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indobert-emotion-large-bestfold
Alfanatasya/indobert-emotion-large-bestfold
indobert-emotion-large-bestfold is a text classification model from Alfanatasya. 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 3, 2025
- Updated
- Jun 4, 2025
- SHA
- 28433f85
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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-emotion-large-bestfold
This model is a fine-tuned version of indobenchmark/indobert-large-p1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1461
- Accuracy: 0.8136
- Precision: 0.8217
- Recall: 0.8202
- F1: 0.8182
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAFACTOR and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7344 | 1.0 | 124 | 0.6277 | 0.7886 | 0.8181 | 0.7991 | 0.8033 |
| 0.3657 | 2.0 | 248 | 0.6067 | 0.7886 | 0.8010 | 0.7906 | 0.7916 |
| 0.1533 | 3.0 | 372 | 0.8513 | 0.775 | 0.7876 | 0.7875 | 0.7863 |
| 0.0766 | 4.0 | 496 | 1.1461 | 0.8136 | 0.8217 | 0.8202 | 0.8182 |
| 0.056 | 5.0 | 620 | 1.3434 | 0.7909 | 0.8091 | 0.8061 | 0.8027 |
| 0.0274 | 6.0 | 744 | 1.3658 | 0.7955 | 0.8029 | 0.8037 | 0.8028 |
| 0.0155 | 7.0 | 868 | 1.3065 | 0.8114 | 0.8233 | 0.8194 | 0.8179 |
| 0.0148 | 8.0 | 992 | 1.4321 | 0.8114 | 0.8223 | 0.8258 | 0.8199 |
| 0.004 | 9.0 | 1116 | 1.3645 | 0.8068 | 0.8173 | 0.8135 | 0.8144 |
| 0.0147 | 10.0 | 1240 | 1.4823 | 0.8091 | 0.8152 | 0.8191 | 0.8148 |
| 0.0003 | 11.0 | 1364 | 1.4669 | 0.7977 | 0.8047 | 0.8093 | 0.8065 |
| 0.0045 | 12.0 | 1488 | 1.5087 | 0.8091 | 0.8252 | 0.8167 | 0.8194 |
| 0.0002 | 13.0 | 1612 | 1.5367 | 0.8045 | 0.8201 | 0.8141 | 0.8158 |
| 0.0034 | 14.0 | 1736 | 1.5464 | 0.8114 | 0.8266 | 0.8198 | 0.8217 |
| 0.0032 | 15.0 | 1860 | 1.5602 | 0.8 | 0.8055 | 0.8112 | 0.8079 |
| 0.0004 | 16.0 | 1984 | 1.5832 | 0.8068 | 0.8237 | 0.8167 | 0.8184 |
| 0.0023 | 17.0 | 2108 | 1.5886 | 0.8023 | 0.8165 | 0.8121 | 0.8128 |
| 0.0 | 18.0 | 2232 | 1.5907 | 0.8023 | 0.8165 | 0.8121 | 0.8128 |
| 0.0003 | 19.0 | 2356 | 1.5958 | 0.8045 | 0.8199 | 0.8141 | 0.8154 |
| 0.0001 | 20.0 | 2480 | 1.5966 | 0.8045 | 0.8199 | 0.8141 | 0.8154 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Jun 3, 2025
- Updated
- Jun 4, 2025