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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-tf_v2.21.0-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 | 19.77 | - |
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| resnet50 | offline | 76 | 21.159 | - |

‎open/MLCommons/results/gh_ubuntu-latest_x86-reference-cpu-tf_v2.21.0-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: 3.12.13 (main, Mar 4 2026, 02:26:36) [GCC 13.3.0]
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* Python version: 3.13.13 (main, Apr 8 2026, 02:25:29) [GCC 13.3.0]
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* MLC version: unknown
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## MLC Run Command
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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`: `19.7698`
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`Samples per second`: `21.1591`

‎open/MLCommons/results/gh_ubuntu-latest_x86-reference-cpu-tf_v2.21.0-default_config/resnet50/offline/accuracy/accuracy.txt‎

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accuracy=76.000%, good=380, total=500
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hash=bc80d1de10659d53b92111b00249d5d865a7c92f28eb041dfe95f6da7bc618c8
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hash=2da6917d0f8bb1f504a3471a619efe59578cd36a0486b31b31c594e2ee0b1742

‎open/MLCommons/results/gh_ubuntu-latest_x86-reference-cpu-tf_v2.21.0-default_config/resnet50/offline/accuracy/mlperf_log_accuracy.json‎

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