v1-v4 done, starting v4-v8

deepskies · Aug 24, 2024 · fa7696d · fa7696d
1 parent 5157a1b
commit fa7696d
Show file tree

Hide file tree

Showing 60 changed files with 23,013 additions and 801 deletions.
diff --git a/src/training/PaperMVE/PaperMVE_v1.ipynb b/src/training/PaperMVE/PaperMVE_v1.ipynb
diff --git a/src/training/PaperMVE/PaperMVE_v2.ipynb b/src/training/PaperMVE/PaperMVE_v2.ipynb
diff --git a/src/training/PaperMVE/PaperMVE_v3.ipynb b/src/training/PaperMVE/PaperMVE_v3.ipynb
diff --git a/src/training/PaperMVE/PaperMVE_v4.ipynb b/src/training/PaperMVE/PaperMVE_v4.ipynb
diff --git a/src/training/PaperMVE/PaperMVE_v5.ipynb b/src/training/PaperMVE/PaperMVE_v5.ipynb
diff --git a/src/training/PaperMVE/PaperMVE_v6.ipynb b/src/training/PaperMVE/PaperMVE_v6.ipynb
diff --git a/src/training/PaperMVE/PaperMVE_v7.ipynb b/src/training/PaperMVE/PaperMVE_v7.ipynb
diff --git a/src/training/PaperMVE/PaperMVE_v8.ipynb b/src/training/PaperMVE/PaperMVE_v8.ipynb
diff --git a/src/training/PaperMVE/README.md b/src/training/PaperMVE/README.md
@@ -23,5 +23,33 @@ v4:
     DA Weight = 1.4 
     beta = 1 -> 0.5 (150 ep), 0.5 (50 ep), 0.0 (50 ep)
     batch size = 128
-    lr = 3e-5 (200 ep), step 3e-5 / 25 (100 ep)
+    lr = 3e-5 (200 ep), step 3e-6 (50 ep)
+    seed = 13
+
+v5:
+    DA Weight = 1.4 -> 1.8 (250 ep)
+    beta = 1 -> 0.5 (150 ep), 0.5 (100 ep)
+    batch size = 128
+    lr = 3e-5
+    seed = 13
+
+v6:
+    DA Weight = 1.4
+    beta = 1 -> 0.7 (150 ep), 0.7 (100 ep)
+    batch size = 128
+    lr = 3e-5
+    seed = 13
+
+v7:
+    DA Weight = 1.4 -> 1.8 (250 ep)
+    beta = 1 -> 0.5 (150 ep), 0.5 (50 ep), 0.0 (50 ep)
+    batch size = 128
+    lr = 3e-5 (200 ep), step 3e-6 (50 ep)
+    seed = 13
+
+v8:
+    DA Weight = 1.4
+    beta = 1 -> 0.7 (150 ep), 0.7 (50 ep) 0.0 (50 ep)
+    batch size = 128
+    lr = 3e-5 (200 ep), step 3e-6 (50 ep)
     seed = 13
diff --git a/src/training/PaperMVE/VisualizeModel.ipynb b/src/training/PaperMVE/VisualizeModel.ipynb
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135 b/src/training/PaperMVE/models/papermve_v1_aug24_1135
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135.json b/src/training/PaperMVE/models/papermve_v1_aug24_1135.json
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135_final b/src/training/PaperMVE/models/papermve_v1_aug24_1135_final
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135_final.json b/src/training/PaperMVE/models/papermve_v1_aug24_1135_final.json
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135_mve b/src/training/PaperMVE/models/papermve_v1_aug24_1135_mve
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135_mve.json b/src/training/PaperMVE/models/papermve_v1_aug24_1135_mve.json
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135_nll b/src/training/PaperMVE/models/papermve_v1_aug24_1135_nll
diff --git a/src/training/PaperMVE/models/papermve_v1_aug24_1135_nll.json b/src/training/PaperMVE/models/papermve_v1_aug24_1135_nll.json
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205 b/src/training/PaperMVE/models/papermve_v2_aug24_1205
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205.json b/src/training/PaperMVE/models/papermve_v2_aug24_1205.json
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205_final b/src/training/PaperMVE/models/papermve_v2_aug24_1205_final
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205_final.json b/src/training/PaperMVE/models/papermve_v2_aug24_1205_final.json
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205_mve b/src/training/PaperMVE/models/papermve_v2_aug24_1205_mve
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205_mve.json b/src/training/PaperMVE/models/papermve_v2_aug24_1205_mve.json
