results
This model is a fine-tuned version of sshleifer/distilbart-xsum-12-1 on the ccdv/arxiv-summarization dataset. It achieves the following results on the evaluation set:
- Loss: 4.3066
- Rouge1: 35.6639
- Rouge2: 10.5717
- Rougel: 21.095
- Rougelsum: 31.2685
- Gen Len: 81.44
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2
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Dataset used to train pinglarin/summarization_papers
Evaluation results
- Rouge1 on ccdv/arxiv-summarizationvalidation set self-reported35.664