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distilbert_agnews_padding10model

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: 0.6613
  • Accuracy: 0.9445

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
0.1788 1.0 7500 0.1962 0.9405
0.1396 2.0 15000 0.1946 0.9446
0.1159 3.0 22500 0.2336 0.9433
0.0802 4.0 30000 0.2599 0.9437
0.055 5.0 37500 0.3196 0.9432
0.0408 6.0 45000 0.4017 0.9434
0.0338 7.0 52500 0.4113 0.9412
0.0258 8.0 60000 0.4533 0.9416
0.0159 9.0 67500 0.4573 0.9442
0.0154 10.0 75000 0.4980 0.9420
0.0171 11.0 82500 0.4935 0.9420
0.0105 12.0 90000 0.5304 0.9399
0.0079 13.0 97500 0.5437 0.9439
0.0061 14.0 105000 0.5889 0.9429
0.0056 15.0 112500 0.5444 0.9426
0.0059 16.0 120000 0.6274 0.9429
0.0004 17.0 127500 0.6264 0.9428
0.0014 18.0 135000 0.6138 0.9441
0.0002 19.0 142500 0.6431 0.9447
0.0005 20.0 150000 0.6613 0.9445

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/distilbert_agnews_padding10model

Evaluation results