metadata
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
model-index:
- name: mt5-base-p-l-akk-en-20240709-215100
results: []
mt5-base-p-l-akk-en-20240709-215100
This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1533
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 30.893 | 0.1326 | 500 | 5.1945 |
| 2.9823 | 0.2651 | 1000 | 0.6672 |
| 0.6668 | 0.3977 | 1500 | 0.5089 |
| 0.4944 | 0.5302 | 2000 | 0.3100 |
| 0.3002 | 0.6628 | 2500 | 0.2663 |
| 0.2813 | 0.7953 | 3000 | 0.2493 |
| 0.273 | 0.9279 | 3500 | 0.2369 |
| 0.2544 | 1.0604 | 4000 | 0.2304 |
| 0.2445 | 1.1930 | 4500 | 0.2241 |
| 0.2365 | 1.3256 | 5000 | 0.2190 |
| 0.2305 | 1.4581 | 5500 | 0.2140 |
| 0.2318 | 1.5907 | 6000 | 0.2108 |
| 0.2166 | 1.7232 | 6500 | 0.2060 |
| 0.2195 | 1.8558 | 7000 | 0.2029 |
| 0.2125 | 1.9883 | 7500 | 0.2000 |
| 0.2091 | 2.1209 | 8000 | 0.1963 |
| 0.2092 | 2.2534 | 8500 | 0.1938 |
| 0.2032 | 2.3860 | 9000 | 0.1915 |
| 0.2018 | 2.5186 | 9500 | 0.1892 |
| 0.2017 | 2.6511 | 10000 | 0.1870 |
| 0.1961 | 2.7837 | 10500 | 0.1855 |
| 0.2009 | 2.9162 | 11000 | 0.1841 |
| 0.1956 | 3.0488 | 11500 | 0.1828 |
| 0.1915 | 3.1813 | 12000 | 0.1807 |
| 0.1892 | 3.3139 | 12500 | 0.1790 |
| 0.1908 | 3.4464 | 13000 | 0.1773 |
| 0.1834 | 3.5790 | 13500 | 0.1763 |
| 0.1832 | 3.7116 | 14000 | 0.1744 |
| 0.189 | 3.8441 | 14500 | 0.1734 |
| 0.1848 | 3.9767 | 15000 | 0.1724 |
| 0.1838 | 4.1092 | 15500 | 0.1715 |
| 0.177 | 4.2418 | 16000 | 0.1703 |
| 0.1808 | 4.3743 | 16500 | 0.1692 |
| 0.183 | 4.5069 | 17000 | 0.1680 |
| 0.1753 | 4.6394 | 17500 | 0.1675 |
| 0.1724 | 4.7720 | 18000 | 0.1666 |
| 0.1782 | 4.9046 | 18500 | 0.1656 |
| 0.1799 | 5.0371 | 19000 | 0.1653 |
| 0.1725 | 5.1697 | 19500 | 0.1647 |
| 0.17 | 5.3022 | 20000 | 0.1635 |
| 0.1722 | 5.4348 | 20500 | 0.1630 |
| 0.1697 | 5.5673 | 21000 | 0.1625 |
| 0.1719 | 5.6999 | 21500 | 0.1620 |
| 0.1709 | 5.8324 | 22000 | 0.1611 |
| 0.1727 | 5.9650 | 22500 | 0.1604 |
| 0.1721 | 6.0976 | 23000 | 0.1598 |
| 0.1681 | 6.2301 | 23500 | 0.1602 |
| 0.1699 | 6.3627 | 24000 | 0.1596 |
| 0.1639 | 6.4952 | 24500 | 0.1588 |
| 0.1646 | 6.6278 | 25000 | 0.1584 |
| 0.1691 | 6.7603 | 25500 | 0.1582 |
| 0.1653 | 6.8929 | 26000 | 0.1574 |
| 0.1648 | 7.0255 | 26500 | 0.1572 |
| 0.1669 | 7.1580 | 27000 | 0.1569 |
| 0.16 | 7.2906 | 27500 | 0.1568 |
| 0.1622 | 7.4231 | 28000 | 0.1562 |
| 0.1644 | 7.5557 | 28500 | 0.1561 |
| 0.1674 | 7.6882 | 29000 | 0.1557 |
| 0.1628 | 7.8208 | 29500 | 0.1552 |
| 0.1619 | 7.9533 | 30000 | 0.1551 |
| 0.1636 | 8.0859 | 30500 | 0.1549 |
| 0.1629 | 8.2185 | 31000 | 0.1546 |
| 0.1632 | 8.3510 | 31500 | 0.1545 |
| 0.1641 | 8.4836 | 32000 | 0.1543 |
| 0.1592 | 8.6161 | 32500 | 0.1541 |
| 0.1573 | 8.7487 | 33000 | 0.1539 |
| 0.1607 | 8.8812 | 33500 | 0.1540 |
| 0.1651 | 9.0138 | 34000 | 0.1537 |
| 0.1551 | 9.1463 | 34500 | 0.1537 |
| 0.1621 | 9.2789 | 35000 | 0.1536 |
| 0.166 | 9.4115 | 35500 | 0.1534 |
| 0.1575 | 9.5440 | 36000 | 0.1534 |
| 0.1607 | 9.6766 | 36500 | 0.1534 |
| 0.1627 | 9.8091 | 37000 | 0.1533 |
| 0.1608 | 9.9417 | 37500 | 0.1533 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.5.0.dev20240625
- Datasets 2.20.0
- Tokenizers 0.19.1