Finetuning model

[Srivatsa1648]

bash scripts/DINO_train.sh /home/slam/Downloads/REU_Srivatsa/radar_img --pretrain_model_path /home/slam/Downloads/REU_Srivatsa/checkpoint0011_4scale.pth --finetune_ignore label_enc.weight class_embed
when i give the above command and modify the config file as per the class in my dataset i am facing the below error of torch size mismatch
RuntimeError: Error(s) in loading state_dict for DINO:
size mismatch for transformer.decoder.class_embed.0.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for transformer.decoder.class_embed.0.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for transformer.decoder.class_embed.1.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for transformer.decoder.class_embed.1.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for transformer.decoder.class_embed.2.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for transformer.decoder.class_embed.2.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for transformer.decoder.class_embed.3.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for transformer.decoder.class_embed.3.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for transformer.decoder.class_embed.4.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for transformer.decoder.class_embed.4.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for transformer.decoder.class_embed.5.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for transformer.decoder.class_embed.5.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for transformer.enc_out_class_embed.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for transformer.enc_out_class_embed.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for label_enc.weight: copying a param with shape torch.Size([92, 256]) from checkpoint, the shape in current model is torch.Size([15, 256]).
size mismatch for class_embed.0.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for class_embed.0.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for class_embed.1.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for class_embed.1.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for class_embed.2.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for class_embed.2.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for class_embed.3.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for class_embed.3.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for class_embed.4.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for class_embed.4.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
size mismatch for class_embed.5.weight: copying a param with shape torch.Size([91, 256]) from checkpoint, the shape in current model is torch.Size([11, 256]).
size mismatch for class_embed.5.bias: copying a param with shape torch.Size([91]) from checkpoint, the shape in current model is torch.Size([11]).
and if i finetune without changing config file i am getting very least ap of 0.26 and i am training for dino_4scale model
pls reslove my error asap