MariaDB10ALBERT_Unbalance

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: 0.1092
• Train Accuracy: 0.9665
• Validation Loss: 0.2438
• Validation Accuracy: 0.9447
• Epoch: 7

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', 'weight_decay': 0.001, 'clipnorm': 1.0, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 3e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.2705	0.9155	0.2016	0.9523	0
0.2344	0.9180	0.2089	0.9523	1
0.2400	0.9255	0.1977	0.9523	2
0.2184	0.9247	0.2043	0.9497	3
0.2131	0.9222	0.1947	0.9447	4
0.1781	0.9356	0.2098	0.9447	5
0.1454	0.9448	0.2270	0.9523	6
0.1092	0.9665	0.2438	0.9447	7

Framework versions

• Transformers 4.29.2
• TensorFlow 2.12.0
• Datasets 2.12.0
• Tokenizers 0.13.3