quynh_deberta-v3-Base-finetuned-AI_req_3

This model is a fine-tuned version of microsoft/deberta-v3-Base on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0121
• Train Accuracy: 0.9986
• Validation Loss: 1.0930
• Validation Accuracy: 0.8190
• 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2730, '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
0.8969	0.6099	0.7640	0.7048	0
0.7508	0.6951	0.7178	0.7048	1
0.6149	0.7404	0.5981	0.7714	2
0.5077	0.7720	0.5059	0.8095	3
0.4357	0.8036	0.4621	0.8095	4
0.3671	0.8407	0.4859	0.8190	5
0.2844	0.8777	0.6214	0.8000	6
0.2789	0.8860	0.5499	0.8190	7
0.1938	0.9107	0.8163	0.7810	8
0.1773	0.9231	0.8831	0.7905	9
0.1308	0.9547	0.6316	0.8095	10
0.0803	0.9712	0.8531	0.8286	11
0.0544	0.9849	0.7941	0.7810	12
0.0285	0.9931	0.9530	0.8190	13
0.0121	0.9986	1.0930	0.8190	14

Framework versions

• Transformers 4.28.0
• TensorFlow 2.9.1
• Datasets 2.16.1
• Tokenizers 0.13.3