| --- |
| base_model: bigcode/starcoderbase-1b |
| library_name: peft |
| license: bigcode-openrail-m |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: peft-starcoder-finetuned-cpp |
| 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. --> |
|
|
| # peft-starcoder-finetuned-cpp |
|
|
| This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6176 |
|
|
| ## 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: 5e-06 |
| - train_batch_size: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - 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_steps: 20 |
| - training_steps: 1000 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 0.9707 | 0.1273 | 20 | 0.9157 | |
| | 0.9027 | 0.2546 | 40 | 0.8960 | |
| | 0.7973 | 0.3819 | 60 | 0.8843 | |
| | 0.7716 | 0.5091 | 80 | 0.8618 | |
| | 0.6858 | 0.6364 | 100 | 0.8392 | |
| | 0.6603 | 0.7637 | 120 | 0.8126 | |
| | 0.6288 | 0.8910 | 140 | 0.7950 | |
| | 0.5693 | 1.0183 | 160 | 0.7798 | |
| | 0.5035 | 1.1456 | 180 | 0.7706 | |
| | 0.5376 | 1.2729 | 200 | 0.7583 | |
| | 0.4893 | 1.4002 | 220 | 0.7469 | |
| | 0.5256 | 1.5274 | 240 | 0.7366 | |
| | 0.4646 | 1.6547 | 260 | 0.7262 | |
| | 0.5039 | 1.7820 | 280 | 0.7156 | |
| | 0.4376 | 1.9093 | 300 | 0.7062 | |
| | 0.4262 | 2.0366 | 320 | 0.7000 | |
| | 0.445 | 2.1639 | 340 | 0.6917 | |
| | 0.4307 | 2.2912 | 360 | 0.6847 | |
| | 0.4531 | 2.4185 | 380 | 0.6822 | |
| | 0.4018 | 2.5457 | 400 | 0.6758 | |
| | 0.4466 | 2.6730 | 420 | 0.6695 | |
| | 0.3934 | 2.8003 | 440 | 0.6649 | |
| | 0.3815 | 2.9276 | 460 | 0.6607 | |
| | 0.3834 | 3.0549 | 480 | 0.6575 | |
| | 0.4001 | 3.1822 | 500 | 0.6523 | |
| | 0.398 | 3.3095 | 520 | 0.6481 | |
| | 0.3824 | 3.4368 | 540 | 0.6453 | |
| | 0.3756 | 3.5640 | 560 | 0.6409 | |
| | 0.3843 | 3.6913 | 580 | 0.6382 | |
| | 0.3829 | 3.8186 | 600 | 0.6357 | |
| | 0.3534 | 3.9459 | 620 | 0.6345 | |
| | 0.4136 | 4.0732 | 640 | 0.6343 | |
| | 0.3409 | 4.2005 | 660 | 0.6321 | |
| | 0.357 | 4.3278 | 680 | 0.6288 | |
| | 0.397 | 4.4551 | 700 | 0.6263 | |
| | 0.3713 | 4.5823 | 720 | 0.6255 | |
| | 0.3914 | 4.7096 | 740 | 0.6242 | |
| | 0.3657 | 4.8369 | 760 | 0.6230 | |
| | 0.3711 | 4.9642 | 780 | 0.6216 | |
| | 0.3538 | 5.0915 | 800 | 0.6205 | |
| | 0.377 | 5.2188 | 820 | 0.6199 | |
| | 0.3426 | 5.3461 | 840 | 0.6194 | |
| | 0.3583 | 5.4733 | 860 | 0.6188 | |
| | 0.3643 | 5.6006 | 880 | 0.6180 | |
| | 0.362 | 5.7279 | 900 | 0.6178 | |
| | 0.388 | 5.8552 | 920 | 0.6177 | |
| | 0.3424 | 5.9825 | 940 | 0.6177 | |
| | 0.3614 | 6.1098 | 960 | 0.6176 | |
| | 0.3652 | 6.2371 | 980 | 0.6176 | |
| | 0.3691 | 6.3644 | 1000 | 0.6176 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.13.2 |
| - Transformers 4.46.2 |
| - Pytorch 2.4.1+cu121 |
| - Datasets 3.0.1 |
| - Tokenizers 0.20.3 |
