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Results from R50 GH action on ubuntu-latest
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‎open/MLCommons/results/gh_ubuntu-latest_x86-reference-cpu-onnxruntime_v1.26.0-default_config/README.md‎

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| Model | Scenario | Accuracy | Throughput | Latency (in ms) |
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|----------|------------|------------|--------------|-------------------|
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| resnet50 | offline | 76 | 23.013 | - |
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| resnet50 | offline | 76 | 23.003 | - |

‎open/MLCommons/results/gh_ubuntu-latest_x86-reference-cpu-onnxruntime_v1.26.0-default_config/resnet50/offline/README.md‎

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* OS version: Linux-6.17.0-1010-azure-x86_64-with-glibc2.39
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* CPU version: x86_64
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* Python version: 3.13.13 (main, Apr 8 2026, 02:25:29) [GCC 13.3.0]
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* Python version: 3.12.13 (main, Mar 4 2026, 02:26:36) [GCC 13.3.0]
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* MLC version: unknown
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## MLC Run Command
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mlc rm cache -f
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mlc pull repo GATEOverflow@mlperf-automations --checkout=ad2fb3b0fede2ffba0ed207b1d60407eae310012
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mlc pull repo GATEOverflow@mlperf-automations --checkout=4e55476fb1324b45955057790b26baefef4aa3f1
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```
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`acc`: `76.0`, Required accuracy for closed division `>= 75.6954`
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### Performance Results
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`Samples per second`: `23.0132`
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`Samples per second`: `23.0035`

‎open/MLCommons/results/gh_ubuntu-latest_x86-reference-cpu-onnxruntime_v1.26.0-default_config/resnet50/offline/accuracy/accuracy.txt‎

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accuracy=76.000%, good=380, total=500
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hash=1237252459eec590ed90c71867a6c2251c12eebca4586364056ed8df34387fd8
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hash=6349b70777311a7abae1e05322d14fc5f137b00674405219a8e82fc807773676

‎open/MLCommons/results/gh_ubuntu-latest_x86-reference-cpu-onnxruntime_v1.26.0-default_config/resnet50/offline/accuracy/mlperf_log_accuracy.json‎

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