diff --git a/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/config.yaml b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8e17e4a375896a1f9d549130d21e5d8e5081dd7e
--- /dev/null
+++ b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: automatic-speech-recognition
+  model: jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+  processor: jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/ASR
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: automatic_speech_recognition
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/hydra.yaml b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..4e28591df82030f570fbf60f919837514e215ecf
--- /dev/null
+++ b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42
+  sweep:
+    dir: runs/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42
+    - hydra.mode=RUN
+    task:
+    - backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+    - backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese,backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+    id: ???
+    num: ???
+    config_name: automatic_speech_recognition
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/overrides.yaml b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6a6838f6859f0bb76f2138056ac984bd878ec4d4
--- /dev/null
+++ b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
+- backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese
diff --git a/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/cli.log b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..84b2da95be6adbd3e74aae013047efd0486159ac
--- /dev/null
+++ b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/cli.log
@@ -0,0 +1,25 @@
+[2024-12-07 06:11:45,176][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:11:45,176][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:11:45,188][device-isolation][INFO] - 	+ Launched device(s) isolation process 1684
+[2024-12-07 06:11:45,189][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:11:45,195][process][INFO] - 	+ Launched benchmark in isolated process 1685.
+[PROC-0][2024-12-07 06:11:47,759][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:11:48,710][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:11:48,710][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCTC
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:11:49,096][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:11:49,098][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:11:49,099][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:11:49,100][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:11:49,100][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:11:49,419][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:11:49,425][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:11:49,425][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:11:55,577][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:11:55,577][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:11:59,770][energy_star][INFO] - 	+ Preprocessing dataset
+[2024-12-07 06:12:06,206][experiment][ERROR] - Error during experiment
diff --git a/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/error.log b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..99ab0cda9f908e12445697b7536114b4dab98fb8
--- /dev/null
+++ b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/error.log
@@ -0,0 +1,95 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+
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+
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+[codecarbon INFO @ 06:11:55] [setup] RAM Tracking...
+[codecarbon INFO @ 06:11:55] [setup] GPU Tracking...
+[codecarbon INFO @ 06:11:55] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:11:55] GPU available. Starting setup
+[codecarbon INFO @ 06:11:55] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:11:55] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:11:55] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:11:55] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:11:55] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:11:56] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:11:56] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:56] >>> Tracker's metadata:
+[codecarbon INFO @ 06:11:56]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:11:56]   Python version: 3.9.20
+[codecarbon INFO @ 06:11:56]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:11:56]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:11:56]   CPU count: 48
+[codecarbon INFO @ 06:11:56]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:56]   GPU count: 1
+[codecarbon INFO @ 06:11:56]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:11:57] Not running on AWS
+[codecarbon DEBUG @ 06:11:58] Not running on Azure
+[codecarbon DEBUG @ 06:11:59] Not running on GCP
+[codecarbon INFO @ 06:11:59] Saving emissions data to file /runs/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/codecarbon.csv
+[codecarbon DEBUG @ 06:11:59] EmissionsData(timestamp='2024-12-07T06:11:59', project_name='codecarbon', run_id='a03b476e-f4b5-493a-b12b-aca3f913c3d2', duration=0.0021435300004668534, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+Error executing job with overrides: ['backend.model=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese', 'backend.processor=jonatasgrosman/wav2vec2-large-xlsr-53-portuguese']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
+    benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
+    raise error
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
+    report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
+    while not process_context.join():
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
+    raise ProcessRaisedException(msg, error_index, failed_process.pid)
+torch.multiprocessing.spawn.ProcessRaisedException: 
+
+-- Process 0 terminated with the following error:
+Traceback (most recent call last):
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
+    fn(i, *args)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
+    worker_output = worker(*worker_args)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run
+    benchmark.run(backend)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 122, in run
+    self.dataset = preprocess(
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/preprocessing_utils.py", line 28, in preprocess
+    return task_to_preprocessing[task](dataset, config, preprocessor, pretrained_config)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/preprocessing_utils.py", line 360, in automatic_speech_recognition_preprocessing
+    if getattr(processor.tokenizer, "pad_token", None) is None:
+AttributeError: 'Wav2Vec2CTCTokenizer' object has no attribute 'tokenizer'
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
diff --git a/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/experiment_config.json b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3b6b00a567a75301794e067dc824a2765cc71a64
--- /dev/null
+++ b/automatic_speech_recognition/jonatasgrosman/wav2vec2-large-xlsr-53-portuguese/2024-12-07-06-11-42/experiment_config.json
@@ -0,0 +1,107 @@
+{
+    "experiment_name": "automatic_speech_recognition",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "automatic-speech-recognition",
+        "model": "jonatasgrosman/wav2vec2-large-xlsr-53-portuguese",
+        "processor": "jonatasgrosman/wav2vec2-large-xlsr-53-portuguese",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/ASR",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/config.yaml b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..40d3f9c4fa956f5840c52c65edb0196c4b724680
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: image-classification
+  model: Falconsai/nsfw_image_detection
+  processor: Falconsai/nsfw_image_detection
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/image_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: image_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/hydra.yaml b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d0e7b08d3a1da46685a33dc68c4f61d960cfeac3
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06
+    - hydra.mode=RUN
+    task:
+    - backend.model=Falconsai/nsfw_image_detection
+    - backend.processor=Falconsai/nsfw_image_detection
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=Falconsai/nsfw_image_detection,backend.processor=Falconsai/nsfw_image_detection
+    id: ???
+    num: ???
+    config_name: image_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/overrides.yaml b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2c89aa28676b722ad27a81359cf6f1119934e8d7
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=Falconsai/nsfw_image_detection
+- backend.processor=Falconsai/nsfw_image_detection
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/benchmark_report.json b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/benchmark_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..62dbf086b84d36e97f69dea70e983b5176b0722d
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/benchmark_report.json
@@ -0,0 +1,107 @@
+{
+    "forward": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0002733187473797605,
+            "ram": 3.467745284037441e-06,
+            "gpu": 0.0006654816712738266,
+            "total": 0.0009422681639376247
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 1061269.008411704
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0003119410920825127,
+                "ram": 3.9559487470294475e-06,
+                "gpu": 0.0007466994862481702,
+                "total": 0.0010625965270777123
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00030228011733983705,
+                "ram": 3.836296273777898e-06,
+                "gpu": 0.0007167997401060777,
+                "total": 0.0010229161537196926
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00029974089668523664,
+                "ram": 3.8041189763426866e-06,
+                "gpu": 0.0007288216941678805,
+                "total": 0.0010323667098294598
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0002975935455694222,
+                "ram": 3.776882410463701e-06,
+                "gpu": 0.0007451189294280791,
+                "total": 0.0010464893574079655
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00029881848271812086,
+                "ram": 3.7924211595837367e-06,
+                "gpu": 0.0007189064084578423,
+                "total": 0.0010215173123355467
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003022164312786724,
+                "ram": 3.835532227298596e-06,
+                "gpu": 0.000752818102254027,
+                "total": 0.001058870065759998
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003040544620228603,
+                "ram": 3.851383180007341e-06,
+                "gpu": 0.0007561631049302076,
+                "total": 0.0010640689501330769
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003084752662766226,
+                "ram": 3.915023086995131e-06,
+                "gpu": 0.0007552017152718804,
+                "total": 0.0010675920046354977
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00030806717982432034,
+                "ram": 3.909846778875872e-06,
+                "gpu": 0.0007342875318741005,
+                "total": 0.0010462645584772973
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 6.264318035080375e-05,
+            "ram": 4.424616703390787e-07,
+            "gpu": 9.757063361193197e-05,
+            "total": 0.0001606562756330748
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 6224468.954352673
+        },
+        "measures": null
+    }
+}
\ No newline at end of file
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/cli.log b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..35cdf6f94972a5f8a0e899827ed47886e479aba4
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/cli.log
@@ -0,0 +1,113 @@
+[2024-12-07 06:12:09,474][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:12:09,475][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:12:09,488][device-isolation][INFO] - 	+ Launched device(s) isolation process 1929
+[2024-12-07 06:12:09,488][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:12:09,495][process][INFO] - 	+ Launched benchmark in isolated process 1930.
+[PROC-0][2024-12-07 06:12:12,080][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:12:13,006][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:12:13,006][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:12:13,379][pytorch][INFO] - 	+ Using AutoModel class AutoModelForImageClassification
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:12:13,380][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:12:13,382][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:12:13,383][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:12:13,383][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:12:13,383][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:12:13,648][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:12:13,655][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:12:13,655][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:12:14,284][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:12:14,284][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:12:18,458][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:12:23,765][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:12:23,765][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:12:23,766][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:12:23,766][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:12:24,022][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:12:24,022][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:12:50,450][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:12:50,451][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:13:16,056][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:13:16,057][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:13:41,447][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:13:41,447][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:14:06,656][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:14:06,656][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:14:31,969][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:14:31,969][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:14:57,569][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:14:57,570][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:15:22,882][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:15:22,882][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:15:48,638][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:15:48,639][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:16:14,769][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:16:14,769][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:16:40,865][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ CPU: 0.000273 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ GPU: 0.000665 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ total: 0.000942 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ CPU: 0.000312 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ GPU: 0.000747 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 			+ total: 0.001063 (kWh)
+[PROC-0][2024-12-07 06:16:40,866][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ CPU: 0.000302 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ GPU: 0.000717 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ total: 0.001023 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ CPU: 0.000300 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ GPU: 0.000729 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ total: 0.001032 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ CPU: 0.000298 (kWh)
+[PROC-0][2024-12-07 06:16:40,867][energy][INFO] - 			+ GPU: 0.000745 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ total: 0.001046 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ CPU: 0.000299 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ GPU: 0.000719 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ total: 0.001022 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ CPU: 0.000302 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ GPU: 0.000753 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,868][energy][INFO] - 			+ total: 0.001059 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ CPU: 0.000304 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ GPU: 0.000756 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ total: 0.001064 (kWh)
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:16:40,869][energy][INFO] - 			+ CPU: 0.000308 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ GPU: 0.000755 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ total: 0.001068 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ CPU: 0.000308 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ GPU: 0.000734 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ total: 0.001046 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ CPU: 0.000063 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ GPU: 0.000098 (kWh)
+[PROC-0][2024-12-07 06:16:40,870][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:16:40,871][energy][INFO] - 			+ total: 0.000161 (kWh)
+[PROC-0][2024-12-07 06:16:40,871][energy][INFO] - 		+ forward energy efficiency: 1061269.008412 (samples/kWh)
+[PROC-0][2024-12-07 06:16:40,871][energy][INFO] - 		+ preprocess energy efficiency: 6224468.954353 (samples/kWh)
+[2024-12-07 06:16:41,595][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:16:41,643][datasets][INFO] - PyTorch version 2.4.0 available.
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/error.log b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..e6fd478dc060c906c5a442f1b5d5cb10eca94271
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/error.log
@@ -0,0 +1,169 @@
+[codecarbon INFO @ 06:12:14] [setup] RAM Tracking...
+[codecarbon INFO @ 06:12:14] [setup] GPU Tracking...
+[codecarbon INFO @ 06:12:14] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:12:14] GPU available. Starting setup
+[codecarbon INFO @ 06:12:14] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:12:14] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:12:14] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:12:14] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:12:14] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:12:15] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:12:15] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:12:15] >>> Tracker's metadata:
+[codecarbon INFO @ 06:12:15]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:12:15]   Python version: 3.9.20
+[codecarbon INFO @ 06:12:15]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:12:15]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:12:15]   CPU count: 48
+[codecarbon INFO @ 06:12:15]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:12:15]   GPU count: 1
+[codecarbon INFO @ 06:12:15]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:12:16] Not running on AWS
+[codecarbon DEBUG @ 06:12:17] Not running on Azure
+[codecarbon DEBUG @ 06:12:18] Not running on GCP
+[codecarbon INFO @ 06:12:18] Saving emissions data to file /runs/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/codecarbon.csv
+[codecarbon DEBUG @ 06:12:18] EmissionsData(timestamp='2024-12-07T06:12:18', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.0022014300047885627, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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Running processor on dataset:  99%|█████████▉| 989/1000 [00:05<00:00, 209.31 examples/s]
Running processor on dataset: 100%|██████████| 1000/1000 [00:05<00:00, 188.87 examples/s]
+[codecarbon WARNING @ 06:12:23] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:12:23] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.3003530502319336 W
+[codecarbon DEBUG @ 06:12:23] RAM : 0.30 W during 5.30 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:12:23] Energy consumed for all GPUs : 0.000098 kWh. Total GPU Power : 66.22416968130094 W
+[codecarbon DEBUG @ 06:12:23] GPU : 66.22 W during 5.30 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:12:23] Energy consumed for all CPUs : 0.000063 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:12:23] CPU : 42.50 W during 5.31 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:12:23] 0.000161 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:12:23] last_duration=5.303103837009985
+------------------------
+[codecarbon DEBUG @ 06:12:23] EmissionsData(timestamp='2024-12-07T06:12:23', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=5.306352487008553, emissions=5.9303754360058324e-05, emissions_rate=1.117599226686328e-05, cpu_power=42.5, gpu_power=66.22416968130094, ram_power=0.3003530502319336, cpu_energy=6.264318035080375e-05, gpu_energy=9.757063361193197e-05, ram_energy=4.424616703390787e-07, energy_consumed=0.0001606562756330748, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:12:24] EmissionsData(timestamp='2024-12-07T06:12:24', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.002248351986054331, emissions=5.9303754360058324e-05, emissions_rate=0.026376543676389138, cpu_power=42.5, gpu_power=66.22416968130094, ram_power=0.3003530502319336, cpu_energy=6.264318035080375e-05, gpu_energy=9.757063361193197e-05, ram_energy=4.424616703390787e-07, energy_consumed=0.0001606562756330748, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:12:50] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:12:50] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.5390939712524415 W
+[codecarbon DEBUG @ 06:12:50] RAM : 0.54 W during 26.42 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:12:50] Energy consumed for all GPUs : 0.000844 kWh. Total GPU Power : 101.75324561862581 W
+[codecarbon DEBUG @ 06:12:50] GPU : 101.75 W during 26.42 s [measurement time: 0.0052]
+[codecarbon INFO @ 06:12:50] Energy consumed for all CPUs : 0.000375 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:12:50] CPU : 42.50 W during 26.42 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:12:50] 0.001223 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:12:50] last_duration=26.417224776989315
+------------------------
+[codecarbon DEBUG @ 06:12:50] EmissionsData(timestamp='2024-12-07T06:12:50', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=26.42334758900688, emissions=0.0004515446623317505, emissions_rate=1.7088851471628458e-05, cpu_power=42.5, gpu_power=101.75324561862581, ram_power=0.5390939712524415, cpu_energy=0.0003745842724333165, gpu_energy=0.0008442701198601021, ram_energy=4.398410417368526e-06, energy_consumed=0.0012232528027107871, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:12:50] EmissionsData(timestamp='2024-12-07T06:12:50', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.0020264380145817995, emissions=0.0004515446623317505, emissions_rate=0.22282678230596498, cpu_power=42.5, gpu_power=101.75324561862581, ram_power=0.5390939712524415, cpu_energy=0.0003745842724333165, gpu_energy=0.0008442701198601021, ram_energy=4.398410417368526e-06, energy_consumed=0.0012232528027107871, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:13:16] Background scheduler didn't run for a long period (25s), results might be inaccurate
+[codecarbon INFO @ 06:13:16] Energy consumed for RAM : 0.000008 kWh. RAM Power : 0.5394387245178223 W
+[codecarbon DEBUG @ 06:13:16] RAM : 0.54 W during 25.60 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:13:16] Energy consumed for all GPUs : 0.001561 kWh. Total GPU Power : 100.78962781075715 W
+[codecarbon DEBUG @ 06:13:16] GPU : 100.79 W during 25.60 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:13:16] Energy consumed for all CPUs : 0.000677 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:13:16] CPU : 42.50 W during 25.60 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:13:16] 0.002246 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:13:16] last_duration=25.601819460018305
+------------------------
+[codecarbon DEBUG @ 06:13:16] EmissionsData(timestamp='2024-12-07T06:13:16', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.60500686900923, emissions=0.0008291381803694579, emissions_rate=3.238187689662357e-05, cpu_power=42.5, gpu_power=100.78962781075715, ram_power=0.5394387245178223, cpu_energy=0.0006768643897731535, gpu_energy=0.0015610698599661799, ram_energy=8.234706691146424e-06, energy_consumed=0.0022461689564304797, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:13:16] EmissionsData(timestamp='2024-12-07T06:13:16', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.00499845200101845, emissions=0.0008291381803694579, emissions_rate=0.1658789921760814, cpu_power=42.5, gpu_power=100.78962781075715, ram_power=0.5394387245178223, cpu_energy=0.0006768643897731535, gpu_energy=0.0015610698599661799, ram_energy=8.234706691146424e-06, energy_consumed=0.0022461689564304797, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:13:41] Background scheduler didn't run for a long period (25s), results might be inaccurate
+[codecarbon INFO @ 06:13:41] Energy consumed for RAM : 0.000012 kWh. RAM Power : 0.5394473075866699 W
+[codecarbon DEBUG @ 06:13:41] RAM : 0.54 W during 25.39 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:13:41] Energy consumed for all GPUs : 0.002290 kWh. Total GPU Power : 103.34852407766513 W
+[codecarbon DEBUG @ 06:13:41] GPU : 103.35 W during 25.39 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:13:41] Energy consumed for all CPUs : 0.000977 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:13:41] CPU : 42.50 W during 25.39 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:13:41] 0.003279 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:13:41] last_duration=25.386688063008478
+------------------------
