North-T5_large_NO_CNN-idun
This model is a fine-tuned version of north/t5_large_NCC_modern on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7705
- Rouge1: 32.1183
- Rouge2: 12.1864
- Rougel: 22.008
- Rougelsum: 29.6903
- Gen Len: 96.8196
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.1173 | 1.0 | 6118 | 1.8719 | 31.1024 | 11.4005 | 21.1829 | 28.6286 | 91.2659 |
| 1.9812 | 2.0 | 12236 | 1.8214 | 31.7965 | 11.9251 | 21.6532 | 29.3509 | 95.1182 |
| 1.8761 | 3.0 | 18354 | 1.7854 | 31.8821 | 12.0616 | 21.7162 | 29.4558 | 98.6727 |
| 1.8243 | 4.0 | 24472 | 1.7747 | 32.0071 | 12.1025 | 21.8843 | 29.5732 | 96.5254 |
| 1.7848 | 5.0 | 30590 | 1.7705 | 32.1183 | 12.1864 | 22.008 | 29.6903 | 96.8196 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.3.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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Base model
north/t5_large_NCC_modern