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  1. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/.hydra/config.yaml +94 -0
  2. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/.hydra/hydra.yaml +175 -0
  3. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/.hydra/overrides.yaml +2 -0
  4. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/benchmark_report.json +107 -0
  5. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/cli.log +113 -0
  6. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/error.log +178 -0
  7. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/experiment_config.json +107 -0
  8. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/forward_codecarbon.json +33 -0
  9. runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/preprocess_codecarbon.json +33 -0
runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/.hydra/config.yaml ADDED
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1
+ backend:
2
+ name: pytorch
3
+ version: 2.4.0
4
+ _target_: optimum_benchmark.backends.pytorch.backend.PyTorchBackend
5
+ task: text-classification
6
+ model: distilbert/distilbert-base-uncased-finetuned-sst-2-english
7
+ processor: distilbert/distilbert-base-uncased-finetuned-sst-2-english
8
+ library: null
9
+ device: cuda
10
+ device_ids: '0'
11
+ seed: 42
12
+ inter_op_num_threads: null
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+ intra_op_num_threads: null
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+ hub_kwargs: {}
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+ no_weights: true
16
+ device_map: null
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+ torch_dtype: null
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+ amp_autocast: false
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+ amp_dtype: null
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+ eval_mode: true
21
+ to_bettertransformer: false
22
+ low_cpu_mem_usage: null
23
+ attn_implementation: null
24
+ cache_implementation: null
25
+ torch_compile: false
26
+ torch_compile_config: {}
27
+ quantization_scheme: null
28
+ quantization_config: {}
29
+ deepspeed_inference: false
30
+ deepspeed_inference_config: {}
31
+ peft_type: null
32
+ peft_config: {}
33
+ launcher:
34
+ name: process
35
+ _target_: optimum_benchmark.launchers.process.launcher.ProcessLauncher
36
+ device_isolation: true
37
+ device_isolation_action: warn
38
+ start_method: spawn
39
+ benchmark:
40
+ name: energy_star
41
+ _target_: optimum_benchmark.benchmarks.energy_star.benchmark.EnergyStarBenchmark
42
+ dataset_name: EnergyStarAI/text_classification
43
+ dataset_config: ''
44
+ dataset_split: train
45
+ num_samples: 1000
46
+ input_shapes:
47
+ batch_size: 1
48
+ text_column_name: text
49
+ truncation: true
50
+ max_length: -1
51
+ dataset_prefix1: ''
52
+ dataset_prefix2: ''
53
+ t5_task: ''
54
+ image_column_name: image
55
+ resize: false
56
+ question_column_name: question
57
+ context_column_name: context
58
+ sentence1_column_name: sentence1
59
+ sentence2_column_name: sentence2
60
+ audio_column_name: audio
61
+ iterations: 10
62
+ warmup_runs: 10
63
+ energy: true
64
+ forward_kwargs: {}
65
+ generate_kwargs: {}
66
+ call_kwargs: {}
67
+ experiment_name: text_classification
68
+ environment:
69
+ cpu: ' AMD EPYC 7R32'
70
+ cpu_count: 48
71
+ cpu_ram_mb: 200472.73984
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+ system: Linux
73
+ machine: x86_64
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+ platform: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
75
+ processor: x86_64
76
+ python_version: 3.9.20
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+ gpu:
78
+ - NVIDIA A10G
79
+ gpu_count: 1
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+ gpu_vram_mb: 24146608128
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+ optimum_benchmark_version: 0.2.0
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+ optimum_benchmark_commit: null
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+ transformers_version: 4.44.0
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+ transformers_commit: null
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+ accelerate_version: 0.33.0
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+ accelerate_commit: null
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+ diffusers_version: 0.30.0
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+ diffusers_commit: null
89
+ optimum_version: null
90
+ optimum_commit: null
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+ timm_version: null
92
+ timm_commit: null
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+ peft_version: null
94
+ peft_commit: null
runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/.hydra/hydra.yaml ADDED
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1
+ hydra:
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+ run:
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+ dir: ./runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33
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+ sweep:
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+ dir: sweeps/${experiment_name}/${now:%Y-%m-%d-%H-%M-%S}
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+ subdir: ${hydra.job.num}
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+ launcher:
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+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
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+ sweeper:
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+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
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+ max_batch_size: null
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+ params: null
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+ help:
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+ app_name: ${hydra.job.name}
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+ header: '${hydra.help.app_name} is powered by Hydra.
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+
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+ '
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+ footer: 'Powered by Hydra (https://hydra.cc)
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+
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+ Use --hydra-help to view Hydra specific help
21
+
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+ '
23
+ template: '${hydra.help.header}
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+
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+ == Configuration groups ==
26
+
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+ Compose your configuration from those groups (group=option)
28
+
29
+
30
+ $APP_CONFIG_GROUPS
31
+
32
+
33
+ == Config ==
34
+
35
+ Override anything in the config (foo.bar=value)
36
+
37
+
38
+ $CONFIG
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+
40
+
41
+ ${hydra.help.footer}
42
+
43
+ '
44
+ hydra_help:
45
+ template: 'Hydra (${hydra.runtime.version})
46
+
47
+ See https://hydra.cc for more info.
48
+
49
+
50
+ == Flags ==
51
+
52
+ $FLAGS_HELP
53
+
54
+
55
+ == Configuration groups ==
56
+
57
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
58
+ to command line)
59
+
60
+
61
+ $HYDRA_CONFIG_GROUPS
62
+
63
+
64
+ Use ''--cfg hydra'' to Show the Hydra config.
65
+
66
+ '
67
+ hydra_help: ???
