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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: mt5-base-p-l-akk-en-20240709-215100 |
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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-base-p-l-akk-en-20240709-215100 |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co./google/mt5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1533 |
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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: 4e-05 |
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- train_batch_size: 12 |
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- eval_batch_size: 12 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 30.893 | 0.1326 | 500 | 5.1945 | |
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| 2.9823 | 0.2651 | 1000 | 0.6672 | |
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| 0.6668 | 0.3977 | 1500 | 0.5089 | |
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| 0.4944 | 0.5302 | 2000 | 0.3100 | |
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| 0.3002 | 0.6628 | 2500 | 0.2663 | |
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| 0.2813 | 0.7953 | 3000 | 0.2493 | |
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| 0.273 | 0.9279 | 3500 | 0.2369 | |
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| 0.2544 | 1.0604 | 4000 | 0.2304 | |
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| 0.2445 | 1.1930 | 4500 | 0.2241 | |
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| 0.2365 | 1.3256 | 5000 | 0.2190 | |
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| 0.2305 | 1.4581 | 5500 | 0.2140 | |
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| 0.2318 | 1.5907 | 6000 | 0.2108 | |
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| 0.2166 | 1.7232 | 6500 | 0.2060 | |
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| 0.2195 | 1.8558 | 7000 | 0.2029 | |
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| 0.2125 | 1.9883 | 7500 | 0.2000 | |
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| 0.2091 | 2.1209 | 8000 | 0.1963 | |
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| 0.2092 | 2.2534 | 8500 | 0.1938 | |
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| 0.2032 | 2.3860 | 9000 | 0.1915 | |
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| 0.2018 | 2.5186 | 9500 | 0.1892 | |
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| 0.2017 | 2.6511 | 10000 | 0.1870 | |
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| 0.1961 | 2.7837 | 10500 | 0.1855 | |
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| 0.2009 | 2.9162 | 11000 | 0.1841 | |
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| 0.1956 | 3.0488 | 11500 | 0.1828 | |
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| 0.1915 | 3.1813 | 12000 | 0.1807 | |
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| 0.1892 | 3.3139 | 12500 | 0.1790 | |
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| 0.1908 | 3.4464 | 13000 | 0.1773 | |
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| 0.1834 | 3.5790 | 13500 | 0.1763 | |
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| 0.1832 | 3.7116 | 14000 | 0.1744 | |
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| 0.189 | 3.8441 | 14500 | 0.1734 | |
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| 0.1848 | 3.9767 | 15000 | 0.1724 | |
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| 0.1838 | 4.1092 | 15500 | 0.1715 | |
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| 0.177 | 4.2418 | 16000 | 0.1703 | |
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| 0.1808 | 4.3743 | 16500 | 0.1692 | |
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| 0.183 | 4.5069 | 17000 | 0.1680 | |
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| 0.1753 | 4.6394 | 17500 | 0.1675 | |
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| 0.1724 | 4.7720 | 18000 | 0.1666 | |
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| 0.1782 | 4.9046 | 18500 | 0.1656 | |
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| 0.1799 | 5.0371 | 19000 | 0.1653 | |
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| 0.1725 | 5.1697 | 19500 | 0.1647 | |
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| 0.17 | 5.3022 | 20000 | 0.1635 | |
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| 0.1722 | 5.4348 | 20500 | 0.1630 | |
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| 0.1697 | 5.5673 | 21000 | 0.1625 | |
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| 0.1719 | 5.6999 | 21500 | 0.1620 | |
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| 0.1709 | 5.8324 | 22000 | 0.1611 | |
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| 0.1727 | 5.9650 | 22500 | 0.1604 | |
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| 0.1721 | 6.0976 | 23000 | 0.1598 | |
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| 0.1681 | 6.2301 | 23500 | 0.1602 | |
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| 0.1699 | 6.3627 | 24000 | 0.1596 | |
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| 0.1639 | 6.4952 | 24500 | 0.1588 | |
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| 0.1646 | 6.6278 | 25000 | 0.1584 | |
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| 0.1691 | 6.7603 | 25500 | 0.1582 | |
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| 0.1653 | 6.8929 | 26000 | 0.1574 | |
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| 0.1648 | 7.0255 | 26500 | 0.1572 | |
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| 0.1669 | 7.1580 | 27000 | 0.1569 | |
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| 0.16 | 7.2906 | 27500 | 0.1568 | |
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| 0.1622 | 7.4231 | 28000 | 0.1562 | |
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| 0.1644 | 7.5557 | 28500 | 0.1561 | |
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| 0.1674 | 7.6882 | 29000 | 0.1557 | |
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| 0.1628 | 7.8208 | 29500 | 0.1552 | |
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| 0.1619 | 7.9533 | 30000 | 0.1551 | |
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| 0.1636 | 8.0859 | 30500 | 0.1549 | |
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| 0.1629 | 8.2185 | 31000 | 0.1546 | |
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| 0.1632 | 8.3510 | 31500 | 0.1545 | |
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| 0.1641 | 8.4836 | 32000 | 0.1543 | |
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| 0.1592 | 8.6161 | 32500 | 0.1541 | |
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| 0.1573 | 8.7487 | 33000 | 0.1539 | |
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| 0.1607 | 8.8812 | 33500 | 0.1540 | |
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| 0.1651 | 9.0138 | 34000 | 0.1537 | |
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| 0.1551 | 9.1463 | 34500 | 0.1537 | |
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| 0.1621 | 9.2789 | 35000 | 0.1536 | |
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| 0.166 | 9.4115 | 35500 | 0.1534 | |
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| 0.1575 | 9.5440 | 36000 | 0.1534 | |
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| 0.1607 | 9.6766 | 36500 | 0.1534 | |
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| 0.1627 | 9.8091 | 37000 | 0.1533 | |
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| 0.1608 | 9.9417 | 37500 | 0.1533 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.5.0.dev20240625 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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