checkpoints_berturk – AI Model by hkizilhan | AlphaNeural AI

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hkizilhan/
checkpoints_berturk

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text-classification

generated_from_trainer

dbmdz/bert-base-turkish-cased

text-embeddings-inference

endpoints_compatible

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checkpoints_berturk

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: 0.1264
Accuracy: 0.9633
Macro F1: 0.9595

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
lr_scheduler_warmup_steps: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Macro F1
1.4009	1.0	32	1.1257	0.5413	0.5372
0.9029	2.0	64	0.6056	0.8257	0.8242
0.5490	3.0	96	0.1996	0.9725	0.9704
0.1897	4.0	128	0.1376	0.9633	0.9595
0.1026	5.0	160	0.1264	0.9633	0.9595

Framework versions

Transformers 5.10.2
Pytorch 2.11.0+cpu
Datasets 4.0.0
Tokenizers 0.22.2