phi-3-mini-NER-PII-Vast3

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1122
  • Precision: 0.6826
  • Recall: 0.8382
  • F1: 0.7524
  • Accuracy: 0.9697

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 3

Training results

Training Loss Epoch Step Accuracy F1 Validation Loss Precision Recall
0.1017 1.0 11105 0.9693 0.7506 0.1123 0.6807 0.8364
0.0782 2.0 22210 0.1119 0.6819 0.8382 0.7520 0.9697
0.0944 3.0 33315 0.1122 0.6826 0.8382 0.7524 0.9697

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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