BERT_swedish-ner
This model is a fine-tuned version of KB/bert-base-swedish-cased on the wikiann dataset. It achieves the following results on the evaluation set:
- Loss: 0.1316
- Precision: 0.9340
- Recall: 0.9419
- F1: 0.9379
- Accuracy: 0.9800
Model description
Finetuned the model from KB/bert-base-swedish-cased for Swedish NER task. The model can classify three categories:
- PER (person names)
- LOC (Location)
- ORG (Organization)
Intended uses & limitations
NER, token classification
Training and evaluation data
wikiann-SV dataset
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1