Eval metadata batch 3: Reddit, Rotten Tomatoes, SemEval 2010, Sentiment 140, SMS Spam, Snips, SQuAD, SQuAD v2, Timit ASR (#4337)

* Eval metadata batch 3: Quora, Reddit, Rotten Tomatoes, SemEval 2010, Sentiment 140, SMS Spam, Snips, SQuAD, SQuAD v2, Timit ASR

* Update datasets/quora/README.md

Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>

* Update README.md

removing ROUGE args

* Update datasets/rotten_tomatoes/README.md

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update datasets/rotten_tomatoes/README.md

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update datasets/squad/README.md

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update datasets/squad_v2/README.md

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update datasets/squad/README.md

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update datasets/squad_v2/README.md

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update datasets/squad_v2/README.md

Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* Update README.md

removing eval for quora

Co-authored-by: sashavor <sasha.luccioni@huggingface.co>
Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

Commit from https://github.com/huggingface/datasets/commit/8ccf58b77343f323ba6654250f88b69699a57b8e

README.md

@@ -19,6 +19,18 @@ task_categories:
 - summarization
 task_ids:
 - summarization-other-reddit-posts-summarization
+train-eval-index:
+- config: default
+  task: summarization
+  task_id: summarization
+  splits:
+    train_split: train
+  col_mapping:
+    content: text
+    summary: target
+  metrics:
+    - type: rouge
+      name: Rouge
 ---
 
 # Dataset Card for Reddit Webis-TLDR-17
@@ -49,7 +61,7 @@ task_ids:
 
 ## Dataset Description
 
-- **Homepage:** [https://webis.de/data/webis-tldr-17.html](https://webis.de/data/webis-tldr-17.html) 
+- **Homepage:** [https://webis.de/data/webis-tldr-17.html](https://webis.de/data/webis-tldr-17.html)
 - **Repository:** [https://github.com/webis-de/webis-tldr-17-corpus](https://github.com/webis-de/webis-tldr-17-corpus)
 - **Paper:** [https://aclanthology.org/W17-4508]
 - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
@@ -81,7 +93,7 @@ Known ROUGE scores achieved for the Webis-TLDR-17:
 
 ### Languages
 
-English 
+English
 
 ## Dataset Structure
 
@@ -176,7 +188,7 @@ This dataset has been created to serve as a source of large-scale summarization
 
 Reddit users write TL;DRs with various intentions, such as providing a “true” summary, asking questions or for help, or forming judgments and conclusions. As noted in the paper introducing the dataset, although the first kind of TL;DR posts are most important for training summarization models, yet, the latter allow for various alternative summarization-related tasks.
 
-Although filtering was performed abusive language maybe still be present. 
+Although filtering was performed abusive language maybe still be present.
 
 ## Additional Information