Evaluate Transcoder_model_1 on CodeXGlue benchmark

Hi,
I am trying to follow the instruction in dobf.md to evaluate Transcoder_model_1.pth on Clone detection. After I run following command, the error related to reloading the model appears. I wonder if I did something wrong or if the script needs to be modified to evaluate Transcoder model on CodeXGlue.
```
SOURCEDIR=/home/h6ju/CodeGen
MODEL=/home/h6ju/CodeGen/TransCoder_model_1.pth
lr=2.5e-5
export PYTHONPATH=/home/h6ju/CodeGen
source $SOURCEDIR/newCodeGen/bin/activate

cd CodeXGLUE/Code-Code/Clone-detection-BigCloneBench/code; bash run_xlm_general.sh $MODEL 12 05 roberta_java TransCoder_model_1 $lr 2>&1 | tee logs/TransCoder_model_1_roberta_java_05_12_lr$lr.log
```

Then, following error comes out:
```
tee: logs/TransCoder_model_1_roberta_java_05_12_lr2.5e-5.log: No such file or directory
adding to path /home/h6ju/CodeGen
05/18/2022 17:29:14 - WARNING - __main__ - Process rank: -1, device: cuda, n_gpu: 1, distributed training: False, 16-bits training: False
/home/h6ju/CodeGen/TransCoder_model_1.pth
Traceback (most recent call last):
File "run.py", line 642, in
main()
File "run.py", line 596, in main
model = model_class.from_pretrained(args.model_name_or_path,
File "/home/h6ju/CodeGen/codegen_sources/wrappers/models.py", line 160, in from_pretrained
model.reload_model(model_path)
File "/home/h6ju/CodeGen/codegen_sources/wrappers/models.py", line 124, in reload_model
self.transformer.load_state_dict(model_reloaded, strict=True)
File "/project/6001884/h6ju/CodeGen/newCodeGen/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1406, in load_state_dict
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for TransformerModel:
size mismatch for position_embeddings.weight: copying a param with shape torch.Size([1024, 1024]) from checkpoint, the shape in current model is torch.Size([2048, 1024]).
```

Even I modified `strict=True` to `strict=False` in models.py, the same error still appears.
Thank you for your great help!