metadata

tags:
  - generated_from_trainer
language:
  - swe
datasets:
  - wikiann
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: BERT_swedish-ner
    results:
      - task:
          name: Token Classification
          type: token-classification
        dataset:
          name: wikiann
          type: wikiann
          config: sv
          split: train
          args: sv
        metrics:
          - name: Precision
            type: precision
            value: 0.9340386115444618
          - name: Recall
            type: recall
            value: 0.9418907624993855
          - name: F1
            type: f1
            value: 0.9379482534942355
          - name: Accuracy
            type: accuracy
            value: 0.979997105690534

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.

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