readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wnut_17
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: funnel-transformer-xlarge_ner_wnut_17
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: wnut_17
        type: wnut_17
        args: wnut_17
      metrics:
      - name: Precision
        type: precision
        value: 0.7205240174672489
      - name: Recall
        type: recall
        value: 0.5921052631578947
      - name: F1
        type: f1
        value: 0.650032829940906
      - name: Accuracy
        type: accuracy
        value: 0.9619810541038846
  ---
  
  <!-- 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_wnut_17
  
  This model is a fine-tuned version of [funnel-transformer/xlarge](https://huggingface.co/funnel-transformer/xlarge) on the wnut_17 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2453
  - Precision: 0.7205
  - Recall: 0.5921
  - F1: 0.6500
  - Accuracy: 0.9620
  
  ## 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: cosine
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 213  | 0.2331          | 0.6897    | 0.4067 | 0.5117 | 0.9462   |
  | No log        | 2.0   | 426  | 0.2056          | 0.7097    | 0.5526 | 0.6214 | 0.9587   |
  | 0.1454        | 3.0   | 639  | 0.2379          | 0.7102    | 0.5658 | 0.6298 | 0.9600   |
  | 0.1454        | 4.0   | 852  | 0.2397          | 0.7141    | 0.5885 | 0.6452 | 0.9620   |
  | 0.0319        | 5.0   | 1065 | 0.2453          | 0.7205    | 0.5921 | 0.6500 | 0.9620   |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  