fine-tuned-bert_full

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

• Train Loss: 0.4738
• Train Accuracy: 0.8120
• Validation Loss: 0.7711
• Validation Accuracy: 0.6894
• 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': True, 'is_legacy_optimizer': False, 'learning_rate': 2e-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
0.8973	0.5688	0.7976	0.6460	0
0.6204	0.7478	0.7341	0.7081	1
0.4738	0.8120	0.7711	0.6894	2

Framework versions

• Transformers 4.48.2
• TensorFlow 2.18.0
• Tokenizers 0.21.0