---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: cahya/distilbert-base-indonesian
model-index:
- name: DistilBERT-Hoax-Detection
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# DistilBERT-Hoax-Detection

This model is a fine-tuned version of [cahya/distilbert-base-indonesian](https://huggingface.co/cahya/distilbert-base-indonesian) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5261
- Accuracy: 0.8441

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.15
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6644        | 1.0   | 93   | 0.6368          | 0.6237   |
| 0.4151        | 2.0   | 186  | 0.5300          | 0.7258   |
| 0.3645        | 3.0   | 279  | 0.5003          | 0.7688   |
| 0.3283        | 4.0   | 372  | 0.4585          | 0.7957   |
| 0.2557        | 5.0   | 465  | 0.4599          | 0.8065   |
| 0.3993        | 6.0   | 558  | 0.5004          | 0.8065   |
| 0.0536        | 7.0   | 651  | 0.4658          | 0.8387   |
| 0.1944        | 8.0   | 744  | 0.5264          | 0.8280   |
| 0.0612        | 9.0   | 837  | 0.5195          | 0.8387   |
| 0.0602        | 10.0  | 930  | 0.5261          | 0.8441   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3