Update README.md

README.md

@@ -229,6 +229,28 @@ All models trained with max length 512 and batch size 8. The accuracy values in
 <caption>Table 4. Results for PAWS-X.</caption>
 </figure>
 
+**CNLI** 
+All models trained with max length 256 and batch size 16.
+
+<figure>
+ 
+| Model                                              | Accuracy |  
+|----------------------------------------------------|----------|
+| bert-base-multilingual-cased                       | WIP   |
+| dccuchile/bert-base-spanish-wwm-cased              | WIP   | 
+| BSC-TeMU/roberta-base-bne                          | WIP   |  
+| flax-community/bertin-roberta-large-spanish        | WIP   |  
+| bertin-project/bertin-roberta-base-spanish         | WIP   |  
+| bertin-project/bertin-base-random                  | 0.7745   | 
+| bertin-project/bertin-base-stepwise                | 0.7820   |   
+| bertin-project/bertin-base-gaussian                | **0.7942**   |  
+| bertin-project/bertin-base-random-exp-512seqlen    | 0.7723   |  
+| bertin-project/bertin-base-gaussian-exp-512seqlen  | 0.7878   |
+
+
+<caption>Table 5. Results for CNLI.</caption>
+</figure>
+
 # Conclusions
 
 With roughly 10 days worth of access to 3xTPUv3-8, we have achieved remarkable results surpassing previous state of the art in a few tasks, and even improving document classification on models trained in massive supercomputers with very large—private—and highly curated datasets.