Update README.md

README.md

@@ -19,7 +19,7 @@ This model is reccomended for Japanese SNS tasks, like [sentiment analysis](http
 
 ## Training Data
 
-The Twitter API was used to collect Japnaese Tweets from June 2022 to April 2023.
+The Twitter API was used to collect Japanese tweets from June 2022 to April 2023.
 
 N-gram based deduplication was used to reduce spam content and improve the diversity of the training corpus.
 The refined training corpus was 28 million tweets.
@@ -29,16 +29,4 @@ The refined training corpus was 28 million tweets.
 The vocabulary was prepared using the [WordPieceTrainer](https://huggingface.co/docs/tokenizers/api/trainers) with the Twitter training corpus.
 It shares 60% of its vocabulary with Japanese BERT.
 
-The vocuabulary includes colloquialisms, neologisms, emoji and kaomoji expressions that are common on Twitter.
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** Jordan Wolfgang Klein, as Master's candiate at the University Malta.
-- **Model type:** BERT
-- **Language(s) (NLP):** Japanese
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:**
+The vocabulary includes colloquialisms, neologisms, emoji and kaomoji expressions that are common on Twitter.