---
language:
- pt
license: apache-2.0
tags:
- toxicity
- portuguese
- hate speech
- offensive language
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: neuralmind/bert-large-portuguese-cased
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
should probably proofread and complete it, then remove this comment. -->

# dougtrajano/toxicity-target-type-identification

This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the OLID-BR dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4281
- Accuracy: 0.8002
- F1: 0.7986
- Precision: 0.7990
- Recall: 0.8002

## 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  | 0.7145          | 0.6903   | 0.7052 | 0.7528    | 0.6903 |
| 0.8011        | 2.0   | 710  | 0.9930          | 0.7928   | 0.7840 | 0.7835    | 0.7928 |
| 0.529         | 3.0   | 1065 | 1.4281          | 0.8002   | 0.7986 | 0.7990    | 0.8002 |
| 0.529         | 4.0   | 1420 | 1.6783          | 0.7727   | 0.7753 | 0.7788    | 0.7727 |
| 0.2706        | 5.0   | 1775 | 2.3904          | 0.7727   | 0.7683 | 0.7660    | 0.7727 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.10.2+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2