
## Dataset Description

- **Repository:** [openai/gpt2](https://github.com/openai/gpt-2)
- **Paper:** Radford et al. [Language Models are Unsupervised Multitask Learners](https://d4mucfpksywv.cloudfront.net/better-language-models/language-models.pdf)

### Dataset Summary

This dataset is comprised of the LAMBADA test split as pre-processed by OpenAI (see relevant discussions [here](https://github.com/openai/gpt-2/issues/131#issuecomment-497136199) and [here](https://github.com/huggingface/transformers/issues/491)). It also contains machine translated versions of the split in German, Spanish, French, and Italian.

LAMBADA is used to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative texts sharing the characteristic that human subjects are able to guess their last word if they are exposed to the whole text, but not if they only see the last sentence preceding the target word. To succeed on LAMBADA, computational models cannot simply rely on local context, but must be able to keep track of information in the broader discourse.


### Languages

English, German, Spanish, French, and Italian.

### Source Data

For non-English languages, the data splits were produced by Google Translate. See the [`translation_script.py`](translation_script.py) for more details.

## Additional Information

### Hash Checksums

For data integrity checks we leave the following checksums for the files in this dataset:

| File Name                                                                | Checksum (SHA-256)                                               |
|--------------------------------------------------------------------------|------------------------------------------------------------------|
| lambada_test_de.jsonl                                                    | 51c6c1795894c46e88e4c104b5667f488efe79081fb34d746b82b8caa663865e |
| [openai/lambada_test.jsonl](https://openaipublic.blob.core.windows.net/gpt-2/data/lambada_test.jsonl) | 4aa8d02cd17c719165fc8a7887fddd641f43fcafa4b1c806ca8abc31fabdb226 |
| lambada_test_en.jsonl                                                    | 4aa8d02cd17c719165fc8a7887fddd641f43fcafa4b1c806ca8abc31fabdb226 |
| lambada_test_es.jsonl                                                    | ffd760026c647fb43c67ce1bc56fd527937304b348712dce33190ea6caba6f9c |
| lambada_test_fr.jsonl                                                    | 941ec6a73dba7dc91c860bf493eb66a527cd430148827a4753a4535a046bf362 |
| lambada_test_it.jsonl                                                    | 86654237716702ab74f42855ae5a78455c1b0e50054a4593fb9c6fcf7fad0850 |

### Licensing

License: [Modified MIT](https://github.com/openai/gpt-2/blob/master/LICENSE)

### Citation

```bibtex
@article{radford2019language,
  title={Language Models are Unsupervised Multitask Learners},
  author={Radford, Alec and Wu, Jeff and Child, Rewon and Luan, David and Amodei, Dario and Sutskever, Ilya},
  year={2019}
}
```

```bibtex
@misc{
    author={Paperno, Denis and Kruszewski, Germán and Lazaridou, Angeliki and Pham, Quan Ngoc and Bernardi, Raffaella and Pezzelle, Sandro and Baroni, Marco and Boleda, Gemma and Fernández, Raquel},
    title={The LAMBADA dataset},
    DOI={10.5281/zenodo.2630551},
    publisher={Zenodo},
    year={2016},
    month={Aug}
}
```

### Contributions

Thanks to Sid Black ([@sdtblck](https://github.com/sdtblck)) for translating the `lambada_openai` dataset into the non-English languages.

Thanks to Jonathan Tow ([@jon-tow](https://github.com/jon-tow)) for adding this dataset. 

