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--- |
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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: fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa-loop-3 |
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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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# fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa-loop-3 |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8510 |
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- Accuracy: 0.5303 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 321 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 63 | 2.8211 | 0.2879 | |
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| No log | 2.0 | 126 | 2.0292 | 0.3889 | |
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| No log | 3.0 | 189 | 1.3492 | 0.4293 | |
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| No log | 4.0 | 252 | 0.8583 | 0.5152 | |
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| No log | 5.0 | 315 | 0.8510 | 0.5303 | |
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| No log | 6.0 | 378 | 1.3129 | 0.4848 | |
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| No log | 7.0 | 441 | 0.7994 | 0.4444 | |
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| 1.9846 | 8.0 | 504 | 0.6454 | 0.4697 | |
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| 1.9846 | 9.0 | 567 | 0.8126 | 0.4899 | |
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| 1.9846 | 10.0 | 630 | 0.8618 | 0.4495 | |
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| 1.9846 | 11.0 | 693 | 0.5559 | 0.4848 | |
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| 1.9846 | 12.0 | 756 | 0.5902 | 0.4949 | |
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| 1.9846 | 13.0 | 819 | 0.5117 | 0.5051 | |
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| 1.9846 | 14.0 | 882 | 0.4989 | 0.4848 | |
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| 1.9846 | 15.0 | 945 | 0.4913 | 0.4697 | |
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| 0.2505 | 16.0 | 1008 | 0.4599 | 0.4949 | |
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| 0.2505 | 17.0 | 1071 | 0.3934 | 0.4949 | |
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| 0.2505 | 18.0 | 1134 | 0.4083 | 0.4848 | |
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| 0.2505 | 19.0 | 1197 | 0.4291 | 0.4798 | |
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| 0.2505 | 20.0 | 1260 | 0.4429 | 0.4747 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.0 |
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