readme: ---
  license: gpl-3.0
  tags:
  - generated_from_trainer
  datasets:
  - mim_gold_ner
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  widget:
  - text: Systurnar Guðrún og Monique átu einar á McDonalds og horfðu á Stöð 2, þar glitti í Bruce Willis leika í Die Hard 2.
  model-index:
  - name: IceBERT-finetuned-ner
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: mim_gold_ner
        type: mim_gold_ner
        args: mim-gold-ner
      metrics:
      - name: Precision
        type: precision
        value: 0.9351994710160899
      - name: Recall
        type: recall
        value: 0.9440427188786294
      - name: F1
        type: f1
        value: 0.9396002878813043
      - name: Accuracy
        type: accuracy
        value: 0.9920330921021648
  ---
  
  <!-- 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. -->
  
  # IceBERT-finetuned-ner
  
  This model is a fine-tuned version of [vesteinn/IceBERT](https://huggingface.co/vesteinn/IceBERT) on the mim_gold_ner dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0347
  - Precision: 0.9352
  - Recall: 0.9440
  - F1: 0.9396
  - Accuracy: 0.9920
  
  ## 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: 16
  - eval_batch_size: 16
  - 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.0568        | 1.0   | 2929 | 0.0386          | 0.9114    | 0.9162 | 0.9138 | 0.9897   |
  | 0.0325        | 2.0   | 5858 | 0.0325          | 0.9300    | 0.9363 | 0.9331 | 0.9912   |
  | 0.0184        | 3.0   | 8787 | 0.0347          | 0.9352    | 0.9440 | 0.9396 | 0.9920   |
  
  
  ### Framework versions
  
  - Transformers 4.11.0
  - Pytorch 1.9.0+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  