readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - hi_ner_config
  model-index:
  - name: xlm-roberta-large-finetuned-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. -->
  
  # xlm-roberta-large-finetuned-ner
  
  This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the hi_ner_config dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 0.2329
  - eval_precision: 0.7110
  - eval_recall: 0.6854
  - eval_f1: 0.6980
  - eval_accuracy: 0.9332
  - eval_runtime: 162.3478
  - eval_samples_per_second: 66.9
  - eval_steps_per_second: 16.73
  - epoch: 2.64
  - step: 50198
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  