Vulpeka/autotrain-data-psupportai

---
language:
- en

---
# AutoTrain Dataset for project: psupportai

## Dataset Description

This dataset has been automatically processed by AutoTrain for project psupportai.

### Languages

The BCP-47 code for the dataset's language is en.

## Dataset Structure

### Data Instances

A sample from this dataset looks as follows:

```json
[
{
"context": "Account recovery",
"question": "How can I recover my LoL account",
"answers.text": [
"You need to contact with Player Support, you need to have everything ready to use "
],
"answers.answer_start": [
1
]
},
{
"context": "Billing issue",
"question": "I can't purchase RP with my credit card",
"answers.text": [
"You need to contact with Player Support, you need to have everything ready to use "
],
"answers.answer_start": [
2
]
}
]
```

### Dataset Fields

The dataset has the following fields (also called "features"):

```json
{
"context": "Value(dtype='string', id=None)",
"question": "Value(dtype='string', id=None)",
"answers.text": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
"answers.answer_start": "Sequence(feature=Value(dtype='int32', id=None), length=-1, 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 | 2 |
| valid | 1 |

原始信息汇总

AutoTrain Dataset for project: psupportai

数据集描述

该数据集是为项目psupportai自动处理的数据集。

语言

数据集的语言代码为BCP-47标准下的en。

数据集结构

数据实例

数据集的样本示例如下：

json [ { "context": "Account recovery", "question": "How can I recover my LoL account", "answers.text": [ "You need to contact with Player Support, you need to have everything ready to use " ], "answers.answer_start": [ 1 ] }, { "context": "Billing issue", "question": "I cant purchase RP with my credit card", "answers.text": [ "You need to contact with Player Support, you need to have everything ready to use " ], "answers.answer_start": [ 2 ] } ]

数据集字段

数据集包含以下字段：

json { "context": "Value(dtype=string, id=None)", "question": "Value(dtype=string, id=None)", "answers.text": "Sequence(feature=Value(dtype=string, id=None), length=-1, id=None)", "answers.answer_start": "Sequence(feature=Value(dtype=int32, id=None), length=-1, id=None)" }

数据集分割

数据集被分割为训练集和验证集，分割大小如下：

分割名称	样本数量
训练集	2
验证集	1