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205_nll b/src/training/PaperMVE/models/papermve_v2_aug24_1205_nll
diff --git a/src/training/PaperMVE/models/papermve_v2_aug24_1205_nll.json b/src/training/PaperMVE/models/papermve_v2_aug24_1205_nll.json
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215 b/src/training/PaperMVE/models/papermve_v3_aug24_1215
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215.json b/src/training/PaperMVE/models/papermve_v3_aug24_1215.json
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215_final b/src/training/PaperMVE/models/papermve_v3_aug24_1215_final
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215_final.json b/src/training/PaperMVE/models/papermve_v3_aug24_1215_final.json
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215_mve b/src/training/PaperMVE/models/papermve_v3_aug24_1215_mve
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215_mve.json b/src/training/PaperMVE/models/papermve_v3_aug24_1215_mve.json
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215_nll b/src/training/PaperMVE/models/papermve_v3_aug24_1215_nll
diff --git a/src/training/PaperMVE/models/papermve_v3_aug24_1215_nll.json b/src/training/PaperMVE/models/papermve_v3_aug24_1215_nll.json
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220 b/src/training/PaperMVE/models/papermve_v4_aug24_1220
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220.json b/src/training/PaperMVE/models/papermve_v4_aug24_1220.json
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220_final b/src/training/PaperMVE/models/papermve_v4_aug24_1220_final
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220_final.json b/src/training/PaperMVE/models/papermve_v4_aug24_1220_final.json
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220_mve b/src/training/PaperMVE/models/papermve_v4_aug24_1220_mve
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220_mve.json b/src/training/PaperMVE/models/papermve_v4_aug24_1220_mve.json
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220_nll b/src/training/PaperMVE/models/papermve_v4_aug24_1220_nll
diff --git a/src/training/PaperMVE/models/papermve_v4_aug24_1220_nll.json b/src/training/PaperMVE/models/papermve_v4_aug24_1220_nll.json
diff --git a/src/training/PaperMVE/models/papermve_v5_aug24_1600 b/src/training/PaperMVE/models/papermve_v5_aug24_1600
diff --git a/src/training/PaperMVE/models/papermve_v5_aug24_1600.json b/src/training/PaperMVE/models/papermve_v5_aug24_1600.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.3151848816893436, 0.20076656389225553, 0.13516764084670618, 0.09632676307936038, 0.07679947984610877, 0.06480678841744088, 0.05731792933898391, 0.052150449669584494, 0.047210525809846804, 0.043855818420975475, 0.04163935908560779, 0.03906788178115157, 0.037086023351473825, 0.035531070812092835], "train_regression_loss": [2.074006853199528, 0.4476490915094041, 0.24448237013773247, 0.16882287080261782, 0.11202421932867719, 0.08566228849251484, 0.07052629554756598, 0.05903177993062209, 0.049942233441380525, 0.04188992043231806, 0.03554157664151471, 0.030988892067012663, 0.02758308104026579, 0.024897098488479145, 0.022754495479915652], "train_mve_loss": [0.883496187804386, 0.06467565289426977, -0.04754676097932474, -0.08258738649678732, -0.09234802385747869, -0.09875229366082813, -0.07769576444459136, -0.0710503211282398, -0.07850527555649416, -0.06403432938336673, -0.061292150154900506, -0.05946903445602989, -0.07392872231152638, -0.060159746155660374, -0.048401872925392234], "train_r2_score": [-5.3215408737193775, -0.35311903274446316, 0.2616024380152131, 0.49014089093758556, 0.662058148601214, 0.7410349481195512, 0.7866281870159818, 0.8215683631673003, 0.8490318659238117, 0.8733588968987854, 0.8922918622305532, 0.9061543969577129, 0.9164563746387462, 