readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - wikiann
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  inference: false
  language:
  - sk
  model-index:
  - name: bertoslav-limited-ner
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: wikiann sk
        type: wikiann
        args: sk
      metrics:
      - name: Precision
        type: precision
        value: 0.8985571260306242
      - name: Recall
        type: recall
        value: 0.9173994738819993
      - name: F1
        type: f1
        value: 0.9078805459481573
      - name: Accuracy
        type: accuracy
        value: 0.9700235061239639
  ---
  
  # Named Entity Recognition based on bertoslav-limited
  
  This model is a fine-tuned version of [crabz/bertoslav-limited](https://huggingface.co/crabz/bertoslav-limited) on the Slovak wikiann dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2119
  - Precision: 0.8986
  - Recall: 0.9174
  - F1: 0.9079
  - Accuracy: 0.9700
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 5e-05
  - train_batch_size: 24
  - eval_batch_size: 24
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.2953        | 1.0   | 834  | 0.1516          | 0.8413    | 0.8647 | 0.8529 | 0.9549   |
  | 0.0975        | 2.0   | 1668 | 0.1304          | 0.8787    | 0.9056 | 0.8920 | 0.9658   |
  | 0.0487        | 3.0   | 2502 | 0.1405          | 0.8916    | 0.8958 | 0.8937 | 0.9660   |
  | 0.025         | 4.0   | 3336 | 0.1658          | 0.8850    | 0.9116 | 0.8981 | 0.9669   |
  | 0.0161        | 5.0   | 4170 | 0.1739          | 0.8974    | 0.9127 | 0.9050 | 0.9693   |
  | 0.0074        | 6.0   | 5004 | 0.1888          | 0.8900    | 0.9144 | 0.9020 | 0.9687   |
  | 0.0051        | 7.0   | 5838 | 0.1996          | 0.8946    | 0.9145 | 0.9044 | 0.9693   |
  | 0.0039        | 8.0   | 6672 | 0.2052          | 0.8993    | 0.9158 | 0.9075 | 0.9697   |
  | 0.0024        | 9.0   | 7506 | 0.2112          | 0.8946    | 0.9171 | 0.9057 | 0.9696   |
  | 0.0018        | 10.0  | 8340 | 0.2119          | 0.8986    | 0.9174 | 0.9079 | 0.9700   |
  
  
  ### Framework versions
  
  - Transformers 4.14.0.dev0
  - Pytorch 1.10.0
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  