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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: distilgpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: distilgpt2-finetuned-wellness |
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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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# distilgpt2-finetuned-wellness |
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6526 |
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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: 3e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- lr_scheduler_warmup_steps: 100 |
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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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| 3.0101 | 1.0 | 158 | 2.1220 | |
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| 2.0886 | 2.0 | 316 | 1.9541 | |
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| 1.9941 | 3.0 | 474 | 1.8785 | |
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| 1.8701 | 4.0 | 632 | 1.8243 | |
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| 1.8238 | 5.0 | 790 | 1.7894 | |
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| 1.743 | 6.0 | 948 | 1.7593 | |
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| 1.699 | 7.0 | 1106 | 1.7376 | |
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| 1.6606 | 8.0 | 1264 | 1.7188 | |
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| 1.6345 | 9.0 | 1422 | 1.7027 | |
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| 1.6208 | 10.0 | 1580 | 1.6914 | |
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| 1.5896 | 11.0 | 1738 | 1.6830 | |
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| 1.5694 | 12.0 | 1896 | 1.6722 | |
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| 1.5468 | 13.0 | 2054 | 1.6671 | |
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| 1.5311 | 14.0 | 2212 | 1.6663 | |
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| 1.5172 | 15.0 | 2370 | 1.6602 | |
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| 1.51 | 16.0 | 2528 | 1.6544 | |
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| 1.4916 | 17.0 | 2686 | 1.6555 | |
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| 1.4782 | 18.0 | 2844 | 1.6529 | |
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| 1.4829 | 19.0 | 3002 | 1.6532 | |
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| 1.4639 | 20.0 | 3160 | 1.6526 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.1+cu124 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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