distilbart-cnn-12-6-finetuned-1.1.0

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

• Loss: 0.0274
• Rouge1: 84.662
• Rouge2: 83.5616
• Rougel: 84.4282
• Rougelsum: 84.4667

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.0911	1.0	97	0.0286	85.8678	84.7683	85.7147	85.6949
0.0442	2.0	194	0.0274	84.662	83.5616	84.4282	84.4667

Framework versions

• Transformers 4.22.2
• Pytorch 1.12.1+cu113
• Datasets 2.5.2
• Tokenizers 0.12.1