This is a ruBERT-conversational model trained on the mixture of 3 paraphrase detection datasets:

• ru_paraphraser (with classes -1 and 0 merged)
• RuPAWS
• A dataset containing crowdsourced evaluation of content preservation in Russian text detoxification by Dementieva et al, 2022.

The model can be used to assess semantic similarity of Russian sentences.

Training notebook: task_oriented_TST/similarity/cross_encoders/russian/train_russian_paraphrase_detector__fixed.ipynb (in a private repo).

Training parameters:

• optimizer: Adam
• lr=1e-5
• batch_size=32
• epochs=3

ROC AUC on the development data:

source         score
detox          0.821665
paraphraser    0.848287
rupaws_qqp     0.761481
rupaws_wiki    0.844093

Pleas see also the documentation of SkolkovoInstitute/ruRoberta-large-paraphrase-v1 that performs better on this task.