---
library_name: transformers
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
model-index:
- name: bbau-semeval25_fold2
  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. -->

# bbau-semeval25_fold2

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: 0.4474
- Precision Samples: 1.0
- Recall Samples: 0.0
- F1 Samples: 0.0
- Precision Macro: 1.0
- Recall Macro: 0.3636
- F1 Macro: 0.3636
- Precision Micro: 1.0
- Recall Micro: 0.0
- F1 Micro: 0.0
- Precision Weighted: 1.0
- Recall Weighted: 0.0
- F1 Weighted: 0.0

## 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: 32
- eval_batch_size: 32
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision Samples | Recall Samples | F1 Samples | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro | Precision Weighted | Recall Weighted | F1 Weighted |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:------------------:|:---------------:|:-----------:|
| No log        | 1.0   | 5    | 0.6293          | 0.0783            | 0.3868         | 0.1220     | 0.4983          | 0.5865       | 0.3159   | 0.0751          | 0.375        | 0.1252   | 0.3532             | 0.375           | 0.1464      |
| 0.6408        | 2.0   | 10   | 0.5789          | 0.0787            | 0.2286         | 0.1079     | 0.7311          | 0.4717       | 0.3440   | 0.0839          | 0.2054       | 0.1192   | 0.5702             | 0.2054          | 0.0796      |
| 0.6408        | 3.0   | 15   | 0.5425          | 0.0708            | 0.0583         | 0.0554     | 0.9220          | 0.3953       | 0.3740   | 0.0706          | 0.0536       | 0.0609   | 0.8686             | 0.0536          | 0.0258      |
| 0.552         | 4.0   | 20   | 0.5135          | 0.1125            | 0.0271         | 0.0396     | 0.9759          | 0.3864       | 0.3719   | 0.0952          | 0.0357       | 0.0519   | 0.9634             | 0.0357          | 0.0110      |
| 0.552         | 5.0   | 25   | 0.4912          | 1.0               | 0.0            | 0.0        | 1.0             | 0.3636       | 0.3636   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.5007        | 6.0   | 30   | 0.4745          | 1.0               | 0.0            | 0.0        | 1.0             | 0.3636       | 0.3636   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.5007        | 7.0   | 35   | 0.4624          | 1.0               | 0.0            | 0.0        | 1.0             | 0.3636       | 0.3636   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.4713        | 8.0   | 40   | 0.4543          | 1.0               | 0.0            | 0.0        | 1.0             | 0.3636       | 0.3636   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.4713        | 9.0   | 45   | 0.4493          | 1.0               | 0.0            | 0.0        | 1.0             | 0.3636       | 0.3636   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.4567        | 10.0  | 50   | 0.4474          | 1.0               | 0.0            | 0.0        | 1.0             | 0.3636       | 0.3636   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.3.1
- Datasets 2.21.0
- Tokenizers 0.20.1