| | --- |
| | license: mit |
| | base_model: neuralmind/bert-large-portuguese-cased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - recall |
| | - precision |
| | model-index: |
| | - name: final |
| | 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. --> |
| |
|
| | # final |
| |
|
| | This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3507 |
| | - Accuracy: 0.8945 |
| | - F1: 0.8863 |
| | - Recall: 0.8760 |
| | - Precision: 0.8968 |
| |
|
| | ## 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: 64 |
| | - eval_batch_size: 64 |
| | - seed: 5151 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 100 |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
| | | 0.485 | 0.9756 | 80 | 0.3916 | 0.8182 | 0.7984 | 0.7674 | 0.8319 | |
| | | 0.3395 | 1.9512 | 160 | 0.3039 | 0.8764 | 0.8547 | 0.7752 | 0.9524 | |
| | | 0.2139 | 2.9268 | 240 | 0.3122 | 0.8691 | 0.8548 | 0.8217 | 0.8908 | |
| | | 0.084 | 3.9024 | 320 | 0.3507 | 0.8945 | 0.8863 | 0.8760 | 0.8968 | |
| | | 0.058 | 4.8780 | 400 | 0.5087 | 0.8727 | 0.8571 | 0.8140 | 0.9052 | |
| | | 0.0389 | 5.8537 | 480 | 0.4579 | 0.8982 | 0.888 | 0.8605 | 0.9174 | |
| | | 0.0264 | 6.8293 | 560 | 0.5052 | 0.8873 | 0.8765 | 0.8527 | 0.9016 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.20.0 |
| | - Tokenizers 0.19.1 |
| | |
