EMA FP32 assert classification bug fix (#9016)

* Return EMA float on classification val

* verbose val fix

* EMA check

train.py

@@ -107,8 +107,7 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
         data_dict = data_dict or check_dataset(data)  # check if None
     train_path, val_path = data_dict['train'], data_dict['val']
     nc = 1 if single_cls else int(data_dict['nc'])  # number of classes
-    names = ['item'] if single_cls and len(data_dict['names']) != 1 else data_dict['names']  # class names
-    assert len(names) == nc, f'{len(names)} names found for nc={nc} dataset in {data}'  # check
+    names = {0: 'item'} if single_cls and len(data_dict['names']) != 1 else data_dict['names']  # class names
     is_coco = isinstance(val_path, str) and val_path.endswith('coco/val2017.txt')  # COCO dataset
 
     # Model