| license: mit | |
| base_model: dbmdz/bert-base-turkish-uncased | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: results | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # results | |
| This model is a fine-tuned version of [dbmdz/bert-base-turkish-uncased](https://huggingface.co/dbmdz/bert-base-turkish-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0063 | |
| - Accuracy: 0.9984 | |
| - F1: 0.9988 | |
| - Precision: 0.9995 | |
| - Recall: 0.9980 | |
| ## 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: 5e-05 | |
| - train_batch_size: 128 | |
| - eval_batch_size: 128 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 512 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_ratio: 0.03 | |
| - num_epochs: 2 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | 0.0659 | 1.0 | 169 | 0.0076 | 0.9978 | 0.9983 | 0.9975 | 0.9990 | | |
| | 0.004 | 2.0 | 338 | 0.0063 | 0.9984 | 0.9988 | 0.9995 | 0.9980 | | |
| ### Framework versions | |
| - Transformers 4.42.4 | |
| - Pytorch 2.3.0+cu121 | |
| - Datasets 2.20.0 | |
| - Tokenizers 0.19.1 | |