I am trying to train RTDetrV2 for detection on water meter digit. I use an ipynb file form here https://colab.research.google.com/g...with-transformers.ipynb#scrollTo=a7kZr8OtGkIO. But when I run through the code: model = AutoModelForObjectDetection.from_pretrained( CHECKPOINT, id2label=id2label, label2id=label2id, anchor_image_size=None, ignore_mismatched_sizes=True,) This Warning appear `RuntimeError: Error(s) in loading state_dict for RTDetrV2ForObjectDetection: size mismatch for model.denoising_class_embed.weight: copying a param with shape torch.Size([81, 256]) from checkpoint, the shape in current model is torch.Size([12, 256]). size mismatch for model.enc_score_head.weight: copying a param with shape torch.Size([80, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]). size mismatch for model.enc_score_head.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([11]). size mismatch for model.decoder.class_embed.0.weight: copying a param with shape torch.Size([80, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]). size mismatch for model.decoder.class_embed.0.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([11]). size mismatch for model.decoder.class_embed.1.weight: copying a param with shape torch.Size([80, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]). size mismatch for model.decoder.class_embed.1.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([11]). size mismatch for model.decoder.class_embed.2.weight: copying a param with shape torch.Size([80, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]). size mismatch for model.decoder.class_embed.2.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([11]). size mismatch for model.decoder.class_embed.3.weight: copying a param with shape torch.Size([80, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]). size mismatch for model.decoder.class_embed.3.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([11]). size mismatch for model.decoder.class_embed.4.weight: copying a param with shape torch.Size([80, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]). size mismatch for model.decoder.class_embed.4.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([11]). size mismatch for model.decoder.class_embed.5.weight: copying a param with shape torch.Size([80, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]). size mismatch for model.decoder.class_embed.5.bias: copying a param with shape torch.Size([80]) from checkpoint, the shape in current model is torch.Size([11]). ` I running this ipynb on pycharm. I try to delete id2label and label2id. It does not show the error but when I try to train for only one epoch it still training. IDK how to check if it works or not. Continue reading...
