| --- |
| license: llama2 |
| library_name: peft |
| tags: |
| - generated_from_trainer |
| base_model: codellama/CodeLlama-13b-hf |
| model-index: |
| - name: codellama13B-noautogen-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-noautogen-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: 0.3758 |
|
|
| ## 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: 6 |
| - eval_batch_size: 6 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 24 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.417 | 0.05 | 100 | 0.5468 | |
| | 0.5187 | 0.1 | 200 | 0.4993 | |
| | 0.3279 | 0.15 | 300 | 0.4787 | |
| | 0.452 | 0.2 | 400 | 0.4551 | |
| | 0.4738 | 0.25 | 500 | 0.4402 | |
| | 0.4338 | 0.3 | 600 | 0.4263 | |
| | 0.4024 | 0.35 | 700 | 0.4183 | |
| | 0.4268 | 0.4 | 800 | 0.4082 | |
| | 0.3572 | 0.45 | 900 | 0.4014 | |
| | 0.3584 | 0.5 | 1000 | 0.3967 | |
| | 0.359 | 0.55 | 1100 | 0.3913 | |
| | 0.3023 | 0.6 | 1200 | 0.3865 | |
| | 0.2707 | 0.65 | 1300 | 0.3820 | |
| | 0.2918 | 0.7 | 1400 | 0.3790 | |
| | 0.3188 | 0.75 | 1500 | 0.3757 | |
| | 0.167 | 0.8 | 1600 | 0.3741 | |
| | 0.2962 | 0.85 | 1700 | 0.3742 | |
| | 0.2603 | 0.9 | 1800 | 0.3747 | |
| | 0.2544 | 0.95 | 1900 | 0.3755 | |
| | 0.254 | 1.0 | 2000 | 0.3758 | |
|
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|
|
| ### Framework versions |
|
|
| - PEFT 0.9.0 |
| - Transformers 4.39.0.dev0 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.17.1 |
| - Tokenizers 0.15.2 |
