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: 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-20240221_130443-c2ciedyt
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run luminous-rocket-93
wandb: ⭐️ View project at https://wandb.ai/shion46/huggingface
wandb: 🚀 View run at https://wandb.ai/shion46/huggingface/runs/c2ciedyt
✅ 1 epochは 150 step です。

  0%|          | 0/1490 [00:00<?, ?it/s]You're using a T5TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.

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{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 1.0}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 2.0}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 2.99}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 4.0}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 5.0}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 6.0}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 6.99}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 8.0}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 9.0}
{'loss': 0.0, 'learning_rate': 2e-05, 'epoch': 9.98}
{'train_runtime': 68193.6489, 'train_samples_per_second': 219.962, 'train_steps_per_second': 0.022, 'train_loss': 0.0, 'epoch': 9.98}
👏モデルが FlanT5base_instraction1500000_10epoch_50batch_128len に保存されました。
wandb: - 0.016 MB of 0.016 MB uploaded
wandb: \ 0.031 MB of 0.031 MB uploaded
wandb: | 0.031 MB of 0.031 MB uploaded
wandb: 
wandb: Run history:
wandb:                    train/epoch ▁▂▃▃▄▅▆▆▇██
wandb:              train/global_step ▁▂▃▃▄▅▆▆▇██
wandb:            train/learning_rate ▁▁▁▁▁▁▁▁▁▁
wandb:                     train/loss ▁▁▁▁▁▁▁▁▁▁
wandb:               train/total_flos ▁
wandb:               train/train_loss ▁
wandb:            train/train_runtime ▁
wandb: train/train_samples_per_second ▁
wandb:   train/train_steps_per_second ▁
wandb: 
wandb: Run summary:
wandb:                    train/epoch 9.98
wandb:              train/global_step 1490
wandb:            train/learning_rate 2e-05
wandb:                     train/loss 0.0
wandb:               train/total_flos 2.492082958381056e+18
wandb:               train/train_loss 0.0
wandb:            train/train_runtime 68193.6489
wandb: train/train_samples_per_second 219.962
wandb:   train/train_steps_per_second 0.022
wandb: 
wandb: 🚀 View run luminous-rocket-93 at: https://wandb.ai/shion46/huggingface/runs/c2ciedyt
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-20240221_130443-c2ciedyt/logs