Convert dataset to Parquet

Convert dataset to Parquet.

README.md

@@ -1,5 +1,4 @@
 ---
-pretty_name: IMDB
 annotations_creators:
 - expert-generated
 language_creators:
@@ -19,6 +18,40 @@ task_categories:
 task_ids:
 - sentiment-classification
 paperswithcode_id: imdb-movie-reviews
+pretty_name: IMDB
+dataset_info:
+  config_name: plain_text
+  features:
+  - name: text
+    dtype: string
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': neg
+          '1': pos
+  splits:
+  - name: train
+    num_bytes: 33432823
+    num_examples: 25000
+  - name: test
+    num_bytes: 32650685
+    num_examples: 25000
+  - name: unsupervised
+    num_bytes: 67106794
+    num_examples: 50000
+  download_size: 83446840
+  dataset_size: 133190302
+configs:
+- config_name: plain_text
+  data_files:
+  - split: train
+    path: plain_text/train-*
+  - split: test
+    path: plain_text/test-*
+  - split: unsupervised
+    path: plain_text/unsupervised-*
+  default: true
 train-eval-index:
 - config: plain_text
   task: text-classification
@@ -68,29 +101,6 @@ train-eval-index:
     name: Recall weighted
     args:
       average: weighted
-dataset_info:
-  features:
-  - name: text
-    dtype: string
-  - name: label
-    dtype:
-      class_label:
-        names:
-          0: neg
-          1: pos
-  config_name: plain_text
-  splits:
-  - name: train
-    num_bytes: 33432835
-    num_examples: 25000
-  - name: test
-    num_bytes: 32650697
-    num_examples: 25000
-  - name: unsupervised
-    num_bytes: 67106814
-    num_examples: 50000
-  download_size: 84125825
-  dataset_size: 133190346
 ---
 
 # Dataset Card for "imdb"

dataset_infos.json

@@ -1 +1,60 @@
-{"plain_text": {"description": "Large Movie Review Dataset.\nThis is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well.", "citation": "@InProceedings{maas-EtAl:2011:ACL-HLT2011,\n  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},\n  title     = {Learning Word Vectors for Sentiment Analysis},\n  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},\n  month     = {June},\n  year      = {2011},\n  address   = {Portland, Oregon, USA},\n  publisher = {Association for Computational Linguistics},\n  pages     = {142--150},\n  url       = {http://www.aclweb.org/anthology/P11-1015}\n}\n", "homepage": "http://ai.stanford.edu/~amaas/data/sentiment/", "license": "", "features": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["neg", "pos"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "text-classification", "text_column": "text", "label_column": "label", "labels": ["neg", "pos"]}], "builder_name": "imdb", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 33432835, "num_examples": 25000, "dataset_name": "imdb"}, "test": {"name": "test", "num_bytes": 32650697, "num_examples": 25000, "dataset_name": "imdb"}, "unsupervised": {"name": "unsupervised", "num_bytes": 67106814, "num_examples": 50000, "dataset_name": "imdb"}}, "download_checksums": {"http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz": {"num_bytes": 84125825, "checksum": "c40f74a18d3b61f90feba1e17730e0d38e8b97c05fde7008942e91923d1658fe"}}, "download_size": 84125825, "post_processing_size": null, "dataset_size": 133190346, "size_in_bytes": 217316171}}
+{
+    "plain_text": {
+        "description": "Large Movie Review Dataset.\nThis is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well.",
+        "citation": "@InProceedings{maas-EtAl:2011:ACL-HLT2011,\n  author    = {Maas, Andrew L.  and  Daly, Raymond E.  and  Pham, Peter T.  and  Huang, Dan  and  Ng, Andrew Y.  and  Potts, Christopher},\n  title     = {Learning Word Vectors for Sentiment Analysis},\n  booktitle = {Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies},\n  month     = {June},\n  year      = {2011},\n  address   = {Portland, Oregon, USA},\n  publisher = {Association for Computational Linguistics},\n  pages     = {142--150},\n  url       = {http://www.aclweb.org/anthology/P11-1015}\n}\n",
+        "homepage": "http://ai.stanford.edu/~amaas/data/sentiment/",
+        "license": "",
+        "features": {
+            "text": {
+                "dtype": "string",
+                "_type": "Value"
+            },
+            "label": {
+                "names": [
+                    "neg",
+                    "pos"
+                ],
+                "_type": "ClassLabel"
+            }
+        },
+        "task_templates": [
+            {
+                "task": "text-classification",
+                "label_column": "label"
+            }
+        ],
+        "builder_name": "imdb",
+        "dataset_name": "imdb",
+        "config_name": "plain_text",
+        "version": {
+            "version_str": "1.0.0",
+            "description": "",
+            "major": 1,
+            "minor": 0,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_bytes": 33432823,
+                "num_examples": 25000,
+                "dataset_name": null
+            },
+            "test": {
+                "name": "test",
+                "num_bytes": 32650685,
+                "num_examples": 25000,
+                "dataset_name": null
+            },
+            "unsupervised": {
+                "name": "unsupervised",
+                "num_bytes": 67106794,
+                "num_examples": 50000,
+                "dataset_name": null
+            }
+        },
+        "download_size": 83446840,
+        "dataset_size": 133190302,
+        "size_in_bytes": 216637142
+    }
+}

plain_text/test-00000-of-00001.parquet

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+size 20470363

plain_text/train-00000-of-00001.parquet

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+size 20979968

plain_text/unsupervised-00000-of-00001.parquet

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+size 41996509