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README.md

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+# Amazon Counterfactual Statements
+
+This dataset is the *en-ext* split from [SetFit/amazon_counterfactual](https://huggingface.co/datasets/SetFit/amazon_counterfactual). As the original test set is rather small (1333 examples), a different split was created with 50-50 for training & testing.
+
+The dataset is described in [amazon-multilingual-counterfactual-dataset](https://github.com/amazon-research/amazon-multilingual-counterfactual-dataset) / [Paper](https://arxiv.org/pdf/2104.06893.pdf)
+
+It contains statements from Amazon reviews about events that did not or cannot take place.

prepare_data.py

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+from datasets import load_dataset
+import json
+import random
+
+dataset = load_dataset("SetFit/amazon_counterfactual", "en-ext")
+
+examples = list(dataset['train'])+list(dataset['validation'])+list(dataset['test'])
+random.seed(42)
+random.shuffle(examples)
+
+
+num_test = 5000
+data_splits = {'test': examples[0:num_test], 'train': examples[num_test:]}
+
+
+for split in data_splits.keys():
+    with open(f'{split}.jsonl', 'w') as fOut:
+        for row in data_splits[split]:
+            fOut.write(json.dumps(row)+"\n")

test.jsonl

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+oid sha256:4a8d0d50f925f984a9ae51a42e913178387825bd50cf36372077cfacb1d7b3aa
+size 815592

train.jsonl

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+oid sha256:bbbf41050834d7ca88a9edc47f9035e06d0b72b9bf81263e84ea4c9af7b84860
+size 814811