bert-large-model

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

• Train Loss: 0.5285
• Train Accuracy: 0.6667
• Validation Loss: 0.6526
• Validation Accuracy: 1.0
• Epoch: 2

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': False, 'is_legacy_optimizer': False, 'learning_rate': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.6872	0.6667	0.5984	1.0	0
0.5637	0.6667	0.6125	1.0	1
0.5285	0.6667	0.6526	1.0	2

Framework versions

• Transformers 4.40.0
• TensorFlow 2.15.0
• Tokenizers 0.19.1