metadata

library_name: transformers
license: mit
base_model: akdeniz27/bert-base-turkish-cased-ner
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: bert-base-turkish-cased-ner-finetuned-ner
    results: []

bert-base-turkish-cased-ner-finetuned-ner

This model is a fine-tuned version of akdeniz27/bert-base-turkish-cased-ner on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2379
Precision: 0.9707
Recall: 0.9708
F1: 0.9708
Accuracy: 0.9729

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: 1e-05
train_batch_size: 6
eval_batch_size: 6
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1631	1.0	3334	0.1465	0.9620	0.9627	0.9624	0.9651
0.1162	2.0	6668	0.1524	0.9659	0.9655	0.9657	0.9683
0.0938	3.0	10002	0.1452	0.9686	0.9691	0.9688	0.9712
0.048	4.0	13336	0.1734	0.9698	0.9697	0.9698	0.9719
0.0359	5.0	16670	0.1810	0.9701	0.9703	0.9702	0.9723
0.0274	6.0	20004	0.1941	0.9713	0.9713	0.9713	0.9734
0.0187	7.0	23338	0.2185	0.9700	0.9700	0.9700	0.9722
0.0229	8.0	26672	0.2265	0.9706	0.9707	0.9707	0.9728
0.015	9.0	30006	0.2325	0.9706	0.9705	0.9706	0.9729
0.009	10.0	33340	0.2379	0.9707	0.9708	0.9708	0.9729

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1