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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: 1.7698 |
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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: 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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| 3.4055 | 0.9927 | 102 | 2.8632 | |
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| 2.6839 | 1.9951 | 205 | 2.3235 | |
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| 2.3467 | 2.9976 | 308 | 2.1428 | |
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| 2.1832 | 4.0 | 411 | 2.0383 | |
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| 2.0576 | 4.9927 | 513 | 1.9659 | |
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| 1.9634 | 5.9951 | 616 | 1.9195 | |
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| 1.8834 | 6.9976 | 719 | 1.8783 | |
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| 1.8251 | 8.0 | 822 | 1.8546 | |
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| 1.7861 | 8.9927 | 924 | 1.8331 | |
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| 1.7299 | 9.9951 | 1027 | 1.8186 | |
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| 1.6952 | 10.9976 | 1130 | 1.8070 | |
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| 1.673 | 12.0 | 1233 | 1.7945 | |
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| 1.6387 | 12.9927 | 1335 | 1.7904 | |
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| 1.6138 | 13.9951 | 1438 | 1.7845 | |
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| 1.6028 | 14.9976 | 1541 | 1.7793 | |
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| 1.5778 | 16.0 | 1644 | 1.7761 | |
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| 1.5668 | 16.9927 | 1746 | 1.7727 | |
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| 1.5534 | 17.9951 | 1849 | 1.7719 | |
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| 1.5557 | 18.9976 | 1952 | 1.7711 | |
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| 1.5438 | 19.8540 | 2040 | 1.7698 | |
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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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