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ders-soru-uretici
helinakyildiz/ders-soru-uretici
ders-soru-uretici is a machine learning model from helinakyildiz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- mt5
- Access
- Public
- Created
- Jun 16, 2026
- Updated
- Jun 16, 2026
- SHA
- 554ceb9c
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. -->
ders-soru-uretici
This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2647
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.3663 | 0.2126 | 300 | 2.4418 |
| 2.6894 | 0.4252 | 600 | 2.1777 |
| 2.3458 | 0.6378 | 900 | 1.9197 |
| 2.2044 | 0.8505 | 1200 | 1.7413 |
| 1.8493 | 1.0631 | 1500 | 1.6080 |
| 1.7591 | 1.2757 | 1800 | 1.5205 |
| 1.7067 | 1.4883 | 2100 | 1.4153 |
| 1.5728 | 1.7009 | 2400 | 1.3224 |
| 1.4995 | 1.9135 | 2700 | 1.2258 |
| 1.2553 | 2.1262 | 3000 | 1.1618 |
| 1.2354 | 2.3388 | 3300 | 1.0915 |
| 1.1576 | 2.5514 | 3600 | 1.0160 |
| 1.1443 | 2.7640 | 3900 | 0.9424 |
| 1.1236 | 2.9766 | 4200 | 0.8838 |
| 0.9129 | 3.1892 | 4500 | 0.8344 |
| 0.9065 | 3.4018 | 4800 | 0.7887 |
| 0.8752 | 3.6145 | 5100 | 0.7340 |
| 0.8206 | 3.8271 | 5400 | 0.6945 |
| 0.7643 | 4.0397 | 5700 | 0.6396 |
| 0.6853 | 4.2523 | 6000 | 0.6001 |
| 0.6727 | 4.4649 | 6300 | 0.5610 |
| 0.6436 | 4.6775 | 6600 | 0.5249 |
| 0.6089 | 4.8901 | 6900 | 0.4907 |
| 0.5272 | 5.1028 | 7200 | 0.4541 |
| 0.5080 | 5.3154 | 7500 | 0.4338 |
| 0.5104 | 5.5280 | 7800 | 0.4078 |
| 0.4879 | 5.7406 | 8100 | 0.3836 |
| 0.4876 | 5.9532 | 8400 | 0.3607 |
| 0.4190 | 6.1658 | 8700 | 0.3432 |
| 0.4284 | 6.3785 | 9000 | 0.3269 |
| 0.4111 | 6.5911 | 9300 | 0.3130 |
| 0.3887 | 6.8037 | 9600 | 0.3000 |
| 0.3718 | 7.0163 | 9900 | 0.2863 |
| 0.3324 | 7.2289 | 10200 | 0.2785 |
| 0.3407 | 7.4415 | 10500 | 0.2731 |
| 0.3423 | 7.6541 | 10800 | 0.2673 |
| 0.3520 | 7.8668 | 11100 | 0.2655 |
| 0.3430 | 8.0 | 11288 | 0.2647 |
Framework versions
- Transformers 5.10.2
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Jun 16, 2026
- Updated
- Jun 16, 2026