metadata
library_name: transformers
license: cc-by-sa-4.0
base_model: jcblaise/roberta-tagalog-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: gaslighting-detector-binary-roberta-tagalog-base
results: []
gaslighting-detector-binary-roberta-tagalog-base
This model is a fine-tuned version of jcblaise/roberta-tagalog-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3853
- Accuracy: 0.9222
- F1: 0.9271
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4385 | 1.0 | 80 | 0.1920 | 0.9139 | 0.9147 |
| 0.1363 | 2.0 | 160 | 0.1732 | 0.9451 | 0.9446 |
| 0.0552 | 3.0 | 240 | 0.2290 | 0.9432 | 0.9429 |
| 0.0023 | 4.0 | 320 | 0.2552 | 0.9469 | 0.9468 |
| 0.0087 | 5.0 | 400 | 0.2622 | 0.9469 | 0.9470 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.7.1+cu118
- Datasets 4.5.0
- Tokenizers 0.22.2