0.9246401087405937, 0.9310970375233204], "val_source_regression_loss": [0.7791940901852861, 0.28466814077353175, 0.2011979971128174, 0.13358284674490553, 0.09396284356524673, 0.0770800773856006, 0.06372395247409615, 0.053191423274670975, 0.04593960440988782, 0.03815242452429065, 0.03339041326242157, 0.028941010820526112, 0.026252837757332417, 0.023647266569771345, 0.021768139899248563], "val_target_regression_loss": [0.7236893282660956, 0.29719466272788714, 0.2341066502694842, 0.16704121929935262, 0.122245517618294, 0.0995061389064487, 0.0823204557918295, 0.06857119609094874, 0.05736645928855184, 0.04698791666121423, 0.04078102892241146, 0.03591504780269122, 0.032403678975150556, 0.02983855828642845, 0.026919758300992507], "val_source_r2_score": [-1.3842716219677729, 0.1322551986110978, 0.38661080124769454, 0.5916084663452083, 0.7129440598831682, 0.7650456178337339, 0.8049993189822593, 0.8373414704186516, 0.8603860790546544, 0.8836144894502913, 0.8973907762338363, 0.9104666851309617, 0.919284883083178, 0.927106769871846, 0.9336010757300206], "val_target_r2_score": [-1.1479454603945873, 0.11411292327925415, 0.3071164501084741, 0.5045840800855015, 0.6372425769862232, 0.7032368232204873, 0.7558404721484714, 0.796657213419245, 0.8297098851963337, 0.8598899079587753, 0.8784661716416915, 0.892200519810074, 0.9039473689805866, 0.9113120753691892, 0.9196231152170699], "val_source_mve_loss": [0.23364228519457805, -0.021601545205929235, -0.07153596684242351, -0.08882059180472471, -0.12682263788920414, -0.07771292036469979, -0.06865781588079053, -0.06944114427211918, -0.06227152582399453, -0.057447401217267484, -0.06419621903119208, -0.052544844537218915, -0.04448785736591001, -0.0710959828729871, -0.04454079378820673], "val_target_mve_loss": [0.20261395034156268, -0.019917044930065735, -0.05635408187120021, -0.06428638317539723, -0.1067164760978916, -0.05597573801686492, -0.052202987944400765, -0.057272818411075614, -0.0558979712143729, -0.05330345534448382, -0.06312875907066502, -0.05238567622779291, -0.04442358396570139, -0.06977773108814336, -0.04381852686593804], "val_source_nll_loss": [0.468348626471773, -0.07256644499735741, 294.7994344389137, 1459.271948707066, 326.8099325544472, 8015.804017463817, 4744.323691085169, 2621.4958073104485, 3601.8680732899074, 4027.523785404012, 7910.159259264982, 3262.070846171319, 7403.876609319373, 3511.1041580393344, 2987.2308512005625], "val_target_nll_loss": [0.4783958362627633, -0.04276905995145251, 114.17037622446689, 5831.001442042427, 895.1224421451363, 16065.25053850005, 14157.743982462944, 9152.26730891119, 10380.275531237638, 10954.806879357446, 12208.312727143493, 6570.066041584257, 11026.516508850871, 4437.239898295342, 6459.393034869357], "da_weight": [1.4, 1.4016, 1.4032, 1.4047999999999998, 1.4063999999999999, 1.408, 1.4096, 1.4112, 1.4127999999999998, 1.4143999999999999, 1.416, 1.4176, 1.4192, 1.4207999999999998, 1.4223999999999999], "beta": [1.0, 0.9966666666666667, 0.9933333333333333, 0.99, 0.9866666666666667, 0.9833333333333333, 0.98, 0.9766666666666667, 0.9733333333333334, 0.97, 0.9666666666666667, 0.9633333333333334, 0.96, 0.9566666666666667, 0.9533333333333334], "epoch_no": 15}
diff --git a/src/training/PaperMVE/models/papermve_v5_aug24_1600_mve b/src/training/PaperMVE/models/papermve_v5_aug24_1600_mve
