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yalhessi/lemexp-task1-v2-template_small-Llama-3.2-1B-ddp-8lr-v2
lemexp-task1-v2-template_small-Llama-3.2-1B-ddp-8lr-v2 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 llama3.2.
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 meta-llama/Llama-3.2-1B 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 |
|---|---|---|---|
| 0.444 | 0.2001 | 720 | 0.3647 |
| 0.3484 | 0.4001 | 1440 | 0.3466 |
| 0.3078 | 0.6002 | 2160 | 0.3090 |
| 0.2984 | 0.8002 | 2880 | 0.2984 |
| 0.2837 | 1.0003 | 3600 | 0.2891 |
| 0.2731 | 1.2003 | 4320 | 0.2821 |
| 0.2637 | 1.4004 | 5040 | 0.2773 |
| 0.2617 | 1.6004 | 5760 | 0.2794 |
| 0.2607 | 1.8005 | 6480 | 0.2676 |
| 0.2524 | 2.0006 | 7200 | 0.2582 |
| 0.245 | 2.2006 | 7920 | 0.2528 |
| 0.2408 | 2.4007 | 8640 | 0.2478 |
| 0.2357 | 2.6007 | 9360 | 0.2441 |
| 0.2347 | 2.8008 | 10080 | 0.2395 |
| 0.2354 | 3.0008 | 10800 | 0.2461 |
| 0.2234 | 3.2009 | 11520 | 0.2394 |
| 0.2264 | 3.4009 | 12240 | 0.2314 |
| 0.22 | 3.6010 | 12960 | 0.2321 |
| 0.2183 | 3.8011 | 13680 | 0.2281 |
| 0.2156 | 4.0011 | 14400 | 0.2244 |
| 0.208 | 4.2012 | 15120 | 0.2202 |
| 0.2071 | 4.4012 | 15840 | 0.2187 |
| 0.2027 | 4.6013 | 16560 | 0.2216 |
| 0.2028 | 4.8013 | 17280 | 0.2144 |
| 0.1993 | 5.0014 | 18000 | 0.2138 |
| 0.1919 | 5.2014 | 18720 | 0.2077 |
| 0.1902 | 5.4015 | 19440 | 0.2104 |
| 0.1892 | 5.6016 | 20160 | 0.2115 |
| 0.19 | 5.8016 | 20880 | 0.2020 |
| 0.1847 | 6.0017 | 21600 | 0.2015 |
| 0.1764 | 6.2017 | 22320 | 0.1956 |
| 0.1788 | 6.4018 | 23040 | 0.1907 |
| 0.1742 | 6.6018 | 23760 | 0.1924 |
| 0.1744 | 6.8019 | 24480 | 0.1939 |
| 0.1718 | 7.0019 | 25200 | 0.1847 |
| 0.1632 | 7.2020 | 25920 | 0.1856 |
| 0.1628 | 7.4021 | 26640 | 0.1880 |
| 0.1611 | 7.6021 | 27360 | 0.1837 |
| 0.1572 | 7.8022 | 28080 | 0.1780 |
| 0.1615 | 8.0022 | 28800 | 0.1776 |
| 0.1491 | 8.2023 | 29520 | 0.1739 |
| 0.1453 | 8.4023 | 30240 | 0.1726 |
| 0.1469 | 8.6024 | 30960 | 0.1706 |
| 0.1429 | 8.8024 | 31680 | 0.1701 |
| 0.1453 | 9.0025 | 32400 | 0.1679 |
| 0.1339 | 9.2026 | 33120 | 0.1658 |
| 0.1312 | 9.4026 | 33840 | 0.1626 |
| 0.1325 | 9.6027 | 34560 | 0.1623 |
| 0.1318 | 9.8027 | 35280 | 0.1580 |
| 0.126 | 10.0028 | 36000 | 0.1605 |
| 0.1177 | 10.2028 | 36720 | 0.1553 |
| 0.1168 | 10.4029 | 37440 | 0.1555 |
| 0.1153 | 10.6029 | 38160 | 0.1539 |
| 0.1154 | 10.8030 | 38880 | 0.1522 |
| 0.1158 | 11.0031 | 39600 | 0.1520 |
| 0.1044 | 11.2031 | 40320 | 0.1518 |
| 0.1036 | 11.4032 | 41040 | 0.1509 |
| 0.1016 | 11.6032 | 41760 | 0.1504 |
| 0.1004 | 11.8033 | 42480 | 0.1486 |