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t5-base-finetuned-multi-news
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2612
- Rouge1: 16.6322
- Rouge2: 5.7556
- Rougel: 12.4728
- Rougelsum: 14.4814
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: 5.6e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 2.5641 | 1.0 | 1250 | 2.2636 | 16.6762 | 5.7127 | 12.4648 | 14.5499 |
| 2.3542 | 2.0 | 2500 | 2.2439 | 16.7381 | 5.7345 | 12.5515 | 14.5785 |
| 2.2487 | 3.0 | 3750 | 2.2388 | 16.8879 | 5.8792 | 12.6417 | 14.8011 |
| 2.1705 | 4.0 | 5000 | 2.2413 | 16.5921 | 5.7804 | 12.4539 | 14.4865 |
| 2.1083 | 5.0 | 6250 | 2.2459 | 16.6878 | 5.8593 | 12.5132 | 14.5473 |
| 2.0622 | 6.0 | 7500 | 2.2495 | 16.7267 | 5.7825 | 12.48 | 14.5309 |
| 2.0297 | 7.0 | 8750 | 2.2581 | 16.633 | 5.748 | 12.4418 | 14.4796 |
| 2.0084 | 8.0 | 10000 | 2.2612 | 16.6322 | 5.7556 | 12.4728 | 14.4814 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
