gbert-base-germaner / README.md
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metadata
language:
  - de
license: mit
base_model: deepset/gbert-base
datasets:
  - germaner
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: gbert-base-germaner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: germaner
          type: germaner
          args: default
        metrics:
          - name: precision
            type: precision
            value: 0.8403996101364523
          - name: recall
            type: recall
            value: 0.8674547283702213
          - name: f1
            type: f1
            value: 0.8537128712871287
          - name: accuracy
            type: accuracy
            value: 0.9760785008915815

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: 0.8404
  • recall: 0.8675
  • f1: 0.8537
  • accuracy: 0.9761

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-06
  • weight_decay_rate: 0.01
  • num_warmup_steps: 0
  • fp16: True

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3