andywedlake/test-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: 1.7505
• Validation Loss: 2.0472
• 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0005, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0005, 'decay_steps': 100, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 100, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.0001}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
2.6663	2.5238	0
2.4783	2.6058	1
2.4284	2.5982	2
2.3804	2.5057	3
2.3487	2.6968	4
2.1253	2.1361	5
2.0700	2.2953	6
1.9491	2.3122	7
1.7558	2.5881	8
1.7505	2.0472	9

Framework versions

• Transformers 4.19.2
• TensorFlow 2.8.0
• Datasets 2.2.2
• Tokenizers 0.12.1