---
library_name: transformers
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bertimbau_toldbr
  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. -->

# bertimbau_toldbr

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: 0.6976
- Acc: 0.724
- F1: 0.7107

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Acc   | F1     |
|:-------------:|:-----:|:----:|:---------------:|:-----:|:------:|
| 0.5746        | 1.0   | 63   | 0.6290          | 0.685 | 0.7091 |
| 0.4933        | 2.0   | 126  | 0.5979          | 0.711 | 0.7375 |
| 0.3049        | 3.0   | 189  | 0.6137          | 0.735 | 0.6929 |
| 0.2006        | 4.0   | 252  | 0.6976          | 0.724 | 0.7107 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1