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cpu_inference_transformers_image-classification_google/vit-base-patch16-224/benchmark.json

@@ -3,7 +3,7 @@
         "name": "cpu_inference_transformers_image-classification_google/vit-base-patch16-224",
         "backend": {
             "name": "pytorch",
-            "version": "2.3.0+cpu",
+            "version": "2.3.1+cpu",
             "_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
             "task": "image-classification",
             "library": "transformers",
@@ -73,23 +73,23 @@
         "environment": {
             "cpu": " AMD EPYC 7763 64-Core Processor",
             "cpu_count": 4,
-            "cpu_ram_mb": 16757.354496,
+            "cpu_ram_mb": 16757.338112,
             "system": "Linux",
             "machine": "x86_64",
-            "platform": "Linux-6.5.0-1021-azure-x86_64-with-glibc2.35",
+            "platform": "Linux-6.5.0-1022-azure-x86_64-with-glibc2.35",
             "processor": "x86_64",
             "python_version": "3.10.14",
             "optimum_benchmark_version": "0.2.1",
-            "optimum_benchmark_commit": "347e13ca9f7f904f55669603cfb9f0b6c7e8672c",
-            "transformers_version": "4.41.1",
+            "optimum_benchmark_commit": "d920fe9626db1e7915f6d3574b5b54b0159cd100",
+            "transformers_version": "4.42.3",
             "transformers_commit": null,
-            "accelerate_version": "0.30.1",
+            "accelerate_version": "0.31.0",
             "accelerate_commit": null,
-            "diffusers_version": "0.27.2",
+            "diffusers_version": "0.29.2",
             "diffusers_commit": null,
             "optimum_version": null,
             "optimum_commit": null,
-            "timm_version": "1.0.3",
+            "timm_version": "1.0.7",
             "timm_commit": null,
             "peft_version": null,
             "peft_commit": null
@@ -99,7 +99,7 @@
         "forward": {
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                 "unit": "MB",
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                 "max_process_vram": null,
                 "max_reserved": null,
@@ -108,34 +108,34 @@
             "latency": {
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             "throughput": {
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+                "total": 9.53745524697233e-06
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             "efficiency": {
                 "unit": "samples/kWh",
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+                "value": 104849.77115016613
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