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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-task2-unordered_template_small-deepseek-coder-1.3b-base-ddp-8lr
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-task2-unordered_template_small-deepseek-coder-1.3b-base-ddp-8lr
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: 0.2327
## 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 |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.4681 | 0.2001 | 629 | 0.3776 |
| 0.379 | 0.4001 | 1258 | 0.3465 |
| 0.3592 | 0.6002 | 1887 | 0.3382 |
| 0.334 | 0.8003 | 2516 | 0.3192 |
| 0.3264 | 1.0003 | 3145 | 0.3150 |
| 0.3122 | 1.2004 | 3774 | 0.3127 |
| 0.3073 | 1.4004 | 4403 | 0.3033 |
| 0.2982 | 1.6005 | 5032 | 0.2978 |
| 0.2974 | 1.8006 | 5661 | 0.2936 |
| 0.2911 | 2.0006 | 6290 | 0.2884 |
| 0.2871 | 2.2007 | 6919 | 0.2861 |
| 0.2803 | 2.4008 | 7548 | 0.2783 |
| 0.277 | 2.6008 | 8177 | 0.2820 |
| 0.2778 | 2.8009 | 8806 | 0.2738 |
| 0.272 | 3.0010 | 9435 | 0.2729 |
| 0.2578 | 3.2010 | 10064 | 0.2702 |
| 0.2596 | 3.4011 | 10693 | 0.2718 |
| 0.2586 | 3.6011 | 11322 | 0.2648 |
| 0.257 | 3.8012 | 11951 | 0.2595 |
| 0.2577 | 4.0013 | 12580 | 0.2591 |
| 0.2431 | 4.2013 | 13209 | 0.2589 |
| 0.2401 | 4.4014 | 13838 | 0.2598 |
| 0.2445 | 4.6015 | 14467 | 0.2537 |
| 0.2403 | 4.8015 | 15096 | 0.2544 |
| 0.2405 | 5.0016 | 15725 | 0.2535 |
| 0.2311 | 5.2017 | 16354 | 0.2533 |
| 0.227 | 5.4017 | 16983 | 0.2508 |
| 0.2259 | 5.6018 | 17612 | 0.2450 |
| 0.2238 | 5.8018 | 18241 | 0.2445 |
| 0.2254 | 6.0019 | 18870 | 0.2419 |
| 0.2201 | 6.2020 | 19499 | 0.2426 |
| 0.2096 | 6.4020 | 20128 | 0.2432 |
| 0.2088 | 6.6021 | 20757 | 0.2440 |
| 0.2078 | 6.8022 | 21386 | 0.2386 |
| 0.2114 | 7.0022 | 22015 | 0.2388 |
| 0.1919 | 7.2023 | 22644 | 0.2388 |
| 0.1939 | 7.4024 | 23273 | 0.2351 |
| 0.1947 | 7.6024 | 23902 | 0.2330 |
| 0.1939 | 7.8025 | 24531 | 0.2283 |
| 0.1916 | 8.0025 | 25160 | 0.2262 |
| 0.179 | 8.2026 | 25789 | 0.2330 |
| 0.1784 | 8.4027 | 26418 | 0.2311 |
| 0.1781 | 8.6027 | 27047 | 0.2327 |
| 0.1772 | 8.8028 | 27676 | 0.2260 |
| 0.1783 | 9.0029 | 28305 | 0.2234 |
| 0.1688 | 9.2029 | 28934 | 0.2323 |
| 0.1607 | 9.4030 | 29563 | 0.2269 |
| 0.1613 | 9.6031 | 30192 | 0.2249 |
| 0.1622 | 9.8031 | 30821 | 0.2253 |
| 0.1602 | 10.0032 | 31450 | 0.2239 |
| 0.1444 | 10.2032 | 32079 | 0.2283 |
| 0.1461 | 10.4033 | 32708 | 0.2281 |
| 0.1449 | 10.6034 | 33337 | 0.2282 |
| 0.1455 | 10.8034 | 33966 | 0.2232 |
| 0.1431 | 11.0035 | 34595 | 0.2277 |
| 0.1334 | 11.2036 | 35224 | 0.2302 |
| 0.1304 | 11.4036 | 35853 | 0.2322 |
| 0.1304 | 11.6037 | 36482 | 0.2313 |
| 0.1291 | 11.8038 | 37111 | 0.2327 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0 |