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results_v3

PEFT
Safetensors
Generated from Trainer
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  1. README.md +16 -12
  2. adapter_model.safetensors +1 -1
README.md CHANGED
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  ---
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  library_name: peft
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- license: apache-2.0
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- base_model: Salesforce/codet5-small
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -18,15 +17,15 @@ should probably proofread and complete it, then remove this comment. -->
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  # results_v3
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- This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8696
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- - Accuracy: 0.4779
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- - Precision: 0.0663
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- - Recall: 0.8108
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- - F1 Score: 0.1225
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- - F2 Score: 0.2497
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- - Gmean: 0.6122
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  ## Model description
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@@ -51,13 +50,18 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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- - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | F2 Score | Gmean |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:------:|
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- | 0.7438 | 1.0 | 197 | 0.8696 | 0.4779 | 0.0663 | 0.8108 | 0.1225 | 0.2497 | 0.6122 |
 
 
 
 
 
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  ### Framework versions
 
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  ---
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  library_name: peft
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+ base_model: Vulnerability-Detection/codet5_merged
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # results_v3
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+ This model is a fine-tuned version of [Vulnerability-Detection/codet5_merged](https://huggingface.co/Vulnerability-Detection/codet5_merged) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5425
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+ - Accuracy: 0.7416
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+ - Precision: 0.1241
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+ - Recall: 0.7838
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+ - F1 Score: 0.2143
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+ - F2 Score: 0.3799
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+ - Gmean: 0.7614
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  ## Model description
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  - seed: 42
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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+ - num_epochs: 6
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | F2 Score | Gmean |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:------:|
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+ | 0.6133 | 1.0 | 197 | 0.6332 | 0.6898 | 0.1040 | 0.7748 | 0.1834 | 0.3383 | 0.7289 |
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+ | 0.5995 | 2.0 | 394 | 0.4958 | 0.7594 | 0.1267 | 0.7387 | 0.2164 | 0.3758 | 0.7495 |
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+ | 0.5626 | 3.0 | 591 | 0.5477 | 0.7473 | 0.1255 | 0.7748 | 0.2161 | 0.3809 | 0.7602 |
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+ | 0.5798 | 4.0 | 788 | 0.5719 | 0.7307 | 0.1195 | 0.7838 | 0.2074 | 0.3712 | 0.7555 |
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+ | 0.54 | 5.0 | 985 | 0.5282 | 0.7473 | 0.1255 | 0.7748 | 0.2161 | 0.3809 | 0.7602 |
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+ | 0.514 | 6.0 | 1182 | 0.5425 | 0.7416 | 0.1241 | 0.7838 | 0.2143 | 0.3799 | 0.7614 |
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  ### Framework versions
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