Unet_learner

wondering if someone can help me, I am training with this datablock

dblock = DataBlock(blocks=(ImageBlock, MaskBlock()),
               get_items=get_image_files,
               get_y=lambda o:str(o).replace('images','masks'),
               splitter=RandomSplitter(valid_pct=0.2,seed=2020),
               item_tfms=Resize(352), # transformPipeline]
               batch_tfms=[Normalize.from_stats(*imagenet_stats)])

ds = dblock.datasets(source=path/'images')
dls = dblock.dataloaders(image_path, bs=bs, workers = 8)

Then I create the learner, and traing…

learner = unet_learner(dls,
                     resnet34,
                     opt_func = optimizer,
                     loss_func=symmetric_lovasz,
                     metrics=[Dice_soft(), Dice_th()],
                     config = config,
                     n_out=1 )

But then I get this.

Can someone give me a hint of what I am doing wrong ? thanks.