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

README.md

@@ -9,8 +9,6 @@ metrics:
 model-index:
 - name: cwe-parent-vulnerability-classification-roberta-base
   results: []
-datasets:
-- CIRCL/vulnerability-cwe-patch
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,12 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # cwe-parent-vulnerability-classification-roberta-base
 
-This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base).
-
+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: 1.2078
-- Accuracy: 0.875
-- F1 Macro: 0.6248
+- Loss: 1.8213
+- Accuracy: 0.5673
+- F1 Macro: 0.3582
 
 ## Model description
 
@@ -46,7 +43,7 @@ The following hyperparameters were used during training:
 - 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
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 40
 
@@ -54,51 +51,51 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
-| 3.2699        | 1.0   | 25   | 3.1492          | 0.0341   | 0.0055   |
-| 3.1972        | 2.0   | 50   | 2.9909          | 0.0114   | 0.0064   |
-| 3.1211        | 3.0   | 75   | 3.0017          | 0.0341   | 0.0140   |
-| 3.0888        | 4.0   | 100  | 3.0223          | 0.2841   | 0.0463   |
-| 2.9467        | 5.0   | 125  | 2.9608          | 0.0114   | 0.0018   |
-| 2.9851        | 6.0   | 150  | 2.8743          | 0.1932   | 0.0641   |
-| 2.9083        | 7.0   | 175  | 2.7687          | 0.375    | 0.0963   |
-| 2.7652        | 8.0   | 200  | 2.7049          | 0.4318   | 0.1953   |
-| 2.6893        | 9.0   | 225  | 2.5547          | 0.4886   | 0.1952   |
-| 2.5636        | 10.0  | 250  | 2.4970          | 0.5682   | 0.3314   |
-| 2.477         | 11.0  | 275  | 2.3499          | 0.6136   | 0.3790   |
-| 2.2936        | 12.0  | 300  | 2.2659          | 0.6364   | 0.3949   |
-| 2.1369        | 13.0  | 325  | 2.1758          | 0.625    | 0.4002   |
-| 2.0615        | 14.0  | 350  | 2.1015          | 0.6477   | 0.4169   |
-| 1.9548        | 15.0  | 375  | 1.9444          | 0.6932   | 0.3972   |
-| 1.7943        | 16.0  | 400  | 1.8892          | 0.6818   | 0.4210   |
-| 1.6619        | 17.0  | 425  | 1.8439          | 0.6818   | 0.4149   |
-| 1.5391        | 18.0  | 450  | 1.7247          | 0.7159   | 0.4848   |
-| 1.4415        | 19.0  | 475  | 1.6650          | 0.7273   | 0.4749   |
-| 1.2834        | 20.0  | 500  | 1.5743          | 0.7727   | 0.5574   |
-| 1.2245        | 21.0  | 525  | 1.5396          | 0.7614   | 0.5373   |
-| 1.1629        | 22.0  | 550  | 1.5005          | 0.7614   | 0.5350   |
-| 1.0894        | 23.0  | 575  | 1.4478          | 0.7614   | 0.5383   |
-| 0.9755        | 24.0  | 600  | 1.4335          | 0.7841   | 0.5599   |
-| 0.9271        | 25.0  | 625  | 1.4195          | 0.7841   | 0.5562   |
-| 0.8761        | 26.0  | 650  | 1.3740          | 0.8182   | 0.6015   |
-| 0.8312        | 27.0  | 675  | 1.3479          | 0.8295   | 0.6086   |
-| 0.7523        | 28.0  | 700  | 1.3379          | 0.8295   | 0.5948   |
-| 0.718         | 29.0  | 725  | 1.2991          | 0.8295   | 0.5948   |
-| 0.6819        | 30.0  | 750  | 1.3059          | 0.8409   | 0.6047   |
-| 0.6771        | 31.0  | 775  | 1.2650          | 0.8636   | 0.6167   |
-| 0.6267        | 32.0  | 800  | 1.2905          | 0.8523   | 0.6252   |
-| 0.6068        | 33.0  | 825  | 1.2559          | 0.875    | 0.6248   |
-| 0.5811        | 34.0  | 850  | 1.2371          | 0.875    | 0.6248   |
-| 0.5579        | 35.0  | 875  | 1.2231          | 0.875    | 0.6248   |
-| 0.5385        | 36.0  | 900  | 1.2342          | 0.875    | 0.6248   |
-| 0.5334        | 37.0  | 925  | 1.2255          | 0.875    | 0.6248   |
-| 0.4868        | 38.0  | 950  | 1.2223          | 0.875    | 0.6248   |
-| 0.5228        | 39.0  | 975  | 1.2078          | 0.875    | 0.6248   |
-| 0.5325        | 40.0  | 1000 | 1.2101          | 0.875    | 0.6248   |
+| 3.2359        | 1.0   | 237  | 3.0937          | 0.0334   | 0.0114   |
+| 2.3278        | 2.0   | 474  | 2.2992          | 0.4303   | 0.2323   |
+| 1.8161        | 3.0   | 711  | 1.9653          | 0.5089   | 0.2917   |
+| 1.6283        | 4.0   | 948  | 1.8788          | 0.5292   | 0.3007   |
+| 1.3258        | 5.0   | 1185 | 1.8253          | 0.5864   | 0.3392   |
+| 1.3328        | 6.0   | 1422 | 1.8213          | 0.5673   | 0.3582   |
+| 1.2914        | 7.0   | 1659 | 1.8573          | 0.5900   | 0.3604   |
+| 0.8614        | 8.0   | 1896 | 1.8345          | 0.6198   | 0.3810   |
+| 0.8253        | 9.0   | 2133 | 2.0121          | 0.6067   | 0.3568   |
+| 0.7363        | 10.0  | 2370 | 2.0059          | 0.6508   | 0.4071   |
+| 0.6406        | 11.0  | 2607 | 2.0866          | 0.6472   | 0.3906   |
+| 0.4574        | 12.0  | 2844 | 2.1904          | 0.6377   | 0.3902   |
+| 0.4834        | 13.0  | 3081 | 2.2417          | 0.6281   | 0.3797   |
+| 0.3078        | 14.0  | 3318 | 2.3233          | 0.6830   | 0.4132   |
+| 0.3217        | 15.0  | 3555 | 2.4203          | 0.6639   | 0.4020   |
+| 0.2823        | 16.0  | 3792 | 2.4227          | 0.6615   | 0.3918   |
+| 0.2392        | 17.0  | 4029 | 2.6133          | 0.6865   | 0.3844   |
+| 0.1956        | 18.0  | 4266 | 2.6611          | 0.6675   | 0.3789   |
+| 0.1504        | 19.0  | 4503 | 2.7612          | 0.6746   | 0.4158   |
+| 0.1109        | 20.0  | 4740 | 2.8752          | 0.6710   | 0.3776   |
+| 0.1091        | 21.0  | 4977 | 3.0530          | 0.6949   | 0.3776   |
+| 0.13          | 22.0  | 5214 | 3.0540          | 0.6889   | 0.3766   |
+| 0.0797        | 23.0  | 5451 | 3.2854          | 0.6770   | 0.4038   |
+| 0.145         | 24.0  | 5688 | 3.2146          | 0.6973   | 0.3877   |
+| 0.1004        | 25.0  | 5925 | 3.4159          | 0.6937   | 0.3850   |
+| 0.0486        | 26.0  | 6162 | 3.4003          | 0.6865   | 0.3767   |
+| 0.0544        | 27.0  | 6399 | 3.3643          | 0.6889   | 0.3822   |
+| 0.082         | 28.0  | 6636 | 3.4874          | 0.6913   | 0.3818   |
+| 0.0468        | 29.0  | 6873 | 3.5810          | 0.6877   | 0.3815   |
+| 0.0308        | 30.0  | 7110 | 3.7565          | 0.6949   | 0.3837   |
+| 0.0366        | 31.0  | 7347 | 3.6714          | 0.6961   | 0.3814   |
+| 0.0388        | 32.0  | 7584 | 3.8502          | 0.6973   | 0.3957   |
+| 0.0341        | 33.0  | 7821 | 3.8415          | 0.6973   | 0.3973   |
+| 0.0417        | 34.0  | 8058 | 3.9342          | 0.7056   | 0.3864   |
+| 0.0218        | 35.0  | 8295 | 3.9367          | 0.6996   | 0.3843   |
+| 0.0607        | 36.0  | 8532 | 3.9262          | 0.6996   | 0.3841   |
+| 0.0148        | 37.0  | 8769 | 3.9609          | 0.7020   | 0.4189   |
+| 0.0186        | 38.0  | 9006 | 3.9656          | 0.6985   | 0.3822   |
+| 0.0387        | 39.0  | 9243 | 3.9738          | 0.7044   | 0.3850   |
+| 0.008         | 40.0  | 9480 | 3.9906          | 0.7044   | 0.3861   |
 
