svenbl80/roberta-base-finetuned-new-mnli-run-2

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: 0.0256
• Validation Loss: 0.7289
• Train Accuracy: 0.8643
• 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
0.4540	0.4007	0.8488	0
0.3282	0.3756	0.8566	1
0.2444	0.4087	0.8586	2
0.1789	0.4880	0.8573	3
0.1291	0.4915	0.8621	4
0.0926	0.5759	0.8641	5
0.0665	0.5938	0.8643	6
0.0482	0.6515	0.8632	7
0.0345	0.7010	0.8637	8
0.0256	0.7289	0.8643	9

Framework versions

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