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indobert-base-uncased-bloom-difficulty-prediction
hawalurahman/indobert-base-uncased-bloom-difficulty-prediction
indobert-base-uncased-bloom-difficulty-prediction is a text classification model from hawalurahman. 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
- Jun 12, 2026
- Updated
- Jun 12, 2026
- SHA
- 85982cd0
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Base models
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-base-uncased-bloom-difficulty-prediction
This model is a fine-tuned version of indolem/indobert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7238
- Accuracy: 0.4938
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2038 | 1.0 | 24 | 2.0037 | 0.3312 |
| 1.9734 | 2.0 | 48 | 1.8380 | 0.4688 |
| 1.8189 | 3.0 | 72 | 1.7806 | 0.4625 |
| 1.7607 | 4.0 | 96 | 1.7308 | 0.4938 |
| 1.7105 | 5.0 | 120 | 1.7238 | 0.4938 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu129
- Datasets 4.2.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026