model_from_berturk_Feb_5_TrainTestSplit – AI Model by Buseak | AlphaNeural AI

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model_from_berturk_Feb_5_TrainTestSplit

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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model_from_berturk_Feb_5_TrainTestSplit

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: 0.3125
Precision: 0.9120
Recall: 0.9126
F1: 0.9123
Accuracy: 0.9376

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	185	0.2333	0.9065	0.9066	0.9066	0.9343
No log	2.0	370	0.2115	0.9122	0.9143	0.9133	0.9389
0.3861	3.0	555	0.2049	0.9185	0.9175	0.9180	0.9423
0.3861	4.0	740	0.2073	0.9183	0.9185	0.9184	0.9420
0.3861	5.0	925	0.2174	0.9150	0.9155	0.9153	0.9397
0.1487	6.0	1110	0.2227	0.9177	0.9185	0.9181	0.9415
0.1487	7.0	1295	0.2399	0.9149	0.9160	0.9155	0.9396
0.1487	8.0	1480	0.2504	0.9158	0.9163	0.9160	0.9400
0.0942	9.0	1665	0.2692	0.9141	0.9152	0.9146	0.9392
0.0942	10.0	1850	0.2782	0.9130	0.9153	0.9141	0.9388
0.0589	11.0	2035	0.2908	0.9131	0.9144	0.9138	0.9388
0.0589	12.0	2220	0.2940	0.9121	0.9136	0.9128	0.9377
0.0589	13.0	2405	0.3068	0.9117	0.9130	0.9123	0.9376
0.0407	14.0	2590	0.3107	0.9132	0.9148	0.9140	0.9387
0.0407	15.0	2775	0.3125	0.9120	0.9126	0.9123	0.9376

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2