YAML Metadata
Error:
"widget[0]" must be of type object
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
- Downloads last month
- 22
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Dataset used to train hkaraoguz/BERT_swedish-ner
Evaluation results
- Precision on wikiannself-reported0.934
- Recall on wikiannself-reported0.942
- F1 on wikiannself-reported0.938
- Accuracy on wikiannself-reported0.980