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
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Model tree for GloriaABK1/nort5-finetuned-norsumm
Base model
ltg/nort5-base