svenbl80/roberta-base-finetuned-new-mnli-run-3

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: 1.0986
• Validation Loss: 1.1021
• Train Accuracy: 0.3242
• 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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 245430, '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	Validation Loss	Train Accuracy	Epoch
1.0996	1.1000	0.3242	0
1.0993	1.0986	0.3354	1
1.0991	1.0993	0.3242	2
1.0991	1.1000	0.3242	3
1.0989	1.0991	0.3242	4
1.0988	1.1002	0.3242	5
1.0988	1.0999	0.3354	6
1.0987	1.1016	0.3354	7
1.0986	1.1014	0.3354	8
1.0986	1.1021	0.3242	9

Framework versions

• Transformers 4.28.0
• TensorFlow 2.9.1
• Datasets 2.15.0
• Tokenizers 0.13.3