metadata
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
model-index:
- name: results
results: []
datasets:
- turkish-nlp-suite/turkish-wikiNER
language:
- tr
berturk-ner
This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on turkish-nlp-suite/turkish-wikiNER dataset. It achieves the following results:
Validation Set
- Loss: 0.3693
- Accuracy: 0.9149
- F1: 0.9146
- Precision: 0.9167
- Recall: 0.9149
Test Set
- Accuracy: 0.9241
- F1: 0.8316
- Precision: 0.8341
- Recall: 0.8291
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: 0.0002
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Preicision | Recall |
|---|---|---|---|---|---|---|---|
| 0.5606 | 1.0 | 141 | 0.3018 | 0.9109 | 0.9107 | 0.9127 | 0.9109 |
| 0.2489 | 2.0 | 282 | 0.3185 | 0.9108 | 0.9089 | 0.9107 | 0.9108 |
| 0.1558 | 3.0 | 423 | 0.3378 | 0.9051 | 0.9028 | 0.9056 | 0.9051 |
| 0.0966 | 4.0 | 564 | 0.3472 | 0.9151 | 0.9149 | 0.9170 | 0.9151 |
| 0.0678 | 5.0 | 705 | 0.3693 | 0.9149 | 0.9146 | 0.9167 | 0.9149 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1