---
language:
- pt
license: apache-2.0
tags:
- toxicity
- portuguese
- hate speech
- offensive language
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: dougtrajano/toxicity-target-type-identification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# dougtrajano/toxicity-target-type-identification

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the OLID-BR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7001
- Accuracy: 0.7505
- F1: 0.7603
- Precision: 0.7813
- Recall: 0.7505

## 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: 3.952388499692274e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1993
- optimizer: Adam with betas=(0.9944095815441554,0.8750000522553327) and epsilon=1.8526084265228802e-07
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 355  | 0.7001          | 0.7505   | 0.7603 | 0.7813    | 0.7505 |
| 0.7919        | 2.0   | 710  | 1.0953          | 0.7505   | 0.7452 | 0.7590    | 0.7505 |
| 0.5218        | 3.0   | 1065 | 1.4217          | 0.7484   | 0.7551 | 0.7688    | 0.7484 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.10.2+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2