svenbl80/roberta-base-finetuned-new-mnli-run-7

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: 0.0241
• Validation Loss: 0.7151
• Train Accuracy: 0.8677
• 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
0.4547	0.4001	0.8483	0
0.3254	0.3771	0.8589	1
0.2407	0.4036	0.8664	2
0.1754	0.4243	0.8649	3
0.1262	0.5004	0.8623	4
0.0910	0.5395	0.8643	5
0.0641	0.5816	0.8628	6
0.0455	0.6892	0.8678	7
0.0328	0.6864	0.8663	8
0.0241	0.7151	0.8677	9

Framework versions

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