Qt5ALBERT_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: 0.3374
• Train Accuracy: 0.8943
• Validation Loss: 0.2540
• Validation Accuracy: 0.9294
• Epoch: 8

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
0.3440	0.8894	0.2519	0.9294	0
0.3376	0.8943	0.2590	0.9294	1
0.3333	0.8940	0.2496	0.9294	2
0.3339	0.8943	0.2589	0.9294	3
0.3360	0.8943	0.2470	0.9294	4
0.3340	0.8943	0.2445	0.9294	5
0.3354	0.8943	0.2576	0.9294	6
0.3404	0.8943	0.2572	0.9294	7
0.3374	0.8943	0.2540	0.9294	8

Framework versions

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