--- license: mit base_model: neuralmind/bert-base-portuguese-cased tags: - generated_from_keras_callback model-index: - name: gustavokpc/bert-base-portuguese-cased_LRATE_5e-06_EPOCHS_6 results: [] --- # gustavokpc/bert-base-portuguese-cased_LRATE_5e-06_EPOCHS_6 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: 0.0950 - Train Accuracy: 0.9662 - Train F1 M: 0.5572 - Train Precision M: 0.4033 - Train Recall M: 0.9621 - Validation Loss: 0.1775 - Validation Accuracy: 0.9373 - Validation F1 M: 0.5604 - Validation Precision M: 0.4033 - Validation Recall M: 0.9607 - 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': 5e-06, 'decay_steps': 4548, '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 | |:----------:|:--------------:|:----------:|:-----------------:|:--------------:|:---------------:|:-------------------:|:---------------:|:----------------------:|:-------------------:|:-----:| | 0.2887 | 0.8821 | 0.4544 | 0.3418 | 0.7393 | 0.1871 | 0.9321 | 0.5574 | 0.4039 | 0.9455 | 0 | | 0.1571 | 0.9439 | 0.5463 | 0.3992 | 0.9299 | 0.1740 | 0.9321 | 0.5596 | 0.4040 | 0.9542 | 1 | | 0.1185 | 0.9587 | 0.5529 | 0.4020 | 0.9480 | 0.1714 | 0.9367 | 0.5588 | 0.4030 | 0.9555 | 2 | | 0.0950 | 0.9662 | 0.5572 | 0.4033 | 0.9621 | 0.1775 | 0.9373 | 0.5604 | 0.4033 | 0.9607 | 3 | ### Framework versions - Transformers 4.34.1 - TensorFlow 2.10.0 - Datasets 2.14.5 - Tokenizers 0.14.1