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aytugkaya/python-gpt2-large-issues-128

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face
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Model Card

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python-gpt2-large-issues-128

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2286

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: 8
  • evalbatchsize: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lrschedulertype: linear
  • num_epochs: 16

Training results

Training LossEpochStepValidation Loss
1.98431.011631.6715
1.57132.023261.4301
1.42263.034891.3808
1.3324.046521.3806
1.27085.058151.2737
1.20896.069781.2354
1.1677.081411.2250
1.1268.093041.2262
1.08469.0104671.1891
1.064710.0116301.2263
1.030111.0127931.1383
1.005412.0139561.0922
0.971413.0151191.1141
0.971314.0162821.1614
0.936215.0174451.0753
0.938216.0186081.2286

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.3
  • Tokenizers 0.11.6