metadata
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: text-mod-token-classification-40000-finetuned-ner
results: []
text-mod-token-classification-40000-finetuned-ner
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: 0.0525
- Accuracy: 0.9880
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.037 | 1.0 | 143 | 0.0627 | 0.9754 |
| 0.0191 | 2.0 | 286 | 0.0560 | 0.9788 |
| 0.0343 | 3.0 | 429 | 0.0495 | 0.9840 |
| 0.0082 | 4.0 | 572 | 0.0478 | 0.9853 |
| 0.0066 | 5.0 | 715 | 0.0504 | 0.9882 |
| 0.0012 | 6.0 | 858 | 0.0525 | 0.9880 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3