---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_keras_callback
model-index:
- name: gustavokpc/bert-base-portuguese-cased_LRATE_1e-06_EPOCHS_10
  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-06_EPOCHS_10

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: 0.1512
- Train Accuracy: 0.9471
- Train F1 M: 0.5514
- Train Precision M: 0.4012
- Train Recall M: 0.9396
- Validation Loss: 0.1864
- Validation Accuracy: 0.9307
- Validation F1 M: 0.5599
- Validation Precision M: 0.4032
- Validation Recall M: 0.9613
- Epoch: 8

## 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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-06, 'decay_steps': 7580, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.4813     | 0.7972         | 0.2411     | 0.2093            | 0.3344         | 0.2665          | 0.9090              | 0.5217          | 0.3877                 | 0.8393              | 0     |
| 0.2432     | 0.9126         | 0.5317     | 0.3942            | 0.8764         | 0.2185          | 0.9169              | 0.5490          | 0.3979                 | 0.9239              | 1     |
| 0.2054     | 0.9262         | 0.5438     | 0.3981            | 0.9151         | 0.2059          | 0.9222              | 0.5441          | 0.3948                 | 0.9188              | 2     |
| 0.1883     | 0.9300         | 0.5471     | 0.3992            | 0.9253         | 0.1970          | 0.9294              | 0.5504          | 0.3977                 | 0.9356              | 3     |
| 0.1771     | 0.9359         | 0.5494     | 0.4011            | 0.9339         | 0.1918          | 0.9268              | 0.5550          | 0.4005                 | 0.9486              | 4     |
| 0.1632     | 0.9418         | 0.5507     | 0.4016            | 0.9369         | 0.1889          | 0.9294              | 0.5578          | 0.4023                 | 0.9538              | 5     |
| 0.1591     | 0.9436         | 0.5507     | 0.4023            | 0.9416         | 0.1878          | 0.9307              | 0.5547          | 0.4005                 | 0.9464              | 6     |
| 0.1536     | 0.9452         | 0.5529     | 0.4028            | 0.9419         | 0.1871          | 0.9301              | 0.5561          | 0.4010                 | 0.9521              | 7     |
| 0.1512     | 0.9471         | 0.5514     | 0.4012            | 0.9396         | 0.1864          | 0.9307              | 0.5599          | 0.4032                 | 0.9613              | 8     |


### Framework versions

- Transformers 4.37.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1