---
title: FIRM-Edit-8B
canonical_url: "https://www.modelscope.ai/models/VisionXLab/FIRM-Edit-8B"
md_url: "https://www.modelscope.ai/models/VisionXLab/FIRM-Edit-8B.md"
repository: VisionXLab/FIRM-Edit-8B
last_updated: 2026-04-08
license: other
model_type:
  - qwen3_vl
architectures:
  - Qwen3VLForConditionalGeneration
base_model:
  - Qwen/Qwen3-VL-8B-Instruct
base_model_relation: finetune
parameters: 8.8B
tensor_type:
  - BF16
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 179
stars: 0
tags:
  - llama-factory
  - full
  - generated_from_trainer
---

# FIRM-Edit-8B

> FIRM-Edit-8B - An open-source model by VisionXLab on ModelScope. editevaluationsft202602030104

VisionXLab/FIRM-Edit-8B is a 8.8B-parameter machine learning model on ModelScope. licensed under other. derived from Qwen/Qwen3-VL-8B-Instruct.

- **Repository**: VisionXLab/FIRM-Edit-8B
- **License**: other
- **Parameters**: 8.8B
- **Base model**: Qwen/Qwen3-VL-8B-Instruct
- **Tags**: llama-factory, full, generated_from_trainer
- **Downloads**: 179
- **Stars**: 0
- **Last updated**: 2026-04-08

Source: https://www.modelscope.ai/models/VisionXLab/FIRM-Edit-8B

---

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# edit_evaluation_sft_202602030104

This model is a fine-tuned version of [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) on the instruction_following_train_v3 and the consistency_train_v3 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.5041

## 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: 10
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 160
- total_eval_batch_size: 16
- 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: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.591         | 0.2182 | 500  | 0.5827          |
| 0.5605        | 0.4364 | 1000 | 0.5460          |
| 0.5252        | 0.6546 | 1500 | 0.5199          |
| 0.5075        | 0.8728 | 2000 | 0.5055          |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.7.1+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2