---
license: apache-2.0
language:
- en
metrics:
- rouge
tags:
- nanoT5
datasets:
- allenai/c4
---

[Google's T5-v1.1-base](https://huggingface.co/google/t5-v1_1-base) pre-trained for 2^16 steps in [nanoT5](https://github.com/PiotrNawrot/nanoT5) library for efficient pre-training.

For more details about the model refer to the original [paper](https://arxiv.org/pdf/2002.05202.pdf) and original [model weights](https://huggingface.co/google/t5-v1_1-base).

This checkpoint was pre-trained on a single GPU for 20 hours. 
It can be further fine-tuned on SuperNatural-Instructions dataset to achieve 95% of the performance of the same model pre-trained through "a combination of model and data parallelism [...] on slices of Cloud TPU Pods", each with 1024 TPUs.