readme: add initial version of model card (#1)
Browse files- readme: add initial version of model card (912f8b13c64b3f7ecd451757fcf8b66766dcd727)
README.md
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---
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language: de
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license: mit
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tags:
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- flair
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- token-classification
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- sequence-tagger-model
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base_model: hmteams/teams-base-historic-multilingual-discriminator
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widget:
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- text: — Dramatiſch war der Stoff vor Sophokles von Äſchylos behandelt worden in
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den Θροῇσσαι , denen vielleicht in der Trilogie das Stüc>"OnJw» κοίσις vorherging
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, das Stück Σαλαμίνιαι folgte .
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---
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# Fine-tuned Flair Model on AjMC German NER Dataset (HIPE-2022)
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This Flair model was fine-tuned on the
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[AjMC German](https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-ajmc.md)
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NER Dataset using hmTEAMS as backbone LM.
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The AjMC dataset consists of NE-annotated historical commentaries in the field of Classics,
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and was created in the context of the [Ajax MultiCommentary](https://mromanello.github.io/ajax-multi-commentary/)
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project.
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The following NEs were annotated: `pers`, `work`, `loc`, `object`, `date` and `scope`.
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# Results
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We performed a hyper-parameter search over the following parameters with 5 different seeds per configuration:
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* Batch Sizes: `[8, 4]`
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* Learning Rates: `[3e-05, 5e-05]`
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And report micro F1-score on development set:
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| Configuration | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Avg. |
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|-----------------|--------------|--------------|--------------|--------------|--------------|--------------|
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| bs4-e10-lr3e-05 | [0.8798][1] | [0.8771][2] | [0.8841][3] | [0.8905][4] | [0.8825][5] | 88.28 ± 0.45 |
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| bs4-e10-lr5e-05 | [0.8856][6] | [0.8699][7] | [0.8819][8] | [0.8854][9] | [0.8786][10] | 88.03 ± 0.58 |
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| bs8-e10-lr5e-05 | [0.8948][11] | [0.8685][12] | [0.8766][13] | [0.8726][14] | [0.8791][15] | 87.83 ± 0.9 |
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| bs8-e10-lr3e-05 | [0.873][16] | [0.8851][17] | [0.8746][18] | [0.8785][19] | [0.8647][20] | 87.52 ± 0.67 |
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[1]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1
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[2]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-2
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[3]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3
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[4]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-4
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[5]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5
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[6]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-1
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[7]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2
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[8]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3
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[9]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4
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[10]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-5
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[11]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-1
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[12]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2
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[13]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-3
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[14]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4
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[15]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-5
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[16]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1
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[17]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-2
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[18]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-3
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[19]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-4
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[20]: https://hf.co/stefan-it/hmbench-ajmc-de-hmteams-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-5
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The [training log](training.log) and TensorBoard logs (only for hmByT5 and hmTEAMS based models) are also uploaded to the model hub.
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More information about fine-tuning can be found [here](https://github.com/stefan-it/hmBench).
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# Acknowledgements
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We thank [Luisa März](https://github.com/LuisaMaerz), [Katharina Schmid](https://github.com/schmika) and
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[Erion Çano](https://github.com/erionc) for their fruitful discussions about Historic Language Models.
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Research supported with Cloud TPUs from Google's [TPU Research Cloud](https://sites.research.google/trc/about/) (TRC).
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Many Thanks for providing access to the TPUs ❤️
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