model_TrainTestSplit_berturk_v2_24Feb

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: 0.0003
• Precision: 0.9999
• Recall: 0.9999
• F1: 0.9999
• Accuracy: 0.9999

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	196	0.0058	0.9982	0.9980	0.9981	0.9986
No log	2.0	392	0.0042	0.9987	0.9986	0.9986	0.9990
0.0132	3.0	588	0.0042	0.9985	0.9988	0.9986	0.9990
0.0132	4.0	784	0.0022	0.9993	0.9992	0.9992	0.9993
0.0132	5.0	980	0.0020	0.9993	0.9992	0.9993	0.9995
0.0069	6.0	1176	0.0013	0.9994	0.9994	0.9994	0.9995
0.0069	7.0	1372	0.0008	0.9997	0.9997	0.9997	0.9998
0.0035	8.0	1568	0.0008	0.9997	0.9997	0.9997	0.9998
0.0035	9.0	1764	0.0006	0.9996	0.9997	0.9996	0.9997
0.0035	10.0	1960	0.0004	0.9998	0.9999	0.9998	0.9999
0.0019	11.0	2156	0.0003	0.9999	0.9999	0.9999	0.9999
0.0019	12.0	2352	0.0003	0.9999	0.9999	0.9999	0.9999
0.0012	13.0	2548	0.0004	0.9999	0.9999	0.9999	0.9999
0.0012	14.0	2744	0.0003	0.9999	0.9999	0.9999	0.9999
0.0012	15.0	2940	0.0003	0.9999	0.9999	0.9999	0.9999

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.0
• Tokenizers 0.13.2