metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: toxicity-type-detection
results: []
toxicity-type-detection
This model is a fine-tuned version of 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