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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-arc2000-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-arc2000-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: 13.5990 |
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- Accuracy: 0.4596 |
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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 | 1.59 | 100 | 14.0069 | 0.2828 | |
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| No log | 3.17 | 200 | 15.3225 | 0.4040 | |
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| No log | 4.76 | 300 | 13.6218 | 0.4040 | |
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| No log | 6.35 | 400 | 15.3356 | 0.4242 | |
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| 2.6428 | 7.94 | 500 | 13.0031 | 0.4293 | |
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| 2.6428 | 9.52 | 600 | 13.0853 | 0.4343 | |
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| 2.6428 | 11.11 | 700 | 13.6346 | 0.4545 | |
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| 2.6428 | 12.7 | 800 | 13.1762 | 0.4394 | |
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| 2.6428 | 14.29 | 900 | 12.9734 | 0.4545 | |
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| 0.4544 | 15.87 | 1000 | 13.5990 | 0.4596 | |
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| 0.4544 | 17.46 | 1100 | 13.0461 | 0.4596 | |
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| 0.4544 | 19.05 | 1200 | 12.0434 | 0.4495 | |
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| 0.4544 | 20.63 | 1300 | 12.9092 | 0.4343 | |
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| 0.4544 | 22.22 | 1400 | 12.1925 | 0.4596 | |
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| 0.2055 | 23.81 | 1500 | 13.0411 | 0.4242 | |
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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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