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indobert-hoax
umn-cyber/indobert-hoax
indobert-hoax is a text classification model from umn-cyber. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Nov 14, 2024
- Updated
- Nov 15, 2024
- SHA
- e004d20e
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Model card
From the Hugging Face model README
<!-- 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. -->
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: 0.0556
- Accuracy: 0.9831
- F1: 0.9823
- Precision: 0.9781
- Recall: 0.9865
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0797 | 1.0 | 739 | 0.0485 | 0.9882 | 0.9876 | 0.9858 | 0.9893 |
| 0.0428 | 2.0 | 1478 | 0.0436 | 0.9868 | 0.9862 | 0.9817 | 0.9908 |
| 0.0221 | 3.0 | 2217 | 0.0480 | 0.9885 | 0.9879 | 0.9879 | 0.9879 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1
- Datasets 2.19.2
- Tokenizers 0.20.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Nov 14, 2024
- Updated
- Nov 15, 2024