roberta-base-ner

This model is a fine-tuned version of 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
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