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README.md
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_HW2_RT_GPT2/runs/
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# ADL_HW2_GPT2
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This model is a fine-tuned version of [ckiplab/gpt2-tiny-chinese](https://huggingface.co/ckiplab/gpt2-tiny-chinese) on an unknown dataset.
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The following hyperparameters were used during training:
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- learning_rate: 5.6e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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### Framework versions
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_HW2_RT_GPT2/runs/ov47z0tg)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_HW2_RT_GPT2/runs/ov47z0tg)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_HW2_RT_GPT2/runs/ov47z0tg)
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# ADL_HW2_GPT2
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This model is a fine-tuned version of [ckiplab/gpt2-tiny-chinese](https://huggingface.co/ckiplab/gpt2-tiny-chinese) on an unknown dataset.
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The following hyperparameters were used during training:
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- learning_rate: 5.6e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 8
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### Framework versions
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