dataset_info:
- config_name: continuation
features:
- name: input
dtype: string
- name: output
sequence: string
- name: stripped_input
dtype: string
splits:
- name: train
num_bytes: 163781224
num_examples: 138384
- name: test
num_bytes: 21361028
num_examples: 17944
download_size: 52689348
dataset_size: 185142252
- config_name: empirical_baselines
features:
- name: input
dtype: string
- name: output
sequence: string
- name: stripped_input
dtype: string
splits:
- name: train
num_bytes: 207510568
num_examples: 138384
- name: test
num_bytes: 27031332
num_examples: 17944
download_size: 56458671
dataset_size: 234541900
- config_name: ling_1s
features:
- name: input
dtype: string
- name: output
sequence: string
- name: stripped_input
dtype: string
splits:
- name: train
num_bytes: 309361192
num_examples: 138384
- name: test
num_bytes: 40238116
num_examples: 17944
download_size: 65304933
dataset_size: 349599308
- config_name: verb_1s_top1
features:
- name: input
dtype: string
- name: output
sequence: string
- name: stripped_input
dtype: string
splits:
- name: train
num_bytes: 289710664
num_examples: 138384
- name: test
num_bytes: 37690068
num_examples: 17944
download_size: 63254756
dataset_size: 327400732
- config_name: verb_1s_topk
features:
- name: input
dtype: string
- name: output
sequence: string
- name: stripped_input
dtype: string
splits:
- name: train
num_bytes: 349630936
num_examples: 138384
- name: test
num_bytes: 45459820
num_examples: 17944
download_size: 68270335
dataset_size: 395090756
- config_name: verb_2s_cot
features:
- name: input
dtype: string
- name: output
sequence: string
- name: stripped_input
dtype: string
splits:
- name: train
num_bytes: 276979336
num_examples: 138384
- name: test
num_bytes: 36039220
num_examples: 17944
download_size: 61803930
dataset_size: 313018556
- config_name: verb_2s_top1
features:
- name: input
dtype: string
- name: output
sequence: string
- name: stripped_input
dtype: string
splits:
- name: train
num_bytes: 207510568
num_examples: 138384
- name: test
num_bytes: 27031332
num_examples: 17944
download_size: 56458671
dataset_size: 234541900
configs:
- config_name: continuation
data_files:
- split: train
path: continuation/train-*
- split: test
path: continuation/test-*
- config_name: empirical_baselines
data_files:
- split: train
path: empirical_baselines/train-*
- split: test
path: empirical_baselines/test-*
- config_name: ling_1s
data_files:
- split: train
path: ling_1s/train-*
- split: test
path: ling_1s/test-*
- config_name: verb_1s_top1
data_files:
- split: train
path: verb_1s_top1/train-*
- split: test
path: verb_1s_top1/test-*
- config_name: verb_1s_topk
data_files:
- split: train
path: verb_1s_topk/train-*
- split: test
path: verb_1s_topk/test-*
- config_name: verb_2s_cot
data_files:
- split: train
path: verb_2s_cot/train-*
- split: test
path: verb_2s_cot/test-*
- config_name: verb_2s_top1
data_files:
- split: train
path: verb_2s_top1/train-*
- split: test
path: verb_2s_top1/test-*
Dataset Card for triviaqa
This is a preprocessed version of triviaqa dataset for benchmarks in LM-Polygraph.
Dataset Details
Dataset Description
- Curated by: https://huggingface.co/LM-Polygraph
- License: https://github.com/IINemo/lm-polygraph/blob/main/LICENSE.md
Dataset Sources [optional]
- Repository: https://github.com/IINemo/lm-polygraph
Uses
Direct Use
This dataset should be used for performing benchmarks on LM-polygraph.
Out-of-Scope Use
This dataset should not be used for further dataset preprocessing.
Dataset Structure
This 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.
Each 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.
Dataset Creation
Curation Rationale
This dataset is created in order to separate dataset creation code from benchmarking code.
Source Data
Data Collection and Processing
Data is collected from https://huggingface.co/datasets/triviaqa and processed by using https://github.com/IINemo/lm-polygraph/blob/main/dataset_builders/build_dataset.py script in repository.
Who are the source data producers?
People who created https://huggingface.co/datasets/triviaqa
Bias, Risks, and Limitations
This dataset contains the same biases, risks, and limitations as its source dataset https://huggingface.co/datasets/triviaqa
Recommendations
Users should be made aware of the risks, biases and limitations of the dataset.