+[codecarbon DEBUG @ 06:13:41] EmissionsData(timestamp='2024-12-07T06:13:41', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.38991938298568, emissions=0.0012102202235574656, emissions_rate=4.766538267815295e-05, cpu_power=42.5, gpu_power=103.34852407766513, ram_power=0.5394473075866699, cpu_energy=0.0009766052864583902, gpu_energy=0.0022898915541340603, ram_energy=1.203882566748911e-05, energy_consumed=0.0032785356662599395, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:13:41] EmissionsData(timestamp='2024-12-07T06:13:41', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.005143425019923598, emissions=0.0012102202235574656, emissions_rate=0.2352946176661564, cpu_power=42.5, gpu_power=103.34852407766513, ram_power=0.5394473075866699, cpu_energy=0.0009766052864583902, gpu_energy=0.0022898915541340603, ram_energy=1.203882566748911e-05, energy_consumed=0.0032785356662599395, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:14:06] Background scheduler didn't run for a long period (25s), results might be inaccurate
+[codecarbon INFO @ 06:14:06] Energy consumed for RAM : 0.000016 kWh. RAM Power : 0.5394487380981445 W
+[codecarbon DEBUG @ 06:14:06] RAM : 0.54 W during 25.20 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:14:06] Energy consumed for all GPUs : 0.003035 kWh. Total GPU Power : 106.42177300618566 W
+[codecarbon DEBUG @ 06:14:06] GPU : 106.42 W during 25.21 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:14:06] Energy consumed for all CPUs : 0.001274 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:14:06] CPU : 42.50 W during 25.21 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:14:06] 0.004325 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:14:06] last_duration=25.204850894020637
+------------------------
+[codecarbon DEBUG @ 06:14:06] EmissionsData(timestamp='2024-12-07T06:14:06', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.20802604200435, emissions=0.001596515421473535, emissions_rate=6.333361520704747e-05, cpu_power=42.5, gpu_power=106.42177300618566, ram_power=0.5394487380981445, cpu_energy=0.0012741988320278124, gpu_energy=0.0030350104835621394, ram_energy=1.5815708077952812e-05, energy_consumed=0.004325025023667905, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:14:06] EmissionsData(timestamp='2024-12-07T06:14:06', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.002026167989242822, emissions=0.001596515421473535, emissions_rate=0.7879482007166405, cpu_power=42.5, gpu_power=106.42177300618566, ram_power=0.5394487380981445, cpu_energy=0.0012741988320278124, gpu_energy=0.0030350104835621394, ram_energy=1.5815708077952812e-05, energy_consumed=0.004325025023667905, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:14:31] Background scheduler didn't run for a long period (25s), results might be inaccurate
+[codecarbon INFO @ 06:14:31] Energy consumed for RAM : 0.000020 kWh. RAM Power : 0.5394487380981445 W
+[codecarbon DEBUG @ 06:14:31] RAM : 0.54 W during 25.31 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:14:31] Energy consumed for all GPUs : 0.003754 kWh. Total GPU Power : 102.25727595835876 W
+[codecarbon DEBUG @ 06:14:31] GPU : 102.26 W during 25.31 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:14:31] Energy consumed for all CPUs : 0.001573 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:14:31] CPU : 42.50 W during 25.31 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:14:31] 0.005347 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:14:31] last_duration=25.308556225005304
+------------------------
+[codecarbon DEBUG @ 06:14:31] EmissionsData(timestamp='2024-12-07T06:14:31', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.311783754004864, emissions=0.001973592579067138, emissions_rate=7.797129582994615e-05, cpu_power=42.5, gpu_power=102.25727595835876, ram_power=0.5394487380981445, cpu_energy=0.0015730173147459332, gpu_energy=0.0037539168920199817, ram_energy=1.960812923753655e-05, energy_consumed=0.005346542336003452, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:14:31] EmissionsData(timestamp='2024-12-07T06:14:31', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.0020140370179433376, emissions=0.001973592579067138, emissions_rate=0.9799187211973394, cpu_power=42.5, gpu_power=102.25727595835876, ram_power=0.5394487380981445, cpu_energy=0.0015730173147459332, gpu_energy=0.0037539168920199817, ram_energy=1.960812923753655e-05, energy_consumed=0.005346542336003452, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:14:57] Background scheduler didn't run for a long period (25s), results might be inaccurate
+[codecarbon INFO @ 06:14:57] Energy consumed for RAM : 0.000023 kWh. RAM Power : 0.5394487380981445 W
+[codecarbon DEBUG @ 06:14:57] RAM : 0.54 W during 25.60 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:14:57] Energy consumed for all GPUs : 0.004507 kWh. Total GPU Power : 105.87721643054066 W
+[codecarbon DEBUG @ 06:14:57] GPU : 105.88 W during 25.60 s [measurement time: 0.0024]
+[codecarbon INFO @ 06:14:57] Energy consumed for all CPUs : 0.001875 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:14:57] CPU : 42.50 W during 25.60 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:14:57] 0.006405 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:14:57] last_duration=25.596256913006073
+------------------------
+[codecarbon DEBUG @ 06:14:57] EmissionsData(timestamp='2024-12-07T06:14:57', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.599616974999662, emissions=0.0023644579220585818, emissions_rate=9.2363019507975e-05, cpu_power=42.5, gpu_power=105.87721643054066, ram_power=0.5394487380981445, cpu_energy=0.0018752337460246056, gpu_energy=0.004506734994274009, ram_energy=2.3443661464835144e-05, energy_consumed=0.00640541240176345, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:14:57] EmissionsData(timestamp='2024-12-07T06:14:57', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.0020184570166748017, emissions=0.0023644579220585818, emissions_rate=1.1714185154924828, cpu_power=42.5, gpu_power=105.87721643054066, ram_power=0.5394487380981445, cpu_energy=0.0018752337460246056, gpu_energy=0.004506734994274009, ram_energy=2.3443661464835144e-05, energy_consumed=0.00640541240176345, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:15:22] Background scheduler didn't run for a long period (25s), results might be inaccurate
+[codecarbon INFO @ 06:15:22] Energy consumed for RAM : 0.000027 kWh. RAM Power : 0.5394487380981445 W
+[codecarbon DEBUG @ 06:15:22] RAM : 0.54 W during 25.31 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:15:22] Energy consumed for all GPUs : 0.005251 kWh. Total GPU Power : 105.85402074969691 W
+[codecarbon DEBUG @ 06:15:22] GPU : 105.85 W during 25.31 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:15:22] Energy consumed for all CPUs : 0.002174 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:15:22] CPU : 42.50 W during 25.31 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:15:22] 0.007452 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:15:22] EmissionsData(timestamp='2024-12-07T06:15:22', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.311385103996145, emissions=0.002750864214338455, emissions_rate=0.00010868090398988677, cpu_power=42.5, gpu_power=105.85402074969691, ram_power=0.5394487380981445, cpu_energy=0.0021740477638816326, gpu_energy=0.005250918922953929, ram_energy=2.723603147284466e-05, energy_consumed=0.0074522027183084065, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 06:15:22] 0.015267 g.CO2eq/s mean an estimation of 481.4703190050936 kg.CO2eq/year
+[codecarbon DEBUG @ 06:15:22] last_duration=25.308216695004376
+------------------------
+[codecarbon DEBUG @ 06:15:22] EmissionsData(timestamp='2024-12-07T06:15:22', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.311723250022624, emissions=0.002750864214338455, emissions_rate=0.00010867945209285567, cpu_power=42.5, gpu_power=105.85402074969691, ram_power=0.5394487380981445, cpu_energy=0.0021740477638816326, gpu_energy=0.005250918922953929, ram_energy=2.723603147284466e-05, energy_consumed=0.0074522027183084065, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:15:22] EmissionsData(timestamp='2024-12-07T06:15:22', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.002025657973717898, emissions=0.002750864214338455, emissions_rate=1.3580102120050954, cpu_power=42.5, gpu_power=105.85402074969691, ram_power=0.5394487380981445, cpu_energy=0.0021740477638816326, gpu_energy=0.005250918922953929, ram_energy=2.723603147284466e-05, energy_consumed=0.0074522027183084065, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:15:48] Background scheduler didn't run for a long period (25s), results might be inaccurate
+[codecarbon INFO @ 06:15:48] Energy consumed for RAM : 0.000031 kWh. RAM Power : 0.5394515991210939 W
+[codecarbon DEBUG @ 06:15:48] RAM : 0.54 W during 25.70 s [measurement time: 0.0505]
+[codecarbon INFO @ 06:15:48] Energy consumed for all GPUs : 0.006007 kWh. Total GPU Power : 105.70478937518956 W
+[codecarbon DEBUG @ 06:15:48] GPU : 105.70 W during 25.75 s [measurement time: 0.0024]
+[codecarbon INFO @ 06:15:48] Energy consumed for all CPUs : 0.002478 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:15:48] CPU : 42.50 W during 25.76 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:15:48] 0.008516 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:15:48] last_duration=25.7019018449937
+------------------------
+[codecarbon DEBUG @ 06:15:48] EmissionsData(timestamp='2024-12-07T06:15:48', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=25.75530242099194, emissions=0.0031436486442786814, emissions_rate=0.00012205830833950686, cpu_power=42.5, gpu_power=105.70478937518956, ram_power=0.5394515991210939, cpu_energy=0.002478102225904493, gpu_energy=0.006007082027884136, ram_energy=3.1087414652852e-05, energy_consumed=0.008516271668441483, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:15:48] EmissionsData(timestamp='2024-12-07T06:15:48', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.0020231870003044605, emissions=0.0031436486442786814, emissions_rate=1.5538102230815083, cpu_power=42.5, gpu_power=105.70478937518956, ram_power=0.5394515991210939, cpu_energy=0.002478102225904493, gpu_energy=0.006007082027884136, ram_energy=3.1087414652852e-05, energy_consumed=0.008516271668441483, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:16:14] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:16:14] Energy consumed for RAM : 0.000035 kWh. RAM Power : 0.5394515991210939 W
+[codecarbon DEBUG @ 06:16:14] RAM : 0.54 W during 26.13 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:16:14] Energy consumed for all GPUs : 0.006762 kWh. Total GPU Power : 104.05658885660858 W
+[codecarbon DEBUG @ 06:16:14] GPU : 104.06 W during 26.13 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:16:14] Energy consumed for all CPUs : 0.002787 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:16:14] CPU : 42.50 W during 26.13 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:16:14] 0.009584 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:16:14] last_duration=26.12659707700368
+------------------------
+[codecarbon DEBUG @ 06:16:14] EmissionsData(timestamp='2024-12-07T06:16:14', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=26.129770185012603, emissions=0.003537733554750934, emissions_rate=0.00013539091732158026, cpu_power=42.5, gpu_power=104.05658885660858, ram_power=0.5394515991210939, cpu_energy=0.0027865774921811155, gpu_energy=0.006762283743156017, ram_energy=3.500243773984713e-05, energy_consumed=0.009583863673076981, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:16:14] EmissionsData(timestamp='2024-12-07T06:16:14', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=0.002026277012191713, emissions=0.003537733554750934, emissions_rate=1.7459278931089295, cpu_power=42.5, gpu_power=104.05658885660858, ram_power=0.5394515991210939, cpu_energy=0.0027865774921811155, gpu_energy=0.006762283743156017, ram_energy=3.500243773984713e-05, energy_consumed=0.009583863673076981, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:16:40] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:16:40] Energy consumed for RAM : 0.000039 kWh. RAM Power : 0.5394515991210939 W
+[codecarbon DEBUG @ 06:16:40] RAM : 0.54 W during 26.09 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:16:40] Energy consumed for all GPUs : 0.007497 kWh. Total GPU Power : 101.30887343782058 W
+[codecarbon DEBUG @ 06:16:40] GPU : 101.31 W during 26.09 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:16:40] Energy consumed for all CPUs : 0.003095 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:16:40] CPU : 42.50 W during 26.10 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:16:40] 0.010630 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:16:40] last_duration=26.092054095002823
+------------------------
+[codecarbon DEBUG @ 06:16:40] EmissionsData(timestamp='2024-12-07T06:16:40', project_name='codecarbon', run_id='1227b6b4-bf23-48a4-ac0a-e6b6f69567eb', duration=26.095212693006033, emissions=0.00392394577165358, emissions_rate=0.00015037033105713162, cpu_power=42.5, gpu_power=101.30887343782058, ram_power=0.5394515991210939, cpu_energy=0.003094644672005436, gpu_energy=0.007496571275030117, ram_energy=3.8912284518723004e-05, energy_consumed=0.010630128231554278, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/experiment_config.json b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..ce8d8a636f02d1e5b473011ee914ecf85ede24f0
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/experiment_config.json
@@ -0,0 +1,107 @@
+{
+    "experiment_name": "image_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "image-classification",
+        "model": "Falconsai/nsfw_image_detection",
+        "processor": "Falconsai/nsfw_image_detection",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/image_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/forward_codecarbon.json b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/forward_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..307d3826168428e4fadfc17c0fe68f9bbf5bc4b3
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/forward_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:16:40",
+    "project_name": "codecarbon",
+    "run_id": "1227b6b4-bf23-48a4-ac0a-e6b6f69567eb",
+    "duration": -1733393394.2416937,
+    "emissions": 0.0003862122169026464,
+    "emissions_rate": 1.4801266918704773e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 101.30887343782058,
+    "ram_power": 0.5394515991210939,
+    "cpu_energy": 0.00030806717982432034,
+    "gpu_energy": 0.0007342875318741005,
+    "ram_energy": 3.909846778875872e-06,
+    "energy_consumed": 0.0010462645584772973,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/preprocess_codecarbon.json b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/preprocess_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..ae76476883cc8798d6b4e79cd67d9ce173fe8142
--- /dev/null
+++ b/image_classification/Falconsai/nsfw_image_detection/2024-12-07-06-12-06/preprocess_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:12:23",
+    "project_name": "codecarbon",
+    "run_id": "1227b6b4-bf23-48a4-ac0a-e6b6f69567eb",
+    "duration": -1733393415.0308454,
+    "emissions": 5.9303754360058324e-05,
+    "emissions_rate": 1.1180630740474825e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 66.22416968130094,
+    "ram_power": 0.3003530502319336,
+    "cpu_energy": 6.264318035080375e-05,
+    "gpu_energy": 9.757063361193197e-05,
+    "ram_energy": 4.424616703390787e-07,
+    "energy_consumed": 0.0001606562756330748,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/config.yaml b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2f7b2525741e6905150aa007f119412b2756fad7
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: image-classification
+  model: WinKawaks/vit-tiny-patch16-224
+  processor: WinKawaks/vit-tiny-patch16-224
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/image_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: image_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/hydra.yaml b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..38b15f155941fd95a9227d83bee365e477803eaf
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03
+    - hydra.mode=RUN
+    task:
+    - backend.model=WinKawaks/vit-tiny-patch16-224
+    - backend.processor=WinKawaks/vit-tiny-patch16-224
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=WinKawaks/vit-tiny-patch16-224,backend.processor=WinKawaks/vit-tiny-patch16-224
+    id: ???
+    num: ???
+    config_name: image_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/overrides.yaml b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..e601149dca5fb8b260ad2b4d9ac86e8974053ec3
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=WinKawaks/vit-tiny-patch16-224
+- backend.processor=WinKawaks/vit-tiny-patch16-224
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/benchmark_report.json b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/benchmark_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..a141744eb9c475e21c7a46278c6fd3b86cfea884
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/benchmark_report.json
@@ -0,0 +1,107 @@
+{
+    "forward": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.0002883970840196566,
+            "ram": 5.095733264468404e-06,
+            "gpu": 0.0004787142718599924,
+            "total": 0.0007722070891441174
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 1294989.4064147465
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.00032237290750636023,
+                "ram": 5.68212431902591e-06,
+                "gpu": 0.0005520429416339123,
+                "total": 0.0008800979734592985
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003097717381620088,
+                "ram": 5.479027689579595e-06,
+                "gpu": 0.0005212548614479395,
+                "total": 0.000836505627299528
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003115549147229507,
+                "ram": 5.5103307066773305e-06,
+                "gpu": 0.0005199762493142135,
+                "total": 0.000837041494743842
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003090231170242582,
+                "ram": 5.465771436356048e-06,
+                "gpu": 0.0005080784620177248,
+                "total": 0.0008225673504783388
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003103978889738453,
+                "ram": 5.479996767840904e-06,
+                "gpu": 0.0005124937433280685,
+                "total": 0.0008283716290697547
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00036013543034567005,
+                "ram": 6.369912820287744e-06,
+                "gpu": 0.0005919732513561815,
+                "total": 0.0009584785945221394
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00031267757493666677,
+                "ram": 5.530006381177219e-06,
+                "gpu": 0.0005158204126560761,
+                "total": 0.0008340279939739199
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00032461974724992595,
+                "ram": 5.730779025581735e-06,
+                "gpu": 0.0005323679258939507,
+                "total": 0.0008627184521694583
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003234175212748799,
+                "ram": 5.709383498157549e-06,
+                "gpu": 0.0005331348709518569,
+                "total": 0.0008622617757248954
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 7.654690115844764e-05,
+            "ram": 9.692753425157112e-07,
+            "gpu": 0.00012796260237002421,
+            "total": 0.00020547877887098755
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 4866682.610703379
+        },
+        "measures": null
+    }
+}
\ No newline at end of file
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/cli.log b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..f10946eed0f9b8bb8f2cbb3c091b867e2c1bb4c7
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/cli.log
@@ -0,0 +1,113 @@
+[2024-12-07 06:05:06,630][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:05:06,630][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:05:06,642][device-isolation][INFO] - 	+ Launched device(s) isolation process 674
+[2024-12-07 06:05:06,643][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:05:06,649][process][INFO] - 	+ Launched benchmark in isolated process 675.
+[PROC-0][2024-12-07 06:05:09,305][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:05:10,208][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:05:10,208][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:05:10,688][pytorch][INFO] - 	+ Using AutoModel class AutoModelForImageClassification
+[PROC-0][2024-12-07 06:05:10,688][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:05:10,689][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:05:10,691][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:05:10,691][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:05:10,695][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:05:10,695][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:05:10,863][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:05:10,869][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:05:10,869][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:05:13,479][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:05:13,479][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:05:17,649][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:05:24,134][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:05:24,135][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:05:24,135][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:05:24,135][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:05:24,427][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:05:24,428][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:05:51,735][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:05:51,736][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:06:17,976][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:06:17,976][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:06:44,367][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:06:44,368][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:07:10,544][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:07:10,545][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:07:36,838][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:07:36,839][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:08:07,345][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:08:07,345][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:08:35,256][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:08:35,257][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:09:01,743][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:09:01,744][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:09:29,241][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:09:29,242][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:09:56,638][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ CPU: 0.000288 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ GPU: 0.000479 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ total: 0.000772 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ CPU: 0.000322 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ GPU: 0.000552 (kWh)
+[PROC-0][2024-12-07 06:09:56,639][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ total: 0.000880 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ CPU: 0.000310 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ GPU: 0.000521 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ total: 0.000837 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ CPU: 0.000312 (kWh)
+[PROC-0][2024-12-07 06:09:56,640][energy][INFO] - 			+ GPU: 0.000520 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ total: 0.000837 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ CPU: 0.000309 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ GPU: 0.000508 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ total: 0.000823 (kWh)
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:09:56,641][energy][INFO] - 			+ CPU: 0.000310 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ GPU: 0.000512 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ RAM: 0.000005 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ total: 0.000828 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ CPU: 0.000360 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ GPU: 0.000592 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 			+ total: 0.000958 (kWh)
+[PROC-0][2024-12-07 06:09:56,642][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ CPU: 0.000313 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ GPU: 0.000516 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,643][energy][INFO] - 			+ total: 0.000834 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ CPU: 0.000325 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ GPU: 0.000532 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ total: 0.000863 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ CPU: 0.000323 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ GPU: 0.000533 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ RAM: 0.000006 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 			+ total: 0.000862 (kWh)
+[PROC-0][2024-12-07 06:09:56,644][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ CPU: 0.000077 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ GPU: 0.000128 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 			+ total: 0.000205 (kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 		+ forward energy efficiency: 1294989.406415 (samples/kWh)
+[PROC-0][2024-12-07 06:09:56,645][energy][INFO] - 		+ preprocess energy efficiency: 4866682.610703 (samples/kWh)
+[2024-12-07 06:09:57,358][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:09:57,404][datasets][INFO] - PyTorch version 2.4.0 available.
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/error.log b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..8253484bf9179872fe53d6963a0faf0c029900ec
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/error.log
@@ -0,0 +1,185 @@
+
Downloading readme:   0%|          | 0.00/281 [00:00<?, ?B/s]
Downloading readme: 100%|██████████| 281/281 [00:00<00:00, 3.51MB/s]
+
+
+
Downloading data:   0%|          | 0.00/49.2M [00:00<?, ?B/s]
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+[codecarbon INFO @ 06:05:13] [setup] RAM Tracking...
+[codecarbon INFO @ 06:05:13] [setup] GPU Tracking...
