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bert-small-finetuned-wnut17-ner-longer10

This model is a fine-tuned version of muhtasham/bert-small-finetuned-wnut17-ner-longer6 on the wnut_17 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4693
  • Precision: 0.5547
  • Recall: 0.4306
  • F1: 0.4848
  • Accuracy: 0.9250

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: 4

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 425 0.4815 0.5759 0.3947 0.4684 0.9255
0.0402 2.0 850 0.4467 0.5397 0.4390 0.4842 0.9247
0.0324 3.0 1275 0.4646 0.5332 0.4318 0.4772 0.9244
0.0315 4.0 1700 0.4693 0.5547 0.4306 0.4848 0.9250

Framework versions

  • Transformers 4.21.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Dataset used to train muhtasham/bert-small-finetuned-wnut17-ner-longer10

Evaluation results