---
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: 1.5456
- Accuracy: 0.7822

## 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: 16
- eval_batch_size: 16
- 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   | 203  | 0.7854          | 0.6683   |
| No log        | 2.0   | 406  | 0.6289          | 0.7574   |
| 0.6974        | 3.0   | 609  | 0.6930          | 0.7822   |
| 0.6974        | 4.0   | 812  | 0.7168          | 0.7649   |
| 0.2928        | 5.0   | 1015 | 0.8712          | 0.7822   |
| 0.2928        | 6.0   | 1218 | 0.9827          | 0.7772   |
| 0.2928        | 7.0   | 1421 | 1.1399          | 0.7624   |
| 0.1056        | 8.0   | 1624 | 1.2653          | 0.7847   |
| 0.1056        | 9.0   | 1827 | 1.3478          | 0.7673   |
| 0.0403        | 10.0  | 2030 | 1.4290          | 0.7673   |
| 0.0403        | 11.0  | 2233 | 1.4404          | 0.7797   |
| 0.0403        | 12.0  | 2436 | 1.4250          | 0.7797   |
| 0.016         | 13.0  | 2639 | 1.5548          | 0.7797   |
| 0.016         | 14.0  | 2842 | 1.5110          | 0.7871   |
| 0.0055        | 15.0  | 3045 | 1.5456          | 0.7822   |


### Framework versions

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