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readme: add initial version of model card (#1)
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metadata
language: de
license: mit
tags:
  - flair
  - token-classification
  - sequence-tagger-model
base_model: dbmdz/bert-base-historic-multilingual-64k-td-cased
widget:
  - text: >-
      — Dramatiſch war der Stoff vor Sophokles von Äſchylos behandelt worden in
      den Θροῇσσαι , denen vielleicht in der Trilogie das Stüc>"OnJw» κοίσις
      vorherging , das Stück Σαλαμίνιαι folgte .

Fine-tuned Flair Model on AjMC German NER Dataset (HIPE-2022)

This Flair model was fine-tuned on the AjMC German NER Dataset using hmBERT 64k 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.

Results

We performed a hyper-parameter search over the following parameters with 5 different seeds per configuration:

  • Batch Sizes: [4, 8]
  • Learning Rates: [5e-05, 3e-05]

And report micro F1-score on development set:

Configuration Seed 1 Seed 2 Seed 3 Seed 4 Seed 5 Average
bs4-e10-lr3e-05 0.8806 0.8988 0.8967 0.8924 0.8994 0.8936 ± 0.0078
bs8-e10-lr5e-05 0.8951 0.8972 0.8933 0.8892 0.8902 0.893 ± 0.0033
bs4-e10-lr5e-05 0.8789 0.891 0.9012 0.891 0.8873 0.8899 ± 0.008
bs8-e10-lr3e-05 0.88 0.8889 0.8764 0.897 0.8948 0.8874 ± 0.009

The training log and TensorBoard logs (not available for hmBERT Base model) are also uploaded to the model hub.

More information about fine-tuning can be found here.

Acknowledgements

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 ❤️