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hmteams/teams-base-historic-multilingual-generator
teams-base-historic-multilingual-generator is a fill-mask model from hmteams. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as apache-2.0.
[](https://github.com/stefan-it/hmTEAMS)
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From the Hugging Face model README
Historic Multilingual and Monolingual TEAMS Models. The following languages are covered:
We pretrain a "Training ELECTRA Augmented with Multi-word Selection" (TEAMS) model:
We perform experiments on various historic NER datasets, such as HIPE-2022 or ICDAR Europeana. All details incl. hyper-parameters can be found here.
We test our pretrained language models on various datasets from HIPE-2020, HIPE-2022 and Europeana. The following table shows an overview of used datasets.
| Language | Dataset | Additional Dataset |
|---|---|---|
| English | AjMC | - |
| German | AjMC | - |
| French | AjMC | ICDAR-Europeana |
| Finnish | NewsEye | - |
| Swedish | NewsEye | - |
| Dutch | ICDAR-Europeana | - |
| Model | English AjMC | German AjMC | French AjMC | Finnish NewsEye | Swedish NewsEye | Dutch ICDAR | French ICDAR | Avg. |
|---|---|---|---|---|---|---|---|---|
| hmBERT (32k) Schweter et al. | 85.36 ± 0.94 | 89.08 ± 0.09 | 85.10 ± 0.60 | 77.28 ± 0.37 | 82.85 ± 0.83 | 82.11 ± 0.61 | 77.21 ± 0.16 | 82.71 |
| hmTEAMS (Ours) | 86.41 ± 0.36 | 88.64 ± 0.42 | 85.41 ± 0.67 | 79.27 ± 1.88 | 82.78 ± 0.60 | 88.21 ± 0.39 | 78.03 ± 0.39 | 84.11 |
Our pretrained hmTEAMS model can be obtained from the Hugging Face Model Hub:
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 ❤️