The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowNotImplementedError
Message:      Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 620, in write_table
                  self._build_writer(inferred_schema=pa_table.schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
                  self.pa_writer = self._WRITER_CLASS(self.stream, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1886, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 639, in finalize
                  self._build_writer(self.schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 441, in _build_writer
                  self.pa_writer = self._WRITER_CLASS(self.stream, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1417, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1741, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1897, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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config
dict
report
dict
name
string
backend
dict
scenario
dict
launcher
dict
environment
dict
print_report
bool
log_report
bool
overall
dict
warmup
dict
train
dict
{ "name": "cuda_training_transformers_fill-mask_google-bert/bert-base-uncased", "backend": { "name": "pytorch", "version": "2.3.1+rocm5.7", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "library": "transformers", "model_type": "bert", "model": "google-bert/bert-base-uncased", "processor": "google-bert/bert-base-uncased", "device": "cuda", "device_ids": "5", "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }, "scenario": { "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "evaluation_strategy": "no", "eval_strategy": "no", "save_strategy": "no", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": false }, "launcher": { "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": true, "device_isolation_action": "warn", "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }, "environment": { "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 128, "cpu_ram_mb": 1082014.490624, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.15.0-122-generic-x86_64-with-glibc2.35", "processor": "x86_64", "python_version": "3.10.12", "gpu": [ "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]" ], "gpu_count": 8, "gpu_vram_mb": 549621596160, "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": null, "transformers_version": "4.47.0", "transformers_commit": null, "accelerate_version": "1.2.0", "accelerate_commit": null, "diffusers_version": "0.31.0", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "1.0.12", "timm_commit": null, "peft_version": "0.14.0", "peft_commit": null }, "print_report": true, "log_report": true }
{ "overall": { "memory": { "unit": "MB", "max_ram": 1289.580544, "max_global_vram": 68702.69952, "max_process_vram": 290024.251392, "max_reserved": 2497.708032, "max_allocated": 2195.345408 }, "latency": { "unit": "s", "values": [ 0.594968017578125, 0.041894744873046875, 0.04119970321655273, 0.04116450500488281, 0.041515865325927735 ], "count": 5, "total": 0.7607428359985352, "mean": 0.15214856719970704, "p50": 0.041515865325927735, "p90": 0.3737387084960938, "p95": 0.4843533630371093, "p99": 0.5728450866699218, "stdev": 0.22140988152085378, "stdev_": 145.5221600807031 }, "throughput": { "unit": "samples/s", "value": 65.72523280402771 }, "energy": null, "efficiency": null }, "warmup": { "memory": { "unit": "MB", "max_ram": 1289.580544, "max_global_vram": 68702.69952, "max_process_vram": 290024.251392, "max_reserved": 2497.708032, "max_allocated": 2195.345408 }, "latency": { "unit": "s", "values": [ 0.594968017578125, 0.041894744873046875 ], "count": 2, "total": 0.6368627624511719, "mean": 0.31843138122558595, "p50": 0.31843138122558595, "p90": 0.5396606903076172, "p95": 0.5673143539428711, "p99": 0.5894372848510743, "stdev": 0.27653663635253906, "stdev_": 86.8433994439237 }, "throughput": { "unit": "samples/s", "value": 12.56157601240402 }, "energy": null, "efficiency": null }, "train": { "memory": { "unit": "MB", "max_ram": 1289.580544, "max_global_vram": 68702.69952, "max_process_vram": 290024.251392, "max_reserved": 2497.708032, "max_allocated": 2195.345408 }, "latency": { "unit": "s", "values": [ 0.04119970321655273, 0.04116450500488281, 0.041515865325927735 ], "count": 3, "total": 0.12388007354736327, "mean": 0.04129335784912109, "p50": 0.04119970321655273, "p90": 0.04145263290405273, "p95": 0.04148424911499023, "p99": 0.04150954208374023, "stdev": 0.00015799137413655172, "stdev_": 0.38260723362296023 }, "throughput": { "unit": "samples/s", "value": 145.30181880395827 }, "energy": null, "efficiency": null } }
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cuda_training_transformers_fill-mask_google-bert/bert-base-uncased
