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fresh-8-layer-swag-distill-of-fresh-8-layer-gpqa

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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-8-layer-swag-distill-of-fresh-8-layer-gpqa
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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-8-layer-swag-distill-of-fresh-8-layer-gpqa
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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: 22.9598
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+ - Accuracy: 0.4040
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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 | 22.7715 | 0.2677 |
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+ | No log | 2.0 | 126 | 24.4035 | 0.2879 |
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+ | No log | 3.0 | 189 | 21.6171 | 0.3131 |
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+ | No log | 4.0 | 252 | 22.9241 | 0.3333 |
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+ | No log | 5.0 | 315 | 36.3034 | 0.3788 |
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+ | No log | 6.0 | 378 | 22.9598 | 0.4040 |
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+ | No log | 7.0 | 441 | 25.2469 | 0.3485 |
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+ | 5.5235 | 8.0 | 504 | 29.2667 | 0.3687 |
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+ | 5.5235 | 9.0 | 567 | 24.0718 | 0.3687 |
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+ | 5.5235 | 10.0 | 630 | 25.5240 | 0.3030 |
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+ | 5.5235 | 11.0 | 693 | 28.6147 | 0.3283 |
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+ | 5.5235 | 12.0 | 756 | 33.3811 | 0.3434 |
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+ | 5.5235 | 13.0 | 819 | 28.3026 | 0.3232 |
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+ | 5.5235 | 14.0 | 882 | 27.7010 | 0.2677 |
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+ | 5.5235 | 15.0 | 945 | 26.9798 | 0.3182 |
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+ | 3.9997 | 16.0 | 1008 | 26.8561 | 0.3232 |
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+ | 3.9997 | 17.0 | 1071 | 25.9683 | 0.3687 |
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+ | 3.9997 | 18.0 | 1134 | 23.6478 | 0.3333 |
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+ | 3.9997 | 19.0 | 1197 | 24.1695 | 0.3232 |
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+ | 3.9997 | 20.0 | 1260 | 24.7100 | 0.3485 |
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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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