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

# sft_direct

This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the scope_sft_direct dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3041

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_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: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3289        | 0.0747 | 500  | 0.3394          |
| 0.3445        | 0.1494 | 1000 | 0.3315          |
| 0.3383        | 0.2241 | 1500 | 0.3268          |
| 0.3352        | 0.2987 | 2000 | 0.3224          |
| 0.3027        | 0.3734 | 2500 | 0.3197          |
| 0.3272        | 0.4481 | 3000 | 0.3166          |
| 0.3216        | 0.5228 | 3500 | 0.3138          |
| 0.3223        | 0.5975 | 4000 | 0.3108          |
| 0.3346        | 0.6722 | 4500 | 0.3076          |
| 0.3098        | 0.7468 | 5000 | 0.3065          |
| 0.2938        | 0.8215 | 5500 | 0.3059          |
| 0.315         | 0.8962 | 6000 | 0.3046          |
| 0.301         | 0.9709 | 6500 | 0.3040          |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.22.1