pabRomero / BERT-full-finetuned-ner-pablo-test

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Model's Last Updated: August 25 2024
token-classification

Introduction of BERT-full-finetuned-ner-pablo-test

Model Details of BERT-full-finetuned-ner-pablo-test

BERT-full-finetuned-ner-pablo-test

This model is a fine-tuned version of pabRomero/BERT-finetuned-ner-pablo-just-classifier on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0966
  • Precision: 0.7988
  • Recall: 0.7630
  • F1: 0.7805
  • Accuracy: 0.9740
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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant
  • num_epochs: 2
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.1195 0.4479 1000 0.1186 0.7264 0.7588 0.7423 0.9698
0.0998 0.8959 2000 0.0968 0.7632 0.7875 0.7751 0.9732
0.0755 1.3438 3000 0.0992 0.7669 0.7739 0.7704 0.9722
0.0771 1.7917 4000 0.0966 0.7988 0.7630 0.7805 0.9740
Framework versions
  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1

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https://huggingface.co/pabRomero/BERT-full-finetuned-ner-pablo-test

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BERT-full-finetuned-ner-pablo-test install

BERT-full-finetuned-ner-pablo-test is an open source model from GitHub that offers a free installation service, and any user can find BERT-full-finetuned-ner-pablo-test on GitHub to install. At the same time, huggingface.co provides the effect of BERT-full-finetuned-ner-pablo-test install, users can directly use BERT-full-finetuned-ner-pablo-test installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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