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README.md
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---
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base_model: neuralsentry/starencoder-git-commits-mlm
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: vulnfixClassification-StarEncoder-DCMB
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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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# vulnfixClassification-StarEncoder-DCMB
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This model is a fine-tuned version of [neuralsentry/starencoder-git-commits-mlm](https://huggingface.co/neuralsentry/starencoder-git-commits-mlm) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1797
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- Accuracy: 0.9770
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- Precision: 0.9841
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- Recall: 0.9714
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- F1: 0.9777
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- Roc Auc: 0.9772
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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: 0.0001
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- train_batch_size: 128
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- eval_batch_size: 128
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- seed: 420
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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: 10.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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| 0.2106 | 1.0 | 219 | 0.1196 | 0.9640 | 0.9654 | 0.9654 | 0.9654 | 0.9639 |
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| 0.086 | 2.0 | 438 | 0.0883 | 0.9736 | 0.9859 | 0.9629 | 0.9743 | 0.9740 |
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| 0.0477 | 3.0 | 657 | 0.0944 | 0.9729 | 0.9776 | 0.9700 | 0.9738 | 0.9730 |
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| 0.0269 | 4.0 | 876 | 0.1215 | 0.9723 | 0.9705 | 0.9764 | 0.9734 | 0.9721 |
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| 0.0146 | 5.0 | 1095 | 0.1299 | 0.9743 | 0.9854 | 0.9648 | 0.9750 | 0.9747 |
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| 0.0069 | 6.0 | 1314 | 0.1504 | 0.9750 | 0.9814 | 0.9703 | 0.9758 | 0.9752 |
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| 0.0044 | 7.0 | 1533 | 0.1653 | 0.9743 | 0.9779 | 0.9725 | 0.9752 | 0.9744 |
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| 0.0019 | 8.0 | 1752 | 0.1804 | 0.9756 | 0.9817 | 0.9711 | 0.9764 | 0.9758 |
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| 0.0008 | 9.0 | 1971 | 0.1827 | 0.9767 | 0.9839 | 0.9711 | 0.9775 | 0.9769 |
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| 0.0008 | 10.0 | 2190 | 0.1797 | 0.9770 | 0.9841 | 0.9714 | 0.9777 | 0.9772 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.2
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- Tokenizers 0.13.3
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