| | --- |
| | library_name: transformers |
| | license: other |
| | base_model: Qwen/Qwen3-VL-8B-Instruct |
| | tags: |
| | - llama-factory |
| | - full |
| | - generated_from_trainer |
| | model-index: |
| | - name: gen_reward_sft |
| | 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. --> |
| |
|
| | # gen_reward_sft |
| |
|
| | This model is a fine-tuned version of [Qwen/Qwen3-VL-8B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct) on the gen_reward_sft dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5180 |
| |
|
| | ## 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: 5 |
| | - eval_batch_size: 2 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - num_devices: 8 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 80 |
| | - 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 | |
| | |:-------------:|:------:|:----:|:---------------:| |
| | | 0.6131 | 0.1380 | 500 | 0.6089 | |
| | | 0.5714 | 0.2760 | 1000 | 0.5768 | |
| | | 0.5524 | 0.4140 | 1500 | 0.5562 | |
| | | 0.537 | 0.5520 | 2000 | 0.5407 | |
| | | 0.5282 | 0.6899 | 2500 | 0.5283 | |
| | | 0.5155 | 0.8279 | 3000 | 0.5207 | |
| | | 0.5106 | 0.9659 | 3500 | 0.5181 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.3 |
| | - Pytorch 2.7.1+cu128 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.2 |
| | |
