Update README.md

README.md

@@ -1,13 +1,31 @@
+---
+
 ---
 language: 
+- multilingual
 - en
 tags:
-- text-classification
 - zero-shot-classification
+- text-classification
+- nli
+- pytorch
 metrics:
 - accuracy
+datasets:
+- mnli
+- xnli
+- anli
+license: mit
 pipeline_tag: zero-shot-classification
-
+widget:
+- text: "De pugna erat fantastic. Nam Crixo decem quam dilexit et praeciderunt caput aemulus."
+  candidate_labels: "violent, peaceful"
+- text: "La película empezaba bien pero terminó siendo un desastre." 
+  candidate_labels: "positivo, negativo, neutral"
+- text: "La película empezó siendo un desastre pero en general fue bien." 
+  candidate_labels: "positivo, negativo, neutral"
+- text: "¿A quién vas a votar en 2020?"
+  candidate_labels: "Europa, elecciones, política, ciencia, deportes"
 ---
 # Multilingual mDeBERTa-v3-base-mnli-xnli
 ## Model description
@@ -51,7 +69,11 @@ training_args = TrainingArguments(
 ### Eval results
 The model was evaluated using the matched test set and achieves 0.90 accuracy.
 
+average | ar | bg | de | el | en | es | fr | hi | ru | sw | th | tr | ur | vu | zh 
+---------|----------|---------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------|----------
+0.808 | 0.802 | 0.829 | 0.825 | 0.826 | 0.883 | 0.845 | 0.834 | 0.771 | 0.813 | 0.748 | 0.793 | 0.807 | 0.740 | 0.795 | 0.8116
 
+{'ar': 0.8017964071856287, 'bg': 0.8287425149700599, 'de': 0.8253493013972056, 'el': 0.8267465069860279, 'en': 0.8830339321357286, 'es': 0.8449101796407186, 'fr': 0.8343313373253493, 'hi': 0.7712574850299401, 'ru': 0.8127744510978044, 'sw': 0.7483033932135729, 'th': 0.792814371257485, 'tr': 0.8065868263473054, 'ur': 0.7403193612774451, 'vi': 0.7954091816367266, 'zh': 0.8115768463073852}
 
 ## Limitations and bias
 Please consult the original DeBERTa-V3 paper and literature on different NLI datasets for potential biases.