CIRCL/cwe-parent-vulnerability-classification-roberta-base

README.md

@@ -18,12 +18,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 4.1425
-- Accuracy: 0.0112
-- F1 Macro: 0.0018
-- Top2 Acc: 0.0112
-- Top3 Acc: 0.0449
-- Top5 Acc: 0.0562
+- Loss: 2.4210
+- Accuracy: 0.5393
+- F1 Macro: 0.2289
 
 ## Model description
 
@@ -52,12 +49,38 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Top2 Acc | Top3 Acc | Top5 Acc |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:--------:|:--------:|
-| 2.9029        | 1.0   | 25   | 4.1425          | 0.0112   | 0.0018   | 0.0112   | 0.0449   | 0.0562   |
-| 2.9321        | 2.0   | 50   | 4.2946          | 0.0112   | 0.0030   | 0.0562   | 0.0562   | 0.1011   |
-| 3.0394        | 3.0   | 75   | 4.4905          | 0.0337   | 0.0060   | 0.0562   | 0.1011   | 0.1236   |
-| 2.8752        | 4.0   | 100  | 4.5061          | 0.0225   | 0.0054   | 0.0449   | 0.0674   | 0.1011   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
+| 3.2216        | 1.0   | 25   | 3.1710          | 0.2921   | 0.0396   |
+| 3.1942        | 2.0   | 50   | 3.0741          | 0.0337   | 0.0041   |
+| 3.1191        | 3.0   | 75   | 3.0549          | 0.0337   | 0.0126   |
+| 3.0134        | 4.0   | 100  | 3.0421          | 0.0225   | 0.0030   |
+| 2.9421        | 5.0   | 125  | 3.0235          | 0.1685   | 0.0372   |
+| 2.9003        | 6.0   | 150  | 3.0508          | 0.0337   | 0.0192   |
+| 2.8848        | 7.0   | 175  | 3.0571          | 0.0337   | 0.0046   |
+| 2.7802        | 8.0   | 200  | 3.0904          | 0.1011   | 0.0441   |
+| 2.7221        | 9.0   | 225  | 3.0587          | 0.1011   | 0.0297   |
+| 2.6257        | 10.0  | 250  | 3.0672          | 0.4045   | 0.0974   |
+| 2.6718        | 11.0  | 275  | 2.9936          | 0.1910   | 0.0680   |
+| 2.4743        | 12.0  | 300  | 2.9018          | 0.3483   | 0.0942   |
+| 2.3287        | 13.0  | 325  | 2.9504          | 0.2472   | 0.0624   |
+| 2.2387        | 14.0  | 350  | 2.8915          | 0.3483   | 0.0974   |
+| 2.2311        | 15.0  | 375  | 2.7952          | 0.2921   | 0.0958   |
+| 2.0399        | 16.0  | 400  | 2.7364          | 0.3371   | 0.1322   |
+| 1.9886        | 17.0  | 425  | 2.8209          | 0.3596   | 0.0969   |
+| 1.9451        | 18.0  | 450  | 2.7339          | 0.3596   | 0.1238   |
+| 1.7988        | 19.0  | 475  | 2.7224          | 0.4045   | 0.1037   |
+| 1.7638        | 20.0  | 500  | 2.6566          | 0.3596   | 0.1215   |
+| 1.7109        | 21.0  | 525  | 2.5994          | 0.4494   | 0.1917   |
+| 1.6364        | 22.0  | 550  | 2.5708          | 0.4382   | 0.1878   |
+| 1.5985        | 23.0  | 575  | 2.5225          | 0.4944   | 0.2005   |
+| 1.5154        | 24.0  | 600  | 2.4922          | 0.4831   | 0.2198   |
+| 1.4841        | 25.0  | 625  | 2.4594          | 0.4944   | 0.2236   |
+| 1.4782        | 26.0  | 650  | 2.4578          | 0.4944   | 0.1985   |
+| 1.4064        | 27.0  | 675  | 2.4545          | 0.5393   | 0.2282   |
+| 1.3746        | 28.0  | 700  | 2.4423          | 0.5169   | 0.2197   |
+| 1.3514        | 29.0  | 725  | 2.4210          | 0.5393   | 0.2289   |
+| 1.34          | 30.0  | 750  | 2.4356          | 0.5281   | 0.2237   |
 
