readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - tagged_uni500v6_wikigold_split
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: Tagged_Uni_500v6_NER_Model_3Epochs_AUGMENTED
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: tagged_uni500v6_wikigold_split
        type: tagged_uni500v6_wikigold_split
        args: default
      metrics:
      - name: Precision
        type: precision
        value: 0.699155524278677
      - name: Recall
        type: recall
        value: 0.6986638537271449
      - name: F1
        type: f1
        value: 0.6989096025325361
      - name: Accuracy
        type: accuracy
        value: 0.9317908843795436
  ---
  
  <!-- 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. -->
  
  # Tagged_Uni_500v6_NER_Model_3Epochs_AUGMENTED
  
  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the tagged_uni500v6_wikigold_split dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2386
  - Precision: 0.6992
  - Recall: 0.6987
  - F1: 0.6989
  - Accuracy: 0.9318
  
  ## 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: 8
  - eval_batch_size: 8
  - 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   | 182  | 0.2452          | 0.5956    | 0.5432 | 0.5682 | 0.9189   |
  | No log        | 2.0   | 364  | 0.2571          | 0.6832    | 0.6354 | 0.6584 | 0.9204   |
  | 0.1093        | 3.0   | 546  | 0.2386          | 0.6992    | 0.6987 | 0.6989 | 0.9318   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.4.0
  - Tokenizers 0.11.6
  