---
datasets:
- bs-la/xP3ru
license: bigscience-bloom-rail-1.0
model-index:
- name: bloomz-7b1
  results:
  - task:
      type: Coreference resolution
    dataset:
      type: Muennighoff/xwinograd
      name: XWinograd (ru)
      config: ru
      split: test
      revision: 9dd5ea5505fad86b7bedad667955577815300cee
    metrics:
    - type: Accuracy
      value: 53.97
  - task:
      type: Natural language inference
    dataset:
      type: xnli
      name: XNLI (ru)
      config: ru
      split: validation
      revision: a5a45e4ff92d5d3f34de70aaf4b72c3bdf9f7f16
    metrics:
    - type: Accuracy
      value: 33.49
  - task:
      type: Sentence completion
    dataset:
      type: Muennighoff/xstory_cloze
      name: XStoryCloze (ru)
      config: ru
      split: validation
      revision: 8bb76e594b68147f1a430e86829d07189622b90d
    metrics:
    - type: Accuracy
      value: 48.64 
---

# Model Summary

[bloom-7b1](https://huggingface.co/bigscience/bloom-7b1) finetuned on Russian multitask data. Hence the same as [bloomz-7b1](https://huggingface.co/bigscience/bloomz-7b1), but with **only** Russian finetuning data. 4b stands for 4 billion finetuning tokens (same as bloomz-7b1).

# Citation

```
BLOOM+1 - TODO
```

```bibtex
@misc{muennighoff2022crosslingual,
      title={Crosslingual Generalization through Multitask Finetuning}, 
      author={Niklas Muennighoff and Thomas Wang and Lintang Sutawika and Adam Roberts and Stella Biderman and Teven Le Scao and M Saiful Bari and Sheng Shen and Zheng-Xin Yong and Hailey Schoelkopf and Xiangru Tang and Dragomir Radev and Alham Fikri Aji and Khalid Almubarak and Samuel Albanie and Zaid Alyafeai and Albert Webson and Edward Raff and Colin Raffel},
      year={2022},
      eprint={2211.01786},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```