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xlm-roberta-large-finetuned-ner

This model is a fine-tuned version of 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
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