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metadata
language: fr
license: mit
datasets:
  - amazon_reviews_multi
  - allocine
widget:
  - text: Je pensais lire un livre nul, mais finalement je l'ai trouvé super...

DistilCamemBERT-Sentiment

We present DistilCamemBERT-Sentiment which is DistilCamemBERT fine tuned for the sentiment analysis task for the French language. This model is construct over 2 datasets: amazon_reviews_multi and allocine to aims minimize the biais. Inded, Amazon review are very similare beetwen the messages and relatevely short. To opposate Allocine criticims are long and rich text.

This modelisation is closely of tblard/tf-allocine base on CamemBERT model. The problem of the modelizations based on CamemBERT is at the scaling moment, for the production phase for example. Indeed, inference cost can be a technological issue. To counteract this effect, we propose this modelization which divides the inference time by 2 with the same consumption power thanks to DistilCamemBERT.

Dataset

Evaluation results

Benchmark

How to use DistilCamemBERT-Sentiment