README.md

---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: hate_BERTimbau_v1
  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_BERTimbau_v1

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: 1.1746
- Precision: 0.7707
- Recall: 0.7707
- F1: 0.7707
- Accuracy: 0.7707

## 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: 5e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5246        | 1.0   | 284  | 0.4708          | 0.7707    | 0.7707 | 0.7707 | 0.7707   |
| 0.394         | 2.0   | 568  | 0.4454          | 0.7919    | 0.7919 | 0.7919 | 0.7919   |
| 0.2585        | 3.0   | 852  | 0.8828          | 0.7407    | 0.7407 | 0.7407 | 0.7407   |
| 0.153         | 4.0   | 1136 | 1.1051          | 0.7372    | 0.7372 | 0.7372 | 0.7372   |
| 0.0935        | 5.0   | 1420 | 1.1746          | 0.7707    | 0.7707 | 0.7707 | 0.7707   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1