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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