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---
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_7
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_7
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: 0.0650
- Train Accuracy: 0.9758
- Train F1 M: 0.5601
- Train Precision M: 0.4039
- Train Recall M: 0.9754
- Validation Loss: 0.1751
- Validation Accuracy: 0.9466
- Validation F1 M: 0.5620
- Validation Precision M: 0.4036
- Validation Recall M: 0.9696
- Epoch: 3
## 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': 5306, '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 |
|:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:|
| 0.2473 | 0.9048 | 0.5004 | 0.3720 | 0.8254 | 0.1669 | 0.9340 | 0.5489 | 0.3976 | 0.9281 | 0 |
| 0.1350 | 0.9505 | 0.5530 | 0.4016 | 0.9485 | 0.1610 | 0.9420 | 0.5661 | 0.4073 | 0.9706 | 1 |
| 0.0890 | 0.9685 | 0.5595 | 0.4035 | 0.9677 | 0.1719 | 0.9446 | 0.5691 | 0.4082 | 0.9825 | 2 |
| 0.0650 | 0.9758 | 0.5601 | 0.4039 | 0.9754 | 0.1751 | 0.9466 | 0.5620 | 0.4036 | 0.9696 | 3 |
### Framework versions
- Transformers 4.34.1
- TensorFlow 2.10.0
- Datasets 2.14.5
- Tokenizers 0.14.1
|