MoL2/autotrain-data-dnabert_classfy_chr1
AutoTrain Dataset for project: dnabert_classfy_chr1 Dataset Description This dataset has been automatically processed by AutoTrain for project dnabert_classfy_chr1. Languages The BCP-47 code for the dataset's language is unk. Dataset Structure Data Instances A sample from this dataset looks as follows: [ { "target": 13, "text":… See the full description on the dataset page: https://huggingface.co/datasets/MoL2/autotrain-data-dnabert_classfy_chr1.
AutoTrain Dataset for project: dnabertclassfychr1
Dataset Description
This dataset has been automatically processed by AutoTrain for project dnabertclassfychr1.
Languages
The BCP-47 code for the dataset's language is unk.
Dataset Structure
Data Instances
A sample from this dataset looks as follows:
[
{
"target": 13,
"text": "tctgaaaataactgtattgcttctgtttgtaaggtcagtttgctggatgtattaacagaattctcagcactttgagtgttgtcttttgagttgcattattaagttagccgttaatttaattgttatttctttgtagttaatgccttttttctctggctgcttttaagatcttctgtgtgactttggtgtgctaagtaagttctgctatgatatgtccagtagaacttctttttttattattatccttaggatttgataggttttctgaatctgagaattggtatctttcatccattctggaacatttttatatattatttcttcaattgtgcttttctttcattcctctatcatctccatctagatctcttgtttagacaggctcaccctatcctctgtatttgctgcattctcgataatttcacagtctgtcttctaggtcactaattccttctttagttgtgtctaaactcttttccacctgcacattgagtttctgg"
},
{
"target": 13,
"text": "GCCAGTGTCTCTCGTGGTCTCTCAAATTCCTTTCCTTCCTGAAAAGAAAAAAAATGATACCTTACATTTTTTAACTTAAGATTTAAAAATATGTTATATAGAGTAAAATTGGGCTTCTCTCATCCTTTAGCCATGAGAAAAAAAATGTTCTTTTGTTAGGAGGACCATGGTCACCATGAAGGTCAGTCATAGGCATCCATGGAGTCAATTGTGGCAGCCATGTCCCCCCAGCAGCAGATCCCTACTACTTAGATCCAGCCACTCCTCAGAGGTGGAGAAGGGGAAGTGAGAAAAGGTCCATCCTGGCCCCTAGGAAACTCTCCCCAAAGAAAAACCAAGAAGAAACACTTTCCAAATGTTTCTTTCCTTTAAAATAAAGTTAGTTAGCAACCCTGATGCCTTCATCAAAACAAAGAAAGACCTTCTGATGACAGAGTCTGAGGATGATCATGCAAAGTGCTGAACAAAGTGAAAAATGAAATCAAGATTTTTTCCATTCT"
}
]Dataset Fields
The dataset has the following fields (also called "features"):
{
"target": "ClassLabel(names=['0', '1', '10', '11', '12', '13', '14', '15', '2', '3', '4', '5', '6', '7', '8', '9'], id=None)",
"text": "Value(dtype='string', id=None)"
}Dataset Splits
This dataset is split into a train and validation split. The split sizes are as follow: