End of training

.gitattributes

@@ -33,3 +33,12 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+confusion_matrix_test.tiff filter=lfs diff=lfs merge=lfs -text
+confusion_matrix_train.tiff filter=lfs diff=lfs merge=lfs -text
+confusion_matrix_val.tiff filter=lfs diff=lfs merge=lfs -text
+long_tail_f1_vs_freq_test.tiff filter=lfs diff=lfs merge=lfs -text
+long_tail_f1_vs_freq_train.tiff filter=lfs diff=lfs merge=lfs -text
+long_tail_f1_vs_freq_val.tiff filter=lfs diff=lfs merge=lfs -text
+per_class_accuracy_test.tiff filter=lfs diff=lfs merge=lfs -text
+per_class_accuracy_train.tiff filter=lfs diff=lfs merge=lfs -text
+per_class_accuracy_val.tiff filter=lfs diff=lfs merge=lfs -text

per_class_results_test.csv

@@ -0,0 +1,11 @@
+class,accuracy,precision,recall,f1,top5_accuracy
+chikissha,0.5,0.3333333333333333,0.5,0.4,0.7
+apartment,0.0,0.0,0.0,0.0,0.7
+ac,0.5,0.3333333333333333,0.5,0.4,0.7
+cream,0.5,0.5,0.5,0.5,0.7
+attio,0.0,0.0,0.0,0.0,0.7
+ayna,0.0,0.0,0.0,0.0,0.7
+alu,0.0,0.0,0.0,0.0,0.7
+balti,1.0,0.2857142857142857,1.0,0.4444444444444444,0.7
+angur,0.5,0.25,0.5,0.3333333333333333,0.7
+anaros,0.0,0.0,0.0,0.0,0.7

per_class_results_train.csv

@@ -0,0 +1,11 @@
+class,accuracy,precision,recall,f1,top5_accuracy
+chikissha,0.8333333333333334,0.7142857142857143,0.8333333333333334,0.7692307692307693,0.8916666666666667
+apartment,0.25,1.0,0.25,0.4,0.8916666666666667
+ac,0.6666666666666666,0.8,0.6666666666666666,0.7272727272727273,0.8916666666666667
+cream,0.75,1.0,0.75,0.8571428571428571,0.8916666666666667
+attio,0.0,0.0,0.0,0.0,0.8916666666666667
+ayna,0.6666666666666666,0.6666666666666666,0.6666666666666666,0.6666666666666666,0.8916666666666667
+alu,0.4166666666666667,1.0,0.4166666666666667,0.5882352941176471,0.8916666666666667
+balti,1.0,0.5454545454545454,1.0,0.7058823529411765,0.8916666666666667
+angur,0.75,0.36,0.75,0.4864864864864865,0.8916666666666667
+anaros,1.0,0.6,1.0,0.75,0.8916666666666667

per_class_results_val.csv

@@ -0,0 +1,11 @@
+class,accuracy,precision,recall,f1,top5_accuracy
+chikissha,0.0,0.0,0.0,0.0,0.6
+apartment,0.0,0.0,0.0,0.0,0.6
+ac,0.0,0.0,0.0,0.0,0.6
+cream,0.0,0.0,0.0,0.0,0.6
+attio,0.0,0.0,0.0,0.0,0.6
+ayna,0.0,0.0,0.0,0.0,0.6
+alu,0.0,0.0,0.0,0.0,0.6
+balti,1.0,0.3333333333333333,1.0,0.5,0.6
+angur,1.0,0.5,1.0,0.6666666666666666,0.6
+anaros,1.0,0.25,1.0,0.4,0.6