t5-small-finetuned-multi-news

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

• Loss: 2.7775
• Rouge1: 14.5549
• Rouge2: 4.5934
• Rougel: 11.1178
• Rougelsum: 12.8964
• Gen Len: 19.0

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.0211	1.0	1405	2.7775	14.5549	4.5934	11.1178	12.8964	19.0

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6