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--- |
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library_name: transformers |
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base_model: microsoft/graphcodebert-base |
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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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model-index: |
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- name: cwe-parent-vulnerability-classification-microsoft-graphcodebert-base |
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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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# cwe-parent-vulnerability-classification-microsoft-graphcodebert-base |
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This model is a fine-tuned version of [microsoft/graphcodebert-base](https://huggingface.co/microsoft/graphcodebert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8233 |
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- Accuracy: 0.6517 |
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- F1 Macro: 0.3050 |
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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: 1e-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: Use OptimizerNames.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: 40 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| |
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| 3.255 | 1.0 | 25 | 3.2962 | 0.0225 | 0.0083 | |
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| 3.1345 | 2.0 | 50 | 3.3120 | 0.2697 | 0.0544 | |
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| 3.0539 | 3.0 | 75 | 3.3627 | 0.3820 | 0.0582 | |
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| 2.9349 | 4.0 | 100 | 3.3122 | 0.3596 | 0.0921 | |
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| 2.9555 | 5.0 | 125 | 3.2926 | 0.4045 | 0.1695 | |
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| 2.7748 | 6.0 | 150 | 3.3514 | 0.4607 | 0.1757 | |
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| 2.803 | 7.0 | 175 | 3.3219 | 0.5169 | 0.1884 | |
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| 2.67 | 8.0 | 200 | 3.2696 | 0.4831 | 0.2198 | |
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| 2.5684 | 9.0 | 225 | 3.2657 | 0.4944 | 0.2445 | |
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| 2.4226 | 10.0 | 250 | 3.1999 | 0.3371 | 0.1697 | |
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| 2.4615 | 11.0 | 275 | 3.1954 | 0.4270 | 0.1996 | |
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| 2.2738 | 12.0 | 300 | 3.1108 | 0.4157 | 0.1954 | |
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| 2.2423 | 13.0 | 325 | 3.0714 | 0.3933 | 0.1862 | |
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| 2.2066 | 14.0 | 350 | 3.0598 | 0.3820 | 0.1975 | |
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| 1.9919 | 15.0 | 375 | 3.0252 | 0.4382 | 0.1992 | |
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| 1.9622 | 16.0 | 400 | 2.9873 | 0.3708 | 0.1981 | |
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| 1.9415 | 17.0 | 425 | 2.9783 | 0.4494 | 0.2166 | |
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| 1.8459 | 18.0 | 450 | 2.9570 | 0.4831 | 0.2304 | |
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| 1.7008 | 19.0 | 475 | 2.9116 | 0.4607 | 0.2104 | |
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| 1.6705 | 20.0 | 500 | 2.9134 | 0.4607 | 0.2152 | |
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| 1.6422 | 21.0 | 525 | 2.9341 | 0.4607 | 0.2554 | |
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| 1.4982 | 22.0 | 550 | 2.8852 | 0.5056 | 0.2604 | |
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| 1.5523 | 23.0 | 575 | 2.9029 | 0.5056 | 0.2555 | |
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| 1.3784 | 24.0 | 600 | 2.8782 | 0.5393 | 0.2840 | |
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| 1.4479 | 25.0 | 625 | 2.8525 | 0.5730 | 0.2558 | |
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| 1.2508 | 26.0 | 650 | 2.9039 | 0.5730 | 0.2563 | |
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| 1.3662 | 27.0 | 675 | 2.8784 | 0.6067 | 0.3081 | |
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| 1.2199 | 28.0 | 700 | 2.8704 | 0.6180 | 0.2729 | |
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| 1.1903 | 29.0 | 725 | 2.8577 | 0.6404 | 0.2811 | |
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| 1.1881 | 30.0 | 750 | 2.8612 | 0.6404 | 0.2890 | |
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| 1.1572 | 31.0 | 775 | 2.8371 | 0.6292 | 0.2968 | |
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| 1.0623 | 32.0 | 800 | 2.8413 | 0.6404 | 0.2969 | |
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| 1.0405 | 33.0 | 825 | 2.8233 | 0.6517 | 0.3050 | |
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| 1.1084 | 34.0 | 850 | 2.8323 | 0.6404 | 0.3012 | |
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| 1.0211 | 35.0 | 875 | 2.8341 | 0.6404 | 0.3042 | |
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| 1.0215 | 36.0 | 900 | 2.8391 | 0.6404 | 0.3006 | |
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| 0.9438 | 37.0 | 925 | 2.8321 | 0.6404 | 0.3006 | |
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| 0.9383 | 38.0 | 950 | 2.8266 | 0.6404 | 0.3012 | |
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| 1.017 | 39.0 | 975 | 2.8236 | 0.6404 | 0.3037 | |
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| 0.9262 | 40.0 | 1000 | 2.8264 | 0.6404 | 0.3037 | |
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### Framework versions |
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- Transformers 4.55.4 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.2 |
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