AbdullahImran/DeepLearningProject
Deep Learning Project Dataset Summary This repository contains the datasets, trained models, notebooks, experiments, feature-extraction outputs, and supporting resources developed for a deep learning project focused on fire detection, fire severity classification, and related computer vision tasks. The project covers multiple stages of a deep learning workflow, including binary fire classification, three-class fire severity classification, feature extraction… See the full description on the dataset page: https://huggingface.co/datasets/AbdullahImran/DeepLearningProject.
0583
1epoch,accuracy,learning_rate,loss,val_accuracy,val_loss
20,0.5972443222999573,9.999999747378752e-05,0.6746674180030823,0.611940324306488,0.6676298975944519
31,0.6126126050949097,9.999999747378752e-05,0.673737645149231,0.611940324306488,0.6680760383605957
42,0.6120826601982117,9.999999747378752e-05,0.6707905530929565,0.611940324306488,0.6684873700141907
53,0.6115527153015137,9.999999747378752e-05,0.6697947382926941,0.611940324306488,0.6680285930633545
64,0.6131425499916077,1.9999999494757503e-05,0.6710286736488342,0.611940324306488,0.667712926864624
75,0.6136724948883057,1.9999999494757503e-05,0.6718284487724304,0.611940324306488,0.6677477359771729
86,0.6131425499916077,1.9999999494757503e-05,0.6724565625190735,0.611940324306488,0.6677679419517517
97,0.6131425499916077,3.999999989900971e-06,0.6694717407226562,0.611940324306488,0.6677601933479309
108,0.6131425499916077,3.999999989900971e-06,0.6681018471717834,0.611940324306488,0.6677380204200745
119,0.6131425499916077,3.999999989900971e-06,0.6697616577148438,0.611940324306488,0.6677106618881226
1210,0.6126126050949097,9.999999974752427e-07,0.6711200475692749,0.611940324306488,0.6677142977714539
1311,0.6120826601982117,9.999999974752427e-07,0.6693242192268372,0.611940324306488,0.6677123308181763
1412,0.6131425499916077,9.999999974752427e-07,0.6679030060768127,0.611940324306488,0.6677241325378418
1513,0.6131425499916077,9.999999974752427e-07,0.6673402190208435,0.611940324306488,0.6677058339118958
1614,0.6131425499916077,9.999999974752427e-07,0.6695672869682312,0.611940324306488,0.6677066087722778
1715,0.6136724948883057,9.999999974752427e-07,0.6721477508544922,0.611940324306488,0.6677122116088867
1816,0.6147323846817017,9.999999974752427e-07,0.668448805809021,0.611940324306488,0.6677098274230957
1917,0.6131425499916077,9.999999974752427e-07,0.6685675978660583,0.611940324306488,0.6677029132843018
2018,0.6131425499916077,9.999999974752427e-07,0.671786904335022,0.611940324306488,0.6677051186561584
2119,0.6120826601982117,9.999999974752427e-07,0.6727443337440491,0.611940324306488,0.6677204370498657
22 