diff --git a/src/training/PaperMVE/models/papermve_v5_aug24_1600_mve.json b/src/training/PaperMVE/models/papermve_v5_aug24_1600_mve.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.3151848816893436, 0.20076656389225553, 0.13516764084670618, 0.09632676307936038], "train_regression_loss": [2.074006853199528, 0.4476490915094041, 0.24448237013773247, 0.16882287080261782, 0.11202421932867719], "train_mve_loss": [0.883496187804386, 0.06467565289426977, -0.04754676097932474, -0.08258738649678732, -0.09234802385747869], "train_r2_score": [-5.3215408737193775, -0.35311903274446316, 0.2616024380152131, 0.49014089093758556, 0.662058148601214], "val_source_regression_loss": [0.7791940901852861, 0.28466814077353175, 0.2011979971128174, 0.13358284674490553, 0.09396284356524673], "val_target_regression_loss": [0.7236893282660956, 0.29719466272788714, 0.2341066502694842, 0.16704121929935262, 0.122245517618294], "val_source_r2_score": [-1.3842716219677729, 0.1322551986110978, 0.38661080124769454, 0.5916084663452083, 0.7129440598831682], "val_target_r2_score": [-1.1479454603945873, 0.11411292327925415, 0.3071164501084741, 0.5045840800855015, 0.6372425769862232], "val_source_mve_loss": [0.23364228519457805, -0.021601545205929235, -0.07153596684242351, -0.08882059180472471, -0.12682263788920414], "val_target_mve_loss": [0.20261395034156268, -0.019917044930065735, -0.05635408187120021, -0.06428638317539723, -0.1067164760978916], "val_source_nll_loss": [0.468348626471773, -0.07256644499735741, 294.7994344389137, 1459.271948707066, 326.8099325544472], "val_target_nll_loss": [0.4783958362627633, -0.04276905995145251, 114.17037622446689, 5831.001442042427, 895.1224421451363], "da_weight": [1.4, 1.4016, 1.4032, 1.4047999999999998, 1.4063999999999999], "beta": [1.0, 0.9966666666666667, 0.9933333333333333, 0.99, 0.9866666666666667], "epoch_no": 5}
diff --git a/src/training/PaperMVE/models/papermve_v5_aug24_1600_nll b/src/training/PaperMVE/models/papermve_v5_aug24_1600_nll
diff --git a/src/training/PaperMVE/models/papermve_v5_aug24_1600_nll.json b/src/training/PaperMVE/models/papermve_v5_aug24_1600_nll.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.3151848816893436], "train_regression_loss": [2.074006853199528, 0.4476490915094041], "train_mve_loss": [0.883496187804386, 0.06467565289426977], "train_r2_score": [-5.3215408737193775, -0.35311903274446316], "val_source_regression_loss": [0.7791940901852861, 0.28466814077353175], "val_target_regression_loss": [0.7236893282660956, 0.29719466272788714], "val_source_r2_score": [-1.3842716219677729, 0.1322551986110978], "val_target_r2_score": [-1.1479454603945873, 0.11411292327925415], "val_source_mve_loss": [0.23364228519457805, -0.021601545205929235], "val_target_mve_loss": [0.20261395034156268, -0.019917044930065735], "val_source_nll_loss": [0.468348626471773, -0.07256644499735741], "val_target_nll_loss": [0.4783958362627633, -0.04276905995145251], "da_weight": [1.4, 1.4016], "beta": [1.0, 0.9966666666666667], "epoch_no": 2}
diff --git a/src/training/PaperMVE/models/papermve_v6_aug24_1605 b/src/training/PaperMVE/models/papermve_v6_aug24_1605
diff --git a/src/training/PaperMVE/models/papermve_v6_aug24_1605.json b/src/training/PaperMVE/models/papermve_v6_aug24_1605.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.315237564077325, 0.20089994024968888, 0.13540037241262098, 0.09680369437776057, 0.07652339561275416, 0.06341705544148546, 0.05567595707269648, 0.05033812257146269, 0.04535639477413577], "train_regression_loss": [2.074006853199528, 0.44776723164744964, 0.24461440382426575, 0.16879648889603954, 0.11172398630618177, 0.08273072078333694, 0.06730642569484614, 0.05609614752110441, 0.04719995137242774, 0.040268454435102685], "train_mve_loss": [0.883496187804386, 0.06469119077640326, -0.04735850606971783, -0.08248399292038826, -0.08955707330890068, -0.0790670649667817, -0.07754444899599339, -0.06237429872808988, -0.05657308543240566, -0.08305641473483778], "train_r2_score": [-5.3215408737193775, -0.3534775992502385, 0.2612026977254223, 0.4902293203751974, 0.6629716115915095, 0.7499127626845695, 0.7963180910593207, 0.8304195815066611, 0.8573191551984016, 