+[codecarbon INFO @ 06:05:13] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:05:13] GPU available. Starting setup
+[codecarbon INFO @ 06:05:13] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:05:13] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:05:13] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:05:13] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:05:13] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:05:14] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:05:14] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:05:14] >>> Tracker's metadata:
+[codecarbon INFO @ 06:05:14]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:05:14]   Python version: 3.9.20
+[codecarbon INFO @ 06:05:14]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:05:14]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:05:14]   CPU count: 48
+[codecarbon INFO @ 06:05:14]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:05:14]   GPU count: 1
+[codecarbon INFO @ 06:05:14]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:05:15] Not running on AWS
+[codecarbon DEBUG @ 06:05:16] Not running on Azure
+[codecarbon DEBUG @ 06:05:17] Not running on GCP
+[codecarbon INFO @ 06:05:17] Saving emissions data to file /runs/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/codecarbon.csv
+[codecarbon DEBUG @ 06:05:17] EmissionsData(timestamp='2024-12-07T06:05:17', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.0021764500124845654, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
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+[codecarbon WARNING @ 06:05:24] Background scheduler didn't run for a long period (6s), results might be inaccurate
+[codecarbon INFO @ 06:05:24] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.5384030342102051 W
+[codecarbon DEBUG @ 06:05:24] RAM : 0.54 W during 6.48 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:05:24] Energy consumed for all GPUs : 0.000128 kWh. Total GPU Power : 71.0711882800841 W
+[codecarbon DEBUG @ 06:05:24] GPU : 71.07 W during 6.48 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:05:24] Energy consumed for all CPUs : 0.000077 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:05:24] CPU : 42.50 W during 6.48 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:05:24] 0.000205 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:05:24] last_duration=6.4807795860106125
+------------------------
+[codecarbon DEBUG @ 06:05:24] EmissionsData(timestamp='2024-12-07T06:05:24', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=6.484081496018916, emissions=7.584928120829092e-05, emissions_rate=1.1697768026953502e-05, cpu_power=42.5, gpu_power=71.0711882800841, ram_power=0.5384030342102051, cpu_energy=7.654690115844764e-05, gpu_energy=0.00012796260237002421, ram_energy=9.692753425157112e-07, energy_consumed=0.00020547877887098755, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:05:24] EmissionsData(timestamp='2024-12-07T06:05:24', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.004220338014420122, emissions=7.584928120829092e-05, emissions_rate=0.01797232376864787, cpu_power=42.5, gpu_power=71.0711882800841, ram_power=0.5384030342102051, cpu_energy=7.654690115844764e-05, gpu_energy=0.00012796260237002421, ram_energy=9.692753425157112e-07, energy_consumed=0.00020547877887098755, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
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+[codecarbon WARNING @ 06:05:51] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:05:51] Energy consumed for RAM : 0.000007 kWh. RAM Power : 0.7506995201110841 W
+[codecarbon DEBUG @ 06:05:51] RAM : 0.75 W during 27.25 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:05:51] Energy consumed for all GPUs : 0.000680 kWh. Total GPU Power : 72.93181373162592 W
+[codecarbon DEBUG @ 06:05:51] GPU : 72.93 W during 27.25 s [measurement time: 0.0574]
+[codecarbon INFO @ 06:05:51] Energy consumed for all CPUs : 0.000399 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:05:51] CPU : 42.50 W during 27.31 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:05:51] 0.001086 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:05:51] last_duration=27.248693358007586
+------------------------
+[codecarbon DEBUG @ 06:05:51] EmissionsData(timestamp='2024-12-07T06:05:51', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=27.306987279007444, emissions=0.00040072369912409, emissions_rate=1.4674767854458662e-05, cpu_power=42.5, gpu_power=72.93181373162592, ram_power=0.7506995201110841, cpu_energy=0.0003989198086648079, gpu_energy=0.0006800055440039365, ram_energy=6.6513996615416216e-06, energy_consumed=0.001085576752330286, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:05:51] EmissionsData(timestamp='2024-12-07T06:05:51', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.0021291300072334707, emissions=0.00040072369912409, emissions_rate=0.18821006597186551, cpu_power=42.5, gpu_power=72.93181373162592, ram_power=0.7506995201110841, cpu_energy=0.0003989198086648079, gpu_energy=0.0006800055440039365, ram_energy=6.6513996615416216e-06, energy_consumed=0.001085576752330286, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:06:17] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:06:17] Energy consumed for RAM : 0.000012 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:06:17] RAM : 0.75 W during 26.24 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:06:17] Energy consumed for all GPUs : 0.001201 kWh. Total GPU Power : 71.52144180378073 W
+[codecarbon DEBUG @ 06:06:17] GPU : 71.52 W during 26.24 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:06:17] Energy consumed for all CPUs : 0.000709 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:06:17] CPU : 42.50 W during 26.24 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:06:17] 0.001922 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:06:17] last_duration=26.2363426410011
+------------------------
+[codecarbon DEBUG @ 06:06:17] EmissionsData(timestamp='2024-12-07T06:06:17', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=26.239594511018367, emissions=0.0007095066834594046, emissions_rate=2.703954450063902e-05, cpu_power=42.5, gpu_power=71.52144180378073, ram_power=0.751798152923584, cpu_energy=0.0007086915468268167, gpu_energy=0.001201260405451876, ram_energy=1.2130427351121217e-05, energy_consumed=0.001922082379629814, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:06:17] EmissionsData(timestamp='2024-12-07T06:06:17', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.002029747993219644, emissions=0.0007095066834594046, emissions_rate=0.3495540755943623, cpu_power=42.5, gpu_power=71.52144180378073, ram_power=0.751798152923584, cpu_energy=0.0007086915468268167, gpu_energy=0.001201260405451876, ram_energy=1.2130427351121217e-05, energy_consumed=0.001922082379629814, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:06:44] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:06:44] Energy consumed for RAM : 0.000018 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:06:44] RAM : 0.75 W during 26.39 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:06:44] Energy consumed for all GPUs : 0.001721 kWh. Total GPU Power : 70.940680081549 W
+[codecarbon DEBUG @ 06:06:44] GPU : 70.94 W during 26.39 s [measurement time: 0.0035]
+[codecarbon INFO @ 06:06:44] Energy consumed for all CPUs : 0.001020 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:06:44] CPU : 42.50 W during 26.39 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:06:44] 0.002759 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:06:44] last_duration=26.386212502984563
+------------------------
+[codecarbon DEBUG @ 06:06:44] EmissionsData(timestamp='2024-12-07T06:06:44', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=26.390646324987756, emissions=0.0010184874748904078, emissions_rate=3.8592744654611274e-05, cpu_power=42.5, gpu_power=70.940680081549, ram_power=0.751798152923584, cpu_energy=0.0010202464615497674, gpu_energy=0.0017212366547660896, ram_energy=1.7640758057798547e-05, energy_consumed=0.002759123874373656, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:06:44] EmissionsData(timestamp='2024-12-07T06:06:44', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.0020360380003694445, emissions=0.0010184874748904078, emissions_rate=0.5002300913369989, cpu_power=42.5, gpu_power=70.940680081549, ram_power=0.751798152923584, cpu_energy=0.0010202464615497674, gpu_energy=0.0017212366547660896, ram_energy=1.7640758057798547e-05, energy_consumed=0.002759123874373656, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:07:10] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:07:10] Energy consumed for RAM : 0.000023 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:07:10] RAM : 0.75 W during 26.17 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:07:10] Energy consumed for all GPUs : 0.002229 kWh. Total GPU Power : 69.88259126746114 W
+[codecarbon DEBUG @ 06:07:10] GPU : 69.88 W during 26.17 s [measurement time: 0.0024]
+[codecarbon INFO @ 06:07:10] Energy consumed for all CPUs : 0.001329 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:07:10] CPU : 42.50 W during 26.18 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:07:10] 0.003582 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:07:10] last_duration=26.172862924984656
+------------------------
+[codecarbon DEBUG @ 06:07:10] EmissionsData(timestamp='2024-12-07T06:07:10', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=26.176180256996304, emissions=0.0013221253620824636, emissions_rate=5.050872010743772e-05, cpu_power=42.5, gpu_power=69.88259126746114, ram_power=0.751798152923584, cpu_energy=0.0013292695785740256, gpu_energy=0.0022293151167838143, ram_energy=2.3106529494154596e-05, energy_consumed=0.003581691224851995, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:07:10] EmissionsData(timestamp='2024-12-07T06:07:10', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.002011698001297191, emissions=0.0013221253620824636, emissions_rate=0.657218608971091, cpu_power=42.5, gpu_power=69.88259126746114, ram_power=0.751798152923584, cpu_energy=0.0013292695785740256, gpu_energy=0.0022293151167838143, ram_energy=2.3106529494154596e-05, energy_consumed=0.003581691224851995, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:07:36] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:07:36] Energy consumed for RAM : 0.000029 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:07:36] RAM : 0.75 W during 26.24 s [measurement time: 0.0489]
+[codecarbon INFO @ 06:07:36] Energy consumed for all GPUs : 0.002742 kWh. Total GPU Power : 70.17721455571517 W
+[codecarbon DEBUG @ 06:07:36] GPU : 70.18 W during 26.29 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:07:36] Energy consumed for all CPUs : 0.001640 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:07:36] CPU : 42.50 W during 26.29 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:07:36] 0.004410 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:07:36] last_duration=26.24098143100855
+------------------------
+[codecarbon DEBUG @ 06:07:36] EmissionsData(timestamp='2024-12-07T06:07:36', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=26.29262985699461, emissions=0.0016279058080414664, emissions_rate=6.191490987762092e-05, cpu_power=42.5, gpu_power=70.17721455571517, ram_power=0.751798152923584, cpu_energy=0.001639667467547871, gpu_energy=0.002741808860111883, ram_energy=2.85865262619955e-05, energy_consumed=0.0044100628539217495, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:07:36] EmissionsData(timestamp='2024-12-07T06:07:36', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.0020348870020825416, emissions=0.0016279058080414664, emissions_rate=0.7999981357075047, cpu_power=42.5, gpu_power=70.17721455571517, ram_power=0.751798152923584, cpu_energy=0.001639667467547871, gpu_energy=0.002741808860111883, ram_energy=2.85865262619955e-05, energy_consumed=0.0044100628539217495, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:08:07] Background scheduler didn't run for a long period (30s), results might be inaccurate
+[codecarbon INFO @ 06:08:07] Energy consumed for RAM : 0.000035 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:08:07] RAM : 0.75 W during 30.50 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:08:07] Energy consumed for all GPUs : 0.003334 kWh. Total GPU Power : 69.86479694349366 W
+[codecarbon DEBUG @ 06:08:07] GPU : 69.86 W during 30.50 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:08:07] Energy consumed for all CPUs : 0.002000 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:08:07] CPU : 42.50 W during 30.51 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:08:07] 0.005369 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:08:07] last_duration=30.50235290400451
+------------------------
+[codecarbon DEBUG @ 06:08:07] EmissionsData(timestamp='2024-12-07T06:08:07', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=30.50572541600559, emissions=0.001981713207751987, emissions_rate=6.496200895823417e-05, cpu_power=42.5, gpu_power=69.86479694349366, ram_power=0.751798152923584, cpu_energy=0.001999802897893541, gpu_energy=0.0033337821114680644, ram_energy=3.495643908228324e-05, energy_consumed=0.005368541448443889, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:08:07] EmissionsData(timestamp='2024-12-07T06:08:07', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.002043087995843962, emissions=0.001981713207751987, emissions_rate=0.969959792129941, cpu_power=42.5, gpu_power=69.86479694349366, ram_power=0.751798152923584, cpu_energy=0.001999802897893541, gpu_energy=0.0033337821114680644, ram_energy=3.495643908228324e-05, energy_consumed=0.005368541448443889, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:08:35] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:08:35] Energy consumed for RAM : 0.000041 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:08:35] RAM : 0.75 W during 27.91 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:08:35] Energy consumed for all GPUs : 0.003874 kWh. Total GPU Power : 69.72583482597477 W
+[codecarbon DEBUG @ 06:08:35] GPU : 69.73 W during 27.91 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:08:35] Energy consumed for all CPUs : 0.002329 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:08:35] CPU : 42.50 W during 27.91 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:08:35] 0.006244 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:08:35] EmissionsData(timestamp='2024-12-07T06:08:35', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=27.910323977004737, emissions=0.0023050204056838217, emissions_rate=8.258665888589913e-05, cpu_power=42.5, gpu_power=69.72583482597477, ram_power=0.751798152923584, cpu_energy=0.0023292987802305412, gpu_energy=0.0038743105994458737, ram_energy=4.07843797313968e-05, energy_consumed=0.006244393759407812, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 06:08:35] 0.011585 g.CO2eq/s mean an estimation of 365.3329932620017 kg.CO2eq/year
+[codecarbon DEBUG @ 06:08:35] last_duration=27.907112407992827
+------------------------
+[codecarbon DEBUG @ 06:08:35] EmissionsData(timestamp='2024-12-07T06:08:35', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=27.910660583002027, emissions=0.0023050204056838217, emissions_rate=8.258566288064176e-05, cpu_power=42.5, gpu_power=69.72583482597477, ram_power=0.751798152923584, cpu_energy=0.0023292987802305412, gpu_energy=0.0038743105994458737, ram_energy=4.07843797313968e-05, energy_consumed=0.006244393759407812, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:08:35] EmissionsData(timestamp='2024-12-07T06:08:35', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.0020115480001550168, emissions=0.0023050204056838217, emissions_rate=1.1458938118832804, cpu_power=42.5, gpu_power=69.72583482597477, ram_power=0.751798152923584, cpu_energy=0.0023292987802305412, gpu_energy=0.0038743105994458737, ram_energy=4.07843797313968e-05, energy_consumed=0.006244393759407812, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:09:01] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:09:01] Energy consumed for RAM : 0.000046 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:09:01] RAM : 0.75 W during 26.48 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:09:01] Energy consumed for all GPUs : 0.004390 kWh. Total GPU Power : 70.12335369940763 W
+[codecarbon DEBUG @ 06:09:01] GPU : 70.12 W during 26.48 s [measurement time: 0.0044]
+[codecarbon INFO @ 06:09:01] Energy consumed for all CPUs : 0.002642 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:09:01] CPU : 42.50 W during 26.49 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:09:01] 0.007078 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:09:01] last_duration=26.480451790994266
+------------------------
+[codecarbon DEBUG @ 06:09:01] EmissionsData(timestamp='2024-12-07T06:09:01', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=26.485741579002934, emissions=0.0026128888103828466, emissions_rate=9.865265817039697e-05, cpu_power=42.5, gpu_power=70.12335369940763, ram_power=0.751798152923584, cpu_energy=0.002641976355167208, gpu_energy=0.00439013101210195, ram_energy=4.631438611257402e-05, energy_consumed=0.007078421753381732, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:09:01] EmissionsData(timestamp='2024-12-07T06:09:01', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.0020345580123830587, emissions=0.0026128888103828466, emissions_rate=1.2842537762402728, cpu_power=42.5, gpu_power=70.12335369940763, ram_power=0.751798152923584, cpu_energy=0.002641976355167208, gpu_energy=0.00439013101210195, ram_energy=4.631438611257402e-05, energy_consumed=0.007078421753381732, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:09:29] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:09:29] Energy consumed for RAM : 0.000052 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:09:29] RAM : 0.75 W during 27.44 s [measurement time: 0.0495]
+[codecarbon INFO @ 06:09:29] Energy consumed for all GPUs : 0.004922 kWh. Total GPU Power : 69.71279642578968 W
+[codecarbon DEBUG @ 06:09:29] GPU : 69.71 W during 27.49 s [measurement time: 0.0055]
+[codecarbon INFO @ 06:09:29] Energy consumed for all CPUs : 0.002967 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:09:29] CPU : 42.50 W during 27.50 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:09:29] 0.007941 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:09:29] last_duration=27.44185244300752
+------------------------
+[codecarbon DEBUG @ 06:09:29] EmissionsData(timestamp='2024-12-07T06:09:29', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=27.49730276199989, emissions=0.0029313478495192817, emissions_rate=0.00010660492321342442, cpu_power=42.5, gpu_power=69.71279642578968, ram_power=0.751798152923584, cpu_energy=0.002966596102417134, gpu_energy=0.0049224989379959005, ram_energy=5.2045165138155755e-05, energy_consumed=0.00794114020555119, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:09:29] EmissionsData(timestamp='2024-12-07T06:09:29', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=0.0020482379768509418, emissions=0.0029313478495192817, emissions_rate=1.4311558923568417, cpu_power=42.5, gpu_power=69.71279642578968, ram_power=0.751798152923584, cpu_energy=0.002966596102417134, gpu_energy=0.0049224989379959005, ram_energy=5.2045165138155755e-05, energy_consumed=0.00794114020555119, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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 98%|█████████▊| 976/1000 [00:26<00:00, 34.79it/s]
 98%|█████████▊| 980/1000 [00:26<00:00, 35.94it/s]
 98%|█████████▊| 984/1000 [00:26<00:00, 36.15it/s]
 99%|█████████▉| 988/1000 [00:27<00:00, 36.64it/s]
 99%|█████████▉| 992/1000 [00:27<00:00, 36.96it/s]
100%|█████████▉| 996/1000 [00:27<00:00, 37.67it/s]
100%|██████████| 1000/1000 [00:27<00:00, 37.43it/s]
100%|██████████| 1000/1000 [00:27<00:00, 36.58it/s]
+[codecarbon WARNING @ 06:09:56] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:09:56] Energy consumed for RAM : 0.000058 kWh. RAM Power : 0.751798152923584 W
+[codecarbon DEBUG @ 06:09:56] RAM : 0.75 W during 27.34 s [measurement time: 0.0533]
+[codecarbon INFO @ 06:09:56] Energy consumed for all GPUs : 0.005456 kWh. Total GPU Power : 70.06460857296656 W
+[codecarbon DEBUG @ 06:09:56] GPU : 70.06 W during 27.39 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:09:56] Energy consumed for all CPUs : 0.003290 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:09:56] CPU : 42.50 W during 27.40 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:09:56] 0.008803 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:09:56] last_duration=27.33940107599483
+------------------------
+[codecarbon DEBUG @ 06:09:56] EmissionsData(timestamp='2024-12-07T06:09:56', project_name='codecarbon', run_id='b311f965-506c-43d6-9dbb-d13cb8595e0d', duration=27.39547044999199, emissions=0.0032496383136804557, emissions_rate=0.0001186195476953894, cpu_power=42.5, gpu_power=70.06460857296656, ram_power=0.751798152923584, cpu_energy=0.003290013623692014, gpu_energy=0.005455633808947757, ram_energy=5.7754548636313304e-05, energy_consumed=0.008803401981276085, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/experiment_config.json b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..0c45cd9199672472c3c20f970e341589dcfcd5c0
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/experiment_config.json
@@ -0,0 +1,107 @@
+{
+    "experiment_name": "image_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "image-classification",
+        "model": "WinKawaks/vit-tiny-patch16-224",
+        "processor": "WinKawaks/vit-tiny-patch16-224",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/image_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/forward_codecarbon.json b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/forward_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..f6cd10777e8f3f7277228e5cb851de26629293d3
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/forward_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:09:56",
+    "project_name": "codecarbon",
+    "run_id": "b311f965-506c-43d6-9dbb-d13cb8595e0d",
+    "duration": -1733393392.9414692,
+    "emissions": 0.00031829046416117406,
+    "emissions_rate": 1.1619229671186078e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 70.06460857296656,
+    "ram_power": 0.751798152923584,
+    "cpu_energy": 0.0003234175212748799,
+    "gpu_energy": 0.0005331348709518569,
+    "ram_energy": 5.709383498157549e-06,
+    "energy_consumed": 0.0008622617757248954,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/preprocess_codecarbon.json b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/preprocess_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..98623849af009952601f638e3080f863b717d10d
--- /dev/null
+++ b/image_classification/WinKawaks/vit-tiny-patch16-224/2024-12-07-06-05-03/preprocess_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:05:24",
+    "project_name": "codecarbon",
+    "run_id": "b311f965-506c-43d6-9dbb-d13cb8595e0d",
+    "duration": -1733393413.8530831,
+    "emissions": 7.584928120829092e-05,
+    "emissions_rate": 1.1701695823980396e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 71.0711882800841,
+    "ram_power": 0.5384030342102051,
+    "cpu_energy": 7.654690115844764e-05,
+    "gpu_energy": 0.00012796260237002421,
+    "ram_energy": 9.692753425157112e-07,
+    "energy_consumed": 0.00020547877887098755,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/config.yaml b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..18328700bdc32655b2f5f1de652442c63364836d
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: image-classification
+  model: google/vit-base-patch16-224
+  processor: google/vit-base-patch16-224
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/image_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: image_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/hydra.yaml b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..891b05804efa5b70c3f59a24e06913746075e1e6
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42
+    - hydra.mode=RUN
+    task:
+    - backend.model=google/vit-base-patch16-224
+    - backend.processor=google/vit-base-patch16-224
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=google/vit-base-patch16-224,backend.processor=google/vit-base-patch16-224
+    id: ???
+    num: ???
+    config_name: image_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/overrides.yaml b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6d22cd168be4f8e22cb0a3e139b71d3faa3f02e2
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=google/vit-base-patch16-224
+- backend.processor=google/vit-base-patch16-224
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/benchmark_report.json b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/benchmark_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..301c14065dd11ebc860cad87fed873f4a87669ae
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/benchmark_report.json
@@ -0,0 +1,107 @@
+{
+    "forward": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.00028822040023362614,
+            "ram": 3.5272563509285996e-06,
+            "gpu": 0.0006893041069983674,
+            "total": 0.000981051763582922
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 1019314.2065693624
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.0003177506570188295,
+                "ram": 3.886291944887147e-06,
+                "gpu": 0.0007644681115739349,
+                "total": 0.0010861050605376515
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00031711550502560486,
+                "ram": 3.875477642158934e-06,
+                "gpu": 0.0007402558699818318,
+                "total": 0.0010612468526495955
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003216082188071596,
+                "ram": 3.93805759963951e-06,
+                "gpu": 0.0007633367217803055,
+                "total": 0.0010888829981871048
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00032353544770165994,
+                "ram": 3.961662284390647e-06,
+                "gpu": 0.0007541436588698325,
+                "total": 0.0010816407688558826
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003211450012368005,
+                "ram": 3.9252920368007145e-06,
+                "gpu": 0.0007757611761640693,
+                "total": 0.001100831469437671
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00032040755130718847,
+                "ram": 3.923201633461277e-06,
+                "gpu": 0.0007621575541698622,
+                "total": 0.0010864883071105115
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003198497844708781,
+                "ram": 3.916567980948225e-06,
+                "gpu": 0.0007765461767921256,
+                "total": 0.0011003125292439525
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003199601480929535,
+                "ram": 3.917423951203709e-06,
+                "gpu": 0.0007754214536699333,
+                "total": 0.0010992990257140903
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003208316886751869,
+                "ram": 3.928588435795838e-06,
+                "gpu": 0.0007809503469817791,
+                "total": 0.0011057106240927612
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.4096954865736837e-07,
+            "ram": 6.497742946753871e-10,
+            "gpu": 0.0,
+            "total": 1.4161932295204375e-07
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 7061183312.807023
+        },
+        "measures": null
+    }
+}
\ No newline at end of file
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/cli.log b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..38df168d067f995f225ace38f03320b883ea2281
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/cli.log
@@ -0,0 +1,113 @@
+[2024-12-07 06:16:45,475][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:16:45,475][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:16:45,489][device-isolation][INFO] - 	+ Launched device(s) isolation process 2197
+[2024-12-07 06:16:45,489][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:16:45,496][process][INFO] - 	+ Launched benchmark in isolated process 2198.
+[PROC-0][2024-12-07 06:16:48,069][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:16:49,008][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:16:49,009][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:16:49,526][pytorch][INFO] - 	+ Using AutoModel class AutoModelForImageClassification
+[PROC-0][2024-12-07 06:16:49,526][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:16:49,526][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:16:49,526][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:16:49,526][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:16:49,527][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:16:49,529][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:16:49,529][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:16:49,533][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:16:49,533][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:16:49,697][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:16:49,704][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:16:49,704][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:16:50,448][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:16:50,449][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:16:54,622][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:16:54,635][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:16:54,635][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:16:54,635][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:16:54,636][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:16:54,953][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:16:54,953][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:17:21,873][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:17:21,873][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:17:48,735][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:17:48,736][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:18:15,978][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:18:15,979][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:18:43,385][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:18:43,435][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:19:10,638][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:19:10,639][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:19:37,780][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:19:37,780][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:20:04,976][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:20:04,976][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:20:32,070][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:20:32,071][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:20:59,174][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:20:59,174][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:21:26,351][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:21:26,352][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:21:26,352][energy][INFO] - 			+ CPU: 0.000288 (kWh)
+[PROC-0][2024-12-07 06:21:26,352][energy][INFO] - 			+ GPU: 0.000689 (kWh)
+[PROC-0][2024-12-07 06:21:26,352][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,352][energy][INFO] - 			+ total: 0.000981 (kWh)
+[PROC-0][2024-12-07 06:21:26,352][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ CPU: 0.000318 (kWh)
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ GPU: 0.000764 (kWh)
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ total: 0.001086 (kWh)
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ CPU: 0.000317 (kWh)
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ GPU: 0.000740 (kWh)
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,353][energy][INFO] - 			+ total: 0.001061 (kWh)
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 			+ CPU: 0.000322 (kWh)
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 			+ GPU: 0.000763 (kWh)
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 			+ total: 0.001089 (kWh)
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 			+ CPU: 0.000324 (kWh)
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 			+ GPU: 0.000754 (kWh)
+[PROC-0][2024-12-07 06:21:26,354][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 			+ total: 0.001082 (kWh)
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 			+ CPU: 0.000321 (kWh)
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 			+ GPU: 0.000776 (kWh)
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 			+ total: 0.001101 (kWh)
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 			+ CPU: 0.000320 (kWh)
+[PROC-0][2024-12-07 06:21:26,355][energy][INFO] - 			+ GPU: 0.000762 (kWh)
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 			+ total: 0.001086 (kWh)
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:21:26,356][energy][INFO] - 			+ CPU: 0.000320 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 			+ GPU: 0.000777 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 			+ total: 0.001100 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 			+ CPU: 0.000320 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 			+ GPU: 0.000775 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 			+ total: 0.001099 (kWh)
+[PROC-0][2024-12-07 06:21:26,357][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ CPU: 0.000321 (kWh)
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ GPU: 0.000781 (kWh)
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ RAM: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ total: 0.001106 (kWh)
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,358][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:21:26,359][energy][INFO] - 		+ forward energy efficiency: 1019314.206569 (samples/kWh)
+[PROC-0][2024-12-07 06:21:26,359][energy][INFO] - 		+ preprocess energy efficiency: 7061183312.807023 (samples/kWh)
+[2024-12-07 06:21:27,098][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:21:27,147][datasets][INFO] - PyTorch version 2.4.0 available.
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/error.log b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..2431d321f046939d3afea684376e3ff60b4a1134
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/error.log
@@ -0,0 +1,167 @@
+[codecarbon INFO @ 06:16:50] [setup] RAM Tracking...
+[codecarbon INFO @ 06:16:50] [setup] GPU Tracking...
