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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_TrainTestSplit_berturk_v2_24Feb
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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_TrainTestSplit_berturk_v2_24Feb
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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: 0.0003
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- Precision: 0.9999
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- Recall: 0.9999
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- F1: 0.9999
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- Accuracy: 0.9999
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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 | 196 | 0.0058 | 0.9982 | 0.9980 | 0.9981 | 0.9986 |
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| No log | 2.0 | 392 | 0.0042 | 0.9987 | 0.9986 | 0.9986 | 0.9990 |
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| 0.0132 | 3.0 | 588 | 0.0042 | 0.9985 | 0.9988 | 0.9986 | 0.9990 |
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| 0.0132 | 4.0 | 784 | 0.0022 | 0.9993 | 0.9992 | 0.9992 | 0.9993 |
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| 0.0132 | 5.0 | 980 | 0.0020 | 0.9993 | 0.9992 | 0.9993 | 0.9995 |
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| 0.0069 | 6.0 | 1176 | 0.0013 | 0.9994 | 0.9994 | 0.9994 | 0.9995 |
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| 0.0069 | 7.0 | 1372 | 0.0008 | 0.9997 | 0.9997 | 0.9997 | 0.9998 |
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| 0.0035 | 8.0 | 1568 | 0.0008 | 0.9997 | 0.9997 | 0.9997 | 0.9998 |
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| 0.0035 | 9.0 | 1764 | 0.0006 | 0.9996 | 0.9997 | 0.9996 | 0.9997 |
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| 0.0035 | 10.0 | 1960 | 0.0004 | 0.9998 | 0.9999 | 0.9998 | 0.9999 |
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| 0.0019 | 11.0 | 2156 | 0.0003 | 0.9999 | 0.9999 | 0.9999 | 0.9999 |
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| 0.0019 | 12.0 | 2352 | 0.0003 | 0.9999 | 0.9999 | 0.9999 | 0.9999 |
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| 0.0012 | 13.0 | 2548 | 0.0004 | 0.9999 | 0.9999 | 0.9999 | 0.9999 |
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| 0.0012 | 14.0 | 2744 | 0.0003 | 0.9999 | 0.9999 | 0.9999 | 0.9999 |
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| 0.0012 | 15.0 | 2940 | 0.0003 | 0.9999 | 0.9999 | 0.9999 | 0.9999 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.0
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- Tokenizers 0.13.2
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