---
library_name: transformers
license: other
base_model: Qwen/Qwen3-4B-Instruct-2507
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: qwen3-4B-instruct-refiner-sft
  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. -->

# qwen3-4B-instruct-refiner-sft

This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the refiner_sft_hard_filtered_train dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1232

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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: 0.05
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4937        | 0.1874 | 100  | 0.6320          |
| 0.511         | 0.3749 | 200  | 0.6321          |
| 0.4657        | 0.5623 | 300  | 0.6459          |
| 0.4577        | 0.7498 | 400  | 0.6420          |
| 0.4634        | 0.9372 | 500  | 0.6470          |
| 0.2661        | 1.1256 | 600  | 0.6921          |
| 0.2427        | 1.3130 | 700  | 0.6904          |
| 0.2608        | 1.5005 | 800  | 0.6896          |
| 0.2811        | 1.6879 | 900  | 0.6763          |
| 0.2506        | 1.8754 | 1000 | 0.6782          |
| 0.1031        | 2.0619 | 1100 | 0.7820          |
| 0.1053        | 2.2493 | 1200 | 0.7939          |
| 0.1009        | 2.4367 | 1300 | 0.7773          |
| 0.1022        | 2.6242 | 1400 | 0.7983          |
| 0.1087        | 2.8116 | 1500 | 0.8067          |
| 0.1046        | 2.9991 | 1600 | 0.8037          |
| 0.0311        | 3.1856 | 1700 | 0.9448          |
| 0.0343        | 3.3730 | 1800 | 0.9443          |
| 0.0322        | 3.5604 | 1900 | 0.9526          |
| 0.0299        | 3.7479 | 2000 | 0.9680          |
| 0.0335        | 3.9353 | 2100 | 0.9606          |
| 0.0073        | 4.1218 | 2200 | 1.0976          |
| 0.0069        | 4.3093 | 2300 | 1.1145          |
| 0.0064        | 4.4967 | 2400 | 1.1218          |
| 0.0086        | 4.6842 | 2500 | 1.1228          |
| 0.0072        | 4.8716 | 2600 | 1.1233          |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.21.1