ImNotTarzan/my_awesome_model

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

• Train Loss: 0.1337
• Validation Loss: 0.7933
• Train Accuracy: 0.7572
• Epoch: 9

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2250, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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
0.6844	0.6378	0.7261	0
0.4811	0.6566	0.7272	1
0.3302	0.6824	0.755	2
0.2186	0.7633	0.7539	3
0.1501	0.7933	0.7572	4
0.1350	0.7933	0.7572	5
0.1340	0.7933	0.7572	6
0.1304	0.7933	0.7572	7
0.1303	0.7933	0.7572	8
0.1337	0.7933	0.7572	9

Framework versions

• Transformers 4.37.2
• TensorFlow 2.15.0
• Datasets 2.17.0
• Tokenizers 0.15.2