nort5-base-finetuned-cnn-dm

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

• Loss: 2.3067
• Rouge1: 27.3203
• Rouge2: 11.4707
• Rougel: 22.6808
• Rougelsum: 25.4955

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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• 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: 500
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
1.6729	1.4526	5000	2.2324	26.1211	10.5481	21.7932	24.3286
0.9704	2.9053	10000	2.2965	27.5021	11.6469	22.8721	25.6558

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1