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update model card README.md
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README.md
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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: MammoLLM_bz32_acc4_lr1e4_large_epoch20
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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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# MammoLLM_bz32_acc4_lr1e4_large_epoch20
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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: 1.0667
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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: 0.0001
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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: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 3.5007 | 0.48 | 500 | 2.1723 |
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| 1.9621 | 0.96 | 1000 | 1.7328 |
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| 1.6708 | 1.44 | 1500 | 1.5700 |
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| 1.5458 | 1.92 | 2000 | 1.4780 |
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| 1.453 | 2.4 | 2500 | 1.4207 |
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| 1.4098 | 2.87 | 3000 | 1.3808 |
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| 1.3492 | 3.35 | 3500 | 1.3499 |
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| 1.3205 | 3.83 | 4000 | 1.3220 |
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| 1.2694 | 4.31 | 4500 | 1.2945 |
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| 1.2459 | 4.79 | 5000 | 1.2724 |
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| 1.2006 | 5.27 | 5500 | 1.2482 |
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| 1.1749 | 5.75 | 6000 | 1.2302 |
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| 1.139 | 6.23 | 6500 | 1.2146 |
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| 1.105 | 6.71 | 7000 | 1.1944 |
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| 1.0754 | 7.19 | 7500 | 1.1791 |
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| 1.0407 | 7.66 | 8000 | 1.1618 |
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| 1.0188 | 8.14 | 8500 | 1.1497 |
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| 0.9787 | 8.62 | 9000 | 1.1374 |
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| 0.9652 | 9.1 | 9500 | 1.1300 |
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| 0.9177 | 9.58 | 10000 | 1.1139 |
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| 0.9165 | 10.06 | 10500 | 1.1088 |
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| 0.8636 | 10.54 | 11000 | 1.0979 |
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| 0.8693 | 11.02 | 11500 | 1.0909 |
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| 0.812 | 11.5 | 12000 | 1.0895 |
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| 0.8243 | 11.98 | 12500 | 1.0779 |
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| 0.7734 | 12.46 | 13000 | 1.0796 |
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| 0.7792 | 12.93 | 13500 | 1.0717 |
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| 0.74 | 13.41 | 14000 | 1.0763 |
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| 0.7403 | 13.89 | 14500 | 1.0681 |
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| 0.7088 | 14.37 | 15000 | 1.0699 |
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| 0.708 | 14.85 | 15500 | 1.0650 |
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| 0.6846 | 15.33 | 16000 | 1.0684 |
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| 0.6811 | 15.81 | 16500 | 1.0652 |
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| 0.6644 | 16.29 | 17000 | 1.0688 |
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| 0.6582 | 16.77 | 17500 | 1.0665 |
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| 0.6512 | 17.25 | 18000 | 1.0669 |
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| 0.6433 | 17.72 | 18500 | 1.0663 |
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| 0.6403 | 18.2 | 19000 | 1.0668 |
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| 0.6347 | 18.68 | 19500 | 1.0666 |
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| 0.6318 | 19.16 | 20000 | 1.0668 |
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| 0.6304 | 19.64 | 20500 | 1.0667 |
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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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