68
+ hydra_logging:
69
+ version: 1
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+ formatters:
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+ colorlog:
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+ (): colorlog.ColoredFormatter
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+ format: '[%(cyan)s%(asctime)s%(reset)s][%(purple)sHYDRA%(reset)s] %(message)s'
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+ handlers:
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+ console:
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+ class: logging.StreamHandler
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+ formatter: colorlog
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+ stream: ext://sys.stdout
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+ root:
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+ level: INFO
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+ handlers:
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+ - console
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+ disable_existing_loggers: false
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+ job_logging:
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+ version: 1
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+ formatters:
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+ simple:
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+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
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+ colorlog:
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+ (): colorlog.ColoredFormatter
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+ format: '[%(cyan)s%(asctime)s%(reset)s][%(blue)s%(name)s%(reset)s][%(log_color)s%(levelname)s%(reset)s]
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+ - %(message)s'
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+ log_colors:
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+ DEBUG: purple
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+ INFO: green
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+ WARNING: yellow
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+ ERROR: red
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+ CRITICAL: red
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+ handlers:
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+ console:
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+ class: logging.StreamHandler
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+ formatter: colorlog
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+ stream: ext://sys.stdout
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+ file:
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+ class: logging.FileHandler
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+ formatter: simple
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+ filename: ${hydra.job.name}.log
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+ root:
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+ level: INFO
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+ handlers:
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+ - console
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+ - file
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+ disable_existing_loggers: false
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+ env: {}
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+ mode: RUN
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+ searchpath: []
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+ callbacks: {}
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+ output_subdir: .hydra
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+ overrides:
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+ hydra:
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+ - hydra.run.dir=./runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33
122
+ - hydra.mode=RUN
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+ task:
124
+ - backend.model=distilbert/distilbert-base-uncased-finetuned-sst-2-english
125
+ - backend.processor=distilbert/distilbert-base-uncased-finetuned-sst-2-english
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+ job:
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+ name: cli
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+ chdir: true
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+ override_dirname: backend.model=distilbert/distilbert-base-uncased-finetuned-sst-2-english,backend.processor=distilbert/distilbert-base-uncased-finetuned-sst-2-english
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+ id: ???
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+ num: ???
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+ config_name: text_classification
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+ env_set:
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+ OVERRIDE_BENCHMARKS: '1'
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+ env_copy: []
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+ config:
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+ override_dirname:
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+ kv_sep: '='
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+ item_sep: ','
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+ exclude_keys: []
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+ runtime:
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+ version: 1.3.2
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+ version_base: '1.3'
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+ cwd: /
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+ config_sources:
146
+ - path: hydra.conf
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+ schema: pkg
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+ provider: hydra
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+ - path: optimum_benchmark
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+ schema: pkg
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+ provider: main
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+ - path: hydra_plugins.hydra_colorlog.conf
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+ schema: pkg
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+ provider: hydra-colorlog
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+ - path: /optimum-benchmark/examples/energy_star
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+ schema: file
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+ provider: command-line
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+ - path: ''
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+ schema: structured
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+ provider: schema
161
+ output_dir: /runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33
162
+ choices:
163
+ benchmark: energy_star
164
+ launcher: process
165
+ backend: pytorch
166
+ hydra/env: default
167
+ hydra/callbacks: null
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+ hydra/job_logging: colorlog
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+ hydra/hydra_logging: colorlog
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+ hydra/hydra_help: default
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+ hydra/help: default
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+ hydra/sweeper: basic
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+ hydra/launcher: basic
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+ hydra/output: default
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+ verbose: false
runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/.hydra/overrides.yaml ADDED
@@ -0,0 +1,2 @@
 
 
 
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+ - backend.model=distilbert/distilbert-base-uncased-finetuned-sst-2-english
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+ - backend.processor=distilbert/distilbert-base-uncased-finetuned-sst-2-english
runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/benchmark_report.json ADDED
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runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/cli.log ADDED
@@ -0,0 +1,113 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [2024-10-08 17:37:36,010][launcher][INFO] - ََAllocating process launcher
2
+ [2024-10-08 17:37:36,010][process][INFO] - + Setting multiprocessing start method to spawn.
3
+ [2024-10-08 17:37:36,020][device-isolation][INFO] - + Launched device(s) isolation process 180
4
+ [2024-10-08 17:37:36,020][device-isolation][INFO] - + Isolating device(s) [0]
5
+ [2024-10-08 17:37:36,025][process][INFO] - + Launched benchmark in isolated process 181.
6
+ [PROC-0][2024-10-08 17:37:38,588][datasets][INFO] - PyTorch version 2.4.0 available.
