updated readme

README.md

@@ -1,288 +1,3 @@
----
-license: apache-2.0
-language: en
-tags:
-- deberta-v3-base
-- deberta-v3
-- deberta
-- text-classification
-- nli
-- natural-language-inference
-- multitask
-- multi-task
-- pipeline
-- extreme-multi-task
-- extreme-mtl
-- tasksource
-- zero-shot
-- rlhf
-model-index:
-- name: deberta-v3-base-tasksource-nli
-  results:
-  - task:
-      type: text-classification
-      name: Text Classification
-    dataset:
-      name: glue
-      type: glue
-      config: rte
-      split: validation
-    metrics:
-    - type: accuracy
-      value: 0.89
-  - task:
-      type: natural-language-inference
-      name: Natural Language Inference
-    dataset:
-      name: anli-r3
-      type: anli
-      config: plain_text
-      split: validation
-    metrics:
-      - type: accuracy
-        value: 0.52
-        name: Accuracy
-datasets:
-- glue
-- super_glue
-- anli
-- tasksource/babi_nli
-- sick
-- snli
-- scitail
-- OpenAssistant/oasst1
-- universal_dependencies
-- hans
-- qbao775/PARARULE-Plus
-- alisawuffles/WANLI
-- metaeval/recast
-- sileod/probability_words_nli
-- joey234/nan-nli
-- pietrolesci/nli_fever
-- pietrolesci/breaking_nli
-- pietrolesci/conj_nli
-- pietrolesci/fracas
-- pietrolesci/dialogue_nli
-- pietrolesci/mpe
-- pietrolesci/dnc
-- pietrolesci/gpt3_nli
-- pietrolesci/recast_white
-- pietrolesci/joci
-- martn-nguyen/contrast_nli
-- pietrolesci/robust_nli
-- pietrolesci/robust_nli_is_sd
-- pietrolesci/robust_nli_li_ts
-- pietrolesci/gen_debiased_nli
-- pietrolesci/add_one_rte
-- metaeval/imppres
-- pietrolesci/glue_diagnostics
-- hlgd
-- PolyAI/banking77
-- paws
-- quora
-- medical_questions_pairs
-- conll2003
-- nlpaueb/finer-139
-- Anthropic/hh-rlhf
-- Anthropic/model-written-evals
-- truthful_qa
-- nightingal3/fig-qa
-- tasksource/bigbench
-- blimp
-- cos_e
-- cosmos_qa
-- dream
-- openbookqa
-- qasc
-- quartz
-- quail
-- head_qa
-- sciq
-- social_i_qa
-- wiki_hop
-- wiqa
-- piqa
-- hellaswag
-- pkavumba/balanced-copa
-- 12ml/e-CARE
-- art
-- tasksource/mmlu
-- winogrande
-- codah
-- ai2_arc
-- definite_pronoun_resolution
-- swag
-- math_qa
-- metaeval/utilitarianism
-- mteb/amazon_counterfactual
-- SetFit/insincere-questions
-- SetFit/toxic_conversations
-- turingbench/TuringBench
-- trec
-- tals/vitaminc
-- hope_edi
-- strombergnlp/rumoureval_2019
-- ethos
-- tweet_eval
-- discovery
-- pragmeval
-- silicone
-- lex_glue
-- papluca/language-identification
-- imdb
-- rotten_tomatoes
-- ag_news
-- yelp_review_full
-- financial_phrasebank
-- poem_sentiment
-- dbpedia_14
-- amazon_polarity
-- app_reviews
-- hate_speech18
-- sms_spam
-- humicroedit
-- snips_built_in_intents
-- banking77
-- hate_speech_offensive
-- yahoo_answers_topics
-- pacovaldez/stackoverflow-questions
-- zapsdcn/hyperpartisan_news
-- zapsdcn/sciie
-- zapsdcn/citation_intent
-- go_emotions
-- allenai/scicite
-- liar
-- relbert/lexical_relation_classification
-- metaeval/linguisticprobing
-- tasksource/crowdflower
-- metaeval/ethics
-- emo
-- google_wellformed_query
-- tweets_hate_speech_detection
-- has_part
-- wnut_17
-- ncbi_disease
-- acronym_identification
