.923, 'eval_steps_per_second': 20.639, 'epoch': 58.0}
{'loss': 0.0156, 'learning_rate': 2.277777777777778e-05, 'epoch': 59.0}


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  warnings.warn(
{'eval_loss': 2.940194606781006, 'eval_accuracy': 48.26, 'eval_runtime': 3.3925, 'eval_samples_per_second': 329.849, 'eval_steps_per_second': 20.634, 'epoch': 59.0}
{'loss': 0.0138, 'learning_rate': 2.2222222222222223e-05, 'epoch': 60.0}


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                                               {'eval_loss': 3.038668632507324, 'eval_accuracy': 47.81, 'eval_runtime': 3.4147, 'eval_samples_per_second': 327.698, 'eval_steps_per_second': 20.499, 'epoch': 60.0}
Traceback (most recent call last):
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/torch/serialization.py", line 619, in save
    _save(obj, opened_zipfile, pickle_module, pickle_protocol, _disable_byteorder_record)
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/torch/serialization.py", line 853, in _save
    zip_file.write_record(name, storage.data_ptr(), num_bytes)
RuntimeError: [enforce fail at inline_container.cc:588] . PytorchStreamWriter failed writing file data/632: file write failed

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/ace14459tv/Shion_onon/Flan_T5/train_QA.py", line 260, in <module>
    trainer.train()
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/trainer.py", line 1537, in train
    return inner_training_loop(
           ^^^^^^^^^^^^^^^^^^^^
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/trainer.py", line 1929, in _inner_training_loop
    self._maybe_log_save_evaluate(tr_loss, model, trial, epoch, ignore_keys_for_eval)
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/trainer.py", line 2279, in _maybe_log_save_evaluate
    self._save_checkpoint(model, trial, metrics=metrics)
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/trainer.py", line 2359, in _save_checkpoint
    self._save_optimizer_and_scheduler(staging_output_dir)
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/transformers/trainer.py", line 2462, in _save_optimizer_and_scheduler
    torch.save(self.optimizer.state_dict(), os.path.join(output_dir, OPTIMIZER_NAME))
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/torch/serialization.py", line 618, in save
    with _open_zipfile_writer(f) as opened_zipfile:
  File "/home/ace14459tv/cuda121/lib/python3.11/site-packages/torch/serialization.py", line 466, in __exit__
    self.file_like.write_end_of_file()
RuntimeError: [enforce fail at inline_container.cc:424] . unexpected pos 567552064 vs 567551952
wandb: - 0.016 MB of 0.016 MB uploaded
wandb: \ 0.061 MB of 0.061 MB uploaded
wandb: | 0.061 MB of 0.061 MB uploaded
wandb: 
wandb: Run history:
wandb:           eval/accuracy ▂▁▁▁▇▇▇▇▇▇▇▇█▇▇█▇██▇████████████▇▇█████▇
wandb:               eval/loss ▂▁▁▁▁▁▁▁▂▂▂▂▃▄▄▄▄▄▅▅▅▅▅▆▆▅▅▅▆▆▆▆▆▆▇▇▇▆██
wandb:            eval/runtime ▂▂▂▁▂▂▁▁▁▁▃▂▂▂▃▃▂▂▁▂▂▅▂▃▂▂▃▂▁▁▁█▆▂▁▁▁▃▁▁
wandb: eval/samples_per_second ▆▇▇█▇▇████▆▇▇▇▅▆▇▇▇▇▆▄▇▆▇▇▆▇█▇█▁▃▇█▇█▆█▇
wandb:   eval/steps_per_second ▆▇▇█▇▇████▆▇▇▇▅▆▇▇▇▇▆▄▇▆▇▇▆▇█▇█▁▃▇█▇█▆█▇
wandb:             train/epoch ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇▇███
wandb:       train/global_step ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▆▆▆▆▆▆▇▇▇▇▇▇███
wandb:     train/learning_rate ▁▂▃▄▆▆████▇▇▇▇▇▇▇▇▆▆▆▆▆▆▆▆▅▅▅▅▅▅▅▅▄▄▄▄▄▄
wandb:              train/loss █▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁
wandb: 
wandb: Run summary:
wandb:           eval/accuracy 47.81
wandb:               eval/loss 3.03867
wandb:            eval/runtime 3.4147
wandb: eval/samples_per_second 327.698
wandb:   eval/steps_per_second 20.499
wandb:             train/epoch 60.0
wandb:       train/global_step 33540
wandb:     train/learning_rate 2e-05
wandb:              train/loss 0.0138
wandb: 
wandb: 🚀 View run chromatic-wonton-107 at: https://wandb.ai/shion46/huggingface/runs/np2744rt
wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)
wandb: Find logs at: ./wandb/run-20240224_072910-np2744rt/logs

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