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metadata
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: Sidziesama/Legal_NER_Support_Model_distilledbert
    results: []
datasets:
  - opennyaiorg/InLegalNER

Sidziesama/Legal_NER_Support_Model_distilledbert

This model is a fine-tuned version of distilbert/distilbert-base-uncased on opennyaiorg/InLegalNER. It achieves the following results on the evaluation set:

  • Train Loss: 0.0582
  • Validation Loss: 0.0980
  • Train Precision: 0.7952
  • Train Recall: 0.8552
  • Train F1: 0.8241
  • Train Accuracy: 0.9716
  • Epoch: 4

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3435, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Precision Train Recall Train F1 Train Accuracy Epoch
0.4207 0.1608 0.6623 0.7498 0.7034 0.9557 0
0.1304 0.1118 0.7580 0.8116 0.7839 0.9668 1
0.0891 0.1012 0.7698 0.8525 0.8090 0.9701 2
0.0699 0.0976 0.7933 0.8507 0.8210 0.9713 3
0.0582 0.0980 0.7952 0.8552 0.8241 0.9716 4

Framework versions

  • Transformers 4.39.3
  • TensorFlow 2.15.0
  • Datasets 2.18.0
  • Tokenizers 0.15.2