--- 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](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