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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_EVAL_gpqa |
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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_EVAL_gpqa |
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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: 8.0989 |
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- Accuracy: 0.6566 |
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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: 32 |
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- eval_batch_size: 32 |
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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 | 125 | 13.0027 | 0.4747 | |
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| No log | 2.0 | 250 | 10.8183 | 0.5404 | |
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| No log | 3.0 | 375 | 11.0325 | 0.5909 | |
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| 3.3093 | 4.0 | 500 | 11.0605 | 0.5808 | |
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| 3.3093 | 5.0 | 625 | 9.5436 | 0.5758 | |
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| 3.3093 | 6.0 | 750 | 9.1106 | 0.6515 | |
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| 3.3093 | 7.0 | 875 | 8.4697 | 0.6212 | |
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| 0.675 | 8.0 | 1000 | 9.1724 | 0.6212 | |
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| 0.675 | 9.0 | 1125 | 8.4508 | 0.6515 | |
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| 0.675 | 10.0 | 1250 | 8.5147 | 0.6111 | |
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| 0.675 | 11.0 | 1375 | 8.4648 | 0.6414 | |
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| 0.2645 | 12.0 | 1500 | 8.2626 | 0.6515 | |
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| 0.2645 | 13.0 | 1625 | 8.2865 | 0.6515 | |
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| 0.2645 | 14.0 | 1750 | 8.1180 | 0.6465 | |
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| 0.2645 | 15.0 | 1875 | 8.5052 | 0.6414 | |
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| 0.1402 | 16.0 | 2000 | 7.9762 | 0.6515 | |
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| 0.1402 | 17.0 | 2125 | 8.1063 | 0.6515 | |
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| 0.1402 | 18.0 | 2250 | 8.0695 | 0.6515 | |
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| 0.1402 | 19.0 | 2375 | 8.0989 | 0.6566 | |
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| 0.07 | 20.0 | 2500 | 8.0972 | 0.6566 | |
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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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