+[codecarbon INFO @ 06:16:50] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:16:50] GPU available. Starting setup
+[codecarbon INFO @ 06:16:50] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:16:50] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:16:50] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:16:50] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:16:50] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:16:51] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:16:51] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:16:51] >>> Tracker's metadata:
+[codecarbon INFO @ 06:16:51]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:16:51]   Python version: 3.9.20
+[codecarbon INFO @ 06:16:51]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:16:51]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:16:51]   CPU count: 48
+[codecarbon INFO @ 06:16:51]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:16:51]   GPU count: 1
+[codecarbon INFO @ 06:16:51]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:16:52] Not running on AWS
+[codecarbon DEBUG @ 06:16:53] Not running on Azure
+[codecarbon DEBUG @ 06:16:54] Not running on GCP
+[codecarbon INFO @ 06:16:54] Saving emissions data to file /runs/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/codecarbon.csv
+[codecarbon DEBUG @ 06:16:54] EmissionsData(timestamp='2024-12-07T06:16:54', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0022072010033298284, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 06:16:54] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.2560844421386719 W
+[codecarbon DEBUG @ 06:16:54] RAM : 0.26 W during 0.01 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:16:54] Energy consumed for all GPUs : 0.000000 kWh. Total GPU Power : 0.0 W
+[codecarbon DEBUG @ 06:16:54] GPU : 0.00 W during 0.01 s [measurement time: 0.0021]
+[codecarbon INFO @ 06:16:54] Energy consumed for all CPUs : 0.000000 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:16:54] CPU : 42.50 W during 0.01 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:16:54] 0.000000 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:16:54] last_duration=0.009131788014201447
+------------------------
+[codecarbon DEBUG @ 06:16:54] EmissionsData(timestamp='2024-12-07T06:16:54', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.012067432020558044, emissions=5.2276560675210465e-08, emissions_rate=4.332036889551336e-06, cpu_power=42.5, gpu_power=0.0, ram_power=0.2560844421386719, cpu_energy=1.4096954865736837e-07, gpu_energy=0.0, ram_energy=6.497742946753871e-10, energy_consumed=1.4161932295204375e-07, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:16:54] EmissionsData(timestamp='2024-12-07T06:16:54', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0022103410155978054, emissions=5.2276560675210465e-08, emissions_rate=2.3650902872592186e-05, cpu_power=42.5, gpu_power=0.0, ram_power=0.2560844421386719, cpu_energy=1.4096954865736837e-07, gpu_energy=0.0, ram_energy=6.497742946753871e-10, energy_consumed=1.4161932295204375e-07, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:17:21] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:17:21] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.5198593139648438 W
+[codecarbon DEBUG @ 06:17:21] RAM : 0.52 W during 26.91 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:17:21] Energy consumed for all GPUs : 0.000764 kWh. Total GPU Power : 102.25835716859314 W
+[codecarbon DEBUG @ 06:17:21] GPU : 102.26 W during 26.91 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:17:21] Energy consumed for all CPUs : 0.000318 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:17:21] CPU : 42.50 W during 26.92 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:17:21] 0.001086 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:17:21] last_duration=26.912182391999522
+------------------------
+[codecarbon DEBUG @ 06:17:21] EmissionsData(timestamp='2024-12-07T06:17:21', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=26.91545412299456, emissions=0.00040097099240622567, emissions_rate=1.4897426236017542e-05, cpu_power=42.5, gpu_power=102.25835716859314, ram_power=0.5198593139648438, cpu_energy=0.00031789162656748686, gpu_energy=0.0007644681115739349, ram_energy=3.886941719181822e-06, energy_consumed=0.0010862466798606035, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:17:21] EmissionsData(timestamp='2024-12-07T06:17:21', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0020082069968339056, emissions=0.00040097099240622567, emissions_rate=0.19966616640534945, cpu_power=42.5, gpu_power=102.25835716859314, ram_power=0.5198593139648438, cpu_energy=0.00031789162656748686, gpu_energy=0.0007644681115739349, ram_energy=3.886941719181822e-06, energy_consumed=0.0010862466798606035, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
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+[codecarbon WARNING @ 06:17:48] Background scheduler didn't run for a long period (26s), results might be inaccurate
+[codecarbon INFO @ 06:17:48] Energy consumed for RAM : 0.000008 kWh. RAM Power : 0.5204486846923828 W
+[codecarbon DEBUG @ 06:17:48] RAM : 0.52 W during 26.81 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:17:48] Energy consumed for all GPUs : 0.001505 kWh. Total GPU Power : 99.40841651041603 W
+[codecarbon DEBUG @ 06:17:48] GPU : 99.41 W during 26.81 s [measurement time: 0.0537]
+[codecarbon INFO @ 06:17:48] Energy consumed for all CPUs : 0.000635 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:17:48] CPU : 42.50 W during 26.86 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:17:48] 0.002147 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:17:48] last_duration=26.807009834010387
+------------------------
+[codecarbon DEBUG @ 06:17:48] EmissionsData(timestamp='2024-12-07T06:17:48', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=26.861653842992382, emissions=0.0007927136891475399, emissions_rate=2.9510978504189964e-05, cpu_power=42.5, gpu_power=99.40841651041603, ram_power=0.5204486846923828, cpu_energy=0.0006350071315930917, gpu_energy=0.0015047239815557667, ram_energy=7.762419361340756e-06, energy_consumed=0.002147493532510199, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:17:48] EmissionsData(timestamp='2024-12-07T06:17:48', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0020962380222044885, emissions=0.0007927136891475399, emissions_rate=0.37816015202027975, cpu_power=42.5, gpu_power=99.40841651041603, ram_power=0.5204486846923828, cpu_energy=0.0006350071315930917, gpu_energy=0.0015047239815557667, ram_energy=7.762419361340756e-06, energy_consumed=0.002147493532510199, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:18:15] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:18:15] Energy consumed for RAM : 0.000012 kWh. RAM Power : 0.5204644203186035 W
+[codecarbon DEBUG @ 06:18:15] RAM : 0.52 W during 27.24 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:18:15] Energy consumed for all GPUs : 0.002268 kWh. Total GPU Power : 100.88210006696625 W
+[codecarbon DEBUG @ 06:18:15] GPU : 100.88 W during 27.24 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:18:15] Energy consumed for all CPUs : 0.000957 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:18:15] CPU : 42.50 W during 27.24 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:18:15] 0.003236 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:18:15] last_duration=27.239060859021265
+------------------------
+[codecarbon DEBUG @ 06:18:15] EmissionsData(timestamp='2024-12-07T06:18:15', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.242214508005418, emissions=0.0011946578372791406, emissions_rate=4.38531837023777e-05, cpu_power=42.5, gpu_power=100.88210006696625, ram_power=0.5204644203186035, cpu_energy=0.0009566153504002513, gpu_energy=0.0022680607033360722, ram_energy=1.1700476960980266e-05, energy_consumed=0.003236376530697304, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:18:15] EmissionsData(timestamp='2024-12-07T06:18:15', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.006346417008899152, emissions=0.0011946578372791406, emissions_rate=0.1882413077495463, cpu_power=42.5, gpu_power=100.88210006696625, ram_power=0.5204644203186035, cpu_energy=0.0009566153504002513, gpu_energy=0.0022680607033360722, ram_energy=1.1700476960980266e-05, energy_consumed=0.003236376530697304, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:18:43] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:18:43] Energy consumed for RAM : 0.000016 kWh. RAM Power : 0.5204658508300781 W
+[codecarbon DEBUG @ 06:18:43] RAM : 0.52 W during 27.40 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:18:43] Energy consumed for all GPUs : 0.003022 kWh. Total GPU Power : 99.07359517307262 W
+[codecarbon DEBUG @ 06:18:43] GPU : 99.07 W during 27.40 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:18:43] Energy consumed for all CPUs : 0.001280 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:18:43] CPU : 42.50 W during 27.41 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:18:43] 0.004318 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:18:43] last_duration=27.4022541110171
+------------------------
+[codecarbon DEBUG @ 06:18:43] EmissionsData(timestamp='2024-12-07T06:18:43', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.405459672008874, emissions=0.0015939286295920186, emissions_rate=5.816098867409293e-05, cpu_power=42.5, gpu_power=99.07359517307262, ram_power=0.5204658508300781, cpu_energy=0.0012801507981019112, gpu_energy=0.0030222043622059047, ram_energy=1.5662139245370913e-05, energy_consumed=0.0043180172995531865, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:18:43] EmissionsData(timestamp='2024-12-07T06:18:43', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0022104719828348607, emissions=0.0015939286295920186, emissions_rate=0.721080675063728, cpu_power=42.5, gpu_power=99.07359517307262, ram_power=0.5204658508300781, cpu_energy=0.0012801507981019112, gpu_energy=0.0030222043622059047, ram_energy=1.5662139245370913e-05, energy_consumed=0.0043180172995531865, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:19:10] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:19:10] Energy consumed for RAM : 0.000020 kWh. RAM Power : 0.5204672813415527 W
+[codecarbon DEBUG @ 06:19:10] RAM : 0.52 W during 27.15 s [measurement time: 0.0496]
+[codecarbon INFO @ 06:19:10] Energy consumed for all GPUs : 0.003798 kWh. Total GPU Power : 102.67206205030085 W
+[codecarbon DEBUG @ 06:19:10] GPU : 102.67 W during 27.20 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:19:10] Energy consumed for all CPUs : 0.001601 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:19:10] CPU : 42.50 W during 27.20 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:19:10] 0.005419 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:19:10] last_duration=27.150610877986765
+------------------------
+[codecarbon DEBUG @ 06:19:10] EmissionsData(timestamp='2024-12-07T06:19:10', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.202974744985113, emissions=0.0020002833692254426, emissions_rate=7.353178790103447e-05, cpu_power=42.5, gpu_power=102.67206205030085, ram_power=0.5204672813415527, cpu_energy=0.0016012957993387117, gpu_energy=0.003797965538369974, ram_energy=1.9587431282171628e-05, energy_consumed=0.0054188487689908575, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:19:10] EmissionsData(timestamp='2024-12-07T06:19:10', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0020186470064800233, emissions=0.0020002833692254426, emissions_rate=0.9909029973067942, cpu_power=42.5, gpu_power=102.67206205030085, ram_power=0.5204672813415527, cpu_energy=0.0016012957993387117, gpu_energy=0.003797965538369974, ram_energy=1.9587431282171628e-05, energy_consumed=0.0054188487689908575, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:19:37] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:19:37] Energy consumed for RAM : 0.000024 kWh. RAM Power : 0.5204672813415527 W
+[codecarbon DEBUG @ 06:19:37] RAM : 0.52 W during 27.14 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:19:37] Energy consumed for all GPUs : 0.004560 kWh. Total GPU Power : 101.10817896698951 W
+[codecarbon DEBUG @ 06:19:37] GPU : 101.11 W during 27.14 s [measurement time: 0.0034]
+[codecarbon INFO @ 06:19:37] Energy consumed for all CPUs : 0.001922 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:19:37] CPU : 42.50 W during 27.14 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:19:37] 0.006505 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:19:37] last_duration=27.13615284700063
+------------------------
+[codecarbon DEBUG @ 06:19:37] EmissionsData(timestamp='2024-12-07T06:19:37', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.14050996801234, emissions=0.0024013435545562445, emissions_rate=8.847820315043657e-05, cpu_power=42.5, gpu_power=101.10817896698951, ram_power=0.5204672813415527, cpu_energy=0.0019217033506459002, gpu_energy=0.004560123092539836, ram_energy=2.3510632915632905e-05, energy_consumed=0.006505337076101369, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:19:37] EmissionsData(timestamp='2024-12-07T06:19:37', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0020154670055489987, emissions=0.0024013435545562445, emissions_rate=1.1914576363417746, cpu_power=42.5, gpu_power=101.10817896698951, ram_power=0.5204672813415527, cpu_energy=0.0019217033506459002, gpu_energy=0.004560123092539836, ram_energy=2.3510632915632905e-05, energy_consumed=0.006505337076101369, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:20:04] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:20:04] Energy consumed for RAM : 0.000027 kWh. RAM Power : 0.520470142364502 W
+[codecarbon DEBUG @ 06:20:04] RAM : 0.52 W during 27.19 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:20:04] Energy consumed for all GPUs : 0.005333 kWh. Total GPU Power : 102.27494731194948 W
+[codecarbon DEBUG @ 06:20:04] GPU : 102.27 W during 27.19 s [measurement time: 0.0024]
+[codecarbon INFO @ 06:20:04] Energy consumed for all CPUs : 0.002243 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:20:04] CPU : 42.50 W during 27.19 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:20:04] 0.007603 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:20:04] EmissionsData(timestamp='2024-12-07T06:20:04', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.19485926401103, emissions=0.0028064709320706686, emissions_rate=0.00010319858267421444, cpu_power=42.5, gpu_power=102.27494731194948, ram_power=0.520470142364502, cpu_energy=0.0022427527262806612, gpu_energy=0.005332648988337851, ram_energy=2.7441857164323505e-05, energy_consumed=0.007602843571782835, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 06:20:04] 0.014898 g.CO2eq/s mean an estimation of 469.8330587513545 kg.CO2eq/year
+[codecarbon DEBUG @ 06:20:04] last_duration=27.19149045200902
+------------------------
+[codecarbon DEBUG @ 06:20:04] EmissionsData(timestamp='2024-12-07T06:20:04', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.195217071013758, emissions=0.0028064709320706686, emissions_rate=0.00010319722489223917, cpu_power=42.5, gpu_power=102.27494731194948, ram_power=0.520470142364502, cpu_energy=0.0022427527262806612, gpu_energy=0.005332648988337851, ram_energy=2.7441857164323505e-05, energy_consumed=0.007602843571782835, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:20:04] EmissionsData(timestamp='2024-12-07T06:20:04', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0020770090050064027, emissions=0.0028064709320706686, emissions_rate=1.3512078788806297, cpu_power=42.5, gpu_power=102.27494731194948, ram_power=0.520470142364502, cpu_energy=0.0022427527262806612, gpu_energy=0.005332648988337851, ram_energy=2.7441857164323505e-05, energy_consumed=0.007602843571782835, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:20:32] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:20:32] Energy consumed for RAM : 0.000031 kWh. RAM Power : 0.520470142364502 W
+[codecarbon DEBUG @ 06:20:32] RAM : 0.52 W during 27.09 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:20:32] Energy consumed for all GPUs : 0.006109 kWh. Total GPU Power : 103.1921423842175 W
+[codecarbon DEBUG @ 06:20:32] GPU : 103.19 W during 27.09 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:20:32] Energy consumed for all CPUs : 0.002563 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:20:32] CPU : 42.50 W during 27.09 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:20:32] 0.008703 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:20:32] last_duration=27.090116387000307
+------------------------
+[codecarbon DEBUG @ 06:20:32] EmissionsData(timestamp='2024-12-07T06:20:32', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.093261996022193, emissions=0.0032126341130385215, emissions_rate=0.00011857686658440012, cpu_power=42.5, gpu_power=103.1921423842175, ram_power=0.520470142364502, cpu_energy=0.0025626025107515393, gpu_energy=0.006109195165129977, ram_energy=3.135842514527173e-05, energy_consumed=0.008703156101026788, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:20:32] EmissionsData(timestamp='2024-12-07T06:20:32', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0020247680076863617, emissions=0.0032126341130385215, emissions_rate=1.5866677569197158, cpu_power=42.5, gpu_power=103.1921423842175, ram_power=0.520470142364502, cpu_energy=0.0025626025107515393, gpu_energy=0.006109195165129977, ram_energy=3.135842514527173e-05, energy_consumed=0.008703156101026788, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:20:59] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:20:59] Energy consumed for RAM : 0.000035 kWh. RAM Power : 0.520470142364502 W
+[codecarbon DEBUG @ 06:20:59] RAM : 0.52 W during 27.10 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:20:59] Energy consumed for all GPUs : 0.006885 kWh. Total GPU Power : 103.02009314527248 W
+[codecarbon DEBUG @ 06:20:59] GPU : 103.02 W during 27.10 s [measurement time: 0.0057]
+[codecarbon INFO @ 06:20:59] Energy consumed for all CPUs : 0.002883 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:20:59] CPU : 42.50 W during 27.10 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:20:59] 0.009802 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:20:59] last_duration=27.096041791985044
+------------------------
+[codecarbon DEBUG @ 06:20:59] EmissionsData(timestamp='2024-12-07T06:20:59', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.102611153997714, emissions=0.003618423175011389, emissions_rate=0.00013350828650610151, cpu_power=42.5, gpu_power=103.02009314527248, ram_power=0.520470142364502, cpu_energy=0.002882562658844493, gpu_energy=0.00688461661879991, ram_energy=3.527584909647544e-05, energy_consumed=0.009802455126740878, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:20:59] EmissionsData(timestamp='2024-12-07T06:20:59', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=0.0020880090014543384, emissions=0.003618423175011389, emissions_rate=1.732953819878692, cpu_power=42.5, gpu_power=103.02009314527248, ram_power=0.520470142364502, cpu_energy=0.002882562658844493, gpu_energy=0.00688461661879991, ram_energy=3.527584909647544e-05, energy_consumed=0.009802455126740878, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:21:26] Background scheduler didn't run for a long period (27s), results might be inaccurate
+[codecarbon INFO @ 06:21:26] Energy consumed for RAM : 0.000039 kWh. RAM Power : 0.520470142364502 W
+[codecarbon DEBUG @ 06:21:26] RAM : 0.52 W during 27.17 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:21:26] Energy consumed for all GPUs : 0.007666 kWh. Total GPU Power : 103.45981394372168 W
+[codecarbon DEBUG @ 06:21:26] GPU : 103.46 W during 27.17 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:21:26] Energy consumed for all CPUs : 0.003203 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:21:26] CPU : 42.50 W during 27.18 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:21:26] 0.010908 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:21:26] last_duration=27.17326125901309
+------------------------
+[codecarbon DEBUG @ 06:21:26] EmissionsData(timestamp='2024-12-07T06:21:26', project_name='codecarbon', run_id='46d0333d-2e22-48c6-971d-c3bac025b79e', duration=27.1764354580082, emissions=0.004026578978363052, emissions_rate=0.0001481643530692147, cpu_power=42.5, gpu_power=103.45981394372168, ram_power=0.520470142364502, cpu_energy=0.0032033943475196797, gpu_energy=0.007665566965781689, ram_energy=3.920443753227128e-05, energy_consumed=0.01090816575083364, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/experiment_config.json b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..93efca2ec3df83c5c6accd6b360c624d92a8ea8e
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/experiment_config.json
@@ -0,0 +1,107 @@
+{
+    "experiment_name": "image_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "image-classification",
+        "model": "google/vit-base-patch16-224",
+        "processor": "google/vit-base-patch16-224",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/image_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/forward_codecarbon.json b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/forward_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..5eb59ce89e1500e6e0d6472e4ca4b969b34c466c
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/forward_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:21:26",
+    "project_name": "codecarbon",
+    "run_id": "46d0333d-2e22-48c6-971d-c3bac025b79e",
+    "duration": -1733393393.1605492,
+    "emissions": 0.0004081558033516633,
+    "emissions_rate": 1.5019893453470282e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 103.45981394372168,
+    "ram_power": 0.520470142364502,
+    "cpu_energy": 0.0003208316886751869,
+    "gpu_energy": 0.0007809503469817791,
+    "ram_energy": 3.928588435795838e-06,
+    "energy_consumed": 0.0011057106240927612,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/preprocess_codecarbon.json b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/preprocess_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..c7707dc0d2d9cc800e80a0e50a5df12750db8dbb
--- /dev/null
+++ b/image_classification/google/vit-base-patch16-224/2024-12-07-06-16-42/preprocess_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:16:54",
+    "project_name": "codecarbon",
+    "run_id": "46d0333d-2e22-48c6-971d-c3bac025b79e",
+    "duration": -1733393420.3251574,
+    "emissions": 5.2276560675210465e-08,
+    "emissions_rate": 5.30175820260911e-06,
+    "cpu_power": 42.5,
+    "gpu_power": 0.0,
+    "ram_power": 0.2560844421386719,
+    "cpu_energy": 1.4096954865736837e-07,
+    "gpu_energy": 0.0,
+    "ram_energy": 6.497742946753871e-10,
+    "energy_consumed": 1.4161932295204375e-07,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/config.yaml b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fbeda016ac769ed4a9464595050f50809011a465
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: sentence-similarity
+  model: sentence-transformers/bert-base-nli-mean-tokens
+  processor: sentence-transformers/bert-base-nli-mean-tokens
+  library: transformers
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/sentence_similarity
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: sentence_similarity_udever-bloom-7b1
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/hydra.yaml b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..08c94a4cfc30df1c70eb550fc168ea5b3319eb4f
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58
+    - hydra.mode=RUN
+    task:
+    - backend.model=sentence-transformers/bert-base-nli-mean-tokens
+    - backend.processor=sentence-transformers/bert-base-nli-mean-tokens
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=sentence-transformers/bert-base-nli-mean-tokens,backend.processor=sentence-transformers/bert-base-nli-mean-tokens
+    id: ???
+    num: ???
+    config_name: sentence_similarity
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/overrides.yaml b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..6f0931769d1f18017d234a3ce80482d88a6b660f
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=sentence-transformers/bert-base-nli-mean-tokens
+- backend.processor=sentence-transformers/bert-base-nli-mean-tokens
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/benchmark_report.json b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/benchmark_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..67823b7419fb73441a86ffc37b9520152dcd0024
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/benchmark_report.json
@@ -0,0 +1,107 @@
+{
+    "forward": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 5.838554521864758e-05,
+            "ram": 4.6905822894143913e-07,
+            "gpu": 0.000158767043680208,
+            "total": 0.00021762164712779697
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 4595131.105743153
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 6.365620490857206e-05,
+                "ram": 5.113224976861025e-07,
+                "gpu": 0.00017263597144201448,
+                "total": 0.00023680349884827264
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.526524878152285e-05,
+                "ram": 5.243854712336291e-07,
+                "gpu": 0.00017513041788186356,
+                "total": 0.00024092005213462004
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.526298394437618e-05,
+                "ram": 5.2440797052777e-07,
+                "gpu": 0.00017576541839003923,
+                "total": 0.00024155281030494317
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.603356241206105e-05,
+                "ram": 5.302470282179411e-07,
+                "gpu": 0.00017796708681805384,
+                "total": 0.0002445308962583329
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.596495707003163e-05,
+                "ram": 5.300457246890137e-07,
+                "gpu": 0.00017858569842421623,
+                "total": 0.0002450807012189368
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.535241250336791e-05,
+                "ram": 5.251255449329028e-07,
+                "gpu": 0.00017925486562586634,
+                "total": 0.00024513240367416713
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.424752087831522e-05,
+                "ram": 5.162447989481432e-07,
+                "gpu": 0.00017465736194788306,
+                "total": 0.00023942112762514642
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.398907030349314e-05,
+                "ram": 5.14162151759751e-07,
+                "gpu": 0.000175087917847927,
+                "total": 0.00023959115030317978
+            },
+            {
+                "unit": "kWh",
+                "cpu": 6.408349138473568e-05,
+                "ram": 5.146411014191382e-07,
+                "gpu": 0.00017858569842421623,
+                "total": 0.000243183830910371
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.9556499311066647e-06,
+            "ram": 1.2099861976244407e-08,
+            "gpu": 1.8438903641726512e-06,
+            "total": 3.81164015725556e-06
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 262354251.38348198
+        },
+        "measures": null
+    }
+}
\ No newline at end of file
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/cli.log b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..cd1675b288fb65315ed63b75da07a6dea632d1c6
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/cli.log
@@ -0,0 +1,113 @@
+[2024-12-07 06:10:01,230][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:10:01,231][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:10:01,243][device-isolation][INFO] - 	+ Launched device(s) isolation process 944
+[2024-12-07 06:10:01,243][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:10:01,250][process][INFO] - 	+ Launched benchmark in isolated process 945.
+[PROC-0][2024-12-07 06:10:03,983][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:10:04,904][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:10:04,904][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:10:05,544][pytorch][INFO] - 	+ Using AutoModel class AutoModel
+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:10:05,545][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:10:05,548][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:10:05,548][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:10:05,549][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:10:05,549][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:10:05,844][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:10:05,850][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:10:05,850][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:10:07,912][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:10:07,912][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:10:12,092][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:10:12,259][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:10:12,259][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:10:12,259][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:10:12,260][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:10:12,927][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:10:12,927][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:10:18,320][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:18,320][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:10:23,849][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:23,850][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:10:29,379][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:29,379][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:10:34,973][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:34,974][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:10:40,562][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:40,562][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:10:46,099][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:46,099][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:10:51,489][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:51,489][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:10:56,932][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:10:56,932][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:11:02,353][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:11:02,354][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 			+ CPU: 0.000058 (kWh)
+[PROC-0][2024-12-07 06:11:07,783][energy][INFO] - 			+ GPU: 0.000159 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ total: 0.000218 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ GPU: 0.000173 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ total: 0.000237 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ CPU: 0.000065 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ GPU: 0.000175 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,784][energy][INFO] - 			+ total: 0.000241 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ CPU: 0.000065 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ GPU: 0.000176 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ total: 0.000242 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ CPU: 0.000066 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ GPU: 0.000178 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ total: 0.000245 (kWh)
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:11:07,785][energy][INFO] - 			+ CPU: 0.000066 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ GPU: 0.000179 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ total: 0.000245 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ CPU: 0.000065 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ GPU: 0.000179 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ total: 0.000245 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,786][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ GPU: 0.000175 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ total: 0.000239 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ GPU: 0.000175 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,787][energy][INFO] - 			+ total: 0.000240 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ CPU: 0.000064 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ GPU: 0.000179 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ total: 0.000243 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ CPU: 0.000002 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ GPU: 0.000002 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 			+ total: 0.000004 (kWh)
+[PROC-0][2024-12-07 06:11:07,788][energy][INFO] - 		+ forward energy efficiency: 4595131.105743 (samples/kWh)
+[PROC-0][2024-12-07 06:11:07,789][energy][INFO] - 		+ preprocess energy efficiency: 262354251.383482 (samples/kWh)
+[2024-12-07 06:11:08,433][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:11:08,479][datasets][INFO] - PyTorch version 2.4.0 available.
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/error.log b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..473a13df3423d0d5e8af47599a651d128d88d45c
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/error.log
@@ -0,0 +1,178 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+
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+
+
+
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+
+
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Downloading data: 100%|██████████| 142k/142k [00:00<00:00, 640kB/s]
+
Generating train split:   0%|          | 0/1000 [00:00<?, ? examples/s]
Generating train split: 100%|██████████| 1000/1000 [00:00<00:00, 325999.07 examples/s]
+[codecarbon INFO @ 06:10:07] [setup] RAM Tracking...
+[codecarbon INFO @ 06:10:07] [setup] GPU Tracking...
+[codecarbon INFO @ 06:10:07] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:10:07] GPU available. Starting setup
+[codecarbon INFO @ 06:10:07] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:10:07] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:10:07] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:10:07] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:10:07] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:10:09] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:10:09] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:10:09] >>> Tracker's metadata:
+[codecarbon INFO @ 06:10:09]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:10:09]   Python version: 3.9.20
+[codecarbon INFO @ 06:10:09]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:10:09]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:10:09]   CPU count: 48
+[codecarbon INFO @ 06:10:09]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:10:09]   GPU count: 1
+[codecarbon INFO @ 06:10:09]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:10:10] Not running on AWS
+[codecarbon DEBUG @ 06:10:11] Not running on Azure
+[codecarbon DEBUG @ 06:10:12] Not running on GCP
+[codecarbon INFO @ 06:10:12] Saving emissions data to file /runs/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/codecarbon.csv
+[codecarbon DEBUG @ 06:10:12] EmissionsData(timestamp='2024-12-07T06:10:12', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.002482334995875135, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
Filter:   0%|          | 0/1000 [00:00<?, ? examples/s]
Filter: 100%|██████████| 1000/1000 [00:00<00:00, 138034.09 examples/s]
+
Running tokenizer on dataset:   0%|          | 0/1000 [00:00<?, ? examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 7098.96 examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 7002.33 examples/s]
+[codecarbon INFO @ 06:10:12] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.2677788734436035 W
+[codecarbon DEBUG @ 06:10:12] RAM : 0.27 W during 0.16 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:10:12] Energy consumed for all GPUs : 0.000002 kWh. Total GPU Power : 40.61219768306994 W
+[codecarbon DEBUG @ 06:10:12] GPU : 40.61 W during 0.16 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:10:12] Energy consumed for all CPUs : 0.000002 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:12] CPU : 42.50 W during 0.17 s [measurement time: 0.0001]
+[codecarbon INFO @ 06:10:12] 0.000004 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:12] last_duration=0.16266650799661875
+------------------------
+[codecarbon DEBUG @ 06:10:12] EmissionsData(timestamp='2024-12-07T06:10:12', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.1657926649786532, emissions=1.4070074181918935e-06, emissions_rate=8.486548053094231e-06, cpu_power=42.5, gpu_power=40.61219768306994, ram_power=0.2677788734436035, cpu_energy=1.9556499311066647e-06, gpu_energy=1.8438903641726512e-06, ram_energy=1.2099861976244407e-08, energy_consumed=3.81164015725556e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:12] EmissionsData(timestamp='2024-12-07T06:10:12', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.00221453100675717, emissions=1.4070074181918935e-06, emissions_rate=0.0006353523224098963, cpu_power=42.5, gpu_power=40.61219768306994, ram_power=0.2677788734436035, cpu_energy=1.9556499311066647e-06, gpu_energy=1.8438903641726512e-06, ram_energy=1.2099861976244407e-08, energy_consumed=3.81164015725556e-06, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:18] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:18] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3415718078613281 W
+[codecarbon DEBUG @ 06:10:18] RAM : 0.34 W during 5.39 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:18] Energy consumed for all GPUs : 0.000174 kWh. Total GPU Power : 115.30912870229479 W
+[codecarbon DEBUG @ 06:10:18] GPU : 115.31 W during 5.39 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:18] Energy consumed for all CPUs : 0.000066 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:18] CPU : 42.50 W during 5.39 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:18] 0.000241 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:18] last_duration=5.38887751600123
+------------------------
+[codecarbon DEBUG @ 06:10:18] EmissionsData(timestamp='2024-12-07T06:10:18', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.3921635360165965, emissions=8.881931964789958e-05, emissions_rate=1.6471926167416264e-05, cpu_power=42.5, gpu_power=115.30912870229479, ram_power=0.3415718078613281, cpu_energy=6.561185483967872e-05, gpu_energy=0.00017447986180618713, ram_energy=5.234223596623469e-07, energy_consumed=0.0002406151390055282, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:18] EmissionsData(timestamp='2024-12-07T06:10:18', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020258680160623044, emissions=8.881931964789958e-05, emissions_rate=0.04384259929259281, cpu_power=42.5, gpu_power=115.30912870229479, ram_power=0.3415718078613281, cpu_energy=6.561185483967872e-05, gpu_energy=0.00017447986180618713, ram_energy=5.234223596623469e-07, energy_consumed=0.0002406151390055282, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
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+[codecarbon WARNING @ 06:10:23] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:23] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3416590690612793 W
+[codecarbon DEBUG @ 06:10:23] RAM : 0.34 W during 5.53 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:23] Energy consumed for all GPUs : 0.000350 kWh. Total GPU Power : 114.08938471435098 W
+[codecarbon DEBUG @ 06:10:23] GPU : 114.09 W during 5.53 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:10:23] Energy consumed for all CPUs : 0.000131 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:23] CPU : 42.50 W during 5.53 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:23] 0.000482 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:23] last_duration=5.525269418023527
+------------------------
+[codecarbon DEBUG @ 06:10:23] EmissionsData(timestamp='2024-12-07T06:10:23', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.528453146020183, emissions=0.00017775119321401719, emissions_rate=3.215206650380614e-05, cpu_power=42.5, gpu_power=114.08938471435098, ram_power=0.3416590690612793, cpu_energy=0.00013087710362120157, gpu_energy=0.0003496102796880507, ram_energy=1.047807830895976e-06, energy_consumed=0.00048153519114014825, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:23] EmissionsData(timestamp='2024-12-07T06:10:23', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.006460198987042531, emissions=0.00017775119321401719, emissions_rate=0.027514817046741063, cpu_power=42.5, gpu_power=114.08938471435098, ram_power=0.3416590690612793, cpu_energy=0.00013087710362120157, gpu_energy=0.0003496102796880507, ram_energy=1.047807830895976e-06, energy_consumed=0.00048153519114014825, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:29] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:29] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:29] RAM : 0.34 W during 5.53 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:29] Energy consumed for all GPUs : 0.000525 kWh. Total GPU Power : 114.50733413763714 W
+[codecarbon DEBUG @ 06:10:29] GPU : 114.51 W during 5.53 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:10:29] Energy consumed for all CPUs : 0.000196 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:29] CPU : 42.50 W during 5.53 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:29] 0.000723 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:29] last_duration=5.525112133997027
+------------------------
+[codecarbon DEBUG @ 06:10:29] EmissionsData(timestamp='2024-12-07T06:10:29', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.528263721993426, emissions=0.0002669166395736923, emissions_rate=4.8282182796707346e-05, cpu_power=42.5, gpu_power=114.50733413763714, ram_power=0.34168338775634766, cpu_energy=0.00019614008756557776, gpu_energy=0.0005253756980780899, ram_energy=1.572215801423746e-06, energy_consumed=0.0007230880014450914, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:29] EmissionsData(timestamp='2024-12-07T06:10:29', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020149170013610274, emissions=0.0002669166395736923, emissions_rate=0.13247029003844657, cpu_power=42.5, gpu_power=114.50733413763714, ram_power=0.34168338775634766, cpu_energy=0.00019614008756557776, gpu_energy=0.0005253756980780899, ram_energy=1.572215801423746e-06, energy_consumed=0.0007230880014450914, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:34] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:34] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:34] RAM : 0.34 W during 5.59 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:34] Energy consumed for all GPUs : 0.000703 kWh. Total GPU Power : 114.66394570645916 W
+[codecarbon DEBUG @ 06:10:34] GPU : 114.66 W during 5.59 s [measurement time: 0.0059]
+[codecarbon INFO @ 06:10:34] Energy consumed for all CPUs : 0.000262 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:34] CPU : 42.50 W during 5.59 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:34] 0.000968 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:34] last_duration=5.586633354017977
+------------------------
+[codecarbon DEBUG @ 06:10:34] EmissionsData(timestamp='2024-12-07T06:10:34', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.593534631014336, emissions=0.00035718139983907714, emissions_rate=6.385611664199272e-05, cpu_power=42.5, gpu_power=114.66394570645916, ram_power=0.34168338775634766, cpu_energy=0.0002621736499776388, gpu_energy=0.0007033427848961438, ram_energy=2.102462829641687e-06, energy_consumed=0.0009676188977034244, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:34] EmissionsData(timestamp='2024-12-07T06:10:34', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020358879992272705, emissions=0.00035718139983907714, emissions_rate=0.17544255871376363, cpu_power=42.5, gpu_power=114.66394570645916, ram_power=0.34168338775634766, cpu_energy=0.0002621736499776388, gpu_energy=0.0007033427848961438, ram_energy=2.102462829641687e-06, energy_consumed=0.0009676188977034244, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:40] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:40] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:40] RAM : 0.34 W during 5.58 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:10:40] Energy consumed for all GPUs : 0.000882 kWh. Total GPU Power : 115.10660681789726 W
+[codecarbon DEBUG @ 06:10:40] GPU : 115.11 W during 5.59 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:40] Energy consumed for all CPUs : 0.000328 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:40] CPU : 42.50 W during 5.59 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:40] 0.001213 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:40] last_duration=5.584514144982677
+------------------------
+[codecarbon DEBUG @ 06:10:40] EmissionsData(timestamp='2024-12-07T06:10:40', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.587722925003618, emissions=0.0004476491120165557, emissions_rate=8.01129758981859e-05, cpu_power=42.5, gpu_power=115.10660681789726, ram_power=0.34168338775634766, cpu_energy=0.00032813860704767044, gpu_energy=0.00088192848332036, ram_energy=2.632508554330701e-06, energy_consumed=0.0012126995989223612, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:40] EmissionsData(timestamp='2024-12-07T06:10:40', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020298569870647043, emissions=0.0004476491120165557, emissions_rate=0.2205323403910752, cpu_power=42.5, gpu_power=115.10660681789726, ram_power=0.34168338775634766, cpu_energy=0.00032813860704767044, gpu_energy=0.00088192848332036, ram_energy=2.632508554330701e-06, energy_consumed=0.0012126995989223612, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:46] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:46] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:46] RAM : 0.34 W during 5.53 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:46] Energy consumed for all GPUs : 0.001061 kWh. Total GPU Power : 116.62129331846901 W
+[codecarbon DEBUG @ 06:10:46] GPU : 116.62 W during 5.53 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:46] Energy consumed for all CPUs : 0.000393 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:46] CPU : 42.50 W during 5.54 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:46] 0.001458 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:46] last_duration=5.532675098977052
+------------------------
+[codecarbon DEBUG @ 06:10:46] EmissionsData(timestamp='2024-12-07T06:10:46', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.535838896990754, emissions=0.0005381359093476812, emissions_rate=9.720945991405356e-05, cpu_power=42.5, gpu_power=116.62129331846901, ram_power=0.34168338775634766, cpu_energy=0.00039349101955103835, gpu_energy=0.0010611833489462263, ram_energy=3.1576340992636036e-06, energy_consumed=0.0014578320025965283, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:46] EmissionsData(timestamp='2024-12-07T06:10:46', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.002027657988946885, emissions=0.0005381359093476812, emissions_rate=0.2653977703740736, cpu_power=42.5, gpu_power=116.62129331846901, ram_power=0.34168338775634766, cpu_energy=0.00039349101955103835, gpu_energy=0.0010611833489462263, ram_energy=3.1576340992636036e-06, energy_consumed=0.0014578320025965283, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:51] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:51] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:51] RAM : 0.34 W during 5.38 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:51] Energy consumed for all GPUs : 0.001236 kWh. Total GPU Power : 117.18411053858756 W
+[codecarbon DEBUG @ 06:10:51] GPU : 117.18 W during 5.39 s [measurement time: 0.0037]
+[codecarbon INFO @ 06:10:51] Energy consumed for all CPUs : 0.000457 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:51] CPU : 42.50 W during 5.39 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:51] 0.001697 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:51] EmissionsData(timestamp='2024-12-07T06:10:51', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.389227389008738, emissions=0.0006265187749095551, emissions_rate=0.00011625391353635075, cpu_power=42.5, gpu_power=117.18411053858756, ram_power=0.34168338775634766, cpu_energy=0.00045711285309183347, gpu_energy=0.0012364832114082347, ram_energy=3.6687052824912656e-06, energy_consumed=0.0016972647697825593, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 06:10:51] 0.016406 g.CO2eq/s mean an estimation of 517.3823484416522 kg.CO2eq/year
+[codecarbon DEBUG @ 06:10:51] last_duration=5.384598153992556
+------------------------
+[codecarbon DEBUG @ 06:10:51] EmissionsData(timestamp='2024-12-07T06:10:51', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.389564844983397, emissions=0.0006265187749095551, emissions_rate=0.00011624663454837515, cpu_power=42.5, gpu_power=117.18411053858756, ram_power=0.34168338775634766, cpu_energy=0.00045711285309183347, gpu_energy=0.0012364832114082347, ram_energy=3.6687052824912656e-06, energy_consumed=0.0016972647697825593, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:51] EmissionsData(timestamp='2024-12-07T06:10:51', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.003103366994764656, emissions=0.0006265187749095551, emissions_rate=0.20188355936197203, cpu_power=42.5, gpu_power=117.18411053858756, ram_power=0.34168338775634766, cpu_energy=0.00045711285309183347, gpu_energy=0.0012364832114082347, ram_energy=3.6687052824912656e-06, energy_consumed=0.0016972647697825593, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:10:56] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:10:56] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:10:56] RAM : 0.34 W during 5.44 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:10:56] Energy consumed for all GPUs : 0.001411 kWh. Total GPU Power : 115.58506166044792 W
+[codecarbon DEBUG @ 06:10:56] GPU : 115.59 W during 5.44 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:10:56] Energy consumed for all CPUs : 0.000521 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:10:56] CPU : 42.50 W during 5.44 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:10:56] 0.001937 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:10:56] last_duration=5.4391074090090115
+------------------------
+[codecarbon DEBUG @ 06:10:56] EmissionsData(timestamp='2024-12-07T06:10:56', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.442248937004479, emissions=0.0007148973439093629, emissions_rate=0.00013136064744271998, cpu_power=42.5, gpu_power=115.58506166044792, ram_power=0.34168338775634766, cpu_energy=0.0005213603739701487, gpu_energy=0.0014111405733561178, ram_energy=4.184950081439409e-06, energy_consumed=0.0019366858974077057, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:10:56] EmissionsData(timestamp='2024-12-07T06:10:56', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.002036777004832402, emissions=0.0007148973439093629, emissions_rate=0.3509944103911311, cpu_power=42.5, gpu_power=115.58506166044792, ram_power=0.34168338775634766, cpu_energy=0.0005213603739701487, gpu_energy=0.0014111405733561178, ram_energy=4.184950081439409e-06, energy_consumed=0.0019366858974077057, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:11:02] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:11:02] Energy consumed for RAM : 0.000005 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:11:02] RAM : 0.34 W during 5.42 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:11:02] Energy consumed for all GPUs : 0.001586 kWh. Total GPU Power : 116.33827522121558 W
+[codecarbon DEBUG @ 06:11:02] GPU : 116.34 W during 5.42 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:11:02] Energy consumed for all CPUs : 0.000585 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:11:02] CPU : 42.50 W during 5.42 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:11:02] 0.002176 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:11:02] last_duration=5.4171664439782035
+------------------------
+[codecarbon DEBUG @ 06:11:02] EmissionsData(timestamp='2024-12-07T06:11:02', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.420353812980466, emissions=0.000803338674124654, emissions_rate=0.0001482077926722879, cpu_power=42.5, gpu_power=116.33827522121558, ram_power=0.34168338775634766, cpu_energy=0.0005853494442736418, gpu_energy=0.0015862284912040447, ram_energy=4.69911223319916e-06, energy_consumed=0.0021762770477108855, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:11:02] EmissionsData(timestamp='2024-12-07T06:11:02', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=0.0020206469926051795, emissions=0.000803338674124654, emissions_rate=0.39756507547561565, cpu_power=42.5, gpu_power=116.33827522121558, ram_power=0.34168338775634766, cpu_energy=0.0005853494442736418, gpu_energy=0.0015862284912040447, ram_energy=4.69911223319916e-06, energy_consumed=0.0021762770477108855, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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 89%|████████▉ | 893/1000 [00:04<00:00, 183.82it/s]
 91%|█████████ | 912/1000 [00:04<00:00, 184.85it/s]
 93%|█████████▎| 931/1000 [00:05<00:00, 183.67it/s]
 95%|█████████▌| 950/1000 [00:05<00:00, 182.85it/s]
 97%|█████████▋| 969/1000 [00:05<00:00, 182.47it/s]
 99%|█████████▉| 988/1000 [00:05<00:00, 182.52it/s]
100%|██████████| 1000/1000 [00:05<00:00, 184.51it/s]
+[codecarbon WARNING @ 06:11:07] Background scheduler didn't run for a long period (5s), results might be inaccurate
+[codecarbon INFO @ 06:11:07] Energy consumed for RAM : 0.000005 kWh. RAM Power : 0.34168338775634766 W
+[codecarbon DEBUG @ 06:11:07] RAM : 0.34 W during 5.42 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:11:07] Energy consumed for all GPUs : 0.001765 kWh. Total GPU Power : 118.55366026700273 W
+[codecarbon DEBUG @ 06:11:07] GPU : 118.55 W during 5.42 s [measurement time: 0.0053]
+[codecarbon INFO @ 06:11:07] Energy consumed for all CPUs : 0.000649 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:11:07] CPU : 42.50 W during 5.43 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:11:07] 0.002419 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:11:07] last_duration=5.422210680990247
+------------------------
+[codecarbon DEBUG @ 06:11:07] EmissionsData(timestamp='2024-12-07T06:11:07', project_name='codecarbon', run_id='e865c20a-47a1-42bb-8b80-58e4f2b5419a', duration=5.428357224009233, emissions=0.0008931061862608407, emissions_rate=0.00016452605261693104, cpu_power=42.5, gpu_power=118.55366026700273, ram_power=0.34168338775634766, cpu_energy=0.0006494329356583775, gpu_energy=0.001764814189628261, ram_energy=5.213753334618298e-06, energy_consumed=0.0024194608786212565, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/experiment_config.json b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3ec05957a2f75931e10e6b7f95ed65bfb344d001
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/experiment_config.json
@@ -0,0 +1,107 @@
+{
+    "experiment_name": "sentence_similarity_udever-bloom-7b1",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "sentence-similarity",
+        "model": "sentence-transformers/bert-base-nli-mean-tokens",
+        "processor": "sentence-transformers/bert-base-nli-mean-tokens",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/sentence_similarity",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/forward_codecarbon.json b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/forward_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..b20f1134fb3c56b820aba3fdd6a522941681e1d7
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/forward_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:11:07",
+    "project_name": "codecarbon",
+    "run_id": "e865c20a-47a1-42bb-8b80-58e4f2b5419a",
+    "duration": -1733393414.9085443,
+    "emissions": 8.976751213618669e-05,
+    "emissions_rate": 1.6542931103168025e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 118.55366026700273,
+    "ram_power": 0.34168338775634766,
+    "cpu_energy": 6.408349138473568e-05,
+    "gpu_energy": 0.00017858569842421623,
+    "ram_energy": 5.146411014191382e-07,
+    "energy_consumed": 0.000243183830910371,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/preprocess_codecarbon.json b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/preprocess_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..45e371adc7f6913a74446f62c0dbe14bf675a97d
--- /dev/null
+++ b/sentence_similarity/sentence-transformers/bert-base-nli-mean-tokens/2024-12-07-06-09-58/preprocess_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:10:12",
+    "project_name": "codecarbon",
+    "run_id": "e865c20a-47a1-42bb-8b80-58e4f2b5419a",
+    "duration": -1733393420.1716886,
+    "emissions": 1.4070074181918935e-06,
+    "emissions_rate": 8.615544517853035e-06,
+    "cpu_power": 42.5,
+    "gpu_power": 40.61219768306994,
+    "ram_power": 0.2677788734436035,
+    "cpu_energy": 1.9556499311066647e-06,
+    "gpu_energy": 1.8438903641726512e-06,
+    "ram_energy": 1.2099861976244407e-08,
+    "energy_consumed": 3.81164015725556e-06,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/config.yaml b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..591582c9c50bdcb263906cf5af76752cf4e6e48a
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/config.yaml
@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: summarization
+  model: facebook/bart-large-cnn
+  processor: facebook/bart-large-cnn
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/summarization
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs:
+    max_length: 10
+    min_new_tokens: 10
+  call_kwargs: {}
+experiment_name: summarization
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/hydra.yaml b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..0b38b00cfd80c898669255a296364797e31877c9
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14
+    - hydra.mode=RUN
+    task:
+    - backend.model=facebook/bart-large-cnn
+    - backend.processor=facebook/bart-large-cnn
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=facebook/bart-large-cnn,backend.processor=facebook/bart-large-cnn
+    id: ???
