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flair-hipe-2022-topres19th-en
hmbert-tiny/flair-hipe-2022-topres19th-en
flair-hipe-2022-topres19th-en is a token classification model from hmbert-tiny. 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 TopRes19th English NER Dataset using hmBERT Tiny as backbone LM.
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At a glance
- Task
- Token Classification
- Library
- flair
- License
- mit
- Access
- Public
- Created
- Oct 20, 2023
- Updated
- Oct 24, 2023
- SHA
- 88151bdc
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Base models
Model card
From the Hugging Face model README
Fine-tuned Flair Model on TopRes19th English NER Dataset (HIPE-2022)
This Flair model was fine-tuned on the TopRes19th English NER Dataset using hmBERT Tiny as backbone LM.
The TopRes19th dataset consists of NE-annotated historical English newspaper articles from 19C.
The following NEs were annotated: BUILDING, LOC and STREET.
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-lr5e-05 | 0.6681 | 0.5754 | 0.628 | 0.6565 | 0.658 | 0.6372 ± 0.0376 |
bs8-e10-lr5e-05 | 0.6491 | 0.5812 | 0.565 | 0.587 | 0.5938 | 0.5952 ± 0.0319 |
bs4-e10-lr3e-05 | 0.6154 | 0.5782 | 0.5519 | 0.5929 | 0.5931 | 0.5863 ± 0.0234 |
bs8-e10-lr3e-05 | 0.5978 | 0.5489 | 0.528 | 0.5483 | 0.5754 | 0.5597 ± 0.0272 |
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 ❤️
- Task
- Token Classification
- Library
- flair
- License
- mit
- Languages
- en
- Created
- Oct 20, 2023
- Updated
- Oct 24, 2023