andreiliphdpr/distilbert-base-uncased-finetuned-cola

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: 0.0015
• Train Accuracy: 0.9995
• Validation Loss: 0.0570
• Validation Accuracy: 0.9915
• Epoch: 4

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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 43750, '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}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.0399	0.9870	0.0281	0.9908	0
0.0182	0.9944	0.0326	0.9901	1
0.0089	0.9971	0.0396	0.9912	2
0.0040	0.9987	0.0486	0.9918	3
0.0015	0.9995	0.0570	0.9915	4

Framework versions

• Transformers 4.15.0.dev0
• TensorFlow 2.6.2
• Datasets 1.15.1
• Tokenizers 0.10.3