DeBERTa v3 large mnli fever anli ling wanli Model description This model was fine tuned on the MultiNLI, Fever NLI, Adversarial NLI (ANLI), LingNLI and WANLI datasets, which comprise 885 242 NLI hypothesis premise pairs. This model is the best performing NLI model on the Hugging Face Hub as of 06.06.22 and can be used for zero shot classification. It significantly outperforms all other large models on the ANLI benchmark. The foundation model is DeBERTa v3 large from Microsoft. DeBERTa v3 combines several recent innovations compared to classical Masked Language Models like BERT, RoBERTa etc., see the paper How to use the model Simple zero shot classification pipeline NLI use case Training data DeBERTa v3 large mnli fever anli ling wanli was trained on the MultiNLI, Fever NLI, Adversarial NLI (ANLI), LingNLI and WANLI datasets, which comprise 885 242 NLI hypothesis premise pairs. Note that SNLI was explicitly excluded due to quality issues with the dataset. More data does not necessarily make for better NLI models. Training procedure DeBERTa v3 large mnli fever anli ling wanli was trained using the Hugging Face trainer with the following hyperparameters. Note that longer training wit…
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