readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: bert-finetuned-ner_swedish_small_set_health_and_prices
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # bert-finetuned-ner_swedish_small_set_health_and_prices
  
  This model is a fine-tuned version of [KBLab/bert-base-swedish-cased-ner](https://huggingface.co/KBLab/bert-base-swedish-cased-ner) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0942
  - Precision: 0.7709
  - Recall: 0.8118
  - F1: 0.7908
  - Accuracy: 0.9741
  
  ## 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:
  - learning_rate: 2e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 250  | 0.1310          | 0.6116    | 0.7471 | 0.6726 | 0.9578   |
  | 0.1583        | 2.0   | 500  | 0.0939          | 0.7560    | 0.8020 | 0.7783 | 0.9737   |
  | 0.1583        | 3.0   | 750  | 0.0942          | 0.7709    | 0.8118 | 0.7908 | 0.9741   |
  
  
  ### Framework versions
  
  - Transformers 4.19.3
  - Pytorch 1.7.1
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  