README.md

---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- f1
model-index:
- name: bert-base-banking77-pt2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: banking77
      type: banking77
      config: default
      split: test
      args: default
    metrics:
    - type: f1
      value: 0.9311734343722707
      name: F1
    - type: accuracy
      value: 0.9308441558441558
      name: Accuracy
      verified: true
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    - type: f1
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      name: F1 Macro
      verified: true
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    - type: f1
      value: 0.9308441558441558
      name: F1 Micro
      verified: true
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    - type: f1
      value: 0.9308950029410716
      name: F1 Weighted
      verified: true
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    - type: precision
      value: 0.9335975349016483
      name: Precision Macro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGJmYzYwOGY5NDFkYTk1ZmU2YTAzNWJmNDFhOTcxYjkyNGUyMzgzNjg3NDhiY2ExMGE0N2FkOGZjNDE4MzAwNCIsInZlcnNpb24iOjF9.d1ON4n0wz8ac4SEsSzahXfp-p72kBRXpqfZ2BeTHmW-Fz_LW6ORe3cC6XXIabS8Odtl4oPSBJj6cVkfjAFI5AA
    - type: precision
      value: 0.9308441558441558
      name: Precision Micro
      verified: true
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    - type: precision
      value: 0.9335975349016484
      name: Precision Weighted
      verified: true
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    - type: recall
      value: 0.930844155844156
      name: Recall Macro
      verified: true
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    - type: recall
      value: 0.9308441558441558
      name: Recall Micro
      verified: true
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    - type: recall
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      name: Recall Weighted
      verified: true
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    - type: loss
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      name: loss
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---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-base-banking77-pt2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the banking77 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2844
- F1: 0.9312

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.2215        | 1.0   | 313  | 1.1811          | 0.7646 |
| 0.6252        | 2.0   | 626  | 0.4665          | 0.9120 |
| 0.3323        | 3.0   | 939  | 0.3294          | 0.9281 |
| 0.1446        | 4.0   | 1252 | 0.3051          | 0.9267 |
| 0.0994        | 5.0   | 1565 | 0.2844          | 0.9312 |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.1
- Datasets 2.9.0
- Tokenizers 0.13.3