RuCLIP -- new models and experiments: a technical report

Autor: Shonenkov, Alex, Kuznetsov, Andrey, Dimitrov, Denis, Shavrina, Tatyana, Chesakov, Daniil, Maltseva, Anastasia, Fenogenova, Alena, Pavlov, Igor, Emelyanov, Anton, Markov, Sergey, Bakshandaeva, Daria, Shybaeva, Vera, Chertok, Andrey
Rok vydání: 2022
Předmět:
Druh dokumentu: Working Paper
Popis: In the report we propose six new implementations of ruCLIP model trained on our 240M pairs. The accuracy results are compared with original CLIP model with Ru-En translation (OPUS-MT) on 16 datasets from different domains. Our best implementations outperform CLIP + OPUS-MT solution on most of the datasets in few-show and zero-shot tasks. In the report we briefly describe the implementations and concentrate on the conducted experiments. Inference execution time comparison is also presented in the report.
Databáze: arXiv