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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 |
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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 |
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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: 2.2824 |
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- Rouge1: 0.1798 |
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- Rouge2: 0.1214 |
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- Rougel: 0.1629 |
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- Rougelsum: 0.1734 |
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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 | 3.1376 | 0.1326 | 0.089 | 0.1198 | 0.1274 | 19.0 | |
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| No log | 2.0 | 176 | 2.5907 | 0.1782 | 0.1106 | 0.1507 | 0.169 | 19.0 | |
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| 3.838 | 3.0 | 264 | 2.4840 | 0.1816 | 0.1192 | 0.1607 | 0.1747 | 19.0 | |
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| 3.838 | 4.0 | 352 | 2.4281 | 0.1784 | 0.117 | 0.1605 | 0.1725 | 19.0 | |
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| 2.4977 | 5.0 | 440 | 2.3860 | 0.1757 | 0.1138 | 0.158 | 0.1697 | 19.0 | |
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| 2.4977 | 6.0 | 528 | 2.3611 | 0.18 | 0.121 | 0.1628 | 0.1744 | 19.0 | |
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| 2.3101 | 7.0 | 616 | 2.3437 | 0.1792 | 0.1203 | 0.1625 | 0.1733 | 19.0 | |
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| 2.3101 | 8.0 | 704 | 2.3327 | 0.1791 | 0.121 | 0.1625 | 0.1734 | 19.0 | |
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| 2.3101 | 9.0 | 792 | 2.3165 | 0.1795 | 0.1217 | 0.1625 | 0.1741 | 19.0 | |
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| 2.1814 | 10.0 | 880 | 2.3109 | 0.1772 | 0.1186 | 0.1598 | 0.1711 | 19.0 | |
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| 2.1814 | 11.0 | 968 | 2.2978 | 0.1785 | 0.1201 | 0.1611 | 0.1726 | 19.0 | |
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| 2.1193 | 12.0 | 1056 | 2.2923 | 0.1792 | 0.1204 | 0.1618 | 0.1733 | 19.0 | |
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| 2.1193 | 13.0 | 1144 | 2.2958 | 0.1789 | 0.1204 | 0.1613 | 0.1729 | 19.0 | |
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| 2.0126 | 14.0 | 1232 | 2.2870 | 0.1785 | 0.1204 | 0.161 | 0.1725 | 19.0 | |
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| 2.0126 | 15.0 | 1320 | 2.2872 | 0.1789 | 0.1204 | 0.1613 | 0.1728 | 19.0 | |
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| 1.9237 | 16.0 | 1408 | 2.2799 | 0.1792 | 0.1204 | 0.1618 | 0.1733 | 19.0 | |
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| 1.9237 | 17.0 | 1496 | 2.2825 | 0.1787 | 0.1219 | 0.1626 | 0.1732 | 19.0 | |
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| 1.9237 | 18.0 | 1584 | 2.2788 | 0.1787 | 0.1219 | 0.1626 | 0.1729 | 19.0 | |
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| 1.9157 | 19.0 | 1672 | 2.2787 | 0.1784 | 0.1215 | 0.1622 | 0.1727 | 19.0 | |
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| 1.9157 | 20.0 | 1760 | 2.2835 | 0.1776 | 0.1211 | 0.1614 | 0.1721 | 19.0 | |
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| 1.8614 | 21.0 | 1848 | 2.2785 | 0.1808 | 0.1218 | 0.1636 | 0.1752 | 19.0 | |
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| 1.8614 | 22.0 | 1936 | 2.2823 | 0.1795 | 0.1214 | 0.1626 | 0.1732 | 19.0 | |
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| 1.8565 | 23.0 | 2024 | 2.2774 | 0.1798 | 0.1214 | 0.1629 | 0.1734 | 19.0 | |
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| 1.8565 | 24.0 | 2112 | 2.2797 | 0.1798 | 0.1214 | 0.1629 | 0.1734 | 19.0 | |
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| 1.8076 | 25.0 | 2200 | 2.2818 | 0.1798 | 0.1214 | 0.1629 | 0.1734 | 19.0 | |
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| 1.8076 | 26.0 | 2288 | 2.2825 | 0.1795 | 0.1214 | 0.1626 | 0.1732 | 19.0 | |
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| 1.8076 | 27.0 | 2376 | 2.2825 | 0.1795 | 0.1214 | 0.1626 | 0.1732 | 19.0 | |
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| 1.7745 | 28.0 | 2464 | 2.2823 | 0.1798 | 0.1214 | 0.1629 | 0.1734 | 19.0 | |
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| 1.7745 | 29.0 | 2552 | 2.2829 | 0.1795 | 0.1214 | 0.1626 | 0.1732 | 19.0 | |
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| 1.8083 | 30.0 | 2640 | 2.2824 | 0.1798 | 0.1214 | 0.1629 | 0.1734 | 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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