Librarian Bot: Update Hugging Face dataset ID
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by
librarian-bot
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README.md
CHANGED
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---
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language:
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- en
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tags:
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- text-classification
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- zero-shot-classification
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license: mit
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metrics:
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- accuracy
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datasets:
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- multi_nli
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- anli
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- fever
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- lingnli
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- alisawuffles/WANLI
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pipeline_tag: zero-shot-classification
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#widget:
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#- text: "I first thought that I really liked the movie, but upon second thought it was actually disappointing. [SEP] The movie was not good."
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model-index: # info: https://github.com/huggingface/hub-docs/blame/main/modelcard.md
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- name: DeBERTa-v3-large-mnli-fever-anli-ling-wanli
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results:
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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split: validation_matched
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metrics:
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verified: false # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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split: validation_mismatched
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metrics:
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-
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verified: false # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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split: test_r1+test_r2+test_r3
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metrics:
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verified: false # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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split: test_r3
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metrics:
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-
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verified: false # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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split: test
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metrics:
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verified: false # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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split: test
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metrics:
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verified: false # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
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---
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# DeBERTa-v3-large-mnli-fever-anli-ling-wanli
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---
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language:
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- en
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license: mit
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tags:
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- text-classification
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- zero-shot-classification
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datasets:
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- multi_nli
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- facebook/anli
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- fever
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- lingnli
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- alisawuffles/WANLI
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metrics:
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- accuracy
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pipeline_tag: zero-shot-classification
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model-index:
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- name: DeBERTa-v3-large-mnli-fever-anli-ling-wanli
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results:
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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name: MultiNLI-matched
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type: multi_nli
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split: validation_matched
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metrics:
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- type: accuracy
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value: 0,912
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verified: false
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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name: MultiNLI-mismatched
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type: multi_nli
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split: validation_mismatched
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metrics:
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- type: accuracy
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value: 0,908
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verified: false
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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name: ANLI-all
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type: anli
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split: test_r1+test_r2+test_r3
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metrics:
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- type: accuracy
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value: 0,702
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verified: false
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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name: ANLI-r3
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type: anli
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split: test_r3
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metrics:
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- type: accuracy
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value: 0,64
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verified: false
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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name: WANLI
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type: alisawuffles/WANLI
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split: test
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metrics:
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- type: accuracy
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value: 0,77
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verified: false
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- task:
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type: text-classification
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name: Natural Language Inference
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dataset:
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name: LingNLI
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type: lingnli
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split: test
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metrics:
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- type: accuracy
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value: 0,87
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verified: false
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---
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# DeBERTa-v3-large-mnli-fever-anli-ling-wanli
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