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End of training
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metadata
license: mit
base_model: roberta-base
tags:
  - generated_from_trainer
datasets:
  - ag_news
metrics:
  - accuracy
model-index:
  - name: roberta_agnews_padding10model
    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: 0.9502631578947368

roberta_agnews_padding10model

This model is a fine-tuned version of roberta-base on the ag_news dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5337
  • Accuracy: 0.9503

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
0.1966 1.0 7500 0.2068 0.9404
0.1632 2.0 15000 0.1954 0.9457
0.1432 3.0 22500 0.2422 0.9478
0.1223 4.0 30000 0.2275 0.9486
0.0994 5.0 37500 0.2442 0.9486
0.079 6.0 45000 0.3053 0.9486
0.0759 7.0 52500 0.3104 0.9463
0.0506 8.0 60000 0.3757 0.9472
0.0436 9.0 67500 0.3468 0.9470
0.025 10.0 75000 0.4170 0.9468
0.0303 11.0 82500 0.4168 0.9462
0.0273 12.0 90000 0.4173 0.9486
0.024 13.0 97500 0.4305 0.9476
0.0139 14.0 105000 0.4549 0.9480
0.0111 15.0 112500 0.4961 0.9483
0.0102 16.0 120000 0.4733 0.9488
0.0036 17.0 127500 0.5044 0.9493
0.0025 18.0 135000 0.5070 0.95
0.0024 19.0 142500 0.5196 0.9508
0.0018 20.0 150000 0.5337 0.9503

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.1.1
  • Datasets 2.12.0
  • Tokenizers 0.13.3