ratish/bert-textClassification_v1.4

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: 0.3431
• Validation Loss: 0.8618
• Train Accuracy: 0.7273
• 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': 285, '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
2.2087	1.9909	0.4091	0
1.7130	1.6444	0.5909	1
1.3350	1.3844	0.5455	2
1.0642	1.2276	0.6136	3
0.8599	1.1036	0.6818	4
0.7216	1.0790	0.6818	5
0.6305	1.0403	0.6818	6
0.5304	0.9581	0.7045	7
0.4899	0.8977	0.7273	8
0.4332	0.8907	0.7273	9
0.4000	0.9072	0.7273	10
0.3740	0.8734	0.7273	11
0.3579	0.8726	0.7273	12
0.3448	0.8648	0.7273	13
0.3431	0.8618	0.7273	14

Framework versions

• Transformers 4.27.4
• TensorFlow 2.12.0
• Datasets 2.11.0
• Tokenizers 0.13.3