Qwen2.5-VL-7B-Instruct_arc-agi-transduction100k-images-ft-v1

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

• Loss: 0.0501

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: 2
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• total_eval_batch_size: 8
• 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: 0.01
• num_epochs: 2.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.0447	1.0	2936	0.0768
0.0219	2.0	5872	0.0501

Framework versions

• Transformers 4.50.0.dev0
• Pytorch 2.5.1+cu124
• Datasets 3.0.2
• Tokenizers 0.21.0