ratish/DBERT_Fault_LR_v2

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

• Train Loss: 0.4241
• Validation Loss: 0.5145
• Train Accuracy: 0.7692
• Epoch: 14

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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-06, 'decay_steps': 2128, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
0.6872	0.6932	0.5128	0
0.6761	0.6965	0.5128	1
0.6638	0.7020	0.5128	2
0.6590	0.7093	0.5128	3
0.6532	0.7112	0.5128	4
0.6469	0.7067	0.5128	5
0.6359	0.7101	0.5128	6
0.6236	0.7103	0.5128	7
0.6120	0.6865	0.5641	8
0.5913	0.6576	0.5641	9
0.5618	0.6206	0.5897	10
0.5286	0.5765	0.5897	11
0.4931	0.5502	0.6667	12
0.4574	0.5154	0.7692	13
0.4241	0.5145	0.7692	14

Framework versions

• Transformers 4.28.1
• TensorFlow 2.12.0
• Datasets 2.12.0
• Tokenizers 0.13.3