7
+ [PROC-0][2024-10-08 17:37:39,504][backend][INFO] - َAllocating pytorch backend
8
+ [PROC-0][2024-10-08 17:37:39,504][backend][INFO] - + Setting random seed to 42
9
+ [PROC-0][2024-10-08 17:37:40,038][pytorch][INFO] - + Using AutoModel class AutoModelForSequenceClassification
10
+ [PROC-0][2024-10-08 17:37:40,039][pytorch][INFO] - + Creating backend temporary directory
11
+ [PROC-0][2024-10-08 17:37:40,039][pytorch][INFO] - + Loading model with random weights
12
+ [PROC-0][2024-10-08 17:37:40,039][pytorch][INFO] - + Creating no weights model
13
+ [PROC-0][2024-10-08 17:37:40,039][pytorch][INFO] - + Creating no weights model directory
14
+ [PROC-0][2024-10-08 17:37:40,039][pytorch][INFO] - + Creating no weights model state dict
15
+ [PROC-0][2024-10-08 17:37:40,041][pytorch][INFO] - + Saving no weights model safetensors
16
+ [PROC-0][2024-10-08 17:37:40,041][pytorch][INFO] - + Saving no weights model pretrained config
17
+ [PROC-0][2024-10-08 17:37:40,042][pytorch][INFO] - + Loading no weights AutoModel
18
+ [PROC-0][2024-10-08 17:37:40,042][pytorch][INFO] - + Loading model directly on device: cuda
19
+ [PROC-0][2024-10-08 17:37:40,194][pytorch][INFO] - + Turning on model's eval mode
20
+ [PROC-0][2024-10-08 17:37:40,200][benchmark][INFO] - Allocating energy_star benchmark
21
+ [PROC-0][2024-10-08 17:37:40,200][energy_star][INFO] - + Loading raw dataset
22
+ [PROC-0][2024-10-08 17:37:40,989][energy_star][INFO] - + Initializing Inference report
23
+ [PROC-0][2024-10-08 17:37:40,989][energy][INFO] - + Tracking GPU energy on devices [0]
24
+ [PROC-0][2024-10-08 17:37:45,184][energy_star][INFO] - + Preprocessing dataset
25
+ [PROC-0][2024-10-08 17:37:45,609][energy][INFO] - + Saving codecarbon emission data to preprocess_codecarbon.json
26
+ [PROC-0][2024-10-08 17:37:45,610][energy_star][INFO] - + Preparing backend for Inference
27
+ [PROC-0][2024-10-08 17:37:45,610][energy_star][INFO] - + Initialising dataloader
28
+ [PROC-0][2024-10-08 17:37:45,610][energy_star][INFO] - + Warming up backend for Inference
29
+ [PROC-0][2024-10-08 17:37:46,118][energy_star][INFO] - + Running Inference energy tracking for 10 iterations
30
+ [PROC-0][2024-10-08 17:37:46,118][energy_star][INFO] - + Iteration 1/10
31
+ [PROC-0][2024-10-08 17:37:50,097][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
32
+ [PROC-0][2024-10-08 17:37:50,097][energy_star][INFO] - + Iteration 2/10
33
+ [PROC-0][2024-10-08 17:37:54,065][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
34
+ [PROC-0][2024-10-08 17:37:54,066][energy_star][INFO] - + Iteration 3/10
35
+ [PROC-0][2024-10-08 17:37:58,012][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
36
+ [PROC-0][2024-10-08 17:37:58,012][energy_star][INFO] - + Iteration 4/10
37
+ [PROC-0][2024-10-08 17:38:01,935][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
38
+ [PROC-0][2024-10-08 17:38:01,935][energy_star][INFO] - + Iteration 5/10
39
+ [PROC-0][2024-10-08 17:38:05,838][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
40
+ [PROC-0][2024-10-08 17:38:05,838][energy_star][INFO] - + Iteration 6/10
41
+ [PROC-0][2024-10-08 17:38:09,741][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
42
+ [PROC-0][2024-10-08 17:38:09,741][energy_star][INFO] - + Iteration 7/10
43
+ [PROC-0][2024-10-08 17:38:13,679][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
44
+ [PROC-0][2024-10-08 17:38:13,680][energy_star][INFO] - + Iteration 8/10
45
+ [PROC-0][2024-10-08 17:38:17,624][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
46
+ [PROC-0][2024-10-08 17:38:17,624][energy_star][INFO] - + Iteration 9/10
47
+ [PROC-0][2024-10-08 17:38:21,563][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
48
+ [PROC-0][2024-10-08 17:38:21,563][energy_star][INFO] - + Iteration 10/10
49
+ [PROC-0][2024-10-08 17:38:25,541][energy][INFO] - + Saving codecarbon emission data to forward_codecarbon.json
50
+ [PROC-0][2024-10-08 17:38:25,542][energy][INFO] - + forward energy consumption:
51
+ [PROC-0][2024-10-08 17:38:25,542][energy][INFO] - + CPU: 0.000042 (kWh)
52
+ [PROC-0][2024-10-08 17:38:25,542][energy][INFO] - + GPU: 0.000166 (kWh)
53
+ [PROC-0][2024-10-08 17:38:25,542][energy][INFO] - + RAM: 0.000000 (kWh)
54
+ [PROC-0][2024-10-08 17:38:25,542][energy][INFO] - + total: 0.000208 (kWh)
55
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + forward_iteration_1 energy consumption:
56
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + CPU: 0.000047 (kWh)
57
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + GPU: 0.000178 (kWh)
58
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + RAM: 0.000000 (kWh)
59
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + total: 0.000226 (kWh)
60
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + forward_iteration_2 energy consumption:
61
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + CPU: 0.000047 (kWh)
62
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + GPU: 0.000184 (kWh)
63
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + RAM: 0.000000 (kWh)
64
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + total: 0.000231 (kWh)
65
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + forward_iteration_3 energy consumption:
66
+ [PROC-0][2024-10-08 17:38:25,543][energy][INFO] - + CPU: 0.000047 (kWh)
67
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + GPU: 0.000181 (kWh)
68
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + RAM: 0.000000 (kWh)
69
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + total: 0.000227 (kWh)
70
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + forward_iteration_4 energy consumption:
71
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + CPU: 0.000046 (kWh)
72
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + GPU: 0.000186 (kWh)
73
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + RAM: 0.000000 (kWh)
74
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + total: 0.000233 (kWh)
75
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + forward_iteration_5 energy consumption:
76
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + CPU: 0.000046 (kWh)
77
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + GPU: 0.000182 (kWh)
78
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + RAM: 0.000000 (kWh)
79
+ [PROC-0][2024-10-08 17:38:25,544][energy][INFO] - + total: 0.000229 (kWh)
80
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + forward_iteration_6 energy consumption:
81
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + CPU: 0.000046 (kWh)
82
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + GPU: 0.000185 (kWh)
83
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + RAM: 0.000000 (kWh)
84
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + total: 0.000232 (kWh)
85
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + forward_iteration_7 energy consumption:
86
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + CPU: 0.000000 (kWh)
87
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + GPU: 0.000000 (kWh)
88
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + RAM: 0.000000 (kWh)
89
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + total: 0.000000 (kWh)
90
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + forward_iteration_8 energy consumption:
91
+ [PROC-0][2024-10-08 17:38:25,545][energy][INFO] - + CPU: 0.000047 (kWh)
92
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + GPU: 0.000190 (kWh)
93
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + RAM: 0.000000 (kWh)
94
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + total: 0.000237 (kWh)
95
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + forward_iteration_9 energy consumption:
96
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + CPU: 0.000046 (kWh)
97
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + GPU: 0.000186 (kWh)
98
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + RAM: 0.000000 (kWh)
99
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + total: 0.000233 (kWh)
100
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + forward_iteration_10 energy consumption:
101
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + CPU: 0.000047 (kWh)
102
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + GPU: 0.000190 (kWh)
103
+ [PROC-0][2024-10-08 17:38:25,546][energy][INFO] - + RAM: 0.000000 (kWh)
104
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + total: 0.000237 (kWh)
105
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + preprocess energy consumption:
106
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + CPU: 0.000005 (kWh)
107
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + GPU: 0.000007 (kWh)
108
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + RAM: 0.000000 (kWh)
109
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + total: 0.000013 (kWh)
110
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + forward energy efficiency: 4797090.026904 (samples/kWh)
111
+ [PROC-0][2024-10-08 17:38:25,547][energy][INFO] - + preprocess energy efficiency: 79811202.478559 (samples/kWh)
112
+ [2024-10-08 17:38:26,141][device-isolation][INFO] - + Closing device(s) isolation process...
113
+ [2024-10-08 17:38:26,191][datasets][INFO] - PyTorch version 2.4.0 available.
runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/error.log ADDED
@@ -0,0 +1,178 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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1
+ /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
2
+ warnings.warn(
3
+
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+
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+
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+
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+
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+
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+
10
+ [codecarbon INFO @ 17:37:40] [setup] RAM Tracking...
11
+ [codecarbon INFO @ 17:37:40] [setup] GPU Tracking...
12
+ [codecarbon INFO @ 17:37:40] Tracking Nvidia GPU via pynvml
13
+ [codecarbon DEBUG @ 17:37:40] GPU available. Starting setup
14
+ [codecarbon INFO @ 17:37:40] [setup] CPU Tracking...
15
+ [codecarbon DEBUG @ 17:37:40] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
16
+ [codecarbon DEBUG @ 17:37:40] Not using the RAPL interface, an exception occurred while instantiating IntelRAPL : Intel RAPL files not found at /sys/class/powercap/intel-rapl on linux
17
+ [codecarbon DEBUG @ 17:37:40] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
18
+ [codecarbon WARNING @ 17:37:40] No CPU tracking mode found. Falling back on CPU constant mode.
19
+ [codecarbon WARNING @ 17:37:42] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
20
+ [codecarbon INFO @ 17:37:42] CPU Model on constant consumption mode: AMD EPYC 7R32
21
+ [codecarbon INFO @ 17:37:42] >>> Tracker's metadata:
22
+ [codecarbon INFO @ 17:37:42] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
23
+ [codecarbon INFO @ 17:37:42] Python version: 3.9.20
24
+ [codecarbon INFO @ 17:37:42] CodeCarbon version: 2.5.1
25
+ [codecarbon INFO @ 17:37:42] Available RAM : 186.705 GB
26
+ [codecarbon INFO @ 17:37:42] CPU count: 48
27
+ [codecarbon INFO @ 17:37:42] CPU model: AMD EPYC 7R32
28
+ [codecarbon INFO @ 17:37:42] GPU count: 1
29
+ [codecarbon INFO @ 17:37:42] GPU model: 1 x NVIDIA A10G
30
+ [codecarbon DEBUG @ 17:37:43] Not running on AWS
31
+ [codecarbon DEBUG @ 17:37:44] Not running on Azure
32
+ [codecarbon DEBUG @ 17:37:45] Not running on GCP
33
+ [codecarbon INFO @ 17:37:45] Saving emissions data to file /runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/codecarbon.csv
34
+ [codecarbon DEBUG @ 17:37:45] EmissionsData(timestamp='2024-10-08T17:37:45', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.002186324003560003, 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)
35
+
36
+
37
+ [codecarbon INFO @ 17:37:45] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.27330780029296875 W
38
+ [codecarbon DEBUG @ 17:37:45] RAM : 0.27 W during 0.42 s [measurement time: 0.0005]
39
+ [codecarbon INFO @ 17:37:45] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 64.11599605880454 W
40
+ [codecarbon DEBUG @ 17:37:45] GPU : 64.12 W during 0.42 s [measurement time: 0.0022]
41
+ [codecarbon INFO @ 17:37:45] Energy consumed for all CPUs : 0.000005 kWh. Total CPU Power : 42.5 W
42
+ [codecarbon DEBUG @ 17:37:45] CPU : 42.50 W during 0.42 s [measurement time: 0.0000]
43
+ [codecarbon INFO @ 17:37:45] 0.000013 kWh of electricity used since the beginning.
44
+ [codecarbon DEBUG @ 17:37:45] last_duration=0.4202911949978443
45
+ ------------------------
46
+ [codecarbon DEBUG @ 17:37:45] EmissionsData(timestamp='2024-10-08T17:37:45', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.4234626850011409, emissions=4.625094804077252e-06, emissions_rate=1.0922083498490052e-05, cpu_power=42.5, gpu_power=64.11599605880454, ram_power=0.27330780029296875, cpu_energy=4.9979329326207435e-06, gpu_energy=7.499728221782576e-06, ram_energy=3.1908241179319e-08, energy_consumed=1.2529569395582638e-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)
47
+ [codecarbon DEBUG @ 17:37:46] EmissionsData(timestamp='2024-10-08T17:37:46', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.0034372650043223985, emissions=4.625094804077252e-06, emissions_rate=0.0013455741114697716, cpu_power=42.5, gpu_power=64.11599605880454, ram_power=0.27330780029296875, cpu_energy=4.9979329326207435e-06, gpu_energy=7.499728221782576e-06, ram_energy=3.1908241179319e-08, energy_consumed=1.2529569395582638e-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 @ 17:37:50] Background scheduler didn't run for a long period (3s), results might be inaccurate
89
+ [codecarbon INFO @ 17:37:50] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.3439607620239258 W
90
+ [codecarbon DEBUG @ 17:37:50] RAM : 0.34 W during 3.97 s [measurement time: 0.0004]
91
+ [codecarbon INFO @ 17:37:50] Energy consumed for all GPUs : 0.000186 kWh. Total GPU Power : 161.44397794678872 W
92
+ [codecarbon DEBUG @ 17:37:50] GPU : 161.44 W during 3.98 s [measurement time: 0.0023]
93
+ [codecarbon INFO @ 17:37:50] Energy consumed for all CPUs : 0.000052 kWh. Total CPU Power : 42.5 W
94
+ [codecarbon DEBUG @ 17:37:50] CPU : 42.50 W during 3.98 s [measurement time: 0.0000]
95
+ [codecarbon INFO @ 17:37:50] 0.000238 kWh of electricity used since the beginning.
96
+ [codecarbon DEBUG @ 17:37:50] last_duration=3.9742983460018877
97
+ ------------------------
98
+ [codecarbon DEBUG @ 17:37:50] EmissionsData(timestamp='2024-10-08T17:37:50', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9775514510038192, emissions=8.790327114163085e-05, emissions_rate=2.2099845149569743e-05, cpu_power=42.5, gpu_power=161.44397794678872, ram_power=0.3439607620239258, cpu_energy=5.195395079718361e-05, gpu_energy=0.00018576792639213302, ram_energy=4.1164926226009786e-07, energy_consumed=0.00023813352645157674, 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)
99
+ [codecarbon DEBUG @ 17:37:50] EmissionsData(timestamp='2024-10-08T17:37:50', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.0020054440028616227, emissions=8.790327114163085e-05, emissions_rate=0.04383232392238291, cpu_power=42.5, gpu_power=161.44397794678872, ram_power=0.3439607620239258, cpu_energy=5.195395079718361e-05, gpu_energy=0.00018576792639213302, ram_energy=4.1164926226009786e-07, energy_consumed=0.00023813352645157674, 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 @ 17:37:54] Background scheduler didn't run for a long period (3s), results might be inaccurate
141
+ [codecarbon INFO @ 17:37:54] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.3440437316894531 W
142
+ [codecarbon DEBUG @ 17:37:54] RAM : 0.34 W during 3.96 s [measurement time: 0.0004]
143
+ [codecarbon INFO @ 17:37:54] Energy consumed for all GPUs : 0.000370 kWh. Total GPU Power : 167.21059015879567 W
144
+ [codecarbon DEBUG @ 17:37:54] GPU : 167.21 W during 3.97 s [measurement time: 0.0023]
145
+ [codecarbon INFO @ 17:37:54] Energy consumed for all CPUs : 0.000099 kWh. Total CPU Power : 42.5 W
146
+ [codecarbon DEBUG @ 17:37:54] CPU : 42.50 W during 3.97 s [measurement time: 0.0000]
147
+ [codecarbon INFO @ 17:37:54] 0.000470 kWh of electricity used since the beginning.
148
+ [codecarbon DEBUG @ 17:37:54] last_duration=3.96440924199851
149
+ ------------------------
150
+ [codecarbon DEBUG @ 17:37:54] EmissionsData(timestamp='2024-10-08T17:37:54', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9676029440015554, emissions=0.0001733175164626588, emissions_rate=4.368318072872941e-05, cpu_power=42.5, gpu_power=167.21059015879567, ram_power=0.3440437316894531, cpu_energy=9.879252491733598e-05, gpu_energy=0.0003699411292861221, ram_energy=7.905268089076112e-07, energy_consumed=0.0004695241810123657, 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)
151
+ [codecarbon DEBUG @ 17:37:54] EmissionsData(timestamp='2024-10-08T17:37:54', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.005237747995124664, emissions=0.0001733175164626588, emissions_rate=0.03309008310899724, cpu_power=42.5, gpu_power=167.21059015879567, ram_power=0.3440437316894531, cpu_energy=9.879252491733598e-05, gpu_energy=0.0003699411292861221, ram_energy=7.905268089076112e-07, energy_consumed=0.0004695241810123657, 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 @ 17:37:58] Background scheduler didn't run for a long period (3s), results might be inaccurate
192
+ [codecarbon INFO @ 17:37:58] Energy consumed for RAM : 0.000001 kWh. RAM Power : 0.34405088424682617 W
193
+ [codecarbon DEBUG @ 17:37:58] RAM : 0.34 W during 3.94 s [measurement time: 0.0004]
194
+ [codecarbon INFO @ 17:37:58] Energy consumed for all GPUs : 0.000550 kWh. Total GPU Power : 165.02422403602208 W
195
+ [codecarbon DEBUG @ 17:37:58] GPU : 165.02 W during 3.94 s [measurement time: 0.0070]
196
+ [codecarbon INFO @ 17:37:58] Energy consumed for all CPUs : 0.000145 kWh. Total CPU Power : 42.5 W
197
+ [codecarbon DEBUG @ 17:37:58] CPU : 42.50 W during 3.95 s [measurement time: 0.0000]
198
+ [codecarbon INFO @ 17:37:58] 0.000697 kWh of electricity used since the beginning.
