TheHidden/autotrain-data-facebook2

---
task_categories:
- summarization

---
# AutoTrain Dataset for project: facebook2

## Dataset Description

This dataset has been automatically processed by AutoTrain for project facebook2.

### 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": "\u201cWhen the vessel is anchored or docked, the sonar is set up with continuous surveillance 360\u00b0 around the vessel for detection of underwater threats; such as divers, diver delivery vehicles, or submersibles.\u201d",
"target": "identify underwater threats"
},
{
"text": "\u201cLimiter: Useful to reduce external interference, such as acoustic interference from other sonar/sounder equipment on board and electrical interference from power supplies and power cables.\u201d",
"target": "identify the limiter settings"
}
]
```

### Dataset Fields

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

```json
{
"text": "Value(dtype='string', id=None)",
"target": "Value(dtype='string', 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 | 264 |
| valid | 66 |

原始信息汇总

AutoTrain Dataset for project: facebook2

数据集描述

该数据集由AutoTrain自动处理，用于facebook2项目。

语言

数据集的语言BCP-47代码为unk。

数据集结构

数据实例

数据集的一个样本如下：

json [ { "text": "u201cWhen the vessel is anchored or docked, the sonar is set up with continuous surveillance 360u00b0 around the vessel for detection of underwater threats; such as divers, diver delivery vehicles, or submersibles.u201d", "target": "identify underwater threats" }, { "text": "u201cLimiter: Useful to reduce external interference, such as acoustic interference from other sonar/sounder equipment on board and electrical interference from power supplies and power cables.u201d", "target": "identify the limiter settings" } ]

数据集字段

数据集包含以下字段（也称为“特征”）：

json { "text": "Value(dtype=string, id=None)", "target": "Value(dtype=string, 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
train	264
valid	66