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umit_7allV3_full
Dataset:
https://www.kaggle.com/datasets/savasy/ttc4900
0:siyaset 1:dünya 2:ekonomi 3:kültür 4:saglik 5:spor 6:teknoloji
This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on given dataset. It achieves the following results on the evaluation set:
- Loss: 0.2934
- Accuracy: 0.9293
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2867 | 1.0 | 214 | 0.2880 | 0.9136 |
| 0.1672 | 2.0 | 428 | 0.2658 | 0.9327 |
| 0.0735 | 3.0 | 642 | 0.2934 | 0.9293 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
