This model is a fine-tuned version of 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

VisionXLab/FIRM-Gen-8B

gen_reward_sft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

VisionXLab/
FIRM-Gen-8B