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N_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: 0.6409
  • Accuracy: 0.9447

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
0.1753 1.0 7500 0.1871 0.9414
0.1361 2.0 15000 0.2002 0.9443
0.1127 3.0 22500 0.2222 0.9439
0.0824 4.0 30000 0.2883 0.9411
0.0503 5.0 37500 0.3229 0.9405
0.0379 6.0 45000 0.3573 0.9426
0.0336 7.0 52500 0.3657 0.9421
0.0287 8.0 60000 0.4377 0.9433
0.0174 9.0 67500 0.4701 0.9421
0.0177 10.0 75000 0.4664 0.9436
0.0176 11.0 82500 0.4614 0.9461
0.0106 12.0 90000 0.5123 0.9436
0.0091 13.0 97500 0.5772 0.9428
0.0043 14.0 105000 0.5659 0.9436
0.0048 15.0 112500 0.5934 0.9442
0.0037 16.0 120000 0.5910 0.945
0.0039 17.0 127500 0.6058 0.9461
0.0022 18.0 135000 0.6002 0.9468
0.0025 19.0 142500 0.6316 0.9461
0.0018 20.0 150000 0.6409 0.9447

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_padding20model

Evaluation results