0.8782399348380491], "val_source_regression_loss": [0.7791940901852861, 0.2847505353296859, 0.20139117840724655, 0.13331747875560687, 0.09271204547037053, 0.07390698771688002, 0.06078962495998491, 0.050770748642426505, 0.043556257681567456, 0.03760790905054612], "val_target_regression_loss": [0.7236893282660956, 0.29725311715391617, 0.2342913726085349, 0.16704242289820803, 0.11961549162110195, 0.09553210984302472, 0.07870707708069041, 0.0656783492599107, 0.05473903113905387, 0.04656949535578112], "val_source_r2_score": [-1.3842716219677729, 0.13200355246354703, 0.3860215107924687, 0.5924305768379741, 0.7167924904625651, 0.7746828250617666, 0.8140216243752014, 0.8447634960919743, 0.8676822155907377, 0.8852407530557125], "val_target_r2_score": [-1.1479454603945873, 0.11393842321645495, 0.3065694518697815, 0.5046008208207339, 0.6450814133102007, 0.7150463324987868, 0.7665514031314306, 0.8052175540505162, 0.8374794211032204, 0.8611438685727509], "val_source_mve_loss": [0.23364228519457805, -0.021520939201729584, -0.07125181426541714, -0.08930688601317285, -0.09590166014961049, -0.06878988718307472, -0.06503916588387912, -0.05876560820431649, -0.05433297147856483, -0.059952775464404987], "val_target_mve_loss": [0.20261395034156268, -0.019862271014223748, -0.05611975538202479, -0.06478368957774548, -0.0775539688294447, -0.04802976437856125, -0.0484169274097002, -0.04612387782787975, -0.045572721505466894, -0.05436991353200961], "val_source_nll_loss": [0.468348626471773, -0.0724605364795727, 296.3569799975221, 1460.9741126608244, 350.58524396298805, 4775.629548385928, 6539.194262635859, 3535.0327973524227, 3411.630783337581, 8405.160072809533], "val_target_nll_loss": [0.4783958362627633, -0.04268265239116323, 114.4749104722957, 5622.230435017166, 1858.299458033205, 13673.729533539543, 13938.191131205498, 9678.003199727098, 8893.452757044684, 15747.961753362342], "da_weight": [1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4, 1.4], "beta": [1.0, 0.998, 0.996, 0.994, 0.992, 0.99, 0.988, 0.986, 0.984, 0.982], "epoch_no": 10}
diff --git a/src/training/PaperMVE/models/papermve_v6_aug24_1605_mve b/src/training/PaperMVE/models/papermve_v6_aug24_1605_mve
diff --git a/src/training/PaperMVE/models/papermve_v6_aug24_1605_mve.json b/src/training/PaperMVE/models/papermve_v6_aug24_1605_mve.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.315237564077325, 0.20089994024968888, 0.13540037241262098, 0.09680369437776057], "train_regression_loss": [2.074006853199528, 0.44776723164744964, 0.24461440382426575, 0.16879648889603954, 0.11172398630618177], "train_mve_loss": [0.883496187804386, 0.06469119077640326, -0.04735850606971783, -0.08248399292038826, -0.08955707330890068], "train_r2_score": [-5.3215408737193775, -0.3534775992502385, 0.2612026977254223, 0.4902293203751974, 0.6629716115915095], "val_source_regression_loss": [0.7791940901852861, 0.2847505353296859, 0.20139117840724655, 0.13331747875560687, 0.09271204547037053], "val_target_regression_loss": [0.7236893282660956, 0.29725311715391617, 0.2342913726085349, 0.16704242289820803, 0.11961549162110195], "val_source_r2_score": [-1.3842716219677729, 0.13200355246354703, 0.3860215107924687, 0.5924305768379741, 0.7167924904625651], "val_target_r2_score": [-1.1479454603945873, 0.11393842321645495, 0.3065694518697815, 0.5046008208207339, 0.6450814133102007], "val_source_mve_loss": [0.23364228519457805, -0.021520939201729584, -0.07125181426541714, -0.08930688601317285, -0.09590166014961049], "val_target_mve_loss": [0.20261395034156268, -0.019862271014223748, -0.05611975538202479, -0.06478368957774548, -0.0775539688294447], "val_source_nll_loss": [0.468348626471773, -0.0724605364795727, 296.3569799975221, 1460.9741126608244, 350.58524396298805], "val_target_nll_loss": [0.4783958362627633, -0.04268265239116323, 114.4749104722957, 5622.230435017166, 1858.299458033205], "da_weight": [1.4, 1.4, 1.4, 1.4, 1.4], "beta": [1.0, 0.998, 0.996, 0.994, 0.992], "epoch_no": 5}
