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End of training
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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: N_distilbert_agnews_padding50model
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: ag_news
          type: ag_news
          config: default
          split: test
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9418421052631579

N_distilbert_agnews_padding50model

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: 0.6732
  • Accuracy: 0.9418

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
0.1757 1.0 7500 0.1847 0.9428
0.1399 2.0 15000 0.1983 0.9439
0.1196 3.0 22500 0.2251 0.9418
0.0894 4.0 30000 0.2583 0.9436
0.0587 5.0 37500 0.3116 0.9425
0.0404 6.0 45000 0.3567 0.9432
0.0318 7.0 52500 0.4279 0.9392
0.0257 8.0 60000 0.4443 0.9407
0.0212 9.0 67500 0.4974 0.9378
0.0106 10.0 75000 0.4965 0.9417
0.0145 11.0 82500 0.4986 0.9433
0.011 12.0 90000 0.5389 0.9392
0.0121 13.0 97500 0.5671 0.9441
0.0046 14.0 105000 0.6063 0.9396
0.0011 15.0 112500 0.6245 0.9414
0.002 16.0 120000 0.6103 0.9426
0.001 17.0 127500 0.6181 0.9426
0.0017 18.0 135000 0.6401 0.9408
0.0002 19.0 142500 0.6667 0.9422
0.0004 20.0 150000 0.6732 0.9418

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.5
  • Tokenizers 0.13.3