metadata
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-tr-intent
results: []
bert-tr-intent
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: 1.0251
- Accuracy: 0.8686
- F1 Macro: 0.7074
- F1 Weighted: 0.8692
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: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| 0.7419 | 1.0 | 5604 | 0.7934 | 0.8591 | 0.6766 | 0.8597 |
| 0.38 | 2.0 | 11208 | 0.8155 | 0.8618 | 0.7012 | 0.8646 |
| 0.2601 | 3.0 | 16812 | 1.0251 | 0.8686 | 0.7074 | 0.8692 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.6.0+cu124
- Datasets 4.4.1
- Tokenizers 0.22.1