Upload DebertaV2ForSequenceClassification
Browse files- config.json +153 -147
- pytorch_model.bin +1 -1
config.json
CHANGED
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@@ -549,17 +552,17 @@
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"scitail/snli_format",
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"hans",
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"WANLI",
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"recast/recast_factuality",
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"recast/recast_puns",
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"recast/recast_kg_relations",
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"recast/recast_sentiment",
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"recast/recast_ner",
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"recast/recast_verbcorner",
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"recast/recast_megaveridicality",
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"recast/recast_verbnet",
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"
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"
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"probability_words_nli/reasoning_2hop",
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"nan-nli/joey234--nan-nli",
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"nli_fever",
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"breaking_nli",
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"robust_nli_is_sd",
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"robust_nli_li_ts",
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"add_one_rte",
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"imppres/implicature_gradable_verb/log",
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"imppres/implicature_modals/log",
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"imppres/implicature_connectives/log",
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"imppres/implicature_quantifiers/log",
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"imppres/implicature_numerals_2_3/log",
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"imppres/implicature_gradable_adjective/log",
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"imppres/implicature_numerals_10_100/log",
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"glue_diagnostics/diagnostics",
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"hlgd",
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"paws/labeled_final",
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"model-written-evals",
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"truthful_qa/multiple_choice",
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"fig-qa",
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"bigbench/metaphor_boolean",
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"bigbench/fantasy_reasoning",
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"bigbench/ruin_names",
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"bigbench/
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"bigbench/timedial",
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"bigbench/
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"bigbench/cifar10_classification",
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"bigbench/riddle_sense",
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"bigbench/empirical_judgments",
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"bigbench/evaluating_information_essentiality",
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"bigbench/elementary_math_qa",
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"bigbench/emojis_emotion_prediction",
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"bigbench/reasoning_about_colored_objects",
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"bigbench/physical_intuition",
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"bigbench/undo_permutation",
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"bigbench/analytic_entailment",
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"bigbench/cause_and_effect",
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"bigbench/presuppositions_as_nli",
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"bigbench/movie_recommendation",
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"bigbench/penguins_in_a_table",
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"bigbench/social_iqa",
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"bigbench/phrase_relatedness",
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"bigbench/logic_grid_puzzle",
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"bigbench/logical_args",
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"bigbench/nonsense_words_grammar",
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"bigbench/cs_algorithms",
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"bigbench/epistemic_reasoning",
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"bigbench/social_support",
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"bigbench/moral_permissibility",
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"bigbench/abstract_narrative_understanding",
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"bigbench/human_organs_senses",
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"bigbench/checkmate_in_one",
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"bigbench/
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"bigbench/crass_ai",
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"bigbench/causal_judgment",
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"bigbench/authorship_verification",
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"bigbench/goal_step_wikihow",
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"bigbench/identify_odd_metaphor",
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"bigbench/gre_reading_comprehension",
