ratish/DBERT_MAKE_NewData_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: 0.2959
• Validation Loss: 0.4909
• Train Accuracy: 0.8545
• 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-05, 'decay_steps': 360, '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
2.3353	1.9477	0.6545	0
1.7645	1.4417	0.6545	1
1.3097	1.1007	0.8364	2
0.9860	0.8667	0.8364	3
0.7850	0.7599	0.8364	4
0.6603	0.6913	0.8545	5
0.5657	0.6254	0.8545	6
0.5007	0.5763	0.8545	7
0.4480	0.5492	0.8364	8
0.4014	0.5328	0.8545	9
0.3611	0.5035	0.8364	10
0.3295	0.5296	0.8545	11
0.3177	0.4930	0.8545	12
0.3103	0.4904	0.8545	13
0.2959	0.4909	0.8545	14

Framework versions

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