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kobert-sentiment-analysis-restaurant
jin-soo/kobert-sentiment-analysis-restaurant
kobert-sentiment-analysis-restaurant is a text classification model from jin-soo. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Dec 26, 2025
- Updated
- Dec 27, 2025
- SHA
- ce22668a
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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. -->
kobert-sentiment-analysis-restaurant
This model is a fine-tuned version of skt/kobert-base-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0617
- Accuracy: 0.9861
- F1 Macro: 0.9861
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: 64
- eval_batch_size: 64
- 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 | F1 Macro |
|---|---|---|---|---|---|
| 0.1134 | 1.0 | 8490 | 0.1089 | 0.9666 | 0.9666 |
| 0.0644 | 2.0 | 16980 | 0.0721 | 0.9802 | 0.9802 |
| 0.032 | 3.0 | 25470 | 0.0617 | 0.9861 | 0.9861 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Dec 26, 2025
- Updated
- Dec 27, 2025