---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bertimbau-base-finetuned-lener-br-finetuned-brazilian_court_decisions
  results: []
---

<!-- 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. -->

# bertimbau-base-finetuned-lener-br-finetuned-brazilian_court_decisions

This model is a fine-tuned version of [Luciano/bertimbau-base-finetuned-lener-br](https://huggingface.co/Luciano/bertimbau-base-finetuned-lener-br) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8017
- Accuracy: 0.7698

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 405  | 0.7790          | 0.6535   |
| 0.8276        | 2.0   | 810  | 0.6739          | 0.7277   |
| 0.5818        | 3.0   | 1215 | 0.8767          | 0.7302   |
| 0.4147        | 4.0   | 1620 | 0.8229          | 0.7896   |
| 0.287         | 5.0   | 2025 | 0.9874          | 0.7921   |
| 0.287         | 6.0   | 2430 | 1.2301          | 0.7772   |
| 0.1727        | 7.0   | 2835 | 1.2864          | 0.7946   |
| 0.1179        | 8.0   | 3240 | 1.5097          | 0.7772   |
| 0.0709        | 9.0   | 3645 | 1.4772          | 0.7921   |
| 0.0437        | 10.0  | 4050 | 1.5581          | 0.7797   |
| 0.0437        | 11.0  | 4455 | 1.6317          | 0.7896   |
| 0.0318        | 12.0  | 4860 | 1.7295          | 0.7822   |
| 0.0158        | 13.0  | 5265 | 1.7333          | 0.7797   |
| 0.0108        | 14.0  | 5670 | 1.8008          | 0.7772   |
| 0.0137        | 15.0  | 6075 | 1.8017          | 0.7698   |


### Framework versions

- Transformers 4.22.0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1