metadata
license: cc-by-sa-4.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-tagalog-profanity-classifier
results: []
roberta-tagalog-profanity-classifier
This model is a fine-tuned version of jcblaise/roberta-tagalog-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2897
- Accuracy: 0.8855
- Precision: 0.8864
- Recall: 0.9126
- F1: 0.8993
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 174 | 0.3082 | 0.8790 | 0.8900 | 0.8946 | 0.8923 |
| No log | 2.0 | 348 | 0.2861 | 0.8848 | 0.8902 | 0.9062 | 0.8981 |
| 0.2991 | 3.0 | 522 | 0.2897 | 0.8855 | 0.8864 | 0.9126 | 0.8993 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3