deep-learning-flower-classification/EfficientNet/evaluation_results/evaluation_results.csv

1	accuracy	precision_macro	recall_macro	f1_macro	precision_weighted	recall_weighted	f1_weighted	avg_inference_time	total_inference_time	images_per_second	precision_daisy	recall_daisy	f1_daisy	precision_dandelion	recall_dandelion	f1_dandelion	precision_roses	recall_roses	f1_roses	precision_sunflowers	recall_sunflowers	f1_sunflowers	precision_tulips	recall_tulips	f1_tulips	model
2	0.957592339261286	0.9577966282225473	0.9562733310129442	0.9567672214182226	0.9583364479556171	0.957592339261286	0.9576985362250258	0.016896361890046493	0.7772326469421387	940.5163342996058	0.975609756097561	0.9523809523809523	0.963855421686747	0.9567567567567568	0.9888268156424581	0.9725274725274725	0.9029850746268657	0.9453125	0.9236641221374046	0.9925925925925926	0.9640287769784173	0.9781021897810219	0.961038961038961	0.9308176100628931	0.9456869009584664	EfficientNet-B0
3	0.9712722298221614	0.9696336624400939	0.9710926049211679	0.9702721673943255	0.9715562886900023	0.9712722298221614	0.9713231175356396	0.014946569567141325	0.687542200088501	1063.2074655285232	0.9534883720930233	0.9761904761904762	0.9647058823529412	0.9831460674157303	0.9776536312849162	0.9803921568627451	0.9534883720930233	0.9609375	0.9571984435797666	0.9645390070921985	0.9784172661870504	0.9714285714285714	0.9935064935064936	0.9622641509433962	0.9776357827476039	EfficientNet-B1
4	0.9767441860465116	0.9758506980950198	0.9759251028569246	0.975863977685071	0.9767211148025102	0.9767441860465116	0.9767118713443993	0.014863568803538446	0.6837241649627686	1069.1446016681389	0.96875	0.9841269841269841	0.9763779527559056	0.9888268156424581	0.9888268156424581	0.9888268156424581	0.9603174603174603	0.9453125	0.952755905511811	0.9928057553956835	0.9928057553956835	0.9928057553956835	0.9685534591194969	0.9685534591194969	0.9685534591194969	EfficientNet-B2
5	0.9740082079343365	0.9741130496386882	0.9735993455382512	0.9737579622397536	0.9742066830281588	0.9740082079343365	0.9740063993250383	0.019874458727629288	0.9142251014709473	799.5842586512377	0.96875	0.9841269841269841	0.9763779527559056	0.9672131147540983	0.9888268156424581	0.9779005524861878	0.9612403100775194	0.96875	0.9649805447470817	0.9925925925925926	0.9640287769784173	0.9781021897810219	0.9807692307692307	0.9622641509433962	0.9714285714285714	EfficientNet-B3
6	0.9767441860465116	0.9752607491378678	0.9772841995155099	0.9761568002196187	0.9769907043693243	0.9767441860465116	0.9767535240605703	0.01837624674258025	0.8453073501586914	864.7742148021873	0.96875	0.9841269841269841	0.9763779527559056	0.9943502824858758	0.9832402234636871	0.9887640449438202	0.946969696969697	0.9765625	0.9615384615384616	0.9857142857142858	0.9928057553956835	0.989247311827957	0.9805194805194806	0.949685534591195	0.9648562300319489	EfficientNet-B4
7	0.9753761969904241	0.9741550080328338	0.9756800058078792	0.9747398058300302	0.9757384563373198	0.9753761969904241	0.9753865089344038	0.022696059683094853	1.0440187454223633	700.1789988974481	0.968503937007874	0.9761904761904762	0.9723320158102767	0.9888268156424581	0.9888268156424581	0.9888268156424581	0.9402985074626866	0.984375	0.9618320610687023	0.9927536231884058	0.9856115107913669	0.9891696750902527	0.9803921568627451	0.9433962264150944	0.9615384615384616	EfficientNet-B5