Add efficientnet model finetune on trash-optimizer v2 composite dataset

efficientnet_custom_v2/categories.txt

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+battery:0
+car_battery:1
+cardboard:2
+food_organics:3
+glass:4
+light_bulb:5
+metal:6
+mirror:7
+miscellaneous_trash:8
+neon:9
+paper:10
+pharmacy:11
+plastic:12
+printer_cartridge:13
+textile_trash:14
+tire:15
+vegetation:16
+wood:17

efficientnet_custom_v2/model.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:081209b721c1e4b161340bf0eaafb4cbe1004eeaaf2eee30adbffc8f3aff8555
+size 16422311

efficientnet_custom_v2/training_history.txt

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+Epoch 1: Train Loss: 1.9566204987190798, Train Accuracy: 0.48373908195502696, Val Accuracy: 0.7204460966542751
+Epoch 2: Train Loss: 0.9399006773140146, Train Accuracy: 0.7454004831815647, Val Accuracy: 0.8022304832713755
+Epoch 3: Train Loss: 0.6114745529206175, Train Accuracy: 0.8225236944805798, Val Accuracy: 0.8342007434944237
+Epoch 4: Train Loss: 0.469262702871357, Train Accuracy: 0.858390633711206, Val Accuracy: 0.8706319702602231
+Epoch 5: Train Loss: 0.379376363242521, Train Accuracy: 0.8832930682029363, Val Accuracy: 0.8802973977695168
+Epoch 6: Train Loss: 0.2938720184926804, Train Accuracy: 0.9143281917859134, Val Accuracy: 0.8810408921933085
+Epoch 7: Train Loss: 0.2506893135162783, Train Accuracy: 0.9271510871585207, Val Accuracy: 0.8921933085501859
+Epoch 8: Train Loss: 0.21149635227434121, Train Accuracy: 0.9373722356439323, Val Accuracy: 0.8862453531598513
+Epoch 9: Train Loss: 0.1771526111144821, Train Accuracy: 0.9468500278758595, Val Accuracy: 0.8869888475836432
+Epoch 10: Train Loss: 0.15994525379993685, Train Accuracy: 0.9544694294740754, Val Accuracy: 0.8892193308550186
+Epoch 11: Train Loss: 0.14939564941951144, Train Accuracy: 0.9527968779037354, Val Accuracy: 0.8921933085501859
+Epoch 12: Train Loss: 0.11702485665294057, Train Accuracy: 0.964504738896116, Val Accuracy: 0.8951672862453531
+Epoch 13: Train Loss: 0.11728716561218727, Train Accuracy: 0.9635755435792603, Val Accuracy: 0.8921933085501859
+Epoch 14: Train Loss: 0.10896556243602283, Train Accuracy: 0.967664002973425, Val Accuracy: 0.8973977695167287
+Epoch 15: Train Loss: 0.09880308192960614, Train Accuracy: 0.9700799107972495, Val Accuracy: 0.8847583643122676
+Epoch 16: Train Loss: 0.09762978056420449, Train Accuracy: 0.9726816576844453, Val Accuracy: 0.8884758364312267
+Epoch 17: Train Loss: 0.07307354702401883, Train Accuracy: 0.9791860249024344, Val Accuracy: 0.8996282527881041
+Epoch 18: Train Loss: 0.07619433692204555, Train Accuracy: 0.9765842780152388, Val Accuracy: 0.8981412639405204
+Epoch 19: Train Loss: 0.08345427751386061, Train Accuracy: 0.9747258873815275, Val Accuracy: 0.9026022304832714
+Epoch 20: Train Loss: 0.06655490370437882, Train Accuracy: 0.9808585764727745, Val Accuracy: 0.8944237918215613
+Epoch 21: Train Loss: 0.06763106351934652, Train Accuracy: 0.9797435420925479, Val Accuracy: 0.9033457249070632
+Epoch 22: Train Loss: 0.05898239614213184, Train Accuracy: 0.9823452889797435, Val Accuracy: 0.8973977695167287
+Epoch 23: Train Loss: 0.06448322343485126, Train Accuracy: 0.9829028061698569, Val Accuracy: 0.8951672862453531
+Epoch 24: Train Loss: 0.056376636708132775, Train Accuracy: 0.9834603233599702, Val Accuracy: 0.9033457249070632
+Epoch 25: Train Loss: 0.0538214755141919, Train Accuracy: 0.984575357740197, Val Accuracy: 0.8981412639405204
+Epoch 26: Train Loss: 0.05079069800219379, Train Accuracy: 0.9853187139936814, Val Accuracy: 0.8936802973977696
+Epoch 27: Train Loss: 0.048973060940814446, Train Accuracy: 0.9847611968035681, Val Accuracy: 0.8973977695167287
+Epoch 28: Train Loss: 0.039453479324468695, Train Accuracy: 0.9873629436907638, Val Accuracy: 0.9048327137546468
+Epoch 29: Train Loss: 0.048613772752991266, Train Accuracy: 0.9843895186768259, Val Accuracy: 0.891449814126394
+Epoch 30: Train Loss: 0.03574296091180423, Train Accuracy: 0.9903363687047018, Val Accuracy: 0.8973977695167287
+Epoch 31: Train Loss: 0.0329542507183328, Train Accuracy: 0.9903363687047018, Val Accuracy: 0.9018587360594795
+Epoch 32: Train Loss: 0.03682109079057345, Train Accuracy: 0.9886638171343617, Val Accuracy: 0.8966542750929368
+Epoch 33: Train Loss: 0.029441020974349055, Train Accuracy: 0.9908938858948151, Val Accuracy: 0.9055762081784386
+Epoch 34: Train Loss: 0.027282510453319708, Train Accuracy: 0.9920089202750418, Val Accuracy: 0.8981412639405204
+Epoch 35: Train Loss: 0.029237230576968032, Train Accuracy: 0.9918230812116707, Val Accuracy: 0.9026022304832714
+Epoch 36: Train Loss: 0.031097381512979395, Train Accuracy: 0.9903363687047018, Val Accuracy: 0.8944237918215613
+Epoch 37: Train Loss: 0.030549738186109888, Train Accuracy: 0.9912655640215573, Val Accuracy: 0.9033457249070632
+Epoch 38: Train Loss: 0.03437556433488813, Train Accuracy: 0.9905222077680729, Val Accuracy: 0.8951672862453531
+Epoch 39: Train Loss: 0.031857591022004694, Train Accuracy: 0.9903363687047018, Val Accuracy: 0.8929368029739777
+Epoch 40: Train Loss: 0.027313779068245718, Train Accuracy: 0.992380598401784, Val Accuracy: 0.9033457249070632
+Epoch 41: Train Loss: 0.02539280861653519, Train Accuracy: 0.9927522765285263, Val Accuracy: 0.8996282527881041
+Epoch 42: Train Loss: 0.027334057906830515, Train Accuracy: 0.992380598401784, Val Accuracy: 0.8988847583643123
+Epoch 43: Train Loss: 0.03104475953613952, Train Accuracy: 0.990708046831444, Val Accuracy: 0.9033457249070632