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N_distilbert_agnews_padding0model

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

  • Loss: 0.6408
  • Accuracy: 0.9464

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
0.1774 1.0 7500 0.1995 0.9392
0.1403 2.0 15000 0.1939 0.9447
0.1114 3.0 22500 0.2186 0.9459
0.0741 4.0 30000 0.2832 0.9446
0.0499 5.0 37500 0.3070 0.9408
0.0376 6.0 45000 0.3704 0.9434
0.0341 7.0 52500 0.3999 0.9426
0.0319 8.0 60000 0.4505 0.9425
0.0191 9.0 67500 0.4649 0.9399
0.013 10.0 75000 0.5064 0.9403
0.0184 11.0 82500 0.4858 0.9405
0.0081 12.0 90000 0.5358 0.9432
0.0065 13.0 97500 0.5440 0.9436
0.0053 14.0 105000 0.5755 0.9436
0.0017 15.0 112500 0.5907 0.9457
0.0042 16.0 120000 0.5916 0.9455
0.0031 17.0 127500 0.5976 0.9468
0.0017 18.0 135000 0.6063 0.9474
0.0003 19.0 142500 0.6248 0.9467
0.0003 20.0 150000 0.6408 0.9464

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_distilbert_agnews_padding0model

Evaluation results