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"bigbench/similarities_abstraction",
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"bigbench/fact_checker",
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"bigbench/emoji_movie",
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"bigbench/bbq_lite_json",
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"bigbench/unit_interpretation",
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"bigbench/logical_sequence",
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"bigbench/irony_identification",
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"bigbench/color",
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"bigbench/entailed_polarity",
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"bigbench/tracking_shuffled_objects",
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"bigbench/understanding_fables",
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"bigbench/mnist_ascii",
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"bigbench/
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"bigbench/movie_dialog_same_or_different",
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"bigbench/hyperbaton",
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"bigbench/contextual_parametric_knowledge_conflicts",
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"bigbench/english_proverbs",
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"dream",
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"rumoureval_2019/RumourEval2019",
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"scruples",
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"wouldyourather",
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"recast/recast_megaveridicality",
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"probability_words_nli/reasoning_2hop",
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"nan-nli/joey234--nan-nli",
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"nli_fever",
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"breaking_nli",
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586 |
"robust_nli_is_sd",
|
587 |
"robust_nli_li_ts",
|
588 |
"add_one_rte",
|
|
|
589 |
"imppres/implicature_modals/log",
|
590 |
"imppres/implicature_connectives/log",
|
591 |
"imppres/implicature_quantifiers/log",
|
|
|
592 |
"imppres/implicature_gradable_adjective/log",
|
593 |
+
"imppres/implicature_numerals_2_3/log",
|
594 |
"imppres/implicature_numerals_10_100/log",
|
595 |
+
"imppres/implicature_gradable_verb/log",
|
596 |
"glue_diagnostics/diagnostics",
|
597 |
"hlgd",
|
598 |
"paws/labeled_final",
|
|
|
605 |
"model-written-evals",
|
606 |
"truthful_qa/multiple_choice",
|
607 |
"fig-qa",
|
608 |
+
"bigbench/tracking_shuffled_objects",
|
609 |
+
"bigbench/movie_recommendation",
|
610 |
+
"bigbench/key_value_maps",
|
611 |
+
"bigbench/discourse_marker_prediction",
|
612 |
+
"bigbench/human_organs_senses",
|
613 |
+
"bigbench/physical_intuition",
|
614 |
+
"bigbench/presuppositions_as_nli",
|
615 |
+
"bigbench/undo_permutation",
|
616 |
+
"bigbench/analytic_entailment",
|
617 |
+
"bigbench/abstract_narrative_understanding",
|
618 |
+
"bigbench/general_knowledge",
|
619 |
+
"bigbench/dark_humor_detection",
|
620 |
+
"bigbench/evaluating_information_essentiality",
|
621 |
+
"bigbench/social_support",
|
622 |
+
"bigbench/logical_sequence",
|
623 |
+
"bigbench/understanding_fables",
|
624 |
+
"bigbench/dyck_languages",
|
625 |
+
"bigbench/date_understanding",
|
626 |
+
"bigbench/salient_translation_error_detection",
|
627 |
+
"bigbench/authorship_verification",
|
628 |
+
"bigbench/logical_args",
|
629 |
+
"bigbench/international_phonetic_alphabet_nli",
|
630 |
+
"bigbench/mathematical_induction",
|
631 |
+
"bigbench/causal_judgment",
|
632 |
+
"bigbench/logic_grid_puzzle",
|
633 |
+
"bigbench/suicide_risk",
|
634 |
+
"bigbench/symbol_interpretation",
|
635 |
+
"bigbench/bbq_lite_json",
|
636 |
+
"bigbench/color",
|
637 |
+
"bigbench/english_proverbs",
|
638 |
+
"bigbench/navigate",
|
639 |
+
"bigbench/unit_interpretation",
|
640 |
+
"bigbench/logical_fallacy_detection",
|
641 |
"bigbench/metaphor_boolean",
|
642 |
+
"bigbench/arithmetic",
|
643 |
+
"bigbench/vitaminc_fact_verification",
|
644 |
+
"bigbench/strategyqa",
|
645 |
"bigbench/fantasy_reasoning",
|
646 |
"bigbench/ruin_names",
|
647 |
+
"bigbench/code_line_description",
|
648 |
"bigbench/timedial",
|
649 |
+
"bigbench/hhh_alignment",
|
|
|
|
|
|
|
|
|
|
|
650 |
"bigbench/emojis_emotion_prediction",
|
651 |
+
"bigbench/known_unknowns",
|
652 |
+
"bigbench/question_selection",
|
653 |
+
"bigbench/hyperbaton",
|
654 |
+
"bigbench/analogical_similarity",
|
655 |
+
"bigbench/temporal_sequences",
|
656 |
+
"bigbench/irony_identification",
|
657 |
+
"bigbench/winowhy",
|
658 |
+
"bigbench/novel_concepts",
|
659 |
+
"bigbench/cifar10_classification",
|
660 |
+
"bigbench/logical_deduction",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
661 |
"bigbench/penguins_in_a_table",
|
|
|
662 |
"bigbench/phrase_relatedness",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
663 |
"bigbench/checkmate_in_one",
|
664 |
+
"bigbench/crash_blossom",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
665 |
"bigbench/similarities_abstraction",
|
666 |
+
"bigbench/implicatures",
|
667 |
"bigbench/fact_checker",
|
668 |
+
"bigbench/reasoning_about_colored_objects",
|
669 |
+
"bigbench/physics",
|
670 |
+
"bigbench/elementary_math_qa",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
671 |
"bigbench/entailed_polarity",
|
672 |
+
"bigbench/riddle_sense",
|
|
|
|
|
673 |
"bigbench/mnist_ascii",
|
674 |
+
"bigbench/odd_one_out",
|
675 |
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
676 |
"bigbench/metaphor_understanding",
|
677 |
+
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|
678 |
+
"bigbench/cause_and_effect",
|
679 |
+
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|
