CIRCL/cwe-parent-vulnerability-classification-microsoft-graphcodebert-base

README.md

@@ -0,0 +1,100 @@
+---
+library_name: transformers
+base_model: microsoft/graphcodebert-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: cwe-parent-vulnerability-classification-microsoft-graphcodebert-base
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# cwe-parent-vulnerability-classification-microsoft-graphcodebert-base
+
+This model is a fine-tuned version of [microsoft/graphcodebert-base](https://huggingface.co/microsoft/graphcodebert-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.8233
+- Accuracy: 0.6517
+- F1 Macro: 0.3050
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 40
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 3.255         | 1.0   | 25   | 3.2962          | 0.0225   | 0.0083   |
+| 3.1345        | 2.0   | 50   | 3.3120          | 0.2697   | 0.0544   |
+| 3.0539        | 3.0   | 75   | 3.3627          | 0.3820   | 0.0582   |
+| 2.9349        | 4.0   | 100  | 3.3122          | 0.3596   | 0.0921   |
+| 2.9555        | 5.0   | 125  | 3.2926          | 0.4045   | 0.1695   |
+| 2.7748        | 6.0   | 150  | 3.3514          | 0.4607   | 0.1757   |
+| 2.803         | 7.0   | 175  | 3.3219          | 0.5169   | 0.1884   |
+| 2.67          | 8.0   | 200  | 3.2696          | 0.4831   | 0.2198   |
+| 2.5684        | 9.0   | 225  | 3.2657          | 0.4944   | 0.2445   |
+| 2.4226        | 10.0  | 250  | 3.1999          | 0.3371   | 0.1697   |
+| 2.4615        | 11.0  | 275  | 3.1954          | 0.4270   | 0.1996   |
+| 2.2738        | 12.0  | 300  | 3.1108          | 0.4157   | 0.1954   |
+| 2.2423        | 13.0  | 325  | 3.0714          | 0.3933   | 0.1862   |
+| 2.2066        | 14.0  | 350  | 3.0598          | 0.3820   | 0.1975   |
+| 1.9919        | 15.0  | 375  | 3.0252          | 0.4382   | 0.1992   |
+| 1.9622        | 16.0  | 400  | 2.9873          | 0.3708   | 0.1981   |
+| 1.9415        | 17.0  | 425  | 2.9783          | 0.4494   | 0.2166   |
+| 1.8459        | 18.0  | 450  | 2.9570          | 0.4831   | 0.2304   |
+| 1.7008        | 19.0  | 475  | 2.9116          | 0.4607   | 0.2104   |
+| 1.6705        | 20.0  | 500  | 2.9134          | 0.4607   | 0.2152   |
+| 1.6422        | 21.0  | 525  | 2.9341          | 0.4607   | 0.2554   |
+| 1.4982        | 22.0  | 550  | 2.8852          | 0.5056   | 0.2604   |
+| 1.5523        | 23.0  | 575  | 2.9029          | 0.5056   | 0.2555   |
+| 1.3784        | 24.0  | 600  | 2.8782          | 0.5393   | 0.2840   |
+| 1.4479        | 25.0  | 625  | 2.8525          | 0.5730   | 0.2558   |
+| 1.2508        | 26.0  | 650  | 2.9039          | 0.5730   | 0.2563   |
+| 1.3662        | 27.0  | 675  | 2.8784          | 0.6067   | 0.3081   |
+| 1.2199        | 28.0  | 700  | 2.8704          | 0.6180   | 0.2729   |
+| 1.1903        | 29.0  | 725  | 2.8577          | 0.6404   | 0.2811   |
+| 1.1881        | 30.0  | 750  | 2.8612          | 0.6404   | 0.2890   |
+| 1.1572        | 31.0  | 775  | 2.8371          | 0.6292   | 0.2968   |
+| 1.0623        | 32.0  | 800  | 2.8413          | 0.6404   | 0.2969   |
+| 1.0405        | 33.0  | 825  | 2.8233          | 0.6517   | 0.3050   |
+| 1.1084        | 34.0  | 850  | 2.8323          | 0.6404   | 0.3012   |
+| 1.0211        | 35.0  | 875  | 2.8341          | 0.6404   | 0.3042   |
+| 1.0215        | 36.0  | 900  | 2.8391          | 0.6404   | 0.3006   |
+| 0.9438        | 37.0  | 925  | 2.8321          | 0.6404   | 0.3006   |
+| 0.9383        | 38.0  | 950  | 2.8266          | 0.6404   | 0.3012   |
+| 1.017         | 39.0  | 975  | 2.8236          | 0.6404   | 0.3037   |
+| 0.9262        | 40.0  | 1000 | 2.8264          | 0.6404   | 0.3037   |
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.2

config.json

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emissions.csv

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+2025-09-03T13:21:50,codecarbon,3e519de9-4764-48ec-9aaf-36761959b92c,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,384.9297951501794,0.006275683567718154,1.630344973755464e-05,42.5,419.7123319081902,94.34468507766725,0.004539716701293461,0.045002576835372565,0.010076789785281433,0.059619083321947444,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-71-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.5858268737793,machine,N,1.0

metrics.json

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+{
+    "eval_loss": 2.823303461074829,
+    "eval_accuracy": 0.651685393258427,
+    "eval_f1_macro": 0.30500876658151677,
+    "eval_runtime": 0.2994,
+    "eval_samples_per_second": 297.285,
+    "eval_steps_per_second": 10.021,
+    "epoch": 40.0
+}

model.safetensors

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