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fresh-2-layer-medmcqa20000-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-medmcqa20000-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-medmcqa20000-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: 6.0579
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+ - Accuracy: 0.7222
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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 | 15.7756 | 0.3838 |
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+ | No log | 0.32 | 200 | 11.4980 | 0.5152 |
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+ | No log | 0.48 | 300 | 9.4964 | 0.5909 |
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+ | No log | 0.64 | 400 | 8.9627 | 0.6212 |
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+ | 3.5065 | 0.8 | 500 | 8.5232 | 0.6061 |
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+ | 3.5065 | 0.96 | 600 | 7.7951 | 0.6717 |
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+ | 3.5065 | 1.12 | 700 | 8.2685 | 0.6616 |
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+ | 3.5065 | 1.28 | 800 | 7.1380 | 0.6869 |
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+ | 3.5065 | 1.44 | 900 | 7.3768 | 0.6818 |
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+ | 0.9883 | 1.6 | 1000 | 6.9322 | 0.6970 |
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+ | 0.9883 | 1.76 | 1100 | 6.7062 | 0.6818 |
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+ | 0.9883 | 1.92 | 1200 | 6.6068 | 0.6919 |
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+ | 0.9883 | 2.08 | 1300 | 6.3543 | 0.6818 |
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+ | 0.9883 | 2.24 | 1400 | 6.0225 | 0.7020 |
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+ | 0.5892 | 2.4 | 1500 | 6.6609 | 0.6667 |
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+ | 0.5892 | 2.56 | 1600 | 6.3811 | 0.6919 |
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+ | 0.5892 | 2.72 | 1700 | 6.2649 | 0.6970 |
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+ | 0.5892 | 2.88 | 1800 | 6.8477 | 0.6919 |
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+ | 0.5892 | 3.04 | 1900 | 5.6575 | 0.7071 |
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+ | 0.4134 | 3.2 | 2000 | 5.8076 | 0.7071 |
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+ | 0.4134 | 3.36 | 2100 | 6.0579 | 0.7222 |
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+ | 0.4134 | 3.52 | 2200 | 5.7613 | 0.6970 |
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+ | 0.4134 | 3.68 | 2300 | 5.6748 | 0.7222 |
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+ | 0.4134 | 3.84 | 2400 | 5.8306 | 0.7121 |
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+ | 0.3115 | 4.0 | 2500 | 5.7578 | 0.7071 |
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+ | 0.3115 | 4.16 | 2600 | 5.5201 | 0.7172 |
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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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