model_from_berturk_1401 – AI Model by Buseak | AlphaNeural AI

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model_from_berturk_1401

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token-classification

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autotrain_compatible

endpoints_compatible

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model_from_berturk_1401

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: 0.2702
Precision: 0.8979
Recall: 0.8911
F1: 0.8945
Accuracy: 0.9254

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	244	0.4037	0.8571	0.8504	0.8537	0.8950
No log	2.0	488	0.3194	0.8798	0.8741	0.8769	0.9126
0.6153	3.0	732	0.2787	0.8954	0.8862	0.8908	0.9230
0.6153	4.0	976	0.2702	0.8979	0.8911	0.8945	0.9254

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2