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yalhessi/lemexp-task1-v2-template_small_notypes-deepseek-coder-1.3b-base-8lr-12epochs-normal-eos
lemexp-task1-v2-template_small_notypes-deepseek-coder-1.3b-base-8lr-12epochs-normal-eos is a machine learning model from yalhessi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4238 | 0.2001 | 720 | 0.3327 |
| 0.3258 | 0.4001 | 1440 | 0.2945 |
| 0.2855 | 0.6002 | 2160 | 0.2871 |
| 0.2758 | 0.8002 | 2880 | 0.2714 |
| 0.2595 | 1.0003 | 3600 | 0.2656 |
| 0.2464 | 1.2003 | 4320 | 0.2556 |
| 0.2409 | 1.4004 | 5040 | 0.2492 |
| 0.2366 | 1.6004 | 5760 | 0.2484 |
| 0.2385 | 1.8005 | 6480 | 0.2382 |
| 0.2294 | 2.0006 | 7200 | 0.2394 |
| 0.2194 | 2.2006 | 7920 | 0.2376 |
| 0.2149 | 2.4007 | 8640 | 0.2289 |
| 0.2118 | 2.6007 | 9360 | 0.2247 |
| 0.2113 | 2.8008 | 10080 | 0.2233 |
| 0.2123 | 3.0008 | 10800 | 0.2208 |
| 0.1975 | 3.2009 | 11520 | 0.2212 |
| 0.1978 | 3.4009 | 12240 | 0.2129 |
| 0.1942 | 3.6010 | 12960 | 0.2106 |
| 0.1932 | 3.8011 | 13680 | 0.2094 |
| 0.1947 | 4.0011 | 14400 | 0.2134 |
| 0.1801 | 4.2012 | 15120 | 0.2122 |
| 0.1818 | 4.4012 | 15840 | 0.2033 |
| 0.177 | 4.6013 | 16560 | 0.2028 |
| 0.178 | 4.8013 | 17280 | 0.2030 |
| 0.1737 | 5.0014 | 18000 | 0.1973 |
| 0.1643 | 5.2014 | 18720 | 0.1941 |
| 0.1654 | 5.4015 | 19440 | 0.1945 |
| 0.1657 | 5.6016 | 20160 | 0.1927 |
| 0.1654 | 5.8016 | 20880 | 0.1919 |
| 0.1603 | 6.0017 | 21600 | 0.1871 |
| 0.153 | 6.2017 | 22320 | 0.1861 |
| 0.1514 | 6.4018 | 23040 | 0.1840 |
| 0.1498 | 6.6018 | 23760 | 0.1848 |
| 0.1494 | 6.8019 | 24480 | 0.1823 |
| 0.1475 | 7.0019 | 25200 | 0.1785 |
| 0.1368 | 7.2020 | 25920 | 0.1810 |
| 0.137 | 7.4021 | 26640 | 0.1792 |
| 0.137 | 7.6021 | 27360 | 0.1792 |
| 0.1335 | 7.8022 | 28080 | 0.1734 |
| 0.1354 | 8.0022 | 28800 | 0.1697 |
| 0.1211 | 8.2023 | 29520 | 0.1739 |
| 0.1198 | 8.4023 | 30240 | 0.1724 |
| 0.1225 | 8.6024 | 30960 | 0.1717 |
| 0.121 | 8.8024 | 31680 | 0.1673 |
| 0.1199 | 9.0025 | 32400 | 0.1673 |
| 0.1061 | 9.2026 | 33120 | 0.1705 |
| 0.1065 | 9.4026 | 33840 | 0.1684 |
| 0.1084 | 9.6027 | 34560 | 0.1652 |
| 0.1075 | 9.8027 | 35280 | 0.1627 |
| 0.1022 | 10.0028 | 36000 | 0.1648 |
| 0.0921 | 10.2028 | 36720 | 0.1703 |
| 0.0921 | 10.4029 | 37440 | 0.1659 |
| 0.0927 | 10.6029 | 38160 | 0.1685 |
| 0.0917 | 10.8030 | 38880 | 0.1654 |
| 0.0916 | 11.0031 | 39600 | 0.1655 |
| 0.0815 | 11.2031 | 40320 | 0.1719 |
| 0.0811 | 11.4032 | 41040 | 0.1719 |
| 0.0794 | 11.6032 | 41760 | 0.1704 |
| 0.0794 | 11.8033 | 42480 | 0.1712 |