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distilbert-base-uncased-finetuned-banking77

Text Classification
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PyTorch
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distilbert
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distilbert-base-uncased-finetuned-banking77

This model is a fine-tuned version of distilbert-base-uncased on the banking77 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2935
  • Accuracy: 0.925
  • F1: 0.9250

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: 9.686210354742596e-05
  • train_batch_size: 64
  • eval_batch_size: 32
  • seed: 40
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
No log 1.0 126 1.1457 0.7896 0.7685
No log 2.0 252 0.4673 0.8906 0.8889
No log 3.0 378 0.3488 0.9150 0.9151
0.9787 4.0 504 0.3238 0.9180 0.9179
0.9787 5.0 630 0.3126 0.9225 0.9226

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.11.0
  • Datasets 2.0.0
  • Tokenizers 0.11.6
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Base model

distilbert/distilbert-base-uncased
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Dataset used to train optimum/distilbert-base-uncased-finetuned-banking77

Evaluation results

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