hmByT5 - Preliminary Language Models
Preliminary Historic Multilingual and Monolingual ByT5 Models. Following languages are currently covered:
- Dutch (Delpher Corpus)
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.
This model was trained with mean_noise_span_length=20.
Evaluation on Downstream Tasks (NER)
We evaluated the hmByT5 model on ICDAR Europeana dataset:
| Configuration | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Avg. |
|---|---|---|---|---|---|---|
wsFalse-bs4-e10-lr0.00015-poolingfirst |
86.61 | 85.88 | 87.65 | 87.93 | 88.01 | 87.22 ± 0.83 |
wsFalse-bs8-e10-lr0.00015-poolingfirst |
87.88 | 87.56 | 85.62 | 86.52 | 87.03 | 86.92 ± 0.8 |
wsFalse-bs4-e10-lr0.00016-poolingfirst |
86.17 | 85.87 | 87.77 | 86.58 | 87.96 | 86.87 ± 0.85 |
wsFalse-bs8-e10-lr0.00016-poolingfirst |
87.67 | 86.02 | 85.66 | 87 | 85.99 | 86.47 ± 0.75 |
The results show no performance improvement of the model
trained with mean_noise_span_length=3, that achieved 87.90 ± 0.71.
Acknowledgements
Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC). Many Thanks for providing access to the TPUs ❤️
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