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distilbert-base-uncased-finetuned-banking77

Text Classification
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distilbert
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distilbert-base-uncased-finetuned-banking77 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - banking77
metrics:
  - accuracy
  - f1
widget:
  - text: Could you assist me in finding my lost card?
    example_title: Example 1
  - text: I found my lost card. Am I still able to use it?
    example_title: Example 2
  - text: >-
      Hey, I thought my topup was all done but now the money is gone again –
      what’s up with that?
    example_title: Example 3
  - text: Tell me why my topup wouldn’t go through?
    example_title: Example 4
model-index:
  - name: distilbert-base-uncased-finetuned-banking77
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: banking77
          type: banking77
          args: default
        metrics:
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            value: 0.925
            name: Accuracy
          - type: f1
            value: 0.925018570680639
            name: F1
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: banking77
          type: banking77
          config: default
          split: test
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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