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

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

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)

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