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---
task_categories:
- text-classification
---
# AutoTrain Dataset for project: twitter-goemotions-binary-fear-classification
## Dataset Description
This dataset has been automatically processed by AutoTrain for project twitter-goemotions-binary-fear-classification.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A sample from this dataset looks as follows:
```json
[
{
"text": "Downvoting comments you don't like is your right.",
"feat_id": "ed62dkv",
"feat_author": "128bitworm",
"feat_subreddit": "im14andthisisdeep",
"feat_link_id": "t3_ac6bna",
"feat_parent_id": "t1_ed5trip",
"feat_created_utc": 1546542336.0,
"feat_rater_id": 35,
"feat_example_very_unclear": false,
"feat_admiration": 0,
"feat_amusement": 0,
"feat_anger": 0,
"feat_annoyance": 0,
"feat_approval": 0,
"feat_caring": 0,
"feat_confusion": 0,
"feat_curiosity": 0,
"feat_desire": 0,
"feat_disappointment": 0,
"feat_disapproval": 1,
"feat_disgust": 0,
"feat_embarrassment": 0,
"feat_excitement": 0,
"target": 0,
"feat_gratitude": 0,
"feat_grief": 0,
"feat_joy": 0,
"feat_love": 0,
"feat_nervousness": 0,
"feat_optimism": 0,
"feat_pride": 0,
"feat_realization": 0,
"feat_relief": 0,
"feat_remorse": 0,
"feat_sadness": 0,
"feat_surprise": 0,
"feat_neutral": 0
},
{
"text": "I fucking love this",
"feat_id": "edxv95q",
"feat_author": "fueryerhealth",
"feat_subreddit": "FellowKids",
"feat_link_id": "t3_af72i1",
"feat_parent_id": "t3_af72i1",
"feat_created_utc": 1547342464.0,
"feat_rater_id": 19,
"feat_example_very_unclear": false,
"feat_admiration": 1,
"feat_amusement": 0,
"feat_anger": 0,
"feat_annoyance": 0,
"feat_approval": 0,
"feat_caring": 0,
"feat_confusion": 0,
"feat_curiosity": 0,
"feat_desire": 0,
"feat_disappointment": 0,
"feat_disapproval": 0,
"feat_disgust": 0,
"feat_embarrassment": 0,
"feat_excitement": 0,
"target": 0,
"feat_gratitude": 0,
"feat_grief": 0,
"feat_joy": 0,
"feat_love": 1,
"feat_nervousness": 0,
"feat_optimism": 0,
"feat_pride": 0,
"feat_realization": 0,
"feat_relief": 0,
"feat_remorse": 0,
"feat_sadness": 0,
"feat_surprise": 0,
"feat_neutral": 0
}
]
```
### Dataset Fields
The dataset has the following fields (also called "features"):
```json
{
"text": "Value(dtype='string', id=None)",
"feat_id": "Value(dtype='string', id=None)",
"feat_author": "Value(dtype='string', id=None)",
"feat_subreddit": "Value(dtype='string', id=None)",
"feat_link_id": "Value(dtype='string', id=None)",
"feat_parent_id": "Value(dtype='string', id=None)",
"feat_created_utc": "Value(dtype='float32', id=None)",
"feat_rater_id": "Value(dtype='int32', id=None)",
"feat_example_very_unclear": "Value(dtype='bool', id=None)",
"feat_admiration": "Value(dtype='int32', id=None)",
"feat_amusement": "Value(dtype='int32', id=None)",
"feat_anger": "Value(dtype='int32', id=None)",
"feat_annoyance": "Value(dtype='int32', id=None)",
"feat_approval": "Value(dtype='int32', id=None)",
"feat_caring": "Value(dtype='int32', id=None)",
"feat_confusion": "Value(dtype='int32', id=None)",
"feat_curiosity": "Value(dtype='int32', id=None)",
"feat_desire": "Value(dtype='int32', id=None)",
"feat_disappointment": "Value(dtype='int32', id=None)",
"feat_disapproval": "Value(dtype='int32', id=None)",
"feat_disgust": "Value(dtype='int32', id=None)",
"feat_embarrassment": "Value(dtype='int32', id=None)",
"feat_excitement": "Value(dtype='int32', id=None)",
"target": "ClassLabel(names=['0', '1'], id=None)",
"feat_gratitude": "Value(dtype='int32', id=None)",
"feat_grief": "Value(dtype='int32', id=None)",
"feat_joy": "Value(dtype='int32', id=None)",
"feat_love": "Value(dtype='int32', id=None)",
"feat_nervousness": "Value(dtype='int32', id=None)",
"feat_optimism": "Value(dtype='int32', id=None)",
"feat_pride": "Value(dtype='int32', id=None)",
"feat_realization": "Value(dtype='int32', id=None)",
"feat_relief": "Value(dtype='int32', id=None)",
"feat_remorse": "Value(dtype='int32', id=None)",
"feat_sadness": "Value(dtype='int32', id=None)",
"feat_surprise": "Value(dtype='int32', id=None)",
"feat_neutral": "Value(dtype='int32', id=None)"
}
```
### Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow:
| Split name | Num samples |
| ------------ | ------------------- |
| train | 168979 |
| valid | 42246 |
|