---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen3-4B-Instruct-2507
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: appworld_distillation_sft_v2-SFT-Qwen3-4B-Instruct-2507
  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-Qwen3-4B-Instruct-2507

This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the appworld_distillation_sft_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7486

## 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: 4
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- 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: 30.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7313        | 1.0   | 2    | 1.7900          |
| 1.6378        | 2.0   | 4    | 1.5365          |
| 1.1356        | 3.0   | 6    | 1.1186          |
| 0.9041        | 4.0   | 8    | 0.9372          |
| 0.8762        | 5.0   | 10   | 0.8529          |
| 0.7807        | 6.0   | 12   | 0.8198          |
| 0.7323        | 7.0   | 14   | 0.7646          |
| 0.6814        | 8.0   | 16   | 0.7229          |
| 0.6211        | 9.0   | 18   | 0.6847          |
| 0.5738        | 10.0  | 20   | 0.6639          |
| 0.5171        | 11.0  | 22   | 0.6499          |
| 0.4868        | 12.0  | 24   | 0.6385          |
| 0.4371        | 13.0  | 26   | 0.6327          |
| 0.407         | 14.0  | 28   | 0.6306          |
| 0.3924        | 15.0  | 30   | 0.6330          |
| 0.3505        | 16.0  | 32   | 0.6393          |
| 0.3339        | 17.0  | 34   | 0.6493          |
| 0.3086        | 18.0  | 36   | 0.6623          |
| 0.2803        | 19.0  | 38   | 0.6748          |
| 0.2687        | 20.0  | 40   | 0.6873          |
| 0.25          | 21.0  | 42   | 0.6983          |
| 0.2306        | 22.0  | 44   | 0.7100          |
| 0.2168        | 23.0  | 46   | 0.7205          |
| 0.2125        | 24.0  | 48   | 0.7301          |
| 0.2031        | 25.0  | 50   | 0.7378          |
| 0.1975        | 26.0  | 52   | 0.7433          |
| 0.2001        | 27.0  | 54   | 0.7474          |
| 0.1953        | 28.0  | 56   | 0.7487          |
| 0.1895        | 29.0  | 58   | 0.7487          |
| 0.1976        | 30.0  | 60   | 0.7486          |


### Framework versions

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