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text_classification/avichr/heBERT_sentiment_analysis/.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: avichr/heBERT_sentiment_analysis
+  processor: avichr/heBERT_sentiment_analysis
+  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

text_classification/avichr/heBERT_sentiment_analysis/.hydra/hydra.yaml

@@ -0,0 +1,175 @@
+hydra:
+  run:
+    dir: ./runs/text_classification/avichr/heBERT_sentiment_analysis/
+  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/avichr/heBERT_sentiment_analysis/
+    - hydra.mode=RUN
+    task:
+    - backend.model=avichr/heBERT_sentiment_analysis
+    - backend.processor=avichr/heBERT_sentiment_analysis
+  job:
+    name: cli
+    chdir: true
+    override_dirname: backend.model=avichr/heBERT_sentiment_analysis,backend.processor=avichr/heBERT_sentiment_analysis
+    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/avichr/heBERT_sentiment_analysis
+    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

text_classification/avichr/heBERT_sentiment_analysis/.hydra/overrides.yaml

@@ -0,0 +1,2 @@
+- backend.model=avichr/heBERT_sentiment_analysis
+- backend.processor=avichr/heBERT_sentiment_analysis

text_classification/avichr/heBERT_sentiment_analysis/benchmark_report.json

@@ -0,0 +1,107 @@
+{
+    "forward": {
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+        "latency": null,
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+        "energy": {
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+            "total": 0.00045157895352636676
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 2214452.1842548894
+        },
+        "measures": [
+            {
+                "unit": "kWh",
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+            {
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+            {
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+            },
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+                "gpu": 0.00041981228029364104,
+                "total": 0.0004964972772546136
+            },
+            {
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+            {
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+                "ram": 6.299462761465285e-07,
+                "gpu": 0.0004321947901999579,
+                "total": 0.000508184979327116
+            },
+            {
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+                "ram": 6.411044620813194e-07,
+                "gpu": 0.0004362136823043983,
+                "total": 0.0005135488521434781
+            }
+        ]
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+    "preprocess": {
+        "memory": null,
+        "latency": null,
+        "throughput": null,
+        "energy": {
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+            "ram": 4.131239601138592e-08,
+            "gpu": 1.020028593679001e-05,
+            "total": 1.6517976882029355e-05
+        },
+        "efficiency": {
+            "unit": "samples/kWh",
+            "value": 60540101.680850804
+        },
+        "measures": null
+    }
+}

