Update parquet files

.gitattributes

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-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
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-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.lz4 filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
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-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
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-*.pickle filter=lfs diff=lfs merge=lfs -text
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-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
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-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
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-*.raw filter=lfs diff=lfs merge=lfs -text
-# Audio files - compressed
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-# Image files - uncompressed
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README.txt

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-This is a version of squad derived from SQuAD v2 on which we did the following changes:
-
-def remove_long_answers(example): #MAP
-    new_answers = {'text':[], 'answer_start':[]}
-    answers_set = set()
-    for text, start in zip(example['answers']['text'], example['answers']['answer_start']):
-        if len(text.split()) > 10:
-            continue
-        else:
-            if (text, start) not in answers_set:
-                new_answers['text'].append(text)
-                new_answers['answer_start'].append(start)
-                answers_set.add((text, start))
-    example['answers'] = new_answers
-    return example
-   
-     
-def filter_whitespace(example): #MAP
-    example['context'] = ' '.join(example['context'].split())
-    example['question'] = ' '.join(example['question'].split())
-    example['answers']['text'] = [' '.join(answer.split()) for answer in example['answers']['text']]
-    return example
-  
-      
-def checks(example): #FILTER
-    if example['answers']['text'] == []:
-        return False
-
-    if len(example['question'].split()) > 35:
-        return False
-    
-    if len(example['question'].split()) < 3:
-        return False
-
-    return True

dataset_infos.json

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-{"readerbench--squad_qgen": {"description": "combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers\n to look similar to answerable ones. To do well on SQuAD2.0, systems must not only answer questions when possible, but\n also determine when no answer is supported by the paragraph and abstain from answering.\n", "citation": "@article{2016arXiv160605250R,\n       author = {{Rajpurkar}, Pranav and {Zhang}, Jian and {Lopyrev},\n                 Konstantin and {Liang}, Percy},\n        title = \"{SQuAD: 100,000+ Questions for Machine Comprehension of Text}\",\n      journal = {arXiv e-prints},\n         year = 2016,\n          eid = {arXiv:1606.05250},\n        pages = {arXiv:1606.05250},\narchivePrefix = {arXiv},\n       eprint = {1606.05250},\n}\n", "homepage": "https://rajpurkar.github.io/SQuAD-explorer/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "question-answering-extractive", "question_column": "question", "context_column": "context", "answers_column": "answers"}], "builder_name": "squad_v2", "config_name": "squad_v2", "version": {"version_str": "2.0.0", "description": null, "major": 2, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 73975024.51139128, "num_examples": 82900, "dataset_name": "squad_qgen"}, "validation": {"name": "validation", "num_bytes": 5611788.221679441, "num_examples": 5866, "dataset_name": "squad_qgen"}}, "download_checksums": null, "download_size": 15653160, "post_processing_size": null, "dataset_size": 79586812.73307072, "size_in_bytes": 95239972.73307072}}

data/train-00000-of-00001-06445eab05f4a339.parquet → readerbench--squad_qgen/parquet-train.parquet

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data/validation-00000-of-00001-b4a4096a07671fcb.parquet → readerbench--squad_qgen/parquet-validation.parquet

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