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lemexp-afp-small-thms-deepseek-coder-1.3b-base
yalhessi/lemexp-afp-small-thms-deepseek-coder-1.3b-base
lemexp-afp-small-thms-deepseek-coder-1.3b-base is a machine learning model from yalhessi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- other
- Access
- Public
- Created
- Feb 11, 2025
- Updated
- Feb 11, 2025
- SHA
- 3af223ad
Base models
Model card
From the Hugging Face model README
<!-- 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-afp-small-thms-deepseek-coder-1.3b-base
This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1166
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.4601 | 0.2001 | 2492 | 0.3758 |
| 0.369 | 0.4001 | 4984 | 0.3327 |
| 0.327 | 0.6002 | 7476 | 0.2894 |
| 0.2988 | 0.8003 | 9968 | 0.2848 |
| 0.2873 | 1.0003 | 12460 | 0.2698 |
| 0.2487 | 1.2004 | 14952 | 0.2669 |
| 0.2371 | 1.4004 | 17444 | 0.2430 |
| 0.2324 | 1.6005 | 19936 | 0.2373 |
| 0.2278 | 1.8006 | 22428 | 0.2372 |
| 0.2212 | 2.0006 | 24920 | 0.2190 |
| 0.1991 | 2.2007 | 27412 | 0.2131 |
| 0.1854 | 2.4008 | 29904 | 0.2092 |
| 0.1769 | 2.6008 | 32396 | 0.2034 |
| 0.1818 | 2.8009 | 34888 | 0.1904 |
| 0.1798 | 3.0010 | 37380 | 0.1980 |
| 0.1656 | 3.2010 | 39872 | 0.1820 |
| 0.1533 | 3.4011 | 42364 | 0.1724 |
| 0.1557 | 3.6012 | 44856 | 0.1687 |
| 0.1536 | 3.8012 | 47348 | 0.1721 |
| 0.1531 | 4.0013 | 49840 | 0.1634 |
| 0.1256 | 4.2013 | 52332 | 0.1529 |
| 0.1274 | 4.4014 | 54824 | 0.1471 |
| 0.1294 | 4.6015 | 57316 | 0.1433 |
| 0.1209 | 4.8015 | 59808 | 0.1375 |
| 0.1298 | 5.0016 | 62300 | 0.1308 |
| 0.1064 | 5.2017 | 64792 | 0.1269 |
| 0.1063 | 5.4017 | 67284 | 0.1262 |
| 0.1036 | 5.6018 | 69776 | 0.1213 |
| 0.1084 | 5.8019 | 72268 | 0.1166 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Library
- peft
- License
- other
- Created
- Feb 11, 2025
- Updated
- Feb 11, 2025