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N_bert_agnews_padding40model

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: 0.5661
  • Accuracy: 0.9474

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
0.1785 1.0 7500 0.1884 0.9421
0.1379 2.0 15000 0.1990 0.9478
0.1127 3.0 22500 0.2389 0.9408
0.0846 4.0 30000 0.2528 0.9492
0.0581 5.0 37500 0.3041 0.9436
0.0456 6.0 45000 0.3415 0.9468
0.0411 7.0 52500 0.4081 0.9430
0.0239 8.0 60000 0.4415 0.9433
0.0202 9.0 67500 0.4380 0.9404
0.0126 10.0 75000 0.4637 0.9425
0.0175 11.0 82500 0.4485 0.9455
0.0126 12.0 90000 0.4761 0.9449
0.0046 13.0 97500 0.5009 0.9455
0.0038 14.0 105000 0.4784 0.9482
0.0035 15.0 112500 0.5282 0.9451
0.0046 16.0 120000 0.5256 0.9464
0.0026 17.0 127500 0.5081 0.9501
0.0008 18.0 135000 0.5543 0.9467
0.0002 19.0 142500 0.5448 0.9488
0.0016 20.0 150000 0.5661 0.9474

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_padding40model

Evaluation results