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---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: murat_5e-05_4_10_categorize
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. -->
# murat_5e-05_4_10_categorize
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: 0.8692
- Precision: 0.1736
- Recall: 0.2509
- F1: 0.2052
- Accuracy: 0.8592
## 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
- optimizer: Use 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_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.34 | 1.0 | 685 | 0.3619 | 0.2368 | 0.0526 | 0.0861 | 0.9143 |
| 0.2437 | 2.0 | 1370 | 0.3131 | 0.1412 | 0.2164 | 0.1709 | 0.9130 |
| 0.1881 | 3.0 | 2055 | 0.3078 | 0.1648 | 0.1754 | 0.1700 | 0.9212 |
| 0.078 | 4.0 | 2740 | 0.4330 | 0.1788 | 0.1871 | 0.1829 | 0.9116 |
| 0.1051 | 5.0 | 3425 | 0.4202 | 0.1782 | 0.2105 | 0.1930 | 0.9157 |
| 0.0583 | 6.0 | 4110 | 0.4818 | 0.1780 | 0.1988 | 0.1878 | 0.9154 |
| 0.0321 | 7.0 | 4795 | 0.5147 | 0.1857 | 0.2281 | 0.2047 | 0.9137 |
| 0.0211 | 8.0 | 5480 | 0.5777 | 0.2071 | 0.2047 | 0.2059 | 0.9154 |
| 0.0189 | 9.0 | 6165 | 0.5808 | 0.2074 | 0.2281 | 0.2173 | 0.9149 |
| 0.0089 | 10.0 | 6850 | 0.5985 | 0.2021 | 0.2222 | 0.2117 | 0.9152 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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