svenbl80/albert-base-v2-finetuned-mnli

This model is a fine-tuned version of albert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.2712
• Validation Loss: 0.4705
• Train Accuracy: 0.8264
• Epoch: 3

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': 736290, '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
0.5312	0.4792	0.8117	0
0.4204	0.4335	0.8344	1
0.3465	0.4351	0.8317	2
0.2712	0.4705	0.8264	3

Framework versions

• Transformers 4.28.0
• TensorFlow 2.7.0
• Datasets 2.3.2
• Tokenizers 0.12.1