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indobert-hoax-classification
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: 0.6230
- Accuracy: 0.8059
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: 4.2173070213315e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 30
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 85 | 0.5540 | 0.7029 |
| No log | 2.0 | 170 | 0.5432 | 0.7029 |
| No log | 3.0 | 255 | 0.4963 | 0.7441 |
| No log | 4.0 | 340 | 0.5791 | 0.7971 |
| No log | 5.0 | 425 | 0.6230 | 0.8059 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
