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---
library_name: transformers
license: mit
base_model: akdeniz27/bert-base-turkish-cased-ner
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-turkish-cased-ner-finetuned-ner
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. -->
# bert-base-turkish-cased-ner-finetuned-ner
This model is a fine-tuned version of [akdeniz27/bert-base-turkish-cased-ner](https://huggingface.co/akdeniz27/bert-base-turkish-cased-ner) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2379
- Precision: 0.9707
- Recall: 0.9708
- F1: 0.9708
- Accuracy: 0.9729
## 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: 1e-05
- train_batch_size: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1631 | 1.0 | 3334 | 0.1465 | 0.9620 | 0.9627 | 0.9624 | 0.9651 |
| 0.1162 | 2.0 | 6668 | 0.1524 | 0.9659 | 0.9655 | 0.9657 | 0.9683 |
| 0.0938 | 3.0 | 10002 | 0.1452 | 0.9686 | 0.9691 | 0.9688 | 0.9712 |
| 0.048 | 4.0 | 13336 | 0.1734 | 0.9698 | 0.9697 | 0.9698 | 0.9719 |
| 0.0359 | 5.0 | 16670 | 0.1810 | 0.9701 | 0.9703 | 0.9702 | 0.9723 |
| 0.0274 | 6.0 | 20004 | 0.1941 | 0.9713 | 0.9713 | 0.9713 | 0.9734 |
| 0.0187 | 7.0 | 23338 | 0.2185 | 0.9700 | 0.9700 | 0.9700 | 0.9722 |
| 0.0229 | 8.0 | 26672 | 0.2265 | 0.9706 | 0.9707 | 0.9707 | 0.9728 |
| 0.015 | 9.0 | 30006 | 0.2325 | 0.9706 | 0.9705 | 0.9706 | 0.9729 |
| 0.009 | 10.0 | 33340 | 0.2379 | 0.9707 | 0.9708 | 0.9708 | 0.9729 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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