distilbart-cnn-6-6-reddit

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

• Loss: 2.9883
• Rouge1: 0.1849
• Rouge2: 0.0437
• Rougel: 0.1273
• Rougelsum: 0.1601

More information and training script

You can find more information about how this model was trained, including the actual training script in this github repository.

Training and evaluation data

I made a split in a train and test set. The test size is 1% of the total dataset, which comes down to about 38k samples.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.13	1.0	238116	3.2736	0.1773	0.0392	0.1223	0.1539
2.8586	2.0	476232	3.0449	0.1846	0.0431	0.127	0.1601
2.7844	3.0	714348	2.9883	0.1849	0.0437	0.1273	0.1601

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.1+cu116
• Datasets 2.8.0
• Tokenizers 0.13.2