diff --git a/src/training/PaperMVE/models/papermve_v6_aug24_1605_nll b/src/training/PaperMVE/models/papermve_v6_aug24_1605_nll
diff --git a/src/training/PaperMVE/models/papermve_v6_aug24_1605_nll.json b/src/training/PaperMVE/models/papermve_v6_aug24_1605_nll.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.315237564077325], "train_regression_loss": [2.074006853199528, 0.44776723164744964], "train_mve_loss": [0.883496187804386, 0.06469119077640326], "train_r2_score": [-5.3215408737193775, -0.3534775992502385], "val_source_regression_loss": [0.7791940901852861, 0.2847505353296859], "val_target_regression_loss": [0.7236893282660956, 0.29725311715391617], "val_source_r2_score": [-1.3842716219677729, 0.13200355246354703], "val_target_r2_score": [-1.1479454603945873, 0.11393842321645495], "val_source_mve_loss": [0.23364228519457805, -0.021520939201729584], "val_target_mve_loss": [0.20261395034156268, -0.019862271014223748], "val_source_nll_loss": [0.468348626471773, -0.0724605364795727], "val_target_nll_loss": [0.4783958362627633, -0.04268265239116323], "da_weight": [1.4, 1.4], "beta": [1.0, 0.998], "epoch_no": 2}
diff --git a/src/training/PaperMVE/models/papermve_v7_aug24_1610 b/src/training/PaperMVE/models/papermve_v7_aug24_1610
diff --git a/src/training/PaperMVE/models/papermve_v7_aug24_1610.json b/src/training/PaperMVE/models/papermve_v7_aug24_1610.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.3151848816893436, 0.20076656389225553, 0.13516764084670618, 0.09632676307936038, 0.07679947984610877], "train_regression_loss": [2.074006853199528, 0.4476490915094041, 0.24448237013773247, 0.16882287080261782, 0.11202421932867719, 0.08566228849251484], "train_mve_loss": [0.883496187804386, 0.06467565289426977, -0.04754676097932474, -0.08258738649678732, -0.09234802385747869, -0.09875229366082813], "train_r2_score": [-5.3215408737193775, -0.35311903274446316, 0.2616024380152131, 0.49014089093758556, 0.662058148601214, 0.7410349481195512], "val_source_regression_loss": [0.7791940901852861, 0.28466814077353175, 0.2011979971128174, 0.13358284674490553, 0.09396284356524673, 0.0770800773856006], "val_target_regression_loss": [0.7236893282660956, 0.29719466272788714, 0.2341066502694842, 0.16704121929935262, 0.122245517618294, 0.0995061389064487], "val_source_r2_score": [-1.3842716219677729, 0.1322551986110978, 0.38661080124769454, 0.5916084663452083, 0.7129440598831682, 0.7650456178337339], "val_target_r2_score": [-1.1479454603945873, 0.11411292327925415, 0.3071164501084741, 0.5045840800855015, 0.6372425769862232, 0.7032368232204873], "val_source_mve_loss": [0.23364228519457805, -0.021601545205929235, -0.07153596684242351, -0.08882059180472471, -0.12682263788920414, -0.07771292036469979], "val_target_mve_loss": [0.20261395034156268, -0.019917044930065735, -0.05635408187120021, -0.06428638317539723, -0.1067164760978916, -0.05597573801686492], "val_source_nll_loss": [0.468348626471773, -0.07256644499735741, 294.7994344389137, 1459.271948707066, 326.8099325544472, 8015.804017463817], "val_target_nll_loss": [0.4783958362627633, -0.04276905995145251, 114.17037622446689, 5831.001442042427, 895.1224421451363, 16065.25053850005], "da_weight": [1.4, 1.4016, 1.4032, 1.4047999999999998, 1.4063999999999999, 1.408], "beta": [1.0, 0.9966666666666667, 0.9933333333333333, 0.99, 0.9866666666666667, 0.9833333333333333], "epoch_no": 6}
diff --git a/src/training/PaperMVE/models/papermve_v7_aug24_1610_mve b/src/training/PaperMVE/models/papermve_v7_aug24_1610_mve
