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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-medmcqa-distill-of-bert-base-uncased-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-medmcqa-distill-of-bert-base-uncased-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: 9.2527 |
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- Accuracy: 0.4242 |
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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: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 20 |
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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 | 1.0 | 63 | 9.8453 | 0.2626 | |
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| No log | 2.0 | 126 | 12.6958 | 0.3131 | |
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| No log | 3.0 | 189 | 10.7690 | 0.3232 | |
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| No log | 4.0 | 252 | 9.5414 | 0.3737 | |
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| No log | 5.0 | 315 | 9.9080 | 0.3687 | |
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| No log | 6.0 | 378 | 9.5831 | 0.3889 | |
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| No log | 7.0 | 441 | 9.5607 | 0.3687 | |
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| 2.7217 | 8.0 | 504 | 10.5312 | 0.3283 | |
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| 2.7217 | 9.0 | 567 | 9.4693 | 0.4040 | |
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| 2.7217 | 10.0 | 630 | 9.5568 | 0.3889 | |
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| 2.7217 | 11.0 | 693 | 9.0092 | 0.3636 | |
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| 2.7217 | 12.0 | 756 | 8.9660 | 0.3889 | |
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| 2.7217 | 13.0 | 819 | 9.2727 | 0.3838 | |
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| 2.7217 | 14.0 | 882 | 9.3829 | 0.3636 | |
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| 2.7217 | 15.0 | 945 | 8.9537 | 0.3889 | |
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| 0.4611 | 16.0 | 1008 | 9.1312 | 0.3939 | |
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| 0.4611 | 17.0 | 1071 | 9.2527 | 0.4242 | |
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| 0.4611 | 18.0 | 1134 | 9.2069 | 0.4242 | |
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| 0.4611 | 19.0 | 1197 | 9.0783 | 0.4091 | |
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| 0.4611 | 20.0 | 1260 | 9.0630 | 0.4040 | |
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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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