long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP14
This model is a fine-tuned version of pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP13 on the kmfoda/booksum dataset.
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: 0.0006
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- 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
Framework versions
- Transformers 4.22.0
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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Dataset used to train pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP14
Evaluation results
- ROUGE-1 on samsumtest set verified23.518
- ROUGE-2 on samsumtest set verified4.668
- ROUGE-L on samsumtest set verified16.609
- ROUGE-LSUM on samsumtest set verified20.317
- loss on samsumtest set verified3.217
- gen_len on samsumtest set verified57.197
- ROUGE-1 on kmfoda/booksumtest set verified35.988
- ROUGE-2 on kmfoda/booksumtest set verified6.060
- ROUGE-L on kmfoda/booksumtest set verified16.142
- ROUGE-LSUM on kmfoda/booksumtest set verified32.999