distilbart-cnn-12-6-samsum

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

• Loss: 1.4753
• Rouge1: 39.3733
• Rouge2: 19.4821
• Rougel: 29.8944
• Rougelsum: 36.7688
• Gen Len: 59.4750

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: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.4685	1.0	14732	1.4753	39.3733	19.4821	29.8944	36.7688	59.4750

Framework versions

• Transformers 4.30.2
• Pytorch 1.12.1
• Datasets 2.13.1
• Tokenizers 0.11.0