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fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa-loop-7

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README.md ADDED
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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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+
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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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+
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+ # fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa-loop-7
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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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