finetune-newwiki-summarization-ver1
This model is a fine-tuned version of VietAI/vit5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4720
- Rouge1: 48.6293
- Rouge2: 25.6053
- Rougel: 35.2967
- Rougelsum: 37.4842
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: 1e-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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.7106 | 1.0 | 1980 | 0.5006 | 46.5921 | 22.8276 | 33.1994 | 35.6330 |
| 0.621 | 2.0 | 3960 | 0.4774 | 47.4426 | 24.1508 | 34.1315 | 36.5692 |
| 0.5607 | 3.0 | 5940 | 0.4690 | 48.1503 | 24.7217 | 34.5071 | 36.7568 |
| 0.5241 | 4.0 | 7920 | 0.4673 | 48.2480 | 25.0604 | 34.4937 | 36.9301 |
| 0.499 | 5.0 | 9900 | 0.4678 | 48.1659 | 25.1857 | 34.9460 | 37.1931 |
| 0.4592 | 6.0 | 11880 | 0.4694 | 48.5839 | 25.5925 | 35.2301 | 37.5352 |
| 0.4535 | 7.0 | 13860 | 0.4720 | 48.6293 | 25.6053 | 35.2967 | 37.4842 |
Framework versions
- Transformers 4.17.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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