wine-reviews-roberta

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

• Train Loss: 0.2715
• Train Acc: 0.8906
• Validation Loss: 0.6536
• Validation Acc: 0.7701
• Epoch: 4

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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 24455, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Acc	Validation Loss	Validation Acc	Epoch
0.6164	0.7297	0.5360	0.7665	0
0.5040	0.7820	0.5145	0.7739	1
0.4248	0.8206	0.5470	0.7744	2
0.3413	0.8583	0.6132	0.7699	3
0.2715	0.8906	0.6536	0.7701	4

Framework versions

• Transformers 4.28.1
• TensorFlow 2.11.0
• Datasets 2.1.0
• Tokenizers 0.13.3