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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: DistilBERT-Hoax-Detection
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# DistilBERT-Hoax-Detection
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This model is a fine-tuned version of [cahya/distilbert-base-indonesian](https://huggingface.co/cahya/distilbert-base-indonesian) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5261
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- Accuracy: 0.8441
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-06
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.15
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.6644 | 1.0 | 93 | 0.6368 | 0.6237 |
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| 0.4151 | 2.0 | 186 | 0.5300 | 0.7258 |
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| 0.3645 | 3.0 | 279 | 0.5003 | 0.7688 |
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| 0.3283 | 4.0 | 372 | 0.4585 | 0.7957 |
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| 0.2557 | 5.0 | 465 | 0.4599 | 0.8065 |
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| 0.3993 | 6.0 | 558 | 0.5004 | 0.8065 |
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| 0.0536 | 7.0 | 651 | 0.4658 | 0.8387 |
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| 0.1944 | 8.0 | 744 | 0.5264 | 0.8280 |
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| 0.0612 | 9.0 | 837 | 0.5195 | 0.8387 |
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| 0.0602 | 10.0 | 930 | 0.5261 | 0.8441 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.0
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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