---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
datasets:
- glue-ptpt
metrics:
- accuracy
- f1
model-index:
- name: paraphrase-bert-portuguese
  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: 0.8676470588235294
    - name: F1
      type: f1
      value: 0.9028776978417268
---

<!-- 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. -->

# paraphrase-bert-portuguese

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: 1.2267
- Accuracy: 0.8676
- F1: 0.9029

## 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  | 0.7241          | 0.8603   | 0.9012 |
| 0.0658        | 2.0   | 918  | 0.7902          | 0.8725   | 0.9071 |
| 0.1499        | 3.0   | 1377 | 0.7895          | 0.8676   | 0.9022 |
| 0.0654        | 4.0   | 1836 | 0.9841          | 0.8676   | 0.9036 |
| 0.018         | 5.0   | 2295 | 1.0520          | 0.8627   | 0.8989 |
| 0.0144        | 6.0   | 2754 | 1.1002          | 0.8725   | 0.9081 |
| 0.007         | 7.0   | 3213 | 1.1303          | 0.8652   | 0.9005 |
| 0.0056        | 8.0   | 3672 | 1.2298          | 0.8725   | 0.9081 |
| 0.0019        | 9.0   | 4131 | 1.2353          | 0.8701   | 0.9038 |
| 0.0001        | 10.0  | 4590 | 1.2267          | 0.8676   | 0.9029 |


### Framework versions

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