write finetune result to csv

convlab/base_models/t5/key2gen/evaluate.py

@@ -4,6 +4,7 @@ import json
 from tqdm import tqdm
 from datasets import load_metric
 import numpy as np
+import csv
 
 def evaluate(filename, metric):
     """
@@ -50,7 +51,8 @@ if __name__ == '__main__':
     args = parser.parse_args()
     print(args)
     
-    tables = []
+    table = []
+    fieldnames = []
     for task_name in tqdm(args.tasks, desc='tasks'):
         metric = load_metric("metric.py", task_name)
         dataset_name = task_name if task_name != "nlg" else "multiwoz21"
@@ -78,8 +80,17 @@ if __name__ == '__main__':
                         "model": f"{model_name}",
                         **avg_result(results)
                     }
-                    tables.append(res)
-                    # print(res)
-    res = tabulate(tables, headers='keys', tablefmt='github')
+                    table.append(res)
+                    for k in res:
+                        if k not in fieldnames:
+                            fieldnames.append(k)
+                    
+    res = tabulate(table, headers='keys', tablefmt='github')
     with open(f'eval_results.txt', 'w', encoding='utf-8') as f:
         print(res, file=f)
+    with open('eval_results.csv', 'w', newline='') as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+
+        writer.writeheader()
+        for res in table:
+            writer.writerow(res)