Librarian Bot: Update Hugging Face dataset ID

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).

README.md

@@ -1,5 +1,5 @@
 ---
-language: 
+language:
 - multilingual
 - zh
 - ja
@@ -27,118 +27,106 @@ language:
 - he
 - sw
 - ps
+license: mit
 tags:
 - zero-shot-classification
 - text-classification
 - nli
 - pytorch
-license: mit
-metrics:
-- accuracy
 datasets:
 - MoritzLaurer/multilingual-NLI-26lang-2mil7
 - xnli
 - multi_nli
-- anli
+- facebook/anli
 - fever
 - lingnli
 - alisawuffles/WANLI
+metrics:
+- accuracy
 pipeline_tag: zero-shot-classification
-#- text-classification
 widget:
-- text: "Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU"
-  candidate_labels: "politics, economy, entertainment, environment"
-
-model-index:  # info: https://github.com/huggingface/hub-docs/blame/main/modelcard.md
+- text: Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU
+  candidate_labels: politics, economy, entertainment, environment
+model-index:
 - name: DeBERTa-v3-base-xnli-multilingual-nli-2mil7
   results:
   - task:
-      type: text-classification             # Required. Example: automatic-speech-recognition
-      name: Natural Language Inference             # Optional. Example: Speech Recognition
+      type: text-classification
+      name: Natural Language Inference
     dataset:
-      type: multi_nli          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: MultiNLI-matched         # Required. A pretty name for the dataset. Example: Common Voice (French)
-      split: validation_matched        # Optional. Example: test
+      name: MultiNLI-matched
+      type: multi_nli
+      split: validation_matched
     metrics:
-      - type: accuracy         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0,857      # Required. Example: 20.90
-        #name:           # Optional. Example: Test WER
-        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+    - type: accuracy
+      value: 0,857
+      verified: false
   - task:
-      type: text-classification             # Required. Example: automatic-speech-recognition
-      name: Natural Language Inference             # Optional. Example: Speech Recognition
+      type: text-classification
+      name: Natural Language Inference
     dataset:
-      type: multi_nli          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: MultiNLI-mismatched         # Required. A pretty name for the dataset. Example: Common Voice (French)
-      split: validation_mismatched        # Optional. Example: test
+      name: MultiNLI-mismatched
+      type: multi_nli
+      split: validation_mismatched
     metrics:
-      - type: accuracy         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0,856       # Required. Example: 20.90
-        #name:           # Optional. Example: Test WER
-        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+    - type: accuracy
+      value: 0,856
+      verified: false
   - task:
-      type: text-classification             # Required. Example: automatic-speech-recognition
-      name: Natural Language Inference             # Optional. Example: Speech Recognition
+      type: text-classification
+      name: Natural Language Inference
     dataset:
-      type: anli          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: ANLI-all         # Required. A pretty name for the dataset. Example: Common Voice (French)
-      split: test_r1+test_r2+test_r3        # Optional. Example: test
+      name: ANLI-all
+      type: anli
+      split: test_r1+test_r2+test_r3
     metrics:
-      - type: accuracy         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0,537       # Required. Example: 20.90
-        #name:           # Optional. Example: Test WER
-        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+    - type: accuracy
+      value: 0,537
+      verified: false
   - task:
-      type: text-classification             # Required. Example: automatic-speech-recognition
-      name: Natural Language Inference             # Optional. Example: Speech Recognition
+      type: text-classification
+      name: Natural Language Inference
     dataset:
-      type: anli          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: ANLI-r3         # Required. A pretty name for the dataset. Example: Common Voice (French)
-      split: test_r3        # Optional. Example: test
+      name: ANLI-r3
+      type: anli
+      split: test_r3
     metrics:
-      - type: accuracy         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0,497       # Required. Example: 20.90
-        #name:           # Optional. Example: Test WER
-        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+    - type: accuracy
+      value: 0,497
+      verified: false
   - task:
-      type: text-classification             # Required. Example: automatic-speech-recognition
-      name: Natural Language Inference             # Optional. Example: Speech Recognition
+      type: text-classification
+      name: Natural Language Inference
     dataset:
-      type: alisawuffles/WANLI          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: WANLI         # Required. A pretty name for the dataset. Example: Common Voice (French)
-      split: test        # Optional. Example: test
+      name: WANLI
+      type: alisawuffles/WANLI
+      split: test
     metrics:
-      - type: accuracy         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0,732       # Required. Example: 20.90
-        #name:           # Optional. Example: Test WER
-        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+    - type: accuracy
+      value: 0,732
+      verified: false
   - task:
-      type: text-classification             # Required. Example: automatic-speech-recognition
-      name: Natural Language Inference             # Optional. Example: Speech Recognition
+      type: text-classification
+      name: Natural Language Inference
     dataset:
-      type: lingnli          # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: LingNLI         # Required. A pretty name for the dataset. Example: Common Voice (French)
-      split: test        # Optional. Example: test
+      name: LingNLI
+      type: lingnli
+      split: test
     metrics:
-      - type: accuracy         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0,788      # Required. Example: 20.90
-        #name:           # Optional. Example: Test WER
-        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
+    - type: accuracy
+      value: 0,788
+      verified: false
   - task:
-      type: text-classification             # Required. Example: automatic-speech-recognition
-      name: Natural Language Inference             # Optional. Example: Speech Recognition
+      type: text-classification
+      name: Natural Language Inference
     dataset:
-      type: fever-nli  # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
-      name: fever-nli  # Required. A pretty name for the dataset. Example: Common Voice (French)
-      split: test        # Optional. Example: test
+      name: fever-nli
+      type: fever-nli
+      split: test
     metrics:
-      - type: accuracy         # Required. Example: wer. Use metric id from https://hf.co/metrics
-        value: 0,761     # Required. Example: 20.90
-        #name:           # Optional. Example: Test WER
-        verified: false              # Optional. If true, indicates that evaluation was generated by Hugging Face (vs. self-reported).
-
-
-
+    - type: accuracy
+      value: 0,761
+      verified: false
 ---
 # Model card for mDeBERTa-v3-base-xnli-multilingual-nli-2mil7