---
library_name: transformers
license: mit
base_model: neuralmind/bert-large-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: BingoGuard-bert-large-pt3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# BingoGuard-bert-large-pt3

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: 0.4693
- Accuracy: 0.8945
- F1: 0.9011

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use 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 | Accuracy | F1     |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
| 0.2595        | 1.0    | 2783  | 0.2779          | 0.8928   | 0.9018 |
| 0.2046        | 2.0    | 5566  | 0.2849          | 0.8998   | 0.9078 |
| 0.1646        | 3.0    | 8349  | 0.3121          | 0.8987   | 0.9075 |
| 0.1563        | 4.0    | 11132 | 0.3768          | 0.8968   | 0.9033 |
| 0.1114        | 4.9984 | 13910 | 0.4693          | 0.8945   | 0.9011 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.4