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readme: add initial version of model card (#1)
babdd35
metadata
language: fr
license: mit
tags:
  - flair
  - token-classification
  - sequence-tagger-model
base_model: hmteams/teams-base-historic-multilingual-discriminator
widget:
  - text: >-
      Nous recevons le premier numéro d ' un nouveau journal , le Radical -
      Libéral , qui paraîtra à Genève deux fois la semaine . Son but est de
      représenter l ' élément national du radicalisme genevois , en d ' autres
      termes , de défendre la politique intransigeante do M . Carteret , en
      opposition aux tendances du groupe _ > dont le Genevois est l ' organe .
      Bétail .

Fine-tuned Flair Model on French HIPE-2020 Dataset (HIPE-2022)

This Flair model was fine-tuned on the French HIPE-2020 NER Dataset using hmTEAMS as backbone LM.

The HIPE-2020 dataset is comprised of newspapers from mid 19C to mid 20C. For information can be found here.

The following NEs were annotated: loc, org, pers, prod, time and comp.

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 0.8652 0.8552 0.8526 0.8585 0.8615 85.86 ± 0.45
bs4-e10-lr3e-05 0.8602 0.8556 0.8512 0.8511 0.8595 85.55 ± 0.39
bs8-e10-lr5e-05 0.85 0.8592 0.8534 0.8473 0.8505 85.21 ± 0.41
bs4-e10-lr5e-05 0.839 0.8473 0.8385 0.839 0.8488 84.25 ± 0.45

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.

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 ❤️