---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
datasets:
- glue-ptpt
metrics:
- accuracy
- f1
model-index:
- name: bert-base-portuguese-fine-tuned-mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue-ptpt
      type: glue-ptpt
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8504901960784313
    - name: F1
      type: f1
      value: 0.8920353982300885
---

<!-- 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-portuguese-fine-tuned-mrpc

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the glue-ptpt dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2843
- Accuracy: 0.8505
- F1: 0.8920

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 459  | 0.6757          | 0.8603   | 0.8966 |
| 0.2011        | 2.0   | 918  | 0.7120          | 0.8505   | 0.8897 |
| 0.1215        | 3.0   | 1377 | 0.9679          | 0.8382   | 0.8764 |
| 0.0901        | 4.0   | 1836 | 1.0548          | 0.8333   | 0.8799 |
| 0.0478        | 5.0   | 2295 | 1.3125          | 0.8260   | 0.8769 |
| 0.0312        | 6.0   | 2754 | 1.0122          | 0.8578   | 0.8953 |
| 0.0309        | 7.0   | 3213 | 1.2197          | 0.8431   | 0.8849 |
| 0.0095        | 8.0   | 3672 | 1.1705          | 0.8554   | 0.8941 |
| 0.0076        | 9.0   | 4131 | 1.3132          | 0.8480   | 0.8912 |
| 0.0014        | 10.0  | 4590 | 1.2843          | 0.8505   | 0.8920 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3