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kennethge123/superglue_rte-bert-base-uncased

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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superglue_rte-bert-base-uncased

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

  • Loss: 1.5070
  • Accuracy: 0.6739

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
  • trainbatchsize: 4
  • evalbatchsize: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 20

Training results

Training LossEpochStepValidation LossAccuracy
0.7041.06230.66530.6159
0.68482.012460.71440.4203
0.70833.018690.69220.5797
0.70144.024920.73270.6232
0.65285.031150.67270.6522
0.64716.037380.84130.6159
0.58727.043610.87800.5507
0.59548.049840.76040.6377
0.55669.056070.85780.6812
0.557610.062302.04980.5362
0.492311.068531.40970.6304
0.568812.074761.41460.6667
0.43313.080991.33540.6594
0.425914.087221.32710.6957
0.386915.093451.28810.6812
0.364116.099681.44850.6739
0.329217.0105911.34450.6739
0.373418.0112141.49170.6739
0.322719.0118371.52810.6739
0.313320.0124601.50700.6739

Framework versions

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