---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- banking77
metrics:
- f1
model-index:
- name: bert-base-banking77-pt2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: banking77
      type: banking77
      config: default
      split: test
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.9231109184950563
---

<!-- 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: 0.3604
- F1: 0.9231

## 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: 64
- eval_batch_size: 64
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 157  | 1.8492          | 0.6818 |
| 2.8429        | 2.0   | 314  | 0.7977          | 0.8704 |
| 0.8817        | 3.0   | 471  | 0.4966          | 0.9071 |
| 0.3842        | 4.0   | 628  | 0.3884          | 0.9196 |
| 0.3842        | 5.0   | 785  | 0.3604          | 0.9231 |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.1+cu118
- Datasets 2.9.0
- Tokenizers 0.13.3