---
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:
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      value: 0.9317233921464609
      name: F1
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      name: Accuracy
      verified: true
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    - type: f1
      value: 0.9317233921464607
      name: F1 Macro
      verified: true
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    - type: f1
      value: 0.9314935064935065
      name: F1 Micro
      verified: true
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    - type: f1
      value: 0.9317233921464609
      name: F1 Weighted
      verified: true
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    - type: precision
      value: 0.935331493948515
      name: Precision Macro
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTdhYWM0NWM5ZDMwODg1ZjlhZWNjMmIxZjI0ZTk2NjVmYzFkMWVjMzg1NGEyYzAwN2UzZWY4MmYxYmVhNjk0NyIsInZlcnNpb24iOjF9.uEUA0UVZOV5FwpRQSp2Qq3DzHwdbGxJFxicStScMlSkjuHMacnk7ef2IND1jfHSfQuSDe99tUxptXiVkxsnPBw
    - type: precision
      value: 0.9314935064935065
      name: Precision Micro
      verified: true
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    - type: precision
      value: 0.935331493948515
      name: Precision Weighted
      verified: true
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    - type: recall
      value: 0.9314935064935064
      name: Recall Macro
      verified: true
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    - type: recall
      value: 0.9314935064935065
      name: Recall Micro
      verified: true
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    - type: recall
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      verified: true
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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: 0.2995
- F1: 0.9317

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.0666        | 1.0   | 626  | 0.7760          | 0.8472 |
| 0.3748        | 2.0   | 1252 | 0.3521          | 0.9264 |
| 0.1853        | 3.0   | 1878 | 0.2995          | 0.9317 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 2.0.0.dev20230213+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2