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fresh-2-layer-medmcqa-distill-of-fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa
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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: >-
      fresh-2-layer-medmcqa-distill-of-fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa
    results: []

fresh-2-layer-medmcqa-distill-of-fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa

This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9186
  • Accuracy: 0.5152

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0005
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 321
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 63 4.2492 0.2727
No log 2.0 126 3.2851 0.3889
No log 3.0 189 2.1889 0.4444
No log 4.0 252 4.3537 0.4646
No log 5.0 315 1.4476 0.4697
No log 6.0 378 1.1196 0.4646
No log 7.0 441 1.5751 0.4646
2.425 8.0 504 0.9802 0.4343
2.425 9.0 567 2.4061 0.4495
2.425 10.0 630 0.9186 0.5152
2.425 11.0 693 0.9569 0.4848
2.425 12.0 756 0.9649 0.4798
2.425 13.0 819 1.3807 0.4899
2.425 14.0 882 0.6900 0.4899
2.425 15.0 945 0.8787 0.4747
0.3146 16.0 1008 0.7985 0.4949
0.3146 17.0 1071 0.9305 0.4899
0.3146 18.0 1134 0.9062 0.4848
0.3146 19.0 1197 0.8571 0.5051
0.3146 20.0 1260 0.8674 0.5

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.14.0