diff --git a/src/training/PaperMVE/models/papermve_v7_aug24_1610_mve.json b/src/training/PaperMVE/models/papermve_v7_aug24_1610_mve.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.3151848816893436, 0.20076656389225553, 0.13516764084670618, 0.09632676307936038], "train_regression_loss": [2.074006853199528, 0.4476490915094041, 0.24448237013773247, 0.16882287080261782, 0.11202421932867719], "train_mve_loss": [0.883496187804386, 0.06467565289426977, -0.04754676097932474, -0.08258738649678732, -0.09234802385747869], "train_r2_score": [-5.3215408737193775, -0.35311903274446316, 0.2616024380152131, 0.49014089093758556, 0.662058148601214], "val_source_regression_loss": [0.7791940901852861, 0.28466814077353175, 0.2011979971128174, 0.13358284674490553, 0.09396284356524673], "val_target_regression_loss": [0.7236893282660956, 0.29719466272788714, 0.2341066502694842, 0.16704121929935262, 0.122245517618294], "val_source_r2_score": [-1.3842716219677729, 0.1322551986110978, 0.38661080124769454, 0.5916084663452083, 0.7129440598831682], "val_target_r2_score": [-1.1479454603945873, 0.11411292327925415, 0.3071164501084741, 0.5045840800855015, 0.6372425769862232], "val_source_mve_loss": [0.23364228519457805, -0.021601545205929235, -0.07153596684242351, -0.08882059180472471, -0.12682263788920414], "val_target_mve_loss": [0.20261395034156268, -0.019917044930065735, -0.05635408187120021, -0.06428638317539723, -0.1067164760978916], "val_source_nll_loss": [0.468348626471773, -0.07256644499735741, 294.7994344389137, 1459.271948707066, 326.8099325544472], "val_target_nll_loss": [0.4783958362627633, -0.04276905995145251, 114.17037622446689, 5831.001442042427, 895.1224421451363], "da_weight": [1.4, 1.4016, 1.4032, 1.4047999999999998, 1.4063999999999999], "beta": [1.0, 0.9966666666666667, 0.9933333333333333, 0.99, 0.9866666666666667], "epoch_no": 5}
diff --git a/src/training/PaperMVE/models/papermve_v7_aug24_1610_nll b/src/training/PaperMVE/models/papermve_v7_aug24_1610_nll
diff --git a/src/training/PaperMVE/models/papermve_v7_aug24_1610_nll.json b/src/training/PaperMVE/models/papermve_v7_aug24_1610_nll.json
@@ -0,0 +1 @@
+{"train_DA_loss": [0.46571406569515766, 0.3151848816893436], "train_regression_loss": [2.074006853199528, 0.4476490915094041], "train_mve_loss": [0.883496187804386, 0.06467565289426977], "train_r2_score": [-5.3215408737193775, -0.35311903274446316], "val_source_regression_loss": [0.7791940901852861, 0.28466814077353175], "val_target_regression_loss": [0.7236893282660956, 0.29719466272788714], "val_source_r2_score": [-1.3842716219677729, 0.1322551986110978], "val_target_r2_score": [-1.1479454603945873, 0.11411292327925415], "val_source_mve_loss": [0.23364228519457805, -0.021601545205929235], "val_target_mve_loss": [0.20261395034156268, -0.019917044930065735], "val_source_nll_loss": [0.468348626471773, -0.07256644499735741], "val_target_nll_loss": [0.4783958362627633, -0.04276905995145251], "da_weight": [1.4, 1.4016], "beta": [1.0, 0.9966666666666667], "epoch_no": 2}
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		{"train_DA_loss": [0.46571406569515766, 0.3151848816893436, 0.20076656389225553, 0.13516764084670618, 0.09632676307936038, 0.07679947984610877, 0.06480678841744088, 0.05731792933898391, 0.052150449669584494, 0.047210525809846804, 0.043855818420975475, 0.04163935908560779, 0.03906788178115157, 0.037086023351473825, 0.035531070812092835], "train_regression_loss": [2.074006853199528, 0.4476490915094041, 0.24448237013773247, 0.16882287080261782, 0.11202421932867719, 0.08566228849251484, 0.07052629554756598, 0.05903177993062209, 0.049942233441380525, 0.04188992043231806, 0.03554157664151471, 0.030988892067012663, 0.02758308104026579, 0.024897098488479145, 0.022754495479915652], "train_mve_loss": [0.883496187804386, 