---
library_name: transformers
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: finetuned-bertimbau-portuguese-metaphors-4fold
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetuned-bertimbau-portuguese-metaphors-4fold

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: 0.2013
- Precision: 0.5294
- Recall: 0.4091
- F1: 0.4615
- Accuracy: 0.9536

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4658        | 1.0   | 23   | 0.2788          | 0.0       | 0.0    | 0.0    | 0.9174   |
| 0.2197        | 2.0   | 46   | 0.2264          | 0.2       | 0.0909 | 0.1250 | 0.9391   |
| 0.1186        | 3.0   | 69   | 0.2154          | 0.7273    | 0.3636 | 0.4848 | 0.9536   |
| 0.0637        | 4.0   | 92   | 0.2114          | 0.5625    | 0.4091 | 0.4737 | 0.9478   |
| 0.0375        | 5.0   | 115  | 0.2013          | 0.5294    | 0.4091 | 0.4615 | 0.9536   |


### Framework versions

- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1