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fresh-2-layer-qasc5000-distill-of-fresh-2-layer-mmlu_EVAL_mmlu

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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-qasc5000-distill-of-fresh-2-layer-mmlu_EVAL_mmlu
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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-qasc5000-distill-of-fresh-2-layer-mmlu_EVAL_mmlu
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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: 207.7788
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+ - Accuracy: 0.3764
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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 | 0.64 | 100 | 202.2836 | 0.24 |
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+ | No log | 1.27 | 200 | 206.3151 | 0.34 |
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+ | No log | 1.91 | 300 | 195.0245 | 0.35 |
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+ | No log | 2.55 | 400 | 201.5064 | 0.388 |
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+ | 98.9054 | 3.18 | 500 | 200.6433 | 0.386 |
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+ | 98.9054 | 3.82 | 600 | 193.7714 | 0.388 |
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+ | 98.9054 | 4.46 | 700 | 189.6684 | 0.39 |
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+ | 98.9054 | 5.1 | 800 | 192.2281 | 0.378 |
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+ | 98.9054 | 5.73 | 900 | 194.5975 | 0.388 |
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+ | 23.6632 | 6.37 | 1000 | 199.0726 | 0.42 |
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+ | 23.6632 | 7.01 | 1100 | 192.3244 | 0.402 |
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+ | 23.6632 | 7.64 | 1200 | 186.5772 | 0.402 |
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+ | 23.6632 | 8.28 | 1300 | 190.7620 | 0.402 |
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+ | 23.6632 | 8.92 | 1400 | 198.1279 | 0.394 |
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+ | 14.2685 | 9.55 | 1500 | 194.6297 | 0.366 |
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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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