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+version https://git-lfs.github.com/spec/v1
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+size 160549
diff --git a/dataset/tweet_topic/valid_test2_seed2.jsonl b/dataset/tweet_topic/valid_test2_seed2.jsonl
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+version https://git-lfs.github.com/spec/v1
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diff --git a/dataset/tweet_topic/valid_test3_seed0.jsonl b/dataset/tweet_topic/valid_test3_seed0.jsonl
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+version https://git-lfs.github.com/spec/v1
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+version https://git-lfs.github.com/spec/v1
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+version https://git-lfs.github.com/spec/v1
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diff --git a/process/tweet_ner7.py b/process/tweet_ner7.py
new file mode 100644
index 0000000000000000000000000000000000000000..99582d30446054218b9665b47a9b0f5cb7165d75
--- /dev/null
+++ b/process/tweet_ner7.py
@@ -0,0 +1,66 @@
+import json
+import os
+from random import shuffle, seed
+from datasets import load_dataset
+
+os.makedirs("dataset/tweet_topic", exist_ok=True)
+test = load_dataset("cardiffnlp/super_tweeteval", "tweet_topic", split="test").shuffle(seed=42)
+test = list(test.to_pandas().T.to_dict().values())
+train = load_dataset("cardiffnlp/super_tweeteval", "tweet_topic", split="train").shuffle(seed=42)
+train = list(train.to_pandas().T.to_dict().values())
+validation = load_dataset("cardiffnlp/super_tweeteval", "tweet_topic", split="validation").shuffle(seed=42)
+validation = list(validation.to_pandas().T.to_dict().values())
+n_train = len(train)
+n_validation = len(validation)
+for data in [train, validation, test]:
+    for i in data:
+        i["gold_label_list"] = i["gold_label_list"].tolist()
+
+n_test = int(len(test)/4)
+test_1 = test[:n_test]
+test_2 = test[n_test:n_test*2]
+test_3 = test[n_test*2:n_test*3]
+test_4 = test[n_test*3:]
+
+with open("dataset/tweet_topic/test_1.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_1]))
+with open("dataset/tweet_topic/test_2.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_2]))
+with open("dataset/tweet_topic/test_3.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_3]))
+with open("dataset/tweet_topic/test_4.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_4]))
+with open("dataset/tweet_topic/train.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in train]))
+with open("dataset/tweet_topic/valid.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in validation]))
+
+
+def sampler(dataset_test, r_seed):
+    seed(r_seed)
+    shuffle(dataset_test)
+    shuffle(train)
+    shuffle(validation)
+    test_tr = dataset_test[:int(n_train / 2)]
+    test_vl = dataset_test[int(n_train / 2): int(n_train / 2) + int(n_validation / 2)]
+    new_train = test_tr + train[:n_train - len(test_tr)]
+    new_validation = test_vl + validation[:n_validation - len(test_vl)]
+    return new_train, new_validation
+
+
+for n, _test in enumerate([
+        test_4 + test_2 + test_3,
+        test_1 + test_4 + test_3,
+        test_1 + test_2 + test_4,
+        test_1 + test_2 + test_3]):
+    for s in range(3):
+        _train, _valid = sampler(_test, s)
+        with open(f"dataset/tweet_topic/train_test{n}_seed{s}.jsonl", "w") as f:
+            f.write("\n".join([json.dumps(i) for i in _train]))
+        with open(f"dataset/tweet_topic/valid_test{n}_seed{s}.jsonl", "w") as f:
+            f.write("\n".join([json.dumps(i) for i in _valid]))
+
+
+
+
+
diff --git a/process/tweet_nerd.py b/process/tweet_nerd.py
new file mode 100644
index 0000000000000000000000000000000000000000..99582d30446054218b9665b47a9b0f5cb7165d75
--- /dev/null
+++ b/process/tweet_nerd.py
@@ -0,0 +1,66 @@
+import json
+import os
+from random import shuffle, seed
+from datasets import load_dataset
+
+os.makedirs("dataset/tweet_topic", exist_ok=True)
+test = load_dataset("cardiffnlp/super_tweeteval", "tweet_topic", split="test").shuffle(seed=42)
+test = list(test.to_pandas().T.to_dict().values())
+train = load_dataset("cardiffnlp/super_tweeteval", "tweet_topic", split="train").shuffle(seed=42)
+train = list(train.to_pandas().T.to_dict().values())
+validation = load_dataset("cardiffnlp/super_tweeteval", "tweet_topic", split="validation").shuffle(seed=42)
+validation = list(validation.to_pandas().T.to_dict().values())
+n_train = len(train)
+n_validation = len(validation)
+for data in [train, validation, test]:
+    for i in data:
+        i["gold_label_list"] = i["gold_label_list"].tolist()
+
+n_test = int(len(test)/4)
+test_1 = test[:n_test]
+test_2 = test[n_test:n_test*2]
+test_3 = test[n_test*2:n_test*3]
+test_4 = test[n_test*3:]
+
+with open("dataset/tweet_topic/test_1.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_1]))
+with open("dataset/tweet_topic/test_2.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_2]))
+with open("dataset/tweet_topic/test_3.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_3]))
+with open("dataset/tweet_topic/test_4.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in test_4]))
+with open("dataset/tweet_topic/train.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in train]))
+with open("dataset/tweet_topic/valid.jsonl", "w") as f:
+    f.write("\n".join([json.dumps(i) for i in validation]))
+
+
+def sampler(dataset_test, r_seed):
+    seed(r_seed)
+    shuffle(dataset_test)
+    shuffle(train)
+    shuffle(validation)
+    test_tr = dataset_test[:int(n_train / 2)]
+    test_vl = dataset_test[int(n_train / 2): int(n_train / 2) + int(n_validation / 2)]
+    new_train = test_tr + train[:n_train - len(test_tr)]
+    new_validation = test_vl + validation[:n_validation - len(test_vl)]
+    return new_train, new_validation
+
+
+for n, _test in enumerate([
+        test_4 + test_2 + test_3,
+        test_1 + test_4 + test_3,
+        test_1 + test_2 + test_4,
+        test_1 + test_2 + test_3]):
+    for s in range(3):
+        _train, _valid = sampler(_test, s)
+        with open(f"dataset/tweet_topic/train_test{n}_seed{s}.jsonl", "w") as f:
+            f.write("\n".join([json.dumps(i) for i in _train]))
+        with open(f"dataset/tweet_topic/valid_test{n}_seed{s}.jsonl", "w") as f:
+            f.write("\n".join([json.dumps(i) for i in _valid]))
+
+
+
+
+