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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-7 |
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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-7 |
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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: 0.7407 |
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- Accuracy: 0.4899 |
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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 | 2.8066 | 0.2626 | |
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| No log | 2.0 | 126 | 1.7729 | 0.3535 | |
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| No log | 3.0 | 189 | 1.8116 | 0.4394 | |
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| No log | 4.0 | 252 | 0.8183 | 0.4091 | |
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| No log | 5.0 | 315 | 0.9311 | 0.4242 | |
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| No log | 6.0 | 378 | 1.3171 | 0.4495 | |
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| No log | 7.0 | 441 | 0.7661 | 0.4545 | |
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| 2.0871 | 8.0 | 504 | 0.8889 | 0.4242 | |
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| 2.0871 | 9.0 | 567 | 0.6170 | 0.4394 | |
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| 2.0871 | 10.0 | 630 | 0.7407 | 0.4899 | |
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| 2.0871 | 11.0 | 693 | 0.6189 | 0.4697 | |
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| 2.0871 | 12.0 | 756 | 0.5956 | 0.4747 | |
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| 2.0871 | 13.0 | 819 | 0.5274 | 0.4596 | |
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| 2.0871 | 14.0 | 882 | 0.5014 | 0.4646 | |
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| 2.0871 | 15.0 | 945 | 0.4660 | 0.4545 | |
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| 0.2452 | 16.0 | 1008 | 0.4361 | 0.4495 | |
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| 0.2452 | 17.0 | 1071 | 0.3798 | 0.4697 | |
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| 0.2452 | 18.0 | 1134 | 0.3735 | 0.4697 | |
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| 0.2452 | 19.0 | 1197 | 0.3530 | 0.4646 | |
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| 0.2452 | 20.0 | 1260 | 0.3681 | 0.4646 | |
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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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