README.md

metadata

license: mit

This classification model is based on cointegrated/rubert-tiny2. The model should be used to produce relevance and specificity of the last message in the context of a dialog.

It is pretrained on corpus of dialog data from social networks and finetuned on tinkoff-ai/context_similarity. The performance of the model on validation split tinkoff-ai/context_similarity (with the best thresholds for validation samples):

relevance		specificity
f0.5	roc-auc	f0.5	roc-auc
0.82	0.74	0.81	0.8

The model can be loaded as follows:

# pip install transformers
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("tinkoff-ai/context_similarity")
model = AutoModel.from_pretrained("tinkoff-ai/context_similarity")
# model.cuda()