example fix

README.md

@@ -34,7 +34,7 @@ predictions = ["the cat is on the mat", "hello there"]
 references = ["the cat is on the mat", "hello there"]
 results = rougeraw.compute(predictions=predictions, references=references)
 print(results)
-{'1_precision': 1.0, '1_recall': 1.0, '1_fmeasure': 1.0, '2_precision': 1.0, '2_recall': 1.0, '2_fmeasure': 1.0, 'l_precision': 1.0, 'l_recall': 1.0, 'l_fmeasure': 1.0}
+{'1_low_precision': 1.0, '1_low_recall': 1.0, '1_low_fmeasure': 1.0, '1_mid_precision': 1.0, '1_mid_recall': 1.0, '1_mid_fmeasure': 1.0, '1_high_precision': 1.0, '1_high_recall': 1.0, '1_high_fmeasure': 1.0, '2_low_precision': 1.0, '2_low_recall': 1.0, '2_low_fmeasure': 1.0, '2_mid_precision': 1.0, '2_mid_recall': 1.0, '2_mid_fmeasure': 1.0, '2_high_precision': 1.0, '2_high_recall': 1.0, '2_high_fmeasure': 1.0, 'L_low_precision': 1.0, 'L_low_recall': 1.0, 'L_low_fmeasure': 1.0, 'L_mid_precision': 1.0, 'L_mid_recall': 1.0, 'L_mid_fmeasure': 1.0, 'L_high_precision': 1.0, 'L_high_recall': 1.0, 'L_high_fmeasure': 1.0}
 ```
 
 
@@ -50,13 +50,13 @@ There are precision, recall, F1 values for rougeraw-1, rougeraw-2 and rougeraw-l
 
 Key format: 
 ```
-{1|2|l}_{low|mid|high}_{precision|recall|fmeasure}
+{1|2|L}_{low|mid|high}_{precision|recall|fmeasure}
 e.g.: 1_low_precision
 ```
 
 If aggregate is False the format is:
 ```
-{1|2|l}_{precision|recall|fmeasure}
+{1|2|L}_{precision|recall|fmeasure}
 e.g.: 1_precision
 ```
 

rouge_raw.py

@@ -380,9 +380,9 @@ class RougeRaw(evaluate.Metric):
                 "2_precision": res["2"].p,
                 "2_recall": res["2"].r,
                 "2_fmeasure": res["2"].f,
-                "l_precision": res["L"].p,
-                "l_recall": res["L"].r,
-                "l_fmeasure": res["L"].f,
+                "L_precision": res["L"].p,
+                "L_recall": res["L"].r,
+                "L_fmeasure": res["L"].f,
             }
 
         if select is not None: