trained-distilbart-abs-3008

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-6 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 6.4112
• Rouge/rouge1: 0.0
• Rouge/rouge2: 0.0
• Rouge/rougel: 0.0
• Rouge/rougelsum: 0.0
• Bertscore/bertscore-precision: 0.0
• Bertscore/bertscore-recall: 0.0
• Bertscore/bertscore-f1: 0.0
• Meteor: 0.0
• Gen Len: 80.0

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: 0.003
• 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: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge/rouge1	Rouge/rouge2	Rouge/rougel	Rouge/rougelsum	Bertscore/bertscore-precision	Bertscore/bertscore-recall	Bertscore/bertscore-f1	Meteor	Gen Len
6.2931	1.0	109	6.4112	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	80.0

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1