Update README.md

README.md

@@ -46,6 +46,7 @@ print(time_reduced_hidden_states.shape) # [13, 768]
 # you can even use a learnable weighted average representation
 aggregator = nn.Conv1d(in_channels=13, out_channels=1, kernel_size=1)
 weighted_avg_hidden_states = aggregator(time_reduced_hidden_states).squeeze()
+print(weighted_avg_hidden_states.shape)
 ```
 
 Our model is based on the [data2vec audio model](https://huggingface.co/docs/transformers/model_doc/data2vec#transformers.Data2VecAudioModel).