metadata
license: apache-2.0
datasets:
- stacked-summaries/stacked-samsum-1024
language:
- en
metrics:
- rouge
tags:
- stacked summaries
- samsum
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 several doc-summary pairs stacked on top of each other.
You can separate it's predictions by using it's special token [NEXT_CONCEPT]
to split the outputs in "separate topics".
Intended uses & limitations
- this is meant to be used as a baseline/reference for comparison to 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
- train_batch_size: 16
- eval_batch_size: 16
- seed: 22138
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.9011 | 1.0 | 230 | 1.7986 | 45.4597 | 19.6956 | 34.6878 | 42.3724 | 74.16 |
1.8297 | 2.0 | 460 | 1.7609 | 46.0427 | 20.2299 | 35.2076 | 43.0549 | 70.56 |
1.7637 | 3.0 | 690 | 1.7573 | 46.6072 | 19.9754 | 35.2715 | 43.3599 | 72.64 |