hmByT5 - Preliminary Language Models
Preliminary Historic Multilingual and Monolingual ByT5 Models. Following languages are currently covered:
- English (British Library Corpus - Books)
More details can be found in our GitHub repository.
Pretraining
We use the official JAX/FLAX example in Hugging Face Transformers to pretrain a ByT5 model on a single v3-8 TPU. Details about the training can be found here.
Evaluation on Downstream Tasks (NER)
We evaluated the hmByT5 Base model on English AjMC dataset:
Configuration | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Avg. |
---|---|---|---|---|---|---|
wsFalse-bs4-e10-lr0.00015-poolingfirst |
86.78 | 87.46 | 85.75 | 88.41 | 86.6 | 87.0 ± 0.89 |
wsFalse-bs8-e10-lr0.00016-poolingfirst |
86.79 | 86.29 | 86.67 | 87.14 | 85.82 | 86.54 ± 0.45 |
wsFalse-bs4-e10-lr0.00016-poolingfirst |
87.04 | 87.34 | 86.63 | 84.09 | 87.04 | 86.43 ± 1.19 |
wsFalse-bs8-e10-lr0.00015-poolingfirst |
86.87 | 86.43 | 86.88 | 85.15 | 85.25 | 86.12 ± 0.77 |
The ByT5 Small model achieves 85.65 ± 1.21 on this dataset.
Acknowledgements
Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC). Many Thanks for providing access to the TPUs ❤️
- Downloads last month
- 16
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.