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turkish-sentiment4
dexter231/turkish-sentiment4
turkish-sentiment4 is a text classification model from dexter231. 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
- modernbert
- Access
- Public
- Created
- Nov 10, 2025
- Updated
- Nov 19, 2025
- SHA
- 280bb395
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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. -->
turkish-sentiment4
This model is a fine-tuned version of artiwise-ai/modernbert-base-tr-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1083
- Accuracy: 0.9615
- F1 Macro: 0.9351
- F1 Weighted: 0.9612
- Precision Macro: 0.9415
- Recall Macro: 0.9291
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: 16
- eval_batch_size: 16
- 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: linear
- lr_scheduler_warmup_steps: 400
- training_steps: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|---|
| 0.1987 | 0.0073 | 200 | 0.1654 | 0.9400 | 0.9074 | 0.9413 | 0.8944 | 0.9236 |
| 0.1978 | 0.0145 | 400 | 0.1653 | 0.9407 | 0.9092 | 0.9427 | 0.8938 | 0.9303 |
| 0.1444 | 0.0218 | 600 | 0.1572 | 0.9520 | 0.9157 | 0.9502 | 0.9425 | 0.8957 |
| 0.1446 | 0.0290 | 800 | 0.1252 | 0.9560 | 0.9239 | 0.9549 | 0.9407 | 0.9101 |
| 0.1067 | 0.0363 | 1000 | 0.1389 | 0.9574 | 0.9294 | 0.9574 | 0.9313 | 0.9275 |
| 0.1333 | 0.0436 | 1200 | 0.1244 | 0.9587 | 0.9279 | 0.9576 | 0.9464 | 0.9128 |
| 0.0935 | 0.0508 | 1400 | 0.1297 | 0.9596 | 0.9336 | 0.9598 | 0.9309 | 0.9365 |
| 0.1072 | 0.0581 | 1600 | 0.1196 | 0.9604 | 0.9309 | 0.9593 | 0.9497 | 0.9156 |
| 0.1235 | 0.0654 | 1800 | 0.1121 | 0.9613 | 0.9338 | 0.9607 | 0.9450 | 0.9240 |
| 0.1097 | 0.0726 | 2000 | 0.1083 | 0.9615 | 0.9351 | 0.9612 | 0.9415 | 0.9291 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- mit
- Created
- Nov 10, 2025
- Updated
- Nov 19, 2025