FYP2022

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

• Train Loss: 0.6016
• Train Sparse Categorical Accuracy: 0.7503
• Train Sparse Top 3 Categorical Accuracy: 0.9901
• Epoch: 5

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', 'clipnorm': 1.0, 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Sparse Categorical Accuracy	Train Sparse Top 3 Categorical Accuracy	Epoch
0.9433	0.5975	0.9523	0
0.8257	0.6498	0.9704	1
0.7625	0.6765	0.9778	2
0.7062	0.7014	0.9832	3
0.6526	0.7263	0.9872	4
0.6016	0.7503	0.9901	5

Framework versions

• Transformers 4.19.2
• TensorFlow 2.8.0
• Tokenizers 0.12.1