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metadata
language:
  - de
license: mit
datasets:
  - germaner
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: gbert-large-germaner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: germaner
          type: germaner
          args: default
        metrics:
          - name: precision
            type: precision
            value: 0.8693333333333333
          - name: recall
            type: recall
            value: 0.885640362225097
          - name: f1
            type: f1
            value: 0.8774110861903236
          - name: accuracy
            type: accuracy
            value: 0.9784210744831022

gbert-large-germaner

This model is a fine-tuned version of deepset/gbert-large on the germaner dataset. It achieves the following results on the evaluation set:

  • precision: 0.8693
  • recall: 0.8856
  • f1: 0.8774
  • accuracy: 0.9784

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: 8
  • eval_batch_size: 8
  • learning_rate: 2e-05
  • weight_decay_rate: 0.01
  • num_warmup_steps: 0
  • fp16: True

Framework versions

  • Transformers 4.18.0
  • Datasets 1.18.0
  • Tokenizers 0.12.1