ratish/DBERT_ZS_Desc_MAKE_v1.1

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: 0.1764
• Validation Loss: 0.1006
• Train Accuracy: 1.0
• Epoch: 9

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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2240, '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
2.1556	1.6810	0.6818	0
1.5423	1.0933	0.9091	1
1.0577	0.6895	0.9545	2
0.7397	0.4597	1.0	3
0.5366	0.3215	1.0	4
0.4081	0.2415	1.0	5
0.3190	0.1867	1.0	6
0.2588	0.1485	1.0	7
0.2132	0.1212	1.0	8
0.1764	0.1006	1.0	9

Framework versions

• Transformers 4.28.1
• TensorFlow 2.12.0
• Datasets 2.11.0
• Tokenizers 0.13.3