long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP15
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: 0.0004
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 64
- 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: 0.01
- num_epochs: 1.4
Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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Evaluation results
- ROUGE-1 on samsumtest set verified24.548
- ROUGE-2 on samsumtest set verified4.811
- ROUGE-L on samsumtest set verified17.250
- ROUGE-LSUM on samsumtest set verified20.906
- loss on samsumtest set verified3.300
- gen_len on samsumtest set verified52.000
- ROUGE-1 on kmfoda/booksumtest set verified35.331
- ROUGE-2 on kmfoda/booksumtest set verified5.800
- ROUGE-L on kmfoda/booksumtest set verified16.056
- ROUGE-LSUM on kmfoda/booksumtest set verified32.341