gor1/my_awesome_model_A1

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: 0.2153
• Validation Loss: 0.1843
• Train Accuracy: 1.0
• Epoch: 11

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': 80, '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
0.6745	0.6418	0.6692	0
0.6265	0.6085	0.6692	1
0.6114	0.5811	0.6692	2
0.5707	0.5465	0.6692	3
0.5432	0.5032	0.6692	4
0.4996	0.4534	0.6923	5
0.4458	0.4010	0.8308	6
0.3902	0.3462	0.8538	7
0.3359	0.2963	0.9077	8
0.3111	0.2598	0.9615	9
0.2633	0.2147	0.9846	10
0.2153	0.1843	1.0	11

Framework versions

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