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---
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
|