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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-4-layer-swag-distill-of-fresh-4-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-4-layer-swag-distill-of-fresh-4-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: 11.8632 |
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- Accuracy: 0.4293 |
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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 | 125 | 13.8015 | 0.2778 | |
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| No log | 2.0 | 250 | 14.0268 | 0.3535 | |
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| No log | 3.0 | 375 | 13.0123 | 0.3838 | |
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| 1.8616 | 4.0 | 500 | 12.3288 | 0.3535 | |
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| 1.8616 | 5.0 | 625 | 12.1718 | 0.3737 | |
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| 1.8616 | 6.0 | 750 | 12.7654 | 0.3889 | |
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| 1.8616 | 7.0 | 875 | 12.6711 | 0.3838 | |
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| 0.4769 | 8.0 | 1000 | 12.0719 | 0.4141 | |
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| 0.4769 | 9.0 | 1125 | 11.8960 | 0.4091 | |
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| 0.4769 | 10.0 | 1250 | 12.0726 | 0.4192 | |
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| 0.4769 | 11.0 | 1375 | 11.8632 | 0.4293 | |
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| 0.1853 | 12.0 | 1500 | 11.6135 | 0.4141 | |
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| 0.1853 | 13.0 | 1625 | 12.2307 | 0.4141 | |
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| 0.1853 | 14.0 | 1750 | 11.7646 | 0.4040 | |
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| 0.1853 | 15.0 | 1875 | 11.6897 | 0.4141 | |
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| 0.0913 | 16.0 | 2000 | 12.0394 | 0.4091 | |
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| 0.0913 | 17.0 | 2125 | 11.7915 | 0.4040 | |
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| 0.0913 | 18.0 | 2250 | 12.0047 | 0.3990 | |
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| 0.0913 | 19.0 | 2375 | 11.9798 | 0.3939 | |
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| 0.0436 | 20.0 | 2500 | 12.0208 | 0.4040 | |
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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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