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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: toxicity-type-detection
  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. -->

# toxicity-type-detection

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: 2.2337
- Accuracy: 0.4214
- F1: 0.7645
- Precision: 0.8180
- Recall: 0.7230

## 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: 7.044186985160909e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1993
- optimizer: Adam with betas=(0.9339215524915885,0.9916979096990963) and epsilon=3.4435900142455904e-07
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.1107        | 1.0   | 534  | 0.9282          | 0.2823   | 0.6762 | 0.7419    | 0.6630 |
| 0.8974        | 2.0   | 1068 | 0.8605          | 0.2754   | 0.6324 | 0.7759    | 0.5913 |
| 0.7436        | 3.0   | 1602 | 1.0151          | 0.3150   | 0.6870 | 0.7828    | 0.6512 |
| 0.644         | 4.0   | 2136 | 1.1455          | 0.3519   | 0.7114 | 0.7857    | 0.6865 |
| 0.4704        | 5.0   | 2670 | 1.4827          | 0.3387   | 0.7109 | 0.7814    | 0.6843 |
| 0.3316        | 6.0   | 3204 | 1.6275          | 0.3602   | 0.7217 | 0.8020    | 0.6816 |
| 0.2717        | 7.0   | 3738 | 2.2337          | 0.4214   | 0.7645 | 0.8180    | 0.7230 |
| 0.231         | 8.0   | 4272 | 2.0275          | 0.3651   | 0.7194 | 0.8271    | 0.6528 |
| 0.197         | 9.0   | 4806 | 1.9878          | 0.4033   | 0.7409 | 0.8240    | 0.6812 |


### Framework versions

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