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--- |
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library_name: peft |
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license: other |
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base_model: deepseek-ai/deepseek-coder-1.3b-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: lemexp-task3-v2-small_no_defs-deepseek-coder-1.3b-base-ddp-8lr-v2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# lemexp-task3-v2-small_no_defs-deepseek-coder-1.3b-base-ddp-8lr-v2 |
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This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1245 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0008 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 16 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 12 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:-----:|:---------------:| |
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| 0.4237 | 0.2001 | 720 | 0.2939 | |
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| 0.2873 | 0.4001 | 1440 | 0.2619 | |
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| 0.2345 | 0.6002 | 2160 | 0.2396 | |
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| 0.2212 | 0.8002 | 2880 | 0.2263 | |
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| 0.2041 | 1.0003 | 3600 | 0.2142 | |
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| 0.1872 | 1.2003 | 4320 | 0.2103 | |
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| 0.1829 | 1.4004 | 5040 | 0.1951 | |
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| 0.1807 | 1.6004 | 5760 | 0.1921 | |
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| 0.1776 | 1.8005 | 6480 | 0.1884 | |
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| 0.1759 | 2.0006 | 7200 | 0.1840 | |
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| 0.1658 | 2.2006 | 7920 | 0.1791 | |
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| 0.1627 | 2.4007 | 8640 | 0.1727 | |
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| 0.1574 | 2.6007 | 9360 | 0.1716 | |
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| 0.1571 | 2.8008 | 10080 | 0.1727 | |
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| 0.1549 | 3.0008 | 10800 | 0.1675 | |
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| 0.1441 | 3.2009 | 11520 | 0.1620 | |
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| 0.1447 | 3.4009 | 12240 | 0.1606 | |
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| 0.1433 | 3.6010 | 12960 | 0.1668 | |
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| 0.1409 | 3.8011 | 13680 | 0.1674 | |
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| 0.1415 | 4.0011 | 14400 | 0.1585 | |
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| 0.1282 | 4.2012 | 15120 | 0.1583 | |
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| 0.1332 | 4.4012 | 15840 | 0.1567 | |
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| 0.1296 | 4.6013 | 16560 | 0.1559 | |
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| 0.1332 | 4.8013 | 17280 | 0.1477 | |
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| 0.1268 | 5.0014 | 18000 | 0.1507 | |
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| 0.1176 | 5.2014 | 18720 | 0.1490 | |
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| 0.1166 | 5.4015 | 19440 | 0.1494 | |
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| 0.1196 | 5.6016 | 20160 | 0.1442 | |
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| 0.1193 | 5.8016 | 20880 | 0.1416 | |
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| 0.1156 | 6.0017 | 21600 | 0.1390 | |
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| 0.1067 | 6.2017 | 22320 | 0.1446 | |
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| 0.1069 | 6.4018 | 23040 | 0.1418 | |
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| 0.1085 | 6.6018 | 23760 | 0.1385 | |
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| 0.1062 | 6.8019 | 24480 | 0.1312 | |
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| 0.1074 | 7.0019 | 25200 | 0.1343 | |
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| 0.0986 | 7.2020 | 25920 | 0.1362 | |
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| 0.0965 | 7.4021 | 26640 | 0.1360 | |
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| 0.0967 | 7.6021 | 27360 | 0.1335 | |
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| 0.0955 | 7.8022 | 28080 | 0.1275 | |
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| 0.0986 | 8.0022 | 28800 | 0.1328 | |
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| 0.0876 | 8.2023 | 29520 | 0.1348 | |
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| 0.0867 | 8.4023 | 30240 | 0.1314 | |
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| 0.087 | 8.6024 | 30960 | 0.1290 | |
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| 0.0863 | 8.8024 | 31680 | 0.1261 | |
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| 0.087 | 9.0025 | 32400 | 0.1244 | |
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| 0.0775 | 9.2026 | 33120 | 0.1293 | |
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| 0.0768 | 9.4026 | 33840 | 0.1260 | |
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| 0.0797 | 9.6027 | 34560 | 0.1277 | |
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| 0.0779 | 9.8027 | 35280 | 0.1234 | |
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| 0.0765 | 10.0028 | 36000 | 0.1230 | |
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| 0.0692 | 10.2028 | 36720 | 0.1267 | |
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| 0.0697 | 10.4029 | 37440 | 0.1259 | |
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| 0.0691 | 10.6029 | 38160 | 0.1263 | |
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| 0.0692 | 10.8030 | 38880 | 0.1229 | |
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| 0.0694 | 11.0031 | 39600 | 0.1227 | |
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| 0.0647 | 11.2031 | 40320 | 0.1255 | |
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| 0.0632 | 11.4032 | 41040 | 0.1250 | |
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| 0.0636 | 11.6032 | 41760 | 0.1260 | |
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| 0.0626 | 11.8033 | 42480 | 0.1245 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
