turkish-hs-target-prediction

This model is a fine-tuned version of dbmdz/bert-base-turkish-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.2668
• F1: 0.7805
• Roc Auc: 0.8458
• Accuracy: 0.7403

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-06
• train_batch_size: 48
• eval_batch_size: 20
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.4848	0.4348	100	0.4292	0.5819	0.7133	0.5283
0.3992	0.8696	200	0.3402	0.7118	0.7908	0.6311
0.3272	1.3043	300	0.3015	0.7529	0.8218	0.6857
0.3005	1.7391	400	0.2821	0.7684	0.8348	0.7124
0.2771	2.1739	500	0.2802	0.7749	0.8401	0.7251
0.2666	2.6087	600	0.2693	0.7746	0.8406	0.7263
0.2668	3.0435	700	0.2653	0.7766	0.8414	0.7365
0.2482	3.4783	800	0.2691	0.7715	0.8389	0.7213
0.2457	3.9130	900	0.2615	0.7767	0.8432	0.7359
0.2327	4.3478	1000	0.2616	0.7789	0.8443	0.7435
0.2299	4.7826	1100	0.2625	0.7768	0.8419	0.7302
0.2203	5.2174	1200	0.2612	0.7844	0.8480	0.7441
0.2164	5.6522	1300	0.2586	0.7859	0.8492	0.7505
0.2152	6.0870	1400	0.2649	0.7760	0.8422	0.7384
0.209	6.5217	1500	0.2635	0.7769	0.8424	0.7410
0.2085	6.9565	1600	0.2661	0.7819	0.8470	0.7371
0.2052	7.3913	1700	0.2651	0.7798	0.8451	0.7378
0.1983	7.8261	1800	0.2640	0.7860	0.8494	0.7467
0.1946	8.2609	1900	0.2666	0.7852	0.8489	0.7454
0.192	8.6957	2000	0.2667	0.7826	0.8474	0.7422
0.1965	9.1304	2100	0.2662	0.7804	0.8455	0.7416
0.1924	9.5652	2200	0.2668	0.7801	0.8458	0.7435
0.1854	10.0	2300	0.2668	0.7805	0.8458	0.7403

Framework versions

• Transformers 4.49.0
• Pytorch 2.5.1+cu124
• Datasets 3.3.2
• Tokenizers 0.21.0