svenbl80/roberta-base-finetuned-new-mnli-run-4

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: 0.0254
• Validation Loss: 0.7597
• Train Accuracy: 0.8592
• 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
0.4543	0.3920	0.8526	0
0.3298	0.3979	0.8546	1
0.2478	0.4089	0.8603	2
0.1821	0.4577	0.8575	3
0.1309	0.4901	0.8556	4
0.0947	0.5514	0.8551	5
0.0682	0.6368	0.8553	6
0.0489	0.6589	0.8577	7
0.0343	0.7216	0.8599	8
0.0254	0.7597	0.8592	9

Framework versions

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