| --- |
| library_name: transformers |
| license: mit |
| base_model: neuralmind/bert-base-portuguese-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: TOTVS_Churn_Risk_V2 |
| 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. --> |
|
|
| # TOTVS_Churn_Risk_V2 |
| |
| This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2512 |
| - Accuracy: 0.9375 |
| - F1: 0.9378 |
| - Precision: 0.9608 |
| - Recall: 0.9159 |
| |
| ## 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: 1e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 5 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 1.2545 | 1.0 | 52 | 0.9010 | 0.8317 | 0.8523 | 0.7769 | 0.9439 | |
| | 0.5754 | 2.0 | 104 | 0.4523 | 0.9087 | 0.9073 | 0.9490 | 0.8692 | |
| | 0.4382 | 3.0 | 156 | 0.2997 | 0.9327 | 0.9346 | 0.9346 | 0.9346 | |
| | 0.2150 | 4.0 | 208 | 0.2800 | 0.9327 | 0.9320 | 0.9697 | 0.8972 | |
| | 0.1737 | 5.0 | 260 | 0.2512 | 0.9375 | 0.9378 | 0.9608 | 0.9159 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.8.3 |
| - Tokenizers 0.22.2 |
| |
