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