CIRCL/cwe-parent-vulnerability-classification-huggingface-CodeBERTa-small-v1

README.md

@@ -0,0 +1,100 @@
+---
+library_name: transformers
+base_model: huggingface/CodeBERTa-small-v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: cwe-parent-vulnerability-classification-huggingface-CodeBERTa-small-v1
+  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-huggingface-CodeBERTa-small-v1
+
+This model is a fine-tuned version of [huggingface/CodeBERTa-small-v1](https://huggingface.co/huggingface/CodeBERTa-small-v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3718
+- Accuracy: 0.7753
+- F1 Macro: 0.3835
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 3.2521        | 1.0   | 25   | 3.3015          | 0.0112   | 0.0057   |
+| 3.037         | 2.0   | 50   | 3.2608          | 0.3258   | 0.1301   |
+| 3.0191        | 3.0   | 75   | 3.3140          | 0.3146   | 0.0568   |
+| 2.8876        | 4.0   | 100  | 3.2111          | 0.2472   | 0.2190   |
+| 2.7888        | 5.0   | 125  | 3.1305          | 0.2360   | 0.2394   |
+| 2.6762        | 6.0   | 150  | 3.1370          | 0.3146   | 0.1503   |
+| 2.5905        | 7.0   | 175  | 3.0446          | 0.3933   | 0.2144   |
+| 2.4173        | 8.0   | 200  | 2.9769          | 0.3933   | 0.1999   |
+| 2.2706        | 9.0   | 225  | 2.9704          | 0.3708   | 0.1825   |
+| 2.1355        | 10.0  | 250  | 2.9071          | 0.3820   | 0.2097   |
+| 2.0722        | 11.0  | 275  | 2.9189          | 0.4382   | 0.1855   |
+| 1.8111        | 12.0  | 300  | 2.7873          | 0.4157   | 0.2257   |
+| 1.7056        | 13.0  | 325  | 2.7584          | 0.4607   | 0.2217   |
+| 1.6693        | 14.0  | 350  | 2.7394          | 0.5169   | 0.2370   |
+| 1.496         | 15.0  | 375  | 2.6647          | 0.5506   | 0.2630   |
+| 1.3093        | 16.0  | 400  | 2.6477          | 0.5843   | 0.2644   |
+| 1.251         | 17.0  | 425  | 2.6355          | 0.6067   | 0.2654   |
+| 1.1316        | 18.0  | 450  | 2.5521          | 0.6404   | 0.3000   |
+| 1.049         | 19.0  | 475  | 2.5236          | 0.6404   | 0.2951   |
+| 0.9441        | 20.0  | 500  | 2.5538          | 0.6404   | 0.2957   |
+| 0.8752        | 21.0  | 525  | 2.5020          | 0.6742   | 0.3259   |
+| 0.7623        | 22.0  | 550  | 2.4927          | 0.6966   | 0.3339   |
+| 0.7938        | 23.0  | 575  | 2.4595          | 0.7079   | 0.3413   |
+| 0.6321        | 24.0  | 600  | 2.4564          | 0.7079   | 0.3369   |
+| 0.6245        | 25.0  | 625  | 2.4537          | 0.7191   | 0.3631   |
+| 0.5502        | 26.0  | 650  | 2.4470          | 0.7416   | 0.3764   |
+| 0.5805        | 27.0  | 675  | 2.4588          | 0.7528   | 0.3849   |
+| 0.5042        | 28.0  | 700  | 2.4243          | 0.7640   | 0.3930   |
+| 0.464         | 29.0  | 725  | 2.4051          | 0.7640   | 0.3930   |
+| 0.4349        | 30.0  | 750  | 2.4361          | 0.7753   | 0.4034   |
+| 0.4347        | 31.0  | 775  | 2.4062          | 0.7640   | 0.3906   |
+| 0.3953        | 32.0  | 800  | 2.3939          | 0.7753   | 0.3835   |
+| 0.3775        | 33.0  | 825  | 2.4091          | 0.7865   | 0.3958   |
+| 0.3948        | 34.0  | 850  | 2.4018          | 0.7865   | 0.3958   |
+| 0.348         | 35.0  | 875  | 2.3718          | 0.7753   | 0.3835   |
+| 0.3328        | 36.0  | 900  | 2.3843          | 0.7865   | 0.3947   |
+| 0.3291        | 37.0  | 925  | 2.3843          | 0.7978   | 0.3965   |
+| 0.3211        | 38.0  | 950  | 2.3764          | 0.7865   | 0.3958   |
+| 0.307         | 39.0  | 975  | 2.3822          | 0.7978   | 0.3975   |
+| 0.3055        | 40.0  | 1000 | 2.3855          | 0.7978   | 0.3965   |
+
+
+### 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": 514,

emissions.csv

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+2025-09-03T13:13:25,codecarbon,193f927f-2f36-4440-aed9-ad8565907b06,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,220.4319850918837,0.0034426589515920277,1.5617783191295982e-05,42.5,410.95217986747076,94.34468507766725,0.0026010783994230833,0.02433042140876296,0.005773809289901861,0.03270530909808791,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": 2.371821165084839,
+    "eval_accuracy": 0.7752808988764045,
+    "eval_f1_macro": 0.38348560354374306,
+    "eval_runtime": 0.1883,
+    "eval_samples_per_second": 472.774,
+    "eval_steps_per_second": 15.936,
+    "epoch": 40.0
+}

model.safetensors

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