svenbl80/xlnet-base-cased-finetuned-mnli

This model is a fine-tuned version of xlnet-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0221
• Validation Loss: 0.7391
• 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
0.4828	0.4066	0.8426	0
0.3364	0.3842	0.8598	1
0.2419	0.3913	0.8672	2
0.1713	0.4653	0.8624	3
0.1212	0.5090	0.8625	4
0.0857	0.5733	0.8684	5
0.0620	0.6176	0.8635	6
0.0435	0.6781	0.8670	7
0.0309	0.7102	0.8668	8
0.0221	0.7391	0.8677	9

Framework versions

• Transformers 4.35.2
• TensorFlow 2.9.1
• Datasets 2.15.0
• Tokenizers 0.15.0