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End of training

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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1404
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  ## Model description
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@@ -52,65 +52,65 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-------:|:-----:|:---------------:|
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- | 0.2947 | 0.2001 | 720 | 0.1929 |
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- | 0.1972 | 0.4001 | 1440 | 0.1784 |
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- | 0.1679 | 0.6002 | 2160 | 0.1608 |
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- | 0.1584 | 0.8002 | 2880 | 0.1579 |
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- | 0.1478 | 1.0003 | 3600 | 0.1473 |
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- | 0.1315 | 1.2003 | 4320 | 0.1439 |
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- | 0.128 | 1.4004 | 5040 | 0.1358 |
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- | 0.126 | 1.6004 | 5760 | 0.1329 |
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- | 0.1255 | 1.8005 | 6480 | 0.1322 |
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- | 0.1199 | 2.0006 | 7200 | 0.1269 |
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- | 0.108 | 2.2006 | 7920 | 0.1255 |
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- | 0.1047 | 2.4007 | 8640 | 0.1224 |
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- | 0.1038 | 2.6007 | 9360 | 0.1205 |
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- | 0.1043 | 2.8008 | 10080 | 0.1158 |
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- | 0.1042 | 3.0008 | 10800 | 0.1148 |
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- | 0.0884 | 3.2009 | 11520 | 0.1130 |
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- | 0.0903 | 3.4009 | 12240 | 0.1104 |
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- | 0.0889 | 3.6010 | 12960 | 0.1132 |
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- | 0.0885 | 3.8011 | 13680 | 0.1122 |
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- | 0.0882 | 4.0011 | 14400 | 0.1118 |
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- | 0.0753 | 4.2012 | 15120 | 0.1177 |
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- | 0.0764 | 4.4012 | 15840 | 0.1131 |
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- | 0.0755 | 4.6013 | 16560 | 0.1104 |
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- | 0.077 | 4.8013 | 17280 | 0.1090 |
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- | 0.0745 | 5.0014 | 18000 | 0.1091 |
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- | 0.0641 | 5.2014 | 18720 | 0.1118 |
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- | 0.0648 | 5.4015 | 19440 | 0.1087 |
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- | 0.0661 | 5.6016 | 20160 | 0.1093 |
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- | 0.0666 | 5.8016 | 20880 | 0.1060 |
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- | 0.065 | 6.0017 | 21600 | 0.1019 |
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- | 0.0565 | 6.2017 | 22320 | 0.1103 |
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- | 0.0575 | 6.4018 | 23040 | 0.1072 |
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- | 0.057 | 6.6018 | 23760 | 0.1105 |
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- | 0.057 | 6.8019 | 24480 | 0.1103 |
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- | 0.0566 | 7.0019 | 25200 | 0.1054 |
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- | 0.049 | 7.2020 | 25920 | 0.1135 |
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- | 0.0471 | 7.4021 | 26640 | 0.1102 |
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- | 0.0481 | 7.6021 | 27360 | 0.1120 |
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- | 0.0481 | 7.8022 | 28080 | 0.1071 |
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- | 0.0486 | 8.0022 | 28800 | 0.1090 |
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- | 0.0404 | 8.2023 | 29520 | 0.1156 |
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- | 0.0396 | 8.4023 | 30240 | 0.1120 |
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- | 0.0406 | 8.6024 | 30960 | 0.1184 |
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- | 0.0413 | 8.8024 | 31680 | 0.1123 |
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- | 0.0407 | 9.0025 | 32400 | 0.1140 |
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- | 0.033 | 9.2026 | 33120 | 0.1215 |
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- | 0.0345 | 9.4026 | 33840 | 0.1236 |
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- | 0.0344 | 9.6027 | 34560 | 0.1232 |
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- | 0.0351 | 9.8027 | 35280 | 0.1216 |
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- | 0.0336 | 10.0028 | 36000 | 0.1204 |
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- | 0.0289 | 10.2028 | 36720 | 0.1270 |
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- | 0.0286 | 10.4029 | 37440 | 0.1251 |
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- | 0.0292 | 10.6029 | 38160 | 0.1280 |
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- | 0.0287 | 10.8030 | 38880 | 0.1312 |
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- | 0.0297 | 11.0031 | 39600 | 0.1314 |
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- | 0.0256 | 11.2031 | 40320 | 0.1425 |
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- | 0.0254 | 11.4032 | 41040 | 0.1405 |
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- | 0.0254 | 11.6032 | 41760 | 0.1425 |
