---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: file_classifier_v3
  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. -->

# file_classifier_v3

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: 0.6714
- Accuracy: 0.8586

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 73   | 0.7821          | 0.7966   |
| No log        | 2.0   | 146  | 0.7362          | 0.8103   |
| No log        | 3.0   | 219  | 0.6557          | 0.8207   |
| No log        | 4.0   | 292  | 0.7113          | 0.8069   |
| No log        | 5.0   | 365  | 0.6241          | 0.8379   |
| No log        | 6.0   | 438  | 0.6169          | 0.8448   |
| 0.206         | 7.0   | 511  | 0.6305          | 0.8345   |
| 0.206         | 8.0   | 584  | 0.6552          | 0.8621   |
| 0.206         | 9.0   | 657  | 0.6110          | 0.8724   |
| 0.206         | 10.0  | 730  | 0.6937          | 0.8552   |
| 0.206         | 11.0  | 803  | 0.6749          | 0.8552   |
| 0.206         | 12.0  | 876  | 0.6484          | 0.8690   |
| 0.206         | 13.0  | 949  | 0.6889          | 0.8586   |
| 0.0253        | 14.0  | 1022 | 0.6630          | 0.8586   |
| 0.0253        | 15.0  | 1095 | 0.6714          | 0.8586   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1