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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_old_defs-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_old_defs-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: 0.1551
## 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 |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.438 | 0.2002 | 721 | 0.3096 |
| 0.3098 | 0.4003 | 1442 | 0.2840 |
| 0.2714 | 0.6005 | 2163 | 0.2634 |
| 0.2619 | 0.8007 | 2884 | 0.2561 |
| 0.2529 | 1.0008 | 3605 | 0.2385 |
| 0.2363 | 1.2010 | 4326 | 0.2378 |
| 0.2334 | 1.4012 | 5047 | 0.2336 |
| 0.2275 | 1.6013 | 5768 | 0.2318 |
| 0.2263 | 1.8015 | 6489 | 0.2268 |
| 0.223 | 2.0017 | 7210 | 0.2194 |
| 0.2133 | 2.2018 | 7931 | 0.2129 |
| 0.2104 | 2.4020 | 8652 | 0.2150 |
| 0.2073 | 2.6022 | 9373 | 0.2089 |
| 0.206 | 2.8023 | 10094 | 0.2061 |
| 0.2045 | 3.0025 | 10815 | 0.2018 |
| 0.1949 | 3.2027 | 11536 | 0.1990 |
| 0.1919 | 3.4028 | 12257 | 0.2000 |
| 0.1917 | 3.6030 | 12978 | 0.1974 |
| 0.1893 | 3.8032 | 13699 | 0.1960 |
| 0.189 | 4.0033 | 14420 | 0.1947 |
| 0.1783 | 4.2035 | 15141 | 0.1881 |
| 0.1759 | 4.4037 | 15862 | 0.1905 |
| 0.1767 | 4.6038 | 16583 | 0.1871 |
| 0.1761 | 4.8040 | 17304 | 0.1867 |
| 0.1757 | 5.0042 | 18025 | 0.1866 |
| 0.1631 | 5.2043 | 18746 | 0.1840 |
| 0.1642 | 5.4045 | 19467 | 0.1840 |
| 0.1629 | 5.6047 | 20188 | 0.1791 |
| 0.1626 | 5.8048 | 20909 | 0.1781 |
| 0.1621 | 6.0050 | 21630 | 0.1761 |
| 0.1535 | 6.2052 | 22351 | 0.1774 |
| 0.1506 | 6.4053 | 23072 | 0.1769 |
| 0.1507 | 6.6055 | 23793 | 0.1700 |
| 0.1507 | 6.8057 | 24514 | 0.1722 |
| 0.1494 | 7.0058 | 25235 | 0.1688 |
| 0.141 | 7.2060 | 25956 | 0.1671 |
| 0.1404 | 7.4062 | 26677 | 0.1681 |
| 0.1388 | 7.6063 | 27398 | 0.1657 |
| 0.1368 | 7.8065 | 28119 | 0.1629 |
| 0.1365 | 8.0067 | 28840 | 0.1610 |
| 0.1238 | 8.2068 | 29561 | 0.1599 |
| 0.1253 | 8.4070 | 30282 | 0.1577 |
| 0.1253 | 8.6072 | 31003 | 0.1566 |
| 0.127 | 8.8073 | 31724 | 0.1567 |
| 0.124 | 9.0075 | 32445 | 0.1571 |
| 0.1119 | 9.2077 | 33166 | 0.1584 |
| 0.1113 | 9.4078 | 33887 | 0.1570 |
| 0.1125 | 9.6080 | 34608 | 0.1525 |
| 0.1121 | 9.8082 | 35329 | 0.1563 |
| 0.1121 | 10.0083 | 36050 | 0.1559 |
| 0.099 | 10.2085 | 36771 | 0.1581 |
| 0.0986 | 10.4087 | 37492 | 0.1541 |
| 0.0998 | 10.6088 | 38213 | 0.1531 |
| 0.0992 | 10.8090 | 38934 | 0.1530 |
| 0.0981 | 11.0092 | 39655 | 0.1546 |
| 0.0909 | 11.2093 | 40376 | 0.1566 |
| 0.0887 | 11.4095 | 41097 | 0.1568 |
| 0.0895 | 11.6097 | 41818 | 0.1546 |
| 0.0887 | 11.8098 | 42539 | 0.1551 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0 |