---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/bert-base-portuguese-cased_LRATE_1e-05_EPOCHS_5
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# gustavokpc/bert-base-portuguese-cased_LRATE_1e-05_EPOCHS_5

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:
- Train Loss: 0.0570
- Train Accuracy: 0.9806
- Train F1 M: 0.5606
- Train Precision M: 0.4043
- Train Recall M: 0.9769
- Validation Loss: 0.1851
- Validation Accuracy: 0.9446
- Validation F1 M: 0.5629
- Validation Precision M: 0.4035
- Validation Recall M: 0.9763
- Epoch: 4

## 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:
- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 3790, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Train Accuracy | Train F1 M | Train Precision M | Train Recall M | Validation Loss | Validation Accuracy | Validation F1 M | Validation Precision M | Validation Recall M | Epoch |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.2400     | 0.9057         | 0.5084     | 0.3774            | 0.8407         | 0.1924          | 0.9294              | 0.5681          | 0.4101                 | 0.9715              | 0     |
| 0.1325     | 0.9529         | 0.5557     | 0.4036            | 0.9509         | 0.1685          | 0.9367              | 0.5519          | 0.3998                 | 0.9380              | 1     |
| 0.0929     | 0.9681         | 0.5582     | 0.4031            | 0.9644         | 0.1650          | 0.9426              | 0.5583          | 0.4027                 | 0.9554              | 2     |
| 0.0703     | 0.9764         | 0.5599     | 0.4042            | 0.9720         | 0.1808          | 0.9426              | 0.5670          | 0.4068                 | 0.9794              | 3     |
| 0.0570     | 0.9806         | 0.5606     | 0.4043            | 0.9769         | 0.1851          | 0.9446              | 0.5629          | 0.4035                 | 0.9763              | 4     |


### Framework versions

- Transformers 4.34.1
- TensorFlow 2.10.0
- Datasets 2.14.5
- Tokenizers 0.14.1