MariaDB20ALBERT_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: 0.0754
• Train Accuracy: 0.9808
• Validation Loss: 0.1763
• Validation Accuracy: 0.9548
• 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
0.2348	0.9356	0.1533	0.9698	0
0.2017	0.9364	0.1380	0.9698	1
0.1968	0.9372	0.1435	0.9698	2
0.1729	0.9372	0.1365	0.9673	3
0.1448	0.9490	0.1350	0.9673	4
0.1314	0.9523	0.1401	0.9648	5
0.1095	0.9690	0.1530	0.9673	6
0.0754	0.9808	0.1763	0.9548	7

Framework versions

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