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sonuclar – AI Model by Sanarin1334 | AlphaNeural AI
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Sanarin1334
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sonuclar
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transformers
safetensors
bert
text-classification
generated_from_trainer
dbmdz/bert-base-turkish-cased
finetune
mit
endpoints_compatible
us
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sonuclar
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: 0.2497
Accuracy: 0.9236
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: 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
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2599
1.0
1089
0.2497
0.9236
0.1837
2.0
2178
0.2735
0.9302
0.1164
3.0
3267
0.2858
0.9318
Framework versions
Transformers 4.57.3
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
