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kvkk-ner-bert-turkish – AI Model by btniq | AlphaNeural AI
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btniq
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kvkk-ner-bert-turkish
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transformers
safetensors
bert
token-classification
ner
kvkk
turkish
pii-detection
tr
generated_from_trainer
dbmdz/bert-base-turkish-cased
finetune
mit
endpoints_compatible
us
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kvkk-ner-bert-turkish
This model is a fine-tuned version of
dbmdz/bert-base-turkish-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0802
Precision: 0.9152
Recall: 0.9203
F1: 0.9177
Accuracy: 0.9759
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.1429
1.0
3246
0.0861
0.8965
0.9167
0.9065
0.9732
0.0970
2.0
6492
0.0958
0.9100
0.9095
0.9097
0.9730
0.0716
3.0
9738
0.1025
0.9059
0.9100
0.9079
0.9724
Framework versions
Transformers 5.5.4
Pytorch 2.11.0+cu130
Datasets 4.8.4
Tokenizers 0.22.2
