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metadata
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: []

dougtrajano/toxic-comment-classification

This model is a fine-tuned version of 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