t5-small-summarization-samsum

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

• Loss: 1.7907
• Rouge1: 0.4318
• Rouge2: 0.2005
• Rougel: 0.3629
• Rougelsum: 0.3629
• Gen Len: 16.8971

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:

• learning_rate: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.1074	0.54	500	1.9230	0.4011	0.182	0.3418	0.3417	15.7439
2.0526	1.09	1000	1.8559	0.4122	0.1841	0.3478	0.348	16.386
2.0075	1.63	1500	1.8193	0.4273	0.1955	0.3552	0.3551	16.8554
1.97	2.17	2000	1.8086	0.4222	0.1922	0.3551	0.3552	16.761
1.931	2.72	2500	1.7907	0.4318	0.2005	0.3629	0.3629	16.8971

Framework versions

• Transformers 4.36.0.dev0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1