metadata
language:
- pt
license: apache-2.0
tags:
- toxicity
- portuguese
- hate speech
- offensive language
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: dougtrajano/toxicity-target-type-identification
results: []
dougtrajano/toxicity-target-type-identification
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the OLID-BR dataset. It achieves the following results on the evaluation set:
- Loss: 0.7001
- Accuracy: 0.7505
- F1: 0.7603
- Precision: 0.7813
- Recall: 0.7505
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 | 0.7001 | 0.7505 | 0.7603 | 0.7813 | 0.7505 |
| 0.7919 | 2.0 | 710 | 1.0953 | 0.7505 | 0.7452 | 0.7590 | 0.7505 |
| 0.5218 | 3.0 | 1065 | 1.4217 | 0.7484 | 0.7551 | 0.7688 | 0.7484 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.10.2+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2