| --- |
| base_model: bigcode/starcoderbase-1b |
| library_name: peft |
| license: bigcode-openrail-m |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: peft-starcoder-lora-a100 |
| 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-lora-a100 |
|
|
| This model is a fine-tuned version of [bigcode/starcoderbase-1b](https://huggingface.co/bigcode/starcoderbase-1b) on chargoddard/commitpack-ft-instruct filtered only for Python examples |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8388 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| Intended for merging |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 30 |
| - training_steps: 2000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 0.8844 | 0.05 | 100 | 0.8664 | |
| | 0.8718 | 0.1 | 200 | 0.8622 | |
| | 0.8754 | 0.15 | 300 | 0.8603 | |
| | 0.8898 | 0.2 | 400 | 0.8581 | |
| | 0.8722 | 0.25 | 500 | 0.8565 | |
| | 0.8592 | 0.3 | 600 | 0.8554 | |
| | 0.8655 | 0.35 | 700 | 0.8537 | |
| | 0.8546 | 0.4 | 800 | 0.8514 | |
| | 0.8776 | 0.45 | 900 | 0.8493 | |
| | 0.852 | 0.5 | 1000 | 0.8477 | |
| | 0.8702 | 0.55 | 1100 | 0.8451 | |
| | 0.8745 | 0.6 | 1200 | 0.8438 | |
| | 0.8613 | 0.65 | 1300 | 0.8422 | |
| | 0.8602 | 0.7 | 1400 | 0.8412 | |
| | 0.8584 | 0.75 | 1500 | 0.8400 | |
| | 0.8455 | 0.8 | 1600 | 0.8398 | |
| | 0.8388 | 0.85 | 1700 | 0.8393 | |
| | 0.8222 | 0.9 | 1800 | 0.8388 | |
| | 0.8413 | 0.95 | 1900 | 0.8389 | |
| | 0.8337 | 1.0 | 2000 | 0.8388 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.11.1 |
| - Transformers 4.41.2 |
| - Pytorch 2.3.1 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