{ "name": "pytorch", "version": "2.3.1+rocm5.7", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "library": "transformers", "model_type": "bert", "model": "google-bert/bert-base-uncased", "processor": "google-bert/bert-base-uncased", "device": "cuda", "device_ids": "5", "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }
{ "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "evaluation_strategy": "no", "eval_strategy": "no", "save_strategy": "no", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": false }
{ "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": true, "device_isolation_action": "warn", "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }
{ "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 128, "cpu_ram_mb": 1082014.490624, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.15.0-122-generic-x86_64-with-glibc2.35", "processor": "x86_64", "python_version": "3.10.12", "gpu": [ "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]" ], "gpu_count": 8, "gpu_vram_mb": 549621596160, "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": null, "transformers_version": "4.47.0", "transformers_commit": null, "accelerate_version": "1.2.0", "accelerate_commit": null, "diffusers_version": "0.31.0", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "1.0.12", "timm_commit": null, "peft_version": "0.14.0", "peft_commit": null }
true
true
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{ "memory": { "unit": "MB", "max_ram": 1289.580544, "max_global_vram": 68702.69952, "max_process_vram": 290024.251392, "max_reserved": 2497.708032, "max_allocated": 2195.345408 }, "latency": { "unit": "s", "values": [ 0.594968017578125, 0.041894744873046875, 0.04119970321655273, 0.04116450500488281, 0.041515865325927735 ], "count": 5, "total": 0.7607428359985352, "mean": 0.15214856719970704, "p50": 0.041515865325927735, "p90": 0.3737387084960938, "p95": 0.4843533630371093, "p99": 0.5728450866699218, "stdev": 0.22140988152085378, "stdev_": 145.5221600807031 }, "throughput": { "unit": "samples/s", "value": 65.72523280402771 }, "energy": null, "efficiency": null }
{ "memory": { "unit": "MB", "max_ram": 1289.580544, "max_global_vram": 68702.69952, "max_process_vram": 290024.251392, "max_reserved": 2497.708032, "max_allocated": 2195.345408 }, "latency": { "unit": "s", "values": [ 0.594968017578125, 0.041894744873046875 ], "count": 2, "total": 0.6368627624511719, "mean": 0.31843138122558595, "p50": 0.31843138122558595, "p90": 0.5396606903076172, "p95": 0.5673143539428711, "p99": 0.5894372848510743, "stdev": 0.27653663635253906, "stdev_": 86.8433994439237 }, "throughput": { "unit": "samples/s", "value": 12.56157601240402 }, "energy": null, "efficiency": null }
{ "memory": { "unit": "MB", "max_ram": 1289.580544, "max_global_vram": 68702.69952, "max_process_vram": 290024.251392, "max_reserved": 2497.708032, "max_allocated": 2195.345408 }, "latency": { "unit": "s", "values": [ 0.04119970321655273, 0.04116450500488281, 0.041515865325927735 ], "count": 3, "total": 0.12388007354736327, "mean": 0.04129335784912109, "p50": 0.04119970321655273, "p90": 0.04145263290405273, "p95": 0.04148424911499023, "p99": 0.04150954208374023, "stdev": 0.00015799137413655172, "stdev_": 0.38260723362296023 }, "throughput": { "unit": "samples/s", "value": 145.30181880395827 }, "energy": null, "efficiency": null }
{ "name": "cuda_training_transformers_fill-mask_hf-internal-testing/tiny-random-BertModel", "backend": { "name": "pytorch", "version": "2.3.1+rocm5.7", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "library": "transformers", "model_type": "bert", "model": "hf-internal-testing/tiny-random-BertModel", "processor": "hf-internal-testing/tiny-random-BertModel", "device": "cuda", "device_ids": "6", "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }, "scenario": { "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "evaluation_strategy": "no", "eval_strategy": "no", "save_strategy": "no", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": false }, "launcher": { "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": true, "device_isolation_action": "warn", "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }, "environment": { "cpu": " AMD EPYC 7763 64-Core Processor", "cpu_count": 128, "cpu_ram_mb": 1082014.490624, "system": "Linux", "machine": "x86_64", "platform": "Linux-5.15.0-122-generic-x86_64-with-glibc2.35", "processor": "x86_64", "python_version": "3.10.12", "gpu": [ "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]", "Advanced Micro Devices, Inc. [AMD/ATI]" ], "gpu_count": 8, "gpu_vram_mb": 549621596160, "optimum_benchmark_version": "0.5.0.dev0", "optimum_benchmark_commit": null, "transformers_version": "4.47.0", "transformers_commit": null, "accelerate_version": "1.2.0", "accelerate_commit": null, "diffusers_version": "0.31.0", "diffusers_commit": null, "optimum_version": null, "optimum_commit": null, "timm_version": "1.0.12", "timm_commit": null, "peft_version": "0.14.0", "peft_commit": null }, "print_report": true, "log_report": true }
