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vulnerability-attack-technique-classification-roberta-base-llm-expanded

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multi-label-classification

negative-result

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Eval Results (legacy)

text-embeddings-inference

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vulnerability-attack-technique-classification-roberta-base-llm-expanded / emissions.csv

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	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,water_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,cpu_utilization_percent,gpu_utilization_percent,ram_utilization_percent,ram_used_gb,on_cloud,pue,wue
	2026-07-17T08:56:36,VulnTrain,1eaa856d-df2e-44f8-b888-05b64cfa4d04,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,390.7911756411195,0.007907393375858981,2.0234319167740586e-05,70.00014612092788,557.3628228684195,70.0,0.007334659547583945,0.06045171391690474,0.0073339762866962725,0.07512034975118495,0.0,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-106-generic-x86_64-with-glibc2.39,3.12.3,3.2.8,224,Intel(R) Xeon(R) Platinum 8480+,2,2 x NVIDIA H100 NVL,6.1327,49.6098,2015.336296081543,machine,0.8956072351421189,56.51679586563308,1.7968992248062015,35.70702654816384,N,1.0,0.0