datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sst5
Stanford Sentiment Treebank - Fine-Grained
Stanford Sentiment Treebank with 5 labels: very positive, positive, neutral, negative, very negative
Splits are from:
https://github.com/AcademiaSinicaNLPLab/sentiment_dataset/tree/master/data
Training data is on sentence level, not on phrase level!
emotion** Attention: There appears an overlap in train / test. I trained a model on the train set and achieved 100% acc on test set. With the original emotion dataset this is not the case (92.4% acc)**
20_newsgroupsThis is a version of the 20 newsgroups dataset that is provided in Scikit-learn. From the Scikit-learn docs:
The 20 newsgroups dataset comprises around 18000 newsgroups posts on 20 topics split in two subsets: one for training (or development) and the other one for testing (or for performance evaluation). The split between the train and test set is based upon a messages posted before and after a specific date.
We followed the recommended practice to remove headers, signature blocks, and… See the full description on the dataset page: https://huggingface.co/datasets/SetFit/20_newsgroups.enron_spamThis is a version of the Enron Spam Email Dataset, containing emails (subject + message) and a label whether it is spam or ham.
sst2
Stanford Sentiment Treebank - Binary
Stanford Sentiment Treebank with 2 labels: negative, positive
Splits are from:
https://github.com/AcademiaSinicaNLPLab/sentiment_dataset/tree/master/data
Training data is on sentence level, not on phrase level!
ag_newsrte
Glue RTE
This dataset is a port of the official rte dataset on the Hub.
Note that the sentence1 and sentence2 columns have been renamed to text1 and text2 respectively.
Also, the test split is not labeled; the label column values are always -1.
TREC-QC
TREC Question Classification
Question classification in coarse and fine-grained categories.
Source:
Experimental Data for Question Classification
Xin Li, Dan Roth, Learning Question Classifiers. COLING'02, Aug., 2002.
bbc-news
BBC News Topic Dataset
Dataset on BBC News Topic Classification consisting of 2,225 articles published on the BBC News website corresponding during 2004-2005. Each article is labeled under one of 5 categories: business, entertainment, politics, sport or tech.
Original source for this dataset:
Derek Greene, Pádraig Cunningham, “Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clustering,” in Proc. 23rd International Conference on Machine learning (ICML’06)… See the full description on the dataset page: https://huggingface.co/datasets/SetFit/bbc-news.amazon_reviews_multi_enamazon_counterfactual_en
Amazon Counterfactual Statements
This dataset is the en-ext split from SetFit/amazon_counterfactual. As the original test set is rather small (1333 examples), a different split was created with 50-50 for training & testing.
The dataset is described in amazon-multilingual-counterfactual-dataset / Paper
It contains statements from Amazon reviews about events that did not or cannot take place.
CR
Customer Reviews
This dataset is a port of the official CR dataset from this paper.
There is no validation split.
SentEval-CR
SentEval Customer Reviews
This dataset is a port of the official SentEval CR dataset from this paper. The test split was created from the by randomly sampling 20% of the original data and the train split is the remaining 80%. there are no official train/test splits of CR.
There is no validation split. This was used in the STraTA paper.
subj
Subjective vs Objective
This is the SUBJ dataset as used in SentEval. It contains sentences with an annotation if they sentence describes something subjective about a movie or something objective
robo_set_rawade_corpus_v2_classification
ADE-Corpus-V2 Dataset: Adverse Drug Reaction Data.
This is a dataset for classification if a sentence is ADE-related (True) or not (False).
Train size: 17,637
Test size: 5,879
Source dataset
Paper
sn38-set-csn38-set-asn38-set-bsn38-set-esn38-set-damazon_massive_intent_en-USqqp
Glue QQP
This dataset is a port of the official qqp dataset on the Hub.
Note that the question1 and question2 columns have been renamed to text1 and text2 respectively.
Also, the test split is not labeled; the label column values are always -1.
mnli
Glue MNLI
This dataset is a port of the official mnli dataset on the Hub.
It contains the matched version.
Note that the premise and hypothesis columns have been renamed to text1 and text2 respectively.
Also, the test split is not labeled; the label column values are always -1.
genomes-v4-genome_set-animals-intervals-v5_256_128genomes-v5-genome_set-animals-intervals-v1_255_128
bolinas-dna/genomes-v5-genome_set-animals-intervals-v1_255_128
Animals promoters (v1) sequences — 255 bp DNA windows
for genomic language model pretraining.
Part of the bolinas-dna/genomes-v5 training-dataset family produced by the
snakemake/training_dataset pipeline (commit
8db58254831f). Each repo in the family is one
(genome_set, region-recipe) combination.
Size
68,286,166 sequences across 64 data/train/*.jsonl.zst shards
(reverse complements included). This is… See the full description on the dataset page: https://huggingface.co/datasets/marin-dna/genomes-v5-genome_set-animals-intervals-v1_255_128.genomes-v4-genome_set-animals-intervals-v11_256_128genomes-v5-genome_set-animals_order204-intervals-v5_255_128
bolinas-dna/genomes-v5-genome_set-animals_order204-intervals-v5_255_128
204 animals (one per order) CDS (v5) sequences — 255 bp DNA windows
for genomic language model pretraining.
Part of the bolinas-dna/genomes-v5 training-dataset family produced by the
snakemake/training_dataset pipeline (commit
main). Each repo in the family is one
(genome_set, region-recipe) combination.
Size
101,114,252 sequences across 64 data/train/*.jsonl.zst shards
(reverse complements… See the full description on the dataset page: https://huggingface.co/datasets/marin-dna/genomes-v5-genome_set-animals_order204-intervals-v5_255_128.genomes-v4-genome_set-animals-intervals-v10_256_128genomes-v4-genome_set-animals-intervals-v12_256_128