Dataset Viewer
model
stringlengths 11
65
| status
stringclasses 3
values | submitted_time
timestamp[us]date 2024-10-04 14:58:35
2025-10-31 15:27:23
| task
stringclasses 13
values | likes
int64 0
12.5k
| params
float64 0
685
| leaderboard_version
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value | error_message
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|---|---|---|---|---|---|---|---|
meta-llama/Llama-3.2-1B
|
COMPLETED
| 2024-10-04T14:58:35
|
Text Generation
| 320
| 1.236
|
v0
| |
cardiffnlp/twitter-roberta-base-sentiment-latest
|
FAILED
| 2024-10-07T15:30:10
|
Text Classification
| 526
| 0
|
v0
|
/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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Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.83MB/s][A[A
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Generating train split: 0%| | 0/1000 [00:00<?, ? examples/s]
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[codecarbon INFO @ 23:20:33] [setup] RAM Tracking...
[codecarbon INFO @ 23:20:33] [setup] GPU Tracking...
[codecarbon INFO @ 23:20:33] Tracking Nvidia GPU via pynvml
[codecarbon DEBUG @ 23:20:33] GPU available. Starting setup
[codecarbon INFO @ 23:20:33] [setup] CPU Tracking...
[codecarbon DEBUG @ 23:20:33] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
[codecarbon DEBUG @ 23:20:33] 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 @ 23:20:33] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
[codecarbon WARNING @ 23:20:33] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 23:20:34] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
[codecarbon INFO @ 23:20:34] CPU Model on constant consumption mode: AMD EPYC 7R32
[codecarbon INFO @ 23:20:34] >>> Tracker's metadata:
[codecarbon INFO @ 23:20:34] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
[codecarbon INFO @ 23:20:34] Python version: 3.9.20
[codecarbon INFO @ 23:20:34] CodeCarbon version: 2.5.1
[codecarbon INFO @ 23:20:34] Available RAM : 186.705 GB
[codecarbon INFO @ 23:20:34] CPU count: 48
[codecarbon INFO @ 23:20:34] CPU model: AMD EPYC 7R32
[codecarbon INFO @ 23:20:34] GPU count: 1
[codecarbon INFO @ 23:20:34] GPU model: 1 x NVIDIA A10G
[codecarbon DEBUG @ 23:20:35] Not running on AWS
[codecarbon DEBUG @ 23:20:36] Not running on Azure
[codecarbon DEBUG @ 23:20:37] Not running on GCP
[codecarbon INFO @ 23:20:37] Saving emissions data to file /runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-10-07-23-20-25/codecarbon.csv
[codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.0031156789045780897, 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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Filter: 100%|██████████| 1000/1000 [00:00<00:00, 159984.13 examples/s]
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[codecarbon INFO @ 23:20:38] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.27353525161743164 W
[codecarbon DEBUG @ 23:20:38] RAM : 0.27 W during 0.41 s [measurement time: 0.0005]
[codecarbon INFO @ 23:20:38] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 65.45066620881586 W
[codecarbon DEBUG @ 23:20:38] GPU : 65.45 W during 0.41 s [measurement time: 0.0022]
[codecarbon INFO @ 23:20:38] Energy consumed for all CPUs : 0.000005 kWh. Total CPU Power : 42.5 W
[codecarbon DEBUG @ 23:20:38] CPU : 42.50 W during 0.41 s [measurement time: 0.0000]
[codecarbon INFO @ 23:20:38] 0.000012 kWh of electricity used since the beginning.
[codecarbon DEBUG @ 23:20:38] last_duration=0.40900541795417666
------------------------
[codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.4121430969098583, emissions=4.5573209828862485e-06, emissions_rate=1.1057618135681164e-05, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-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 @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.002233574981801212, emissions=4.5573209828862485e-06, emissions_rate=0.002040370715117479, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-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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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.
|
cardiffnlp/twitter-roberta-base-sentiment-latest
|
FAILED
| 2024-10-07T17:51:22
|
Text Generation
| 526
| 0
|
v0
|
/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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Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.83MB/s][A[A
Downloading data: 100%|██████████| 453k/453k [00:00<00:00, 2.83MB/s]
Generating train split: 0%| | 0/1000 [00:00<?, ? examples/s]
Generating train split: 100%|██████████| 1000/1000 [00:00<00:00, 201368.48 examples/s]
[codecarbon INFO @ 23:20:33] [setup] RAM Tracking...
[codecarbon INFO @ 23:20:33] [setup] GPU Tracking...
[codecarbon INFO @ 23:20:33] Tracking Nvidia GPU via pynvml
[codecarbon DEBUG @ 23:20:33] GPU available. Starting setup
[codecarbon INFO @ 23:20:33] [setup] CPU Tracking...
[codecarbon DEBUG @ 23:20:33] Not using PowerGadget, an exception occurred while instantiating IntelPowerGadget : Platform not supported by Intel Power Gadget
[codecarbon DEBUG @ 23:20:33] 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 @ 23:20:33] Not using PowerMetrics, an exception occurred while instantiating Powermetrics : Platform not supported by Powermetrics
[codecarbon WARNING @ 23:20:33] No CPU tracking mode found. Falling back on CPU constant mode.
