| | --- |
| | license: llama2 |
| | library_name: peft |
| | tags: |
| | - generated_from_trainer |
| | base_model: codellama/CodeLlama-13b-hf |
| | model-index: |
| | - name: codeLlama13B-StaproCoder |
| | 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. --> |
| |
|
| | # codeLlama13B-StaproCoder |
| |
|
| | This model is a fine-tuned version of [codellama/CodeLlama-13b-hf](https://huggingface.co/codellama/CodeLlama-13b-hf) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1794 |
| |
|
| | ## 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: 0.0005 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - training_steps: 2000 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 0.2404 | 0.05 | 100 | 0.2456 | |
| | | 0.289 | 0.1 | 200 | 0.2349 | |
| | | 0.236 | 0.15 | 300 | 0.2281 | |
| | | 0.1928 | 0.2 | 400 | 0.2200 | |
| | | 0.1999 | 0.25 | 500 | 0.2217 | |
| | | 0.1697 | 0.3 | 600 | 0.2134 | |
| | | 0.1825 | 0.35 | 700 | 0.2129 | |
| | | 0.1904 | 0.4 | 800 | 0.2093 | |
| | | 0.159 | 0.45 | 900 | 0.2054 | |
| | | 0.1448 | 0.5 | 1000 | 0.1994 | |
| | | 0.1993 | 0.55 | 1100 | 0.1954 | |
| | | 0.2424 | 0.6 | 1200 | 0.1896 | |
| | | 0.1385 | 0.65 | 1300 | 0.1891 | |
| | | 0.1427 | 0.7 | 1400 | 0.1860 | |
| | | 0.2021 | 0.75 | 1500 | 0.1836 | |
| | | 0.1884 | 0.8 | 1600 | 0.1824 | |
| | | 0.26 | 0.85 | 1700 | 0.1809 | |
| | | 0.1641 | 0.9 | 1800 | 0.1799 | |
| | | 0.1503 | 0.95 | 1900 | 0.1794 | |
| | | 0.1613 | 1.0 | 2000 | 0.1794 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - PEFT 0.9.0 |
| | - Transformers 4.39.0.dev0 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.17.1 |
| | - Tokenizers 0.15.2 |
