LM-Polygraph/samsum

1---2dataset_info:3- config_name: continuation4  features:5  - name: input6    dtype: string7  - name: output8    dtype: string9  splits:10  - name: train11    num_bytes: 1067144912    num_examples: 1473213  - name: test14    num_bytes: 60077915    num_examples: 81916  download_size: 644517317  dataset_size: 1127222818- config_name: simple_instruct19  features:20  - name: input21    dtype: string22  - name: output23    dtype: string24  splits:25  - name: train26    num_bytes: 1307276527    num_examples: 1473228  - name: test29    num_bytes: 73427630    num_examples: 81931  download_size: 666996132  dataset_size: 1380704133configs:34- config_name: continuation35  data_files:36  - split: train37    path: continuation/train-*38  - split: test39    path: continuation/test-*40- config_name: simple_instruct41  data_files:42  - split: train43    path: simple_instruct/train-*44  - split: test45    path: simple_instruct/test-*46---47 48# Dataset Card for samsum49 50<!-- Provide a quick summary of the dataset. -->51 52This is a preprocessed version of samsum dataset for benchmarks in LM-Polygraph.53 54## Dataset Details55 56### Dataset Description57 58<!-- Provide a longer summary of what this dataset is. -->59 60- **Curated by:** https://huggingface.co/LM-Polygraph61- **License:** https://github.com/IINemo/lm-polygraph/blob/main/LICENSE.md62 63### Dataset Sources [optional]64 65<!-- Provide the basic links for the dataset. -->66 67- **Repository:** https://github.com/IINemo/lm-polygraph68 69## Uses70 71<!-- Address questions around how the dataset is intended to be used. -->72 73### Direct Use74 75<!-- This section describes suitable use cases for the dataset. -->76 77This dataset should be used for performing benchmarks on LM-polygraph.78 79### Out-of-Scope Use80 81<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->82 83This dataset should not be used for further dataset preprocessing.84 85## Dataset Structure86 87<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->88 89This dataset contains the "continuation" subset, which corresponds to main dataset, used in LM-Polygraph. It may also contain other subsets, which correspond to instruct methods, used in LM-Polygraph.90 91Each subset contains two splits: train and test. Each split contains two string columns: "input", which corresponds to processed input for LM-Polygraph, and "output", which corresponds to processed output for LM-Polygraph.92 93## Dataset Creation94 95### Curation Rationale96 97<!-- Motivation for the creation of this dataset. -->98 99This dataset is created in order to separate dataset creation code from benchmarking code.100 101### Source Data102 103<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->104 105#### Data Collection and Processing106 107<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->108 109Data is collected from https://huggingface.co/datasets/samsum and processed by using https://github.com/IINemo/lm-polygraph/blob/main/dataset_builders/build_dataset.py script in repository.110 111#### Who are the source data producers?112 113<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->114 115People who created https://huggingface.co/datasets/samsum116 117## Bias, Risks, and Limitations118 119<!-- This section is meant to convey both technical and sociotechnical limitations. -->120 121This dataset contains the same biases, risks, and limitations as its source dataset https://huggingface.co/datasets/samsum122 123### Recommendations124 125<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->126 127Users should be made aware of the risks, biases and limitations of the dataset.128