text_classification/avichr/heBERT_sentiment_analysis/cli.log

@@ -0,0 +1,113 @@
+[2024-10-03 19:42:43,063][launcher][INFO] - ََAllocating process launcher
+[2024-10-03 19:42:43,063][process][INFO] - 	+ Setting multiprocessing start method to spawn.
+[2024-10-03 19:42:43,073][device-isolation][INFO] - 	+ Launched device(s) isolation process 180
+[2024-10-03 19:42:43,073][device-isolation][INFO] - 	+ Isolating device(s) [0]
+[2024-10-03 19:42:43,078][process][INFO] - 	+ Launched benchmark in isolated process 181.
+[PROC-0][2024-10-03 19:42:45,657][datasets][INFO] - PyTorch version 2.4.0 available.
+[PROC-0][2024-10-03 19:42:46,554][backend][INFO] - َAllocating pytorch backend
+[PROC-0][2024-10-03 19:42:46,554][backend][INFO] - 	+ Setting random seed to 42
+[PROC-0][2024-10-03 19:42:46,948][pytorch][INFO] - 	+ Using AutoModel class AutoModelForSequenceClassification
+[PROC-0][2024-10-03 19:42:46,948][pytorch][INFO] - 	+ Creating backend temporary directory
+[PROC-0][2024-10-03 19:42:46,949][pytorch][INFO] - 	+ Loading model with random weights
+[PROC-0][2024-10-03 19:42:46,949][pytorch][INFO] - 	+ Creating no weights model
+[PROC-0][2024-10-03 19:42:46,949][pytorch][INFO] - 	+ Creating no weights model directory
+[PROC-0][2024-10-03 19:42:46,949][pytorch][INFO] - 	+ Creating no weights model state dict
+[PROC-0][2024-10-03 19:42:46,951][pytorch][INFO] - 	+ Saving no weights model safetensors
+[PROC-0][2024-10-03 19:42:46,951][pytorch][INFO] - 	+ Saving no weights model pretrained config
+[PROC-0][2024-10-03 19:42:46,952][pytorch][INFO] - 	+ Loading no weights AutoModel
+[PROC-0][2024-10-03 19:42:46,952][pytorch][INFO] - 	+ Loading model directly on device: cuda
+[PROC-0][2024-10-03 19:42:47,201][pytorch][INFO] - 	+ Turning on model's eval mode
+[PROC-0][2024-10-03 19:42:47,207][benchmark][INFO] - Allocating energy_star benchmark
+[PROC-0][2024-10-03 19:42:47,207][energy_star][INFO] - 	+ Loading raw dataset
+[PROC-0][2024-10-03 19:42:47,732][energy_star][INFO] - 	+ Initializing Inference report
+[PROC-0][2024-10-03 19:42:47,732][energy][INFO] - 	+ Tracking GPU energy on devices [0]
+[PROC-0][2024-10-03 19:42:51,911][energy_star][INFO] - 	+ Preprocessing dataset
+[PROC-0][2024-10-03 19:42:52,443][energy][INFO] - 	+ Saving codecarbon emission data to preprocess_codecarbon.json
+[PROC-0][2024-10-03 19:42:52,443][energy_star][INFO] - 	+ Preparing backend for Inference
+[PROC-0][2024-10-03 19:42:52,443][energy_star][INFO] - 	+ Initialising dataloader
+[PROC-0][2024-10-03 19:42:52,444][energy_star][INFO] - 	+ Warming up backend for Inference
+[PROC-0][2024-10-03 19:42:53,186][energy_star][INFO] - 	+ Running Inference energy tracking for 10 iterations
+[PROC-0][2024-10-03 19:42:53,186][energy_star][INFO] - 	+ Iteration 1/10
+[PROC-0][2024-10-03 19:42:59,630][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:42:59,630][energy_star][INFO] - 	+ Iteration 2/10
+[PROC-0][2024-10-03 19:43:06,055][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:06,055][energy_star][INFO] - 	+ Iteration 3/10
+[PROC-0][2024-10-03 19:43:12,457][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:12,458][energy_star][INFO] - 	+ Iteration 4/10
+[PROC-0][2024-10-03 19:43:18,876][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:18,876][energy_star][INFO] - 	+ Iteration 5/10
+[PROC-0][2024-10-03 19:43:25,328][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:25,329][energy_star][INFO] - 	+ Iteration 6/10
+[PROC-0][2024-10-03 19:43:31,771][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:31,772][energy_star][INFO] - 	+ Iteration 7/10
+[PROC-0][2024-10-03 19:43:38,200][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:38,200][energy_star][INFO] - 	+ Iteration 8/10
+[PROC-0][2024-10-03 19:43:44,682][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:44,683][energy_star][INFO] - 	+ Iteration 9/10
+[PROC-0][2024-10-03 19:43:51,067][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:51,067][energy_star][INFO] - 	+ Iteration 10/10
+[PROC-0][2024-10-03 19:43:57,564][energy][INFO] - 	+ Saving codecarbon emission data to forward_codecarbon.json
+[PROC-0][2024-10-03 19:43:57,565][energy][INFO] - 		+ forward energy consumption:
+[PROC-0][2024-10-03 19:43:57,565][energy][INFO] - 			+ CPU: 0.000068 (kWh)
+[PROC-0][2024-10-03 19:43:57,565][energy][INFO] - 			+ GPU: 0.000383 (kWh)
+[PROC-0][2024-10-03 19:43:57,565][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,565][energy][INFO] - 			+ total: 0.000452 (kWh)
+[PROC-0][2024-10-03 19:43:57,565][energy][INFO] - 		+ forward_iteration_1 energy consumption:
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ CPU: 0.000076 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ GPU: 0.000421 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ total: 0.000498 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 		+ forward_iteration_2 energy consumption:
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ CPU: 0.000076 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ GPU: 0.000420 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ total: 0.000497 (kWh)
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 		+ forward_iteration_3 energy consumption:
+[PROC-0][2024-10-03 19:43:57,566][energy][INFO] - 			+ CPU: 0.000076 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ GPU: 0.000429 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ total: 0.000505 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 		+ forward_iteration_4 energy consumption:
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ CPU: 0.000076 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ GPU: 0.000423 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ total: 0.000499 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 		+ forward_iteration_5 energy consumption:
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ CPU: 0.000076 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ GPU: 0.000423 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,567][energy][INFO] - 			+ total: 0.000500 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 		+ forward_iteration_6 energy consumption:
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ CPU: 0.000076 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ GPU: 0.000420 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ total: 0.000496 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 		+ forward_iteration_7 energy consumption:
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ CPU: 0.000000 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ GPU: 0.000000 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ total: 0.000000 (kWh)
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 		+ forward_iteration_8 energy consumption:
+[PROC-0][2024-10-03 19:43:57,568][energy][INFO] - 			+ CPU: 0.000077 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ GPU: 0.000421 (kWh)
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+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ total: 0.000498 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 		+ forward_iteration_9 energy consumption:
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ CPU: 0.000075 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ GPU: 0.000432 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ total: 0.000508 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 		+ forward_iteration_10 energy consumption:
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ CPU: 0.000077 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ GPU: 0.000436 (kWh)
+[PROC-0][2024-10-03 19:43:57,569][energy][INFO] - 			+ RAM: 0.000001 (kWh)
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 			+ total: 0.000514 (kWh)
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 		+ preprocess energy consumption:
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 			+ CPU: 0.000006 (kWh)
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 			+ GPU: 0.000010 (kWh)
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 			+ RAM: 0.000000 (kWh)
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 			+ total: 0.000017 (kWh)
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 		+ forward energy efficiency: 2214452.184255 (samples/kWh)
+[PROC-0][2024-10-03 19:43:57,570][energy][INFO] - 		+ preprocess energy efficiency: 60540101.680851 (samples/kWh)
+[2024-10-03 19:43:58,198][device-isolation][INFO] - 	+ Closing device(s) isolation process...
+[2024-10-03 19:43:58,247][datasets][INFO] - PyTorch version 2.4.0 available.

