| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: model_from_berturk_Feb_5_TrainTestSplit |
| | 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. --> |
| |
|
| | # model_from_berturk_Feb_5_TrainTestSplit |
| | |
| | This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3125 |
| | - Precision: 0.9120 |
| | - Recall: 0.9126 |
| | - F1: 0.9123 |
| | - Accuracy: 0.9376 |
| | |
| | ## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 15 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | | No log | 1.0 | 185 | 0.2333 | 0.9065 | 0.9066 | 0.9066 | 0.9343 | |
| | | No log | 2.0 | 370 | 0.2115 | 0.9122 | 0.9143 | 0.9133 | 0.9389 | |
| | | 0.3861 | 3.0 | 555 | 0.2049 | 0.9185 | 0.9175 | 0.9180 | 0.9423 | |
| | | 0.3861 | 4.0 | 740 | 0.2073 | 0.9183 | 0.9185 | 0.9184 | 0.9420 | |
| | | 0.3861 | 5.0 | 925 | 0.2174 | 0.9150 | 0.9155 | 0.9153 | 0.9397 | |
| | | 0.1487 | 6.0 | 1110 | 0.2227 | 0.9177 | 0.9185 | 0.9181 | 0.9415 | |
| | | 0.1487 | 7.0 | 1295 | 0.2399 | 0.9149 | 0.9160 | 0.9155 | 0.9396 | |
| | | 0.1487 | 8.0 | 1480 | 0.2504 | 0.9158 | 0.9163 | 0.9160 | 0.9400 | |
| | | 0.0942 | 9.0 | 1665 | 0.2692 | 0.9141 | 0.9152 | 0.9146 | 0.9392 | |
| | | 0.0942 | 10.0 | 1850 | 0.2782 | 0.9130 | 0.9153 | 0.9141 | 0.9388 | |
| | | 0.0589 | 11.0 | 2035 | 0.2908 | 0.9131 | 0.9144 | 0.9138 | 0.9388 | |
| | | 0.0589 | 12.0 | 2220 | 0.2940 | 0.9121 | 0.9136 | 0.9128 | 0.9377 | |
| | | 0.0589 | 13.0 | 2405 | 0.3068 | 0.9117 | 0.9130 | 0.9123 | 0.9376 | |
| | | 0.0407 | 14.0 | 2590 | 0.3107 | 0.9132 | 0.9148 | 0.9140 | 0.9387 | |
| | | 0.0407 | 15.0 | 2775 | 0.3125 | 0.9120 | 0.9126 | 0.9123 | 0.9376 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.0 |
| | - Pytorch 1.13.1+cu116 |
| | - Datasets 2.9.0 |
| | - Tokenizers 0.13.2 |
| | |
