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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-task1-v2-template_small-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-task1-v2-template_small-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: 0.1630 |
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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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| 0.3915 | 0.2001 | 720 | 0.3026 | |
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| 0.2875 | 0.4001 | 1440 | 0.2625 | |
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| 0.254 | 0.6002 | 2160 | 0.2493 | |
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| 0.2464 | 0.8002 | 2880 | 0.2448 | |
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| 0.2334 | 1.0003 | 3600 | 0.2371 | |
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| 0.2206 | 1.2003 | 4320 | 0.2485 | |
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| 0.2162 | 1.4004 | 5040 | 0.2268 | |
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| 0.2149 | 1.6004 | 5760 | 0.2221 | |
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| 0.2132 | 1.8005 | 6480 | 0.2160 | |
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| 0.2071 | 2.0006 | 7200 | 0.2112 | |
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| 0.1996 | 2.2006 | 7920 | 0.2102 | |
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| 0.1972 | 2.4007 | 8640 | 0.2123 | |
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| 0.1936 | 2.6007 | 9360 | 0.2065 | |
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| 0.1931 | 2.8008 | 10080 | 0.1994 | |
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| 0.1937 | 3.0008 | 10800 | 0.2040 | |
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| 0.1812 | 3.2009 | 11520 | 0.1981 | |
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| 0.1849 | 3.4009 | 12240 | 0.2016 | |
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| 0.1791 | 3.6010 | 12960 | 0.2017 | |
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| 0.1785 | 3.8011 | 13680 | 0.1919 | |
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| 0.1784 | 4.0011 | 14400 | 0.1907 | |
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| 0.1683 | 4.2012 | 15120 | 0.1929 | |
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| 0.1697 | 4.4012 | 15840 | 0.1862 | |
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| 0.1658 | 4.6013 | 16560 | 0.1837 | |
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| 0.1673 | 4.8013 | 17280 | 0.1918 | |
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| 0.1641 | 5.0014 | 18000 | 0.1847 | |
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| 0.1549 | 5.2014 | 18720 | 0.1813 | |
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| 0.1542 | 5.4015 | 19440 | 0.1885 | |
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| 0.1561 | 5.6016 | 20160 | 0.1792 | |
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| 0.1569 | 5.8016 | 20880 | 0.1751 | |
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| 0.1513 | 6.0017 | 21600 | 0.1710 | |
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| 0.143 | 6.2017 | 22320 | 0.1737 | |
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| 0.1443 | 6.4018 | 23040 | 0.1725 | |
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| 0.1422 | 6.6018 | 23760 | 0.1689 | |
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| 0.1444 | 6.8019 | 24480 | 0.1668 | |
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| 0.1406 | 7.0019 | 25200 | 0.1649 | |
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| 0.1325 | 7.2020 | 25920 | 0.1691 | |
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| 0.1312 | 7.4021 | 26640 | 0.1656 | |
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| 0.1307 | 7.6021 | 27360 | 0.1629 | |
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| 0.1288 | 7.8022 | 28080 | 0.1638 | |
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| 0.131 | 8.0022 | 28800 | 0.1632 | |
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| 0.1201 | 8.2023 | 29520 | 0.1647 | |
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| 0.1179 | 8.4023 | 30240 | 0.1626 | |
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| 0.1188 | 8.6024 | 30960 | 0.1619 | |
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| 0.1176 | 8.8024 | 31680 | 0.1569 | |
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| 0.1182 | 9.0025 | 32400 | 0.1578 | |
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| 0.1067 | 9.2026 | 33120 | 0.1634 | |
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| 0.1071 | 9.4026 | 33840 | 0.1586 | |
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| 0.1075 | 9.6027 | 34560 | 0.1557 | |
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| 0.1067 | 9.8027 | 35280 | 0.1536 | |
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| 0.1038 | 10.0028 | 36000 | 0.1572 | |
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| 0.0954 | 10.2028 | 36720 | 0.1634 | |
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| 0.0949 | 10.4029 | 37440 | 0.1577 | |
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| 0.0944 | 10.6029 | 38160 | 0.1591 | |
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| 0.0944 | 10.8030 | 38880 | 0.1575 | |
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| 0.0943 | 11.0031 | 39600 | 0.1551 | |
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| 0.0855 | 11.2031 | 40320 | 0.1632 | |
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| 0.0848 | 11.4032 | 41040 | 0.1618 | |
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| 0.0841 | 11.6032 | 41760 | 0.1619 | |
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| 0.0838 | 11.8033 | 42480 | 0.1630 | |
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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 |
