init

data/tweet_nerd_new/validation.jsonl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ca3f9f434dce5156178748a4d8f8ae48457a1205761869f64ce774af56118186
-size 1230500
+oid sha256:291ea200cebc1446707138bbc7ebf2257589a8af99cb3b07ac5cde1032d6ef8d
+size 1425119

experiments/main.sh

@@ -7,7 +7,7 @@ MODEL="cardiffnlp/twitter-roberta-base-2022-154m"
 
 # topic, ner [hawk]
 MODEL="vinai/bertweet-base"
-# topic [hawk], ner [ukri]
+# topic [hawk], ner
 MODEL="jhu-clsp/bernice"
 
 

process/tweet_nerd.py

@@ -23,13 +23,13 @@ while True:
     if dist_date[:n].sum() > total_n/2:
         break
 split_date = dist_date.index[n]
-input(split_date)
+print(split_date)
 
 train = df[df["date_dt"] <= split_date]
 test = df[df["date_dt"] > split_date]
 print(train.date_dt.min(), train.date_dt.max())
 print(test.date_dt.min(), test.date_dt.max())
-input()
+
 train.pop("date_dt")
 test.pop("date_dt")
 train = list(train.T.to_dict().values())
@@ -62,7 +62,7 @@ with open("data/tweet_nerd_new/test_4.jsonl", "w") as f:
 with open("data/tweet_nerd_new/train.jsonl", "w") as f:
     f.write("\n".join([json.dumps(i) for i in train]))
 with open("data/tweet_nerd_new/validation.jsonl", "w") as f:
-    f.write("\n".join([json.dumps(i) for i in validation]))
+    f.write("\n".join([json.dumps(i) for i in valid]))
 
 
 def sampler(dataset_test, r_seed):

statistics.py

@@ -22,7 +22,7 @@ for i in ["nerd_temporal", "ner_temporal", "topic_temporal"]:
             "size": len(dataset),
             "size (token length < 128)": len(token_length_in),
             "mean_token_length": sum(token_length)/len(token_length),
-            "date": f'{str(date[0]).split(" ")[0]} / {str(date[-1]).split(" ")[0]}',
+            "date": f'{str(date[0]).split("T")[0]} / {str(date[-1]).split("T")[0]}',
          })
     break
 df = pd.DataFrame(stats)

tweet_temporal_shift.py

@@ -2,7 +2,7 @@
 import json
 import datasets
 
-_VERSION = "1.0.2"
+_VERSION = "1.0.3"
 _TWEET_TEMPORAL_DESCRIPTION = """"""
 _TWEET_TEMPORAL_CITATION = """"""
 _TWEET_TOPIC_DESCRIPTION = """