distilbart-cnn-12-6-ftn-multi_news

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the multi_news dataset. It achieves the following results on the evaluation set:

• Loss: 3.8143
• Rouge1: 41.6136
• Rouge2: 14.7454
• Rougel: 23.3597
• Rougelsum: 36.1973
• Gen Len: 130.874

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: 2e-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
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.8821	0.89	2000	3.8143	41.6136	14.7454	23.3597	36.1973	130.874

Framework versions

• Transformers 4.20.1
• Pytorch 1.11.0+cu113
• Datasets 2.3.2
• Tokenizers 0.12.1