-- jnlpba
-- species_800
-- SpeedOfMagic/ontonotes_english
-- blog_authorship_corpus
-- launch/open_question_type
-- health_fact
-- commonsense_qa
-- mc_taco
-- ade_corpus_v2
-- prajjwal1/discosense
-- circa
-- PiC/phrase_similarity
-- copenlu/scientific-exaggeration-detection
-- quarel
-- mwong/fever-evidence-related
-- numer_sense
-- dynabench/dynasent
-- raquiba/Sarcasm_News_Headline
-- sem_eval_2010_task_8
-- demo-org/auditor_review
-- medmcqa
-- aqua_rat
-- RuyuanWan/Dynasent_Disagreement
-- RuyuanWan/Politeness_Disagreement
-- RuyuanWan/SBIC_Disagreement
-- RuyuanWan/SChem_Disagreement
-- RuyuanWan/Dilemmas_Disagreement
-- lucasmccabe/logiqa
-- wiki_qa
-- metaeval/cycic_classification
-- metaeval/cycic_multiplechoice
-- metaeval/sts-companion
-- metaeval/commonsense_qa_2.0
-- metaeval/lingnli
-- metaeval/monotonicity-entailment
-- metaeval/arct
-- metaeval/scinli
-- metaeval/naturallogic
-- onestop_qa
-- demelin/moral_stories
-- corypaik/prost
-- aps/dynahate
-- metaeval/syntactic-augmentation-nli
-- metaeval/autotnli
-- lasha-nlp/CONDAQA
-- openai/webgpt_comparisons
-- Dahoas/synthetic-instruct-gptj-pairwise
-- metaeval/scruples
-- metaeval/wouldyourather
-- sileod/attempto-nli
-- metaeval/defeasible-nli
-- metaeval/help-nli
-- metaeval/nli-veridicality-transitivity
-- metaeval/natural-language-satisfiability
-- metaeval/lonli
-- tasksource/dadc-limit-nli
-- ColumbiaNLP/FLUTE
-- metaeval/strategy-qa
-- openai/summarize_from_feedback
-- tasksource/folio
-- metaeval/tomi-nli
-- metaeval/avicenna
-- stanfordnlp/SHP
-- GBaker/MedQA-USMLE-4-options-hf
-- GBaker/MedQA-USMLE-4-options
-- sileod/wikimedqa
-- declare-lab/cicero
-- amydeng2000/CREAK
-- metaeval/mutual
-- inverse-scaling/NeQA
-- inverse-scaling/quote-repetition
-- inverse-scaling/redefine-math
-- tasksource/puzzte
-- metaeval/implicatures
-- race
-- metaeval/spartqa-yn
-- metaeval/spartqa-mchoice
-- metaeval/temporal-nli
-- metaeval/ScienceQA_text_only
-- AndyChiang/cloth
-- metaeval/logiqa-2.0-nli
-- tasksource/oasst1_dense_flat
-- metaeval/boolq-natural-perturbations
-- metaeval/path-naturalness-prediction
-- riddle_sense
-- Jiangjie/ekar_english
-- metaeval/implicit-hate-stg1
-- metaeval/chaos-mnli-ambiguity
-- IlyaGusev/headline_cause
-- metaeval/race-c
-- metaeval/equate
-- metaeval/ambient
-- AndyChiang/dgen
-- metaeval/clcd-english
-- civil_comments
-- metaeval/acceptability-prediction
-- maximedb/twentyquestions
-- metaeval/counterfactually-augmented-snli
-- tasksource/I2D2
-- sileod/mindgames
-- metaeval/counterfactually-augmented-imdb
-- metaeval/cnli
-- metaeval/reclor
-- tasksource/oasst1_pairwise_rlhf_reward
-- tasksource/zero-shot-label-nli
-- webis/args_me
-- webis/Touche23-ValueEval
-- tasksource/starcon
-- tasksource/ruletaker
-- lighteval/lsat_qa
-- tasksource/ConTRoL-nli
-- tasksource/tracie
-- tasksource/sherliic
-- tasksource/sen-making
-metrics:
-- accuracy
-library_name: transformers
-pipeline_tag: zero-shot-classification
----
-
 # Model Card for DeBERTa-v3-base-tasksource-nli
 
 This is [DeBERTa-v3-base](https://hf.co/microsoft/deberta-v3-base) fine-tuned with multi-task learning on 600 tasks.