| --- |
| base_model: codellama/CodeLlama-7b-Instruct-hf |
| library_name: peft |
| license: llama2 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: codellama-adb-sdk |
| 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. --> |
|
|
| # codellama-adb-sdk |
|
|
| This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.9731 |
|
|
| ## 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: 0.0003 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 16 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - training_steps: 2000 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.2695 | 0.05 | 100 | 0.5778 | |
| | 0.0568 | 0.1 | 200 | 0.7456 | |
| | 0.0411 | 0.15 | 300 | 0.8092 | |
| | 0.0366 | 0.2 | 400 | 0.8567 | |
| | 0.032 | 0.25 | 500 | 0.8574 | |
| | 0.0256 | 0.3 | 600 | 0.8451 | |
| | 0.0258 | 0.35 | 700 | 0.8729 | |
| | 0.0245 | 0.4 | 800 | 0.8760 | |
| | 0.0222 | 0.45 | 900 | 0.8999 | |
| | 0.0199 | 0.5 | 1000 | 0.8617 | |
| | 0.0215 | 0.55 | 1100 | 0.9148 | |
| | 0.0226 | 0.6 | 1200 | 0.9237 | |
| | 0.0206 | 0.65 | 1300 | 0.9307 | |
| | 0.0209 | 0.7 | 1400 | 0.9392 | |
| | 0.0184 | 0.75 | 1500 | 0.9659 | |
| | 0.0189 | 0.8 | 1600 | 0.9492 | |
| | 0.0202 | 0.85 | 1700 | 0.9660 | |
| | 0.0192 | 0.9 | 1800 | 0.9668 | |
| | 0.0176 | 0.95 | 1900 | 0.9722 | |
| | 0.0186 | 1.0 | 2000 | 0.9731 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.13.2.dev0 |
| - Transformers 4.46.0.dev0 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.1 |
