Sidziesama/Legal_NER_Support_Model

This model is a fine-tuned version of nlpaueb/legal-bert-base-uncased on opennyaiorg/InLegalNER. 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