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finetuned-ner-offer

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

  • Loss: 0.3242
  • Precision: 0.2254
  • Recall: 0.2453
  • F1: 0.2349
  • Accuracy: 0.9209

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

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 100 0.3344 0.2162 0.2013 0.2085 0.9217
No log 2.0 200 0.3167 0.1804 0.2201 0.1983 0.9204
No log 3.0 300 0.3242 0.2254 0.2453 0.2349 0.9209

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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Inference API
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Evaluation results