bart-base-cnn-xsum-cite-swe

This model is a fine-tuned version of Gabriel/bart-base-cnn-xsum-swe on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.4203
• Rouge1: 29.6279
• Rouge2: 11.5697
• Rougel: 24.2429
• Rougelsum: 24.4557
• Gen Len: 19.9371

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.4833	1.0	2558	2.4203	29.6279	11.5697	24.2429	24.4557	19.9371

Framework versions

• Transformers 4.22.2
• Pytorch 1.12.1+cu113
• Datasets 2.5.1
• Tokenizers 0.12.1