+    num: ???
+    config_name: summarization
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/overrides.yaml b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ec1f9b7ad1cc6c35c264aa7a69dcdea036aa6c78
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=facebook/bart-large-cnn
+- backend.processor=facebook/bart-large-cnn
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/benchmark_report.json b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/benchmark_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..b7570d5f446b1826611f1ebbd4cff4ff1d76123d
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/benchmark_report.json
@@ -0,0 +1,107 @@
+{
+    "forward": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 0.00033725407026002766,
+            "ram": 2.8385279556699335e-06,
+            "gpu": 0.0023033434260065987,
+            "total": 0.002643436024222297
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 378295.5179685885
+        },
+        "measures": [
+            {
+                "unit": "kWh",
+                "cpu": 0.00037202300129172527,
+                "ram": 3.128831391636421e-06,
+                "gpu": 0.0025199834048739156,
+                "total": 0.0028951352375572777
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003746899272678801,
+                "ram": 3.153775677801041e-06,
+                "gpu": 0.0025484531498720653,
+                "total": 0.0029262968528177466
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003737423095375562,
+                "ram": 3.145811380055178e-06,
+                "gpu": 0.00255550982218411,
+                "total": 0.0029323979431017232
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003744044694422781,
+                "ram": 3.1516145240151375e-06,
+                "gpu": 0.002554680654853758,
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+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00037510538581732875,
+                "ram": 3.15751070464253e-06,
+                "gpu": 0.002561981494028087,
+                "total": 0.0029402443905500574
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00037548567679720384,
+                "ram": 3.160425521265898e-06,
+                "gpu": 0.0025706890009939976,
+                "total": 0.002949335103312467
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0,
+                "ram": 0.0,
+                "gpu": 0.0,
+                "total": 0.0
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00037559326133254634,
+                "ram": 3.161518989833574e-06,
+                "gpu": 0.0025780095624059474,
+                "total": 0.002956764342728329
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.0003756093367569824,
+                "ram": 3.1616459024560377e-06,
+                "gpu": 0.002569132888638137,
+                "total": 0.002947903871297574
+            },
+            {
+                "unit": "kWh",
+                "cpu": 0.00037588733435677544,
+                "ram": 3.1641454649935176e-06,
+                "gpu": 0.00257499428221597,
+                "total": 0.002954045762037741
+            }
+        ]
+    },
+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
+            "unit": "kWh",
+            "cpu": 1.1241840643722552e-05,
+            "ram": 7.543256492501751e-08,
+            "gpu": 1.8234736809841223e-05,
+            "total": 2.955201001848879e-05
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 33838645.81036499
+        },
+        "measures": null
+    }
+}
\ No newline at end of file
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/cli.log b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..954fa2e5446077cba953f11edf3d90c0ccbbb624
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/cli.log
@@ -0,0 +1,114 @@
+[2024-12-07 05:59:17,596][energy_star][WARNING] - Setting `min_new_tokens` without `max_new_tokens` results in non-deterministic behavior. Setting `max_new_tokens` to `min_new_tokens`.
+[2024-12-07 05:59:17,599][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 05:59:17,599][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 05:59:17,609][device-isolation][INFO] - 	+ Launched device(s) isolation process 181
+[2024-12-07 05:59:17,609][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 05:59:17,614][process][INFO] - 	+ Launched benchmark in isolated process 182.
+[PROC-0][2024-12-07 05:59:20,266][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 05:59:21,219][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 05:59:21,219][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSeq2SeqLM
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 05:59:22,011][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 05:59:22,013][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 05:59:22,014][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 05:59:22,015][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 05:59:22,015][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 05:59:22,209][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 05:59:22,215][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 05:59:22,215][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 05:59:23,693][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 05:59:23,693][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 05:59:27,876][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 05:59:28,829][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 05:59:28,830][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 05:59:28,830][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 05:59:28,830][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 05:59:29,771][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 05:59:29,771][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-12-07 06:00:01,298][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:00:01,311][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-12-07 06:00:33,050][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:00:33,065][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-12-07 06:01:04,724][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:01:04,740][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-12-07 06:01:36,455][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:01:36,470][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-12-07 06:02:08,244][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:02:08,260][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-12-07 06:02:40,066][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:02:40,078][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-12-07 06:03:11,897][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:03:11,911][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-12-07 06:03:43,727][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:03:43,740][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-12-07 06:04:15,557][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:04:15,571][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-12-07 06:04:47,411][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ CPU: 0.000337 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ GPU: 0.002303 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 			+ total: 0.002643 (kWh)
+[PROC-0][2024-12-07 06:04:47,427][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ CPU: 0.000372 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ GPU: 0.002520 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ total: 0.002895 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ CPU: 0.000375 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ GPU: 0.002548 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ total: 0.002926 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ CPU: 0.000374 (kWh)
+[PROC-0][2024-12-07 06:04:47,428][energy][INFO] - 			+ GPU: 0.002556 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ total: 0.002932 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ CPU: 0.000374 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ GPU: 0.002555 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ total: 0.002932 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ CPU: 0.000375 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ GPU: 0.002562 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,429][energy][INFO] - 			+ total: 0.002940 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ CPU: 0.000375 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ GPU: 0.002571 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ total: 0.002949 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-12-07 06:04:47,430][energy][INFO] - 			+ CPU: 0.000376 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ GPU: 0.002578 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ total: 0.002957 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ CPU: 0.000376 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ GPU: 0.002569 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ total: 0.002948 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ CPU: 0.000376 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ GPU: 0.002575 (kWh)
+[PROC-0][2024-12-07 06:04:47,431][energy][INFO] - 			+ RAM: 0.000003 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ total: 0.002954 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ CPU: 0.000011 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ GPU: 0.000018 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 			+ total: 0.000030 (kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 		+ forward energy efficiency: 378295.517969 (samples/kWh)
+[PROC-0][2024-12-07 06:04:47,432][energy][INFO] - 		+ preprocess energy efficiency: 33838645.810365 (samples/kWh)
+[2024-12-07 06:04:48,082][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-12-07 06:04:48,132][datasets][INFO] - PyTorch version 2.4.0 available.
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/error.log b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..e417c37f5d1d2291c78781fadea3adfab5a99e62
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/error.log
@@ -0,0 +1,178 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+
Downloading readme:   0%|          | 0.00/274 [00:00<?, ?B/s]
Downloading readme: 100%|██████████| 274/274 [00:00<00:00, 3.46MB/s]
+
+
+
Downloading data:   0%|          | 0.00/1.12M [00:00<?, ?B/s]
+
+
Downloading data: 100%|██████████| 1.12M/1.12M [00:00<00:00, 4.37MB/s]
Downloading data: 100%|██████████| 1.12M/1.12M [00:00<00:00, 4.36MB/s]
+
Generating train split:   0%|          | 0/1000 [00:00<?, ? examples/s]
Generating train split: 100%|██████████| 1000/1000 [00:00<00:00, 121566.98 examples/s]
+[codecarbon INFO @ 05:59:23] [setup] RAM Tracking...
+[codecarbon INFO @ 05:59:23] [setup] GPU Tracking...
+[codecarbon INFO @ 05:59:23] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 05:59:23] GPU available. Starting setup
+[codecarbon INFO @ 05:59:23] [setup] CPU Tracking...
+[codecarbon DEBUG @ 05:59:23] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 05:59:23] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 05:59:23] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 05:59:23] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 05:59:24] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 05:59:24] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 05:59:24] >>> Tracker's metadata:
+[codecarbon INFO @ 05:59:24]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 05:59:24]   Python version: 3.9.20
+[codecarbon INFO @ 05:59:24]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 05:59:24]   Available RAM : 186.705 GB
+[codecarbon INFO @ 05:59:24]   CPU count: 48
+[codecarbon INFO @ 05:59:24]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 05:59:24]   GPU count: 1
+[codecarbon INFO @ 05:59:24]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 05:59:25] Not running on AWS
+[codecarbon DEBUG @ 05:59:26] Not running on Azure
+[codecarbon DEBUG @ 05:59:27] Not running on GCP
+[codecarbon INFO @ 05:59:27] Saving emissions data to file /runs/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/codecarbon.csv
+[codecarbon DEBUG @ 05:59:27] EmissionsData(timestamp='2024-12-07T05:59:27', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.002186931000323966, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
Filter:   0%|          | 0/1000 [00:00<?, ? examples/s]
Filter: 100%|██████████| 1000/1000 [00:00<00:00, 145448.69 examples/s]
+
Running tokenizer on dataset:   0%|          | 0/1000 [00:00<?, ? examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 1099.59 examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 1091.74 examples/s]
+[codecarbon INFO @ 05:59:28] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.28609800338745117 W
+[codecarbon DEBUG @ 05:59:28] RAM : 0.29 W during 0.95 s [measurement time: 0.0006]
+[codecarbon INFO @ 05:59:28] Energy consumed for all GPUs : 0.000018 kWh. Total GPU Power : 69.1002619246679 W
+[codecarbon DEBUG @ 05:59:28] GPU : 69.10 W during 0.95 s [measurement time: 0.0022]
+[codecarbon INFO @ 05:59:28] Energy consumed for all CPUs : 0.000011 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 05:59:28] CPU : 42.50 W during 0.95 s [measurement time: 0.0000]
+[codecarbon INFO @ 05:59:28] 0.000030 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 05:59:28] last_duration=0.9491704440151807
+------------------------
+[codecarbon DEBUG @ 05:59:28] EmissionsData(timestamp='2024-12-07T05:59:28', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.9523611240147147, emissions=1.0908662833595775e-05, emissions_rate=1.1454334452051014e-05, cpu_power=42.5, gpu_power=69.1002619246679, ram_power=0.28609800338745117, cpu_energy=1.1241840643722552e-05, gpu_energy=1.8234736809841223e-05, ram_energy=7.543256492501751e-08, energy_consumed=2.955201001848879e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 05:59:29] EmissionsData(timestamp='2024-12-07T05:59:29', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.0024698160123080015, emissions=1.0908662833595775e-05, emissions_rate=0.004416791687815568, cpu_power=42.5, gpu_power=69.1002619246679, ram_power=0.28609800338745117, cpu_energy=1.1241840643722552e-05, gpu_energy=1.8234736809841223e-05, ram_energy=7.543256492501751e-08, energy_consumed=2.955201001848879e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:00:01] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:00:01] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.35749197006225586 W
+[codecarbon DEBUG @ 06:00:01] RAM : 0.36 W during 31.51 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:00:01] Energy consumed for all GPUs : 0.002538 kWh. Total GPU Power : 287.91997531418536 W
+[codecarbon DEBUG @ 06:00:01] GPU : 287.92 W during 31.51 s [measurement time: 0.0040]
+[codecarbon INFO @ 06:00:01] Energy consumed for all CPUs : 0.000383 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:00:01] CPU : 42.50 W during 31.51 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:00:01] 0.002925 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:00:01] last_duration=31.507618099014508
+------------------------
+[codecarbon DEBUG @ 06:00:01] EmissionsData(timestamp='2024-12-07T06:00:01', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.512645952025196, emissions=0.0010796026076588612, emissions_rate=3.4259344940518374e-05, cpu_power=42.5, gpu_power=287.91997531418536, ram_power=0.35749197006225586, cpu_energy=0.0003832648419354478, gpu_energy=0.002538218141683757, ram_energy=3.2042639565614385e-06, energy_consumed=0.0029246872475757663, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:00:01] EmissionsData(timestamp='2024-12-07T06:00:01', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.004691796988481656, emissions=0.0010796026076588612, emissions_rate=0.23010428846543907, cpu_power=42.5, gpu_power=287.91997531418536, ram_power=0.35749197006225586, cpu_energy=0.0003832648419354478, gpu_energy=0.002538218141683757, ram_energy=3.2042639565614385e-06, energy_consumed=0.0029246872475757663, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:00:33] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:00:33] Energy consumed for RAM : 0.000006 kWh. RAM Power : 0.35775947570800787 W
+[codecarbon DEBUG @ 06:00:33] RAM : 0.36 W during 31.74 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:00:33] Energy consumed for all GPUs : 0.005087 kWh. Total GPU Power : 289.0864733204254 W
+[codecarbon DEBUG @ 06:00:33] GPU : 289.09 W during 31.74 s [measurement time: 0.0025]
+[codecarbon INFO @ 06:00:33] Energy consumed for all CPUs : 0.000758 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:00:33] CPU : 42.50 W during 31.74 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:00:33] 0.005851 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:00:33] last_duration=31.73516171699157
+------------------------
+[codecarbon DEBUG @ 06:00:33] EmissionsData(timestamp='2024-12-07T06:00:33', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.738543679995928, emissions=0.0021597993759473705, emissions_rate=6.80497315101651e-05, cpu_power=42.5, gpu_power=289.0864733204254, ram_power=0.35775947570800787, cpu_energy=0.0007579547692033279, gpu_energy=0.005086671291555822, ram_energy=6.35803963436248e-06, energy_consumed=0.005850984100393513, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:00:33] EmissionsData(timestamp='2024-12-07T06:00:33', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.002107178996084258, emissions=0.0021597993759473705, emissions_rate=1.024971955377733, cpu_power=42.5, gpu_power=289.0864733204254, ram_power=0.35775947570800787, cpu_energy=0.0007579547692033279, gpu_energy=0.005086671291555822, ram_energy=6.35803963436248e-06, energy_consumed=0.005850984100393513, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:01:04] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:01:04] Energy consumed for RAM : 0.000010 kWh. RAM Power : 0.35775947570800787 W
+[codecarbon DEBUG @ 06:01:04] RAM : 0.36 W during 31.66 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:01:04] Energy consumed for all GPUs : 0.007642 kWh. Total GPU Power : 290.6207603784396 W
+[codecarbon DEBUG @ 06:01:04] GPU : 290.62 W during 31.66 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:01:04] Energy consumed for all CPUs : 0.001132 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:01:04] CPU : 42.50 W during 31.66 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:01:04] 0.008783 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:01:04] last_duration=31.65502932399977
+------------------------
+[codecarbon DEBUG @ 06:01:04] EmissionsData(timestamp='2024-12-07T06:01:04', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.658283213997493, emissions=0.0032422482664023105, emissions_rate=0.00010241390047862016, cpu_power=42.5, gpu_power=290.6207603784396, ram_power=0.35775947570800787, cpu_energy=0.0011316970787408841, gpu_energy=0.007642181113739932, ram_energy=9.503851014417658e-06, energy_consumed=0.008783382043495236, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:01:04] EmissionsData(timestamp='2024-12-07T06:01:04', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.002147849998436868, emissions=0.0032422482664023105, emissions_rate=1.5095319825695035, cpu_power=42.5, gpu_power=290.6207603784396, ram_power=0.35775947570800787, cpu_energy=0.0011316970787408841, gpu_energy=0.007642181113739932, ram_energy=9.503851014417658e-06, energy_consumed=0.008783382043495236, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:01:36] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:01:36] Energy consumed for RAM : 0.000013 kWh. RAM Power : 0.35778379440307617 W
+[codecarbon DEBUG @ 06:01:36] RAM : 0.36 W during 31.71 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:01:36] Energy consumed for all GPUs : 0.010197 kWh. Total GPU Power : 290.0114232732793 W
+[codecarbon DEBUG @ 06:01:36] GPU : 290.01 W during 31.71 s [measurement time: 0.0022]
+[codecarbon INFO @ 06:01:36] Energy consumed for all CPUs : 0.001506 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:01:36] CPU : 42.50 W during 31.71 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:01:36] 0.011716 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:01:36] last_duration=31.711274834990036
+------------------------
+[codecarbon DEBUG @ 06:01:36] EmissionsData(timestamp='2024-12-07T06:01:36', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.714364362997003, emissions=0.004324637650815023, emissions_rate=0.00013636211028277234, cpu_power=42.5, gpu_power=290.0114232732793, ram_power=0.35778379440307617, cpu_energy=0.0015061015481831622, gpu_energy=0.01019686176859369, ram_energy=1.2655465538432795e-05, energy_consumed=0.011715618782315288, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:01:36] EmissionsData(timestamp='2024-12-07T06:01:36', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.0021415499795693904, emissions=0.004324637650815023, emissions_rate=2.019396087914135, cpu_power=42.5, gpu_power=290.0114232732793, ram_power=0.35778379440307617, cpu_energy=0.0015061015481831622, gpu_energy=0.01019686176859369, ram_energy=1.2655465538432795e-05, energy_consumed=0.011715618782315288, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:02:08] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:02:08] Energy consumed for RAM : 0.000016 kWh. RAM Power : 0.35778379440307617 W
+[codecarbon DEBUG @ 06:02:08] RAM : 0.36 W during 31.77 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:02:08] Energy consumed for all GPUs : 0.012759 kWh. Total GPU Power : 290.297407583527 W
+[codecarbon DEBUG @ 06:02:08] GPU : 290.30 W during 31.77 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:02:08] Energy consumed for all CPUs : 0.001881 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:02:08] CPU : 42.50 W during 31.77 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:02:08] 0.014656 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:02:08] last_duration=31.770602304983186
+------------------------
+[codecarbon DEBUG @ 06:02:08] EmissionsData(timestamp='2024-12-07T06:02:08', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.77373810298741, emissions=0.005409982934767456, emissions_rate=0.00017026586287179104, cpu_power=42.5, gpu_power=290.297407583527, ram_power=0.35778379440307617, cpu_energy=0.001881206934000491, gpu_energy=0.012758843262621777, ram_energy=1.5812976243075325e-05, energy_consumed=0.014655863172865345, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:02:08] EmissionsData(timestamp='2024-12-07T06:02:08', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.0021387799934018403, emissions=0.005409982934767456, emissions_rate=2.529471451695505, cpu_power=42.5, gpu_power=290.297407583527, ram_power=0.35778379440307617, cpu_energy=0.001881206934000491, gpu_energy=0.012758843262621777, ram_energy=1.5812976243075325e-05, energy_consumed=0.014655863172865345, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:02:40] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:02:40] Energy consumed for RAM : 0.000019 kWh. RAM Power : 0.3577909469604492 W
+[codecarbon DEBUG @ 06:02:40] RAM : 0.36 W during 31.80 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:02:40] Energy consumed for all GPUs : 0.015330 kWh. Total GPU Power : 291.0207754307126 W
+[codecarbon DEBUG @ 06:02:40] GPU : 291.02 W during 31.80 s [measurement time: 0.0058]
+[codecarbon INFO @ 06:02:40] Energy consumed for all CPUs : 0.002257 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:02:40] CPU : 42.50 W during 31.81 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:02:40] 0.017605 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:02:40] last_duration=31.799300222977763
+------------------------
+[codecarbon DEBUG @ 06:02:40] EmissionsData(timestamp='2024-12-07T06:02:40', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.80595147598069, emissions=0.0064986839133200245, emissions_rate=0.00020432288963993794, cpu_power=42.5, gpu_power=291.0207754307126, ram_power=0.3577909469604492, cpu_energy=0.002256692610797695, gpu_energy=0.015329532263615775, ram_energy=1.8973401764341223e-05, energy_consumed=0.017605198276177812, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:02:40] EmissionsData(timestamp='2024-12-07T06:02:40', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.006906588998390362, emissions=0.0064986839133200245, emissions_rate=0.9409397192788795, cpu_power=42.5, gpu_power=291.0207754307126, ram_power=0.3577909469604492, cpu_energy=0.002256692610797695, gpu_energy=0.015329532263615775, ram_energy=1.8973401764341223e-05, energy_consumed=0.017605198276177812, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:03:11] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:03:11] Energy consumed for RAM : 0.000022 kWh. RAM Power : 0.3577909469604492 W
+[codecarbon DEBUG @ 06:03:11] RAM : 0.36 W during 31.81 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:03:11] Energy consumed for all GPUs : 0.017899 kWh. Total GPU Power : 290.76987543618213 W
+[codecarbon DEBUG @ 06:03:11] GPU : 290.77 W during 31.81 s [measurement time: 0.0039]
+[codecarbon INFO @ 06:03:11] Energy consumed for all CPUs : 0.002632 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:03:11] CPU : 42.50 W during 31.82 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:03:11] 0.020554 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:03:11] EmissionsData(timestamp='2024-12-07T06:03:11', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.81822130898945, emissions=0.007587042443725498, emissions_rate=0.00023844960942496075, cpu_power=42.5, gpu_power=290.76987543618213, ram_power=0.3577909469604492, cpu_energy=0.0026323233439078954, gpu_energy=0.017899147097083956, ram_energy=2.213523257991547e-05, energy_consumed=0.020553605673571767, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon INFO @ 06:03:11] 0.034213 g.CO2eq/s mean an estimation of 1,078.9392050275078 kg.CO2eq/year
+[codecarbon DEBUG @ 06:03:11] last_duration=31.813439519988606
+------------------------
