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--- |
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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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model-index: |
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- name: MammoLLM2 |
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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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# MammoLLM2 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6666 |
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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: 0.0005 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 1.7888 | 1.24 | 500 | 1.0984 | |
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| 1.1179 | 2.49 | 1000 | 1.0209 | |
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| 1.0556 | 3.73 | 1500 | 0.9913 | |
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| 1.01 | 4.98 | 2000 | 0.9653 | |
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| 0.9723 | 6.22 | 2500 | 0.9608 | |
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| 0.9425 | 7.47 | 3000 | 0.9455 | |
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| 0.9149 | 8.71 | 3500 | 0.9391 | |
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| 0.8877 | 9.96 | 4000 | 0.9253 | |
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| 0.8478 | 11.2 | 4500 | 0.9317 | |
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| 0.8142 | 12.45 | 5000 | 0.9313 | |
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| 0.7814 | 13.69 | 5500 | 0.9299 | |
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| 0.7494 | 14.93 | 6000 | 0.9330 | |
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| 0.7071 | 16.18 | 6500 | 0.9588 | |
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| 0.6774 | 17.42 | 7000 | 0.9704 | |
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| 0.6511 | 18.67 | 7500 | 0.9828 | |
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| 0.6275 | 19.91 | 8000 | 1.0007 | |
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| 0.595 | 21.16 | 8500 | 1.0432 | |
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| 0.5698 | 22.4 | 9000 | 1.0641 | |
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| 0.546 | 23.65 | 9500 | 1.0879 | |
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| 0.523 | 24.89 | 10000 | 1.0982 | |
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| 0.4913 | 26.14 | 10500 | 1.1579 | |
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| 0.4622 | 27.38 | 11000 | 1.1923 | |
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| 0.4378 | 28.62 | 11500 | 1.2152 | |
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| 0.4131 | 29.87 | 12000 | 1.2440 | |
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| 0.3846 | 31.11 | 12500 | 1.3181 | |
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| 0.3592 | 32.36 | 13000 | 1.3497 | |
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| 0.3411 | 33.6 | 13500 | 1.3847 | |
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| 0.324 | 34.85 | 14000 | 1.4070 | |
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| 0.3061 | 36.09 | 14500 | 1.4755 | |
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| 0.2903 | 37.34 | 15000 | 1.5078 | |
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| 0.2795 | 38.58 | 15500 | 1.5351 | |
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| 0.2701 | 39.83 | 16000 | 1.5639 | |
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| 0.2605 | 41.07 | 16500 | 1.5972 | |
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| 0.2521 | 42.31 | 17000 | 1.6191 | |
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| 0.2467 | 43.56 | 17500 | 1.6300 | |
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| 0.2425 | 44.8 | 18000 | 1.6453 | |
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| 0.2386 | 46.05 | 18500 | 1.6554 | |
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| 0.2356 | 47.29 | 19000 | 1.6628 | |
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| 0.2344 | 48.54 | 19500 | 1.6663 | |
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| 0.2333 | 49.78 | 20000 | 1.6666 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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