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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: gpt_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. -->
# gpt_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: 0.9790
- Precision: 0.2163
- Recall: 0.3439
- F1: 0.2656
- Accuracy: 0.8541
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.3889 | 1.0 | 1151 | 0.4005 | 0.1733 | 0.1860 | 0.1794 | 0.8792 |
| 0.3552 | 2.0 | 2302 | 0.4328 | 0.1560 | 0.2229 | 0.1836 | 0.8549 |
| 0.2336 | 3.0 | 3453 | 0.4759 | 0.1595 | 0.2151 | 0.1832 | 0.8681 |
| 0.1549 | 4.0 | 4604 | 0.5553 | 0.1601 | 0.2132 | 0.1829 | 0.8703 |
| 0.0994 | 5.0 | 5755 | 0.6101 | 0.1893 | 0.2539 | 0.2169 | 0.8722 |
| 0.0727 | 6.0 | 6906 | 0.6757 | 0.2049 | 0.2422 | 0.2220 | 0.8727 |
| 0.0509 | 7.0 | 8057 | 0.7397 | 0.2054 | 0.2519 | 0.2263 | 0.8703 |
| 0.0339 | 8.0 | 9208 | 0.8222 | 0.2388 | 0.2578 | 0.2479 | 0.8788 |
| 0.0249 | 9.0 | 10359 | 0.8676 | 0.2309 | 0.2752 | 0.2511 | 0.8736 |
| 0.0122 | 10.0 | 11510 | 0.8985 | 0.2432 | 0.2752 | 0.2582 | 0.8777 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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