ateffal/question-recognizer

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: 0.0006
• Validation Loss: 0.0119
• Train Accuracy: 0.998
• 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 5100, '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
0.0953	0.0062	0.9985	0
0.0196	0.0105	0.9972	1
0.0076	0.0051	0.9988	2
0.0081	0.0048	0.9985	3
0.0052	0.0117	0.998	4
0.0030	0.0101	0.9982	5
0.0019	0.0112	0.998	6
0.0013	0.0113	0.9982	7
0.0008	0.0120	0.998	8
0.0006	0.0119	0.998	9

Framework versions

• Transformers 4.27.4
• TensorFlow 2.11.0
• Datasets 2.1.0
• Tokenizers 0.13.2