{ "overall": { "memory": { "unit": "MB", "max_ram": 1274.167296, "max_global_vram": 68702.69952, "max_process_vram": 54144.069632, "max_reserved": 2.097152, "max_allocated": 1.940992 }, "latency": { "unit": "s", "values": [ 0.6560673828125, 0.01654225730895996, 0.015230574607849122, 0.015319055557250976, 0.015638574600219727 ], "count": 5, "total": 0.7187978448867799, "mean": 0.14375956897735598, "p50": 0.015638574600219727, "p90": 0.40025733261108404, "p95": 0.5281623577117919, "p99": 0.6304863777923584, "stdev": 0.25615432753952116, "stdev_": 178.1824537745163 }, "throughput": { "unit": "samples/s", "value": 69.56058696569362 }, "energy": null, "efficiency": null }, "warmup": { "memory": { "unit": "MB", "max_ram": 1274.167296, "max_global_vram": 68702.69952, "max_process_vram": 54144.069632, "max_reserved": 2.097152, "max_allocated": 1.940992 }, "latency": { "unit": "s", "values": [ 0.6560673828125, 0.01654225730895996 ], "count": 2, "total": 0.67260964012146, "mean": 0.33630482006073, "p50": 0.33630482006073, "p90": 0.592114870262146, "p95": 0.624091126537323, "p99": 0.6496721315574646, "stdev": 0.31976256275177, "stdev_": 95.08117150804655 }, "throughput": { "unit": "samples/s", "value": 11.893971663200306 }, "energy": null, "efficiency": null }, "train": { "memory": { "unit": "MB", "max_ram": 1274.167296, "max_global_vram": 68702.69952, "max_process_vram": 54144.069632, "max_reserved": 2.097152, "max_allocated": 1.940992 }, "latency": { "unit": "s", "values": [ 0.015230574607849122, 0.015319055557250976, 0.015638574600219727 ], "count": 3, "total": 0.046188204765319825, "mean": 0.015396068255106608, "p50": 0.015319055557250976, "p90": 0.015574670791625977, "p95": 0.015606622695922851, "p99": 0.015632184219360353, "stdev": 0.00017524119600682866, "stdev_": 1.1382204411097243 }, "throughput": { "unit": "samples/s", "value": 389.7098857047418 }, "energy": null, "efficiency": null } }
null
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cuda_training_transformers_fill-mask_hf-internal-testing/tiny-random-BertModel
{ "name": "pytorch", "version": "2.3.1+rocm5.7", "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend", "task": "fill-mask", "library": "transformers", "model_type": "bert", "model": "hf-internal-testing/tiny-random-BertModel", "processor": "hf-internal-testing/tiny-random-BertModel", "device": "cuda", "device_ids": "6", "seed": 42, "inter_op_num_threads": null, "intra_op_num_threads": null, "model_kwargs": {}, "processor_kwargs": {}, "no_weights": true, "device_map": null, "torch_dtype": null, "eval_mode": true, "to_bettertransformer": false, "low_cpu_mem_usage": null, "attn_implementation": null, "cache_implementation": null, "autocast_enabled": false, "autocast_dtype": null, "torch_compile": false, "torch_compile_target": "forward", "torch_compile_config": {}, "quantization_scheme": null, "quantization_config": {}, "deepspeed_inference": false, "deepspeed_inference_config": {}, "peft_type": null, "peft_config": {} }
{ "name": "training", "_target_": "optimum_benchmark.scenarios.training.scenario.TrainingScenario", "max_steps": 5, "warmup_steps": 2, "dataset_shapes": { "dataset_size": 500, "sequence_length": 16, "num_choices": 1 }, "training_arguments": { "per_device_train_batch_size": 2, "gradient_accumulation_steps": 1, "output_dir": "./trainer_output", "evaluation_strategy": "no", "eval_strategy": "no", "save_strategy": "no", "do_train": true, "use_cpu": false, "max_steps": 5, "do_eval": false, "do_predict": false, "report_to": "none", "skip_memory_metrics": true, "ddp_find_unused_parameters": false }, "latency": true, "memory": true, "energy": false }
{ "name": "process", "_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher", "device_isolation": true, "device_isolation_action": "warn", "numactl": false, "numactl_kwargs": {}, "start_method": "spawn" }
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cuda_training_transformers_image-classification_google/vit-base-patch16-224
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cuda_training_transformers_multiple-choice_FacebookAI/roberta-base
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cuda_training_transformers_text-classification_FacebookAI/roberta-base
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cuda_training_transformers_text-generation_hf-internal-testing/tiny-random-LlamaForCausalLM
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cuda_training_transformers_text-generation_openai-community/gpt2
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cuda_training_transformers_token-classification_microsoft/deberta-v3-base
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