Upload README.md

README.md

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----
-license: mit
----
+---
+annotations_creators:
+- expert-generated
+language_creators:
+- expert-generated
+language:
+- en
+license: mit
+multilinguality:
+- monolingual
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- text-classification
+- text-generation
+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
+  task_id: binary_classification
+  splits:
+    train_split: train
+    eval_split: test
+  col_mapping:
+    text: text
+    label: target
+  metrics:
+  - type: accuracy
+  - name: Accuracy
+  - type: f1
+    name: F1 macro
+    args:
+      average: macro
+  - type: f1
+    name: F1 micro
+    args:
+      average: micro
+  - type: f1
+    name: F1 weighted
+    args:
+      average: weighted
+  - type: precision
+    name: Precision macro
+    args:
+      average: macro
+  - type: precision
+    name: Precision micro
+    args:
+      average: micro
+  - type: precision
+    name: Precision weighted
+    args:
+      average: weighted
+  - type: recall
+    name: Recall macro
+    args:
+      average: macro
+  - type: recall
+    name: Recall micro
+    args:
+      average: micro
+  - type: recall
+    name: Recall weighted
+    args:
+      average: weighted
+---
+
+# Dataset Card for "imdb"
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [http://ai.stanford.edu/~amaas/data/sentiment/](http://ai.stanford.edu/~amaas/data/sentiment/)
+- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+- **Size of downloaded dataset files:** 84.13 MB
+- **Size of the generated dataset:** 133.23 MB
+- **Total amount of disk used:** 217.35 MB
+
+### Dataset Summary
+
+Large Movie Review Dataset.
+This 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.
+
+## Dataset Structure
+
+### Data Instances
+
+#### plain_text
+
+- **Size of downloaded dataset files:** 84.13 MB
+- **Size of the generated dataset:** 133.23 MB
+- **Total amount of disk used:** 217.35 MB
+
+An example of 'train' looks as follows.
+```
+{
+    "label": 0,
+    "text": "Goodbye world2\n"
+}
+```
+
+### Data Fields
+
+The data fields are the same among all splits.
+
+#### plain_text
+- `text`: a `string` feature.
+- `label`: a classification label, with possible values including `neg` (0), `pos` (1).
+
+### Data Splits
+
+|   name   |train|unsupervised|test |
+|----------|----:|-----------:|----:|
+|plain_text|25000|       50000|25000|