pii_mbert_az / README.md
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metadata
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: pii_mbert_az
    results: []

pii_mbert_az

This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1319
  • Precision: 0.8726
  • Recall: 0.9026
  • F1: 0.8874
  • Accuracy: 0.9619

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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: reduce_lr_on_plateau
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 313 0.1464 0.8797 0.8615 0.8705 0.9587
0.2128 2.0 626 0.1319 0.8726 0.9026 0.8874 0.9619
0.2128 3.0 939 0.1461 0.8689 0.8924 0.8805 0.9596
0.0783 4.0 1252 0.1529 0.8837 0.9049 0.8942 0.9620
0.0443 5.0 1565 0.1921 0.8657 0.9157 0.8900 0.9615
0.0443 6.0 1878 0.1647 0.8975 0.9224 0.9098 0.9685
0.0201 7.0 2191 0.1725 0.8904 0.9183 0.9041 0.9674
0.0098 8.0 2504 0.1766 0.8917 0.9199 0.9056 0.9682
0.0098 9.0 2817 0.1756 0.8926 0.9202 0.9062 0.9686
0.007 10.0 3130 0.1763 0.8916 0.9189 0.9051 0.9684
0.007 11.0 3443 0.1772 0.8907 0.9183 0.9043 0.9682
0.007 12.0 3756 0.1773 0.8895 0.9173 0.9032 0.9680
0.0067 13.0 4069 0.1775 0.8892 0.9170 0.9029 0.9680
0.0067 14.0 4382 0.1775 0.8897 0.9170 0.9032 0.9679
0.0062 15.0 4695 0.1775 0.8897 0.9170 0.9032 0.9679

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1