199
+ [codecarbon DEBUG @ 17:37:58] last_duration=3.9375561119959457
200
+ ------------------------
201
+ [codecarbon DEBUG @ 17:37:58] EmissionsData(timestamp='2024-10-08T17:37:58', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9454774929981795, emissions=0.0002572908462865598, emissions_rate=6.52115863651889e-05, cpu_power=42.5, gpu_power=165.02422403602208, ram_power=0.34405088424682617, cpu_energy=0.00014536988433330104, gpu_energy=0.0005504746070459365, ram_energy=1.16684567567956e-06, energy_consumed=0.0006970113370549173, 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)
202
+ [codecarbon DEBUG @ 17:37:58] EmissionsData(timestamp='2024-10-08T17:37:58', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.0033903829971677624, emissions=0.0002572908462865598, emissions_rate=0.0758884310420073, cpu_power=42.5, gpu_power=165.02422403602208, ram_power=0.34405088424682617, cpu_energy=0.00014536988433330104, gpu_energy=0.0005504746070459365, ram_energy=1.16684567567956e-06, energy_consumed=0.0006970113370549173, 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 @ 17:38:01] Background scheduler didn't run for a long period (3s), results might be inaccurate
243
+ [codecarbon INFO @ 17:38:01] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34405088424682617 W
244
+ [codecarbon DEBUG @ 17:38:01] RAM : 0.34 W during 3.92 s [measurement time: 0.0004]
245
+ [codecarbon INFO @ 17:38:01] Energy consumed for all GPUs : 0.000737 kWh. Total GPU Power : 170.89968410172335 W
246
+ [codecarbon DEBUG @ 17:38:01] GPU : 170.90 W during 3.92 s [measurement time: 0.0023]
247
+ [codecarbon INFO @ 17:38:01] Energy consumed for all CPUs : 0.000192 kWh. Total CPU Power : 42.5 W
248
+ [codecarbon DEBUG @ 17:38:01] CPU : 42.50 W during 3.92 s [measurement time: 0.0000]
249
+ [codecarbon INFO @ 17:38:01] 0.000930 kWh of electricity used since the beginning.
250
+ [codecarbon DEBUG @ 17:38:01] last_duration=3.9191808239993406
251
+ ------------------------
252
+ [codecarbon DEBUG @ 17:38:01] EmissionsData(timestamp='2024-10-08T17:38:01', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.922366005994263, emissions=0.0003432133425656571, emissions_rate=8.750161051802648e-05, cpu_power=42.5, gpu_power=170.89968410172335, ram_power=0.34405088424682617, cpu_energy=0.00019167436568746376, gpu_energy=0.0007365630892499642, ram_energy=1.541409135873614e-06, energy_consumed=0.0009297788640733017, 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)
253
+ [codecarbon DEBUG @ 17:38:01] EmissionsData(timestamp='2024-10-08T17:38:01', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.002048575996013824, emissions=0.0003432133425656571, emissions_rate=0.1675375203231372, cpu_power=42.5, gpu_power=170.89968410172335, ram_power=0.34405088424682617, cpu_energy=0.00019167436568746376, gpu_energy=0.0007365630892499642, ram_energy=1.541409135873614e-06, energy_consumed=0.0009297788640733017, 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 @ 17:38:05] Background scheduler didn't run for a long period (3s), results might be inaccurate
294
+ [codecarbon INFO @ 17:38:05] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.34405088424682617 W
295
+ [codecarbon DEBUG @ 17:38:05] RAM : 0.34 W during 3.90 s [measurement time: 0.0004]
296
+ [codecarbon INFO @ 17:38:05] Energy consumed for all GPUs : 0.000919 kWh. Total GPU Power : 168.31849930846278 W
297
+ [codecarbon DEBUG @ 17:38:05] GPU : 168.32 W during 3.90 s [measurement time: 0.0022]
298
+ [codecarbon INFO @ 17:38:05] Energy consumed for all CPUs : 0.000238 kWh. Total CPU Power : 42.5 W
299
+ [codecarbon DEBUG @ 17:38:05] CPU : 42.50 W during 3.90 s [measurement time: 0.0000]
300
+ [codecarbon INFO @ 17:38:05] 0.001159 kWh of electricity used since the beginning.
