Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -1,5 +1,4 @@
 ---
-pretty_name: DROP
 annotations_creators:
 - crowdsourced
 language_creators:
@@ -21,6 +20,7 @@ task_ids:
 - extractive-qa
 - abstractive-qa
 paperswithcode_id: drop
+pretty_name: DROP
 dataset_info:
   features:
   - name: section_id
@@ -39,13 +39,20 @@ dataset_info:
       dtype: string
   splits:
   - name: train
-    num_bytes: 105572762
+    num_bytes: 105572506
     num_examples: 77400
   - name: validation
-    num_bytes: 11737787
+    num_bytes: 11737755
     num_examples: 9535
-  download_size: 8308692
-  dataset_size: 117310549
+  download_size: 11538387
+  dataset_size: 117310261
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: validation
+    path: data/validation-*
 ---
 
 # Dataset Card for "drop"

data/train-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:abb5e578c2156a61f83b56c066a922ec1c7c5140638a3f0f2a7c348fafe1cb35
+size 10333127

data/validation-00000-of-00001.parquet

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7f9a3bdbb1b5909abfa25cbab693f89f47568c98e6e03473500d604f044c8f68
+size 1205260

dataset_infos.json

@@ -1 +1,65 @@
-{"default": {"description": "DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.\n. DROP is a crowdsourced, adversarially-created, 96k-question benchmark, in which a system must resolve references in a\nquestion, perhaps to multiple input positions, and perform discrete operations over them (such as addition, counting, or\n sorting). These operations require a much more comprehensive understanding of the content of paragraphs than what was\n necessary for prior datasets.\n", "citation": "@inproceedings{Dua2019DROP,\n  author={Dheeru Dua and Yizhong Wang and Pradeep Dasigi and Gabriel Stanovsky and Sameer Singh and Matt Gardner},\n  title={DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs},\n  booktitle={Proc. of NAACL},\n  year={2019}\n}\n", "homepage": "https://allennlp.org/drop", "license": "", "features": {"section_id": {"dtype": "string", "id": null, "_type": "Value"}, "query_id": {"dtype": "string", "id": null, "_type": "Value"}, "passage": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers_spans": {"feature": {"spans": {"dtype": "string", "id": null, "_type": "Value"}, "types": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "drop", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 105572762, "num_examples": 77400, "dataset_name": "drop"}, "validation": {"name": "validation", "num_bytes": 11737787, "num_examples": 9535, "dataset_name": "drop"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/allennlp/datasets/drop/drop_dataset.zip": {"num_bytes": 8308692, "checksum": "39d2278a29fd729de301b111a45f434c24834f40df8f4ff116d864589e3249d6"}}, "download_size": 8308692, "post_processing_size": null, "dataset_size": 117310549, "size_in_bytes": 125619241}}
+{
+    "default": {
+        "description": "DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.\n. DROP is a crowdsourced, adversarially-created, 96k-question benchmark, in which a system must resolve references in a\nquestion, perhaps to multiple input positions, and perform discrete operations over them (such as addition, counting, or\n sorting). These operations require a much more comprehensive understanding of the content of paragraphs than what was\n necessary for prior datasets.\n",
+        "citation": "@inproceedings{Dua2019DROP,\n  author={Dheeru Dua and Yizhong Wang and Pradeep Dasigi and Gabriel Stanovsky and Sameer Singh and Matt Gardner},\n  title={DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs},\n  booktitle={Proc. of NAACL},\n  year={2019}\n}\n",
+        "homepage": "https://allennlp.org/drop",
+        "license": "",
+        "features": {
+            "section_id": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "query_id": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "passage": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "question": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "answers_spans": {
+                "feature": {
+                    "spans": {
+                        "dtype": "string",
+                        "_type": "Value"
+                    },
+                    "types": {
+                        "dtype": "string",
+                        "_type": "Value"
+                    }
+                },
+                "_type": "Sequence"
+            }
+        },
+        "builder_name": "drop",
+        "dataset_name": "drop",
+        "config_name": "default",
+        "version": {
+            "version_str": "0.1.0",
+            "major": 0,
+            "minor": 1,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 105572506,
+                "num_examples": 77400,
+                "dataset_name": null
+            },
+            "validation": {
+                "name": "validation",
+                "num_bytes": 11737755,
+                "num_examples": 9535,
+                "dataset_name": null
+            }
+        },
+        "download_size": 11538387,
+        "dataset_size": 117310261,
+        "size_in_bytes": 128848648
+    }
+}