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--- |
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library_name: transformers |
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license: mit |
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base_model: danghuy1999/gpt2-viwiki |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: vietnamese-poem-gpt2-sauchu |
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results: [] |
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--- |
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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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# vietnamese-poem-gpt2-sauchu |
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This model is a fine-tuned version of [danghuy1999/gpt2-viwiki](https://huggingface.co/danghuy1999/gpt2-viwiki) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.2482 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 1.0 | 136 | 6.4141 | |
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| No log | 2.0 | 272 | 6.0165 | |
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| No log | 3.0 | 408 | 5.7615 | |
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| 6.3641 | 4.0 | 544 | 5.5938 | |
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| 6.3641 | 5.0 | 680 | 5.4852 | |
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| 6.3641 | 6.0 | 816 | 5.4277 | |
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| 6.3641 | 7.0 | 952 | 5.3807 | |
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| 5.418 | 8.0 | 1088 | 5.3497 | |
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| 5.418 | 9.0 | 1224 | 5.3235 | |
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| 5.418 | 10.0 | 1360 | 5.3024 | |
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| 5.418 | 11.0 | 1496 | 5.2961 | |
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| 5.1065 | 12.0 | 1632 | 5.2781 | |
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| 5.1065 | 13.0 | 1768 | 5.2753 | |
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| 5.1065 | 14.0 | 1904 | 5.2596 | |
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| 4.9363 | 15.0 | 2040 | 5.2568 | |
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| 4.9363 | 16.0 | 2176 | 5.2558 | |
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| 4.9363 | 17.0 | 2312 | 5.2497 | |
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| 4.9363 | 18.0 | 2448 | 5.2536 | |
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| 4.8312 | 19.0 | 2584 | 5.2485 | |
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| 4.8312 | 20.0 | 2720 | 5.2482 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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