svenbl80/roberta-base-finetuned-new-mnli-run-9

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: 0.0252
• Validation Loss: 0.7593
• Train Accuracy: 0.8627
• 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
0.4595	0.4097	0.8456	0
0.3288	0.3983	0.8531	1
0.2471	0.4441	0.8556	2
0.1807	0.4561	0.8596	3
0.1303	0.5280	0.8598	4
0.0932	0.5839	0.8555	5
0.0672	0.6134	0.8604	6
0.0484	0.6650	0.8589	7
0.0348	0.7089	0.8597	8
0.0252	0.7593	0.8627	9

Framework versions

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