long-t5-tglobal-xl-16384-booksci-summary-v1
This model is a fine-tuned version of pszemraj/long-t5-tglobal-xl-16384-book-summary on the pszemraj/scientific_lay_summarisation-elife-norm dataset. It achieves the following results on the evaluation set:
- Loss: 1.7518
- Rouge1: 47.4591
- Rouge2: 12.7287
- Rougel: 21.5549
- Rougelsum: 44.8709
- Gen Len: 384.39
Model description
An experiment of further fine-tuning a booksum model on a different dataset. Compare to either the starting checkpoint (linked above) or to the variant only fine-tuned on the scientific lay summaries.
Intended uses & limitations
More information needed
Training and evaluation data
the pszemraj/scientific_lay_summarisation-elife-norm dataset, input 16384 tokens then truncate, output 1024 tokens then truncate.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 878
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 2.0
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.9629 | 1.0 | 543 | 1.7637 | 46.6926 | 12.4769 | 21.4364 | 44.4329 | 381.23 |
1.8555 | 2.0 | 1086 | 1.7518 | 47.4591 | 12.7287 | 21.5549 | 44.8709 | 384.39 |
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Dataset used to train pszemraj/long-t5-tglobal-xl-16384-booksci-summary-v1
Evaluation results
- Rouge1 on pszemraj/scientific_lay_summarisation-elife-normvalidation set self-reported47.459