BART_reddit_advice_story

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: 3.2552
• Rouge1: 21.9349
• Rouge2: 6.3417
• Rougel: 17.7133
• Rougelsum: 18.7199
• Gen Len: 21.092

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
3.3743	1.0	1875	3.2787	21.1275	5.9618	17.3772	18.317	20.447
3.025	2.0	3750	3.2466	21.8443	6.2351	17.6358	18.6259	21.506
2.7628	3.0	5625	3.2552	21.9349	6.3417	17.7133	18.7199	21.092

Framework versions

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