text_classifier

This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 3.2472
  • Accuracy: 0.6158

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: 5e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
2.4863 1.0 760 2.0973 0.2474
1.8132 2.0 1520 1.7995 0.4237
1.5143 3.0 2280 1.5842 0.5053
1.3095 4.0 3040 1.8946 0.5553
1.0743 5.0 3800 1.9189 0.5684
0.9554 6.0 4560 2.1748 0.5974
0.7778 7.0 5320 2.2701 0.6263
0.5849 8.0 6080 2.5282 0.6237
0.5472 9.0 6840 2.7330 0.6184
0.4232 10.0 7600 2.9518 0.6079
0.2858 11.0 8360 2.8892 0.6263
0.2908 12.0 9120 3.0251 0.6289
0.2391 13.0 9880 3.1414 0.6211
0.1569 14.0 10640 3.2581 0.6184
0.1405 15.0 11400 3.2472 0.6158

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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