stacked-summaries/flan-t5-small-stacked-samsum-1024

flan-t5-small-stacked-samsum-1024

This model is a fine-tuned version of google/flan-t5-small on the stacked-summaries/stacked-samsum-1024 dataset. It achieves the following results on the evaluation set:

• —Loss: 1.7573
• —Rouge1: 46.6072
• —Rouge2: 19.9754
• —Rougel: 35.2715
• —Rougelsum: 43.3599
• —Gen Len: 72.64

Model Description

Trained on a summarization task with potentially multiple doc-summary pairs stacked on top of each other.

You can separate its predictions by using it's special token [NEXT_CONCEPT] to split the output into "separate topics".

Intended use & limitations

• —This is intended to be used as a baseline/reference for comparison with the larger models.

Training and evaluation data

See stacked-summaries/stacked-samsum-1024.

Training Procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 0.0001
• —trainbatchsize: 16
• —evalbatchsize: 16
• —seed: 22138
• —distributed_type: multi-GPU
• —gradientaccumulationsteps: 8
• —totaltrainbatch_size: 128
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.05
• —num_epochs: 3.0

Training results