berturk-cased-keyword-discriminator – AI Model by yanekyuk | AlphaNeural AI

You can deploy this model and start earning money today!

yanekyuk/
berturk-cased-keyword-discriminator

like

0

token-classification

generated_from_trainer

dbmdz/bert-base-turkish-cased

autotrain_compatible

endpoints_compatible

Views

No views yet

berturk-keyword-discriminator

This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4196
Precision: 0.6729
Recall: 0.6904
Accuracy: 0.9163
F1: 0.6815
Ent/precision: 0.6776
Ent/accuracy: 0.7365
Ent/f1: 0.7058
Con/precision: 0.6640
Con/accuracy: 0.6151
Con/f1: 0.6386

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	Accuracy	F1	Ent/precision	Ent/accuracy	Ent/f1	Con/precision	Con/accuracy	Con/f1
0.1899	1.0	1875	0.1927	0.6330	0.6682	0.9163	0.6502	0.6283	0.7398	0.6795	0.6438	0.5513	0.5940
0.137	2.0	3750	0.1988	0.6405	0.6959	0.9160	0.6671	0.6461	0.7475	0.6931	0.6297	0.6116	0.6205
0.101	3.0	5625	0.2375	0.6494	0.7188	0.9173	0.6824	0.6497	0.7743	0.7066	0.6488	0.6281	0.6383
0.0767	4.0	7500	0.2699	0.6533	0.7188	0.9154	0.6845	0.6575	0.7741	0.7111	0.6449	0.6285	0.6366
0.057	5.0	9375	0.3188	0.6696	0.6914	0.9163	0.6803	0.6790	0.7405	0.7084	0.6518	0.6112	0.6308
0.0423	6.0	11250	0.3646	0.6773	0.6846	0.9171	0.6809	0.6787	0.7388	0.7075	0.6746	0.5959	0.6328
0.0339	7.0	13125	0.4007	0.6711	0.6816	0.9151	0.6763	0.6782	0.7283	0.7023	0.6575	0.6055	0.6304
0.0282	8.0	15000	0.4196	0.6729	0.6904	0.9163	0.6815	0.6776	0.7365	0.7058	0.6640	0.6151	0.6386

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1