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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: model_from_berturk_Feb_5_TrainTestSplit
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# model_from_berturk_Feb_5_TrainTestSplit
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.3125
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- Precision: 0.9120
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- Recall: 0.9126
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- F1: 0.9123
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- Accuracy: 0.9376
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 185 | 0.2333 | 0.9065 | 0.9066 | 0.9066 | 0.9343 |
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| No log | 2.0 | 370 | 0.2115 | 0.9122 | 0.9143 | 0.9133 | 0.9389 |
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| 0.3861 | 3.0 | 555 | 0.2049 | 0.9185 | 0.9175 | 0.9180 | 0.9423 |
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| 0.3861 | 4.0 | 740 | 0.2073 | 0.9183 | 0.9185 | 0.9184 | 0.9420 |
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| 0.3861 | 5.0 | 925 | 0.2174 | 0.9150 | 0.9155 | 0.9153 | 0.9397 |
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| 0.1487 | 6.0 | 1110 | 0.2227 | 0.9177 | 0.9185 | 0.9181 | 0.9415 |
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| 0.1487 | 7.0 | 1295 | 0.2399 | 0.9149 | 0.9160 | 0.9155 | 0.9396 |
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| 0.1487 | 8.0 | 1480 | 0.2504 | 0.9158 | 0.9163 | 0.9160 | 0.9400 |
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| 0.0942 | 9.0 | 1665 | 0.2692 | 0.9141 | 0.9152 | 0.9146 | 0.9392 |
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| 0.0942 | 10.0 | 1850 | 0.2782 | 0.9130 | 0.9153 | 0.9141 | 0.9388 |
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| 0.0589 | 11.0 | 2035 | 0.2908 | 0.9131 | 0.9144 | 0.9138 | 0.9388 |
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| 0.0589 | 12.0 | 2220 | 0.2940 | 0.9121 | 0.9136 | 0.9128 | 0.9377 |
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| 0.0589 | 13.0 | 2405 | 0.3068 | 0.9117 | 0.9130 | 0.9123 | 0.9376 |
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| 0.0407 | 14.0 | 2590 | 0.3107 | 0.9132 | 0.9148 | 0.9140 | 0.9387 |
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| 0.0407 | 15.0 | 2775 | 0.3125 | 0.9120 | 0.9126 | 0.9123 | 0.9376 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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