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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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