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superglue_rte-gpt2

This model is a fine-tuned version of gpt2 on the super_glue dataset. It achieves the following results on the evaluation set:

  • Loss: 4.4821
  • Accuracy: 0.5435

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.778 1.0 623 0.6845 0.5797
0.7042 2.0 1246 0.6909 0.5797
0.7022 3.0 1869 0.6608 0.5507
0.7145 4.0 2492 0.7206 0.5797
0.6183 5.0 3115 0.8510 0.5435
0.5855 6.0 3738 1.7010 0.5362
0.5468 7.0 4361 2.3186 0.5362
0.4411 8.0 4984 2.6790 0.5435
0.3226 9.0 5607 2.6486 0.5507
0.2479 10.0 6230 3.2958 0.5362
0.1632 11.0 6853 3.3893 0.5290
0.1526 12.0 7476 3.2382 0.5942
0.1127 13.0 8099 4.0889 0.4855
0.0902 14.0 8722 3.7049 0.5580
0.0997 15.0 9345 3.6377 0.5290
0.083 16.0 9968 3.6723 0.6087
0.0612 17.0 10591 4.2905 0.5870
0.0357 18.0 11214 4.4611 0.5145
0.0643 19.0 11837 4.4033 0.5217
0.0348 20.0 12460 4.4821 0.5435

Framework versions

  • Transformers 4.32.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.15.0
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train kennethge123/superglue_rte-gpt2

Evaluation results