mallikrao2/qa-finetuned-swag

This model is a fine-tuned version of mallikrao2/sQuad_bertmodel1_ on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0020
• Train Accuracy: 0.9994
• Validation Loss: 1.9750
• Validation Accuracy: 0.7508
• Epoch: 19

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': 5e-05, 'decay_steps': 66860, '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
0.8405	0.6630	0.6156	0.7596	0
0.4697	0.8233	0.6102	0.7643	1
0.2479	0.9087	0.7102	0.7573	2
0.1571	0.9439	0.8434	0.7482	3
0.1139	0.9599	1.0923	0.7453	4
0.0881	0.9698	1.0614	0.7421	5
0.0705	0.9758	1.1311	0.7412	6
0.0577	0.9802	1.1761	0.7387	7
0.0453	0.9845	1.3310	0.7446	8
0.0379	0.9869	1.3076	0.7361	9
0.0301	0.9898	1.3147	0.7434	10
0.0228	0.9923	1.6641	0.7388	11
0.0195	0.9932	1.6168	0.7397	12
0.0165	0.9948	1.6042	0.7458	13
0.0118	0.9960	1.6922	0.7426	14
0.0098	0.9970	1.7052	0.7449	15
0.0059	0.9982	1.8137	0.7453	16
0.0040	0.9986	1.9369	0.7504	17
0.0032	0.9991	1.9089	0.7498	18
0.0020	0.9994	1.9750	0.7508	19

Framework versions

• Transformers 4.29.2
• TensorFlow 2.8.0
• Datasets 2.12.0
• Tokenizers 0.13.3