--- license: mit base_model: neuralmind/bert-base-portuguese-cased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: bert-base-portuguese-cased-finetuned-ner results: [] --- # bert-base-portuguese-cased-finetuned-ner 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: - Loss: 0.0156 - Precision: 0.6569 - Recall: 0.4290 - F1: 0.5190 - Accuracy: 0.9959 ## 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: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 137 | 0.0394 | 0.0419 | 0.0191 | 0.0263 | 0.9893 | | No log | 2.0 | 274 | 0.0195 | 0.5622 | 0.3825 | 0.4553 | 0.9956 | | No log | 3.0 | 411 | 0.0156 | 0.6569 | 0.4290 | 0.5190 | 0.9959 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1