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---
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 |