readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - conll2003
  model_index:
  - name: roberta-base-ner
    results:
    - task:
        name: Token Classification
        type: token-classification
      dataset:
        name: conll2003
        type: conll2003
        args: conll2003
  ---
  
  <!-- 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. -->
  
  # roberta-base-ner
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the conll2003 dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 0.0814
  - eval_precision: 0.9101
  - eval_recall: 0.9336
  - eval_f1: 0.9217
  - eval_accuracy: 0.9799
  - eval_runtime: 10.2964
  - eval_samples_per_second: 315.646
  - eval_steps_per_second: 39.529
  - epoch: 1.14
  - step: 500
  
  ## 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: 5e-05
  - train_batch_size: 32
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4.0
  
  ### Framework versions
  
  - Transformers 4.8.2
  - Pytorch 1.8.1+cu111
  - Datasets 1.8.0
  - Tokenizers 0.10.3
  