---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-0.5B
tags:
- generated_from_trainer
model-index:
- name: sparql-qwen
  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. -->

# sparql-qwen

This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-0.5B](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6232

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.7485        | 0.1048 | 500   | 0.8336          |
| 0.7336        | 0.2096 | 1000  | 0.7696          |
| 0.6787        | 0.3143 | 1500  | 0.7376          |
| 0.6756        | 0.4191 | 2000  | 0.7190          |
| 0.6651        | 0.5239 | 2500  | 0.7038          |
| 0.6835        | 0.6287 | 3000  | 0.6932          |
| 0.6572        | 0.7334 | 3500  | 0.6810          |
| 0.6664        | 0.8382 | 4000  | 0.6773          |
| 0.6304        | 0.9430 | 4500  | 0.6675          |
| 0.7408        | 1.0478 | 5000  | 0.6648          |
| 0.7004        | 1.1526 | 5500  | 0.6616          |
| 0.6466        | 1.2573 | 6000  | 0.6579          |
| 0.6914        | 1.3621 | 6500  | 0.6543          |
| 0.6885        | 1.4669 | 7000  | 0.6507          |
| 0.6508        | 1.5717 | 7500  | 0.6478          |
| 0.7039        | 1.6764 | 8000  | 0.6442          |
| 0.665         | 1.7812 | 8500  | 0.6436          |
| 0.6483        | 1.8860 | 9000  | 0.6405          |
| 0.699         | 1.9908 | 9500  | 0.6373          |
| 0.4961        | 2.0956 | 10000 | 0.6380          |
| 0.5103        | 2.2003 | 10500 | 0.6367          |
| 0.5443        | 2.3051 | 11000 | 0.6349          |
| 0.4813        | 2.4099 | 11500 | 0.6340          |
| 0.5555        | 2.5147 | 12000 | 0.6324          |
| 0.5711        | 2.6194 | 12500 | 0.6313          |
| 0.5088        | 2.7242 | 13000 | 0.6309          |
| 0.492         | 2.8290 | 13500 | 0.6297          |
| 0.4936        | 2.9338 | 14000 | 0.6267          |
| 0.6411        | 3.0386 | 14500 | 0.6271          |
| 0.6618        | 3.1433 | 15000 | 0.6267          |
| 0.6212        | 3.2481 | 15500 | 0.6260          |
| 0.6337        | 3.3529 | 16000 | 0.6253          |
| 0.6412        | 3.4577 | 16500 | 0.6234          |
| 0.6208        | 3.5624 | 17000 | 0.6232          |
| 0.676         | 3.6672 | 17500 | 0.6226          |
| 0.6465        | 3.7720 | 18000 | 0.6217          |
| 0.6157        | 3.8768 | 18500 | 0.6210          |
| 0.6622        | 3.9816 | 19000 | 0.6200          |
| 0.4811        | 4.0863 | 19500 | 0.6219          |
| 0.5264        | 4.1911 | 20000 | 0.6213          |
| 0.4738        | 4.2959 | 20500 | 0.6232          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3