---
library_name: transformers
license: mit
base_model: neuralmind/bert-large-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test_trainer
  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. -->

# test_trainer

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: 2.2830
- Accuracy: 0.4335
- F1-macro: 0.4110
- F1-micro: 0.4335

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-macro | F1-micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.3757        | 1.0   | 191  | 1.3268          | 0.3716   | 0.3142   | 0.3716   |
| 1.1447        | 2.0   | 382  | 1.2496          | 0.4197   | 0.4421   | 0.4197   |
| 0.8885        | 3.0   | 573  | 1.4038          | 0.4174   | 0.3850   | 0.4174   |
| 0.4716        | 4.0   | 764  | 1.7668          | 0.4243   | 0.4081   | 0.4243   |
| 0.2784        | 5.0   | 955  | 2.0514          | 0.4404   | 0.4047   | 0.4404   |
| 0.1178        | 6.0   | 1146 | 2.2830          | 0.4335   | 0.4110   | 0.4335   |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0