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---
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
results: []
---
<!-- 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. -->
# results
This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3687
- Accuracy: 0.9130
## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8572 | 0.14 | 200 | 1.4831 | 0.4714 |
| 1.2551 | 0.27 | 400 | 0.9639 | 0.6684 |
| 0.886 | 0.41 | 600 | 0.7681 | 0.7507 |
| 0.7313 | 0.55 | 800 | 0.5526 | 0.8317 |
| 0.5804 | 0.69 | 1000 | 0.5308 | 0.8312 |
| 0.5407 | 0.82 | 1200 | 0.4486 | 0.8595 |
| 0.502 | 0.96 | 1400 | 0.5216 | 0.8516 |
| 0.3737 | 1.1 | 1600 | 0.4527 | 0.8763 |
| 0.3367 | 1.23 | 1800 | 0.4716 | 0.8544 |
| 0.3272 | 1.37 | 2000 | 0.3905 | 0.8862 |
| 0.2988 | 1.51 | 2200 | 0.3661 | 0.8926 |
| 0.298 | 1.64 | 2400 | 0.4301 | 0.8898 |
| 0.2856 | 1.78 | 2600 | 0.3944 | 0.8943 |
| 0.2832 | 1.92 | 2800 | 0.3608 | 0.8979 |
| 0.2483 | 2.06 | 3000 | 0.3757 | 0.8987 |
| 0.1699 | 2.19 | 3200 | 0.3802 | 0.9100 |
| 0.1433 | 2.33 | 3400 | 0.4144 | 0.9114 |
| 0.1826 | 2.47 | 3600 | 0.3533 | 0.9124 |
| 0.159 | 2.6 | 3800 | 0.3708 | 0.9107 |
| 0.1601 | 2.74 | 4000 | 0.3775 | 0.9118 |
| 0.1442 | 2.88 | 4200 | 0.3687 | 0.9130 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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