---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: appworld_distillation_sft_v2-SFT-Qwen3-8B
  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. -->

# appworld_distillation_sft_v2-SFT-Qwen3-8B

This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on the appworld_distillation_sft_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6342

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- 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_ratio: 0.1
- num_epochs: 25.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1697        | 1.0   | 2    | 1.2944          |
| 1.0781        | 2.0   | 4    | 1.1407          |
| 0.9806        | 3.0   | 6    | 1.0041          |
| 0.9093        | 4.0   | 8    | 0.9051          |
| 0.8595        | 5.0   | 10   | 0.8866          |
| 0.7688        | 6.0   | 12   | 0.8013          |
| 0.7223        | 7.0   | 14   | 0.7614          |
| 0.689         | 8.0   | 16   | 0.7272          |
| 0.6641        | 9.0   | 18   | 0.7127          |
| 0.5795        | 10.0  | 20   | 0.6720          |
| 0.5451        | 11.0  | 22   | 0.6551          |
| 0.5059        | 12.0  | 24   | 0.6409          |
| 0.5035        | 13.0  | 26   | 0.6352          |
| 0.484         | 14.0  | 28   | 0.6281          |
| 0.4436        | 15.0  | 30   | 0.6252          |
| 0.4347        | 16.0  | 32   | 0.6250          |
| 0.4139        | 17.0  | 34   | 0.6253          |
| 0.4108        | 18.0  | 36   | 0.6265          |
| 0.3969        | 19.0  | 38   | 0.6287          |
| 0.3825        | 20.0  | 40   | 0.6303          |
| 0.3839        | 21.0  | 42   | 0.6313          |
| 0.3699        | 22.0  | 44   | 0.6326          |
| 0.3871        | 23.0  | 46   | 0.6336          |
| 0.382         | 24.0  | 48   | 0.6338          |
| 0.3879        | 25.0  | 50   | 0.6342          |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
