---
language:
- pt
license: mit
tags:
- generated_from_keras_callback
datasets:
- assin2
metrics:
- accuracy
- f1
pipeline_tag: text-classification
base_model: neuralmind/bert-base-portuguese-cased
model-index:
- name: pmfsl/bertimbau-base-finetuned-rte
  results:
  - task:
      type: text-classification
      name: Natural Lenguage Inference
    dataset:
      name: ASSIN2
      type: assin2
    metrics:
    - type: accuracy
      value: 0.877859477124183
    - type: f1
      value: 0.8860083873427372
---

<!-- 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. -->

# pmfsl/bertimbau-base-finetuned-rte

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: 0.0326
- Validation Loss: 0.1834
- Test Loss: 0.5695
- Train Accuracy: 0.9531
- Train F1: 0.9534
- Test Accuracy: 0.8778
- Test F1: 0.8860
- 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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 505, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Train Accuracy | Train F1 | Epoch |
|:----------:|:---------------:|:--------------:|:--------:|:-----:|
| 0.3846     | 0.2204          | 0.9152         | 0.9191   | 0     |
| 0.1981     | 0.1577          | 0.9442         | 0.9455   | 1     |
| 0.1026     | 0.1348          | 0.9509         | 0.9511   | 2     |
| 0.0593     | 0.1492          | 0.9531         | 0.9542   | 3     |
| 0.0326     | 0.1834          | 0.9531         | 0.9534   | 4     |


### Framework versions

- Transformers 4.27.4
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.2