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--- |
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license: apache-2.0 |
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base_model: Hasanur525/deed_summarization_mt5_version_1 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-deed-sum |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# mt5-deed-sum |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4953 |
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- Rouge1: 1.5754 |
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- Rouge2: 1.087 |
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- Rougel: 1.5005 |
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- Rougelsum: 1.4211 |
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- Gen Len: 310.6981 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 5000 |
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- num_epochs: 22 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:| |
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| 0.0915 | 1.0 | 375 | 0.5844 | 0.7311 | 0.4193 | 0.7311 | 0.7311 | 289.3396 | |
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| 0.9545 | 2.0 | 750 | 0.5858 | 0.6289 | 0.444 | 0.6289 | 0.6289 | 291.5912 | |
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| 0.8026 | 3.0 | 1125 | 0.5817 | 1.1119 | 0.6733 | 1.067 | 1.0428 | 295.0692 | |
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| 0.2525 | 4.0 | 1500 | 0.5698 | 0.7311 | 0.4193 | 0.7311 | 0.7311 | 299.7987 | |
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| 1.5794 | 5.0 | 1875 | 0.5685 | 0.8096 | 0.4733 | 0.7714 | 0.7549 | 286.0126 | |
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| 0.0558 | 6.0 | 2250 | 0.5701 | 0.5003 | 0.3431 | 0.5003 | 0.4785 | 301.6855 | |
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| 0.4973 | 7.0 | 2625 | 0.5521 | 1.1281 | 0.7349 | 0.9983 | 0.9983 | 295.0692 | |
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| 1.1935 | 8.0 | 3000 | 0.5661 | 1.3444 | 0.9964 | 1.2673 | 1.2213 | 324.3648 | |
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| 0.0752 | 9.0 | 3375 | 0.5531 | 1.4883 | 1.0199 | 1.4252 | 1.3979 | 301.0377 | |
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| 0.216 | 10.0 | 3750 | 0.5573 | 1.5516 | 1.0371 | 1.5047 | 1.4656 | 319.195 | |
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| 0.3619 | 11.0 | 4125 | 0.5571 | 1.2368 | 0.8055 | 1.2326 | 1.2146 | 294.4717 | |
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| 0.1881 | 12.0 | 4500 | 0.5293 | 1.2922 | 0.941 | 1.2149 | 1.2084 | 305.9057 | |
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| 0.2247 | 13.0 | 4875 | 0.5340 | 1.0581 | 0.594 | 0.9989 | 0.987 | 306.3774 | |
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| 0.0715 | 14.0 | 5250 | 0.5211 | 1.2905 | 0.8861 | 1.259 | 1.2143 | 321.6226 | |
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| 0.1851 | 15.0 | 5625 | 0.5231 | 1.4625 | 0.9737 | 1.3919 | 1.3637 | 318.4969 | |
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| 0.5285 | 16.0 | 6000 | 0.5154 | 1.1892 | 0.8552 | 1.1401 | 1.1061 | 313.2138 | |
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| 0.0482 | 17.0 | 6375 | 0.5032 | 1.1826 | 0.8687 | 1.1554 | 1.1554 | 327.1824 | |
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| 0.0733 | 18.0 | 6750 | 0.5193 | 1.6133 | 1.1373 | 1.5626 | 1.5085 | 317.8113 | |
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| 0.2814 | 19.0 | 7125 | 0.5007 | 1.5689 | 1.1133 | 1.5189 | 1.4606 | 307.7421 | |
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| 0.0672 | 20.0 | 7500 | 0.4959 | 1.5754 | 1.078 | 1.489 | 1.4166 | 316.6164 | |
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| 0.2456 | 21.0 | 7875 | 0.4966 | 1.5754 | 1.087 | 1.5005 | 1.4211 | 314.3396 | |
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| 0.0405 | 22.0 | 8250 | 0.4953 | 1.5754 | 1.087 | 1.5005 | 1.4211 | 310.6981 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0.dev20230811+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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