 
 ### Framework versions
 
-- Transformers 4.55.4
-- Pytorch 2.7.1+cu126
-- Datasets 4.0.0
-- Tokenizers 0.21.2
+- Transformers 4.57.1
+- Pytorch 2.9.1+cu128
+- Datasets 4.4.1
+- Tokenizers 0.22.1

config.json

@@ -11,62 +11,62 @@
   "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",
+    "15": "697",
+    "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,
-    "LABEL_11": 11,
-    "LABEL_12": 12,
-    "LABEL_13": 13,
-    "LABEL_14": 14,
-    "LABEL_15": 15,
-    "LABEL_16": 16,
-    "LABEL_17": 17,
-    "LABEL_18": 18,
-    "LABEL_19": 19,
-    "LABEL_2": 2,
-    "LABEL_20": 20,
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-    "LABEL_24": 24,
-    "LABEL_25": 25,
-    "LABEL_3": 3,
-    "LABEL_4": 4,
-    "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
-2025-09-03T13:07:51,codecarbon,a4931482-bbba-40f5-bb09-0c95cf8cc22d,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,381.010146320099,0.006199580425386055,1.6271431312954028e-05,42.5,399.8939178594448,94.34468507766725,0.004493555260882164,0.04442788498671746,0.009974662137721463,0.05889610238532109,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
+2025-11-21T08:46:27,codecarbon,bc463c8d-dd69-42da-9801-e35dabee8711,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,2632.649387937039,0.050220601954459286,1.9076069219309326e-05,42.5,302.47241372038087,94.34468507766725,0.031054272330529063,0.3771095669652027,0.06893259491628256,0.4770964342120145,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

@@ -1,9 +1,9 @@
 {
-    "eval_loss": 1.2077823877334595,
-    "eval_accuracy": 0.875,
-    "eval_f1_macro": 0.6247628726287263,
-    "eval_runtime": 0.2845,
-    "eval_samples_per_second": 309.345,
-    "eval_steps_per_second": 10.546,
+    "eval_loss": 1.821271300315857,
+    "eval_accuracy": 0.567342073897497,
+    "eval_f1_macro": 0.35818372664233605,
+    "eval_runtime": 2.5279,
+    "eval_samples_per_second": 331.898,
+    "eval_steps_per_second": 10.681,
     "epoch": 40.0
 }

model.safetensors

@@ -1,3 +1,3 @@
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 size 498686648