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: 0.8755
- recall: 0.8862
- f1: 0.8808
- accuracy: 0.9789
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: 3e-05
- weight_decay_rate: 0.01
- num_warmup_steps: 0
- fp16: True
Framework versions
- Transformers 4.21.3
- Datasets 1.18.0
- Tokenizers 0.12.1
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Dataset used to train HuggingAlex1247/gbert-large-germaner
Evaluation results
- precision on germanerself-reported0.876
- recall on germanerself-reported0.886
- f1 on germanerself-reported0.881
- accuracy on germanerself-reported0.979