---
library_name: peft
license: apache-2.0
base_model: Qwen/Qwen3-0.6B
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Extractor_Adaptor_Qwen3_Final
  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. -->

# Extractor_Adaptor_Qwen3_Final

This model is a fine-tuned version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) on the web_finetune_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2849

## 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: 1.7e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.2465        | 0.1180 | 50   | 0.3812          |
| 0.2805        | 0.2360 | 100  | 0.3440          |
| 0.2016        | 0.3540 | 150  | 0.3299          |
| 0.3261        | 0.4720 | 200  | 0.3187          |
| 0.2523        | 0.5900 | 250  | 0.3116          |
| 0.2505        | 0.7080 | 300  | 0.3049          |
| 0.2371        | 0.8260 | 350  | 0.2978          |
| 0.2177        | 0.9440 | 400  | 0.2940          |
| 0.1686        | 1.0614 | 450  | 0.2935          |
| 0.1189        | 1.1794 | 500  | 0.2935          |
| 0.1955        | 1.2973 | 550  | 0.2907          |
| 0.1341        | 1.4153 | 600  | 0.2885          |
| 0.1591        | 1.5333 | 650  | 0.2874          |
| 0.1594        | 1.6513 | 700  | 0.2859          |
| 0.1452        | 1.7693 | 750  | 0.2850          |
| 0.1845        | 1.8873 | 800  | 0.2849          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1