---
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