mt5-deed-sum
This model is a fine-tuned version of Hasanur525/deed_summarization_mt5_version_1 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4953
- Rouge1: 1.5754
- Rouge2: 1.087
- Rougel: 1.5005
- Rougelsum: 1.4211
- Gen Len: 310.6981
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 22
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.0915 | 1.0 | 375 | 0.5844 | 0.7311 | 0.4193 | 0.7311 | 0.7311 | 289.3396 |
| 0.9545 | 2.0 | 750 | 0.5858 | 0.6289 | 0.444 | 0.6289 | 0.6289 | 291.5912 |
| 0.8026 | 3.0 | 1125 | 0.5817 | 1.1119 | 0.6733 | 1.067 | 1.0428 | 295.0692 |
| 0.2525 | 4.0 | 1500 | 0.5698 | 0.7311 | 0.4193 | 0.7311 | 0.7311 | 299.7987 |
| 1.5794 | 5.0 | 1875 | 0.5685 | 0.8096 | 0.4733 | 0.7714 | 0.7549 | 286.0126 |
| 0.0558 | 6.0 | 2250 | 0.5701 | 0.5003 | 0.3431 | 0.5003 | 0.4785 | 301.6855 |
| 0.4973 | 7.0 | 2625 | 0.5521 | 1.1281 | 0.7349 | 0.9983 | 0.9983 | 295.0692 |
| 1.1935 | 8.0 | 3000 | 0.5661 | 1.3444 | 0.9964 | 1.2673 | 1.2213 | 324.3648 |
| 0.0752 | 9.0 | 3375 | 0.5531 | 1.4883 | 1.0199 | 1.4252 | 1.3979 | 301.0377 |
| 0.216 | 10.0 | 3750 | 0.5573 | 1.5516 | 1.0371 | 1.5047 | 1.4656 | 319.195 |
| 0.3619 | 11.0 | 4125 | 0.5571 | 1.2368 | 0.8055 | 1.2326 | 1.2146 | 294.4717 |
| 0.1881 | 12.0 | 4500 | 0.5293 | 1.2922 | 0.941 | 1.2149 | 1.2084 | 305.9057 |
| 0.2247 | 13.0 | 4875 | 0.5340 | 1.0581 | 0.594 | 0.9989 | 0.987 | 306.3774 |
| 0.0715 | 14.0 | 5250 | 0.5211 | 1.2905 | 0.8861 | 1.259 | 1.2143 | 321.6226 |
| 0.1851 | 15.0 | 5625 | 0.5231 | 1.4625 | 0.9737 | 1.3919 | 1.3637 | 318.4969 |
| 0.5285 | 16.0 | 6000 | 0.5154 | 1.1892 | 0.8552 | 1.1401 | 1.1061 | 313.2138 |
| 0.0482 | 17.0 | 6375 | 0.5032 | 1.1826 | 0.8687 | 1.1554 | 1.1554 | 327.1824 |
| 0.0733 | 18.0 | 6750 | 0.5193 | 1.6133 | 1.1373 | 1.5626 | 1.5085 | 317.8113 |
| 0.2814 | 19.0 | 7125 | 0.5007 | 1.5689 | 1.1133 | 1.5189 | 1.4606 | 307.7421 |
| 0.0672 | 20.0 | 7500 | 0.4959 | 1.5754 | 1.078 | 1.489 | 1.4166 | 316.6164 |
| 0.2456 | 21.0 | 7875 | 0.4966 | 1.5754 | 1.087 | 1.5005 | 1.4211 | 314.3396 |
| 0.0405 | 22.0 | 8250 | 0.4953 | 1.5754 | 1.087 | 1.5005 | 1.4211 | 310.6981 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0.dev20230811+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
- Downloads last month
- 2