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
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Finetuned from
Dataset used to train pankaj10034/gbert-base-germaner
Evaluation results
- precision on germanerself-reported0.840
- recall on germanerself-reported0.867
- f1 on germanerself-reported0.854
- accuracy on germanerself-reported0.976