Datasets:
| license: apache-2.0 | |
| task_categories: | |
| - text-generation | |
| - fill-mask | |
| language: | |
| - en | |
| size_categories: | |
| - 1B<n<10B | |
| # LM1B - One Billion Word Benchmark | |
| ## Dataset Description | |
| The One Billion Word Benchmark is a large language modeling dataset. | |
| It contains approximately one billion words of training data derived from news articles. | |
| ## How was this dataset built? | |
| We download the full LM1B dataset from TensorFlow Datasets (TFDS) and convert it to HuggingFace format automatically. The full script is in `lm1b.py`. The required environment is: | |
| - tensorflow==2.20.0 | |
| - tensorflow-datasets==4.9.9 | |
| - huggingface_hub==1.3.3 | |
| - datasets==4.4.1 | |
| ```bash | |
| pip install tensorflow==2.20.0 tensorflow-datasets==4.9.9 huggingface_hub==1.3.3 datasets==4.4.1 | |
| python lm1b_builder.py --action all | |
| ``` | |
| ## Dataset Structure | |
| ### Data Fields | |
| - `text`: A string containing the text content | |
| ### Data Splits | |
| | Split | Examples | | |
| |-------|----------| | |
| | train | 30,301,028 | | |
| | test | 306,688 | | |
| ## Citation | |
| ```bibtex | |
| @inproceedings{chelba2013one, | |
| title={One billion word benchmark for measuring progress in statistical language modeling}, | |
| author={Chelba, Ciprian and Mikolov, Tomas and Schuster, Mike and Ge, Qi and Brants, Thorsten and Koehn, Phillipp and Robinson, Tony}, | |
| booktitle={Interspeech}, | |
| year={2014} | |
| } | |
| ``` | |
| ## License | |
| Apache 2.0 | |