---
library_name: peft
license: other
base_model: Qwen/Qwen3-Coder-30B-A3B-Instruct
tags:
- base_model:adapter:Qwen/Qwen3-Coder-30B-A3B-Instruct
- llama-factory
- lora
- transformers
metrics:
- accuracy
pipeline_tag: text-generation
model-index:
- name: factory_qwen_results1
  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. -->

# factory_qwen_results1

This model is a fine-tuned version of [Qwen/Qwen3-Coder-30B-A3B-Instruct](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct) on the train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1022
- Accuracy: 0.9780

## 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: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 50
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3137        | 0.0724 | 30   | 0.3017          | 0.9260   |
| 0.2642        | 0.1448 | 60   | 0.2687          | 0.9343   |
| 0.2464        | 0.2171 | 90   | 0.2397          | 0.9387   |
| 0.2345        | 0.2895 | 120  | 0.2179          | 0.9462   |
| 0.2104        | 0.3619 | 150  | 0.2028          | 0.9488   |
| 0.1645        | 0.4343 | 180  | 0.2001          | 0.9499   |
| 0.1761        | 0.5066 | 210  | 0.1826          | 0.9543   |
| 0.1668        | 0.5790 | 240  | 0.1741          | 0.9568   |
| 0.156         | 0.6514 | 270  | 0.1672          | 0.9566   |
| 0.1416        | 0.7238 | 300  | 0.1686          | 0.9553   |
| 0.1361        | 0.7961 | 330  | 0.1587          | 0.9592   |
| 0.162         | 0.8685 | 360  | 0.1539          | 0.9607   |
| 0.1177        | 0.9409 | 390  | 0.1495          | 0.9621   |
| 0.1276        | 1.0121 | 420  | 0.1450          | 0.9640   |
| 0.113         | 1.0844 | 450  | 0.1454          | 0.9626   |
| 0.0844        | 1.1568 | 480  | 0.1387          | 0.9642   |
| 0.1035        | 1.2292 | 510  | 0.1353          | 0.9660   |
| 0.0903        | 1.3016 | 540  | 0.1352          | 0.9660   |
| 0.0927        | 1.3739 | 570  | 0.1316          | 0.9672   |
| 0.1017        | 1.4463 | 600  | 0.1259          | 0.9695   |
| 0.0805        | 1.5187 | 630  | 0.1295          | 0.9691   |
| 0.1307        | 1.5911 | 660  | 0.1211          | 0.9709   |
| 0.0863        | 1.6634 | 690  | 0.1184          | 0.9711   |
| 0.065         | 1.7358 | 720  | 0.1169          | 0.9714   |
| 0.0899        | 1.8082 | 750  | 0.1112          | 0.9724   |
| 0.0736        | 1.8806 | 780  | 0.1083          | 0.9734   |
| 0.0772        | 1.9530 | 810  | 0.1094          | 0.9728   |
| 0.047         | 2.0241 | 840  | 0.1118          | 0.9734   |
| 0.0389        | 2.0965 | 870  | 0.1143          | 0.9735   |
| 0.0519        | 2.1689 | 900  | 0.1111          | 0.9742   |
| 0.0417        | 2.2413 | 930  | 0.1100          | 0.9751   |
| 0.0485        | 2.3136 | 960  | 0.1085          | 0.9748   |
| 0.0539        | 2.3860 | 990  | 0.1055          | 0.9758   |
| 0.031         | 2.4584 | 1020 | 0.1068          | 0.9760   |
| 0.0367        | 2.5308 | 1050 | 0.1076          | 0.9761   |
| 0.0294        | 2.6031 | 1080 | 0.1054          | 0.9773   |
| 0.0329        | 2.6755 | 1110 | 0.1049          | 0.9771   |
| 0.0358        | 2.7479 | 1140 | 0.1027          | 0.9773   |
| 0.0321        | 2.8203 | 1170 | 0.1033          | 0.9776   |
| 0.0337        | 2.8926 | 1200 | 0.1033          | 0.9777   |
| 0.0456        | 2.9650 | 1230 | 0.1022          | 0.9780   |


### Framework versions

- PEFT 0.17.1
- Transformers 4.57.1
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2