| # Dataset Card for "Scored-Summarization-datasets" | |
| A collection of Text summarization datasets geared towards training a multi-purpose text summarizer. | |
| Each dataset is a parquet file with the following features. | |
| #### default | |
| - `text`: a `string` feature. The `source` document | |
| - `summary`: a `string` feature. The summary of the document | |
| - `provenance`: a `string` feature. Information about the sub dataset. | |
| - `t5_text_token_count`: a `int64` feature. The number of tokens the text is encoded in. | |
| - `t5_summary_token_count `: a `int64` feature. The number of tokens the summary is encoded in. | |
| - `contriever_cos`: a `float64` feature. The Cosine Similarity of the Contriever text embedding and Contriever summary embedding. | |
| ### Sub-datasets | |
| - billsum | |
| - cnn_dailymail/3.0.0 | |
| - multixscience | |
| - newsroom | |
| - samsum | |
| - scitldr/AIC | |
| - tldr-challenge | |
| - wikihow | |
| - xsum | |
| Information about the Contriever model can be found here: https://github.com/facebookresearch/contriever. | |