t5-small_readme_summarization

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.2745
• Rouge1: 0.4187
• Rouge2: 0.2851
• Rougel: 0.3962
• Rougelsum: 0.3961
• Gen Len: 14.4964

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: 2e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.6771	1.0	1458	2.3971	0.389	0.2544	0.3675	0.3667	14.723
2.5887	2.0	2916	2.3279	0.3967	0.2645	0.3744	0.3752	14.4664
2.4793	3.0	4374	2.2969	0.4124	0.2786	0.3896	0.3905	14.5564
2.4421	4.0	5832	2.2758	0.4148	0.2804	0.3923	0.3924	14.3993
2.3985	5.0	7290	2.2745	0.4187	0.2851	0.3962	0.3961	14.4964

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1