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# judicial_brazil

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3551
- Accuracy: 0.8564
- Precision: 0.8611
- Recall: 0.8564
- F1: 0.8529

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.0   | 405  | 0.4573          | 0.8267   | 0.8318    | 0.8267 | 0.8230 |
| 0.7643        | 2.0   | 810  | 0.3391          | 0.8540   | 0.8612    | 0.8540 | 0.8481 |
| 0.3575        | 3.0   | 1215 | 0.3551          | 0.8564   | 0.8611    | 0.8564 | 0.8529 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "bert-base-cased", "model-index": [{"name": "judicial_brazil", "results": []}]}
transformers safetensors bert text-classification generated_from_trainer base_model:bert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us