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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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<!-- 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-8-layer-swag-distill-of-fresh-8-layer-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: 22.9598 |
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- Accuracy: 0.4040 |
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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 | 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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### 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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