readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - conll2003
  model-index:
  - name: bert-to-distilbert-NER
    results: []
  ---
  
  <!-- 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. -->
  
  # bert-to-distilbert-NER
  
  This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the conll2003 dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 5.9063
  - eval_precision: 0.0120
  - eval_recall: 0.0069
  - eval_f1: 0.0088
  - eval_accuracy: 0.7600
  - eval_runtime: 8.6309
  - eval_samples_per_second: 376.671
  - eval_steps_per_second: 3.012
  - epoch: 1.0
  - step: 110
  
  ## 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: 0.00023888106906613202
  - train_batch_size: 128
  - eval_batch_size: 128
  - seed: 33
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 2
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.19.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  