cetusian/ner-model-furniture-names

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: 0.6861
• Validation Loss: 0.7336
• Train Precision: 0.4712
• Train Recall: 0.4993
• Train F1: 0.4848
• Train Accuracy: 0.6975
• Epoch: 2

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': 3e-05, 'decay_steps': 42, '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
0.6938	0.7336	0.4712	0.4993	0.4848	0.6975	0
0.6834	0.7336	0.4712	0.4993	0.4848	0.6975	1
0.6861	0.7336	0.4712	0.4993	0.4848	0.6975	2

Framework versions

• Transformers 4.41.1
• TensorFlow 2.15.0
• Datasets 2.19.2
• Tokenizers 0.19.1