Edit model card

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
Downloads last month
22
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train philschmid/gbert-base-germaner

Evaluation results