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

# hate_speech_detection_with_target-bert-large-portuguese-cased

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: 0.0610
- Accuracy: 0.9892

## 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: 0.0001
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8021        | 1.0   | 93   | 0.1410          | 0.9594   |
| 0.0974        | 2.0   | 186  | 0.0974          | 0.9770   |
| 0.1401        | 3.0   | 279  | 0.0550          | 0.9838   |
| 0.046         | 4.0   | 372  | 0.0618          | 0.9878   |
| 0.0344        | 5.0   | 465  | 0.0469          | 0.9892   |
| 0.2429        | 6.0   | 558  | 0.0854          | 0.9878   |
| 0.0696        | 7.0   | 651  | 0.0451          | 0.9892   |
| 0.0394        | 8.0   | 744  | 0.0460          | 0.9892   |
| 0.0279        | 9.0   | 837  | 0.0469          | 0.9892   |
| 0.0362        | 10.0  | 930  | 0.0779          | 0.9865   |
| 0.0215        | 11.0  | 1023 | 0.0655          | 0.9878   |
| 0.0193        | 12.0  | 1116 | 0.0587          | 0.9892   |
| 0.0154        | 13.0  | 1209 | 0.0594          | 0.9892   |
| 0.015         | 14.0  | 1302 | 0.0601          | 0.9905   |
| 0.0156        | 15.0  | 1395 | 0.0604          | 0.9892   |
| 0.0157        | 16.0  | 1488 | 0.0604          | 0.9892   |
| 0.0145        | 17.0  | 1581 | 0.0607          | 0.9892   |
| 0.0176        | 18.0  | 1674 | 0.0607          | 0.9892   |
| 0.0193        | 19.0  | 1767 | 0.0609          | 0.9892   |
| 0.0206        | 20.0  | 1860 | 0.0610          | 0.9892   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0