Flaubert_1619

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: 0.2458
• Validation Loss: 0.5339
• Train Accuracy: 0.8170
• Epoch: 19

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': 1432, '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
1.0000	0.5841	0.7769	0
0.5526	0.5284	0.7845	1
0.3909	0.4806	0.8221	2
0.2798	0.5339	0.8170	3
0.2378	0.5339	0.8170	4
0.2514	0.5339	0.8170	5
0.2403	0.5339	0.8170	6
0.2373	0.5339	0.8170	7
0.2441	0.5339	0.8170	8
0.2529	0.5339	0.8170	9
0.2400	0.5339	0.8170	10
0.2337	0.5339	0.8170	11
0.2394	0.5339	0.8170	12
0.2383	0.5339	0.8170	13
0.2464	0.5339	0.8170	14
0.2464	0.5339	0.8170	15
0.2468	0.5339	0.8170	16
0.2427	0.5339	0.8170	17
0.2546	0.5339	0.8170	18
0.2458	0.5339	0.8170	19

Framework versions

• Transformers 4.30.2
• TensorFlow 2.12.0
• Datasets 2.12.0
• Tokenizers 0.13.3