| | --- |
| | license: apache-2.0 |
| | base_model: Hasanur525/deed_summarization_mt5_version_1 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: mt5-deed-sum |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # mt5-deed-sum |
| |
|
| | This model is a fine-tuned version of [Hasanur525/deed_summarization_mt5_version_1](https://huggingface.co/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 |
| | |
