aknaraya/summarization_fine_tune

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 2.1935
• Validation Loss: 1.7967
• Train Lr: 2e-05
• 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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Lr	Epoch
4.1837	2.9615	2e-05	0
3.6637	2.7191	2e-05	1
3.0591	2.5365	2e-05	2
2.9262	2.3642	2e-05	3
2.7445	2.2407	2e-05	4
2.6800	2.1417	2e-05	5
2.5280	2.0674	2e-05	6
2.4547	2.0001	2e-05	7
2.3370	1.9446	2e-05	8
2.3950	1.9100	2e-05	9
2.2658	1.8836	2e-05	10
2.2373	1.8596	2e-05	11
2.2645	1.8371	2e-05	12
2.2296	1.8161	2e-05	13
2.1935	1.7967	2e-05	14

Framework versions

• Transformers 4.41.1
• TensorFlow 2.15.0
• Datasets 2.19.1
• Tokenizers 0.19.1