301
+ [codecarbon DEBUG @ 17:38:05] last_duration=3.898909368996101
302
+ ------------------------
303
+ [codecarbon DEBUG @ 17:38:05] EmissionsData(timestamp='2024-10-08T17:38:05', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9020374169995193, emissions=0.00042765901837953145, emissions_rate=0.00010959890249037664, cpu_power=42.5, gpu_power=168.31849930846278, ram_power=0.34405088424682617, cpu_energy=0.00023773891036380014, gpu_energy=0.0009188926795578034, ram_energy=1.914034637142231e-06, energy_consumed=0.0011585456245587458, 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)
304
+ [codecarbon DEBUG @ 17:38:05] EmissionsData(timestamp='2024-10-08T17:38:05', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.002029044997470919, emissions=0.00042765901837953145, emissions_rate=0.21076862214124495, cpu_power=42.5, gpu_power=168.31849930846278, ram_power=0.34405088424682617, cpu_energy=0.00023773891036380014, gpu_energy=0.0009188926795578034, ram_energy=1.914034637142231e-06, energy_consumed=0.0011585456245587458, 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 @ 17:38:09] Background scheduler didn't run for a long period (3s), results might be inaccurate
345
+ [codecarbon INFO @ 17:38:09] Energy consumed for RAM : 0.000002 kWh. RAM Power : 0.3440537452697754 W
346
+ [codecarbon DEBUG @ 17:38:09] RAM : 0.34 W during 3.90 s [measurement time: 0.0004]
347
+ [codecarbon INFO @ 17:38:09] Energy consumed for all GPUs : 0.001104 kWh. Total GPU Power : 170.9065803122797 W
348
+ [codecarbon DEBUG @ 17:38:09] GPU : 170.91 W during 3.90 s [measurement time: 0.0023]
349
+ [codecarbon INFO @ 17:38:09] Energy consumed for all CPUs : 0.000284 kWh. Total CPU Power : 42.5 W
350
+ [codecarbon DEBUG @ 17:38:09] CPU : 42.50 W during 3.90 s [measurement time: 0.0000]
351
+ [codecarbon INFO @ 17:38:09] 0.001390 kWh of electricity used since the beginning.
352
+ [codecarbon DEBUG @ 17:38:09] last_duration=3.899036896000325
353
+ ------------------------
354
+ [codecarbon DEBUG @ 17:38:09] EmissionsData(timestamp='2024-10-08T17:38:09', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9021763350028777, emissions=0.0005131423612664712, emissions_rate=0.00013150158199247365, cpu_power=42.5, gpu_power=170.9065803122797, ram_power=0.3440537452697754, cpu_energy=0.0002838050751991937, gpu_energy=0.0011040317165578184, ram_energy=2.286675470838585e-06, energy_consumed=0.0013901234672278509, 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)
355
+ [codecarbon DEBUG @ 17:38:09] EmissionsData(timestamp='2024-10-08T17:38:09', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.005117132001032587, emissions=0.0005131423612664712, emissions_rate=0.10027928948538442, cpu_power=42.5, gpu_power=170.9065803122797, ram_power=0.3440537452697754, cpu_energy=0.0002838050751991937, gpu_energy=0.0011040317165578184, ram_energy=2.286675470838585e-06, energy_consumed=0.0013901234672278509, 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 @ 17:38:13] Background scheduler didn't run for a long period (3s), results might be inaccurate
396
+ [codecarbon INFO @ 17:38:13] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.3440537452697754 W
397
+ [codecarbon DEBUG @ 17:38:13] RAM : 0.34 W during 3.93 s [measurement time: 0.0004]
398
+ [codecarbon INFO @ 17:38:13] Energy consumed for all GPUs : 0.001288 kWh. Total GPU Power : 168.5056725508812 W
399
+ [codecarbon DEBUG @ 17:38:13] GPU : 168.51 W during 3.93 s [measurement time: 0.0023]
400
+ [codecarbon INFO @ 17:38:13] Energy consumed for all CPUs : 0.000330 kWh. Total CPU Power : 42.5 W
401
+ [codecarbon DEBUG @ 17:38:13] CPU : 42.50 W during 3.94 s [measurement time: 0.0000]
402
+ [codecarbon INFO @ 17:38:13] 0.001621 kWh of electricity used since the beginning.
403
+ [codecarbon DEBUG @ 17:38:13] EmissionsData(timestamp='2024-10-08T17:38:13', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.93702660100098, emissions=0.0005984210389597376, emissions_rate=0.00015199822089279012, cpu_power=42.5, gpu_power=168.5056725508812, ram_power=0.3440537452697754, cpu_energy=0.0003302829055179397, gpu_energy=0.001288201308337955, ram_energy=2.6626497311756516e-06, energy_consumed=0.0016211468635870705, 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)
404
+ [codecarbon INFO @ 17:38:13] 0.021689 g.CO2eq/s mean an estimation of 683.9802393565444 kg.CO2eq/year
405
+ [codecarbon DEBUG @ 17:38:13] last_duration=3.9339104940008838
406
+ ------------------------
407
+ [codecarbon DEBUG @ 17:38:13] EmissionsData(timestamp='2024-10-08T17:38:13', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9373618210011045, emissions=0.0005984210389597376, emissions_rate=0.00015198528003392497, cpu_power=42.5, gpu_power=168.5056725508812, ram_power=0.3440537452697754, cpu_energy=0.0003302829055179397, gpu_energy=0.001288201308337955, ram_energy=2.6626497311756516e-06, energy_consumed=0.0016211468635870705, 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)
408
+ [codecarbon DEBUG @ 17:38:13] EmissionsData(timestamp='2024-10-08T17:38:13', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.005522163999557961, emissions=0.0005984210389597376, emissions_rate=0.10836712546161978, cpu_power=42.5, gpu_power=168.5056725508812, ram_power=0.3440537452697754, cpu_energy=0.0003302829055179397, gpu_energy=0.001288201308337955, ram_energy=2.6626497311756516e-06, energy_consumed=0.0016211468635870705, 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 @ 17:38:17] Background scheduler didn't run for a long period (3s), results might be inaccurate
449
+ [codecarbon INFO @ 17:38:17] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.3440537452697754 W
450
+ [codecarbon DEBUG @ 17:38:17] RAM : 0.34 W during 3.94 s [measurement time: 0.0004]
451
+ [codecarbon INFO @ 17:38:17] Energy consumed for all GPUs : 0.001478 kWh. Total GPU Power : 173.81885248019637 W
452
+ [codecarbon DEBUG @ 17:38:17] GPU : 173.82 W during 3.94 s [measurement time: 0.0068]
453
+ [codecarbon INFO @ 17:38:17] Energy consumed for all CPUs : 0.000377 kWh. Total CPU Power : 42.5 W
454
+ [codecarbon DEBUG @ 17:38:17] CPU : 42.50 W during 3.94 s [measurement time: 0.0000]
455
+ [codecarbon INFO @ 17:38:17] 0.001858 kWh of electricity used since the beginning.
