results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the wiki_lingua dataset. It achieves the following results on the evaluation set:

• Loss: 7.4393
• Rouge1: 16.9502
• Rouge2: 1.9608
• Rougel: 15.0983
• Rougelsum: 16.9502
• Gen Len: 19.3333

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
• lr_scheduler_warmup_steps: 500
• num_epochs: 1
• label_smoothing_factor: 0.1

Training results

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3