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--- |
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library_name: transformers |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: js-fake-bach-epochs20 |
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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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# js-fake-bach-epochs20 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5973 |
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- Accuracy: 0.0033 |
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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: 0.0006058454513356471 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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- seed: 1 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:| |
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| 1.2427 | 1.2550 | 315 | 0.8253 | 0.0007 | |
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| 0.8106 | 2.5100 | 630 | 0.7777 | 0.0021 | |
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| 0.7663 | 3.7649 | 945 | 0.7449 | 0.0017 | |
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| 0.7263 | 5.0199 | 1260 | 0.6997 | 0.0027 | |
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| 0.689 | 6.2749 | 1575 | 0.6683 | 0.0018 | |
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| 0.6524 | 7.5299 | 1890 | 0.6396 | 0.0008 | |
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| 0.6158 | 8.7849 | 2205 | 0.6139 | 0.0021 | |
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| 0.5807 | 10.0398 | 2520 | 0.5981 | 0.0010 | |
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| 0.5437 | 11.2948 | 2835 | 0.5848 | 0.0030 | |
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| 0.5109 | 12.5498 | 3150 | 0.5841 | 0.0026 | |
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| 0.4781 | 13.8048 | 3465 | 0.5799 | 0.0028 | |
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| 0.4453 | 15.0598 | 3780 | 0.5867 | 0.0034 | |
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| 0.4169 | 16.3147 | 4095 | 0.5915 | 0.0034 | |
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| 0.3972 | 17.5697 | 4410 | 0.5968 | 0.0034 | |
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| 0.3847 | 18.8247 | 4725 | 0.5973 | 0.0033 | |
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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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