readme: ---
  license: cc-by-nc-sa-4.0
  tags:
  - generated_from_trainer
  datasets:
  - skript
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: wikineural-multilingual-ner-finetuned-ner
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: skript
        type: skript
        config: myscript
        split: train
        args: myscript
      metrics:
      - name: Precision
        type: precision
        value: 0.9007335298553506
      - name: Recall
        type: recall
        value: 0.9301946902654867
      - name: F1
        type: f1
        value: 0.9152270827528559
      - name: Accuracy
        type: accuracy
        value: 0.9653644982020269
  ---
  
  <!-- 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. -->
  
  # wikineural-multilingual-ner-finetuned-ner
  
  This model is a fine-tuned version of [Babelscape/wikineural-multilingual-ner](https://huggingface.co/Babelscape/wikineural-multilingual-ner) on the skript dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1243
  - Precision: 0.9007
  - Recall: 0.9302
  - F1: 0.9152
  - Accuracy: 0.9654
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 298  | 0.1179          | 0.8975    | 0.8981 | 0.8978 | 0.9592   |
  | 0.104         | 2.0   | 596  | 0.1161          | 0.9051    | 0.9201 | 0.9126 | 0.9648   |
  | 0.104         | 3.0   | 894  | 0.1243          | 0.9007    | 0.9302 | 0.9152 | 0.9654   |
  
  
  ### Framework versions
  
  - Transformers 4.21.0
  - Pytorch 1.12.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  