RuBERT for NLI (natural language inference) This is the DeepPavlov/rubert base cased fine tuned to predict the logical relationship between two short texts: entailment, contradiction, or neutral. Usage How to run the model for NLI: You can also use this model for zero shot short text classification (by labels only), e.g. for sentiment analysis: Alternatively, you can use Huggingface pipelines for inference. Sources The model has been trained on a series of NLI datasets automatically translated to Russian from English. Most datasets were taken from the repo of Felipe Salvatore: JOCI, MNLI, MPE, SICK, SNLI. Some datasets obtained from the original sources: ANLI, NLI style FEVER, IMPPRES. Performance The table below shows ROC AUC (one class vs rest) for five models on the corresponding dev sets: tiny: a small BERT predicting entailment vs not entailment twoway: a base sized BERT predicting entailment vs not entailment threeway ( this model ): a base sized BERT predicting entailment vs contradiction vs neutral vicgalle xlm: a large multilingual NLI model facebook bart: a large multilingual NLI model model add one rte anli r1 anli r2 anli r3 copa fever help iie imppres joci mnli monli m…
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