feat(weights): sync vit/none/finetune_robust/seed_7 (best.pth and metrics)

.gitattributes

@@ -319,3 +319,4 @@ vit/srm_only/finetune_robust/seed_42/plots/roc_auc.png filter=lfs diff=lfs merge
 vit/none/finetune_robust/seed_2024/plots/roc_auc.png filter=lfs diff=lfs merge=lfs -text
 vit/none/finetune_robust/seed_123/plots/roc_auc.png filter=lfs diff=lfs merge=lfs -text
 vit/none/finetune_robust/seed_42/plots/roc_auc.png filter=lfs diff=lfs merge=lfs -text
+vit/none/finetune_robust/seed_7/plots/roc_auc.png filter=lfs diff=lfs merge=lfs -text

vit/none/finetune_robust/seed_7/results/history.csv

@@ -0,0 +1,31 @@
+epoch,train_loss,val_loss,val_auc,val_acc,threshold,threshold_score
+1,0.38984847043510384,0.3937936506589573,0.8620975683087287,0.7222437111079443,0.09203285723924637,0.8225398156354315
+2,0.3467266186594461,0.36263936947136666,0.8917090683480549,0.7108093619158133,0.0809367224574089,0.8424754022583698
+3,0.32991868109820244,0.3391929527051517,0.8962161271481932,0.7548570536701886,0.12549345195293427,0.8468428716410008
+4,0.3203092570317127,0.3286218308300569,0.9082049511581819,0.7764364189111242,0.09138209372758865,0.8577910328838524
+5,0.3130256060029671,0.31111371092242723,0.91505439485351,0.7941002829746951,0.14175598323345184,0.8654812780939306
+6,0.3069928622892606,0.29708240490974525,0.9238193047041301,0.7847288668118862,0.10521053522825241,0.8733131045581801
+7,0.3012326274996156,0.3076227512331926,0.9220273973276772,0.7748213595000102,0.07696084678173065,0.8704449170187839
+8,0.29388963315217453,0.29377183054472333,0.9254545644430443,0.8112551997448477,0.10521053522825241,0.8742393282640494
+9,0.2933632208496847,0.2990332407229008,0.9282198449091279,0.8440789071883715,0.2120688110589981,0.8795606339680104
+10,0.2871133550847891,0.29092058625243705,0.9302934799483586,0.8282947551284923,0.1063188686966896,0.8808308179135294
+11,0.28423569411033894,0.3058763750914939,0.9231577619146263,0.8319456037132794,0.13799647986888885,0.8733519687104208
+12,0.2825309633460848,0.28440336859047,0.9311081894062613,0.819635865176469,0.09467770159244537,0.8810200193843789
+13,0.2789124011560621,0.27101854465762737,0.9364602770473889,0.814960336040933,0.10447732359170914,0.8849166567549658
+14,0.2756746887416966,0.2777514875515862,0.9340383275815136,0.8480758399326832,0.14706452190876007,0.8855409105021027
+15,0.2741625509804742,0.2806027903910233,0.9325931577848947,0.8294144391740125,0.11676400899887085,0.8815712806820046
+16,0.27257846052504325,0.2873480647941465,0.933449211612083,0.8342596174073547,0.10123348236083984,0.8834961210023999
+17,0.26999610542761876,0.27712622720787006,0.938583877587121,0.8353657295250504,0.08694165199995041,0.8901985216117463
+18,0.26727731742996325,0.2848263175812717,0.9347548912909001,0.8292651479679432,0.07477004081010818,0.8838699163233996
+19,0.26704250173642663,0.2699111239767067,0.9400191423623585,0.8334928034852711,0.0809367224574089,0.8893225377588342
+20,0.26442223141922616,0.29008422447615184,0.9368875143392931,0.8383651255742622,0.07055959850549698,0.8882341652838452
+21,0.2618895973024865,0.2901716953356998,0.9349840714851547,0.8489512292773627,0.10594828426837921,0.8896578799775658
+22,0.26134070694861167,0.25124170781888433,0.9458347184753612,0.860365220577757,0.13986565172672272,0.8965614637645956
+23,0.2601772254606006,0.27519094343392214,0.9374346599555076,0.8463182752794121,0.11879339814186096,0.8902203280615879
+24,0.25743860125962653,0.29607703036350036,0.9279384683917002,0.8244267556985132,0.08694165199995041,0.8774481494149112
+25,0.25600094267033213,0.28079918323184194,0.936199155663595,0.8501523448898298,0.12463857978582382,0.8897908071422981
+26,0.25506733749494837,0.2574446366697912,0.9447825296950547,0.8590894593622551,0.13206616044044495,0.8953787523253249
+27,0.24346640451299648,0.2672594134407494,0.943457065377111,0.8617427712519424,0.10557884722948074,0.8974747332563835
+28,0.2393482428009303,0.26193193271327514,0.945516439677985,0.8617156273962935,0.09534946084022522,0.8989141209335857
+29,0.23812655217134554,0.2699285961608303,0.9431612001596441,0.8657736338158154,0.12852515280246735,0.8980123782066833
+30,0.23614368240615907,0.2632587994119258,0.9448630512638381,0.8653054023058705,0.12002561241388321,0.8987885493800891

vit/none/finetune_robust/seed_7/results/metrics_celeb_df.csv

@@ -0,0 +1,2 @@
+model_family,fourier_mode,regime,seed,split,threshold,auc,acc,f1,precision,recall,specificity,loss,frame_auc,frame_acc,frame_f1,video_auc,video_acc,video_f1
+vit,none,finetune_robust,7,celeb_df,0.1398656517267227,0.6082145847102886,0.636936936936937,0.7411689145793192,0.6964993964476633,0.7919607843137255,0.3408239700374532,0.0,0.6082145847102886,0.636936936936937,0.7411689145793192,0.6437210839391937,0.6563706563706564,0.7807881773399015

