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--- |
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license: mit |
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base_model: arthurmluz/ptt5-wikilingua-30epochs |
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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: ptt5-wikilingua-temario |
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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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# ptt5-wikilingua-temario |
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This model is a fine-tuned version of [arthurmluz/ptt5-wikilingua-30epochs](https://huggingface.co/arthurmluz/ptt5-wikilingua-30epochs) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4753 |
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- Rouge1: 0.0857 |
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- Rouge2: 0.0533 |
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- Rougel: 0.0749 |
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- Rougelsum: 0.0832 |
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- Gen Len: 19.0 |
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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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- num_epochs: 30 |
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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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| No log | 1.0 | 88 | 2.7296 | 0.0742 | 0.0322 | 0.0612 | 0.0713 | 19.0 | |
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| No log | 2.0 | 176 | 2.6540 | 0.0825 | 0.0406 | 0.0667 | 0.0799 | 19.0 | |
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| 2.9757 | 3.0 | 264 | 2.6052 | 0.0844 | 0.0446 | 0.0692 | 0.0811 | 19.0 | |
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| 2.9757 | 4.0 | 352 | 2.5790 | 0.0839 | 0.0454 | 0.0696 | 0.0812 | 19.0 | |
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| 2.6661 | 5.0 | 440 | 2.5549 | 0.0856 | 0.0463 | 0.0711 | 0.0819 | 19.0 | |
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| 2.6661 | 6.0 | 528 | 2.5343 | 0.0851 | 0.0479 | 0.0717 | 0.0819 | 19.0 | |
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| 2.5257 | 7.0 | 616 | 2.5250 | 0.0856 | 0.049 | 0.0734 | 0.0826 | 19.0 | |
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| 2.5257 | 8.0 | 704 | 2.5128 | 0.087 | 0.0498 | 0.0748 | 0.0842 | 19.0 | |
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| 2.5257 | 9.0 | 792 | 2.5042 | 0.0849 | 0.0493 | 0.0738 | 0.082 | 19.0 | |
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| 2.433 | 10.0 | 880 | 2.4957 | 0.0838 | 0.0486 | 0.0726 | 0.081 | 19.0 | |
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| 2.433 | 11.0 | 968 | 2.4922 | 0.0844 | 0.0483 | 0.0723 | 0.0815 | 19.0 | |
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| 2.3774 | 12.0 | 1056 | 2.4894 | 0.0852 | 0.0517 | 0.0737 | 0.0826 | 19.0 | |
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| 2.3774 | 13.0 | 1144 | 2.4833 | 0.0857 | 0.0523 | 0.0738 | 0.083 | 19.0 | |
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| 2.3029 | 14.0 | 1232 | 2.4773 | 0.0853 | 0.0524 | 0.0738 | 0.0826 | 19.0 | |
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| 2.3029 | 15.0 | 1320 | 2.4783 | 0.0854 | 0.0532 | 0.0739 | 0.0829 | 19.0 | |
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| 2.2314 | 16.0 | 1408 | 2.4806 | 0.086 | 0.0535 | 0.0747 | 0.0834 | 19.0 | |
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| 2.2314 | 17.0 | 1496 | 2.4788 | 0.0861 | 0.0532 | 0.0746 | 0.0833 | 19.0 | |
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| 2.2314 | 18.0 | 1584 | 2.4769 | 0.0854 | 0.053 | 0.0744 | 0.0829 | 19.0 | |
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| 2.1949 | 19.0 | 1672 | 2.4722 | 0.0851 | 0.053 | 0.0744 | 0.0825 | 19.0 | |
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| 2.1949 | 20.0 | 1760 | 2.4707 | 0.086 | 0.0531 | 0.0751 | 0.0831 | 19.0 | |
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| 2.1735 | 21.0 | 1848 | 2.4737 | 0.0855 | 0.0534 | 0.0751 | 0.0829 | 19.0 | |
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| 2.1735 | 22.0 | 1936 | 2.4753 | 0.0857 | 0.0533 | 0.0745 | 0.083 | 19.0 | |
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| 2.1643 | 23.0 | 2024 | 2.4762 | 0.0852 | 0.0534 | 0.0748 | 0.0828 | 19.0 | |
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| 2.1643 | 24.0 | 2112 | 2.4747 | 0.0854 | 0.0534 | 0.0748 | 0.0829 | 19.0 | |
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| 2.1276 | 25.0 | 2200 | 2.4746 | 0.0854 | 0.0534 | 0.0748 | 0.0829 | 19.0 | |
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| 2.1276 | 26.0 | 2288 | 2.4761 | 0.0857 | 0.0533 | 0.0749 | 0.0832 | 19.0 | |
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| 2.1276 | 27.0 | 2376 | 2.4758 | 0.0857 | 0.0533 | 0.0749 | 0.0832 | 19.0 | |
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| 2.0938 | 28.0 | 2464 | 2.4757 | 0.0857 | 0.0533 | 0.0749 | 0.0832 | 19.0 | |
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| 2.0938 | 29.0 | 2552 | 2.4762 | 0.0857 | 0.0533 | 0.0749 | 0.0832 | 19.0 | |
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| 2.1207 | 30.0 | 2640 | 2.4753 | 0.0857 | 0.0533 | 0.0749 | 0.0832 | 19.0 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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