t5-small-text_summarization

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

• Loss: 2.4591
• Rouge1: 28.6917
• Rouge2: 7.976
• Rougel: 22.6383
• Rougelsum: 22.6353
• Gen Len: 18.8185

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: 25
• eval_batch_size: 25
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.7006	1.0	8162	2.4591	28.6917	7.976	22.6383	22.6353	18.8185

Framework versions

• Transformers 4.12.3
• Pytorch 1.10.0+cu111
• Datasets 1.15.1
• Tokenizers 0.10.3