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: []

Sidziesama/Legal_NER_Support_Model_distilledbert

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

Train Loss: 0.4151
Validation Loss: 0.1581
Train Precision: 0.7851
Train Recall: 0.7884
Train F1: 0.7770
Train Accuracy: 0.9548
Epoch: 0

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
0.4151	0.1581	0.7851	0.7884	0.7770	0.9548	0

Framework versions

Transformers 4.39.3
TensorFlow 2.15.0
Datasets 2.18.0
Tokenizers 0.15.2