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hmteams/flair-hipe-2022-ajmc-de
flair-hipe-2022-ajmc-de is a token classification model from hmteams. Use it when you need labels on individual words, such as names. It is set up for flair. The card lists the license as mit.
This Flair model was fine-tuned on the AjMC German NER Dataset using hmTEAMS as backbone LM.
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From the Hugging Face model README
This Flair model was fine-tuned on the AjMC German NER Dataset using hmTEAMS as backbone LM.
The AjMC dataset consists of NE-annotated historical commentaries in the field of Classics, and was created in the context of the Ajax MultiCommentary project.
The following NEs were annotated: pers, work, loc, object, date and scope.
We performed a hyper-parameter search over the following parameters with 5 different seeds per configuration:
[8, 4][3e-05, 5e-05]And report micro F1-score on development set:
| Configuration | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Avg. |
|---|---|---|---|---|---|---|
| bs4-e10-lr3e-05 | 0.8798 | 0.8771 | 0.8841 | 0.8905 | 0.8825 | 88.28 ± 0.45 |
| bs4-e10-lr5e-05 | 0.8856 | 0.8699 | 0.8819 | 0.8854 | 0.8786 | 88.03 ± 0.58 |
| bs8-e10-lr5e-05 | 0.8948 | 0.8685 | 0.8766 | 0.8726 | 0.8791 | 87.83 ± 0.9 |
| bs8-e10-lr3e-05 | 0.873 | 0.8851 | 0.8746 | 0.8785 | 0.8647 | 87.52 ± 0.67 |
The 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.
We thank Luisa März, Katharina Schmid and Erion Çano for their fruitful discussions about Historic Language Models.
Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC). Many Thanks for providing access to the TPUs ❤️