Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Sub-tasks:
topic-classification
Languages:
Ukrainian
Size:
1K - 10K
License:
File size: 765 Bytes
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import json
import polars as pl
test = pl.read_ndjson("data/raw_test.jsonl")
train = pl.read_ndjson("data/raw_train.jsonl")
print(test)
print(train)
unique_test_labels = test.select("label").unique()
unique_train_labels = train.select("label").unique()
print("Unique labels in test data:", unique_test_labels)
print("Unique labels in train data:", unique_train_labels)
unique_concatenated = pl.concat([unique_test_labels, unique_train_labels]).unique()
print("Unique labels in both test and train data:", unique_concatenated)
print(unique_concatenated)
labels = {}
for idx, value in enumerate(unique_concatenated.rows()):
print(idx, value[0])
labels[value[0]] = idx
print(labels)
with open("data/labels.json", "w") as f:
json.dump(labels, f)
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