 
 ### Framework versions

config.json

@@ -10,62 +10,62 @@
   "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
   "id2label": {
-    "0": "LABEL_0",
-    "1": "LABEL_1",
-    "2": "LABEL_2",
-    "3": "LABEL_3",
-    "4": "LABEL_4",
-    "5": "LABEL_5",
-    "6": "LABEL_6",
-    "7": "LABEL_7",
-    "8": "LABEL_8",
-    "9": "LABEL_9",
-    "10": "LABEL_10",
-    "11": "LABEL_11",
-    "12": "LABEL_12",
-    "13": "LABEL_13",
-    "14": "LABEL_14",
-    "15": "LABEL_15",
-    "16": "LABEL_16",
-    "17": "LABEL_17",
-    "18": "LABEL_18",
-    "19": "LABEL_19",
-    "20": "LABEL_20",
-    "21": "LABEL_21",
-    "22": "LABEL_22",
-    "23": "LABEL_23",
-    "24": "LABEL_24",
-    "25": "LABEL_25"
+    "0": "1025",
+    "1": "1071",
+    "2": "131",
+    "3": "138",
+    "4": "284",
+    "5": "285",
+    "6": "435",
+    "7": "436",
+    "8": "595",
+    "9": "657",
+    "10": "664",
+    "11": "682",
+    "12": "684",
+    "13": "691",
+    "14": "693",
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+    "16": "703",
+    "17": "706",
+    "18": "707",
+    "19": "710",
+    "20": "74",
+    "21": "754",
+    "22": "829",
+    "23": "862",
+    "24": "913",
+    "25": "94"
   },
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "LABEL_0": 0,
-    "LABEL_1": 1,
-    "LABEL_10": 10,
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-    "LABEL_5": 5,
-    "LABEL_6": 6,
-    "LABEL_7": 7,
-    "LABEL_8": 8,
-    "LABEL_9": 9
+    "1025": 0,
+    "1071": 1,
+    "131": 2,
+    "138": 3,
+    "284": 4,
+    "285": 5,
+    "435": 6,
+    "436": 7,
+    "595": 8,
+    "657": 9,
+    "664": 10,
+    "682": 11,
+    "684": 12,
+    "691": 13,
+    "693": 14,
+    "697": 15,
+    "703": 16,
+    "706": 17,
+    "707": 18,
+    "710": 19,
+    "74": 20,
+    "754": 21,
+    "829": 22,
+    "862": 23,
+    "913": 24,
+    "94": 25
   },
   "layer_norm_eps": 1e-05,
   "max_position_embeddings": 514,

emissions.csv

@@ -1,2 +1,2 @@
 timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue
-2025-09-02T08:34:59,codecarbon,4300f665-5d3d-460c-bd73-601d1d03e5d3,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,34.12328125699423,0.0005746714895095483,1.684103838612408e-05,42.5,369.6914459781543,94.34468507766725,0.00040215994350890265,0.004164867220779911,0.0008923601751329034,0.005459387339421717,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
+2025-09-02T08:50:21,codecarbon,2664b472-8e38-43b8-ae2d-497b80d15f92,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,371.1448491369374,0.0064907567902602005,1.748847331534803e-05,42.5,479.247001834791,94.34468507766725,0.004378942286911964,0.04756333749507746,0.009720002218905472,0.0616622820008949,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

@@ -1,12 +1,9 @@
 {
-    "eval_loss": 4.142518043518066,
-    "eval_accuracy": 0.011235955056179775,
-    "eval_f1_macro": 0.0017683465959328027,
-    "eval_top2_acc": 0.011235955056179775,
-    "eval_top3_acc": 0.0449438202247191,
-    "eval_top5_acc": 0.056179775280898875,
-    "eval_runtime": 0.3071,
-    "eval_samples_per_second": 289.777,
-    "eval_steps_per_second": 9.768,
-    "epoch": 4.0
+    "eval_loss": 2.421022653579712,
+    "eval_accuracy": 0.5393258426966292,
+    "eval_f1_macro": 0.22885547452822638,
+    "eval_runtime": 0.5079,
+    "eval_samples_per_second": 175.234,
+    "eval_steps_per_second": 5.907,
+    "epoch": 30.0
 }

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:c17890e8e68887e66226a4cf0dbfad64c48d8f968d19d61d628e66d14679b440
 size 498686648