+[codecarbon DEBUG @ 06:03:11] EmissionsData(timestamp='2024-12-07T06:03:11', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.81856143497862, emissions=0.007587042443725498, emissions_rate=0.00023844706050679427, cpu_power=42.5, gpu_power=290.76987543618213, ram_power=0.3577909469604492, cpu_energy=0.0026323233439078954, gpu_energy=0.017899147097083956, ram_energy=2.213523257991547e-05, energy_consumed=0.020553605673571767, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:03:11] EmissionsData(timestamp='2024-12-07T06:03:11', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.004395411990117282, emissions=0.007587042443725498, emissions_rate=1.726127712438409, cpu_power=42.5, gpu_power=290.76987543618213, ram_power=0.3577909469604492, cpu_energy=0.0026323233439078954, gpu_energy=0.017899147097083956, ram_energy=2.213523257991547e-05, energy_consumed=0.020553605673571767, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:03:43] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:03:43] Energy consumed for RAM : 0.000025 kWh. RAM Power : 0.3577909469604492 W
+[codecarbon DEBUG @ 06:03:43] RAM : 0.36 W during 31.81 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:03:43] Energy consumed for all GPUs : 0.020477 kWh. Total GPU Power : 291.7485618784074 W
+[codecarbon DEBUG @ 06:03:43] GPU : 291.75 W during 31.81 s [measurement time: 0.0039]
+[codecarbon INFO @ 06:03:43] Energy consumed for all CPUs : 0.003008 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:03:43] CPU : 42.50 W during 31.81 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:03:43] 0.023510 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:03:43] last_duration=31.810300100012682
+------------------------
+[codecarbon DEBUG @ 06:03:43] EmissionsData(timestamp='2024-12-07T06:03:43', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.815061828994658, emissions=0.008678485809948042, emissions_rate=0.00027277915902206116, cpu_power=42.5, gpu_power=291.7485618784074, ram_power=0.3577909469604492, cpu_energy=0.0030079166052404418, gpu_energy=0.020477156659489903, ram_energy=2.5296751569749045e-05, energy_consumed=0.023510370016300096, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:03:43] EmissionsData(timestamp='2024-12-07T06:03:43', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.005464821995701641, emissions=0.008678485809948042, emissions_rate=1.5880637680008811, cpu_power=42.5, gpu_power=291.7485618784074, ram_power=0.3577909469604492, cpu_energy=0.0030079166052404418, gpu_energy=0.020477156659489903, ram_energy=2.5296751569749045e-05, energy_consumed=0.023510370016300096, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:04:15] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:04:15] Energy consumed for RAM : 0.000028 kWh. RAM Power : 0.3577909469604492 W
+[codecarbon DEBUG @ 06:04:15] RAM : 0.36 W during 31.81 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:04:15] Energy consumed for all GPUs : 0.023046 kWh. Total GPU Power : 290.7324631578723 W
+[codecarbon DEBUG @ 06:04:15] GPU : 290.73 W during 31.81 s [measurement time: 0.0040]
+[codecarbon INFO @ 06:04:15] Energy consumed for all CPUs : 0.003384 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:04:15] CPU : 42.50 W during 31.82 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:04:15] 0.026458 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:04:15] last_duration=31.811574992985697
+------------------------
+[codecarbon DEBUG @ 06:04:15] EmissionsData(timestamp='2024-12-07T06:04:15', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.8164337319904, emissions=0.009766658471561177, emissions_rate=0.00030696898822262143, cpu_power=42.5, gpu_power=290.7324631578723, ram_power=0.3577909469604492, cpu_energy=0.003383525941997424, gpu_energy=0.02304628954812804, ram_energy=2.8458397472205083e-05, energy_consumed=0.02645827388759767, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:04:15] EmissionsData(timestamp='2024-12-07T06:04:15', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=0.004423101985594258, emissions=0.009766658471561177, emissions_rate=2.2081015774383044, cpu_power=42.5, gpu_power=290.7324631578723, ram_power=0.3577909469604492, cpu_energy=0.003383525941997424, gpu_energy=0.02304628954812804, ram_energy=2.8458397472205083e-05, energy_consumed=0.02645827388759767, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+[codecarbon WARNING @ 06:04:47] Background scheduler didn't run for a long period (31s), results might be inaccurate
+[codecarbon INFO @ 06:04:47] Energy consumed for RAM : 0.000032 kWh. RAM Power : 0.3577909469604492 W
+[codecarbon DEBUG @ 06:04:47] RAM : 0.36 W during 31.84 s [measurement time: 0.0004]
+[codecarbon INFO @ 06:04:47] Energy consumed for all GPUs : 0.025621 kWh. Total GPU Power : 291.16559529099845 W
+[codecarbon DEBUG @ 06:04:47] GPU : 291.17 W during 31.84 s [measurement time: 0.0024]
+[codecarbon INFO @ 06:04:47] Energy consumed for all CPUs : 0.003759 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:04:47] CPU : 42.50 W during 31.84 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:04:47] 0.029412 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:04:47] last_duration=31.836727773974417
+------------------------
+[codecarbon DEBUG @ 06:04:47] EmissionsData(timestamp='2024-12-07T06:04:47', project_name='codecarbon', run_id='d9969f35-5239-46e5-99c5-b3063a70b123', duration=31.839970912988065, emissions=0.010857098316191756, emissions_rate=0.0003409895802311478, cpu_power=42.5, gpu_power=291.16559529099845, ram_power=0.3577909469604492, cpu_energy=0.0037594132763541996, gpu_energy=0.02562128383034401, ram_energy=3.16225429371986e-05, energy_consumed=0.02941231964963541, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/experiment_config.json b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..6e618f443d4725bdfb0de3b8bf344e9786ed949d
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/experiment_config.json
@@ -0,0 +1,111 @@
+{
+    "experiment_name": "summarization",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "summarization",
+        "model": "facebook/bart-large-cnn",
+        "processor": "facebook/bart-large-cnn",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/summarization",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {
+            "max_length": 10,
+            "min_new_tokens": 10,
+            "max_new_tokens": 10
+        },
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/forward_codecarbon.json b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/forward_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..b04af0c8a1ce6c15ea198cdd6d6d3b7ed6984418
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/forward_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:04:47",
+    "project_name": "codecarbon",
+    "run_id": "d9969f35-5239-46e5-99c5-b3063a70b123",
+    "duration": -1733393388.4993432,
+    "emissions": 0.0010904398446305794,
+    "emissions_rate": 3.4252272054628185e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 291.16559529099845,
+    "ram_power": 0.3577909469604492,
+    "cpu_energy": 0.00037588733435677544,
+    "gpu_energy": 0.00257499428221597,
+    "ram_energy": 3.1641454649935176e-06,
+    "energy_consumed": 0.002954045762037741,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/preprocess_codecarbon.json b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/preprocess_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..011652e4471ca758c42eb4f65a3f821ebf72c85c
--- /dev/null
+++ b/summarization/facebook/bart-large-cnn/2024-12-07-05-59-14/preprocess_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T05:59:28",
+    "project_name": "codecarbon",
+    "run_id": "d9969f35-5239-46e5-99c5-b3063a70b123",
+    "duration": -1733393419.3848207,
+    "emissions": 1.0908662833595775e-05,
+    "emissions_rate": 1.1480697869712148e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 69.1002619246679,
+    "ram_power": 0.28609800338745117,
+    "cpu_energy": 1.1241840643722552e-05,
+    "gpu_energy": 1.8234736809841223e-05,
+    "ram_energy": 7.543256492501751e-08,
+    "energy_consumed": 2.955201001848879e-05,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/config.yaml b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fdf34e297e206dfdb03db22d408e889e94421511
--- /dev/null
+++ b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-classification
+  model: cardiffnlp/twitter-roberta-base-sentiment-latest
+  processor: cardiffnlp/twitter-roberta-base-sentiment-latest
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: text_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/hydra.yaml b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..d870a8998517c9979eb67e335dea69be6e17f885
--- /dev/null
+++ b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49
+    - hydra.mode=RUN
+    task:
+    - backend.model=cardiffnlp/twitter-roberta-base-sentiment-latest
+    - backend.processor=cardiffnlp/twitter-roberta-base-sentiment-latest
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=cardiffnlp/twitter-roberta-base-sentiment-latest,backend.processor=cardiffnlp/twitter-roberta-base-sentiment-latest
+    id: ???
+    num: ???
+    config_name: text_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/overrides.yaml b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..67808d0b7bba6e3f32671242aeb0ddaf0d812c03
--- /dev/null
+++ b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=cardiffnlp/twitter-roberta-base-sentiment-latest
+- backend.processor=cardiffnlp/twitter-roberta-base-sentiment-latest
diff --git a/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/cli.log b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..977dceff6d4ccdbdbc7bf2e7393c12d76897cb72
--- /dev/null
+++ b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/cli.log
@@ -0,0 +1,31 @@
+[2024-12-07 06:04:51,930][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:04:51,930][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:04:51,941][device-isolation][INFO] - 	+ Launched device(s) isolation process 428
+[2024-12-07 06:04:51,942][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:04:51,948][process][INFO] - 	+ Launched benchmark in isolated process 429.
+[PROC-0][2024-12-07 06:04:54,496][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:04:55,405][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:04:55,405][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:04:56,101][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSequenceClassification
+[PROC-0][2024-12-07 06:04:56,102][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:04:56,102][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:04:56,102][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:04:56,102][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:04:56,102][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:04:56,104][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:04:56,105][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:04:56,106][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:04:56,106][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:04:56,272][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:04:56,278][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:04:56,279][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:04:57,439][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:04:57,440][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:05:01,611][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:05:02,022][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:05:02,022][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:05:02,022][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:05:02,023][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:05:02,612][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:05:02,612][energy_star][INFO] - 	+ Iteration 1/10
+[2024-12-07 06:05:03,412][experiment][ERROR] - Error during experiment
diff --git a/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/error.log b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..4bb18d5a99b41603e0cf31320432b249efde4662
--- /dev/null
+++ b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/error.log
@@ -0,0 +1,468 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+
Downloading readme:   0%|          | 0.00/271 [00:00<?, ?B/s]
Downloading readme: 100%|██████████| 271/271 [00:00<00:00, 3.52MB/s]
+
+
+
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+
+
Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.10MB/s]
Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.09MB/s]
+
Generating train split:   0%|          | 0/1000 [00:00<?, ? examples/s]
Generating train split: 100%|██████████| 1000/1000 [00:00<00:00, 212069.17 examples/s]
+[codecarbon INFO @ 06:04:57] [setup] RAM Tracking...
+[codecarbon INFO @ 06:04:57] [setup] GPU Tracking...
+[codecarbon INFO @ 06:04:57] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:04:57] GPU available. Starting setup
+[codecarbon INFO @ 06:04:57] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:04:57] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:04:57] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:04:57] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:04:57] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:04:58] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:04:58] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:04:58] >>> Tracker's metadata:
+[codecarbon INFO @ 06:04:58]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:04:58]   Python version: 3.9.20
+[codecarbon INFO @ 06:04:58]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:04:58]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:04:58]   CPU count: 48
+[codecarbon INFO @ 06:04:58]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:04:58]   GPU count: 1
+[codecarbon INFO @ 06:04:58]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:04:59] Not running on AWS
+[codecarbon DEBUG @ 06:05:00] Not running on Azure
+[codecarbon DEBUG @ 06:05:01] Not running on GCP
+[codecarbon INFO @ 06:05:01] Saving emissions data to file /runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/codecarbon.csv
+[codecarbon DEBUG @ 06:05:01] EmissionsData(timestamp='2024-12-07T06:05:01', project_name='codecarbon', run_id='6deca56d-ef84-4ddc-841c-e2c87160ce3e', duration=0.002153368986910209, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
Filter:   0%|          | 0/1000 [00:00<?, ? examples/s]
Filter: 100%|██████████| 1000/1000 [00:00<00:00, 138695.94 examples/s]
+
Running tokenizer on dataset:   0%|          | 0/1000 [00:00<?, ? examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2705.26 examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2681.40 examples/s]
+[codecarbon INFO @ 06:05:02] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.2731304168701172 W
+[codecarbon DEBUG @ 06:05:02] RAM : 0.27 W during 0.41 s [measurement time: 0.0006]
+[codecarbon INFO @ 06:05:02] Energy consumed for all GPUs : 0.000008 kWh. Total GPU Power : 72.741217736018 W
+[codecarbon DEBUG @ 06:05:02] GPU : 72.74 W during 0.41 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:05:02] Energy consumed for all CPUs : 0.000005 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:05:02] CPU : 42.50 W during 0.41 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:05:02] 0.000013 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:05:02] last_duration=0.40725997000117786
+------------------------
+[codecarbon DEBUG @ 06:05:02] EmissionsData(timestamp='2024-12-07T06:05:02', project_name='codecarbon', run_id='6deca56d-ef84-4ddc-841c-e2c87160ce3e', duration=0.41054266900755465, emissions=4.843944946233634e-06, emissions_rate=1.1798883068460047e-05, cpu_power=42.5, gpu_power=72.741217736018, ram_power=0.2731304168701172, cpu_energy=4.845426735523183e-06, gpu_energy=8.24611770822159e-06, ram_energy=3.089886243624274e-08, energy_consumed=1.3122443306181015e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:05:02] EmissionsData(timestamp='2024-12-07T06:05:02', project_name='codecarbon', run_id='6deca56d-ef84-4ddc-841c-e2c87160ce3e', duration=0.004147885018028319, emissions=4.843944946233634e-06, emissions_rate=0.0011678108060324643, cpu_power=42.5, gpu_power=72.741217736018, ram_power=0.2731304168701172, cpu_energy=4.845426735523183e-06, gpu_energy=8.24611770822159e-06, ram_energy=3.089886243624274e-08, energy_consumed=1.3122443306181015e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
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+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [33,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [34,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [35,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [36,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [37,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [38,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [39,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [40,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [517,0,0], thread: [41,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
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+
  2%|▏         | 22/1000 [00:00<00:08, 119.39it/s]
+Error executing job with overrides: ['backend.model=cardiffnlp/twitter-roberta-base-sentiment-latest', 'backend.processor=cardiffnlp/twitter-roberta-base-sentiment-latest']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
+    benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
+    raise error
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
+    report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
+    while not process_context.join():
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
+    raise ProcessRaisedException(msg, error_index, failed_process.pid)
+torch.multiprocessing.spawn.ProcessRaisedException: 
+
+-- Process 0 terminated with the following error:
+Traceback (most recent call last):
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
+    fn(i, *args)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
+    worker_output = worker(*worker_args)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run
+    benchmark.run(backend)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 178, in run
+    self.run_inference_energy_tracking(backend)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 262, in run_inference_energy_tracking
+    inputs = backend.prepare_inputs(inputs)
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 338, in prepare_inputs
+    inputs[key] = value.to(self.config.device)
+RuntimeError: CUDA error: device-side assert triggered
+CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
+For debugging consider passing CUDA_LAUNCH_BLOCKING=1
+Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
+
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
diff --git a/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/experiment_config.json b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..7afbc2d076427523b554d5e4d4edac37106d1001
--- /dev/null
+++ b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/experiment_config.json
@@ -0,0 +1,107 @@
+{
+    "experiment_name": "text_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-classification",
+        "model": "cardiffnlp/twitter-roberta-base-sentiment-latest",
+        "processor": "cardiffnlp/twitter-roberta-base-sentiment-latest",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/preprocess_codecarbon.json b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/preprocess_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..e7bd4da6bd2ad7afb36a7bd5132ed900329a2f76
--- /dev/null
+++ b/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-12-07-06-04-49/preprocess_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:05:02",
+    "project_name": "codecarbon",
+    "run_id": "6deca56d-ef84-4ddc-841c-e2c87160ce3e",
+    "duration": -1733393419.9265978,
+    "emissions": 4.843944946233634e-06,
+    "emissions_rate": 1.1861096620280621e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 72.741217736018,
+    "ram_power": 0.2731304168701172,
+    "cpu_energy": 4.845426735523183e-06,
+    "gpu_energy": 8.24611770822159e-06,
+    "ram_energy": 3.089886243624274e-08,
+    "energy_consumed": 1.3122443306181015e-05,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/config.yaml b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..17dcb4b824134928e4dcdb6e2e65c11e9a18a141
--- /dev/null
+++ b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-classification
+  model: facebook/fasttext-language-identification
+  processor: facebook/fasttext-language-identification
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: text_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/hydra.yaml b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7b3ad4c041dde7f8ed261e59fe7b3776312a48a6
--- /dev/null
+++ b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39
+    - hydra.mode=RUN
+    task:
+    - backend.model=facebook/fasttext-language-identification
+    - backend.processor=facebook/fasttext-language-identification
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=facebook/fasttext-language-identification,backend.processor=facebook/fasttext-language-identification
+    id: ???
+    num: ???
+    config_name: text_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/overrides.yaml b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..b966145f0c13be6b21c9f1110afbb8ee700bb447
--- /dev/null
+++ b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=facebook/fasttext-language-identification
+- backend.processor=facebook/fasttext-language-identification
diff --git a/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/cli.log b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/error.log b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..c941bf795bb43c3edd3e23b0ec199c6198007393
--- /dev/null
+++ b/text_classification/facebook/fasttext-language-identification/2024-12-07-06-11-39/error.log
@@ -0,0 +1,7 @@
+Error executing job with overrides: ['backend.model=facebook/fasttext-language-identification', 'backend.processor=facebook/fasttext-language-identification']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 62, in benchmark_cli
+    experiment_config: ExperimentConfig = OmegaConf.to_object(experiment_config)
+ValueError: `library` must be either `transformers`, `diffusers` or `timm`, but got fasttext
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
diff --git a/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/config.yaml b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..4a0589b3a9146907c10310c8bc0db2ff89901ecc
--- /dev/null
+++ b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/config.yaml
@@ -0,0 +1,94 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-classification
+  model: papluca/xlm-roberta-base-language-detection
+  processor: papluca/xlm-roberta-base-language-detection
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: true
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_classification
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs: {}
+  call_kwargs: {}
+experiment_name: text_classification
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/hydra.yaml b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..80a44202067358c5de8550d82e19e991c951c9f2
--- /dev/null
+++ b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09
+  sweep:
+    dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09
+    - hydra.mode=RUN
+    task:
+    - backend.model=papluca/xlm-roberta-base-language-detection
+    - backend.processor=papluca/xlm-roberta-base-language-detection
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=papluca/xlm-roberta-base-language-detection,backend.processor=papluca/xlm-roberta-base-language-detection
+    id: ???
+    num: ???
+    config_name: text_classification
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/overrides.yaml b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fffc1dc893184d533840955c811c6d2121e29278
--- /dev/null
+++ b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=papluca/xlm-roberta-base-language-detection
+- backend.processor=papluca/xlm-roberta-base-language-detection
diff --git a/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/cli.log b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..de4a397b54740741762cd7bf383e431c3ebd5720
--- /dev/null
+++ b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/cli.log
@@ -0,0 +1,31 @@
+[2024-12-07 06:11:12,327][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:11:12,327][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:11:12,340][device-isolation][INFO] - 	+ Launched device(s) isolation process 1193
+[2024-12-07 06:11:12,340][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-12-07 06:11:12,347][process][INFO] - 	+ Launched benchmark in isolated process 1194.
+[PROC-0][2024-12-07 06:11:14,884][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:11:15,813][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:11:15,813][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:11:17,870][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSequenceClassification
+[PROC-0][2024-12-07 06:11:17,870][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:11:17,871][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:11:17,871][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:11:17,871][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:11:17,871][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:11:17,873][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:11:17,873][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:11:17,874][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:11:17,874][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:11:18,029][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:11:18,035][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:11:18,036][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:11:18,715][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:11:18,715][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:11:22,898][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-12-07 06:11:23,413][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-12-07 06:11:23,413][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-12-07 06:11:23,413][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-12-07 06:11:23,414][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-12-07 06:11:23,983][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-12-07 06:11:23,984][energy_star][INFO] - 	+ Iteration 1/10
+[2024-12-07 06:11:24,966][experiment][ERROR] - Error during experiment
diff --git a/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/error.log b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..434b74cd11f1d938e6e247d328b28bb4151a6c66
--- /dev/null
+++ b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/error.log
@@ -0,0 +1,332 @@
+/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884
+  warnings.warn(
+[codecarbon INFO @ 06:11:18] [setup] RAM Tracking...
+[codecarbon INFO @ 06:11:18] [setup] GPU Tracking...
