Apv/Flaubert2704_v1

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

• Train Loss: 0.6198
• Validation Loss: 0.6599
• Train Accuracy: 0.7333
• Epoch: 5

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': 804, '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	Validation Loss	Train Accuracy	Epoch
0.9034	0.7880	0.5956	0
0.7819	0.7210	0.6933	1
0.6369	0.6599	0.7333	2
0.6341	0.6599	0.7333	3
0.6243	0.6599	0.7333	4
0.6198	0.6599	0.7333	5

Framework versions

• Transformers 4.28.1
• TensorFlow 2.12.0
• Datasets 2.11.0
• Tokenizers 0.13.3