diff --git a/examples/script_data_processing/make_hf_dataset.py b/examples/script_data_processing/make_hf_dataset.py
index 7c5c059..db2e968 100644
--- a/examples/script_data_processing/make_hf_dataset.py
+++ b/examples/script_data_processing/make_hf_dataset.py
@@ -14,35 +14,40 @@ def make_json_serializable(input_dict):
 
     return input_dict
 
-
 def make_hf_dataset(source_dir, target_dir, split='test'):
     data_pkl = load_pickle(source_dir)
 
-    data_pkl['dim_process'] = int(data_pkl['dim_process'])
-
-    data_json = dict({'dim_process': int(data_pkl['dim_process'])})
-
-    data_json['event_seqs'] = dict()
+    dim_process = int(data_pkl['dim_process'])
 
-    seq_len = []
+    data_json = []
     for idx, seq in enumerate(data_pkl[split]):
-        data_json['event_seqs'][f'seq_{idx}'] = dict()
-        seq_len.append(len(seq))
+        seq_len = len(seq)
+        time_since_start, time_since_last_event, type_event = [], [], []
         for idx_event, event in enumerate(data_pkl[split][idx]):
-            if idx_event == 0:
+            if idx_event == 0 and event['time_since_start'] > 0:
                 start_timestamp = event['time_since_start']
                 event['time_since_last_event'] -= start_timestamp if event[
                                                                          'time_since_last_event'] == start_timestamp else \
-                event['time_since_last_event']
-            event['time_since_start'] -= start_timestamp
-            data_json['event_seqs'][f'seq_{idx}'][f'event_{idx_event}'] = make_json_serializable(event)
-
-    data_json['num_seqs'] = len(data_pkl[split])
-    data_json['avg_seq_len'] = np.mean(seq_len)
-    data_json['min_seq_len'] = min(seq_len)
-    data_json['max_seq_len'] = max(seq_len)
+                    event['time_since_last_event']
+                event['time_since_start'] -= start_timestamp
+            event = make_json_serializable(event)
+            time_since_start.append(event['time_since_start'])
+            time_since_last_event.append(event['time_since_last_event'])
+            type_event.append(event['type_event'])
+
+        temp_dict = {'dim_process': dim_process,
+                     'seq_idx': idx,
+                     'seq_len': seq_len,
+                     'time_since_start': time_since_start,
+                     'time_since_last_event': time_since_last_event,
+                     'type_event': type_event}
+        data_json.append(temp_dict)
 
     with open(target_dir, "w") as outfile:
         json.dump(data_json, outfile)
 
     return
+
+
+if __name__ == '__main__':
+    make_hf_dataset('../data/taxi/test.pkl', 'test.json', split='test')