Downloads · 30 days
11
8% of all-time downloads
indobert-ai-text-classification
PlatinaSB/indobert-ai-text-classification
indobert-ai-text-classification is a text classification model from PlatinaSB. 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. --
All-time downloads
141
Public
Parameters
111M
3.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors442 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Apr 29, 2026
- Updated
- Aug 16, 2026
- SHA
- d296ab63
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-ai-text-classification
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: 0.4725
- Accuracy: 0.9251
- Precision: 0.8796
- Recall: 0.9851
- F1: 0.9293
- Roc Auc: 0.9251
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: 8
- eval_batch_size: 8
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 0.1721 | 1.0 | 2465 | 0.3069 | 0.9326 | 0.9018 | 0.9709 | 0.9351 | 0.9326 |
| 0.1483 | 2.0 | 4930 | 0.4678 | 0.9188 | 0.8686 | 0.9870 | 0.9240 | 0.9188 |
| 0.0749 | 3.0 | 7395 | 0.4725 | 0.9251 | 0.8796 | 0.9851 | 0.9293 | 0.9251 |
Framework versions
- Transformers 5.5.4
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- id
- Created
- Apr 29, 2026
- Updated
- Aug 16, 2026