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---
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/toxic-comment-classification
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/toxic-comment-classification
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: 0.4102
- Accuracy: 0.8547
- F1: 0.8549
- Precision: 0.8669
- Recall: 0.8547
## 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: 3.255788747459486e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1993
- optimizer: Adam with betas=(0.8445637934160373,0.8338816842140165) and epsilon=2.527092625455385e-08
- lr_scheduler_type: linear
- num_epochs: 30
- label_smoothing_factor: 0.07158711257743958
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4465 | 1.0 | 1408 | 0.4102 | 0.8547 | 0.8549 | 0.8669 | 0.8547 |
| 0.3839 | 2.0 | 2816 | 0.4814 | 0.8509 | 0.8497 | 0.8532 | 0.8509 |
| 0.3945 | 3.0 | 4224 | 0.6362 | 0.8002 | 0.7918 | 0.8258 | 0.8002 |
| 0.3643 | 4.0 | 5632 | 0.4961 | 0.8248 | 0.8211 | 0.8349 | 0.8248 |
| 0.3345 | 5.0 | 7040 | 0.5267 | 0.8528 | 0.8532 | 0.8570 | 0.8528 |
| 0.3053 | 6.0 | 8448 | 0.5902 | 0.8002 | 0.7911 | 0.8292 | 0.8002 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.10.2+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2
|