bert-base-uncased-finetuned-swag

This model is a fine-tuned version of Yama/bert-base-uncased-finetuned-swag on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0061
  • Accuracy: 0.9958

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 150 1.3780 0.3592
No log 2.0 300 1.3234 0.4383
No log 3.0 450 1.3158 0.4992
1.3577 4.0 600 1.1356 0.5792
1.3577 5.0 750 0.7939 0.7217
1.3577 6.0 900 0.6167 0.7958
1.0479 7.0 1050 0.4737 0.8467
1.0479 8.0 1200 0.3424 0.8867
1.0479 9.0 1350 0.2448 0.9142
0.5968 10.0 1500 0.2117 0.9158
0.5968 11.0 1650 0.1589 0.9467
0.5968 12.0 1800 0.1420 0.9492
0.5968 13.0 1950 0.0970 0.9675
0.3341 14.0 2100 0.1014 0.9725
0.3341 15.0 2250 0.0678 0.9742
0.3341 16.0 2400 0.0624 0.9825
0.1802 17.0 2550 0.0407 0.9783
0.1802 18.0 2700 0.0501 0.9858
0.1802 19.0 2850 0.0341 0.9867
0.1213 20.0 3000 0.0284 0.9883
0.1213 21.0 3150 0.0398 0.9883
0.1213 22.0 3300 0.0290 0.9908
0.1213 23.0 3450 0.0211 0.9908
0.0758 24.0 3600 0.0179 0.9908
0.0758 25.0 3750 0.0151 0.9917
0.0758 26.0 3900 0.0154 0.9933
0.0464 27.0 4050 0.0216 0.9942
0.0464 28.0 4200 0.0124 0.9942
0.0464 29.0 4350 0.0122 0.9942
0.0306 30.0 4500 0.0103 0.9942
0.0306 31.0 4650 0.0094 0.9942
0.0306 32.0 4800 0.0083 0.9942
0.0306 33.0 4950 0.0079 0.9958
0.0201 34.0 5100 0.0079 0.9950
0.0201 35.0 5250 0.0069 0.9958
0.0201 36.0 5400 0.0069 0.9950
0.0205 37.0 5550 0.0060 0.9967
0.0205 38.0 5700 0.0060 0.9958
0.0205 39.0 5850 0.0061 0.9958
0.0102 40.0 6000 0.0061 0.9958

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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