peft-starcoder-lora-a100
This model is a fine-tuned version of 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
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Base model
bigcode/starcoderbase-1b