Add Japanese translation to the labels

src/about.py

@@ -12,19 +12,19 @@ class Task:
 # ---------------------------------------------------
 class Tasks(Enum):
     AVG = Task("scores", "AVG", "AVG")
-    CG = Task("scores", "CG", "CG")  # Code Generation - コード生成
-    EL = Task("scores", "EL", "EL")  # Entity Linking - エンティティリンキング
-    FA = Task("scores", "FA", "FA")  # Fundamental Analysis - 基礎分析
-    HE = Task("scores", "HE", "HE")  # Human Examination - 人間の評価
-    MC = Task("scores", "MC", "MC")  # Multiple Choice question answering - 多肢選択式質問応答
-    MR = Task("scores", "MR", "MR")  # Mathematical Reasoning - 数学的推論
-    MT = Task("scores", "MT", "MT")  # Machine Translation - 機械翻訳
-    NLI = Task("scores", "NLI", "NLI")  # Natural Language Inference - 自然言語推論
-    QA = Task("scores", "QA", "QA")  # Question Answering - 質問応答
-    RC = Task("scores", "RC", "RC")  # Reading Comprehension - 読解力
-    SUM = Task("scores", "SUM", "SUM")  # Summarization - 要約
-    jsts_pearson = Task("scores", "jsts_pearson", "JSTS (Pearson)")  # Semantic Textual Similarity - 意味的類似度
-    jsts_spearman = Task("scores", "jsts_spearman", "JSTS (Spearman)")  # Semantic Textual Similarity - 意味的類似度
+    CG = Task("scores", "CG", "CG - コード生成")  # Code Generation - コード生成
+    EL = Task("scores", "EL", "EL - エンティティリンキング")  # Entity Linking - エンティティリンキング
+    FA = Task("scores", "FA", "FA - 基礎分析")  # Fundamental Analysis - 基礎分析
+    HE = Task("scores", "HE", "HE - 人間の評価")  # Human Examination - 人間の評価
+    MC = Task("scores", "MC", "MC - 多肢選択式質問応答")  # Multiple Choice question answering - 多肢選択式質問応答
+    MR = Task("scores", "MR", "MR - 数学的推論")  # Mathematical Reasoning - 数学的推論
+    MT = Task("scores", "MT", "MT - 機械翻訳")  # Machine Translation - 機械翻訳
+    NLI = Task("scores", "NLI", "NLI - 自然言語推論")  # Natural Language Inference - 自然言語推論
+    QA = Task("scores", "QA", "QA - 質問応答")  # Question Answering - 質問応答
+    RC = Task("scores", "RC", "RC - 読解力")  # Reading Comprehension - 読解力
+    SUM = Task("scores", "SUM", "SUM - 要約")  # Summarization - 要約
+    jsts_pearson = Task("scores", "jsts_pearson", "JSTS (Pearson) - 意味的類似度")  # Semantic Textual Similarity - 意味的類似度
+    jsts_spearman = Task("scores", "jsts_spearman", "JSTS (Spearman) - 意味的類似度")  # Semantic Textual Similarity - 意味的類似度
 
 
 NUM_FEWSHOT = 0 # Change with your few shot