imagine0711/distilbert-base-uncased-finetuned-spammail

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: 2.5863
• Validation Loss: 2.5684
• Epoch: 18

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': -860, '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
3.6091	3.1950	0
3.2788	3.0446	1
3.1039	2.9565	2
2.9711	2.7311	3
2.8449	2.7261	4
2.7577	2.6587	5
2.6351	2.6087	6
2.5829	2.6379	7
2.5935	2.5966	8
2.6046	2.5328	9
2.6010	2.5452	10
2.6161	2.6581	11
2.5762	2.5291	12
2.5959	2.5302	13
2.5850	2.6093	14
2.6090	2.4866	15
2.6019	2.5759	16
2.6149	2.5350	17
2.5863	2.5684	18

Framework versions

• Transformers 4.41.2
• TensorFlow 2.15.0
• Datasets 2.19.2
• Tokenizers 0.19.1