Fix two typos in text classification examples rnn (#887)

Co-authored-by: Zeyu Chen <[email protected]>

Author: songzy12

examples/text_classification/rnn/model.py

@@ -25,7 +25,7 @@ class BoWModel(nn.Layer):
     """
     This class implements the Bag of Words Classification Network model to classify texts.
     At a high level, the model starts by embedding the tokens and running them through
-    a word embedding. Then, we encode these epresentations with a `BoWEncoder`.
+    a word embedding. Then, we encode these representations with a `BoWEncoder`.
     Lastly, we take the output of the encoder to create a final representation,
     which is passed through some feed-forward layers to output a logits (`output_layer`).
 

examples/text_classification/rnn/train.py

@@ -117,7 +117,7 @@ def create_dataloader(dataset,
             padding_idx=pad_token_id)
     elif network == 'bilstm_attn':
         lstm_hidden_size = 196
-        attention = SelfInteractiveAttention(hidden_size=2 * stm_hidden_size)
+        attention = SelfInteractiveAttention(hidden_size=2 * lstm_hidden_size)
         model = BiLSTMAttentionModel(
             attention_layer=attention,
             vocab_size=vocab_size,