0.06467565289426977, -0.04754676097932474, -0.08258738649678732, -0.09234802385747869, -0.09875229366082813, -0.07769576444459136, -0.0710503211282398, -0.07850527555649416, -0.06403432938336673, -0.061292150154900506, -0.05946903445602989, -0.07392872231152638, -0.060159746155660374, -0.048401872925392234], "train_r2_score": [-5.3215408737193775, -0.35311903274446316, 0.2616024380152131, 0.49014089093758556, 0.662058148601214, 0.7410349481195512, 0.7866281870159818, 0.8215683631673003, 0.8490318659238117, 0.8733588968987854, 0.8922918622305532, 0.9061543969577129, 0.9164563746387462, 0.9246401087405937, 0.9310970375233204], "val_source_regression_loss": [0.7791940901852861, 0.28466814077353175, 0.2011979971128174, 0.13358284674490553, 0.09396284356524673, 0.0770800773856006, 0.06372395247409615, 0.053191423274670975, 0.04593960440988782, 0.03815242452429065, 0.03339041326242157, 0.028941010820526112, 0.026252837757332417, 0.023647266569771345, 0.021768139899248563], "val_target_regression_loss": [0.7236893282660956, 0.29719466272788714, 0.2341066502694842, 0.16704121929935262, 0.122245517618294, 0.0995061389064487, 0.0823204557918295, 0.06857119609094874, 0.05736645928855184, 0.04698791666121423, 0.04078102892241146, 0.03591504780269122, 0.032403678975150556, 0.02983855828642845, 0.026919758300992507], "val_source_r2_score": [-1.3842716219677729, 0.1322551986110978, 0.38661080124769454, 0.5916084663452083, 0.7129440598831682, 0.7650456178337339, 0.8049993189822593, 0.8373414704186516, 0.8603860790546544, 0.8836144894502913, 0.8973907762338363, 0.9104666851309617, 0.919284883083178, 0.927106769871846, 0.9336010757300206], "val_target_r2_score": [-1.1479454603945873, 0.11411292327925415, 0.3071164501084741, 0.5045840800855015, 0.6372425769862232, 0.7032368232204873, 0.7558404721484714, 0.796657213419245, 0.8297098851963337, 0.8598899079587753, 0.8784661716416915, 0.892200519810074, 0.9039473689805866, 0.9113120753691892, 0.9196231152170699], "val_source_mve_loss": [0.23364228519457805, -0.021601545205929235, -0.07153596684242351, -0.08882059180472471, -0.12682263788920414, -0.07771292036469979, -0.06865781588079053, -0.06944114427211918, -0.06227152582399453, -0.057447401217267484, -0.06419621903119208, -0.052544844537218915, -0.04448785736591001, -0.0710959828729871, -0.04454079378820673], "val_target_mve_loss": [0.20261395034156268, -0.019917044930065735, -0.05635408187120021, -0.06428638317539723, -0.1067164760978916, -0.05597573801686492, -0.052202987944400765, -0.057272818411075614, -0.0558979712143729, -0.05330345534448382, -0.06312875907066502, -0.05238567622779291, -0.04442358396570139, -0.06977773108814336, -0.04381852686593804], "val_source_nll_loss": [0.468348626471773, -0.07256644499735741, 294.7994344389137, 1459.271948707066, 326.8099325544472, 8015.804017463817, 4744.323691085169, 2621.4958073104485, 3601.8680732899074, 4027.523785404012, 7910.159259264982, 3262.070846171319, 7403.876609319373, 3511.1041580393344, 2987.2308512005625], "val_target_nll_loss": [0.4783958362627633, -0.04276905995145251, 114.17037622446689, 5831.001442042427, 895.1224421451363, 16065.25053850005, 14157.743982462944, 9152.26730891119, 10380.275531237638, 10954.806879357446, 12208.312727143493, 6570.066041584257, 11026.516508850871, 4437.239898295342, 6459.393034869357], "da_weight": [1.4, 1.4016, 1.4032, 1.4047999999999998, 1.4063999999999999, 1.408, 1.4096, 1.4112, 1.4127999999999998, 1.4143999999999999, 1.416, 1.4176, 1.4192, 1.4207999999999998, 1.4223999999999999], "beta": [1.0, 0.9966666666666667, 0.9933333333333333, 0.99, 0.9866666666666667, 0.9833333333333333, 0.98, 0.9766666666666667, 0.9733333333333334, 0.97, 0.9666666666666667, 0.9633333333333334, 0.96, 0.9566666666666667, 0.9533333333333334], "epoch_no": 15}