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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-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-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: 0.1630

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


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0