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---
library_name: peft
license: other
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
- generated_from_trainer
model-index:
- name: lemexp-task1-v2-template_small_nodefs-deepseek-coder-1.3b-base-ddp-8lr-v2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# lemexp-task1-v2-template_small_nodefs-deepseek-coder-1.3b-base-ddp-8lr-v2
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.
It achieves the following results on the evaluation set:
- Loss: 0.1548
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0008
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.3773 | 0.2001 | 720 | 0.2929 |
| 0.2804 | 0.4001 | 1440 | 0.2615 |
| 0.2488 | 0.6002 | 2160 | 0.2472 |
| 0.2405 | 0.8002 | 2880 | 0.2416 |
| 0.2302 | 1.0003 | 3600 | 0.2355 |
| 0.218 | 1.2003 | 4320 | 0.2305 |
| 0.2138 | 1.4004 | 5040 | 0.2205 |
| 0.2111 | 1.6004 | 5760 | 0.2150 |
| 0.2109 | 1.8005 | 6480 | 0.2147 |
| 0.2035 | 2.0006 | 7200 | 0.2091 |
| 0.1953 | 2.2006 | 7920 | 0.2103 |
| 0.1932 | 2.4007 | 8640 | 0.2053 |
| 0.1897 | 2.6007 | 9360 | 0.1994 |
| 0.1896 | 2.8008 | 10080 | 0.2000 |
| 0.1927 | 3.0008 | 10800 | 0.1980 |
| 0.1785 | 3.2009 | 11520 | 0.1952 |
| 0.18 | 3.4009 | 12240 | 0.1955 |
| 0.176 | 3.6010 | 12960 | 0.1882 |
| 0.1753 | 3.8011 | 13680 | 0.1899 |
| 0.1765 | 4.0011 | 14400 | 0.1840 |
| 0.165 | 4.2012 | 15120 | 0.1892 |
| 0.1653 | 4.4012 | 15840 | 0.1850 |
| 0.1645 | 4.6013 | 16560 | 0.1914 |
| 0.1656 | 4.8013 | 17280 | 0.1821 |
| 0.1607 | 5.0014 | 18000 | 0.1860 |
| 0.1524 | 5.2014 | 18720 | 0.1806 |
| 0.1523 | 5.4015 | 19440 | 0.1771 |
| 0.1529 | 5.6016 | 20160 | 0.1719 |
| 0.1524 | 5.8016 | 20880 | 0.1751 |
| 0.1491 | 6.0017 | 21600 | 0.1706 |
| 0.1412 | 6.2017 | 22320 | 0.1686 |
| 0.1419 | 6.4018 | 23040 | 0.1685 |
| 0.1408 | 6.6018 | 23760 | 0.1653 |
| 0.1413 | 6.8019 | 24480 | 0.1675 |
| 0.1385 | 7.0019 | 25200 | 0.1632 |
| 0.1306 | 7.2020 | 25920 | 0.1650 |
| 0.1286 | 7.4021 | 26640 | 0.1622 |
| 0.1291 | 7.6021 | 27360 | 0.1631 |
| 0.127 | 7.8022 | 28080 | 0.1580 |
| 0.1289 | 8.0022 | 28800 | 0.1584 |
| 0.1177 | 8.2023 | 29520 | 0.1576 |
| 0.1167 | 8.4023 | 30240 | 0.1564 |
| 0.1174 | 8.6024 | 30960 | 0.1550 |
| 0.1156 | 8.8024 | 31680 | 0.1543 |
| 0.1164 | 9.0025 | 32400 | 0.1531 |
| 0.105 | 9.2026 | 33120 | 0.1582 |
| 0.1045 | 9.4026 | 33840 | 0.1557 |
| 0.106 | 9.6027 | 34560 | 0.1534 |
| 0.1058 | 9.8027 | 35280 | 0.1500 |
| 0.1026 | 10.0028 | 36000 | 0.1499 |
| 0.0938 | 10.2028 | 36720 | 0.1540 |
| 0.0937 | 10.4029 | 37440 | 0.1522 |
| 0.0929 | 10.6029 | 38160 | 0.1542 |
| 0.0926 | 10.8030 | 38880 | 0.1537 |
| 0.0931 | 11.0031 | 39600 | 0.1518 |
| 0.0849 | 11.2031 | 40320 | 0.1579 |
| 0.0837 | 11.4032 | 41040 | 0.1560 |
| 0.0828 | 11.6032 | 41760 | 0.1548 |
| 0.0826 | 11.8033 | 42480 | 0.1548 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0 |