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fresh-2-layer-swag10000-distill-of-fresh-2-layer-gpqa_EVAL_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-2-layer-swag10000-distill-of-fresh-2-layer-gpqa_EVAL_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-2-layer-swag10000-distill-of-fresh-2-layer-gpqa_EVAL_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: 14.9335
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+ - Accuracy: 0.4646
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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: 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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+
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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 | 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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+
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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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