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- | 0.0255 | 11.8033 | 42480 | 0.1404 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1382
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-------:|:-----:|:---------------:|
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+ | 0.2943 | 0.2001 | 720 | 0.2140 |
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+ | 0.1986 | 0.4001 | 1440 | 0.1763 |
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+ | 0.1686 | 0.6002 | 2160 | 0.1616 |
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+ | 0.1577 | 0.8002 | 2880 | 0.1504 |
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+ | 0.1477 | 1.0003 | 3600 | 0.1454 |
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+ | 0.1318 | 1.2003 | 4320 | 0.1396 |
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+ | 0.1269 | 1.4004 | 5040 | 0.1409 |
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+ | 0.1263 | 1.6004 | 5760 | 0.1312 |
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+ | 0.1258 | 1.8005 | 6480 | 0.1292 |
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+ | 0.1201 | 2.0006 | 7200 | 0.1226 |
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+ | 0.108 | 2.2006 | 7920 | 0.1280 |
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+ | 0.1055 | 2.4007 | 8640 | 0.1271 |
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+ | 0.1033 | 2.6007 | 9360 | 0.1222 |
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+ | 0.1042 | 2.8008 | 10080 | 0.1169 |
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+ | 0.1032 | 3.0008 | 10800 | 0.1154 |
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+ | 0.0874 | 3.2009 | 11520 | 0.1194 |
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+ | 0.0902 | 3.4009 | 12240 | 0.1132 |
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+ | 0.0891 | 3.6010 | 12960 | 0.1170 |
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+ | 0.0878 | 3.8011 | 13680 | 0.1136 |
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+ | 0.088 | 4.0011 | 14400 | 0.1111 |
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+ | 0.0754 | 4.2012 | 15120 | 0.1146 |
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+ | 0.076 | 4.4012 | 15840 | 0.1115 |
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+ | 0.0762 | 4.6013 | 16560 | 0.1125 |
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+ | 0.0771 | 4.8013 | 17280 | 0.1065 |
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+ | 0.0749 | 5.0014 | 18000 | 0.1085 |
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+ | 0.0642 | 5.2014 | 18720 | 0.1124 |
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+ | 0.0649 | 5.4015 | 19440 | 0.1092 |
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+ | 0.0656 | 5.6016 | 20160 | 0.1073 |
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+ | 0.0673 | 5.8016 | 20880 | 0.1055 |
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+ | 0.065 | 6.0017 | 21600 | 0.1046 |
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+ | 0.0565 | 6.2017 | 22320 | 0.1111 |
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+ | 0.0566 | 6.4018 | 23040 | 0.1106 |
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+ | 0.0567 | 6.6018 | 23760 | 0.1132 |
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+ | 0.057 | 6.8019 | 24480 | 0.1066 |
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+ | 0.0564 | 7.0019 | 25200 | 0.1074 |
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+ | 0.049 | 7.2020 | 25920 | 0.1171 |
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+ | 0.0478 | 7.4021 | 26640 | 0.1096 |
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+ | 0.0481 | 7.6021 | 27360 | 0.1151 |
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+ | 0.0483 | 7.8022 | 28080 | 0.1063 |
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+ | 0.0487 | 8.0022 | 28800 | 0.1124 |
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+ | 0.0411 | 8.2023 | 29520 | 0.1167 |
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+ | 0.0398 | 8.4023 | 30240 | 0.1151 |
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+ | 0.0401 | 8.6024 | 30960 | 0.1173 |
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+ | 0.0411 | 8.8024 | 31680 | 0.1139 |
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+ | 0.0399 | 9.0025 | 32400 | 0.1134 |
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+ | 0.0333 | 9.2026 | 33120 | 0.1223 |
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+ | 0.034 | 9.4026 | 33840 | 0.1184 |
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+ | 0.0345 | 9.6027 | 34560 | 0.1249 |
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+ | 0.0352 | 9.8027 | 35280 | 0.1201 |
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+ | 0.0338 | 10.0028 | 36000 | 0.1183 |
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+ | 0.0288 | 10.2028 | 36720 | 0.1291 |
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+ | 0.0283 | 10.4029 | 37440 | 0.1312 |
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+ | 0.0288 | 10.6029 | 38160 | 0.1287 |
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+ | 0.0289 | 10.8030 | 38880 | 0.1264 |
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+ | 0.0299 | 11.0031 | 39600 | 0.1309 |
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+ | 0.0259 | 11.2031 | 40320 | 0.1409 |
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+ | 0.0254 | 11.4032 | 41040 | 0.1382 |
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+ | 0.0252 | 11.6032 | 41760 | 0.1400 |
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+ | 0.0254 | 11.8033 | 42480 | 0.1382 |
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  ### Framework versions