[codecarbon WARNING @ 23:20:34] We saw that you have a AMD EPYC 7R32 but we don't know it. Please contact us.
[codecarbon INFO @ 23:20:34] CPU Model on constant consumption mode: AMD EPYC 7R32
[codecarbon INFO @ 23:20:34] >>> Tracker's metadata:
[codecarbon INFO @ 23:20:34] Platform system: Linux-5.10.192-183.736.amzn2.x86_64-x86_64-with-glibc2.35
[codecarbon INFO @ 23:20:34] Python version: 3.9.20
[codecarbon INFO @ 23:20:34] CodeCarbon version: 2.5.1
[codecarbon INFO @ 23:20:34] Available RAM : 186.705 GB
[codecarbon INFO @ 23:20:34] CPU count: 48
[codecarbon INFO @ 23:20:34] CPU model: AMD EPYC 7R32
[codecarbon INFO @ 23:20:34] GPU count: 1
[codecarbon INFO @ 23:20:34] GPU model: 1 x NVIDIA A10G
[codecarbon DEBUG @ 23:20:35] Not running on AWS
[codecarbon DEBUG @ 23:20:36] Not running on Azure
[codecarbon DEBUG @ 23:20:37] Not running on GCP
[codecarbon INFO @ 23:20:37] Saving emissions data to file /runs/text_classification/cardiffnlp/twitter-roberta-base-sentiment-latest/2024-10-07-23-20-25/codecarbon.csv
[codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.0031156789045780897, 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, 159984.13 examples/s]
Running tokenizer on dataset: 0%| | 0/1000 [00:00<?, ? examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2691.27 examples/s]
Running tokenizer on dataset: 100%|██████████| 1000/1000 [00:00<00:00, 2667.25 examples/s]
[codecarbon INFO @ 23:20:38] Energy consumed for RAM : 0.000000 kWh. RAM Power : 0.27353525161743164 W
[codecarbon DEBUG @ 23:20:38] RAM : 0.27 W during 0.41 s [measurement time: 0.0005]
[codecarbon INFO @ 23:20:38] Energy consumed for all GPUs : 0.000007 kWh. Total GPU Power : 65.45066620881586 W
[codecarbon DEBUG @ 23:20:38] GPU : 65.45 W during 0.41 s [measurement time: 0.0022]
[codecarbon INFO @ 23:20:38] Energy consumed for all CPUs : 0.000005 kWh. Total CPU Power : 42.5 W
[codecarbon DEBUG @ 23:20:38] CPU : 42.50 W during 0.41 s [measurement time: 0.0000]
[codecarbon INFO @ 23:20:38] 0.000012 kWh of electricity used since the beginning.
[codecarbon DEBUG @ 23:20:38] last_duration=0.40900541795417666
------------------------
[codecarbon DEBUG @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.4121430969098583, emissions=4.5573209828862485e-06, emissions_rate=1.1057618135681164e-05, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-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 @ 23:20:38] EmissionsData(timestamp='2024-10-07T23:20:38', project_name='codecarbon', run_id='0e4bc046-c4df-4e48-866a-9a8d99e426db', duration=0.002233574981801212, emissions=4.5573209828862485e-06, emissions_rate=0.002040370715117479, cpu_power=42.5, gpu_power=65.45066620881586, ram_power=0.27353525161743164, cpu_energy=4.864328597775764e-06, gpu_energy=7.450561515298659e-06, ram_energy=3.1077252325416766e-08, energy_consumed=1.234596736539984e-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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2%|▏ | 22/1000 [00:00<00:07, 124.18it/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.
|
cardiffnlp/twitter-roberta-base-sentiment-latest
|
FAILED
| 2024-10-07T18:03:55
|
Text Generation
| 526
| 0
|
v0
| "/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)
|
cardiffnlp/twitter-roberta-base-sentiment-latest
|
FAILED
| 2024-10-07T18:29:56
|
Text Classification
| 526
| 0
|
v0
| "/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)
|
cardiffnlp/twitter-roberta-base-sentiment-latest
|
FAILED
| 2024-10-07T19:00:22
|
Text Classification
| 526
| 0
|
v0
| "/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)
|
cardiffnlp/twitter-roberta-base-sentiment-latest
|
FAILED
| 2024-10-07T19:36:45
|
Text Classification
| 526
| 0
|
v0
| "/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)
|
Emanuel/twitter-emotion-deberta-v3-base
|
FAILED
| 2024-10-08T12:56:06
|
Text Classification
| 7
| 0
|
v0
| "\nDownloading readme: 0%| | 0.00/271 [00:00<?, ?B/s]\nDownloading readme: 100%|███(...TRUNCATED)
|
distilbert/distilbert-base-uncased-finetuned-sst-2-english
|
COMPLETED
| 2024-10-08T13:01:26
|
Text Classification
| 586
| 0.067
|
v0
| "/opt/conda/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:1601: FutureWarning:(...TRUNCATED)
|
distilbert/distilbert-base-uncased-finetuned-sst-2-english
|
COMPLETED
| 2024-10-08T17:10:36
|
Text Classification
| 586
| 0.067
|
v0
| null |
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