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distilbert-base-uncased-finetuned-yahd

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

  • Loss: 5.7685
  • Accuracy: 0.4010

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.2439 1.0 9142 2.1898 0.2130
1.9235 2.0 18284 2.1045 0.2372
1.5915 3.0 27426 2.1380 0.2550
1.3262 4.0 36568 2.2544 0.2758
1.0529 5.0 45710 2.5662 0.2955
0.8495 6.0 54852 2.8731 0.3078
0.6779 7.0 63994 3.1980 0.3218
0.5546 8.0 73136 3.6289 0.3380
0.4738 9.0 82278 3.9732 0.3448
0.412 10.0 91420 4.2945 0.3565
0.3961 11.0 100562 4.6127 0.3772
0.3292 12.0 109704 4.9586 0.3805
0.318 13.0 118846 5.2615 0.3887
0.2936 14.0 127988 5.4567 0.3931
0.2671 15.0 137130 5.6902 0.3965
0.2301 16.0 146272 5.7685 0.4010

Framework versions

  • Transformers 4.12.3
  • Pytorch 1.9.0+cu102
  • Datasets 1.15.1
  • Tokenizers 0.10.3
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