Keisyahsq/BC2GM_BERT16

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

• Train Loss: 0.0120
• Validation Loss: 0.1307
• Train Precision: 0.8313
• Train Recall: 0.8735
• Train F1: 0.8519
• Train Accuracy: 0.9695
• Epoch: 6

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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7810, '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}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
• training_precision: mixed_float16

Training results

Train Loss	Validation Loss	Train Precision	Train Recall	Train F1	Train Accuracy	Epoch
0.1583	0.0982	0.8165	0.8109	0.8137	0.9639	0
0.0787	0.0860	0.8342	0.8320	0.8331	0.9679	1
0.0502	0.0952	0.8321	0.8482	0.8401	0.9676	2
0.0329	0.1015	0.8259	0.8644	0.8447	0.9681	3
0.0234	0.1165	0.8471	0.8479	0.8475	0.9698	4
0.0167	0.1237	0.8473	0.8610	0.8541	0.9696	5
0.0120	0.1307	0.8313	0.8735	0.8519	0.9695	6

Framework versions

• Transformers 4.31.0
• TensorFlow 2.10.1
• Datasets 3.0.0
• Tokenizers 0.13.3