| | --- |
| | license: mit |
| | base_model: burakaytan/roberta-base-turkish-uncased |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: laptop_kriter |
| | 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. --> |
| |
|
| | # laptop_kriter |
| | |
| | This model is a fine-tuned version of [burakaytan/roberta-base-turkish-uncased](https://huggingface.co/burakaytan/roberta-base-turkish-uncased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2151 |
| | - F1: 0.7709 |
| | - Roc Auc: 0.8574 |
| | - Accuracy: 0.7344 |
| | |
| | ## 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: 2 |
| | - eval_batch_size: 2 |
| | - 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 | F1 | Roc Auc | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:| |
| | | 0.3066 | 1.0 | 1151 | 0.2457 | 0.5688 | 0.7257 | 0.6484 | |
| | | 0.2325 | 2.0 | 2302 | 0.2088 | 0.6630 | 0.7908 | 0.6719 | |
| | | 0.1723 | 3.0 | 3453 | 0.2023 | 0.6933 | 0.8174 | 0.6875 | |
| | | 0.159 | 4.0 | 4604 | 0.2004 | 0.7312 | 0.8363 | 0.7188 | |
| | | 0.1306 | 5.0 | 5755 | 0.2138 | 0.7168 | 0.8104 | 0.7148 | |
| | | 0.1034 | 6.0 | 6906 | 0.2103 | 0.7745 | 0.8641 | 0.7539 | |
| | | 0.0865 | 7.0 | 8057 | 0.2107 | 0.7684 | 0.8530 | 0.75 | |
| | | 0.0733 | 8.0 | 9208 | 0.2099 | 0.7757 | 0.8663 | 0.7383 | |
| | | 0.0643 | 9.0 | 10359 | 0.2130 | 0.7772 | 0.8586 | 0.7539 | |
| | | 0.0617 | 10.0 | 11510 | 0.2151 | 0.7709 | 0.8574 | 0.7344 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.37.0 |
| | - Pytorch 2.1.0+cu121 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.0 |
| | |