task_ids:language-modeling language_creators:machine-generated multilinguality:translation size_categories:1K<n<10K source_datasets:lambada language:de language:en language:es language:fr language:it license:mit region:us
{"language_creators": ["machine-generated"], "language": ["de", "en", "es", "fr", "it"], "license": "mit", "multilinguality": ["translation"], "size_categories": ["1K<n<10K"], "source_datasets": ["lambada"], "task_ids": ["language-modeling"], "pretty_name": "LAMBADA OpenAI", "dataset_info": [{"config_name": "default", "features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1709449, "num_examples": 5153}], "download_size": 1819752, "dataset_size": 1709449}, {"config_name": "de", "features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1904576, "num_examples": 5153}], "download_size": 1985231, "dataset_size": 1904576}, {"config_name": "en", "features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1709449, "num_examples": 5153}], "download_size": 1819752, "dataset_size": 1709449}, {"config_name": "es", "features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1821735, "num_examples": 5153}], "download_size": 1902349, "dataset_size": 1821735}, {"config_name": "fr", "features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1948795, "num_examples": 5153}], "download_size": 2028703, "dataset_size": 1948795}, {"config_name": "it", "features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "test", "num_bytes": 1813420, "num_examples": 5153}], "download_size": 1894613, "dataset_size": 1813420}]}
TAGS
#task_ids-language-modeling #language_creators-machine-generated #multilinguality-translation #size_categories-1K<n<10K #source_datasets-lambada #language-German #language-English #language-Spanish #language-French #language-Italian #license-mit #region-us 

Dataset Description
-------------------


* Repository: openai/gpt2
* Paper: Radford et al. Language Models are Unsupervised Multitask Learners


### Dataset Summary


This dataset is comprised of the LAMBADA test split as pre-processed by OpenAI (see relevant discussions here and here). It also contains machine translated versions of the split in German, Spanish, French, and Italian.


LAMBADA is used to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative texts sharing the characteristic that human subjects are able to guess their last word if they are exposed to the whole text, but not if they only see the last sentence preceding the target word. To succeed on LAMBADA, computational models cannot simply rely on local context, but must be able to keep track of information in the broader discourse.


### Languages


English, German, Spanish, French, and Italian.


### Source Data


For non-English languages, the data splits were produced by Google Translate. See the 'translation\_script.py' for more details.


Additional Information
----------------------


### Hash Checksums


For data integrity checks we leave the following checksums for the files in this dataset:



### Licensing


License: Modified MIT


### Contributions


Thanks to Sid Black (@sdtblck) for translating the 'lambada\_openai' dataset into the non-English languages.


Thanks to Jonathan Tow (@jon-tow) for adding this dataset.



### Dataset Summary


This dataset is comprised of the LAMBADA test split as pre-processed by OpenAI (see relevant discussions here and here). It also contains machine translated versions of the split in German, Spanish, French, and Italian.


LAMBADA is used to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative texts sharing the characteristic that human subjects are able to guess their last word if they are exposed to the whole text, but not if they only see the last sentence preceding the target word. To succeed on LAMBADA, computational models cannot simply rely on local context, but must be able to keep track of information in the broader discourse. ### Languages


English, German, Spanish, French, and Italian. ### Source Data


For non-English languages, the data splits were produced by Google Translate. See the 'translation\_script.py' for more details.


Additional Information
---------------------- ### Hash Checksums


For data integrity checks we leave the following checksums for the files in this dataset: ### Licensing


License: Modified MIT ### Contributions


Thanks to Sid Black (@sdtblck) for translating the 'lambada\_openai' dataset into the non-English languages.


Thanks to Jonathan Tow (@jon-tow) for adding this dataset.
TAGS
#task_ids-language-modeling #language_creators-machine-generated #multilinguality-translation #size_categories-1K<n<10K #source_datasets-lambada #language-German #language-English #language-Spanish #language-French #language-Italian #license-mit #region-us 
 ### Dataset Summary


This dataset is comprised of the LAMBADA test split as pre-processed by OpenAI (see relevant discussions here and here). It also contains machine translated versions of the split in German, Spanish, French, and Italian.


LAMBADA is used to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative texts sharing the characteristic that human subjects are able to guess their last word if they are exposed to the whole text, but not if they only see the last sentence preceding the target word. To succeed on LAMBADA, computational models cannot simply rely on local context, but must be able to keep track of information in the broader discourse. ### Languages


English, German, Spanish, French, and Italian. ### Source Data


For non-English languages, the data splits were produced by Google Translate. See the 'translation\_script.py' for more details.


Additional Information
---------------------- ### Hash Checksums


For data integrity checks we leave the following checksums for the files in this dataset: ### Licensing


License: Modified MIT ### Contributions


Thanks to Sid Black (@sdtblck) for translating the 'lambada\_openai' dataset into the non-English languages.


Thanks to Jonathan Tow (@jon-tow) for adding this dataset.