ohss117/bert-finetuned-ner_v2

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

• Train Loss: 0.0003
• Validation Loss: 0.0919
• Epoch: 21

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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 21950, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, '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: mixed_float16

Training results

Train Loss	Validation Loss	Epoch
0.1785	0.0609	0
0.0493	0.0581	1
0.0288	0.0621	2
0.0187	0.0581	3
0.0141	0.0630	4
0.0096	0.0665	5
0.0060	0.0735	6
0.0064	0.0774	7
0.0055	0.0717	8
0.0028	0.0796	9
0.0020	0.0913	10
0.0024	0.0787	11
0.0023	0.0877	12
0.0024	0.0793	13
0.0010	0.0873	14
0.0008	0.0874	15
0.0013	0.0902	16
0.0007	0.0925	17
0.0005	0.0957	18
0.0005	0.0914	19
0.0004	0.0926	20
0.0003	0.0919	21

Framework versions

• Transformers 4.25.1
• TensorFlow 2.10.1
• Datasets 2.8.0
• Tokenizers 0.13.2