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Librarian Bot: Update Hugging Face dataset ID

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This pull request updates the ID of the dataset used to train the model to the new Hub identifier `facebook/anli` (which has been migrated moved from `anli`). We have been working to migrate datasets to their own repositories on the Hub, and this is part of that effort.

Updating the dataset ID in the model card will ensure that the model card is correctly linked to the dataset repository on the Hub. This will also make it easier for people to find your model via the training data used to create it.

This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bot). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to [@davanstrien](https://huggingface.co/davanstrien).

Files changed (1) hide show
  1. README.md +54 -67
README.md CHANGED
@@ -1,101 +1,88 @@
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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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- #- text-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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-
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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 # Required. Example: automatic-speech-recognition
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- name: Natural Language Inference # Optional. Example: Speech Recognition
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  dataset:
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- type: multi_nli # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: MultiNLI-matched # Required. A pretty name for the dataset. Example: Common Voice (French)
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- split: validation_matched # Optional. Example: test
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  metrics:
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- - type: accuracy # Required. Example: wer. Use metric id from https://hf.co/metrics
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- value: 0,912 # Required. Example: 20.90
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- #name: # Optional. Example: Test WER
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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 # Required. Example: automatic-speech-recognition
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- name: Natural Language Inference # Optional. Example: Speech Recognition
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  dataset:
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- type: multi_nli # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: MultiNLI-mismatched # Required. A pretty name for the dataset. Example: Common Voice (French)
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- split: validation_mismatched # Optional. Example: test
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  metrics:
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- - type: accuracy # Required. Example: wer. Use metric id from https://hf.co/metrics
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- value: 0,908 # Required. Example: 20.90
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- #name: # Optional. Example: Test WER
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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 # Required. Example: automatic-speech-recognition
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- name: Natural Language Inference # Optional. Example: Speech Recognition
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  dataset:
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- type: anli # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: ANLI-all # Required. A pretty name for the dataset. Example: Common Voice (French)
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- split: test_r1+test_r2+test_r3 # Optional. Example: test
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  metrics:
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- - type: accuracy # Required. Example: wer. Use metric id from https://hf.co/metrics
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- value: 0,702 # Required. Example: 20.90
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- #name: # Optional. Example: Test WER
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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 # Required. Example: automatic-speech-recognition
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- name: Natural Language Inference # Optional. Example: Speech Recognition
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  dataset:
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- type: anli # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: ANLI-r3 # Required. A pretty name for the dataset. Example: Common Voice (French)
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- split: test_r3 # Optional. Example: test
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  metrics:
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- - type: accuracy # Required. Example: wer. Use metric id from https://hf.co/metrics
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- value: 0,64 # Required. Example: 20.90
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- #name: # Optional. Example: Test WER
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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 # Required. Example: automatic-speech-recognition
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- name: Natural Language Inference # Optional. Example: Speech Recognition
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  dataset:
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- type: alisawuffles/WANLI # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: WANLI # Required. A pretty name for the dataset. Example: Common Voice (French)
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- split: test # Optional. Example: test
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  metrics:
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- - type: accuracy # Required. Example: wer. Use metric id from https://hf.co/metrics
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- value: 0,77 # Required. Example: 20.90
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- #name: # Optional. Example: Test WER
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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 # Required. Example: automatic-speech-recognition
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- name: Natural Language Inference # Optional. Example: Speech Recognition
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  dataset:
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- type: lingnli # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
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- name: LingNLI # Required. A pretty name for the dataset. Example: Common Voice (French)
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- split: test # Optional. Example: test
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  metrics:
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- - type: accuracy # Required. Example: wer. Use metric id from https://hf.co/metrics
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- value: 0,87 # Required. Example: 20.90
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- #name: # Optional. Example: Test WER
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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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-
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-
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  ---
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  # DeBERTa-v3-large-mnli-fever-anli-ling-wanli
 
1
  ---
2
+ language:
3
  - en
4
+ license: mit
5
  tags:
6
  - text-classification
7
  - zero-shot-classification
 
 
 
8
  datasets:
9
  - multi_nli
10
+ - facebook/anli
11
  - fever
12
  - lingnli
13
  - alisawuffles/WANLI
14
+ metrics:
15
+ - accuracy
16
  pipeline_tag: zero-shot-classification
17
+ model-index:
 
 
 
 
18
  - name: DeBERTa-v3-large-mnli-fever-anli-ling-wanli
19
  results:
20
  - task:
21
+ type: text-classification
22
+ name: Natural Language Inference
23
  dataset:
24
+ name: MultiNLI-matched
25
+ type: multi_nli
26
+ split: validation_matched
27
  metrics:
28
+ - type: accuracy
29
+ value: 0,912
30
+ verified: false
 
31
  - task:
32
+ type: text-classification
33
+ name: Natural Language Inference
34
  dataset:
35
+ name: MultiNLI-mismatched
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+ type: multi_nli
37
+ split: validation_mismatched
38
  metrics:
39
+ - type: accuracy
40
+ value: 0,908
41
+ verified: false
 
42
  - task:
43
+ type: text-classification
44
+ name: Natural Language Inference
45
  dataset:
46
+ name: ANLI-all
47
+ type: anli
48
+ split: test_r1+test_r2+test_r3
49
  metrics:
50
+ - type: accuracy
51
+ value: 0,702
52
+ verified: false
 
53
  - task:
54
+ type: text-classification
55
+ name: Natural Language Inference
56
  dataset:
57
+ name: ANLI-r3
58
+ type: anli
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+ split: test_r3
60
  metrics:
61
+ - type: accuracy
62
+ value: 0,64
63
+ verified: false
 
64
  - task:
65
+ type: text-classification
66
+ name: Natural Language Inference
67
  dataset:
68
+ name: WANLI
69
+ type: alisawuffles/WANLI
70
+ split: test
71
  metrics:
72
+ - type: accuracy
73
+ value: 0,77
74
+ verified: false
 
75
  - task:
76
+ type: text-classification
77
+ name: Natural Language Inference
78
  dataset:
79
+ name: LingNLI
80
+ type: lingnli
81
+ split: test
82
  metrics:
83
+ - type: accuracy
84
+ value: 0,87
85
+ verified: false
 
 
 
 
86
  ---
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  # DeBERTa-v3-large-mnli-fever-anli-ling-wanli