nort5-finetuned-norsumm

This model is a fine-tuned version of ltg/nort5-base on the NorSumm dataset. It achieves the following results on the evaluation set:

• Loss: 3.3348
• Rouge1: 21.0101
• Rouge2: 6.8497
• Rougel: 13.5367
• Rougelsum: 15.8111

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: 3e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
5.9412	1.0	18	3.9197	19.3966	3.9363	12.5629	13.4741
2.7748	2.0	36	3.2998	22.9405	6.2206	14.7181	16.0087
1.9697	3.0	54	3.0458	20.45	5.1949	13.4087	15.0779
1.4216	4.0	72	2.9993	20.2443	5.4771	14.1114	15.6472

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.1
• Tokenizers 0.21.1