readme: ---
  language: 
    - "fr"
  
  tags:
  - twitter
  - DistilCamemBERT
  - sentiment analysis
  - emojis
  
  datasets:
  - 'corpus_tweets_def.csv' 
  
  ---
  
  # CamemBERT-base for sentiment analysis on tweets
  
  This is a Camembert-base model trained on a corpus of 50K french tweets. 
  
   - Git Repo containing the dataset and the code (scraping & training) : [Git](https://git.unistra.fr/nierichlo/projet_tutore_gr1)
  
  The model can predict which of the 25 emojis it has been trained with suits the best on a given sentence / tweet. 
  The 25 emojis are the 25 most frequent in the dataset.
  
  We've succeeded to obtain a 32% accuracy on a small amount of tweets.
  
  **Note**: We've also decided to keep the emojis in their *demojized* versions because some emojis could be seen as two (ex : 👍🏿)
  
  ## Loading the model 
  
  ```python
  from transformers import AutoModelForSequenceClassification, AutoTokenizer, TFAutoModelForSequenceClassification
  
  MODEL = f"Jessy3ric/camembert-twitter-emoji"
  tokenizer = AutoTokenizer.from_pretrained(MODEL)
  
  model = AutoModelForSequenceClassification.from_pretrained(MODEL)
  model.save_pretrained(MODEL)
  
  ```