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yalhessi/lemexp-task1-v3-lemma_object_full_notypes-deepseek-coder-1.3b-base-8lr-12epochs-no-eos
lemexp-task1-v3-lemma_object_full_notypes-deepseek-coder-1.3b-base-8lr-12epochs-no-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 |
|---|---|---|---|
| 0.4232 | 0.2000 | 3114 | 0.4273 |
| 0.3947 | 0.4000 | 6228 | 0.3940 |
| 0.3804 | 0.6000 | 9342 | 0.3804 |
| 0.3689 | 0.8001 | 12456 | 0.3685 |
| 0.3606 | 1.0001 | 15570 | 0.3562 |
| 0.3512 | 1.2001 | 18684 | 0.3498 |
| 0.3433 | 1.4001 | 21798 | 0.3387 |
| 0.3402 | 1.6001 | 24912 | 0.3419 |
| 0.3389 | 1.8001 | 28026 | 0.3369 |
| 0.3334 | 2.0001 | 31140 | 0.3334 |
| 0.3218 | 2.2001 | 34254 | 0.3264 |
| 0.3253 | 2.4002 | 37368 | 0.3244 |
| 0.3221 | 2.6002 | 40482 | 0.3179 |
| 0.3195 | 2.8002 | 43596 | 0.3156 |
| 0.3115 | 3.0002 | 46710 | 0.3117 |
| 0.3037 | 3.2002 | 49824 | 0.3134 |
| 0.2986 | 3.4002 | 52938 | 0.3067 |
| 0.2978 | 3.6002 | 56052 | 0.2991 |
| 0.2962 | 3.8002 | 59166 | 0.2982 |
| 0.2953 | 4.0003 | 62280 | 0.2979 |
| 0.2829 | 4.2003 | 65394 | 0.2898 |
| 0.2813 | 4.4003 | 68508 | 0.2851 |
| 0.2791 | 4.6003 | 71622 | 0.2836 |
| 0.2799 | 4.8003 | 74736 | 0.2824 |
| 0.2806 | 5.0003 | 77850 | 0.2802 |
| 0.2663 | 5.2003 | 80964 | 0.2765 |
| 0.2672 | 5.4003 | 84078 | 0.2748 |
| 0.2639 | 5.6004 | 87192 | 0.2681 |
| 0.2588 | 5.8004 | 90306 | 0.2668 |
| 0.2599 | 6.0004 | 93420 | 0.2626 |
| 0.2491 | 6.2004 | 96534 | 0.2581 |
| 0.2496 | 6.4004 | 99648 | 0.2596 |
| 0.2488 | 6.6004 | 102762 | 0.2561 |
| 0.2453 | 6.8004 | 105876 | 0.2535 |
| 0.2459 | 7.0004 | 108990 | 0.2499 |
| 0.233 | 7.2005 | 112104 | 0.2437 |
| 0.2284 | 7.4005 | 115218 | 0.2458 |
| 0.2305 | 7.6005 | 118332 | 0.2435 |
| 0.2297 | 7.8005 | 121446 | 0.2368 |
| 0.2247 | 8.0005 | 124560 | 0.2334 |
| 0.2142 | 8.2005 | 127674 | 0.2339 |
| 0.2145 | 8.4005 | 130788 | 0.2318 |
| 0.2126 | 8.6006 | 133902 | 0.2267 |
| 0.2167 | 8.8006 | 137016 | 0.2295 |
| 0.206 | 9.0006 | 140130 | 0.2217 |
| 0.1978 | 9.2006 | 143244 | 0.2207 |
| 0.1955 | 9.4006 | 146358 | 0.2186 |
| 0.1941 | 9.6006 | 149472 | 0.2160 |
| 0.1939 | 9.8006 | 152586 | 0.2140 |
| 0.1898 | 10.0006 | 155700 | 0.2109 |
| 0.1792 | 10.2007 | 158814 | 0.2101 |
| 0.1793 | 10.4007 | 161928 | 0.2100 |
| 0.1766 | 10.6007 | 165042 | 0.2051 |
| 0.1738 | 10.8007 | 168156 | 0.2008 |
| 0.1712 | 11.0007 | 171270 | 0.2008 |
| 0.1648 | 11.2007 | 174384 | 0.2006 |
| 0.1623 | 11.4007 | 177498 | 0.1980 |
| 0.157 | 11.6007 | 180612 | 0.1969 |
| 0.1596 | 11.8008 | 183726 | 0.1950 |