| --- |
| base_model: ise-uiuc/Magicoder-S-DS-6.7B |
| datasets: |
| - generator |
| library_name: peft |
| license: other |
| tags: |
| - trl |
| - sft |
| - generated_from_trainer |
| model-index: |
| - name: finetune_starcoder2 |
| 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. --> |
|
|
| # finetune_starcoder2 |
| |
| This model is a fine-tuned version of [ise-uiuc/Magicoder-S-DS-6.7B](https://huggingface.co/ise-uiuc/Magicoder-S-DS-6.7B) on the generator dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3220 |
| |
| ## 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: 1 |
| - eval_batch_size: 5 |
| - seed: 0 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 8 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 100 |
| - training_steps: 2000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 0.8634 | 0.5340 | 50 | 0.6751 | |
| | 0.6619 | 1.0681 | 100 | 0.4653 | |
| | 0.5147 | 1.6021 | 150 | 0.4231 | |
| | 0.4761 | 2.1362 | 200 | 0.3912 | |
| | 0.4348 | 2.6702 | 250 | 0.3663 | |
| | 0.4123 | 3.2043 | 300 | 0.3515 | |
| | 0.3893 | 3.7383 | 350 | 0.3407 | |
| | 0.3769 | 4.2724 | 400 | 0.3329 | |
| | 0.3719 | 4.8064 | 450 | 0.3266 | |
| | 0.3578 | 5.3405 | 500 | 0.3220 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.11.1 |
| - Transformers 4.42.4 |
| - Pytorch 2.3.1+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
