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---
library_name: transformers
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: neuralmind/bert-base-portuguese-cased
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. -->
# neuralmind/bert-base-portuguese-cased
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: 0.0500
- Accuracy: 0.7415
- F1: 0.6919
- Recall: 0.7472
- Precision: 0.6838
## 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: 64
- eval_batch_size: 64
- seed: 5151
- optimizer: Use adamw_torch 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: 150
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.0667 | 1.0 | 18 | 0.0661 | 0.5536 | 0.4531 | 0.4520 | 0.4571 |
| 0.0624 | 2.0 | 36 | 0.0646 | 0.6696 | 0.5743 | 0.5752 | 0.5736 |
| 0.0625 | 3.0 | 54 | 0.0628 | 0.7321 | 0.6510 | 0.6510 | 0.6510 |
| 0.0612 | 4.0 | 72 | 0.0603 | 0.7411 | 0.6733 | 0.6795 | 0.6687 |
| 0.0566 | 5.0 | 90 | 0.0568 | 0.7768 | 0.7184 | 0.7260 | 0.7125 |
| 0.0544 | 6.0 | 108 | 0.0530 | 0.7589 | 0.7216 | 0.7588 | 0.7119 |
| 0.0488 | 7.0 | 126 | 0.0497 | 0.8214 | 0.7812 | 0.8010 | 0.7688 |
| 0.0398 | 8.0 | 144 | 0.0498 | 0.7946 | 0.7629 | 0.8054 | 0.75 |
| 0.0276 | 9.0 | 162 | 0.0540 | 0.8125 | 0.7681 | 0.7838 | 0.7575 |
| 0.0184 | 10.0 | 180 | 0.0674 | 0.7679 | 0.7156 | 0.7312 | 0.7065 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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