vc-01-bert-finetuned

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

• Train Loss: 0.0074
• Validation Loss: 0.4494
• Train Recall: 0.9247
• 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': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7920, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Recall	Epoch
0.3152	0.3003	0.9383	0
0.1993	0.2504	0.9036	1
0.1250	0.2717	0.9232	2
0.0654	0.3074	0.8870	3
0.0347	0.3127	0.9232	4
0.0268	0.4317	0.9217	5
0.0146	0.4449	0.9066	6
0.0092	0.4419	0.9066	7
0.0074	0.4494	0.9247	8

Framework versions

• Transformers 4.31.0
• TensorFlow 2.13.0
• Datasets 2.14.4
• Tokenizers 0.13.3