This model is a fine-tuned version of Qwen3-VL-8B-Instruct on the medonethinker_sft_image dataset. It achieves the following results on the evaluation set:

Loss: 0.5051

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: 0.0001
train_batch_size: 2
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 2
total_train_batch_size: 32
total_eval_batch_size: 16
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_steps: 0.02
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.4586	1.0	11006	0.5051

Framework versions

PEFT 0.18.1
Transformers 5.0.0
Pytorch 2.8.0+rocm6.4
Datasets 4.0.0
Tokenizers 0.22.2

sathiiii/medonethinker-qwen3vl-8b-lora-r64

medonethinker_sft_lora_qwen3vl_8b_r64_sn

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sathiiii/
medonethinker-qwen3vl-8b-lora-r64