Update README.md

README.md

@@ -6,12 +6,14 @@ tags:
 metrics:
 - bleu
 - rouge
+- meteor
 model-index:
 - name: mbart-large-50-English_Spanish_Translation
   results: []
 language:
 - en
 - es
+pipeline_tag: translation
 ---
 
 # mbart-large-50-English_Spanish_Translation
@@ -20,8 +22,12 @@ This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingf
 It achieves the following results on the evaluation set:
 - Loss: 1.0290
 - Bleu: 41.4437
-- Rouge: {'rouge1': 0.6751402780531002, 'rouge2': 0.49769602014143044, 'rougeL': 0.6371513427059108, 'rougeLsum': 0.6376403149816605}
-- Meteor: {'meteor': 0.6479226630466496}
+- Rouge:
+  - Rouge1: 0.6751402780531002
+  - Rouge2: 0.49769602014143044
+  - RougeL: 0.6371513427059108
+  - RougeLsum: 0.6376403149816605
+- Meteor: 0.6479226630466496
 
 ## Model description
 
@@ -52,10 +58,10 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Bleu    | Rouge                                                                                                                        | Meteor                         |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|:----------------------------------------------------------------------------------------------------------------------------:|:------------------------------:|
-| 1.5608        | 1.0   | 900  | 1.0899          | 39.9184 | {'rouge1': 0.6645461901016299, 'rouge2': 0.48457734138815345, 'rougeL': 0.6254335531454508, 'rougeLsum': 0.6258737583448748} | {'meteor': 0.6376166612731494} |
-| 0.9734        | 2.0   | 1800 | 1.0290          | 41.4436 | {'rouge1': 0.6751348620702116, 'rouge2': 0.4976855704059807, 'rougeL': 0.6371345376462452, 'rougeLsum': 0.6376186633843448}  | {'meteor': 0.6479188510808377} |
+| Training Loss | Epoch | Step | Validation Loss | Bleu    | Rouge1 | Rouge2 | RougeL | RougeLsum | Meteor |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:-----:|:-----:|:-----:|:-----:|:-----:|
+| 1.5608        | 1.0   | 900  | 1.0899          | 39.9184 | 0.6645 | 0.4846 | 0.6254 | 0.6259 | 0.6376 |
+| 0.9734        | 2.0   | 1800 | 1.0290          | 41.4436 | 0.6751 | 0.4977 | 0.6371 | 0.6376 | 0.6479 |
 
 
 ### Framework versions