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--- |
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license: mit |
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base_model: unicamp-dl/ptt5-base-portuguese-vocab |
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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-cstnews-1024 |
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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-cstnews-1024 |
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This model is a fine-tuned version of [unicamp-dl/ptt5-base-portuguese-vocab](https://huggingface.co/unicamp-dl/ptt5-base-portuguese-vocab) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4269 |
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- Rouge1: 0.086 |
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- Rouge2: 0.0557 |
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- Rougel: 0.0758 |
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- Rougelsum: 0.0833 |
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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 | 3.0796 | 0.0605 | 0.0381 | 0.0539 | 0.0582 | 19.0 | |
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| No log | 2.0 | 176 | 2.7409 | 0.0841 | 0.0507 | 0.0737 | 0.0817 | 19.0 | |
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| 3.8249 | 3.0 | 264 | 2.6518 | 0.0866 | 0.0508 | 0.0747 | 0.0833 | 19.0 | |
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| 3.8249 | 4.0 | 352 | 2.5961 | 0.0869 | 0.0526 | 0.0758 | 0.0839 | 19.0 | |
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| 2.7351 | 5.0 | 440 | 2.5584 | 0.0869 | 0.0539 | 0.0759 | 0.0841 | 19.0 | |
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| 2.7351 | 6.0 | 528 | 2.5364 | 0.0858 | 0.0521 | 0.0743 | 0.0826 | 19.0 | |
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| 2.5802 | 7.0 | 616 | 2.5092 | 0.0847 | 0.0516 | 0.0736 | 0.0815 | 19.0 | |
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| 2.5802 | 8.0 | 704 | 2.5026 | 0.0855 | 0.055 | 0.075 | 0.0827 | 19.0 | |
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| 2.5802 | 9.0 | 792 | 2.4862 | 0.0852 | 0.0551 | 0.0749 | 0.0825 | 19.0 | |
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| 2.4864 | 10.0 | 880 | 2.4744 | 0.0853 | 0.0553 | 0.0751 | 0.0826 | 19.0 | |
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| 2.4864 | 11.0 | 968 | 2.4676 | 0.0871 | 0.0561 | 0.0764 | 0.0843 | 19.0 | |
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| 2.4328 | 12.0 | 1056 | 2.4627 | 0.0865 | 0.0561 | 0.0763 | 0.0837 | 19.0 | |
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| 2.4328 | 13.0 | 1144 | 2.4566 | 0.0877 | 0.0562 | 0.0765 | 0.0846 | 19.0 | |
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| 2.3615 | 14.0 | 1232 | 2.4495 | 0.0869 | 0.0559 | 0.0761 | 0.0842 | 19.0 | |
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| 2.3615 | 15.0 | 1320 | 2.4439 | 0.0869 | 0.0559 | 0.0761 | 0.0842 | 19.0 | |
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| 2.2926 | 16.0 | 1408 | 2.4447 | 0.0869 | 0.0559 | 0.0761 | 0.0842 | 19.0 | |
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| 2.2926 | 17.0 | 1496 | 2.4437 | 0.0866 | 0.0555 | 0.0759 | 0.0839 | 19.0 | |
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| 2.2926 | 18.0 | 1584 | 2.4345 | 0.0862 | 0.0557 | 0.076 | 0.0834 | 19.0 | |
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| 2.2657 | 19.0 | 1672 | 2.4342 | 0.0871 | 0.056 | 0.0764 | 0.0843 | 19.0 | |
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| 2.2657 | 20.0 | 1760 | 2.4328 | 0.0871 | 0.056 | 0.0764 | 0.0843 | 19.0 | |
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| 2.2425 | 21.0 | 1848 | 2.4317 | 0.0863 | 0.0558 | 0.0761 | 0.0836 | 19.0 | |
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| 2.2425 | 22.0 | 1936 | 2.4311 | 0.0863 | 0.0558 | 0.0761 | 0.0836 | 19.0 | |
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| 2.2338 | 23.0 | 2024 | 2.4292 | 0.0863 | 0.0558 | 0.0761 | 0.0836 | 19.0 | |
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| 2.2338 | 24.0 | 2112 | 2.4268 | 0.0861 | 0.056 | 0.0759 | 0.0836 | 19.0 | |
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| 2.203 | 25.0 | 2200 | 2.4270 | 0.0857 | 0.0559 | 0.0756 | 0.0833 | 19.0 | |
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| 2.203 | 26.0 | 2288 | 2.4290 | 0.0857 | 0.0557 | 0.0756 | 0.0833 | 19.0 | |
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| 2.203 | 27.0 | 2376 | 2.4272 | 0.0857 | 0.0557 | 0.0756 | 0.0833 | 19.0 | |
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| 2.1676 | 28.0 | 2464 | 2.4265 | 0.0857 | 0.0557 | 0.0756 | 0.0833 | 19.0 | |
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| 2.1676 | 29.0 | 2552 | 2.4273 | 0.086 | 0.0557 | 0.0758 | 0.0833 | 19.0 | |
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| 2.1984 | 30.0 | 2640 | 2.4269 | 0.086 | 0.0557 | 0.0758 | 0.0833 | 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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