transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:banking77 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- banking77
license: apache-2.0
metrics:
- f1
tags:
- generated_from_trainer
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: 0.9317731421465705
      name: F1
---

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# 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: 0.3333
- F1: 0.9318

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1101        | 1.0   | 626  | 0.3595          | 0.9181 |
| 0.0658        | 2.0   | 1252 | 0.3570          | 0.9269 |
| 0.0308        | 3.0   | 1878 | 0.3333          | 0.9318 |


### Framework versions

- Transformers 4.27.1
- Pytorch 2.0.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