456
+ [codecarbon DEBUG @ 17:38:17] last_duration=3.9359960869987844
457
+ ------------------------
458
+ [codecarbon DEBUG @ 17:38:17] EmissionsData(timestamp='2024-10-08T17:38:17', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9437155299965525, emissions=0.0006859098031810955, emissions_rate=0.0001739247666227323, cpu_power=42.5, gpu_power=173.81885248019637, ram_power=0.3440537452697754, cpu_energy=0.0003768394129818262, gpu_energy=0.001478279238178004, ram_energy=3.0388228214137838e-06, energy_consumed=0.0018581574739812443, 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)
459
+ [codecarbon DEBUG @ 17:38:17] EmissionsData(timestamp='2024-10-08T17:38:17', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.002038452003034763, emissions=0.0006859098031810955, emissions_rate=0.336485628388572, cpu_power=42.5, gpu_power=173.81885248019637, ram_power=0.3440537452697754, cpu_energy=0.0003768394129818262, gpu_energy=0.001478279238178004, ram_energy=3.0388228214137838e-06, energy_consumed=0.0018581574739812443, 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)
460
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+ [codecarbon WARNING @ 17:38:21] Background scheduler didn't run for a long period (3s), results might be inaccurate
500
+ [codecarbon INFO @ 17:38:21] Energy consumed for RAM : 0.000003 kWh. RAM Power : 0.3440537452697754 W
501
+ [codecarbon DEBUG @ 17:38:21] RAM : 0.34 W during 3.93 s [measurement time: 0.0004]
502
+ [codecarbon INFO @ 17:38:21] Energy consumed for all GPUs : 0.001664 kWh. Total GPU Power : 170.2177825028557 W
503
+ [codecarbon DEBUG @ 17:38:21] GPU : 170.22 W during 3.93 s [measurement time: 0.0031]
504
+ [codecarbon INFO @ 17:38:21] Energy consumed for all CPUs : 0.000423 kWh. Total CPU Power : 42.5 W
505
+ [codecarbon DEBUG @ 17:38:21] CPU : 42.50 W during 3.94 s [measurement time: 0.0000]
506
+ [codecarbon INFO @ 17:38:21] 0.002091 kWh of electricity used since the beginning.
507
+ [codecarbon DEBUG @ 17:38:21] last_duration=3.933801384999242
508
+ ------------------------
509
+ [codecarbon DEBUG @ 17:38:21] EmissionsData(timestamp='2024-10-08T17:38:21', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.9378736580038094, emissions=0.0007718815633932052, emissions_rate=0.00019601481165459436, cpu_power=42.5, gpu_power=170.2177825028557, ram_power=0.3440537452697754, cpu_energy=0.0004233267838894942, gpu_energy=0.0016643168870080771, ram_energy=3.414788094493119e-06, energy_consumed=0.0020910584589920646, 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)
510
+ [codecarbon DEBUG @ 17:38:21] EmissionsData(timestamp='2024-10-08T17:38:21', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=0.002013361001445446, emissions=0.0007718815633932052, emissions_rate=0.38337961390880754, cpu_power=42.5, gpu_power=170.2177825028557, ram_power=0.3440537452697754, cpu_energy=0.0004233267838894942, gpu_energy=0.0016643168870080771, ram_energy=3.414788094493119e-06, energy_consumed=0.0020910584589920646, 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)
511
+
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  0%| | 0/1000 [00:00<?, ?it/s]
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551
+ [codecarbon WARNING @ 17:38:25] Background scheduler didn't run for a long period (3s), results might be inaccurate
552
+ [codecarbon INFO @ 17:38:25] Energy consumed for RAM : 0.000004 kWh. RAM Power : 0.34405517578125 W
553
+ [codecarbon DEBUG @ 17:38:25] RAM : 0.34 W during 3.97 s [measurement time: 0.0004]
554
+ [codecarbon INFO @ 17:38:25] Energy consumed for all GPUs : 0.001854 kWh. Total GPU Power : 171.94132407650213 W
555
+ [codecarbon DEBUG @ 17:38:25] GPU : 171.94 W during 3.97 s [measurement time: 0.0048]
556
+ [codecarbon INFO @ 17:38:25] Energy consumed for all CPUs : 0.000470 kWh. Total CPU Power : 42.5 W
557
+ [codecarbon DEBUG @ 17:38:25] CPU : 42.50 W during 3.98 s [measurement time: 0.0000]
558
+ [codecarbon INFO @ 17:38:25] 0.002328 kWh of electricity used since the beginning.
559
+ [codecarbon DEBUG @ 17:38:25] last_duration=3.9721385410011862
560
+ ------------------------
561
+ [codecarbon DEBUG @ 17:38:25] EmissionsData(timestamp='2024-10-08T17:38:25', project_name='codecarbon', run_id='53146998-521f-417d-b6f1-5de4fa49fe1c', duration=3.977883915998973, emissions=0.0008594002293502864, emissions_rate=0.00021604457231489215, cpu_power=42.5, gpu_power=171.94132407650213, ram_power=0.34405517578125, cpu_energy=0.000470286674259675, gpu_energy=0.0018540689832540203, ram_energy=3.7944168872861273e-06, energy_consumed=0.0023281500744009817, 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)
runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/experiment_config.json ADDED
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runs/text_classification/distilbert/distilbert-base-uncased-finetuned-sst-2-english/2024-10-08-17-37-33/forward_codecarbon.json ADDED
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