--- dataset_info: - config_name: continuation features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 250395957 num_examples: 108647 - name: test num_bytes: 17867381 num_examples: 7983 download_size: 34889442 dataset_size: 268263338 - config_name: empirical_baselines features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 273426556 num_examples: 108647 - name: test num_bytes: 19562658 num_examples: 7983 download_size: 37997246 dataset_size: 292989214 - config_name: ling_1s features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 374685568 num_examples: 108647 - name: test num_bytes: 27017106 num_examples: 7983 download_size: 47525580 dataset_size: 401702674 - config_name: simple_instruct features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 256281221 num_examples: 108647 - name: test num_bytes: 18302567 num_examples: 7983 download_size: 35717691 dataset_size: 274583788 - config_name: verb_1s_top1 features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 362502620 num_examples: 108647 - name: test num_bytes: 26125995 num_examples: 7983 download_size: 45610094 dataset_size: 388628615 - config_name: verb_1s_topk features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 423250785 num_examples: 108647 - name: test num_bytes: 30599799 num_examples: 7983 download_size: 50713294 dataset_size: 453850584 - config_name: verb_2s_cot features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 348364022 num_examples: 108647 - name: test num_bytes: 25084044 num_examples: 7983 download_size: 44216494 dataset_size: 373448066 - config_name: verb_2s_top1 features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 273426556 num_examples: 108647 - name: test num_bytes: 19562658 num_examples: 7983 download_size: 37997246 dataset_size: 292989214 - config_name: verb_2s_topk features: - name: input dtype: string - name: output dtype: string - name: stripped_input dtype: string splits: - name: train num_bytes: 301211218 num_examples: 108647 - name: test num_bytes: 21608703 num_examples: 7983 download_size: 40252015 dataset_size: 322819921 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: simple_instruct data_files: - split: train path: simple_instruct/train-* - split: test path: simple_instruct/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-* - config_name: verb_2s_topk data_files: - split: train path: verb_2s_topk/train-* - split: test path: verb_2s_topk/test-* --- # Dataset Card for coqa This is a preprocessed version of coqa 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/coqa 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/coqa ## Bias, Risks, and Limitations This dataset contains the same biases, risks, and limitations as its source dataset https://huggingface.co/datasets/coqa ### Recommendations Users should be made aware of the risks, biases and limitations of the dataset.