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