---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
tags:
- base_model:adapter:Qwen/Qwen2.5-Coder-1.5B-Instruct
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: qwen-skripsi-v1
  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. -->

# qwen-skripsi-v1

This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1767

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.5668        | 0.3968 | 50   | 0.5044          |
| 0.4804        | 0.7937 | 100  | 0.3970          |
| 0.302         | 1.1905 | 150  | 0.2971          |
| 0.2426        | 1.5873 | 200  | 0.2380          |
| 0.1924        | 1.9841 | 250  | 0.1977          |
| 0.2158        | 2.3810 | 300  | 0.1855          |
| 0.1642        | 2.7778 | 350  | 0.1767          |


### Framework versions

- PEFT 0.18.0
- Transformers 4.57.1
- Pytorch 2.9.1+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1