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distilbert_agnews_padding30model

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: 0.6664
  • Accuracy: 0.9426

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
0.1798 1.0 7500 0.1996 0.9397
0.1377 2.0 15000 0.1984 0.9432
0.1168 3.0 22500 0.2269 0.9429
0.0831 4.0 30000 0.2763 0.9411
0.0581 5.0 37500 0.2916 0.9428
0.0422 6.0 45000 0.3627 0.9424
0.0296 7.0 52500 0.4506 0.94
0.0315 8.0 60000 0.4401 0.9417
0.0224 9.0 67500 0.4668 0.9426
0.0151 10.0 75000 0.5095 0.9416
0.0202 11.0 82500 0.5013 0.9437
0.009 12.0 90000 0.5612 0.9441
0.0105 13.0 97500 0.5372 0.9432
0.0105 14.0 105000 0.5760 0.9409
0.0044 15.0 112500 0.5765 0.9417
0.0029 16.0 120000 0.6285 0.9432
0.002 17.0 127500 0.6484 0.9416
0.0006 18.0 135000 0.6568 0.9428
0.0002 19.0 142500 0.6537 0.9437
0.0004 20.0 150000 0.6664 0.9426

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/distilbert_agnews_padding30model

Evaluation results