---
base_model: bigcode/starcoderbase-7b
library_name: peft
license: bigcode-openrail-m
tags:
- generated_from_trainer
model-index:
- name: peft-starcoder-lora-cutlass
  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-cutlass

This model is a fine-tuned version of [bigcode/starcoderbase-7b](https://huggingface.co/bigcode/starcoderbase-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4322

## 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: 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: 4000

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5409        | 0.025 | 100  | 0.4729          |
| 0.3672        | 0.05  | 200  | 0.4051          |
| 0.3432        | 0.075 | 300  | 0.3876          |
| 0.312         | 0.1   | 400  | 0.3548          |
| 0.2594        | 0.125 | 500  | 0.3507          |
| 0.2821        | 0.15  | 600  | 0.3428          |
| 0.1958        | 0.175 | 700  | 0.3391          |
| 0.2362        | 0.2   | 800  | 0.3405          |
| 0.209         | 0.225 | 900  | 0.3421          |
| 0.2114        | 0.25  | 1000 | 0.3481          |
| 0.1877        | 0.275 | 1100 | 0.3447          |
| 0.1903        | 0.3   | 1200 | 0.3533          |
| 0.1723        | 0.325 | 1300 | 0.3578          |
| 0.1465        | 0.35  | 1400 | 0.3643          |
| 0.1751        | 0.375 | 1500 | 0.3639          |
| 0.1213        | 0.4   | 1600 | 0.3749          |
| 0.119         | 0.425 | 1700 | 0.3692          |
| 0.1199        | 0.45  | 1800 | 0.3820          |
| 0.0986        | 0.475 | 1900 | 0.3816          |
| 0.1232        | 0.5   | 2000 | 0.3868          |
| 0.0819        | 0.525 | 2100 | 0.3923          |
| 0.096         | 0.55  | 2200 | 0.3964          |
| 0.0873        | 0.575 | 2300 | 0.3977          |
| 0.0892        | 0.6   | 2400 | 0.4007          |
| 0.0802        | 0.625 | 2500 | 0.4078          |
| 0.066         | 0.65  | 2600 | 0.4119          |
| 0.0863        | 0.675 | 2700 | 0.4125          |
| 0.0722        | 0.7   | 2800 | 0.4189          |
| 0.0888        | 0.725 | 2900 | 0.4201          |
| 0.0757        | 0.75  | 3000 | 0.4263          |
| 0.0666        | 0.775 | 3100 | 0.4234          |
| 0.0757        | 0.8   | 3200 | 0.4275          |
| 0.053         | 0.825 | 3300 | 0.4289          |
| 0.0772        | 0.85  | 3400 | 0.4290          |
| 0.0546        | 0.875 | 3500 | 0.4297          |
| 0.0601        | 0.9   | 3600 | 0.4311          |
| 0.0606        | 0.925 | 3700 | 0.4317          |
| 0.0544        | 0.95  | 3800 | 0.4314          |
| 0.065         | 0.975 | 3900 | 0.4320          |
| 0.0503        | 1.0   | 4000 | 0.4322          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.4.0a0+07cecf4168.nv24.05
- Datasets 2.20.0
- Tokenizers 0.19.1