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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-swag10000-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-swag10000-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: 14.9335 |
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- Accuracy: 0.4646 |
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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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- training_steps: 5000 |
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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 | 0.32 | 100 | 15.8202 | 0.2778 | |
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| No log | 0.64 | 200 | 14.7041 | 0.3384 | |
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| No log | 0.96 | 300 | 16.9031 | 0.3737 | |
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| No log | 1.28 | 400 | 18.0978 | 0.4141 | |
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| 2.1655 | 1.6 | 500 | 16.5271 | 0.4040 | |
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| 2.1655 | 1.92 | 600 | 14.4014 | 0.3990 | |
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| 2.1655 | 2.24 | 700 | 19.0358 | 0.4242 | |
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| 2.1655 | 2.56 | 800 | 14.9314 | 0.4192 | |
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| 2.1655 | 2.88 | 900 | 14.9335 | 0.4646 | |
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| 0.5334 | 3.19 | 1000 | 15.1769 | 0.4596 | |
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| 0.5334 | 3.51 | 1100 | 15.4032 | 0.4343 | |
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| 0.5334 | 3.83 | 1200 | 13.1365 | 0.4646 | |
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| 0.5334 | 4.15 | 1300 | 12.7464 | 0.4394 | |
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| 0.5334 | 4.47 | 1400 | 13.5877 | 0.4545 | |
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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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