DijitalSessizlik-BERT-Modeli – AI Model by Scaran | AlphaNeural AI | AlphaNeural AI

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Scaran/
DijitalSessizlik-BERT-Modeli

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text-classification

generated_from_trainer

dbmdz/bert-base-turkish-cased

endpoints_compatible

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results

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: 0.4758
Accuracy: 0.812
F1 Macro: 0.6908
Precision Macro: 0.6945
Recall Macro: 0.6920

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: 16
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: 500
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Precision Macro	Recall Macro
0.67	1.0	250	0.5301	0.782	0.6312	0.6490	0.6187
0.4378	2.0	500	0.5178	0.783	0.5908	0.6849	0.6581
0.3296	3.0	750	0.4758	0.812	0.6908	0.6945	0.6920

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1