Eval metadata Batch 4: Tweet Eval, Tweets Hate Speech Detection, VCTK, Weibo NER, Wisesight Sentiment, XSum, Yahoo Answers Topics, Yelp Polarity, Yelp Review Full (#4338)

* Eval metadata for Tweet Eval, Tweets Hate Speech Detection, VCTK, Weibo NER, Wisesight Sentiment, XSum, Yahoo Answers Topics, Yelp Polarity, Yelp Review Full

* Update README.md

oops, duplicate

* Update README.md

adding header

* Update README.md

adding header

* Update datasets/xsum/README.md

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

* Update README.md

removing ROUGE args

* Update README.md

removing F1 params

* Update README.md

* Update README.md

updating to binary F1

* Update README.md

oops typo

* Update README.md

F1 binary

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

Commit from https://github.com/huggingface/datasets/commit/bce8e6541af98cb0e06b24f9c96a6431cf813a38

README.md

@@ -19,6 +19,46 @@ task_ids:
 - sentiment-classification
 paperswithcode_id: null
 pretty_name: Tweets Hate Speech Detection
+train-eval-index:
+- config: default
+  task: text-classification
+  task_id: binary_classification
+  splits:
+    train_split: train
+  col_mapping:
+    tweet: text
+    label: target
+    metrics:
+      - type: accuracy
+        name: Accuracy
+      - type: f1
+        name: F1 binary
+        args:
+          average: binary
+      - 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 Tweets Hate Speech Detection
@@ -86,7 +126,7 @@ The dataset contains a label denoting is the tweet a hate speech or not
 * tweet: content of the tweet as a string.
 
 ### Data Splits
- 
+
 The data contains training data with :31962 entries
 
 ## Dataset Creation
@@ -99,7 +139,7 @@ The data contains training data with :31962 entries
 
 #### Initial Data Collection and Normalization
 
-Crowdsourced from tweets of users 
+Crowdsourced from tweets of users
 
 #### Who are the source language producers?
 
@@ -109,11 +149,11 @@ Cwodsourced from twitter
 
 #### Annotation process
 
-The data has been precprocessed and a model has been trained to assign the relevant label to the tweet 
+The data has been precprocessed and a model has been trained to assign the relevant label to the tweet
 
 #### Who are the annotators?
 
-The data has been provided by Roshan Sharma 
+The data has been provided by Roshan Sharma
 
 ### Personal and Sensitive Information
 
@@ -123,7 +163,7 @@ The data has been provided by Roshan Sharma
 
 ### Social Impact of Dataset
 
-With the help of this dataset, one can understand more about the human sentiments and also analye the situations when a particular person intends to make use of   hatred/racist comments 
+With the help of this dataset, one can understand more about the human sentiments and also analye the situations when a particular person intends to make use of   hatred/racist comments
 
 ### Discussion of Biases
 
@@ -140,7 +180,7 @@ The data could be cleaned up further for additional purposes such as applying a
 
 ### Dataset Curators
 
-Roshan Sharma 
+Roshan Sharma
 
 ### Licensing Information
 
@@ -152,4 +192,4 @@ Roshan Sharma
 
 ### Contributions
 
-Thanks to [@darshan-gandhi](https://github.com/darshan-gandhi) for adding this dataset.
+Thanks to [@darshan-gandhi](https://github.com/darshan-gandhi) for adding this dataset.