680 |
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|
681 |
+
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|
682 |
+
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|
683 |
+
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|
684 |
+
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|
685 |
+
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|
686 |
+
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|
687 |
+
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|
688 |
+
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|
689 |
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|
690 |
+
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|
691 |
+
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|
692 |
+
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|
693 |
+
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|
694 |
+
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|
695 |
+
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|
696 |
+
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|
697 |
+
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|
698 |
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|
699 |
+
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|
700 |
+
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|
701 |
+
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|
702 |
+
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|
703 |
+
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|
704 |
+
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|
705 |
+
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|
706 |
+
"bigbench/intent_recognition",
|
707 |
+
"bigbench/epistemic_reasoning",
|
708 |
"cos_e/v1.0",
|
709 |
"cosmos_qa",
|
710 |
"dream",
|
|
|
743 |
"rumoureval_2019/RumourEval2019",
|
744 |
"ethos/binary",
|
745 |
"ethos/multilabel",
|
746 |
+
"tweet_eval/hate",
|
|
|
|
|
747 |
"tweet_eval/stance_climate",
|
748 |
+
"tweet_eval/irony",
|
749 |
"tweet_eval/stance_abortion",
|
750 |
"tweet_eval/sentiment",
|
751 |
+
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|
752 |
+
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|
753 |
+
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|
754 |
+
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|
755 |
"tweet_eval/emoji",
|
756 |
"tweet_eval/emotion",
|
|
|
|
|
|
|
757 |
"discovery/discovery",
|
|
|
|
|
|
|
758 |
"pragmeval/emobank-dominance",
|
759 |
"pragmeval/emobank-arousal",
|
760 |
+
"pragmeval/emobank-valence",
|
761 |
+
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|
762 |
"pragmeval/squinky-implicature",
|
763 |
"pragmeval/squinky-informativeness",
|
764 |
+
"pragmeval/switchboard",
|
765 |
"pragmeval/mrda",
|
766 |
"pragmeval/verifiability",
|
767 |
"pragmeval/emergent",
|
|
|
|
|
|
|
|
|
768 |
"pragmeval/pdtb",
|
769 |
+
"pragmeval/gum",
|
770 |
+
"pragmeval/persuasiveness-premisetype",
|
771 |
+
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|
772 |
+
"pragmeval/persuasiveness-relevance",
|
773 |
"pragmeval/persuasiveness-specificity",
|
774 |
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|
775 |
"pragmeval/sarcasm",
|
|
|
776 |
"pragmeval/stac",
|
777 |
+
"pragmeval/persuasiveness-claimtype",
|
778 |
+
"silicone/dyda_da",
|
779 |
+
"silicone/dyda_e",
|
780 |
"silicone/sem",
|
|
|
781 |
"silicone/meld_s",
|
782 |
"silicone/meld_e",
|
783 |
"silicone/maptask",
|
784 |
+
"silicone/iemocap",
|
785 |
+
"silicone/oasis",
|
786 |
"lex_glue/eurlex",
|
787 |
"lex_glue/scotus",
|
788 |
"lex_glue/ledgar",
|
|
|
812 |
"go_emotions/simplified",
|
813 |
"scicite",
|
814 |
"liar",
|
|
|
|
|
|
|
815 |
"lexical_relation_classification/BLESS",
|
816 |
+
"lexical_relation_classification/EVALution",
|
817 |
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|
818 |
+
"lexical_relation_classification/ROOT09",
|
819 |
+
"lexical_relation_classification/CogALexV",
|
820 |
"linguisticprobing/bigram_shift",
|
821 |
+
"linguisticprobing/odd_man_out",
|
822 |
+
"linguisticprobing/coordination_inversion",
|
823 |
+
"linguisticprobing/tree_depth",
|
824 |
"linguisticprobing/top_constituents",
|
825 |
"linguisticprobing/sentence_length",
|
826 |
"linguisticprobing/past_present",
|
827 |
"linguisticprobing/obj_number",
|
|
|
828 |
"linguisticprobing/subj_number",
|
|
|
|
|
829 |
"crowdflower/sentiment_nuclear_power",
|
|
|
|
|
|
|
|
|
|
|
|
|
830 |
"crowdflower/political-media-bias",
|
831 |
+
"crowdflower/text_emotion",
|
832 |
"crowdflower/political-media-message",
|
833 |
+
"crowdflower/political-media-audience",
|
834 |
+
"crowdflower/economic-news",
|
835 |
+
"crowdflower/corporate-messaging",
|
836 |
+
"crowdflower/airline-sentiment",
|
837 |
+
"crowdflower/tweet_global_warming",
|
838 |
"ethics/commonsense",
|
839 |
"ethics/deontology",
|
840 |
"ethics/justice",
|
|
|
899 |
"scruples",
|
900 |
"wouldyourather",
|
901 |
"attempto-nli",
|
|
|
902 |
"defeasible-nli/atomic",
|
903 |
+
"defeasible-nli/snli",
|
904 |
"help-nli",
|
905 |
"nli-veridicality-transitivity",
|
906 |
"natural-language-satisfiability",
|
|
|
923 |
"redefine-math",
|
924 |
"puzzte",
|
925 |
"implicatures",
|
|
|
926 |
"race/high",
|
927 |
+
"race/middle",
|
928 |
"race-c",
|
929 |
"spartqa-yn",
|
930 |
"spartqa-mchoice",
|
|
|
952 |
"mindgames",
|
953 |
"universal_dependencies/en_partut/deprel",
|
954 |
"universal_dependencies/en_lines/deprel",
|
|
|
955 |
"universal_dependencies/en_gum/deprel",
|
956 |
+
"universal_dependencies/en_ewt/deprel",
|
957 |
"ambient",
|
958 |
"path-naturalness-prediction",
|
959 |
"civil_comments/toxicity",
|
|
|
1008 |
"winodict",
|
1009 |
"fool-me-twice",
|
1010 |
"monli",
|
1011 |
+
"corr2cause",
|
1012 |
"lsat_qa/all",
|
1013 |
"apt",
|
1014 |
+
"twitter-financial-news-sentiment",
|
1015 |
+
"icl-symbol-tuning-instruct",
|
1016 |
"babi_nli",
|
1017 |
"gen_debiased_nli",
|
1018 |
"imppres/presupposition",
|
pytorch_model.bin
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