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

fresh-2-layer-medmcqa-distill-of-fresh-2-layer-gpqa_EVAL_gpqa

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

  • Loss: 8.0989
  • Accuracy: 0.6566

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: 32
  • eval_batch_size: 32
  • 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 1.0 125 13.0027 0.4747
No log 2.0 250 10.8183 0.5404
No log 3.0 375 11.0325 0.5909
3.3093 4.0 500 11.0605 0.5808
3.3093 5.0 625 9.5436 0.5758
3.3093 6.0 750 9.1106 0.6515
3.3093 7.0 875 8.4697 0.6212
0.675 8.0 1000 9.1724 0.6212
0.675 9.0 1125 8.4508 0.6515
0.675 10.0 1250 8.5147 0.6111
0.675 11.0 1375 8.4648 0.6414
0.2645 12.0 1500 8.2626 0.6515
0.2645 13.0 1625 8.2865 0.6515
0.2645 14.0 1750 8.1180 0.6465
0.2645 15.0 1875 8.5052 0.6414
0.1402 16.0 2000 7.9762 0.6515
0.1402 17.0 2125 8.1063 0.6515
0.1402 18.0 2250 8.0695 0.6515
0.1402 19.0 2375 8.0989 0.6566
0.07 20.0 2500 8.0972 0.6566

Framework versions

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