svenbl80/roberta-base-finetuned-new-mnli-run-8

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: 0.0268
• Validation Loss: 0.7096
• Train Accuracy: 0.8620
• 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
0.4621	0.3920	0.8564	0
0.3309	0.3669	0.8612	1
0.2495	0.3910	0.8651	2
0.1824	0.4444	0.8621	3
0.1339	0.4744	0.8636	4
0.0960	0.5237	0.8595	5
0.0692	0.5846	0.8586	6
0.0507	0.6444	0.8605	7
0.0360	0.6733	0.8612	8
0.0268	0.7096	0.8620	9

Framework versions

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