CIRCL/cwe-parent-vulnerability-classification-distilbert-base-uncased

README.md

@@ -0,0 +1,101 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: cwe-parent-vulnerability-classification-distilbert-base-uncased
+  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-distilbert-base-uncased
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3946
+- Accuracy: 0.7416
+- F1 Macro: 0.4136
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 3.2586        | 1.0   | 25   | 3.2817          | 0.0225   | 0.0037   |
+| 3.1726        | 2.0   | 50   | 3.2811          | 0.0225   | 0.0037   |
+| 3.1195        | 3.0   | 75   | 3.2705          | 0.0225   | 0.0037   |
+| 3.0213        | 4.0   | 100  | 3.2327          | 0.0449   | 0.0325   |
+| 3.0235        | 5.0   | 125  | 3.2046          | 0.2247   | 0.0830   |
+| 2.931         | 6.0   | 150  | 3.2138          | 0.2697   | 0.0725   |
+| 2.9104        | 7.0   | 175  | 3.1642          | 0.4382   | 0.1117   |
+| 2.779         | 8.0   | 200  | 3.1058          | 0.4831   | 0.1095   |
+| 2.7528        | 9.0   | 225  | 3.0725          | 0.5169   | 0.1238   |
+| 2.6453        | 10.0  | 250  | 3.0537          | 0.5730   | 0.2290   |
+| 2.6262        | 11.0  | 275  | 3.0154          | 0.5618   | 0.2103   |
+| 2.4852        | 12.0  | 300  | 2.9611          | 0.5955   | 0.3516   |
+| 2.3778        | 13.0  | 325  | 2.9121          | 0.5955   | 0.3256   |
+| 2.3381        | 14.0  | 350  | 2.8414          | 0.6067   | 0.3057   |
+| 2.2415        | 15.0  | 375  | 2.8161          | 0.6180   | 0.3610   |
+| 2.0991        | 16.0  | 400  | 2.7636          | 0.6180   | 0.3520   |
+| 2.0469        | 17.0  | 425  | 2.7049          | 0.6180   | 0.3175   |
+| 1.9623        | 18.0  | 450  | 2.7100          | 0.6404   | 0.3767   |
+| 1.921         | 19.0  | 475  | 2.6304          | 0.6404   | 0.3320   |
+| 1.8045        | 20.0  | 500  | 2.6552          | 0.6404   | 0.3130   |
+| 1.7417        | 21.0  | 525  | 2.5960          | 0.6517   | 0.3082   |
+| 1.7004        | 22.0  | 550  | 2.5777          | 0.6404   | 0.3183   |
+| 1.6295        | 23.0  | 575  | 2.5849          | 0.6742   | 0.3602   |
+| 1.5823        | 24.0  | 600  | 2.5379          | 0.6742   | 0.345    |
+| 1.4711        | 25.0  | 625  | 2.5262          | 0.6742   | 0.3512   |
+| 1.4868        | 26.0  | 650  | 2.4962          | 0.7079   | 0.3970   |
+| 1.4563        | 27.0  | 675  | 2.4695          | 0.6854   | 0.3438   |
+| 1.3601        | 28.0  | 700  | 2.4549          | 0.6854   | 0.3438   |
+| 1.2847        | 29.0  | 725  | 2.4691          | 0.7079   | 0.3688   |
+| 1.2883        | 30.0  | 750  | 2.4587          | 0.7079   | 0.3966   |
+| 1.316         | 31.0  | 775  | 2.4454          | 0.7191   | 0.3623   |
+| 1.1845        | 32.0  | 800  | 2.4432          | 0.7416   | 0.4111   |
+| 1.24          | 33.0  | 825  | 2.4280          | 0.7079   | 0.3980   |
+| 1.1163        | 34.0  | 850  | 2.4179          | 0.7416   | 0.3871   |
+| 1.1728        | 35.0  | 875  | 2.4326          | 0.7528   | 0.4201   |
+| 1.1013        | 36.0  | 900  | 2.4116          | 0.7416   | 0.4136   |
+| 1.1612        | 37.0  | 925  | 2.3985          | 0.7416   | 0.4136   |
+| 1.1472        | 38.0  | 950  | 2.3956          | 0.7416   | 0.4136   |
+| 1.069         | 39.0  | 975  | 2.3946          | 0.7416   | 0.4136   |
+| 1.0865        | 40.0  | 1000 | 2.3983          | 0.7528   | 0.4201   |
+
+
+### 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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   "max_position_embeddings": 512,
   "model_type": "distilbert",

emissions.csv

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+2025-09-03T13:35:59,codecarbon,1b1c2d45-b5b5-4479-95ad-9b3f70180786,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,195.7275512360502,0.0031719271440446553,1.6205828581686317e-05,42.5,162.96108566089268,94.34468507766725,0.0023084282687747164,0.0227022656617919,0.0051226591378872085,0.030133353068453824,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": 2.394566059112549,
+    "eval_accuracy": 0.7415730337078652,
+    "eval_f1_macro": 0.41364775575301893,
+    "eval_runtime": 0.203,
+    "eval_samples_per_second": 438.53,
+    "eval_steps_per_second": 14.782,
+    "epoch": 40.0
+}

model.safetensors

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