This model is a fine-tuned version of Qwen/Qwen2.5-VL-7B-Instruct on the scanned prescription dataset. It achieves the following results on the evaluation set:

Loss: 0.2785

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
gradient_accumulation_steps: 16
total_train_batch_size: 32
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: 0.03
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
0.0774	1.7569	100	0.2785

Framework versions

PEFT 0.17.1
Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

scanseta/qwen_prescription_model

qwen-finetune-iter2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

scanseta/
qwen_prescription_model