---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: oracle_class_bin
  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. -->

# oracle_class_bin

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: 0.1746
- Precision: 0.8254
- Recall: 0.7923
- Accuracy: 0.9615
- F1: 0.8085

## 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: 5e-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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| 0.1271        | 0.8407 | 1800 | 0.1045          | 0.7513    | 0.8544 | 0.9560   | 0.7996 |
| 0.0913        | 1.6815 | 3600 | 0.1075          | 0.8110    | 0.7968 | 0.9601   | 0.8038 |
| 0.0791        | 2.5222 | 5400 | 0.1283          | 0.8287    | 0.7885 | 0.9615   | 0.8081 |
| 0.0553        | 3.3629 | 7200 | 0.1272          | 0.8160    | 0.8067 | 0.9615   | 0.8113 |
| 0.0384        | 4.2036 | 9000 | 0.1746          | 0.8254    | 0.7923 | 0.9615   | 0.8085 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.0
- Datasets 2.20.0
- Tokenizers 0.19.1