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---
language: en
license: mit
tags:
- flair
- token-classification
- sequence-tagger-model
base_model: hmteams/teams-base-historic-multilingual-discriminator
widget:
- text: On Wednesday , a public dinner was given by the Conservative Burgesses of
Leads , to the Conservative members of the Leeds Town Council , in the Music Hall
, Albion-street , which was very numerously attended .
---
# Fine-tuned Flair Model on TopRes19th English NER Dataset (HIPE-2022)
This Flair model was fine-tuned on the
[TopRes19th English](https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-topres19th.md)
NER Dataset using hmTEAMS as backbone LM.
The TopRes19th dataset consists of NE-annotated historical English newspaper articles from 19C.
The following NEs were annotated: `BUILDING`, `LOC` and `STREET`.
# Results
We performed a hyper-parameter search over the following parameters with 5 different seeds per configuration:
* Batch Sizes: `[8, 4]`
* Learning Rates: `[3e-05, 5e-05]`
And report micro F1-score on development set:
| Configuration | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Avg. |
|-----------------|--------------|--------------|--------------|--------------|--------------|--------------|
| bs8-e10-lr3e-05 | [0.8089][1] | [0.8137][2] | [0.8083][3] | [0.8145][4] | [0.8082][5] | 81.07 ± 0.28 |
| bs4-e10-lr3e-05 | [0.8068][6] | [0.8008][7] | [0.8195][8] | [0.8086][9] | [0.8049][10] | 80.81 ± 0.63 |
| bs8-e10-lr5e-05 | [0.818][11] | [0.795][12] | [0.7992][13] | [0.804][14] | [0.7938][15] | 80.2 ± 0.88 |
| bs4-e10-lr5e-05 | [0.8109][16] | [0.8114][17] | [0.7951][18] | [0.7901][19] | [0.795][20] | 80.05 ± 0.89 |
[1]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1
[2]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-2
[3]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3
[4]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-4
[5]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5
[6]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1
[7]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-2
[8]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3
[9]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-4
[10]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5
[11]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-1
[12]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2
[13]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3
[14]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4
[15]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-5
[16]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-1
[17]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2
[18]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3
[19]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4
[20]: https://hf.co/stefan-it/hmbench-topres19th-en-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-5
The [training log](training.log) and TensorBoard logs (only for hmByT5 and hmTEAMS based models) are also uploaded to the model hub.
More information about fine-tuning can be found [here](https://github.com/stefan-it/hmBench).
# Acknowledgements
We thank [Luisa März](https://github.com/LuisaMaerz), [Katharina Schmid](https://github.com/schmika) and
[Erion Çano](https://github.com/erionc) for their fruitful discussions about Historic Language Models.
Research supported with Cloud TPUs from Google's [TPU Research Cloud](https://sites.research.google/trc/about/) (TRC).
Many Thanks for providing access to the TPUs ❤️
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