readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wikiann
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: funnel-transformer-xlarge_ner_wikiann
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: wikiann
        type: wikiann
        args: en
      metrics:
      - name: Precision
        type: precision
        value: 0.8522084990579862
      - name: Recall
        type: recall
        value: 0.8633535981903011
      - name: F1
        type: f1
        value: 0.8577448467184043
      - name: Accuracy
        type: accuracy
        value: 0.935805105791199
  ---
  
  <!-- 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. -->
  
  # funnel-transformer-xlarge_ner_wikiann
  
  This model is a fine-tuned version of [funnel-transformer/xlarge](https://huggingface.co/funnel-transformer/xlarge) on the wikiann dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4023
  - Precision: 0.8522
  - Recall: 0.8634
  - F1: 0.8577
  - Accuracy: 0.9358
  
  ## 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: 1e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: cosine
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.3193        | 1.0   | 5000  | 0.3116          | 0.8239    | 0.8296 | 0.8267 | 0.9260   |
  | 0.2836        | 2.0   | 10000 | 0.2846          | 0.8446    | 0.8498 | 0.8472 | 0.9325   |
  | 0.2237        | 3.0   | 15000 | 0.3258          | 0.8427    | 0.8542 | 0.8484 | 0.9332   |
  | 0.1303        | 4.0   | 20000 | 0.3801          | 0.8531    | 0.8634 | 0.8582 | 0.9362   |
  | 0.0867        | 5.0   | 25000 | 0.4023          | 0.8522    | 0.8634 | 0.8577 | 0.9358   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  