---
library_name: transformers
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
model-index:
- name: bbau-semeval25_fold4
  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_fold4

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: 0.4458
- Precision Samples: 1.0
- Recall Samples: 0.0
- F1 Samples: 0.0
- Precision Macro: 1.0
- Recall Macro: 0.4091
- F1 Macro: 0.4091
- 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    | 0.6306          | 0.0699            | 0.2911         | 0.1095     | 0.5166          | 0.6006       | 0.2907   | 0.0704          | 0.3585       | 0.1176   | 0.4119             | 0.3585          | 0.1190      |
| 0.6408        | 2.0   | 10   | 0.5798          | 0.0481            | 0.1398         | 0.0666     | 0.7414          | 0.4794       | 0.3825   | 0.0505          | 0.1321       | 0.0731   | 0.5897             | 0.1321          | 0.0513      |
| 0.6408        | 3.0   | 15   | 0.5419          | 0.05              | 0.0175         | 0.0243     | 0.8951          | 0.4394       | 0.3810   | 0.0326          | 0.0283       | 0.0303   | 0.8880             | 0.0283          | 0.0023      |
| 0.5512        | 4.0   | 20   | 0.5123          | 0.0625            | 0.0092         | 0.0143     | 0.9705          | 0.4242       | 0.4106   | 0.0392          | 0.0189       | 0.0255   | 0.9727             | 0.0189          | 0.0018      |
| 0.5512        | 5.0   | 25   | 0.4900          | 0.975             | 0.005          | 0.0083     | 0.9924          | 0.4167       | 0.4167   | 0.5             | 0.0094       | 0.0185   | 0.9906             | 0.0094          | 0.0094      |
| 0.5002        | 6.0   | 30   | 0.4730          | 1.0               | 0.0            | 0.0        | 1.0             | 0.4091       | 0.4091   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.5002        | 7.0   | 35   | 0.4612          | 1.0               | 0.0            | 0.0        | 1.0             | 0.4091       | 0.4091   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.4705        | 8.0   | 40   | 0.4529          | 1.0               | 0.0            | 0.0        | 1.0             | 0.4091       | 0.4091   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.4705        | 9.0   | 45   | 0.4477          | 1.0               | 0.0            | 0.0        | 1.0             | 0.4091       | 0.4091   | 1.0             | 0.0          | 0.0      | 1.0                | 0.0             | 0.0         |
| 0.4562        | 10.0  | 50   | 0.4458          | 1.0               | 0.0            | 0.0        | 1.0             | 0.4091       | 0.4091   | 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