tunarebus/distilbert-base-uncased-finetuned-imdb

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: 2.3941
• Validation Loss: 2.4019
• 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': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -949, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: mixed_float16

Training results

Train Loss	Validation Loss	Epoch
2.3668	2.3869	0
2.4055	2.3907	1
2.3880	2.3301	2
2.3677	2.4133	3
2.3891	2.4048	4
2.3861	2.4312	5
2.4031	2.3794	6
2.3730	2.3708	7
2.4306	2.3910	8
2.4102	2.3748	9
2.4285	2.4060	10
2.4150	2.4133	11
2.3953	2.4465	12
2.4173	2.3387	13
2.3997	2.3561	14
2.4091	2.4217	15
2.4050	2.3832	16
2.4103	2.4008	17
2.4019	2.3851	18
2.3941	2.4019	19

Framework versions

• Transformers 4.35.2
• TensorFlow 2.14.0
• Datasets 2.15.0
• Tokenizers 0.15.0