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gbert-base-germaner
philschmid/gbert-base-germaner
gbert-base-germaner is a token classification model from philschmid. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jan 4, 2022
- SHA
- 98c1dc95
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Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
gbert-base-germaner
This model is a fine-tuned version of deepset/gbert-base on the germaner dataset. It achieves the following results on the evaluation set:
- precision: 0.8521
- recall: 0.8754
- f1: 0.8636
- accuracy: 0.9761
If you want to learn how to fine-tune BERT yourself using Keras and Tensorflow check out this blog post:
https://www.philschmid.de/huggingface-transformers-keras-tf
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- num_train_epochs: 5
- train_batch_size: 16
- eval_batch_size: 32
- learning_rate: 2e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True
Framework versions
- Transformers 4.14.1
- Datasets 1.16.1
- Tokenizers 0.10.3
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- de
- Created
- Mar 2, 2022
- Updated
- Jan 4, 2022