---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen3-8B
tags:
- base_model:adapter:Qwen/Qwen3-8B
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: algsteer
  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. -->

# algsteer

This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1092

## 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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.3399        | 1.3909  | 50   | 0.0722          |
| 0.0379        | 2.7818  | 100  | 0.0320          |
| 0.0291        | 4.1675  | 150  | 0.0308          |
| 0.0303        | 5.5585  | 200  | 0.0310          |
| 0.0265        | 6.9494  | 250  | 0.0306          |
| 0.0245        | 8.3351  | 300  | 0.0326          |
| 0.023         | 9.7260  | 350  | 0.0337          |
| 0.0218        | 11.1117 | 400  | 0.0369          |
| 0.0209        | 12.5026 | 450  | 0.0369          |
| 0.0202        | 13.8935 | 500  | 0.0388          |
| 0.0197        | 15.2792 | 550  | 0.0411          |
| 0.019         | 16.6702 | 600  | 0.0418          |
| 0.0186        | 18.0558 | 650  | 0.0442          |
| 0.0178        | 19.4468 | 700  | 0.0454          |
| 0.0174        | 20.8377 | 750  | 0.0473          |
| 0.0167        | 22.2234 | 800  | 0.0499          |
| 0.0161        | 23.6143 | 850  | 0.0492          |
| 0.0155        | 25.0    | 900  | 0.0508          |
| 0.0145        | 26.3909 | 950  | 0.0564          |
| 0.0138        | 27.7818 | 1000 | 0.0566          |
| 0.0131        | 29.1675 | 1050 | 0.0621          |
| 0.0122        | 30.5585 | 1100 | 0.0633          |
| 0.0115        | 31.9494 | 1150 | 0.0675          |
| 0.0105        | 33.3351 | 1200 | 0.0736          |
| 0.0098        | 34.7260 | 1250 | 0.0740          |
| 0.009         | 36.1117 | 1300 | 0.0807          |
| 0.0081        | 37.5026 | 1350 | 0.0832          |
| 0.0076        | 38.8935 | 1400 | 0.0855          |
| 0.007         | 40.2792 | 1450 | 0.0911          |
| 0.0064        | 41.6702 | 1500 | 0.0946          |
| 0.0061        | 43.0558 | 1550 | 0.0972          |
| 0.0056        | 44.4468 | 1600 | 0.1019          |
| 0.0055        | 45.8377 | 1650 | 0.1036          |
| 0.0053        | 47.2234 | 1700 | 0.1064          |
| 0.0051        | 48.6143 | 1750 | 0.1084          |
| 0.005         | 50.0    | 1800 | 0.1092          |


### Framework versions

- PEFT 0.18.0.rc0
- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.2