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---
library_name: peft
license: other
base_model: deepseek-ai/deepseek-coder-6.7b-base
tags:
- generated_from_trainer
model-index:
- name: lemexp-task1-v3-template_small-deepseek-coder-6.7b-base
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-v3-template_small-deepseek-coder-6.7b-base
This model is a fine-tuned version of [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1445
## 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: 0.0004
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- 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 |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.6105 | 0.2001 | 720 | 0.1979 |
| 0.3924 | 0.4002 | 1440 | 0.1762 |
| 0.3264 | 0.6003 | 2160 | 0.1657 |
| 0.3094 | 0.8003 | 2880 | 0.1514 |
| 0.2879 | 1.0003 | 3600 | 0.1473 |
| 0.2563 | 1.2004 | 4320 | 0.1422 |
| 0.2479 | 1.4004 | 5040 | 0.1370 |
| 0.2451 | 1.6005 | 5760 | 0.1394 |
| 0.2413 | 1.8006 | 6480 | 0.1315 |
| 0.2317 | 2.0006 | 7200 | 0.1288 |
| 0.2101 | 2.2006 | 7920 | 0.1282 |
| 0.2039 | 2.4007 | 8640 | 0.1231 |
| 0.2006 | 2.6008 | 9360 | 0.1211 |
| 0.2003 | 2.8009 | 10080 | 0.1172 |
| 0.2044 | 3.0008 | 10800 | 0.1192 |
| 0.1712 | 3.2009 | 11520 | 0.1202 |
| 0.1762 | 3.4010 | 12240 | 0.1164 |
| 0.1732 | 3.6011 | 12960 | 0.1136 |
| 0.1731 | 3.8012 | 13680 | 0.1141 |
| 0.1723 | 4.0011 | 14400 | 0.1121 |
| 0.1466 | 4.2012 | 15120 | 0.1163 |
| 0.1491 | 4.4013 | 15840 | 0.1121 |
| 0.1485 | 4.6014 | 16560 | 0.1144 |
| 0.1515 | 4.8014 | 17280 | 0.1088 |
| 0.1496 | 5.0014 | 18000 | 0.1089 |
| 0.1261 | 5.2015 | 18720 | 0.1125 |
| 0.1281 | 5.4016 | 19440 | 0.1087 |
| 0.1308 | 5.6016 | 20160 | 0.1090 |
| 0.1319 | 5.8017 | 20880 | 0.1106 |
| 0.13 | 6.0017 | 21600 | 0.1058 |
| 0.1119 | 6.2018 | 22320 | 0.1176 |
| 0.1134 | 6.4018 | 23040 | 0.1124 |
| 0.1133 | 6.6019 | 23760 | 0.1133 |
| 0.1141 | 6.8020 | 24480 | 0.1135 |
| 0.1134 | 7.0019 | 25200 | 0.1110 |
| 0.1 | 7.2020 | 25920 | 0.1170 |
| 0.0964 | 7.4021 | 26640 | 0.1099 |
| 0.0986 | 7.6022 | 27360 | 0.1141 |
| 0.0984 | 7.8023 | 28080 | 0.1096 |
| 0.0992 | 8.0022 | 28800 | 0.1101 |
| 0.0832 | 8.2023 | 29520 | 0.1185 |
| 0.0808 | 8.4024 | 30240 | 0.1157 |
| 0.0837 | 8.6025 | 30960 | 0.1191 |
| 0.0845 | 8.8026 | 31680 | 0.1213 |
| 0.0834 | 9.0025 | 32400 | 0.1222 |
| 0.0703 | 9.2026 | 33120 | 0.1285 |
| 0.0714 | 9.4027 | 33840 | 0.1220 |
| 0.0725 | 9.6028 | 34560 | 0.1245 |
| 0.0742 | 9.8028 | 35280 | 0.1253 |
| 0.0709 | 10.0028 | 36000 | 0.1231 |
| 0.0618 | 10.2029 | 36720 | 0.1325 |
| 0.0611 | 10.4029 | 37440 | 0.1318 |
| 0.0621 | 10.6030 | 38160 | 0.1354 |
| 0.062 | 10.8031 | 38880 | 0.1352 |
| 0.063 | 11.0031 | 39600 | 0.1332 |
| 0.0554 | 11.2031 | 40320 | 0.1455 |
| 0.0552 | 11.4032 | 41040 | 0.1436 |
| 0.0546 | 11.6033 | 41760 | 0.1423 |
| 0.0552 | 11.8034 | 42480 | 0.1445 |
### Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.1 |