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fresh-2-layer-swag20000-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-swag20000-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-swag20000-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: 15.3688
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+ - Accuracy: 0.4747
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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 | 0.16 | 100 | 14.6793 | 0.2677 |
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+ | No log | 0.32 | 200 | 21.2273 | 0.3687 |
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+ | No log | 0.48 | 300 | 19.4173 | 0.3485 |
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+ | No log | 0.64 | 400 | 23.6541 | 0.4343 |
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+ | 2.2803 | 0.8 | 500 | 18.0346 | 0.4091 |
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+ | 2.2803 | 0.96 | 600 | 20.1434 | 0.4293 |
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+ | 2.2803 | 1.12 | 700 | 16.6838 | 0.4192 |
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+ | 2.2803 | 1.28 | 800 | 15.3688 | 0.4747 |
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+ | 2.2803 | 1.44 | 900 | 16.6134 | 0.4444 |
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+ | 0.5776 | 1.6 | 1000 | 15.2527 | 0.4192 |
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+ | 0.5776 | 1.76 | 1100 | 13.8964 | 0.4444 |
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+ | 0.5776 | 1.92 | 1200 | 15.0290 | 0.4444 |
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+ | 0.5776 | 2.08 | 1300 | 14.4659 | 0.4495 |
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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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+ "layer_norm_eps": 1e-12,
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