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bert-finetuned-ner

This model is a fine-tuned version of MarcosAutuori/bert-finetuned-ner on the conll2003 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0639
  • Precision: 0.9379
  • Recall: 0.9532
  • F1: 0.9455
  • Accuracy: 0.9870

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0123 1.0 1756 0.0639 0.9379 0.9532 0.9455 0.9870

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Finetuned from

Dataset used to train MarcosAutuori/bert-finetuned-ner

Evaluation results