vit/none/finetune_robust/seed_7/results/metrics_celeb_df_video.csv

@@ -0,0 +1,2 @@
+model_family,fourier_mode,regime,seed,split,threshold,auc,acc,f1,precision,recall,specificity,loss
+vit,none,finetune_robust,7,celeb_df_video,0.1398656517267227,0.6437210839391937,0.6563706563706564,0.7807881773399015,0.6716101694915254,0.9323529411764706,0.12921348314606743,0.0

vit/none/finetune_robust/seed_7/results/metrics_df40.csv

@@ -0,0 +1,2 @@
+model_family,fourier_mode,regime,seed,split,threshold,loss,acc,precision,recall,f1,auc,specificity,tp,fp,fn,tn
+vit,none,finetune_robust,7,df40,0.1398656517267227,0.9793574779286426,0.671003050421676,0.6853512705530643,0.7458923051895233,0.7143413570148789,0.6964316077791775,0.5789157831566313,4585,2105,1562,2894

vit/none/finetune_robust/seed_7/results/metrics_summary.csv

@@ -0,0 +1,2 @@
+acc,precision,f1,auc,recall,specificity,model_family,architecture,fourier_mode,regime,seed,seeds,epochs,batch_size,num_workers,image_size,data_limit,raw_min,lr_head,lr_backbone,weight_decay,early_stop_patience,scheduler_patience,max_grad_norm,dropout,augment,train_backbone,use_weighted_sampler,use_class_weights,label_smoothing,threshold_strategy,mixup_alpha,cutmix_alpha,unfreeze_last_n,multi_gpu,allow_pretrained,patch_size,hidden_size,num_hidden_layers,num_attention_heads,projection_dim,variant,model_size,expert_family,num_experts,routing_strategy,top_k,in_channels_override,in_channels,threshold
+0.7428042232078572,0.8399111667631389,0.752399496290966,0.8304703930747267,0.6814030379989459,0.8253653256359372,vit,resnet18,none,finetune,7,"[42, 123, 2024, 7, 2025]",50,32,4,224,,False,0.001,0.0001,0.0001,8,3,1.0,0.2,True,True,True,True,0.0,f1,0.2,0.0,2,False,True,16,256,6,8,128,large,base,mobilenet,7,dense,3,,3,0.13986565172672272

vit/none/finetune_robust/seed_7/results/metrics_test.csv

@@ -0,0 +1,2 @@
+model_family,fourier_mode,regime,seed,split,threshold,loss,acc,precision,recall,f1,auc,specificity,tp,fp,fn,tn
+vit,none,finetune,7,test,0.13986565172672272,0.5216599602266658,0.7428042232078572,0.8399111667631389,0.6814030379989459,0.752399496290966,0.8304703930747267,0.8253653256359372,71101,13552,33244,64050

vit/none/finetune_robust/seed_7/results/metrics_test_d.csv

@@ -0,0 +1,2 @@
+model_family,fourier_mode,regime,seed,split,threshold,loss,acc,precision,recall,f1,auc,specificity,tp,fp,fn,tn
+vit,none,finetune_robust,7,test_d,0.1398656517267227,1.0297932254122337,0.6878706436489747,0.792921204356182,0.6168287891130385,0.6938771109925236,0.7712870272621455,0.7833947578670653,64363,16809,39982,60793

vit/none/finetune_robust/seed_7/results/metrics_val.csv

@@ -0,0 +1,2 @@
+model_family,fourier_mode,regime,seed,split,threshold,loss,acc,precision,recall,f1,auc,specificity,tp,fp,fn,tn
+vit,none,finetune,7,val,0.13986565172672272,0.25124170781888433,0.8757422148029017,0.894242796452598,0.8988921864026642,0.8965614637645956,0.9458347184753612,0.8411502852016722,79356,9385,8926,49696

vit/none/finetune_robust/seed_7/results/run_config.json

@@ -0,0 +1,51 @@
+{
+  "allow_pretrained": true,
+  "architecture": "resnet18",
+  "augment": true,
+  "batch_size": 32,
+  "cutmix_alpha": 0.0,
+  "data_limit": null,
+  "dropout": 0.2,
+  "early_stop_patience": 8,
+  "epochs": 50,
+  "expert_family": "mobilenet",
+  "fourier_mode": "none",
+  "hidden_size": 256,
+  "image_size": 224,
+  "in_channels": 3,
+  "in_channels_override": null,
+  "label_smoothing": 0.0,
+  "lr_backbone": 0.0001,
+  "lr_head": 0.001,
+  "max_grad_norm": 1.0,
+  "mixup_alpha": 0.2,
+  "model_family": "vit",
+  "model_size": "base",
+  "multi_gpu": false,
+  "num_attention_heads": 8,
+  "num_experts": 7,
+  "num_hidden_layers": 6,
+  "num_workers": 4,
+  "patch_size": 16,
+  "projection_dim": 128,
+  "raw_min": false,
+  "regime": "finetune",
+  "routing_strategy": "dense",
+  "scheduler_patience": 3,
+  "seed": 7,
+  "seeds": [
+    42,
+    123,
+    2024,
+    7,
+    2025
+  ],
+  "threshold_strategy": "f1",
+  "top_k": 3,
+  "train_backbone": true,
+  "unfreeze_last_n": 2,
+  "use_class_weights": true,
+  "use_weighted_sampler": true,
+  "variant": "large",
+  "weight_decay": 0.0001
+}

vit/none/finetune_robust/seed_7/weights/best.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d6143d38486e62bde343944acaf5c5322870e1be06c918f61d8c73638fe2f7f0
+size 345639254