---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: oracle_class_vert_v3
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/generation_jur/oracle_text_classification/runs/fi2ble5z)
# oracle_class_vert_v3

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5665
- Precision: 0.8326
- Recall: 0.8336
- Accuracy: 0.8477
- F1: 0.8310

## 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: 6e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| 0.5484        | 1.4589 | 550  | 0.5911          | 0.8063    | 0.8028 | 0.8308   | 0.8010 |
| 0.3253        | 2.9178 | 1100 | 0.5665          | 0.8326    | 0.8336 | 0.8477   | 0.8310 |


### Framework versions

- Transformers 4.43.1
- Pytorch 2.2.0
- Datasets 2.20.0
- Tokenizers 0.19.1