| 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 | |