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"AutoTrain generated dataset"
{ "text": { "dtype": "string", "id": null, "_type": "Value" }, "target": { "num_classes": 2, "names": [ "irrelevant", "relevant" ], "id": null, "_type": "ClassLabel" } }
{ "train": { "name": "train", "num_bytes": 3062259, "num_examples": 780, "dataset_name": null } }
[ { "filename": "dataset.arrow" } ]
[ "target", "text" ]

AutoTrain Dataset for project: security-texts-classification-distilroberta

Dataset Descritpion

This dataset has been automatically processed by AutoTrain for project security-texts-classification-distilroberta.


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

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

    "text": "Netgear launches Bug Bounty Program for Hacker; Offering up to $15,000 in Rewards It might be the ea[...]",
    "target": 0
    "text": "Popular Malware Families Using 'Process Doppelg\u00e4nging' to Evade Detection The fileless code injectio[...]",
    "target": 1

Dataset Fields

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

  "text": "Value(dtype='string', id=None)",
  "target": "ClassLabel(num_classes=2, names=['irrelevant', 'relevant'], 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 780
valid 196
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Models trained or fine-tuned on vlsb/autotrain-data-security-texts-classification-distilroberta