Common use of Bias Model Clause in Contracts

Bias Model. ‌ As mentioned in Section 4.1.3, we train the bias model with spurious features. For MNLI and QQP, we adopt the hand-crafted word overlapping features proposed by [5], which includes: • Whether all the hypothesis words also belong to the premise. 7▇▇▇▇▇://▇▇▇▇▇▇▇.▇▇▇/‌ 8▇▇▇▇▇://▇▇▇▇▇▇.▇▇▇/huggingface/transformers MNLI HANS QQP PAWSqqp PAWSwiki FEVER Symm1 Symm2 ent 33.3% 50% dulp 36.9% 31.5% 44.2% supp 41.4% - - Train cont 33.3% neutral 33.3% 50% 0% Train non-dulp 63.1% 68.5% 55.8% Train refute not-info 17.2% 41.4% - - - -