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mt5-small_summarization
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.1774
- Rouge1: 18.2118
- Rouge2: 6.6244
- Rougel: 15.4682
- Rougelsum: 15.3942
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|
| 17.7253 | 1.0 | 50 | 7.6921 | 6.677 | 1.1111 | 6.5586 | 6.6861 |
| 9.8457 | 2.0 | 100 | 4.5604 | 12.8991 | 1.9103 | 11.2559 | 10.9036 |
| 6.2403 | 3.0 | 150 | 3.9071 | 16.463 | 4.0695 | 14.3098 | 14.4065 |
| 5.2032 | 4.0 | 200 | 3.4869 | 17.6601 | 4.0878 | 14.2931 | 14.2743 |
| 4.8331 | 5.0 | 250 | 3.3472 | 18.5241 | 5.3312 | 15.8993 | 16.0559 |
| 4.526 | 6.0 | 300 | 3.2346 | 19.0264 | 5.7839 | 15.8013 | 16.1208 |
| 4.5378 | 7.0 | 350 | 3.1927 | 18.9843 | 6.992 | 16.3787 | 16.3574 |
| 4.3278 | 8.0 | 400 | 3.1774 | 18.2118 | 6.6244 | 15.4682 | 15.3942 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.3.2
- Tokenizers 0.12.1
