BART_reddit_gaming

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: 3.7373
• Rouge1: 18.1202
• Rouge2: 4.6045
• Rougel: 15.1273
• Rougelsum: 15.7601
• Gen Len: 18.208

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
3.864	1.0	1875	3.7752	17.3754	4.51	14.6763	15.22	16.944
3.4755	2.0	3750	3.7265	17.8066	4.4188	14.9432	15.5396	18.104
3.2629	3.0	5625	3.7373	18.1202	4.6045	15.1273	15.7601	18.208

Framework versions

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