---
base_model: bigcode/starcoderbase-1b
library_name: peft
license: bigcode-openrail-m
tags:
- generated_from_trainer
model-index:
- name: peft-starcoder-finetuned
  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

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: 1.0382

## 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: 10
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.276         | 0.0416 | 10   | 1.0832          |
| 1.2151        | 0.0833 | 20   | 1.0789          |
| 1.2213        | 0.1249 | 30   | 1.0736          |
| 1.1694        | 0.1666 | 40   | 1.0718          |
| 1.2627        | 0.2082 | 50   | 1.0696          |
| 1.1801        | 0.2499 | 60   | 1.0690          |
| 1.1013        | 0.2915 | 70   | 1.0637          |
| 1.082         | 0.3332 | 80   | 1.0643          |
| 1.0783        | 0.3748 | 90   | 1.0638          |
| 1.1166        | 0.4164 | 100  | 1.0615          |
| 1.1207        | 0.4581 | 110  | 1.0581          |
| 1.197         | 0.4997 | 120  | 1.0562          |
| 1.012         | 0.5414 | 130  | 1.0583          |
| 1.1291        | 0.5830 | 140  | 1.0515          |
| 1.0695        | 0.6247 | 150  | 1.0520          |
| 1.0924        | 0.6663 | 160  | 1.0514          |
| 1.1287        | 0.7080 | 170  | 1.0536          |
| 1.0514        | 0.7496 | 180  | 1.0508          |
| 1.1101        | 0.7913 | 190  | 1.0491          |
| 1.1474        | 0.8329 | 200  | 1.0489          |
| 1.1451        | 0.8745 | 210  | 1.0476          |
| 1.1688        | 0.9162 | 220  | 1.0434          |
| 1.053         | 0.9578 | 230  | 1.0447          |
| 1.0146        | 0.9995 | 240  | 1.0438          |
| 1.1127        | 1.0411 | 250  | 1.0442          |
| 0.9734        | 1.0828 | 260  | 1.0420          |
| 1.0315        | 1.1244 | 270  | 1.0445          |
| 1.0803        | 1.1661 | 280  | 1.0435          |
| 1.0892        | 1.2077 | 290  | 1.0440          |
| 1.0191        | 1.2493 | 300  | 1.0427          |
| 1.034         | 1.2910 | 310  | 1.0416          |
| 1.1136        | 1.3326 | 320  | 1.0413          |
| 0.9837        | 1.3743 | 330  | 1.0413          |
| 1.0659        | 1.4159 | 340  | 1.0405          |
| 0.9931        | 1.4576 | 350  | 1.0409          |
| 1.1141        | 1.4992 | 360  | 1.0403          |
| 1.0851        | 1.5409 | 370  | 1.0399          |
| 1.053         | 1.5825 | 380  | 1.0390          |
| 1.0652        | 1.6242 | 390  | 1.0395          |
| 1.0998        | 1.6658 | 400  | 1.0396          |
| 0.9909        | 1.7074 | 410  | 1.0390          |
| 1.0946        | 1.7491 | 420  | 1.0386          |
| 1.0471        | 1.7907 | 430  | 1.0382          |
| 0.9719        | 1.8324 | 440  | 1.0382          |
| 1.0641        | 1.8740 | 450  | 1.0382          |
| 1.0003        | 1.9157 | 460  | 1.0383          |
| 1.0128        | 1.9573 | 470  | 1.0383          |
| 1.0637        | 1.9990 | 480  | 1.0384          |
| 1.0583        | 2.0406 | 490  | 1.0383          |
| 0.991         | 2.0822 | 500  | 1.0382          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.3