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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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<!-- 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-medmcqa20000-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: 5.6554 |
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- Accuracy: 0.7323 |
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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 | 0.16 | 100 | 15.6094 | 0.3384 | |
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| No log | 0.32 | 200 | 11.2486 | 0.4747 | |
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| No log | 0.48 | 300 | 9.7003 | 0.5556 | |
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| No log | 0.64 | 400 | 9.0128 | 0.6212 | |
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| 3.508 | 0.8 | 500 | 9.0146 | 0.6111 | |
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| 3.508 | 0.96 | 600 | 7.8672 | 0.6465 | |
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| 3.508 | 1.12 | 700 | 7.4123 | 0.6768 | |
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| 3.508 | 1.28 | 800 | 7.4161 | 0.6515 | |
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| 3.508 | 1.44 | 900 | 7.3679 | 0.6667 | |
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| 0.9934 | 1.6 | 1000 | 6.8781 | 0.6768 | |
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| 0.9934 | 1.76 | 1100 | 6.7447 | 0.6717 | |
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| 0.9934 | 1.92 | 1200 | 7.6242 | 0.6818 | |
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| 0.9934 | 2.08 | 1300 | 6.6278 | 0.6869 | |
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| 0.9934 | 2.24 | 1400 | 6.4569 | 0.6970 | |
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| 0.6102 | 2.4 | 1500 | 6.7556 | 0.7121 | |
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| 0.6102 | 2.56 | 1600 | 6.3065 | 0.7020 | |
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| 0.6102 | 2.72 | 1700 | 6.2906 | 0.7071 | |
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| 0.6102 | 2.88 | 1800 | 6.2230 | 0.7121 | |
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| 0.6102 | 3.04 | 1900 | 6.9069 | 0.7172 | |
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| 0.4278 | 3.2 | 2000 | 6.0706 | 0.7172 | |
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| 0.4278 | 3.36 | 2100 | 6.0340 | 0.7172 | |
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| 0.4278 | 3.52 | 2200 | 5.6554 | 0.7323 | |
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| 0.4278 | 3.68 | 2300 | 5.8829 | 0.7020 | |
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| 0.4278 | 3.84 | 2400 | 5.6822 | 0.7222 | |
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| 0.3174 | 4.0 | 2500 | 5.7620 | 0.7222 | |
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| 0.3174 | 4.16 | 2600 | 5.7952 | 0.7172 | |
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| 0.3174 | 4.32 | 2700 | 5.6193 | 0.7222 | |
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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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