# AutoTrain Dataset for project: entericdisease50articlefinetune

## Dataset Description

This dataset has been automatically processed by AutoTrain for project entericdisease50articlefinetune.

### 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
[
  {
    "context": "\ufeff\n\nNew Role for the ibeA Gene in H2O2 Stress Resistance of\nEscherichia coli\nMaud Fl\u00e9chard,a,b M\u00e9lanie A. M. Cortes,a,b Maryline R\u00e9p\u00e9rant,a,b and Pierre Germona,b\nINRA, UMR 1282 Infectiologie et Sant\u00e9 Publique, Nouzilly, France,a and Universit\u00e9 Fran\u00e7ois Rabelais, UMR 1282, Tours, Franceb\n\nibeA is a virulence factor found in",
    "question": "What genes are mentioned in this article",
    "answers.text": [
      "ibeA"
    ],
    "answers.answer_start": [
      20
    ],
    "feat_answer_id": [
      798798
    ],
    "feat_document_id": [
      1442778
    ],
    "feat_question_id": [
      915217
    ],
    "feat_answer_end": [
      24.0
    ],
    "feat_answer_category": [
      null
    ],
    "feat_file_name": [
      "53_JB.00089-12.txt"
    ]
  },
  {
    "context": "\ufeffInternational Journal of Food Microbiology 166 (2013) 65\u201371\n\n\n\n\n\n\n\n\n\n\nLoss of cAMP/CRP regulation confers extreme high hydrostatic pressure resistance in Escherichia coli O157:H7\nDietrich Vanlint, Brecht J.Y. Pype, Nele Rutten, Kristof G.A. Vanoirbeek, Chris W. Michiels, Abram Aertsen \u204e\nLaboratory of Food Microbiology and Leuven Food Science and Nutrition Research Centre (LFoRCe), De",
    "question": "What genes are mentioned in this article",
    "answers.text": [
      "CRP"
    ],
    "answers.answer_start": [
      84
    ],
    "feat_answer_id": [
      798875
    ],
    "feat_document_id": [
      1442807
    ],
    "feat_question_id": [
      915217
    ],
    "feat_answer_end": [
      87.0
    ],
    "feat_answer_category": [
      null
    ],
    "feat_file_name": [
      "82_1-s2.0-S0168160513003115-main.txt"
    ]
  }
]
```

### 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)",
  "feat_answer_id": "Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)",
  "feat_document_id": "Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)",
  "feat_question_id": "Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)",
  "feat_answer_end": "Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None)",
  "feat_answer_category": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
  "feat_file_name": "Sequence(feature=Value(dtype='string', 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        | 80 |
| valid        | 20 |

region:us
{}
TAGS
#region-us 

AutoTrain Dataset for project: entericdisease50articlefinetune
==============================================================


Dataset Description
-------------------


This dataset has been automatically processed by AutoTrain for project entericdisease50articlefinetune.


### Languages


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


Dataset Structure
-----------------


### Data Instances


A sample from this dataset looks as follows:


### Dataset Fields


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


### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:




### Languages


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


Dataset Structure
----------------- ### Data Instances


A sample from this dataset looks as follows: ### Dataset Fields


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


This dataset is split into a train and validation split. The split sizes are as follow:
TAGS
#region-us 
 ### Languages


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


Dataset Structure
----------------- ### Data Instances


A sample from this dataset looks as follows: ### Dataset Fields


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


This dataset is split into a train and validation split. The split sizes are as follow:
passage: TAGS
#region-us 
### Languages


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


Dataset Structure
-----------------### Data Instances


A sample from this dataset looks as follows:### Dataset Fields


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


This dataset is split into a train and validation split. The split sizes are as follow: