pabRomero / BERT-finetuned-ner-pablo-just-classifier

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Total runs: 1
24-hour runs: 0
7-day runs: 1
30-day runs: 0
Model's Last Updated: August 17 2024

Introduction of BERT-finetuned-ner-pablo-just-classifier

Model Details of BERT-finetuned-ner-pablo-just-classifier

BERT-finetuned-ner-pablo-just-classifier

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

  • Loss: 0.1826
  • Precision: 0.6355
  • Recall: 0.6417
  • F1: 0.6386
  • Accuracy: 0.9550
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: 0.1
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 3
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.6403 0.9996 652 0.4524 0.4481 0.5957 0.5114 0.9347
0.5852 1.9992 1304 0.3430 0.4741 0.6281 0.5404 0.9373
0.3808 2.9989 1956 0.1826 0.6355 0.6417 0.6386 0.9550
Framework versions
  • Transformers 4.44.0
  • Pytorch 2.4.0+cu124
  • Datasets 2.21.0
  • Tokenizers 0.19.1

Runs of pabRomero BERT-finetuned-ner-pablo-just-classifier on huggingface.co

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Total runs: 5
Run Growth: -1
Growth Rate: -20.00%
Updated:September 30 2024