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MarkerPipeline/2025-02-03 14-53-22-304029/codecarbon_results.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,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
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2025-02-03T14:53:22,Evaluator___evaluate_file_parsing______,eca247ec-3dd5-43c8-96cc-4d1eb6809079,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,2922.663997137919,0.006936930166516469,2.3734956099331316e-06,75.0,58.433866990350126,7.747897624969482,0.06086416815186384,0.05808880841544806,0.004834567223913324,0.12378754379122518,France,FRA,,,,Linux-5.15.0-122-generic-x86_64-with-glibc2.35,3.11.10,2.8.3,60,Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz,1,1 x Tesla V100S-PCIE-32GB,,,172.71782684326172,process,N,1.0
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