P3ps / bert-finetuned-cross-ner-v4

huggingface.co
Total runs: 10
24-hour runs: 0
7-day runs: 2
30-day runs: 7
Model's Last Updated: June 08 2023
token-classification

Introduction of bert-finetuned-cross-ner-v4

Model Details of bert-finetuned-cross-ner-v4

bert-finetuned-cross-ner-v4

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1777
  • Precision: 0.8300
  • Recall: 0.8637
  • F1: 0.8465
  • Accuracy: 0.9560
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: 3
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.2044 1.0 2607 0.1963 0.7779 0.8180 0.7975 0.9459
0.124 2.0 5214 0.1713 0.8158 0.8527 0.8338 0.9546
0.0818 3.0 7821 0.1777 0.8300 0.8637 0.8465 0.9560
Framework versions
  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3

Runs of P3ps bert-finetuned-cross-ner-v4 on huggingface.co

10
Total runs
0
24-hour runs
1
3-day runs
2
7-day runs
7
30-day runs

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