gustavokpc/bert-base-portuguese-cased_LRATE_2e-05_EPOCHS_5

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0733
• Train Accuracy: 0.9750
• Train F1 M: 0.5536
• Train Precision M: 0.4010
• Train Recall M: 0.9577
• Validation Loss: 0.1758
• Validation Accuracy: 0.9426
• Validation F1 M: 0.5568
• Validation Precision M: 0.4015
• Validation Recall M: 0.9529
• Epoch: 2

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': 2e-05, 'decay_steps': 3790, '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
0.2270	0.9119	0.5181	0.3865	0.8561	0.1618	0.9367	0.5592	0.4050	0.9478	0
0.1186	0.9551	0.5516	0.4007	0.9397	0.1621	0.9347	0.5628	0.4068	0.9580	1
0.0733	0.9750	0.5536	0.4010	0.9577	0.1758	0.9426	0.5568	0.4015	0.9529	2

Framework versions

• Transformers 4.34.1
• TensorFlow 2.10.0
• Datasets 2.14.5
• Tokenizers 0.14.1