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distilbert_agnews_padding20model

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: 0.6477
  • Accuracy: 0.9453

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
0.18 1.0 7500 0.1831 0.9426
0.1365 2.0 15000 0.2039 0.9420
0.1176 3.0 22500 0.2202 0.9470
0.0899 4.0 30000 0.2601 0.9443
0.0547 5.0 37500 0.2919 0.9429
0.0387 6.0 45000 0.3618 0.9459
0.0351 7.0 52500 0.4129 0.9413
0.031 8.0 60000 0.4379 0.9436
0.0171 9.0 67500 0.4794 0.9429
0.0156 10.0 75000 0.4744 0.9438
0.0147 11.0 82500 0.4832 0.9457
0.0108 12.0 90000 0.5166 0.9447
0.0034 13.0 97500 0.5083 0.9459
0.0065 14.0 105000 0.5451 0.9446
0.0062 15.0 112500 0.5926 0.9443
0.0031 16.0 120000 0.6059 0.9433
0.001 17.0 127500 0.6312 0.9463
0.0004 18.0 135000 0.6197 0.9454
0.0004 19.0 142500 0.6472 0.9455
0.0002 20.0 150000 0.6477 0.9453

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_padding20model

Evaluation results