Ioana23/bert-finetuned-resumes-ner

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: 0.1439
• Validation Loss: 0.3965
• Epoch: 8

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': 500, '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
0.8008	0.5863	0
0.4590	0.4465	1
0.3443	0.3876	2
0.2827	0.3977	3
0.2285	0.3824	4
0.1962	0.3965	5
0.1699	0.3259	6
0.1559	0.4927	7
0.1439	0.3965	8

Framework versions

• Transformers 4.32.1
• TensorFlow 2.10.0
• Datasets 2.14.4
• Tokenizers 0.13.3