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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-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: 0.1478
- Train Accuracy: 0.9481
- Train F1 M: 0.5518
- Train Precision M: 0.4013
- Train Recall M: 0.9436
- Validation Loss: 0.1862
- Validation Accuracy: 0.9307
- Validation F1 M: 0.5600
- Validation Precision M: 0.4033
- Validation Recall M: 0.9613
- Epoch: 9
## 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 |
| 0.1478 | 0.9481 | 0.5518 | 0.4013 | 0.9436 | 0.1862 | 0.9307 | 0.5600 | 0.4033 | 0.9613 | 9 |
### Framework versions
- Transformers 4.37.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1
|