metadata
library_name: transformers
license: mit
base_model: indobenchmark/indobert-base-p1
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: indobert-hoax-detection
results: []
indobert-hoax-detection
This model is a fine-tuned version of indobenchmark/indobert-base-p1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0543
- Accuracy: 0.9848
- F1: 0.9840
- Precision: 0.9857
- Recall: 0.9822
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0898 | 1.0 | 739 | 0.0585 | 0.9875 | 0.9869 | 0.9858 | 0.9879 |
| 0.0464 | 2.0 | 1478 | 0.0493 | 0.9861 | 0.9854 | 0.9858 | 0.9851 |
| 0.0247 | 3.0 | 2217 | 0.0629 | 0.9868 | 0.9862 | 0.9830 | 0.9893 |
| 0.0097 | 4.0 | 2956 | 0.0773 | 0.9871 | 0.9865 | 0.9858 | 0.9872 |
| 0.0031 | 5.0 | 3695 | 0.0862 | 0.9854 | 0.9847 | 0.9851 | 0.9844 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 2.19.2
- Tokenizers 0.20.1