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N_distilbert_agnews_padding90model

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: 0.6235
  • 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
0.1806 1.0 7500 0.1897 0.9411
0.1426 2.0 15000 0.2027 0.9421
0.1169 3.0 22500 0.2151 0.9447
0.0978 4.0 30000 0.2648 0.9421
0.0634 5.0 37500 0.3140 0.9393
0.0385 6.0 45000 0.3887 0.9413
0.0335 7.0 52500 0.4336 0.9378
0.0317 8.0 60000 0.4547 0.9405
0.0192 9.0 67500 0.4665 0.9389
0.0091 10.0 75000 0.4814 0.9422
0.0142 11.0 82500 0.5405 0.9422
0.0131 12.0 90000 0.5560 0.9416
0.0131 13.0 97500 0.5343 0.9413
0.005 14.0 105000 0.5242 0.9430
0.0013 15.0 112500 0.5975 0.9425
0.003 16.0 120000 0.5905 0.9430
0.0024 17.0 127500 0.5740 0.9453
0.0009 18.0 135000 0.6001 0.9457
0.0012 19.0 142500 0.6177 0.9467
0.0002 20.0 150000 0.6235 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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Finetuned from

Dataset used to train Realgon/N_distilbert_agnews_padding90model

Evaluation results