N_bert_agnews_padding50model

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

  • Loss: 0.5754
  • Accuracy: 0.9467

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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.1754 1.0 7500 0.1909 0.9428
0.1362 2.0 15000 0.1928 0.9461
0.1139 3.0 22500 0.2106 0.9461
0.0825 4.0 30000 0.2544 0.9466
0.0565 5.0 37500 0.3046 0.9367
0.0372 6.0 45000 0.3764 0.9436
0.0347 7.0 52500 0.3646 0.9425
0.0346 8.0 60000 0.3826 0.9461
0.0247 9.0 67500 0.4244 0.9455
0.0113 10.0 75000 0.4418 0.9446
0.0166 11.0 82500 0.4917 0.9462
0.0157 12.0 90000 0.4662 0.9442
0.0124 13.0 97500 0.4864 0.9438
0.0055 14.0 105000 0.4912 0.9457
0.0102 15.0 112500 0.5040 0.9446
0.0045 16.0 120000 0.5200 0.9441
0.0038 17.0 127500 0.5374 0.9467
0.0012 18.0 135000 0.5605 0.9459
0.0005 19.0 142500 0.5809 0.9455
0.0003 20.0 150000 0.5754 0.9467

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Dataset used to train Realgon/N_bert_agnews_padding50model

Evaluation results