InternImage not loading custom classes

I followed all the tutorials I could find and have defined a custom .py config file and a custom .py dataset config file with classes defined. However, when I try to train, it still tries to use the coco classes:

CocoDataset Test dataset with number of images 6042, and instance counts: +---------------------+-------+-----------------+-------+--------------------+-------+--------------------+-------+-------------------+-------+ | category | count | category | count | category | count | category | count | category | count | +---------------------+-------+-----------------+-------+--------------------+-------+--------------------+-------+-------------------+-------+ | 0 [person] | 0 | 1 [bicycle] | 0 | 2 [car] | 0 | 3 [motorcycle] | 0 | 4 [airplane] | 0 | | 5 [bus] | 0 | 6 [train] | 0 | 7 [truck] | 0 | 8 [boat] | 0 | 9 [traffic light] | 0 | | 10 [fire hydrant] | 0 | 11 [stop sign] | 0 | 12 [parking meter] | 0 | 13 [bench] | 0 | 14 [bird] | 0 | | 15 [cat] | 0 | 16 [dog] | 0 | 17 [horse] | 0 | 18 [sheep] | 0 | 19 [cow] | 0 | | 20 [elephant] | 0 | 21 [bear] | 0 | 22 [zebra] | 0 | 23 [giraffe] | 0 | 24 [backpack] | 0 | | 25 [umbrella] | 0 | 26 [handbag] | 0 | 27 [tie] | 0 | 28 [suitcase] | 0 | 29 [frisbee] | 0 | | 30 [skis] | 0 | 31 [snowboard] | 0 | 32 [sports ball] | 0 | 33 [kite] | 0 | 34 [baseball bat] | 0 | | 35 [baseball glove] | 0 | 36 [skateboard] | 0 | 37 [surfboard] | 0 | 38 [tennis racket] | 0 | 39 [bottle] | 0 | | 40 [wine glass] | 0 | 41 [cup] | 0 | 42 [fork] | 0 | 43 [knife] | 0 | 44 [spoon] | 0 | | 45 [bowl] | 0 | 46 [banana] | 0 | 47 [apple] | 0 | 48 [sandwich] | 0 | 49 [orange] | 0 | | 50 [broccoli] | 0 | 51 [carrot] | 0 | 52 [hot dog] | 0 | 53 [pizza] | 0 | 54 [donut] | 0 | | 55 [cake] | 0 | 56 [chair] | 0 | 57 [couch] | 0 | 58 [potted plant] | 0 | 59 [bed] | 0 | | 60 [dining table] | 0 | 61 [toilet] | 0 | 62 [tv] | 0 | 63 [laptop] | 0 | 64 [mouse] | 0 | | 65 [remote] | 0 | 66 [keyboard] | 0 | 67 [cell phone] | 0 | 68 [microwave] | 0 | 69 [oven] | 0 | | 70 [toaster] | 0 | 71 [sink] | 0 | 72 [refrigerator] | 0 | 73 [book] | 0 | 74 [clock] | 0 | | 75 [vase] | 0 | 76 [scissors] | 0 | 77 [teddy bear] | 0 | 78 [hair drier] | 0 | 79 [toothbrush] | 0 | | | | | | | | | | | | | -1 background | 6042 | | | | | | | | | +---------------------+-------+-----------------+-------+--------------------+-------+--------------------+-------+-------------------+-------+