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v6_balanced_dataset_fine-tuning-java-indo-sentiment-analysist-3-class
johannawawi/v6_balanced_dataset_fine-tuning-java-indo-sentiment-analysist-3-class
v6_balanced_dataset_fine-tuning-java-indo-sentiment-analysist-3-class is a text classification model from johannawawi. 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
- roberta
- Access
- Public
- Created
- May 16, 2025
- Updated
- May 16, 2025
- SHA
- 3e53327f
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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. -->
results_final
This model is a fine-tuned version of w11wo/indonesian-roberta-base-sentiment-classifier on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3507
- Accuracy: 0.9056
- F1 Macro: 0.9055
- F1 Weighted: 0.9055
- Precision Macro: 0.9057
- Recall Macro: 0.9056
- Precision Weighted: 0.9057
- Recall Weighted: 0.9056
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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Precision Weighted | Recall Weighted |
|---|---|---|---|---|---|---|---|---|---|---|
| 0.4024 | 1.8519 | 500 | 0.2951 | 0.9 | 0.9002 | 0.9002 | 0.9011 | 0.9000 | 0.9011 | 0.9 |
| 0.3394 | 3.7037 | 1000 | 0.3384 | 0.8944 | 0.8946 | 0.8946 | 0.8960 | 0.8944 | 0.8960 | 0.8944 |
| 0.2395 | 5.5556 | 1500 | 0.3507 | 0.9056 | 0.9055 | 0.9055 | 0.9057 | 0.9056 | 0.9057 | 0.9056 |
| 0.2222 | 7.4074 | 2000 | 0.3621 | 0.9 | 0.9000 | 0.9000 | 0.9003 | 0.9 | 0.9003 | 0.9 |
| 0.1813 | 9.2593 | 2500 | 0.3718 | 0.8963 | 0.8963 | 0.8963 | 0.8963 | 0.8963 | 0.8963 | 0.8963 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- May 16, 2025
- Updated
- May 16, 2025