README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - banking77
metrics:
  - f1
model-index:
  - name: test-bert-base-banking77
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: banking77
          type: banking77
          config: default
          split: test
          args: default
        metrics:
          - type: f1
            value: 0.9307471722060918
            name: F1
          - type: accuracy
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            name: Accuracy
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          - type: f1
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          - type: precision
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          - type: precision
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            name: Precision Micro
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          - type: precision
            value: 0.9341498488099383
            name: Precision Weighted
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          - type: recall
            value: 0.9308441558441556
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          - type: recall
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            name: loss
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test-bert-base-banking77

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

• Loss: 0.2828
• F1: 0.9307

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: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	F1
1.0786	1.0	626	0.7667	0.8429
0.3836	2.0	1252	0.3487	0.9223
0.1855	3.0	1878	0.2828	0.9307

Framework versions

• Transformers 4.29.2
• Pytorch 2.0.1
• Datasets 2.14.2
• Tokenizers 0.13.2