+[codecarbon INFO @ 06:11:18] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:11:18] GPU available. Starting setup
+[codecarbon INFO @ 06:11:18] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:11:18] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:11:18] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:11:18] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:11:18] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:11:19] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:11:19] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:19] >>> Tracker's metadata:
+[codecarbon INFO @ 06:11:19]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:11:19]   Python version: 3.9.20
+[codecarbon INFO @ 06:11:19]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:11:19]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:11:19]   CPU count: 48
+[codecarbon INFO @ 06:11:19]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:19]   GPU count: 1
+[codecarbon INFO @ 06:11:19]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:11:20] Not running on AWS
+[codecarbon DEBUG @ 06:11:21] Not running on Azure
+[codecarbon DEBUG @ 06:11:22] Not running on GCP
+[codecarbon INFO @ 06:11:22] Saving emissions data to file /runs/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/codecarbon.csv
+[codecarbon DEBUG @ 06:11:22] EmissionsData(timestamp='2024-12-07T06:11:22', project_name='codecarbon', run_id='923157f8-64f5-41ff-85ca-223e77dee9d3', duration=0.002174720022594556, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
Running tokenizer on dataset:   0%|          | 0/1000 [00:00<?, ? examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2095.23 examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2081.87 examples/s]
+[codecarbon INFO @ 06:11:23] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.35901117324829107 W
+[codecarbon DEBUG @ 06:11:23] RAM : 0.36 W during 0.51 s [measurement time: 0.0005]
+[codecarbon INFO @ 06:11:23] Energy consumed for all GPUs : 0.000009 kWh. Total GPU Power : 65.64555861505409 W
+[codecarbon DEBUG @ 06:11:23] GPU : 65.65 W during 0.51 s [measurement time: 0.0023]
+[codecarbon INFO @ 06:11:23] Energy consumed for all CPUs : 0.000006 kWh. Total CPU Power : 42.5 W
+[codecarbon DEBUG @ 06:11:23] CPU : 42.50 W during 0.51 s [measurement time: 0.0000]
+[codecarbon INFO @ 06:11:23] 0.000015 kWh of electricity used since the beginning.
+[codecarbon DEBUG @ 06:11:23] last_duration=0.5110249360150192
+------------------------
+[codecarbon DEBUG @ 06:11:23] EmissionsData(timestamp='2024-12-07T06:11:23', project_name='codecarbon', run_id='923157f8-64f5-41ff-85ca-223e77dee9d3', duration=0.5142133350018412, emissions=5.704357718406114e-06, emissions_rate=1.1093367927507538e-05, cpu_power=42.5, gpu_power=65.64555861505409, ram_power=0.35901117324829107, cpu_energy=6.0693109938155335e-06, gpu_energy=9.33306302175474e-06, ram_energy=5.0962384580857615e-08, energy_consumed=1.545333640015113e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+[codecarbon DEBUG @ 06:11:23] EmissionsData(timestamp='2024-12-07T06:11:23', project_name='codecarbon', run_id='923157f8-64f5-41ff-85ca-223e77dee9d3', duration=0.002264071983518079, emissions=5.704357718406114e-06, emissions_rate=0.0025195125243068777, cpu_power=42.5, gpu_power=65.64555861505409, ram_power=0.35901117324829107, cpu_energy=6.0693109938155335e-06, gpu_energy=9.33306302175474e-06, ram_energy=5.0962384580857615e-08, energy_consumed=1.545333640015113e-05, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
  0%|          | 0/1000 [00:00<?, ?it/s]
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+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [518,0,0], thread: [34,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [518,0,0], thread: [35,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [518,0,0], thread: [36,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
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+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [518,0,0], thread: [43,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
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+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [37,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [38,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [39,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [40,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [41,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [42,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [43,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [44,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [45,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [46,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [47,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [48,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [49,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [50,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [51,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [52,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [53,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [54,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [55,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [56,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [57,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [58,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [59,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [60,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [61,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [62,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+/opt/conda/conda-bld/pytorch_1720538643151/work/aten/src/ATen/native/cuda/Indexing.cu:1284: indexSelectLargeIndex: block: [520,0,0], thread: [63,0,0] Assertion `srcIndex < srcSelectDimSize` failed.
+
  2%|▏         | 22/1000 [00:00<00:07, 124.95it/s]
+Error executing job with overrides: ['backend.model=papluca/xlm-roberta-base-language-detection', 'backend.processor=papluca/xlm-roberta-base-language-detection']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
+    benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
+    raise error
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
+    report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
+    while not process_context.join():
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
+    raise ProcessRaisedException(msg, error_index, failed_process.pid)
+torch.multiprocessing.spawn.ProcessRaisedException: 
+
+-- Process 0 terminated with the following error:
+Traceback (most recent call last):
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
+    fn(i, *args)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
+    worker_output = worker(*worker_args)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run
+    benchmark.run(backend)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 178, in run
+    self.run_inference_energy_tracking(backend)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 262, in run_inference_energy_tracking
+    inputs = backend.prepare_inputs(inputs)
+  File "/optimum-benchmark/optimum_benchmark/backends/pytorch/backend.py", line 338, in prepare_inputs
+    inputs[key] = value.to(self.config.device)
+RuntimeError: CUDA error: device-side assert triggered
+CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
+For debugging consider passing CUDA_LAUNCH_BLOCKING=1
+Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
+
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
diff --git a/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/experiment_config.json b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..77cbcb7597780312a4c454791dd25bf436482e04
--- /dev/null
+++ b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/experiment_config.json
@@ -0,0 +1,107 @@
+{
+    "experiment_name": "text_classification",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-classification",
+        "model": "papluca/xlm-roberta-base-language-detection",
+        "processor": "papluca/xlm-roberta-base-language-detection",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": true,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_classification",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {},
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file
diff --git a/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/preprocess_codecarbon.json b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/preprocess_codecarbon.json
new file mode 100644
index 0000000000000000000000000000000000000000..64692c6d58a9da3c1b625e2ad179de31fb6e47e1
--- /dev/null
+++ b/text_classification/papluca/xlm-roberta-base-language-detection/2024-12-07-06-11-09/preprocess_codecarbon.json
@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-12-07T06:11:23",
+    "project_name": "codecarbon",
+    "run_id": "923157f8-64f5-41ff-85ca-223e77dee9d3",
+    "duration": -1733393419.8229399,
+    "emissions": 5.704357718406114e-06,
+    "emissions_rate": 1.1140483454821696e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 65.64555861505409,
+    "ram_power": 0.35901117324829107,
+    "cpu_energy": 6.0693109938155335e-06,
+    "gpu_energy": 9.33306302175474e-06,
+    "ram_energy": 5.0962384580857615e-08,
+    "energy_consumed": 1.545333640015113e-05,
+    "country_name": "United States",
+    "country_iso_code": "USA",
+    "region": "virginia",
+    "cloud_provider": "",
+    "cloud_region": "",
+    "os": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+    "python_version": "3.9.20",
+    "codecarbon_version": "2.5.1",
+    "cpu_count": 48,
+    "cpu_model": "AMD EPYC 7R32",
+    "gpu_count": 1,
+    "gpu_model": "1 x NVIDIA A10G",
+    "longitude": -77.4903,
+    "latitude": 39.0469,
+    "ram_total_size": 186.7047882080078,
+    "tracking_mode": "process",
+    "on_cloud": "N",
+    "pue": 1.0
+}
\ No newline at end of file
diff --git a/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/config.yaml b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..41586d98d372f5416cec93f358526e591ca1006b
--- /dev/null
+++ b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/config.yaml
@@ -0,0 +1,96 @@
+backend:
+  name: pytorch
+  version: 2.4.0
+  _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
+  task: text-generation
+  model: distributed/optimized-gpt2-1b
+  processor: distributed/optimized-gpt2-1b
+  library: null
+  device: cuda
+  device_ids: '0'
+  seed: 42
+  inter_op_num_threads: null
+  intra_op_num_threads: null
+  hub_kwargs: {}
+  no_weights: true
+  device_map: null
+  torch_dtype: null
+  amp_autocast: false
+  amp_dtype: null
+  eval_mode: true
+  to_bettertransformer: false
+  low_cpu_mem_usage: null
+  attn_implementation: null
+  cache_implementation: null
+  torch_compile: false
+  torch_compile_config: {}
+  quantization_scheme: null
+  quantization_config: {}
+  deepspeed_inference: false
+  deepspeed_inference_config: {}
+  peft_type: null
+  peft_config: {}
+launcher:
+  name: process
+  _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
+  device_isolation: false
+  device_isolation_action: warn
+  start_method: spawn
+benchmark:
+  name: energy_star
+  _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
+  dataset_name: EnergyStarAI/text_generation
+  dataset_config: ''
+  dataset_split: train
+  num_samples: 1000
+  input_shapes:
+    batch_size: 1
+  text_column_name: text
+  truncation: true
+  max_length: -1
+  dataset_prefix1: ''
+  dataset_prefix2: ''
+  t5_task: ''
+  image_column_name: image
+  resize: false
+  question_column_name: question
+  context_column_name: context
+  sentence1_column_name: sentence1
+  sentence2_column_name: sentence2
+  audio_column_name: audio
+  iterations: 10
+  warmup_runs: 10
+  energy: true
+  forward_kwargs: {}
+  generate_kwargs:
+    max_new_tokens: 10
+    min_new_tokens: 10
+  call_kwargs: {}
+experiment_name: text_generation
+environment:
+  cpu: ' AMD EPYC 7R32'
+  cpu_count: 48
+  cpu_ram_mb: 200472.73984
+  system: Linux
+  machine: x86_64
+  platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+  processor: x86_64
+  python_version: 3.9.20
+  gpu:
+  - NVIDIA A10G
+  gpu_count: 1
+  gpu_vram_mb: 24146608128
+  optimum_benchmark_version: 0.2.0
+  optimum_benchmark_commit: null
+  transformers_version: 4.44.0
+  transformers_commit: null
+  accelerate_version: 0.33.0
+  accelerate_commit: null
+  diffusers_version: 0.30.0
+  diffusers_commit: null
+  optimum_version: null
+  optimum_commit: null
+  timm_version: null
+  timm_commit: null
+  peft_version: null
+  peft_commit: null
diff --git a/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/hydra.yaml b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/hydra.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..64bf4ca2da728e50b9f55afb6edcf0749ba8e49c
--- /dev/null
+++ b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/hydra.yaml
@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: /runs/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25
+  sweep:
+    dir: sweeps/${experiment_name}/${backend.model}/${now:%Y-%m-%d-%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+      colorlog:
+        (): colorlog.ColoredFormatter
+        format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
+          - %(message)s'
+        log_colors:
+          DEBUG: purple
+          INFO: green
+          WARNING: yellow
+          ERROR: red
+          CRITICAL: red
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: colorlog
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.run.dir=/runs/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25
+    - hydra.mode=RUN
+    task:
+    - backend.model=distributed/optimized-gpt2-1b
+    - backend.processor=distributed/optimized-gpt2-1b
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=distributed/optimized-gpt2-1b,backend.processor=distributed/optimized-gpt2-1b
+    id: ???
+    num: ???
+    config_name: text_generation
+    env_set:
+      OVERRIDE_BENCHMARKS: '1'
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: optimum_benchmark
+      schema: pkg
+      provider: main
+    - path: hydra_plugins.hydra_colorlog.conf
+      schema: pkg
+      provider: hydra-colorlog
+    - path: /optimum-benchmark/examples/energy_star
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /runs/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25
+    choices:
+      benchmark: energy_star
+      launcher: process
+      backend: pytorch
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: colorlog
+      hydra/hydra_logging: colorlog
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false
diff --git a/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/overrides.yaml b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/overrides.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..aa341f72ee3759c430f510ecc235b14b5ed098ba
--- /dev/null
+++ b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/.hydra/overrides.yaml
@@ -0,0 +1,2 @@
+- backend.model=distributed/optimized-gpt2-1b
+- backend.processor=distributed/optimized-gpt2-1b
diff --git a/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/cli.log b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/cli.log
new file mode 100644
index 0000000000000000000000000000000000000000..26d32db5c7e9a80c4842f94e26663130b80c57cd
--- /dev/null
+++ b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/cli.log
@@ -0,0 +1,23 @@
+[2024-12-07 06:11:28,214][launcher][INFO] - ََAllocating process launcher
+[2024-12-07 06:11:28,214][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-12-07 06:11:28,228][process][INFO] - 	+ Launched benchmark in isolated process 1437.
+[PROC-0][2024-12-07 06:11:30,765][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-12-07 06:11:31,710][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-12-07 06:11:31,711][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-12-07 06:11:32,377][pytorch][INFO] - 	+ Using AutoModel class AutoModelForCausalLM
+[PROC-0][2024-12-07 06:11:32,377][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-12-07 06:11:32,377][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-12-07 06:11:32,377][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-12-07 06:11:32,377][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-12-07 06:11:32,378][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-12-07 06:11:32,400][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-12-07 06:11:32,400][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-12-07 06:11:32,402][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-12-07 06:11:32,402][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-12-07 06:11:32,699][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-12-07 06:11:32,706][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-12-07 06:11:32,706][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-12-07 06:11:33,875][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-12-07 06:11:33,876][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-12-07 06:11:38,067][energy_star][INFO] - 	+ Preprocessing dataset
+[2024-12-07 06:11:38,690][experiment][ERROR] - Error during experiment
diff --git a/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/error.log b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/error.log
new file mode 100644
index 0000000000000000000000000000000000000000..1ec301ed7ee9d94cc4fdfdd33a63e4fef63ee9b7
--- /dev/null
+++ b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/error.log
@@ -0,0 +1,63 @@
+
Downloading readme:   0%|          | 0.00/289 [00:00<?, ?B/s]
Downloading readme: 100%|██████████| 289/289 [00:00<00:00, 3.59MB/s]
+
+
Downloading data:   0%|          | 0.00/1.07M [00:00<?, ?B/s]
+
Downloading data: 100%|██████████| 1.07M/1.07M [00:00<00:00, 5.91MB/s]
Downloading data: 100%|██████████| 1.07M/1.07M [00:00<00:00, 5.90MB/s]
+
Generating train split:   0%|          | 0/1000 [00:00<?, ? examples/s]
Generating train split: 100%|██████████| 1000/1000 [00:00<00:00, 111328.57 examples/s]
+[codecarbon INFO @ 06:11:33] [setup] RAM Tracking...
+[codecarbon INFO @ 06:11:33] [setup] GPU Tracking...
+[codecarbon INFO @ 06:11:33] Tracking Nvidia GPU via pynvml
+[codecarbon DEBUG @ 06:11:33] GPU available. Starting setup
+[codecarbon INFO @ 06:11:33] [setup] CPU Tracking...
+[codecarbon DEBUG @ 06:11:33] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
+[codecarbon DEBUG @ 06:11:33] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
+[codecarbon DEBUG @ 06:11:33] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
+[codecarbon WARNING @ 06:11:33] No CPU tracking mode found. Falling back on CPU constant mode.
+[codecarbon WARNING @ 06:11:35] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
+[codecarbon INFO @ 06:11:35] CPU Model on constant consumption mode: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:35] >>> Tracker's metadata:
+[codecarbon INFO @ 06:11:35]   Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
+[codecarbon INFO @ 06:11:35]   Python version: 3.9.20
+[codecarbon INFO @ 06:11:35]   CodeCarbon version: 2.5.1
+[codecarbon INFO @ 06:11:35]   Available RAM : 186.705 GB
+[codecarbon INFO @ 06:11:35]   CPU count: 48
+[codecarbon INFO @ 06:11:35]   CPU model: AMD EPYC 7R32
+[codecarbon INFO @ 06:11:35]   GPU count: 1
+[codecarbon INFO @ 06:11:35]   GPU model: 1 x NVIDIA A10G
+[codecarbon DEBUG @ 06:11:36] Not running on AWS
+[codecarbon DEBUG @ 06:11:37] Not running on Azure
+[codecarbon DEBUG @ 06:11:38] Not running on GCP
+[codecarbon INFO @ 06:11:38] Saving emissions data to file /runs/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/codecarbon.csv
+[codecarbon DEBUG @ 06:11:38] EmissionsData(timestamp='2024-12-07T06:11:38', project_name='codecarbon', run_id='b9b03429-845c-4691-90c3-af17425fd4b3', duration=0.0022394309926312417, emissions=0.0, emissions_rate=0.0, cpu_power=0.0, gpu_power=0.0, ram_power=0.0, cpu_energy=0, gpu_energy=0, ram_energy=0, energy_consumed=0, country_name='United States', country_iso_code='USA', region='virginia', cloud_provider='', cloud_region='', os='Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35', python_version='3.9.20', codecarbon_version='2.5.1', cpu_count=48, cpu_model='AMD EPYC 7R32', gpu_count=1, gpu_model='1 x NVIDIA A10G', longitude=-77.4903, latitude=39.0469, ram_total_size=186.7047882080078, tracking_mode='process', on_cloud='N', pue=1.0)
+
Filter:   0%|          | 0/1000 [00:00<?, ? examples/s]
Filter: 100%|██████████| 1000/1000 [00:00<00:00, 127123.23 examples/s]
+Error executing job with overrides: ['backend.model=distributed/optimized-gpt2-1b', 'backend.processor=distributed/optimized-gpt2-1b']
+Traceback (most recent call last):
+  File "/optimum-benchmark/optimum_benchmark/cli.py", line 65, in benchmark_cli
+    benchmark_report: BenchmarkReport = launch(experiment_config=experiment_config)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 102, in launch
+    raise error
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 90, in launch
+    report = launcher.launch(run, experiment_config.benchmark, experiment_config.backend)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 47, in launch
+    while not process_context.join():
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 189, in join
+    raise ProcessRaisedException(msg, error_index, failed_process.pid)
+torch.multiprocessing.spawn.ProcessRaisedException: 
+
+-- Process 0 terminated with the following error:
+Traceback (most recent call last):
+  File "/opt/conda/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 76, in _wrap
+    fn(i, *args)
+  File "/optimum-benchmark/optimum_benchmark/launchers/process/launcher.py", line 63, in entrypoint
+    worker_output = worker(*worker_args)
+  File "/optimum-benchmark/optimum_benchmark/experiment.py", line 62, in run
+    benchmark.run(backend)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/benchmark.py", line 122, in run
+    self.dataset = preprocess(
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/preprocessing_utils.py", line 28, in preprocess
+    return task_to_preprocessing[task](dataset, config, preprocessor, pretrained_config)
+  File "/optimum-benchmark/optimum_benchmark/benchmarks/energy_star/preprocessing_utils.py", line 274, in text_generation_preprocessing
+    tokenizer.pad_token = tokenizer.eos_token
+AttributeError: 'NoneType' object has no attribute 'eos_token'
+
+
+Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
diff --git a/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/experiment_config.json b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/experiment_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..756a118571fc3aa37c0edf32fe8c82f1d6139078
--- /dev/null
+++ b/text_generation/distributed/optimized-gpt2-1b/2024-12-07-06-11-25/experiment_config.json
@@ -0,0 +1,110 @@
+{
+    "experiment_name": "text_generation",
+    "backend": {
+        "name": "pytorch",
+        "version": "2.4.0",
+        "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
+        "task": "text-generation",
+        "model": "distributed/optimized-gpt2-1b",
+        "processor": "distributed/optimized-gpt2-1b",
+        "library": "transformers",
+        "device": "cuda",
+        "device_ids": "0",
+        "seed": 42,
+        "inter_op_num_threads": null,
+        "intra_op_num_threads": null,
+        "hub_kwargs": {
+            "revision": "main",
+            "force_download": false,
+            "local_files_only": false,
+            "trust_remote_code": true
+        },
+        "no_weights": true,
+        "device_map": null,
+        "torch_dtype": null,
+        "amp_autocast": false,
+        "amp_dtype": null,
+        "eval_mode": true,
+        "to_bettertransformer": false,
+        "low_cpu_mem_usage": null,
+        "attn_implementation": null,
+        "cache_implementation": null,
+        "torch_compile": false,
+        "torch_compile_config": {},
+        "quantization_scheme": null,
+        "quantization_config": {},
+        "deepspeed_inference": false,
+        "deepspeed_inference_config": {},
+        "peft_type": null,
+        "peft_config": {}
+    },
+    "launcher": {
+        "name": "process",
+        "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
+        "device_isolation": false,
+        "device_isolation_action": "warn",
+        "start_method": "spawn"
+    },
+    "benchmark": {
+        "name": "energy_star",
+        "_target_": "optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark",
+        "dataset_name": "EnergyStarAI/text_generation",
+        "dataset_config": "",
+        "dataset_split": "train",
+        "num_samples": 1000,
+        "input_shapes": {
+            "batch_size": 1
+        },
+        "text_column_name": "text",
+        "truncation": true,
+        "max_length": -1,
+        "dataset_prefix1": "",
+        "dataset_prefix2": "",
+        "t5_task": "",
+        "image_column_name": "image",
+        "resize": false,
+        "question_column_name": "question",
+        "context_column_name": "context",
+        "sentence1_column_name": "sentence1",
+        "sentence2_column_name": "sentence2",
+        "audio_column_name": "audio",
+        "iterations": 10,
+        "warmup_runs": 10,
+        "energy": true,
+        "forward_kwargs": {},
+        "generate_kwargs": {
+            "max_new_tokens": 10,
+            "min_new_tokens": 10
+        },
+        "call_kwargs": {}
+    },
+    "environment": {
+        "cpu": " AMD EPYC 7R32",
+        "cpu_count": 48,
+        "cpu_ram_mb": 200472.73984,
+        "system": "Linux",
+        "machine": "x86_64",
+        "platform": "Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35",
+        "processor": "x86_64",
+        "python_version": "3.9.20",
+        "gpu": [
+            "NVIDIA A10G"
+        ],
+        "gpu_count": 1,
+        "gpu_vram_mb": 24146608128,
+        "optimum_benchmark_version": "0.2.0",
+        "optimum_benchmark_commit": null,
+        "transformers_version": "4.44.0",
+        "transformers_commit": null,
+        "accelerate_version": "0.33.0",
+        "accelerate_commit": null,
+        "diffusers_version": "0.30.0",
+        "diffusers_commit": null,
+        "optimum_version": null,
+        "optimum_commit": null,
+        "timm_version": null,
+        "timm_commit": null,
+        "peft_version": null,
+        "peft_commit": null
+    }
+}
\ No newline at end of file