text_classification/avichr/heBERT_sentiment_analysis/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": "avichr/heBERT_sentiment_analysis",
+        "processor": "avichr/heBERT_sentiment_analysis",
+        "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
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+        "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
+    }
+}

text_classification/avichr/heBERT_sentiment_analysis/forward_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-10-03T19:43:57",
+    "project_name": "codecarbon",
+    "run_id": "d6b7512b-be70-4762-9e1e-6f44bc04be86",
+    "duration": -1727471021.775965,
+    "emissions": 0.00018956853605248646,
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+    "cpu_energy": 7.669406537699818e-05,
+    "gpu_energy": 0.0004362136823043983,
+    "ram_energy": 6.411044620813194e-07,
+    "energy_consumed": 0.0005135488521434781,
+    "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
+}

text_classification/avichr/heBERT_sentiment_analysis/preprocess_codecarbon.json

@@ -0,0 +1,33 @@
+{
+    "timestamp": "2024-10-03T19:42:52",
+    "project_name": "codecarbon",
+    "run_id": "d6b7512b-be70-4762-9e1e-6f44bc04be86",
+    "duration": -1727471027.7412832,
+    "emissions": 6.097353120361531e-06,
+    "emissions_rate": 1.1519685043833091e-05,
+    "cpu_power": 42.5,
+    "gpu_power": 69.36066379667973,
+    "ram_power": 0.281341552734375,
+    "cpu_energy": 6.2763785492279575e-06,
+    "gpu_energy": 1.020028593679001e-05,
+    "ram_energy": 4.131239601138592e-08,
+    "energy_consumed": 1.6517976882029355e-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
+}