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bert-finetuned-ner1

This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0493
  • Precision: 0.5627
  • Recall: 0.3880
  • F1: 0.4593
  • Accuracy: 0.9888

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
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0677 0.0444 5000 0.0493 0.5627 0.3880 0.4593 0.9888

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0+cpu
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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