Update README.md

README.md

@@ -100,6 +100,8 @@ The model was evaluated using the XNLI test sets on 15 languages: English (en),
 |[multilingual-e5-base-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-base-xnli-anli)|0.811|0.711|0.751|0.759|0.746|0.778|0.765|0.685|0.728|0.662|0.705|0.716|0.683|0.736|0.740|
 |[multilingual-e5-large-xnli](https://huggingface.co/mjwong/multilingual-e5-large-xnli)|0.867|0.791|0.832|0.825|0.823|0.837|0.824|0.778|0.806|0.749|0.787|0.793|0.738|0.813|0.808|
 |[multilingual-e5-large-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-large-xnli-anli)|0.865|0.765|0.811|0.811|0.795|0.823|0.816|0.743|0.785|0.713|0.765|0.774|0.706|0.788|0.787|
+|[multilingual-e5-large-instruct-xnli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli)|0.864|0.793|0.839|0.821|0.824|0.837|0.823|0.770|0.810|0.744|0.784|0.791|0.716|0.807|0.807|
+|[multilingual-e5-large-instruct-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli-anli)|0.861|0.780|0.816|0.808|0.806|0.825|0.816|0.758|0.799|0.727|0.775|0.780|0.721|0.787|0.795|
 
 The model was also evaluated using the dev sets for MultiNLI and test sets for ANLI. The metric used is accuracy.
 
@@ -109,6 +111,8 @@ The model was also evaluated using the dev sets for MultiNLI and test sets for A
 |[multilingual-e5-base-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-base-xnli-anli)|0.814|0.811|0.588|0.437|0.439|
 |[multilingual-e5-large-xnli](https://huggingface.co/mjwong/multilingual-e5-large-xnli)|0.865|0.865|0.312|0.316|0.300|
 |[multilingual-e5-large-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-large-xnli-anli)|0.863|0.863|0.623|0.456|0.455|
+|[multilingual-e5-large-instruct-xnli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli)|0.867|0.866|0.341|0.330|0.323|
+|[multilingual-e5-large-instruct-xnli-anli](https://huggingface.co/mjwong/multilingual-e5-large-instruct-xnli-anli)|0.862|0.862|0.615|0.459|0.462|
 
 ### Training hyperparameters