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sabanci-it-destek-v2
denizzay/sabanci-it-destek-v2
sabanci-it-destek-v2 is a text classification model from denizzay. 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
- Jan 14, 2026
- Updated
- Jan 15, 2026
- SHA
- 66fc4bb0
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. -->
Sabanci-IT-Destek-v2
This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1084
- Accuracy: 0.8131
- F1: 0.8114
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: 16
- eval_batch_size: 16
- 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 422 | 4.0712 | 0.0383 | 0.0360 |
| 4.2799 | 2.0 | 844 | 3.3001 | 0.3098 | 0.2829 |
| 3.6351 | 3.0 | 1266 | 2.3719 | 0.5754 | 0.5485 |
| 2.6628 | 4.0 | 1688 | 1.7979 | 0.6600 | 0.6509 |
| 1.8814 | 5.0 | 2110 | 1.5134 | 0.7042 | 0.6993 |
| 1.3619 | 6.0 | 2532 | 1.2919 | 0.7403 | 0.7257 |
| 1.3619 | 7.0 | 2954 | 1.1487 | 0.7344 | 0.7301 |
| 0.9968 | 8.0 | 3376 | 1.1233 | 0.7609 | 0.7568 |
| 0.7387 | 9.0 | 3798 | 1.0679 | 0.7712 | 0.7688 |
| 0.5883 | 10.0 | 4220 | 1.0569 | 0.7763 | 0.7680 |
| 0.4789 | 11.0 | 4642 | 1.0722 | 0.7873 | 0.7802 |
| 0.4034 | 12.0 | 5064 | 1.0593 | 0.7918 | 0.7883 |
| 0.4034 | 13.0 | 5486 | 1.0518 | 0.7859 | 0.7792 |
| 0.3146 | 14.0 | 5908 | 1.0920 | 0.7910 | 0.7851 |
| 0.2744 | 15.0 | 6330 | 1.0781 | 0.8035 | 0.7984 |
| 0.243 | 16.0 | 6752 | 1.0820 | 0.8072 | 0.8010 |
| 0.2105 | 17.0 | 7174 | 1.1077 | 0.8065 | 0.8030 |
| 0.1966 | 18.0 | 7596 | 1.1005 | 0.8138 | 0.8110 |
| 0.1774 | 19.0 | 8018 | 1.1022 | 0.8138 | 0.8114 |
| 0.1774 | 20.0 | 8440 | 1.1084 | 0.8131 | 0.8114 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- tr
- Created
- Jan 14, 2026
- Updated
- Jan 15, 2026