BART_reddit_other

This model is a fine-tuned version of sshleifer/distilbart-xsum-6-6 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.5792
• Rouge1: 18.5705
• Rouge2: 5.0107
• Rougel: 15.2581
• Rougelsum: 16.082
• Gen Len: 19.402

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: 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: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.7887	1.0	1875	3.6044	18.4668	5.182	15.359	16.169	19.341
3.3816	2.0	3750	3.5628	18.0998	4.8937	15.0179	15.7615	17.789
3.134	3.0	5625	3.5792	18.5705	5.0107	15.2581	16.082	19.402

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0+cu113
• Datasets 2.3.2
• Tokenizers 0.12.1