PlasmicZ/SIH3

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

• Train Loss: 3.1868
• Validation Loss: 3.1679
• Train Accuracy: 0.6194
• Epoch: 14

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 450, '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
3.6966	3.6944	0.0139	0
3.6920	3.6912	0.0278	1
3.6463	3.5387	0.3056	2
3.4074	3.2592	0.5667	3
3.2234	3.1679	0.6194	4
3.1902	3.1679	0.6194	5
3.1887	3.1679	0.6194	6
3.1907	3.1679	0.6194	7
3.1893	3.1679	0.6194	8
3.1843	3.1679	0.6194	9
3.1894	3.1679	0.6194	10
3.1893	3.1679	0.6194	11
3.1881	3.1679	0.6194	12
3.1935	3.1679	0.6194	13
3.1868	3.1679	0.6194	14

Framework versions

• Transformers 4.42.4
• TensorFlow 2.17.0
• Datasets 2.21.0
• Tokenizers 0.19.1