| license: mit | |
| base_model: neuralmind/bert-base-portuguese-cased | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - accuracy | |
| - f1 | |
| model-index: | |
| - name: oracle_class_vert_v3 | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/generation_jur/oracle_text_classification/runs/fi2ble5z) | |
| # oracle_class_vert_v3 | |
| 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: 0.5665 | |
| - Precision: 0.8326 | |
| - Recall: 0.8336 | |
| - Accuracy: 0.8477 | |
| - F1: 0.8310 | |
| ## 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: 6e-05 | |
| - train_batch_size: 24 | |
| - eval_batch_size: 24 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 4 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | | |
| |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:| | |
| | 0.5484 | 1.4589 | 550 | 0.5911 | 0.8063 | 0.8028 | 0.8308 | 0.8010 | | |
| | 0.3253 | 2.9178 | 1100 | 0.5665 | 0.8326 | 0.8336 | 0.8477 | 0.8310 | | |
| ### Framework versions | |
| - Transformers 4.43.1 | |
| - Pytorch 2.2.0 | |
| - Datasets 2.20.0 | |
| - Tokenizers 0.19.1 | |