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metadata
license: cc-by-sa-4.0
base_model: nlpaueb/legal-bert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: Sidziesama/Legal_NER_Support_Model
    results: []

Sidziesama/Legal_NER_Support_Model

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

  • Train Loss: 0.0501
  • Validation Loss: 0.0883
  • Train Precision: 0.8848
  • Train Recall: 0.9160
  • Train F1: 0.9001
  • Train Accuracy: 0.9757
  • 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': 2945, '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
0.3771 0.1228 0.8400 0.8644 0.8520 0.9655 0
0.1172 0.0962 0.8715 0.9001 0.8856 0.9725 1
0.0801 0.0895 0.8805 0.9112 0.8956 0.9745 2
0.0597 0.0881 0.8840 0.9112 0.8974 0.9751 3
0.0501 0.0883 0.8848 0.9160 0.9001 0.9757 4

Framework versions

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