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--- |
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license: mit |
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base_model: arthurmluz/ptt5-xlsumm-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-xlsumm-gptextsum |
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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-xlsumm-gptextsum |
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This model is a fine-tuned version of [arthurmluz/ptt5-xlsumm-30epochs](https://huggingface.co/arthurmluz/ptt5-xlsumm-30epochs) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1132 |
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- Rouge1: 0.1715 |
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- Rouge2: 0.0919 |
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- Rougel: 0.1417 |
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- Rougelsum: 0.1611 |
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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 | 70 | 2.3037 | 0.1617 | 0.0691 | 0.1287 | 0.1467 | 19.0 | |
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| No log | 2.0 | 140 | 2.2106 | 0.1722 | 0.082 | 0.1362 | 0.1585 | 19.0 | |
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| 2.3539 | 3.0 | 210 | 2.1604 | 0.1738 | 0.0854 | 0.1387 | 0.1604 | 19.0 | |
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| 2.3539 | 4.0 | 280 | 2.1325 | 0.1727 | 0.0868 | 0.1407 | 0.1632 | 19.0 | |
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| 2.3539 | 5.0 | 350 | 2.1117 | 0.1707 | 0.0875 | 0.137 | 0.1603 | 19.0 | |
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| 2.0032 | 6.0 | 420 | 2.0957 | 0.1723 | 0.0907 | 0.1415 | 0.1607 | 19.0 | |
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| 2.0032 | 7.0 | 490 | 2.0848 | 0.1722 | 0.09 | 0.1414 | 0.1617 | 19.0 | |
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| 2.0032 | 8.0 | 560 | 2.0790 | 0.1757 | 0.0918 | 0.1429 | 0.164 | 19.0 | |
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| 1.8158 | 9.0 | 630 | 2.0800 | 0.1723 | 0.0929 | 0.1421 | 0.1614 | 19.0 | |
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| 1.8158 | 10.0 | 700 | 2.0736 | 0.1733 | 0.0923 | 0.1428 | 0.1617 | 19.0 | |
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| 1.8158 | 11.0 | 770 | 2.0721 | 0.1755 | 0.0955 | 0.1454 | 0.1631 | 19.0 | |
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| 1.6764 | 12.0 | 840 | 2.0784 | 0.1763 | 0.0973 | 0.1459 | 0.1637 | 19.0 | |
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| 1.6764 | 13.0 | 910 | 2.0761 | 0.1752 | 0.094 | 0.1456 | 0.1638 | 19.0 | |
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| 1.6764 | 14.0 | 980 | 2.0802 | 0.1745 | 0.0951 | 0.145 | 0.1631 | 19.0 | |
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| 1.5616 | 15.0 | 1050 | 2.0790 | 0.1745 | 0.0952 | 0.1458 | 0.1632 | 19.0 | |
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| 1.5616 | 16.0 | 1120 | 2.0841 | 0.1735 | 0.0946 | 0.1447 | 0.1629 | 19.0 | |
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| 1.5616 | 17.0 | 1190 | 2.0904 | 0.1731 | 0.0943 | 0.1444 | 0.1622 | 19.0 | |
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| 1.4821 | 18.0 | 1260 | 2.0909 | 0.1727 | 0.0934 | 0.1433 | 0.1613 | 19.0 | |
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| 1.4821 | 19.0 | 1330 | 2.0934 | 0.1738 | 0.0948 | 0.1448 | 0.1632 | 19.0 | |
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| 1.4256 | 20.0 | 1400 | 2.0948 | 0.1726 | 0.0935 | 0.1434 | 0.1621 | 19.0 | |
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| 1.4256 | 21.0 | 1470 | 2.0981 | 0.173 | 0.0942 | 0.1435 | 0.1621 | 19.0 | |
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| 1.4256 | 22.0 | 1540 | 2.1023 | 0.1734 | 0.0945 | 0.1445 | 0.1631 | 19.0 | |
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| 1.3691 | 23.0 | 1610 | 2.1048 | 0.1726 | 0.0941 | 0.1436 | 0.1616 | 19.0 | |
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| 1.3691 | 24.0 | 1680 | 2.1058 | 0.1721 | 0.0948 | 0.1435 | 0.1619 | 19.0 | |
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| 1.3691 | 25.0 | 1750 | 2.1095 | 0.1721 | 0.0945 | 0.1435 | 0.1619 | 19.0 | |
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| 1.3444 | 26.0 | 1820 | 2.1103 | 0.1721 | 0.0948 | 0.1436 | 0.1624 | 19.0 | |
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| 1.3444 | 27.0 | 1890 | 2.1113 | 0.1715 | 0.0923 | 0.1417 | 0.1611 | 19.0 | |
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| 1.3444 | 28.0 | 1960 | 2.1121 | 0.1715 | 0.0919 | 0.1417 | 0.1611 | 19.0 | |
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| 1.3145 | 29.0 | 2030 | 2.1130 | 0.172 | 0.093 | 0.1425 | 0.1619 | 19.0 | |
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| 1.3145 | 30.0 | 2100 | 2.1132 | 0.1715 | 0.0919 | 0.1417 | 0.1611 | 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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